Python for the Web

Having worked on so many Python Web projects recently, it became obvious I needed some kind of boilerplate to get new projects started, hence flask-boilerplate.

A lof of this is based on the excellent cookiecutter-flask - I’ve learned a lot from it, but made enough modifications and additions to call this my own.

I have a few requirements, the most important one being simplicity. I dislike large dependencies and complicated “pythonic” code. Typically, I will also need some sort of CLI (for crons, scripts, etc), so I try to fulfil that requirement, on top of the web stack.

Let’s go over some of the requirements,


Flask is simple and comes with all essentials. The routing system is accessible, and concepts like blueprints tie it all up into a nice package. Programming languages aside, I almost always favour a small framework like Flask. Other, large and opinionated frameworks (like Django) don’t click with me. This isn’t to say I would never use a large framework, I believe that it all depends on the scope and size of the project (as well as the development team).

Very importantly, Flask allows me to develop around it, with ease.


uWSGI is my preferred way to serve web applications. I like to run it in both development and production, with different configuration files. This forces me and other developers to be in contact with uWSGI all the time, and not just in a production environment.

To run the webserver locally, simply execute uwsgi --ini web/uwsgi/development.ini from the command line.

The development.ini file includes all the required settings for a smooth development experience:

http =
home = env
wsgi-file =
callable = app
py-autoreload = 1
master = true
reload-mercy = 0
worker-reload-mercy = 0
enable-threads = true
touch-reload = web/uwsgi/development.ini

reload-mercy and worker-reload-mercy will take care of ensuring fast reload times. py-autoreload will detect changes to any .py file and trigger an automatic reload.

For production, you’ll want to introduce a few more settings, such as processes and threads - More details on the official uWSGI docs.

In the past, we have also used Apache + mod_wsgi for production, but that presented a few issues that I would rather not get into in this post.

(Note: In production, I also run NGINX on top of uWSGI)


Unpopular opinion: I dislike SQLAlchemy. It’s the opposite of simplicity. Yes, even when just using “Core”.

In another life, I did quite a bit of PHP programming, and for all its flaws, the PHP community did one thing right: SQL. A vast amount of ORMs and query builders gave developers a lot of choice. This is not the case with Python. The community is happy with SQLAlchemy, and that’s it. Very little development has gone towards alternatives - A curious case in the vast world of choice in Python. A good example is the utter lack of actively supported SQL query builders (which I tend to prefer over full blown ORMs).

Not all is doom and gloom, though! - peewee to the rescue! A simple and expressive way to handle SQL. It’s the only ORM I seem to tolerate in Python.

Here is a peewee model example from /models/ (A Postgres table):

import peewee
from peewee import *

from models import BaseModel

class ApiIpWhitelist(BaseModel):
    comment = CharField(null=True)
    dt_created = DateTimeField()
    ip_address = CharField()  # inet field, peewee does not support this type!

    class Meta:
        db_table = "api_ip_whitelist"

    def is_valid_ip(ip_address: str):
        Validates a single IP (i.e. is it in the database?).
        # Check ip.
            valid = == ip_address).get()
        except ApiIpWhitelist.DoesNotExist:
            valid = False

        if not valid:
            # Check ip range.
                valid = ApiIpWhitelist.raw(
                    "SELECT * FROM api_ip_whitelist WHERE ip_address >> %s::inet;", ip_address
            except peewee.DataError:
                valid = False

        if valid:
            return True

        return False

For integration with Flask, there is flask-peewee. It works great, but since I want to take advantage of peewee in both a web and cli environment, I tend to skip it.

(Note: Postgres is my choice for a RDBMS, which peewee supports handsomely via the playhouse extension)


Python Fire by Google is the answer for my CLIs.

A CLI has become essential in my web projects, typically in the form of crons or small management scripts. This is why I like to decouple my dependencies from the web aspect of the project.

A simple CLI example is provided in cli/

import fire
from logzero import logger

from cli import Cli

class Example(Cli):
    def __init__(self):

    def example(self, num1: int = 2, num2: int = 2):

        total = num1 + num2
        total_minus_one = total - 1"{num1} plus {num2} is {total}")"minus 1 that's {total_minus_one}")
        logger.warn("QUICK MATHS")

if __name__ == "__main__":

Simply run python cli/ example from your command line to execute.

(Note: Click is also a good alternative that I have used in the past.)


Logging in Python via the logging is fantastic, but I always end up with a lot of boilerplate code to get it to where I want it to be - Logging to files, formatting, levels, colors, file rotation/removal… It’s a lot. One day I found Logzero and never went back. The defaults are sensible and it has all the features I need.

Here is the very simple setup from the cli/ file:

# Set the logger.
logzero.logfile(f"{self.logs_dir}/{}.log", maxBytes=1000000, backupCount=3)

Sentry (optional)

Sentry styles itself as “Error tracking software”. It has become a staple of my projects (not just Python!). I’ve made it an optional in flask-boilerplate, but I definitely recommend it. There is a free plan for small projects, and you can even host it yourself!

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