Flask Brief


This document is a brief of the offical flaskr tutorial.


Create Project Directory

mkdir flask-tutorial
cd flask-tutorial

Setup A Virtual Environment

Use a virtual environment to manage the dependencies for your project, both in development and in production.

Virtual environments are independent groups of Python libraries, one for each project. Packages installed for one project will not affect other projects or the operating system’s packages.

Python 3 comes bundled with the venv module to create virtual environments. We’ll use it to create a virtual environment for our project.

Create virtual environment for your project in venv directory:

python -m venv venv

Activate the virtual environment:

. venv/bin/activate

Activate for Windows:


Upgrade python package tools(optional):

python -m pip install --upgrade pip setuptools wheel

Install Flask and its dependencies:

pip install flask

Recommandation dependencies(optional):

Project Layout

The offical flaskr tutorial project directory structure:

├── flaskr/
│   ├── __init__.py
│   ├── db.py
│   ├── schema.sql
│   ├── auth.py
│   ├── blog.py
│   ├── templates/
│   │   ├── base.html
│   │   ├── auth/
│   │   │   ├── login.html
│   │   │   └── register.html
│   │   └── blog/
│   │       ├── create.html
│   │       ├── index.html
│   │       └── update.html
│   └── static/
│       └── style.css
├── tests/
│   ├── conftest.py
│   ├── data.sql
│   ├── test_factory.py
│   ├── test_db.py
│   ├── test_auth.py
│   └── test_blog.py
├── venv/
├── setup.py
  • flaskr/, a Python package containing your application code and files.
  • tests/, a directory containing test modules.
  • venv/, a Python virtual environment where Flask and other dependencies are installed.
  • Installation files telling Python how to install your project.
  • Version control config, such as git. You should make a habit of using some type of version control for all your projects, no matter the size.
  • Any other project files you might add in the future.

Version Control Ignore

For example, with git:










A view function is the code you write to respond to requests to your application. Flask uses patterns to match the incoming request URL to the view that should handle it. The view returns data that Flask turns into an outgoing response.


A Blueprint is a way to organize a group of related views and other code. Rather than registering views and other code directly with an application, they are registered with a blueprint. Then the blueprint is registered with the application when it is available in the factory function, e.g., app.register_blueprint(your_blueprint).


URL is the HTTP access interface.

A view is to handle the corresponding HTTP request for a URL.

Endpoint is a string reference to the view in application.

The url_for() function generates the URL to a view based on a name and arguments. The name associated with a view is also called the endpoint, and by default it’s the same as the name of the view function.

For example, the hello() view that was added to the app factory earlier in the tutorial has the name 'hello' and can be linked to with url_for('hello'). If it took an argument, which you’ll see later, it would be linked to using url_for('hello',who='World').

When using a blueprint, the name of the blueprint is prepended to the name of the function, so the endpoint for the loginfunction you wrote above is 'auth.login' because you added it to the 'auth' blueprint.


Flask uses the Jinja template library to render templates.


Flask automatically adds a static view that takes a path relative to the flaskr/static directory and serves it. For example:

{{ url_for('static', filename='style.css') }}

Application Factory and Instance

The most straightforward way to create a Flask application is to create a global Flask instance directly at the top of your code. While this is simple and useful in some cases, it can cause some tricky issues as the project grows.

Instead of creating a Flask instance globally, you will create it inside a function. This function is known as the application factory. Any configuration, registration, and other setup the application needs will happen inside the function, then the application will be returned.

Create the flaskr directory and add the __init__.py file. And create application factory in it.

Application Factory example:

import os

from flask import Flask

def create_app(test_config=None):
    # create and configure the app
    app = Flask(__name__, instance_relative_config=True)
        DATABASE=os.path.join(app.instance_path, 'flaskr.sqlite'),

    if test_config is None:
        # load the instance config, if it exists, when not testing
        app.config.from_pyfile('config.py', silent=True)
        # load the test config if passed in

    # ensure the instance folder exists
    except OSError:

    # a simple page that says hello
    def hello():
        return 'Hello, World!'

    return app

Application Configuration

Configure application in the factory function for different mode

  • test mode

    The test_config dict argument for the factory function.

  • development mode

        DATABASE=os.path.join(app.instance_path, 'flaskr.sqlite'),
  • production mode

    Load the config file from instance folder: app.config.from_pyfile('config.py', silent=True).

Note: Production and test configurations wil override the development.

Running In Development

Run your application in the development mode. Development mode shows an interactive debugger whenever a page raises an exception, and restarts the server whenever you make changes to the code.

For Linux and Mac:

export FLASK_APP=flaskr
export FLASK_ENV=development
flask run

For Windows cmd, use set instead of export:

set FLASK_APP=flaskr
set FLASK_ENV=development
flask run

For Windows PowerShell, use $env: instead of export:

$env:FLASK_APP = "flaskr"
$env:FLASK_ENV = "development"
flask run

Make the Project Installable

Making your project installable means that you can build a distribution file and install that in another environment, just like you installed Flask in your project’s environment.

Describe Project

The setup.py file describes your project and the files that belong to it.


from setuptools import find_packages, setup


To include other files, such as the static and templates directories,include_package_data is set. Python needs another file named MANIFEST.in to tell what this other data is.


include flaskr/schema.sql
graft flaskr/static
graft flaskr/templates
global-exclude *.pyc

Install Project

Use pip to install your project in the virtual environment.

pip install -e .

This tells pip to find setup.py in the current directory and install it in editable or development mode. Editable mode means that as you make changes to your local code, you’ll only need to re-install if you change the metadata about the project, such as its dependencies.


  • Test tools can isolate your test environment from your development environment.
  • You can manage your project’s dependencies just like other packages do. pip install will automatically install dependencies.
  • You can import the project package from any python module.

Command Line Interface

The flask command is implemented using Click.

This example adds the command create_user that takes the argument name.

import click
from flask import Flask

app = Flask(__name__)

def create_user(name):
flask create_user admin

This example adds the same command, but as user create, a command in a group. This is useful if you want to organize multiple related commands.

import click
from flask import Flask
from flask.cli import AppGroup

app = Flask(__name__)
user_cli = AppGroup('user')

def create_user(name):

flask user create demo


Flask provides a test client that simulates requests to the application and returns the response data.

You’ll use pytest and coverage to test and measure your code. Install them both:

pip install pytest coverage


Use pytest framework to run test.

Run test cases: pytest

Test Coverage

You should test as much of your code as possible. Code in functions only runs when the function is called, and code in branches, such as if blocks, only runs when the condition is met. You want to make sure that each function is tested with data that covers each branch.

The closer you get to 100% coverage, the more comfortable you can be that making a change won’t unexpectedly change other behavior. However, 100% coverage doesn’t guarantee that your application doesn’t have bugs. In particular, it doesn’t test how the user interacts with the application in the browser. Despite this, test coverage is an important tool to use during development.

Some extra configuration, which is not required but makes running tests with coverage less verbose, can be added to the project’ssetup.cfg file. Put the following into setup.cfg file:

testpaths = tests

branch = True
source =

To measure the code coverage of your tests, use the coverage command to run pytest instead of running it directly.

coverage run -m pytest

View coverage report in command line:

coverage report

Convert report file into HTML file(see directory htmlcov):

coverage html



When you want to deploy your application elsewhere, you build a distribution file. The current standard for Python distribution is the wheel format, with the .whl extension. Make sure the wheel library is installed first:

pip install wheel

Running setup.py with Python gives you a command line tool to issue build-related commands. The bdist_wheel command will build a wheel distribution file.

python setup.py bdist_wheel

You can find the file in dist/yourpackagename-1.0.0-py3-none-any.whl. The file name is the name of the project, the version, and some tags about the file can install.


Copy this file to another machine, set up a new virtualenv with venv, then install the file with pip(not in editable mode).

pip install yourpackagename-1.0.0-py3-none-any.whl

Pip will install your project along with its dependencies.

Init DB

Since this is a different machine, you need to run init-db again to create the database in the instance folder.

export FLASK_APP=yourpackagename
flask init-db

When Flask detects that it’s installed (not in editable mode), it uses a different directory for the instance folder. You can find it at venv/var/yourpackagename-instance instead.

Production config

Create the config.py file in the instance folder, which the application factory will read from if it exists.

You muest set a Secret Key first.

Generate a random key: python -c 'import os; print(os.urandom(16))'

Copy the generated value into it the config file:

SECRET_KEY = b'_5#y2L"F4Q8z\n\xec]/'

Runing in Production

When running publicly rather than in development, you should not use the built-in development server (flask run). The development server is provided by Werkzeug for convenience, but is not designed to be particularly efficient, stable, or secure.

Instead, use a production WSGI server. For example, to use Waitress, first install it in the virtual environment:

pip install waitress

You need to tell Waitress about your application, but it doesn’t use FLASK_APP like flask run does. You need to tell it to import and call the application factory to get an application object.

waitress-serve --call 'flaskr:create_app'

Or you can choose another deploy options.


Check out the Quickstart for an overview of what Flask can do, then dive into the docs to keep learning. Flask uses Jinja, Click, Werkzeug, and ItsDangerous behind the scenes, and they all have their own documentation too. You’ll also be interested in Extensions which make tasks like working with the database or validating form data easier and more powerful.

Xiao Wenbin
Xiao Wenbin
Natural Language Processing Engineer

My research interests include machine learning, information retrieval and natural language processing.