semver VS Poetry

It seems to me that a lot of people are forgetting that when updating to next major version of a package, breaking changes are expected - that's the whole point of major version number in SemVer [1]. What they actually want is seamless updates (or never changing APIs, but that not possible in most situations, and also not what you want as a package developer - you want to be able to correct your API design mistakes). That requires a lot of work from the package developers.

Look for example how people at Remix do it: breaking changes are hidden behind future flags [2], so you a user can turn them on one by one and adapt their code on gradually without surprises. Another solution is creating codemods for upgrades. But how many open-source package developers are willing do to this extra work?

Same story with peer dependencies - they're completely fine, if package developers know how to use them.

As always, don't be mad at React, don't curse Npm, it's not their fault. There is no great package without great effort.

[1] https://semver.org/

You can always check the official Semantic Versioning Specification.

Using Semantic Versioning for version control.

Suppose our pre-pre-production environment is named STAGING, and our pre-production environment is named UAT. STAGING corresponds to the latest commit in the main branch - that's the 'bleeding edge'. UAT corresponds to the latest release candidate tag on the main branch. In semantic versioning, this would be achieved by adding the suffix -rc.N to the name of the release it's targeting. For example, if our goal is to create production release v12.0.0, our UAT environment commits would be tagged v12.0.0-rc.1, then v12.0.0-rc.2, and so on. Suppose on v12.0.0-rc.5 we finally feel confident enough to push to production. We would then add the tag v12.0.0 to the same commit, which would constitute a full release and then be automatically deployed to production.

SemVer.org

If you don't know what semantic versioning is, I suggest you read up on it. In a nutshell, it is a standard/guideline for defining version numbers and how to increase them:

We know that our packages need to have a version. This version follows a format called semantic versioning. This is where the job called generate-version comes in. The output of this job is a version number that will be used when we publish our package in the package-and-publish-lib job.

I frequently need to set a semantic versioning version number when building ASP.NET Core API projects, then read or report this at runtime.

Since this is a coding challenge, I will be using Poetry to help me create the structure of the project, and to facilitate anyone running it. You can check how to install and use Poetry on their website.

For managing dependencies in this project, I used Poetry. Poetry simplifies the package management process and automates much of the heavy lifting involved with dependencies. It relies on the pyproject.toml file, which is now the standard for defining build requirements in modern Python projects.

# Palindrome project Project used to explain my view on a django project architecture ## Tools, libs, etc. Some time related files. Versions on Poetry. - [Python](https://www.python.org/) Programming languange - [django-environ](https://django-environ.readthedocs.io) Manage .envs in Django - [Poetry](https://python-poetry.org/) Python packaging and dependency management - poetry.lock - pyproject.toml - [Django](https://www.djangoproject.com/) Web framework written in Python - [Docker](https://www.docker.com/) Manage containers for dev environment - compose.yaml - compose/dev/Dockerfile - compose/dev/start - .env - [Just](https://just.systems/) encapsulate commands for easier use - justfile ## Dev environment setup 1. Install Just, Docker and Poetry(opcional). 2. Copy .env.example to .env, no need for edtion. 3. Certified that docker is up and running 4. `$ just build` ## Run the server for development 1. Certified that docker is up and running 2. `$ just runserver` You can access on http://0.0.0.0:8000/

Tools like Poetry aim to fix this problem, but vanilla pip can do just fine.

Our first step is to create our development environment, and install all required dependencies for this project. The good thing is that for this example we only need to install flama to have all the necessary tools to implement JWT authentication. We'll be using poetry to manage our dependencies, but you can also use pip if you prefer:

I use Python Poetry as the package management tool, so for this example I asume you have it already. First thing to do is install the dependencies with poetry install. You could also use pip to install them with: pip install pymongo loguru.

# Official Python runtime as a parent image FROM python:3.10 RUN set -xe # Install Poetry RUN curl -sSL https://install.python-poetry.org | python3 - --git https://github.com/python-poetry/poetry.git@master ENV PATH="/root/.local/bin:$PATH" # Confirm poetry version RUN poetry --version # Set up the working directory WORKDIR /app # Copy and install dependencies COPY . /app RUN poetry install EXPOSE 8000 # Start the application CMD ["bash", "-c", "poetry run bash ./prestart.sh && poetry run uvicorn app.main:app --reload --host 0.0.0.0"]

python and/or poetry