mirror of https://github.com/zulip/zulip.git
100 lines
2.5 KiB
Python
100 lines
2.5 KiB
Python
import re
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from collections import defaultdict
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from typing import Dict, List
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from .template_parser import FormattedError, Token, tokenize
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class TagInfo:
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def __init__(self, tag: str, classes: List[str], ids: List[str], token: Token) -> None:
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self.tag = tag
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self.classes = classes
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self.ids = ids
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self.token = token
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self.words = [
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self.tag,
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*("." + s for s in classes),
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*("#" + s for s in ids),
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]
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def text(self) -> str:
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s = self.tag
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if self.classes:
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s += "." + ".".join(self.classes)
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if self.ids:
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s += "#" + "#".join(self.ids)
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return s
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def get_tag_info(token: Token) -> TagInfo:
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s = token.s
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tag = token.tag
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classes: List[str] = []
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ids: List[str] = []
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searches = [
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(classes, ' class="(.*?)"'),
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(classes, " class='(.*?)'"),
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(ids, ' id="(.*?)"'),
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(ids, " id='(.*?)'"),
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]
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for lst, regex in searches:
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m = re.search(regex, s)
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if m:
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for g in m.groups():
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lst += split_for_id_and_class(g)
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return TagInfo(tag=tag, classes=classes, ids=ids, token=token)
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def split_for_id_and_class(element: str) -> List[str]:
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# Here we split a given string which is expected to contain id or class
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# attributes from HTML tags. This also takes care of template variables
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# in string during splitting process. For eg. 'red black {{ a|b|c }}'
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# is split as ['red', 'black', '{{ a|b|c }}']
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outside_braces: bool = True
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lst = []
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s = ""
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for ch in element:
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if ch == "{":
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outside_braces = False
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if ch == "}":
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outside_braces = True
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if ch == " " and outside_braces:
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if not s == "":
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lst.append(s)
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s = ""
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else:
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s += ch
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if not s == "":
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lst.append(s)
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return lst
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def build_id_dict(templates: List[str]) -> (Dict[str, List[str]]):
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template_id_dict: (Dict[str, List[str]]) = defaultdict(list)
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for fn in templates:
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with open(fn) as f:
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text = f.read()
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try:
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list_tags = tokenize(text)
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except FormattedError as e:
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raise Exception(
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f"""
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fn: {fn}
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{e}"""
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)
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for tag in list_tags:
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info = get_tag_info(tag)
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for ids in info.ids:
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template_id_dict[ids].append("Line " + str(info.token.line) + ":" + fn)
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return template_id_dict
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