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-3.0.3.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-3.0.3-py3-none-any.whl (20.8 MB view details)

Uploaded Python 3

File details

Details for the file tdda-3.0.3.tar.gz.

File metadata

  • Download URL: tdda-3.0.3.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-3.0.3.tar.gz
Algorithm Hash digest
SHA256 5ca12350beba7b0ac1f0e345f6ddae0db403234b3a0b3c98b6d9704159879a39
MD5 32fa43cdca0d5bc49f7808dd0b84b004
BLAKE2b-256 398c3ac796858f15149bb7d5ee6375fdd59db34fafbced4881f1e713431ffbe5

See more details on using hashes here.

File details

Details for the file tdda-3.0.3-py3-none-any.whl.

File metadata

  • Download URL: tdda-3.0.3-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-3.0.3-py3-none-any.whl
Algorithm Hash digest
SHA256 4f9c8be4039f4c96b96a5a22bac4d0329c3a84664f741d84fa5b05c63b67a52b
MD5 c4058d8e6bc05e7550eaf01db6f2779f
BLAKE2b-256 870593b37f52457bb9a811f5e0bc9c22af9f7599990210bb6f43fb3c0d9c2db7

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