Using Conda allows you to keep each of your Python projects cleanly separated. These environments include all the Python libraries that you need to be a productive MicroPython developer. To simply switch between environments, all you need to do is run steps 2 and 4.Raspberry Pi Pico Forum on MicroPython SiteĬreating a Conda Environment for MicroPythonĬonda is a powerful tool for building consistent and stable Python environments.

Reactivate the environment by conda activate.

Deactivate the environment you are in by typing in the terminal: conda deactivate(this step is necessary only if you are currently in the environment you want to update).

First make all the wanted changes to the yaml file.

To add a library or modify a version of a package in an existing environment, you need to: This procedure is not advisable because you can easily lose track of what libraries and what versions you are working with.

While in a certain environment you can still install new packages that will be part of the environment, but will not be part of the yaml file. Success! You are in your newly created environment. From within your terminal, type: conda env create -f conda activate An eventual pip list for the libraries that normally need to be installed through pip install might be needed here.Ī new environment can be built in any folder as long as you are aware of the path to the yaml file you want to use. For a practical example of what a file like this looks like, have a look at my repo containing the example from this post. Note that if you substitute any of the version fields with an *, the most recent version of that field will be installed. Dependencies, such as the libraries you want available for import and their versions.The yaml file contains information on the environment you want to build such as:

Yaml is a recursive acronym for “YAML Ain’t Markup Language” and it is a format commonly used for configuration files. If you want to be more organized and efficient by separating environments for different projects that might require specific libraries, Anaconda allows you to easily create environments through yaml files.

Creating conda environment