Skip to main content

Tools for creating and reusing high-quality spreadsheets

Project description

PyPI package Documentation Test results Test coverage Code analysis License Analytics

ObjTables: Tools for creating and reusing high-quality spreadsheets

ObjTables is a toolkit which makes it easy to use spreadsheets (e.g., XLSX workbooks) to work with complex datasets by combining spreadsheets with rigorous schemas and an object-relational mapping system (ORM; similar to Active Record (Ruby), Django (Python), Doctrine (PHP), Hibernate (Java), Propel (PHP), SQLAlchemy (Python), etc.). This combination enables users to use programs such as Microsoft Excel, LibreOffice Calc, and OpenOffice Calc to view and edit spreadsheets and use schemas and the ObjTables software to validate the syntax and semantics of datasets, compare and merge datasets, and parse datasets into object-oriented data structures for further querying and analysis with languages such as Python.

ObjTables makes it easy to:

  • Use collections of tables (e.g., an XLSX workbook) to represent complex data consisting of multiple related objects of multiple types (e.g., rows of worksheets), each with multiple attributes (e.g., columns).

  • Use complex data types (e.g., numbers, strings, numerical arrays, symbolic mathematical expressions, chemical structures, biological sequences, etc.) within tables.

  • Use progams such as Excel and LibreOffice as a graphical interface for viewing and editing complex datasets.

  • Use embedded tables and grammars to encode relational information into columns and groups of columns of tables.

  • Define clear schemas for tabular datasets.

  • Use schemas to rigorously validate tabular datasets.

  • Use schemas to parse tabular datasets into data structures for further analysis in languages such as Python.

  • Compare, merge, split, revision, and migrate tabular datasets.

The ObjTables toolkit includes five components:

  • Format for schemas for tabular datasets

  • Numerous data types

  • Format for tabular datasets

  • Software tools for parsing, validating, and manipulating tabular datasets

  • Python package for more flexibility and analysis

Please see https://objtables.org for more information.

Installing the command-line program and Python API

Please see the documentation.

Examples, tutorials, and documentation

Please see the user documentation, developer documentation, and tutorials.

License

ObjTables is released under the MIT license.

Development team

ObjTables was developed by the Karr Lab at the Icahn School of Medicine at Mount Sinai in New York, USA and the Applied Mathematics and Computer Science, from Genomes to the Environment research unit at the National Research Institute for Agriculture, Food and Environment in Jouy en Josas, FR.

Questions and comments

Please contact the developers with any questions or comments.

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

obj_tables-1.0.14.tar.gz (167.3 kB view details)

Uploaded Source

Built Distribution

obj_tables-1.0.14-py2.py3-none-any.whl (179.0 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file obj_tables-1.0.14.tar.gz.

File metadata

  • Download URL: obj_tables-1.0.14.tar.gz
  • Upload date:
  • Size: 167.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.5

File hashes

Hashes for obj_tables-1.0.14.tar.gz
Algorithm Hash digest
SHA256 0c3d384b08047bf7b9ac34cd0508064adcba8353927d1e516dbc0a8a51484e7e
MD5 eed6f0c75f7109386d15ce31a32103be
BLAKE2b-256 b2e58862547c8276347eaf43fbf47d64d79a2b1a01e9db384f8cf7f64e3a7fd9

See more details on using hashes here.

File details

Details for the file obj_tables-1.0.14-py2.py3-none-any.whl.

File metadata

  • Download URL: obj_tables-1.0.14-py2.py3-none-any.whl
  • Upload date:
  • Size: 179.0 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/47.3.1 requests-toolbelt/0.9.1 tqdm/4.40.2 CPython/3.7.5

File hashes

Hashes for obj_tables-1.0.14-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 d2f147608e72770f96c264a93b6e558b35e746dadcc09ecfb54f80d8eb94bbcb
MD5 ceb24b9f56697a7988f523064dd88042
BLAKE2b-256 bc237c7f2a899ccc5082345241dc0721a26b249f2cf7a23d2d48f40947c4211d

See more details on using hashes here.

Supported by

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