Skip to main content

Calculate XLSX formulas

Project description

Calculate XLSX formulas

CI Coverage Status PyPI version License: MIT

xlsx_evaluate - python library to convert excel functions in python code without the need for Excel itself within the scope of supported features.

This library is fork xlcalculator. Use this library.

Summary

Installation

# pip
pip install xlsx-evaluate
# poetry
poetry add xlsx-evaluate

Example

input_dict = {
    'B4': 0.95,
    'B2': 1000,
    "B19": 0.001,
    'B20': 4,
    'B22': 1,
    'B23': 2,
    'B24': 3,
    'B25': '=B2*B4',
    'B26': 5,
    'B27': 6,
    'B28': '=B19 * B20 * B22',
    'C22': '=SUM(B22:B28)',
    "D1": "abc",
    "D2": "bca",
    "D3": "=CONCATENATE(D1, D2)",
  }

from xlsx_evaluate import ModelCompiler
from xlsx_evaluate import Evaluator

compiler = ModelCompiler()
my_model = compiler.read_and_parse_dict(input_dict)
evaluator = Evaluator(my_model)

for formula in my_model.formulae:
    print(f'Formula {formula} evaluates to {evaluator.evaluate(formula)}')

# cells need a sheet and Sheet1 is default.
evaluator.set_cell_value('Sheet1!B22', 100)
print('Formula B28 now evaluates to', evaluator.evaluate('Sheet1!B28'))
print('Formula C22 now evaluates to', evaluator.evaluate('Sheet1!C22'))
print('Formula D3 now evaluates to', evaluator.evaluate("Sheet1!D3"))

TODO

  • Do not treat ranges as a granular AST node it instead as an operation ":" of two cell references to create the range. That will make implementing features like A1:OFFSET(...) easy to implement.

  • Support for alternative range evaluation: by ref (pointer), by expr (lazy eval) and current eval mode.

    • Pointers would allow easy implementations of functions like OFFSET().

    • Lazy evals will allow efficient implementation of IF() since execution of true and false expressions can be delayed until it is decided which expression is needed.

  • Implement array functions. It is really not that hard once a proper RangeData class has been implemented on which one can easily act with scalar functions.

  • Improve testing

  • Refactor model and evaluator to use pass-by-object-reference for values of cells which then get "used"/referenced by ranges, defined names and formulas

  • Handle multi-file addresses

  • Improve integration with pyopenxl for reading and writing files example of problem space

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

xlsx_evaluate-0.5.0.tar.gz (41.0 kB view details)

Uploaded Source

Built Distribution

xlsx_evaluate-0.5.0-py3-none-any.whl (48.2 kB view details)

Uploaded Python 3

File details

Details for the file xlsx_evaluate-0.5.0.tar.gz.

File metadata

  • Download URL: xlsx_evaluate-0.5.0.tar.gz
  • Upload date:
  • Size: 41.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.9.6 readme-renderer/37.3 requests/2.28.2 requests-toolbelt/0.10.1 urllib3/1.26.15 tqdm/4.65.0 importlib-metadata/6.3.0 keyring/23.13.1 rfc3986/2.0.0 colorama/0.4.6 CPython/3.10.11

File hashes

Hashes for xlsx_evaluate-0.5.0.tar.gz
Algorithm Hash digest
SHA256 29a7cbd6e5bea0014678d7ec2e29581715fdb6ef7ecb9e27a4b8523da7abfdf1
MD5 b446cb58630554b078c45a9d796be3c7
BLAKE2b-256 7cb0194fe96f3b962c335ef183548cd00e68c4827fc87bf93d67432aec389d4e

See more details on using hashes here.

File details

Details for the file xlsx_evaluate-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: xlsx_evaluate-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 48.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.9.6 readme-renderer/37.3 requests/2.28.2 requests-toolbelt/0.10.1 urllib3/1.26.15 tqdm/4.65.0 importlib-metadata/6.3.0 keyring/23.13.1 rfc3986/2.0.0 colorama/0.4.6 CPython/3.10.11

File hashes

Hashes for xlsx_evaluate-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 a327f7ac653f2436e2eb4119aaf9fe8dc75a3820ffa458d67314715a0acb0b83
MD5 28fbf2381409d4e4321232ece758da05
BLAKE2b-256 fea0b6f384a5e0cc3f43f0439c7bc46535d9a11c0ba09b6a051f4e4b6d40f3ad

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