





'''simple docstring'''






from __future__ import annotations

import requests

lowerCAmelCase       		=      set(
    """approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc downs
edited gilded gildings hidden hide_score is_created_from_ads_ui is_meta
is_original_content is_reddit_media_domain is_video link_flair_css_class
link_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title
name permalink pwls quarantine saved score secure_media secure_media_embed selftext
subreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type
total_awards_received ups upvote_ratio url user_reports""".split()
)






def      __A						(							a_						:  str      ,a_						:  int = 1      ,a_						:  str = "new"      ,a_						:  list | None = None	):
  lowerCAmelCase     :    Optional[Any]						=   wanted_data or []
  if invalid_search_terms := ", ".join(sorted(set(a_	) - valid_terms	)	):
    lowerCAmelCase     :    Optional[int]						=   f'''Invalid search term: {invalid_search_terms}'''
    raise ValueError(a_	)
  lowerCAmelCase     :    Optional[Any]						=   requests.get(
      f'''https://reddit.com/r/{subreddit}/{age}.json?limit={limit}'''      ,headers={"User-agent": "A random string"}      ,)
  if response.status_code == 4_2_9:
    raise requests.HTTPError

  lowerCAmelCase     :    List[Any]						=   response.json()
  if not wanted_data:
    return {id_: data["data"]["children"][id_] for id_ in range(a_	)}

  lowerCAmelCase     :    List[str]						=   {}
  for id_ in range(a_	):
    lowerCAmelCase     :    Dict						=   {
        item: data["data"]["children"][id_]["data"][item] for item in wanted_data
    }
  return data_dict


if __name__ == "__main__":
     # If you get Error 429, that means you are rate limited.Try after some time
     print(get_subreddit_data("""learnpython""", wanted_data=["""title""", """url""", """selftext"""]))










'''simple docstring'''






import math_equivalence  # From: git+https://github.com/hendrycks/math.git

import datasets


lowerCAmelCase       		=      """\
@article{hendrycksmath2021,
  title={Measuring Mathematical Problem Solving With the MATH Dataset},
  author={Dan Hendrycks
    and Collin Burns
    and Saurav Kadavath
    and Akul Arora
    and Steven Basart
    and Eric Tang
    and Dawn Song
    and Jacob Steinhardt},
  journal={arXiv preprint arXiv:2103.03874},
  year={2021}
}
"""


lowerCAmelCase       		=      """\
This metric is used to assess performance on the Mathematics Aptitude Test of Heuristics (MATH) dataset.
It first canonicalizes the inputs (e.g., converting \"1/2\" to \"\\frac{1}{2}\") and then computes accuracy.
"""


lowerCAmelCase       		=      R"""
Calculates accuracy after canonicalizing inputs.

Args:
    predictions: list of predictions to score. Each prediction
        is a string that contains natural language and LaTex.
    references: list of reference for each prediction. Each
        reference is a string that contains natural language
        and LaTex.
Returns:
    accuracy: accuracy after canonicalizing inputs
        (e.g., converting \"1/2\" to \"\\frac{1}{2}\")

Examples:
    >>> metric = datasets.load_metric(\"competition_math\")
    >>> results = metric.compute(references=[\"\\frac{1}{2}\"], predictions=[\"1/2\"])
    >>> print(results)
    {'accuracy': 1.0}
"""
@datasets.utils.file_utils.add_end_docstrings(_DESCRIPTION      ,   _KWARGS_DESCRIPTION       )
class 		lowerCamelCase  (      datasets.Metric       ):



	def   _lowerCamelCase    (   self	):
			return datasets.MetricInfo(
			    description=_DESCRIPTION		,      citation=_CITATION		,      inputs_description=_KWARGS_DESCRIPTION		,      features=datasets.Features(
			        {
			            "predictions": datasets.Value("string"	),
			            "references": datasets.Value("string"	),
			        }	)		,      homepage="https://github.com/hendrycks/math"		,      codebase_urls=["https://github.com/hendrycks/math"]		,      )





	def   _lowerCamelCase    (   self		,      a_		,      a_	):
			lowerCAmelCase     :    Any						=   0.0
			for i, j in zip(a_		,      a_	):
					n_correct += 1.0 if math_equivalence.is_equiv(a_		,      a_	) else 0.0
			lowerCAmelCase     :    List[str]						=   n_correct / len(a_	)
			return {
			    "accuracy": accuracy,
			}



