Python is a popular, high-level programming language that is widely used in a variety of fields. It is known for its simplicity, readability, and flexibility, as well as its large standard library and active developer community.

Using Python in Codesphere

Python 3.8 comes pre-installed in all workspaces. The easiest way to get started with Python in Codesphere is to create a workspace from the Hello, Python! template. This template contains a ready to run Flask app. Once provisioned head over to CI-Pipeline, run the prepare stage and, once completed, the run stage.

Changing the Python version in Codesphere

Pyenv is pre-installed in all workspaces and can be used to install other versions of Python. If you want to persistently change the version, i.e. across workspace restarts or for off-when-unused workspaces, you need to follow the steps described below.

These are the steps:

1. Set PYENV_ROOT to /home/user/app/.pyenv via setup/env vars
2. Open a new terminal (existing terminals don't get updated env vars)
3. Type pipenv install --python 3.9.0 (or any other Python version)
4. Or alternatively add PIPENV_YES=1 pipenv install --python 3.9.0 to your CI prepare stage
5. Activate with pipenv shell

Important note for Micro and Free workspaces: following the previous steps may lead to the terminal/pipeline being killed halfway through - this is because the installation of CPython versions tends to exceed the compute and storage in these workspaces. Current alternatives are using a pypy version of your target Python version (list available versions via: pyenv install --list | grep -i pypy - use non-src versions) or if that is incompatible with some of your packages upgrade to a bigger workspace plan.

To work with a pypy Python version follow these steps:

• Install with pyenv install pypy3.9-7.3.8 - replace last part with your target version
• Create a pipenv with pipenv --python /home/user/app/.pyenv/versions/pypy3.9-7.3.8/bin/python3.9 - replace last part with your target version
• Activate with pipenv shell

Explore our Python Tutorials

• Create your own voice assistant
• Create your own chatbot
• Visualizing color spaces of images with Matplotlib
• Scrape your first website with Python
• Create a Discord bot in minutes
• Creating your first neural network with TensorFlow in Python
• Build a stock trading bot with Python
• Deploy web based data visualizations with Bokeh in Python

Customer Use Cases

How Project Count uses Codesphere to make their deployment and hosting trivial

> “With AWS, even just getting something set up that works is a huge pain and then platforms like Heroku are so inflexible with what you can and can’t install for your project. It just made sense to use Codesphere” This past week we sat down with Simon Pfeiffer, Founder and CEO of Project Count. Project Count aims to make product carbon footprints easily accessible for everyone, so they can better understand how to reduce their footprint. Before founding Project Count, Simon earned a Masters d

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