Datasets:
Tasks:
Text Generation
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Text
Sub-tasks:
language-modeling
Languages:
English
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100K - 1M
License:
File size: 6,597 Bytes
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from dataclasses import dataclass, field, fields
from functools import lru_cache
from xml.etree import ElementTree
from datetime import datetime
from enum import Enum
import typing
from typing import List, Optional, Union
import os.path
from itertools import groupby
import dataclasses
from tqdm import tqdm
from bs4 import BeautifulSoup
import sys
from pathlib import Path
"""
Author: E.W.Ayers
This code takes a dump of math overflow XML and produces
a structured set of questions with answers.
1. Get mathoverflow.net.7z file
2. Extract this to `DATA_DIR = 'data/mathoverflow.net'`
3. Run `questions()` and run it to get a dictionary of mathoverflow questions.
Each question has an `Answers` field that contains a list of answers for the given q.
"""
def batch_loader(seq, size):
"""
Iterator that takes in a list `seq` and returns
chunks of size `size`
"""
return [seq[pos:pos + size] for pos in range(0, len(seq), size)]
DOC_SEP = "<|endoftext|>"
# source: https://meta.stackexchange.com/questions/2677/database-schema-documentation-for-the-public-data-dump-and-sede
class PostType(Enum):
Question = 1
Answer = 2
OrphanedTagWiki = 3
TagWikiExcerpt = 4
TagWiki = 5
ModeratorNomination = 6
WikiPlaceholder = 7
PrivilegeWiki = 8
def is_optional(field):
return typing.get_origin(field) is Union and type(None) in typing.get_args(field)
def fromXML(cls, element):
out = {}
for field in fields(cls):
field_key = field.name
field_type = field.type
f = field.metadata.get('from_xml')
if f == 'skip':
continue
attr_key = f['key'] if (f is not None and f['key'] is not None) else field_key
v = element.attrib.get(attr_key)
if v is None:
if field.default is not dataclasses.MISSING:
out[field_key] = field.default
elif field.default_factory is not dataclasses.MISSING:
out[field_key] = field.default_factory() # type: ignore
elif is_optional(field_type):
out[field_key] = None
else:
raise Exception(f"Missing field {attr_key}")
continue
if is_optional(field_type):
field_type = typing.get_args(field_type)[0]
if f is not None and f['fn'] is not None:
out[field_key] = f['fn'](v)
elif field_type is int:
out[field_key] = int(v)
elif field_type is str:
out[field_key] = str(v)
elif field_type is datetime:
out[field_key] = datetime.fromisoformat(v)
else:
raise Exception(f"Don't know how to decode {field_type}")
return cls(**out)
def use(fn, key=None):
return field(metadata={'from_xml': {'fn': fn, 'key': key}})
def skip(default):
return field(default=default, metadata={'from_xml': 'skip'})
def iter_rows(path):
for [_, element] in ElementTree.iterparse(path, events = ['start']):
if (element.tag == 'row'):
yield element
DATA_DIR = 'stack_exchange/mathoverflow.net'
@dataclass
class Comment:
Id: int
PostId: int
Score: int
Text: str
CreationDate: datetime
UserId: Optional[int]
@lru_cache()
def comments():
path = os.path.join(DATA_DIR, 'Comments.xml')
out = {}
for element in iter_rows(path):
x : Comment = fromXML(Comment, element)
out[x.Id] = x
print(f"Processed {len(out)} comments.")
return out
@dataclass
class Post:
Id: int
CreationDate: datetime
DeletionDate: Optional[datetime]
Score: int
Body: str # in html; need to parse out?
Title: Optional[str]
OwnerUserId: Optional[int]
ViewCount: Optional[int]
AcceptedAnswerId: Optional[int]
ParentId: Optional[int]
PostType: "PostType" = use(lambda x: PostType(int(x)), 'PostTypeId')
Comments: List[Comment] = skip(None)
Answers: Optional[List["Post"]] = skip(None)
Tags: str = field(default="")
@lru_cache()
def questions():
path = os.path.join(DATA_DIR, 'Posts.xml')
cs = {}
for k, c in groupby(comments().values(), lambda c: c.PostId):
x = list(c)
x.sort(key = lambda x: -x.Score)
cs[k] = x
qs = {}
answers = {}
for element in iter_rows(path):
post = fromXML(Post, element)
post.Comments = cs.get(post.Id, [])
if (post.PostType is PostType.Question):
post.Answers = []
qs[post.Id] = post
elif (post.PostType is PostType.Answer):
answers[post.Id] = post
for qk, aa in groupby(answers.values(), lambda a: a.ParentId):
x = list(aa)
x.sort(key = lambda x: -x.Score)
qs[qk].Answers = x
print(f"Processed {len(qs)} questions with {len(answers)} answers.")
return qs
def strip_html(string):
soup = BeautifulSoup(string, 'html.parser')
return soup.get_text()
def text_of_post(post):
text = ""
if post.Title:
text += "TITLE: " + post.Title
text += f"\nQUESTION [{post.Score} upvotes]: {strip_html(post.Body).strip()}"
commented = False
answered = False
for answer in post.Answers:
if answer.Score >= 2:
answered = True
text += f"\n\nREPLY [{answer.Score} votes]: {strip_html(answer.Body).strip()}"
return text, post.Score, post.Id, answered
def get_and_format(url, save_dir):
Path(save_dir).mkdir(exist_ok=True, parents=True)
archive_path = os.path.join(save_dir, "archive.7z")
os.system(f"wget -O {archive_path} {url}")
global DATA_DIR
DATA_DIR = os.path.join(save_dir, "xml")
os.system(f"7z e {archive_path} -o{DATA_DIR}")
print("parsing xml...")
qs = questions()
print("converting xml to text...")
qs_texts = [text_of_post(qs[key]) for key in tqdm(qs.keys())]
batches = batch_loader(qs_texts, 5000)
for i, batch in tqdm(enumerate(batches)):
shard_path = os.path.join(save_dir, f"shard_{i}.txt")
to_cat = [post for post, score, _, answered in batch
if score >=5 and answered]
shard = f"{DOC_SEP}\n".join(to_cat)
with open(shard_path, "w") as f:
f.write(shard)
os.system(f"rm -r {DATA_DIR}")
os.remove(archive_path)
if __name__ == '__main__':
get_and_format("https://archive.org/download/stackexchange/mathoverflow.net.7z",
"stack-exchange/math_overflow")
get_and_format("https://archive.org/download/stackexchange/math.stackexchange.com.7z",
"stack-exchange/math_stack_exchange")
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