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


Release history Release notifications | RSS feed

Download files

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

Source Distribution

tdda-3.3.0.tar.gz (19.4 MB view details)

Uploaded Source

Built Distribution

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

tdda-3.3.0-py3-none-any.whl (20.3 MB view details)

Uploaded Python 3

File details

Details for the file tdda-3.3.0.tar.gz.

File metadata

  • Download URL: tdda-3.3.0.tar.gz
  • Upload date:
  • Size: 19.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for tdda-3.3.0.tar.gz
Algorithm Hash digest
SHA256 a08d2dfb775103e0b3edc13d33e082a1cea6adb956d3da97ff10cc7cdfd340d0
MD5 294983fd1db6dae56360f25d81b6f0f4
BLAKE2b-256 0dae31e91559120cb5eab28006f03a1b377ec1b2f7e35ab4fde7edcc84889bf2

See more details on using hashes here.

File details

Details for the file tdda-3.3.0-py3-none-any.whl.

File metadata

  • Download URL: tdda-3.3.0-py3-none-any.whl
  • Upload date:
  • Size: 20.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for tdda-3.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 112110d9872f5d847513c2c11c0a5ffd3f31b30f6192df93410e9fc40c7a23db
MD5 638f0c610619244520749b36c4835980
BLAKE2b-256 4eb810ace602e39747c90bcc44fab6ecf294254bd4bdb20729b73c0ba9673623

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