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Watchful1 2021-09-04 23:17:53 -07:00
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.gitignore vendored Normal file
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.idea/*
logs/*
__pycache__/*
*.db
*.ini
*.txt

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Pipfile Normal file
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[[source]]
url = "https://pypi.org/simple"
verify_ssl = true
name = "pypi"
[packages]
zstandard = "*"
[dev-packages]
[requires]
python_version = "3.8"

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{
"_meta": {
"hash": {
"sha256": "03662c664bce0cd9fad7ea3062bb09bfe999f755a00e0f4de720c66955ccae62"
},
"pipfile-spec": 6,
"requires": {
"python_version": "3.8"
},
"sources": [
{
"name": "pypi",
"url": "https://pypi.org/simple",
"verify_ssl": true
}
]
},
"default": {
"zstandard": {
"hashes": [
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"index": "pypi",
"version": "==0.15.2"
}
},
"develop": {}
}

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coming soon

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scripts/combine_folder_multiprocess.py Normal file
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import zstandard
import os
import json
import sys
import time
import argparse
from datetime import datetime
import logging.handlers
import multiprocessing
# sets up logging to the console as well as a file
log = logging.getLogger("bot")
log.setLevel(logging.INFO)
log_formatter = logging.Formatter('%(asctime)s - %(levelname)s: %(message)s')
log_stderr_handler = logging.StreamHandler()
log_stderr_handler.setFormatter(log_formatter)
log.addHandler(log_stderr_handler)
if not os.path.exists("logs"):
os.makedirs("logs")
log_file_handler = logging.handlers.RotatingFileHandler(
os.path.join("logs", "bot.log"), maxBytes=1024*1024*16, backupCount=5)
log_file_handler.setFormatter(log_formatter)
log.addHandler(log_file_handler)
# this script iterates through zst compressed ndjson files, like the pushshift reddit dumps, loads each line
# and passes it into the save_obj function, if it function returns true for a line, it's written out into a
# separate file for that month. After all the ndjson files are processed, it iterates through the resulting
# files and combines them into a final file.
# once complete, the combined file can easily be processed like
# with open(file_path, 'r') as file:
# for line in file:
# obj = json.loads(line)
# features:
# - multiple processes in parallel to maximize drive read and decompression
# - saves state as it completes each file and picks up where it stopped
# - detailed progress indicators
# convenience object used to pass status information between processes
class FileConfig:
def __init__(self, input_path, output_path=None, complete=False, lines_processed=0, error_lines=0):
self.input_path = input_path
self.output_path = output_path
self.file_size = os.stat(input_path).st_size
self.complete = complete
self.bytes_processed = self.file_size if complete else 0
self.lines_processed = lines_processed if complete else 0
self.error_message = None
self.error_lines = error_lines
def __str__(self):
return f"{self.input_path} : {self.output_path} : {self.file_size} : {self.complete} : {self.bytes_processed} : {self.lines_processed}"
# used for calculating running average of read speed
class Queue:
def __init__(self, max_size):
self.list = []
self.max_size = max_size
def put(self, item):
if len(self.list) >= self.max_size:
self.list.pop(0)
self.list.append(item)
def peek(self):
return self.list[0] if len(self.list) > 0 else None
# builds file paths
def folder_helper(output_folder, output_file_name):
working_folder = os.path.join(output_folder, "pushshift_working_dir_" + output_file_name)
status_file = os.path.join(working_folder, output_file_name + ".json")
return working_folder, status_file
# save file information and progress to a json file
# we don't want to save the whole FileConfig object, since some of the info resets if we restart
def save_file_list(input_files, output_folder, output_file_name):
working_folder, status_json_file_name = folder_helper(output_folder, output_file_name)
if not os.path.exists(working_folder):
os.makedirs(working_folder)
simple_file_list = []
for file in input_files:
simple_file_list.append([file.input_path, file.output_path, file.complete, file.lines_processed, file.error_lines])
with open(status_json_file_name, 'w') as status_json_file:
status_json_file.write(json.dumps(simple_file_list, indent=4))
# load file information from the json file and recalculate file sizes
def load_file_list(output_folder, output_file_name):
_, status_json_file_name = folder_helper(output_folder, output_file_name)
if os.path.exists(status_json_file_name):
with open(status_json_file_name, 'r') as status_json_file:
simple_file_list = json.load(status_json_file)
input_files = []
for simple_file in simple_file_list:
input_files.append(
FileConfig(simple_file[0], simple_file[1], simple_file[2], simple_file[3], simple_file[4])
)
return input_files
else:
return None
# open a zst compressed ndjson file and yield lines one at a time
# also passes back file progress
def read_lines_zst(file_name):
with open(file_name, 'rb') as file_handle:
buffer = ''
reader = zstandard.ZstdDecompressor(max_window_size=2**31).stream_reader(file_handle)
while True:
chunk = reader.read(2**27).decode()
if not chunk:
break
lines = (buffer + chunk).split("\n")
for line in lines[:-1]:
yield line, file_handle.tell()
buffer = lines[-1]
reader.close()
# base of each separate process. Loads a file, iterates through lines and writes out
# the ones where save_obj() returns true. Also passes status information back to the parent via a queue
def process_file(file, working_folder, queue, field, value):
output_file = None
try:
for line, file_bytes_processed in read_lines_zst(file.input_path):
try:
obj = json.loads(line)
if obj[field] == value:
if output_file is None:
if file.output_path is None:
created = datetime.utcfromtimestamp(int(obj['created_utc']))
file.output_path = os.path.join(working_folder, created.strftime("%Y-%m"))
output_file = open(file.output_path, 'w')
output_file.write(line)
output_file.write("\n")
except (KeyError, json.JSONDecodeError) as err:
file.error_lines += 1
file.lines_processed += 1
if file.lines_processed % 1000000 == 0:
file.bytes_processed = file_bytes_processed
queue.put(file)
if output_file is not None:
output_file.close()
file.complete = True
file.bytes_processed = file.file_size
except Exception as err:
file.error_message = str(err)
queue.put(file)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="Use multiple processes to decompress and iterate over pushshift dump files")
parser.add_argument("input", help="The input folder to read files from")
parser.add_argument("output", help="The output folder to store temporary files in and write the output to")
parser.add_argument("--name", help="What to name the output file", default="pushshift")
parser.add_argument("--field", help="When deciding what lines to keep, use this field for comparisons", default="subreddit")
parser.add_argument("--value", help="When deciding what lines to keep, compare the field to this value", default="pushshift")
parser.add_argument("--processes", help="Number of processes to use", default=10, type=int)
parser.add_argument(
"--error_rate", help=
"Percentage as an integer from 0 to 100 of the lines where the field can be missing. For the subreddit field especially, "
"there are a number of posts that simply don't have a subreddit attached", default=1, type=int)
parser.add_argument("--debug", help="Enable debug logging", action='store_const', const=True, default=False)
args = parser.parse_args()
if args.debug:
log.setLevel(logging.DEBUG)
log.info(f"Loading files from: {args.input}")
log.info(f"Writing output to: {(os.path.join(args.output, args.name + '.txt'))}")
multiprocessing.set_start_method('spawn')
queue = multiprocessing.Manager().Queue()
input_files = load_file_list(args.output, args.name)
working_folder, _ = folder_helper(args.output, args.name)
# if the file list wasn't loaded from the json, this is the first run, find what files we need to process
if input_files is None:
input_files = []
for subdir, dirs, files in os.walk(args.input):
files.sort()
for file_name in files:
if file_name.endswith(".zst"):
input_path = os.path.join(subdir, file_name)
input_files.append(FileConfig(input_path))
save_file_list(input_files, args.output, args.name)
files_processed = 0
total_bytes = 0
total_bytes_processed = 0
total_lines_processed = 0
files_to_process = []
# calculate the total file size for progress reports, build a list of incomplete files to process
for file in input_files:
total_bytes += file.file_size
if file.complete:
files_processed += 1
total_lines_processed += file.lines_processed
total_bytes_processed += file.file_size
else:
files_to_process.append(file)
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")
start_time = time.time()
if len(files_to_process):
progress_queue = Queue(40)
progress_queue.put([start_time, total_lines_processed, total_bytes_processed])
speed_queue = Queue(40)
for file in files_to_process:
log.debug(f"Processing file: {file.input_path}")
# start the workers
with multiprocessing.Pool(processes=min(args.processes, len(files_to_process))) as pool:
workers = pool.starmap_async(process_file, [(file, working_folder, queue, args.field, args.value) for file in files_to_process], error_callback=log.info)
while not workers.ready():
# loop until the workers are all done, pulling in status messages as they are sent
file_update = queue.get()
if file_update.error_message is not None:
log.warning(f"File failed {file_update.input_path}: {file_update.error_message}")
continue
# I'm going to assume that the list of files is short enough that it's no
# big deal to just iterate each time since that saves a bunch of work
total_lines_processed = 0
total_bytes_processed = 0
total_lines_errored = 0
files_processed = 0
i = 0
for file in input_files:
if file.input_path == file_update.input_path:
input_files[i] = file_update
file = file_update
total_lines_processed += file.lines_processed
total_bytes_processed += file.bytes_processed
total_lines_errored += file.error_lines
files_processed += 1 if file.complete else 0
i += 1
if file_update.complete:
save_file_list(input_files, args.output, args.name)
current_time = time.time()
progress_queue.put([current_time, total_lines_processed, total_bytes_processed])
first_time, first_lines, first_bytes = progress_queue.peek()
bytes_per_second = int((total_bytes_processed - first_bytes)/(current_time - first_time))
speed_queue.put(bytes_per_second)
seconds_left = int((total_bytes - total_bytes_processed) / int(sum(speed_queue.list) / len(speed_queue.list)))
minutes_left = int(seconds_left / 60)
hours_left = int(minutes_left / 60)
days_left = int(hours_left / 24)
log.info(
f"{total_lines_processed:,} lines at {(total_lines_processed - first_lines)/(current_time - first_time):,.0f}/s, {total_lines_errored:,} errored : "
f"{(total_bytes_processed / (2**30)):.2f} gb at {(bytes_per_second / (2**20)):,.0f} mb/s, {(total_bytes_processed / total_bytes) * 100:.0f}% : "
f"{files_processed}/{len(input_files)} files : "
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")
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)}")
working_file_paths = []
count_incomplete = 0
# build a list of output files to combine
for file in input_files:
if not file.complete:
log.info(f"File {file.input_path} is not marked as complete")
count_incomplete += 1
else:
if file.error_lines > file.lines_processed * (args.error_rate * 0.01):
log.info(
f"File {file.input_path} has {file.error_lines:,} errored lines out of {file.lines_processed:,}, "
f"{(file.error_lines / file.lines_processed) * (args.error_rate * 0.01):.2f}% which is above the limit of {args.error_rate}%")
count_incomplete += 1
elif file.output_path is not None:
if not os.path.exists(file.output_path):
log.info(f"Output file {file.output_path} doesn't exist")
count_incomplete += 1
else:
working_file_paths.append(file.output_path)
if count_incomplete > 0:
log.info(f"{count_incomplete} files were not completed, errored or don't exist, something went wrong. Aborting")
sys.exit()
log.info(f"Processing complete, combining {len(working_file_paths)} result files")
output_lines = 0
output_file_path = os.path.join(args.output, args.name + ".txt")
# combine all the output files into the final results file
with open(output_file_path, 'w') as output_file:
i = 0
for working_file_path in working_file_paths:
i += 1
log.info(f"Reading {i}/{len(working_file_paths)}")
with open(working_file_path, 'r') as input_file:
for line in input_file.readlines():
output_lines += 1
output_file.write(line)
log.info(f"Finished combining files, {output_lines:,} lines written to {output_file_path}")
# test file sorting
# compress results
# example command line call in comment

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scripts/iterate_folder.py Normal file
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import zstandard
import os
import json
import sys
from datetime import datetime
import logging.handlers
log = logging.getLogger("bot")
log.setLevel(logging.DEBUG)
log.addHandler(logging.StreamHandler())
def read_lines_zst(file_name):
with open(file_name, 'rb') as file_handle:
buffer = ''
reader = zstandard.ZstdDecompressor(max_window_size=2**28).stream_reader(file_handle)
while True:
chunk = reader.read(2**24).decode() # read a 16mb chunk at a time. There are some really big comments
if not chunk:
break
lines = (buffer + chunk).split("\n")
for line in lines[:-1]:
yield line, file_handle.tell()
buffer = lines[-1]
reader.close()
input_folder = sys.argv[1]
input_files = []
total_size = 0
for subdir, dirs, files in os.walk(input_folder):
for filename in files:
input_path = os.path.join(subdir, filename)
if input_path.endswith(".zst"):
file_size = os.stat(input_path).st_size
total_size += file_size
input_files.append([input_path, file_size])
log.info(f"Processing {len(input_files)} files of {(total_size / (2**30)):.2f} gigabytes")
total_lines = 0
total_bytes_processed = 0
for input_file in input_files:
file_lines = 0
file_bytes_processed = 0
created = None
for line, file_bytes_processed in read_lines_zst(input_file[0]):
obj = json.loads(line)
created = datetime.utcfromtimestamp(int(obj['created_utc']))
file_lines += 1
if file_lines == 1:
log.info(f"{created.strftime('%Y-%m-%d %H:%M:%S')} : {file_lines + total_lines:,} : 0% : {(total_bytes_processed / total_size) * 100:.0f}%")
if file_lines % 100000 == 0:
log.info(f"{created.strftime('%Y-%m-%d %H:%M:%S')} : {file_lines + total_lines:,} : {(file_bytes_processed / input_file[1]) * 100:.0f}% : {(total_bytes_processed / total_size) * 100:.0f}%")
total_lines += file_lines
total_bytes_processed += input_file[1]
log.info(f"{created.strftime('%Y-%m-%d %H:%M:%S')} : {total_lines:,} : 100% : {(total_bytes_processed / total_size) * 100:.0f}%")
log.info(f"Total: {total_lines}")

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scripts/single_file.py Normal file
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import zstandard
import os
import json
import sys
from datetime import datetime
import logging.handlers
log = logging.getLogger("bot")
log.setLevel(logging.DEBUG)
log.addHandler(logging.StreamHandler())
def read_lines_zst(file_name):
with open(file_name, 'rb') as file_handle:
buffer = ''
reader = zstandard.ZstdDecompressor(max_window_size=2**31).stream_reader(file_handle)
while True:
chunk = reader.read(2**27).decode()
if not chunk:
break
lines = (buffer + chunk).split("\n")
for line in lines[:-1]:
yield line, file_handle.tell()
buffer = lines[-1]
reader.close()
if __name__ == "__main__":
file_path = r"\\MYCLOUDPR4100\Public\reddit\submissions\RS_2013-03.zst"
file_size = os.stat(file_path).st_size
file_lines = 0
file_bytes_processed = 0
created = None
field = "subreddit"
value = "wallstreetbets"
bad_lines = 0
try:
for line, file_bytes_processed in read_lines_zst(file_path):
try:
obj = json.loads(line)
created = datetime.utcfromtimestamp(int(obj['created_utc']))
temp = obj[field] == value
except (KeyError, json.JSONDecodeError) as err:
bad_lines += 1
file_lines += 1
if file_lines % 100000 == 0:
log.info(f"{created.strftime('%Y-%m-%d %H:%M:%S')} : {file_lines:,} : {bad_lines:,} : {(file_bytes_processed / file_size) * 100:.0f}%")
except Exception as err:
log.info(err)
log.info(f"Complete : {file_lines:,} : {bad_lines:,}")