data-documenter 0.3.4

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Data Documenter

A package to generate documentation from pandera schema using mkdocs material.

Installation

pip install data-documenter

Quick start

1. Create schema using pandera

from pandera import DataFrameSchema, Column

schema = DataFrameSchema(
    title="Title of dataset",
    description="Description of dataset",
    columns={
        "COLUMN_NAME": Column(
            dtype="str",
            nullable=False,
            unique=True,
            description="Description of column",
            title="Column Name"
        ),
    },
)

2. Create documentation using schema

from data_documenter.pandera_plugin import create_documentation

docs = create_documentation(
    schema, 
    docs_path = 'docs_folder', 
    title = 'page title',
    filename = 'index.md'
)

3. Run server

docs.run()

4. Stop server

docs.stop()

It is better to use mkdocs command instead of run, stop for better control of processes. See alternative usage.

cd path/to/folder
mkdocs serve

5. Build and deploy documentation
   See mkdocs documentation.

Alternative usage

1. Create pandera schema

from pandera import DataFrameSchema, Column

schema = DataFrameSchema(
    title="Title of dataset",
    description="Description of dataset",
    columns={
        "COLUMN_NAME": Column(
            dtype="str",
            nullable=False,
            unique=True,
            description="Description of column",
            title="Column Name"
        ),
    },
)

2. Create new folder for documentation server.

from data_documenter.metadocs import MetaDocs

docs = MetaDocs(docs_path = 'my_docs')
docs.new()

This will simply run mkdocs new my_docs and replace mkdocs.yml file.

3. Save documentation for schema in a markdown file.

from data_documenter.pandera_plugin import pandera_to_markdown
text_markdown = pandera_to_markdown(schema, title = 'Homepage')
docs.save_markdown(text_markdown, filename = 'index.md')

4. See generated documentation.

cd my_docs
mkdocs serve

5. Build and deploy
   See mkdocs documentation.