


from argparse import ArgumentParser

from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand


lowerCAmelCase       		=    logging.get_logger(__name__)  # pylint: disable=invalid-name




def     __SCREAMING_SNAKE_CASE							(       lowercase_      )		->     List[Any]:




						'''simple docstring'''







						if not path:
												return "pipe"

						for ext in PipelineDataFormat.SUPPORTED_FORMATS:
												if path.endswith(lowercase_      ):
																		return ext

						raise Exception(
						    f"Unable to determine file format from file extension {path}. "
						    f"Please provide the format through --format {PipelineDataFormat.SUPPORTED_FORMATS}"      )




def     __SCREAMING_SNAKE_CASE							(       lowercase_      )		->     int:




						'''simple docstring'''







						__UpperCAmelCase			:							Any	    =	pipeline(
						    task=args.task      ,       model=args.model if args.model else None      ,       config=args.config      ,       tokenizer=args.tokenizer      ,       device=args.device      ,       )
						__UpperCAmelCase			:							int	    =	try_infer_format_from_ext(args.input      ) if args.format == '''infer''' else args.format
						__UpperCAmelCase			:							Tuple	    =	PipelineDataFormat.from_str(
						    format=lowercase_      ,       output_path=args.output      ,       input_path=args.input      ,       column=args.column if args.column else nlp.default_input_names      ,       overwrite=args.overwrite      ,       )
						return RunCommand(lowercase_      ,       lowercase_      )





class 							lowerCamelCase   (  _UpperCamelCase ):


	def __init__(    self				,     lowercase__				,     lowercase__):
							__UpperCAmelCase			:							Any	    =	nlp
							__UpperCAmelCase			:							Any	    =	reader


	@staticmethod
	def  A(    lowercase__):
							__UpperCAmelCase			:							Optional[Any]	    =	parser.add_parser('''run'''				,     help='''Run a pipeline through the CLI''')
							run_parser.add_argument('''--task'''				,     choices=get_supported_tasks()				,     help='''Task to run''')
							run_parser.add_argument('''--input'''				,     type=lowercase__				,     help='''Path to the file to use for inference''')
							run_parser.add_argument('''--output'''				,     type=lowercase__				,     help='''Path to the file that will be used post to write results.''')
							run_parser.add_argument('''--model'''				,     type=lowercase__				,     help='''Name or path to the model to instantiate.''')
							run_parser.add_argument('''--config'''				,     type=lowercase__				,     help='''Name or path to the model\'s config to instantiate.''')
							run_parser.add_argument(
							    '''--tokenizer'''				,     type=lowercase__				,     help='''Name of the tokenizer to use. (default: same as the model name)''')
							run_parser.add_argument(
							    '''--column'''				,     type=lowercase__				,     help='''Name of the column to use as input. (For multi columns input as QA use column1,columns2)'''				,     )
							run_parser.add_argument(
							    '''--format'''				,     type=lowercase__				,     default='''infer'''				,     choices=PipelineDataFormat.SUPPORTED_FORMATS				,     help='''Input format to read from'''				,     )
							run_parser.add_argument(
							    '''--device'''				,     type=lowercase__				,     default=-1				,     help='''Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)'''				,     )
							run_parser.add_argument('''--overwrite'''				,     action='''store_true'''				,     help='''Allow overwriting the output file.''')
							run_parser.set_defaults(func=lowercase__)


	def  A(    self):
							__UpperCAmelCase    ,      __UpperCAmelCase			:							List[str]	    =	self._nlp, []

							for entry in self._reader:
													__UpperCAmelCase			:							Union[str, Any]	    =	nlp(**lowercase__) if self._reader.is_multi_columns else nlp(lowercase__)
													if isinstance(lowercase__				,     lowercase__):
																			outputs.append(lowercase__)
													else:
																			outputs += output

        # Saving data
							if self._nlp.binary_output:
													__UpperCAmelCase			:							List[str]	    =	self._reader.save_binary(lowercase__)
													logger.warning(F"Current pipeline requires output to be in binary format, saving at {binary_path}")
							else:
													self._reader.save(lowercase__)





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     __SCREAMING_SNAKE_CASE							(       lowercase_      ,       lowercase_ = 1      ,       lowercase_ = "new"      ,       lowercase_ = None      )		->     dict:




						'''simple docstring'''







						__UpperCAmelCase			:							Tuple	    =	wanted_data or []
						if invalid_search_terms := ", ".join(sorted(set(lowercase_      ) - valid_terms      )      ):
												__UpperCAmelCase			:							List[Any]	    =	f"Invalid search term: {invalid_search_terms}"
												raise ValueError(lowercase_      )
						__UpperCAmelCase			:							Optional[int]	    =	requests.get(
						    f"https://reddit.com/r/{subreddit}/{age}.json?limit={limit}"      ,       headers={'''User-agent''': '''A random string'''}      ,       )
						if response.status_code == 429:
												raise requests.HTTPError

						__UpperCAmelCase			:							List[str]	    =	response.json()
						if not wanted_data:
												return {id_: data["data"]["children"][id_] for id_ in range(lowercase_      )}

						__UpperCAmelCase			:							List[Any]	    =	{}
						for id_ in range(lowercase_      ):
												__UpperCAmelCase			:							str	    =	{
												    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"""]))

