Welcome to Good Tables’s documentation!¶
Good Tables is a python library and command line tool for validating and transforming tabular data.
Tabular data in the form of CSV or Excel is passed through a pipeline of validators. These validators can check structure, for example are their blank rows or columns, do rows have the same length as the header etc, and they can also validate against a schema, for example does the data have the expected columns, is the data of the right type (are dates actually dates).
Optionally, the data source is transformed as it passes through the pipeline.
In return, the client receives a report on processing performed and, optionally, the output data.
You can contribute to the project with content, code, and ideas!
Start at one of the following channels:
Documentation: An overview of the features that are currently in place.
Issues: See current issues, the backlog, and/or file a new issue.
Code: Get the code here.
Table of contents¶
High-level design goals for Good Tables:
- Process tabular data in CSV, Excel and JSON formats
- Provide a suite of small tools that each implement a type of processing to run
- Provide a pipeline API for registering built-in and custom processors
- Components should be easily usable in 3rd party (Python) code