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My requirements.txt workflow for a new Python project

· 2 min read

I usually create a requirements.txt when I start a new Python project. I will do something like this:

# Create a new project
mkdir new-project
cd new-project

# Create requirements.txt
tee -a requirements.txt <<EOF
pandas
pyarrow
EOF

# Create a virtual environment and install dependencies
python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip wheel setuptools
python -m pip install -r requirements.txt

This lets me get a new project up and running quickly. I have documented which packages I am using, which is good, but I have not documented which version of the package I am using. Since it is a new project, I want to use the latest version of every package. I could search PyPI for each package and find the latest version, but that takes a lot of time. Instead, I only document the package name in my initial requirements.txt. When I am ready to pin the versions, I use this bash script to check the version I have installed for each dependency listed in requirements.txt:

python -m pip freeze | grep -E $(cat requirements.txt | sed ':a;N;$!ba;s/\n/==|/g')

The result will be something like this:

pandas==2.1.4
pyarrow==14.0.2

I can then paste this output into my requirements.txt file.

Why not use pip freeze?

I could have also used pip freeze to get the version of the packages I have installed. The downside is that it will get the installed version of every package. Usually, I only want to pin the "top-level" dependency and not the sub-dependencies. For example, if I have pandas installed, I do not want to pin the version of numpy that pandas depends on. I only want to pin the version of pandas itself. I find that this makes it easier to update packages for my project in the future.