Ladsgroup

class FeatureTestCase:
    """docstring for FeatureTestCase"""
    def __init__(self, name):
        super(FeatureTestCase, self).__init__()
        self.name = name

    def test_pickle(test_case):
        return eq_(pickle.loads(pickle.dumps(test_case)), test_case)

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import json
import pywikibase
with open('alan_touring.json', 'r') as f:
    res = json.loads(f.read())
item = pywikibase.ItemPage()
item.get(res)

qua = 0
for p_number in item.claims:
    claim = item.claims[p_number]

Ladsgroup

import urllib.request
import json
with open('/home/ladsgroup/res_aaron.txt', 'r') as f:
    res = f.read().split('\n')[1:]

def chunks(l, n):
    """Yield successive n-sized chunks from l."""
    for i in range(0, len(l), n):
        yield l[i:i+n]

Ladsgroup

from revscoring.features.modifiers import not_, log
from revscoring.features.revision_oriented import revision

from revscoring.datasources.revision_oriented import revision as revision_datasource

from revscoring.features.wikibase.datasources.revision_oriented import Revision
from revscoring.features.wikibase.features.revision_oriented import Revision as it_is_driving_me_crazy

revision_wikibase_datasource = Revision('wikibase.revision', revision_datasource)
wikibase_revision = it_is_driving_me_crazy('wikibase.revision', revision_wikibase_datasource)

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from ipaddress import ip_address
try:
    ip_address(user.name)
except ValueError:
    return False
else:
    return True

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{
    "continue": {
        "rvcontinue": "20151226095623|696846306",
        "continue": "||"
    },
    "query": {
        "pages": {
            "15580374": {
                "pageid": 15580374,
                "ns": 0,

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AUC of the classifier: 0.91944
f0.125-score (thrashhold, precision, recall, edits to review, total edits): 0.974, 0.875, 0.075269, 16, 4960 (0.32258%)
f0.25-score (thrashhold, precision, recall, edits to review, total edits): 0.931, 0.78049, 0.17204, 41, 4960 (0.82661%)
f0.5-score (thrashhold, precision, recall, edits to review, total edits): 0.892, 0.67606, 0.25806, 71, 4960 (1.4315%)
f1-score (thrashhold, precision, recall, edits to review, total edits): 0.847, 0.53571, 0.40323, 140, 4960 (2.8226%)
f2-score (thrashhold, precision, recall, edits to review, total edits): 0.749, 0.25, 0.73118, 544, 4960 (10.968%)
f3-score (thrashhold, precision, recall, edits to review, total edits): 0.749, 0.25, 0.73118, 544, 4960 (10.968%)
f4-score (thrashhold, precision, recall, edits to review, total edits): 0.578, 0.14734, 0.9086, 1147, 4960 (23.125%)

Ladsgroup

"""
``time_scorer -h``
::

    Tests a scorer model.  This utility expects to get a file of
    tab-separated feature values and labels from which to test a model.

    Usage:
        time_scorer -h | --help
        time_scorer <wiki> [--revs=<path>] [--model=<model>] [--batch]

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from collections import OrderedDict
import json
import os

path = '.'
i18n_dir = os.path.join(path, 'i18n')
js_file = os.path.join(path, 'wsgi/static/js/wikiLabels/wikiLabels.js')

i18n = {}
for lang_file in os.listdir(i18n_dir):

Ladsgroup

Extracting 77 features

stat	value
extractions	148
total_time	81.527
min_time	0.114
max_time	3.539
mean_time	0.551
median_time	0.337