Virtual environments are used to create an isolated environment for Python projects. This means that each project can have its own dependencies, regardless of what dependencies every other project has. First of all let’s review how to install, update, and uninstall packages in a virtual environment with pip. Note: The command specified below are for linux (ubuntu).
pip3 install {package_name}
pip3 install -r requirements.txt
pip3 uninstall {package_name}
pip3 install --upgrade {package_name}
pip3 freeze > requirements.txt
To create a virtual environment, you must use the venv module that
comes with Python.
# Run the venv module as a script with the -m option, passing the route
# where the virtual environment info will be store (environment name).
python3 -m venv {env_name}
source {env_name}/bin/activate
pip3 install -r requirements.txt
pip3 freeze > requirements.txt
deactivate
pip3 install virtualenv
virtualenv --no-site-packages {env_name}
# specify the python version, note that the python version must be installed
# in the system.
virtualenv --python=/usr/bin/python2.7 {env_name}
lsvirtualenv # list all the virtual environments
source {env_name}/bin/activate
pip3 install -r requirements.txt # All other pip commands work as usual
deactivate
rm -rf {env_name} # remove the virtual environment
pip3 install pipenv
cd {project_dir}
pipenv install -r requirements.txt
pipenv uninstall {package_name}
pipenv install -e git+repo_url@branch#egg=package_name
# install a package from a git repo
pipenv shell
pipenv lock # creates a Pipfile.lock file
exit
Install all the packages in the Pipfile.lock file (replicates the environment)
pipenv install --ignore-pipfile
pipenv graph # shows the dependency graph
pipenv check # checks for security vulnerabilities
exit
Different projects may require different versions of Python.
To isolate the versions of Python, you can use pyenv or pyenv-virtualenv.
It allows you to create virtual environments for different versions of python.
pyenv install --list to see all the versions of python available.
pyenv versions to see all the versions of python installed.
pyenv virtualenvs to see all the virtual environments created.
pyenv global {version} to set the global version of python.
pyenv local {version} to set the local version of python.
pyenv shell {version} to set the shell version of python.
pip3 install pyenv
pyenv install {version}
pyenv virtualenv {env_name}
pyenv activate {env_name}
pyenv deactivate
pyenv install {version}
pyenv virtualenv {version} {env_name}
pyenv local {env_name}
Anaconda is a free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment.
wget -O anaconda.sh https://repo.anaconda.com/archive/Anaconda3-2022.10-Linux-x86_64.sh
bash anaconda.sh
#source ~/.bashrc
conda info
conda create --name {env_name} python={version}
conda activate {env_name}
conda install {package_name}
conda list
conda update {package_name}
conda remove {package_name}
conda deactivate
conda remove --name {env_name} --all
conda create --name {env_name} --clone {env_name} # clone an environment
conda env export > environment.yml # export an environment
conda env create -f environment.yml # create an environment from a yml file
conda env list
conda env remove -n {env_name} # remove an environment
some useful commands
conda list # list all the packages installed in the current environment
# list all the packages installed in the current environment with their versions
conda list --explicit
# install a package from a specific channel
conda install --channel {conda-forge} {package_name}
conda list --revisions # list all the revisions of the environment
# install a specific revision of the environment
conda install --revision {revision_number}
# export the environment to a yml file
conda env export --from-history --file environment.yml
Mamba is a fast, drop-in replacement for the conda package manager. It is a C++ implementation of the conda package manager, that uses multi-threading and a sophisticated dependency solver to achieve maximum performance.
conda install -c conda-forge mamba
mamba --help
mamba create --name {env_name} python={version}
mamba activate {env_name}
mamba install {package_name}
mamba list
mamba update {package_name}
mamba remove {package_name}
mamba deactivate
mamba env create -f environment.yml # create an environment from a yml file
Docker is a containerization platform that allows you to create and run containers. Docker containers are isolated environments that run on a single host. To install docker on ubuntu, follow this tutorial.
# Dockerfile
FROM python:3.7
WORKDIR ["/app"]
COPY ["requirements.txt", "/app"]
RUN ["pip", "install", "--no-cache-dir", "upgrade", "-r", "requirements.txt"]
COPY ["app.py", "/app"] # copy the app.py file to the /app directory if you want to run the app
CMD ["python", "app.py"]
Alternatively, you can use docker-compose to build and run the docker container.
# docker-compose.yml
services:
app-csv:
build:
context: .
dockerfile: Dockerfile
volumes:
- .:/app
docker-compose build
docker-compose up -d
docker-compose ps
docker-compose logs
docker-compose exec app-csv bash
cd /app
python3 app.py
exit
docker-compose down
# Dockerfile
FROM python:3.7
WORKDIR ["/app"]
COPY ["requirements.txt", "/app"]
RUN ["pip", "install", "--no-cache-dir", "upgrade", "-r", "requirements.txt"]
COPY ["/app", "/app"]
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "80"]
# docker-compose.yml
services:
app-flask:
build:
context: .
dockerfile: Dockerfile
volumes:
- .:/app
ports:
- "80:80"
docker-compose build
docker-compose up -d
docker-compose ps
mamba to manage the versions of Python.pipenv to manage the packages of your project.more info here