- Flux RSS en pagaille (pour en ajouter : @ moi)

❌ À propos de FreshRSS
Il y a de nouveaux articles disponibles, cliquez pour rafraîchir la page.
À partir d’avant-hierDjangoTricks

Guest Post: Django Crispy Forms Advanced Usage Example

Par Aidas Bendoraitis a.k.a. archatas
Guest Post: Django Crispy Forms Advanced Usage Example

This is a guest post by Serhii Kushchenko, Python/Django developer and data analyst. He is skillful in SQL, Python, Django, RESTful APIs, statistics, and machine learning.

This post aims to demonstrate the creation and processing of the large and complex form in Django using django-crispy-forms. The form contains several buttons that require executing different actions during the processing phase. Also, in the form, the number of rows and columns is not static but varies depending on some conditions. In our case, the set of rows and columns changes depending on the number of instances (columns) associated with the main object (data schema) in a many-to-one relationship.

The django-crispy-forms documentation includes a page Updating layouts on the go. That page is quite helpful. However, it does not contain any detailed example of a working project. IMHO such an example is much needed. I hope my project serves as a helpful addition to the official Django Crispy Forms documentation. Feel free to copy-paste the pieces of code that you find applicable.

Please see the full codebase here. It is ready for Heroku deployment.


Suppose we have a database with information about people: name, surname, phone numbers, place of work, companies owned, etc. The task is not to process the data but to work with meta-information about that data.

Different users may need to extract varying information from the database. These users do not want to write and run SQL queries. They demand some simple and more visual solutions. The assignment is to make it possible for users to create the data schemas visually. In other words, to develop such a form and make it fully functioning.

Schema editing form

Using their schemas, users will be able to CRUD data in the database. However, these operations are beyond the scope of the current project.

Different columns can have their specific parameters. For example, integer columns have lower and upper bounds. It is necessary to develop functionality for editing those parameters for all types of columns. For that editing, forms are used that arise after clicking the "Edit details" button on the main form.

Moreover, we have to develop a form "Create new schema" and a page with a list of all available schemas.


Described below:

  1. Data models used.
  2. How the required forms are generated.
  3. Recognizing and handling the user-initiated state changes.

The task described above can be better solved using JavaScript together with Django forms. It would reduce the number of requests to the server and increase the speed of the application. So the user experience would improve. However, the project aimed to create an advanced example of working with Django Crispy Forms.

Here you can learn the following tricks:

  1. Compose a complex Django Crispy Form using the Layout, Row, Column, Fieldset, Field, and other available classes.
  2. During form generation, iterate over the Foreign Key related objects and create a form row for each of them.
  3. When it makes sense to use an abstract base class and when it doesn't.
  4. How to encode the required action and other data in the button name during its creation.
  5. Determine which button the user clicked and implement the analog of switch-case statement to perform the required action.
  6. Automatically populate the newly generated form with the request.POST data if you want and if that data is available.
  7. Validation of user-entered data (phone number) using a regular expression.
  8. If you have many similar models, use metaprogramming to generate ModelForm classes for those models without violating the DRY principle.


According to the task, the number of columns in the schemas can be different. The users add new columns and delete existing columns. Also, they can change the type and order of columns. The columns and schemas have a many-to-one relationship that is described using the Foreign Key in Django models.

The picture shows that every schema has its name, 'Column separator' field, and 'String character' field. Also, it would be nice to save the date of the last schema modification. The following code from schemas\ file is pretty simple.

INTEGER_CH = "IntegerColumn"
FULLNAME_CH = "FullNameColumn"
JOB_CH = "JobColumn"
PHONE_CH = "PhoneColumn"
COMPANY_CH = "CompanyColumn"
(INTEGER_CH, "Integer"),
(FULLNAME_CH, "Full Name"),
(JOB_CH, "Job"),
(PHONE_CH, "Phone"),
(COMPANY_CH, "Company"),

(DOUBLE_QUOTE, 'Double-quote(")'),
(SINGLE_QUOTE, "Single-quote(')"),

COMMA = ","
COLUMN_SEPARATOR_CHOICES = [(COMMA, "Comma(,)"), (SEMICOLON, "Semicolon(;)")]

class DataSchemas(models.Model):

name = models.CharField(max_length=100)
column_separator = models.CharField(
string_character = models.CharField(
modif_date = models.DateField(auto_now=True)

def get_absolute_url(self):
return reverse("schema_add_update", args=[str(])

Each column has a name, type, and order. All of these fields are in the base SchemaColumn(models.Model) class. This class cannot be abstract because in such a case, the code schema.schemacolumn_set.all() would not work.

Columns of type integer, first and last name, job, company, and phone number are implemented as classes derived from the base class SchemaColumn.

class SchemaColumn(models.Model):
name = models.CharField(max_length=100)
schema = models.ForeignKey(DataSchemas, on_delete=models.CASCADE)
order = models.PositiveIntegerField()

class Meta:
unique_together = [["schema", "name"], ["schema", "order"]]

def save(self, *args, **kwargs):
super(SchemaColumn, self).save(*args, **kwargs)

class IntegerColumn(SchemaColumn):
range_low = models.IntegerField(blank=True, null=True, default=-20)
range_high = models.IntegerField(blank=True, null=True, default=40)

class FullNameColumn(SchemaColumn):
first_name = models.CharField(max_length=10, blank=True, null=True)
last_name = models.CharField(max_length=15, blank=True, null=True)

class JobColumn(SchemaColumn):
job_name = models.CharField(max_length=100, blank=True, null=True)

class CompanyColumn(SchemaColumn):
company_name = models.CharField(max_length=100, blank=True, null=True)

class PhoneColumn(SchemaColumn):
phone_regex = RegexValidator(
message="Phone number must be entered in the format: '+999999999'. Up to 15 digits allowed.",
phone_number = models.CharField(
validators=[phone_regex], max_length=17, blank=True, null=True
) # validators should be a list


The schema editing form is quite complex. We do not use the Django built-in ModelForm class here because it is not flexible enough. Our class DataSchemaForm is a derivative of the forms.Form class. Of course, django-crispy-forms was very helpful and even essential.

from crispy_forms.layout import (

The type of column in the form depends on the class of the column. How to determine that class? The problems can arise if we use the built-in isinstance() function for derived classes such as our various column types. The following code demonstrates how the subclass check was implemented in the file when generating the form.

INTEGER_CH = "IntegerColumn"
FULLNAME_CH = "FullNameColumn"
JOB_CH = "JobColumn"
PHONE_CH = "PhoneColumn"
COMPANY_CH = "CompanyColumn"
(INTEGER_CH, "Integer"),
(FULLNAME_CH, "Full Name"),
(JOB_CH, "Job"),
(PHONE_CH, "Phone"),
(COMPANY_CH, "Company"),

subclasses = [
for subclass in SchemaColumn.__subclasses__()

# yes, somewhat redundant
column_type_switcher = {
"integercolumn": INTEGER_CH,
"fullnamecolumn": FULLNAME_CH,
"jobcolumn": JOB_CH,
"companycolumn": COMPANY_CH,
"phonecolumn": PHONE_CH,

column_type_field_name = "col_type_%s" % (,)
self.fields[column_type_field_name] = forms.ChoiceField(
label="Column type", choices=COLUMN_TYPE_CHOICES
for subclass in subclasses:
if hasattr(column, subclass):
self.fields[column_type_field_name].initial = [

How new schemas are created

The function that generates the schema editing form may get the primary key of the existing schema. If such a key is not available, then the function creates a new schema and its first column. After that, the user can change the parameters of the schema, as well as add new columns.

if schema_pk:
schema = DataSchemas.objects.get(pk=schema_pk)
# no existing schema primary key passed from the caller,
# so create new schema and its first column
# with default parameters
schema = DataSchemas.objects.create(name="New Schema")
int1 = IntegerColumn.objects.create(
name="First Column",

self.fields["name"].initial =
self.fields["column_separator"].initial = schema.column_separator
self.fields["string_character"].initial = schema.string_character

In addition to the schema editing form, the application also contains a list of all created schemas.

All schemas list

There is nothing special about that page, so I will not describe it in detail here. Pleas see the full code and templates at

Requests processing

The picture shows that the schema editing form contains several types of buttons:

  • Submit form
  • Add new column
  • Delete column
  • Edit column details

We need to determine which button the user pressed and perform the required action.

During the form creation, the required action is encoded in the names of all the buttons. Also, the column primary key or schema primary key is encoded there. For example, delete_btn = 'delete_col_%s' % (,) or submit_form_btn = 'submit_form_%s' % (,).

The name of the button can be found in the request.POST data only if the user has pressed that button. The following code from the file searches for the button name in the request.POST data and calls the required function. A well-known method is used to implement the Python analog of switch-case statement.

btn_functions = {
"add_new_col": process_btn_add_column,
"delete_col": process_btn_delete_column,
"edit_col": process_btn_edit_column_details,
"submit_form": process_btn_submit_form,
"save_column_chng": process_btn_save_chng_column,
btn_pressed = None

# source of key.startswith idea -
for key in request.POST:
if key.startswith("delete_col_"):
btn_pressed = "delete_col"
if key.startswith("edit_col_"):
btn_pressed = "edit_col"
if key.startswith("add_column_btn_"):
btn_pressed = "add_new_col"
if key.startswith("submit_form_"):
btn_pressed = "submit_form"
if key.startswith("save_column_chng_btn_"):
btn_pressed = "save_column_chng"

if btn_pressed is not None:
func_to_call = self.btn_functions.get(btn_pressed), form = func_to_call(self, key, form_data=request.POST)

Editing parameters of different types of columns

Different types of columns have their specific parameters. For example, integer columns have lower and upper bounds. Phone columns have the phone number field that requires validation before saving. The number of different types of columns can increase over time.

How to handle the Edit Details button click? The straightforward solution is to make individual ModelForm classes for each type of column. However, it would violate the DRY principle. Perhaps, in this case, the use of metaprogramming is justified.

def get_general_column_form(self, model_class, column_pk):
class ColumnFormGeneral(ModelForm):
def __init__(self, *args, **kwargs):
super(ColumnFormGeneral, self).__init__(*args, **kwargs)
self.helper = FormHelper(self)
save_chng_btn = "save_column_chng_btn_%s" % (column_pk,)
self.helper.layout.append(Submit(save_chng_btn, "Save changes"))

class Meta:
model = model_class
exclude = ["schema", "order"]

return ColumnFormGeneral

First, the type of column is determined using its primary key. After that, the get_general_column_form function is called. It returns the customized ModelForm class. Next, an instance of that class is created and used.

column = get_object_or_404(SchemaColumn, pk=column_pk)
for subclass in self.subclasses:
if hasattr(column, subclass):
column_model = apps.get_model("schemas", subclass)
column = get_object_or_404(column_model, pk=column_pk)
form_class = self.get_general_column_form(column_model, column_pk)
form = form_class(
column, fields=[ for field in column._meta.fields]

Handling of the column type change

The user may change the type of one or several columns. If it happens, it means that the class of these columns has changed. Here, it is not enough to change the value of some attribute of the object. We have to delete the old object and create a new object belonging to the new class instead. How do we handle it:

  1. First, a form is generated using the schema's primary key.
  2. Then, in the newly created form, the data from the database is replaced with the request.POST data, if that data is available. It happens automatically.
  3. In the next step, the form is validated. For that, we have to call the form.is_valid() method explicitly.
  4. If the validation is successful, then we process every column of the schema. For each column, its type from the database is compared with its type from the form. It means that its database type is compared with its request.POST type. If these types differ, the old column is deleted, and a new one is created instead.
# elem is a 'Submit Form' button that the user pressed.
# schema primary key is encoded in its name
# first, let's decode it = [int(s) for s in elem.split("_") if s.isdigit()][0]

# form_data is request.POST
form = DataSchemaForm(form_data,
if form.is_valid():
schema = get_object_or_404(DataSchemas, = form.cleaned_data["name"]
schema.column_separator = form.cleaned_data["column_separator"]
schema.string_character = form.cleaned_data["string_character"]

# the following code is in the save_schema_columns(self, schema, form) function
schema_columns = schema.schemacolumn_set.all()
for column in schema_columns:
column_name_field_name = "col_name_%s" % (,)
column_order_field_name = "col_order_%s" % (,)
column_type_field_name = "col_type_%s" % (,)

type_form = form.cleaned_data[column_type_field_name]
type_changed = False
for subclass in self.subclasses:
if hasattr(column, subclass):
type_db = self.column_type_switcher.get(subclass)
if type_db != type_form:
new_class = globals()[type_form]
new_column = new_class() = form.cleaned_data[column_name_field_name]
new_column.order = form.cleaned_data[column_order_field_name]
new_column.schema = schema
type_changed = True
if not type_changed: = form.cleaned_data[column_name_field_name]
column.order = form.cleaned_data[column_order_field_name]

Final Words

I hope this post serves as a helpful addition to the official Django Crispy Forms documentation. Feel free to copy-paste the pieces of code that you find applicable. Also, write comments and share your experience of using Django Crispy Forms.

Cover photo by Juan Pablo Malo.

How I Tested ReactJS-based Webapp with Selenium

Par Aidas Bendoraitis a.k.a. archatas

How I Tested ReactJS-based Webapp with Selenium

For quite some time, I have been building a SaaS product - strategic prioritizer 1st things 1st. It's using Django in the backend and ReactJS in the frontend and communicating between those ends by REST API. Every week I try to make progress with this project, be it a more prominent feature, some content changes, or small styling tweaks. In the past week, I implemented frontend testing with Selenium, and I want to share my journey with you.

What can you do with 1st things 1st

1st things 1st allows you to evaluate a list of items by multiple criteria and calculates priorities for you to follow and take action. The service has 4 main steps:

  1. Defining criteria.
  2. Listing out things.
  3. Evaluating things by each criterion.
  4. Exploring the priorities.

Selenium is a testing tool that mimics user interaction in the browser: you can fill in fields, trigger events, or read out information from the HTML tags. To test the frontend of 1st things 1st with Selenium, I had to

  1. enter the user credentials and login,
  2. create a project from a blank project template,
  3. add some criteria,
  4. add some things to do,
  5. evaluate each thing by each criterion, and
  6. see if the generated list of priorities was correct.

Let's see how I did it.


In 2020, Chrome is the most popular browser, and it's my default browser, so I decided to develop tests using it.

I had to install Selenium with pip into my virtual environment:

(venv)$ pip install selenium

Also, I needed a binary chromedriver, which makes Selenium talk to your Chrome browser. I downloaded it and placed it under myproject/drivers/chromedriver.

In the Django project configuration, I needed a couple of settings. I usually have separate settings-file for each of the environments, such as:

  • myproject.settings.local for the local development,
  • myproject.settings.staging for the staging server,
  • myproject.settings.test for testing, and
  • myproject.settings.production for production.

All of them import defaults from a common base, and I have to set only the differences for each environment.

In the myproject.settings.test I added these settings:

WEBSITE_URL = ''  # no trailing slash


Here for the WEBSITE_URL, I was using the service. It allows you to create domains dynamically pointing to the localhost or any other IP. The Selenium tests will use this URL.

The TEST_SHOW_BROWSER was my custom setting, telling whether to show a browser while testing the frontend or just to run the tests in the background.

The test case

In one of my apps, myproject.apps.evaluations, I created a tests package, and there I placed a test case with the following content:

import os
from time import sleep
from datetime import timedelta

from django.conf import settings
from django.test import LiveServerTestCase
from django.test import override_settings
from django.contrib.auth import get_user_model
from django.utils import timezone

from selenium import webdriver
from import Options
from import WebDriverWait

User = get_user_model()

SHOW_BROWSER = getattr(settings, "TESTS_SHOW_BROWSER", False)

class EvaluationTest(LiveServerTestCase):
host = settings.WEBSITE_URL.rsplit(":", 1)[0].replace(
"http://", ""
) # domain before port
port = int(settings.WEBSITE_URL.rsplit(":", 1)[1]) # port
USER1_USERNAME = "user1"
USER1_FIRST_NAME = "user1"
USER1_LAST_NAME = "user1"
USER1_PASSWORD = "change-me"

def setUpClass(cls):
# …

def tearDownClass(cls):
# …

def wait_until_element_found(self, xpath):
# …

def wait_a_little(self, seconds=2):
# …

def test_evaluations(self):
# …

It's a live-server test case, which runs a Django development server under the specified IP and port and then runs the Chrome browser via Selenium and navigates through the DOM and fills in forms.

By default, the LiveServerTestCase runs in non-debug mode, but I want to have the debug mode on so that I could see any causes of server errors. With the @override_settings decorator, I could change the DEBUG setting to True.

The host and port attributes define on which host and port the test server will be running (instead of a and a random port). I extracted those values from the WEBSITE_URL setting.

The test case also had some attributes for the user who will be navigating through the web app.

Let's dig deeper into the code for each method.

Test-case setup and teardown

Django test cases can have class-level setup and teardown, which run before and after all methods whose names start with test_:

def setUpClass(cls):
cls.user1 = User.objects.create_user(
# … add subscription for this new user …

driver_path = os.path.join(settings.BASE_DIR, "drivers", "chromedriver")
chrome_options = Options()

cls.browser = webdriver.Chrome(
executable_path=driver_path, options=chrome_options

def tearDownClass(cls):
# … delete subscription for the user …

In the setup, I created a new user, added a subscription to them, and prepared the Chrome browser to use.

If the TEST_SHOW_BROWSER setting was False, Chrome was running headless, that is, in the background without displaying a browser window.

When the tests were over, the browser closed, and the subscription, as well as the user, were deleted.

Utility methods

I created two utility methods for my Selenium test: wait_until_element_found() and wait_a_little():

    def wait_until_element_found(self, xpath):
WebDriverWait(self.browser, timeout=10).until(
lambda x: self.browser.find_element_by_xpath(xpath)

def wait_a_little(self, seconds=2):

I used the wait_until_element_found(xpath) method to keep the test running while pages switched.

I used the wait_a_little(seconds) method to stop the execution for 2 or more seconds so that I could follow what's on the screen, make some screenshots, or even inspect the DOM in the Web Developer Inspector.


Selenium allows to select DOM elements by ID, name, CSS class, tag name, and other ways, but the most flexible approach, in my opinion, is selecting elements by XPath (XML Path Language).

Contrary to jQuery, ReactJS doesn't use IDs or CSS classes in the markup to update the contents of specific widgets. So the straightforward Selenium's methods for finding elements by IDs or classes won't always work.

XPath is a very flexible and powerful tool. For example, you can:

  • Select elements by ID: "//input[@id='id_title']"
  • Select elements by any other attribute: "//div[@aria-label='Blank']"
  • Select elements by innerText: "//button[.='Save']"
  • Select elements by CSS class and innerText: "//button[contains(@class,'btn-primary')][.='Save']"
  • Select the first element by innerText: "(//button[.='yes'])[1]"

You can try out XPath syntax and capabilities in Web Developer Console in Chrome and Firefox, using the $x() function, for example:

»  $x("//h1[.='Projects']")
← Array [ h1.display-4.mb-4 ]

Login and adding a project

I started with opening a login page, dismissing cookie consent notification, filling in user credentials into the login form, creating a new project from a blank template, setting title and description, etc.

    def test_evaluations(self):
self.wait_until_element_found("//h1[.='Log in or Sign up']")
# Accept Cookie Consent
self.wait_until_element_found("//a[.='Got it!']")
self.browser.find_element_by_xpath("//a[.='Got it!']").click()
# Log in
self.browser.find_element_by_xpath('//button[text()="Log in"]').send_keys(
) # submit the form


# Click on "Add new project"
self.wait_until_element_found("//a[.='Add new project']")

self.browser.find_element_by_xpath("//a[.='Add new project']").send_keys("\n")


# Create a project from the project template "Blank"

# Enter project title and description
"Urgent and Important Activities"
).send_keys("I want to find which things to do and which to skip.")

# Keep the default verbose names for the criteria and initiatives

If TESTS_SHOW_BROWSER was set to True, we would see all this workflow in an opened browser window.

I was creating the test by carefully inspecting the markup in Web Developer Inspector and creating appropriate DOM navigation with XPath. For most of the navigation, I was using send_keys() method, which triggers keyboard events. During the testing, I also noticed that my cookie consent only worked with a mouse click, and I couldn't approve it by the keyboard. That's some room for improving accessibility.

I ran the test with the following command each time I added some more lines:

(venv)$ python test myproject.apps.evaluations --settings=myproject.settings.test

The test case failed if any command in the test failed. I didn't even need asserts.

Adding criteria

Now it was time to add some criteria:


# Add new criterion "Urgent" with the evaluation type Yes/No/Maybe
self.wait_until_element_found("//a[.='Add new criterion']")
self.browser.find_element_by_xpath("//a[.='Add new criterion']").send_keys("\n")
self.browser.find_element_by_xpath("//input[@id='widget_y']").send_keys(" ")

# Add new criterion "Important" with the evaluation type Yes/No/Maybe
self.wait_until_element_found("//a[.='Add new criterion']")
self.browser.find_element_by_xpath("//a[.='Add new criterion']").send_keys("\n")
self.browser.find_element_by_xpath("//input[@id='widget_y']").send_keys(" ")

# Click on the button "Done"

I added two criteria, "Urgent" and "Important", with evaluation type "Yes/No/Maybe".

Defining criteria

Adding things

Then I created some activities to evaluate:


# Add new thing "Write a blog post"
self.wait_until_element_found("//a[.='Add new thing']")
self.browser.find_element_by_xpath("//a[.='Add new thing']").send_keys("\n")
"Write a blog post"
"I have an idea of a blog post that I want to write."

# Add new thing "Fix a bug"
self.wait_until_element_found("//a[.='Add new thing']")
self.browser.find_element_by_xpath("//a[.='Add new thing']").send_keys("\n")
"Fix a bug"
"There is a critical bug that bothers our clients."

# Add new thing "Binge-watch a series"
self.wait_until_element_found("//a[.='Add new thing']")
self.browser.find_element_by_xpath("//a[.='Add new thing']").send_keys("\n")
"Binge-watch a series"
"There is an exciting series that I would like to watch."

# Click on the button "Done"

These were three activities: "Write a blog post", "Fix a bug", and "Binge-watch a series" with their descriptions:

Listing out things

Evaluating things

In this step, there was a list of widgets to evaluate each thing by each criterion with answers "No", "Maybe", or "Yes". The buttons for those answers had no specific id or CSS class, but I could target them by the text on the button using XPath like "//button[.='maybe']":


# Evaluate all things by Urgency
self.wait_until_element_found("//footer[.='Evaluation saved.']")
self.wait_until_element_found("//footer[.='Evaluation saved.']")
self.wait_until_element_found("//footer[.='Evaluation saved.']")

# Evaluate all things by Importance
self.wait_until_element_found("//footer[.='Evaluation saved.']")
self.wait_until_element_found("//footer[.='Evaluation saved.']")
self.wait_until_element_found("//footer[.='Evaluation saved.']")

# Click on the button "Done"

Evaluating things

These were my evaluations:

  • "Write a blog post" was not urgent, but important.
  • "Fix a bug" was urgent and important.
  • "Binge-watch a series" was not urgent and maybe important (because one has to have rest and feed imagination too).

Checking priorities

So in the last step, I got the calculated priorities:


self.wait_until_element_found("//h5[.='1. Fix a bug (100%)']")
self.wait_until_element_found("//h5[.='2. Write a blog post (50%)']")
self.wait_until_element_found("//h5[.='3. Binge-watch a series (25%)']")

Exploring priorities

The results looked correct:

  • "Fix a bug" was of the 100% priority.
  • "Write a blog post" was of the 50% priority.
  • "Binge-watch a series was of the 25% priority.

Final words

  • Selenium needs a binary browser driver that lets you manipulate DOM in the browser from Python.
  • You can set a specific host and port for a LiveServerTestCase.
  • The Chrome browser can be displayed or executed in the background, depending on your settings.
  • XPath is a flexible and powerful tool to address DOM elements by any attributes or even inner text.
  • Selenium can trigger keyboard or mouse events that are handled by JavaScript functions.

I hope that my journey was useful to you too.

Happy coding!

Thanks a lot to Adam Johnson for the review.
Cover photo by Science in HD.

How to Upload a File Using Django REST Framework

Par Aidas Bendoraitis a.k.a. archatas
How to Upload a File Using Django REST Framework

When you develop a web app or a mobile app with Django, it is common to use the Django REST Framework for communication with the server-side. The client-side makes GET, POST, PUT, and DELETE requests to the REST API to read, create, update, or delete data there. The communication by Ajax is pretty uncomplicated, but how would you upload an image or another file to the server? I will show you that in this article by creating user avatar upload via REST API. Find the full code for this feature on Github.

Extend Django User model

We will start by installing Pillow for image handling to the virtual environment using the standard pip command:

(venv)$ pip install Pillow

Create accounts app with a custom User model:

# myproject/apps/accounts/
import os
import sys
from django.db import models
from django.contrib.auth.models import AbstractUser
from django.utils import timezone
from django.utils.translation import gettext_lazy as _

def upload_to(instance, filename):
now =
base, extension = os.path.splitext(filename.lower())
milliseconds = now.microsecond // 1000
return f"users/{}/{now:%Y%m%d%H%M%S}{milliseconds}{extension}"

class User(AbstractUser):
# …
avatar = models.ImageField(_("Avatar"), upload_to=upload_to, blank=True)

You can add there as many fields as you need, but the noteworthy part there is the avatar field.

Update the settings and add the accounts app to INSTALLED_APPS, set the AUTH_USER_MODEL, and the configuration for the static and media directories:

# myproject/
# …

AUTH_USER_MODEL = "accounts.User"

STATICFILES_DIRS = [os.path.join(BASE_DIR, "myproject", "site_static")]
STATIC_ROOT = os.path.join(BASE_DIR, "myproject", "static")
STATIC_URL = "/static/"
MEDIA_ROOT = os.path.join(BASE_DIR, "myproject", "media")
MEDIA_URL = "/media/"

Next small steps:

  • Create and run migrations with the makemigrations and migrate management commands.
  • Set up the custom model administration for the new User model.
  • Create the superuser with the createsuperuser management command.

Install and configure Django REST Framework

Install Django REST Framework for the REST APIs to your virtual environment, as always, using pip:

(venv)$ pip install djangorestframework

We'll be using authentication by tokens in this example. So add Django REST Framework to INSTALLED_APPS in the settings and set TokenAuthentication as the default authentication in the REST_FRAMEWORK configuration:

# myproject/
# …
# …


Prepare the serializer and the view

In Django REST Framework, serializers are used for data validation, rendering, and saving. They are similar to Django forms. Prepare UserAvatarSerializer for avatar uploads:

# myproject/apps/accounts/
from django.contrib.auth import get_user_model
from rest_framework.serializers import ModelSerializer
User = get_user_model()

class UserAvatarSerializer(ModelSerializer):
class Meta:
model = User
fields = ["avatar"]

def save(self, *args, **kwargs):
if self.instance.avatar:
return super().save(*args, **kwargs)

Now create an API view UserAvatarUpload for avatar uploads.

# myproject/apps/accounts/
from rest_framework import status
from rest_framework.parsers import MultiPartParser, FormParser
from rest_framework.permissions import IsAuthenticated
from rest_framework.response import Response
from rest_framework.views import APIView
from .serializers import UserAvatarSerializer

class UserAvatarUpload(APIView):
parser_classes = [MultiPartParser, FormParser]
permission_classes = [IsAuthenticated]

def post(self, request, format=None):
serializer = UserAvatarSerializer(, instance=request.user)
if serializer.is_valid():
return Response(, status=status.HTTP_200_OK)
return Response(serializer.errors, status=status.HTTP_400_BAD_REQUEST)

Make sure that the view uses MultiPartParser as one of the parser classes. That's necessary for the file transfers.

Prepare the URL configuration

In the URL configuration, we will need those URL rules:

  • The path for the index page. Let's make it a direct TemplateView.
  • The path for logging in by user credentials and obtaining the authentication token.
  • The path for user avatar upload.
  • The path for model administration.
  • The path for static URLs.
  • And finally, the path for media URLs.
# myroject/
from django.conf.urls.static import static
from django.contrib import admin
from django.urls import path
from django.views.generic import TemplateView
from django.conf import settings
from myproject.accounts.views import UserAvatarUpload
from rest_framework.authtoken.views import obtain_auth_token

urlpatterns = [
path("", TemplateView.as_view(template_name="index.html")),
path("api/auth-token/", obtain_auth_token, name="rest_auth_token"),
path("api/user-avatar/", UserAvatarUpload.as_view(), name="rest_user_avatar_upload"),

urlpatterns += static(settings.STATIC_URL, document_root=settings.STATIC_ROOT)
urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)

Prepare the frontend HTML and JavaScript

I will illustrate the frontend using Bootstrap HTML and Vanilla JavaScript. Of course, you can implement the same using ReactJS, Vue, Angular, or other JavaScript framework and any other CSS framework.

The template for the index page has one login form with username and password or email and password fields (depending on your implementation), and one avatar upload form with a file selection field. Also, it includes a JavaScript file avatar.js for Ajax communication.

{# myproject/templates/index.html #}
<!doctype html>
{% load static %}
<html lang="en">
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">

<link rel="stylesheet" href=""
integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh" crossorigin="anonymous">

<title>Hello, World!</title>
<div class="container">
<div class="row">
<div class="col-md-8">
<p class="text-muted my-3"><small>Open Developer Console for information about responses.</small></p>
<h1 class="my-3">1. Log in</h1>
<form id="login_form">
<div class="form-group">
<label for="id_email">Email address</label>
<input type="email" class="form-control" id="id_email" aria-describedby="emailHelp"
placeholder="Enter email"/>
<div class="form-group">
<label for="id_password">Password</label>
<input type="password" class="form-control" id="id_password" placeholder="Password"/>
<button type="submit" class="btn btn-primary">Log in</button>

<h1 class="my-3">2. Upload an avatar</h1>
<form id="avatar_form">
<div class="form-group">
<label for="id_avatar">Choose an image for your avatar</label>
<input type="file" class="form-control-file" id="id_avatar"/>
<button type="submit" class="btn btn-primary">Upload</button>

<script src="{% static 'site/js/avatar.js' %}"></script>

Last but not least, create the JavaScript file avatar.js. It contains these things:

  • a global variable to store the user token. In the real-world application, you would probably save the token in a cookie or local storage.
  • a login-form submit handler which posts user credentials to the server and retrieves the authentication token.
  • an avatar-form submit handler which posts the selected file and the token to the server and retrieves the path of the saved file on the server.
// myproject/site_static/site/js/avatar.js
let userToken;

document.getElementById('login_form').addEventListener('submit', function(event) {
let email = document.getElementById('id_email').value;
let password = document.getElementById('id_password').value;

fetch('', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
body: JSON.stringify({
"username": email,
"password": password,
}).then( response => {
return response.json();
}).then(data => {
userToken = data.token;
console.log('Logged in. Got the token.');
}).catch((error) => {
console.error('Error:', error);

document.getElementById('avatar_form').addEventListener('submit', function(event) {
let input = document.getElementById('id_avatar');

let data = new FormData();
data.append('avatar', input.files[0]);

fetch('', {
method: 'POST',
headers: {
'Authorization': `Token ${userToken}`
body: data
}).then(response => {
return response.json();
}).then(data => {
}).catch((error) => {
console.error('Error:', error);

In the JavaScript file, we are using fetch API for the REST API requests. The noteworthy part there is the FormData class that we use to send the file to the server.

Now run the local development server and go to the There you will have something like this:

The frontend of the experiment

Final Thoughts

As more than a half Internet usage happens on mobile devices, there is a demand to switch from usual HTML websites and platforms to mobile apps. Whether you create a native mobile app, a hybrid app, or Progressive Web App, you will likely have to communicate with the server via REST API or GraphQL. It is pretty clear how to transfer textual data from and to a remote server. But after this exercise, we can also transfer binary files like images, PDF or Word documents, music, and videos.

Happy coding!

Cover Photo by Dan Silva

Guest Post: Sending Emails with Django

Par Aidas Bendoraitis a.k.a. archatas

This is a guest post by team. The original post on Sending emails with Django was published at Mailtrap's blog.

Some time ago, we discovered how to send an email with Python using smtplib, a built-in email module. Back then, the focus was made on the delivery of different types of messages via SMTP server. Today, we prepared a similar tutorial but for Django. This popular Python web framework allows you to accelerate email delivery and make it much easier. And these code samples of sending emails with Django are going to prove that.

A simple code example of how to send an email

Let's start our tutorial with a few lines of code that show you how simple it is to send an email in Django. 

Import send_mail at the beginning of the file

from django.core.mail import send_mail

And call the code below in the necessary place.

    "That's your subject",
    "That's your message body",

These lines are enclosed in the django.core.mail module that is based on smtplib. The message delivery is carried out via SMTP host, and all the settings are set by default:

  • EMAIL_HOST: "localhost"
  • EMAIL_PORT: 25
  • EMAIL_HOST_USER: (Empty string)
  • EMAIL_HOST_PASSWORD: (Empty string)
  • EMAIL_USE_TLS: False
  • EMAIL_USE_SSL: False

You can learn other default values here. Most likely you will need to adjust them. Therefore, let's tweak the file.

Setting up

Before actually sending your email, you need to set up for it. So, let's add some lines to the file of your Django app.

EMAIL_BACKEND = "django.core.mail.backends.smtp.EmailBackend"
EMAIL_PORT = "<your-server-port>"
EMAIL_HOST_PASSWORD = "your-email account-password"

EMAIL_HOST is different for each email provider you use. For example, if you use Gmail SMTP server, you'll have EMAIL_HOST = "". Also, validate other values that are relevant to your email server. Eventually, you need to choose the way to encrypt the mail and protect your user account by setting the variable EMAIL_USE_TLS or EMAIL_USE_SSL. If you have an email provider that explicitly tells you which option to use, then it is clear. Otherwise, you may try different combinations using True and False operators. Mind that only one of these options can be set to True.

EMAIL_BACKEND tells Django which custom or predefined email backend will work with EMAIL_HOST. You can set up this parameter as well. 

SMTP email backend 

In the example above, EMAIL_BACKEND is specified as django.core.mail.backends.smtp.EmailBackend. It is the default configuration that uses SMTP server for email delivery. Defined email settings will be passed as matching arguments to EmailBackend. 

Unspecified arguments default to None

Besides django.core.mail.backends.smtp.EmailBackend, you can use:

  • django.core.mail.backends.console.EmailBackend - the console backend that composes the emails that will be sent to the standard output. Not intended for production use.
  • django.core.mail.backends.filebased.EmailBackend - the file backend that creates emails in the form of a new file per each new session opened on the backend. Not intended for production use.
  • django.core.mail.backends.locmem.EmailBackend - the in-memory backend that stores messages in the local memory cache of django.core.mail.outbox. Not intended for production use.
  • django.core.mail.backends.dummy.EmailBackend - the dummy cache backend that implements the cache interface and does nothing with your emails. Not intended for production use.
  • Any out-of-the-box backend for Amazon SES, Mailgun, SendGrid, and other services. 

How to send emails via SMTP 

Once you have that configured, all you need to do to send an email is to import the send_mail or send_mass_mail function from django.core.mail. These functions differ in the connection they use for messages. The send_mail uses a separate connection for each message. The send_mass_mail opens a single connection to the mail server and is mostly intended to handle mass emailing. 

Sending email with send_mail

This is the most basic function for email delivery in Django. It comprises four obligatory parameters to be specified: subject, message, from_email, and recipient_list

In addition to them, you can adjust the following:

  • auth_user: If EMAIL_HOST_USER has not been specified, or you want to override it, this username will be used to authenticate to the SMTP server. 
  • auth_password: If EMAIL_HOST_PASSWORD has not been specified, this password will be used to authenticate to the SMTP server.
  • connection: The optional email backend you can use without tweaking EMAIL_BACKEND.
  • html_message: Lets you send multipart emails.
  • fail_silently: A boolean that controls how the backend should handle errors. If True - exceptions will be silently ignored. If False - smtplib.SMTPException will be raised. 

For example, it may look like this:

from django.core.mail import send_mail

    subject="That's your subject",
    message="That's your message body",

Other functions for email delivery include mailadmins and mailmanagers. Both are shortcuts to send emails to the recipients predefined in ADMINS and MANAGERS settings, respectively. For them, you can specify such arguments as subject, message, fail_silently, connection, and html_message. The from_email argument is defined by the SERVER_EMAIL setting.

What is EmailMessage for? 

If the email backend handles the email sending, the EmailMessage class answers for the message creation. You'll need it when some advanced features like BCC or an attachment are desirable. That's how an initialized EmailMessage may look:

from django.core.mail import EmailMessage

email = EmailMessage(
    subject="That's your subject",
    body="That's your message body",

In addition to the EmailMessage objects you can see in the example, there are also other optional parameters:

  • connection: defines an email backend instance for multiple messages. 
  • attachments: specifies the attachment for the message.
  • headers: specifies extra headers like Message-ID or CC for the message. 
  • cc: specifies email addresses used in the "CC" header.

The methods you can use with the EmailMessage class are the following:

  • send: get the message sent.
  • message: composes a MIME object (django.core.mail.SafeMIMEText or django.core.mail.SafeMIMEMultipart).
  • recipients: returns a list of the recipients specified in all the attributes including to, cc, and bcc.
  • attach: creates and adds a file attachment. It can be called with a MIMEBase instance or a triple of arguments consisting of filename, content, and mime type.
  • attach_file: creates an attachment using a file from a filesystem. We'll talk about adding attachments a bit later.

How to send multiple emails

To deliver a message via SMTP, you need to open a connection and close it afterward. This approach is quite awkward when you need to send multiple transactional emails. Instead, it is better to create one connection and reuse it for all messages. This can be done with the send_messages method. Check out the following example:

from django.core import mail

connection = mail.get_connection()

email1 = mail.EmailMessage(
    "That's your subject",
    "That's your message body",

email2 = mail.EmailMessage(
    "That's your subject #2",
    "That's your message body #2",
email3 = mail.EmailMessage(
   "That's your subject #3",
    "That's your message body #3",
connection.send_messages([email2, email3])

What you can see here is that the connection was opened for email1, and send_messages uses it to send emails #2 and #3. After that, you close the connection manually.

How to send multiple emails with sendmassmail

send_mass_mail is another option to use only one connection for sending different messages.

message1 = (
"That's your subject #1", 
  "That's your message body #1",
  ["", ""]

message2 = (
"That's your subject #2",
  "That's your message body #2",

message3 = (
"That's your subject #3",
"That's your message body #3",

send_mass_mail((message1, message2, message3), fail_silently=False)

Each email message contains a datatuple made of subject, message, from_email, and recipient_list. Optionally, you can add other arguments that are the same as for send_mail.

How to send an HTML email

When the article was published, the latest Django official version was 2.2.4. All versions starting from 1.7 let you send an email with HTML content using send_mail like this:

from django.core.mail import send_mail

subject = "That's your subject" 
html_message = render_to_string("mail_template.html", {"context": "values"})
plain_message = strip_tags(html_message)
from_email = ">"
to = ""

mail.send_mail(subject, plain_message, from_email, [to], html_message=html_message)

Older versions users will have to mess about with EmailMessage and its subclass EmailMultiAlternatives. It lets you include different versions of the message body using the attach_alternative method. For example:

from django.core.mail import EmailMultiAlternatives

subject = "That's your subject"
from_email = ">" 
to = ""
text_content = "That's your plain text."
html_content = """<p>That's <strong>the HTML part</strong></p>"""
message = EmailMultiAlternatives(subject, text_content, from_email, [to])
message.attach_alternative(html_content, "text/html")

How to send an email with attachments 

In the EmailMessage section, we've already mentioned sending emails with attachments. This can be implemented using attach or attach_file methods. The first one creates and adds a file attachment through a triple of arguments - filename, content, and mime type. The second method uses a file from a filesystem as an attachment. That's how each method would look like in practice:

message.attach("Attachment.pdf", file_to_be_sent, "file/pdf")



Custom email backend

Obviously, you're not limited to the abovementioned email backend options and are able to tailor your own. For this, you can use standard backends as a reference. Let's say you need to create a custom email backend with the SMTP_SSL connection support required to interact with Amazon SES. The default SMTP backend will be the reference. First, add a new email option to

AWS_ACCESS_KEY_ID = "your-aws-access-key-id"
AWS_SECRET_ACCESS_KEY = "your-aws-secret-access-key"
AWS_REGION = "your-aws-region"
EMAIL_BACKEND = "your_project_name.email_backend.SesEmailBackend"

Make sure that you are allowed to send emails with Amazon SES using these AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY (or an error message will tell you about it :D)

Then create a file your_project_name/ with the following content:

import boto3

from django.core.mail.backends.smtp import EmailBackend
from django.conf import settings

class SesEmailBackend(EmailBackend):
def __init__(
     self.connection = boto3.client(

   def send_messages(self, email_messages):
     for email_message in email_messages:
         RawMessage={"Data": email_message.message().as_bytes(linesep="\r\n")}

This is the minimum needed to send an email using SES. Surely you will need to add some error handling, input sanitization, retries, etc. but this is out of our topic. 

You might see that we have imported boto3 at the beginning of the file. Don't forget to install it using a command

pip install boto3

It's not necessary to reinvent the wheel every time you need a custom email backend. You can find already existing libraries, or just receive SMTP credentials in your Amazon console and use default email backend. 

Sending emails using SES from Amazon

So far, you can benefit from several services that allow you to send transactional emails at ease. If you can't choose one, check out our blogpost about Sendgrid vs. Mandrill vs. Mailgun. It will help a lot. But today, we'll discover how to make your Django app send emails via Amazon SES. It is one of the most popular services so far. Besides, you can take advantage of a ready-to-use Django email backend for this service - django-ses.

Set up the library

You need to execute pip install django-ses to install django-ses. Once it's done, tweak your with the following line:

EMAIL_BACKEND = "django_ses.SESBackend"

AWS credentials

Don't forget to set up your AWS account to get the required credentials - AWS access keys that consist of access key ID and secret access key. For this, add a user in Identity and Access Management (IAM) service. Then, choose a user name and Programmatic access type. Attach AmazonSESFullAccess permission and create a user. Once you've done this, you should see AWS access keys. Update your

AWS_ACCESS_KEY_ID = "********"

Email sending

Now, you can send your emails using django.core.mail.send_mail:

from django.core.mail import send_mail

    "That's your subject",
    "That's your message body",

django-ses is not the only preset email backend you can leverage. At the end of our article, you'll find more useful libraries to optimize email delivery of your Django app. But first, a step you should never send emails without.

Testing email sending in Django 

Once you've got everything prepared for sending email messages, it is necessary to do some initial testing of your mail server. In Python, this can be done with one command:

python -m smtpd -n -c DebuggingServer localhost:1025

It allows you to send emails to your local SMTP server. The DebuggingServer feature won't actually send the email but will let you see the content of your message in the shell window. That's an option you can use off-hand.

Django's TestCase

TestCase is a solution to test a few aspects of your email delivery. It uses django.core.mail.backends.locmem.EmailBackend, which, as you remember, stores messages in the local memory cache - django.core.mail.outbox. So, this test runner does not actually send emails. Once you've selected this email backend

EMAIL_BACKEND = "django.core.mail.backends.locmem.EmailBackend"

you can use the following unit test sample to test your email sending capability.

from django.core import mail
from django.test import TestCase

class EmailTest(TestCase):
    def test_send_email(self):
            "That's your subject", "That's your message body",
            "", [""],

        self.assertEqual(len(mail.outbox), 1)        
        self.assertEqual(mail.outbox[0].subject, "That's your subject")
        self.assertEqual(mail.outbox[0].body, "That's your message body")

This code will test not only your email sending but also the correctness of the subject and message body. 

Testing with Mailtrap

Mailtrap can be a rich solution for testing. First, it lets you test not only the SMTP server but also the email content and do other essential checks from the email testing checklist. Second, it is a rather easy-to-use tool.

All you need to do is to copy the SMTP credentials from your demo inbox and tweak your Or you can just copy/paste these four lines from the Integrations section by choosing Django in the pop-up menu.

EMAIL_HOST_USER = "********"
EMAIL_PORT = "2525"

After that, feel free to send your HTML email with an attachment to check how it goes.

from django.core.mail import EmailMultiAlternatives
from django.template.loader import render_to_string

subject = "That's your subject" 
html_message = render_to_string("mail_template.html", {"context": "values"})
plain_message = strip_tags(html_message)
from_email = ""
to_email = ""
message = EmailMultiAlternatives(subject, plain_message, from_email, [to_email])
message.attach_alternative(html_message, "text/html")

If there is no message in the Mailtrap Demo inbox or there are some issues with HTML content, you need to polish your code. 

Django email libraries to simplify your life

As a conclusion to this blog post about sending emails with Django, we've included a brief introduction of a few libraries that will facilitate your email workflow. 


This is a collection of email backends and webhooks for numerous famous email services, including SendGrid, Mailgun, and others. django-anymail works with django.core.mail module and normalizes the functionality of transactional email service providers.


django-mailer is a Django app you can use to queue the email sending. With it, scheduling your emails is much easier.


With this app, you can send and manage your emails. django-post_office offers many cool features like asynchronous email sending, built-in scheduling, multiprocessing, etc.


This app is about sending templated emails. In addition to its own functionalities, django-templated-email can be used in tow with django-anymail to integrate transactional email service providers.


You might use django-mailbox if you need to import messages from local mailboxes, POP3, IMAP, or directly receive messages from Postfix or Exim4.

We hope that this small list of packages will facilitate your email workflow. You can always find more apps at Django Packages.

Cover Photo by Chris Ried

Things I want to remember about SSH

Par Aidas Bendoraitis a.k.a. archatas

SSH, short for Secure Shell, is a protocol for secure network communications. It is widely used for executing commands on remote servers, and for file uploads or downloads. If you are working with Django, use Git version control, or administrate servers, you surely are using SSH. In this post, I want to share some technical details about it.

Secure Shell is using private and public key pairs. You can either use automatically generated private and public keys combined with a password, or manually generated private and public keys. In the latter case, you need to keep your private key on your computer and upload the public key to the remote server.

Creating a pair of SSH keys manually

If you are using GitHub, Bitbucket, DigitalOcean, or some other service, you might have seen the possibility to upload public SSH keys for direct access to remote servers.

Here is how you usually create the SSH keys on the computer from which you want to establish a secure connection (your local machine or one of your servers that has access to other servers or services). In the Terminal you would execute these commands:

$ ssh-keygen
$ ssh-agent /usr/local/bin/bash
$ ssh-add ~/.ssh/id_rsa

The id_rsa is the name of the default SSH private key. The public key would be And by default they both will be located under ~/.ssh/.

When running ssh-keygen you can choose different key names and even add a passphrase. For instance, you could have github_id_rsa and keys for communication with GitHub. My recommendation would be for each new service to create a new private-public key pair so that in case you need to transfer your computer's data to a different machine, you could selectively transfer the access to the remote servers.

Also, if you are not using the passphrase for the SSH key pair, I would recommend having your disk encrypted and a secure user password for your computer. If your laptop gets stolen, the thief wouldn't be able to get to your remote servers without knowing your computer's password.

Creating an access to a remote server by SSH key

In the case of GitHub, Bitbucket, and other online services with SSH communication, you usually have to copy the contents of the public key into a text field in a web form.

If you want to create a secure communication by manually generated private-public keys with a server where your Django project is deployed, you should append the contents of the public key to the ~/.ssh/authorized_keys file on the remote server.

To get the content of the public key in the Terminal, you can use:

$ cat ~/.ssh/

Then copy the output to the clipboard.

Or on macOS you can run pbcopy as follows:

$ pbcopy < ~/.ssh/ 

To append the contents of the public key to the remote server, you can do this:

$  echo "...pasted public key...">>~/.ssh/authorized_keys

Creating authorization at a remote server by password

If you want to establish an SSH connection with a password and automatically generated private-public keys, you would need to edit /etc/ssh/sshd_config and ensure these two settings:

PasswordAuthentication yes
PermitEmptyPasswords no

After the change, you would restart the ssh server with the following command:

$ sudo service ssh restart

Also, make sure that the user you are connecting with has a password:

$ sudo passwd the_user

Connecting to a remote server

The default way to connect via SSH to a remote server with a password is executing the following in the Terminal:

$ ssh

To connect with a private key, you would execute this:

$ ssh -i ~/.ssh/examplecom_id_rsa

Next, let's see how we can simplify this using some local SSH configuration.

Configuring local SSH client

Edit ~/.ssh/config and add the following lines for each SSH connection that you want to define:

Host examplecom
User the_user
IdentityFile ~/.ssh/examplecom_id_rsa

If the domain of the website is not yet pointing to the IP address of the server, you can also connect by IP address:

Host examplecom
User the_user
IdentityFile ~/.ssh/examplecom_id_rsa

The following allows you to login to your remote servers by manually generated private-public key with just these lines:

$ ssh examplecom

To request for password instead of using the manually generated keys, you would need to modify the snippet as follows:

Host examplecom
User the_user

When you connect via SSH and wait don't type anything for 30 minutes or so, the connection gets lost. But you can require your client to connect to the server every 4 minutes or so by adding the following lines to the beginning of the ~/.ssh/config on your local computer:

Host *
ServerAliveInterval 240

Uploading and downloading files using SSH connection

Typically, Secure Shell allows you to execute terminal commands on the remote server using bash, zsh, sh, or another shell. But very often, you also need to transfer files securely to and from the server. For that, you have these options: scp command, rsync command, or FTP client with SFTP support.


The scp stands for Secure Copy.

This is how you would copy the secrets.json file from the remote server to your local development environment:

$ scp ./myproject/settings/secrets.json

Here is an example of the same, but with custom ~/.ssh/config configuration:

$ scp examplecom:~/src/myproject/myproject/settings/secrets.json ./myproject/settings/secrets.json

To copy the file from the local computer to the remote server, you would switch the places of source and target:

$ scp ./myproject/settings/secrets.json examplecom:~/src/myproject/myproject/settings/secrets.json


To synchronize directories on the server and locally, you can use the rsync command. This is how to do it for downloading the media/ directory (note that the trailing slashes matter):

$ rsync --archive --compress --partial --progress ./myproject/media/

Here is an example of the same with a custom ~/.ssh/config configuration:

$ rsync --archive --compress --partial --progress examplecom:~/src/myproject/myproject/media/ ./myproject/media/

To upload the media/ directory to the remote server, you would again switch places for the source and target:

$ rsync --archive --compress --partial --progress ./myproject/media/ examplecom:~/src/myproject/myproject/media/


FTP clients like Transmit allow you to have SFTP connections either by username and password or by username and private key. You can even generate the private-public keys directly in the app there.

SFTP works like FTP, but all communication is encrypted there.

The final words

Use only encrypted connections for your network communications, encrypt your hard disk if you use manually generated private-public keys, and use strong passwords.

Be safe!

Cover photo by Jason D.

Working with Dates and Times in the Forms

Par Aidas Bendoraitis a.k.a. archatas

HTML5 comes with a bunch of new types for the input fields that are rendered as rich native widgets. Browsers even restrict invalid values and validate the input immediately. Let's explore how we could make use of them in Django forms.

We will be using an Exhibition model with models.DateField, models.TimeField, and models.DateTimeField:

# exhibitions/
from django.db import models
from django.utils.translation import gettext_lazy as _

class Exhibition(models.Model):
title = models.CharField(_("Title"), max_length=200)
start = models.DateField(_("Start"))
end = models.DateField(_("End"), blank=True, null=True)
opening = models.TimeField(_("Opening every day"))
closing = models.TimeField(_("Closing every day"))
vernissage = models.DateTimeField(_("Vernissage"), blank=True, null=True)
finissage = models.DateTimeField(_("Finissage"), blank=True, null=True)

class Meta:
verbose_name = _("Exhibition")
verbose_name_plural = _("Exhibitions")

def __str__(self):
return self.title

Here is a quick model form for the Exhibition model:

# exhibitions/
from django import forms
from .models import Exhibition

class ExhibitionForm(forms.ModelForm):
class Meta:
model = Exhibition
fields = "__all__"

If we now open a Django shell and create an instance of the model form with some initial values, then print the form as HTML to the console, we will notice, that all date and time fields are rendered as <input type="text" /> and the values for the dates are in a local format, not the ISO standard YYYY-MM-DD:

(venv)$ python shell
>>> from exhibitions.forms import ExhibitionForm
>>> from datetime import datetime, date, time
>>> form = ExhibitionForm(initial={
... "start": date(2020, 1, 1),
... "end": date(2020, 3, 31),
... "opening": time(11, 0),
... "closing": time(20, 0),
... "vernissage": datetime(2019, 12, 27, 19, 0),
... "finissage": datetime(2020, 4, 1, 19, 0),
>>> })
>>> print(form.as_p())
<p><label for="id_title">Title:</label> <input type="text" name="title" maxlength="200" required id="id_title"></p>
<p><label for="id_start">Start:</label> <input type="text" name="start" value="01.01.2020" required id="id_start"></p>
<p><label for="id_end">End:</label> <input type="text" name="end" value="31.03.2020" id="id_end"></p>
<p><label for="id_opening">Opening every day:</label> <input type="text" name="opening" value="11:00:00" required id="id_opening"></p>
<p><label for="id_closing">Closing every day:</label> <input type="text" name="closing" value="20:00:00" required id="id_closing"></p>
<p><label for="id_vernissage">Vernissage:</label> <input type="text" name="vernissage" value="27.12.2019 19:00:00" id="id_vernissage"></p>
<p><label for="id_finissage">Finissage:</label> <input type="text" name="finissage" value="01.04.2020 19:00:00" id="id_finissage"></p>

Let's modify the model form and customize the date and time inputs. We will extend and use forms.DateInput, forms.TimeInput, and forms.DateTimeInput widgets. We want to show date inputs as <input type="date" />, time inputs as <input type="time" />, and date-time inputs as <input type="datetime-local" />. In addition, the format for the dates should be based on ISO standard.

# exhibitions/
from django import forms
from .models import Exhibition

class DateInput(forms.DateInput):
input_type = "date"

def __init__(self, **kwargs):
kwargs["format"] = "%Y-%m-%d"

class TimeInput(forms.TimeInput):
input_type = "time"

class DateTimeInput(forms.DateTimeInput):
input_type = "datetime-local"

def __init__(self, **kwargs):
kwargs["format"] = "%Y-%m-%dT%H:%M"

class ExhibitionForm(forms.ModelForm):
class Meta:
model = Exhibition
fields = "__all__"

def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.fields["start"].widget = DateInput()
self.fields["end"].widget = DateInput()
self.fields["opening"].widget = TimeInput()
self.fields["closing"].widget = TimeInput()
self.fields["vernissage"].widget = DateTimeInput()
self.fields["vernissage"].input_formats = ["%Y-%m-%dT%H:%M", "%Y-%m-%d %H:%M"]
self.fields["finissage"].widget = DateTimeInput()
self.fields["finissage"].input_formats = ["%Y-%m-%dT%H:%M", "%Y-%m-%d %H:%M"]

Let's see now in the Django shell if that worked as expected:

(venv)$ python shell
>>> from exhibitions.forms import ExhibitionForm
>>> from datetime import datetime, date, time
>>> form = ExhibitionForm(initial={
... "start": date(2020, 1, 1),
... "end": date(2020, 3, 31),
... "opening": time(11, 0),
... "closing": time(20, 0),
... "vernissage": datetime(2019, 12, 27, 19, 0),
... "finissage": datetime(2020, 4, 1, 19, 0),
>>> })
>>> print(form.as_p())
<p><label for="id_title">Title:</label> <input type="text" name="title" maxlength="200" required id="id_title"></p>
<p><label for="id_start">Start:</label> <input type="date" name="start" value="2020-01-01" required id="id_start"></p>
<p><label for="id_end">End:</label> <input type="date" name="end" value="2020-03-31" id="id_end"></p>
<p><label for="id_opening">Opening every day:</label> <input type="time" name="opening" value="11:00:00" required id="id_opening"></p>
<p><label for="id_closing">Closing every day:</label> <input type="time" name="closing" value="20:00:00" required id="id_closing"></p>
<p><label for="id_vernissage">Vernissage:</label> <input type="datetime-local" name="vernissage" value="2019-12-27T19:00" id="id_vernissage"></p>
<p><label for="id_finissage">Finissage:</label> <input type="datetime-local" name="finissage" value="2020-04-01T19:00" id="id_finissage"></p>

The same way you can also create widgets for other HTML5 input types: color, email, month, number, range, tel, url, week, and alike.

Happy coding!

Cover photo by Eric Rothermel.

My 5 Favorite Talks at DjangoCon Europe 2019

Par Aidas Bendoraitis a.k.a. archatas
Django people at the DjangoCon Europe 2019

This year DjangoCon Europe happened in Copenhagen, Denmark, at a very creative and special place AFUK - Academy for Untamed Creativity. Surrounded by artistic souls, we learned more about web technologies, got to know each other at ecologic reusable disposable cups of coffee, enjoyed delicious authentic food, and socialized with Django-branded beverages. As always, there was also a party with people drinking IPA (not to be confused with API). And at the weekend Django developers were solving bugs for Django and related open-source software at the coding sprints.

Here I would like to present you with the top 5 talks that I liked most of all.

Django and Web Security Headers

Adam Johnson (@AdamChainz) was talking about special response headers that tell browsers to treat data of the website more securely and which Django settings are responsible for those headers.

Summary by rixx

Docs or it didn't Happen!

Mikey Ariel (@ThatDocsLady) was talking about the necessity of documentation and what to write there.

Summary by rixx

Pushing the ORM to its Limits

Sigurd Ljødal (@sigurdlj) was talking about advanced Django ORM use cases.

Summary by rixx

Logging Rethought 2: The Actions of Frank Taylor Jr.

Markus Holtermann (@m_holtermann) was talking about logging structured data to log files instead of the traditional plain text messages.

Summary by rixx

Maintaining a Django Codebase after 10k Commits

Joachim Jablon (@Ewjoachim) and Stéphane Angel (@twidi) were talking about the best practices developing large-scale Django projects.

Summary by rixx

Honorable Mentions

More Information

You can see all talk descriptions, video records and some slides at the official conference website.

Amazing conference photos were taken by Bartek Pawlik.

I was also really astonished how effective were the talk summaries written by rixx almost in real time.

Cover photo by Bartek Pawlik.

Improving Page Speed with Incremental Loading

Par Aidas Bendoraitis a.k.a. archatas
Improving Page Speed with Incremental Loading

Summary: you can use django-include-by-ajax to improve the performance and usability of your website by forcing some parts of the Django website page to be loaded and shown before other parts of the page.

Web browsers load and render traditional HTML pages from top to down, from left to right and as a developer you have little control over what will be shown first, second, and last. However, sometimes you need a different loading sequence to improve user experience and usability. Let's examine a couple of cases when it is advantageous to have primary content showing up immediately and secondary content loading in a moment.

Case 1. Above the Fold vs. Below the Fold

People want speed. 47% of visitors expect the website to be loaded in less than 2 seconds. If the website takes more than 3 seconds to show up, it's a big chance, that you will lose 40% of visitors. If you sell something on your website, every one-second delay causes 7% fewer visitors becoming buyers.

One technique to improve the perception of the speed of the website is to display the visible part of the screen as soon as possible, and then load the rest of the website in another go. Usually, the website pages are long vertically scrollable areas. The part of it that fits in the screen is called "above the fold" and the part underneath is called "below the fold".

Primary content above the fold and secondary content below the fold

It is recommended to load the part above the fold in 6 requests, including all your HTML, CSS, JavaScript, images and fonts. It's only 6 requests for a reason - that's the maximal number of requests that most browsers keep to the same HTTP/1.1 server at the same time. With HTTP/2 there is no such limitation.

You can only achieve this minimal load if you bundle and minimize your CSS and JavaScript to single files, and use only a couple of images and fonts. Going one step further you can split your CSS and JavaScript into parts that are used above the fold, and the ones that are used below the fold.

Case 2. Main Content vs. Navigation

For the users to have best user experience and smooth loading, you could display the content of articles or blog post first, and then load and display the website navigation in the header, sidebars, or footer.

Content is primary and the navigation is secondary

If the visitor navigated to a specific page of your website, they most likely want to see the content of that page rather than navigate out to other pages.

If you have extensive nested navigation, you can also save some milliseconds of its loading at the first request, by skipping it there, but loading it by Ajax at the next go.

Additionally, if visitor disables JavaScript in their browser, they will still be able to read the content.

Case 3. Own Content vs. Third-party Content

Wouldn't you agree, websites that show ads before their own content are pretty annoying? One way to improve the user experience is to show the main content at first and show the ads or third-party widgets after several seconds.

Own content is primary and third-party widgets are secondary

The primary content will be correctly indexed by search engines, whereas the included widgets might be skipped, depending on implementation, which we'll examine next.

Solution 1. Iframes

One way to load the delayed secondary content is to use iframes.


  • Works without JavaScript.


  • For each iframed section, you need a separate HTML with custom CSS.
  • You have to predefine and hardcode all heights of each secondary section, so it wouldn't work well with increased or decreased font size or different amounts of content.
  • You cannot have interactive elements like tooltips that would go outside the boundaries of the iframe.

Solution 2. API Calls by Ajax

The page would load with empty placeholders for the secondary content and then some JavaScript function would load content for the missing sections in HTML, JSON, or XML format by Ajax, parse them, and include into the placeholders. This approach has been used by Facebook.


  • You can use the same global CSS for everything.
  • The amount of content is flexible, so the designs would look good with different variations.


  • For each secondary section, you need to define a separate API endpoint.
  • There are many extra requests (unless you use GraphQL for that).

Solution 3. A Second Request to the Same Page with Specific Query Parameters

The page loads with empty placeholders for the secondary content. A JavaScript function uses Ajax to load the HTML of the same page this time containing all rendered primary and secondary content. Then another JavaScript function goes through all placeholders and fills the content from the second load.


  • You can use the same global CSS for everything.
  • The amount of content is flexible, so the designs could look good with different variations.
  • Each page uses a single data endpoint.
  • Only one extra request is necessary for the full HTML.


  • If there is a lot of primary content and not so much of secondary content, it might take too long to load and parse the secondary content.

Implementation for a Django Website using django-include-by-ajax

You can implement the third solution in a Django website using my open-source Django app django-include-by-ajax. It is meant to be understandable and simple to use for frontend Django developers, who don't touch Python code but need to work on the layouts and styling.

The idea is that instead of including different sections of a template with the {% include template_name %} template tag, you do the same using {% include_by_ajax template_name %} template tag. This template tag renders as an empty placeholder unless you access the page from a search crawler or if you access the page with a specific query parameter. Otherwise, it works more-or-less the same as the {% include %} template tag.

By adding jQuery and one jQuery-based JavaScript file to your page template, you enable the magic that does all the loading and parsing. Since version 1.0, CSS and JavaScript files can also be included in those delayed sections.

You can see django-include-by-ajax in action at the start page of my personal project 1st things 1st. There I use the above-the-fold case with the visible content coming to the screen almost immediately and the offscreen content loading in several more seconds.


It should be trivial to convert any standard heavy website page to a page loading the secondary content dynamically. There are mainly these steps to follow:

  1. Install the app with your Python package manager:

    (venv)$ pip install django-include-by-ajax==1.0.0
  2. Put the app into the INSTALLED_APPS in your Django project settings:

    # ...
    # Third-party apps
    # ...
  3. Put these in your base.html:

    {% load staticfiles %}
    <script src="" crossorigin="anonymous"></script>
    <script src="{% static 'include_by_ajax/js/include_by_ajax.min.js' %}" defer></script>

    It should also work with older or newer jQuery versions.

  4. Use the new template tag in any template where you need it:

    {% load include_by_ajax_tags %}
    {% include_by_ajax "blog/includes/latest_blog_posts.html" %}

    You can even define the content for the placeholder that will be shown while the main content is loading:

    {% load include_by_ajax_tags %}
    {% include_by_ajax "blog/includes/latest_blog_posts.html" placeholder_template_name="utils/loading.html" %}
  5. If you need some JavaScript action to be called after all content is loaded, you can use the custom include_by_ajax_all_loaded event on the document like this:

    $(document).on('include_by_ajax_all_loaded', function() {
    console.log('Now all placeholders are loaded and replaced with content. Hurray!');

I would be glad if you tried it on some of your projects and see how it improved user experience and loading times. If you use it in production, please mention it in the comments of this blog post.

More Information

The app on Github: A Django App Providing the {% include_by_ajax %} Template Tag

The practical usage example: Strategic planner - Prioritizer - 1st things 1st.

An article on performance and usability: 5 Reasons Visitors Leave Your Website

Cover photo by Thomas Tucker.

Thanks to Adam Johnson for reviewing this post.

How to Export Data to XLSX Files

Par Aidas Bendoraitis a.k.a. archatas

A while ago I wrote an article about exporting data to different spreadsheet formats. As recently I was reimplementing export to Excel for the 1st things 1st project, I noticed that the API changed a little, so it's time to blog about that again.

For Excel export I am using the XLSX file format which is a zipped XML-based format for spreadsheets with formatting support. XLSX files can be opened with Microsoft Excel, Apache OpenOffice, Apple Numbers, LibreOffice, Google Drive, and a handful of other applications. For building the XLSX file I am using openpyxl library.

Installing openpyxl

You can install openpyxl to your virtual environment the usual way with pip:

(venv) pip install openpyxl==2.6.0

Simplest Export View

To create a function exporting data from a QuerySet to XLSX file, you would need to create a view that returns a response with a special content type and file content as an attachment. Plug that view to URL rules and then link it from an export button in a template.

Probably the simplest view that generates XLSX file out of Django QuerySet would be this:

# movies/
from datetime import datetime
from datetime import timedelta
from openpyxl import Workbook
from django.http import HttpResponse

from .models import MovieCategory, Movie

def export_movies_to_xlsx(request):
Downloads all movies as Excel file with a single worksheet
movie_queryset = Movie.objects.all()

response = HttpResponse(
response['Content-Disposition'] = 'attachment; filename={date}-movies.xlsx'.format('%Y-%m-%d'),
workbook = Workbook()

# Get active worksheet/tab
worksheet =
worksheet.title = 'Movies'

# Define the titles for columns
columns = [
row_num = 1

# Assign the titles for each cell of the header
for col_num, column_title in enumerate(columns, 1):
cell = worksheet.cell(row=row_num, column=col_num)
cell.value = column_title

# Iterate through all movies
for movie in movie_queryset:
row_num += 1

# Define the data for each cell in the row
row = [,

# Assign the data for each cell of the row
for col_num, cell_value in enumerate(row, 1):
cell = worksheet.cell(row=row_num, column=col_num)
cell.value = cell_value

return response

If you try this, you will notice, that there is no special formatting in it, all columns are of the same width, the value types are barely recognized, the header is displayed the same as the content. This is enough for further data export to CSV or manipulation with pandas. But if you want to present the data for the user in a friendly way, you need to add some magic.

Creating More Worksheets

By default, each Excel file has one worksheet represented as a tab. You can access it with:

worksheet =
worksheet.title = 'The New Tab Title'

If you want to create tabs dynamically with data from the database of Python structures, you can at first delete the current tab and add the others with:


for index, category in enumerate(category_queryset):
worksheet = workbook.create_sheet(

Although not all spreadsheet applications support this, you can set the background color of the worksheet tab with:

worksheet.sheet_properties.tabColor = 'f7f7f9'

Working with Cells

Each cell can be accessed by its 1-based indexes for the rows and for the columns:

top_left_cell = worksheet.cell(row=1, column=1)
top_left_cell.value = "This is good!"

Styles and formatting are applied to individual cells instead of rows or columns. There are several styling categories with multiple configurations for each of them. You can find some available options from the documentation, but even more by exploring the source code.

from openpyxl.styles import Font, Alignment, Border, Side, PatternFill

top_left_cell.font = Font(name='Calibri', bold=True)
top_left_cell.alignment = Alignment(horizontal='center')
top_left_cell.border = Border(
bottom=Side(border_style='medium', color='FF000000'),
top_left_cell.fill = PatternFill(

If you are planning to have multiple styled elements, instantiate the font, alignment, border, fill options upfront and then assign the instances to the cell attributes. Otherwise, you can get into memory issues when you have a lot of data entries.

Setting Column Widths

If you want to have some wider or narrower width for some of your columns, you can do this by modifying column dimensions. They are accessed by column letter which can be retrieved using a utility function:

from openpyxl.utils import get_column_letter

column_letter = get_column_letter(col_num)
column_dimensions = worksheet.column_dimensions[column_letter]
column_dimensions.width = 40

The units here are some relative points depending on the width of the letters in the specified font. I would suggest playing around with the width value until you find what works for you.

When defining column width is not enough, you might want to wrap text into multiple lines so that everything can be read by people without problems. This can be done with the alignment setting for the cell as follows:

from openpyxl.styles import Alignment

wrapped_alignment = Alignment(vertical='top', wrap_text=True)
cell.alignment = wrapped_alignment

Data Formatting

Excel automatically detects text or number types and aligns text to the left and numbers to the right. If necessary that can be overwritten.

There are some gotchas on how to format cells when you need a percentage, prices, or time durations.


For percentage, you have to pass the number in float format from 0.0 till 1.0 and style should be 'Percent' as follows:

cell.value = 0.75 = 'Percent'


For currency, you need values of Decimal format, the style should be 'Currency', and you will need a special number format for currency other than American dollars, for example:

from decimal import Decimal
cell.value = Decimal('14.99') = 'Currency'
cell.number_format = '#,##0.00 €'


For time duration, you have to pass timedelta as the value and define special number format:

from datetime import timedelta

cell.value = timedelta(minutes=90)
cell.number_format = '[h]:mm;@'

This number format ensures that your duration can be greater than '23:59', for example, '140:00'.

Freezing Rows and Columns

In Excel, you can freeze rows and columns so that they stay fixed when you scroll the content vertically or horizontally. That's similar to position: fixed in CSS.

To freeze the rows and columns, locate the top-left cell that is below the row that you want to freeze and is on the right from the column that you want to freeze. For example, if you want to freeze one row and one column, the cell would be 'B2'. Then run this:

worksheet.freeze_panes = worksheet['B2']

Fully Customized Export View

So having the knowledge of this article now we can build a view that creates separate sheets for each movie category. Each sheet would list movies of the category with titles, descriptions, length in hours and minutes, rating in percent, and price in Euros. The tabs, as well as the headers, can have different background colors for each movie category. Cells would be well formatted. Titles and descriptions would use multiple lines to fully fit into the cells.

# movies/
from datetime import datetime
from datetime import timedelta
from openpyxl import Workbook
from openpyxl.styles import Font, Alignment, Border, Side, PatternFill
from openpyxl.utils import get_column_letter
from django.http import HttpResponse

from .models import MovieCategory, Movie

def export_movies_to_xlsx(request):
Downloads all movies as Excel file with a worksheet for each movie category
category_queryset = MovieCategory.objects.all()

response = HttpResponse(
response['Content-Disposition'] = 'attachment; filename={date}-movies.xlsx'.format('%Y-%m-%d'),
workbook = Workbook()

# Delete the default worksheet

# Define some styles and formatting that will be later used for cells
header_font = Font(name='Calibri', bold=True)
centered_alignment = Alignment(horizontal='center')
border_bottom = Border(
bottom=Side(border_style='medium', color='FF000000'),
wrapped_alignment = Alignment(

# Define the column titles and widths
columns = [
('ID', 8),
('Title', 40),
('Description', 80),
('Length', 15),
('Rating', 15),
('Price', 15),

# Iterate through movie categories
for category_index, category in enumerate(category_queryset):
# Create a worksheet/tab with the title of the category
worksheet = workbook.create_sheet(
# Define the background color of the header cells
fill = PatternFill(
row_num = 1

# Assign values, styles, and formatting for each cell in the header
for col_num, (column_title, column_width) in enumerate(columns, 1):
cell = worksheet.cell(row=row_num, column=col_num)
cell.value = column_title
cell.font = header_font
cell.border = border_bottom
cell.alignment = centered_alignment
cell.fill = fill
# set column width
column_letter = get_column_letter(col_num)
column_dimensions = worksheet.column_dimensions[column_letter]
column_dimensions.width = column_width

# Iterate through all movies of a category
for movie in category.movie_set.all():
row_num += 1

# Define data and formats for each cell in the row
row = [
(, 'Normal'),
(movie.title, 'Normal'),
(movie.description, 'Normal'),
(timedelta(minutes=movie.length_in_minutes), 'Normal'),
(movie.rating / 100, 'Percent'),
(movie.price, 'Currency'),

# Assign values, styles, and formatting for each cell in the row
for col_num, (cell_value, cell_format) in enumerate(row, 1):
cell = worksheet.cell(row=row_num, column=col_num)
cell.value = cell_value = cell_format
if cell_format == 'Currency':
cell.number_format = '#,##0.00 €'
if col_num == 4:
cell.number_format = '[h]:mm;@'
cell.alignment = wrapped_alignment

# freeze the first row
worksheet.freeze_panes = worksheet['A2']

# set tab color
worksheet.sheet_properties.tabColor = category.html_color

return response

The Takeaways

  • Spreadsheet data can be used for further mathematical processing with pandas.
  • XLSX file format allows quite a bunch of formatting options that can make your spreadsheet data more presentable and user-friendly.
  • To see Excel export in action, go to 1st things 1st, log in as a demo user, and navigate to project results where you can export them as XLSX. Feedback is always welcome.

Cover photo by Tim Evans.

Equivalents in Python and JavaScript. Bonus

Par Aidas Bendoraitis a.k.a. archatas

From time to time I google for the right syntax how to process lists and dictionaries in Python or arrays and objects in JavaScript. So I decided to extend my series of equivalents with those functions. After all, it's me too, who will be using the information I provide here.

All truthful elements

Sometimes we need to check from a list of conditions if all of them are true, or from a list of elements if all of them are not empty.

This can be checked with the following in Python:

items = [1, 2, 3]
all_truthy = all(items)
# True

And here is an equivalent in JavaScript:

items = [1, 2, 3];
all_truthy = items.every(Boolean);
// true

Any truthful elements

Similarly, we can check if at least one of the conditions is true, or there is at least one non-empty element in a list.

It Python we would do that with:

items = [0, 1, 2, 3]
some_truthy = any(items)
# True

And in JavaScript we would check it like this:

items = [0, 1, 2, 3];
some_truthy = items.some(Boolean);
// true

Iterate through each element and its index

Here is an example of how to iterate through a list of items and also check their indices in Python. It is useful for verbose console output when creating different command line tools that process data:

items = ['a', 'b', 'c', 'd']
for index, element in enumerate(items):
print(f'{index}: {element};')

In JavaScript an analogous way to do the same would be using the forEach() method. The usual for loop is also an option, but I find the forEach() more elegant and clear.

items = ['a', 'b', 'c', 'd'];
items.forEach(function(element, index) {
console.log(`${index}: ${element};`);

Map elements to the results of a function

To process all elements of a list, you can either iterate through them with the for loop and create a new list with modifications, or you can do that in one step by mapping the list items to a modification function. In Python this can be done with the map() function:

items = [0, 1, 2, 3]
all_doubled = list(map(lambda x: 2 * x, items))
# [0, 2, 4, 6]

In JavaScript the map() is a method of an array:

items = [0, 1, 2, 3];
all_doubled = => 2 * x);
// [0, 2, 4, 6]

Filter elements by a function

When you need to search for some elements in a list or array and want to avoid for loops, you can use the filtering functionality. In Python that is doable with the filter() function that accepts the filtering function and the list and returns a new filtered list.

items = [0, 1, 2, 3]
only_even = list(filter(lambda x: x % 2 == 0, items))
# [0, 2]

In JavaScript there is a filter() method of the array for that.

items = [0, 1, 2, 3];
only_even = items.filter(x => x % 2 === 0);
// [0, 2]

In both cases, the filtering function checks each item if it is matching the filter criteria and returns true in that case.

Reduce elements by a function to a single value

When you want to apply some function to a list of items to get a single result in one go, you can use the reduce function. It works for summing, multiplying, ORing, ANDing, or checking maximums and minimums.

In Python there is a reduce() function for that.

from functools import reduce
items = [1, 2, 3, 4]
total = reduce(lambda total, current: total + current, items)
# 10

In JavaScript there is a reduce() method of the array.

items = [1, 2, 3, 4];
total = items.reduce((total, current) => total + current);
// 10

Merge dictionaries

There are multiple ways to merge dictionaries in Python or objects in JavaScript. But these are probably the simplest ones.

In Python it's decomposing dictionaries to tuples of keys and arrays, joining them, and creating a new dictionary.

d1 = {'a': 'A', 'b': 'B'}
d2 = {'a': 'AAA', 'c': 'CCC'}
merged = dict(list(d1.items()) + list(d2.items()))
# {'a': 'AAA', 'b': 'B', 'c': 'CCC'}

Analogously, in JavaScript it's spreading two objects into a new object:

d1 = {a: 'A', b: 'B'}
d2 = {a: 'AAA', c: 'CCC'}
merged = {...d1, ...d2};
// {a: 'AAA', b: 'B', c: 'CCC'}

The Takeaways

  • In both languages, you can traverse through lists of items without explicitly incrementing and referencing an index.
  • For processing list items, you don't necessarily need a loop. The dedicated methods or functions all() / every(), any() / some(), map(), filter(), and reduce() are there to help you.
  • In both languages, you can merge multiple dictionaries into one. If the same key appears in several dictionaries, the latest one will be used in the merged dictionary.

Of course, I also updated the cheat sheet with the full list of equivalents in Python and JavaScript that you saw here described. This cheat sheet helps me with a good overview next to my laptop, so I believe that it would be helpful to you too. The new revision 10 is with syntax highlighting, so it makes it even better to explore and understand.

Get the Ultimate Cheat Sheet of Equivalents in Python and JavaScript

Use it for good!

Cover photo by Darren Chan.

How to Create PDF Documents with Django in 2019

Par Aidas Bendoraitis a.k.a. archatas

If you've read my Web Development with Django Cookbook, you might remember a recipe for creating PDF documents using Pisa xhtml2pdf. Well, this library does its job, but it supports only a subset of HTML and CSS features. For example, for multi-column layouts, you have to use tables, like it's 1994.

I needed some fresh and flexible option to generate donation receipts for the donation platform and reports for the strategic planner 1st things 1st I have been building. After a quick research I found another much more suitable library. It's called WeasyPrint. In this article, I will tell you how to use it with Django and what's valuable in it.


WeasyPrint uses HTML and CSS 2.1 to create pixel-perfect, or let's rather say point-perfect, PDF documents. WeasyPrint doesn't use WebKit or Gecko but has its own rendering engine. As a proof that it works correctly, it passes the famous among web developers Acid2 test which was created back in the days before HTML5 to check how compatible browsers are with CSS 2 standards.

All supported features (and unsupported exceptions) are listed in the documentation. But my absolute favorites are these:

  • Layouts with floated elements. You don't have to use tables anymore if you want to have the recipient address on the left side and the sender information on the right side in a letter, or if you want to have the main content and the side notes in an exercise book. Just use floated elements.
  • Working links. The generated document can have clickable links to external URLs and internal anchors. You can straightforwardly create a clickable table of contents or a banner that leads back to your website.
  • Support for web fonts. With the wide variety of embeddable web fonts, your documents don't need to look boring anymore. Why not write titles in elegant cursive or in bold western letters?
  • Background images. By default, when you print an HTML page, all foreground images get printed, but the backgrounds are skipped. When you generate a PDF document for printing, you can show background images anywhere, even in the margins of the printed page.
  • SVG kept as vector images. When you have diagrams and graphics in a PDF document, you usually want to preserve the quality of the lines. Even if they look good on the screen, raster images might be not what you want, because on a printed page the resolution will differ and the quality can be lost. WeasyPrint keeps SVG images as vector images, so you have the highest possible quality in the prints.

Important Notes

WeasyPrint needs Python 3.4 or newer. That's great for new Django projects, but might be an obstacle if you want to integrate it into an existing website running on Python 2.7. Can it be the main argumentation for you to upgrade your old Django projects to the new Python version?

WeasyPrint is dependent on several OS libraries: Pango, GdkPixbuf, Cairo, and Libffi. In the documentation, there are understandable one-line instructions how to install them on different operating systems. You can have a problem only if you don't have full control of the server where you are going to deploy your project.

If you need some basic headers and footers for all pages, you can use @page CSS selector for that. If you need extended headers and footers for each page, it's best to combine the PDF document out of separate HTML documents for each page. Examples follow below.

The fun fact, Emojis are drawn using some weird raster single-color font. I don't recommend using them in your PDFs unless you replace them with SVG images.

Show Me the Code

A technical article is always more valuable when it has some quick code snippets to copy and paste. Here you go!

Simple PDF View

This snippet generates a donation receipt and shows it directly in the browser. Should the PDF be downloadable immediately, change content disposition from inline to attachment.

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals

from django.http import HttpResponse
from django.template.loader import render_to_string
from django.utils.text import slugify
from django.contrib.auth.decorators import login_required

from weasyprint import HTML
from weasyprint.fonts import FontConfiguration

from .models import Donation

def donation_receipt(request, donation_id):
donation = get_object_or_404(Donation, pk=donation_id, user=request.user)
response = HttpResponse(content_type="application/pdf")
response['Content-Disposition'] = "inline; filename={date}-{name}-donation-receipt.pdf".format(
html = render_to_string("donations/receipt_pdf.html", {
'donation': donation,

font_config = FontConfiguration()
HTML(string=html).write_pdf(response, font_config=font_config)
return response

Page Configuration Using CSS

Your PDF document can have a footer with an image and text on every page, using background-image and content properties:

{% load staticfiles i18n %}
<link href=",400i,700,700i,900" rel="stylesheet" />
@page {
size: "A4";
margin: 2.5cm 1.5cm 3.5cm 1.5cm;
@bottom-center {
background: url({% static 'site/img/logo-pdf.svg' %}) no-repeat center top;
background-size: auto 1.5cm;
padding-top: 1.8cm;
content: "{% trans "Donation made via" %}";
font: 10pt "Playfair Display";
text-align: center;
vertical-align: top;


You can show page numbers in the footer using CSS as follows.

@page {
margin: 3cm 2cm;
@top-center {
content: "Documentation";
@bottom-right {
content: "Page " counter(page) " of " counter(pages);

Horizontal Page Layout

You can rotate the page to horizontal layout with size: landscape.

@page {
size: landscape;

HTML-based Footer

Another option to show an image and text in the header or footer on every page is to use an HTML element with position: fixed. This way you have more flexibility about formatting, but the element on all your pages will have the same content.

footer {
position: fixed;
bottom: -2.5cm;
width: 100%;
text-align: center;
font-size: 10pt;
footer img {
height: 1.5cm;
{% with website_url="" %}
<a href="{{ website_url }}">
<img alt="" src="{% static 'site/img/logo-contoured.svg' %}" />
</a><br />
{% blocktrans %}Donation made via <a href="{{ website_url }}"></a>{% endblocktrans %}
{% endwith %}

Document Rendering from Page to Page

When you need to have a document with complex unique headers and footers, it is best to render each page as a separate HTML document and then to combine them into one. This is how to do that:

def letter_pdf(request, letter_id):
letter = get_object_or_404(Letter, pk=letter_id)
response = HttpResponse(content_type='application/pdf')
response['Content-Disposition'] = (
'inline; '
documents = []
font_config = FontConfiguration()
for template_name in COMPONENTS:
html = render_to_string(template_name, {
'letter': letter,
document = HTML(string=html).render(font_config=font_config)

all_pages = [page for document in documents for page in document.pages]

return response

Final Thoughts

I believe that WeasyPrint could be used not only for invoices, tickets, or booking confirmations but also for online magazines and small booklets. If you want to see PDF rendering with WeasyPrint in action, make a donation to your chosen organization at (when it's ready) and download the donation receipt. Or check the demo account at and find the button to download the results of a prioritization project as PDF document.

Cover photo by Daniel Korpai.

What's New in the Third Edition of Web Development with Django Cookbook?

Par Aidas Bendoraitis a.k.a. archatas

A couple of months ago the third release of Django Cookbook was published under the title Django 2 Web Development Cookbook - Third Edition. This edition was thoroughly and progressively re-written by Jake Kronika, the guy who had reviewed my second edition and had added a lot of value to it. I was sure that he wouldn't disappoint the readers, so I invited him to write the update. In this article, I will guide you through the main new highlights of over 500 pages of this new book.

Up to Date

Just like William S. Vincent's books, Django 2 Web Development Cookbook - Third Edition is adapted to Django 2.1 and Python 3.6. So you will be dealing with the state of the art technologies building your Django projects. Unicode strings, f-strings, super() without parameters, HTML5 tags, and object-oriented JavaScript to mention a few are used all over the book. The code is carefully generalized and even more adapted to the Don't-Repeat-Yourself (DRY) principle.

Working with Docker

Docker is one of the most popular deployment technologies and Jake gives a good compact introduction how to use it with Django.

Using Environment Variables for Configuration

12-factor app guidelines suggest saving app configuration in environment variables. In the book, there is a practical example of how to use it.

Multilingual Fields even with Region-specific Language Codes

I introduced multilingual fields in previous editions of the book, but there they had a limitation, that region-specific languages like Australian English or Swiss German were not supported. Now they are!

Using Precisely Semantic Markup with Microdata Microdata allows you to define the context of the content more specifically so that the content is more machine-readable. This was new to me and I still don't know the exact practical value of it, but I guess it is related to accessibility, new ways of presenting data via plugins, and Artificial Intelligence.

Defining Custom Templates for the Default Django Form Fields

Since Django 1.11 form fields are rendered using templates instead of Python code and those templates can be customized. There is a recipe that shows you how to do that.

Providing Responsive Images

HTML5 has the <picture> tag with <source> children that can be used in combination with the sorl-thumbnail Python package to generate different versions of the image based on your viewport size: load small image on the mobile, middle image on the tablet, and big image on the desktop or smart TV.

Uploading Images and Deleting them by Ajax

In my previous editions, I only showed how to upload a file by Ajax and attach it to a Django model. In Jake's update, it is shown how you can also delete the image.

Validating Passwords with Special Requirements

Since Django 1.11 you can define special requirements for the passwords of your users, for example, have a mix of small and big letters or include at least 1 number and 3 special characters, etc. There is a practical recipe how to do that.

Adding Watermarks to Images

When it comes to branding or copyright protection, it is common to add special watermarks, semitransparent images on top of your normal pictures. Jake added an example, how to do that and it was very interesting to me.

Authenticating with Auth0

In one recipe it is shown how to login to a Django website using Auth0, which seems to be a passwordless authentication system with integrations of popular connection services like OpenID Connect, Facebook, Google, Github, LinkedIn, PayPal, Yahoo!, and others. I haven't tried that myself yet, but it can be an interesting option for a social website.

Using Redis for Caching

It is common to cache websites using Memcached service, but a good alternative is caching with Redis and django-redis. Moreover, you can easily save user sessions there.

Creating Hierarchies with django-treebeard

In the previous editions, I introduced django-mptt for creating hierarchical structures. However, recently many projects are moving towards its alternative - django-treebeard which has more stability and writing speed. In the book, Jake shows you how to work with it.


There was a lot of new things to learn. For example, for me personally Docker usage was new, and I haven't heard of microdata and Auth0 which were introduced in this book. All in all, I think, Jake Kronika did an enormous job with this update and it's really worth purchasing this book, especially as there is a winter-holidays sale where you can get the EPUB, MOBI, and PDF with the code examples just for ~ 5 €.

Have a nice Christmas time and come back to this blog next year!

Cover photo by chuttersnap.

Equivalents in Python and JavaScript. Part 4

Par Aidas Bendoraitis a.k.a. archatas

In the last three parts of the series of articles about analogies in Python and JavaScript, we explored lots of interesting concepts like serializing to JSON, error handling, using regular expressions, string interpolation, generators, lambdas, and many more. This time we will delve into function arguments, creating classes, using class inheritance, and defining getters and setters of class properties.

Function arguments

Python is very flexible with argument handling for functions: you can set default values there, allow a flexible amount of positional or keyword arguments (*args and **kwargs). When you pass values to a function, you can define by name to which argument that value should be assigned. All that in a way is now possible in JavaScript too.

Default values for function arguments in Python can be defined like this:

from pprint import pprint

def report(post_id, reason='not-relevant'):
pprint({'post_id': post_id, 'reason': reason})

report(post_id=24, reason='spam')

In JavaScript that can be achieved similarly:

function report(post_id, reason='not-relevant') {
console.log({post_id: post_id, reason: reason});

report(post_id=24, reason='spam');

Positional arguments in Python can be accepted using the * operator like this:

from pprint import pprint

def add_tags(post_id, *tags):
pprint({'post_id': post_id, 'tags': tags})

add_tags(42, 'python', 'javascript', 'django')

In JavaScript positional arguments can be accepted using the ... operator:

function add_tags(post_id, ...tags) {
console.log({post_id: post_id, tags: tags});

add_tags(42, 'python', 'javascript', 'django');

Keyword arguments are often used in Python when you want to allow a flexible amount of options:

from pprint import pprint

def create_post(**options):

title='Hello, World!',
content='This is our first post.',
title='Hello again!',
content='This is our second post.',

A common practice to pass multiple optional arguments to a JavaScript function is through a dictionary object, for example, options.

function create_post(options) {

'title': 'Hello, World!',
'content': 'This is our first post.',
'is_published': true
'title': 'Hello again!',
'content': 'This is our second post.'

Classes and inheritance

Python is an object-oriented language. Since ECMAScript 6 standard support, it's also possible to write object-oriented code in JavaScript without hacks and weird prototype syntax.

In Python you would create a class with the constructor and a method to represent its instances textually like this:

class Post(object):
def __init__(self, id, title): = id
self.title = title

def __str__(self):
return self.title

post = Post(42, 'Hello, World!')
isinstance(post, Post) == True
print(post) # Hello, World!

In JavaScript to create a class with the constructor and a method to represent its instances textually, you would write:

class Post {
constructor (id, title) { = id;
this.title = title;
toString() {
return this.title;

post = new Post(42, 'Hello, World!');
post instanceof Post === true;
console.log(post.toString()); // Hello, World!

Now we can create two classes Article and Link in Python that will extend the Post class. Here you can also see how we are using super to call methods from the base Post class.

class Article(Post):
def __init__(self, id, title, content):
super(Article, self).__init__(id, title)
self.content = content

class Link(Post):
def __init__(self, id, title, url):
super(Link, self).__init__(id, title)
self.url = url

def __str__(self):
return '{} ({})'.format(
super(Link, self).__str__(),

article = Article(1, 'Hello, World!', 'This is my first article.')
link = Link(2, 'DjangoTricks', '')
isinstance(article, Post) == True
isinstance(link, Post) == True
# DjangoTricks (

In JavaScript the same is also doable by the following code:

class Article extends Post {
constructor (id, title, content) {
super(id, title);
this.content = content;

class Link extends Post {
constructor (id, title, url) {
super(id, title);
this.url = url;
toString() {
return super.toString() + ' (' + this.url + ')';

article = new Article(1, 'Hello, World!', 'This is my first article.');
link = new Link(2, 'DjangoTricks', '');
article instanceof Post === true;
link instanceof Post === true;
// DjangoTricks (

Class properties: getters and setters

In object oriented programming, classes can have attributes, methods, and properties. Properties are a mixture of attributes and methods. You deal with them as attributes, but in the background they call special getter and setter methods to process data somehow before setting or returning to the caller.

The basic wireframe for getters and setters of the slug property in Python would be like this:

class Post(object):
def __init__(self, id, title): = id
self.title = title
self._slug = ''

def slug(self):
return self._slug

def slug(self, value):
self._slug = value

post = new Post(1, 'Hello, World!')
post.slug = 'hello-world'

In JavaScript getters and setters for the slug property can be defined as:

class Post {
constructor (id, title) { = id;
this.title = title;
this._slug = '';

set slug(value) {
this._slug = value;

get slug() {
return this._slug;

post = new Post(1, 'Hello, World!');
post.slug = 'hello-world';

The Takeaways

  • In both languages, you can define default argument values for functions.
  • In both languages, you can pass a flexible amount of positional or keyword arguments for functions.
  • In both languages, object-oriented programming is possible.

As you might have noticed, I am offering a cheat sheet with the full list of equivalents in Python and JavaScript that you saw here described. At least for me, it is much more convenient to have some printed sheet of paper with valuable information next to my laptop, rather than switching among windows or tabs and scrolling to get the right piece of snippet. So I encourage you to get this cheat sheet and improve your programming!

Get the Ultimate Cheat Sheet of Equivalents in Python and JavaScript

Use it for good!

Cover photo by Andre Benz

Equivalents in Python and JavaScript. Part 3

Par Aidas Bendoraitis a.k.a. archatas

This is the 3rd part of 4-article series about analogies in Python and JavaScript. In the previous parts we covered a large part of the traditional Python 2.7 and JavaScript based on the ECMAScript 5 standard. This time we will start looking into Python 3.6 and JavaScript based on the ECMAScript 6 standard. ECMAScript 6 standard is pretty new and supported only the newest versions of browsers. For older browsers you will need Babel to compile your next-generation JavaScript code to the cross-browser-compatible equivalents. It opens the door to so many interesting things to explore. We will start from string interpolation, unpacking lists, lambda functions, iterations without indexes, generators, and sets!

Variables in strings

The old and inefficient way to build strings with values from variables is this concatenation:

name = 'World'
value = 'Hello, ' + name + '!\nWelcome!'

This can get very sparse and difficult to read. Also it is very easy to miss whitespaces in the sentence around variables.

Since Python version 3.6 and JavaScript based on the ECMAScript 6 standard, you can use so called string interpolation. These are string templates which are filled in with values from variables.

In Python they are also called f-string, because their notation starts with letter "f":

name = 'World'
value = f"""Hello, {name}!

price = 14.9
value = f'Price: {price:.2f} €' # 'Price: 14.90 €'

In JavaScript string templates start and end with backticks:

name = 'World';
value = `Hello, ${name}!

price = 14.9;
value = `Price ${price.toFixed(2)} €`; // 'Price: 14.90 €'

Note that string templates can be of a single line as well as of multiple lines. For f-strings in Python you can pass the format for variables, but you can't call methods of a variable unless they are properties and call getter methods.

Unpacking lists

Python and now JavaScript has an interesting feature to assign items of sequences into separate variables. For example, we can read the three values of a list into variables a, b, and c with the following syntax:

[a, b, c] = [1, 2, 3]

For tuples the parenthesis can be omitted. The following is a very popular way to swap values of two variables in Python:

a = 1
b = 2
a, b = b, a # swap values

With the next generation JavaScript this can also be achieved:

a = 1;
b = 2;
[a, b] = [b, a]; // swap values

In Python 3.6 if we have an unknown number of items in a list or tuple, we can assign them to a tuple of several values while also unpacking the rest to a list:

first, second, *the_rest = [1, 2, 3, 4]
# first == 1
# second == 2
# the_rest == [3, 4]

This can also be done with JavaScript (ECMAScript 6):

[first, second, ...the_rest] = [1, 2, 3, 4];
// first === 1
// last === 2
// the_rest === [3, 4]

Lambda functions

Python and JavaScript have a very neat functionality to create functions in a single line. These functions are called lambdas. Lambdas are very simple functions that take one or more arguments and return some calculated value. Usually lambdas are used when you need to pass a function to another function as a callback or as a function to manipulate every separate elements in a sequence.

In Python, you would define a lambda using the lambda keyword, like this:

sum = lambda x, y: x + y
square = lambda x: x ** 2

In JavaScript lambdas use the => notation. If there are more than one arguments, they have to be in parenthesis:

sum = (x, y) => x + y;
square = x => Math.pow(x, 2);

Iteration without indexes

Many programming languages allow iterating through a sequence only by using indexes and incrementing their values. Then to get an item at some position, you would read it from an array, for example:

for (i=0; i<items.length; i++) {

This is not a nice syntax and is very technical - it doesn't read naturally. What we really want is just to grab each value from the list. And Python has a very neat possibility just to iterate through the elements:

for item in ['A', 'B', 'C']:

In the modern JavaScript this is also possible with the for..of operator:

for (let item of ['A', 'B', 'C']) {

You can also iterate through a string characters in Python:

for character in 'ABC':

And in the modern JavaScript:

for (let character of 'ABC') {


Python and modern JavaScript has a possibility to define special functions through which you can iterate. With each iteration they return the next generated value in a sequence. These functions are called generators. With generators you can get numbers in a range, lines from a file, data from different paginated API calls, fibonacci numbers, and any other dynamicly generated sequences.

Technically generators are like normal functions, but instead of returning a value, they yield a value. This value will be returned for one iteration. And this generation happens as long as the end of the function is reached.

To illustrate that, the following Python code will create a generator countdown() which will return numbers from the given one back to 1, (like 10, 9, 8, ..., 1):

def countdown(counter):
while counter > 0:
yield counter
counter -= 1

for counter in countdown(10):

Exactly the same can be achieved in modern JavaScript, but notice the asterisk at the function statement. It defines that it's a generator:

function* countdown(counter) {
while (counter > 0) {
yield counter;
for (let counter of countdown(10)) {


We already had a look at lists, tuples and arrays. But here is another type of data - sets. Sets are groups of elements that ensure that each element there exists only once. Set theory also specifies set operations like union, intersection, and difference, but we won't cover them here today.

This is how to create a set, add elements to it, check if a value exists, check the total amount of elements in a set, and iterate through its values, and remove a value using Python:

s = set(['A'])
s.add('B'); s.add('C')
'A' in s
len(s) == 3
for elem in s:

Here is how to achieve the same in modern JavaScript:

s = new Set(['A']);
s.has('A') === true;
s.size === 3;
for (let elem of s.values()) {

The Takeaways

  • String interpolation or literal templates allows you to have much cleaner and nicer code even with a possibility to have multiple lines of text.
  • You can iterate through elements in a sequence or group without using indexes.
  • Use generators when you have a sequence of nearly unlimited elements.
  • Use sets when you want to ensure fast check if data exists in a collection.
  • Use lambdas when you need short and clear single-line functions.

As you know from the previous parts, I am offering a cheat sheet with the whole list of equivalents in Python and JavaScript, both, time honored and future proof. To have something printed in front of your eyes is much more convenient than switching among windows or scrolling up and down until you find what you exactly were searching for. So I suggest you to get the cheat sheet and use it for good!

Get the Ultimate Cheat Sheet of Equivalents in Python and JavaScript

In the next and last part of the series, we will have a look at function arguments, classes, inheritance, and properties. Stay tuned!

Cover photo by Alex Knight

Equivalents in Python and JavaScript. Part 2

Par Aidas Bendoraitis a.k.a. archatas

Last time we started a new series of articles about analogies in Python and JavaScript. We had a look at lists, arrays, dictionaries, objects, and strings, conditional assignments, and parsing integers. This time we will go through more interesting and more complex things like serializing dictionaries and lists to JSON, operations with regular expressions, as well as raising and catching errors.


When working with APIs it is very usual to serialize objects to JSON format and be able to parse JSON strings.

In Python it is done with the json module like this:

import json
json_data = json.dumps(dictionary, indent=4)
dictionary = json.loads(json_data)

Here we'll indent the nested elements in the JSON string by 4 spaces.

In JavaScript there is a JSON object that has methods to create and parse JSON strings:

json_data = JSON.stringify(dictionary, null, 4);
dictionary = JSON.parse(json_data);

Splitting strings by regular expressions

Regular expressions are multi-tool that once you master, you can accomplish lots of things.

In the last article, we saw how one can join lists of strings into a single string. But how can you split a long string into lists of strings? What if the delimiter can be not a single character as the comma, but a range of possible variations? This can be done with regular expressions and the split() method.

In Python, the split() method belongs to the regular expression pattern object. This is how you could split a text string into sentences by punctuation marks:

import re

# One or more characters of "!?." followed by whitespace
delimiter = re.compile(r'[!?\.]+\s*')

text = "Hello!!! What's new? Follow me."
sentences = delimiter.split(text)
# sentences == ['Hello', "What's new", 'Follow me', '']

In JavaScript the split() method belongs to the string:

// One or more characters of "!?." followed by whitespace
delimiter = /[!?\.]+\s*/;

text = "Hello!!! What's new? Follow me.";
sentences = text.split(delimiter)
// sentences === ["Hello", "What's new", "Follow me", ""]

Matching regular expression patterns in strings

Regular expressions are often used to validate data from the forms.

For example, to validate if the entered email address is correct, you would need to match it against a regular expression pattern. In Python that would look like this:

import re

# name, "@", and domain
pattern = re.compile(r'([\w.+\-]+)@([\w\-]+\.[\w\-.]+)')

match = pattern.match('')
# == ''
# == 'hi'
# == ''

If the text matches the pattern, it returns a match object with the group() method to read the whole matched string, or separate captures of the pattern that were defined with the parenthesis. 0 means getting the whole string, 1 means getting the match in the first group, 2 means getting the match in the second group, and so on. If the text doesn't match the pattern, the None value will be returned.

In JavaScript the match() method belongs to the string and it returns either a match object, or null. Pretty similar:

// name, "@", and domain
pattern = /([\w.+\-]+)@([\w\-]+\.[\w\-.]+)/;

match = ''.match(pattern);
// match[0] === ''
// match[1] === 'hi'
// match[2] === ''

The match object in JavaScript acts as an array. Its value at the zeroth position is the whole matched string. The other indexes correspond to the captures of the pattern defined with the parenthesis.

Moreover, sometimes you need to search if a specific value exists in a string and at which letter position it will be found. That can be done with the search() method.

In Python this method belongs to the regular expression pattern and it returns the match object. The match object has the start() method telling at which letter position the match starts:

text = 'Say hi at'
first_match =
if first_match:
start = first_match.start() # start == 10

In JavaScript the search() method belongs to the string and it returns just an integer telling at which letter position the match starts. If nothing is found, -1 is returned:

text = 'Say hi at';
first_match =;
if (first_match > -1) {
start = first_match; // start === 10

Replacing patterns in strings using regular expressions

Replacing with regular expressions usually happen when cleaning up data, or adding additional features. For example, we could take some text and make all email addresses clickable.

Python developers would use the sub() method of the regular expression pattern:

html = pattern.sub(
r'<a href="mailto:\g<0>">\g<0></a>',
'Say hi at',
# html == 'Say hi at <a href=""></a>'

JavaScript developers would use the replace() method of the string:

html = 'Say hi at'.replace(
'<a href="mailto:$&">$&</a>',
// html === 'Say hi at <a href=""></a>'

In Python the captures, also called as "backreferences", are accessible in the replacement string as \g<0>, \g<1>, \g<2>, etc. In JavaScript the same is accessible as $&, $1, $2, etc. Backreferences are usually used to wrap some strings or to switch places of different pieces of text.

It is also possible to replace a match with a function call. This can be used to do replacements within replacements or to count or collect some features of a text. For example, using replacements with function calls in JavaScript, I once wrote a fully functional HTML syntax highlighter.

Here let's change all email addresses in a text to UPPERCASE.

In Python, the replacement function receives the match object. We can use its group() method to do something with the matched text and return a text as a replacement:

text = pattern.sub(
lambda match:,
'Say hi at',
# text == 'Say hi at HI@EXAMPLE.COM'

In JavaScript the replacement function receives the whole match string, the first capture, the second capture, etc. We can do what we need with those values and then return some string as a replacement:

text = 'Say hi at'.replace(
function(match, p1, p2) {
return match.toUpperCase();
// text === 'Say hi at HI@EXAMPLE.COM'

Error handling

Contrary to Python, client-side JavaScript normally isn't used for saving or reading files or connecting to remote databases. So try..catch blocks are quite rare in JavaScript compared to try..except analogy in Python.

Anyway, error handling can be used with custom user errors implemented and raised in JavaScript libraries and caught in the main code.

The following example in Python shows how to define a custom exception class MyException, how to raise it in a function, and how to catch it and handle in a try..except..finally block:

class MyException(Exception):
def __init__(self, message):
self.message = message

def __str__(self):
return self.message

def proceed():
raise MyException('Error happened!')

except MyException as err:
print('Sorry! {}'.format(err))

The following example in JavaScript does exactly the same: here we define a MyException class, throw it in a function, and catch it and handle in the try..catch..finally block.

function MyException(message) {
this.message = message;
this.toString = function() {
return this.message;

function proceed() {
throw new MyException('Error happened!');

try {
} catch (err) {
if (err instanceof MyException) {
console.log('Sorry! ' + err);
} finally {

The MyException class in both languages has a parameter message and a method to represent itself as a string using the value of the message.

Of course, exceptions should be raised/thrown just in the case of errors. And you define what is an error in your module design.

The Takeaways

  • Serialization to JSON is quite straightforward in both, Python and JavaScript.
  • Regular expressions can be used as multi-tools when working with textual data.
  • You can do replacements with function calls in both languages.
  • For more sophisticated software design you can use custom error classes.

As I mentioned last time, you can grab a side-by-side comparison of Python and JavaScript that I compiled for you (and my future self). Side by side you will see features from traditional list, array, dictionary, object, and string handling to modern string interpolation, lambdas, generators, sets, classes, and everything else. Use it for good.

Get the Ultimate Cheat Sheet of Equivalents in Python and JavaScript

In the next part of the series, we will have a look at textual templates, list unpacking, lambda functions, iteration without indexes, generators, and sets. Stay tuned!

Cover photo by Benjamin Hung.

Equivalents in Python and JavaScript. Part 1

Par Aidas Bendoraitis a.k.a. archatas

Although Python and JavaScript are quite different languages, there are some analogies which full stack Python developers should know when developing web projects. In this series of 4 parts, I will explore what is similar in each of those languages and what are the common ways to solve common problems. This is not meant to be a reference and I will skip the basics like primitive variable types, conditions, and loops. But I will dig into more complex structures and data operations using both, Python and JavaScript. Also, I will try to focus on the practical use cases. This series should be interesting for the developers of Django, Flask, or another Python framework who want to get a grasp of traditional and modern vanilla JavaScript. On the other hand, it will be useful for the front-enders who want to better understand how the backend is working and maybe even start their own Django website.

Parsing integers

We'll begin with integer parsing.

In Python that's straightforward:

number = int(text)

But in JavaScript you have to explain what number system you expect: decimal, octal, hexadecimal, or binary:

number = parseInt(text, 10);

To use the "normal" decimal number system we are passing number 10 as the second parameter of the parseInt() function. 8 goes for octal, 16 for hexadecimal, or 2 – for binary. If the second parameter is missing, the number in text starts with zero, and you are using a slightly older browser, the number in the text will be interpreted as octal. For example,

parseInt('012') == 10  // in some older browsers
parseInt('012', 10) == 12

And that can really mess up your calculations.

Conditional assignment

For conditional assignment, Python and JavaScript have different syntaxes, but conditional assignments are quite popular in both languages. That's popular, because it's just a single statement to have a condition checking, the true-case value, and the false-case value.

Since Python 2.7 you can write conditional assignments like this:

value = 'ADULT' if age >= 18 else 'CHILD'

In JavaScript conditional assignments are done using ternary operator ?:, similar to the ones in C, C++, C#, Java, Ruby, PHP, Perl, Swift, and ActionScript:

value = age >= 18? 'ADULT': 'CHILD';

Object attribute value by attribute name

The normal way to access an object's attribute is by the dot notation in both, Python and JavaScript:

obj.color = 'YELLOW'

But what if you want to refer to an attribute by its name saved as a string? For example, the attribute name could be coming from a list of attributes or the attribute name is combined from two strings like 'title_' + lang_code.

For that reason, in Python, there are functions getattr() and setattr(). I use them a lot.

attribute = 'color'
value = getattr(obj, attribute, 'GREEN')
setattr(obj, attribute, value)

In JavaScript you can treat an object like a dictionary and pass the attribute name in square brackets:

attribute = 'color';
value = obj[attribute] || 'GREEN';
obj[attribute] = value;

To retrieve a default value when an object has no such attribute, in Python, getattr() has the third parameter. In JavaScript, if obj attribute doesn't exist, it will return the undefined value. Then it can be OR-ed with the default value that you want to assign. That's a common practice in JavaScript that you can find in many JavaScript libraries and frameworks.

Dictionary value by key

This is similar to the previous one. The normal way to assign a dictionary's value by key in both languages is using the square brackets:

dictionary = {}
dictionary['color'] = 'YELLOW'

To read a value in Python you can use the square-bracket notation, but it will fail on non-existing keys with KeyError. The more flexible way is to use the get() method which returns None for non-existing keys. Also you can pass an optional default value as the second parameter:

key = 'color'
value = dictionary.get(key, 'GREEN')

In JavaScript you would use the same trick as with object attributes, because dictionaries and objects are the same there:

key = 'color';
value = dictionary[key] || 'GREEN';

Slicing lists and strings

Python has the slice [:] operator to get parts of lists, tuples, and similar more complex structures, for example Django QuerySets:

items = [1, 2, 3, 4, 5]
first_two = items[:2] # [1, 2]
last_two = items[-2:] # [4, 5]
middle_three = items[1:4] # [2, 3, 4]

In JavaScript arrays have the slice() method with the same effect and similar usage:

items = [1, 2, 3, 4, 5];
first_two = items.slice(0, 2); // [1, 2]
last_two = items.slice(-2); // [4, 5]
middle_three = items.slice(1, 4); // [2, 3, 4]

But don't mix it up with the splice() method which modifies the original array!

The [:] slice operator in Python also works for strings:

text = 'ABCDE'
first_two = text[:2] # 'AB'
last_two = text[-2:] # 'DE'
middle_three = text[1:4] # 'BCD'

In JavaScript strings just like arrays have the slice() method:

text = 'ABCDE';
first_two = text.slice(0, 2); // 'AB'
last_two = text.slice(-2); // 'DE'
middle_three = text.slice(1, 4); // 'BCD'

Operations with list items

In programming it is very common to collect and analyze sequences of elements. In Python that is usually done with lists and in JavaScript with arrays. They have similar syntax and operations, but different method names to add and remove values.

This is how to concatenate two lists, add one value to the end, add one value to the beginning, get and remove a value from the beginning, get and remove a value from the end, and delete a certain value by index in Python:

items1 = ['A']
items2 = ['B']
items = items1 + items2 # items == ['A', 'B']
items.append('C') # ['A', 'B', 'C']
items.insert(0, 'D') # ['D', 'A', 'B', 'C']
first = items.pop(0) # ['A', 'B', 'C']
last = items.pop() # ['A', 'B']
items.delete(0) # ['B']

This is how to do exactly the same with arrays in JavaScript:

items1 = ['A'];
items2 = ['B'];
items = items1.concat(items2); // items === ['A', 'B']
items.push('C'); // ['A', 'B', 'C']
items.unshift('D'); // ['D', 'A', 'B', 'C']
first = items.shift(); // ['A', 'B', 'C']
last = items.pop(); // ['A', 'B']
items.splice(0, 1); // ['B']

Joining lists of strings

It is very common after having a list or array of strings, to combine them into one string by a separator like comma or new line.

In Python that is done by the join() method of a string where you pass the list or tuple. Although it might feel unnatural, you start with the separator there. But I can assure that you get used to it after several times of usage.

items = ['A', 'B', 'C']
text = ', '.join(items) # 'A, B, C'

In JavaScript the array has the join() method where you pass the separator:

items = ['A', 'B', 'C'];
text = items.join(', '); // 'A, B, C'

The Takeaways

  • List and tuples in Python are similar to arrays in JavaScript.
  • Dictionaries in Python are similar to objects in JavaScript.
  • Strings in Python are similar to strings in JavaScript.
  • Numbers in JavaScript should be parsed with care.
  • Single-line conditional assignments exist in both languages.
  • Joining sequences of strings in Python is confusing, but you can quickly get used to it.

I compiled the whole list of equivalents of Python and JavaScript to a cheat sheet that you can print out and use for good. Side by side it compares traditional Python 2.7 and JavaScript based on ECMAScript 5 standard, as well as newer Python 3.6 and JavaScript based on ECMAScript 6 standard with such goodies as string interpolation, lambdas, generators, classes, etc.

Get the Ultimate Cheat Sheet of Equivalents in Python and JavaScript

In the next part of the series, we will have a look at JSON creation and parsing, operations with regular expressions, and error handling. Stay tuned!

Cover photo by Benjamin Hung.

Data Filtering in a Django Website using Elasticsearch

Par Aidas Bendoraitis a.k.a. archatas

In my Web Development with Django Cookbook section Forms and Views there is a recipe Filtering object lists. It shows you how to filter a Django QuerySet dynamically by different filter parameters selected in a form. From practice, the approach is working well, but with lots of data and complex nested filters, the performance might get slow. You know - because of all those INNER JOINS in SQL, the page might take even 12 seconds to load. And that is not preferable behavior. I know that I could denormalize the database or play with indices to optimize SQL. But I found a better way to increase the loading speed. Recently we started using Elasticsearch for one of the projects and its data filtering performance seems to be enormously faster: in our case, it increased from 2 to 16 times depending on which query parameters you choose.

What is Elasticsearch?

Elasticsearch is java-based search engine which stores data in JSON format and allows you to query it using special JSON-based query language. Using elasticsearch-dsl and django-elasticsearch-dsl, I can bind my Django models to Elasticsearch indexes and rewrite my object list views to use Elasticsearch queries instead of Django ORM. The API of Elasticsearch DSL is chainable like with Django QuerySets or jQuery functions, and we'll have a look at it soon.

The Setup

At first, let's install Elasticsearch server. Elasticsearch is quite a complex system, but it comes with convenient configuration defaults.

On macOS you can install and start the server with Homebrew:

$ brew install elasticsearch
$ brew services start elasticsearch

For other platforms, the installation instructions are also quite clear.

Then in your Django project's virtual environment install django-elasticsearch-dsl. I guess, "DSL" stands for "domain specific language".

With pipenv it would be the following from the project's directory:

$ pipenv install django-elasticsearch-dsl

If you are using just pip and virtual environment, then you would do this with your project's environment activated.

(venv)$ pip install django-elasticsearch-dsl

This, in turn, will install related lower level client libraries: elasticsearch-dsl and elasticsearch-py.

In the Django project settings, add 'django_elasticsearch_dsl' to INSTALLED_APPS.

Finally, add the lines defining default connection configuration there:

'default': {
'hosts': 'localhost:9200'

Elasticsearch Documents for Django Models

For the illustration how to use Elasticsearch with Django, I'll create Author and Book models, and then I will create Elasticsearch index document for the books.

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals

from django.db import models
from django.utils.translation import ugettext_lazy as _
from django.utils.encoding import python_2_unicode_compatible

class Author(models.Model):
first_name = models.CharField(_("First name"), max_length=200)
last_name = models.CharField(_("Last name"), max_length=200)
author_name = models.CharField(_("Author name"), max_length=200)

class Meta:
verbose_name = _("Author")
verbose_name_plural = _("Authors")
ordering = ("author_name",)

def __str__(self):
return self.author_name

class Book(models.Model):
title = models.CharField(_("Title"), max_length=200)
authors = models.ManyToManyField(Author, verbose_name=_("Authors"))
publishing_date = models.DateField(_("Publishing date"), blank=True, null=True)
isbn = models.CharField(_("ISBN"), blank=True, max_length=20)

class Meta:
verbose_name = _("Book")
verbose_name_plural = _("Books")
ordering = ("title",)

def __str__(self):
return self.title

Nothing fancy here. Just an Author model with fields id, first_name, last_name, author_name, and a Book model with fields id, title, authors, publishing_date, and isbn. Let's go to the documents.

In the same directory of your app, create with the following content:

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals

from django_elasticsearch_dsl import DocType, Index, fields
from .models import Author, Book

# Name of the Elasticsearch index
search_index = Index('library')
# See Elasticsearch Indices API reference for available settings

class BookDocument(DocType):
authors = fields.NestedField(properties={
'first_name': fields.TextField(),
'last_name': fields.TextField(),
'author_name': fields.TextField(),
'pk': fields.IntegerField(),
}, include_in_root=True)

isbn = fields.KeywordField(

class Meta:
model = Book # The model associated with this DocType

# The fields of the model you want to be indexed in Elasticsearch
fields = [
related_models = [Author]

def get_instances_from_related(self, related_instance):
"""If related_models is set, define how to retrieve the Book instance(s) from the related model."""
if isinstance(related_instance, Author):
return related_instance.book_set.all()

Here we defined a BookDocument which will have fields: title, publishing_date, authors, and isbn.

The authors will be a list of nested dictionaries at the BookDocument. The isbn will be a KeywordField which means that it will be not tokenized, lowercased, nor otherwise processed and handled the whole as is.

The values for those document fields will be read from the Book model.

Using signals, the document will be automatically updated either when a Book instance or Author instance is added, changed, or deleted. In the method get_instances_from_related(), we tell the search engine which books to update when an author is updated.

Building the Index

When the index document is ready, let's build the index at the server:

(venv)$ python search_index --rebuild

Django QuerySets vs. Elasticsearch Queries

The concepts of SQL and Elasticsearch queries are quite different. One is working with relational tables and the other works with dictionaries. One is using queries that are kind of human-readable logical sentences and another is using nested JSON structures. One is using the content verbosely and another does string processing in the background and gives search relevance for each result.

Even when there are lots of differences, I will try to draw analogies between Django ORM and elasticsearch-dsl API as close as possible.

1. Query definition

Django QuerySet:

queryset = MyModel.objects.all()

Elasticsearch query:

search =

2. Count

Django QuerySet:

queryset = queryset.count()

Elasticsearch query:

search = search.count()

3. Iteration

Django QuerySet:

for item in queryset:

Elasticsearch query:

for item in search:

4. To see the generated query:

Django QuerySet:

>>> queryset.query

Elasticsearch query:

>>> search.to_dict()

5. Filter by single field containing a value

Django QuerySet:

queryset = queryset.filter(my_field__icontains=value)

Elasticsearch query:

search = search.filter('match_phrase', my_field=value)

6. Filter by single field equal to a value

Django QuerySet:

queryset = queryset.filter(my_field__exact=value)

Elasticsearch query:

search = search.filter('match', my_field=value)

If a field type is a string, not a number, it has to be defined as KeywordField in the index document:

my_field = fields.KeywordField()

7. Filter with either of the conditions (OR)

Django QuerySet:

from django.db import models
queryset = queryset.filter(
models.Q(my_field=value) |

Elasticsearch query:

from elasticsearch_dsl.query import Q
search = search.query(
Q('match', my_field=value) |
Q('match', my_field2=value2)

8. Filter with all of the conditions (AND)

Django QuerySet:

from django.db import models
queryset = queryset.filter(
models.Q(my_field=value) &

Elasticsearch query:

from elasticsearch_dsl.query import Q
search = search.query(
Q('match', my_field=value) &
Q('match', my_field2=value2)

9. Filter by values less than or equal to certain value

Django QuerySet:

from datetime import datetime

queryset = queryset.filter(,

Elasticsearch query:

from datetime import datetime

search = search.filter(

10. Filter by a value in a nested field

Django QuerySet:

queryset = queryset.filter(

Elasticsearch query:

from elasticsearch_dsl.query import Q

search = search.filter(
query=Q('match', category__pk=category_id)

11. Filter by one of many values in a related model

Django QuerySet:

queryset = queryset.filter(

Elasticsearch query:

from django.utils.six.moves import reduce
from elasticsearch_dsl.query import Q

search = search.query(
reduce(operator.ior, [
query=Q('match', category__pk=category_id),
for category_id in category_ids

Here the reduce() function combines a list of Q() conditions using the bitwise OR operator (|).

12. Ordering

Django QuerySet:

queryset = queryset.order_by('-my_field', 'my_field2')

Elasticsearch query:

search = search.sort('-my_field', 'my_field2')

13. Creating query dynamically

Django QuerySet:

import operator
from django.utils.six.moves import reduce

filters = []
if value1:
if value2:
queryset = queryset.filter(
reduce(operator.iand, filters)

Elasticsearch query:

import operator
from django.utils.six.moves import reduce
from elasticsearch_dsl.query import Q

queries = []
if value1:
if value2:
search = search.query(
reduce(operator.iand, queries)

14. Pagination

Django QuerySet:

from django.core.paginator import (
Paginator, Page, EmptyPage, PageNotAnInteger

paginator = Paginator(queryset, paginate_by)
page_number = request.GET.get('page')
page =
except PageNotAnInteger:
page =
except EmptyPage:
page =

Elasticsearch query:

from django.core.paginator import (
Paginator, Page, EmptyPage, PageNotAnInteger
from django.utils.functional import LazyObject

class SearchResults(LazyObject):
def __init__(self, search_object):
self._wrapped = search_object

def __len__(self):
return self._wrapped.count()

def __getitem__(self, index):
search_results = self._wrapped[index]
if isinstance(index, slice):
search_results = list(search_results)
return search_results

search_results = SearchResults(search)

paginator = Paginator(search_results, paginate_by)
page_number = request.GET.get('page')
page =
except PageNotAnInteger:
page =
except EmptyPage:
page =

ElasticSearch doesn't work with Django's pagination by default. Therefore, we have to wrap the search query with lazy SearchResults class to provide the necessary functionality.


I built an example with books written about Django. You can download it from Github and test it.


  • Filtering with Elasticsearch is much faster than with SQL databases.
  • But it comes at the cost of additional deployment and support time.
  • If you have multiple websites using Elasticsearch on the same server, configure a new cluster and node for each of those websites.
  • Django ORM can be in a way mapped to Elasticsearch DSL.
  • I summarized the comparison of Django ORM and Elasticsearch DSL, mentioned in this article, into a cheat sheet. Print it on a single sheet of paper and use it as a reference for your developments.

Get Django ORM vs. Elasticsearch DSL Cheat Sheet

Cover photo by Karl Fredrickson.

QuerySet Filters on Many-to-many Relations

Par Aidas Bendoraitis a.k.a. archatas

Django ORM (Object-relational mapping) makes querying the database so intuitive, that at some point you might forget that SQL is being used in the background.

This year at the DjangoCon Europe Katie McLaughlin was giving a talk and mentioned one thing that affects the SQL query generated by Django ORM, depending on how you call the QuerySet or manager methods. This particularity is especially relevant when you are creating your QuerySets dynamically. Here it is. When you have a many-to-many relationship, and you try to filter objects by the fields of the related model, every new filter() method of a QuerySet creates a new INNER JOIN clause. I won't discuss whether that's a Django bug or a feature, but these are my observations about it.

The Books and Authors Example

Let's create an app with books and authors, where each book can be written by multiple authors.

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals

from django.db import models
from django.utils.translation import ugettext_lazy as _
from django.utils.encoding import python_2_unicode_compatible

class Author(models.Model):
first_name = models.CharField(_("First name"), max_length=200)
last_name = models.CharField(_("Last name"), max_length=200)
author_name = models.CharField(_("Author name"), max_length=200)

class Meta:
verbose_name = _("Author")
verbose_name_plural = _("Authors")
ordering = ("author_name",)

def __str__(self):
return self.author_name

class Book(models.Model):
title = models.CharField(_("Title"), max_length=200)
authors = models.ManyToManyField(Author, verbose_name=_("Authors"))
publishing_date = models.DateField(_("Publishing date"), blank=True, null=True)

class Meta:
verbose_name = _("Book")
verbose_name_plural = _("Books")
ordering = ("title",)

def __str__(self):
return self.title

The similar app with sample data can be found in this repository.

Inefficient Filter

With the above models, you could define the following QuerySet to select books which author is me, Aidas Bendoraitis.

queryset = Book.objects.filter(

We can check what SQL query it would generate with str(queryset.query) (or queryset.query.__str__()).

The output would be something like this:

SELECT `libraryapp_book`.`id`, `libraryapp_book`.`title`, `libraryapp_book`.`publishing_date`
FROM `libraryapp_book`
INNER JOIN `libraryapp_book_authors` ON ( `libraryapp_book`.`id` = `libraryapp_book_authors`.`book_id` )
INNER JOIN `libraryapp_author` ON ( `libraryapp_book_authors`.`author_id` = `libraryapp_author`.`id` )
INNER JOIN `libraryapp_book_authors` T4 ON ( `libraryapp_book`.`id` = T4.`book_id` )
INNER JOIN `libraryapp_author` T5 ON ( T4.`author_id` = T5.`id` )
WHERE (`libraryapp_author`.`first_name` = 'Aidas' AND T5.`last_name` = 'Bendoraitis')
ORDER BY `libraryapp_book`.`title` ASC;

Did you notice, that the database table libraryapp_author was attached through the libraryapp_book_authors table to the libraryapp_book table TWICE where just ONCE would be enough?

Efficient Filter

On the other hand, if you are defining query expressions in the same filter() method like this:

queryset = Book.objects.filter(

The generated SQL query will be much shorter and (theoretically) would perform faster:

SELECT `libraryapp_book`.`id`, `libraryapp_book`.`title`, `libraryapp_book`.`publishing_date`
FROM `libraryapp_book`
INNER JOIN `libraryapp_book_authors` ON ( `libraryapp_book`.`id` = `libraryapp_book_authors`.`book_id` )
INNER JOIN `libraryapp_author` ON ( `libraryapp_book_authors`.`author_id` = `libraryapp_author`.`id` )
WHERE (`libraryapp_author`.`first_name` = 'Aidas' AND `libraryapp_author`.`last_name` = 'Bendoraitis')
ORDER BY `libraryapp_book`.`title` ASC;

The same SQL query can be achieved using the Q() objects:

queryset = Book.objects.filter(
models.Q(authors__first_name='Aidas') &

The Q() objects add a lot of flexibility to filters allowing to OR, AND, and negate query expressions.

Dynamic Filtering

So to have faster performance, when creating QuerySets dynamically, DON'T use filter() multiple times:

queryset = Book.objects.all()
if first_name:
queryset = queryset.filter(
if last_name:
queryset = queryset.filter(

DO this instead:

filters = models.Q()
if first_name:
filters &= models.Q(
if last_name:
filters &= models.Q(
queryset = Book.objects.filter(filters)

Here the empty Q() doesn't have any impact for the generated SQL query, so you don't need the complexity of creating a list of filters and then joining all of them with the bitwise AND operator, like this:

import operator
from django.utils.six.moves import reduce

filters = []
if first_name:
if last_name:
queryset = Book.objects.filter(reduce(operator.iand, filters))


In DEBUG mode, you can check how long the previously executed SQL queries took by checking django.db.connection.queries:

>>> from django.db import connection
>>> connection.queries
[{'sql': 'SELECT …', 'time': '0.001'}, {'sql': 'SELECT …', 'time': '0.004'}]

The Takeaways

  • When querying many-to-many relationships, avoid using multiple filter() methods, make use of Q() objects instead.
  • You can check the SQL query of a QuerySet with str(queryset.query).
  • Check the performance of recently executed SQL queries with django.db.connection.queries.
  • With small datasets, the performance difference is not so obvious. For your specific cases you should do the benchmarks yourself.

Cover photo by Tobias Fischer.

From MySQL to PostgreSQL

Par Aidas Bendoraitis a.k.a. archatas

In this article I will guide you through the steps I had to take to migrate Django projects from MySQL to PostgreSQL.

MySQL database has proven to be a good start for small and medium scale projects. It is known and used widely and has good documentation. Also there are great clients for easy management, like phpMyAdmin (web), HeidiSQL (windows), or Sequel Pro (macOS). However, in my professional life there were unfortunate moments, when databases from different projects crashed because of large queries or file system errors. Also I had database integrity errors which appeared in the MySQL databases throughout years because of different bugs at the application level.

When one thinks about scaling a project, they have to choose something more suitable. It should be something that is fast, reliable, and well supports ANSI standards of relational databases. Something that most top Django developers use. And the database of choice for most professionals happens to be PostgreSQL. PostgreSQL enables using several vendor-specific features that were not possible with MySQL, e.g. multidimensional arrays, JSON fields, key-value pair fields, special case-insensitive text fields, range fields, special indexes, full-text search, etc. For a newcomer, the best client that I know - pgAdmin (macOS, linux, windows) - might seem too complex at first, compared with MySQL clients, but as you have Django administration and handy ORM, you probably won't need to inspect the database in raw format too often.

So what does it take to migrate from MySQL to PostgreSQL? We will do that in a few steps and we will be using pgloader to help us with data migration. I learned about this tool from Louise Grandjonc, who was giving a presentation about PostgreSQL query optimization at DjangoCon Europe 2017.

One prerequisite for the migration are passing tests. You need to have functional tests to check if all pages are functioning correctly and unit tests to check at least the most critical or complex classes, methods, and functions.

1. Prepare your MySQL database

Make sure that your production MySQL database migration state is up to date:

(env)$ python migrate --settings=settings.production

Then create a local copy of your production MySQL database. We are going to use it for the migration.

2. Install pgloader

As I mentioned before, for the database migration we will use a tool called pgloader (version 3.4.1 or higher). This tool was programmed by Dimitri Fontaine and is available as an open source project on GitHub. You can compile the required version from the source. Or if you are using macOS, you can install it with Homebrew:

$ brew update
$ brew install pgloader

Note that PostgreSQL will also be installed as a dependency.

3. Create a new PostgreSQL user and database

Unlike with MySQL, creating new database users and databases with PostgreSQL usually happen in the shell rather than in the database client.

Let's create a user and database with the same name myproject.

$ createuser --createdb --password myproject
$ createdb --username=myproject myproject

The --createdb parameter will enable privilege to create databases. The --password parameter will offer to enter a password. The --username parameter will set the owner of the created database.

4. Create the schema

Link the project to this new PostgreSQL database in the settings, for example:

'postgresql': {
'ENGINE': 'django.db.backends.postgresql_psycopg2',
'NAME': get_secret("DATABASE_NAME"),
'USER': get_secret("DATABASE_USER"),
DATABASES['default'] = DATABASES['postgresql']

Here the custom get_secret() function returns sensitive information from environment variables or a text file that is not tracked under version control. Its implementation is up to you.

Run the migrations to create tables and foreign key constraints in the new PostgreSQL database:

(env)$ python migrate --settings=settings.local

5. Create the data migration script

The pgloader uses configuration files with the settings defining how to deal with migrations. Let's create the configuration file myproject.load with the following content:

FROM mysql://mysql_username:mysql_password@localhost/mysql_dbname
INTO postgresql:///myproject
WITH truncate, data only, disable triggers, preserve index names, include no drop, reset sequences
ALTER SCHEMA 'mysql_dbname' RENAME TO 'public'

6. Run data migration

Now it's time to copy the data:

$ pgloader myproject.load

Typically you will get a bunch of warnings about type conversions. These can probably be ignored, because the script will take its best guess how to convert data when importing. If in addition you get errors about duplicated data or tables with foreign keys to missing entries, you will need to fix the issues at MySQL database and then repeat the process. In that case, clean up the MySQL database, update your local copy, recreate PostgreSQL database with dropdb and createdb commands, run Django migrations to create the database schema, and copy the data again.

7. Adapt the code

When the database is successfully migrated, we should run Django project tests and fix all PostgreSQL-specific problems in the project's code. The code running Django ORM will run smoothly, but very likely there will be issues with raw SQL, QuerySet's extra() method, and type conversions.

Typically, these are the differences that you might have to keep in mind:

  • String values in PostgreSQL queries are always quoted with 'single quotes'.

  • PostgreSQL doesn't convert types when comparing values automatically as MySQL does. If you use any raw SQL, you will need to do some casting before comparison like CAST( AS text) = likes_like.object_id or = likes_like.object_id. The latter double-colon syntax is not understood by MySQL, so if you want to support both databases, you will need to write vendor-specific cases for each database management system.

  • PostgreSQL is case-sensitive for string comparisons, so in the QuerySet filters you will need to use *__iexact lookup instead *__exact and *__icontains lookup instead of *__contains.

  • When ordering, convert the column to lowercase with the Lower() function:

    from django.db import models
    posts = Post.objects.order_by(models.Lower('title'))
  • When using *__in lookup, make sure that the type of the listed elements matches the type of the model field. For example, you may have a Like model with generic relation, i.e. content_type and object_id fields that together combine a generic foreign key to any model instance. The object_id field is usually of a string type, but the IDs of related models might be integers, strings, or UUIDs. If you then want to get the liked Posts which primary keys are integers, you would need to convert the object_id values to integers before assigning them to the pk__in lookup in the filter:

    liked_ids = map(int, Like.objects.filter(
    ).values("object_id", flat=True))

    liked_posts = Post.objects.filter(pk__in=liked_ids)

8. Repeat the process for production

When you are sure that the migration process is fluent and all Django tests pass, you can take your production website down, repeat the migration process locally with the latest production data, copy the migrated local database to production server, update the production code, install new dependencies, and take the website back online.

To create a database dump you can use command:

$ pg_dump --format=c --compress=9 --file=myproject.backup myproject

To restore or create the database from dump use commands:

$ dropdb --username=pgsql myproject
$ createdb --username=myproject myproject
$ pg_restore --dbname=myproject --role=myproject --schema=public myproject.backup

I might probably miss some points and there are some ways to automate the upgrade process for production, but you got the idea.


PostgreSQL is more restrictive than MySQL, but it provides greater performance, more stability, and better compliance with standards. In addition, in PostgreSQL there is a bunch of features that were not available in MySQL. If you are lucky, you can switch your project from MySQL to PostgreSQL in one day.

Cover photo by Casey Allen

Numbers in Translatable Strings

Par Aidas Bendoraitis a.k.a. archatas

Sentences in websites like "You've got 1 messages." or "Messages you've got: 5" sound unnatural and not human-friendly. But the GNU gettext tool used with Django for translations has an option to define different pluralization depending on the number which goes together with the counted noun. Things get even more interesting with certain languages which have not just singular and plural like English, German, French, or Spanish, but more plural forms or just a single one.

Tell me the background

Let's talk about grammar. Most languages have two plural forms for counted elements: one for singular, like "1 thing", and one for plural, like "n things". However, certain languages have either just one form for singular and plural, or multiple plural forms depending on the number of elements that go with them.

For example, my mother tongue Lithuanian is a Baltic language coming from Indo-European language family keeping archaic features from ancient Sanskrit. Lithuanian has 3 plural forms. When one counts apples in Lithuanian, they say "1 obuolys", "2-9 obuoliai", "10-20 obuol", "21 obuolys", "22-29 obuoliai", "30 obuol", "31 obuolys", "32-39 obuoliai", etc.

The second most widespread language on the web after English is Russian. Russian is an Eastern Slavic language from Indo-European language family officially used as the main language in Russia, Belarus, Kazakhstan, Kyrgyzstan and some smaller countries. Russian is using a special Cyrillic alphabet and it has 3 plural forms too. When one counts apples in Russian, they say "1 яблоко", "2-4 яблока", "5-20 яблок", "21 яблоко", "22-24 яблока", "25-30 яблок", etc.

Arabic is the 5th most spoken language in the world. It is written from right to left and Arabic language is an interesting example having even 6 plural forms. When counting apples, they would say:

‫"0 تفاحة"، "تفاح واحدة"، "تفاحتين"، "3-10 التفاح"، "11-99 التفاح"، "100-102 التفاح"

OK OK, with apples starting from 3 it's all the same, but theoretically it differs with other words or in different contexts.

On the contrary, Japanese - East Asian language with 125 million speakers - has just one plural form. No matter, whether it's 1 apple or 100 apples, they will be counted using the same words: "りんご1個" or "りんご100個".

By the way, please correct me if there are any translation mistakes in my examples.

Show me some code

If you want to localize your Django website, you will need to do quite a bunch of things:

  1. Add the LANGUAGES setting in your settings:

    ('ar', _('Arabic')),
    ('en', _('English')),
    ('ja', _('Japanese')),
    ('lt', _('Lithuanian')),
    ('ru', _('Russian')),
  2. Add 'django.middleware.locale.LocaleMiddleware' to your MIDDLEWARE list in the settings.

  3. Create a directory locale in your project directory with subdirectories called after each language code for which you need translations, e.g. ar, ja, lt, ru.

  4. Add LOCALE_PATHS in the settings to define where the translations will be localed:

    os.path.join(BASE_DIR, 'locale'),
  5. Use i18n_patterns() for your translatable URLs to prefix all paths with language code:

    from django.conf.urls import url
    from django.conf.urls.i18n import i18n_patterns

    from notifications.views import notification_list

    urlpatterns = i18n_patterns(
    url(r'^$', notification_list),
  6. Use gettext() and its flavors in Python code and {% trans %} and {% blocktrans %} template tags in Django templates to define translatable strings.

  7. Use ungettext() in Python code to create translatable strings with counted elements:

    # using the new-style Python string format:
    notification = ungettext(
    "You've got {n} message.",
    "You've got {n} messages.",

    # using the old-style Python string format
    notification = ungettext(
    "You've got %(n)d message.",
    "You've got %(n)d messages.",
    ) % {'n': message_count}
  8. Use {% blocktrans %} with count to create translatable strings with counted elements in Django templates:

    {% load i18n %}

    {# will create the old-style Python string #}
    {% blocktrans trimmed count n=message_count %}
    You've got {{ n }} message.
    {% plural %}
    You've got {{ n }} messages.
    {% endblocktrans %}
  9. Run makemessages management command to collect translatable strings:

    (myenv)$ python makemessages --all
  10. Translate the English terms into other languages in the locale/*/LC_MESSAGES/django.po files.

  11. Compile translations into files using the compilemessages management command:

    (myenv)$ python compilemessages
  12. Restart the webserver to reload the translations.

So what about the plural forms?

As you might know, the most common translation in the *.po file looks like this:

    #: templates/base.html
#, fuzzy
msgid "My Original String"
msgstr "My Translated String"

Very long strings are broken into multiple lines using the Pythonic concatenation without any joining symbol:

    msgstr ""
"Very very very very very very ve"
"ry very very very very very very"
" very very very very long string."

Just before the msgid you see some comments where the string is being used, in what context, whether it is "fuzzy", i.e. not yet active, or what kind of format it is using for variables: old-style "python-format" like %(variable)s or new-style "python-brace-format" like {variable}.

The first msgid is an empty string which translation has some meta information about the translation file: language, translation timestamps, author information, contacts, version, etc. One piece of the meta information is the plural forms for that language. For example, Lithuanian part looks like this:

"Plural-Forms: nplurals=3; plural=(n%10==1 && n%100!=11 ? 0 : n%10>=2 && (n%100<10 || n%100>=20) ? 1 : 2);\n"

as in:

#, fuzzy
msgid ""
msgstr ""
"Project-Id-Version: 1.0.0\n"
"POT-Creation-Date: 2017-09-18 01:12+0000\n"
"PO-Revision-Date: 2017-12-12 17:20+0000\n"
"Last-Translator: Vardenis Pavardenis <>\n"
"Language-Team: Lithuanian <>\n"
"Language: Lithuanian\n"
"MIME-Version: 1.0\n"
"Content-Type: text/plain; charset=UTF-8\n"
"Content-Transfer-Encoding: 8bit\n"
"Plural-Forms: nplurals=3; plural=(n%10==1 && n%100!=11 ? 0 : n%10>=2 && (n"
"%100<10 || n%100>=20) ? 1 : 2);\n"

It is using JavaScript-like syntax to define how many plural forms the language has, and what conditions define which type of the plural form each count gets.

Then the plurals are defined like this:

#: notifications/templates/notifications/notification_list.html:2
#, python-format
msgid "You've got %(n)s message."
msgid_plural "You've got %(n)s messages."
msgstr[0] "Jūs gavote %(n)s žinutę."
msgstr[1] "Jūs gavote %(n)s žinutes."
msgstr[2] "Jūs gavote %(n)s žinučių."

#: notifications/
#, python-brace-format
msgid "You've got {n} message."
msgid_plural "You've got {n} messages."
msgstr[0] "Jūs gavote {n} žinutę."
msgstr[1] "Jūs gavote {n} žinutes."
msgstr[2] "Jūs gavote {n} žinučių."

Let's have a look at the other languages mentioned before. The Russian language would have plural forms defined like this:

"Plural-Forms: nplurals=3; plural=(n%10==1 && n%100!=11 ? 0 : n%10>=2 && n%10<=4 && (n%100<10 || n%100>=20) ? 1 : 2);\n"

Then then translations for each of the 3 forms would go like this:

#: notifications/
#, python-brace-format
msgid "You've got {n} message."
msgid_plural "You've got {n} messages."
msgstr[0] "У вас есть {n} сообщение."
msgstr[1] "У вас есть {n} сообщения."
msgstr[2] "У вас есть {n} сообщений."

You would define 6 plural forms for the Arabic language:

"Plural-Forms: nplurals=6; plural=(n==0 ? 0 : n==1 ? 1 : n==2 ? 2 : n%100>=3 && n%100<=10 ? 3 : n%100>=11 ? 4 : 5);\n"

And the translations for Arabic would look like this:

#: notifications/
#, python-brace-format
msgid "You've got {n} message."
msgid_plural "You've got {n} messages."
msgstr[0] "لديك {n} رسائل."
msgstr[1] "لديك رسالة واحدة."
msgstr[2] "لديك رسالتان."
msgstr[3] "لديك {n} رسائل."
msgstr[4] "لديك {n} رسالة."
msgstr[5] "لديك {n} رسالة."

The Japanese language would have just one plural form defined:

"Plural-Forms: nplurals=1; plural=0;\n"

And it would have just one translation:

#: notifications/
#, python-brace-format
msgid "You've got {n} message."
msgid_plural "You've got {n} messages."
msgstr[0] "あなたはメッセージが{n}つを持っています。"

Tips to take away

  • Use the new-style Python format for variables whenever possible, because it is more understandable and less error prone for not-so-technical translators and it looks cleaner in the Python code.
  • Note that {% blocktrans %} template tag produces the old-style Python format for variables, whereas in Python code you can decide for yourself which format to use.
  • For the first entry msgstr[0], which usually represents singular form, don't replace the first {n} with 1 in the translation, because in many languages it also means 21, 31, 41, 101, etc. Let the variable be passed.
  • You can look up for the plural forms of a certain language at But the latest versions of Django also include some kind of plural forms, although they don't always match the conditions from the mentioned list.
  • If you want to edit plural forms more human-friendly than in a text editor, you can use the Poedit translation editor with graphical user interface. It shows the numbering cases listed, so you don't need reverse-engineer the conditions and guess about the leftovers in the else case.
  • Unfortunately, it is not possible to have multiple translatable counted objects in the same sentence using gettext. For example, "There are 5 apples, 3 pears, and 1 orange on the table" with changeable numbers is not a valid translatable sentence if you want to keep the counted elements human-friendly. To work around, you need to formulate three different translatable sentences.

Cover photo by Romain Vignes

Domain Name for Django Development Server

Par Aidas Bendoraitis a.k.a. archatas

Isn't it strange that browsing the web you usually access the websites by domain names, however, while developing a Django website, you usually access it through IP address? Wouldn't it be handy to navigate through your local website by domain name too? Let's have a look what possibilities there are to access the local development server by a domain name.

Access via IP Address

You probably know the following line by heart since the first day of developing with Django and can type it with closed eyes?

(myenv)$ python runserver

When you run a management command runserver, it starts a lightweight Django development server which by default listens to HTTP requests on your local machine's port 8000, whereas by default, HTTP websites are running on the 80 and HTTPS websites are running on 443. Enter in a browser and you can click through your Django project.

Note that this is a local address and it is not accessible from other devices in the network. Other people accessing the same address from their computers will see what is provided by web servers on their own machines, if any web server is running there at all.

Each device in a local network has its own Internet Protocol (IP) address. There are two versions of IP addresses: IPv4, typically formed from 4 decimal numbers separated by dots (e.g., and IPv6, formed from hexadecimal numbers separated by colons (e.g. [fe80::200:f8ff:fe21:67cf]). The IP address can be set automatically and generated dynamically when you connect to the network, or you can set it manually and make it static. For example, the printer in the network will usually have a static address, whereas a mobile phone or tablet will have a dynamically attached IP addresses.

If you want to access a responsive website on your computer from another device in the network, I recommend you to set the IP address manually in the network settings. It is much more convenient to have an address that doesn't change every time you connect to the same network - you can bookmark it or use in different configuration files. Just don't let it clash with the IP addresses of other devices in the network.

Then run the local development server passing IP address and port 8000:

(myenv)$ python runserver

The is a special case. It allows you to access the website through any IP address that is assigned to your computer: or, or the one that is set in your network settings. To access the website through any of those addresses, you will have to list those IP addresses in your Django setting ALLOWED_HOSTS.

Moreover, this allows you to check the website you are building through your computer's IP address, e.g., not only from your computer, but from any smartphone, tablet, or another computer in the same local network. Also through the same IP address you can access the website from a virtual machine. For example, by installing Windows in Parallels Desktop on a Mac, you can test how Django websites behave in Opera, Microsoft Edge, or Internet Explorer.

Domain Names for Local Host

Sometimes you want to address the website you are developing using a unique host name. This is necessary either when you have subdomains which lead to different parts of the website (e.g. should show my profile), or when you need to test social authentication (e.g. using Python Social Auth).

One of the ways to deal with that is configuring a hosts file, which allows to map host names to IP addresses manually. Unfortunately, the hosts file doesn't support wildcard entries, such as <anything>, so for any new subdomain, you will need to modify the file as a Super User on Unix-based operating systems or as System Administrator on Windows.

A better way is to use a wildcard domain name that points to the IP of local host: You can either set it up yourself at a domain provider, or use one of the available services.

For example, by Scott Forsyth allows you to have unlimited wildcard entries pointing to local host. So all of the following domains would show a website at local host:

Whichever domains you need to make work, don't forget to add them to ALLOWED_HOSTS in the Django project settings.

This enables to use authentication at Facebook or payments by PayPal (except the Instant Payment Notification which we'll cover a little later).

Also you can test subdomain resolution. For example, Django context processor might parse the subdomain and add some context variables, or a middleware might parse the subdomain and rewrite the path or redirect to a specific view.

Unfortunately, you can't test the website from an iPhone or iPad, using such address. And setting up your own domain's Address Record (A record) to the static IP of a computer in a local network is too inconvenient.

Domain Names for Local IP

There is another service - provided by Basecamp which allows you to use a wild card domain entries pointing to specific IP address.

Supposing that your computer's IP address is, all of the following domains would show a website on your computer's local web server:

Add them to ALLOWED_HOSTS in the project settings and you can check the website from any capable device in the local network.

Unless you are using the standard port 80, you will always have to add the port number. Also your website will be shown unsecured under HTTP, not HTTPS, and in some cases you will need to test the Django website under secure conditions, for example, when creating a Facebook canvas app or working with payments.


Sometimes you want to demonstrate your fresh website to other participants at a hackathon. Or you want to share your website temporarily with the interested colleagues or friends. Or you need to test services that use Webhooks - HTTP callbacks, that post data to your server on specific events, like Instant Payment Notification at PayPal or notifications about sent SMS messages at twilio.

One way to do that is to have a remote staging website and to deploy to it very often to test the development results. For that you need a specific domain and server, and probably some automation for deployment. Also you will need to log all activities and edit log files in Terminal - no ability to make use of handy visual PyCharm debugging with breakpoints.

This is quite inconvenient. Luckily, alternatives to this method exist.

Tunnels are systems making your local host open to the public Internet. Tunnels have a frontend - that's the server by which the website will be accessed, and backend - that's your own development machine. By creating a tunnel, you open access through a firewall from a frontend server to local servers running on specified ports.

The best known open source tunnelling systems are,, and Let's have a look at each of them.

Although it is not under active development now - the last commit was more than a year ago - ngrok is the most popular one. At the time of writing, it has 10573 GitHub stars. The tool was coded in the go programming language.

The ngrok is a freemium service giving you one persistent session and one randomly generated subdomain for free, but if you want to customize the setup or even install it on your own servers, you have to pay an annual fee.

To start a tunnel for a local Django project, you would type the following in the Terminal:

$ ngrok http 8000

Then anybody on the Internet could access your entering something like in their browser's address bar.

The default ngrok configuration would also start a special website running at http://localhost:4040 that would show the details of the traffic to and from your Django website.

If you are a paying customer and want to have a custom subdomain for your website, you can start the tunnel typing this in the Terminal:

$ ngrok http -subdomain=myproject 8000

This would create a domain like that would show the content of the Django project on your local host.

Using Canonical Name Records (CNAME records) in DNS configuration, it is also possible to create tunnels within ngrok under custom domain names like, and even wildcard entries like https://<anything>

To restrict access only to specific users, you can also use the Basic authentication with the following command:

$ ngrok http -auth="username:password" 8000

This service was created overnight at a hackathon and then published and maintained as it proved to be a useful tool. doesn't require any user account, and it creates a temporary access to your localhost under a randomly generated subdomain like or a custom subdomain like if it is available. When you close the tunnel, the address is not saved for you for future usage.

Localtunnel is free and open source. If you want or need, you can install the frontend part on your own server, so called "on premise".

To start a tunnel you would normally type the following in the Terminal:

$ lt --port 8000

If you need a custom domain, you can also type this instead:

$ lt --port 8000 --subdomain myproject

Localtunnel is meant to be relatively simple for quick temporary access. Therefore, CNAME configuration and wildcard subdomains are not possible.

Still this project is under active development. It was programmed in Node JS and by the time of writing it received 4832 GitHub Stars.

Pagekite is open source, python based, pay-what-you-want solution. Comparing to the previous projects, it has only 368 GitHub Stars, but is also worth giving a try.

You can start a tunnel with Pagekite, by entering a command with your private user's domain name in the Terminal:

$ 8000

This will open a secure access to your local Django project from

For each project you can then have a separate project's address, like which can be created starting the tunnel like this:

$ 8000

With Pagekite you can have custom domains like for your tunnel using CNAME setting in the domain configuration. It's possible to expose non-web services, for example SSH or Minecraft server, too.

The Basic authentication is available using a command like this:

$ 8000 +password/username=password

Django Project Configuration

If you want to use tunnelling with your Django project, you will have to do a couple of modifications here and there:

  • Change the URL configuration to show static and media files even in non DEBUG mode:

    # ...
    import re
    from django.views.static import serve

    if settings.STATIC_URL.startswith("/"):
    urlpatterns += [
    # {'document_root': settings.STATIC_ROOT},
    if settings.MEDIA_URL.startswith("/"):
    urlpatterns += [
    {'document_root': settings.MEDIA_ROOT},

    If you want the static files to get recognized from various apps automatically, omit the {'document_root': settings.STATIC_ROOT}. Otherwise you will have to run collectstatic management command every time you change a CSS, JavaScript, or styling image file.

  • Have separate settings for the exposed access.

    # settings.local_exposed
    from .local import *
    DEBUG = False
    ALLOWED_HOSTS = [...] # enter the domains of your tunnel's frontend

    To use those settings run the following in your virtual environment:

    (myenv)$ python runserver --settings=settings.local_exposed --insecure

    Here the --insecure directive forces automatic static file recognition from different places in your project even in non DEBUG mode. Leave it out, if you are serving the static files collected by collectstatic command.

Security Recommendations

This list of security recommendations is by no means complete. Use tunnelling at your own risk.

  • Don't keep tunnels running all the time. When not in need, close the connection.
  • Share the frontend URL only with trusted people. If you make the URL easy to remember or guess, set the Basic authentication for the tunnel's frontend.
  • Switch off the DEBUG mode in your Django project.
  • Have frequent backups of your project's code, media files, and database.
  • Don't use production data for development.
  • Don't use sensitive data for testing: no real passwords or API tokens of live system, use sandbox credentials for PayPal or Stripe payments, etc.
  • If you don't trust the tunnelling services, you can set up a tunnelling frontend on your own servers.

Do you see any other security issues about using tunnelling with Django development server? Then please share your thoughts in the comments.

Final Thoughts

When you are developing a responsive website with Django and need to check how it works on a mobile device, you can run the development server with and access it on your Wifi network through the IP address of your computer, or you can use to analogically check it by a domain name.

When you need to check subdomain resolution, you can use the hosts file, configure your private subdomain pointing directly to your local IP, or use,, or one of the tunnelling services.

When you want to debug Webhooks in order to get notified about executed payments, received messages, or completed serverless processes, you can use,, or some other tunnelling service. Or of course you can set a staging website with logging, but that makes a lot of hassle debugging.

Perhaps you know some other interesting solutions how to deal with domains and local development server. If you do, don't hesitate to share your tips in the comments.

Cover photo by Michael D Beckwith

Recap of DjangoCon Europe 2017

Par Aidas Bendoraitis a.k.a. archatas

"DjangoCon, why is everybody wearing this t-shirt?" wondered the security guys in the airport of Florence, Italy, in the beginning of April. The reason for that was DjangoCon Europe 2017 happening there for a week, full of interesting talks in an exciting location.

What I liked, was that the conference was not only about technical novelties in Django world, but also about human issues that programmers deal with in everyday life.

Interesting Non-tech Topics

According to a manifest, the conference had a goal to strengthen the Django community and to shape responsible attitude towards the works done with Django.

Healthy and Successful Community

We have to build stronger communities including everyone who wants to participate without discrimination. Although, at first, it might be difficult as people have biases, i.e. prejudices for or against one person or group; by being emphatic we can accept and include everyone no matter what is their gender identity or expression, sexual orientation, ethnicity, race, neurodiversity, age, religion, disabilities, geographical location, food diversities, body size, or family status.

Valuing diversity and individual differences is the key for a healthy, positive and successful community, that empowers its members and helps them grow stronger and happier.

Responsibility for How We Use Technology

Information technology companies (Apple, Alphabet, Microsoft, Amazon, and Facebook) are among the most traded companies in the world. IT connects people and their things, automates processes, stores and treats historical data. Usually you don't need many physical resources to start an IT business. Software developers have a power to shape the future, but should use this power responsibly:

With this, great responsibility is upon us: to make the future a better place, to make the future more evenly distributed, across gender gaps and discriminations, breaking economical, political and geographical barriers.


  • When creating an online business, it is important to think about the business value that your product will give to people and the way you will make money with it. Don't make assumptions without talking to your customers.
  • When choosing employees for your company, give them freedom how to prove their knowledge: by a quiz, or whiteboard interview, or a take-home programming task. Different people have different ways how to best represent their skills.
  • Launch as early as possible. Track the usage statistics with Google Analytics or other analytics service. Collect emails for the mailing list. Write about your product in a blog and personalized emails.
  • Django is an open-source project based on the hard work of many professionals, and if you gain any commercial value of it and appreciate the framework, you should donate to the Django Software Foundation.

Interesting Tech Topics

From the technical point of view, I liked several ideas mentioned in the conference:

Automate your processes

  • For starting new projects, you can have boilerplates with the mostly used functionalities already prepared. Django management command startproject has a parameter --template for that where you can pass a URL to a zip file.
  • Developers should have troubleshooting checklists for debugging, just like airplane pilots.
  • There are several types of tests. Unit tests check the functionality of individual functions or methods. Integration tests check how different units work together. The functional tests check how the processes of business requirements work from start to end. Finally, there is manual testing requiring people to click through the website and fill in the forms. Some tests like the ones involving third-party authentication or mobile phones, are hardly possible to automate. Anyway, manual testing is the most expensive in time and resources (besides it being boring for the tester), functional tests go after them, then integration tests, and lastly unit tests. Although automatic testing adds up to the development time, in the long run it makes the systems more stable and error proof.

What about Django

  • You can extend the Django ORM with custom lookups, transactions, and filtered prefetchings, to make your QuerySets more readable and more capable.
  • Once again, PostgreSQL has more capabilities than MySQL and is more stable. Use EXPLAIN ANALYZE ... SQL command to find the bottlenecks of your database queries. You can usually fix them by adding indexes.
  • You can have custom indexes for your database tables, to optimize the performance on PostgreSQL (or some other vendor) database.
  • Django 1.11 is out and it's a long-term support version.

What about Third Party Django Packages

  • After analyzing the 6 most popular model translation packages (parler, hvad, klingon, modeltranslation, nece, and i18nfield) from different angles (database support, integration in django admin and forms, performance, etc.), django-hvad seemed to be the winning approach.
  • You can visually build static websites with very little coded configuration using django-cms and djangocms-cascade. The djangocms-cascade provides an alternative nested-plugins system for Django CMS.

What about Django Projects

  • If you build web apps for developing countries, you have to keep these things in mind: people might be using cell phones instead of computers (you need responsive design with small or no images), Internet connectivity is slow and unstable (websites have to be fast and should preferably have offline versions), the users do not always understand English (the websites should be translated and adapted), and locations where people live do not always have street addresses.
  • Some interesting use cases: tracking the health of the heart with Arduino and Django, providing weather data to the whole Europe using Django, managing a radio station in Birmingham using Django.


Finally, thanks to the organizers for making this conference as great as it was. The city was beautiful, the food and coffee was delicious, the location for the talks was impressive. Looking forward to the next DjangoCon Europe!

Cover photo by Aidas Bendoraitis

Tracking the Results of Cron Jobs

Par Aidas Bendoraitis a.k.a. archatas

Every Django website needs some automatic background tasks to execute regularly. The outdated sessions need to be cleaned up, search index needs to be updated, some data needs to be imported from RSS feeds or APIs, backups need to be created, you name it. Usually, if not all the time, those regular tasks are being set as cron jobs. However, when some task is run in the background, by default, you don't get any feedback whether it was successfully completed, or whether it crashed on the way. In this post I will show you how I handle the results of cron jobs.

In a Django project, all those tasks are usually implemented as management commands. For each such command I write a short bash script, that will call the management command with specific parameters and will print the verbose output to a log file.

Let's say my project structure is like this on a remote server:

├── bin
├── include
├── lib
├── public_html
├── backups
├── project
│ └── myproject
├── scripts
└── logs

A virtual environment is created in the home directory of myproject linux user. The Django project itself is kept under project directory. The scripts directory is for my bash scripts. And the logs directory is for the verbose output of the bash scripts.

For example, for the default clearsessions command that removes outdated sessions, I would create scripts/ bash script as follows:

#!/usr/bin/env bash

echo "Cleaning up the database" > ${CRON_LOG_FILE}
date >> ${CRON_LOG_FILE}

source bin/activate
cd project/myproject
python clearsessions --verbosity=2 --traceback >> ${CRON_LOG_FILE} 2>&1

echo "Finished." >> ${CRON_LOG_FILE}
echo "$(($duration / 60)) minutes and $(($duration % 60)) seconds elapsed." >> ${CRON_LOG_FILE}

To run this command every night at 1 AM, you could create a file myproject_crontab with the following content:

00 01 * * * /home/myproject/scripts/

Then register the cron jobs with:

$ crontab myproject_crontab

By such a bash script, I can track:

  • At what time the script was last executed.
  • What is the verbose output of the management command.
  • If the management command broke, what was in the traceback.
  • Whether the command finished executing or hung up.
  • How long it took to run the command.

In addition, this gives me information whether the crontab was registered and whether the cron service was running at all. As I get the total time of execution in minutes and seconds, I can decide how often I can call the cron job regularly so that it doesn't clash with another cron job.

When you have multiple Django management commands, you can group them thematically into single bash script, or you can wrap them into individual bash scripts. After putting them into the crontab, the only thing left is manually checking the logs from time to time.

If you have any suggestions how I could even improve this setup, I would be glad to hear your opinion in the comments.

Here is the Gist of the scripts in this post. To see some examples of custom Django management commands, you can check Chapter 9, Data Import and Export in my book Web Development with Django Cookbook - Second Edition.

Cover photo by Redd Angelo

Django Administration: Inlines for Inlines

Par Aidas Bendoraitis a.k.a. archatas

The default Django model administration comes with a concept of inlines. If you have a one-to-many relationship, you can edit the parent and its children in the same form. However, you are limited in a way that you cannot have inlines under inlines at nested one-to-many relations. For example, you can't show models Painter, Picture, and Review in the same form if one painter may have drawn multiple pictures and each picture may have several reviews.

In this article I would like to share a workaround allowing you to quickly access the inlines of an inline model. The idea is that for every inline you can provide a HTML link leading to the separate form where you can edit the related model and its own relations. It's as simple as that.

For example, in the form of Painter model, you have the instances of Picture listed with specific links "Edit this Picture separately":

When such a link is clicked, the administrator goes to the form of the Picture model which shows the instances of Review model listed underneath:

Let's have a look, how to implement this.

First of all, I will create a gallery app and define the three models there. Nothing fancy here. The important part there is just that the Picture model has a foreign key to the Painter model and the Review model has a foreign key to the Picture model.

# gallery/
# -*- coding: UTF-8 -*-
from __future__ import unicode_literals

import os

from django.db import models
from django.utils.encoding import python_2_unicode_compatible
from django.utils.translation import ugettext_lazy as _
from django.utils.text import slugify

class Painter(models.Model):
name = models.CharField(_("Name"), max_length=255)

class Meta:
verbose_name = _("Painter")
verbose_name_plural = _("Painters")

def __str__(self):

def upload_to(instance, filename):
filename_base, filename_ext = os.path.splitext(filename)
return "painters/{painter}/{filename}{extension}".format(

class Picture(models.Model):
painter = models.ForeignKey(Painter, verbose_name=_("Painter"), on_delete=models.CASCADE)
title = models.CharField(_("Title"), max_length=255)
picture = models.ImageField(_("Picture"), upload_to=upload_to)

class Meta:
verbose_name = _("Picture")
verbose_name_plural = _("Pictures")

def __str__(self):
return self.title

class Review(models.Model):
picture = models.ForeignKey(Picture, verbose_name=_("Picture"), on_delete=models.CASCADE)
reviewer = models.CharField(_("Reviewer name"), max_length=255)
comment = models.TextField(_("Comment"))

class Meta:
verbose_name = _("Review")
verbose_name_plural = _("Reviews")

def __str__(self):
return self.reviewer

Then I will create the administration definition for the models of the gallery app. Here I will set two types of administration for the Picture model:

  • By extending admin.StackedInline I will create administration stacked as inline.
  • By extending admin.ModelAdmin I will create administration in a separate form.

In Django model administration besides usual form fields, you can also include some computed values. This can be done by your fields (or fieldsets) and readonly_fields attributes referring to a callable or a method name.

You can set a translatable label for those computed values by defining short_description attribute for the callable or method. If you want to render some HTML, you can also set the allow_tags attribute to True (otherwise your HTML string will be escaped).

# gallery/
# -*- coding: UTF-8 -*-
from django.contrib import admin
from django.core.urlresolvers import reverse
from django.utils.translation import ugettext_lazy as _
from django.utils.text import force_text

from .models import Painter, Picture, Review

def get_picture_preview(obj):
if # if object has already been saved and has a primary key, show picture preview
return """<a href="{src}" target="_blank"><img src="{src}" alt="{title}" style="max-width: 200px; max-height: 200px;" /></a>""".format(
return _("(choose a picture and save and continue editing to see the preview)")
get_picture_preview.allow_tags = True
get_picture_preview.short_description = _("Picture Preview")

class PictureInline(admin.StackedInline):
model = Picture
extra = 0
fields = ["get_edit_link", "title", "picture", get_picture_preview]
readonly_fields = ["get_edit_link", get_picture_preview]

def get_edit_link(self, obj=None):
if # if object has already been saved and has a primary key, show link to it
url = reverse('admin:%s_%s_change' % (obj._meta.app_label, obj._meta.model_name), args=[force_text(])
return """<a href="{url}">{text}</a>""".format(
text=_("Edit this %s separately") % obj._meta.verbose_name,
return _("(save and continue editing to create a link)")
get_edit_link.short_description = _("Edit link")
get_edit_link.allow_tags = True

class PainterAdmin(admin.ModelAdmin):
save_on_top = True
fields = ["name"]
inlines = [PictureInline]

class ReviewInline(admin.StackedInline):
model = Review
extra = 0
fields = ["reviewer", "comment"]

class PictureAdmin(admin.ModelAdmin):
save_on_top = True
fields = ["painter", "title", "picture", get_picture_preview]
readonly_fields = [get_picture_preview]
inlines = [ReviewInline]

UPDATE! Since Django 2.0, the get_picture_preview() function should use mark_safe() instead of allow_tags=True:

from django.utils.safestring import mark_safe
# ...
def get_edit_link(self, obj=None):
if # if object has already been saved and has a primary key, show link to it
url = reverse(
'admin:%s_%s_change' % (obj._meta.app_label, obj._meta.model_name),
return mark_safe("""<a href="{url}">{text}</a>""".format(
text=_("Edit this %s separately") % obj._meta.verbose_name,
return _("(save and continue editing to create a link)")
get_edit_link.short_description = _("Edit link")

In this administration setup, the get_edit_link() method creates a HTML link between the inline and the separate administration form for the Picture model. As you can see, I also added the get_picture_preview() function as a bonus. It is included in both administration definitions for the Picture model and its purpose is to show a preview of the uploaded picture after saving it.

To recap, nested inlines are not supported by Django out of the box. However, you can have your inlines edited in a separate page with the forms linked to each other. For the linking you would use some magic of the readonly_fields attribute.

What if you really need to have inlines under inlines in your project? In that case you might check django-nested-admin and don't hesitate to share your experience with it in the comments.

Cover photo by Denys Nevozhai

Debugging Django Management Commands in PyCharm

Par Aidas Bendoraitis a.k.a. archatas

My favorite editor for Python projects is PyCharm. Besides editing code, it allows you to inspect the database, work with Git repositories, run management commands, execute bash commands and Python scripts, and debug code just in the same window. In this article, I will show you how to set breakpoints and debug Django management commands visually in PyCharm.

Django management commands are scripts that can be executed on your Django project to do something with the project database, media files, or code. Django itself comes with a bunch of commands like: migrate, runserver, collectstatic, makemessages, and clearsessions. Management commands can be executed like this:

(myproject_env)$ python clearsessions

If you want to create a custom management command in your project, you can find how to do that in the official Django documentation. Also you can find some practical examples in the Chapter 9, Data Import and Export of the Web Development with Django Cookbook - Second Edition.

In this example, I won't create any new management command, but will debug the clearsessions command that is coming from Django and is located at django/contrib/sessions/management/commands/

First of all, let's click on "Edit Configurations..." in the top toolbar just before the Run button (with the Play icon). In the opened dialog box "Run/Debug Configurations" click on the "Add New Configuration" button (with the Plus icon) and choose "Python".

Let's fill in the configuration with these values:

Name: Clear Outdated Sessions
Script: /Users/me/DjangoProjects/myproject_env/project/myproject/
Script paramethers: clearsessions --traceback --verbosity=2
Python interpreter: Python 2.7.6 virtualenv at ~/DjangoProjects/myproject_env
Working directory: /Users/me/DjangoProjects/myproject_env/project/myproject/

Then open the file with the definition of the management command django/contrib/sessions/management/commands/ Click on the left padding of the editor to add a breakpoint (marked with a red circle) where the script should stop executing for inspection.

Normally to run this script, you could click on the Run button (with the Play icon). But as we want to debug the script, we will click on the Debug button (with the Bug icon) in the toolbar.

The script will start executing and will stop temporarily at the breakpoint you made. You will be able to inspect all local variables in the debug panel that is opened at the bottom of your window by default.

You can navigate through code execution with the arrow buttons "Step Over", "Step Into", etc. To evaluate local or global variables or values, click on the "Evaluate Expression" button (with the Calculator icon) and enter some Python code.

Click on the "Resume Program" button (with the Fast Play icon) to continue execution of the script, when you are ready.

Analogously, you can debug your models, views, forms, or middlewares by running a development server ("Django server") in debug mode.

Cover photo by Jill Heyer

Deploying a Django Website on Heroku

Par Aidas Bendoraitis a.k.a. archatas

Once you have a working project, you have to host it somewhere. One of the most popular deployment platforms nowadays is Heroku. Heroku belongs to a Platform as a Service (PaaS) category of cloud computing services. Every Django project you host on Heroku is running inside a smart container in a fully managed runtime environment. Your project can scale horizontally (adding more computing machines) and you pay for what you use starting with a free tier. Moreover, you won't need much of system administrator's skills to do the deployment - once you do the initial setup, the further deployment is as simple as pushing Git repository to a special heroku remote.

However, there are some gotchas to know before choosing Heroku for your Django project:

  • One uses PostgreSQL database with your project. MySQL is not an option.
  • You cannot store your static and media files on Heroku. One should use Amazon S3 or some other storage for that.
  • There is no mailing server associated with Heroku. One can use third-party SendGrid plugin with additional costs, GMail SMTP server with sent email amount limitations, or some other SMTP server.
  • The Django project must be version-controlled under Git.
  • Heroku works with Python 2.7. Python 3 is not yet supported.

Recently I deployed a small Django project on Heroku. To have a quick reference for the future, I summed up the process here providing instructions how to do that for future reference.

1. Install Heroku Toolbelt

Sign up for a Heroku account. Then install Heroku tools for doing all the deployment work in the shell.

To connect your shell with Heroku, type:

$ heroku login

When asked, enter your Heroku account's email and password.

2. Prepare Pip Requirements

Activate your project's virtual environment and install Python packages required for Heroku:

(myproject_env)$ pip install django-toolbelt

This will install django, psycopg2, gunicorn, dj-database-url, static3, and dj-static to your virtual environment.

Install boto and Django Storages to be able to store static and media files on an S3 bucket:

(myproject_env)$ pip install boto
(myproject_env)$ pip install django-storages

Go to your project's directory and create the pip requirements that Heroku will use in the cloud for your project:

(myproject_env)$ pip freeze -l > requirements.txt

3. Create Heroku-specific Files

You will need two files to tell Heroku what Python version to use and how to start a webserver.

In your project's root directory create a file named runtime.txt with the following content:


Then at the same location create a file named Procfile with the following content:

web: gunicorn myproject.wsgi --log-file -

4. Configure the Settings

As mentioned in the "Web Development with Django Cookbook - Second Edition", we keep the developmnent and production settings in separate files both importing the common settings from a base file.

Basically we have myproject/conf/ with the settings common for all environments.

Then myproject/conf/ contains the local database and dummy email configuration as follows:

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals
from .base import *

"default": {
"ENGINE": "django.db.backends.postgresql",
"HOST": "localhost",
"NAME": "myproject",
"PORT": "",
"USER": "postgres"

EMAIL_BACKEND = "django.core.mail.backends.console.EmailBackend"

Lastly for the production settings we need myproject/conf/ with special database configuration, non-debug mode, and unrestrictive allowed hosts as follows:

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals
from .base import *
import dj_database_url

"default": dj_database_url.config()


DEBUG = False

Now let's open myproject/ and add the following content:

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals
from import *

Finally, open the myproject/ and change the location of the DJANGO_SETTINGS_MODULE there:

os.environ.setdefault("DJANGO_SETTINGS_MODULE", "")

5. Set Up Amazon S3 for Static and Media Files

Create an Amazon S3 bucket at the AWS Console (web interface for Amazon Web Services). Go to the properties of the bucket, expand "Permissions" section, click on the "add bucket policy" button and enter the following:

"Version": "2008-10-17",
"Statement": [
"Sid": "AllowPublicRead",
"Effect": "Allow",
"Principal": {
"AWS": "*"
"Action": "s3:GetObject",
"Resource": "*"

This ensures that files on the S3 bucket will be accessible publicly without any API keys.

Go back to your Django project and add storages to the INSTALLED_APPS in myproject/conf/

# ...

Media files and static files will be stored on different paths under S3 bucket. To implement that, we need to create two Python classes under a new file myproject/ as follows:

# -*- coding: UTF-8 -*-
from __future__ import unicode_literals
from storages.backends.s3boto import S3BotoStorage

class StaticS3BotoStorage(S3BotoStorage):
Storage for static files.

def __init__(self, *args, **kwargs):
kwargs['location'] = 'static'
super(StaticS3BotoStorage, self).__init__(*args, **kwargs)

class MediaS3BotoStorage(S3BotoStorage):
Storage for uploaded media files.

def __init__(self, *args, **kwargs):
kwargs['location'] = 'media'
super(MediaS3BotoStorage, self).__init__(*args, **kwargs)

Finally, let's edit the myproject/conf/ and add AWS settings:

AWS_S3_SECURE_URLS = False       # use http instead of https
AWS_QUERYSTRING_AUTH = False # don't add complex authentication-related query parameters for requests
AWS_S3_ACCESS_KEY_ID = "..." # Your S3 Access Key
AWS_S3_SECRET_ACCESS_KEY = "..." # Your S3 Secret
AWS_S3_HOST = "" # Change to the media center you chose when creating the bucket

STATICFILES_STORAGE = "myproject.s3utils.StaticS3BotoStorage"
DEFAULT_FILE_STORAGE = "myproject.s3utils.MediaS3BotoStorage"

# the next monkey patch is necessary to allow dots in the bucket names
import ssl
if hasattr(ssl, '_create_unverified_context'):
ssl._create_default_https_context = ssl._create_unverified_context

Collect static files to the S3 bucket:

(myproject_env)$ python collectstatic --noinput

6. Set Up Gmail to Send Emails

Open myproject/conf/ and add the following settings:

EMAIL_HOST_PASSWORD = "mygmailpassword"

7. Push to Heroku

Commit and push all the changes to your Git origin remote. Personally I prefer using SourceTree to do that, but you can also do that in the command line, PyCharm, or another software.

In your project directory type the following:

(myproject_env)$ heroku create my-unique-project

This will create a Git remote called "heroku", and a new Heroku project "my-unique-project" which can be later accessed at

Push the changes to heroku remote:

(myproject_env)$ git push heroku master

8. Transfer Your Local Postgres Database To Heroku

Create local database dump:

(myproject_env)$ PGPASSWORD=mypassword pg_dump -Fc --no-acl --no-owner -h localhost -U myuser mydb > mydb.dump

Upload the database dump temporarily to some server, for example, S3 bucket: Then import that dump into the Heroku database:

(myproject_env)$ heroku pg:backups restore '' DATABASE_URL

Remove the database dump from S3 server.

9. Set Environment Variables

If your Git repository is not private, put your secret values in environment variables rather than in the Git repository directly.

(myproject_env)$ heroku config:set AWS_S3_ACCESS_KEY_ID=ABCDEFG123
$ heroku config:set AWS_S3_SECRET_ACCESS_KEY=aBcDeFg123

To read out the environment variables you can type:

(myproject_env)$ heroku config

To read out the environment variables in the Python code open myproject/conf/ and type:

import os
AWS_S3_ACCESS_KEY_ID = os.environ.get("AWS_S3_ACCESS_KEY_ID", "")

10. Set DNS Settings

Open your domain settings and set CNAME to "".

At last, you are done! Drop in the comments if I missed some part. For the new updates, see the next section.

*. Update Production

Push the changes to heroku remote:

(myproject_env)$ git push heroku master

If you have changed something in the static files, collect them again:

(myproject_env)$ python collectstatic --noinput

Collecting static files to S3 bucket takes quite a long time, so I do not recommend to do that automatically every time when you want to deploy to Heroku.

Further Reading

You can read more about Django on Heroku in the following resources:

Cover photo by Frances Gunn

Special Offer for the Readers of DjangoTricks Blog

Par Aidas Bendoraitis a.k.a. archatas

Packt Publishing, the company that published my Django book, has a special offer for enthusiast and professional developers reading this blog. For two weeks you can get the eBook "Web Development with Django Cookbook - Second Edition" for half price. The eBook is available in PDF, ePub, Mobi, and Kindle formats. Also you will get access to download the related code files.

Use the discount code DJGTRK50 at the Packt Publishing bookstore.
The discount is valid until the 24th of February, 2016.

Fresh Book for Django Developers

Par Aidas Bendoraitis a.k.a. archatas

This week the post office delivered a package that made me very satisfied. It was a box with three paper versions of my "Web Development with Django Cookbook - Second Edition". The book was published at the end of January after months of hard, but fulfilling work in the late evenings and at weekends.

The first Django Cookbook was dealing with Django 1.6. Unfortunately, the support for that version is over. So it made sense to write an update for a newer Django version. The second edition was adapted for Django 1.8 which has a long-term support until April 2018 or later. This edition introduces new features added to Django 1.7 and Django 1.8, such as database migrations, QuerySet expressions, or System Check Framework. Most concepts in this new book should also be working with Django 1.9.

My top 5 favourite new recipes are these:

  • Configuring settings for development, testing, staging, and production environments
  • Using database query expressions
  • Implementing a multilingual search with Haystack
  • Testing pages with Selenium
  • Releasing a reusable Django app

The book is worth reading for any Django developer, but will be best understood by those who already know the basics of web development with Django. You can learn more about the book and buy it at the Packt website or Amazon.

I thank the Packt Publishing very much for long cooperation in the development of this book. I am especially thankful to acquisition editor Nadeem N. Bagban, content development editors Arwa Manasawala and Sumeet Sawant, and technical editor Bharat Patil. Also I am grateful for insightful feedback from the reviewer Jake Kronika.

What 5 recipes do you find the most useful?

How to Find the Performance Bottlenecks in Your Django Views?

Par Aidas Bendoraitis a.k.a. archatas

Once you have your Django projects running, you come to situations, when you need to optimize for performance. The rule of thumb is to find the bottlenecks and then to take action to eliminate them by more idiomatic Python code, database denormalization, caching, or other techniques.

What is a bottleneck? Literally it refers to the top narrow part of a bottle. In engineering, bottleneck is a case where the performance or capacity of an entire system is limited by a single or small number of components or resources.

How to find these parts of your code? The most trivial way is to check the current time before specific code execution and after that code execution, and then count the time difference:

from datetime import datetime
start =
# heavy execution ...
end =
d = end - start # datetime.timedelta object
print d.total_seconds() # prints something like 7.861985

However, measuring code performance for Django projects like this is inefficient, because you need a lot of such wrappers for your code until you find which part is the most critical. Also you need a lot of manual computation to find the critical parts.

Recently I found line_profiler module that can inspect the performance of the code line by line. By default, to use line_profiler for your functions, you should decorate them with @profile decorator and then to execute the script:

$ kernprof -l

This script will execute your script, analize the decorated function, and will save results to a binary file that can later be inspected with:

$ python -m line_profiler

That's quite complicated, but to use line_profiler for Django views, you can install django-devserver which replaces the original development server of Django and will output the performance calculations immediately in the shell like this:

[30/Jan/2015 02:26:40] "GET /quotes/json/ HTTP/1.1" 200 137
[sql] 1 queries with 0 duplicates
[profile] Total time to render was 0.01s
[profile] Timer unit: 1e-06 s

Total time: 0.001965 s
File: /Users/archatas/Projects/quotes_env/project/inspirational/quotes/
Function: quote_list_json at line 27

Line # Hits Time Per Hit % Time Line Contents
27 def quote_list_json(request):
28 1 2 2.0 0.1 quote_dict_list = []
29 2 1184 592.0 60.3 for quote in InspirationQuote.objects.all():
30 1 1 1.0 0.1 quote_dict = {
31 1 1 1.0 0.1 'author':,
32 1 1 1.0 0.1 'quote': quote.quote,
33 1 363 363.0 18.5 'picture': quote.get_medium_picture_url(),
34 }
35 1 1 1.0 0.1 quote_dict_list.append(quote_dict)
37 1 42 42.0 2.1 json_data = json.dumps(quote_dict_list)
38 1 370 370.0 18.8 return HttpResponse(json_data, content_type="application/json")

The most interesting data in this table is the "% Time" column, giving an overview in percentage which lines of the Django view function are the most time-consuming. For example, here it says that I should pay the most attention to the QuerySet, the method get_medium_picture_url() and the HttpResponse object.

To setup line profiling, install line_profiler and django-devserver to you virtual environment:

(myproject_env)$ pip install line_profiler
(myproject_env)$ pip install django-devserver

Then make sure that you have the following settings in your or

# ...

# ...


# Modules not enabled by default

DEVSERVER_AUTO_PROFILE = True # profiles all views without the need of function decorator

When you execute

(myproject_env)$ python runserver

it will run the development server from django-devserver and for each visited view, it will show the analysis of code performance. I have tested this setup with Django 1.7, but it should work since Django 1.3.

Do you know any more useful tools to check for performance bottlenecks?