spaCy/spacy/lang/ca/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

63 lines
1012 B
Python

# coding: utf8
from __future__ import unicode_literals
from ...attrs import LIKE_NUM
_num_words = [
"zero",
"un",
"dos",
"tres",
"quatre",
"cinc",
"sis",
"set",
"vuit",
"nou",
"deu",
"onze",
"dotze",
"tretze",
"catorze",
"quinze",
"setze",
"disset",
"divuit",
"dinou",
"vint",
"trenta",
"quaranta",
"cinquanta",
"seixanta",
"setanta",
"vuitanta",
"noranta",
"cent",
"mil",
"milió",
"bilió",
"trilió",
"quatrilió",
"gazilió",
"bazilió",
]
def like_num(text):
if text.startswith(("+", "-", "±", "~")):
text = text[1:]
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 in _num_words:
return True
return False
LEX_ATTRS = {LIKE_NUM: like_num}