mirror of
https://github.com/Watchful1/PushshiftDumps.git
synced 2025-07-03 19:06:39 -04:00
325 lines
13 KiB
Python
325 lines
13 KiB
Python
import zstandard
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import os
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import json
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import sys
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import time
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import argparse
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import re
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from collections import defaultdict
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from datetime import datetime
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import logging.handlers
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import multiprocessing
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# sets up logging to the console as well as a file
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log = logging.getLogger("bot")
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log.setLevel(logging.INFO)
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log_formatter = logging.Formatter('%(asctime)s - %(levelname)s: %(message)s')
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log_stderr_handler = logging.StreamHandler()
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log_stderr_handler.setFormatter(log_formatter)
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log.addHandler(log_stderr_handler)
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if not os.path.exists("logs"):
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os.makedirs("logs")
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log_file_handler = logging.handlers.RotatingFileHandler(
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os.path.join("logs", "bot.log"), maxBytes=1024*1024*16, backupCount=5)
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log_file_handler.setFormatter(log_formatter)
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log.addHandler(log_file_handler)
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# convenience object used to pass status information between processes
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class FileConfig:
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def __init__(self, input_path, output_path=None, complete=False, lines_processed=0, error_lines=0):
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self.input_path = input_path
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self.output_path = output_path
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self.file_size = os.stat(input_path).st_size
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self.complete = complete
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self.bytes_processed = self.file_size if complete else 0
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self.lines_processed = lines_processed if complete else 0
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self.error_message = None
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self.error_lines = error_lines
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def __str__(self):
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return f"{self.input_path} : {self.output_path} : {self.file_size} : {self.complete} : {self.bytes_processed} : {self.lines_processed}"
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# used for calculating running average of read speed
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class Queue:
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def __init__(self, max_size):
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self.list = []
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self.max_size = max_size
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def put(self, item):
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if len(self.list) >= self.max_size:
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self.list.pop(0)
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self.list.append(item)
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def peek(self):
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return self.list[0] if len(self.list) > 0 else None
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# save file information and progress to a json file
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# we don't want to save the whole FileConfig object, since some info resets if we restart
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def save_file_list(input_files, working_folder, status_json, script_type):
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if not os.path.exists(working_folder):
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os.makedirs(working_folder)
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simple_file_list = []
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for file in input_files:
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simple_file_list.append([file.input_path, file.output_path, file.complete, file.lines_processed, file.error_lines])
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with open(status_json, 'w') as status_json_file:
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output_dict = {
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"files": simple_file_list,
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"type": script_type,
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}
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status_json_file.write(json.dumps(output_dict, indent=4))
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# load file information from the json file and recalculate file sizes
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def load_file_list(status_json):
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if os.path.exists(status_json):
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with open(status_json, 'r') as status_json_file:
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output_dict = json.load(status_json_file)
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input_files = []
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for simple_file in output_dict["files"]:
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input_files.append(
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FileConfig(simple_file[0], simple_file[1], simple_file[2], simple_file[3], simple_file[4])
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)
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return input_files, output_dict["type"]
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else:
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return None, None
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# recursively decompress and decode a chunk of bytes. If there's a decode error then read another chunk and try with that, up to a limit of max_window_size bytes
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def read_and_decode(reader, chunk_size, max_window_size, previous_chunk=None, bytes_read=0):
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chunk = reader.read(chunk_size)
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bytes_read += chunk_size
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if previous_chunk is not None:
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chunk = previous_chunk + chunk
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try:
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return chunk.decode()
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except UnicodeDecodeError:
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if bytes_read > max_window_size:
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raise UnicodeError(f"Unable to decode frame after reading {bytes_read:,} bytes")
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return read_and_decode(reader, chunk_size, max_window_size, chunk, bytes_read)
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# open a zst compressed ndjson file and yield lines one at a time
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# also passes back file progress
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def read_lines_zst(file_name):
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with open(file_name, 'rb') as file_handle:
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buffer = ''
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reader = zstandard.ZstdDecompressor(max_window_size=2**31).stream_reader(file_handle)
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while True:
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chunk = read_and_decode(reader, 2**27, (2**29) * 2)
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if not chunk:
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break
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lines = (buffer + chunk).split("\n")
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for line in lines[:-1]:
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yield line, file_handle.tell()
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buffer = lines[-1]
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reader.close()
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# base of each separate process. Loads a file, iterates through lines and writes out
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# the ones where the `field` of the object matches `value`. Also passes status
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# information back to the parent via a queue
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def process_file(file, queue, field):
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output_file = None
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try:
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for line, file_bytes_processed in read_lines_zst(file.input_path):
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try:
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obj = json.loads(line)
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observed = obj[field].lower()
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if output_file is None:
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output_file = open(file.output_path, 'w', encoding="utf-8")
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output_file.write(observed)
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output_file.write("\n")
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except (KeyError, json.JSONDecodeError) as err:
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file.error_lines += 1
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file.lines_processed += 1
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if file.lines_processed % 1000000 == 0:
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file.bytes_processed = file_bytes_processed
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queue.put(file)
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if output_file is not None:
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output_file.close()
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file.complete = True
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file.bytes_processed = file.file_size
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except Exception as err:
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file.error_message = str(err)
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queue.put(file)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description="Use multiple processes to decompress and iterate over pushshift dump files")
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parser.add_argument("input", help="The input folder to recursively read files from")
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parser.add_argument("--output", help="Name of the output file", default="field_counts")
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parser.add_argument("--working", help="The folder to store temporary files in", default="pushshift_working")
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parser.add_argument("--field", help="Which field to count", default="subreddit")
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parser.add_argument("--min_count", help="Dont write any counts below this number", default=1000)
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parser.add_argument("--processes", help="Number of processes to use", default=10, type=int)
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parser.add_argument("--file_filter", help="Regex filenames have to match to be processed", default="^rc_|rs_")
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parser.add_argument(
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"--error_rate", help=
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"Percentage as an integer from 0 to 100 of the lines where the field can be missing. For the subreddit field especially, "
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"there are a number of posts that simply don't have a subreddit attached", default=1, type=int)
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parser.add_argument("--debug", help="Enable debug logging", action='store_const', const=True, default=False)
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script_type = "count"
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args = parser.parse_args()
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if args.debug:
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log.setLevel(logging.DEBUG)
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log.info(f"Loading files from: {args.input}")
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if args.output:
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log.info(f"Writing output to: {args.output}")
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else:
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log.info(f"Writing output to working folder")
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multiprocessing.set_start_method('spawn')
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queue = multiprocessing.Manager().Queue()
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status_json = os.path.join(args.working, "status.json")
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input_files, saved_type = load_file_list(status_json)
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if saved_type and saved_type != script_type:
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log.warning(f"Script type doesn't match type from json file. Delete working folder")
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sys.exit(0)
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# if the file list wasn't loaded from the json, this is the first run, find what files we need to process
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if input_files is None:
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input_files = []
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for subdir, dirs, files in os.walk(args.input):
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files.sort()
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for file_name in files:
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if file_name.endswith(".zst") and re.search(args.file_filter, file_name, re.IGNORECASE) is not None:
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input_path = os.path.join(subdir, file_name)
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output_path = os.path.join(args.working, file_name[:-4])
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input_files.append(FileConfig(input_path, output_path=output_path))
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save_file_list(input_files, args.working, status_json, script_type)
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else:
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log.info(f"Existing input file was read, if this is not correct you should delete the {args.working} folder and run this script again")
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files_processed = 0
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total_bytes = 0
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total_bytes_processed = 0
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total_lines_processed = 0
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total_lines_errored = 0
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files_to_process = []
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# calculate the total file size for progress reports, build a list of incomplete files to process
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# do this largest to smallest by file size so that we aren't processing a few really big files with only a few threads at the end
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for file in sorted(input_files, key=lambda item: item.file_size, reverse=True):
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total_bytes += file.file_size
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if file.complete:
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files_processed += 1
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total_lines_processed += file.lines_processed
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total_bytes_processed += file.file_size
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total_lines_errored += file.error_lines
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else:
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files_to_process.append(file)
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log.info(f"Processed {files_processed} of {len(input_files)} files with {(total_bytes_processed / (2**30)):.2f} of {(total_bytes / (2**30)):.2f} gigabytes")
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start_time = time.time()
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if len(files_to_process):
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progress_queue = Queue(40)
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progress_queue.put([start_time, total_lines_processed, total_bytes_processed])
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speed_queue = Queue(40)
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for file in files_to_process:
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log.info(f"Processing file: {file.input_path}")
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# start the workers
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with multiprocessing.Pool(processes=min(args.processes, len(files_to_process))) as pool:
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workers = pool.starmap_async(process_file, [(file, queue, args.field) for file in files_to_process], error_callback=log.info)
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while not workers.ready():
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# loop until the workers are all done, pulling in status messages as they are sent
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file_update = queue.get()
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if file_update.error_message is not None:
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log.warning(f"File failed {file_update.input_path}: {file_update.error_message}")
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# I'm going to assume that the list of files is short enough that it's no
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# big deal to just iterate each time since that saves a bunch of work
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total_lines_processed = 0
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total_bytes_processed = 0
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total_lines_errored = 0
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files_processed = 0
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files_errored = 0
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i = 0
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for file in input_files:
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if file.input_path == file_update.input_path:
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input_files[i] = file_update
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file = file_update
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total_lines_processed += file.lines_processed
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total_bytes_processed += file.bytes_processed
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total_lines_errored += file.error_lines
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files_processed += 1 if file.complete or file.error_message is not None else 0
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files_errored += 1 if file.error_message is not None else 0
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i += 1
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if file_update.complete or file_update.error_message is not None:
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save_file_list(input_files, args.working, status_json, script_type)
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current_time = time.time()
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progress_queue.put([current_time, total_lines_processed, total_bytes_processed])
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first_time, first_lines, first_bytes = progress_queue.peek()
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bytes_per_second = int((total_bytes_processed - first_bytes)/(current_time - first_time))
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speed_queue.put(bytes_per_second)
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seconds_left = int((total_bytes - total_bytes_processed) / int(sum(speed_queue.list) / len(speed_queue.list)))
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minutes_left = int(seconds_left / 60)
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hours_left = int(minutes_left / 60)
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days_left = int(hours_left / 24)
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log.info(
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f"{total_lines_processed:,} lines at {(total_lines_processed - first_lines)/(current_time - first_time):,.0f}/s, {total_lines_errored:,} errored : "
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f"{(total_bytes_processed / (2**30)):.2f} gb at {(bytes_per_second / (2**20)):,.0f} mb/s, {(total_bytes_processed / total_bytes) * 100:.0f}% : "
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f"{files_processed}({files_errored})/{len(input_files)} files : "
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f"{(str(days_left) + 'd ' if days_left > 0 else '')}{hours_left - (days_left * 24)}:{minutes_left - (hours_left * 60):02}:{seconds_left - (minutes_left * 60):02} remaining")
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log.info(f"{total_lines_processed:,}, {total_lines_errored} errored : {(total_bytes_processed / (2**30)):.2f} gb, {(total_bytes_processed / total_bytes) * 100:.0f}% : {files_processed}/{len(input_files)}")
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working_file_paths = []
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count_incomplete = 0
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# build a list of output files to combine
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for file in sorted(input_files, key=lambda item: os.path.split(item.output_path)[1]):
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if not file.complete:
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if file.error_message is not None:
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log.info(f"File {file.input_path} errored {file.error_message}")
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else:
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log.info(f"File {file.input_path} is not marked as complete")
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count_incomplete += 1
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else:
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if file.error_lines > file.lines_processed * (args.error_rate * 0.01):
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log.info(
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f"File {file.input_path} has {file.error_lines:,} errored lines out of {file.lines_processed:,}, "
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f"{(file.error_lines / file.lines_processed) * (args.error_rate * 0.01):.2f}% which is above the limit of {args.error_rate}%")
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count_incomplete += 1
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elif file.output_path is not None:
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if os.path.exists(file.output_path):
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working_file_paths.append(file.output_path)
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if count_incomplete > 0:
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log.info(f"{count_incomplete} files were not completed, errored or don't exist, something went wrong. Aborting")
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sys.exit()
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log.info(f"Processing complete, combining {len(working_file_paths)} result files")
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input_lines = 0
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files_combined = 0
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field_counts = defaultdict(int)
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for working_file_path in working_file_paths:
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files_combined += 1
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log.info(f"Reading {files_combined}/{len(working_file_paths)} : {input_lines:,} : {len(field_counts):,} : {os.path.split(working_file_path)[1]}")
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with open(working_file_path, 'r') as input_file:
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for line in input_file:
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input_lines += 1
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field_counts[line.strip()] += 1
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output_counts = 0
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with open(f"{args.output}.txt", 'w') as output_handle:
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for field, count in field_counts.items():
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if count >= args.min_count:
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output_counts += 1
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output_handle.write(f"{field} {count}\n")
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log.info(f"Finished combining files, {input_lines:,} lines read, {output_counts:,} field counts written")
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