11  Python environments

Python -

Poetry - you specify python version BUT you have to have it already Venv - no python version Conda - you specific python version and it gets it for you Mamba - quicker version of conda https://alpopkes.com/posts/python/packaging_tools/

11.1 Conda

To see conda environments: conda env list
To see packages in current environment: conda list
To activate environment: conda activate env_name
To create environment from yml file: conda env create --name env_name --file environment.yml
To edit yml file from terminal: nano environment.yml
To update current environment from yml file: conda env update --file environment.yml --prune
To delete environment: deactivate then conda remove -n env_name --all

11.2 Virtualenv

11.2.1 Virtualenvwrapper

Recommend using virtualenvwrapper so all your environments are stored in the same place, otherwise its easy to forget what you named it

  1. pip install virtualenvwrapper
  2. Go to Home
  3. nano .bashrc
  4. Add the following:
export WORKON_HOME=$HOME/.virtualenvs
export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3
export VIRTUALENVWRAPPER_VIRTUALENV=/usr/local/bin/virtualenv
source /usr/local/bin/virtualenvwrapper.sh
  1. Reload with source ~/.bashrc
  2. Create environment with mkvirtualenv env_name. This will be located in home/.virtualenvs.
  3. Environment activated with workon env_name
  4. See list of all available environments with command workon
  5. Delete environment - rmvirtualenv env_name

11.2.2 Virtualenv

WARNING: NEVER NAME YOUR ENVIRONMENT THE SAME AS YOUR FOLDER - as the command for deleting the environment would delete the folder…!

Steps for setting up virtual environment: 1. If not already installed, pip install virtualenv 2. Create new environment: virtualenv env_name 3. Enter the environment: source env_name/bin/activate 4. Install requirements into environment: pip install -r requirements.txt 5. Update environment from requirements: pip install -r requirements.txt --upgrade 6. Delete environment: deactivate then rm -r env_name be careful! will delete folder of same name! 7. List packages in environment: pip list

11.3 Docker

Successfully installed docker on Ubuntu using following instructions: https://docs.docker.com/engine/install/ubuntu/

Will need requirements.txt file. To create this from conda environment (with pip install in that environment and environment activated): pip list --format=freeze > requirements.txt (although may not have identifical packages - pip may have fewer). There is a simpler command of pip freeze > requirements.txt but I found that gave odd path references.

To create dockerfile:
* touch Dockerfile
* nano Dockerfile

# kailo_dashboards/Dockerfile

FROM python:3.10-slim

WORKDIR /kailo_dashboards

RUN apt-get update && apt-get install -y \
    build-essential \
    curl \
    software-properties-common \
    git \
    && rm -rf /var/lib/apt/lists/*

COPY . .

RUN pip3 install -r requirements.txt

EXPOSE 8501

HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health

ENTRYPOINT ["streamlit", "run", "streamlit_app.py", "--server.port=8501", "--se>

Explanation of Dockerfile:
* FROM - sets base image, various possible - https://hub.docker.com/_/python
* WORKDIR - sets working directory
* RUN apt-get… to install git
* COPY . . to get copy of all app files. If it was in a public GitHub repo, you could do RUN git clone https://github.com/amyheather/kailo_area_dashboard ., and if it was in a private repo, you could use SSH
* Install dependencies from requirements.txt
* EXPOSE - informs Docker that the container listens on the specified network ports at runtime. For streamlit, Your container needs to listen to Streamlit’s (default) port 8501
* HEALTHCHECK - tells Docker how to test a container to check that it is still working. Your container needs to listen to Streamlit’s (default) port 8501
* ENTRYPOINT - allows you to configure a container that will run as an executable. Here, it also contains the entire streamlit run command for your app, so you don’t have to call it from the command line

To set up docker:
* sudo docker build -t streamlit . to build an image from the Dockerfile. -t is used to tag the file, here tagged as streamlit. Can see streamlit image under repository column if run sudo docker images