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https://github.com/cfhamlet/os-urlpattern

Unsupervised URLs clustering, generate and match URL pattern.
https://github.com/cfhamlet/os-urlpattern

cluster pattern regular-expression url

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Unsupervised URLs clustering, generate and match URL pattern.

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=============
os-urlpattern
=============

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This package is used for unsupervised URLs clustering. Furthermore, it generate URL patterns(RegEx)
from clusters for matching purpose. It is a pure python package tested under python2.7 python3.6,
`pypy `_ can also be used for performance(4x-8x). Command line tools are provided
for standalone clustering and matching, APIs are also convenient. Several extra packages can be
installed for additional features. Under CPython 1cpu, 100 thousand URLs clustering cost almost 1min
and 200M memory. Built-in matching strategy is efficient enough in most use cases(4k/s, depend on
patterns complexity).

.. code:: console

$ pip install -U os-urlpattern
$ wget -qO- 'https://git.io/f4QlP' | pattern-make
/[0-9]{2}[\.]html
http://example.com/01.html
http://example.com/02.html
http://example.com/03.html
/[0-9]{3}/test[0-9]{2}[\.]html
http://example.com/123/test01.html
http://example.com/456/test02.html
http://example.com/789/test03.html

==============
Aknowledgement
==============

Similar URLs
=============

* URLs with the same **URL structure**.

* Components of the parsed URLs at the same position are in the same **character space**.

* Different types of charactors may be in the same order in most cases.

URL structure
==============

Typically, URL can be parsed into 6 components:

``:///;?#``

Because different sites may have similar URLs structure and is rare, so
and are ignored, are used to define URL structure.

If the URLs have the same path levels, same query keys(also keys order) and with the same
fragment existence, their URL structure should be the same.

::

http://example.com/p1/p2?k1=v1&k2=v2#pos

URL structure:
path levels: 2
query keys: k1, k2
have fragment: True

Character space
===============

Consider `RFC 3986 (Section 2: Characters) `_,
URL with the following characters would be legal:

``ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789-._~:/?#[]@!$&'()*+,;=%<>\"{}^|``

There are three major character space: lower-case letters(a-z), upper-case letters(A-Z),
number letters(0-9). Other symbols are in their own character space.

::

HeLlOwoRd666!

character space: a-z A-Z 0-9 !

Order consideration
=====================

Split a string by character, consecutive character space can be joined. In most cases, order is a
distinguished feature.

::

HELLOword666!

split into: HELLO word 666 !

character space order: A-Z a-z 0-9 !

Mix
=====================
Complex consecutive major character space can be mixed, order is less important.

::

HellWorld666!

split into: H ell W orld 666 !

major join: HellWorld666 !

character space order: A-Za-z0-9 !

Because of URL quote, '%' can be mixed with major character space.

::

%E4%BD%A0%E5%A5%BD!

split into: % E 4 % BD % A 0 % E 5 % A 5 % BD !

major join: %E4%BD%A0%E5%A5%BD !

character space order: A-Z0-9% !

URL pattern
============

URL pattern is used to express each cluster. It is normal regex string. Each URL in
the same cluster can be matched with the pattern.

::

pattern examples:

/news/[0-9]{8}/[a-z]+[\\.]html
/newsShow[\\.]asp[\\?]dataID=[0-9]+
/thread[\\-][0-9]+[\\-][0-9][\\-]1[\\.]html

The built-in matching strategy is strict, it can't tolerate incomplet matching.

::

letter: helloword

pattern01: [a-z0-9]+ # not match, because no number in the letter
pattern02: [a-z]+ # match

========
Install
========

Install with pip

``$ pip install os-urlpattern``

Install extra packages

.. list-table::
:header-rows: 1

* - subpackage
- install command
- enables
* - memory
- ``pip install os-urlpattern[memroy]``
- Show memory useage
* - ete-tree
- ``pip install os-urlpattern[ete-tree]``
- Enable `ete `_ pattern tree formatter

========
Usage
========

Command line
=============

* **pattern-make**

Load urls, cluster and dump patterns.

.. code:: console

$ pattern-make -h
usage: pattern-make [-h] [-v] [-i INPUTS [INPUTS ...]]
[-l {NOTSET,DEBUG,INFO,WARN,ERROR,FATAL}] [-c CONFIG]
[-f {PATTERN,CLUSTER,JSON,ETE,INLINE,NULL}]

optional arguments:
-h, --help show this help message and exit
-v, --version show program's version number and exit
-i INPUTS [INPUTS ...], --inputs INPUTS [INPUTS ...]
input files to be processed (default: stdin)
-l {NOTSET,DEBUG,INFO,WARN,ERROR,FATAL}, --loglevel {NOTSET,DEBUG,INFO,WARN,ERROR,FATAL}
log level (default: NOTSET)
-c CONFIG, --config CONFIG
config file
-f {PATTERN,CLUSTER,JSON,ETE,INLINE,NULL}, --formatter {PATTERN,CLUSTER,JSON,ETE,INLINE,NULL}
output formatter (default: CLUSTER)

Dump clustered URLs with patterns:

.. code:: console

$ cat urls.txt | pattern-make -L debug > clustered.txt

Only generate URL patterns:

.. code:: console

$ cat urls.txt | pattern-make -L debug -F pattern > patterns.txt

Generate pattern tree from URLs(`ete `_ installed):

.. code:: console

$ cat urls.txt | pattern-make -L debug -F ete

* **pattern-match**

Load patterns, dump URLs matched results.

.. code:: console

$ pattern-match -h
usage: pattern-match [-h] [-v] [-i INPUTS [INPUTS ...]]
[-l {NOTSET,DEBUG,INFO,WARN,ERROR,FATAL}] -p
PATTERN_FILES [PATTERN_FILES ...] [-a]

optional arguments:
-h, --help show this help message and exit
-v, --version show program's version number and exit
-i INPUTS [INPUTS ...], --inputs INPUTS [INPUTS ...]
input files to be processed (default: stdin)
-l {NOTSET,DEBUG,INFO,WARN,ERROR,FATAL}, --loglevel {NOTSET,DEBUG,INFO,WARN,ERROR,FATAL}
log level (default: NOTSET)
-p PATTERN_FILES [PATTERN_FILES ...], --pattern-files PATTERN_FILES [PATTERN_FILES ...]
pattern files to be loaded
-a, --all-matched all matched patterns

Match URLs:

.. code:: console

$ cat urls.txt | pattern-match -L debug -p patterns.txt

APIs
=====

* Cluster and generate URL patterns:

.. code:: python

from os_urlpattern.formatter import pformat
from os_urlpattern.pattern_maker import PatternMaker

pattern_maker = PatternMaker()

# load URLs(unicode)
for url in urls:
pattern_maker.load(url)

# cluster and print pattern
for url_meta, clustered in pattern_maker.make():
for pattern in pformat('pattern', url_meta, clustered):
# do whatever you want
pass

* Match URLs:

.. code:: python

from os_urlpattern.pattern_matcher import PatternMatcher

pattern_matcher = PatternMatcher()

# load url_pattern(unicode)
for url_pattern in url_patterns:
# meta will bind to matched result
pattern_matcher.load(url_pattern, meta=url_pattern)

# match URL(unicode)
for url in urls:
matched_results = patterm_matcher.match(url)
# the best matched result:
# sorted(matched_results, reverse=True)[0]
patterns = [n.meta for n in matched_results]

* Low-level APIs:

It is necessary to use low-level APIs for customizing processing procdure,
especially for parallel computing or working on an distributed cluster(hadoop).

**Key points: same fuzzy-digest same maker and same matcher.**

Use ``os_urlpattern.parser.fuzzy_digest`` to get fuzzy digest from URL,
URL pattern or URLMeta and parsed pieces/patterns.

A brief All-In-One example:

.. code:: python

from __future__ import print_function, unicode_literals
from os_urlpattern.formatter import pformat
from os_urlpattern.parser import fuzzy_digest, parse
from os_urlpattern.pattern_maker import Maker
from os_urlpattern.pattern_matcher import Matcher

urls = ['http://t.com/%02d.html' % i for i in xrange(0,10)]
makers = {}
matchers = {}

# Init makers from URLs(unicode).
for url in urls:
url_meta, parsed_pieces = parse(url)

# same digest same maker
digest = fuzzy_digest(url_meta, parsed_pieces)
if digest not in makers:
makers[digest] = Maker(url_meta)
makers[digest].load(parsed_pieces)

# Iterate makers, do clustering, generate URL pattern and init matchers.
for maker in makers.values():
for clustered in maker.make():
for pattern in pformat('pattern', maker.url_meta, clustered):
# init matchers
url_meta, parsed_patterns = parse(pattern)
digest = fuzzy_digest(url_meta, parsed_patterns)
if digest not in matchers:
matchers[digest] = Matcher(url_meta)
matchers[digest].load(parsed_patterns, pattern)

# Match URLs(unicode).
for url in urls:
url_meta, parsed_pieces = parse(url)

# same digest same matcher
digest = fuzzy_digest(url_meta, parsed_pieces)
if digest in matchers:
matched = [n.meta for n in matchers[digest].match(parsed_pieces)]
print(url, *matched, sep="\t")
else: # no matched at all
pass

============
Unit Tests
============

``$ tox``

============
License
============

MIT licensed.