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"""
Clustering part of matching.
We want to have generic and fast way to derive various clusters. Input is json
lines of release entities, e.g. from a database dump.
Map and reduce.
* input (json) blob -> (ident, value) -> group by value -> emit idents per group
Example output:
{
"v": [
"7uvh4z6zsjcptia5ig6swu4fre",
"chlthrumyfg23aqw4r477j3vge",
"yuo4smv4bzefdjsudbbzka3qv4"
],
"k": "124-5_0137.dcm",
"c": "t"
}
Performance data points:
$ time zstdcat -T0 release_export_expanded.json.zst | pv -l | \
parallel --roundrobin --pipe -j 16 fuzzycat-cluster /bigger/tmp -t title > cluster_title.json
Takes 607 min (around 3800 docs/s).
"""
import argparse
import fileinput
import itertools
import json
import os
import subprocess
import tempfile
import re
import string
import operator
import orjson as json
import fuzzy
DEFAULT_CACHE_DIR = os.path.join(os.path.expanduser("~"), ".cache", "fuzzycat")
def sort_by_column(filename, mode="w", opts="-k 2", fast=True, prefix="fuzzycat-"):
"""
Sort tabular file with sort(1), returns the filename of the sorted file.
"""
with tempfile.NamedTemporaryFile(delete=False, mode=mode, prefix=prefix) as tf:
env = os.environ.copy()
if fast:
env["LC_ALL"] = "C"
subprocess.run(["sort"] + opts.split() + [filename], stdout=tf)
return tf.name
def group_by_column(filename, key=None, value=None, comment=""):
"""
Group a sorted file with given key function. Use another function to
extract the value.
"""
with open(filename) as f:
for k, g in itertools.groupby(f, key=key):
doc = {
"v": [value(v) for v in g],
"c": comment,
"k": k.strip(),
}
yield doc
# XXX: LineOps
def cut(f=0, sep='\t'):
"""
Similar to cut(1), but zero indexed.
"""
return lambda v: v.split(sep)[f]
def cluster_by_title(args):
"""
Basic example for a three stage process: extract, sort, group. Speed is
about: 20K/s (json roundtrip, sorting, grouping).
"""
files = args.files if len(args.files) > 0 else ('-', )
fg = operator.itemgetter("ident", "title")
with tempfile.NamedTemporaryFile(delete=False, mode="w", prefix=args.tmp_prefix) as tf:
for line in fileinput.input(files=files)
try:
doc = json.loads(line)
id, title = fg(doc)
if not title:
continue
title = title.replace("\t", " ").replace("\n", " ").strip()
except KeyError as err:
continue
print("%s\t%s" % (id, title), file=tf)
sbc = sort_by_column(tf.name, opts="-k 2", prefix=args.tmp_prefix)
for doc in group_by_column(sbc, key=cut(f=1), value=cut(f=0), comment="t"):
print(json.dumps(doc).decode("utf-8"))
os.remove(sbc)
os.remove(tf.name)
def cluster_by_title_normalized(args):
"""
Normalize title, e.g. analysisofheritability. 17k/s.
"""
files = args.files if len(args.files) > 0 else ('-', )
fg = operator.itemgetter("ident", "title")
pattern = re.compile('[\W_]+', re.UNICODE)
with tempfile.NamedTemporaryFile(delete=False, mode="w", prefix=args.tmp_prefix) as tf:
for line in fileinput.input(files=files):
try:
doc = json.loads(line)
id, title = fg(doc)
if not title:
continue
title = title.replace("\t", " ").replace("\n", " ").strip().lower()
title = pattern.sub('', title)
except KeyError as err:
continue
print("%s\t%s" % (id, title), file=tf)
sbc = sort_by_column(tf.name, opts="-k 2")
for doc in group_by_column(sbc, key=cut(f=1), value=cut(f=0), comment="tn"):
print(json.dumps(doc).decode("utf-8"))
os.remove(sbc)
os.remove(tf.name)
def cluster_by_title_nysiis(args):
"""
Soundex on title.
"""
files = args.files if len(args.files) > 0 else ('-', )
fg = operator.itemgetter("ident", "title")
with tempfile.NamedTemporaryFile(delete=False, mode="w", prefix=args.tmp_prefix) as tf:
for line in fileinput.input(files=files):
try:
doc = json.loads(line)
id, title = fg(doc)
if not title:
continue
title = fuzzy.nysiis(title)
except KeyError as err:
continue
print("%s\t%s" % (id, title), file=tf)
sbc = sort_by_column(tf.name, opts="-k 2")
for doc in group_by_column(sbc, key=cut(f=1), value=cut(f=0), comment="nysiis"):
print(json.dumps(doc).decode("utf-8"))
os.remove(sbc)
os.remove(tf.name)
def main():
types = {
"title": cluster_by_title,
"title_normalized": cluster_by_title_normalized,
"title_nysiis": cluster_by_title_nysiis,
}
parser = argparse.ArgumentParser(prog='fuzzycat-cluster',
usage='%(prog)s [options]',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("-t", "--type", default="title", help="clustering variant to use")
parser.add_argument("-l", "--list", action="store_true", help="list cluster variants")
parser.add_argument("--tmp-prefix", default="fuzzycat-", help="prefix for tmp file")
parser.add_argument("--tmpdir", default=tempfile.gettempdir(), help="temp directory")
parser.add_argument('files', metavar='FILE', nargs='*', help='files to read, if empty, stdin is used')
args = parser.parse_args()
tempfile.tempdir = args.tmpdir
if args.list:
print("\n".join(types.keys()))
return
func = types.get(args.type)
if func is None:
print("invalid type: {}".format(args.type))
return
func(args)
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