environments
Last updated
Last updated
Recommended is venv because rest don't really work, but maybe should try mamba.
is a faster drop in replacement for conda (100% faster, takes half the time)
Conda
List all packages
List all environments
Not recommended sometimes it just doesn't work, but venv does like with dlib
ERROR: Could not build wheels for dlib, which is required to install pyproject.toml-based projects
pyproject.toml(PEP spec) vs Pipfile to store more deps info
Pipenv has python version management
Faster
Setup
Use asdf to manage python versions
Pull from existing
Make sure to put poetry.lock in VC
Benefits of pipenv
deterministic install with pipfile.lock
Manages environment and pip simuletously
Using new commands mean you dont have to remember to pip freeze
can have dev and prod envs
Easy way to enforce others use the best practice of environments, environments allow different global versions of packages
Actually better syntax then virtual environments and pip freeze and requirements.txt
Disadvantages
New intrusive commands for installation and running
another layer of abstraction using virtualenvs underneath
https://github.com/pypa/pipenv/issues/796, if you mv the file you have to reinstall the pipenv :O [fix by having ]
pip install pipenv
pip install --user pipenv
pipenv install
create env if one doesn't exist or install everything
pipenv --python 3
to specify version
pipenv install requests
instead of pip install
pipenv install pymongo==3.4.0
for specific version
pipenv run
to run stuff in virtual env
pipenv run python
instead of python
Deploying
pipenv install --deploy —system
Looks like Poetry is a