from deltas import SequenceMatcher
from deltas import SegmentMatcher
+from dataclasses import dataclass
+import pandas as pd
+import pyarrow as pa
+import pyarrow.parquet as pq
+
+from typing import List
+
class PersistMethod:
none = 0
sequence = 1
# there are no capture groups, we just search for all the matches of the regex
else:
#given that there are matches to be made
- if self.pattern.search(content) is not None:
- m = self.pattern.findall(content)
- temp_dict[self.label] = ', '.join(m)
- else:
- temp_dict[self.label] = None
+ if type(content) in(str, bytes):
+ if self.pattern.search(content) is not None:
+ m = self.pattern.findall(content)
+ temp_dict[self.label] = ', '.join(m)
+ else:
+ temp_dict[self.label] = None
+
# update rev_data with our new columns
rev_data.update(temp_dict)
return rev_data
-
+@dataclass
+class RevData():
+ revid: int
+ date_time: datetime
+ articleid: int
+ editorid: int
+ title: str
+ namespace: int
+ deleted: bool
+ text_chars: int
+ revert: bool
+ reverteds: list[bool]
+ sha1: str
+ text_chars: int
+ revert: bool
+ reverteds: list[int]
+ minor: bool
+ editor: str
+ anon: bool
+ collapsed_revs:int
+ token_revs:int
+ tokens_added:int
+ tokens_removed:int
+ tokens_window:int
+
class WikiqParser():
- def __init__(self, input_file, output_file, regex_match_revision, regex_match_comment, regex_revision_label, regex_comment_label, collapse_user=False, persist=None, urlencode=False, namespaces = None, revert_radius=15):
+ def __init__(self, input_file, output_file, regex_match_revision, regex_match_comment, regex_revision_label, regex_comment_label, collapse_user=False, persist=None, urlencode=False, namespaces = None, revert_radius=15, output_parquet=True, parquet_buffer_size=2000):
"""
Parameters:
persist : what persistence method to use. Takes a PersistMethod value
"""
self.input_file = input_file
- self.output_file = output_file
+
self.collapse_user = collapse_user
self.persist = persist
self.printed_header = False
self.namespaces = []
self.urlencode = urlencode
self.revert_radius = revert_radius
+
+ self.parquet_buffer = []
+ self.parquet_buffer_size = parquet_buffer_size
if namespaces is not None:
self.namespace_filter = set(namespaces)
else:
self.namespace_filter = None
+ self.regex_schemas = []
self.regex_revision_pairs = self.make_matchmake_pairs(regex_match_revision, regex_revision_label)
self.regex_comment_pairs = self.make_matchmake_pairs(regex_match_comment, regex_comment_label)
-
+
+
+ if output_parquet is True:
+ self.output_parquet = True
+ self.pq_writer = None
+ self.output_file = output_file
+ else:
+ self.output_file = open(output_file,'w')
+
def make_matchmake_pairs(self, patterns, labels):
if (patterns is not None and labels is not None) and \
(len(patterns) == len(labels)):
- return [RegexPair(pattern, label) for pattern, label in zip(patterns, labels)]
+ result = []
+ for pattern, label in zip(patterns, labels):
+ result.append(RegexPair(pattern, label))
+ self.regex_schemas.append(pa.field(label, pa.list_(pa.string())))
+
+ return result
elif (patterns is None and labels is None):
return []
else:
'revid':rev.id,
'date_time' : rev.timestamp.strftime('%Y-%m-%d %H:%M:%S'),
'articleid' : page.id,
- 'editor_id' : "" if rev.deleted.user == True or rev.user.id is None else rev.user.id,
+ 'editorid' : "" if rev.deleted.user == True or rev.user.id is None else rev.user.id,
'title' : '"' + page.title + '"',
'namespace' : namespace,
'deleted' : "TRUE" if rev.deleted.text else "FALSE"
rev_data["tokens_added"] = num_tokens
rev_data["tokens_removed"] = len(tokens_removed)
rev_data["tokens_window"] = len(window)-(i+1)
-
self.print_rev_data(rev_data)
page_count += 1
print("Done: %s revisions and %s pages." % (rev_count, page_count),
file=sys.stderr)
+ if self.output_parquet is True:
+ self.flush_parquet_buffer()
+ self.pq_writer.close()
+
+ else:
+ output_file.close()
+
+
+ def write_parquet_row(self, rev_data):
+ if 'deleted' in rev_data.keys():
+ rev_data['deleted'] = True if rev_data['deleted'] == "TRUE" else False
+
+ if 'minor' in rev_data.keys():
+ rev_data['minor'] = True if rev_data['minor'] == "TRUE" else False
+
+
+ if 'anon' in rev_data.keys():
+ rev_data['anon'] = True if rev_data['anon'] == "TRUE" else False
+
+
+ self.parquet_buffer.append(rev_data)
+
+ if len(self.parquet_buffer) >= self.parquet_buffer_size:
+ self.flush_parquet_buffer()
+
+ def flush_parquet_buffer(self):
+ outtable = pd.DataFrame.from_records(self.parquet_buffer)
+ outtable = pa.Table.from_pandas(outtable)
+ if self.pq_writer is None:
+ schema = outtable.schema
+ for regex_schema in self.regex_schemas:
+ schema.append(regex_schema)
+
+ self.pq_writer = pq.ParquetWriter(self.output_file, schema, flavor='spark')
+
+ self.pq_writer.write_table(outtable)
+
def print_rev_data(self, rev_data):
+
+ if self.output_parquet is False:
+ printfunc = lambda rev_data: print("\t".join(rev_data), file=self.output_file)
+ else:
+ printfunc = self.write_parquet_row
+
# if it's the first time through, print the header
if self.urlencode:
for field in TO_ENCODE:
rev_data[field] = quote(str(rev_data[field]))
if not self.printed_header:
- print("\t".join([str(k) for k in sorted(rev_data.keys())]), file=self.output_file)
+ printfunc(rev_data)
self.printed_header = True
- print("\t".join([str(v) for k, v in sorted(rev_data.items())]), file=self.output_file)
+ printfunc(rev_data)
def open_input_file(input_filename):
if re.match(r'.*\.7z$', input_filename):
- cmd = ["7za", "x", "-so", input_filename, '*']
+ cmd = ["7za", "x", "-so", input_filename, "*.xml"]
elif re.match(r'.*\.gz$', input_filename):
cmd = ["zcat", input_filename]
elif re.match(r'.*\.bz2$', input_filename):
return input_file
-def open_output_file(input_filename):
- # create a regex that creates the output filename
+def get_output_filename(input_filename, parquet = False):
output_filename = re.sub(r'\.(7z|gz|bz2)?$', '', input_filename)
output_filename = re.sub(r'\.xml', '', output_filename)
- output_filename = output_filename + ".tsv"
- output_file = open(output_filename, "w")
+ if parquet is False:
+ output_filename = output_filename + ".tsv"
+ else:
+ output_filename = output_filename + ".parquet"
+ return output_filename
+def open_output_file(input_filename):
+ # create a regex that creates the output filename
+ output_filename = get_output_filename(input_filename, parquet = False)
+ output_file = open(output_filename, "w")
return output_file
parser = argparse.ArgumentParser(description='Parse MediaWiki XML database dumps into tab delimitted data.')
help="Filename of the compressed or uncompressed XML database dump. If absent, we'll look for content on stdin and output on stdout.")
parser.add_argument('-o', '--output-dir', metavar='DIR', dest='output_dir', type=str, nargs=1,
- help="Directory for output files.")
+ help="Directory for output files. If it ends with .parquet output will be in parquet format.")
parser.add_argument('-s', '--stdout', dest="stdout", action="store_true",
help="Write output to standard out (do not create dump file)")
args = parser.parse_args()
+
+
# set persistence method
if args.persist is None:
namespaces = None
if len(args.dumpfiles) > 0:
+ output_parquet = False
for filename in args.dumpfiles:
input_file = open_input_file(filename)
else:
output_dir = "."
+ if output_dir.endswith(".parquet"):
+ output_parquet = True
+
print("Processing file: %s" % filename, file=sys.stderr)
if args.stdout:
output_file = sys.stdout
else:
filename = os.path.join(output_dir, os.path.basename(filename))
- output_file = open_output_file(filename)
+ output_file = get_output_filename(filename, parquet = output_parquet)
wikiq = WikiqParser(input_file,
output_file,
regex_match_revision = args.regex_match_revision,
regex_revision_label = args.regex_revision_label,
regex_match_comment = args.regex_match_comment,
- regex_comment_label = args.regex_comment_label)
+ regex_comment_label = args.regex_comment_label,
+ output_parquet=output_parquet)
+ print(wikiq.output_parquet)
wikiq.process()
# close things
input_file.close()
- output_file.close()
+
else:
wikiq = WikiqParser(sys.stdin,
sys.stdout,
projects / mediawiki_dump_tools.git / commitdiff