spaCy/spacy/lang/si/lex_attrs.py
Ines Montani eddeb36c96
💫 Tidy up and auto-format .py files (#2983)
<!--- Provide a general summary of your changes in the title. -->

## Description
- [x] Use [`black`](https://github.com/ambv/black) to auto-format all `.py` files.
- [x] Update flake8 config to exclude very large files (lemmatization tables etc.)
- [x] Update code to be compatible with flake8 rules
- [x] Fix various small bugs, inconsistencies and messy stuff in the language data
- [x] Update docs to explain new code style (`black`, `flake8`, when to use `# fmt: off` and `# fmt: on` and what `# noqa` means)

Once #2932 is merged, which auto-formats and tidies up the CLI, we'll be able to run `flake8 spacy` actually get meaningful results.

At the moment, the code style and linting isn't applied automatically, but I'm hoping that the new [GitHub Actions](https://github.com/features/actions) will let us auto-format pull requests and post comments with relevant linting information.

### Types of change
enhancement, code style

## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
2018-11-30 17:03:03 +01:00

65 lines
1.3 KiB
Python

# coding: utf8
from __future__ import unicode_literals
from ...attrs import LIKE_NUM
_num_words = [
"බින්දුව",
"බිංදුව",
"එක",
"දෙක",
"තුන",
"හතර",
"පහ",
"හය",
"හත",
"අට",
"නවය",
"නමය",
"දහය",
"එකොළහ",
"දොළහ",
"දහතුන",
"දහහතර",
"දාහතර",
"පහළව",
"පහළොව",
"දහසය",
"දහහත",
"දාහත",
"දහඅට",
"දහනවය",
"විස්ස",
"තිහ",
"හතළිහ",
"පනහ",
"හැට",
"හැත්තෑව",
"අසූව",
"අනූව",
"සියය",
"දහස",
"දාහ",
"ලක්ෂය",
"මිලියනය",
"කෝටිය",
"බිලියනය",
"ට්‍රිලියනය",
]
def like_num(text):
text = text.replace(",", "").replace(".", "")
if text.isdigit():
return True
if text.count("/") == 1:
num, denom = text.split("/")
if num.isdigit() and denom.isdigit():
return True
if text.lower() in _num_words:
return True
return False
LEX_ATTRS = {LIKE_NUM: like_num}