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Avro Python API References

Avro is a Data Serialization framework that converts any data format into machine and binary format. Avro supports Python3. These documentation will guide you through the Python's Avro APIs, classes, and methods. The documentation are generated using Sphinx and pages are built using the Myst in Sphinx.

Consideration before running the Docs.

  • Clone the repo https://github.com/codewithdev/Apache-Avro-Docs.git.
  • Open the Apache-Avro-Docs directory with an IDE (Recommended Pycharm).
  • Open the terminal and type pip install -r requirement.txt to install required packages.
  • You will see conf.py a configuration file which you can use to modify the template, extensions, and other configuration of Sphinx.
  • To play with the documentation, in the terminal, type make html to create HTML version of pages. The HTML version of the pages are always generated and stored within the build > html folder.

Installing Sphinx docs using Python Virtual Environment

Create a virtual environment using python3 -m venv venv. If you are using PyCharm IDE, by default it creates a new virtual environment. You can choose to select the virtual environment where you want to install the librarires.

Running Docs locally

Sphinx is a Open Source Python documentation generator. The Avro documentation pages are generated using the markdown (Myst) library in Sphinx. Once the .md pages are converted into HTML, you can see it live on your local server by typing; sphinx-autobuild source build/html. You will see the localserver has started running on http://localhost:8000/ or http://127.0.0.1:8000/.

Sphinx Documentation Theme

The documentation is crafted on Furo theme. However, after installing the packages from requirement.txt and running the docs locally, if you are still seeing the default theme albaster, you can refer to the Furo docs.

Accessing the Example Code

Avro sample file uses DataFileReader and DataFileWriter in the example.py file to read/write data to Avro files. For more information, access the file from the example.py. If you run the code, it generates the output in the example.avro Avro file.