Skip to main content

Test-driven data analysis: command-line tools and Python APIs for data validation, testing analytical pipelines, automatic test generation and more.

Project description

Test-Driven Data Analysis (TDDA)

The tdda package provides Python support for test-driven data analysis (1-page summary, blog, book).

Features

  • Reference Testing (tdda.referencetest): extensions to unittest and pytest for testing data analysis pipelines. Supports file-based comparisons, semantic equivalence, automatic rewriting of reference results, and test tagging.

  • Automatic Test Generation (tdda gentest): generates reference tests for any command-line script or program (Python, R, shell, Makefile, ...). *"Gentest writes tests, so you don't have to."*™

  • Constraints (tdda.constraints): discovers constraints from Pandas DataFrames, Parquet files, flat files, and relational databases; verifies new data against those constraints; detects failing records.

  • Regular Expression Inference (tdda.rexpy): automatically infers regular expressions from a column of string data.

  • Data Diff (tdda diff): compares data frames in Parquet or flat files and reports differences in a visual format.

  • Serial Format (tdda.serial): documents CSV and flat-file formats in .serial metadata files for accurate, portable reading and writing. Supports conversion to/from CSVW and Frictionless metadata.

  • Utility Functions (tdda.utils): Unicode normalization (Normal Form TK), glyph counting, and RFC 9839 support.

Documentation

Full documentation: tdda.readthedocs.io

Installation

pip install tdda

To upgrade an existing installation:

pip install -U tdda

Source installation

git clone https://github.com/tdda/tdda.git
cd tdda
pip install .

Optional database support

pip install pygresql                  # PostgreSQL
pip install mysql-connector-python   # MySQL/MariaDB
pip install pymongo                  # MongoDB

Testing

tdda test

Resources

Authors

  • Nick Radcliffe
  • Simon Brown

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tdda-3.0.4.tar.gz (20.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tdda-3.0.4-py3-none-any.whl (20.8 MB view details)

Uploaded Python 3

File details

Details for the file tdda-3.0.4.tar.gz.

File metadata

  • Download URL: tdda-3.0.4.tar.gz
  • Upload date:
  • Size: 20.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for tdda-3.0.4.tar.gz
Algorithm Hash digest
SHA256 7671f3657c40d4472f55d2afc4b164aab8637e29304be18fbecb32cb866026c7
MD5 48d5fccb4a648371107efa36fc2e93de
BLAKE2b-256 497fb2fcfbe8604b86192dcf2861183ff8071932a342f2630c923532500256ab

See more details on using hashes here.

File details

Details for the file tdda-3.0.4-py3-none-any.whl.

File metadata

  • Download URL: tdda-3.0.4-py3-none-any.whl
  • Upload date:
  • Size: 20.8 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for tdda-3.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 a8e0b4b382f4f588532f3e3603d03212a10b202eeb5eb2734b836b4a5fa14391
MD5 e36e347787f464eea14c879b3f357f1f
BLAKE2b-256 1dd168bb935f8c6b7a1f09a04062f85b54e747ea8283bb9db5737c9d18f782f8

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page