xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

2f62eb2bd16e126e173ae3fb73afbf46ef442d59

158

py

Python

utils/command.py

Etuloser/e-flask

0cdc6ae324b3cfe696b69b85ad0189516ba9a25f

[ "MIT" ]

null

utils/command.py

Etuloser/e-flask

0cdc6ae324b3cfe696b69b85ad0189516ba9a25f

[ "MIT" ]

null

utils/command.py

Etuloser/e-flask

0cdc6ae324b3cfe696b69b85ad0189516ba9a25f

[ "MIT" ]

null

import subprocess class Command: def __init__(self): pass def get_status_output(self, cmd): return subprocess.getstatusoutput(cmd)

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2f9a5c53b454e23ddef3d9a7c39712a0f3a0324b

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py

Python

googleanalytics/commands/__init__.py

ruber0id/google-analytics

477e5c109db606d8388350df2508333958ef30a0

[ "ISC" ]

170

2015-02-16T19:16:41.000Z

2021-10-11T16:32:17.000Z

googleanalytics/commands/__init__.py

ruber0id/google-analytics

477e5c109db606d8388350df2508333958ef30a0

[ "ISC" ]

46

2015-01-05T17:11:57.000Z

2021-11-07T19:20:54.000Z

googleanalytics/commands/__init__.py

ruber0id/google-analytics

477e5c109db606d8388350df2508333958ef30a0

[ "ISC" ]

64

2015-03-27T21:59:18.000Z

2022-03-16T16:19:45.000Z

# encoding: utf-8 from . import authorize, common, list, query, revoke, shell from .common import cli

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2f9f376bd4c0b636b56c6120e107a0f1e0b83c37

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py

Python

responses/management/commands/__init__.py

nickcatal/petitionviewer

68b27080235740842da5f03a5d991b668c3daa94

[ "Apache-2.0" ]

null

responses/management/commands/__init__.py

nickcatal/petitionviewer

68b27080235740842da5f03a5d991b668c3daa94

[ "Apache-2.0" ]

null

responses/management/commands/__init__.py

nickcatal/petitionviewer

68b27080235740842da5f03a5d991b668c3daa94

[ "Apache-2.0" ]

null

"""Management commands for responses app"""

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null

0

1

0

5

85f23d56b8373768861b0d12df752d19718cda1b

145

py

Python

mymod.py

robbroadhead/PythonCertificationSeries

15a9907b6bd05d6419e9472b56666dacf7dc8333

[ "CC0-1.0" ]

null

mymod.py

robbroadhead/PythonCertificationSeries

15a9907b6bd05d6419e9472b56666dacf7dc8333

[ "CC0-1.0" ]

1

2021-08-21T15:20:56.000Z

mymod.py

robbroadhead/PythonCertificationSeries

15a9907b6bd05d6419e9472b56666dacf7dc8333

[ "CC0-1.0" ]

null

# A python module for example purposes myName = "mymod module for examples" def add(a,b): return a + b def multiply(a,b): return a * b

16.111111

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0.662069

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145

3.84

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5

c8015f6104da44980663bebda0a0a7e54da46060

154

py

Python

Python/Curos_Python_curemvid/Exercicios_dos_videos/Ex057.py

Jhonattan-rocha/Meus-primeiros-programas

f5971b66c0afd049b5d0493e8b7a116b391d058e

[ "MIT" ]

null

Python/Curos_Python_curemvid/Exercicios_dos_videos/Ex057.py

Jhonattan-rocha/Meus-primeiros-programas

f5971b66c0afd049b5d0493e8b7a116b391d058e

[ "MIT" ]

null

Python/Curos_Python_curemvid/Exercicios_dos_videos/Ex057.py

Jhonattan-rocha/Meus-primeiros-programas

f5971b66c0afd049b5d0493e8b7a116b391d058e

[ "MIT" ]

null

nome = input("Digite seu nome: ") s = input("Digite seu sexo(M/N): ").upper() while s != 'M' != 'F': s = input("Digite seu sexo novamente: ").upper()

30.8

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1

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null

0

5

c802532a26ffb3a3811fedeb5015b9fdab7f45dc

2,470

py

Python

tests/tests_queries.py

ktosiu/tinydb-1

34d6ec3a1f462b1bf7e33f88c500c4a93486bea4

[ "MIT" ]

1

2019-06-27T08:13:10.000Z

tests/tests_queries.py

ktosiu/tinydb-1

34d6ec3a1f462b1bf7e33f88c500c4a93486bea4

[ "MIT" ]

null

tests/tests_queries.py

ktosiu/tinydb-1

34d6ec3a1f462b1bf7e33f88c500c4a93486bea4

[ "MIT" ]

null

from nose.tools import * from tinydb.queries import where def test_eq(): query = where('value') == 1 assert_true(query({'value': 1})) assert_false(query({'value': 2})) def test_ne(): query = where('value') != 1 assert_true(query({'value': 2})) assert_false(query({'value': 1})) def test_lt(): query = where('value') < 1 assert_true(query({'value': 0})) assert_false(query({'value': 1})) def test_le(): query = where('value') <= 1 assert_true(query({'value': 0})) assert_true(query({'value': 1})) assert_false(query({'value': 2})) def test_gt(): query = where('value') > 1 assert_true(query({'value': 2})) assert_false(query({'value': 1})) def test_ge(): query = where('value') >= 1 assert_true(query({'value': 2})) assert_true(query({'value': 1})) assert_false(query({'value': 0})) def test_or(): query = ( (where('val1') == 1) | (where('val2') == 2) ) assert_true(query({'val1': 1})) assert_true(query({'val2': 2})) assert_true(query({'val1': 1, 'val2': 2})) assert_false(query({'val1': '', 'val2': ''})) def test_and(): query = ( (where('val1') == 1) & (where('val2') == 2) ) assert_true(query({'val1': 1, 'val2': 2})) assert_false(query({'val1': 1})) assert_false(query({'val2': 2})) assert_false(query({'val1': '', 'val2': ''})) def test_not(): query = ~ (where('val1') == 1) assert_true(query({'val1': 5, 'val2': 2})) assert_false(query({'val1': 1, 'val2': 2})) query = ( (~ (where('val1') == 1)) & (where('val2') == 2) ) assert_true(query({'val1': '', 'val2': 2})) assert_true(query({'val2': 2})) assert_false(query({'val1': 1, 'val2': 2})) assert_false(query({'val1': 1})) assert_false(query({'val1': '', 'val2': ''})) def test_has_key(): query = where('val3') assert_true(query({'val3': 1})) assert_false(query({'val1': 1, 'val2': 2})) def test_regex(): query = where('val').matches(r'\d{2}\.') assert_true(query({'val': '42.'})) assert_false(query({'val': '44'})) assert_false(query({'val': 'ab.'})) assert_false(query({'': None})) def test_custom(): def test(value): return value == 42 query = where('val').test(test) assert_true(query({'val': 42})) assert_false(query({'val': 40})) assert_false(query({'val': '44'})) assert_false(query({'': None}))

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null

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1

0

null

0

1

0

5

c81b64fb9c71cc59c803ae12f6877016ea38b4cd

118

py

Python

bin/anthology/__init__.py

nschneid/acl-anthology

d75335fcb95150517416a8a13532c386746d83f0

[ "Apache-2.0" ]

221

2017-06-05T04:44:41.000Z

2022-02-11T20:23:31.000Z

bin/anthology/__init__.py

nschneid/acl-anthology

d75335fcb95150517416a8a13532c386746d83f0

[ "Apache-2.0" ]

1,498

2017-08-09T13:41:49.000Z

2022-03-31T02:56:58.000Z

bin/anthology/__init__.py

nschneid/acl-anthology

d75335fcb95150517416a8a13532c386746d83f0

[ "Apache-2.0" ]

183

2017-10-28T00:56:49.000Z

2022-03-14T14:55:00.000Z

from .anthology import Anthology from .people import PersonName from .papers import Paper from .volumes import Volume

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null

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1

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1

0

1

0

5

c087afe5956dca60b99f1b10f9c122a9c51dc60f

150

py

Python

shamanld/__init__.py

Prev/shaman

7878e931a7bdbae99432d16e388e67ee92b1e2bd

[ "MIT" ]

25

2017-07-19T16:03:11.000Z

2021-05-25T09:47:11.000Z

shamanld/__init__.py

Prev/shaman

7878e931a7bdbae99432d16e388e67ee92b1e2bd

[ "MIT" ]

null

shamanld/__init__.py

Prev/shaman

7878e931a7bdbae99432d16e388e67ee92b1e2bd

[ "MIT" ]

1

2018-04-11T07:39:22.000Z

""" shaman/shaman ----------------- Programming Language Detector :author: Prev(prevdev@gmail.com) :license: MIT """ from .shaman import Shaman

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null

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1

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1

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1

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5

c0aecdf16bbc3b4eda262d1577e4eede8cb298bb

42

py

Python

components/crud-web-apps/common/backend/kubeflow/kubeflow/crud_backend/rok/__init__.py

phvalguima/kubeflow

d224549f11b671c2ee9e97380e4525bb698c0a68

[ "Apache-2.0" ]

9,272

2018-01-29T14:14:06.000Z

2022-03-31T14:01:45.000Z

components/crud-web-apps/common/backend/kubeflow/kubeflow/crud_backend/rok/__init__.py

zhou762/kubeflow

5bf005f21647c2238b8f863e9e51e9c81872b2f5

[ "Apache-2.0" ]

6,321

2018-01-29T14:00:15.000Z

2022-03-31T21:21:07.000Z

components/crud-web-apps/common/backend/kubeflow/kubeflow/crud_backend/rok/__init__.py

zhou762/kubeflow

5bf005f21647c2238b8f863e9e51e9c81872b2f5

[ "Apache-2.0" ]

1,909

2018-01-30T01:31:58.000Z

2022-03-30T07:43:48.000Z

from .routes import bp # noqa E402, F401

21

41

0.714286

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42

4.285714

1

0

0.181818

0.214286

42

1

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true

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c0e2305119899e797b7e7f069ea1fddac0231277

61

py

Python

src/seeds/problems/hello-world/python/main.py

tabjy/cmpt383-project

47b6010b5ec277e8020b0a333cb2ee3fff06928a

[ "MIT" ]

null

src/seeds/problems/hello-world/python/main.py

tabjy/cmpt383-project

47b6010b5ec277e8020b0a333cb2ee3fff06928a

[ "MIT" ]

null

src/seeds/problems/hello-world/python/main.py

tabjy/cmpt383-project

47b6010b5ec277e8020b0a333cb2ee3fff06928a

[ "MIT" ]

null

from solution import Solution print(Solution().helloWorld())

20.333333

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7

61

7

0.714286

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0.081967

61

3

30

20.333333

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true

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0.5

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0

1

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null

0

1

0

1

0

1

0

5

23854706a79139ba1fc02eebbf884d242527e328

9

py

Python

stupidity/braces.py

koirikivi/stupidity

d0190b7af454ee74111e9059d9a61650cd43df83

[ "MIT" ]

3

2020-05-19T07:24:04.000Z

2021-03-18T19:29:17.000Z

stupidity/braces.py

koirikivi/stupidity

d0190b7af454ee74111e9059d9a61650cd43df83

[ "MIT" ]

null

stupidity/braces.py

koirikivi/stupidity

d0190b7af454ee74111e9059d9a61650cd43df83

[ "MIT" ]

null

'PSYCH!'

4.5

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0.555556

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9

1

9

0.625

0.666667

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true

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1

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1

0

null

0

1

0

5

2392158c5ebf5785c09e7b7bb7acedb82c2af7b9

123

py

Python

mobtexting_sms/models/__init__.py

mobtexting/mobtexting-odoo

01b1a6f87fc41b8c9f4099476d00023ff84b8372

[ "MIT" ]

null

mobtexting_sms/models/__init__.py

mobtexting/mobtexting-odoo

01b1a6f87fc41b8c9f4099476d00023ff84b8372

[ "MIT" ]

null

mobtexting_sms/models/__init__.py

mobtexting/mobtexting-odoo

01b1a6f87fc41b8c9f4099476d00023ff84b8372

[ "MIT" ]

null

# -*- coding: utf-8 - from . import gateway_setup from . import ir_actions from . import send_sms from . import sms_track

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6

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null

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5

23a75b870bd832adda868a89a06c8cc344c797a8

173

py

Python

prediction/endpoints/worker_microsoft.py

ecosystemai/ecosystem-notebooks

7282f22fbe7ab7a43b2b0c06c74b3f176defaca4

[ "MIT" ]

2

2020-08-30T12:50:47.000Z

2020-11-24T12:59:43.000Z

prediction/endpoints/worker_microsoft.py

ecosystemai/ecosystem-notebooks

7282f22fbe7ab7a43b2b0c06c74b3f176defaca4

[ "MIT" ]

null

prediction/endpoints/worker_microsoft.py

ecosystemai/ecosystem-notebooks

7282f22fbe7ab7a43b2b0c06c74b3f176defaca4

[ "MIT" ]

2

2020-09-02T16:54:25.000Z

2021-06-20T20:30:11.000Z

# Worker: Microsoft GET_ANOMALY = { "type": "get", "endpoint": "/getAnomaly", "call_message": "{type} {endpoint}", "error_message": "{type} {endpoint} {response_code}" }

24.714286

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7

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23a7e9a09e2c4900060a68a26059fcb3411be5ef

1,015

py

Python

Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/removendo-files.py

Matheusfarmaceutico/Exercicios-Python

d1821bd9d11ea0707074c5fe11dead2e85476ebd

[ "MIT" ]

null

Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/removendo-files.py

Matheusfarmaceutico/Exercicios-Python

d1821bd9d11ea0707074c5fe11dead2e85476ebd

[ "MIT" ]

null

Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/removendo-files.py

Matheusfarmaceutico/Exercicios-Python

d1821bd9d11ea0707074c5fe11dead2e85476ebd

[ "MIT" ]

null

import os try: os.remove("Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/teste.txt") except: pass cmd = "git status ." chamada = os.system(cmd) print(chamada) try: os.rename(src="/home/matheus/Documentos/Repositorios_Linux/Exercicios-Python/Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/velho.txt",dst="/home/matheus/Documentos/Repositorios_Linux/Exercicios-Python/Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/novo.txt") except: pass #consigo mover um arquivo com os.rename origin = "/home/matheus/Documentos/Repositorios_Linux/Exercicios-Python/Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/movendo.txt" destiny = "/home/matheus/Documentos/Repositorios_Linux/Exercicios-Python/Curso Udemy 2022/Nova_organizacao/aula_89_criando-lendo-escrevendo-apagando/movendo/movendo.txt" try: os.rename(origin,destiny) except: print("Codigo já executado e arquivo já movido")

37.592593

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23bd110c9738698f1d256ce13e2c741f420f1139

451

py

Python

chapter_10_testing_and_tdd/advanced_pytest/test_markers.py

Tm2197/Python-Architecture-Patterns

8091b4d8e2580763ceb55a83c75aa9b6225fcb72

[ "MIT" ]

12

2021-07-20T12:55:39.000Z

2022-02-05T10:53:38.000Z

chapter_10_testing_and_tdd/advanced_pytest/test_markers.py

Tm2197/Python-Architecture-Patterns

8091b4d8e2580763ceb55a83c75aa9b6225fcb72

[ "MIT" ]

null

chapter_10_testing_and_tdd/advanced_pytest/test_markers.py

Tm2197/Python-Architecture-Patterns

8091b4d8e2580763ceb55a83c75aa9b6225fcb72

[ "MIT" ]

9

2021-07-22T06:01:03.000Z

2022-03-01T05:50:45.000Z

import pytest from tdd_example import parameter_tdd @pytest.mark.edge def test_negative(): assert parameter_tdd(-1) == 0 @pytest.mark.edge def test_zero(): assert parameter_tdd(0) == 0 def test_five(): assert parameter_tdd(5) == 25 def test_seven(): assert parameter_tdd(7) == 49 @pytest.mark.edge def test_ten(): assert parameter_tdd(10) == 100 @pytest.mark.edge def test_eleven(): assert parameter_tdd(11) == 100

14.548387

37

0.696231

68

451

4.411765

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0.36

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451

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true

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0

null

1

0

null

0

1

0

5

9b0968f2114870dce95dd7b1d5f878d6174f1d94

230

py

Python

.ipynb_checkpoints/__init__.py

kfinc/maze-generator

eac806819e328e5c8c8453dd6dd923e060fbbcc4

[ "Apache-2.0" ]

null

.ipynb_checkpoints/__init__.py

kfinc/maze-generator

eac806819e328e5c8c8453dd6dd923e060fbbcc4

[ "Apache-2.0" ]

null

.ipynb_checkpoints/__init__.py

kfinc/maze-generator

eac806819e328e5c8c8453dd6dd923e060fbbcc4

[ "Apache-2.0" ]

null

from .random_maze import random_maze from .random_shape_maze import random_shape_maze from .u_maze import u_maze from .morris_water_maze import morris_water_maze from .t_maze import t_maze from .double_t_maze import double_t_maze

32.857143

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1

0

1

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1

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5

f1adf0116ee85d99a2204a70292404ec0c64a43c

24

py

Python

tests/__init__.py

iboraham/changepoint_detector

275e378e9deb08a08954c3d73cb4ef8bb72464c2

[ "MIT" ]

2

2021-11-02T10:49:02.000Z

2022-02-17T11:38:15.000Z

tests/__init__.py

iboraham/changepoint_detector

275e378e9deb08a08954c3d73cb4ef8bb72464c2

[ "MIT" ]

38

2021-08-03T17:28:55.000Z

2021-08-21T14:52:01.000Z

tests/__init__.py

iboraham/online_changepoint_detector

275e378e9deb08a08954c3d73cb4ef8bb72464c2

[ "MIT" ]

null

import main main.run()

6

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null

0

1

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1

0

5

f1b1d4cd97ab99345b89ce0a5f23bc1440605951

6,080

py

Python

eland/tests/ml/test_imported_ml_model_pytest.py

redNixon/eland

1b9cb1db6d30f0662fe3679c7bb31e2c0865f0c3

[ "Apache-2.0" ]

null

eland/tests/ml/test_imported_ml_model_pytest.py

redNixon/eland

1b9cb1db6d30f0662fe3679c7bb31e2c0865f0c3

[ "Apache-2.0" ]

null

eland/tests/ml/test_imported_ml_model_pytest.py

redNixon/eland

1b9cb1db6d30f0662fe3679c7bb31e2c0865f0c3

[ "Apache-2.0" ]

null

# Copyright 2020 Elasticsearch BV # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import numpy as np from sklearn import datasets from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor from xgboost import XGBRegressor, XGBClassifier from eland.ml import ImportedMLModel from eland.tests import ES_TEST_CLIENT class TestImportedMLModel: def test_decision_tree_classifier(self): # Train model training_data = datasets.make_classification(n_features=5) classifier = DecisionTreeClassifier() classifier.fit(training_data[0], training_data[1]) # Get some test results test_data = [[0.1, 0.2, 0.3, -0.5, 1.0], [1.6, 2.1, -10, 50, -1.0]] test_results = classifier.predict(test_data) # Serialise the models to Elasticsearch feature_names = ["f0", "f1", "f2", "f3", "f4"] model_id = "test_decision_tree_classifier" es_model = ImportedMLModel( ES_TEST_CLIENT, model_id, classifier, feature_names, overwrite=True ) es_results = es_model.predict(test_data) np.testing.assert_almost_equal(test_results, es_results, decimal=4) # Clean up es_model.delete_model() def test_decision_tree_regressor(self): # Train model training_data = datasets.make_regression(n_features=5) regressor = DecisionTreeRegressor() regressor.fit(training_data[0], training_data[1]) # Get some test results test_data = [[0.1, 0.2, 0.3, -0.5, 1.0], [1.6, 2.1, -10, 50, -1.0]] test_results = regressor.predict(test_data) # Serialise the models to Elasticsearch feature_names = ["f0", "f1", "f2", "f3", "f4"] model_id = "test_decision_tree_regressor" es_model = ImportedMLModel( ES_TEST_CLIENT, model_id, regressor, feature_names, overwrite=True ) es_results = es_model.predict(test_data) np.testing.assert_almost_equal(test_results, es_results, decimal=4) # Clean up es_model.delete_model() def test_random_forest_classifier(self): # Train model training_data = datasets.make_classification(n_features=5) classifier = RandomForestClassifier() classifier.fit(training_data[0], training_data[1]) # Get some test results test_data = [[0.1, 0.2, 0.3, -0.5, 1.0], [1.6, 2.1, -10, 50, -1.0]] test_results = classifier.predict(test_data) # Serialise the models to Elasticsearch feature_names = ["f0", "f1", "f2", "f3", "f4"] model_id = "test_random_forest_classifier" es_model = ImportedMLModel( ES_TEST_CLIENT, model_id, classifier, feature_names, overwrite=True ) es_results = es_model.predict(test_data) np.testing.assert_almost_equal(test_results, es_results, decimal=4) # Clean up es_model.delete_model() def test_random_forest_regressor(self): # Train model training_data = datasets.make_regression(n_features=5) regressor = RandomForestRegressor() regressor.fit(training_data[0], training_data[1]) # Get some test results test_data = [[0.1, 0.2, 0.3, -0.5, 1.0], [1.6, 2.1, -10, 50, -1.0]] test_results = regressor.predict(test_data) # Serialise the models to Elasticsearch feature_names = ["f0", "f1", "f2", "f3", "f4"] model_id = "test_random_forest_regressor" es_model = ImportedMLModel( ES_TEST_CLIENT, model_id, regressor, feature_names, overwrite=True ) es_results = es_model.predict(test_data) np.testing.assert_almost_equal(test_results, es_results, decimal=4) # Clean up es_model.delete_model() def test_xgb_classifier(self): # Train model training_data = datasets.make_classification(n_features=5) classifier = XGBClassifier() classifier.fit(training_data[0], training_data[1]) # Get some test results test_data = [[0.1, 0.2, 0.3, -0.5, 1.0], [1.6, 2.1, -10, 50, -1.0]] test_results = classifier.predict(np.asarray(test_data)) # Serialise the models to Elasticsearch feature_names = ["f0", "f1", "f2", "f3", "f4"] model_id = "test_xgb_classifier" es_model = ImportedMLModel( ES_TEST_CLIENT, model_id, classifier, feature_names, overwrite=True ) es_results = es_model.predict(test_data) np.testing.assert_almost_equal(test_results, es_results, decimal=4) # Clean up es_model.delete_model() def test_xgb_regressor(self): # Train model training_data = datasets.make_regression(n_features=5) regressor = XGBRegressor() regressor.fit(training_data[0], training_data[1]) # Get some test results test_data = [[0.1, 0.2, 0.3, -0.5, 1.0], [1.6, 2.1, -10, 50, -1.0]] test_results = regressor.predict(np.asarray(test_data)) # Serialise the models to Elasticsearch feature_names = ["f0", "f1", "f2", "f3", "f4"] model_id = "test_xgb_regressor" es_model = ImportedMLModel( ES_TEST_CLIENT, model_id, regressor, feature_names, overwrite=True ) es_results = es_model.predict(test_data) np.testing.assert_almost_equal(test_results, es_results, decimal=4) # Clean up es_model.delete_model()

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null

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5

f1d070ba2314967f762483d0a1ec5c2b7eefc89b

42,896

py

Python

census_geocoder/metaclasses.py

insightindustry/census-geocoder

fa2763e82135f2cdea91ab9431ce61769a778296

[ "MIT" ]

2

2021-12-29T04:34:48.000Z

2022-01-11T18:23:33.000Z

census_geocoder/metaclasses.py

insightindustry/census-geocoder

fa2763e82135f2cdea91ab9431ce61769a778296

[ "MIT" ]

3

2021-08-19T18:47:55.000Z

2021-12-28T17:50:43.000Z

census_geocoder/metaclasses.py

insightindustry/census-geocoder

fa2763e82135f2cdea91ab9431ce61769a778296

[ "MIT" ]

null

""" ################################### census_geocoder/metaclasses.py ################################### Defines the metaclasses that are used throughout the library. """ import os from abc import ABC, abstractmethod import csv import json import requests from validator_collection import validators from backoff_utils import backoff from census_geocoder import errors from census_geocoder.constants import CENSUS_API_URL, BENCHMARKS, VINTAGES, LAYERS DEFAULT_BENCHMARK = os.environ.get('CENSUS_GEOCODER_BENCHMARK', 'CURRENT') DEFAULT_VINTAGE = os.environ.get('CENSUS_GEOCODER_VINTAGE', 'CURRENT') DEFAULT_LAYERS = os.environ.get('CENSUS_GEOCODER_LAYERS', 'all') def parse_benchmark_vintage_layers(benchmark = DEFAULT_BENCHMARK, vintage = DEFAULT_VINTAGE, layers = DEFAULT_LAYERS): """Parse the benchmark and vintage received. :param benchmark: The :term:`Benchmark` value to parse into its canonical form. Defaults to ``CURRENT`` unless overridden by the ``CENSUS_GEOCODER_BENCHMARK`` environment variable. :type benchmark: :class:`str <python:str>` :param vintage: The :term:`Vintage` value to parse into its canonical form. Defaults to ``CURRENT`` unless overridden by the ``CENSUS_GEOCODER_VINTAGE`` environment variable. :type vintage: :class:`str <python:str>` :param layers: The :term:`Layers <Layer>` that should be parsed into its canonical form. Defaults to ``all`` unless overridden by the ``CENSUS_GEOCODER_LAYERS`` environment variable. :type layers: :class:`str <python:str>` :returns: The canonical ``(benchmark, vintage, layers)``. :rtype: :class:`tuple <python:tuple>` of :class:`str <python:str>`, :class:`str <python:str>`, and :class:`str <python:str>` :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized within the ``benchmark`` specified """ target_benchmark = validators.string(benchmark, allow_empty = False).upper() benchmark = BENCHMARKS.get(target_benchmark, None) if not benchmark: raise errors.UnrecognizedBenchmarkError( f'Benchmark ({target_benchmark}) is not a recognized benchmark.' ) possible_vintages = VINTAGES.get(benchmark, None) target_vintage = validators.string(vintage, allow_empty = False).upper() vintage = possible_vintages.get(target_vintage, None) if not vintage: raise errors.UnrecognizedVintageError( f'Vintage ({target_vintage}) is not a recognized/available vintage within the' f' "{benchmark}" benchmark.' ) if layers != 'all': layer_set = LAYERS.get(vintage, None) if layer_set: layer_set_lowercase = {} for key in layer_set: layer_set_lowercase[key.lower()] = layer_set.get(key) layer_targets = layers.split(',') layer_targets = [x.strip() for x in layer_targets] layers = [] for layer in layer_targets: layer_lower = layer.lower() if layer_lower in layer_set_lowercase: layers.append(str(layer_set_lowercase.get(layer_lower, None))) layers = ','.join(layers) else: layers = None return benchmark, vintage, layers def check_length(file_): """Returns the number of records in the indicated file. :param file_: The filename of the file to check. Expects a CSV or TXT file. :type file_: :class:`str <python:str>` :returns: The number of records in the indicated file. :rtype: :class:`int <python:int>` """ file_ = validators.file_exists(file_, allow_empty = False) with open(file_, 'r') as file_object: csv_reader = csv.reader(file_object) row_count = sum(1 for row in csv_reader) return row_count class BaseEntity(ABC): """Abstract base clase for geographic entities that may or may not be supported by the API.""" @property @abstractmethod def entity_type(self): """The type of geographic entity that the object represents. Supports either: ``locations`` or ``geographies``. :rtype: :class:`str <python:str>` """ raise NotImplementedError() @classmethod @abstractmethod def from_dict(cls, as_dict): """Create an instance of the geographic entity from its :class:`dict <python:dict>` representation. :param as_dict: The :class:`dict <python:dict>` representation of the geographic entity. :type as_dict: :class:`dict <python:dict>` :returns: An instance of the geographic entity. :rtype: :class:`GeographicEntity` """ raise NotImplementedError() @classmethod def from_json(cls, as_json): """Create an instance of the geographic entity from its JSON representation. :param as_json: The JSON representation of the geographic entity. :type as_json: :class:`str <python:str>`, :class:`dict <python:dict>`, or :class:`list <python:list>` :returns: An instance of the geographic entity. :rtype: :class:`GeographicEntity` """ as_dict = validators.json(as_json, allow_empty = False) return cls.from_dict(as_dict) @classmethod @abstractmethod def from_csv_record(cls, csv_record): """Create an instance of the geographic entity from its CSV record. :param csv_record: The list of columns for the CSV record. :type csv_record: :class:`list <python:list>` of :class:`str <python:str>` :returns: An instance of the geographic entity. :rtype: :class:`GeographicEntity` """ raise NotImplementedError() @abstractmethod def to_dict(self): """Returns a :class:`dict <python:dict>` representation of the geographic entity. .. note:: The :class:`dict <python:dict>` representation matches the JSON structure for the US Census Geocoder API. This is a not-very-pythonic :class:`dict <python:dict>` structure, but at least this ensures idempotency. :returns: :class:`dict <python:dict>` representation of the entity. :rtype: :class:`dict <python:dict>` """ raise NotImplementedError() def to_json(self): """Returns a JSON representation of the geographic entity. .. note:: The JSON representation matches the JSON structure for the US Census Geocoder API. This is a not-very-pythonic structure, but at least this ensures idempotency. :returns: :class:`str <python:str>` representation of the entity. :rtype: :class:`str <python:str>` """ as_dict = self.to_dict() return json.dumps(as_dict) class GeographicEntity(BaseEntity): """Abstract base class for geographic entities that *are* supported by the API. """ @classmethod def _get_one_line(cls, one_line, benchmark = DEFAULT_BENCHMARK, vintage = DEFAULT_VINTAGE, layers = DEFAULT_LAYERS): """Return data from a single-line address. :param one_line: The one-line address to geocode. :type one_line: :class:`str <python:str>` :param benchmark: The name of the :term:`benchmark` of data to return. The default value is determined by the ``CENSUS_GEOCODER_BENCHMARK`` environment variable, and if that is not set defaults to ``'Current'`` which represents the current default benchmark, per the `Census Geocoder API`_. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` :type benchmark: :class:`str <python:str>` :param vintage: The vintage of Census data for which data should be returned. The default value is determined by the ``CENSUS_GEOCODER_VINTAGE`` environment variable, and if that is not set defaults to ``'Current'`` which represents the default vintage per the `Census Geocoder API`_. Acceptable values are dependent on the ``benchmark`` specified, as per the table below: +--------------+---------------------+---------------------+ | | BENCHMARKS | + +---------------------+---------------------+ | | Current | Census2020 | +==============+=====================+=====================+ | **VINTAGES** | Current | Census2020 | + +---------------------+---------------------+ | | Census2020 | Census2010 | + +---------------------+---------------------+ | | ACS2019 | | + +---------------------+---------------------+ | | ACS2018 | | + +---------------------+---------------------+ | | ACS2017 | | + +---------------------+---------------------+ | | Census2010 | | +--------------+---------------------+---------------------+ :type vintage: :class:`str <python:str>` :param layers: The set of geographic layers to return for the request. The default value is determined by the ``CENSUS_GEOCODER_LAYERS`` environment variable, and if that is not set defaults to ``'all'``. .. seealso:: * :doc:`Geographies <geographies>` :ref:`Benchmarks, Vintages, and Layers <benchmarks_vintages_and_layers>` :type layers: :class:`str <python:str>` :rtype: :class:`dict <python:dict>` :raises CensusAPIError: if the Census Geocoder API returned an error :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized """ one_line = validators.string(one_line) benchmark, vintage, layers = parse_benchmark_vintage_layers(benchmark, vintage, layers) parameters = { 'address': one_line, 'benchmark': benchmark, 'vintage': vintage, 'format': 'json' } if layers: parameters['layers'] = layers instance = cls() url = f'{CENSUS_API_URL}/geocoder/{instance.entity_type}/onelineaddress' result = backoff(requests.get, args = [url], kwargs = {'params': parameters}, max_tries = 5, max_delay = 10) if 'Specify street' in result.text: raise errors.ConfigurationError(f'Did not provide a properly parametrized ' 'address.') elif errors.EntityNotFoundError.evaluate(result, request_type = instance.entity_type): raise errors.EntityNotFoundError( f'Census Geocoder API was unable to find a matching geographic entity.' ) elif result.status_code >= 400: raise errors.CensusAPIError( f'Census Geocoder API returned status code {result.status_code} with ' f'message: "{result.text}".' ) return result.json() @classmethod def _get_address(cls, street_1 = None, city = None, state = None, zip_code = None, benchmark = DEFAULT_BENCHMARK, vintage = DEFAULT_VINTAGE, layers = DEFAULT_LAYERS): """Return data from a :term:`parametrized address`. :param street_1: A street address, e.g. ``'4600 Silver Hill Rd'``. Defaults to :obj:`None <python:None>`. :type street_1: :class:`str <python:str>` / :obj:`None <python:None>` :param street_2: A secondary component of a street address, e.g. ``'Floor 3'``. Defaults to :obj:`None <python:None>`. :type street_2: :class:`str <python:str>` / :obj:`None <python:None>` :param street_3: A tertiary component of a street address, e.g. ``'Apt. B'``. Defaults to :obj:`None <python:None>`. :type street_3: :class:`str <python:str>` / :obj:`None <python:None>` :param city: The city or town of a street address, e.g. ``'Washington'``. Defaults to :obj:`None <python:None>`. :type city: :class:`str <python:str>` / :obj:`None <python:None>` :param state: The state or territory of a street address, e.g. ``'DC'``. Defaults to :obj:`None <python:None>`. :type state: :class:`str <python:str>` / :obj:`None <python:None>` :param zip_code: The zip code (or zip code + 4) of a street address, e.g. ``'20233'``. Defaults to :obj:`None <python:None>`. :type zip_code: :class:`str <python:str>` / :obj:`None <python:None>` :param benchmark: The name of the :term:`benchmark` of data to return. The default value is determined by the ``CENSUS_GEOCODER_BENCHMARK`` environment variable, and if that is not set defaults to ``'Current'`` which represents the current default benchmark, per the `Census Geocoder API`_. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` :type benchmark: :class:`str <python:str>` :param vintage: The vintage of Census data for which data should be returned. The default value is determined by the ``CENSUS_GEOCODER_VINTAGE`` environment variable, and if that is not set defaults to ``'Current'`` which represents the default vintage per the `Census Geocoder API`_. Acceptable values are dependent on the ``benchmark`` specified, as per the table below: +--------------+---------------------+---------------------+ | | BENCHMARKS | + +---------------------+---------------------+ | | Current | Census2020 | +==============+=====================+=====================+ | **VINTAGES** | Current | Census2020 | + +---------------------+---------------------+ | | Census2020 | Census2010 | + +---------------------+---------------------+ | | ACS2019 | | + +---------------------+---------------------+ | | ACS2018 | | + +---------------------+---------------------+ | | ACS2017 | | + +---------------------+---------------------+ | | Census2010 | | +--------------+---------------------+---------------------+ :type vintage: :class:`str <python:str>` :param layers: The set of geographic layers to return for the request. The default value is determined by the ``CENSUS_GEOCODER_LAYERS`` environment variable, and if that is not set defaults to ``'all'``. .. seealso:: * :doc:`Geographies <geographies>` :ref:`Benchmarks, Vintages, and Layers <benchmarks_vintages_and_layers>` :type layers: :class:`str <python:str>` :rtype: :class:`dict <python:dict>` :raises NoAddressError: if the address information is completely empty :raises CensusAPIError: if the Census Geocoder API returned an error :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized """ street_1 = validators.string(street_1, allow_empty = True) city = validators.string(city, allow_empty = True) state = validators.string(state, allow_empty = True) zip_code = validators.string(zip_code, allow_empty = True) benchmark, vintage, layers = parse_benchmark_vintage_layers(benchmark, vintage, layers) parameters = { 'benchmark': benchmark, 'vintage': vintage, 'format': 'json' } if layers: parameters['layers'] = layers is_valid = False if street_1: is_valid = True parameters['street'] = street_1 if city: is_valid = True parameters['city'] = city if state: is_valid = True parameters['state'] = state if zip_code: is_valid = True parameters['zip'] = zip_code if not is_valid: raise errors.NoAddressError() instance = cls() url = f'{CENSUS_API_URL}/geocoder/{instance.entity_type}/address' result = backoff(requests.get, args = [url], kwargs = {'params': parameters}, max_tries = 5, max_delay = 10) if 'Specify street' in result.text: raise errors.ConfigurationError(f'Did not provide a properly parametrized ' f'address.') elif errors.EntityNotFoundError.evaluate(result, request_type = instance.entity_type): raise errors.EntityNotFoundError( f'Census Geocoder API was unable to find a matching geographic entity.' ) elif result.status_code >= 400: raise errors.CensusAPIError( f'Census Geocoder API returned status code {result.status_code} with ' f'message: "{result.text}".' ) return result.json() @classmethod def _get_batch_addresses(cls, file_, benchmark = DEFAULT_BENCHMARK, vintage = DEFAULT_VINTAGE, layers = DEFAULT_LAYERS): """Return data from a batch file in CSV, XLS/X, TXT, or DAT format. :param file_: The name of a file in CSV, XLS/X, DAT, or TXT format. Expects the file to have the following columns *without a header row*: * Unique ID * Street Address * City * State * Zip Code :type file_: :class:`str <python:str>` :param benchmark: The name of the :term:`benchmark` of data to return. Defaults to ``'Current'`` which represents the current default benchmark, per the Census Geocoder API. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` :type benchmark: :class:`str <python:str>` :param vintage: The vintage of Census data for which data should be returned. Defaults to ``'Current'`` which represents the current default vintage per the Census Geocoder API. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` * ``'ACS2019'`` * ``'ACS2018'`` * ``'ACS2017'`` * ``'Census2010'`` :type vintage: :class:`str <python:str>` :param layers: The set of geographic layers to return for the request. Defaults to ``'all'``. :type layers: :class:`str <python:str>` :rtype: :class:`list <python:list>` of :class:`GeographicEntity` :raises NoFileProvidedError: if no ``file_`` is provided :raises FileNotFoundError: if ``file_`` does not exist on the filesystem :raises BatchSizeTooLargeError: if ``file_`` contains more than 10,000 records :raises CensusAPIError: if the Census Geocoder API returned an error :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized """ benchmark, vintage, layers = parse_benchmark_vintage_layers(benchmark, vintage, layers) file_ = validators.file_exists(file_, allow_empty = False) file_length = check_length(file_) if file_length > 10000: raise errors.BatchSizeTooLargeError(f'Batch Too Large. Max of 10,000 entries ' f'supported. File contains {file_length}') parameters = { 'benchmark': benchmark, 'vintage': vintage, 'format': 'json' } if layers: parameters['layers'] = layers instance = cls() url = f'{CENSUS_API_URL}/geocoder/{instance.entity_type}/addressbatch' with open(file_, 'rb') as file_object: files = { 'addressFile': (file_, file_object) } result = backoff(requests.post, args = [url], kwargs = { 'files': files, 'params': parameters }, max_tries = 5, max_delay = 10) if result.status_code >= 400 and 'Malformed input' in result.text: raise errors.MalformedBatchFileError('The batch file submitted did not have ' 'the expected/required structure. Please' ' check and resubmit.') elif result.status_code >= 400: raise errors.CensusAPIError( f'Census Geocoder API returned status code {result.status_code} with ' f'message: "{result.text}".' ) content = result.content.decode('utf-8') csv_reader = csv.reader(content.splitlines(), delimiter = ',') csv_list = list(csv_reader) return csv_list @classmethod def _get_coordinates(cls, longitude, latitude, benchmark = DEFAULT_BENCHMARK, vintage = DEFAULT_VINTAGE, layers = DEFAULT_LAYERS): """Return data from a pair of geographic coordinates (longitude / latitude). :param longitude: The longitude coordinate. :type longitude: numeric :param latitude: The latitude coordinate. :type latitude: numeric :param benchmark: The name of the :term:`benchmark` of data to return. Defaults to ``'Current'`` which represents the current default benchmark, per the Census Geocoder API. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` :type benchmark: :class:`str <python:str>` :param vintage: The vintage of Census data for which data should be returned. Defaults to ``'Current'`` which represents the current default vintage per the Census Geocoder API. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` * ``'ACS2019'`` * ``'ACS2018'`` * ``'ACS2017'`` * ``'Census2010'`` :type vintage: :class:`str <python:str>` :param layers: The set of geographic layers to return for the request. Defaults to ``'all'``. :type layers: :class:`str <python:str>` :rtype: :class:`dict <python:dict>` :raises CensusAPIError: if the Census Geocoder API returned an error :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized """ longitude = validators.decimal(longitude, allow_empty = False) latitude = validators.decimal(latitude, allow_empty = False) benchmark, vintage, layers = parse_benchmark_vintage_layers(benchmark, vintage, layers) parameters = { 'x': '{0:.6f}'.format(longitude), 'y': '{0:.6f}'.format(latitude), 'benchmark': benchmark, 'vintage': vintage, 'format': 'json' } if layers: parameters['layers'] = layers instance = cls() url = f'{CENSUS_API_URL}/geocoder/geographies/coordinates' result = backoff(requests.get, args = [url], kwargs = {'params': parameters}, max_tries = 5, max_delay = 10) if errors.EntityNotFoundError.evaluate(result, request_type = 'geographies'): raise errors.EntityNotFoundError( f'Census Geocoder API was unable to find a matching geogrpahic entity.' ) elif result.status_code >= 400: raise errors.CensusAPIError( f'Census Geocoder API returned status code {result.status_code} with ' f'message: "{result.text}".' ) return result.json() @classmethod def from_address(cls, *args, **kwargs): """Return data from an adddress, supplied either as a single :term:`one-line address` or a :term:`parametrized address`. :param one_line: A single-line address, e.g. ``'4600 Silver Hill Rd, Washington, DC 20233'``. Defaults to :obj:`None <python:None>`. :type one_line: :class:`str <python:str>` / :obj:`None <python:None>` :param street_1: A street address, e.g. ``'4600 Silver Hill Rd'``. Defaults to :obj:`None <python:None>`. :type street_1: :class:`str <python:str>` / :obj:`None <python:None>` :param street_2: A secondary component of a street address, e.g. ``'Floor 3'``. Defaults to :obj:`None <python:None>`. :type street_2: :class:`str <python:str>` / :obj:`None <python:None>` :param street_3: A tertiary component of a street address, e.g. ``'Apt. B'``. Defaults to :obj:`None <python:None>`. :type street_3: :class:`str <python:str>` / :obj:`None <python:None>` :param city: The city or town of a street address, e.g. ``'Washington'``. Defaults to :obj:`None <python:None>`. :type city: :class:`str <python:str>` / :obj:`None <python:None>` :param state: The state or territory of a street address, e.g. ``'DC'``. Defaults to :obj:`None <python:None>`. :type state: :class:`str <python:str>` / :obj:`None <python:None>` :param zip_code: The zip code (or zip code + 4) of a street address, e.g. ``'20233'``. Defaults to :obj:`None <python:None>`. :type zip_code: :class:`str <python:str>` / :obj:`None <python:None>` :param benchmark: The name of the :term:`benchmark` of data to return. The default value is determined by the ``CENSUS_GEOCODER_BENCHMARK`` environment variable, and if that is not set defaults to ``'Current'`` which represents the current default benchmark, per the `Census Geocoder API`_. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` :type benchmark: :class:`str <python:str>` :param vintage: The vintage of Census data for which data should be returned. The default value is determined by the ``CENSUS_GEOCODER_VINTAGE`` environment variable, and if that is not set defaults to ``'Current'`` which represents the default vintage per the `Census Geocoder API`_. Acceptable values are dependent on the ``benchmark`` specified, as per the table below: +--------------+---------------------+---------------------+ | | BENCHMARKS | + +---------------------+---------------------+ | | Current | Census2020 | +==============+=====================+=====================+ | **VINTAGES** | Current | Census2020 | + +---------------------+---------------------+ | | Census2020 | Census2010 | + +---------------------+---------------------+ | | ACS2019 | | + +---------------------+---------------------+ | | ACS2018 | | + +---------------------+---------------------+ | | ACS2017 | | + +---------------------+---------------------+ | | Census2010 | | +--------------+---------------------+---------------------+ :type vintage: :class:`str <python:str>` :param layers: The set of geographic layers to return for the request. The default value is determined by the ``CENSUS_GEOCODER_LAYERS`` environment variable, and if that is not set defaults to ``'all'``. .. seealso:: * :doc:`Geographies <geographies>` :ref:`Benchmarks, Vintages, and Layers <benchmarks_vintages_and_layers>` :type layers: :class:`str <python:str>` .. note:: If more than one address-related parameter are supplied, this method will assume that a :term:`parametrized address` is provided. :returns: A given geographic entity. :rtype: :class:`GeographicEntity` :raises NoAddressError: if no address information is supplied :raises EntityNotFoundError: if no geographic entity was found matching the address supplied :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized """ if not args and not kwargs: raise errors.NoAddressError('No address information supplied.') if args: one_line = args[0] else: one_line = kwargs.get('one_line', None) street_1 = kwargs.get('street_1', None) city = kwargs.get('city', None) state = kwargs.get('state', None) zip_code = kwargs.get('zip_code', None) benchmark = kwargs.get('benchmark', DEFAULT_BENCHMARK) vintage = kwargs.get('vintage', DEFAULT_VINTAGE) layers = kwargs.get('layers', DEFAULT_LAYERS) if one_line: result = cls._get_one_line(one_line, benchmark = benchmark, vintage = vintage, layers = layers) else: result = cls._get_address(street_1 = street_1, city = city, state = state, zip_code = zip_code, benchmark = benchmark, vintage = vintage, layers = layers) return cls.from_json(result) @classmethod def from_batch(cls, *args, **kwargs): """Return geographic entities for a batch collection of inputs. :param file_: The name of a file in CSV, XLS/X, DAT, or TXT format. Expects the file to have the following columns *without a header row*: * Unique ID * Street Address * City * State * Zip Code :type file_: :class:`str <python:str>` :param benchmark: The name of the :term:`benchmark` of data to return. The default value is determined by the ``CENSUS_GEOCODER_BENCHMARK`` environment variable, and if that is not set defaults to ``'Current'`` which represents the current default benchmark, per the `Census Geocoder API`_. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` :type benchmark: :class:`str <python:str>` :param vintage: The vintage of Census data for which data should be returned. The default value is determined by the ``CENSUS_GEOCODER_VINTAGE`` environment variable, and if that is not set defaults to ``'Current'`` which represents the default vintage per the `Census Geocoder API`_. Acceptable values are dependent on the ``benchmark`` specified, as per the table below: +--------------+---------------------+---------------------+ | | BENCHMARKS | + +---------------------+---------------------+ | | Current | Census2020 | +==============+=====================+=====================+ | **VINTAGES** | Current | Census2020 | + +---------------------+---------------------+ | | Census2020 | Census2010 | + +---------------------+---------------------+ | | ACS2019 | | + +---------------------+---------------------+ | | ACS2018 | | + +---------------------+---------------------+ | | ACS2017 | | + +---------------------+---------------------+ | | Census2010 | | +--------------+---------------------+---------------------+ :type vintage: :class:`str <python:str>` :param layers: The set of geographic layers to return for the request. The default value is determined by the ``CENSUS_GEOCODER_LAYERS`` environment variable, and if that is not set defaults to ``'all'``. .. seealso:: * :doc:`Geographies <geographies>` :ref:`Benchmarks, Vintages, and Layers <benchmarks_vintages_and_layers>` :type layers: :class:`str <python:str>` :returns: A collection of geographic entities. :rtype: :class:`list <python:list>` of :class:`GeographicEntity` :raises NoFileProvidedError: if no ``file_`` is provided :raises FileNotFoundError: if ``file_`` does not exist on the filesystem :raises BatchSizeTooLargeError: if ``file_`` contains more than 10,000 records :raises EntityNotFoundError: if no geographic entity was found matching the address supplied :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized """ if args: file_ = args[0] else: file_ = kwargs.get('file_', None) if not file_: raise errors.NoFileProvidedError() file_ = validators.file_exists(file_, allow_empty = False) benchmark = kwargs.get('benchmark', DEFAULT_BENCHMARK) vintage = kwargs.get('vintage', DEFAULT_VINTAGE) layers = kwargs.get('layers', DEFAULT_LAYERS) result = cls._get_batch_addresses(file_ = file_, benchmark = benchmark, vintage = vintage, layers = layers) return [cls.from_csv_record(x) for x in result] @classmethod def from_coordinates(cls, *args, **kwargs): """Return data from a pair of geographic coordinates (longitude and latitude). :param longitude: The longitude coordinate. :type longitude: numeric :param latitude: The latitude coordinate. :type latitude: numeric :param benchmark: The name of the :term:`benchmark` of data to return. The default value is determined by the ``CENSUS_GEOCODER_BENCHMARK`` environment variable, and if that is not set defaults to ``'Current'`` which represents the current default benchmark, per the `Census Geocoder API`_. Accepts the following values: * ``'Current'`` (default) * ``'Census2020'`` :type benchmark: :class:`str <python:str>` :param vintage: The vintage of Census data for which data should be returned. The default value is determined by the ``CENSUS_GEOCODER_VINTAGE`` environment variable, and if that is not set defaults to ``'Current'`` which represents the default vintage per the `Census Geocoder API`_. Acceptable values are dependent on the ``benchmark`` specified, as per the table below: +--------------+---------------------+---------------------+ | | BENCHMARKS | + +---------------------+---------------------+ | | Current | Census2020 | +==============+=====================+=====================+ | **VINTAGES** | Current | Census2020 | + +---------------------+---------------------+ | | Census2020 | Census2010 | + +---------------------+---------------------+ | | ACS2019 | | + +---------------------+---------------------+ | | ACS2018 | | + +---------------------+---------------------+ | | ACS2017 | | + +---------------------+---------------------+ | | Census2010 | | +--------------+---------------------+---------------------+ :type vintage: :class:`str <python:str>` :param layers: The set of geographic layers to return for the request. The default value is determined by the ``CENSUS_GEOCODER_LAYERS`` environment variable, and if that is not set defaults to ``'all'``. .. seealso:: * :doc:`Geographies <geographies>` :ref:`Benchmarks, Vintages, and Layers <benchmarks_vintages_and_layers>` :type layers: :class:`str <python:str>` .. note:: If more than one address-related parameter are supplied, this method will assume that a :term:`parametrized address` is provided. :returns: A given geographic entity. :rtype: :class:`GeographicEntity` :raises NoAddressError: if no address information is supplied :raises EntityNotFound: if no geographic entity was found matching the address supplied :raises UnrecognizedBenchmarkError: if the ``benchmark`` supplied is not recognized :raises UnrecognizedVintageError: if the ``vintage`` supplied is not recognized """ if not args and not kwargs: raise errors.NoAddressError('No coordinates supplied.') try: longitude = args[0] except (IndexError, TypeError): longitude = kwargs.get('longitude', None) try: latitude = args[1] except (IndexError, TypeError): latitude = kwargs.get('latitude', None) if not longitude and not latitude: raise errors.NoAddressError('No coordinates supplied.') elif not longitude: raise errors.NoAddressError('No longitude supplied.') elif not latitude: raise errors.NoAddressError('No latitude supplied.') longitude = validators.decimal(longitude, allow_empty = False) latitude = validators.decimal(latitude, allow_empty = False) benchmark = kwargs.get('benchmark', DEFAULT_BENCHMARK) vintage = kwargs.get('vintage', DEFAULT_VINTAGE) layers = kwargs.get('layers', DEFAULT_LAYERS) result = cls._get_coordinates(longitude = longitude, latitude = latitude, benchmark = benchmark, vintage = vintage, layers = layers) return cls.from_json(result) def inspect(self, as_census_fields = False): """Produce a list of the entity's properties that have values. :param as_census_fields: If ``True``, return property names as they appear in Census databases or the output of the `Census Geocoder API`_. If ``False``, return properties as they are defined on the **Census Geocoder** objects. Defaults to ``False``. :type as_census_fields: :class:`bool <python:bool>` :rtype: :class:`list <python:list>` of :class:`str <python:str>` """ raise NotImplementedError()

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9e3406ab6ab71966edd4c82582e5083309e5376c

4,745

py

Python

3-AI-for-Medical-Treatment/week2-medical-question-answering/NegBio/negbio/pipeline/dner_mm.py

pranshuag9/AI-for-Medicine

daba0054e14c6b5ececd35d700244aa978e84b11

[ "Apache-2.0" ]

1

2020-09-21T22:05:19.000Z

3-AI-for-Medical-Treatment/week2-medical-question-answering/assignment/NegBio/negbio/pipeline/dner_mm.py

pranshuag9/AI-for-Medicine

daba0054e14c6b5ececd35d700244aa978e84b11

[ "Apache-2.0" ]

null

3-AI-for-Medical-Treatment/week2-medical-question-answering/assignment/NegBio/negbio/pipeline/dner_mm.py

pranshuag9/AI-for-Medicine

daba0054e14c6b5ececd35d700244aa978e84b11

[ "Apache-2.0" ]

null

import collections import itertools import logging import re import bioc def remove_newline(s): return re.sub(r'[\n\r]', ' ', s) def adapt_concept_index(index): m = re.match(r"'.*?'", index) if m: return index[1:-1] m = re.match(r"'.*", index) if m: return index[1:] return index def run_metamap_col(collection, mm, cuis=None, extra_args=None): """ Get CUIs from metamap. Args: collection(BioCCollection): mm(MetaMap): MetaMap instance Returns: BioCCollection """ try: annIndex = itertools.count() sentence_map = collections.OrderedDict() for document in collection.documents: for passage in document.passages: for sentence in passage.sentences: sentence_map['{}-{}'.format(document.id.replace('.', '-'), sentence.offset)] = (passage, sentence) sents = [] ids = [] for k in sentence_map: ids.append(k) sents.append(remove_newline(sentence_map[k][1].text)) if extra_args is None: concepts, error = mm.extract_concepts(sents, ids) else: concepts, error = mm.extract_concepts(sents, ids, **extra_args) if error is None: for concept in concepts: concept_index = adapt_concept_index(concept.index) try: if cuis is not None: # if no CUI is returned for this concept - skip it concept_cui = getattr(concept, 'cui', None) if concept_cui not in cuis: continue m = re.match(r'(\d+)/(\d+)', concept.pos_info) if m: passage = sentence_map[concept_index][0] sentence = sentence_map[concept_index][1] start = int(m.group(1)) - 1 length = int(m.group(2)) ann = bioc.BioCAnnotation() ann.id = str(next(annIndex)) ann.infons['CUI'] = concept.cui ann.infons['semtype'] = concept.semtypes[1:-1] ann.infons['term'] = concept.preferred_name ann.infons['annotator'] = 'MetaMap' ann.add_location(bioc.BioCLocation(sentence.offset + start, length)) ann.text = sentence.text[start:start+length] passage.annotations.append(ann) except: logging.exception('') except: logging.exception("Cannot process %s", collection.source) return collection def run_metamap(document, mm, cuis=None): """ Get CUIs from metamap. Args: document(BioCDocument): mm(MetaMap): MetaMap instance Returns: BioCDocument """ try: annIndex = itertools.count() sentence_map = collections.OrderedDict() for passage in document.passages: for sentence in passage.sentences: sentence_map[str(sentence.offset)] = (passage, sentence) sents = [] ids = [] for k in sentence_map: ids.append(k) sents.append(remove_newline(sentence_map[k][1].text)) concepts, error = mm.extract_concepts(sents, ids) if error is None: for concept in concepts: concept_index = adapt_concept_index(concept.index) try: if cuis is not None and concept.cui not in cuis: continue m = re.match(r'(\d+)/(\d+)', concept.pos_info) if m: passage = sentence_map[concept_index][0] sentence = sentence_map[concept_index][1] start = int(m.group(1)) - 1 length = int(m.group(2)) ann = bioc.BioCAnnotation() ann.id = str(next(annIndex)) ann.infons['CUI'] = concept.cui ann.infons['semtype'] = concept.semtypes[1:-1] ann.infons['term'] = concept.preferred_name ann.infons['annotator'] = 'MetaMap' ann.add_location(bioc.BioCLocation(sentence.offset + start, length)) ann.text = sentence.text[start:start+length] passage.annotations.append(ann) except: logging.exception('') except: logging.exception("Cannot process %s", document.id) return document

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1

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null

0

1

0

5

9e3f0cb16e10a7bc48166105ad13d677f8358a40

1,518

py

Python

objects/test.py

kerven88/k8s-cluster-checker

99f4175086bc42793da6bca6c4ef25a9f8252c16

[ "Apache-2.0" ]

10

2020-08-06T11:40:46.000Z

2021-10-18T12:41:15.000Z

objects/test.py

kerven88/k8s-cluster-checker

99f4175086bc42793da6bca6c4ef25a9f8252c16

[ "Apache-2.0" ]

1

2021-01-29T02:42:16.000Z

2021-05-22T08:51:13.000Z

objects/test.py

kerven88/k8s-cluster-checker

99f4175086bc42793da6bca6c4ef25a9f8252c16

[ "Apache-2.0" ]

6

2020-09-10T05:51:06.000Z

2022-01-25T03:01:39.000Z

import unittest import warnings from modules.logging import Logger logger = Logger.get_logger('', '') class TestK8sClusterChecker(unittest.TestCase): def test_cluster(self): import cluster as cluster warnings.filterwarnings("ignore", category=ResourceWarning, message="unclosed.*<ssl.SSLSocket.*>") self.assertRaises(TypeError, cluster.call_all(True, True, logger), True) with self.assertRaises(Exception) as x: print("Exception ignored: {}".format(x.exception)) def test_nodes(self): import nodes as nodes warnings.filterwarnings("ignore", category=ResourceWarning, message="unclosed.*<ssl.SSLSocket.*>") with self.assertRaises(Exception) as x: print("Exception ignored: {}".format(x.exception)) def test_namespace(self): import namespace as namespace warnings.filterwarnings("ignore", category=ResourceWarning, message="unclosed.*<ssl.SSLSocket.*>") self.assertRaises(TypeError, namespace.call_all(True, 'all', True, logger), True) with self.assertRaises(Exception) as x: print("Exception ignored: {}".format(x.exception)) def test_pods(self): import pods as pods warnings.filterwarnings("ignore", category=ResourceWarning, message="unclosed.*<ssl.SSLSocket.*>") self.assertRaises(TypeError, pods.call_all(True, 'all', True, logger), True) with self.assertRaises(Exception) as x: print("Exception ignored: {}".format(x.exception))

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null

0

1

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null

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5

9e5d1aac687924b906e4fef7cdfc1adb74e0a3e0

525

py

Python

aims/ml/chemprop/__init__.py

Xiangyan93/AIMS

1d0d6de03ef79d3cbfe2cd244f12c41d18acb61d

[ "MIT" ]

3

2021-05-14T04:27:53.000Z

2022-01-11T17:47:20.000Z

aims/ml/chemprop/__init__.py

Xiangyan93/AIMS

1d0d6de03ef79d3cbfe2cd244f12c41d18acb61d

[ "MIT" ]

null

aims/ml/chemprop/__init__.py

Xiangyan93/AIMS

1d0d6de03ef79d3cbfe2cd244f12c41d18acb61d

[ "MIT" ]

null

import aims.ml.chemprop.data import aims.ml.chemprop.features import aims.ml.chemprop.models import aims.ml.chemprop.train # import aims.ml.chemprop.web import aims.ml.chemprop.args import aims.ml.chemprop.constants import aims.ml.chemprop.hyperparameter_optimization import aims.ml.chemprop.interpret import aims.ml.chemprop.nn_utils import aims.ml.chemprop.utils import aims.ml.chemprop.rdkit import aims.ml.chemprop.sklearn_predict import aims.ml.chemprop.sklearn_train from aims.ml.chemprop._version import __version__

29.166667

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0.206897

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525

17

52

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true

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1

0

null

0

1

0

1

0

5

9e61f1a9b94433fd0994a2b5e42284a50d6f68d1

85

py

Python

dash/map/__init__.py

defgsus/thegame

38a627d9108f1418b94b08831fd640dd87fbba83

[ "MIT" ]

1

2021-11-05T11:49:26.000Z

dash/map/__init__.py

defgsus/thegame

38a627d9108f1418b94b08831fd640dd87fbba83

[ "MIT" ]

null

dash/map/__init__.py

defgsus/thegame

38a627d9108f1418b94b08831fd640dd87fbba83

[ "MIT" ]

null

from .object import Object from .tilemap import TileMap from .objects import Objects

21.25

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85

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28.333333

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null

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1

0

1

0

1

0

5

9e9c45fd56f81fd0401c398898a7e89c1fcb8aee

71

py

Python

mak/libs/pyxx/cxx/grammar/expression/primary/id/__init__.py

motor-dev/Motor

98cb099fe1c2d31e455ed868cc2a25eae51e79f0

[ "BSD-3-Clause" ]

4

2015-05-13T16:28:36.000Z

2017-05-24T15:34:14.000Z

mak/libs/pyxx/cxx/grammar/expression/primary/id/__init__.py

motor-dev/Motor

98cb099fe1c2d31e455ed868cc2a25eae51e79f0

[ "BSD-3-Clause" ]

null

mak/libs/pyxx/cxx/grammar/expression/primary/id/__init__.py

motor-dev/Motor

98cb099fe1c2d31e455ed868cc2a25eae51e79f0

[ "BSD-3-Clause" ]

1

2017-03-21T08:28:07.000Z

from . import general from . import unqualified from . import qualified

23.666667

25

0.802817

9

71

6.333333

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true

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0

5

7b8c3158e2319cba197b5d5a118eeeca69b90889

243

py

Python

experimentor/core/exceptions.py

aquilesC/experimentor

1a70760912ef40f0e2aaee44ed1a1e5594fd5b45

[ "MIT" ]

4

2020-05-15T04:07:25.000Z

2020-09-30T22:20:46.000Z

experimentor/core/exceptions.py

aquilesC/experimentor

1a70760912ef40f0e2aaee44ed1a1e5594fd5b45

[ "MIT" ]

null

experimentor/core/exceptions.py

aquilesC/experimentor

1a70760912ef40f0e2aaee44ed1a1e5594fd5b45

[ "MIT" ]

null

class ExperimentorException(Exception): pass class ModelDefinitionException(ExperimentorException): pass class ExperimentDefinitionException(ExperimentorException): pass class DuplicatedParameter(ExperimentorException): pass

22.090909

59

0.82716

16

243

12.5625

0.4375

0.134328

0.298507

0

0.123457

243

11

60

22.090909

0.943662

0

0.5

0

1

0

true

0.5

0

0.5

0

1

0

1

null

0

1

0

null

0

1

0

5

7ba52e3ecb57391092cb42330e2ff3accc82ab40

75

py

Python

LINEBALI/__init__.py

cipul404/cipul

dea423b83381119c46f35be9c13e6daa38568603

[ "MIT" ]

1

2018-09-06T17:42:58.000Z

LINEBALI/__init__.py

cipul404/cipul

dea423b83381119c46f35be9c13e6daa38568603

[ "MIT" ]

null

LINEBALI/__init__.py

cipul404/cipul

dea423b83381119c46f35be9c13e6daa38568603

[ "MIT" ]

null

#-*- coding: utf-8 -*- from Apline import LINE from libapi.ttypes import *

18.75

27

0.693333

11

75

4.727273

0.818182

0

0.015873

0.16

75

3

28

25

0.809524

0.28

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7bb20d2b625bcd2281288524806fb8c1e73df67f

2,645

py

Python

tests/test_g_fast_ssc/test_codec.py

MingxuZhang/python-polar-coding

bfab8e1cdcffaefea8e6d0209b13465fbd7fa936

[ "MIT" ]

2

2021-12-07T09:52:15.000Z

2022-01-06T14:35:37.000Z

tests/test_g_fast_ssc/test_codec.py

manhduc1811/python-polar-coding

bfab8e1cdcffaefea8e6d0209b13465fbd7fa936

[ "MIT" ]

null

tests/test_g_fast_ssc/test_codec.py

manhduc1811/python-polar-coding

bfab8e1cdcffaefea8e6d0209b13465fbd7fa936

[ "MIT" ]

4

2020-07-03T14:20:04.000Z

2021-07-04T13:20:40.000Z

from unittest import TestCase from python_polar_coding.polar_codes.g_fast_ssc import GFastSSCPolarCodec from tests.base import BasicVerifyPolarCode class TestGeneralizedFastSSCCode_1024_256_AF_0(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 256, 'AF': 0, } class TestGeneralizedFastSSCCode_1024_256_AF_1(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 256, 'AF': 1, } class TestGeneralizedFastSSCCode_1024_256_AF_2(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 256, 'AF': 2, } class TestGeneralizedFastSSCCode_1024_256_AF_3(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 256, 'AF': 3, } class TestGeneralizedFastSSCCode_1024_512_AF_0(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 512, 'AF': 0, } class TestGeneralizedFastSSCCode_1024_512_AF_1(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 512, 'AF': 1, } class TestGeneralizedFastSSCCode_1024_512_AF_2(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 512, 'AF': 2, } class TestGeneralizedFastSSCCode_1024_512_AF_3(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 512, 'AF': 3, } class TestGeneralizedFastSSCCode_1024_768_AF_0(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 768, 'AF': 0, } class TestGeneralizedFastSSCCode_1024_768_AF_1(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 768, 'AF': 1, } class TestGeneralizedFastSSCCode_1024_768_AF_2(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 768, 'AF': 2, } class TestGeneralizedFastSSCCode_1024_768_AF_3(BasicVerifyPolarCode, TestCase): polar_code_class = GFastSSCPolarCodec code_parameters = { 'N': 1024, 'K': 768, 'AF': 3, }

23.40708

79

0.658223

260

2,645

6.353846

0.115385

0.225182

0.254237

0.268765

0.921913

0.639225

0

0.096774

0.249905

2,645

112

80

23.616071

0.735887

0

0.689655

0

0.018147

0

1

0

false

0

0.034483

0

0.448276

0

null

1

0

1

0

null

0

5

c89d488cf2ecead3a80b7a4a30f6bfcd0ac568bb

129

py

Python

account/admin.py

lindsthemormon/fomo_intex2

3d500414fb17db64929da40e27cbd4ea916ec936

[ "Apache-2.0" ]

null

account/admin.py

lindsthemormon/fomo_intex2

3d500414fb17db64929da40e27cbd4ea916ec936

[ "Apache-2.0" ]

null

account/admin.py

lindsthemormon/fomo_intex2

3d500414fb17db64929da40e27cbd4ea916ec936

[ "Apache-2.0" ]

null

from django.contrib import admin from account import models as amod # Register your models here. admin.site.register(amod.User)

21.5

34

0.806202

20

129

5.2

0.7

0

0.131783

129

5

35

25.8

0.928571

0.20155

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c8eff3d49f91ab01dc95dbb9bbdf8c3c4249b42e

428

py

Python

desafios/des109b/teste.py

Ericssm96/python

764d0d704be685db9e993c4b74d3df78da12cc6f

[ "MIT" ]

null

desafios/des109b/teste.py

Ericssm96/python

764d0d704be685db9e993c4b74d3df78da12cc6f

[ "MIT" ]

null

desafios/des109b/teste.py

Ericssm96/python

764d0d704be685db9e993c4b74d3df78da12cc6f

[ "MIT" ]

null

import des109moeda n1 = float(input('Digite o preço: R$')) print(f'O valor {des109moeda.moeda(n1)} dobrado é {des109moeda.dobro(n1, True)}.') print(f'O valor {des109moeda.moeda(n1)} pela metade é {des109moeda.metade(n1, True)}.') print(f'O valor {des109moeda.moeda(n1)} aumentado em 15% é {des109moeda.aumenta(n1, 15, True)}.') print(f'O valor {des109moeda.moeda(n1)} diminuído em 15% é {des109moeda.diminui(n1, 15, True)}.')

47.555556

97

0.714953

68

428

4.5

0.367647

0.078431

0.091503

0.156863

0.444444

0.346405

0.235294

0

0.114883

0.10514

428

8

98

53.5

0.684073

0

0.5

0.796729

0.432243

0

1

0

false

0

0.166667

0

0.166667

0.666667

0

null

0

1

0

1

null

0

1

0

5

cde30a48317e970cfec21e480e13965aa29217bc

44

py

Python

bin/Python27/Lib/site-packages/mgardf/__init__.py

lefevre-fraser/openmeta-mms

08f3115e76498df1f8d70641d71f5c52cab4ce5f

[ "MIT" ]

1

2018-02-27T01:59:25.000Z

bin/Python27/Lib/site-packages/mgardf/__init__.py

lefevre-fraser/openmeta-mms

08f3115e76498df1f8d70641d71f5c52cab4ce5f

[ "MIT" ]

6

2017-10-27T01:07:35.000Z

2018-02-06T00:15:21.000Z

bin/Python27/Lib/site-packages/mgardf/__init__.py

lefevre-fraser/openmeta-mms

08f3115e76498df1f8d70641d71f5c52cab4ce5f

[ "MIT" ]

null

from .mgardfconverter import MgaRdfConverter

44

0.909091

4

44

10

0.75

0

0.068182

44

1

44

0.97561

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

a80457349f138290c05adeaff94dfe9050b0c60c

32

py

Python

qredis/__main__.py

barjomet/qredis

cea51b23b32721cf28ef760b238b210b09ff6af9

[ "MIT" ]

null

qredis/__main__.py

barjomet/qredis

cea51b23b32721cf28ef760b238b210b09ff6af9

[ "MIT" ]

null

qredis/__main__.py

barjomet/qredis

cea51b23b32721cf28ef760b238b210b09ff6af9

[ "MIT" ]

1

2019-01-17T04:10:03.000Z

from .window import main main()

10.666667

24

0.75

5

32

4.8

0.8

0

0.15625

32

2

25

16

0.888889

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

a80b6eb450caa008778411f202b167c43bc67418

127

py

Python

acl2_kernel/__main__.py

tojoqk/acl2-kernel

9c36a01f46f58628585e87101db9da61cab42891

[ "BSD-3-Clause" ]

4

2020-06-24T12:43:29.000Z

2021-11-26T12:45:05.000Z

acl2_kernel/__main__.py

tojoqk/acl2-kernel

9c36a01f46f58628585e87101db9da61cab42891

[ "BSD-3-Clause" ]

9

2021-05-11T23:53:35.000Z

2021-09-30T10:40:55.000Z

acl2_kernel/__main__.py

tojoqk/acl2-kernel

9c36a01f46f58628585e87101db9da61cab42891

[ "BSD-3-Clause" ]

1

2021-09-15T01:02:00.000Z

from ipykernel.kernelapp import IPKernelApp from .kernel import ACL2Kernel IPKernelApp.launch_instance(kernel_class=ACL2Kernel)

42.333333

52

0.889764

15

127

7.4

0.666667

0

0.016807

0.062992

127

3

52

42.333333

0.915966

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

a82d36e0f020d41fdfd7f88a38fba3a97d461227

64

py

Python

pyvainglory/__init__.py

xKynn/PyVainglory

91cb8a14b1b6d9e077ed1a19264bf6fcac981459

[ "MIT" ]

4

2018-01-02T11:09:24.000Z

2018-06-01T03:41:46.000Z

pyvainglory/__init__.py

xKynn/PyVainglory

91cb8a14b1b6d9e077ed1a19264bf6fcac981459

[ "MIT" ]

null

pyvainglory/__init__.py

xKynn/PyVainglory

91cb8a14b1b6d9e077ed1a19264bf6fcac981459

[ "MIT" ]

null

from .asyncclient import AsyncClient from .client import Client

21.333333

36

0.84375

8

64

6.75

0.5

0

0.125

64

2

37

32

0.964286

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

a835eb7448b7643717ab4e5443d816fe99097e6f

185

py

Python

malaya_speech/train/model/melgan/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

111

2020-08-31T04:58:54.000Z

2022-03-29T15:44:18.000Z

malaya_speech/train/model/melgan/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

14

2020-12-16T07:27:22.000Z

2022-03-15T17:39:01.000Z

malaya_speech/train/model/melgan/__init__.py

ishine/malaya-speech

fd34afc7107af1656dff4b3201fa51dda54fde18

[ "MIT" ]

29

2021-02-09T08:57:15.000Z

2022-03-12T14:09:19.000Z

from .config import GeneratorConfig, DiscriminatorConfig from . import layer from . import loss from . import model from .model import Generator, Discriminator, MultiScaleDiscriminator

30.833333

68

0.832432

20

185

7.7

0.55

0.194805

0

0.124324

185

5

69

37

0.950617

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

b522506d0b25a57ac5ee64793e6bb9d6c0dfc8d5

105

py

Python

boj/15552.py

pparkddo/ps

7164c694403c2087a7b4b16a64f521ae327e328f

[ "MIT" ]

1

2021-04-02T09:37:11.000Z

boj/15552.py

pparkddo/ps

7164c694403c2087a7b4b16a64f521ae327e328f

[ "MIT" ]

null

boj/15552.py

pparkddo/ps

7164c694403c2087a7b4b16a64f521ae327e328f

[ "MIT" ]

null

import sys; input=sys.stdin.readline for _ in range(int(input())): print(sum(map(int, input().split())))

35

67

0.695238

17

105

4.235294

0.764706

0.222222

0

0.085714

105

2

68

52.5

0.75

0

1

0

false

0

0.5

0

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

5

b52ed7bcd61a97904431ecf320c5dfd0bba5d0ad

151

py

Python

fake_http_header/data_import.py

MichaelTatarski/fake-http-header

3e410ffde87e677baab8651ee9d146b3138640f1

[ "MIT" ]

2

2022-01-25T21:09:25.000Z

2022-02-14T14:01:35.000Z

fake_http_header/data_import.py

MichaelTatarski/fake-http-header

3e410ffde87e677baab8651ee9d146b3138640f1

[ "MIT" ]

1

2022-01-25T20:31:34.000Z

2022-01-26T12:57:14.000Z

fake_http_header/data_import.py

MichaelTatarski/fake-http-header

3e410ffde87e677baab8651ee9d146b3138640f1

[ "MIT" ]

null

import json def load_dict(json_file) -> dict: json_acceptable_string = json_file.replace("'", '"') return json.loads(json_acceptable_string)

21.571429

56

0.728477

20

151

5.15

0.55

0.15534

0.38835

0

0.145695

151

6

57

25.166667

0.79845

0

0.013245

0

1

0.25

false

0

0.25

0

0.75

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

b55620c3b5e760b69f54178576f7f3f778ed9df2

8,935

py

Python

grids/cube.py

R-Laurent/detection

66823e8664b66caadef2ee35ee197fd9a5066f56

[ "MIT" ]

null

grids/cube.py

R-Laurent/detection

66823e8664b66caadef2ee35ee197fd9a5066f56

[ "MIT" ]

null

grids/cube.py

R-Laurent/detection

66823e8664b66caadef2ee35ee197fd9a5066f56

[ "MIT" ]

null

import numpy as np from data.constants import Bohr2Angstrom def generate_cubefile(geom, grid_values, dx, dy, dz, nptx, npty, nptz): grid = None return generate_cubefile(geom, grid, grid_values, dx, dy, dz, nptx, npty, nptz) def generate_cubefile(geom, grid, grid_values, dx, dy, dz, nptx, npty, nptz): """ Generate a cube file for the given geometry and grid """ cubefile = "ims.cube" fio = open(cubefile, "w+") nat = len(geom) fio.write("head 1\n".format()) fio.write("head 2\n".format()) fio.write("{0:5d} {1[0]:12.6f} {1[1]:12.6f} {1[2]:12.6f}\n".format( nat, grid[0] / Bohr2Angstrom)) fio.write("{:5d} {:12.6f} {:12.6f} {:12.6f}\n".format( nptx, dx / Bohr2Angstrom, 0, 0)) fio.write("{:5d} {:12.6f} {:12.6f} {:12.6f}\n".format( npty, 0, dy / Bohr2Angstrom, 0)) fio.write("{:5d} {:12.6f} {:12.6f} {:12.6f}\n".format( nptz, 0, 0, dz / Bohr2Angstrom)) for el in geom: if (el['label'].strip().lower() == "c"): nuclear_charge = 6 elif (el['label'].strip().lower() == "h"): nuclear_charge = 1 charge = 0.0 fio.write( "{:5d} {:12.6f} {:12.6f} {:12.6f} {:12.6f}\n".format( nuclear_charge, charge, el['x'] / Bohr2Angstrom, el['y'] / Bohr2Angstrom, el['z'] / Bohr2Angstrom)) idx = 0 for x in range(0, nptx + 1): for y in range(0, npty + 1): for z in range(0, nptz + 1): k = str(idx) val = 0 if (k in grid_values.keys()): val = grid_values[k] fio.write("{:12.6f}".format(val)) if (z % 6 == 5): fio.write("\n".format()) idx = idx + 1 fio.write("\n".format()) return cubefile def closest_node(node, nodes): # from # https://codereview.stackexchange.com/questions/28207/finding-the-closest-point-to-a-list-of-points return nodes[cdist([node], nodes).argmin()] def generate_values_on_grid(geom, ims_grid, npts): """ Put the ims_values on a cubic grid based on the proximity of a measured point and a grid point """ xmin = min(a['x'] for a in ims_grid) xmax = max(a['x'] for a in ims_grid) ymin = min(a['y'] for a in ims_grid) ymax = max(a['y'] for a in ims_grid) zmin = min(a['z'] for a in ims_grid) zmax = max(a['z'] for a in ims_grid) # # Add 5% margin to handle volume plotting # xmin = xmin - xmin * .05 ymin = ymin - ymin * .05 zmin = zmin - zmin * .05 xmax = xmax + xmax * .05 ymax = ymax + ymax * .05 zmax = zmax + zmax * .05 logger.info( "xmin={} xmax={} ymin={} ymax={} zmin={} zmax={}".format( xmin, xmax, ymin, ymax, zmin, zmax)) nptx = npty = nptz = npts tmp_lst = [] # Generate grid : there is probably more efficient logger.info("Generating grid") for x in np.linspace(xmin, xmax, nptx): # see dz for y in np.linspace(ymin, ymax, npty): # see dz # dz = ( zmax - zmin ) / ( npts - 1 ) for z in np.linspace(zmin, zmax, nptz): tmp_lst.append([x, y, z]) grid = np.array(tmp_lst) grid_values = {} # remember dz = ( zmax - zmin ) / ( npts - 1 ) dx = (xmax - xmin) / (nptx - 1) dy = (ymax - ymin) / (npty - 1) # idem dz = (zmax - zmin) / (nptz - 1) # idem for el in ims_grid: el_prox = closest_node([el['x'], el['y'], el['z']], grid) idz = (el_prox[2] - zmin) / dz idy = (el_prox[1] - ymin) / dy idx = (el_prox[0] - xmin) / dx index = idx * npty * nptz + idy * nptz + idz grid_values[str(int(index))] = el['ims'] # store the value as a pair index (in str format), ims value: it is much better than storing a large number of # zero ims values on the grid return grid, grid_values, dx, dy, dz, nptx, npty, nptz def generate_values_on_grid(geom, xmin, xmax, nptx, ymin, ymax, npty, zmin, zmax, nptz): """ Put the ims_values on a cubic grid by computing the indices """ # # Add 5% margin to handle volume plotting # xmin = xmin - xmin * .05 ymin = ymin - ymin * .05 zmin = zmin - zmin * .05 xmax = xmax + xmax * .05 ymax = ymax + ymax * .05 zmax = zmax + zmax * .05 logger.info( "xmin={} xmax={} ymin={} ymax={} zmin={} zmax={}".format( xmin, xmax, ymin, ymax, zmin, zmax)) tmp_lst = [] # Generate grid : there is probably more efficient logger.info("Generating grid") for x in np.linspace(xmin, xmax, nptx): # see dz for y in np.linspace(ymin, ymax, npty): # see dz # dz = ( zmax - zmin ) / ( npts - 1 ) for z in np.linspace(zmin, zmax, nptz): tmp_lst.append([x, y, z]) grid = np.array(tmp_lst) grid_values = {} # remember dz = ( zmax - zmin ) / ( npts - 1 ) dx = (xmax - xmin) / (nptx - 1) dy = (ymax - ymin) / (npty - 1) # idem dz = (zmax - zmin) / (nptz - 1) # idem for el in ims_grid: el_prox = closest_node([el['x'], el['y'], el['z']], grid) idz = (el_prox[2] - zmin) / dz idy = (el_prox[1] - ymin) / dy idx = (el_prox[0] - xmin) / dx index = idx * npty * nptz + idy * nptz + idz grid_values[str(int(index))] = el['ims'] # store the value as a pair index (in str format), ims value: it is much better than storing a large number of # zero ims values on the grid return grid, grid_values, dx, dy, dz, nptx, npty, nptz def getIdx(value, val_min, val_max=None, npts=None, dval=None): """ Return the index of a 1D value on a linear grid. Either val_max and npts or dval must be present """ if (dval==None): dval = (val_max-val_min)/(npts - 1) return np.round((value-val_min)/dval) def getIdx_cube(x, y, z, xmin, xmax, nptx, ymin, ymax, npty, zmin, zmax, nptz): """ Returns the index of a point on a 3D rectangular grid The cube order is assumed (from http://paulbourke.net/dataformats/cube/) for (ix=0;ix<NX;ix++) { for (iy=0;iy<NY;iy++) { for (iz=0;iz<NZ;iz++) { printf("%g ",data[ix][iy][iz]); if (iz % 6 == 5) printf("\n"); } printf("\n"); } } """ idx = getIdx(x, xmin, xmax, nptx) idy = getIdx(y, ymin, ymax, npty) idz = getIdx(z, zmin, zmax, nptz) index = idx * npty * nptz + idy * nptz + idz return index def generate_cube_volume(geom, points, xmin, xmax, nptx, ymin, ymax, npty, zmin, zmax, nptz): index_values = [] for pt in points: x = pt[0] y = pt[1] z = pt[2] index_values.append(getIdx_cube(x, y, z, xmin, xmax, nptx, ymin, ymax, npty, zmin, zmax, nptz)) return index_values def generate_cubefile_new(filename, geom, grid, xmin, xmax, nptx, ymin, ymax, npty, zmin, zmax, nptz): """ Generate a cube file for the given geometry and grid """ dx = ( xmax - xmin ) / ( nptx - 1 ) dy = ( ymax - ymin ) / ( npty - 1 ) dz = ( zmax - zmin ) / ( nptz - 1 ) cubefile = filename nat = len(geom.atoms) fio = open(cubefile, "w+") nat = len(geom.atoms) fio.write("head 1\n".format()) fio.write("head 2\n".format()) fio.write("{0:5d} {1[0]:12.6f} {1[1]:12.6f} {1[2]:12.6f}\n".format( nat, [xmin/Bohr2Angstrom, ymin/Bohr2Angstrom, zmin/Bohr2Angstrom])) fio.write("{:5d} {:12.6f} {:12.6f} {:12.6f}\n".format( nptx, dx / Bohr2Angstrom, 0, 0)) fio.write("{:5d} {:12.6f} {:12.6f} {:12.6f}\n".format( npty, 0, dy / Bohr2Angstrom, 0)) fio.write("{:5d} {:12.6f} {:12.6f} {:12.6f}\n".format( nptz, 0, 0, dz / Bohr2Angstrom)) for el in geom.atoms: if (el['label'].strip().lower() == "c"): nuclear_charge = 6 elif (el['label'].strip().lower() == "h"): nuclear_charge = 1 charge = 0.0 fio.write( "{:5d} {:12.6f} {:12.6f} {:12.6f} {:12.6f}\n".format( nuclear_charge, charge, el['x'] / Bohr2Angstrom, el['y'] / Bohr2Angstrom, el['z'] / Bohr2Angstrom)) idx = 0 for ix in range(0, nptx): for iy in range(0, npty): for iz in range(0, nptz): val=0 if idx in grid: val=1 fio.write("{:12.6f}".format(val)) if (iz % 6 == 5): fio.write("\n".format()) idx = idx + 1 fio.write("\n".format()) return cubefile

35.74

118

0.511696

1,269

8,935

3.548463

0.13554

0.030202

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0.031979

0.743948

0.731068

0.721519

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0.632689

0

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8,935

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null

0

1

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1

0

1

0

null

0

5

b56a090364cca0d993414c9181f7b5f7858921ca

26

py

Python

trunk/VyPy/regression/gpr/scaling/__init__.py

jiaxu825/VyPy

47100bad9dea46f12cb8bfa1ba86886e06f5c85d

[ "BSD-3-Clause" ]

1

2021-12-28T06:39:54.000Z

trunk/VyPy/regression/gpr/scaling/__init__.py

paulcon/VyPy

5acb40e8d19ea76f3cd45f9cf98f252ca15e23f6

[ "BSD-3-Clause" ]

null

trunk/VyPy/regression/gpr/scaling/__init__.py

paulcon/VyPy

5acb40e8d19ea76f3cd45f9cf98f252ca15e23f6

[ "BSD-3-Clause" ]

null

from Linear import Linear

13

25

0.846154

4

26

5.5

0.75

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2

25

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0

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0

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null

0

1

0

1

0

5

b56a24e716ce42f9939a22dfec69c71243693065

91

py

Python

altair/main.py

lyeeer/altair

e1244d6db7b705e37bdf1b44f1ee077b6208cec6

[ "Apache-2.0" ]

43

2017-04-19T00:31:05.000Z

2021-11-05T12:29:58.000Z

altair/main.py

lyeeer/altair

e1244d6db7b705e37bdf1b44f1ee077b6208cec6

[ "Apache-2.0" ]

2

2017-03-07T22:08:52.000Z

2017-10-20T20:12:55.000Z

altair/main.py

lyeeer/altair

e1244d6db7b705e37bdf1b44f1ee077b6208cec6

[ "Apache-2.0" ]

15

2017-02-22T18:07:56.000Z

2021-07-12T13:22:06.000Z

def main(): pass # Run this when called from CLI if __name__ == "__main__": main()

15.166667

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null

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1

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null

0

1

0

5

b56c72e2615da80a89419b155c38cd4f75d3e390

3,142

py

Python

wepay/calls/subscription_charge.py

wann100/Groomer

c290c00cebc453d71f32f45bff72653130add592

[ "MIT" ]

3

2015-03-04T19:13:02.000Z

2016-02-10T15:47:18.000Z

wepay/calls/subscription_charge.py

lehins/python-wepay

414d25a1a8d0ecb22a3ddd1f16c60b805bb52a1f

[ "MIT" ]

null

wepay/calls/subscription_charge.py

lehins/python-wepay

414d25a1a8d0ecb22a3ddd1f16c60b805bb52a1f

[ "MIT" ]

null

from wepay.calls.base import Call class SubscriptionCharge(Call): """The /subscription_charge API calls""" call_name = 'subscription_charge' def __call__(self, subscription_charge_id, **kwargs): """Call documentation: `/subscription_charge <https://www.wepay.com/developer/reference/subscription_charge#lookup>`_, plus extra keyword parameters: :keyword str access_token: will be used instead of instance's ``access_token``, with ``batch_mode=True`` will set `authorization` param to it's value. :keyword bool batch_mode: turn on/off the batch_mode, see :class:`wepay.api.WePay` :keyword str batch_reference_id: `reference_id` param for batch call, see :class:`wepay.api.WePay` :keyword str api_version: WePay API version, see :class:`wepay.api.WePay` """ params = { 'subscription_charge_id': subscription_charge_id } return self.make_call(self, params, kwargs) allowed_params = ['subscription_charge_id'] def __find(self, subscription_id, **kwargs): """Call documentation: `/subscription_charge/find <https://www.wepay.com/developer/reference/subscription_charge#find>`_, plus extra keyword parameters: :keyword str access_token: will be used instead of instance's ``access_token``, with ``batch_mode=True`` will set `authorization` param to it's value. :keyword bool batch_mode: turn on/off the batch_mode, see :class:`wepay.api.WePay` :keyword str batch_reference_id: `reference_id` param for batch call, see :class:`wepay.api.WePay` :keyword str api_version: WePay API version, see :class:`wepay.api.WePay` """ params = { 'subscription_id': subscription_id } return self.make_call(self.__find, params, kwargs) __find.allowed_params = [ 'subscription_id', 'start', 'limit', 'start_time', 'end_time', 'type', 'amount', 'state' ] find = __find def __refund(self, subscription_charge_id, **kwargs): """Call documentation: `/subscription_charge/refund <https://www.wepay.com/developer/reference/subscription_charge#refund>`_, plus extra keyword parameters: :keyword str access_token: will be used instead of instance's ``access_token``, with ``batch_mode=True`` will set `authorization` param to it's value. :keyword bool batch_mode: turn on/off the batch_mode, see :class:`wepay.api.WePay` :keyword str batch_reference_id: `reference_id` param for batch call, see :class:`wepay.api.WePay` :keyword str api_version: WePay API version, see :class:`wepay.api.WePay` """ params = { 'subscription_charge_id': subscription_charge_id } return self.make_call(self.__refund, params, kwargs) __refund.allowed_params = ['subscription_charge_id', 'refund_reason'] refund = __refund

36.114943

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0.636219

368

3,142

5.192935

0.1875

0.150706

0.061224

0.075353

0.819466

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0.749869

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0.600209

0

0.260025

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36.534884

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0

null

0

1

0

1

0

null

0

5

b57738459b87d130cc1d48317d6d54e9bef94fd9

215

py

Python

script.py

esweep/casimirprogramming_els

da8b785415c7798a6ccb4c90b9af6bba9960f46e

[ "MIT" ]

null

script.py

esweep/casimirprogramming_els

da8b785415c7798a6ccb4c90b9af6bba9960f46e

[ "MIT" ]

null

script.py

esweep/casimirprogramming_els

da8b785415c7798a6ccb4c90b9af6bba9960f46e

[ "MIT" ]

null

print('hello github') from test import circumference, surface_area print("the circumference of the circle is", circumference(5)) print("The surface area of the circle is", surface_area(5)) print("another test")

21.5

61

0.762791

32

215

5.0625

0.46875

0.203704

0.135802

0.160494

0

0.010695

0.130233

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62

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1

0

null

0

1

0

1

0

5

a90d78dfb295595f9899b6c85a04d6329cb2c551

361

py

Python

tipico/types/instrument_status.py

lbusoni/tipico

364a0d2321508e62bafae5037f435c1df3588814

[ "MIT" ]

null

tipico/types/instrument_status.py

lbusoni/tipico

364a0d2321508e62bafae5037f435c1df3588814

[ "MIT" ]

1

2020-10-29T19:53:15.000Z

tipico/types/instrument_status.py

ArcetriAdaptiveOptics/tipico

364a0d2321508e62bafae5037f435c1df3588814

[ "MIT" ]

null

class InstrumentStatus(object): def __init__(self, actuatorCommands, commandCounter): self._actuatorCommands= actuatorCommands self._commandCounter= commandCounter def commandCounter(self): return self._commandCounter def actuatorCommands(self): return self._actuatorCommands

20.055556

48

0.65928

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361

8.846154

0.346154

0.26087

0.121739

0

0.285319

361

17

49

21.235294

0.891473

0

1

0.3

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0

null

1

0

null

0

1

0

1

0

5

a924305b6275f1a8ba443ab32a66bc6c5974434a

129

py

Python

web/project/settings/__init__.py

borzunov/django-forum

37ee43327575e59a4f7e1fcaa9f3a1c0de08d2b3

[ "MIT" ]

6

2016-12-08T17:35:46.000Z

2019-12-05T07:17:26.000Z

web/project/settings/__init__.py

borzunov/django-forum

37ee43327575e59a4f7e1fcaa9f3a1c0de08d2b3

[ "MIT" ]

1

2020-06-05T17:28:56.000Z

web/project/settings/__init__.py

borzunov/django-forum

37ee43327575e59a4f7e1fcaa9f3a1c0de08d2b3

[ "MIT" ]

1

2017-01-12T17:53:52.000Z

import os if os.environ.get('ENVIRONMENT') == 'production': from .production import * else: from .development import *

16.125

49

0.682171

15

129

5.866667

0.666667

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0.193798

129

7

50

18.428571

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0

1

0

true

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1

0

1

0

1

0

5

a9483d7f93445176347f712faf6f5a8de08a3853

121

py

Python

setup.py

neurodata/boss-export

16e9d2b0319876e36e53d3a01622e83e75fc48f1

[ "Apache-2.0" ]

null

setup.py

neurodata/boss-export

16e9d2b0319876e36e53d3a01622e83e75fc48f1

[ "Apache-2.0" ]

null

setup.py

neurodata/boss-export

16e9d2b0319876e36e53d3a01622e83e75fc48f1

[ "Apache-2.0" ]

null

from setuptools import setup, find_packages setup(name="boss-export", author="Benjamin Falk", packages=find_packages())

30.25

75

0.793388

16

121

5.875

0.75

0.255319

0

0.082645

121

3

76

40.333333

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0

0.198347

0

1

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true

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1

0

null

0

1

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1

0

5

8d8d1e6acfffd114882679b0e6cf2b21bf331d4b

397

py

Python

slack_bolt/kwargs_injection/__init__.py

hirosassa/bolt-python

befc3a1463f3ac8dbb780d66decc304e2bdf3e7a

[ "MIT" ]

504

2020-08-07T05:02:57.000Z

2022-03-31T14:32:46.000Z

slack_bolt/kwargs_injection/__init__.py

hirosassa/bolt-python

befc3a1463f3ac8dbb780d66decc304e2bdf3e7a

[ "MIT" ]

560

2020-08-07T01:16:06.000Z

2022-03-30T00:40:56.000Z

slack_bolt/kwargs_injection/__init__.py

hirosassa/bolt-python

befc3a1463f3ac8dbb780d66decc304e2bdf3e7a

[ "MIT" ]

150

2020-08-07T09:41:14.000Z

2022-03-30T04:54:51.000Z

"""For middleware/listener arguments, Bolt does flexible data injection in accordance with their names. To learn the available arguments, check `slack_bolt.kwargs_injection.args`'s API document. For Workflow steps, checking `slack_bolt.workflows.step.utilities` as well should be helpful. """ # Don't add async module imports here from .args import Args from .utils import build_required_kwargs

39.7

103

0.806045

59

397

5.338983

0.813559

0.057143

0

0.125945

397

9

104

44.111111

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0.813602

0

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true

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null

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5

8da9b96454b2bbf87d8d4e83346f31f3a1097fd9

74

py

Python

Programmers/src/12918/solution.py

lstar2397/algorithms

686ea882079e26111f86b5bd5a7ab1b14ccf0fa2

[ "MIT" ]

null

Programmers/src/12918/solution.py

lstar2397/algorithms

686ea882079e26111f86b5bd5a7ab1b14ccf0fa2

[ "MIT" ]

null

Programmers/src/12918/solution.py

lstar2397/algorithms

686ea882079e26111f86b5bd5a7ab1b14ccf0fa2

[ "MIT" ]

null

def solution(s): return ((len(s) == 4 or len(s) == 6) and s.isdigit())

37

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0.554054

14

74

2.928571

0.714286

0.195122

0

0.033898

0.202703

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0

1

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false

0

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null

0

1

0

null

0

1

0

1

0

5

8daaa0dc15d3f1c191ab25da4f8317cca5eb37ad

100

py

Python

vaillant.py

thomasgermain/vr900-connector

86828b17b8c16f28b684e8236ab2c46e2475f026

[ "MIT" ]

12

2019-01-04T18:51:39.000Z

2019-11-13T09:49:46.000Z

vaillant.py

thomasgermain/vr900-connector

86828b17b8c16f28b684e8236ab2c46e2475f026

[ "MIT" ]

13

2019-01-30T17:39:44.000Z

2019-10-04T15:59:43.000Z

vaillant.py

thomasgermain/vr900-connector

86828b17b8c16f28b684e8236ab2c46e2475f026

[ "MIT" ]

2

2019-02-28T21:54:49.000Z

2019-03-11T12:05:13.000Z

""" Command line interface for Vaillant API """ from vr900connector import __main__ __main__.main()

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0.034483

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0

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null

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1

0

1

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5

a5d2d8aeee3eab26d800bfc83884a1aef451edcd

109

py

Python

Python/GoogleTrendingSearches.py

propil5/WarelogManager

6baf338855175259877257352f9986a02ffd3e2e

[ "MIT" ]

null

Python/GoogleTrendingSearches.py

propil5/WarelogManager

6baf338855175259877257352f9986a02ffd3e2e

[ "MIT" ]

null

Python/GoogleTrendingSearches.py

propil5/WarelogManager

6baf338855175259877257352f9986a02ffd3e2e

[ "MIT" ]

null

from pytrends.request import TrendReq import numpy as np import sys pytrends.trending_searches(pn='poland')

21.8

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109

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0.8125

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109

5

40

21.8

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null

0

1

0

1

0

1

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5

a5d2ffb0dedaf74c230e159708a1e53644eb038c

182

py

Python

iceworm/sql/sql.py

wrmsr0/iceworm

09431bb3cdc4f6796aafca41e37d42ebe0ddfeef

[ "BSD-3-Clause" ]

null

iceworm/sql/sql.py

wrmsr0/iceworm

09431bb3cdc4f6796aafca41e37d42ebe0ddfeef

[ "BSD-3-Clause" ]

1

2021-01-19T14:29:19.000Z

2021-01-19T14:34:27.000Z

iceworm/sql/sql.py

wrmsr0/iceworm

09431bb3cdc4f6796aafca41e37d42ebe0ddfeef

[ "BSD-3-Clause" ]

1

2020-12-31T22:29:52.000Z

""" TODO: - QualifiedName visitability.. somewhere - CreateOrReplaceTable (w/ prefixes) - batching for snowflake... - helper against sqla inserts with nonexisting columns :/ """

22.75

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0.730769

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182

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0.153846

182

7

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0

null

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1

0

1

0

null

0

1

0

1

0

5

573a7289145eb1393400fd94014dd0afdf49b2cf

1,117

py

Python

prepare.py

m32/pdfium

334beec62b65199add3257aaf2338f78cb5e6026

[ "Apache-2.0" ]

null

prepare.py

m32/pdfium

334beec62b65199add3257aaf2338f78cb5e6026

[ "Apache-2.0" ]

null

prepare.py

m32/pdfium

334beec62b65199add3257aaf2338f78cb5e6026

[ "Apache-2.0" ]

null

#!/usr/bin/env vpython3 def onefile(fname): data = open(fname, 'rt').read() data = data.replace('FPDF_EXPORT', 'extern') data = data.replace('FPDF_CALLCONV', '') open(fname, 'wt').write(data) onefile('pdfium/include/fpdf_annot.h') onefile('pdfium/include/fpdf_attachment.h') onefile('pdfium/include/fpdf_catalog.h') onefile('pdfium/include/fpdf_dataavail.h') onefile('pdfium/include/fpdf_doc.h') onefile('pdfium/include/fpdf_edit.h') onefile('pdfium/include/fpdf_ext.h') onefile('pdfium/include/fpdf_flatten.h') onefile('pdfium/include/fpdf_formfill.h') onefile('pdfium/include/fpdf_fwlevent.h') onefile('pdfium/include/fpdf_javascript.h') onefile('pdfium/include/fpdf_ppo.h') onefile('pdfium/include/fpdf_progressive.h') onefile('pdfium/include/fpdf_save.h') onefile('pdfium/include/fpdf_searchex.h') onefile('pdfium/include/fpdf_signature.h') onefile('pdfium/include/fpdf_structtree.h') onefile('pdfium/include/fpdf_sysfontinfo.h') onefile('pdfium/include/fpdf_text.h') onefile('pdfium/include/fpdf_thumbnail.h') onefile('pdfium/include/fpdf_transformpage.h') onefile('pdfium/include/fpdfview.h')

36.032258

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1,117

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0.524434

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0.595948

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0.000944

0.051925

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0

0.037037

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null

1

0

1

null

0

5

573e7f649643731aee9f4ed8350504851c91422b

207

py

Python

lib/models/__init__.py

yandex-research/learnable-init

480627217763912e83251833df2d678c8b6ea6fd

[ "Apache-2.0" ]

4

2021-07-14T19:18:47.000Z

2022-03-21T17:50:46.000Z

lib/models/__init__.py

yandex-research/learnable-init

480627217763912e83251833df2d678c8b6ea6fd

[ "Apache-2.0" ]

null

lib/models/__init__.py

yandex-research/learnable-init

480627217763912e83251833df2d678c8b6ea6fd

[ "Apache-2.0" ]

null

from .fixup_resnet import FixupResNet18#, DIMAMLFixupResNet18 # from .metainit_resnet import MetaInitFixupResNet18 from .language_model import LanguageModel, convert_to_cudnn_lstm from .autoencoder import AE

51.75

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207

7.291667

0.708333

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0

0.031746

0.086957

207

4

65

51.75

0.89418

0.347826

0

1

0

true

0

1

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1

0

1

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null

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1

0

null

0

1

0

1

0

1

0

5

5755145cab44e1b704bfb86f392bc4b9858a9e27

272

py

Python

List/NestedList.py

poojavaibhavsahu/Pooja_Python

58122bfa8586883145042b11fe1cc013c803ab4f

[ "bzip2-1.0.6" ]

null

List/NestedList.py

poojavaibhavsahu/Pooja_Python

58122bfa8586883145042b11fe1cc013c803ab4f

[ "bzip2-1.0.6" ]

null

List/NestedList.py

poojavaibhavsahu/Pooja_Python

58122bfa8586883145042b11fe1cc013c803ab4f

[ "bzip2-1.0.6" ]

null

mylist=['hello',[2,3,4],[40,50,60],['hi'],'how',"bye"] print(mylist) print(mylist[1][1]) mylist=['hello',[2,3,4]] print(mylist[1][0]) num1=[0,32,444,4453,[23,43,54,12,3]] print(num1) num2=[0,32,444,4453] num2.extend([23,43,54,12,3]) print(num2)

7.157895

54

0.5625

52

272

2.942308

0.461538

0.215686

0.156863

0.169935

0.366013

0.183007

0

0.251064

0.136029

272

37

55

7.351351

0.4

0

0.066915

0

1

0

false

0

0.5

0

null

1

0

1

0

1

0

1

0

null

0

1

0

5

93a591f657556efd521fdc284bf00f1fdbcc4a4a

159

py

Python

aiomatrix/types/responses/create_room.py

Forden/aiomatrix

d258076bae8eb776495b92be46ee9f4baec8d9a6

[ "MIT" ]

2

2021-10-29T18:07:08.000Z

2021-11-19T00:25:43.000Z

aiomatrix/types/responses/create_room.py

Forden/aiomatrix

d258076bae8eb776495b92be46ee9f4baec8d9a6

[ "MIT" ]

1

2022-03-06T11:17:43.000Z

aiomatrix/types/responses/create_room.py

Forden/aiomatrix

d258076bae8eb776495b92be46ee9f4baec8d9a6

[ "MIT" ]

null

import pydantic from .. import primitives class CreateRoomResponse(pydantic.BaseModel): room_id: primitives.RoomID room_alias: primitives.RoomAlias

17.666667

45

0.792453

17

159

7.294118

0.705882

0

0.144654

159

8

46

19.875

0.911765

0

1

0

true

0

0.4

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

93c83dec5e12629606577baaa10197aa7c3646c8

40

py

Python

lib/python3.6/site-packages/requests_async/status_codes.py

EricVanDerDijs/admissions-frontend

3a7f18b91ebd07f0fff6f4a2dc360637d735fa77

[ "BSD-3-Clause" ]

1,057

2019-03-21T12:43:58.000Z

2022-02-04T15:07:33.000Z

lib/python3.6/site-packages/requests_async/status_codes.py

EricVanDerDijs/admissions-frontend

3a7f18b91ebd07f0fff6f4a2dc360637d735fa77

[ "BSD-3-Clause" ]

42

2019-03-21T13:58:49.000Z

2019-07-22T21:40:21.000Z

lib/python3.6/site-packages/requests_async/status_codes.py

EricVanDerDijs/admissions-frontend

3a7f18b91ebd07f0fff6f4a2dc360637d735fa77

[ "BSD-3-Clause" ]

48

2019-03-21T12:45:10.000Z

2022-01-20T03:24:07.000Z

from requests.status_codes import codes

20

39

0.875

6

40

5.666667

0.833333

0

0.1

40

1

40

0.944444

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

93df023767e81b3fcdb47c4afa23c4915b2bc932

35

py

Python

styledating/challenges/robot_sc.py

jnngu/codingdatingsite

18187f95d3864f23b005a7ceba932cdba78638a0

[ "MIT" ]

null

styledating/challenges/robot_sc.py

jnngu/codingdatingsite

18187f95d3864f23b005a7ceba932cdba78638a0

[ "MIT" ]

null

styledating/challenges/robot_sc.py

jnngu/codingdatingsite

18187f95d3864f23b005a7ceba932cdba78638a0

[ "MIT" ]

null

def judge(moves): print(False)

17.5

18

0.657143

5

35

4.6

1

0

0.2

35

2

19

17.5

0.821429

0

1

0.5

false

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

5

9e068d9a917080d18e76969a60b72ba0f6023cc5

161

py

Python

webdev/materiais/apps.py

h-zanetti/jewelry-manager

74166b89f492303b8ebf5ff8af058f394eb2a28b

[ "MIT" ]

null

webdev/materiais/apps.py

h-zanetti/jewelry-manager

74166b89f492303b8ebf5ff8af058f394eb2a28b

[ "MIT" ]

103

2021-04-25T21:28:11.000Z

2022-03-15T01:36:31.000Z

webdev/materiais/apps.py

h-zanetti/jewelry-manager

74166b89f492303b8ebf5ff8af058f394eb2a28b

[ "MIT" ]

null

from django.apps import AppConfig class MateriaisConfig(AppConfig): name = 'webdev.materiais' def ready(self): import webdev.materiais.signals

20.125

39

0.726708

18

161

6.5

0.777778

0.25641

0

0.192547

161

8

39

20.125

0.9

0

0.098765

0

1

0.2

false

0

0.4

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

9e0f084225235fd1b519a46c9c39239def7dbe51

162

py

Python

env/lib/python2.7/site-packages/scratchpad/jpnames.py

ramshresh/nset-ci-template-hmvc-boilerplate

04d3a8cff54e9fa49d12efe0cadc0352897fdd62

[ "MIT" ]

null

env/lib/python2.7/site-packages/scratchpad/jpnames.py

ramshresh/nset-ci-template-hmvc-boilerplate

04d3a8cff54e9fa49d12efe0cadc0352897fdd62

[ "MIT" ]

null

env/lib/python2.7/site-packages/scratchpad/jpnames.py

ramshresh/nset-ci-template-hmvc-boilerplate

04d3a8cff54e9fa49d12efe0cadc0352897fdd62

[ "MIT" ]

null

from openpyxl import load_workbook src = "Issues/bug722.xlsx" #src = "../fixed.xlsx" #src = "../Issues/bug722-xl.xlsx" wb = load_workbook(src, keep_links=True)

20.25

40

0.709877

24

162

4.666667

0.625

0.214286

0.267857

0

0.041958

0.117284

162

7

41

23.142857

0.741259

0.32716

0

0.168224

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

5

f55acb41c615d43b25d34ec9af8b8ec1bdad0fbf

47

py

Python

test/login.py

haorenshiwo/testing001

0f17f6433e6cc1f11aada03b56c099a42630b182

[ "MIT" ]

null

test/login.py

haorenshiwo/testing001

0f17f6433e6cc1f11aada03b56c099a42630b182

[ "MIT" ]

null

test/login.py

haorenshiwo/testing001

0f17f6433e6cc1f11aada03b56c099a42630b182

[ "MIT" ]

null

num1 = 1 num2 = 2 num3 = 3 num4 = 33 num6 = 66

7.833333

9

0.574468

10

47

2.7

1

0

0.375

0.319149

47

5

10

9.4

0.46875

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

1977998cdef59ee4b7858e61f7e49ee9e4c6c64b

126

py

Python

exercicios/ex007.py

luccasocastro/Curso-Python

7ad2b980bb2f95f833811291273d6ca1beb0fe77

[ "MIT" ]

null

exercicios/ex007.py

luccasocastro/Curso-Python

7ad2b980bb2f95f833811291273d6ca1beb0fe77

[ "MIT" ]

null

exercicios/ex007.py

luccasocastro/Curso-Python

7ad2b980bb2f95f833811291273d6ca1beb0fe77

[ "MIT" ]

null

n1 = float(input('Informe a nota 1: ')) n2 = float(input('Informe a nota 2: ')) m = (n1+n2)/2 print('A média é {}'.format(m))

25.2

39

0.595238

24

126

3.125

0.583333

0.266667

0.453333

0.48

0.586667

0

0.066667

0.166667

126

4

40

31.5

0.647619

0

0.380952

0

1

0

false

0

0.25

1

0

null

1

0

1

0

null

0

5

270124b31d7e32a99e1045657505853e800272a5

197

py

Python

finance/admin.py

pkimber/account

41c31cb01fb26481c345a5b65a8c931adedd1591

[ "Apache-2.0" ]

null

finance/admin.py

pkimber/account

41c31cb01fb26481c345a5b65a8c931adedd1591

[ "Apache-2.0" ]

null

finance/admin.py

pkimber/account

41c31cb01fb26481c345a5b65a8c931adedd1591

[ "Apache-2.0" ]

null

# -*- encoding: utf-8 -*- from django.contrib import admin from .models import VatSettings class VatSettingsAdmin(admin.ModelAdmin): pass admin.site.register(VatSettings, VatSettingsAdmin)

17.909091

50

0.766497

22

197

6.863636

0.727273

0

0.005848

0.13198

197

10

51

19.7

0.877193

0.116751

0

1

0

true

0.2

0.4

0

0.6

0

1

0

null

0

null

0

1

0

1

0

5

2705c146532381c7979c0c26f36ac4cd991cd648

55

py

Python

logical/converter/qiskit/validation/__init__.py

malcolmregan/GateCircuit-to-AnnealerEmbedding

33a1a4ea2ebd707ade0677e0df468d5120a861db

[ "Apache-2.0" ]

null

logical/converter/qiskit/validation/__init__.py

malcolmregan/GateCircuit-to-AnnealerEmbedding

33a1a4ea2ebd707ade0677e0df468d5120a861db

[ "Apache-2.0" ]

1

2019-04-09T02:22:38.000Z

logical/converter/qiskit/validation/__init__.py

malcolmregan/GateCircuit-to-AnnealerEmbedding

33a1a4ea2ebd707ade0677e0df468d5120a861db

[ "Apache-2.0" ]

null

from .base import BaseModel, BaseSchema, bind_schema

13.75

52

0.8

7

55

6.142857

1

0

0.145455

55

3

53

18.333333

0.914894

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

27089f8f614f566f98f3449d0f1a657a42287a0f

130

py

Python

blog/admin.py

antonarnaudov/BlogWebsiteAPI

66b29679c8b53f8039b46396de7c07c63368791f

[ "MIT" ]

null

blog/admin.py

antonarnaudov/BlogWebsiteAPI

66b29679c8b53f8039b46396de7c07c63368791f

[ "MIT" ]

1

2021-07-29T21:44:24.000Z

blog/admin.py

antonarnaudov/BlogWebsiteAPI

66b29679c8b53f8039b46396de7c07c63368791f

[ "MIT" ]

null

from django.contrib import admin from blog.models import BlogPost, Like admin.site.register(BlogPost) admin.site.register(Like)

18.571429

38

0.815385

19

130

5.578947

0.578947

0.169811

0.320755

0

0.1

130

6

39

21.666667

0.905983

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

270bc165ced8f4548e09c7921833d08bb32ecccf

34

py

Python

ipwb/__init__.py

oduwsdl/IPFSWayback

42685149c3058e27ced7129fbb8ae24fea6edb78

[ "MIT" ]

1

2016-03-06T21:31:34.000Z

ipwb/__init__.py

oduwsdl/IPFSWayback

42685149c3058e27ced7129fbb8ae24fea6edb78

[ "MIT" ]

1

2016-03-09T15:42:14.000Z

ipwb/__init__.py

oduwsdl/IPFSWayback

42685149c3058e27ced7129fbb8ae24fea6edb78

[ "MIT" ]

null

__version__ = '0.2022.04.06.1939'

17

33

0.705882

6

34

3.333333

1

0

0.419355

0.088235

34

1

34

0.225806

0

0.5

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

2726308644403d0cbc1814d19c2c6ce8ae481462

103

py

Python

mmtrack/models/losses/__init__.py

callzhang/mmtracking

52a2ed94297685d4fe47ee7ece18917961cc39f0

[ "Apache-2.0" ]

null

mmtrack/models/losses/__init__.py

callzhang/mmtracking

52a2ed94297685d4fe47ee7ece18917961cc39f0

[ "Apache-2.0" ]

null

mmtrack/models/losses/__init__.py

callzhang/mmtracking

52a2ed94297685d4fe47ee7ece18917961cc39f0

[ "Apache-2.0" ]

1

2021-07-15T00:26:35.000Z

from .l2_loss import L2Loss from .triplet_loss import TripletLoss __all__ = ['L2Loss', 'TripletLoss']

20.6

37

0.776699

13

103

5.692308

0.615385

0.27027

0

0.033333

0.126214

103

4

38

25.75

0.788889

0

0.165049

0

1

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false

0

0.666667

0

0.666667

0

1

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null

1

0

1

0

null

0

1

0

1

0

5

274abbea502d5c5199303d54846906fbcff1a427

195

py

Python

newssimilarity/model/feature_instances/ne_syn_feature_instance.py

imackerracher/NewsSimilarity

2e6a85dc9e95ef94bec2339987950f4e88f5d909

[ "Apache-2.0" ]

null

newssimilarity/model/feature_instances/ne_syn_feature_instance.py

imackerracher/NewsSimilarity

2e6a85dc9e95ef94bec2339987950f4e88f5d909

[ "Apache-2.0" ]

null

newssimilarity/model/feature_instances/ne_syn_feature_instance.py

imackerracher/NewsSimilarity

2e6a85dc9e95ef94bec2339987950f4e88f5d909

[ "Apache-2.0" ]

null

from newssimilarity.model.feature_instances.feature_instance import FeatureInstance class NESynFeatureInstance(FeatureInstance): def get_feature_instance(self): return self.content

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27594071c3c146886974dac5c8801ad98fb56d79

12,807

py

Python

evaluation/test/test_detection_metric.py

EmmaSRH/2

c2e5b085a82d7d47d426c203776b7720872ae546

[ "MIT" ]

4

2020-02-26T02:28:45.000Z

2020-04-04T13:47:11.000Z

evaluation/test/test_detection_metric.py

EmmaSRH/2

c2e5b085a82d7d47d426c203776b7720872ae546

[ "MIT" ]

null

evaluation/test/test_detection_metric.py

EmmaSRH/2

c2e5b085a82d7d47d426c203776b7720872ae546

[ "MIT" ]

null

import unittest import numpy as np from evaluation.mean_average_precision_calculations import compute_mean_average_precision, compute_iou, \ compute_statistics class TestMAPCalculation(unittest.TestCase): def test_intersection_over_union(self): # define ground truth gt_1 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) gt_2 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) # full intersection expected_iou_1 = 1 pred_1 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) # one missing expected_iou_2 = 0.8888888 pred_2 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 0, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) # just one intersected expected_iou_3 = 0.11111 pred_3 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) # no intersection expected_iou_4 = 0 pred_4 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1]], np.uint8) # empty prediction expected_iou_5 = 0 pred_5 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) delta = 0.0005 self.assertAlmostEqual(compute_iou(mask_gt=gt_1, mask_pred=pred_1), expected_iou_1, delta=delta) self.assertAlmostEqual(compute_iou(mask_gt=gt_1, mask_pred=pred_2), expected_iou_2, delta=delta) self.assertAlmostEqual(compute_iou(mask_gt=gt_1, mask_pred=pred_3), expected_iou_3, delta=delta) self.assertAlmostEqual(compute_iou(mask_gt=gt_1, mask_pred=pred_4), expected_iou_4, delta=delta) self.assertAlmostEqual(compute_iou(mask_gt=gt_1, mask_pred=pred_5), expected_iou_5, delta=delta) self.assertAlmostEqual(compute_iou(mask_gt=gt_2, mask_pred=pred_4), expected_iou_4, delta=delta) self.assertAlmostEqual(compute_iou(mask_gt=gt_2, mask_pred=pred_5), expected_iou_5, delta=delta) self.assertTrue(np.isnan(compute_iou(mask_gt=pred_5, mask_pred=pred_5))) def test_detection_statistics(self): # define images img_1 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) img_2 = np.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) img_3 = np.array([[1, 1, 0, 0, 0, 0, 0], [1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 0, 2, 2, 0], [0, 0, 0, 0, 0, 0, 0]], np.uint8) img_4 = np.array([[1, 1, 0, 0, 0, 0, 0], [1, 1, 0, 0, 3, 3, 0], [0, 0, 0, 0, 3, 3, 0], [0, 4, 4, 0, 0, 0, 0], [0, 4, 4, 0, 2, 2, 0], [5, 5, 0, 0, 2, 2, 0], [5, 5, 0, 0, 0, 0, 0]], np.uint8) # statistics # precision = true_positive / (true_positive + false_positive) # recall = true_positive / (true_positive + false_negative) result_test_case_1 = compute_statistics(mask_gt=img_1, mask_pred=img_1) expectation_test_case_1 = dict( true_positive=0, false_positive=0, false_negative=0, precision=0, recall=0 ) result_test_case_2 = compute_statistics(mask_gt=img_1, mask_pred=img_2) expectation_test_case_2 = dict( true_positive=0, false_positive=1, false_negative=0, precision=0, recall=0 ) result_test_case_3 = compute_statistics(mask_gt=img_2, mask_pred=img_1) expectation_test_case_3 = dict( true_positive=0, false_positive=0, false_negative=1, precision=0, recall=0 ) result_test_case_4 = compute_statistics(mask_gt=img_3, mask_pred=img_2) expectation_test_case_4 = dict( true_positive=0, false_positive=1, false_negative=2, precision=0, recall=0 ) result_test_case_5 = compute_statistics(mask_gt=img_3, mask_pred=img_4) expectation_test_case_5 = dict( true_positive=2, false_positive=3, false_negative=0, precision=2 / (2 + 3), recall=2 / (2 + 0) ) result_test_case_6 = compute_statistics(mask_gt=img_4, mask_pred=img_4) # expect fp=0, tp=2, fn=3 expectation_test_case_6 = dict( true_positive=5, false_positive=0, false_negative=0, precision=1, recall=1 ) self.assertDictEqual(result_test_case_1, expectation_test_case_1) self.assertDictEqual(result_test_case_2, expectation_test_case_2) self.assertDictEqual(result_test_case_3, expectation_test_case_3) self.assertDictEqual(result_test_case_4, expectation_test_case_4) self.assertDictEqual(result_test_case_5, expectation_test_case_5) self.assertDictEqual(result_test_case_6, expectation_test_case_6) def test_mean_average_precision(self): statistics_list_1 = [ dict(true_positive=0, false_positive=0, false_negative=0, precision=1.0, recall=0.2), dict(true_positive=0, false_positive=0, false_negative=0, precision=1.0, recall=0.4), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.67, recall=0.4), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=0.4), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.4, recall=0.4), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=0.6), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.57, recall=0.8), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=0.8), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.44, recall=0.8), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=1.0) ] statistics_list_2 = [ dict(true_positive=0, false_positive=0, false_negative=0, precision=1.0, recall=0.090909), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=0.090909), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.666667, recall=0.166667), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.75, recall=0.230769), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.6, recall=0.230769), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.666667, recall=0.285714), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.714286, recall=0.33333), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.75, recall=0.375), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.66667, recall=0.375), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.7, recall=0.411765), ] statistics_list_3 = [ dict(true_positive=0, false_positive=0, false_negative=0, precision=1.0, recall=0.33), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=0.33), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.67, recall=0.67), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=0.67), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.4, recall=0.67), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.5, recall=1.0), dict(true_positive=0, false_positive=0, false_negative=0, precision=0.43, recall=1.0), ] delta = 0.0005 self.assertAlmostEqual(compute_mean_average_precision(statistics_list_1), (0.4*1.0+0.4*0.57+0.2*0.5), delta=delta) self.assertAlmostEqual(compute_mean_average_precision(statistics_list_2), (0.09*1+0.285*0.75+0.625*0.7), delta=delta) self.assertAlmostEqual(compute_mean_average_precision(statistics_list_3), 0.33*1+0.34*0.67+0.33*0.5, delta=delta) if __name__ == '__main__': unittest.main()

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null

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275a07ffc59e39ff0240143379ebed028dbfa0ad

226

py

Python

src/pacman/__init__.py

sebastian-zieba/PACMAN

2eb1e4b450c97dc28d5a05b3ebddd80706cfca79

[ "MIT" ]

1

2022-03-23T10:26:33.000Z

src/pacman/__init__.py

sebastian-zieba/PACMAN

2eb1e4b450c97dc28d5a05b3ebddd80706cfca79

[ "MIT" ]

null

src/pacman/__init__.py

sebastian-zieba/PACMAN

2eb1e4b450c97dc28d5a05b3ebddd80706cfca79

[ "MIT" ]

1

2022-03-29T13:37:31.000Z

import pacman.s00_table import pacman.s01_horizons import pacman.s02_barycorr import pacman.s03_refspectra import pacman.s10_direct_images import pacman.s20_extract import pacman.s21_bin_spectroscopic_lc import pacman.s30_run

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5

2798272ae6a42b6612dabcc8f92d17dc3a3f5cec

1,412

py

Python

dex2c/insert_smali.py

LiHerman/python-aguard

448d6a292460bcd6e70acfff9bac1f7dcebdd9f3

[ "Apache-2.0" ]

null

dex2c/insert_smali.py

LiHerman/python-aguard

448d6a292460bcd6e70acfff9bac1f7dcebdd9f3

[ "Apache-2.0" ]

null

dex2c/insert_smali.py

LiHerman/python-aguard

448d6a292460bcd6e70acfff9bac1f7dcebdd9f3

[ "Apache-2.0" ]

null

whole_clinit = [ '\n' '.method static constructor <clinit>()V\n' ' .locals 1\n' '\n' ' :try_start_0\n' ' const-string v0, "nc"\n' '\n' ' invoke-static {v0}, Ljava/lang/System;->loadLibrary(Ljava/lang/String;)V\n' ' :try_end_0\n' ' .catch Ljava/lang/UnsatisfiedLinkError; {:try_start_0 .. :try_end_0} :catch_0\n' '\n' ' goto :goto_0\n' '\n' ' :catch_0\n' ' move-exception v0\n' '\n' ' .local v0, "e":Ljava/lang/UnsatisfiedLinkError;\n' ' invoke-virtual {v0}, Ljava/lang/UnsatisfiedLinkError;->printStackTrace()V\n' '\n' ' .end local v0 # "e":Ljava/lang/UnsatisfiedLinkError;\n' ' :goto_0\n' ' return-void\n' '.end method\n' ] insert_clinit = [ '\n' ' :try_start_ab\n' ' const-string v0, "nc"\n' '\n' ' invoke-static {v0}, Ljava/lang/System;->loadLibrary(Ljava/lang/String;)V\n' ' :try_end_ab\n' ' .catch Ljava/lang/UnsatisfiedLinkError; {:try_start_ab .. :try_end_ab} :catch_ab\n' '\n' ' goto :goto_ab\n' '\n' ' :catch_ab\n' ' move-exception v0\n' '\n' ' .local v0, "e":Ljava/lang/UnsatisfiedLinkError;\n' ' invoke-virtual {v0}, Ljava/lang/UnsatisfiedLinkError;->printStackTrace()V\n' '\n' ' .end local v0 # "e":Ljava/lang/UnsatisfiedLinkError;\n' ' :goto_ab\n' ]

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1

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5

279afd47a27ed3232793f9ff8d03044daf02d1a1

87

py

Python

WEEKS/wk17/CodeSignal-Solutions/Core_039_-_removeArrayPart.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

WEEKS/wk17/CodeSignal-Solutions/Core_039_-_removeArrayPart.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

WEEKS/wk17/CodeSignal-Solutions/Core_039_-_removeArrayPart.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

def removeArrayPart(inputArray, l, r): return inputArray[:l] + inputArray[r + 1 :]

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27a8b6f0b929b951defe0a26249cf8204acac3d3

91

py

Python

tools/sql/__init__.py

xmy88/AppWishList

780f93ee6154df17e48c9d550debd1a72cf63e4e

[ "Apache-2.0" ]

1

2020-12-02T11:34:59.000Z

tools/sql/__init__.py

xmy88/AppWishList

780f93ee6154df17e48c9d550debd1a72cf63e4e

[ "Apache-2.0" ]

null

tools/sql/__init__.py

xmy88/AppWishList

780f93ee6154df17e48c9d550debd1a72cf63e4e

[ "Apache-2.0" ]

null

# -*- coding:utf-8 -*- """ @author:SiriYang @file: __init__.py @time: 2019.12.24 20:33 """

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1

0

1

0

null

0

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0

5

27e9a6a394ec702ae5a8799c4430e7d525245572

228

py

Python

kompassi/wsgi.py

Siikakala/kompassi

14cdcd966ab689d762cc885e28b6d15465c216f0

[ "CC-BY-3.0" ]

null

kompassi/wsgi.py

Siikakala/kompassi

14cdcd966ab689d762cc885e28b6d15465c216f0

[ "CC-BY-3.0" ]

null

kompassi/wsgi.py

Siikakala/kompassi

14cdcd966ab689d762cc885e28b6d15465c216f0

[ "CC-BY-3.0" ]

null

import os os.environ.setdefault("DJANGO_SETTINGS_MODULE", "kompassi.settings") from django.core.wsgi import get_wsgi_application from dj_static import Cling, MediaCling application = Cling(MediaCling(get_wsgi_application()))

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null

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1

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1

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5

27ff5102020fb76da12be7064492024475ee770c

184

py

Python

ModelsLibraries.py

ekletikstudios/EK

1c4e6e76751293bdddbdba634753458adc99a42e

[ "MIT" ]

null

ModelsLibraries.py

ekletikstudios/EK

1c4e6e76751293bdddbdba634753458adc99a42e

[ "MIT" ]

null

ModelsLibraries.py

ekletikstudios/EK

1c4e6e76751293bdddbdba634753458adc99a42e

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals import uuid from django.db import models from django.urls import reverse from datetime import date from Choices import *

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0.141304

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7

40

26.285714

0.886076

0.11413

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null

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1

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null

0

1

0

1

0

1

0

5

7e0df30f99f7a16a384974175e4aec60994bdbb5

177

py

Python

ase-quantumespresso/test_pw.py

renpj/ase-quantumespresso

8aa8ad00f89016374a990ce3764f52e0f720b810

[ "MIT" ]

1

2019-02-06T20:43:26.000Z

ase-quantumespresso/test_pw.py

renpj/ase-quantumespresso

8aa8ad00f89016374a990ce3764f52e0f720b810

[ "MIT" ]

null

ase-quantumespresso/test_pw.py

renpj/ase-quantumespresso

8aa8ad00f89016374a990ce3764f52e0f720b810

[ "MIT" ]

1

2020-04-14T07:16:20.000Z

from pw import * a = PWInput.from_file('../test_files/pw_scf.in') a.write_file('test.in') #a = PWInput.from_file('../test_files/pw_scf_cell.in') #a.write_file('test_cell.in')

22.125

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0.275862

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1

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null

0

1

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5

fd65bd16df064310fb55cfac40c956361784a7cc

360

py

Python

test/unittests/util/test_string_utils.py

assistent-cat/mycroft-core

6f8bae6ba136c9dd66ca47aaadd75e214d006190

[ "Apache-2.0" ]

6,099

2016-05-17T19:41:56.000Z

2022-03-31T15:34:48.000Z

test/unittests/util/test_string_utils.py

assistent-cat/mycroft-core

6f8bae6ba136c9dd66ca47aaadd75e214d006190

[ "Apache-2.0" ]

2,567

2016-05-20T16:23:11.000Z

2022-03-23T01:54:39.000Z

test/unittests/util/test_string_utils.py

assistent-cat/mycroft-core

6f8bae6ba136c9dd66ca47aaadd75e214d006190

[ "Apache-2.0" ]

1,563

2016-05-20T15:06:21.000Z

2022-03-30T01:28:12.000Z

from unittest import TestCase from mycroft.util import camel_case_split class TestStringFunctions(TestCase): def test_camel_case_split(self): """Check that camel case string is split properly.""" self.assertEqual(camel_case_split('MyCoolSkill'), 'My Cool Skill') self.assertEqual(camel_case_split('MyCOOLSkill'), 'My COOL Skill')

36

74

0.744444

46

360

5.630435

0.521739

0.173745

0.216216

0.185328

0.393822

0

0.161111

360

9

75

40

0.857616

0.130556

0

0.156352

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0.333333

1

0.166667

false

0

0.333333

0

0.666667

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null

0

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0

1

0

null

0

1

0

1

0

5

fd6f6d3e5a2f6ff7098b2cd84c28bc4d05e88162

164

py

Python

Django/django-rest-framework/api-level-1/news/admin.py

piaochung/blog

3fc518c6b681e070e46dffaf64fae1086423a5e6

[ "MIT" ]

null

Django/django-rest-framework/api-level-1/news/admin.py

piaochung/blog

3fc518c6b681e070e46dffaf64fae1086423a5e6

[ "MIT" ]

null

Django/django-rest-framework/api-level-1/news/admin.py

piaochung/blog

3fc518c6b681e070e46dffaf64fae1086423a5e6

[ "MIT" ]

null

from django.contrib import admin from .models import Journalist, Article # Register your models here. admin.site.register(Journalist) admin.site.register(Article)

23.428571

39

0.817073

22

164

6.090909

0.545455

0.134328

0.253731

0

0.103659

164

6

40

27.333333

0.911565

0.158537

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

fdd1e28e5effb84cf2035b49d5034eae831551e7

40

py

Python

src/configuration/__init__.py

UoE-TTDS/project

9e98bcab6d561038aea6a987c44211c98068bfed

[ "MIT" ]

2

2016-12-12T21:45:12.000Z

2016-12-19T23:53:43.000Z

src/configuration/__init__.py

UoE-TTDS/project

9e98bcab6d561038aea6a987c44211c98068bfed

[ "MIT" ]

null

src/configuration/__init__.py

UoE-TTDS/project

9e98bcab6d561038aea6a987c44211c98068bfed

[ "MIT" ]

null

from .configuration import Configuration

40

0.9

4

40

9

0.75

0

0.075

40

1

40

0.972973

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fdd3bb983331b45d4d413250dc1a875f1e104b71

182

py

Python

miniProj/miniApp/admin.py

cs-fullstack-2019-spring/django-mini-project5-DB225

c8d6823056a7c68a53c465468b8efc58b873b846

[ "Apache-2.0" ]

null

miniProj/miniApp/admin.py

cs-fullstack-2019-spring/django-mini-project5-DB225

c8d6823056a7c68a53c465468b8efc58b873b846

[ "Apache-2.0" ]

null

miniProj/miniApp/admin.py

cs-fullstack-2019-spring/django-mini-project5-DB225

c8d6823056a7c68a53c465468b8efc58b873b846

[ "Apache-2.0" ]

null

from django.contrib import admin from .models import UserLoginModel, RecipesModel # Register your models here. admin.site.register(UserLoginModel) admin.site.register(RecipesModel)

26

48

0.835165

22

182

6.909091

0.545455

0.118421

0.223684

0

0.093407

182

6

49

30.333333

0.921212

0.142857

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

fde2ea7e65fd557e48f96f35da7bf653b41c7125

151

py

Python

dnnv/verifiers/common/errors.py

nathzi1505/DNNV

16c6e6ecb681ce66196f9274d4a43eede8686319

[ "MIT" ]

33

2019-12-13T18:54:52.000Z

2021-11-16T06:29:29.000Z

dnnv/verifiers/common/errors.py

nathzi1505/DNNV

16c6e6ecb681ce66196f9274d4a43eede8686319

[ "MIT" ]

28

2020-01-30T14:06:03.000Z

2022-01-27T01:07:37.000Z

dnnv/verifiers/common/errors.py

nathzi1505/DNNV

16c6e6ecb681ce66196f9274d4a43eede8686319

[ "MIT" ]

14

2020-04-08T01:57:00.000Z

2021-11-26T09:35:02.000Z

class VerifierError(Exception): pass class VerifierTranslatorError(Exception): pass __all__ = ["VerifierError", "VerifierTranslatorError"]

15.1

54

0.761589

11

151

10.090909

0.545455

0.234234

0

0.145695

151

9

55

16.777778

0.860465

0

0.4

0

0.238411

0.152318

0

1

0

false

0.4

0

0.4

0

1

0

1

null

1

0

1

0

null

0

1

0

5

fde4a63fae8dba9854119e528ffc647317fe9cd5

87

py

Python

docs/admin.py

the-mandarine/mypanamsquad

b34c1c6169a3b7496e171b9536472a1ede0bdc84

[ "Beerware" ]

null

docs/admin.py

the-mandarine/mypanamsquad

b34c1c6169a3b7496e171b9536472a1ede0bdc84

[ "Beerware" ]

null

docs/admin.py

the-mandarine/mypanamsquad

b34c1c6169a3b7496e171b9536472a1ede0bdc84

[ "Beerware" ]

null

from django.contrib import admin from docs.models import Doc admin.site.register(Doc)

17.4

32

0.816092

14

87

5.071429

0.714286

0

0.114943

87

4

33

21.75

0.922078

0

1

0

true

0

0.666667

0

0.666667

0

1

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null

0

1

0

null

0

1

0

1

0

1

0

5

e303814420b445ab0a1c03ba043642eb6872b280

1,209

py

Python

pillow/save-numpy-array-face/main-RGB.py

whitmans-max/python-examples

881a8f23f0eebc76816a0078e19951893f0daaaa

[ "MIT" ]

140

2017-02-21T22:49:04.000Z

2022-03-22T17:51:58.000Z

pillow/save-numpy-array-face/main-RGB.py

whitmans-max/python-examples

881a8f23f0eebc76816a0078e19951893f0daaaa

[ "MIT" ]

5

2017-12-02T19:55:00.000Z

2021-09-22T23:18:39.000Z

pillow/save-numpy-array-face/main-RGB.py

whitmans-max/python-examples

881a8f23f0eebc76816a0078e19951893f0daaaa

[ "MIT" ]

79

2017-01-25T10:53:33.000Z

2022-03-11T16:13:57.000Z

import numpy as np import csv from PIL import Image counter = dict() row = [ 128, 255, 128, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 255, 128, 0, 0, 0, 128, 255, 128, 128, 255, 128, 128, 255, 128, 128, 255, 128, 128, 255, 128, 0, 0, 0, 0, 0, 0, 128, 255, 128, 0, 0, 0, 128, 255, 128, 0, 0, 0, 128, 255, 128, 0, 0, 0, 0, 0, 0, 128, 255, 128, 128, 255, 128, 128, 255, 128, 128, 255, 128, 128, 255, 128, 0, 0, 0, 0, 0, 0, 128, 255, 128, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 255, 128, 0, 0, 0, 0, 0, 0, 128, 255, 128, 128, 255, 128, 128, 255, 128, 128, 255, 128, 128, 255, 128, 0, 0, 0, 128, 255, 128, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 128, 255, 128, 'face' ] pixels = row[:-1] pixels = np.array(pixels, dtype='uint8') pixels = pixels.reshape((7, 7, 3)) image = Image.fromarray(pixels) label = row[-1] if label not in counter: counter[label] = 0 counter[label] += 1 filename = '{}{}.png'.format(label, counter[label]) image.save(filename) print('saved:', filename)

34.542857

112

0.463193

206

1,209

2.718447

0.165049

0.228571

0.283929

0.3

0.519643

0

0.385806

0.358974

1,209

34

113

35.558824

0.336774

0

0.2

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0.019024

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1

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false

0

0.12

0

0.12

0.04

0

null

1

0

1

0

1

0

null

0

5

e30b47689b78b58e7214784dfd47cb6c8e82a0e0

232,266

py

Python

classicrack/ngrams/trigrams.py

starkfire/classicrack

ed7200de76587167fe2f0ad7677431c799ca009d

[ "MIT" ]

1

2020-10-18T11:26:49.000Z

classicrack/ngrams/trigrams.py

starkfire/classicrack

ed7200de76587167fe2f0ad7677431c799ca009d

[ "MIT" ]

null

classicrack/ngrams/trigrams.py

starkfire/classicrack

ed7200de76587167fe2f0ad7677431c799ca009d

[ "MIT" ]

null

# fetched from http://practicalcryptography.com/media/cryptanalysis/files/english_trigrams.txt.zip trigrams = {'THE': 77534223, 'AND': 30997177, 'ING': 30679488, 'ENT': 17902107, 'ION': 17769261, 'HER': 15277018, 'FOR': 14686159, 'THA': 14222073, 'NTH': 14115952, 'INT': 13656197, 'ERE': 13287155, 'TIO': 13285065, 'TER': 12769843, 'EST': 11956466, 'ERS': 11823017, 'ATI': 11227573, 'HAT': 10900482, 'ATE': 10712298, 'ALL': 10501105, 'ETH': 10304110, 'HES': 10189449, 'VER': 10156140, 'HIS': 10051039, 'OFT': 9434246, 'ITH': 9142241, 'FTH': 9036651, 'STH': 9024058, 'OTH': 8869058, 'RES': 8835871, 'ONT': 8757161, 'DTH': 8745845, 'ARE': 8741156, 'REA': 8700830, 'EAR': 8697937, 'WAS': 8640940, 'SIN': 8629893, 'STO': 8556837, 'TTH': 8476119, 'STA': 8399345, 'THI': 8363593, 'TIN': 8218047, 'TED': 8041574, 'ONS': 8021511, 'EDT': 8020254, 'WIT': 8004722, 'SAN': 7891127, 'DIN': 7875604, 'ORT': 7874634, 'CON': 7783588, 'RTH': 7614477, 'EVE': 7496438, 'ECO': 7431806, 'ERA': 7356760, 'IST': 7313698, 'NGT': 7144484, 'AST': 7076453, 'ILL': 6975276, 'COM': 6822254, 'ORE': 6741972, 'IVE': 6712953, 'NCE': 6427055, 'ONE': 6425910, 'EDI': 6392677, 'PRO': 6391322, 'ESS': 6386660, 'OUT': 6378894, 'EIN': 6185157, 'ATT': 6182518, 'MEN': 6180305, 'HEC': 6149122, 'ESA': 6111223, 'HEN': 6104692, 'INA': 6075550, 'ERI': 6050105, 'ERT': 5996178, 'AME': 5865810, 'ITI': 5865519, 'OME': 5860498, 'SON': 5847185, 'ART': 5831801, 'MAN': 5817313, 'EAN': 5799025, 'ONA': 5779945, 'EOF': 5756556, 'TOR': 5747955, 'HEA': 5690657, 'RAN': 5689705, 'RIN': 5638699, 'INE': 5633622, 'EDA': 5631878, 'NTO': 5586276, 'AVE': 5572665, 'NIN': 5546959, 'OVE': 5531804, 'OUN': 5481400, 'AIN': 5432669, 'ANT': 5421991, 'STR': 5396497, 'ETO': 5376005, 'HEM': 5373422, 'SOF': 5368053, 'PER': 5287148, 'NDE': 5281816, 'STE': 5280710, 'NTE': 5254251, 'EAS': 5242816, 'DTO': 5221682, 'OUR': 5202269, 'RED': 5156973, 'ROM': 5100537, 'TOF': 5096219, 'GHT': 5092181, 'TOT': 5056852, 'ESE': 5051138, 'CHA': 5041682, 'ICA': 5019144, 'HEI': 5014871, 'HIN': 5012646, 'IDE': 4997387, 'NDT': 4988098, 'HAN': 4986889, 'TAN': 4986672, 'LIN': 4958736, 'NOT': 4926753, 'DER': 4926618, 'ECT': 4884814, 'TRA': 4876453, 'IGH': 4863948, 'FRO': 4829903, 'EAT': 4829589, 'STI': 4809152, 'HEP': 4734063, 'NDI': 4733858, 'INS': 4731177, 'SHE': 4695713, 'NAL': 4588739, 'PLA': 4569489, 'ALS': 4535715, 'EEN': 4523428, 'NTI': 4517533, 'YOU': 4497537, 'LAN': 4497041, 'UND': 4458299, 'NDA': 4455712, 'RAT': 4421262, 'LEA': 4411707, 'CAN': 4410865, 'HAS': 4380710, 'NDS': 4369577, 'NGA': 4351576, 'HEL': 4339499, 'HED': 4315177, 'INC': 4296681, 'USE': 4234618, 'ESI': 4227261, 'GTH': 4226728, 'ASA': 4218160, 'HET': 4213058, 'NTS': 4199148, 'HAV': 4185092, 'HEW': 4184148, 'THO': 4180901, 'BUT': 4177438, 'NAN': 4169159, 'ASS': 4163441, 'HEF': 4130591, 'IES': 4122201, 'RET': 4119632, 'END': 4086364, 'PAR': 4078396, 'WER': 4049354, 'CTI': 4040752, 'REN': 4028281, 'REC': 4007198, 'CAL': 3993323, 'ITS': 3991750, 'REE': 3967861, 'ENE': 3964480, 'RST': 3957939, 'EAL': 3953609, 'ANA': 3928099, 'NST': 3917821, 'COU': 3904778, 'TUR': 3898211, 'MIN': 3872245, 'ITY': 3867433, 'YTH': 3864146, 'HEY': 3860009, 'ECA': 3843331, 'OUL': 3841433, 'LLE': 3814820, 'ARD': 3801093, 'ROU': 3800095, 'ANC': 3795939, 'OST': 3793366, 'PRE': 3756624, 'AGE': 3754029, 'EFO': 3748577, 'LES': 3743640, 'SSI': 3725958, 'EMA': 3718163, 'ESO': 3717656, 'TAT': 3713099, 'ATH': 3709084, 'WOR': 3693086, 'UST': 3688271, 'HEB': 3686363, 'EWA': 3681800, 'SHO': 3671437, 'IND': 3654793, 'SED': 3611490, 'HOU': 3592900, 'LLY': 3592380, 'ULD': 3587562, 'ASE': 3574910, 'URE': 3574802, 'ONO': 3567789, 'ELE': 3563169, 'ENC': 3544513, 'NAT': 3534314, 'EAD': 3528638, 'WHE': 3521734, 'ELL': 3518676, 'BLE': 3507036, 'KIN': 3501761, 'ANS': 3499108, 'TIC': 3488924, 'ALI': 3484802, 'SCO': 3482956, 'ERO': 3478803, 'WHI': 3477798, 'CES': 3462307, 'OWN': 3448194, 'NTA': 3445108, 'ACT': 3435753, 'BER': 3434019, 'VEN': 3419784, 'TIM': 3398024, 'DON': 3379285, 'DAN': 3372178, 'OSE': 3371757, 'ICE': 3371391, 'ISA': 3370411, 'TON': 3353323, 'DEN': 3344602, 'NGS': 3330887, 'UGH': 3317738, 'NES': 3309971, 'LAT': 3301464, 'TAL': 3291050, 'EDO': 3288422, 'TEN': 3283334, 'IME': 3280655, 'EME': 3269842, 'ACK': 3266991, 'TES': 3261242, 'PLE': 3255207, 'OUS': 3244841, 'OFF': 3240799, 'TTO': 3212842, 'CHI': 3205773, 'ANI': 3205086, 'ORM': 3199470, 'NED': 3184818, 'ENS': 3182416, 'SHA': 3173536, 'MOR': 3166737, 'ISS': 3165374, 'ITE': 3156935, 'NGE': 3151309, 'TIS': 3146867, 'ORA': 3143350, 'LLI': 3136609, 'EDE': 3129961, 'SSE': 3127188, 'ADE': 3123890, 'RIE': 3113740, 'AID': 3113433, 'EMO': 3110111, 'RAL': 3107661, 'SIT': 3101675, 'OIN': 3088712, 'HTH': 3060456, 'TRE': 3052381, 'ANY': 3050533, 'AKE': 3044556, 'ERN': 3041646, 'MER': 3035537, 'RIC': 3027796, 'DIS': 3027620, 'ISH': 3024492, 'OUG': 3024430, 'INI': 3019795, 'ONG': 3012833, 'NTR': 3012084, 'ELI': 3008425, 'WIL': 3000772, 'LED': 2999231, 'SAR': 2998776, 'HOW': 2984334, 'EDB': 2964266, 'ICH': 2961735, 'SPE': 2959184, 'SEA': 2956202, 'LIT': 2955844, 'YIN': 2951913, 'SAI': 2950251, 'NDO': 2945961, 'GIN': 2943401, 'SHI': 2938082, 'ORD': 2930631, 'MON': 2928062, 'ENA': 2927601, 'NEW': 2923860, 'POR': 2913196, 'SER': 2910499, 'IAL': 2904791, 'ORI': 2904248, 'TTE': 2896816, 'MAR': 2888260, 'EPR': 2880538, 'ACH': 2875296, 'HAR': 2871397, 'YEA': 2868255, 'TRI': 2866053, 'CHE': 2845883, 'TEA': 2838622, 'UNT': 2838483, 'OMP': 2837254, 'WHO': 2814944, 'TAR': 2792635, 'OWE': 2781353, 'RIT': 2761257, 'DED': 2753361, 'ORS': 2748974, 'DAY': 2743116, 'HEE': 2740198, 'THR': 2735049, 'EIR': 2733155, 'OND': 2727008, 'MES': 2724139, 'EFI': 2723419, 'HAD': 2720653, 'NER': 2711700, 'ELA': 2709547, 'LET': 2707044, 'LSO': 2705546, 'RIS': 2704354, 'IRE': 2671468, 'ISI': 2670537, 'MET': 2662370, 'ARS': 2649688, 'HIC': 2647497, 'CEN': 2640052, 'ARI': 2638406, 'FIN': 2636201, 'TOB': 2630326, 'NSI': 2628939, 'LAS': 2628928, 'OPE': 2622250, 'LAR': 2615291, 'DES': 2611133, 'FTE': 2609919, 'NIT': 2603876, 'SEN': 2603148, 'ANG': 2602649, 'SOM': 2589499, 'ABO': 2580787, 'SIO': 2579046, 'TWO': 2579039, 'IAN': 2576268, 'EIS': 2575332, 'TSA': 2574013, 'NGI': 2571550, 'UNI': 2567464, 'SES': 2562382, 'REP': 2561408, 'RAC': 2559421, 'TOP': 2544041, 'ABL': 2540517, 'ETI': 2525353, 'EBE': 2524168, 'EHA': 2512754, 'NOW': 2510743, 'ONI': 2508299, 'VES': 2501984, 'FIR': 2498628, 'ERC': 2496623, 'OFA': 2496302, 'ACE': 2494820, 'SAL': 2486424, 'GET': 2470450, 'APP': 2466311, 'ANE': 2464984, 'RSA': 2460648, 'NOF': 2459001, 'HEH': 2449367, 'GRE': 2446901, 'WIN': 2446474, 'CAR': 2441448, 'ETE': 2441107, 'MAT': 2437642, 'CHO': 2434122, 'LAY': 2432717, 'SWE': 2405370, 'ESP': 2403354, 'PRI': 2401791, 'TIV': 2399821, 'ROF': 2399401, 'GRA': 2397193, 'LLO': 2396797, 'COR': 2395975, 'EAC': 2395043, 'NIS': 2393749, 'DIT': 2388160, 'GAN': 2383084, 'GTO': 2380628, 'ENO': 2377544, 'BOU': 2375317, 'OBE': 2373367, 'ESH': 2364550, 'TOS': 2357896, 'ERY': 2357442, 'RMA': 2355852, 'NGO': 2355332, 'EWI': 2353887, 'ARA': 2352538, 'RTO': 2347763, 'REL': 2346911, 'OMA': 2338186, 'ALA': 2336606, 'ASI': 2327348, 'TST': 2322274, 'UTT': 2320714, 'IRS': 2319648, 'YAN': 2319387, 'LLA': 2318801, 'SFO': 2317576, 'ORK': 2313798, 'ETT': 2310024, 'LTH': 2309490, 'SID': 2309025, 'ASO': 2302496, 'SWI': 2302441, 'ITA': 2296822, 'SET': 2293924, 'TWA': 2290810, 'ERM': 2287584, 'EPA': 2287225, 'RON': 2286879, 'TIT': 2286372, 'AFT': 2285964, 'DRE': 2276501, 'TLE': 2274431, 'MIL': 2272608, 'DBY': 2271890, 'ALE': 2270031, 'PEN': 2258154, 'BEC': 2255869, 'MBE': 2249956, 'TOA': 2249363, 'HEG': 2247902, 'SCH': 2241757, 'SIS': 2237771, 'RTI': 2236581, 'HEO': 2235077, 'LOW': 2229147, 'LIS': 2227116, 'OLL': 2221181, 'WAR': 2218688, 'ALT': 2217527, 'ELO': 2217042, 'TRO': 2211596, 'CAT': 2201423, 'MED': 2201202, 'LIC': 2199356, 'HIL': 2195082, 'ILE': 2194746, 'THT': 2194530, 'REM': 2192851, 'RRE': 2192796, 'AYS': 2189923, 'OLI': 2188506, 'RSO': 2185861, 'NSA': 2176150, 'OMM': 2171097, 'OLD': 2165975, 'CRE': 2144746, 'ATA': 2142046, 'ISE': 2139169, 'CIA': 2122300, 'POS': 2117203, 'GER': 2116445, 'SMA': 2104563, 'UTI': 2103488, 'STS': 2101136, 'SEC': 2100837, 'SBE': 2099662, 'ENI': 2086703, 'SRE': 2085472, 'LON': 2085276, 'ISC': 2083075, 'NSE': 2074596, 'NOR': 2069326, 'BEE': 2065528, 'ANO': 2063752, 'NCO': 2060275, 'FER': 2058315, 'ITT': 2050561, 'SNO': 2047854, 'EPO': 2044817, 'EON': 2044067, 'EDS': 2037518, 'EAM': 2036924, 'ESC': 2036009, 'FIC': 2033404, 'ECH': 2028173, 'WAY': 2027041, 'VED': 2026846, 'IKE': 2026414, 'ALO': 2023953, 'YOF': 2021352, 'ASH': 2015194, 'OTE': 2008201, 'OOK': 1999949, 'ETA': 1996461, 'ERF': 1988818, 'ONC': 1984989, 'EMI': 1982819, 'ECI': 1972328, 'ATS': 1972278, 'ERV': 1970915, 'RSI': 1967666, 'SST': 1964979, 'ILI': 1962435, 'EED': 1955714, 'ARY': 1952466, 'SSO': 1951058, 'MTH': 1947257, 'VEL': 1945990, 'DAT': 1941336, 'MEA': 1936265, 'ESU': 1936169, 'URI': 1935162, 'PAN': 1932891, 'RCH': 1926389, 'UTH': 1926382, 'SPO': 1923682, 'WOU': 1923420, 'FFE': 1922327, 'SEL': 1921792, 'REI': 1917688, 'RGE': 1916665, 'RSE': 1915405, 'TOM': 1913479, 'USI': 1911341, 'EGA': 1900673, 'SAS': 1899943, 'SSA': 1897725, 'ATO': 1892931, 'ERW': 1888240, 'OOD': 1886459, 'AMA': 1883841, 'SAT': 1883499, 'ECE': 1883004, 'MPL': 1882970, 'TSO': 1879869, 'GEN': 1874679, 'ARR': 1868467, 'DEA': 1866349, 'SCA': 1864375, 'DOF': 1863197, 'UAL': 1862470, 'DBE': 1858905, 'EWO': 1857253, 'NSO': 1856959, 'RTE': 1856509, 'VIN': 1851748, 'ADI': 1851016, 'NDW': 1850414, 'NDH': 1849404, 'EDF': 1848247, 'SWH': 1844352, 'SEE': 1841310, 'TOC': 1836740, 'TCH': 1832199, 'EWH': 1821567, 'EBA': 1811725, 'ONL': 1806999, 'TEM': 1805921, 'DWI': 1790037, 'ERR': 1787600, 'LEC': 1784146, 'LAC': 1781542, 'EOP': 1780687, 'TEL': 1776664, 'AMI': 1770347, 'EHE': 1769301, 'DFO': 1768076, 'IEN': 1767735, 'UCH': 1765400, 'NDC': 1765357, 'ELY': 1763560, 'DST': 1760687, 'ICI': 1759901, 'EDW': 1744328, 'AUS': 1739916, 'NFO': 1738113, 'NTT': 1737999, 'NNE': 1735576, 'EWE': 1733602, 'SUR': 1732785, 'EXP': 1731960, 'BET': 1726872, 'KET': 1724117, 'INF': 1723019, 'ETR': 1721605, 'YTO': 1720045, 'RDE': 1718798, 'RCE': 1711836, 'OMT': 1711478, 'EVI': 1709656, 'VET': 1709103, 'PEC': 1705376, 'RAI': 1704886, 'ARL': 1699355, 'YST': 1698599, 'SOU': 1698194, 'HIM': 1697355, 'REF': 1690774, 'LIK': 1684406, 'GES': 1684204, 'CTO': 1684050, 'URN': 1681169, 'FOU': 1679554, 'LLS': 1678097, 'RNE': 1676735, 'WHA': 1674516, 'TOW': 1674141, 'NDR': 1673266, 'DAS': 1668669, 'SSU': 1668562, 'SPR': 1665665, 'OPL': 1665409, 'RAD': 1657646, 'ESW': 1655566, 'ONF': 1653251, 'COL': 1653235, 'OMI': 1652948, 'DUC': 1647753, 'MOS': 1646365, 'ARK': 1645609, 'TAI': 1644521, 'ICK': 1643469, 'HOS': 1637290, 'ULT': 1637016, 'EMB': 1634801, 'IGN': 1631196, 'HOO': 1628375, 'TOO': 1625886, 'NEA': 1624887, 'ITW': 1616943, 'PPE': 1615061, 'FFI': 1612124, 'ULA': 1611192, 'NAM': 1609688, 'MIS': 1605479, 'CED': 1603598, 'LOS': 1602442, 'GAM': 1602247, 'NAS': 1601741, 'REG': 1597733, 'LIE': 1594739, 'OLO': 1594420, 'TWE': 1587270, 'ANN': 1586455, 'TOD': 1581803, 'AIL': 1580257, 'OTA': 1579930, 'ISO': 1579642, 'AYE': 1577851, 'TCO': 1576339, 'GRO': 1575747, 'CAM': 1574337, 'EFE': 1573141, 'ONW': 1566810, 'BEA': 1565698, 'NGL': 1565333, 'WEE': 1562110, 'EDU': 1553785, 'REW': 1548929, 'AGA': 1546877, 'TIL': 1545610, 'ODE': 1543174, 'ORY': 1541795, 'ERB': 1541342, 'BAC': 1540779, 'LEN': 1536397, 'NLY': 1536381, 'IMP': 1535894, 'ARO': 1532759, 'EHI': 1530705, 'AMP': 1530333, 'MPA': 1529992, 'SPA': 1528054, 'IVI': 1526689, 'ICT': 1522977, 'STT': 1520500, 'NET': 1518271, 'RTA': 1515487, 'HRE': 1514079, 'ERH': 1512676, 'EET': 1506042, 'ROW': 1502520, 'SOR': 1500949, 'EPE': 1494253, 'TIE': 1489751, 'NCH': 1489431, 'TRU': 1489404, 'MAL': 1487982, 'CTE': 1487884, 'NDM': 1484172, 'ATC': 1482545, 'FAC': 1480054, 'TWI': 1479582, 'ORC': 1478504, 'DCO': 1476786, 'NDP': 1474820, 'FRE': 1474808, 'OFS': 1472502, 'ARG': 1472465, 'IMA': 1471252, 'DEC': 1470797, 'ENG': 1470110, 'RIA': 1469607, 'OWI': 1466971, 'EIT': 1466665, 'POL': 1460040, 'KED': 1458064, 'INN': 1457052, 'BLI': 1455188, 'DOW': 1453863, 'ETW': 1453345, 'CLU': 1453288, 'HOL': 1452519, 'AIR': 1452477, 'RRI': 1451834, 'RIG': 1451573, 'SLA': 1451493, 'ROP': 1450690, 'OFI': 1442502, 'TOH': 1442156, 'NON': 1440732, 'OOL': 1439680, 'ISP': 1438457, 'MAK': 1436485, 'REV': 1436262, 'EQU': 1435915, 'LYT': 1435747, 'JUS': 1432941, 'LYA': 1432205, 'OLE': 1432129, 'CIT': 1430939, 'PEA': 1429742, 'VEA': 1428357, 'KNO': 1427519, 'OCA': 1426991, 'TAK': 1426629, 'ACC': 1425476, 'CER': 1423677, 'ADA': 1423365, 'SUP': 1422660, 'NGW': 1422627, 'PEO': 1422371, 'DSO': 1419444, 'RDI': 1418963, 'TOU': 1417176, 'CAU': 1416389, 'ROV': 1414811, 'TFO': 1411495, 'STU': 1409543, 'PIN': 1407254, 'TLY': 1402323, 'IED': 1397547, 'UES': 1397451, 'TSI': 1397349, 'AWA': 1393952, 'LER': 1393473, 'WEL': 1391559, 'EPL': 1386318, 'HOR': 1386236, 'ERP': 1385471, 'HRO': 1383286, 'UTE': 1381204, 'OSS': 1381105, 'TBE': 1380773, 'TYO': 1377771, 'TOG': 1377004, 'HEU': 1374864, 'BYT': 1372919, 'NGF': 1372845, 'NGH': 1370514, 'HAL': 1366096, 'BAN': 1364335, 'ISM': 1364013, 'ROL': 1362117, 'ATU': 1360997, 'SAM': 1357990, 'HOM': 1356978, 'DHI': 1356938, 'ILD': 1353068, 'GAI': 1352873, 'RDS': 1350997, 'EDH': 1350936, 'INO': 1349660, 'EGO': 1344776, 'EGI': 1343491, 'LLT': 1342420, 'ARC': 1342124, 'RAM': 1336917, 'OTO': 1333585, 'CLE': 1331933, 'DHE': 1330580, 'ACO': 1326689, 'ORL': 1324745, 'CAS': 1323734, 'RIV': 1323585, 'OFC': 1322736, 'ORN': 1321723, 'RNA': 1320486, 'URS': 1319719, 'AVI': 1319342, 'NAR': 1308406, 'UBL': 1305930, 'TTI': 1303589, 'MEM': 1299230, 'AMO': 1298805, 'RME': 1297846, 'QUI': 1297027, 'QUE': 1295216, 'NEE': 1295028, 'NDF': 1293951, 'INH': 1291301, 'INK': 1291259, 'EHO': 1290659, 'NCL': 1287912, 'OCK': 1285973, 'VIC': 1285160, 'RTS': 1285059, 'ETS': 1283594, 'LEG': 1280961, 'CLA': 1280292, 'TSE': 1278787, 'EOR': 1277439, 'NCI': 1277098, 'SLI': 1276516, 'ERG': 1275250, 'DID': 1273273, 'RCO': 1272521, 'BAS': 1269571, 'LOC': 1267778, 'EBU': 1267644, 'HIG': 1266946, 'ASP': 1264261, 'EXT': 1264120, 'EGR': 1263778, 'DIA': 1263355, 'TAB': 1262022, 'BRI': 1258167, 'CEI': 1256877, 'RAS': 1256196, 'DAL': 1253918, 'ALC': 1252782, 'RUN': 1252259, 'PPO': 1251513, 'OFH': 1251418, 'CKE': 1251112, 'ATW': 1251071, 'CEA': 1249363, 'OTT': 1248716, 'BAL': 1247492, 'NSH': 1247220, 'MAI': 1247125, 'DAR': 1246732, 'ASB': 1246692, 'RFO': 1246153, 'VIS': 1246067, 'OWA': 1244485, 'UDE': 1244334, 'RSH': 1242784, 'IFI': 1242367, 'LOO': 1237754, 'HIT': 1236658, 'UAR': 1235409, 'CET': 1234925, 'OVI': 1230666, 'NDB': 1229829, 'TOL': 1229522, 'UTO': 1228795, 'LEM': 1226802, 'BRO': 1226231, 'VID': 1226025, 'RIO': 1225040, 'UCT': 1223250, 'TRY': 1221955, 'EFR': 1219841, 'SDE': 1218798, 'DHA': 1216559, 'BEL': 1216264, 'BIL': 1216161, 'TAS': 1212346, 'SUC': 1212180, 'EBO': 1211243, 'ORO': 1210118, 'SEV': 1209104, 'MIT': 1207978, 'YCO': 1205248, 'NWH': 1202340, 'NEO': 1201979, 'RVI': 1201676, 'DEV': 1201012, 'EUN': 1199397, 'WAN': 1199161, 'SIG': 1198981, 'THS': 1198494, 'ASC': 1198386, 'DSA': 1195432, 'TAC': 1194122, 'EMP': 1190815, 'ANK': 1190563, 'RKE': 1189902, 'NHE': 1187989, 'NME': 1186511, 'NRE': 1186133, 'ROS': 1185577, 'NGC': 1185531, 'MAY': 1184263, 'UNC': 1184159, 'NIC': 1179045, 'NNI': 1178268, 'URA': 1178165, 'FUL': 1177774, 'OCO': 1176155, 'OSI': 1175625, 'DEF': 1173126, 'NGR': 1172606, 'TEC': 1171805, 'SAY': 1167136, 'NBE': 1166379, 'YRE': 1163260, 'NTL': 1158736, 'DGE': 1158225, 'SAC': 1157300, 'SFR': 1156780, 'TSH': 1155832, 'ISN': 1155747, 'LDI': 1154685, 'ARM': 1154487, 'CUR': 1154026, 'EAG': 1152862, 'NDL': 1152382, 'ELD': 1151107, 'SMO': 1151066, 'ORG': 1150650, 'LLB': 1146334, 'DEL': 1142439, 'POI': 1142345, 'IAT': 1138390, 'URT': 1138386, 'KER': 1138342, 'SOL': 1135331, 'TMA': 1135216, 'MUS': 1134974, 'BEI': 1129248, 'QUA': 1128688, 'LYS': 1127961, 'DWA': 1126001, 'NMA': 1124451, 'HIP': 1121067, 'ROD': 1117901, 'EFA': 1117822, 'INV': 1117314, 'ISL': 1114965, 'PON': 1114638, 'YON': 1110394, 'PAS': 1110326, 'LIA': 1110281, 'REO': 1109542, 'LIF': 1106740, 'TIA': 1101436, 'CRI': 1101185, 'NSU': 1101079, 'RLY': 1101077, 'LBE': 1100732, 'OHA': 1100513, 'NDD': 1099241, 'HAM': 1095060, 'EPT': 1094478, 'EBR': 1092945, 'BES': 1091585, 'NGP': 1087836, 'YHA': 1086604, 'TME': 1085683, 'LEF': 1085376, 'ADD': 1085339, 'OFM': 1084713, 'MAD': 1084502, 'DMA': 1083866, 'DUR': 1082620, 'MME': 1082430, 'MAS': 1082265, 'IZE': 1081305, 'ICS': 1081149, 'YBE': 1079784, 'DNO': 1079585, 'EGE': 1078863, 'GAT': 1078328, 'DDE': 1077820, 'CUL': 1076597, 'UTA': 1073065, 'MEO': 1071803, 'LCO': 1070168, 'VAL': 1068682, 'ATR': 1068298, 'ECU': 1066153, 'GED': 1064754, 'NDU': 1064326, 'YAR': 1064023, 'DET': 1064013, 'ISF': 1063940, 'OFP': 1062855, 'SPI': 1061878, 'ROT': 1057524, 'ROB': 1056410, 'PED': 1054595, 'LDE': 1053046, 'OTI': 1053021, 'EEK': 1052504, 'DEM': 1052486, 'BEF': 1052183, 'MOV': 1050191, 'ELS': 1046167, 'IOU': 1044561, 'SWA': 1043925, 'ERL': 1043663, 'IMI': 1042889, 'FAM': 1042513, 'NEX': 1041420, 'LOF': 1041254, 'FAN': 1037972, 'OES': 1036896, 'SCR': 1036292, 'ISW': 1035637, 'ULL': 1035476, 'ERD': 1035369, 'INM': 1031264, 'SOC': 1030632, 'RNI': 1029771, 'EEL': 1029077, 'APA': 1024211, 'MIC': 1022874, 'DEP': 1021947, 'RDA': 1021457, 'PIT': 1020699, 'OGR': 1020261, 'SUN': 1018713, 'ESF': 1016834, 'IDA': 1015249, 'GAR': 1014790, 'CKS': 1013705, 'RAG': 1012208, 'GEO': 1010675, 'GOO': 1010645, 'LUD': 1010627, 'NHI': 1010492, 'IFE': 1010418, 'BRA': 1010344, 'DDI': 1007782, 'PAT': 1007038, 'CEO': 1006221, 'NGB': 1005382, 'KES': 1004681, 'YER': 1003964, 'NWA': 1003919, 'DRA': 1002812, 'LYI': 1002743, 'ODU': 1002645, 'PUB': 1001460, 'INU': 1000911, 'ORR': 1000290, 'AYA': 996464, 'LOR': 995464, 'TTL': 994910, 'HON': 993715, 'SAB': 992618, 'NHA': 992520, 'LDB': 991325, 'LIV': 991168, 'EDR': 990568, 'SEO': 990217, 'OAD': 989827, 'RMO': 989810, 'DLE': 988862, 'ECR': 987834, 'UDI': 987132, 'GON': 986074, 'ALF': 985711, 'DIE': 985489, 'RWA': 985285, 'LST': 984346, 'LIG': 983332, 'RID': 983247, 'RMI': 983003, 'OFE': 982887, 'URC': 982799, 'SIC': 981605, 'APE': 981487, 'AYI': 979574, 'BOT': 978895, 'EYE': 978505, 'FRI': 977788, 'ILA': 977050, 'RYO': 976002, 'ADO': 975029, 'ALM': 973709, 'SAG': 971371, 'NWI': 970417, 'WED': 968979, 'NNO': 967863, 'ABI': 967606, 'RVE': 963010, 'EES': 962543, 'AKI': 961187, 'FIE': 958012, 'BOR': 957789, 'DOU': 956789, 'EEP': 956756, 'DIF': 955736, 'TET': 953672, 'ORP': 951409, 'ITO': 950819, 'AYT': 950677, 'ONH': 950343, 'OBA': 949834, 'TUD': 949705, 'VIE': 948746, 'NYO': 948617, 'SBU': 947427, 'DIC': 946442, 'DRI': 944706, 'OFO': 944159, 'OAN': 942758, 'RYA': 941495, 'RUS': 940945, 'XPE': 940860, 'NCA': 940507, 'NVE': 940457, 'ILY': 940279, 'HOT': 940089, 'NAG': 939358, 'UTS': 938259, 'LRE': 936657, 'RAP': 936308, 'ECL': 935699, 'DSE': 935507, 'OUP': 934968, 'LEO': 934394, 'UPP': 932971, 'ROA': 932716, 'NAD': 932247, 'BUS': 931889, 'NTW': 931065, 'ALP': 930693, 'URR': 929826, 'YFO': 927898, 'OMO': 927335, 'ONM': 926902, 'NTU': 925885, 'OWS': 925801, 'IFF': 924171, 'RSW': 922934, 'ASW': 922855, 'ASN': 921959, 'HAP': 921917, 'CCE': 921547, 'CRO': 920008, 'IER': 919867, 'CCO': 918426, 'CAP': 917801, 'LEV': 917563, 'TSW': 916039, 'KEN': 915282, 'OKE': 914528, 'OWT': 913700, 'ASM': 913312, 'NGM': 909434, 'CTS': 908610, 'NOU': 908318, 'PUT': 907446, 'REB': 907423, 'TTA': 907276, 'EDM': 907261, 'LIO': 905570, 'NEY': 903730, 'ONB': 902750, 'SFI': 902516, 'TAG': 899915, 'EEM': 899762, 'UMB': 898970, 'CRA': 897487, 'ANU': 897419, 'SWO': 896032, 'WEV': 894124, 'EIG': 894075, 'SSH': 893882, 'EUS': 893372, 'EYO': 893226, 'SIM': 892620, 'GLE': 891111, 'ROC': 890590, 'CIE': 889282, 'LOG': 887902, 'REH': 887583, 'WTH': 887581, 'SLO': 886813, 'EER': 885791, 'IFT': 885634, 'HEV': 885429, 'FIT': 885162, 'TUA': 884810, 'EPU': 883236, 'GOV': 882757, 'GOT': 881689, 'CIN': 881481, 'INW': 881201, 'INP': 880744, 'WES': 880455, 'AGO': 878275, 'AMS': 877451, 'SAP': 877362, 'ITU': 874511, 'OAC': 874056, 'OPP': 873487, 'ETU': 873006, 'WAT': 872808, 'SUS': 872787, 'LAI': 871693, 'ARN': 870961, 'EEA': 870693, 'ITC': 870348, 'ISR': 869416, 'TCA': 869399, 'RLD': 869118, 'ALR': 867408, 'ASK': 866144, 'CTU': 864234, 'LTO': 864157, 'OGE': 863518, 'OOT': 863453, 'EAP': 861991, 'PTI': 860467, 'EDP': 860390, 'FEA': 859460, 'FIL': 859216, 'TWH': 858217, 'NGU': 857993, 'EMS': 855525, 'VEB': 855318, 'UIL': 855123, 'MOT': 853945, 'ROO': 853786, 'RPR': 853610, 'RLI': 853213, 'MPO': 851424, 'ISB': 850560, 'ELF': 850206, 'DFR': 850149, 'SEI': 849888, 'OON': 849833, 'SLE': 849731, 'MOU': 848665, 'NEV': 848535, 'NEC': 847896, 'CLO': 847813, 'IEL': 847624, 'LOT': 847535, 'USA': 846781, 'APR': 843542, 'EDC': 843066, 'RER': 842459, 'LEI': 842440, 'FRA': 842263, 'WEA': 841454, 'NEN': 841269, 'ALW': 841195, 'ESB': 840316, 'BAR': 840216, 'EYA': 839220, 'NEI': 837374, 'NSW': 836504, 'ELP': 835693, 'OLA': 834566, 'EAK': 833378, 'FEN': 832986, 'ESN': 832939, 'RYT': 832890, 'ORH': 830305, 'ANB': 829651, 'LSA': 828413, 'FAR': 826427, 'GIV': 826400, 'PIC': 825459, 'CEP': 825186, 'TOE': 824070, 'DPR': 822558, 'RIM': 822547, 'EAB': 822472, 'PAC': 821850, 'LTI': 816837, 'HOF': 815652, 'ASU': 814744, 'SAF': 814636, 'EWS': 814323, 'STW': 812774, 'EEX': 812632, 'ATM': 812391, 'MPE': 809957, 'TBA': 808271, 'TEE': 807868, 'INB': 807768, 'EAV': 807633, 'DWH': 806469, 'NOM': 803907, 'MUN': 803602, 'ENH': 802824, 'RRO': 801038, 'PET': 800747, 'NSP': 800525, 'MTO': 800464, 'AGR': 800409, 'LEW': 799958, 'RHA': 799892, 'LVE': 799393, 'ALB': 797031, 'ODO': 796908, 'TUN': 793099, 'LWA': 792872, 'GUE': 792851, 'DCA': 791031, 'RAR': 790991, 'RWH': 790470, 'PAI': 789880, 'HOP': 789691, 'ROG': 789669, 'NFR': 789285, 'FAL': 788506, 'ONN': 788333, 'INL': 785826, 'SEP': 785709, 'BAT': 784957, 'SMI': 784836, 'VEM': 783222, 'CUS': 781942, 'EPI': 781039, 'WAL': 780890, 'DSH': 780123, 'LAB': 780098, 'THC': 779681, 'APO': 779192, 'AAN': 778034, 'ODI': 778023, 'FOL': 777834, 'GOF': 777113, 'SQU': 775089, 'SFA': 774151, 'BUR': 773363, 'NAC': 772048, 'RGA': 771129, 'VIL': 768622, 'NGD': 768292, 'OCI': 767682, 'HIR': 767491, 'RHE': 767325, 'USS': 766882, 'EFU': 766869, 'YWI': 766717, 'ESM': 766378, 'YWA': 765965, 'NPR': 765697, 'UME': 764858, 'ODA': 764180, 'OSA': 761513, 'DRO': 760176, 'GHE': 759642, 'GHI': 758796, 'OPR': 758671, 'VAN': 758117, 'LDS': 758046, 'KAN': 757432, 'BEG': 756632, 'RPO': 756089, 'ORW': 755584, 'ISD': 755138, 'DMI': 754985, 'GOI': 754257, 'FUN': 753435, 'OAR': 753004, 'OFR': 752128, 'ONP': 751018, 'RIB': 750630, 'IDI': 750544, 'RWI': 750504, 'LOP': 749405, 'HTO': 749075, 'EDD': 748966, 'STP': 747680, 'MAG': 747120, 'SNE': 747053, 'SEM': 746824, 'ERU': 745597, 'ADT': 745427, 'BUI': 743523, 'MMI': 743346, 'ALK': 741403, 'GAL': 741281, 'IBL': 740604, 'OPU': 739787, 'ALD': 739561, 'OAL': 739052, 'YSA': 738863, 'TSC': 738296, 'IDT': 737288, 'PLI': 736543, 'MUC': 734243, 'NUM': 733495, 'SBA': 733488, 'NEL': 732493, 'NIA': 731949, 'ENU': 731273, 'RUC': 730658, 'LYO': 729096, 'STM': 729012, 'BRE': 728972, 'TOI': 728263, 'ESD': 727442, 'DMO': 727349, 'RYI': 726845, 'OTS': 726751, 'SDA': 726137, 'VOL': 725080, 'DAM': 725025, 'ACA': 723596, 'RBE': 723228, 'PUL': 722952, 'WON': 722713, 'EXA': 722289, 'YED': 722156, 'LSE': 721672, 'ACI': 721498, 'STC': 721341, 'OFW': 721017, 'LIM': 720600, 'ATL': 720504, 'AIS': 720394, 'FLO': 719836, 'CEL': 719551, 'RNO': 719357, 'CHT': 718107, 'STY': 716897, 'BOO': 716442, 'AUG': 716308, 'RYS': 716185, 'UPT': 715152, 'SEX': 713764, 'SPL': 713561, 'RTY': 713321, 'EVA': 712427, 'YSI': 711593, 'OFB': 710199, 'LDR': 708872, 'UIT': 708569, 'CLI': 708407, 'MEI': 708327, 'IOR': 708025, 'DOE': 707379, 'IRA': 706829, 'LYW': 706710, 'IGI': 706526, 'SIV': 706163, 'NAB': 704679, 'LAW': 703214, 'TPR': 702904, 'LDA': 702508, 'AYO': 699492, 'RKI': 699433, 'IDN': 698899, 'NIO': 698381, 'IVA': 698321, 'TYA': 697860, 'PHO': 697238, 'COA': 697032, 'ILT': 697018, 'CHR': 696938, 'NDG': 696524, 'PHI': 694638, 'EFF': 694298, 'EYW': 694094, 'RAF': 693840, 'YIS': 693485, 'ASR': 692889, 'NOV': 692671, 'LYB': 692635, 'AUT': 692495, 'NAP': 692352, 'FEE': 691884, 'NDN': 691649, 'GFO': 691219, 'SUB': 687314, 'SKI': 687268, 'NTY': 686772, 'ASF': 685871, 'OOR': 685384, 'AFF': 684405, 'ENN': 684319, 'SDI': 683865, 'HUR': 683790, 'STL': 682423, 'LYC': 682030, 'DIR': 681719, 'CUT': 680248, 'WEN': 678834, 'AFE': 677985, 'DNE': 677379, 'KTH': 677290, 'PLO': 676417, 'RAB': 675092, 'NFI': 674720, 'YMA': 674417, 'OFL': 673526, 'UNG': 673098, 'ANW': 671305, 'TMO': 670892, 'ENW': 669856, 'GAS': 669056, 'TSS': 668030, 'JEC': 666952, 'FOO': 666339, 'GIS': 666021, 'VAT': 665784, 'LEY': 665497, 'TNE': 665303, 'USH': 664646, 'RNM': 664276, 'TSP': 664116, 'NSC': 663870, 'GEA': 663465, 'DIV': 663392, 'SAD': 662849, 'DSI': 662681, 'FCO': 662572, 'OPO': 661292, 'FHI': 660939, 'EDL': 660146, 'YOR': 659656, 'YCA': 659168, 'IEV': 657853, 'YWE': 657204, 'OMB': 657110, 'IRD': 656794, 'BIG': 656158, 'TIF': 655864, 'DLI': 655395, 'RHI': 654575, 'RCA': 654499, 'GHA': 653609, 'PTH': 651995, 'SGO': 651623, 'YWH': 651447, 'AVA': 650371, 'SIB': 649324, 'GWI': 648238, 'SUM': 648210, 'ATP': 647883, 'LEB': 647227, 'TSU': 646947, 'CKI': 646171, 'FEC': 645871, 'NCR': 645359, 'RLE': 645167, 'SME': 643840, 'CIS': 643554, 'TDO': 643395, 'OLU': 643228, 'KEA': 642826, 'IEW': 642230, 'YSE': 642198, 'MOD': 641999, 'UCE': 641986, 'FAI': 641095, 'NIG': 640768, 'TYE': 639722, 'TLI': 638560, 'TSF': 638419, 'RBA': 637207, 'DOR': 637114, 'ABA': 636023, 'ENB': 635879, 'BLA': 635788, 'RSC': 635650, 'THH': 635356, 'MPI': 634841, 'ADS': 633339, 'MMU': 633203, 'POW': 633181, 'LFO': 632552, 'GST': 631234, 'ASD': 630807, 'EGU': 629493, 'SNT': 627623, 'TNO': 626469, 'ADV': 625751, 'IET': 625730, 'BYA': 625497, 'NVI': 625320, 'AHA': 624623, 'OFD': 622723, 'COV': 622007, 'POP': 621776, 'RRA': 621221, 'NLI': 620769, 'LTE': 620647, 'UCA': 620588, 'DWE': 620118, 'TEI': 620001, 'NUE': 619320, 'FLA': 619320, 'SDO': 618505, 'RIL': 618424, 'IRO': 618372, 'IAM': 617315, 'TEV': 617226, 'ESL': 617035, 'MPR': 616160, 'EDG': 614818, 'MEW': 614610, 'ICO': 613938, 'YAL': 613547, 'YLE': 612247, 'NTF': 610686, 'STB': 610684, 'LYD': 610225, 'EFT': 609753, 'ORB': 609578, 'HTE': 609463, 'CEM': 609095, 'BEN': 608693, 'YAS': 608227, 'KEE': 608204, 'NTC': 607811, 'NTB': 606735, 'UNE': 606148, 'NEM': 605878, 'EOU': 604857, 'OUC': 603583, 'PPL': 603167, 'THU': 602655, 'TEX': 601212, 'ICU': 600343, 'RDO': 600167, 'SEW': 600057, 'SUL': 599610, 'OSP': 599565, 'EXC': 598704, 'OTB': 597457, 'GNE': 597340, 'IDS': 597319, 'KIL': 596517, 'LOV': 596167, 'SYS': 595842, 'IMS': 594877, 'NIV': 594561, 'OOM': 594423, 'STF': 593875, 'IRC': 593467, 'OHI': 593271, 'NMO': 593043, 'ASL': 592890, 'ONV': 592688, 'TDE': 591919, 'OCE': 589867, 'EBI': 589639, 'PTO': 589182, 'LDH': 588186, 'YPE': 586973, 'NIE': 585394, 'NSF': 584634, 'ELT': 584302, 'IBE': 584035, 'FIG': 583619, 'NPA': 583247, 'FAT': 582931, 'LYM': 582806, 'TYT': 582701, 'TYP': 582667, 'DNT': 582639, 'LUE': 582588, 'URO': 581947, 'OWH': 580772, 'OHE': 580308, 'BLO': 579956, 'WRI': 579264, 'HTS': 577913, 'RKS': 576408, 'DEO': 575421, 'HRI': 574942, 'SOT': 574851, 'LYR': 573992, 'DUS': 573106, 'AYB': 572949, 'CHU': 571970, 'TFR': 570894, 'WOM': 570036, 'YDE': 569800, 'BIN': 569494, 'REQ': 569352, 'GGE': 569035, 'MEL': 568097, 'FFO': 567614, 'ARB': 567346, 'SOP': 567101, 'UMA': 566671, 'VIO': 565932, 'INR': 565532, 'RTU': 565492, 'ROR': 565019, 'TAF': 565018, 'DAB': 564586, 'MEE': 564382, 'LEE': 564063, 'INJ': 563954, 'MSE': 563803, 'VEI': 563398, 'BED': 563256, 'BIT': 563243, 'HEK': 563111, 'URY': 563102, 'PPR': 562337, 'TEP': 561626, 'DAC': 560810, 'MAC': 560466, 'ACR': 560392, 'MMA': 560100, 'ENR': 559896, 'UTW': 559890, 'ONR': 559879, 'NJU': 559740, 'EYS': 558978, 'FAS': 558916, 'KTO': 557955, 'ORF': 557739, 'PTE': 557205, 'CID': 557156, 'YSH': 557064, 'VAR': 554992, 'SAW': 554210, 'EAF': 553523, 'TLA': 552885, 'CKA': 552873, 'SIA': 552868, 'OBL': 552685, 'UEN': 552559, 'RSU': 552342, 'OKI': 550803, 'UAT': 550712, 'UET': 550590, 'AJO': 550271, 'COS': 548835, 'CKT': 548249, 'CHW': 547094, 'OAS': 547084, 'LLH': 546923, 'SBO': 546255, 'FEW': 546208, 'MST': 545818, 'SCU': 545747, 'BOA': 545518, 'RRY': 544591, 'EEV': 544371, 'LMA': 543365, 'LYF': 542748, 'VEH': 542516, 'IDO': 542455, 'MID': 542131, 'OIS': 541358, 'TEO': 541333, 'SCI': 540904, 'OWO': 540143, 'UCK': 539189, 'DCH': 539085, 'IRT': 538812, 'OPA': 538667, 'RSS': 538580, 'AGU': 538214, 'RSP': 538077, 'ULE': 537905, 'EKI': 537234, 'BEH': 536853, 'OYE': 536753, 'NWE': 536458, 'DOM': 536014, 'ADY': 535778, 'YPR': 534788, 'NKI': 534130, 'FES': 533859, 'GIT': 533850, 'NFE': 533716, 'SSP': 533611, 'LOU': 532271, 'YMO': 531944, 'URG': 531285, 'PRA': 530776, 'DME': 530452, 'SOW': 530375, 'EDN': 530369, 'SAV': 529041, 'ICL': 527724, 'OPI': 527628, 'LYP': 527472, 'KOF': 527245, 'NLA': 527108, 'LDT': 526989, 'RAV': 526859, 'TFI': 526850, 'DOT': 526027, 'RFA': 525159, 'EAU': 524482, 'NHO': 524339, 'DBA': 524137, 'NIM': 523850, 'CEW': 523836, 'SKE': 523792, 'ENF': 523355, 'RHO': 523322, 'NNA': 523153, 'TPA': 523107, 'WIS': 522583, 'DFI': 521982, 'ANH': 521711, 'API': 521588, 'RPA': 521064, 'LLC': 520280, 'IPA': 520207, 'ADM': 520060, 'GLA': 519295, 'TAP': 519294, 'ABE': 518372, 'ETY': 518266, 'GCO': 517522, 'RMS': 516670, 'LDN': 516405, 'LAM': 515473, 'TAM': 515082, 'YAT': 514887, 'ANP': 513734, 'DLA': 513515, 'IRI': 513467, 'NBU': 513300, 'EMU': 512519, 'NTP': 511651, 'UNS': 510860, 'OLS': 510360, 'DPA': 509809, 'LMO': 509559, 'GUA': 509237, 'IRL': 509126, 'NEF': 508460, 'RBO': 508139, 'PAL': 508003, 'URD': 507800, 'LYH': 507228, 'SCE': 506920, 'ANF': 506607, 'GNI': 506013, 'RIP': 505801, 'URP': 505265, 'IFY': 505167, 'NLE': 504602, 'EPH': 504267, 'EFL': 503910, 'WOO': 503688, 'MMO': 503497, 'IGA': 503497, 'JOH': 502815, 'SRA': 500885, 'ISG': 500728, 'TIR': 499383, 'TTR': 499147, 'THM': 498790, 'YDI': 498661, 'FEL': 498282, 'JOR': 498205, 'DPO': 498043, 'RTR': 497346, 'SUE': 497335, 'YSO': 497210, 'DHO': 497057, 'LPR': 496606, 'RLA': 496560, 'OPT': 496521, 'KSA': 496476, 'CTA': 496458, 'MPT': 496218, 'YHE': 496155, 'DUP': 495800, 'NOL': 495482, 'OSO': 494708, 'HEJ': 494601, 'ALU': 494465, 'GLI': 494378, 'GOA': 494263, 'ITL': 493958, 'CKO': 493446, 'THW': 493160, 'BLY': 493096, 'DSU': 492092, 'HWA': 492002, 'TSB': 491646, 'OFG': 491637, 'RFI': 490437, 'OTR': 490348, 'WNA': 489842, 'OHN': 489451, 'GIO': 488610, 'PUR': 488258, 'MEC': 488180, 'NFL': 487801, 'ZED': 487593, 'ILM': 487242, 'DBU': 486627, 'DUN': 486473, 'OGI': 486249, 'FLI': 486182, 'UCC': 485996, 'NBA': 485692, 'FLE': 485317, 'RAW': 484515, 'EIV': 484190, 'DEB': 484041, 'EOT': 483990, 'UNN': 483956, 'NTM': 483452, 'EVO': 482756, 'MIG': 482184, 'HAI': 482087, 'LDO': 481971, 'OAT': 481479, 'NFA': 481444, 'SSC': 481234, 'LUS': 481140, 'NAF': 480881, 'IWA': 480253, 'EUP': 479710, 'CIP': 478875, 'PAY': 477785, 'CHS': 477768, 'ATF': 477407, 'AMB': 477033, 'ODY': 477028, 'AGI': 476470, 'YME': 476223, 'EXI': 476011, 'TPE': 475755, 'RPE': 475555, 'IMM': 475550, 'LYE': 473623, 'TBU': 473327, 'CTT': 472606, 'LLP': 472117, 'LHA': 471050, 'TDI': 469714, 'ILS': 469685, 'EUR': 469411, 'LBU': 469269, 'TYI': 469136, 'HUN': 468989, 'HIE': 468968, 'GSA': 468704, 'NIF': 468003, 'NKS': 467976, 'WNT': 467949, 'ATB': 467250, 'DDO': 466728, 'GEL': 466030, 'LEP': 465778, 'MSA': 465592, 'ENM': 464945, 'OMS': 464540, 'YWO': 464136, 'RYE': 463932, 'DAP': 463668, 'OSH': 463662, 'HCO': 463355, 'APT': 462589, 'IRM': 462520, 'MAJ': 461996, 'AIT': 461895, 'YFR': 461193, 'OCR': 461087, 'GHO': 460651, 'YLI': 460235, 'TYS': 460071, 'ATD': 459822, 'UPA': 459674, 'FYO': 459119, 'NUN': 457629, 'AFR': 457104, 'AVO': 456873, 'ADB': 456539, 'EIM': 456080, 'USL': 455635, 'TPO': 455600, 'LAD': 454918, 'OWL': 454598, 'HTT': 454342, 'BOD': 452560, 'DWO': 451350, 'FFA': 450974, 'LIZ': 450659, 'OCH': 450499, 'THL': 450466, 'LAU': 450126, 'SCL': 449760, 'ANM': 449470, 'VOT': 449215, 'NPO': 449188, 'VIT': 449115, 'RDT': 448914, 'HTI': 448845, 'DAF': 448676, 'MOF': 447868, 'IEF': 447703, 'FIV': 447519, 'KEL': 446546, 'POT': 446391, 'ISU': 446330, 'OLV': 445680, 'ENP': 444499, 'KEY': 443950, 'RSF': 443639, 'RLO': 443516, 'NCY': 443271, 'RGI': 443210, 'CHN': 442628, 'UNA': 442592, 'ILO': 442392, 'GHS': 442110, 'ODS': 441928, 'ONY': 441676, 'AFO': 441277, 'MEF': 440759, 'OUB': 440554, 'LSI': 440312, 'THP': 438986, 'SNA': 438926, 'LOY': 438888, 'PIR': 438022, 'TLO': 437667, 'HTA': 437321, 'LAG': 437237, 'YCH': 436029, 'DTR': 435315, 'RNS': 433705, 'CEF': 433482, 'HUM': 433377, 'OFN': 432061, 'LEX': 431567, 'SEF': 431541, 'NDY': 431481, 'AMM': 431036, 'GUI': 430959, 'CIL': 430400, 'DPE': 430118, 'VEC': 430041, 'HUS': 429554, 'KST': 429427, 'LLW': 428966, 'SGR': 428953, 'ESR': 427192, 'APH': 426684, 'UIR': 426397, 'AWI': 426367, 'TMI': 425602, 'TSM': 425404, 'OCU': 425294, 'DRU': 424601, 'JUN': 424505, 'TEW': 423945, 'NIZ': 423720, 'OSU': 423505, 'UFF': 423370, 'SIX': 423176, 'QUO': 422520, 'NKE': 422208, 'HHI': 421646, 'DUA': 421396, 'CHH': 421300, 'DYO': 420696, 'EJU': 419736, 'SIL': 419658, 'TOK': 418746, 'IHA': 417951, 'PHE': 417489, 'WNE': 417203, 'GSO': 417000, 'DSP': 416929, 'DLO': 416908, 'NSS': 416724, 'RFR': 416640, 'EEC': 416188, 'HMA': 415887, 'OIT': 415749, 'DAD': 415527, 'IPS': 414820, 'NBO': 413865, 'GOR': 413759, 'LTA': 413363, 'RTT': 413032, 'YNO': 413031, 'EYC': 412553, 'TIG': 412111, 'WNS': 411796, 'DAV': 411464, 'RAY': 411325, 'HHE': 410593, 'NMI': 410259, 'UMP': 410180, 'IZA': 410096, 'NOC': 410088, 'LUT': 409945, 'VEO': 409829, 'TEF': 409679, 'CCU': 409262, 'AIM': 408694, 'KAT': 407784, 'ALG': 407643, 'DSC': 407638, 'OCC': 407246, 'LDW': 407044, 'IDD': 406667, 'JOB': 406296, 'ANR': 406209, 'NLO': 406083, 'FIS': 405748, 'NYT': 405463, 'RYW': 405113, 'FHE': 404856, 'EYH': 404669, 'UPE': 404349, 'DOC': 404332, 'ORU': 403992, 'CTR': 403967, 'ADU': 403942, 'NGG': 403393, 'RSD': 403336, 'OPS': 402840, 'TUS': 400850, 'SYO': 399048, 'MUL': 398994, 'OGO': 398883, 'UPS': 398782, 'ECK': 398780, 'FED': 398375, 'RTM': 397829, 'TEG': 397247, 'CHM': 397193, 'SBY': 397116, 'TGO': 396918, 'UPO': 396823, 'TYL': 396784, 'RBU': 396746, 'PIE': 396745, 'CEC': 396394, 'SUA': 396112, 'LEL': 395855, 'DEE': 395471, 'NBY': 395359, 'REX': 395131, 'UED': 395022, 'LCA': 394284, 'YNE': 394059, 'COO': 393670, 'MEB': 392673, 'REY': 391971, 'LEH': 391646, 'CEB': 391583, 'MBI': 391091, 'NUS': 390708, 'PME': 390639, 'GOL': 390136, 'DIO': 389524, 'LDC': 389481, 'UBS': 389070, 'AIG': 388787, 'LUM': 387836, 'LLF': 387683, 'YLO': 387402, 'IBU': 387254, 'RWO': 387076, 'STD': 387057, 'GNA': 386724, 'OCT': 386543, 'LIB': 386499, 'LME': 386196, 'CAD': 385584, 'SEB': 385353, 'UTU': 385161, 'EBY': 385123, 'ASG': 384462, 'YDO': 384283, 'GLO': 384211, 'MSO': 384157, 'AHO': 383988, 'AYW': 383561, 'NWO': 383031, 'EBL': 382752, 'VIR': 382292, 'RYC': 382277, 'OOF': 380878, 'LSH': 380861, 'DOI': 380766, 'UIS': 380610, 'SOV': 379762, 'HCA': 379609, 'TAD': 379118, 'CKL': 378610, 'LUN': 378324, 'OOP': 378304, 'RVA': 378211, 'GEI': 378023, 'NUT': 377989, 'NTD': 377555, 'GRI': 377456, 'GUL': 377294, 'THB': 376739, 'RTW': 376717, 'RSB': 376667, 'NUA': 376666, 'IAS': 376523, 'UGG': 376254, 'RCI': 375973, 'AWH': 375746, 'EEI': 375366, 'MEP': 375252, 'SFU': 374860, 'HNO': 374502, 'DEX': 374462, 'ABR': 374445, 'POF': 374393, 'GEM': 374097, 'FMA': 373812, 'TUT': 373588, 'SBR': 373166, 'AUL': 373043, 'VEP': 372586, 'AYF': 372221, 'USP': 371906, 'DLY': 371553, 'OPH': 370713, 'KSO': 370672, 'ENL': 370425, 'SMU': 369977, 'ABU': 369302, 'UMM': 369113, 'NPE': 368957, 'SOI': 368954, 'SEH': 368804, 'SPU': 366949, 'XAM': 366885, 'YBU': 366531, 'LFA': 366357, 'YCL': 366299, 'AUN': 365967, 'PHA': 365934, 'MBA': 365409, 'NGN': 365403, 'REU': 365060, 'OBS': 364429, 'OKS': 364346, 'NAU': 364117, 'PHY': 363878, 'WID': 363457, 'ALH': 362984, 'LLM': 362653, 'IPP': 361829, 'ADR': 361643, 'CHC': 361423, 'DAG': 361336, 'BYS': 360804, 'JAN': 360782, 'GAB': 360393, 'USC': 359983, 'NOP': 359527, 'DTE': 358896, 'SOA': 358463, 'AFI': 358302, 'PPI': 357099, 'KIS': 356812, 'BAB': 356115, 'DVA': 355939, 'IMT': 355896, 'DEI': 355784, 'ISK': 355763, 'GMA': 355495, 'EKE': 355493, 'ETC': 355458, 'HLE': 355235, 'LYN': 355124, 'LFI': 354875, 'EWY': 354513, 'THF': 353849, 'GUN': 353734, 'SYE': 353655, 'RGO': 353215, 'RIF': 352976, 'PES': 352844, 'XPL': 352793, 'ATY': 352730, 'THD': 352168, 'NVO': 351927, 'LID': 351823, 'EMT': 351821, 'NEG': 351565, 'TSN': 350759, 'RWE': 350094, 'DFA': 350055, 'SFE': 349142, 'TUP': 348926, 'NOS': 348830, 'AFA': 348636, 'OJE': 348601, 'LOA': 347458, 'YPA': 346821, 'LWI': 346721, 'URB': 346705, 'ARP': 346304, 'BON': 346189, 'RUL': 345376, 'SRO': 345235, 'IBI': 345229, 'DSW': 345079, 'PIO': 344822, 'ARW': 344641, 'UTC': 344629, 'PLY': 344505, 'WYO': 344330, 'APS': 344205, 'EJO': 344137, 'IGU': 343798, 'SLY': 343778, 'DVI': 343518, 'HST': 343510, 'RKA': 343204, 'OUD': 342618, 'ROJ': 342471, 'NAV': 342019, 'ALY': 341781, 'OBI': 341772, 'DDR': 340911, 'HOC': 340786, 'YES': 340781, 'ASY': 340665, 'TAX': 340551, 'ICC': 340144, 'YBO': 339938, 'FUR': 339815, 'PIS': 339326, 'WHY': 339089, 'DGO': 339079, 'RPL': 339054, 'TOV': 338910, 'SSF': 338543, 'OFU': 337960, 'MFO': 337892, 'HOI': 337873, 'IRP': 337376, 'SOO': 337082, 'TYC': 337065, 'IGE': 337045, 'GUS': 336945, 'YPO': 336923, 'LPA': 336790, 'SJU': 336152, 'LYL': 336004, 'NEP': 335826, 'NRO': 335797, 'HOH': 335686, 'DPL': 335317, 'OYO': 335255, 'CCA': 335186, 'TPL': 334561, 'ITM': 334431, 'GOU': 334079, 'EYR': 334066, 'KON': 333905, 'XTE': 333813, 'NSB': 333455, 'GIC': 333418, 'MPU': 333118, 'YLA': 333096, 'IUM': 332924, 'AWE': 332845, 'RYB': 332300, 'FUS': 332254, 'NDJ': 332220, 'NSL': 331844, 'FTO': 331752, 'OKA': 331287, 'ZIN': 330818, 'AHE': 329815, 'UDG': 329388, 'NEB': 329357, 'RUM': 329298, 'DOL': 329249, 'OPM': 328997, 'LLR': 328807, 'ROY': 328345, 'ITR': 328294, 'RBI': 327852, 'KEI': 327742, 'TBY': 327544, 'LUB': 327484, 'IPL': 327390, 'OIL': 326212, 'USU': 325863, 'NCT': 325842, 'TAY': 325655, 'YSU': 325578, 'OGY': 325324, 'BAM': 325163, 'YHI': 324144, 'OVA': 324097, 'HAB': 324021, 'UPI': 323850, 'DUE': 323499, 'COP': 323123, 'LPE': 323007, 'EXE': 322986, 'OWW': 322922, 'NYA': 322627, 'AEL': 322410, 'DVE': 322254, 'ESY': 321712, 'DUL': 321577, 'JOI': 321531, 'YSC': 321466, 'OEN': 321088, 'IMO': 320360, 'CRU': 320228, 'YGO': 319863, 'RUG': 318979, 'UIN': 318748, 'RCU': 318585, 'TYW': 318459, 'VEW': 318401, 'BRU': 317853, 'HHA': 317828, 'SVI': 317083, 'PEE': 317031, 'FST': 317005, 'DBO': 316943, 'ANL': 316876, 'VEF': 316855, 'NTG': 316648, 'NSM': 316461, 'VEG': 315733, 'JAC': 315364, 'TSL': 315058, 'LAP': 314766, 'SOB': 314719, 'THY': 314538, 'OHO': 314489, 'GPR': 314480, 'GAG': 314381, 'ATN': 314283, 'RSM': 314118, 'ZAT': 313199, 'EOL': 313168, 'RFE': 313095, 'NPL': 313021, 'MEH': 312972, 'HSC': 312781, 'WEH': 312484, 'IDH': 311963, 'IAA': 311767, 'DTA': 311326, 'NJO': 310885, 'APL': 310686, 'DBR': 310663, 'UTF': 310506, 'ENV': 310126, 'RGR': 309617, 'LTU': 309002, 'HOD': 308808, 'GFR': 308652, 'LLN': 308507, 'NJA': 308491, 'MBL': 308400, 'NBR': 308282, 'COT': 307967, 'DDA': 307511, 'YSP': 307366, 'ICR': 307300, 'ISY': 306799, 'NEU': 306674, 'ADC': 306514, 'ENY': 306371, 'OBO': 306146, 'RSQ': 306075, 'GNO': 305873, 'SOD': 305129, 'EYD': 305062, 'SSW': 304755, 'TEH': 304729, 'GSI': 304696, 'LHE': 304666, 'DAU': 304300, 'FWH': 304092, 'ETB': 303860, 'OMH': 303544, 'VAI': 303342, 'EYT': 303192, 'LLD': 302766, 'NAI': 301670, 'AUD': 301476, 'LIP': 301243, 'YFI': 300564, 'OMY': 300207, 'WRO': 300070, 'HFO': 299776, 'RSL': 299286, 'IDG': 299282, 'EAW': 299137, 'LSC': 298755, 'NAW': 298217, 'IRF': 298108, 'YAC': 297843, 'ERK': 297785, 'YIT': 297525, 'AYN': 297164, 'TGE': 297116, 'OGA': 296965, 'YBA': 296299, 'DGR': 296067, 'ONJ': 295928, 'RYF': 295660, 'RYP': 295319, 'EMY': 295298, 'XIS': 294694, 'HME': 294429, 'TSR': 294313, 'UAN': 293591, 'ITB': 293583, 'PST': 293548, 'NYS': 293539, 'LCH': 293157, 'BAD': 293108, 'SOS': 293015, 'BOY': 292956, 'OOS': 292825, 'VOR': 292820, 'OIC': 292597, 'UEL': 292256, 'AHI': 292159, 'TFA': 292153, 'EWR': 291913, 'OBU': 291789, 'ELV': 291536, 'EOV': 291259, 'TBO': 291234, 'FLU': 291098, 'CEH': 291090, 'SSM': 290807, 'DJU': 290414, 'RIZ': 290402, 'IFO': 289814, 'TAU': 289720, 'AYH': 289506, 'CEE': 289418, 'URF': 289273, 'WAI': 289155, 'UTM': 289130, 'USO': 288822, 'XTR': 288666, 'STG': 288666, 'URV': 288661, 'SVE': 288521, 'BUL': 287914, 'TSD': 287665, 'ACL': 287469, 'YHO': 287396, 'EEF': 287187, 'MOC': 287054, 'TDA': 286603, 'IPT': 286572, 'LTS': 286321, 'PAP': 284893, 'GIR': 284771, 'USB': 284688, 'VEY': 284533, 'UIC': 284426, 'EKN': 284370, 'YET': 284330, 'PSA': 284082, 'LBA': 283530, 'RGU': 282842, 'FSE': 282634, 'IOD': 282405, 'OWD': 282283, 'WEB': 282010, 'DAI': 281828, 'DIM': 281776, 'SAU': 281513, 'YAF': 281302, 'AZI': 281187, 'IGG': 281173, 'NOO': 280974, 'ITF': 280560, 'TGA': 280550, 'ULI': 280359, 'LTR': 280346, 'OSC': 280260, 'LNE': 280039, 'CHD': 279920, 'XCE': 279816, 'OUA': 279342, 'EAI': 279158, 'STN': 278971, 'IOL': 278483, 'GWA': 277998, 'RCR': 277499, 'GUR': 277443, 'UTR': 277311, 'LAL': 277203, 'EKS': 276998, 'AYM': 276981, 'SOH': 276953, 'LLU': 276854, 'JUL': 276623, 'IQU': 276530, 'WEW': 276386, 'LSW': 276091, 'UTB': 276041, 'KNE': 276009, 'SHU': 275923, 'VOI': 275833, 'TEB': 274945, 'PEL': 274923, 'ULY': 274628, 'KID': 274097, 'BSE': 273916, 'IAR': 273805, 'HBO': 273651, 'LPO': 273428, 'RBR': 272831, 'HMO': 272791, 'FFT': 272515, 'DDL': 272182, 'DQU': 272172, 'HWE': 272150, 'WST': 272060, 'YTR': 271806, 'YUN': 271491, 'OMU': 271377, 'HSO': 271257, 'PTA': 270021, 'SRI': 269829, 'OYA': 269772, 'SUI': 269713, 'SGE': 269245, 'UTP': 269105, 'YFA': 268856, 'RCL': 268514, 'GSE': 268343, 'ADL': 268330, 'SEY': 267942, 'UGE': 267916, 'KFO': 267848, 'RYD': 267813, 'RDW': 267516, 'POO': 267243, 'JUR': 267186, 'GWH': 267185, 'RFU': 266684, 'PUS': 266537, 'RNT': 266513, 'ITD': 266115, 'ATG': 265245, 'LAK': 265236, 'FTI': 265217, 'DOP': 265121, 'LYG': 264718, 'ESK': 264414, 'FPR': 264266, 'PWI': 264056, 'LWH': 263688, 'UPL': 263672, 'DOO': 263489, 'FCA': 263272, 'AWO': 263178, 'ICP': 263016, 'TFE': 262964, 'NDV': 262854, 'ARF': 262794, 'GCA': 262657, 'EID': 262584, 'ERJ': 262492, 'ONU': 262427, 'EHU': 262020, 'NKA': 261521, 'GEW': 261388, 'YMI': 261320, 'PIL': 261319, 'CUM': 261213, 'EDY': 261164, 'UGU': 261043, 'VEE': 261040, 'NRA': 260993, 'MYS': 260722, 'RMY': 260646, 'IRR': 260596, 'TGR': 260419, 'RUP': 260209, 'KEP': 260176, 'GMO': 260114, 'GUP': 259773, 'CUP': 259565, 'LDM': 259515, 'HSA': 259121, 'CTL': 258977, 'NDK': 258269, 'FSO': 258205, 'OUW': 258170, 'TBR': 258131, 'KEO': 257910, 'KAR': 257726, 'UTL': 257310, 'SDU': 257297, 'OEX': 257208, 'IMB': 256721, 'GBE': 256536, 'OBR': 256513, 'NYE': 255818, 'TTW': 255574, 'EWT': 255572, 'FFS': 255550, 'HWI': 255283, 'NEH': 255086, 'CHB': 254914, 'LKI': 254862, 'GEF': 254737, 'FAV': 254328, 'OID': 254034, 'RDR': 253403, 'GME': 253214, 'YDA': 252594, 'SGA': 252355, 'GAC': 252154, 'AMT': 252041, 'GIA': 252012, 'GHL': 251155, 'RYL': 251008, 'KHA': 250943, 'JAM': 250714, 'BIR': 250662, 'DOV': 250600, 'HTW': 250522, 'HAW': 250437, 'MWI': 250297, 'NOI': 250208, 'CHF': 250098, 'AUR': 249822, 'GBA': 249427, 'FET': 249306, 'BJE': 249274, 'FUT': 249248, 'LLG': 249160, 'OTW': 248831, 'KIT': 248806, 'ENJ': 248187, 'GSH': 248150, 'THN': 248005, 'WIF': 247579, 'LOB': 247579, 'WEI': 247400, 'ESG': 246681, 'FDE': 246592, 'BLU': 246464, 'GAV': 246450, 'HYS': 246071, 'CKW': 245924, 'FPE': 245873, 'CHP': 245854, 'KLE': 245734, 'AMU': 245633, 'ZON': 245547, 'NGY': 245381, 'LLL': 245335, 'SHT': 245041, 'SEQ': 244968, 'BYC': 244847, 'JUD': 244815, 'GOD': 244706, 'TYF': 244703, 'RAH': 244695, 'GUY': 244642, 'WTO': 244506, 'DNA': 244453, 'NKT': 244245, 'UHA': 243995, 'DAW': 243266, 'SDR': 243212, 'BYM': 243015, 'YTE': 243002, 'BEP': 242939, 'RBY': 242612, 'UTD': 242568, 'NVA': 241966, 'OLY': 241541, 'FTW': 241075, 'NOB': 240992, 'RYM': 240814, 'GDO': 240711, 'LFR': 240415, 'ACU': 240201, 'DEG': 240171, 'OLT': 239835, 'CIF': 239717, 'TTY': 239662, 'PAG': 239569, 'DTW': 239446, 'FCH': 239150, 'BYH': 239017, 'VIA': 238968, 'LPH': 237968, 'YAB': 237435, 'GAP': 237432, 'BYP': 236865, 'OTC': 236708, 'PSE': 236487, 'MCO': 236416, 'HPR': 236389, 'SSS': 236179, 'HOA': 236067, 'TCL': 235854, 'ZEN': 235828, 'OWM': 235748, 'DCR': 235679, 'POU': 235668, 'HAC': 235574, 'BUY': 235001, 'HSE': 234835, 'RTF': 234685, 'NYW': 234398, 'OAP': 234371, 'SHM': 234253, 'BUM': 233913, 'UMS': 233829, 'ALV': 233703, 'CHL': 233681, 'EJA': 233336, 'TJU': 232540, 'WLE': 232110, 'IEC': 231942, 'DCL': 231737, 'DGA': 231566, 'LYU': 231380, 'ABS': 231314, 'OMF': 231275, 'NRI': 231210, 'RYH': 231178, 'BOW': 230929, 'YRA': 230711, 'OFJ': 230703, 'BST': 230645, 'UMI': 230385, 'YEN': 230026, 'ROK': 229807, 'MUR': 229737, 'GLY': 229733, 'MWA': 229644, 'WOF': 229452, 'SIF': 229352, 'RUI': 229226, 'YRO': 228773, 'IMU': 228239, 'IAG': 228212, 'LBO': 228136, 'LSU': 228120, 'LSP': 228078, 'MPS': 227450, 'GEC': 227243, 'FMO': 227041, 'ELC': 226793, 'MSI': 226515, 'SBI': 226270, 'HNI': 226202, 'UNL': 226124, 'YEX': 226019, 'UTY': 225436, 'SEU': 225190, 'UTN': 225070, 'OUH': 224962, 'LNO': 224905, 'HTB': 224853, 'LMI': 224848, 'ALN': 224778, 'OFV': 224337, 'IDU': 224333, 'SKA': 224227, 'BUD': 224160, 'SUG': 224122, 'MWH': 223934, 'EEW': 223814, 'ODR': 223685, 'THG': 223518, 'KSH': 223308, 'LDL': 223283, 'RTL': 223254, 'WRE': 222992, 'TKN': 222776, 'PSO': 222714, 'ACY': 222507, 'BSI': 222431, 'GDE': 222394, 'IAB': 222393, 'DIG': 222195, 'YPL': 221849, 'OYS': 221739, 'AKA': 221395, 'FOC': 221239, 'LGA': 220781, 'GHB': 220528, 'ADW': 220528, 'RKO': 220424, 'LDP': 220259, 'DSF': 220157, 'INY': 219786, 'UPW': 219591, 'EKA': 219542, 'OMC': 219469, 'KSI': 218880, 'FEB': 218669, 'SSL': 218313, 'CAB': 218110, 'LHI': 217840, 'ISV': 217574, 'HEQ': 217500, 'SEG': 217349, 'LTY': 217317, 'ILW': 217293, 'FFR': 217147, 'HCE': 217107, 'MBO': 217032, 'NNY': 215903, 'WNI': 215140, 'HWH': 214995, 'OXI': 214978, 'AOF': 214937, 'MIR': 214811, 'FOF': 214779, 'LGO': 214723, 'NYM': 214279, 'CIR': 213813, 'SRU': 213789, 'WEC': 213677, 'UNK': 213577, 'RSR': 213051, 'LKE': 212737, 'WSA': 212347, 'AYL': 212048, 'GPO': 211951, 'YBR': 211535, 'HLI': 211287, 'GEB': 211108, 'MOM': 211091, 'YNA': 210655, 'EDV': 210626, 'SAH': 210565, 'AWS': 210533, 'EYB': 210530, 'DEW': 210139, 'WIC': 209942, 'LHO': 209628, 'KEM': 209202, 'FMI': 209156, 'LDF': 208960, 'YAP': 208948, 'TAW': 208892, 'CTH': 208712, 'RGY': 208543, 'DTI': 208435, 'GTE': 208390, 'VIV': 208012, 'YPI': 207841, 'ARV': 207752, 'IPE': 207514, 'YTA': 207326, 'KLY': 207292, 'KWI': 207252, 'LAV': 207223, 'UMO': 207140, 'OFY': 207083, 'RMU': 207044, 'PUN': 207039, 'EYM': 206987, 'LUC': 206952, 'OTL': 206887, 'FTA': 206663, 'TNA': 206516, 'NYC': 206153, 'MNO': 206067, 'TSG': 205658, 'CYC': 205614, 'OLF': 205584, 'FWA': 205580, 'PSI': 205430, 'BOL': 205326, 'DDU': 205131, 'DPU': 205128, 'DSL': 205059, 'ADN': 204851, 'SIZ': 204694, 'DJO': 204562, 'LWO': 204244, 'VAS': 204100, 'BIS': 203990, 'JAP': 203934, 'BEM': 203822, 'NQU': 203329, 'GBU': 203154, 'YRI': 203083, 'DFE': 203075, 'HAF': 202767, 'EPS': 202630, 'NYP': 202609, 'SIE': 202387, 'TUE': 202366, 'ELM': 202285, 'NNU': 202225, 'NPU': 202224, 'DOS': 202027, 'FON': 201918, 'AMW': 201893, 'DYE': 201834, 'TIP': 201622, 'ARH': 201528, 'WNO': 201509, 'FPO': 201357, 'SUF': 201316, 'TTS': 201257, 'XPA': 201004, 'KWA': 200810, 'AGG': 200713, 'LVI': 200690, 'TOY': 200489, 'NAH': 200489, 'MHA': 200203, 'MBU': 200042, 'DMU': 199711, 'HAE': 199517, 'OCL': 199388, 'DOG': 199375, 'MEG': 199264, 'BOX': 199091, 'USW': 198656, 'EIL': 198544, 'RIK': 198136, 'LSS': 198081, 'DSS': 197478, 'BIA': 197139, 'RUE': 197067, 'CKB': 197059, 'PLU': 196990, 'YAD': 196878, 'EWC': 196641, 'ARU': 196561, 'REJ': 196504, 'BOS': 196426, 'UEA': 196332, 'NSD': 196053, 'RJO': 195953, 'PPA': 195904, 'HLA': 195713, 'EYF': 195528, 'NFU': 195436, 'MOO': 195051, 'HBE': 195045, 'HRA': 194991, 'DSM': 194977, 'OMW': 194924, 'CSA': 194893, 'FPA': 194484, 'IDW': 194128, 'FSA': 194087, 'GAD': 193657, 'YSS': 193566, 'EWM': 193479, 'MPH': 193405, 'TOJ': 192842, 'OFK': 192840, 'ZER': 192775, 'AYC': 192745, 'YGR': 192720, 'KAB': 192594, 'RTN': 192530, 'TCR': 192477, 'YGE': 192111, 'OWC': 192102, 'MHE': 192025, 'TVI': 192022, 'YUS': 191888, 'YSW': 191808, 'SGI': 191544, 'UDO': 191464, 'IGR': 191355, 'TYB': 191312, 'TPU': 191282, 'EJE': 190300, 'RDF': 190255, 'ODT': 190139, 'GPA': 190091, 'RUT': 189839, 'XEC': 189687, 'KAS': 189673, 'IFA': 189660, 'URM': 189395, 'YAM': 189214, 'OWB': 189084, 'LRO': 188660, 'RDL': 188549, 'ROI': 188517, 'KEH': 188499, 'YOT': 188472, 'FLY': 188436, 'YTI': 188406, 'YBY': 188299, 'ADH': 188275, 'IWO': 188048, 'LPL': 188038, 'URL': 187946, 'IBR': 187812, 'DAH': 187633, 'CTW': 187621, 'EIF': 187616, 'CIO': 187473, 'IOS': 187321, 'OTP': 187172, 'RYR': 186859, 'FEM': 186823, 'MAP': 186542, 'HLY': 186536, 'TYH': 186496, 'IOT': 186413, 'UID': 186129, 'UAG': 185667, 'ICY': 185550, 'UNF': 185532, 'RAU': 185495, 'LWE': 185384, 'NKO': 185271, 'LDG': 185152, 'EAH': 185145, 'MSW': 184607, 'MIE': 184573, 'EYI': 184244, 'HUG': 183952, 'USF': 183723, 'TMU': 183374, 'SIR': 183184, 'HSI': 183026, 'FBE': 182965, 'RAE': 182811, 'GYO': 182742, 'MCC': 182712, 'HSH': 182243, 'DYA': 181839, 'FME': 181826, 'JOY': 181756, 'YDR': 181716, 'WSO': 181553, 'PAU': 181387, 'NSR': 180805, 'CAI': 180695, 'GPE': 180678, 'JER': 180657, 'JOU': 180589, 'CIV': 180537, 'IRB': 180492, 'FAB': 180274, 'NCU': 180124, 'GEP': 180111, 'YMP': 180085, 'HIO': 180085, 'EEO': 179594, 'OBB': 179537, 'OWR': 179509, 'FTR': 179504, 'POK': 179205, 'ETF': 179028, 'RKT': 178894, 'UDY': 178815, 'FHO': 178744, 'DCU': 178646, 'KOR': 178633, 'YAG': 178599, 'ABB': 178472, 'ETM': 178339, 'FNE': 177841, 'ELB': 177808, 'HDO': 177712, 'SKN': 177621, 'TYM': 177611, 'AQU': 177486, 'OTM': 177474, 'NYI': 177423, 'IRW': 177394, 'MSH': 177299, 'RRU': 177022, 'GCH': 176885, 'LSF': 176733, 'SPH': 176397, 'WWH': 176123, 'KSW': 175981, 'FNO': 175791, 'MBR': 175511, 'SJO': 175484, 'YEL': 175455, 'UDD': 175203, 'NTN': 175108, 'ODD': 174850, 'GOE': 174842, 'BEO': 174805, 'CKH': 174641, 'HTR': 174591, 'ITN': 174548, 'COG': 174521, 'UER': 174478, 'NAA': 174477, 'OGN': 174298, 'HNS': 174036, 'HAU': 173969, 'IRG': 173962, 'EYL': 173949, 'MRE': 173881, 'BAY': 173738, 'COF': 173615, 'JON': 173421, 'BYR': 173044, 'ADF': 173008, 'PTU': 172994, 'KIE': 172928, 'HIA': 172754, 'FSU': 172710, 'GSW': 172369, 'IXT': 172138, 'TYR': 172065, 'YNI': 172024, 'DGI': 171807, 'GGL': 171783, 'OUI': 171739, 'OKN': 171674, 'HDE': 171657, 'ICF': 171582, 'MCA': 171408, 'NUP': 170928, 'HPO': 170892, 'LDD': 170860, 'COD': 170737, 'AVY': 170431, 'GSU': 170294, 'DEH': 170239, 'ICD': 170195, 'WNF': 170102, 'UOS': 170075, 'OTF': 170001, 'WMA': 169956, 'EOB': 169901, 'LTT': 169726, 'YFE': 169571, 'FAP': 169486, 'BYB': 169169, 'NGV': 169056, 'PFO': 168941, 'HPA': 168888, 'ULS': 168342, 'CKF': 168254, 'MHI': 168246, 'ULO': 168208, 'FWE': 168167, 'OTU': 167850, 'HAG': 167622, 'PTT': 167606, 'WCO': 167594, 'CST': 167463, 'EMW': 167434, 'GGR': 167415, 'AGN': 167094, 'DYS': 165978, 'IPO': 165799, 'EDJ': 165759, 'ELU': 165749, 'KLA': 165704, 'IPI': 165658, 'CKY': 165439, 'HOE': 165299, 'BBE': 165252, 'RDC': 164992, 'YSL': 164727, 'WOS': 164527, 'OKO': 164335, 'NMY': 164074, 'ADP': 163657, 'FHA': 163642, 'TIZ': 163486, 'EYP': 163351, 'GHW': 163026, 'HYO': 162976, 'EBS': 162931, 'FSH': 162858, 'LGR': 162856, 'TJO': 162389, 'UGA': 162255, 'SSR': 162194, 'YEV': 162059, 'GFI': 161935, 'IAI': 161830, 'USM': 161800, 'OKT': 161711, 'REK': 161614, 'TFU': 161461, 'NGJ': 161449, 'RDU': 161403, 'KEW': 161231, 'GGI': 161127, 'EGL': 161122, 'AON': 161095, 'BIO': 161026, 'SHR': 161021, 'GDI': 160987, 'OEA': 160887, 'DKI': 160541, 'HMI': 160369, 'LKS': 160309, 'BOV': 160148, 'KMA': 160088, 'XIN': 160067, 'ASV': 159996, 'GSC': 159854, 'YSB': 159719, 'UCI': 159715, 'RUA': 159703, 'TID': 159674, 'SHS': 159572, 'ICB': 159480, 'XAN': 159457, 'RKW': 159366, 'ONK': 159249, 'EEH': 159196, 'IAC': 159157, 'LVA': 158941, 'DFU': 158895, 'BSO': 158841, 'ANJ': 158737, 'DJA': 158663, 'IDL': 158623, 'LPI': 158558, 'EWP': 158538, 'AFU': 158254, 'EWW': 158111, 'FIF': 158033, 'NMU': 158022, 'HNE': 157525, 'TNI': 157470, 'GWE': 157447, 'UPF': 157388, 'NSY': 157342, 'KOU': 157335, 'BYD': 157098, 'CCI': 157054, 'YSM': 156909, 'YMU': 156566, 'ETP': 156272, 'YCR': 156031, 'YYE': 155847, 'IUS': 155825, 'TAH': 155773, 'LOM': 155590, 'JOS': 155303, 'GWO': 155103, 'SYM': 154924, 'AHU': 154855, 'RLS': 154844, 'AYP': 154833, 'FDI': 154792, 'AAR': 154699, 'FID': 154324, 'GTR': 154184, 'CQU': 154146, 'RDP': 154011, 'BEB': 153621, 'PTS': 153520, 'PID': 153227, 'MEX': 153126, 'COC': 153009, 'FWI': 152954, 'MYO': 152951, 'USD': 152944, 'DIU': 152872, 'KEC': 152843, 'SKY': 152821, 'GTI': 152789, 'FRU': 152694, 'HTF': 152651, 'KUP': 152647, 'XIM': 152592, 'HDI': 152517, 'ELW': 152333, 'KAL': 151884, 'IRH': 151803, 'BYF': 151750, 'OAM': 151691, 'HIB': 151679, 'KIC': 151608, 'RDB': 151492, 'HTL': 151425, 'TQU': 151291, 'OTG': 151172, 'EUT': 151050, 'FTT': 150694, 'UBE': 150528, 'BUN': 150470, 'ISJ': 150411, 'NIQ': 150392, 'IGO': 150176, 'ICM': 150171, 'BYI': 149834, 'UEO': 149755, 'DYI': 149614, 'SHC': 149518, 'SSB': 149468, 'TKI': 149365, 'XPO': 148925, 'DSB': 148849, 'XPR': 148810, 'MOB': 148805, 'WYE': 148589, 'NRU': 148404, 'VAC': 148352, 'NTK': 148351, 'WSP': 148320, 'GAZ': 148075, 'KCO': 147990, 'TCE': 147806, 'DYT': 147765, 'LAH': 147666, 'ITP': 147607, 'GNS': 147289, 'GHH': 147206, 'BEY': 147195, 'TDR': 147017, 'LFT': 146844, 'AKS': 146792, 'HCH': 146708, 'HDA': 146702, 'NGK': 146534, 'GEH': 146527, 'EWB': 146388, 'UPR': 146371, 'FBA': 146370, 'GSP': 146311, 'BEU': 146202, 'DBL': 146187, 'SBL': 146064, 'FTS': 146020, 'TUM': 145985, 'LUR': 145936, 'RQU': 145917, 'AWN': 145846, 'EUM': 145792, 'DBI': 145762, 'MYA': 145673, 'ICW': 145538, 'CKN': 145517, 'DIL': 145429, 'GOS': 145295, 'DUT': 145257, 'GIL': 145217, 'APU': 145093, 'DPI': 145082, 'DOA': 145014, 'RHU': 144806, 'URH': 144780, 'FAD': 144700, 'CAG': 144283, 'RTB': 144245, 'ORV': 144036, 'GBO': 143954, 'MAM': 143952, 'COW': 143941, 'MOL': 143888, 'GAF': 143861, 'AXI': 143785, 'RAZ': 143518, 'MIK': 143510, 'DVO': 143466, 'DFL': 142818, 'ATK': 142816, 'LGE': 142806, 'MSU': 142720, 'PCO': 142708, 'KWH': 142708, 'RPH': 142706, 'NOA': 142664, 'EOC': 142653, 'FAU': 142374, 'UAD': 142268, 'ASJ': 142170, 'SGU': 142130, 'ABY': 141892, 'FGO': 141869, 'ENK': 141742, 'HTN': 141511, 'RPU': 141501, 'BAI': 141478, 'XIC': 141462, 'RTC': 141366, 'HUT': 141366, 'MAH': 141298, 'EEY': 140791, 'SSY': 140649, 'CKM': 140581, 'RSN': 140406, 'IDB': 140359, 'YIM': 140231, 'BYE': 140228, 'LFE': 140186, 'OIM': 140132, 'VOC': 140123, 'SFL': 140034, 'OML': 139960, 'KLI': 139852, 'LEU': 139763, 'ACQ': 139721, 'HID': 139637, 'BAG': 139509, 'SWR': 139465, 'UNO': 139430, 'MAB': 138898, 'BYL': 138771, 'UVE': 138649, 'FEI': 138607, 'YGA': 138419, 'UEE': 138419, 'YVE': 138396, 'HWO': 138226, 'XAS': 138087, 'HLO': 137894, 'MSC': 137826, 'JEW': 137725, 'MIX': 137684, 'NYB': 137594, 'PPY': 137425, 'IKI': 137401, 'IDF': 137372, 'ORJ': 137319, 'UYS': 137312, 'UEI': 137214, 'VEU': 137092, 'CKC': 137047, 'MFR': 136773, 'WNW': 136707, 'PAB': 136680, 'ADJ': 136636, 'RPI': 136396, 'HBA': 136295, 'TEU': 136106, 'UBT': 136103, 'GIE': 136027, 'YYO': 135914, 'CKP': 135826, 'OWF': 135574, 'YPU': 135336, 'LKA': 135295, 'AMC': 135204, 'NIR': 135029, 'IAW': 134933, 'WSH': 134405, 'WOL': 134326, 'OTD': 134175, 'FWO': 134023, 'KAG': 133949, 'IXE': 133863, 'LMS': 133840, 'NKN': 133715, 'RYG': 133713, 'UKE': 133668, 'TBI': 133304, 'EAO': 133150, 'LSB': 133139, 'UBA': 133075, 'YEE': 132994, 'ODF': 132823, 'AYD': 132650, 'BYW': 132633, 'XES': 132160, 'AYR': 132146, 'IPH': 132080, 'MIA': 132009, 'PSH': 131913, 'AGL': 131673, 'KHE': 131667, 'GGA': 131540, 'BEW': 131458, 'GEE': 131265, 'NOD': 131230, 'AAS': 131090, 'LAF': 131060, 'OGU': 131006, 'URK': 130873, 'GPL': 130660, 'ZES': 130527, 'EDK': 130484, 'DOY': 130393, 'STV': 130379, 'IFH': 130085, 'FFL': 129983, 'ODW': 129981, 'FIX': 129823, 'RDM': 129627, 'LDU': 129304, 'WOT': 129101, 'HGR': 129096, 'TPM': 129038, 'MEU': 128800, 'OUM': 128744, 'RAA': 128254, 'YJU': 128173, 'HFR': 128110, 'MYF': 128036, 'EWL': 128024, 'GYA': 127994, 'FSI': 127917, 'OAB': 127872, 'SNI': 127867, 'XTH': 127741, 'HBU': 127696, 'WNB': 127547, 'UBJ': 127497, 'IDM': 127288, 'NID': 127087, 'WCA': 126951, 'USR': 126889, 'BOM': 126767, 'OAF': 126628, 'OEV': 126410, 'XED': 126389, 'MYT': 126335, 'OBJ': 126133, 'HSP': 125998, 'URW': 125966, 'WOY': 125944, 'KRE': 125817, 'NBI': 125697, 'ULF': 125637, 'HPE': 125561, 'GEV': 125528, 'JUM': 125214, 'UOT': 125164, 'EMC': 125151, 'HTC': 125115, 'EYG': 125040, 'TPI': 125007, 'UMN': 124988, 'SHW': 124955, 'RMT': 124796, 'TVE': 124739, 'EPP': 124641, 'TSY': 124633, 'RDH': 124615, 'NSN': 124609, 'EGY': 124543, 'TDU': 124494, 'ZET': 124389, 'ETL': 124374, 'GIM': 124363, 'KYO': 124357, 'FBO': 124348, 'SVA': 124321, 'FSP': 124123, 'IDC': 124039, 'RSY': 123873, 'IEA': 123683, 'EOW': 123601, 'JIM': 123600, 'BYO': 123318, 'GFA': 123218, 'MSS': 123090, 'YVI': 122830, 'OMD': 122824, 'HHO': 122818, 'UBB': 122777, 'OLK': 122529, 'NUR': 122385, 'YCE': 122277, 'TVA': 122237, 'AFL': 122054, 'BID': 121751, 'DCE': 121671, 'PMA': 121628, 'TAV': 121453, 'WOW': 121376, 'YSF': 121301, 'IBA': 121101, 'ROX': 121097, 'OGS': 121096, 'OOU': 121058, 'HSU': 121039, 'HYD': 120950, 'ZAR': 120914, 'OMN': 120865, 'ODG': 120862, 'YKN': 120824, 'OMR': 120778, 'FBU': 120713, 'RSG': 120557, 'FEX': 120530, 'UFA': 120461, 'CKU': 120423, 'NIL': 120363, 'TYD': 120358, 'HYA': 120326, 'CAA': 120173, 'PBE': 120105, 'LRA': 120084, 'DOB': 120044, 'ZEA': 119992, 'LCL': 119732, 'UWA': 119588, 'JOE': 119400, 'GHP': 119378, 'WET': 119239, 'AZA': 119155, 'BUC': 119123, 'YOP': 119106, 'AMH': 118967, 'WNP': 118962, 'BOB': 118938, 'LRI': 118907, 'AKO': 118901, 'HAK': 118889, 'HOB': 118829, 'IPM': 118734, 'OWP': 118647, 'EEU': 118553, 'HEX': 118526, 'HFI': 118367, 'AUC': 118337, 'WOP': 118307, 'NYD': 117859, 'DKE': 117810, 'FSC': 117684, 'FAG': 117423, 'LBR': 117347, 'ILH': 117298, 'RAK': 117227, 'WWE': 117216, 'EWF': 117172, 'SKS': 117157, 'EEB': 117123, 'PAD': 117096, 'MAX': 117030, 'PSW': 116968, 'IZI': 116858, 'KSF': 116849, 'GOP': 116816, 'RNC': 116768, 'DGU': 116736, 'PSY': 116727, 'UIP': 116709, 'EGG': 116664, 'TGI': 116498, 'OQU': 116245, 'NTV': 116095, 'DEU': 116084, 'RAQ': 116025, 'AXE': 116000, 'KRA': 115958, 'MAA': 115722, 'IIN': 115566, 'FGR': 115520, 'DHU': 115459, 'NPI': 115454, 'EXH': 115445, 'OSL': 115387, 'CAC': 115300, 'RJU': 115298, 'FBR': 115222, 'IPW': 115106, 'ADG': 115073, 'EAA': 115041, 'IEG': 114958, 'IVO': 114895, 'MLI': 114828, 'ITZ': 114780, 'CHY': 114736, 'OSW': 114685, 'RKC': 114626, 'EYN': 114594, 'XAC': 114568, 'CAV': 114430, 'KNI': 114309, 'YJO': 114271, 'OSM': 114249, 'WAG': 114218, 'MDE': 114058, 'MYC': 113916, 'RVO': 113667, 'YDU': 113638, 'ETN': 113504, 'IZO': 113493, 'ESV': 113484, 'EWD': 113375, 'NBL': 113347, 'MNE': 113319, 'LLK': 113289, 'WSI': 112649, 'GAW': 112421, 'SYN': 112290, 'WNC': 112270, 'YOV': 112238, 'KEF': 112235, 'TFL': 112193, 'MWE': 112129, 'GOB': 111965, 'IWI': 111849, 'SHL': 111816, 'TUC': 111801, 'CTF': 111738, 'SSD': 111637, 'GMI': 111327, 'TTU': 111318, 'EIC': 111259, 'NNS': 111211, 'SHF': 111087, 'DMY': 111004, 'HYT': 110979, 'MUT': 110964, 'TGU': 110935, 'MSF': 110911, 'HPL': 110849, 'UPH': 110821, 'RFL': 110630, 'MDA': 110570, 'HIF': 110564, 'NSK': 110477, 'AZE': 110426, 'WDE': 110320, 'DNI': 110320, 'FDO': 110269, 'KBE': 110054, 'IDR': 110047, 'LCR': 109995, 'IMW': 109991, 'MMY': 109956, 'RBL': 109692, 'NKL': 109626, 'MSP': 109609, 'IKN': 109500, 'CYA': 109497, 'GRU': 109482, 'KEB': 109472, 'CKD': 109421, 'NUF': 109343, 'OVO': 109328, 'WFO': 109235, 'TMY': 109044, 'ELH': 109015, 'WAV': 108969, 'ODC': 108862, 'SVO': 108777, 'XCH': 108776, 'LSM': 108724, 'CSO': 108718, 'ILB': 108710, 'KEV': 108693, 'DTU': 108525, 'BYG': 108479, 'EMM': 108453, 'MUM': 108426, 'TCU': 108386, 'IIS': 108367, 'HTM': 108276, 'OJO': 108187, 'RTP': 107970, 'WSE': 107778, 'GDA': 107757, 'OEM': 107672, 'POE': 107631, 'MEV': 107458, 'UCO': 107448, 'SHB': 107393, 'TIB': 107290, 'DYW': 107276, 'TBL': 107270, 'BYN': 107053, 'GOW': 107041, 'AAT': 106995, 'KSE': 106946, 'GBY': 106945, 'NYF': 106839, 'ATV': 106765, 'OUV': 106634, 'IAH': 106516, 'RTG': 106473, 'BBI': 106251, 'COI': 106225, 'OLB': 106072, 'UPB': 106063, 'NYR': 106030, 'VOU': 105980, 'FAF': 105908, 'FUE': 105736, 'THK': 105680, 'ZAN': 105649, 'OKL': 105497, 'NYH': 105339, 'OGL': 105036, 'UTG': 104986, 'RYN': 104984, 'BSA': 104948, 'AWT': 104849, 'WOC': 104848, 'TAA': 104840, 'NHU': 104731, 'UEB': 104550, 'OUK': 104512, 'LYK': 104364, 'KSS': 104310, 'CPR': 104269, 'CSC': 104080, 'GEX': 103997, 'MLE': 103920, 'CTC': 103908, 'GGO': 103881, 'OAV': 103880, 'RDD': 103809, 'KHO': 103755, 'BVI': 103722, 'IDP': 103589, 'SYC': 103563, 'HOV': 103555, 'RKN': 103514, 'SAK': 103482, 'ODB': 103350, 'COH': 103271, 'ANV': 103258, 'FDA': 103198, 'RUD': 103095, 'EBT': 103045, 'EKO': 102908, 'UPD': 102902, 'STJ': 102886, 'ATJ': 102836, 'AOR': 102836, 'WNH': 102833, 'CHG': 102726, 'ILR': 102677, 'WWI': 102665, 'AAL': 102622, 'LCU': 102603, 'IRN': 102380, 'JES': 102324, 'HNA': 102320, 'MEY': 102237, 'PWA': 102208, 'STK': 102207, 'AMF': 102174, 'OBT': 102146, 'YTW': 102077, 'DCI': 102057, 'ILV': 102013, 'KSC': 101977, 'YBI': 101847, 'RJA': 101772, 'OBV': 101754, 'SHP': 101649, 'EEG': 101565, 'UDA': 101558, 'DAA': 101528, 'KEU': 101470, 'UNB': 101230, 'AJA': 100886, 'FVI': 100842, 'EOS': 100757, 'UPC': 100676, 'YKI': 100577, 'GIF': 100483, 'OZE': 100412, 'OYM': 100262, 'UEW': 100260, 'OLC': 99990, 'LPU': 99935, 'CSI': 99920, 'WDO': 99885, 'WOD': 99832, 'NSG': 99824, 'LPT': 99809, 'ILU': 99526, 'OET': 99503, 'KIR': 99416, 'LUA': 99296, 'EXU': 99241, 'RKF': 99177, 'FEV': 99135, 'ETD': 99052, 'KSB': 98930, 'LOD': 98920, 'LCE': 98778, 'CKR': 98621, 'PIA': 98525, 'IGS': 98480, 'CKG': 98325, 'THJ': 98269, 'YRU': 98178, 'TKE': 97948, 'DPH': 97866, 'UBI': 97763, 'NAK': 97641, 'UCL': 97423, 'MAZ': 97375, 'UBM': 97358, 'TCI': 97301, 'TIW': 97255, 'ELR': 97137, 'GHC': 97095, 'YAW': 97013, 'GCL': 97007, 'MAF': 96785, 'AWK': 96762, 'SOE': 96704, 'COB': 96693, 'ELG': 96651, 'WSC': 96628, 'OOG': 96504, 'HAY': 96501, 'TYG': 96478, 'UGS': 96379, 'CRY': 96341, 'WLI': 96252, 'GTA': 96213, 'LFU': 96201, 'OIR': 96127, 'ODP': 96054, 'IAP': 95964, 'HYP': 95934, 'NIP': 95819, 'LPS': 95817, 'BYJ': 95526, 'WMO': 95495, 'ICG': 95379, 'ULP': 95334, 'RKH': 95255, 'IMF': 95188, 'OAK': 95092, 'RUB': 95088, 'SAA': 94953, 'FMY': 94830, 'XTT': 94797, 'FBI': 94781, 'LNA': 94621, 'HBR': 94542, 'USN': 94509, 'ESJ': 94496, 'WIR': 94196, 'FNA': 94171, 'GSF': 94138, 'UEF': 94044, 'NUC': 94023, 'CCH': 93967, 'SLU': 93842, 'RSK': 93607, 'EMF': 93573, 'UNW': 93563, 'KOV': 93475, 'WSW': 93473, 'WIM': 93306, 'YGI': 93266, 'OLM': 93256, 'UBU': 93147, 'TSK': 93034, 'NRY': 93016, 'ITG': 92912, 'BTA': 92910, 'HQU': 92754, 'HDR': 92742, 'OEL': 92496, 'UNR': 92479, 'SJA': 92435, 'SUD': 92375, 'MHO': 92338, 'KWE': 92321, 'BIE': 92170, 'LGI': 92141, 'MLA': 92132, 'UNP': 92025, 'FGE': 91911, 'OJU': 91737, 'LTW': 91553, 'IFU': 91511, 'RIU': 91482, 'DYN': 91421, 'IPR': 91088, 'YFU': 90961, 'UEC': 90939, 'NJE': 90938, 'ESQ': 90927, 'BBY': 90857, 'HAH': 90812, 'IMN': 90792, 'KIM': 90788, 'OAG': 90730, 'THV': 90681, 'OOB': 90670, 'DSR': 90632, 'WLY': 90482, 'KSL': 90369, 'XER': 90361, 'OLW': 90256, 'ROE': 90153, 'CSE': 90119, 'WEG': 90051, 'CTM': 90048, 'LSL': 90039, 'LMU': 89984, 'PEF': 89970, 'DRY': 89918, 'RNH': 89814, 'KFR': 89657, 'ULU': 89630, 'OTY': 89457, 'CUE': 89446, 'SSN': 89330, 'WNL': 89281, 'FGA': 89195, 'IFS': 89111, 'KHI': 88976, 'SMY': 88954, 'HGO': 88922, 'ILF': 88904, 'KGR': 88809, 'DUM': 88798, 'IJU': 88792, 'LSY': 88676, 'MYB': 88633, 'ILC': 88605, 'MAW': 88558, 'MYH': 88535, 'HFA': 88480, 'PUP': 88334, 'WSU': 88333, 'OOV': 88324, 'FPL': 88280, 'GAU': 88167, 'KRI': 88166, 'DIB': 87999, 'CEG': 87961, 'MWO': 87940, 'DIP': 87774, 'GHF': 87756, 'YAH': 87624, 'GIB': 87606, 'BAK': 87601, 'OLP': 87569, 'TUF': 87507, 'IKA': 87492, 'RTD': 87478, 'WAK': 87474, 'HOG': 87467, 'NYL': 87374, 'IOC': 87335, 'NKW': 87317, 'IRU': 87274, 'GHM': 87260, 'SYL': 87238, 'HRU': 87221, 'MYW': 87177, 'EFS': 87151, 'WUP': 87148, 'AML': 87145, 'YBL': 86934, 'NPH': 86835, 'IAD': 86807, 'LOI': 86760, 'KAM': 86518, 'HYE': 86496, 'JEF': 86471, 'IAO': 86417, 'XUA': 86176, 'GSS': 86176, 'NTJ': 86038, 'LKN': 86008, 'DSD': 85869, 'PDA': 85649, 'FCR': 85530, 'KBU': 85457, 'IOA': 85286, 'GBR': 85254, 'CYO': 85205, 'NUI': 84978, 'AMN': 84924, 'EEQ': 84845, 'RPS': 84837, 'RII': 84832, 'CUB': 84826, 'KBA': 84819, 'BIC': 84705, 'SKO': 84618, 'TSJ': 84410, 'LYV': 84386, 'YQU': 84283, 'PFR': 84202, 'NDQ': 84102, 'XCI': 84101, 'HTP': 83945, 'ALJ': 83928, 'III': 83861, 'LAA': 83837, 'RNF': 83809, 'POV': 83758, 'ILK': 83666, 'RAO': 83648, 'AGS': 83603, 'USG': 83591, 'DYB': 83576, 'IMH': 83401, 'INQ': 83362, 'MOK': 83359, 'BEV': 83357, 'MLO': 83247, 'KDO': 83036, 'OMG': 83010, 'MCH': 83009, 'UKN': 82963, 'GAY': 82857, 'FMU': 82834, 'WWA': 82746, 'YCU': 82727, 'KSP': 82682, 'FJU': 82608, 'WAB': 82604, 'WEM': 82592, 'AMR': 82554, 'CMA': 82520, 'XHI': 82456, 'AWR': 82242, 'KCA': 82127, 'LBY': 81999, 'WPR': 81991, 'WMU': 81967, 'IEM': 81882, 'FCL': 81847, 'LSD': 81839, 'TSV': 81777, 'CYT': 81645, 'YEM': 81587, 'PWH': 81534, 'OUF': 81478, 'WBE': 81359, 'IFW': 81282, 'DWR': 81151, 'CDE': 81105, 'NAY': 81080, 'GUM': 80963, 'LFW': 80957, 'TJA': 80944, 'FYI': 80906, 'AJU': 80703, 'PAK': 80544, 'IEB': 80509, 'LEK': 80454, 'RGH': 80408, 'EOG': 80376, 'KRO': 80177, 'IXI': 80109, 'DJE': 80084, 'GSB': 80053, 'OYI': 79930, 'UGO': 79919, 'RNB': 79808, 'MYP': 79780, 'SYA': 79738, 'HTY': 79699, 'VAD': 79515, 'DOD': 79506, 'IOW': 79402, 'YSD': 79337, 'RMC': 79316, 'YIF': 79303, 'ASQ': 79179, 'MYM': 79170, 'CTB': 79170, 'JEN': 78934, 'EKT': 78915, 'MSB': 78913, 'MGO': 78908, 'MDO': 78847, 'SOK': 78698, 'MAU': 78685, 'SHH': 78614, 'LFL': 78612, 'KPA': 78600, 'AKT': 78573, 'PEI': 78395, 'BSC': 78385, 'YSR': 78286, 'PSC': 78252, 'FGH': 78191, 'MDI': 78187, 'TUB': 78156, 'NWR': 78019, 'FOX': 77930, 'XCL': 77783, 'ENZ': 77712, 'UWI': 77711, 'NKR': 77696, 'UMT': 77641, 'DSN': 77537, 'ILP': 77510, 'TYN': 77500, 'IHO': 77464, 'UYI': 77457, 'RNW': 77409, 'LAZ': 77390, 'OPY': 77302, 'AER': 77181, 'YJA': 77157, 'RAJ': 77119, 'GYE': 77073, 'WME': 76959, 'GSY': 76925, 'WBU': 76818, 'IOF': 76793, 'HEZ': 76683, 'OJA': 76673, 'OWU': 76571, 'AYG': 76493, 'ODL': 76452, 'AMD': 76423, 'NOH': 76394, 'ECY': 76337, 'OTN': 76289, 'AFG': 76270, 'JAI': 76203, 'NOE': 76158, 'CDO': 76107, 'IAF': 75999, 'EYV': 75977, 'DYH': 75963, 'LJU': 75916, 'EKL': 75912, 'NKY': 75735, 'GYP': 75731, 'LCI': 75704, 'OKP': 75670, 'EZE': 75488, 'YPT': 75480, 'YHU': 75450, 'RNP': 75446, 'IDY': 75401, 'OGG': 75362, 'URU': 75359, 'BBL': 75344, 'MSL': 75312, 'FFW': 75302, 'WOA': 75281, 'XTO': 75208, 'UMW': 75188, 'JAS': 75164, 'LIL': 75161, 'WRA': 75110, 'POC': 75020, 'GCR': 75004, 'HYI': 74905, 'EBB': 74871, 'HVI': 74792, 'CEU': 74789, 'TPH': 74580, 'USY': 74551, 'NRS': 74538, 'HTU': 74537, 'EUK': 74478, 'MYL': 74470, 'XTY': 74387, 'LSR': 74316, 'XTS': 74302, 'CFO': 74204, 'WOB': 74170, 'DNU': 74146, 'CAF': 74086, 'DKA': 74038, 'MYI': 74020, 'DDY': 73873, 'ODH': 73849, 'JET': 73832, 'RNU': 73621, 'PCA': 73584, 'NKH': 73563, 'OKF': 73374, 'OWY': 73331, 'FPU': 73253, 'IBB': 73238, 'PYO': 73228, 'NZA': 73081, 'DYC': 73073, 'SOG': 72986, 'AWY': 72944, 'GSL': 72849, 'WWW': 72840, 'RYU': 72797, 'NIK': 72784, 'RKB': 72707, 'CYI': 72666, 'WBO': 72581, 'IRK': 72486, 'YOW': 72475, 'YFL': 72462, 'MRA': 72383, 'NIW': 72358, 'CEY': 72273, 'PGR': 72263, 'DYF': 72078, 'DSY': 71976, 'MYE': 71956, 'AZZ': 71914, 'WNM': 71899, 'DIW': 71830, 'MFI': 71684, 'GHR': 71636, 'ROH': 71631, 'PSS': 71626, 'GHD': 71555, 'HGA': 71537, 'HCL': 71441, 'DUB': 71346, 'HBI': 71340, 'EIP': 71324, 'DSK': 71253, 'FOT': 71216, 'FTB': 71158, 'LFC': 71101, 'GHN': 71009, 'SIP': 70884, 'ONZ': 70816, 'NMC': 70799, 'ICN': 70768, 'HTD': 70627, 'TVO': 70287, 'EOI': 70178, 'MSM': 70163, 'FHU': 70023, 'OAH': 69947, 'XON': 69875, 'WAD': 69856, 'NOG': 69856, 'KMO': 69833, 'MNA': 69824, 'PEW': 69765, 'MIF': 69741, 'YUP': 69701, 'UOU': 69693, 'HUL': 69607, 'USK': 69587, 'OSB': 69481, 'WEP': 69414, 'AKU': 69340, 'YAV': 69283, 'TUL': 69224, 'JIN': 69222, 'FFU': 69139, 'OTJ': 69119, 'PMO': 69009, 'AAC': 68958, 'GNT': 68890, 'DOZ': 68875, 'MEK': 68782, 'WNR': 68735, 'YKE': 68670, 'NIU': 68615, 'TNU': 68559, 'YVA': 68495, 'GFU': 68438, 'MRS': 68411, 'HIV': 68401, 'EIW': 68322, 'GMU': 68312, 'YSG': 68232, 'YPH': 68232, 'GAH': 68186, 'GEG': 68173, 'ANZ': 68062, 'IEI': 68035, 'DKN': 67961, 'DDS': 67959, 'IXO': 67951, 'YAU': 67916, 'AKN': 67867, 'LBI': 67798, 'CCL': 67721, 'RMW': 67702, 'FYE': 67608, 'XOF': 67516, 'WOH': 67326, 'THQ': 67241, 'IPU': 67142, 'RUR': 67124, 'GSM': 67089, 'LEJ': 66936, 'JEA': 66906, 'KAD': 66874, 'CTP': 66790, 'UPG': 66787, 'JAY': 66719, 'IMC': 66684, 'UDS': 66623, 'MCL': 66589, 'PSP': 66575, 'AYU': 66530, 'GVI': 66511, 'YGU': 66465, 'BHA': 66411, 'UAB': 66260, 'OLN': 66249, 'YVO': 66151, 'ULC': 66127, 'SNU': 66024, 'KPR': 65981, 'KAI': 65971, 'LDQ': 65961, 'IGB': 65935, 'RDN': 65921, 'CEV': 65717, 'WLA': 65714, 'LRU': 65708, 'VEV': 65686, 'VON': 65643, 'KYA': 65641, 'AMY': 65591, 'UEP': 65582, 'UNU': 65574, 'BTH': 65538, 'ZIL': 65427, 'BMI': 65360, 'PIP': 65346, 'FJA': 65332, 'FEO': 65302, 'LLV': 65207, 'KPL': 65155, 'BUF': 65107, 'WOG': 65079, 'SYT': 65048, 'HMU': 65046, 'CUI': 64998, 'GHU': 64955, 'MNI': 64930, 'ICV': 64820, 'YMB': 64793, 'FTF': 64773, 'MTR': 64729, 'SSK': 64617, 'YTU': 64582, 'HFU': 64544, 'ECC': 64477, 'GFE': 64472, 'FOS': 64377, 'MYD': 64351, 'OED': 64312, 'GDR': 64310, 'AWF': 64297, 'KIA': 64258, 'NYG': 64207, 'YLL': 64125, 'CPA': 64094, 'VIG': 64061, 'FJO': 64007, 'WSS': 63983, 'LFS': 63982, 'HFE': 63851, 'ETV': 63818, 'SMS': 63775, 'EMH': 63738, 'KRU': 63728, 'LUG': 63714, 'CDI': 63687, 'HCR': 63596, 'JAR': 63505, 'CWA': 63500, 'IZZ': 63434, 'ODM': 63240, 'GCE': 63230, 'UNH': 63182, 'EEZ': 63146, 'IRV': 63076, 'SHN': 63067, 'GBI': 62835, 'DEQ': 62829, 'PSF': 62790, 'HUA': 62760, 'KUN': 62735, 'RKM': 62651, 'AGH': 62645, 'PEP': 62479, 'LYY': 62466, 'PBU': 62455, 'PHR': 62453, 'YSN': 62402, 'KAY': 62373, 'IMG': 62349, 'RJE': 62099, 'EGS': 62038, 'AHM': 62026, 'KSU': 61964, 'IWH': 61945, 'HIK': 61919, 'MRO': 61882, 'DUK': 61861, 'MYR': 61826, 'ULM': 61759, 'TZE': 61732, 'EWU': 61669, 'AWL': 61559, 'XIT': 61537, 'RDG': 61523, 'EWG': 61482, 'OPF': 61361, 'OAW': 61315, 'BIK': 61279, 'YCI': 61255, 'WLO': 61251, 'EWJ': 61202, 'ZAB': 61081, 'IOG': 61022, 'KSM': 60994, 'CYS': 60988, 'UEH': 60971, 'GPI': 60971, 'OLH': 60959, 'TIH': 60887, 'KUR': 60877, 'SHY': 60834, 'HOK': 60821, 'WPO': 60765, 'IEU': 60680, 'IGT': 60628, 'EMN': 60581, 'OBY': 60562, 'NEK': 60478, 'KLO': 60456, 'YWR': 60444, 'RND': 60382, 'ISQ': 60371, 'ULG': 60362, 'KAW': 60314, 'PSU': 60272, 'KPO': 60254, 'YSY': 60099, 'FIA': 59962, 'GYI': 59951, 'WBA': 59930, 'LBL': 59924, 'PFI': 59896, 'SKT': 59725, 'UIE': 59678, 'BYU': 59678, 'OYT': 59651, 'SJE': 59614, 'NIX': 59579, 'GNU': 59554, 'EMR': 59550, 'OHU': 59537, 'LYJ': 59503, 'CSP': 59491, 'KOS': 59449, 'REZ': 59360, 'RYV': 59290, 'FDR': 59233, 'OPC': 59216, 'CSH': 59174, 'LJO': 59071, 'WSF': 59060, 'JOK': 59025, 'BOF': 59003, 'WDI': 58962, 'ONQ': 58952, 'BBA': 58923, 'KOB': 58911, 'RKP': 58880, 'ULB': 58858, 'HFL': 58731, 'RKL': 58702, 'WAC': 58654, 'OKH': 58631, 'POD': 58601, 'GTW': 58597, 'IRY': 58551, 'MBY': 58507, 'OOC': 58503, 'LKO': 58486, 'IWE': 58398, 'DAK': 58255, 'RWR': 58248, 'AKH': 58248, 'FCE': 58236, 'UZZ': 58224, 'UWO': 58217, 'LIQ': 58116, 'MBS': 58093, 'UYA': 58088, 'LDY': 57983, 'RKR': 57930, 'LKT': 57926, 'PSB': 57896, 'RDY': 57886, 'EMD': 57874, 'YLV': 57866, 'BIB': 57734, 'EEE': 57687, 'KAP': 57673, 'XTI': 57671, 'GJU': 57645, 'IPB': 57636, 'UGL': 57580, 'GPU': 57523, 'MIZ': 57490, 'KEG': 57444, 'DOH': 57434, 'UMU': 57416, 'AES': 57368, 'XFO': 57293, 'DLU': 57233, 'ERQ': 57220, 'FAW': 57146, 'ODN': 57105, 'GNM': 57062, 'HYW': 57053, 'LAX': 57033, 'HBY': 56997, 'MTE': 56857, 'KAC': 56789, 'IFN': 56724, 'NYN': 56723, 'CPO': 56675, 'OKU': 56617, 'OWG': 56602, 'PRU': 56578, 'TWR': 56556, 'NEQ': 56445, 'KWO': 56354, 'AIC': 56288, 'TVS': 56270, 'KFA': 56162, 'NAO': 56143, 'RCY': 56141, 'NSV': 56080, 'CSW': 56034, 'PHS': 56029, 'FIM': 56016, 'IXM': 55985, 'PAW': 55849, 'KME': 55845, 'WFR': 55836, 'VAG': 55833, 'GYT': 55816, 'GOM': 55811, 'OSN': 55758, 'IOP': 55743, 'EOD': 55724, 'SEK': 55707, 'WND': 55696, 'LQU': 55665, 'HUP': 55601, 'MSD': 55577, 'FFB': 55561, 'KNA': 55527, 'KSD': 55450, 'IEH': 55392, 'BCO': 55370, 'BRY': 55324, 'FAH': 55295, 'OAU': 55229, 'FOP': 55218, 'OOW': 55138, 'EGM': 55069, 'IFL': 54991, 'IKO': 54988, 'DGL': 54966, 'FFH': 54961, 'RYY': 54960, 'KDE': 54917, 'PAM': 54904, 'VEJ': 54855, 'FKI': 54837, 'UBO': 54835, 'HGE': 54744, 'UKA': 54717, 'LTD': 54710, 'RGL': 54692, 'EZA': 54621, 'GYM': 54517, 'OTK': 54427, 'LUP': 54425, 'NZE': 54359, 'OMJ': 54348, 'WDA': 54221, 'UPM': 54166, 'AZO': 54143, 'SHD': 54137, 'CSS': 54033, 'GJO': 54031, 'SYR': 53955, 'OYD': 53915, 'KAF': 53807, 'UAS': 53760, 'IGM': 53725, 'NKF': 53687, 'WPA': 53661, 'AWM': 53643, 'UMC': 53618, 'EYU': 53618, 'MOI': 53616, 'NGQ': 53608, 'IHE': 53600, 'WAM': 53579, 'EYK': 53435, 'YAI': 53421, 'PBY': 53374, 'AAD': 53262, 'AII': 53219, 'GQU': 53205, 'ZEO': 53204, 'WAP': 53096, 'CGR': 52846, 'EZO': 52826, 'HJO': 52767, 'YID': 52766, 'HJU': 52617, 'ETG': 52572, 'OUE': 52569, 'LGU': 52558, 'TRS': 52551, 'CWI': 52528, 'CTD': 52372, 'IMD': 52368, 'PTF': 52354, 'LLJ': 52305, 'MTA': 52291, 'IYA': 52233, 'FBL': 52170, 'MJU': 52078, 'UEM': 51999, 'TEJ': 51969, 'WWO': 51884, 'XHA': 51826, 'OXE': 51803, 'BAP': 51746, 'EGN': 51682, 'AXP': 51658, 'KCI': 51656, 'KFI': 51581, 'TOQ': 51539, 'NAZ': 51525, 'LVO': 51522, 'KBO': 51441, 'RMF': 51414, 'GGS': 51305, 'TKA': 51291, 'PDE': 51288, 'RML': 51243, 'EXO': 51209, 'LNU': 51157, 'UTK': 51151, 'WEK': 51130, 'HAZ': 51113, 'AYY': 51078, 'PTR': 51036, 'SSG': 50996, 'KTI': 50918, 'FVA': 50866, 'FFM': 50858, 'MSR': 50823, 'GRY': 50526, 'DYP': 50502, 'LUX': 50486, 'PGA': 50477, 'MFA': 50458, 'CCR': 50443, 'XCO': 50427, 'FFF': 50386, 'KBY': 50335, 'DSG': 50325, 'ABD': 50325, 'YOB': 50301, 'BYK': 50254, 'ULN': 50122, 'ADQ': 50091, 'OEI': 50063, 'IBO': 50004, 'HAO': 50001, 'BMA': 49985, 'IML': 49945, 'GBL': 49880, 'RSV': 49878, 'UOR': 49877, 'FEU': 49831, 'KCH': 49826, 'DYL': 49793, 'FTY': 49778, 'BBO': 49772, 'LTF': 49760, 'BCA': 49758, 'BAU': 49681, 'ALQ': 49672, 'UNM': 49627, 'PUM': 49625, 'AYJ': 49602, 'EOA': 49594, 'TEY': 49589, 'CYB': 49581, 'SOX': 49559, 'EML': 49488, 'SOY': 49484, 'EIA': 49477, 'WMI': 49450, 'EKW': 49421, 'LTB': 49409, 'EPM': 49398, 'BOI': 49384, 'OSF': 49368, 'MYG': 49309, 'XTU': 49291, 'OER': 49239, 'HKO': 49217, 'ULK': 49080, 'ZZA': 49046, 'NKB': 49022, 'STQ': 49021, 'FCI': 49021, 'IPC': 49009, 'MGR': 48998, 'DYM': 48978, 'UKI': 48968, 'LFB': 48960, 'UYE': 48958, 'KOT': 48915, 'BEK': 48848, 'HTG': 48837, 'WEF': 48824, 'TJE': 48814, 'WFA': 48773, 'HMY': 48757, 'PAV': 48649, 'AKF': 48517, 'MFE': 48511, 'RBS': 48451, 'YIE': 48419, 'HSW': 48279, 'FPI': 48218, 'FTC': 48212, 'MUP': 48165, 'LJA': 48070, 'YNC': 48054, 'OPW': 48032, 'NLU': 48024, 'AXA': 48017, 'OSY': 48003, 'IJI': 47999, 'UTJ': 47986, 'BTO': 47962, 'CME': 47956, 'OKW': 47953, 'HYB': 47925, 'BYV': 47916, 'RMB': 47913, 'FVE': 47897, 'EZI': 47884, 'CWH': 47880, 'EWZ': 47819, 'YOC': 47808, 'JUA': 47783, 'GMY': 47776, 'WSM': 47757, 'UWE': 47728, 'YSK': 47710, 'IMR': 47674, 'CAW': 47623, 'GOC': 47607, 'MCG': 47591, 'FUG': 47554, 'ABC': 47520, 'SUT': 47502, 'KYL': 47491, 'JAZ': 47487, 'WZE': 47446, 'CSU': 47423, 'CYW': 47394, 'SGL': 47331, 'HSL': 47267, 'GKO': 47193, 'FCU': 47189, 'LSN': 47184, 'FYT': 47132, 'FPH': 47033, 'LUI': 46955, 'AHS': 46940, 'LRY': 46934, 'ZZL': 46926, 'BAH': 46883, 'OKC': 46833, 'NYY': 46771, 'RSJ': 46749, 'XMO': 46747, 'ULW': 46732, 'CEJ': 46645, 'LHU': 46537, 'HAA': 46500, 'KIP': 46494, 'AUM': 46477, 'WPE': 46395, 'CBO': 46382, 'AJE': 46370, 'LSK': 46222, 'TUG': 46218, 'OKM': 46177, 'AIA': 46163, 'COE': 46093, 'PTW': 46065, 'CUN': 45993, 'NEZ': 45981, 'ILG': 45922, 'DVD': 45896, 'MRI': 45836, 'RNR': 45813, 'FTU': 45809, 'HKI': 45795, 'UGI': 45766, 'CMO': 45758, 'PYT': 45699, 'SMC': 45689, 'CYR': 45689, 'EHY': 45493, 'YND': 45478, 'ZEI': 45430, 'SAJ': 45350, 'NBC': 45283, 'CNE': 45266, 'WCH': 45215, 'WJE': 45179, 'NAE': 44995, 'SIW': 44992, 'GVE': 44974, 'GEU': 44938, 'IIA': 44898, 'LDV': 44866, 'XTD': 44861, 'CBA': 44787, 'RHY': 44764, 'RLU': 44719, 'GDU': 44718, 'IXA': 44715, 'TOX': 44679, 'CYP': 44670, 'SKM': 44656, 'EUL': 44606, 'UFO': 44592, 'EPC': 44564, 'TAO': 44510, 'WTE': 44506, 'CWO': 44495, 'BBC': 44398, 'NDZ': 44385, 'AKL': 44367, 'HVA': 44363, 'DDH': 44346, 'OMV': 44321, 'AMG': 44321, 'HUD': 44292, 'HUB': 44280, 'MPB': 44275, 'MUD': 44246, 'HPI': 44188, 'GSD': 44142, 'PTC': 44026, 'CIZ': 44024, 'PSM': 43928, 'AZY': 43848, 'IOI': 43840, 'ZLE': 43776, 'IDJ': 43768, 'UMF': 43763, 'SHG': 43730, 'VEK': 43716, 'GGU': 43655, 'LIU': 43475, 'XTM': 43470, 'RMP': 43441, 'ZEL': 43398, 'RMR': 43384, 'DYR': 43336, 'PTY': 43290, 'SKF': 43224, 'NII': 43192, 'XCU': 43171, 'VUL': 43162, 'GWR': 43152, 'MVE': 43083, 'GOH': 43075, 'LFH': 43059, 'MGE': 42946, 'IPF': 42934, 'PMT': 42920, 'LDJ': 42919, 'CBE': 42895, 'ELK': 42893, 'HUC': 42857, 'RKD': 42845, 'MEJ': 42809, 'PEG': 42725, 'GEY': 42710, 'EOM': 42702, 'OXF': 42669, 'MIM': 42628, 'OFQ': 42580, 'AAF': 42562, 'SYD': 42555, 'WIG': 42541, 'RIR': 42539, 'IXS': 42515, 'PIK': 42467, 'KTA': 42459, 'HSM': 42449, 'FEF': 42444, 'DIH': 42413, 'NIB': 42397, 'KSR': 42379, 'NOK': 42365, 'NEJ': 42356, 'MCD': 42291, 'DTY': 42254, 'FDU': 42240, 'HPU': 42206, 'HVE': 42205, 'IAE': 42173, 'EYJ': 42158, 'EWN': 42084, 'GCU': 41906, 'IOM': 41898, 'ILN': 41894, 'CHJ': 41891, 'WSB': 41834, 'KOL': 41813, 'OPB': 41806, 'ZIE': 41790, 'NAJ': 41775, 'LFD': 41775, 'WOE': 41765, 'YNT': 41758, 'UEZ': 41755, 'CHK': 41668, 'CBU': 41651, 'IGL': 41637, 'EKH': 41584, 'PPS': 41544, 'KPE': 41535, 'DYD': 41530, 'NIH': 41510, 'LIR': 41489, 'LUK': 41475, 'LPF': 41459, 'GYS': 41454, 'CMI': 41445, 'FJE': 41441, 'EDQ': 41438, 'ITJ': 41434, 'RYJ': 41413, 'IIT': 41402, 'WOI': 41378, 'YAK': 41377, 'FQU': 41372, 'GUT': 41315, 'IGP': 41148, 'LFF': 41111, 'WKS': 41105, 'WNU': 41079, 'OXA': 41064, 'BWA': 41047, 'FFC': 41022, 'WSK': 40997, 'EKR': 40973, 'KUS': 40927, 'FGU': 40880, 'VRE': 40866, 'UIV': 40866, 'HNM': 40860, 'VIK': 40847, 'OSK': 40824, 'XRE': 40822, 'PYR': 40819, 'PBA': 40772, 'IEP': 40750, 'UPU': 40719, 'NZI': 40677, 'OKB': 40674, 'CFI': 40655, 'MOG': 40647, 'LSG': 40639, 'CLY': 40601, 'AOS': 40586, 'FKE': 40549, 'MOH': 40521, 'WFI': 40489, 'HJA': 40466, 'OMK': 40452, 'AXO': 40449, 'ZHA': 40448, 'KTR': 40423, 'LTC': 40420, 'KDA': 40415, 'RGS': 40312, 'MAO': 40298, 'OUO': 40296, 'PYA': 40158, 'KGO': 40157, 'TYU': 40153, 'AUB': 40145, 'FKA': 40113, 'KYS': 40091, 'KAA': 40066, 'SMT': 40056, 'MCR': 40040, 'XTW': 39984, 'TEK': 39964, 'HBL': 39921, 'CVI': 39916, 'RNL': 39907, 'PNE': 39904, 'FEH': 39873, 'AAP': 39862, 'CFA': 39740, 'LAO': 39731, 'NKM': 39718, 'IOO': 39714, 'FAK': 39713, 'EIH': 39656, 'GID': 39646, 'LTL': 39593, 'ZAL': 39555, 'AEN': 39538, 'DMC': 39502, 'AEA': 39415, 'NYU': 39391, 'FYA': 39378, 'MOP': 39367, 'TIQ': 39345, 'OYC': 39321, 'IJA': 39315, 'XTF': 39277, 'PIG': 39249, 'ACS': 39246, 'PDO': 39146, 'GKI': 39080, 'PCH': 39004, 'KAH': 38990, 'IEO': 38978, 'DEY': 38971, 'RMH': 38923, 'AIW': 38905, 'OOH': 38843, 'CIM': 38842, 'MAV': 38828, 'CHV': 38802, 'RIW': 38787, 'TLU': 38776, 'BUG': 38727, 'NUO': 38657, 'OSD': 38642, 'GSR': 38637, 'HYH': 38591, 'MTI': 38532, 'OAI': 38488, 'DOX': 38414, 'TMC': 38280, 'HYM': 38201, 'YLU': 38191, 'VAB': 38132, 'FSW': 38101, 'OLR': 38092, 'DAE': 38073, 'ELN': 38047, 'CPL': 38038, 'SEJ': 38000, 'EIZ': 37966, 'GAA': 37957, 'CNA': 37934, 'KSG': 37931, 'APY': 37929, 'GFL': 37820, 'ZEC': 37792, 'EIJ': 37768, 'EUD': 37764, 'AQI': 37688, 'GHG': 37673, 'BDU': 37660, 'ORQ': 37643, 'UEG': 37579, 'ZIS': 37567, 'YEF': 37490, 'ROZ': 37437, 'YOL': 37416, 'AKR': 37415, 'WBR': 37405, 'GLU': 37394, 'RYK': 37360, 'KDI': 37359, 'UAK': 37355, 'PAF': 37354, 'YEI': 37345, 'GCI': 37337, 'IFR': 37330, 'AWW': 37275, 'VOY': 37214, 'MCE': 37213, 'CEK': 37174, 'ERZ': 37165, 'LDK': 37148, 'BOG': 37102, 'TTP': 37064, 'OLG': 37059, 'ARJ': 37029, 'VAM': 36973, 'BSW': 36854, 'YDN': 36833, 'ZOO': 36795, 'PMI': 36782, 'FSM': 36685, 'ZAC': 36679, 'GIG': 36655, 'NJI': 36641, 'DYG': 36635, 'MYN': 36603, 'YOS': 36589, 'UYT': 36497, 'UBW': 36475, 'HSS': 36434, 'CYL': 36390, 'UBC': 36348, 'HDU': 36304, 'ECS': 36269, 'KBR': 36266, 'WTR': 36168, 'OSQ': 36091, 'OSR': 36074, 'EXS': 35999, 'SMR': 35997, 'XTA': 35952, 'AGM': 35947, 'MGA': 35936, 'YNN': 35934, 'LNI': 35934, 'RIX': 35925, 'FIB': 35849, 'WIE': 35775, 'BCS': 35756, 'EHR': 35730, 'TYY': 35706, 'FNI': 35701, 'YMC': 35624, 'NKC': 35580, 'GNW': 35520, 'WNG': 35482, 'KMI': 35465, 'AJI': 35465, 'TCY': 35447, 'WAU': 35430, 'PKI': 35409, 'FAY': 35377, 'GYC': 35376, 'GVA': 35338, 'IAU': 35332, 'TGL': 35330, 'OEC': 35327, 'CYM': 35313, 'AKW': 35272, 'WSR': 35200, 'IRJ': 35198, 'ULR': 35162, 'MIU': 35067, 'AXC': 35048, 'SHV': 35043, 'DDT': 35008, 'EKM': 35001, 'AWB': 34981, 'OKY': 34973, 'UOF': 34941, 'MSN': 34883, 'LEQ': 34870, 'USV': 34809, 'IGC': 34806, 'EPB': 34773, 'EGH': 34764, 'RKU': 34691, 'FTP': 34690, 'HSB': 34647, 'DMR': 34565, 'OYL': 34527, 'GNC': 34523, 'NOX': 34513, 'JAK': 34508, 'HCU': 34457, 'OIF': 34449, 'RLF': 34417, 'FVO': 34405, 'CTN': 34331, 'LMC': 34326, 'EAY': 34315, 'CSF': 34298, 'AAB': 34294, 'HKE': 34251, 'LUL': 34175, 'MDU': 34166, 'NUL': 34124, 'HCI': 34123, 'PNO': 34046, 'MUG': 34028, 'EPW': 34026, 'DAO': 34025, 'OXY': 34013, 'DEZ': 34000, 'PSL': 33977, 'WUN': 33939, 'CAK': 33900, 'XIL': 33893, 'PEM': 33844, 'KIW': 33824, 'YKA': 33789, 'WEX': 33769, 'UEV': 33743, 'CAH': 33729, 'OEF': 33702, 'ANX': 33681, 'EPF': 33678, 'OZA': 33675, 'CUA': 33620, 'LFP': 33614, 'KOW': 33588, 'UWH': 33552, 'ARQ': 33545, 'VAU': 33520, 'UBR': 33402, 'TSQ': 33398, 'AUK': 33358, 'MAE': 33343, 'AHL': 33279, 'OTV': 33239, 'BSH': 33207, 'NZO': 33184, 'UTV': 33166, 'SIH': 33157, 'LOL': 33085, 'WSL': 33065, 'FFY': 33021, 'MCK': 32958, 'FOV': 32936, 'PEB': 32924, 'WAF': 32895, 'GOG': 32886, 'AAM': 32882, 'BUB': 32856, 'YJE': 32831, 'MPM': 32811, 'KUL': 32807, 'WFU': 32769, 'ULH': 32747, 'BOE': 32731, 'ARZ': 32722, 'KDR': 32698, 'NOY': 32686, 'ECD': 32645, 'SIU': 32632, 'LMT': 32583, 'UGB': 32555, 'WGO': 32548, 'EIK': 32484, 'OOO': 32472, 'FUM': 32469, 'TYV': 32448, 'HHU': 32446, 'AED': 32432, 'YMY': 32422, 'YNU': 32415, 'TUI': 32407, 'SUK': 32389, 'AIK': 32387, 'EAE': 32374, 'TWW': 32356, 'VOW': 32329, 'EZS': 32301, 'CSB': 32287, 'BAA': 32283, 'KIF': 32225, 'OYF': 32208, 'TII': 32207, 'CDA': 32199, 'PSD': 32193, 'OVS': 32191, 'UON': 32174, 'INZ': 32165, 'XWI': 32148, 'MCI': 32111, 'IOB': 32108, 'OPD': 32102, 'DEK': 32096, 'XCA': 32092, 'DIZ': 32075, 'EKB': 32074, 'VOK': 32057, 'FSY': 32057, 'ANQ': 32053, 'RNN': 32042, 'IHI': 32013, 'NSJ': 32011, 'SKU': 32006, 'WOV': 31953, 'EXW': 31943, 'JAV': 31923, 'OXS': 31836, 'HYL': 31835, 'MOA': 31830, 'IGD': 31823, 'XEM': 31746, 'LIH': 31732, 'HNN': 31720, 'GVO': 31638, 'OOA': 31594, 'JOA': 31592, 'CPE': 31575, 'GPH': 31562, 'CAO': 31561, 'EIB': 31499, 'GNP': 31485, 'DEJ': 31474, 'YIL': 31466, 'MVI': 31441, 'HYC': 31441, 'OYW': 31423, 'NSQ': 31416, 'EPD': 31383, 'UCR': 31241, 'UMH': 31201, 'ZEW': 31190, 'WNN': 31190, 'AHN': 31158, 'IBS': 31124, 'AXR': 31091, 'IKH': 31088, 'AAA': 31081, 'AHR': 31044, 'RMM': 31039, 'CGA': 31023, 'KTE': 31022, 'TAJ': 31021, 'CFR': 30974, 'GNF': 30910, 'PSR': 30874, 'TEQ': 30831, 'LWR': 30820, 'HYN': 30805, 'RMD': 30791, 'CNO': 30784, 'SSQ': 30750, 'GYW': 30744, 'FOI': 30733, 'LIW': 30652, 'CKJ': 30646, 'BSS': 30610, 'GJA': 30586, 'UKR': 30508, 'NXI': 30498, 'IXW': 30417, 'ZEM': 30392, 'AUX': 30367, 'WPL': 30310, 'AHT': 30266, 'CEX': 30248, 'BBS': 30247, 'AVR': 30224, 'WGR': 30204, 'ITV': 30195, 'XIA': 30185, 'YRS': 30168, 'GSK': 30161, 'LMY': 30124, 'KII': 30124, 'LTM': 30059, 'KFU': 29935, 'RKY': 29925, 'RDQ': 29919, 'XIE': 29896, 'DGM': 29889, 'PWO': 29869, 'HRY': 29825, 'RTV': 29778, 'YEO': 29771, 'TIK': 29765, 'CYF': 29754, 'MJA': 29747, 'NHL': 29742, 'NKU': 29684, 'OOI': 29664, 'IXY': 29650, 'ABH': 29637, 'AKD': 29590, 'EKU': 29570, 'NKP': 29566, 'TTT': 29498, 'OSG': 29485, 'FFP': 29463, 'FGL': 29386, 'AHW': 29336, 'FSL': 29292, 'IFP': 29280, 'TTC': 29235, 'APM': 29181, 'PDI': 29174, 'PFU': 29115, 'HPH': 29110, 'EFC': 29097, 'GAE': 29089, 'EOH': 29064, 'EII': 29056, 'KEX': 29050, 'ELJ': 29028, 'GSN': 28992, 'XAT': 28975, 'HGU': 28969, 'LYZ': 28963, 'TIU': 28946, 'XYE': 28940, 'DJI': 28920, 'BTE': 28883, 'ETZ': 28881, 'DRS': 28856, 'ZAS': 28832, 'RRS': 28812, 'KOP': 28810, 'KSN': 28805, 'AAG': 28777, 'UBD': 28731, 'XPI': 28710, 'CBS': 28701, 'TZA': 28680, 'ZIM': 28633, 'UPY': 28613, 'FEP': 28602, 'LMW': 28593, 'GSG': 28592, 'UMD': 28557, 'DAJ': 28540, 'FUP': 28515, 'ZSA': 28501, 'FTM': 28440, 'BFO': 28434, 'RIH': 28427, 'EPY': 28408, 'IXP': 28405, 'IGF': 28376, 'YZE': 28366, 'XMA': 28365, 'OUJ': 28343, 'PWE': 28340, 'BWI': 28325, 'LFM': 28320, 'WIP': 28316, 'EOO': 28302, 'PMS': 28282, 'BTS': 28260, 'TAE': 28248, 'JIA': 28244, 'FTL': 28180, 'PBO': 28168, 'KCL': 28166, 'MLY': 28129, 'PEH': 28120, 'SIK': 28114, 'RZA': 28089, 'SMW': 28069, 'AYV': 28050, 'RIJ': 28029, 'WCL': 28006, 'MSG': 27994, 'UDL': 27949, 'UFI': 27902, 'ALZ': 27901, 'WKI': 27853, 'CNN': 27844, 'PYW': 27818, 'EWV': 27802, 'KOM': 27798, 'DZO': 27797, 'UMR': 27796, 'AIV': 27740, 'HVO': 27702, 'SKR': 27695, 'OBW': 27687, 'RTZ': 27686, 'OWJ': 27676, 'FOB': 27644, 'ZZI': 27639, 'UXU': 27607, 'GIU': 27606, 'ZAM': 27605, 'PEV': 27592, 'UAI': 27591, 'KYT': 27576, 'YAA': 27555, 'SAO': 27551, 'FBY': 27542, 'ATZ': 27532, 'MJO': 27507, 'IDK': 27504, 'CWE': 27484, 'RDJ': 27460, 'SPS': 27459, 'OEU': 27457, 'IAK': 27454, 'LOH': 27451, 'YEC': 27442, 'SII': 27428, 'OOE': 27423, 'HGI': 27407, 'BDI': 27400, 'MDR': 27387, 'UYO': 27355, 'POM': 27317, 'CAE': 27312, 'XID': 27300, 'COY': 27271, 'ZOR': 27218, 'LPM': 27216, 'BUZ': 27216, 'HSF': 27165, 'UJU': 27162, 'UYW': 27159, 'SBN': 27146, 'FGI': 27105, 'GYF': 27096, 'NYK': 27092, 'MUE': 27077, 'OWK': 27072, 'ATQ': 27056, 'IUN': 27050, 'RNG': 27044, 'BEJ': 27019, 'EJI': 27004, 'EXM': 26988, 'HII': 26977, 'HKA': 26912, 'GHY': 26896, 'EUG': 26892, 'ADK': 26878, 'IFM': 26854, 'OKR': 26846, 'LII': 26838, 'EUC': 26725, 'IFC': 26709, 'XIB': 26629, 'AUP': 26619, 'MKI': 26616, 'AEM': 26616, 'OBC': 26583, 'AUE': 26562, 'MOW': 26554, 'DYK': 26553, 'NYV': 26515, 'KAU': 26506, 'AEX': 26496, 'SAX': 26480, 'OXO': 26431, 'XUR': 26410, 'BWE': 26391, 'RPM': 26357, 'MCN': 26349, 'WEJ': 26314, 'JAG': 26299, 'JAB': 26299, 'MRU': 26288, 'RZE': 26230, 'TMR': 26221, 'AWC': 26220, 'UPN': 26171, 'GIZ': 26115, 'OFZ': 26108, 'DKO': 26088, 'FEG': 26062, 'ENQ': 26054, 'MFU': 26045, 'ABW': 26045, 'XIO': 26038, 'SSV': 25996, 'SPY': 25987, 'GTU': 25980, 'KUM': 25977, 'WTI': 25959, 'KKE': 25940, 'IGW': 25937, 'ETJ': 25936, 'UML': 25895, 'CZE': 25893, 'YYA': 25867, 'SHK': 25867, 'AEO': 25856, 'XWE': 25847, 'IOH': 25834, 'PCL': 25824, 'VIB': 25822, 'UAC': 25799, 'VAA': 25785, 'ACD': 25779, 'TTM': 25741, 'UBH': 25735, 'NTQ': 25735, 'CYH': 25727, 'ZAK': 25724, 'CGO': 25697, 'EKC': 25669, 'IPG': 25617, 'HNC': 25615, 'HMS': 25606, 'LEZ': 25595, 'AXT': 25594, 'KVI': 25552, 'NNW': 25539, 'SMD': 25525, 'KPI': 25508, 'FFD': 25506, 'BTT': 25489, 'XST': 25460, 'LMM': 25432, 'RTJ': 25413, 'EVS': 25412, 'CTG': 25404, 'KEJ': 25328, 'GAO': 25310, 'EBC': 25299, 'YIR': 25275, 'KMU': 25263, 'RKG': 25260, 'TTB': 25255, 'APB': 25215, 'BOC': 25207, 'PFA': 25167, 'EKF': 25138, 'IXC': 25135, 'SAQ': 25118, 'MPF': 25104, 'WTA': 25081, 'EAJ': 25068, 'UBP': 25048, 'BHO': 24960, 'LAE': 24952, 'DPM': 24927, 'LYQ': 24925, 'BAF': 24904, 'WSD': 24889, 'YIW': 24841, 'MRB': 24832, 'WAH': 24796, 'WLS': 24784, 'OEB': 24783, 'WOK': 24765, 'DUO': 24727, 'CBR': 24725, 'HNB': 24719, 'FFG': 24696, 'AHY': 24675, 'HYF': 24651, 'KYW': 24639, 'KAZ': 24626, 'KKI': 24623, 'XTB': 24617, 'LKW': 24608, 'EZW': 24608, 'DAQ': 24560, 'RLW': 24556, 'DUG': 24545, 'IMJ': 24506, 'TYJ': 24469, 'DIK': 24462, 'PYI': 24457, 'RPT': 24380, 'CSM': 24374, 'WJO': 24358, 'UHE': 24350, 'XWA': 24348, 'MCM': 24340, 'UDR': 24310, 'PBR': 24284, 'FNU': 24233, 'OIA': 24228, 'MNS': 24171, 'BWH': 24163, 'EIE': 24160, 'EFB': 24142, 'KOK': 24126, 'CTY': 24119, 'ITK': 24114, 'YMN': 24106, 'HJE': 24082, 'UFE': 24064, 'MTU': 24051, 'LPP': 24032, 'SYI': 24028, 'CYN': 24011, 'PTL': 23998, 'NUX': 23991, 'RDV': 23985, 'DUD': 23982, 'LUF': 23967, 'MRM': 23958, 'VYW': 23954, 'HNU': 23950, 'PAA': 23938, 'EEJ': 23926, 'EIO': 23880, 'CTV': 23859, 'EXF': 23850, 'AWP': 23844, 'KKA': 23837, 'LOE': 23826, 'MSY': 23815, 'HNW': 23800, 'UJI': 23793, 'AVS': 23786, 'HIW': 23780, 'ZAI': 23772, 'CIG': 23751, 'MIO': 23744, 'PUE': 23731, 'OXT': 23702, 'RCT': 23669, 'UKO': 23662, 'AGT': 23649, 'XBO': 23624, 'APC': 23623, 'HNH': 23610, 'WUS': 23605, 'GGY': 23582, 'MPW': 23577, 'RLT': 23545, 'VAK': 23519, 'SRS': 23491, 'CKV': 23473, 'PAH': 23464, 'EMG': 23427, 'ILJ': 23426, 'TKO': 23416, 'BDE': 23413, 'IOV': 23398, 'VAP': 23338, 'IKS': 23316, 'PEY': 23311, 'WAW': 23249, 'UGT': 23242, 'NCS': 23238, 'ZWA': 23225, 'ODJ': 23199, 'NNC': 23197, 'SAE': 23174, 'AFS': 23143, 'KEK': 23123, 'XRA': 23108, 'BSP': 23082, 'UDT': 23046, 'ZIO': 23032, 'RGW': 23015, 'UVA': 22934, 'AWD': 22929, 'HIH': 22911, 'CIC': 22911, 'WFE': 22898, 'CSL': 22874, 'VII': 22865, 'PTB': 22858, 'EKD': 22853, 'NKD': 22831, 'VYA': 22813, 'CSD': 22806, 'CKK': 22797, 'CFE': 22793, 'AKY': 22767, 'XOR': 22746, 'SPN': 22736, 'NGZ': 22733, 'EUV': 22684, 'DII': 22684, 'UDB': 22682, 'RUF': 22643, 'FWR': 22643, 'OIG': 22631, 'NNB': 22614, 'EPG': 22613, 'UIA': 22610, 'BTR': 22581, 'BSU': 22563, 'BYY': 22548, 'WII': 22532, 'OXC': 22532, 'PUC': 22518, 'YGL': 22500, 'PGO': 22495, 'USJ': 22476, 'AEV': 22447, 'TZI': 22440, 'CYD': 22431, 'EOK': 22416, 'RDK': 22405, 'BPR': 22380, 'AYK': 22371, 'CAY': 22362, 'EZU': 22361, 'AIP': 22341, 'SKH': 22331, 'UEU': 22322, 'WKE': 22309, 'GYB': 22285, 'APW': 22262, 'UCU': 22160, 'KYR': 22160, 'TTF': 22159, 'FTD': 22146, 'PEZ': 22139, 'HSY': 22136, 'SYW': 22126, 'LTP': 22112, 'XWH': 22106, 'AET': 22090, 'MHU': 22084, 'DIX': 22067, 'ZEF': 22063, 'AOU': 22060, 'NNH': 22049, 'BSF': 22010, 'YOG': 22001, 'JOL': 21986, 'XSE': 21966, 'IPD': 21964, 'DSV': 21962, 'CFL': 21962, 'TZS': 21945, 'CPU': 21921, 'GEQ': 21916, 'TYK': 21906, 'IEX': 21882, 'OPK': 21866, 'SMF': 21845, 'AOL': 21841, 'JAD': 21799, 'PHD': 21769, 'IEE': 21751, 'BPA': 21750, 'MVA': 21738, 'HYR': 21713, 'VST': 21711, 'BTI': 21701, 'DPS': 21682, 'AIF': 21612, 'MFL': 21583, 'GEJ': 21575, 'BBR': 21563, 'IKK': 21538, 'YTY': 21531, 'DOK': 21527, 'ETK': 21501, 'OXW': 21481, 'YSV': 21469, 'DHY': 21442, 'DSQ': 21390, 'VSH': 21388, 'VSK': 21384, 'GHV': 21370, 'SKW': 21366, 'EDZ': 21357, 'YUK': 21350, 'AEU': 21344, 'LMF': 21324, 'AXB': 21321, 'ZAA': 21298, 'ICJ': 21290, 'WDR': 21286, 'AKB': 21285, 'OGH': 21269, 'CDR': 21267, 'NTZ': 21262, 'RJI': 21249, 'PEX': 21235, 'AUF': 21228, 'HOY': 21179, 'KCR': 21138, 'URJ': 21136, 'NUG': 21120, 'EVR': 21109, 'LMB': 21094, 'BSB': 21081, 'SCS': 21066, 'IAV': 21048, 'LIX': 21045, 'COX': 21028, 'OYH': 21019, 'NKG': 21008, 'KAV': 21005, 'OZO': 20971, 'HIZ': 20971, 'AHP': 20924, 'WIK': 20916, 'KYI': 20915, 'UVI': 20901, 'IXF': 20867, 'LTZ': 20865, 'ECB': 20857, 'EVY': 20813, 'OPG': 20798, 'KGA': 20790, 'PIZ': 20789, 'NNF': 20762, 'UOI': 20732, 'EXR': 20697, 'JUI': 20694, 'ZEB': 20680, 'MEQ': 20673, 'WEO': 20651, 'CSR': 20650, 'EHM': 20631, 'OWV': 20592, 'NMR': 20586, 'MTW': 20578, 'WSN': 20574, 'OIW': 20558, 'PIM': 20531, 'VYS': 20513, 'UNJ': 20503, 'YPS': 20458, 'OGT': 20452, 'WBI': 20438, 'AUA': 20437, 'AMJ': 20436, 'EXB': 20427, 'UDW': 20424, 'VLA': 20398, 'KAK': 20379, 'UJA': 20369, 'RUZ': 20363, 'IIW': 20343, 'SMB': 20342, 'EFD': 20299, 'XLE': 20295, 'AQA': 20287, 'GNB': 20278, 'GHJ': 20248, 'AOP': 20239, 'XME': 20234, 'CYE': 20218, 'DYU': 20214, 'LPB': 20210, 'VOS': 20207, 'JUV': 20200, 'TLL': 20194, 'HUE': 20186, 'SSJ': 20158, 'DRM': 20151, 'PSN': 20150, 'OKD': 20133, 'HTV': 20133, 'UNV': 20131, 'OYB': 20123, 'FIW': 20122, 'KYE': 20105, 'ZHE': 20091, 'WDS': 20087, 'HUF': 20083, 'ZMA': 20061, 'YOM': 20056, 'BOH': 20046, 'WGE': 20023, 'KHU': 20020, 'WSY': 20002, 'AZU': 19982, 'OBH': 19970, 'VEZ': 19967, 'MIH': 19962, 'CMU': 19934, 'EKP': 19926, 'AIB': 19923, 'FAX': 19904, 'BDO': 19898, 'CGE': 19870, 'ACM': 19869, 'NNT': 19866, 'RGT': 19856, 'PPU': 19830, 'VSE': 19809, 'AXW': 19756, 'ECP': 19755, 'FOW': 19742, 'YUA': 19738, 'AKP': 19727, 'KFE': 19700, 'FKN': 19699, 'APF': 19695, 'WIZ': 19681, 'EFM': 19679, 'GKE': 19645, 'SUZ': 19628, 'EZH': 19613, 'MCU': 19608, 'FRY': 19598, 'IDV': 19590, 'XTP': 19564, 'WAA': 19563, 'UAY': 19537, 'WCR': 19511, 'HAJ': 19507, 'LSQ': 19488, 'YSJ': 19477, 'IXD': 19474, 'UDH': 19473, 'XEL': 19450, 'LOK': 19445, 'KJO': 19441, 'EVU': 19435, 'LJE': 19421, 'BME': 19415, 'ZEP': 19382, 'VTH': 19358, 'OEY': 19348, 'MUH': 19341, 'IEJ': 19340, 'YUR': 19328, 'MKE': 19302, 'VRO': 19295, 'FSK': 19295, 'IEK': 19251, 'XTG': 19239, 'KDU': 19238, 'HND': 19225, 'ZEH': 19215, 'AHB': 19210, 'GKA': 19205, 'EAQ': 19191, 'PUZ': 19173, 'ZUR': 19171, 'NND': 19148, 'IFB': 19148, 'LPC': 19136, 'IXH': 19130, 'SPM': 19127, 'FAA': 19115, 'SYF': 19061, 'FIO': 19059, 'KOO': 19041, 'EBP': 19038, 'TZO': 18997, 'NUK': 18995, 'FUC': 18991, 'LKH': 18972, 'ZTH': 18963, 'GYR': 18958, 'VSA': 18953, 'LPW': 18950, 'WGA': 18939, 'NAQ': 18930, 'UKS': 18925, 'DZI': 18907, 'YZA': 18870, 'AAI': 18869, 'JAW': 18864, 'OUU': 18846, 'MSK': 18805, 'XAR': 18803, 'CSY': 18782, 'BCH': 18781, 'BIZ': 18736, 'RRH': 18735, 'YOK': 18734, 'YAY': 18716, 'UZA': 18691, 'UOM': 18686, 'JAL': 18667, 'PMU': 18665, 'MPC': 18662, 'ZIA': 18650, 'YEW': 18622, 'ORZ': 18616, 'RNY': 18588, 'MRC': 18588, 'IKU': 18584, 'EGT': 18582, 'IIM': 18558, 'BTL': 18549, 'OVT': 18532, 'EWK': 18517, 'YKO': 18502, 'ABT': 18501, 'WIV': 18493, 'USQ': 18477, 'XEN': 18463, 'OGW': 18463, 'OJI': 18393, 'LMD': 18391, 'UXI': 18389, 'WBY': 18375, 'AMV': 18366, 'UKU': 18358, 'FAE': 18345, 'SCY': 18331, 'KJA': 18325, 'PMF': 18321, 'YEP': 18317, 'WEU': 18310, 'AXS': 18273, 'XTC': 18269, 'NPM': 18268, 'FKM': 18267, 'EFW': 18257, 'MEZ': 18245, 'ZHO': 18218, 'UCS': 18209, 'DRH': 18193, 'MYK': 18190, 'QIN': 18180, 'QAN': 18171, 'JAH': 18167, 'FOA': 18159, 'KYB': 18158, 'YEQ': 18144, 'IBM': 18129, 'UQU': 18104, 'LSV': 18088, 'FEY': 18084, 'ZZO': 18053, 'DTV': 18043, 'TOZ': 18036, 'PFE': 18023, 'CIB': 18012, 'UEJ': 17993, 'BYZ': 17976, 'DZE': 17952, 'KOH': 17946, 'MII': 17924, 'IOE': 17920, 'GEK': 17914, 'YMR': 17861, 'BCR': 17857, 'VYC': 17853, 'MBT': 17835, 'MQU': 17831, 'WVE': 17791, 'EFP': 17786, 'MIW': 17776, 'GAK': 17766, 'YIC': 17758, 'UHO': 17741, 'LUO': 17684, 'WYN': 17661, 'JUG': 17648, 'LQA': 17640, 'HNT': 17639, 'OEH': 17638, 'MGU': 17632, 'BNO': 17632, 'MGL': 17602, 'YPM': 17580, 'OEW': 17577, 'TKM': 17566, 'BHI': 17544, 'AHH': 17520, 'AMK': 17503, 'FKO': 17476, 'WNV': 17460, 'RNJ': 17448, 'BUE': 17418, 'DSJ': 17400, 'ZIP': 17380, 'BEQ': 17349, 'JEE': 17330, 'HSD': 17309, 'GJE': 17307, 'PHU': 17280, 'IZU': 17272, 'AOT': 17268, 'MYV': 17263, 'IIO': 17233, 'XVI': 17216, 'DTS': 17207, 'YUG': 17192, 'OPN': 17187, 'DNR': 17182, 'WVI': 17159, 'HLU': 17142, 'MKA': 17107, 'PIX': 17104, 'PDR': 17090, 'HMC': 17088, 'DUI': 17061, 'GYD': 17058, 'ULV': 17055, 'PFL': 17053, 'SMM': 17051, 'YSQ': 17047, 'ACB': 17047, 'CGU': 17045, 'GNH': 17039, 'RLB': 17007, 'KIB': 16998, 'HNF': 16986, 'OEP': 16953, 'PHT': 16952, 'BBU': 16951, 'OBD': 16906, 'XDE': 16888, 'JIT': 16887, 'UDU': 16878, 'CDS': 16874, 'SYB': 16853, 'DRB': 16843, 'HNP': 16828, 'PCR': 16795, 'SNR': 16791, 'PMM': 16769, 'TTD': 16767, 'ZWH': 16721, 'AKM': 16719, 'RLH': 16714, 'KPU': 16711, 'CPH': 16710, 'ZAG': 16704, 'FLS': 16698, 'PSG': 16692, 'UBF': 16690, 'UTZ': 16679, 'FSN': 16671, 'RZO': 16649, 'AKK': 16637, 'SZE': 16633, 'FOG': 16633, 'AAU': 16618, 'MVP': 16612, 'CPI': 16597, 'XBU': 16576, 'KIH': 16565, 'KSY': 16560, 'ZEE': 16523, 'NYJ': 16521, 'CVE': 16510, 'FFN': 16502, 'IXG': 16485, 'PGE': 16480, 'OHY': 16464, 'APD': 16464, 'SJI': 16435, 'AFC': 16430, 'NUD': 16428, 'ZIG': 16427, 'ZAD': 16417, 'ACP': 16393, 'DAZ': 16386, 'KUT': 16370, 'TUO': 16356, 'XCR': 16347, 'AOI': 16338, 'AAV': 16302, 'AKC': 16295, 'WRU': 16293, 'YNS': 16284, 'KOC': 16279, 'LFG': 16275, 'MGI': 16274, 'EUE': 16274, 'HSR': 16258, 'SMP': 16170, 'HWR': 16164, 'YIA': 16161, 'UGM': 16158, 'BCT': 16151, 'LPY': 16150, 'CNI': 16134, 'OXB': 16123, 'BAW': 16110, 'AGW': 16110, 'KFL': 16097, 'RUK': 16095, 'YMM': 16088, 'GPS': 16081, 'AIO': 16077, 'OKG': 16067, 'AHC': 16064, 'BHE': 16058, 'OYN': 16044, 'HUI': 16028, 'GKN': 16000, 'XNE': 15983, 'KOA': 15978, 'PTP': 15968, 'FMR': 15968, 'CIU': 15966, 'BSD': 15934, 'KJU': 15923, 'IIC': 15921, 'ZLI': 15901, 'XYG': 15895, 'RTK': 15891, 'DUF': 15832, 'RPC': 15827, 'DRD': 15818, 'BIP': 15809, 'TTG': 15802, 'ZAP': 15797, 'OZI': 15774, 'UKH': 15753, 'PDU': 15747, 'GDP': 15734, 'IBY': 15690, 'SFY': 15679, 'FYF': 15679, 'PKE': 15675, 'LMP': 15664, 'GND': 15658, 'RMG': 15655, 'JOC': 15653, 'UIZ': 15638, 'TVC': 15627, 'PQU': 15601, 'ODV': 15588, 'HYG': 15584, 'MYU': 15560, 'ARX': 15554, 'QWH': 15547, 'EOX': 15540, 'OTQ': 15527, 'UGR': 15517, 'GHQ': 15511, 'JIL': 15506, 'MMC': 15494, 'XSA': 15489, 'KYP': 15470, 'HNL': 15460, 'VCO': 15453, 'PMW': 15453, 'DZA': 15448, 'KVA': 15440, 'FOE': 15437, 'WPI': 15436, 'NHY': 15435, 'HKN': 15434, 'IXR': 15404, 'DKR': 15401, 'IXB': 15384, 'SOJ': 15359, 'VEQ': 15354, 'SNY': 15354, 'FCC': 15353, 'GYH': 15350, 'PTM': 15321, 'PEU': 15316, 'MYJ': 15314, 'KBL': 15298, 'XHO': 15288, 'MPP': 15267, 'XGA': 15263, 'AOV': 15255, 'RIY': 15236, 'KOI': 15235, 'WBL': 15231, 'SMH': 15223, 'OBM': 15204, 'LKL': 15195, 'GNL': 15190, 'SZA': 15186, 'WKN': 15167, 'EAZ': 15163, 'HSN': 15148, 'HUK': 15145, 'KVE': 15143, 'AUO': 15112, 'YIG': 15089, 'MOZ': 15087, 'RYQ': 15084, 'QIS': 15078, 'KOD': 15077, 'LBS': 15055, 'DCY': 15031, 'NPS': 15030, 'OGB': 15015, 'KTW': 14998, 'CGI': 14992, 'MRP': 14991, 'OHL': 14977, 'EMV': 14944, 'IJO': 14909, 'XAL': 14904, 'TAQ': 14899, 'KMY': 14891, 'ZZE': 14871, 'MTV': 14847, 'NOJ': 14833, 'HTJ': 14819, 'ONX': 14818, 'WCE': 14815, 'MRH': 14808, 'EGW': 14793, 'YEB': 14792, 'VWA': 14752, 'DDW': 14738, 'ZTO': 14727, 'KYM': 14709, 'KIO': 14691, 'AAW': 14685, 'SYP': 14682, 'ECW': 14672, 'ZAW': 14665, 'TDS': 14658, 'KYH': 14652, 'IWR': 14623, 'PCI': 14618, 'MIB': 14604, 'LKR': 14599, 'PCS': 14593, 'BNE': 14592, 'RGM': 14584, 'AOC': 14584, 'WHU': 14552, 'KSV': 14551, 'XLI': 14539, 'AXY': 14535, 'YUT': 14531, 'LMR': 14520, 'IMK': 14514, 'WFL': 14507, 'FSS': 14494, 'RCS': 14490, 'LSJ': 14466, 'UUS': 14443, 'HNR': 14442, 'UUM': 14426, 'LGL': 14410, 'WQU': 14406, 'HIJ': 14400, 'GIW': 14393, 'EGB': 14393, 'FMC': 14366, 'KYC': 14331, 'IYO': 14329, 'AGP': 14327, 'UBY': 14313, 'KLU': 14299, 'YEU': 14297, 'BNA': 14290, 'MOE': 14285, 'POG': 14274, 'LMH': 14255, 'UOW': 14248, 'BPO': 14242, 'ZUE': 14241, 'URQ': 14239, 'HOJ': 14223, 'SDY': 14200, 'AXL': 14195, 'RGC': 14187, 'IAZ': 14184, 'JEL': 14171, 'UEX': 14163, 'VYI': 14146, 'CBC': 14124, 'IMV': 14119, 'PYS': 14083, 'KJE': 14080, 'YAO': 14079, 'NUB': 14060, 'EXL': 14041, 'LAQ': 14018, 'LLQ': 14010, 'EZT': 13990, 'CBY': 13986, 'UMG': 13968, 'DKU': 13941, 'ZOM': 13931, 'RNV': 13926, 'BOP': 13912, 'LCY': 13890, 'LTG': 13884, 'KSK': 13884, 'TJI': 13879, 'IMY': 13871, 'RMN': 13861, 'EKY': 13858, 'XOT': 13852, 'KMM': 13852, 'ZUM': 13845, 'HAQ': 13838, 'IFD': 13832, 'OCS': 13831, 'KUA': 13827, 'MMS': 13826, 'UOV': 13806, 'IVY': 13802, 'UHI': 13797, 'LKM': 13793, 'JRA': 13793, 'HTK': 13789, 'LAJ': 13772, 'LTV': 13771, 'KMH': 13765, 'RAX': 13750, 'FSD': 13750, 'UAM': 13749, 'KBI': 13743, 'KIK': 13718, 'YIH': 13706, 'GMC': 13705, 'EZB': 13688, 'SND': 13684, 'UNY': 13678, 'BWO': 13672, 'YEY': 13655, 'CBI': 13645, 'MKN': 13638, 'PBI': 13637, 'PCU': 13626, 'SHJ': 13622, 'XFI': 13610, 'NRB': 13608, 'OEG': 13598, 'GNR': 13590, 'YRD': 13586, 'GYL': 13579, 'UFR': 13573, 'VAW': 13559, 'ZCO': 13550, 'KUB': 13514, 'UOL': 13496, 'MWR': 13488, 'CTJ': 13486, 'AIH': 13445, 'OBF': 13439, 'JIS': 13423, 'KGE': 13422, 'VYT': 13406, 'OCY': 13406, 'OGD': 13404, 'MIP': 13399, 'GAJ': 13395, 'CDU': 13386, 'LKB': 13383, 'PNA': 13374, 'EUB': 13352, 'BHU': 13343, 'BSM': 13340, 'XMI': 13333, 'EFJ': 13333, 'XAG': 13300, 'PYE': 13292, 'KYD': 13292, 'MPD': 13254, 'AGD': 13254, 'XUS': 13246, 'CVA': 13242, 'OOZ': 13213, 'YOA': 13203, 'ROQ': 13202, 'HSK': 13176, 'HNG': 13176, 'VRA': 13171, 'YOD': 13164, 'AUI': 13164, 'OZZ': 13155, 'OHM': 13123, 'ZBE': 13120, 'ACW': 13105, 'KGI': 13079, 'ZUK': 13075, 'ZAH': 13075, 'WEY': 13071, 'OAA': 13063, 'PJO': 13054, 'PIV': 13042, 'UXE': 13027, 'XBR': 13018, 'CFU': 13017, 'ODK': 13008, 'ZZY': 13001, 'CEQ': 12988, 'PJU': 12985, 'HLS': 12962, 'GMS': 12951, 'AHD': 12944, 'XBE': 12932, 'VOD': 12932, 'EGP': 12931, 'ABN': 12919, 'PIF': 12907, 'KAO': 12906, 'PVI': 12901, 'UCY': 12891, 'TML': 12881, 'GYU': 12870, 'CUF': 12869, 'BUK': 12868, 'OXH': 12864, 'ECF': 12851, 'AXD': 12842, 'MOY': 12839, 'BCN': 12838, 'MNU': 12829, 'TMS': 12825, 'NFC': 12814, 'FIH': 12814, 'TZW': 12812, 'ECM': 12800, 'AEC': 12795, 'EAX': 12787, 'ASZ': 12774, 'FTG': 12765, 'DRC': 12763, 'OGM': 12757, 'BAE': 12752, 'WNY': 12748, 'UKT': 12746, 'TUK': 12743, 'EUA': 12724, 'RKK': 12718, 'GUO': 12707, 'EKK': 12692, 'KMS': 12676, 'WJU': 12671, 'WVA': 12668, 'SUV': 12665, 'AXM': 12639, 'EBM': 12633, 'AEG': 12630, 'OSV': 12627, 'UGC': 12622, 'BCE': 12622, 'PEK': 12618, 'TTV': 12612, 'TZG': 12606, 'AIE': 12601, 'NZY': 12592, 'UDC': 12587, 'BSL': 12565, 'AUW': 12547, 'AOW': 12547, 'FPS': 12539, 'WPU': 12536, 'SGT': 12533, 'NDX': 12528, 'EHN': 12523, 'KNU': 12499, 'CCS': 12494, 'AGB': 12488, 'ISZ': 12477, 'VAH': 12447, 'HNK': 12445, 'NNM': 12443, 'EMK': 12423, 'ECZ': 12423, 'RXI': 12421, 'PPH': 12417, 'KKN': 12416, 'IBN': 12409, 'PHW': 12403, 'WYA': 12401, 'PAO': 12396, 'FEQ': 12382, 'POA': 12377, 'WKW': 12366, 'OGC': 12359, 'LKC': 12344, 'CSN': 12338, 'NCK': 12331, 'AQW': 12324, 'XWO': 12321, 'PUD': 12312, 'TCT': 12279, 'RZI': 12260, 'PSK': 12252, 'OHS': 12252, 'NCC': 12247, 'BTW': 12245, 'ZWI': 12238, 'FTN': 12237, 'HGL': 12233, 'FSF': 12226, 'IIH': 12224, 'KQU': 12218, 'BDA': 12216, 'OGF': 12187, 'XSO': 12175, 'AOA': 12170, 'YDS': 12156, 'KTU': 12150, 'CJO': 12149, 'JED': 12140, 'PMC': 12138, 'PMY': 12124, 'LTN': 12116, 'KCU': 12110, 'OXN': 12104, 'WSG': 12092, 'BOK': 12088, 'JIB': 12080, 'EHL': 12066, 'BSR': 12062, 'COK': 12055, 'WNJ': 12050, 'IAJ': 12011, 'VTO': 12009, 'DMS': 11999, 'SKB': 11971, 'LKF': 11971, 'NGX': 11970, 'PHL': 11967, 'AOH': 11952, 'SPC': 11949, 'WGU': 11946, 'AEF': 11944, 'SPT': 11939, 'RGB': 11937, 'TEZ': 11934, 'MUK': 11925, 'FAJ': 11904, 'UTQ': 11903, 'FSB': 11900, 'XDI': 11897, 'RKJ': 11890, 'EXD': 11864, 'RKV': 11860, 'MRR': 11854, 'ESZ': 11851, 'NRH': 11848, 'KCE': 11845, 'ZGE': 11844, 'OAY': 11834, 'FHY': 11832, 'WCI': 11819, 'MPG': 11815, 'LZA': 11796, 'IHU': 11788, 'TIJ': 11785, 'IFG': 11783, 'KYF': 11779, 'XAV': 11745, 'YMS': 11704, 'CCC': 11702, 'WIW': 11697, 'IRQ': 11692, 'RGP': 11677, 'LKY': 11677, 'ZHI': 11672, 'OKK': 11668, 'NCB': 11658, 'IKM': 11658, 'MRD': 11650, 'WMY': 11649, 'BAV': 11643, 'ZST': 11627, 'YUM': 11624, 'XSP': 11608, 'RPG': 11592, 'MJE': 11574, 'GOK': 11568, 'WCU': 11551, 'UGD': 11542, 'WJA': 11533, 'NOQ': 11525, 'INX': 11525, 'OIH': 11516, 'SUH': 11513, 'BCC': 11501, 'SZO': 11500, 'UZE': 11496, 'DOJ': 11489, 'CUD': 11474, 'NCW': 11473, 'GYN': 11466, 'ZCA': 11463, 'XII': 11431, 'DCC': 11431, 'SBC': 11426, 'BAO': 11422, 'ICZ': 11419, 'IID': 11411, 'TVT': 11402, 'YTV': 11391, 'IYE': 11374, 'MRG': 11367, 'MSV': 11341, 'VYR': 11340, 'BGR': 11340, 'RNK': 11330, 'EHS': 11329, 'CYG': 11326, 'EKG': 11320, 'EHT': 11316, 'EBH': 11299, 'XFR': 11291, 'VIP': 11285, 'BCI': 11285, 'UMV': 11279, 'AAK': 11275, 'KUD': 11274, 'AXF': 11265, 'MPY': 11253, 'XDO': 11246, 'TPW': 11238, 'SLT': 11216, 'UIM': 11215, 'OGP': 11206, 'SKL': 11205, 'BMO': 11188, 'EGF': 11177, 'JEV': 11175, 'HJI': 11174, 'IIB': 11168, 'MMM': 11167, 'OYU': 11163, 'RFS': 11162, 'BIF': 11159, 'XBA': 11156, 'LNS': 11149, 'GOJ': 11144, 'TMP': 11142, 'HYU': 11126, 'HMR': 11118, 'DDC': 11114, 'JAT': 11105, 'WAX': 11101, 'UIG': 11080, 'DDM': 11079, 'YOH': 11076, 'YAJ': 11059, 'TTN': 11036, 'KHS': 11004, 'PYF': 11000, 'IOX': 11000, 'LZO': 10998, 'SPP': 10968, 'DCS': 10961, 'EFH': 10953, 'IKT': 10951, 'UPK': 10947, 'MPK': 10926, 'CUU': 10926, 'UYB': 10923, 'SRH': 10921, 'MRT': 10912, 'XSH': 10898, 'ACF': 10871, 'OBP': 10864, 'SVS': 10852, 'AQS': 10852, 'VDS': 10848, 'MIY': 10848, 'NNP': 10847, 'AIJ': 10831, 'OYP': 10822, 'MLB': 10818, 'CUO': 10818, 'LPD': 10814, 'AIZ': 10810, 'DTD': 10798, 'SOQ': 10783, 'CDC': 10779, 'VSC': 10775, 'LIJ': 10766, 'WDU': 10764, 'RGF': 10758, 'JEO': 10746, 'AGY': 10741, 'BMW': 10729, 'EUF': 10728, 'VYD': 10718, 'MVO': 10718, 'OVW': 10714, 'XRO': 10713, 'UXO': 10711, 'OFX': 10710, 'UAP': 10692, 'EZZ': 10689, 'UAW': 10673, 'YIV': 10667, 'ZYA': 10663, 'XFA': 10654, 'RBT': 10653, 'VHA': 10647, 'HRS': 10641, 'CVO': 10636, 'UOD': 10634, 'EZC': 10631, 'MRK': 10629, 'KKO': 10623, 'ZRE': 10619, 'JUB': 10616, 'TKU': 10609, 'GHK': 10606, 'EXG': 10604, 'MRW': 10586, 'UYH': 10566, 'NNR': 10545, 'YEG': 10539, 'ZYM': 10537, 'PRY': 10536, 'UXA': 10534, 'DKM': 10521, 'UGP': 10511, 'UPJ': 10487, 'RGN': 10474, 'CSG': 10470, 'UZU': 10468, 'KAE': 10467, 'PYC': 10464, 'CHQ': 10454, 'SCB': 10446, 'TPS': 10435, 'VYM': 10408, 'AAH': 10407, 'UGW': 10406, 'VPR': 10405, 'VLI': 10385, 'HSG': 10385, 'KSJ': 10382, 'SCC': 10373, 'EGC': 10367, 'ZOF': 10355, 'VPA': 10353, 'FLC': 10345, 'FTV': 10342, 'KMC': 10325, 'EXY': 10324, 'RBC': 10315, 'YLY': 10313, 'CBL': 10310, 'IPN': 10307, 'LPG': 10291, 'AWG': 10288, 'AEI': 10273, 'AOB': 10269, 'OUX': 10268, 'PTD': 10263, 'KIV': 10246, 'QAE': 10243, 'OEQ': 10229, 'GSQ': 10228, 'IIF': 10227, 'VYL': 10224, 'UFT': 10220, 'ZHU': 10217, 'PUG': 10214, 'AOK': 10211, 'BAZ': 10207, 'MCS': 10185, 'PCE': 10183, 'YOI': 10181, 'FLD': 10178, 'ZBO': 10177, 'BFR': 10175, 'MCF': 10162, 'EUI': 10162, 'GOY': 10161, 'MRL': 10153, 'XSC': 10152, 'NMS': 10144, 'LOQ': 10140, 'TZH': 10136, 'FUK': 10134, 'BSN': 10134, 'MNT': 10132, 'PAE': 10131, 'ECN': 10097, 'IIP': 10096, 'DIJ': 10069, 'NZH': 10066, 'YZI': 10065, 'JIG': 10057, 'AOM': 10044, 'FSQ': 10038, 'NCD': 10035, 'VCH': 10024, 'BCL': 10024, 'APN': 10013, 'YRN': 10003, 'TCS': 9984, 'VDA': 9975, 'AVU': 9969, 'NOZ': 9965, 'XTL': 9953, 'ZOL': 9940, 'OHR': 9929, 'RBH': 9926, 'OZY': 9923, 'ACN': 9922, 'NJR': 9921, 'OXL': 9918, 'XDA': 9912, 'DRJ': 9911, 'KAJ': 9894, 'EBN': 9888, 'WIA': 9887, 'TVW': 9878, 'DYJ': 9876, 'FCS': 9867, 'VCA': 9863, 'PIU': 9857, 'PWW': 9852, 'LMG': 9844, 'VWH': 9839, 'UOA': 9837, 'YJI': 9835, 'NMD': 9832, 'IPY': 9831, 'VYO': 9824, 'KUW': 9817, 'BIM': 9810, 'PPT': 9804, 'BCW': 9804, 'YIP': 9795, 'PGI': 9795, 'RUH': 9792, 'HIU': 9780, 'GJI': 9779, 'VMA': 9767, 'NNG': 9766, 'FRS': 9762, 'OXP': 9741, 'ZIR': 9724, 'AHF': 9717, 'EZR': 9715, 'OYR': 9713, 'HYY': 9707, 'WLT': 9704, 'LML': 9704, 'VYB': 9693, 'QWA': 9684, 'UOY': 9681, 'NYQ': 9679, 'ZOS': 9674, 'RCK': 9670, 'PHC': 9667, 'KRY': 9646, 'DRP': 9640, 'WTW': 9634, 'IIR': 9621, 'THZ': 9616, 'SXI': 9608, 'BPS': 9603, 'BAJ': 9602, 'EOE': 9599, 'RIQ': 9594, 'TVP': 9585, 'SFT': 9581, 'TZK': 9580, 'IXL': 9574, 'KOZ': 9560, 'RLC': 9554, 'NAX': 9542, 'FSR': 9521, 'UAA': 9514, 'UJO': 9505, 'EYY': 9504, 'WGI': 9492, 'ZUN': 9478, 'SNB': 9477, 'EZD': 9473, 'EBD': 9468, 'YDW': 9464, 'PMP': 9444, 'PYL': 9442, 'CNU': 9438, 'EPN': 9436, 'OAQ': 9433, 'XLA': 9432, 'DKH': 9431, 'FUJ': 9418, 'LKU': 9410, 'SKP': 9398, 'RGD': 9398, 'AGF': 9381, 'WRY': 9376, 'OAX': 9352, 'IJE': 9348, 'XOP': 9343, 'BTF': 9341, 'PBL': 9338, 'FYS': 9333, 'SKC': 9331, 'UAH': 9328, 'OAJ': 9328, 'DWY': 9327, 'UPV': 9318, 'OUY': 9312, 'IUL': 9312, 'BIH': 9309, 'NPP': 9303, 'FOD': 9302, 'UBG': 9288, 'CZA': 9287, 'UEY': 9270, 'UUN': 9250, 'KGU': 9248, 'DND': 9248, 'AXH': 9231, 'OBG': 9230, 'FEJ': 9222, 'RLL': 9217, 'UYL': 9213, 'RPP': 9208, 'DRR': 9172, 'UOP': 9171, 'KOE': 9159, 'OXM': 9127, 'WTU': 9126, 'YNG': 9122, 'PYB': 9122, 'VYF': 9108, 'CUC': 9106, 'VAE': 9092, 'DDV': 9091, 'ZDE': 9082, 'FLT': 9063, 'VRI': 9057, 'RCM': 9048, 'VNE': 9036, 'FAQ': 9035, 'SDS': 9032, 'PDF': 9029, 'ORX': 9011, 'KMF': 9002, 'FYW': 9001, 'EGD': 8995, 'VOG': 8985, 'FCY': 8985, 'MLU': 8984, 'TAZ': 8981, 'DHR': 8980, 'ZBA': 8973, 'MBH': 8968, 'WVO': 8963, 'GIH': 8962, 'RLM': 8958, 'PYH': 8957, 'AUH': 8953, 'AUV': 8952, 'ITQ': 8947, 'POB': 8935, 'ZUL': 8931, 'TKR': 8920, 'JIH': 8920, 'LHY': 8913, 'OHT': 8910, 'LFY': 8910, 'YKR': 8906, 'DRW': 8904, 'FOM': 8900, 'ZAF': 8889, 'WNK': 8887, 'JAF': 8881, 'VSP': 8874, 'KPH': 8871, 'LCD': 8870, 'BPL': 8867, 'WOJ': 8866, 'UIF': 8866, 'SRY': 8866, 'OBN': 8847, 'DRG': 8836, 'SCD': 8826, 'EVL': 8823, 'CAJ': 8818, 'GYG': 8817, 'BIW': 8817, 'WSV': 8814, 'RUV': 8793, 'BUO': 8791, 'QUR': 8790, 'MBW': 8781, 'SUW': 8777, 'ZIT': 8775, 'GMR': 8774, 'JOD': 8762, 'TZT': 8761, 'DCT': 8755, 'SYU': 8754, 'UGF': 8744, 'JIR': 8743, 'DGY': 8733, 'UYF': 8723, 'MRF': 8713, 'MUI': 8696, 'VSS': 8693, 'ULJ': 8672, 'ERX': 8671, 'BCU': 8670, 'YCY': 8660, 'PLC': 8659, 'LKP': 8656, 'MYY': 8644, 'SKD': 8642, 'BII': 8636, 'ZEG': 8632, 'YLS': 8625, 'UKW': 8625, 'MSJ': 8620, 'MLS': 8619, 'DCB': 8618, 'OLJ': 8614, 'SCM': 8598, 'EBW': 8597, 'GDY': 8596, 'UAF': 8595, 'UOB': 8576, 'OIP': 8565, 'CCT': 8560, 'DYV': 8559, 'XFE': 8558, 'ZSC': 8555, 'FFJ': 8546, 'APG': 8533, 'OIV': 8532, 'MUA': 8525, 'JAA': 8519, 'LVD': 8509, 'EUX': 8509, 'EVW': 8500, 'SBS': 8496, 'CSK': 8495, 'ADZ': 8493, 'XHE': 8486, 'KVO': 8486, 'PWR': 8483, 'NNL': 8465, 'IKR': 8452, 'AVV': 8452, 'OLZ': 8443, 'YEH': 8442, 'VOF': 8441, 'XSU': 8428, 'VAJ': 8421, 'DDB': 8421, 'MKO': 8412, 'KMN': 8411, 'NMP': 8407, 'WPH': 8406, 'ZBU': 8403, 'ELZ': 8397, 'UYC': 8396, 'JHA': 8395, 'FAZ': 8394, 'PJA': 8393, 'RCC': 8384, 'BTC': 8381, 'OPJ': 8363, 'ABM': 8345, 'SCT': 8334, 'OHW': 8325, 'NHS': 8321, 'SDW': 8314, 'VOO': 8307, 'UZI': 8304, 'SML': 8289, 'NKJ': 8288, 'FKU': 8288, 'HMM': 8286, 'PYM': 8278, 'ZYS': 8269, 'ZEK': 8269, 'AVL': 8268, 'YBC': 8265, 'WLW': 8259, 'UXT': 8255, 'AFP': 8253, 'BEZ': 8250, 'OVC': 8249, 'GIP': 8241, 'JUT': 8235, 'NCN': 8230, 'MCB': 8219, 'JPM': 8218, 'BNI': 8215, 'OII': 8214, 'PBS': 8208, 'NCP': 8208, 'CTK': 8206, 'GSV': 8205, 'CJA': 8205, 'AGC': 8191, 'YHY': 8186, 'SRD': 8186, 'VAO': 8179, 'VAF': 8177, 'PEJ': 8166, 'KWR': 8166, 'YDB': 8164, 'VUE': 8155, 'SYH': 8154, 'BFI': 8148, 'FMS': 8147, 'VDE': 8145, 'LZE': 8145, 'YUL': 8138, 'DRT': 8135, 'SRB': 8134, 'OSJ': 8127, 'NPC': 8126, 'PHB': 8123, 'TTK': 8110, 'MCP': 8106, 'UDM': 8100, 'FJI': 8098, 'LRS': 8083, 'LFN': 8080, 'VIZ': 8079, 'VDI': 8069, 'MBC': 8060, 'TDW': 8058, 'BLV': 8053, 'FYH': 8043, 'NCM': 8039, 'YAQ': 8037, 'EZM': 8022, 'ZRA': 8014, 'EZF': 8014, 'EXX': 8007, 'BJO': 8004, 'JUP': 7999, 'YKU': 7997, 'BEX': 7993, 'KIG': 7991, 'OWQ': 7988, 'UVR': 7982, 'AWU': 7981, 'CDP': 7974, 'XPU': 7969, 'PYD': 7965, 'FOK': 7958, 'PHM': 7951, 'TMD': 7948, 'OXV': 7946, 'PII': 7931, 'KUK': 7923, 'VDR': 7900, 'UYM': 7900, 'YNB': 7899, 'OIE': 7897, 'MGM': 7891, 'AEP': 7888, 'ZTE': 7886, 'FIJ': 7884, 'DAX': 7884, 'XAB': 7882, 'OXR': 7877, 'ICQ': 7874, 'LUV': 7869, 'TCC': 7864, 'PGU': 7864, 'PVE': 7862, 'GZH': 7858, 'EUW': 7858, 'RUW': 7857, 'PHP': 7851, 'LKD': 7843, 'KOG': 7839, 'TRH': 7830, 'HPS': 7821, 'LCS': 7817, 'AKG': 7806, 'KUC': 7804, 'MBB': 7795, 'TVN': 7793, 'OSX': 7792, 'HZA': 7789, 'UPQ': 7781, 'RLP': 7774, 'UYU': 7762, 'WWF': 7758, 'TCB': 7755, 'TZP': 7754, 'BFA': 7751, 'WWR': 7748, 'BPE': 7745, 'WIH': 7736, 'SJR': 7731, 'ABF': 7707, 'AZT': 7694, 'SAZ': 7690, 'UOC': 7686, 'YII': 7682, 'ZEU': 7680, 'ZFO': 7674, 'UDF': 7674, 'PUA': 7672, 'XSI': 7667, 'RMV': 7641, 'DDN': 7636, 'TCW': 7630, 'SPD': 7629, 'ZOI': 7627, 'DBC': 7620, 'SKG': 7616, 'AHG': 7616, 'RHP': 7611, 'GNG': 7610, 'XLO': 7605, 'PUF': 7604, 'ZWE': 7595, 'MHZ': 7595, 'GUB': 7595, 'PYP': 7592, 'LUZ': 7585, 'WSJ': 7578, 'CII': 7573, 'PRS': 7556, 'GUC': 7555, 'LIY': 7554, 'DKY': 7549, 'ZPA': 7547, 'SCF': 7535, 'VWI': 7531, 'PNI': 7530, 'EMJ': 7523, 'RFC': 7522, 'UFC': 7511, 'IEY': 7506, 'KYN': 7505, 'PMD': 7504, 'VOM': 7501, 'DCD': 7492, 'NWY': 7479, 'IZH': 7477, 'SGM': 7473, 'JMA': 7469, 'SLL': 7461, 'BIQ': 7461, 'VSO': 7460, 'ISX': 7453, 'UZH': 7452, 'UDP': 7449, 'TVM': 7444, 'YNM': 7442, 'EFN': 7433, 'YNH': 7432, 'DPC': 7427, 'LZH': 7421, 'UKC': 7417, 'KIY': 7397, 'TVR': 7396, 'PHN': 7396, 'AHJ': 7391, 'AEW': 7380, 'IUR': 7373, 'CJU': 7373, 'OKV': 7371, 'VFO': 7368, 'MUF': 7364, 'TZC': 7361, 'TZM': 7358, 'DPT': 7344, 'YAZ': 7343, 'EVC': 7342, 'DMP': 7336, 'TDY': 7335, 'IKW': 7335, 'PVA': 7332, 'ZIC': 7327, 'NMT': 7326, 'SGH': 7321, 'PMJ': 7321, 'WWS': 7309, 'YMD': 7306, 'YNW': 7305, 'KMT': 7304, 'RLR': 7302, 'VEX': 7292, 'EUO': 7292, 'OYG': 7288, 'SNP': 7286, 'IZS': 7281, 'WDW': 7280, 'SLD': 7277, 'PTG': 7272, 'SNC': 7269, 'CMP': 7268, 'WKA': 7255, 'IXN': 7241, 'XEI': 7237, 'VSI': 7232, 'BYQ': 7231, 'YZO': 7228, 'SDC': 7221, 'FZE': 7221, 'XEX': 7220, 'PHK': 7199, 'VYP': 7197, 'HKM': 7197, 'MSQ': 7191, 'SGS': 7188, 'YAE': 7187, 'RFF': 7174, 'ZLA': 7173, 'CPS': 7167, 'XXX': 7163, 'VYH': 7163, 'GSJ': 7158, 'EZP': 7158, 'PCC': 7157, 'PPP': 7154, 'GMT': 7145, 'EIU': 7145, 'NIJ': 7143, 'HUH': 7135, 'TPC': 7134, 'DIY': 7133, 'SYG': 7120, 'PVO': 7119, 'IVS': 7119, 'SZI': 7111, 'MMR': 7106, 'EVT': 7097, 'KUH': 7096, 'UFL': 7091, 'KHM': 7085, 'EKJ': 7072, 'EBF': 7068, 'ACG': 7068, 'QTH': 7065, 'YUC': 7058, 'OMQ': 7058, 'PHH': 7055, 'ABP': 7053, 'TYQ': 7047, 'YRH': 7044, 'FRH': 7043, 'VVY': 7037, 'TCM': 7020, 'MTS': 7013, 'GTY': 7013, 'CWR': 7011, 'EJR': 7009, 'VOA': 7007, 'SWU': 7007, 'FMP': 7002, 'FEK': 6995, 'IYU': 6992, 'EHW': 6986, 'DNC': 6985, 'FUZ': 6974, 'SCW': 6971, 'TND': 6970, 'ZMI': 6966, 'WWC': 6963, 'QIA': 6959, 'ZDA': 6958, 'DDF': 6958, 'EHD': 6956, 'FIZ': 6952, 'MBP': 6945, 'RPW': 6939, 'SCP': 6931, 'DPP': 6930, 'FYU': 6927, 'NCF': 6923, 'BVE': 6922, 'WLC': 6919, 'WDT': 6917, 'IAY': 6903, 'PSV': 6898, 'AIY': 6888, 'UFU': 6882, 'MRJ': 6871, 'OIK': 6867, 'MUZ': 6861, 'HSQ': 6857, 'XET': 6854, 'TCP': 6853, 'IIL': 6853, 'PHF': 6850, 'SPB': 6847, 'SVU': 6845, 'AEK': 6845, 'DRF': 6835, 'FIP': 6828, 'FLP': 6826, 'DUV': 6820, 'OEK': 6818, 'EFY': 6815, 'NMM': 6814, 'SFC': 6810, 'NRD': 6801, 'IPV': 6801, 'EDX': 6800, 'IFJ': 6798, 'UNQ': 6795, 'DDP': 6791, 'NIY': 6787, 'YOO': 6786, 'IIG': 6775, 'XYA': 6773, 'MBD': 6765, 'TMT': 6763, 'ZWO': 6761, 'IPK': 6759, 'DRK': 6759, 'VPO': 6748, 'FFK': 6747, 'MMT': 6733, 'TTJ': 6724, 'BCP': 6715, 'FTK': 6714, 'EIX': 6711, 'XUN': 6710, 'VSW': 6704, 'YDY': 6702, 'NPT': 6701, 'NBB': 6688, 'UYN': 6687, 'SUO': 6687, 'TDP': 6684, 'RCB': 6678, 'JOG': 6678, 'KGL': 6673, 'KUI': 6671, 'ZMO': 6669, 'DMD': 6660, 'XGO': 6659, 'HIY': 6657, 'VMO': 6627, 'RRB': 6626, 'BJU': 6626, 'AZH': 6622, 'RPD': 6621, 'BUA': 6618, 'UZO': 6617, 'JRW': 6606, 'PMB': 6602, 'YPN': 6598, 'NVS': 6595, 'AFB': 6585, 'PPM': 6583, 'DCP': 6578, 'VIJ': 6574, 'AZD': 6571, 'TKH': 6569, 'FZA': 6569, 'DRL': 6567, 'OVR': 6564, 'MIV': 6563, 'JRS': 6563, 'RPF': 6560, 'ZPR': 6555, 'OEO': 6544, 'OUZ': 6540, 'FKR': 6531, 'WAZ': 6530, 'UOH': 6526, 'IKL': 6516, 'EXN': 6516, 'LNC': 6503, 'XAD': 6500, 'TIY': 6500, 'TVB': 6498, 'OIB': 6488, 'FOH': 6488, 'FUD': 6487, 'GTS': 6480, 'RBB': 6463, 'KYU': 6461, 'DJS': 6452, 'LBC': 6448, 'USZ': 6439, 'IEZ': 6430, 'RCD': 6429, 'UEK': 6426, 'RFT': 6426, 'UBN': 6413, 'IIE': 6411, 'OOY': 6409, 'DLD': 6406, 'IGY': 6400, 'VDO': 6382, 'COZ': 6381, 'UXS': 6379, 'PPC': 6378, 'GCY': 6371, 'EWQ': 6366, 'AOD': 6348, 'EVP': 6346, 'KEZ': 6345, 'ZOP': 6344, 'QAT': 6336, 'DDJ': 6332, 'NKV': 6329, 'GXI': 6329, 'AHK': 6327, 'QAI': 6324, 'WUL': 6323, 'YLT': 6313, 'BAX': 6313, 'BIU': 6312, 'HUY': 6305, 'AQT': 6303, 'MAQ': 6300, 'OVP': 6295, 'AEB': 6293, 'OXD': 6289, 'RJR': 6282, 'DMM': 6277, 'FMT': 6265, 'EYQ': 6262, 'ZYN': 6258, 'OVD': 6258, 'ZYT': 6256, 'YJR': 6254, 'TGM': 6254, 'DDD': 6254, 'VIM': 6235, 'YRY': 6230, 'UVO': 6228, 'BDR': 6226, 'BCB': 6224, 'PPW': 6223, 'MOJ': 6221, 'FAO': 6221, 'FCW': 6219, 'BOJ': 6216, 'NNN': 6215, 'OVB': 6204, 'HPM': 6194, 'UGN': 6191, 'TDB': 6190, 'DCN': 6190, 'NNJ': 6184, 'TCD': 6181, 'AFW': 6181, 'EPJ': 6179, 'XXI': 6175, 'FKH': 6171, 'BSG': 6169, 'GNN': 6165, 'VGA': 6157, 'BNP': 6157, 'GUD': 6152, 'RVS': 6151, 'JIK': 6146, 'STZ': 6137, 'SEZ': 6132, 'RZY': 6131, 'JST': 6131, 'YNY': 6130, 'XNO': 6122, 'YRT': 6121, 'JOO': 6112, 'ZOA': 6111, 'AJP': 6110, 'RRD': 6108, 'RPB': 6092, 'HNJ': 6082, 'YIB': 6081, 'DNY': 6077, 'MFT': 6075, 'SFS': 6073, 'AZM': 6073, 'XIV': 6069, 'UAV': 6065, 'NZU': 6064, 'UMK': 6060, 'ZUC': 6058, 'UDN': 6058, 'ZLO': 6055, 'VSM': 6052, 'EHP': 6052, 'OPV': 6045, 'HNY': 6038, 'ZEY': 6036, 'XHU': 6025, 'GUJ': 6023, 'ODZ': 6022, 'UMY': 6018, 'RRW': 6008, 'XNA': 6007, 'DGH': 6006, 'UYG': 5998, 'NWW': 5984, 'KEQ': 5982, 'PPG': 5976, 'SLS': 5974, 'TZB': 5973, 'VUS': 5972, 'GTV': 5972, 'TFS': 5964, 'LMV': 5962, 'GUZ': 5959, 'IZM': 5958, 'URZ': 5956, 'ZSH': 5953, 'EFG': 5952, 'JRO': 5951, 'RGG': 5930, 'XSY': 5929, 'KYG': 5922, 'IOK': 5921, 'UZB': 5913, 'RWW': 5913, 'DGW': 5912, 'OAO': 5911, 'JAX': 5906, 'TZL': 5901, 'ZVO': 5900, 'XAP': 5897, 'OVM': 5896, 'GNY': 5894, 'SDN': 5887, 'POH': 5886, 'AZL': 5882, 'UBV': 5881, 'FOY': 5876, 'ZOE': 5874, 'MRN': 5873, 'OMZ': 5867, 'PTN': 5850, 'HRH': 5850, 'PAJ': 5849, 'KHT': 5844, 'RRT': 5840, 'DCM': 5839, 'XBI': 5838, 'UOO': 5834, 'LOX': 5834, 'PMN': 5824, 'FII': 5814, 'EPK': 5806, 'AIU': 5803, 'HKU': 5797, 'ZNE': 5793, 'PIW': 5785, 'AYZ': 5784, 'VYE': 5783, 'TVG': 5782, 'IVU': 5780, 'CMS': 5775, 'OIO': 5771, 'MNW': 5765, 'WLG': 5764, 'QAS': 5761, 'BIV': 5758, 'KMW': 5755, 'JAU': 5750, 'SXA': 5749, 'BOZ': 5722, 'PMR': 5711, 'IDZ': 5706, 'MNC': 5704, 'AAY': 5704, 'NLL': 5693, 'CIW': 5691, 'FFV': 5677, 'YIO': 5676, 'MRY': 5676, 'HMP': 5674, 'BTB': 5661, 'KUO': 5653, 'DTC': 5647, 'GAQ': 5644, 'UHL': 5642, 'ESX': 5640, 'SBP': 5636, 'CMC': 5636, 'EVD': 5629, 'DUH': 5628, 'CZY': 5622, 'SMG': 5618, 'HRM': 5614, 'ODQ': 5613, 'GZO': 5611, 'VBE': 5610, 'OCM': 5608, 'GGW': 5603, 'EVM': 5603, 'ZAO': 5601, 'OUQ': 5600, 'XGR': 5594, 'PCT': 5594, 'ZKI': 5592, 'BMC': 5588, 'YDH': 5585, 'RLG': 5583, 'NHT': 5581, 'ZOD': 5571, 'TVU': 5571, 'LOZ': 5568, 'EQI': 5568, 'MPN': 5558, 'JWA': 5557, 'IXU': 5553, 'GII': 5553, 'UKB': 5548, 'MML': 5548, 'IFK': 5548, 'PRC': 5544, 'KRS': 5544, 'VSU': 5542, 'TRP': 5539, 'WWT': 5532, 'ZQU': 5530, 'UXB': 5518, 'CYU': 5516, 'LJI': 5512, 'FLH': 5511, 'DHS': 5511, 'AYQ': 5511, 'HNV': 5510, 'OZH': 5504, 'JEM': 5501, 'PAZ': 5500, 'XML': 5496, 'LNW': 5496, 'XXO': 5495, 'BGA': 5480, 'BMS': 5479, 'BGO': 5479, 'UKK': 5476, 'SBB': 5470, 'EKV': 5468, 'VNA': 5467, 'PKA': 5465, 'BGE': 5454, 'TLT': 5452, 'JUK': 5452, 'GHZ': 5447, 'WWM': 5445, 'OCD': 5445, 'RZH': 5443, 'JOV': 5442, 'EOJ': 5442, 'DTT': 5441, 'SNF': 5438, 'XOD': 5432, 'WGL': 5430, 'NVU': 5428, 'ZSE': 5426, 'TVF': 5426, 'SGY': 5421, 'VLE': 5420, 'GMP': 5418, 'VAZ': 5409, 'AVN': 5409, 'AJS': 5408, 'QHO': 5407, 'DKL': 5404, 'HCY': 5393, 'UNZ': 5392, 'TNT': 5392, 'EUH': 5389, 'ZDI': 5385, 'PUJ': 5373, 'BJA': 5372, 'EZL': 5369, 'SQM': 5356, 'GGH': 5356, 'DLS': 5351, 'TBS': 5349, 'PYG': 5345, 'OTZ': 5342, 'FCB': 5342, 'LTJ': 5338, 'PAQ': 5336, 'WAO': 5334, 'XBY': 5331, 'WUR': 5328, 'TPT': 5328, 'SWW': 5324, 'YDC': 5318, 'OKJ': 5317, 'RBM': 5315, 'HHY': 5307, 'VLO': 5303, 'TVD': 5300, 'AJR': 5297, 'TMM': 5293, 'PSJ': 5289, 'ATX': 5287, 'RRR': 5286, 'DCW': 5282, 'SMN': 5281, 'CGL': 5279, 'FZI': 5278, 'WDY': 5277, 'BSY': 5277, 'ZSI': 5276, 'RLN': 5275, 'RBP': 5274, 'ZKO': 5273, 'IIV': 5269, 'DNB': 5268, 'RCP': 5265, 'TCF': 5264, 'VVI': 5261, 'LUH': 5249, 'LGH': 5249, 'GKU': 5244, 'FCT': 5244, 'XRU': 5243, 'ZOT': 5241, 'DZH': 5236, 'IZT': 5234, 'BCD': 5230, 'TLS': 5229, 'UYP': 5226, 'ECG': 5226, 'HUO': 5217, 'TSX': 5216, 'ZZS': 5214, 'IVT': 5208, 'WOQ': 5200, 'ZOU': 5193, 'PAX': 5193, 'BUH': 5193, 'HLT': 5192, 'EVF': 5191, 'DLL': 5186, 'DNS': 5181, 'GWY': 5174, 'KHR': 5168, 'AEH': 5160, 'TDT': 5159, 'TVL': 5158, 'UWR': 5150, 'KKU': 5147, 'POX': 5143, 'TPP': 5141, 'RBW': 5139, 'UIB': 5134, 'EZV': 5134, 'DBS': 5132, 'TZR': 5130, 'AZS': 5129, 'MOX': 5128, 'TBC': 5126, 'YKM': 5122, 'UKL': 5117, 'CYY': 5116, 'DCF': 5115, 'PNC': 5110, 'CCP': 5107, 'HHH': 5103, 'HRT': 5101, 'BUQ': 5101, 'SPF': 5098, 'JIW': 5097, 'NLC': 5093, 'NHD': 5082, 'RUO': 5080, 'YTS': 5078, 'QMI': 5077, 'YDD': 5075, 'PKN': 5072, 'CCW': 5071, 'DGS': 5069, 'BPI': 5063, 'LUW': 5062, 'TNC': 5061, 'SPW': 5056, 'IZW': 5053, 'BCF': 5046, 'PCM': 5042, 'UYD': 5038, 'PKW': 5034, 'CSV': 5031, 'NKK': 5028, 'APK': 5027, 'ZOW': 5021, 'KUG': 5020, 'UUP': 5018, 'UHU': 5018, 'LMN': 5013, 'SIJ': 5008, 'KIJ': 5008, 'SQL': 5006, 'MBF': 5006, 'TDC': 5004, 'UXW': 5001, 'CPC': 5001, 'VSB': 4998, 'UAE': 4996, 'WLB': 4986, 'YIK': 4985, 'HKH': 4980, 'GMD': 4975, 'XEV': 4971, 'SRT': 4965, 'NLT': 4965, 'ZZB': 4964, 'OVH': 4964, 'YUB': 4963, 'YLD': 4961, 'HPK': 4961, 'DBH': 4957, 'NFS': 4956, 'HDT': 4955, 'XQU': 4947, 'EHB': 4945, 'SDM': 4938, 'TNY': 4935, 'ACZ': 4925, 'WMC': 4924, 'FDY': 4923, 'EPV': 4921, 'CDT': 4919, 'ZNI': 4918, 'RCW': 4918, 'TJR': 4915, 'YPP': 4913, 'IBH': 4913, 'FGD': 4909, 'BUP': 4907, 'MDC': 4906, 'DRN': 4905, 'VMI': 4903, 'JSA': 4903, 'TLB': 4901, 'TVH': 4900, 'SCN': 4900, 'DPG': 4896, 'YKH': 4895, 'MTY': 4893, 'SRC': 4892, 'UKP': 4891, 'FYC': 4891, 'LND': 4890, 'AWV': 4890, 'RYZ': 4888, 'NMB': 4886, 'ABK': 4885, 'QAR': 4880, 'OVN': 4878, 'YUE': 4876, 'JID': 4873, 'TZU': 4870, 'JOT': 4870, 'ZYB': 4866, 'TFT': 4864, 'AWJ': 4861, 'NXA': 4858, 'ZEV': 4856, 'DMT': 4855, 'BKI': 4855, 'HDD': 4852, 'GZA': 4852, 'UZM': 4849, 'TNB': 4847, 'BNS': 4844, 'DLT': 4843, 'YGH': 4840, 'MNF': 4837, 'PJE': 4835, 'AOZ': 4833, 'MCT': 4831, 'KOY': 4823, 'PNS': 4822, 'ZYI': 4811, 'EVH': 4808, 'ZID': 4807, 'YRG': 4806, 'JII': 4803, 'FYB': 4802, 'FLW': 4801, 'RMJ': 4798, 'RSZ': 4797, 'NBH': 4795, 'NUW': 4791, 'YDM': 4789, 'WAJ': 4787, 'BSK': 4787, 'XTN': 4786, 'MND': 4784, 'JRI': 4782, 'VHS': 4776, 'KSQ': 4767, 'SDV': 4764, 'DFS': 4761, 'ZNA': 4757, 'YLC': 4757, 'WLU': 4757, 'BHP': 4752, 'ZZF': 4750, 'OCW': 4749, 'TRM': 4745, 'DFC': 4745, 'FYP': 4739, 'HSV': 4734, 'CPM': 4721, 'FCP': 4718, 'NLS': 4717, 'GUG': 4717, 'ZUS': 4713, 'CRS': 4709, 'IVR': 4708, 'EVG': 4708, 'IBD': 4707, 'OBK': 4703, 'SPG': 4701, 'VSF': 4688, 'NVY': 4688, 'RFW': 4684, 'YNF': 4682, 'ZYO': 4680, 'YYI': 4679, 'UFM': 4679, 'NML': 4678, 'SZT': 4677, 'ZRI': 4671, 'YDL': 4671, 'JOP': 4666, 'PTV': 4664, 'RMK': 4662, 'ZZW': 4659, 'MMW': 4656, 'JTH': 4654, 'HKR': 4652, 'FSG': 4641, 'SMV': 4639, 'SDH': 4638, 'OVU': 4632, 'EQA': 4624, 'DXI': 4624, 'XRI': 4618, 'NZS': 4617, 'WTY': 4615, 'XFU': 4610, 'FLR': 4610, 'GRS': 4609, 'PGS': 4605, 'JOW': 4604, 'FIK': 4604, 'DDG': 4604, 'LCC': 4597, 'ZOG': 4595, 'AFN': 4595, 'NLV': 4594, 'PPF': 4593, 'EBJ': 4593, 'BNT': 4591, 'RFB': 4590, 'VTE': 4589, 'HRB': 4588, 'MDS': 4586, 'ASX': 4585, 'FZO': 4578, 'ZZT': 4575, 'YMT': 4575, 'SRP': 4571, 'KUZ': 4571, 'MKU': 4568, 'IPJ': 4566, 'DBB': 4566, 'KNR': 4563, 'ZYW': 4556, 'ZFE': 4552, 'MBM': 4544, 'GGP': 4544, 'NSZ': 4542, 'AMZ': 4541, 'DHD': 4538, 'NHC': 4536, 'MUJ': 4536, 'UIO': 4534, 'XYO': 4530, 'HUW': 4528, 'ZSP': 4523, 'OXG': 4522, 'OHD': 4518, 'GIK': 4516, 'ZIK': 4515, 'KMR': 4514, 'QWE': 4510, 'PNU': 4507, 'PCB': 4506, 'NCZ': 4500, 'VIW': 4499, 'DZU': 4497, 'IZB': 4495, 'CCD': 4491, 'AOY': 4485, 'NFT': 4483, 'HDS': 4482, 'ZRO': 4481, 'HZO': 4480, 'SBH': 4475, 'ZAV': 4472, 'SDP': 4472, 'PML': 4468, 'GGM': 4468, 'UYR': 4467, 'BCM': 4463, 'HWY': 4462, 'GOZ': 4462, 'VWO': 4458, 'DJR': 4453, 'OCB': 4450, 'AZR': 4450, 'EIY': 4447, 'ZMU': 4446, 'YMF': 4445, 'TCN': 4444, 'UKM': 4434, 'HLC': 4429, 'DHP': 4428, 'OIX': 4423, 'WWB': 4422, 'MMD': 4419, 'EOZ': 4418, 'UIW': 4415, 'TGH': 4415, 'NLD': 4415, 'STX': 4414, 'JJA': 4414, 'YYU': 4413, 'TZF': 4411, 'SXP': 4410, 'HMT': 4408, 'DYY': 4405, 'XAF': 4403, 'MZA': 4402, 'QCO': 4399, 'SLR': 4397, 'BBW': 4395, 'VDC': 4393, 'UVS': 4392, 'OZU': 4392, 'VNI': 4391, 'YUD': 4390, 'LPK': 4390, 'VGE': 4386, 'TSZ': 4386, 'WYC': 4384, 'EZG': 4384, 'HRD': 4379, 'AQB': 4379, 'DUW': 4377, 'YUU': 4376, 'DPW': 4375, 'GMB': 4372, 'ENX': 4372, 'RRC': 4371, 'FCD': 4369, 'IOJ': 4368, 'SDB': 4359, 'DVS': 4349, 'UHR': 4336, 'TRB': 4335, 'IBC': 4335, 'IUT': 4334, 'OVY': 4332, 'MNB': 4324, 'AFM': 4321, 'MYQ': 4318, 'JIE': 4301, 'DMB': 4300, 'TMB': 4295, 'ZME': 4289, 'FMM': 4288, 'OHC': 4284, 'LZI': 4280, 'QHA': 4278, 'OVL': 4276, 'UKY': 4273, 'NFM': 4273, 'CRT': 4273, 'AVC': 4273, 'WLX': 4272, 'IUC': 4269, 'JAE': 4267, 'SNS': 4265, 'AQC': 4263, 'VBU': 4262, 'TDM': 4261, 'OHB': 4259, 'XDR': 4257, 'GBT': 4253, 'SYK': 4250, 'KUY': 4247, 'DFT': 4244, 'SDT': 4243, 'EZN': 4236, 'CKQ': 4233, 'IEQ': 4209, 'UXC': 4208, 'JIV': 4208, 'JEH': 4205, 'XYS': 4204, 'IVP': 4201, 'HYJ': 4201, 'EXV': 4201, 'VSD': 4199, 'IGV': 4199, 'KML': 4198, 'FTJ': 4198, 'AKV': 4197, 'JPA': 4194, 'GPM': 4190, 'BIJ': 4185, 'THX': 4184, 'TDH': 4177, 'GZE': 4174, 'PYN': 4173, 'CFS': 4173, 'YNR': 4169, 'OVG': 4162, 'HLB': 4159, 'FYD': 4158, 'ZIZ': 4154, 'YUI': 4153, 'ZYG': 4152, 'VTA': 4152, 'VNO': 4146, 'MCQ': 4146, 'IRZ': 4141, 'CYV': 4138, 'VSN': 4137, 'DUX': 4129, 'TUW': 4127, 'WWP': 4126, 'TRD': 4125, 'ULZ': 4116, 'VFR': 4115, 'ZIW': 4113, 'YVS': 4113, 'VAY': 4104, 'ZNO': 4101, 'OVF': 4100, 'LFK': 4099, 'GGT': 4099, 'IXV': 4097, 'TNF': 4095, 'TXI': 4092, 'IUD': 4091, 'QUB': 4090, 'TLC': 4086, 'NZL': 4085, 'LGY': 4085, 'VGU': 4082, 'OAE': 4080, 'WCW': 4079, 'NFK': 4079, 'IFV': 4078, 'MKH': 4076, 'UHN': 4072, 'TWY': 4071, 'PMH': 4068, 'SRW': 4062, 'MJI': 4062, 'OEJ': 4060, 'CTQ': 4056, 'RRM': 4052, 'RCF': 4052, 'SLC': 4050, 'UMJ': 4047, 'BMU': 4047, 'YGM': 4046, 'MLL': 4045, 'HYK': 4043, 'ZZC': 4042, 'BJP': 4038, 'IGJ': 4036, 'OZN': 4029, 'UII': 4024, 'YUW': 4022, 'PZI': 4022, 'XIF': 4020, 'LPN': 4020, 'WDC': 4013, 'RFM': 4013, 'BTU': 4009, 'JRE': 4006, 'NRC': 4005, 'HYV': 4005, 'GJR': 3999, 'DLB': 3996, 'BKE': 3993, 'ZSO': 3989, 'VSR': 3987, 'NPD': 3983, 'HZE': 3982, 'HOQ': 3980, 'YDT': 3979, 'FLF': 3977, 'XTV': 3976, 'VIU': 3972, 'SVP': 3972, 'YVU': 3967, 'FCN': 3967, 'KTY': 3965, 'HDF': 3965, 'AJM': 3964, 'XEA': 3961, 'LBF': 3959, 'IDQ': 3958, 'CCF': 3958, 'ZFA': 3956, 'OSZ': 3956, 'JCA': 3956, 'IKB': 3956, 'SLB': 3955, 'ZCH': 3954, 'JIC': 3953, 'CYJ': 3953, 'SYV': 3952, 'VWE': 3951, 'FYM': 3943, 'SIQ': 3941, 'XSL': 3940, 'DIQ': 3940, 'PUK': 3939, 'HRL': 3938, 'VAV': 3936, 'TLD': 3936, 'OHH': 3936, 'MMP': 3936, 'IUP': 3935, 'IPZ': 3933, 'GYZ': 3931, 'DNF': 3930, 'OXX': 3928, 'LNG': 3928, 'ETQ': 3928, 'VHE': 3923, 'JRT': 3922, 'BFL': 3922, 'DTB': 3921, 'AAO': 3920, 'ECV': 3919, 'RUJ': 3918, 'TKY': 3917, 'SNL': 3917, 'KUF': 3913, 'ZFI': 3912, 'MCW': 3912, 'CDM': 3909, 'VUN': 3907, 'HLD': 3903, 'IBW': 3900, 'SOZ': 3899, 'UXD': 3898, 'QYO': 3889, 'TMW': 3886, 'USX': 3885, 'IAQ': 3884, 'HPC': 3884, 'ZZM': 3883, 'CVS': 3881, 'UXF': 3879, 'AAE': 3877, 'ELQ': 3874, 'RWY': 3871, 'RUY': 3870, 'RCN': 3868, 'PDT': 3868, 'OYK': 3868, 'BPM': 3865, 'ZUB': 3864, 'TXA': 3864, 'PPD': 3863, 'NWU': 3861, 'AEE': 3860, 'ZYC': 3859, 'PIQ': 3849, 'TBP': 3848, 'VTR': 3846, 'ZFR': 3843, 'HDY': 3843, 'GCS': 3843, 'AOG': 3843, 'JPU': 3837, 'HDM': 3833, 'XVE': 3832, 'VSL': 3831, 'PCW': 3830, 'RBF': 3827, 'YNP': 3824, 'AHV': 3820, 'LUJ': 3812, 'UKF': 3809, 'HLW': 3809, 'YDG': 3807, 'VDP': 3806, 'YKS': 3804, 'LRH': 3801, 'UCF': 3799, 'VIH': 3798, 'LNB': 3791, 'KOJ': 3791, 'HLP': 3790, 'XOU': 3788, 'FLL': 3787, 'UIK': 3786, 'PCP': 3783, 'NHR': 3782, 'LTK': 3780, 'KUE': 3779, 'VBR': 3776, 'MHY': 3774, 'TZD': 3771, 'TUH': 3770, 'AJJ': 3769, 'PUI': 3766, 'RPK': 3764, 'BKH': 3763, 'LLZ': 3762, 'YKL': 3755, 'BTP': 3754, 'YXI': 3753, 'RHT': 3753, 'WWN': 3749, 'CCB': 3743, 'YCK': 3741, 'CRC': 3740, 'MIJ': 3739, 'RLJ': 3738, 'DVU': 3735, 'OVJ': 3728, 'PLS': 3724, 'NNK': 3723, 'LFV': 3723, 'RBN': 3722, 'ZOV': 3721, 'NBS': 3719, 'WAE': 3718, 'MBN': 3718, 'BFE': 3714, 'FCF': 3713, 'JCO': 3709, 'HOX': 3706, 'RDZ': 3704, 'PPB': 3702, 'VYN': 3691, 'DLC': 3690, 'RXA': 3689, 'NXM': 3687, 'CSQ': 3686, 'XVA': 3684, 'TNG': 3683, 'UOK': 3682, 'MMG': 3680, 'JNA': 3680, 'EXK': 3680, 'EZY': 3677, 'LNT': 3676, 'EJS': 3676, 'ZDO': 3672, 'TKL': 3667, 'LFJ': 3667, 'ZOB': 3665, 'LGB': 3664, 'RRP': 3660, 'EVB': 3660, 'KGB': 3657, 'HPT': 3654, 'DBP': 3653, 'FLB': 3650, 'XGI': 3648, 'HZI': 3647, 'EVJ': 3647, 'COJ': 3644, 'WRT': 3643, 'GMM': 3643, 'FCM': 3643, 'YRR': 3641, 'TMH': 3638, 'EHC': 3635, 'WSX': 3624, 'NUU': 3622, 'XKI': 3609, 'DFF': 3607, 'FOZ': 3606, 'MKR': 3605, 'LVS': 3603, 'UXH': 3602, 'IVC': 3600, 'AFD': 3598, 'POZ': 3593, 'MMB': 3592, 'RZU': 3591, 'CEZ': 3586, 'CJE': 3585, 'IHS': 3582, 'GKR': 3581, 'AJG': 3580, 'XFL': 3576, 'OHP': 3574, 'ZKY': 3573, 'HLH': 3572, 'SBT': 3571, 'NUH': 3571, 'TUX': 3569, 'SBM': 3569, 'PHG': 3568, 'FMB': 3568, 'NTX': 3566, 'CUY': 3564, 'FUA': 3562, 'NNV': 3560, 'DVR': 3560, 'RBD': 3557, 'CIK': 3557, 'ZTR': 3556, 'XYL': 3555, 'HLG': 3553, 'CDW': 3551, 'LCT': 3548, 'OEE': 3546, 'WEQ': 3541, 'TFC': 3538, 'WBC': 3536, 'RVL': 3535, 'CTX': 3533, 'LNH': 3532, 'JGE': 3532, 'SNH': 3531, 'AMQ': 3531, 'MMF': 3530, 'HPP': 3529, 'JDA': 3526, 'LBT': 3525, 'UKG': 3522, 'BBB': 3519, 'YOY': 3518, 'CMT': 3517, 'GMW': 3515, 'IZC': 3511, 'DXA': 3510, 'VTI': 3508, 'IVW': 3508, 'HPB': 3508, 'PIH': 3507, 'SHQ': 3503, 'EFK': 3503, 'WLF': 3500, 'TNS': 3499, 'YSZ': 3497, 'VBA': 3497, 'PRT': 3497, 'AJD': 3497, 'QIF': 3494, 'OOQ': 3491, 'WYS': 3490, 'YPC': 3489, 'BRC': 3486, 'IBT': 3484, 'ZIB': 3482, 'HDC': 3482, 'RPN': 3480, 'BTM': 3480, 'NQI': 3477, 'ZII': 3475, 'EXQ': 3475, 'CCM': 3473, 'GCC': 3472, 'ZYD': 3471, 'VCR': 3468, 'EJM': 3463, 'DTM': 3462, 'PMG': 3455, 'JHO': 3448, 'YPD': 3442, 'FYR': 3441, 'CSJ': 3441, 'FGM': 3438, 'AVP': 3437, 'WLL': 3436, 'WYL': 3435, 'DBM': 3435, 'WLR': 3427, 'TBH': 3424, 'RVU': 3424, 'BTY': 3422, 'XSM': 3421, 'XMU': 3421, 'NZW': 3421, 'BBT': 3420, 'CHZ': 3417, 'AFH': 3417, 'PEQ': 3416, 'GLB': 3416, 'FMW': 3416, 'JAO': 3414, 'DHT': 3414, 'HTQ': 3412, 'SNG': 3404, 'NXB': 3404, 'ABJ': 3404, 'NRT': 3403, 'RHS': 3402, 'IGK': 3401, 'PKR': 3399, 'RQA': 3397, 'YEK': 3394, 'NHB': 3394, 'MHS': 3391, 'VBO': 3389, 'VJO': 3388, 'JDE': 3388, 'NPB': 3379, 'XUP': 3378, 'OOJ': 3372, 'DPY': 3372, 'QAL': 3369, 'BJR': 3369, 'DTJ': 3367, 'QDO': 3365, 'HLM': 3359, 'SLP': 3356, 'ZAU': 3355, 'ZYK': 3354, 'NPY': 3354, 'EQB': 3354, 'QWI': 3353, 'HDW': 3352, 'AQH': 3352, 'PTJ': 3348, 'UAU': 3347, 'HRC': 3347, 'DNG': 3345, 'APJ': 3345, 'OCP': 3341, 'PSQ': 3340, 'KMD': 3338, 'SWS': 3336, 'KTV': 3336, 'GGC': 3335, 'IKP': 3329, 'SDF': 3325, 'JRH': 3323, 'SUY': 3321, 'UYY': 3316, 'OYJ': 3314, 'PDS': 3313, 'RVY': 3312, 'MMH': 3312, 'NFB': 3311, 'WDB': 3310, 'SWC': 3308, 'QIP': 3308, 'VKA': 3307, 'MUB': 3306, 'ZBR': 3299, 'FHR': 3299, 'ZTA': 3298, 'SDL': 3296, 'WUT': 3295, 'RWU': 3295, 'GRH': 3294, 'QTO': 3292, 'QBA': 3292, 'HLL': 3292, 'BPH': 3291, 'IKC': 3290, 'GKH': 3289, 'XOS': 3287, 'YUH': 3286, 'TNW': 3284, 'WWD': 3283, 'IUK': 3283, 'RGV': 3282, 'WWG': 3276, 'SXV': 3275, 'DWW': 3274, 'RNQ': 3272, 'IJK': 3272, 'CAZ': 3271, 'OAZ': 3270, 'OCF': 3267, 'EJP': 3267, 'SXS': 3266, 'FBH': 3266, 'AIX': 3265, 'UKD': 3264, 'FBC': 3264, 'VGO': 3263, 'TRN': 3262, 'ZGR': 3261, 'LOJ': 3261, 'OIJ': 3259, 'WNQ': 3258, 'WLP': 3258, 'PDP': 3257, 'ZYP': 3255, 'LWY': 3255, 'SRM': 3254, 'CYK': 3253, 'XSW': 3249, 'KHZ': 3249, 'GIJ': 3239, 'NLP': 3236, 'IQA': 3236, 'WRS': 3235, 'MHM': 3235, 'ZAY': 3234, 'YCB': 3232, 'EVN': 3232, 'AZP': 3232, 'LNY': 3231, 'JEB': 3231, 'VOB': 3227, 'OYY': 3226, 'SGP': 3223, 'PGL': 3223, 'HTZ': 3223, 'KYK': 3219, 'HSJ': 3219, 'IYI': 3217, 'LKG': 3214, 'HMD': 3214, 'FXI': 3214, 'PUY': 3213, 'DJP': 3212, 'HKL': 3211, 'AUZ': 3211, 'VYG': 3205, 'CIH': 3204, 'KZA': 3202, 'GUK': 3200, 'GWW': 3196, 'MWS': 3195, 'OCN': 3194, 'TIX': 3191, 'AQO': 3191, 'IGQ': 3187, 'AVT': 3183, 'SXM': 3182, 'MNH': 3182, 'FRD': 3182, 'ACV': 3181, 'AVG': 3176, 'ZOH': 3174, 'WSQ': 3171, 'VPE': 3170, 'ZGA': 3166, 'VHO': 3166, 'YNX': 3165, 'CRD': 3163, 'VFI': 3162, 'HUJ': 3160, 'EBV': 3154, 'IIK': 3153, 'ZVI': 3145, 'XYC': 3144, 'UOG': 3144, 'AZW': 3144, 'DBT': 3142, 'HGH': 3139, 'JOF': 3138, 'XGE': 3134, 'YDP': 3129, 'YMW': 3128, 'ZYH': 3127, 'UCD': 3127, 'SZK': 3126, 'NRW': 3124, 'FLG': 3124, 'CML': 3123, 'TMF': 3122, 'RPY': 3122, 'TBB': 3121, 'FPM': 3121, 'PRP': 3119, 'ABG': 3114, 'IJS': 3113, 'DRV': 3110, 'XYT': 3109, 'SCG': 3109, 'RRF': 3109, 'SZU': 3108, 'CMD': 3108, 'EJC': 3102, 'IUB': 3100, 'JOM': 3098, 'VYU': 3087, 'LBW': 3087, 'DPD': 3086, 'RFP': 3085, 'DUQ': 3085, 'SKQ': 3082, 'TWC': 3079, 'SFM': 3079, 'SDJ': 3079, 'ALX': 3075, 'UXL': 3074, 'NQA': 3074, 'ZPI': 3071, 'TUV': 3071, 'GNV': 3071, 'VSG': 3070, 'JSI': 3067, 'VOP': 3066, 'DPF': 3065, 'GRD': 3062, 'YTT': 3059, 'GBS': 3059, 'ZIF': 3056, 'SKJ': 3052, 'SDD': 3052, 'EUZ': 3052, 'RUU': 3051, 'DYQ': 3050, 'KKR': 3046, 'IKY': 3045, 'FBS': 3043, 'GTT': 3041, 'TRC': 3040, 'HCC': 3039, 'OXU': 3038, 'OPQ': 3038, 'NHW': 3038, 'LNF': 3034, 'PIB': 3031, 'CZO': 3030, 'VME': 3029, 'RTQ': 3029, 'MPJ': 3028, 'AVK': 3028, 'NRP': 3026, 'WLH': 3025, 'TZV': 3025, 'SIY': 3024, 'EVV': 3024, 'SUU': 3021, 'DLP': 3019, 'JAJ': 3018, 'YZS': 3017, 'BRS': 3017, 'YUZ': 3015, 'SBD': 3015, 'WDH': 3013, 'EOY': 3006, 'TVV': 3003, 'AZN': 3003, 'ZGO': 2999, 'BPU': 2997, 'EBG': 2996, 'OXJ': 2991, 'XBL': 2990, 'GZI': 2985, 'TDN': 2983, 'IUA': 2983, 'ZKA': 2982, 'LHP': 2982, 'GYV': 2979, 'GPP': 2979, 'BVA': 2979, 'AXN': 2978, 'GGB': 2976, 'GBP': 2976, 'GBH': 2975, 'ZAZ': 2974, 'WCC': 2972, 'DTP': 2971, 'RFD': 2968, 'MZE': 2964, 'ZPO': 2960, 'MTC': 2960, 'NBN': 2959, 'CUZ': 2957, 'UXP': 2955, 'IVN': 2955, 'SWY': 2953, 'EHH': 2952, 'ZAE': 2950, 'RCZ': 2950, 'ZYL': 2949, 'TRT': 2948, 'RBJ': 2948, 'PLT': 2948, 'CRM': 2945, 'MRV': 2942, 'FDN': 2939, 'LBH': 2936, 'JTO': 2936, 'DML': 2935, 'NLW': 2934, 'JEK': 2934, 'FRM': 2934, 'NHP': 2933, 'YLM': 2930, 'WKO': 2930, 'GTC': 2928, 'WIJ': 2927, 'WWL': 2924, 'NWS': 2924, 'AZQ': 2924, 'NXS': 2922, 'NPG': 2922, 'GMF': 2922, 'YNL': 2918, 'YKY': 2913, 'BIY': 2912, 'AJK': 2911, 'KYV': 2910, 'VPI': 2908, 'UHS': 2908, 'IJN': 2908, 'EZK': 2908, 'COQ': 2908, 'LNP': 2905, 'FLN': 2904, 'XJU': 2900, 'VDT': 2898, 'FPC': 2898, 'QAD': 2896, 'SGD': 2889, 'LCW': 2888, 'NJS': 2887, 'EXJ': 2887, 'CNB': 2887, 'GQI': 2881, 'AXX': 2880, 'BMP': 2878, 'MDW': 2875, 'GEZ': 2875, 'YLB': 2873, 'WTV': 2873, 'APV': 2873, 'OOX': 2871, 'NFF': 2871, 'UIH': 2870, 'DPB': 2870, 'OWZ': 2869, 'MDB': 2868, 'FNB': 2863, 'XDU': 2862, 'MTP': 2862, 'JFK': 2862, 'BDY': 2857, 'NYX': 2855, 'IYY': 2855, 'LKV': 2853, 'QSO': 2851, 'CLS': 2851, 'PKO': 2848, 'WLM': 2845, 'SRF': 2845, 'NBP': 2845, 'BRN': 2845, 'CGW': 2843, 'SZC': 2841, 'KHW': 2840, 'HJR': 2840, 'PCG': 2839, 'NXT': 2839, 'JRG': 2838, 'DGB': 2838, 'DHM': 2835, 'BKA': 2835, 'JPE': 2834, 'ZYF': 2831, 'ZUZ': 2831, 'NUV': 2829, 'JWH': 2829, 'YOJ': 2828, 'VPL': 2828, 'MWC': 2828, 'GWU': 2828, 'XIW': 2826, 'ZOC': 2821, 'ZSU': 2819, 'DFM': 2819, 'JIU': 2818, 'WOZ': 2817, 'KHY': 2816, 'HCM': 2815, 'OJR': 2812, 'JRR': 2812, 'JBA': 2812, 'FEZ': 2808, 'NCG': 2807, 'IMQ': 2806, 'VDW': 2805, 'ZSS': 2802, 'QSA': 2802, 'ZLY': 2801, 'AXG': 2801, 'MNP': 2798, 'IKF': 2797, 'SQB': 2795, 'YLP': 2791, 'UOE': 2788, 'XUB': 2787, 'TNH': 2786, 'UZS': 2785, 'FKY': 2781, 'ZCL': 2780, 'ETX': 2778, 'TFM': 2774, 'YGY': 2769, 'LBB': 2768, 'JHE': 2766, 'CFC': 2765, 'FYL': 2764, 'DTF': 2764, 'AOO': 2763, 'ZEJ': 2760, 'MCV': 2758, 'EJT': 2757, 'CDD': 2757, 'SGW': 2752, 'TPG': 2749, 'HHS': 2744, 'AAJ': 2744, 'NVL': 2742, 'HMB': 2741, 'CCY': 2741, 'SSZ': 2740, 'BUJ': 2740, 'MGS': 2738, 'TPB': 2737, 'JWI': 2734, 'DGP': 2734, 'YCS': 2733, 'EBK': 2733, 'IXK': 2731, 'HCS': 2731, 'TPD': 2729, 'NZB': 2728, 'IZR': 2723, 'DMV': 2722, 'KHL': 2721, 'NLB': 2720, 'VIF': 2718, 'UUK': 2717, 'VOE': 2716, 'BNF': 2713, 'SKV': 2707, 'ZKE': 2705, 'NRM': 2694, 'HFC': 2694, 'AQF': 2694, 'ZPE': 2692, 'VIX': 2692, 'EJD': 2692, 'TYZ': 2691, 'TDF': 2691, 'RNZ': 2690, 'GRT': 2690, 'VFA': 2689, 'JEU': 2689, 'FIU': 2686, 'RUX': 2684, 'MCY': 2679, 'HRW': 2676, 'ZJO': 2665, 'WMD': 2661, 'AEZ': 2661, 'YDJ': 2660, 'FDH': 2660, 'AJN': 2660, 'BFU': 2659, 'YLW': 2658, 'QIT': 2655, 'MNG': 2653, 'RHM': 2651, 'OZS': 2648, 'CDB': 2648, 'CBN': 2648, 'WDF': 2646, 'AJB': 2642, 'WIB': 2640, 'LVY': 2639, 'UEQ': 2638, 'LCM': 2637, 'LJR': 2636, 'CLC': 2635, 'XSS': 2634, 'HMW': 2634, 'NHM': 2633, 'NUY': 2632, 'VPS': 2631, 'NWC': 2629, 'EFV': 2627, 'AFY': 2625, 'SZH': 2622, 'GPC': 2621, 'MZO': 2620, 'KNY': 2619, 'MNM': 2618, 'LCP': 2613, 'JRB': 2613, 'YML': 2612, 'SNM': 2603, 'BGI': 2603, 'MNL': 2602, 'FWW': 2600, 'CKZ': 2600, 'AUJ': 2597, 'IBF': 2596, 'HUV': 2594, 'JRN': 2593, 'VVE': 2592, 'AAZ': 2590, 'GMG': 2589, 'NWT': 2588, 'EGK': 2585, 'SWT': 2584, 'XIR': 2582, 'KIU': 2582, 'LZB': 2581, 'FDC': 2580, 'CMY': 2580, 'UDV': 2578, 'AJW': 2576, 'XOV': 2573, 'LCK': 2571, 'ZPL': 2570, 'HWB': 2570, 'RXS': 2568, 'NPF': 2568, 'DGN': 2568, 'WMR': 2567, 'VJA': 2567, 'HDH': 2564, 'YNJ': 2563, 'JFO': 2563, 'MUO': 2557, 'QBS': 2556, 'EMQ': 2556, 'MZI': 2555, 'YDF': 2554, 'ZDU': 2552, 'VOV': 2551, 'PCF': 2551, 'MNR': 2549, 'JRC': 2549, 'JKA': 2549, 'FRB': 2549, 'KYJ': 2547, 'CDF': 2547, 'AJC': 2546, 'AVM': 2543, 'GAX': 2542, 'TNM': 2540, 'BNW': 2540, 'JLA': 2538, 'DHC': 2538, 'MLD': 2535, 'NRL': 2534, 'JIF': 2531, 'LNM': 2530, 'QIC': 2526, 'VYY': 2525, 'SWB': 2525, 'NCV': 2525, 'KRZ': 2524, 'GMH': 2524, 'FNY': 2524, 'AVD': 2522, 'SCJ': 2521, 'GTD': 2520, 'BMX': 2517, 'YPY': 2514, 'CBD': 2513, 'MLT': 2512, 'VYV': 2508, 'AXU': 2507, 'ZZP': 2502, 'QIG': 2502, 'POY': 2502, 'QMA': 2499, 'MNY': 2499, 'HLF': 2499, 'YOX': 2495, 'JMO': 2495, 'BSJ': 2495, 'VUT': 2494, 'HCB': 2494, 'SGN': 2493, 'TUY': 2490, 'TGW': 2490, 'MPV': 2490, 'AKJ': 2488, 'FPT': 2487, 'LXX': 2485, 'WVU': 2483, 'MWW': 2481, 'MDY': 2480, 'YBB': 2478, 'XKE': 2477, 'DFB': 2477, 'RZB': 2476, 'ECJ': 2476, 'VVA': 2474, 'RHD': 2474, 'FDS': 2473, 'CPP': 2472, 'AJH': 2472, 'RYX': 2471, 'SWP': 2470, 'OXK': 2466, 'FKL': 2466, 'LBP': 2464, 'MTB': 2456, 'NXP': 2454, 'IZD': 2454, 'AVH': 2453, 'YIJ': 2451, 'UFS': 2448, 'MFS': 2447, 'FML': 2447, 'BNC': 2447, 'LCB': 2444, 'FXA': 2444, 'VGR': 2442, 'FMF': 2442, 'TGY': 2441, 'CNC': 2440, 'NBT': 2437, 'GML': 2437, 'PGT': 2435, 'TDV': 2434, 'NXE': 2430, 'JSH': 2424, 'BBH': 2424, 'RFH': 2423, 'IKD': 2422, 'FMD': 2422, 'YDV': 2417, 'XYM': 2417, 'BNB': 2417, 'OZL': 2416, 'FBP': 2416, 'YCM': 2415, 'IQI': 2411, 'DGT': 2411, 'WYT': 2410, 'NBM': 2408, 'SNW': 2407, 'FRC': 2407, 'DWU': 2407, 'CWS': 2407, 'TZY': 2406, 'DBN': 2403, 'VDB': 2401, 'UUR': 2399, 'MLC': 2399, 'DKS': 2399, 'VFW': 2397, 'TGS': 2396, 'XIU': 2395, 'NJC': 2389, 'MUW': 2389, 'UZC': 2388, 'XYI': 2387, 'SUJ': 2385, 'FWY': 2384, 'SGC': 2383, 'KMB': 2382, 'CUW': 2382, 'YCD': 2381, 'RLK': 2381, 'JSC': 2381, 'JBU': 2380, 'IVF': 2379, 'RCG': 2378, 'LXL': 2378, 'IAX': 2378, 'DNH': 2378, 'JIO': 2377, 'OLQ': 2376, 'BNH': 2374, 'UJE': 2373, 'GGD': 2373, 'ZBI': 2371, 'ZVA': 2370, 'TZN': 2370, 'TWS': 2370, 'JUE': 2370, 'DTN': 2370, 'YNK': 2369, 'NMH': 2367, 'GUF': 2367, 'JPR': 2365, 'WKR': 2364, 'SQF': 2364, 'FLM': 2363, 'NZF': 2362, 'JSE': 2361, 'RRN': 2360, 'KTS': 2360, 'OMX': 2357, 'YLG': 2356, 'YLR': 2355, 'TBM': 2355, 'NFD': 2355, 'TLP': 2353, 'NUZ': 2352, 'IVL': 2352, 'YRM': 2351, 'FYN': 2348, 'CFM': 2347, 'ZEX': 2346, 'JME': 2344, 'AEQ': 2344, 'MVS': 2343, 'GLS': 2338, 'RRL': 2337, 'YOE': 2336, 'RBG': 2336, 'QFO': 2336, 'SXT': 2335, 'JCI': 2335, 'UCB': 2334, 'HUZ': 2333, 'HLR': 2333, 'JSP': 2332, 'VFL': 2331, 'KJI': 2331, 'KIZ': 2331, 'AHZ': 2331, 'KUJ': 2330, 'ZCZ': 2329, 'IVD': 2329, 'FSV': 2329, 'XAI': 2326, 'TWT': 2326, 'JMI': 2325, 'CPT': 2324, 'VOX': 2322, 'HMG': 2320, 'BUX': 2320, 'FDW': 2317, 'DPN': 2317, 'UHF': 2315, 'BCG': 2315, 'ZHN': 2314, 'AFK': 2313, 'ZYE': 2312, 'VTS': 2311, 'YCT': 2307, 'VCL': 2307, 'WYM': 2306, 'YCN': 2305, 'KKH': 2304, 'JDI': 2303, 'SGB': 2302, 'FNM': 2302, 'HDV': 2301, 'BUW': 2301, 'NJH': 2300, 'TPY': 2299, 'HCP': 2298, 'RVP': 2297, 'DSZ': 2297, 'TDD': 2295, 'TPF': 2294, 'OVK': 2294, 'GRB': 2294, 'RVT': 2293, 'LDZ': 2292, 'IIU': 2290, 'RGK': 2289, 'GLD': 2288, 'CFT': 2286, 'LSZ': 2284, 'BND': 2284, 'JRM': 2281, 'QIR': 2280, 'FBB': 2277, 'CDY': 2275, 'SZY': 2273, 'QCA': 2273, 'HIX': 2272, 'OHK': 2271, 'XJO': 2270, 'HAX': 2269, 'CRP': 2269, 'AZB': 2269, 'ZZU': 2267, 'YCC': 2267, 'UBK': 2267, 'TBN': 2267, 'AVW': 2267, 'OIZ': 2266, 'KMP': 2264, 'TWU': 2262, 'TDJ': 2262, 'SVR': 2261, 'WLD': 2260, 'NJT': 2260, 'DVL': 2260, 'XTJ': 2259, 'HBH': 2258, 'SBW': 2257, 'MDT': 2257, 'AJT': 2256, 'EGJ': 2255, 'DQA': 2252, 'MGH': 2251, 'GRN': 2251, 'YLH': 2250, 'DFW': 2248, 'EZJ': 2245, 'VCI': 2244, 'UXM': 2243, 'HPD': 2242, 'GNJ': 2242, 'GBC': 2241, 'PDC': 2240, 'VPC': 2239, 'HKY': 2236, 'FUH': 2236, 'YRC': 2234, 'FNC': 2234, 'AZC': 2233, 'JOJ': 2231, 'UWS': 2227, 'MRZ': 2227, 'BNM': 2226, 'VCS': 2224, 'JTA': 2223, 'BHS': 2223, 'MVC': 2221, 'FZH': 2219, 'JLI': 2217, 'HIQ': 2216, 'ZYR': 2215, 'UAO': 2214, 'NJP': 2213, 'FGW': 2213, 'XXV': 2212, 'UZT': 2210, 'TRK': 2210, 'KPM': 2210, 'NRF': 2207, 'KCY': 2205, 'SZL': 2204, 'JRD': 2203, 'NMF': 2201, 'KJR': 2201, 'BPC': 2199, 'XMM': 2196, 'WDL': 2194, 'RKZ': 2194, 'OHG': 2194, 'ZCR': 2192, 'JKO': 2192, 'MTT': 2191, 'TKS': 2190, 'YFC': 2189, 'PFC': 2189, 'DFD': 2188, 'CRH': 2188, 'WYD': 2187, 'XXA': 2185, 'DJD': 2184, 'VOH': 2183, 'NVH': 2183, 'QVI': 2181, 'ZIH': 2179, 'DJC': 2177, 'YAX': 2176, 'XYF': 2176, 'MTM': 2175, 'WDP': 2173, 'VHI': 2171, 'TGT': 2169, 'PPN': 2169, 'LBJ': 2169, 'FUB': 2165, 'FCZ': 2165, 'BGU': 2159, 'BSV': 2155, 'QUN': 2154, 'HDB': 2154, 'FNF': 2154, 'SYJ': 2153, 'FND': 2152, 'DKW': 2152, 'FYY': 2148, 'CNS': 2148, 'TGD': 2147, 'QFT': 2147, 'DTL': 2147, 'ULQ': 2144, 'SVT': 2144, 'JUX': 2143, 'FYG': 2142, 'DMG': 2142, 'WTS': 2141, 'WUA': 2139, 'VPH': 2138, 'IGZ': 2138, 'DRZ': 2138, 'DMH': 2138, 'DHB': 2138, 'HDP': 2137, 'SBF': 2136, 'LMK': 2134, 'LMJ': 2134, 'JBE': 2134, 'XVO': 2133, 'OYV': 2132, 'IZP': 2131, 'MLP': 2129, 'TBT': 2128, 'YUJ': 2127, 'RGJ': 2127, 'RHR': 2126, 'WPS': 2125, 'DKG': 2120, 'MDH': 2119, 'NZR': 2118, 'YGN': 2116, 'NFY': 2116, 'MHT': 2116, 'CLT': 2116, 'IVB': 2115, 'PFS': 2113, 'BDP': 2113, 'AXV': 2113, 'OYZ': 2111, 'DNM': 2109, 'VUK': 2108, 'FGT': 2107, 'SDK': 2106, 'IZN': 2106, 'NMW': 2105, 'PNP': 2104, 'FNS': 2104, 'NXR': 2102, 'HOZ': 2102, 'HRP': 2098, 'BTD': 2098, 'JCH': 2097, 'XOL': 2096, 'RLV': 2096, 'PHJ': 2095, 'PCD': 2095, 'PNG': 2093, 'UYV': 2091, 'NPW': 2089, 'VRS': 2088, 'XOB': 2087, 'PYV': 2086, 'JEP': 2081, 'IHY': 2079, 'PNT': 2078, 'JLE': 2078, 'BRT': 2078, 'GGF': 2077, 'DUZ': 2074, 'HUX': 2072, 'PTK': 2071, 'RXE': 2070, 'LBK': 2068, 'BLS': 2067, 'IOZ': 2066, 'BYX': 2066, 'LRT': 2065, 'YRB': 2063, 'WCS': 2063, 'QST': 2061, 'ZAJ': 2060, 'VDF': 2059, 'ZDR': 2057, 'VTU': 2057, 'BSQ': 2057, 'WRC': 2056, 'NMN': 2056, 'HBC': 2056, 'BPP': 2055, 'TKG': 2054, 'XGU': 2053, 'UXK': 2053, 'LRD': 2053, 'GRP': 2053, 'DMW': 2051, 'TXV': 2049, 'XJE': 2046, 'PRD': 2045, 'DMF': 2044, 'ZUT': 2043, 'XAU': 2043, 'LYX': 2043, 'NWV': 2042, 'NBJ': 2041, 'OBZ': 2040, 'SVC': 2039, 'PVC': 2038, 'SCV': 2037, 'LBD': 2036, 'DJM': 2033, 'IKG': 2031, 'RZW': 2030, 'VPT': 2029, 'NZC': 2028, 'NSX': 2028, 'EGV': 2028, 'DWT': 2028, 'GUW': 2027, 'UZW': 2026, 'TUZ': 2026, 'YWY': 2025, 'DHW': 2025, 'PYK': 2023, 'JCP': 2023, 'HCD': 2022, 'BQU': 2022, 'PJI': 2021, 'AQD': 2021, 'MFM': 2020, 'BPW': 2020, 'CMW': 2019, 'DHL': 2017, 'TWP': 2016, 'XNU': 2014, 'TNP': 2012, 'SFB': 2012, 'PGC': 2012, 'QIM': 2011, 'SFW': 2010, 'FHS': 2009, 'XYW': 2006, 'QAB': 2006, 'TMN': 2005, 'AAQ': 2005, 'ZSF': 2004, 'UDK': 2000, 'GLT': 2000, 'GTM': 1998, 'IIJ': 1997, 'HFS': 1997, 'UHT': 1996, 'PLL': 1996, 'SRR': 1995, 'TMG': 1994, 'GYJ': 1989, 'ZUI': 1988, 'VCE': 1987, 'QRE': 1985, 'IZF': 1985, 'NZM': 1984, 'FPP': 1984, 'ZZR': 1979, 'VOJ': 1979, 'JIP': 1979, 'BBQ': 1977, 'TRL': 1975, 'NRN': 1975, 'EHF': 1971, 'UUT': 1970, 'RXB': 1970, 'NMV': 1969, 'SQA': 1968, 'QPR': 1966, 'VMW': 1965, 'JHI': 1964, 'XSF': 1963, 'XIP': 1962, 'HBB': 1962, 'MTL': 1961, 'LHS': 1960, 'EJB': 1960, 'CFB': 1960, 'DVC': 1959, 'SWF': 1958, 'SPX': 1958, 'FWS': 1958, 'WUM': 1955, 'OZM': 1952, 'OCQ': 1951, 'DJT': 1949, 'FPY': 1946, 'PYU': 1945, 'NXW': 1945, 'KHN': 1944, 'BMT': 1944, 'ZUO': 1942, 'ZVE': 1941, 'TCG': 1941, 'SMK': 1940, 'DCZ': 1939, 'FRP': 1937, 'SFD': 1935, 'NZT': 1935, 'MXI': 1935, 'FPG': 1935, 'NFP': 1934, 'NRR': 1933, 'LBM': 1933, 'ZUH': 1932, 'SXR': 1932, 'QBE': 1931, 'FUI': 1931, 'GCD': 1928, 'AQM': 1928, 'GPT': 1927, 'YTL': 1925, 'CBM': 1925, 'KCS': 1924, 'YBP': 1923, 'SVY': 1923, 'VJE': 1920, 'YKW': 1918, 'SFP': 1916, 'MDM': 1916, 'SFF': 1915, 'KUU': 1914, 'GTP': 1913, 'DUJ': 1912, 'BTV': 1912, 'WCD': 1909, 'PRF': 1909, 'IVH': 1909, 'HPW': 1909, 'QAW': 1908, 'XOC': 1907, 'NMG': 1907, 'HGM': 1907, 'UIJ': 1906, 'VUR': 1904, 'WDG': 1903, 'PGW': 1899, 'YZH': 1898, 'IZL': 1898, 'ZUA': 1897, 'WDM': 1897, 'UDZ': 1897, 'PRM': 1897, 'ILZ': 1896, 'EVK': 1895, 'VWR': 1894, 'EYZ': 1894, 'SPV': 1891, 'DJB': 1891, 'TRW': 1890, 'BPT': 1889, 'UDJ': 1887, 'QBU': 1887, 'IXJ': 1887, 'HVS': 1887, 'IZK': 1885, 'XEP': 1884, 'SLF': 1883, 'MBG': 1883, 'GBM': 1879, 'FKS': 1879, 'RQI': 1878, 'XIX': 1876, 'JBL': 1876, 'OGJ': 1875, 'HBP': 1874, 'GGN': 1872, 'QOR': 1870, 'YLK': 1868, 'ZSL': 1867, 'HCT': 1866, 'YBM': 1864, 'HUU': 1864, 'ZZH': 1863, 'VND': 1863, 'UHY': 1862, 'LCF': 1862, 'AEJ': 1862, 'FRT': 1860, 'VRU': 1859, 'TWM': 1856, 'WYR': 1855, 'IVV': 1853, 'AOJ': 1853, 'PYJ': 1851, 'ILQ': 1851, 'BDS': 1851, 'UZN': 1850, 'PRB': 1849, 'NCJ': 1848, 'KZO': 1848, 'BNU': 1848, 'KAQ': 1847, 'BUU': 1847, 'SWM': 1843, 'FIQ': 1843, 'PPV': 1842, 'QAM': 1841, 'JDU': 1840, 'OJS': 1839, 'SLM': 1838, 'NWF': 1837, 'IKV': 1837, 'CZI': 1837, 'VMS': 1836, 'GKM': 1836, 'FZU': 1835, 'PGF': 1834, 'FGS': 1834, 'QON': 1832, 'IUW': 1832, 'EJL': 1832, 'NLR': 1831, 'JUJ': 1830, 'JGR': 1830, 'MGT': 1829, 'CCN': 1829, 'ZBY': 1828, 'PRW': 1827, 'CZS': 1826, 'PGP': 1825, 'LRB': 1825, 'CPD': 1825, 'WKM': 1824, 'AOE': 1824, 'ABV': 1824, 'XPS': 1823, 'EPQ': 1823, 'YBS': 1822, 'RZS': 1822, 'JRF': 1822, 'TLH': 1821, 'SVL': 1821, 'FUF': 1821, 'YXA': 1820, 'LRC': 1820, 'CMB': 1820, 'BIX': 1820, 'LXI': 1817, 'LPV': 1817, 'LCZ': 1817, 'LWW': 1816, 'DTK': 1816, 'RSX': 1815, 'LCN': 1813, 'JUC': 1813, 'LNR': 1812, 'QUH': 1811, 'RVR': 1809, 'DBJ': 1809, 'IBP': 1808, 'DLW': 1808, 'WKH': 1807, 'XIG': 1806, 'UOJ': 1805, 'IOY': 1805, 'WRD': 1804, 'FCK': 1804, 'KND': 1803, 'DLR': 1803, 'OIU': 1802, 'JCR': 1802, 'DMK': 1802, 'XUD': 1801, 'XLU': 1801, 'DJH': 1800, 'YPG': 1798, 'IUJ': 1798, 'XPH': 1797, 'EHK': 1797, 'UMQ': 1794, 'SXC': 1794, 'RKQ': 1794, 'BAQ': 1794, 'BFT': 1791, 'XYB': 1790, 'RCV': 1790, 'NJW': 1790, 'AEY': 1790, 'YBH': 1789, 'ZPU': 1788, 'DXM': 1788, 'SKK': 1787, 'KVS': 1785, 'WLV': 1784, 'MLF': 1784, 'XEG': 1783, 'XOM': 1782, 'UZY': 1782, 'OZT': 1782, 'CNT': 1781, 'YLF': 1780, 'LGD': 1780, 'IMZ': 1780, 'TGB': 1779, 'SXB': 1779, 'MDP': 1779, 'DWS': 1779, 'JRP': 1778, 'IUY': 1777, 'GVS': 1773, 'PVS': 1772, 'TXT': 1771, 'TFW': 1771, 'QBT': 1770, 'CJI': 1770, 'YIU': 1767, 'YCZ': 1767, 'ZYZ': 1765, 'TQB': 1764, 'FUW': 1761, 'AUQ': 1760, 'NLH': 1759, 'NHH': 1758, 'EJV': 1758, 'BKN': 1755, 'UXR': 1754, 'KYY': 1754, 'HML': 1753, 'HCN': 1753, 'WGS': 1752, 'UVU': 1752, 'LBN': 1752, 'NVR': 1751, 'PND': 1750, 'DFG': 1747, 'MFC': 1745, 'WUH': 1743, 'RWS': 1741, 'TGN': 1739, 'KKY': 1738, 'WMS': 1737, 'HBS': 1737, 'CWT': 1735, 'PNR': 1733, 'JDO': 1733, 'RFG': 1732, 'DNP': 1731, 'YCP': 1730, 'NXC': 1729, 'MIQ': 1728, 'DLM': 1728, 'AQP': 1728, 'WUC': 1727, 'RRV': 1727, 'GLC': 1727, 'YWW': 1726, 'YFF': 1726, 'DCG': 1725, 'HDL': 1724, 'FVU': 1724, 'FHP': 1724, 'QDI': 1722, 'JBO': 1721, 'GYK': 1721, 'BLT': 1721, 'PRR': 1720, 'LVU': 1720, 'RXU': 1719, 'TUU': 1718, 'JJO': 1718, 'CMM': 1717, 'BKO': 1716, 'DMN': 1714, 'HMF': 1713, 'BNX': 1713, 'GUH': 1712, 'DFP': 1711, 'OZW': 1709, 'NWB': 1709, 'FPN': 1709, 'DQI': 1708, 'GCM': 1707, 'FKW': 1705, 'RVC': 1703, 'UFK': 1702, 'HPF': 1702, 'SJS': 1701, 'DNW': 1700, 'FDM': 1699, 'YWC': 1698, 'GOX': 1697, 'NYZ': 1696, 'LGM': 1695, 'BVO': 1694, 'WFC': 1693, 'MMN': 1692, 'GRC': 1692, 'DLH': 1692, 'MKM': 1690, 'IPQ': 1688, 'OCZ': 1687, 'VBI': 1686, 'VDU': 1685, 'HMH': 1685, 'WKT': 1683, 'PRN': 1683, 'GRM': 1683, 'GGG': 1683, 'YXM': 1682, 'AJL': 1681, 'FDP': 1680, 'EJH': 1680, 'DXE': 1680, 'DTG': 1680, 'TKW': 1679, 'TGP': 1678, 'JEZ': 1678, 'FQA': 1678, 'UIX': 1677, 'VUI': 1676, 'FQI': 1676, 'NRG': 1675, 'JSO': 1675, 'FHM': 1675, 'HPV': 1674, 'DWB': 1674, 'BBF': 1674, 'MNN': 1673, 'BMG': 1673, 'ZSM': 1672, 'JYO': 1671, 'HKS': 1671, 'UOZ': 1669, 'BRD': 1669, 'NHK': 1666, 'GTZ': 1666, 'DBW': 1666, 'LNN': 1665, 'TJP': 1664, 'ZZG': 1663, 'QBJ': 1662, 'PZO': 1661, 'ZSR': 1660, 'OZC': 1659, 'CMR': 1659, 'IOQ': 1656, 'BBM': 1656, 'NXF': 1655, 'PRH': 1654, 'MDN': 1653, 'EIQ': 1652, 'SJP': 1651, 'KBP': 1651, 'JAQ': 1651, 'DBD': 1651, 'CMH': 1650, 'GLL': 1649, 'YEJ': 1648, 'LUY': 1648, 'KPS': 1648, 'XKM': 1647, 'HPJ': 1646, 'JBR': 1645, 'CNR': 1645, 'IHL': 1644, 'ELX': 1644, 'IJR': 1641, 'BNR': 1641, 'DXB': 1638, 'TWB': 1637, 'HRR': 1637, 'DGC': 1637, 'CWW': 1636, 'SXE': 1635, 'TDL': 1634, 'TDG': 1634, 'PCV': 1634, 'BTN': 1634, 'KZI': 1633, 'AOX': 1632, 'XYZ': 1631, 'NFH': 1631, 'VSY': 1630, 'SLW': 1630, 'CCG': 1629, 'XSB': 1628, 'WDD': 1627, 'FWU': 1627, 'AVB': 1627, 'TPN': 1626, 'SMJ': 1624, 'QAF': 1624, 'CZW': 1624, 'RPV': 1623, 'MHW': 1623, 'VDD': 1622, 'ZGI': 1621, 'DCV': 1620, 'ZTU': 1619, 'PGM': 1619, 'LZS': 1616, 'GCP': 1616, 'EJJ': 1615, 'NWM': 1614, 'NBD': 1614, 'UAJ': 1613, 'JPO': 1613, 'CMF': 1612, 'XJA': 1610, 'LNL': 1610, 'CRB': 1610, 'ZTI': 1609, 'SJC': 1608, 'OJP': 1608, 'GCB': 1607, 'CDV': 1607, 'RQB': 1605, 'SLV': 1604, 'VPU': 1602, 'VKO': 1602, 'NLM': 1601, 'EJN': 1601, 'RJP': 1600, 'NXU': 1600, 'MGP': 1600, 'WFP': 1598, 'WDN': 1598, 'PDW': 1598, 'LGS': 1598, 'VKI': 1596, 'GTB': 1596, 'TFD': 1595, 'RJD': 1595, 'CAQ': 1595, 'WCY': 1594, 'CDN': 1594, 'DGK': 1593, 'RHB': 1591, 'FGY': 1590, 'CGH': 1590, 'AVF': 1589, 'JNI': 1588, 'BBD': 1588, 'KHC': 1587, 'FBN': 1587, 'BNG': 1586, 'UHH': 1585, 'NZD': 1585, 'WKC': 1584, 'WAQ': 1584, 'JGA': 1582, 'AQR': 1582, 'ZUG': 1581, 'HQA': 1581, 'YTC': 1579, 'HDN': 1578, 'XSD': 1577, 'XEE': 1577, 'TXE': 1576, 'LPJ': 1576, 'WCB': 1573, 'DJW': 1573, 'YKJ': 1572, 'FWP': 1572, 'SRN': 1571, 'UQI': 1569, 'YMH': 1568, 'PFF': 1568, 'FGC': 1567, 'JSM': 1564, 'MKL': 1563, 'DWP': 1563, 'TMV': 1562, 'YRW': 1561, 'VTW': 1560, 'PVT': 1560, 'JNO': 1560, 'WWK': 1559, 'WTC': 1557, 'EHG': 1557, 'XTQ': 1556, 'MTN': 1554, 'JSS': 1554, 'LTQ': 1551, 'JTW': 1551, 'NLF': 1550, 'MDD': 1549, 'UXN': 1548, 'SLN': 1546, 'PNW': 1544, 'DJJ': 1543, 'HGY': 1542, 'BMD': 1542, 'ZRU': 1541, 'YGW': 1541, 'XAW': 1540, 'NJD': 1540, 'YUV': 1539, 'BLM': 1539, 'YGG': 1538, 'SBJ': 1538, 'CFD': 1538, 'BWR': 1538, 'PUW': 1537, 'BKG': 1537, 'OQI': 1533, 'WWU': 1532, 'VCU': 1530, 'IUF': 1530, 'MTD': 1529, 'DWC': 1528, 'IQB': 1527, 'KLL': 1526, 'QSH': 1525, 'JRU': 1525, 'DBF': 1525, 'PHV': 1524, 'MXA': 1524, 'SFG': 1523, 'JPL': 1522, 'CUH': 1522, 'TJS': 1520, 'OCG': 1520, 'CMG': 1520, 'HGW': 1519, 'FMH': 1519, 'DKC': 1519, 'KRD': 1518, 'KOX': 1518, 'DQB': 1518, 'GOQ': 1517, 'EMX': 1517, 'VHF': 1516, 'IUE': 1514, 'SRG': 1513, 'RRG': 1513, 'FBM': 1511, 'YHR': 1510, 'VPM': 1510, 'LLX': 1510, 'YEZ': 1508, 'IVK': 1508, 'BBG': 1508, 'VCC': 1507, 'KFC': 1507, 'ACJ': 1506, 'TRG': 1505, 'NXO': 1505, 'RHN': 1504, 'YUF': 1502, 'UAZ': 1502, 'KRH': 1502, 'OHF': 1501, 'SRL': 1500, 'SLG': 1500, 'FDD': 1500, 'CTZ': 1500, 'ZIJ': 1499, 'YMG': 1499, 'VDV': 1497, 'NXX': 1497, 'CBB': 1497, 'XUE': 1496, 'VUA': 1496, 'OHJ': 1496, 'AQE': 1496, 'QUT': 1494, 'YFS': 1493, 'IHT': 1492, 'LKJ': 1490, 'IUI': 1490, 'PGH': 1489, 'IVM': 1489, 'SVM': 1488, 'AZK': 1488, 'QUS': 1487, 'WIO': 1486, 'IHR': 1486, 'IUH': 1484, 'TNR': 1483, 'NHN': 1482, 'XEY': 1481, 'KPP': 1481, 'WYI': 1480, 'BPD': 1480, 'VFE': 1477, 'JNE': 1476, 'HDJ': 1476, 'ZOK': 1475, 'RHC': 1475, 'RFY': 1474, 'HRN': 1474, 'GDC': 1474, 'UUU': 1473, 'UQA': 1473, 'JTR': 1473, 'DCJ': 1473, 'TRF': 1472, 'EWX': 1472, 'DNJ': 1471, 'GTJ': 1470, 'WWJ': 1469, 'OJC': 1468, 'NKZ': 1468, 'WWV': 1467, 'UKV': 1467, 'VPW': 1466, 'UCN': 1465, 'VSV': 1462, 'MTF': 1462, 'UGY': 1461, 'SLH': 1461, 'KKK': 1461, 'JMU': 1461, 'WGM': 1460, 'SSX': 1460, 'SVH': 1459, 'MLW': 1459, 'FPD': 1459, 'OGV': 1458, 'NPN': 1457, 'YFT': 1454, 'MDF': 1451, 'GDS': 1451, 'HHT': 1449, 'JSW': 1448, 'FFQ': 1447, 'CPW': 1447, 'JEI': 1446, 'GBB': 1446, 'CKX': 1445, 'GKY': 1444, 'FPF': 1444, 'QOF': 1442, 'FNG': 1442, 'OKQ': 1440, 'QLA': 1439, 'OPZ': 1438, 'NWN': 1438, 'DGD': 1438, 'TBW': 1437, 'WCT': 1436, 'PCY': 1435, 'HNQ': 1435, 'DVP': 1435, 'CUK': 1435, 'CGT': 1435, 'QIW': 1434, 'FMN': 1432, 'NJB': 1431, 'MHC': 1431, 'FBT': 1431, 'BBP': 1431, 'YRF': 1430, 'TLN': 1429, 'XWR': 1428, 'UTX': 1428, 'RVN': 1428, 'CSX': 1427, 'XRY': 1426, 'MGW': 1426, 'JUW': 1426, 'YZU': 1425, 'KLS': 1425, 'OZD': 1423, 'JIY': 1423, 'DVT': 1423, 'VMU': 1420, 'JUH': 1420, 'FMG': 1420, 'ZGU': 1419, 'XYP': 1419, 'DKB': 1419, 'HFT': 1416, 'RJS': 1415, 'PNM': 1415, 'PFW': 1415, 'DXR': 1415, 'YYY': 1414, 'MKS': 1413, 'JPI': 1413, 'FKG': 1413, 'XNI': 1412, 'JSU': 1411, 'CWC': 1411, 'PRZ': 1410, 'PRK': 1410, 'SXX': 1409, 'ZSW': 1408, 'TRR': 1408, 'OJT': 1408, 'CJS': 1407, 'UYJ': 1405, 'KZE': 1405, 'IVG': 1405, 'VAX': 1404, 'FWC': 1404, 'UHW': 1403, 'NBF': 1403, 'LHT': 1403, 'DLG': 1403, 'AQL': 1403, 'UGK': 1402, 'GNK': 1402, 'VDM': 1401, 'QBR': 1401, 'HPG': 1401, 'CGS': 1401, 'NVP': 1400, 'BLC': 1400, 'CND': 1398, 'KWW': 1397, 'ZSD': 1396, 'WPM': 1395, 'RCJ': 1395, 'YPF': 1394, 'UUA': 1393, 'SYY': 1393, 'NVT': 1393, 'LZU': 1392, 'KLM': 1392, 'YHT': 1391, 'RWC': 1390, 'SXO': 1389, 'CRW': 1388, 'WFS': 1387, 'FYV': 1387, 'CRR': 1387, 'XMR': 1386, 'RXT': 1385, 'VPN': 1384, 'QLS': 1383, 'BNL': 1383, 'AMX': 1382, 'ZIV': 1381, 'TBD': 1380, 'RXM': 1380, 'RRJ': 1380, 'ZNY': 1379, 'OVV': 1379, 'WUW': 1378, 'WMT': 1377, 'SJD': 1377, 'UBZ': 1376, 'DLF': 1376, 'SDG': 1375, 'WPC': 1374, 'TCZ': 1373, 'NWP': 1373, 'MHL': 1372, 'DUY': 1372, 'RJC': 1371, 'TXS': 1369, 'GXU': 1369, 'CIJ': 1369, 'BZA': 1369, 'KRT': 1368, 'KRP': 1368, 'YBD': 1367, 'UHM': 1366, 'SRV': 1366, 'QSE': 1365, 'AZG': 1365, 'BMR': 1364, 'YRP': 1363, 'SCZ': 1363, 'HZW': 1363, 'DJF': 1363, 'CLL': 1363, 'VPP': 1362, 'SWL': 1362, 'NUJ': 1362, 'NJM': 1362, 'CFP': 1362, 'LGP': 1361, 'TJH': 1360, 'OGK': 1360, 'DWM': 1360, 'CDH': 1360, 'SPK': 1359, 'NZP': 1359, 'JMC': 1359, 'FRN': 1359, 'YPB': 1357, 'FDL': 1355, 'QBC': 1354, 'HZU': 1354, 'KCN': 1352, 'CAX': 1352, 'GTL': 1350, 'MGB': 1347, 'FGN': 1347, 'BRZ': 1347, 'BFC': 1347, 'TNL': 1346, 'TFB': 1346, 'LHC': 1346, 'JLO': 1346, 'CLW': 1343, 'ZSB': 1342, 'QDE': 1342, 'LZW': 1342, 'FSJ': 1342, 'HRF': 1341, 'FJR': 1341, 'UZD': 1340, 'IXX': 1340, 'FGP': 1340, 'DKT': 1340, 'BZE': 1339, 'KKL': 1337, 'PNB': 1336, 'HZT': 1336, 'GIY': 1336, 'TGC': 1335, 'KGM': 1334, 'YOZ': 1333, 'DHN': 1333, 'ZJA': 1332, 'PVP': 1332, 'IZG': 1332, 'BFS': 1330, 'KHB': 1329, 'FRF': 1328, 'FDV': 1328, 'DOQ': 1328, 'PLP': 1327, 'WCP': 1325, 'QSI': 1325, 'SXW': 1324, 'PGB': 1324, 'NMK': 1324, 'YFM': 1323, 'SHZ': 1323, 'GKL': 1322, 'IYS': 1321, 'JSK': 1320, 'SFH': 1319, 'QBM': 1319, 'ZZD': 1318, 'RVW': 1317, 'KHP': 1316, 'FRR': 1315, 'NBW': 1314, 'EJF': 1314, 'WBS': 1313, 'JKE': 1313, 'QIO': 1312, 'JOZ': 1312, 'EJW': 1312, 'WHP': 1311, 'OEZ': 1311, 'GDN': 1309, 'WTF': 1308, 'PLD': 1308, 'TLW': 1307, 'GYY': 1307, 'KWU': 1306, 'GTK': 1306, 'PLM': 1304, 'NNZ': 1304, 'IDX': 1304, 'FVL': 1304, 'XCY': 1303, 'WPT': 1303, 'QAA': 1303, 'MLN': 1303, 'CGY': 1303, 'XSR': 1302, 'RDX': 1302, 'FDT': 1302, 'QII': 1301, 'PFT': 1301, 'HLN': 1301, 'CBT': 1301, 'KGT': 1300, 'KCB': 1300, 'YUO': 1298, 'GCN': 1298, 'GFC': 1297, 'BHD': 1297, 'KGW': 1296, 'ZCU': 1295, 'XAA': 1294, 'SCK': 1294, 'UYK': 1293, 'GDV': 1292, 'VSJ': 1289, 'VBY': 1289, 'QTA': 1287, 'KSZ': 1287, 'CLB': 1287, 'WFM': 1286, 'TYX': 1286, 'TJM': 1286, 'MSZ': 1286, 'YCF': 1284, 'JCC': 1281, 'RBK': 1280, 'MHR': 1280, 'TQA': 1279, 'PXI': 1279, 'OZB': 1278, 'JWE': 1278, 'PLW': 1277, 'NVC': 1277, 'TFP': 1275, 'LGW': 1275, 'CPB': 1275, 'SZW': 1274, 'JFR': 1274, 'GDW': 1274, 'WPP': 1272, 'VRT': 1272, 'PMV': 1272, 'GQB': 1272, 'HGS': 1271, 'LKK': 1270, 'KHH': 1270, 'WOX': 1269, 'CRN': 1268, 'UWM': 1267, 'MWT': 1267, 'HKD': 1265, 'PYY': 1264, 'LHD': 1264, 'JIJ': 1264, 'TRZ': 1261, 'AGK': 1261, 'DHH': 1259, 'YHS': 1258, 'DVB': 1257, 'HHP': 1256, 'YKC': 1255, 'TBF': 1255, 'JDS': 1255, 'CBW': 1255, 'AJF': 1254, 'GPW': 1253, 'WRM': 1252, 'HWW': 1252, 'FLQ': 1252, 'PUH': 1251, 'JVA': 1250, 'JYA': 1249, 'QLI': 1248, 'LGT': 1248, 'GWB': 1248, 'SXF': 1247, 'ZJU': 1245, 'ZIY': 1245, 'XAH': 1245, 'MVU': 1245, 'QSC': 1243, 'LGN': 1243, 'GCT': 1243, 'UCP': 1242, 'MMV': 1242, 'TZJ': 1241, 'FPB': 1241, 'ZUP': 1240, 'GTF': 1239, 'PKU': 1236, 'NQB': 1234, 'QHE': 1233, 'TUJ': 1232, 'QIL': 1231, 'PDL': 1231, 'XKL': 1230, 'RWB': 1230, 'MGC': 1230, 'IUZ': 1229, 'DKP': 1229, 'WKU': 1228, 'JFI': 1228, 'BNN': 1228, 'RVM': 1227, 'SVG': 1226, 'PCN': 1225, 'IJD': 1225, 'WUD': 1224, 'KDJ': 1224, 'CZU': 1224, 'AFJ': 1224, 'CNY': 1223, 'XEO': 1222, 'QIB': 1222, 'FVS': 1222, 'FDJ': 1222, 'EQW': 1222, 'YWU': 1221, 'YMK': 1221, 'XYR': 1221, 'QTE': 1221, 'SQI': 1220, 'YBN': 1219, 'JRK': 1219, 'VUM': 1218, 'ZZZ': 1217, 'AGV': 1217, 'MDL': 1216, 'HPY': 1216, 'FRW': 1216, 'CDL': 1216, 'UUD': 1215, 'MHB': 1214, 'FCG': 1214, 'YTM': 1213, 'RVD': 1211, 'MGD': 1211, 'JJI': 1211, 'QUY': 1210, 'MXM': 1209, 'WFT': 1208, 'SVW': 1208, 'FUU': 1208, 'ZUY': 1207, 'TKT': 1207, 'FNH': 1207, 'DXP': 1207, 'ZFU': 1206, 'OJM': 1206, 'TXR': 1205, 'RHW': 1205, 'FXS': 1205, 'DXS': 1205, 'WMP': 1203, 'RWM': 1203, 'MWM': 1203, 'MWY': 1202, 'YLN': 1199, 'WCF': 1199, 'KNS': 1199, 'JRL': 1199, 'ZBL': 1198, 'XOW': 1198, 'VTT': 1198, 'KNJ': 1198, 'JVO': 1198, 'ZCE': 1197, 'JKI': 1197, 'AQG': 1197, 'XEW': 1195, 'BMH': 1195, 'TFF': 1194, 'BTG': 1194, 'RWT': 1192, 'HGP': 1190, 'CVC': 1190, 'SWD': 1189, 'UGV': 1188, 'QID': 1188, 'LRP': 1188, 'NXH': 1187, 'WKB': 1186, 'TKB': 1185, 'WIY': 1184, 'UFW': 1184, 'MKY': 1184, 'FNT': 1184, 'TLM': 1182, 'DDK': 1181, 'JTE': 1180, 'IQS': 1180, 'YKT': 1178, 'MBK': 1178, 'KCC': 1178, 'HCF': 1177, 'KLT': 1175, 'DNL': 1174, 'BHR': 1174, 'AZF': 1174, 'NXN': 1173, 'SZS': 1172, 'IUO': 1172, 'HZH': 1172, 'FXE': 1172, 'DVF': 1171, 'HBF': 1170, 'BRG': 1170, 'AUU': 1169, 'AQQ': 1169, 'ZYU': 1168, 'CNG': 1168, 'XEF': 1167, 'WZI': 1167, 'WJI': 1167, 'PNH': 1167, 'LHR': 1167, 'KGH': 1166, 'JCL': 1166, 'EFX': 1166, 'XMC': 1165, 'TXM': 1165, 'RPJ': 1165, 'SYX': 1164, 'CBP': 1164, 'FXM': 1163, 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'WVT': 427, 'IIQ': 427, 'IYC': 426, 'HTX': 426, 'YJN': 425, 'WXI': 425, 'UWL': 425, 'KVC': 425, 'ZIQ': 424, 'XNF': 424, 'VRR': 424, 'QIJ': 424, 'OKZ': 424, 'BTJ': 424, 'YHF': 423, 'PJR': 423, 'LXT': 423, 'HCK': 423, 'GIX': 423, 'BLK': 423, 'AQJ': 423, 'XBM': 422, 'UVD': 422, 'TXH': 422, 'JWR': 422, 'JBC': 422, 'ABX': 422, 'YHN': 421, 'SGV': 421, 'IYK': 421, 'CNL': 421, 'YXC': 420, 'WCV': 420, 'OKX': 420, 'KFZ': 420, 'GWN': 420, 'EJY': 420, 'DVV': 420, 'XXR': 419, 'OQT': 419, 'KBF': 419, 'FJD': 419, 'CXC': 419, 'XMF': 418, 'DZK': 418, 'BGW': 418, 'PWM': 417, 'LGF': 417, 'HRJ': 417, 'BTK': 417, 'YBK': 416, 'XLV': 416, 'TRJ': 416, 'SHX': 416, 'PXP': 416, 'KWF': 416, 'CJT': 415, 'XUC': 414, 'UJN': 414, 'KIQ': 414, 'FHF': 414, 'ZZK': 413, 'JNT': 413, 'IYW': 413, 'BJT': 413, 'YRV': 412, 'XVC': 412, 'PWT': 412, 'PKL': 412, 'FJM': 412, 'DZR': 412, 'BOQ': 412, 'XPD': 411, 'TXY': 411, 'JGU': 411, 'IHP': 411, 'CVH': 411, 'KVU': 409, 'HQO': 409, 'HLJ': 409, 'DRX': 409, 'XPB': 408, 'VPG': 408, 'MFN': 408, 'JMB': 408, 'BLH': 408, 'YBG': 407, 'SZF': 407, 'RWV': 407, 'QVC': 407, 'OYQ': 407, 'KDP': 407, 'JQU': 407, 'CZB': 407, 'ZTY': 406, 'YZC': 406, 'LZC': 406, 'LWF': 406, 'LQB': 406, 'HWL': 406, 'EJZ': 406, 'DDQ': 406, 'CWN': 406, 'VFC': 405, 'TJN': 405, 'TGG': 405, 'PDJ': 405, 'NHQ': 405, 'HVT': 405, 'HVM': 405, 'WHF': 404, 'VFT': 404, 'SFK': 404, 'PCK': 404, 'LHL': 404, 'QHI': 403, 'MVW': 403, 'FNN': 403, 'YZR': 402, 'BQS': 402, 'BPN': 402, 'RUQ': 401, 'PBG': 401, 'JTG': 401, 'IVJ': 401, 'HHG': 401, 'GXT': 401, 'WMF': 400, 'VRN': 400, 'SQC': 400, 'SMQ': 400, 'XXP': 399, 'RHJ': 399, 'LXW': 399, 'KNP': 399, 'EQD': 399, 'CVM': 399, 'BBV': 399, 'XCC': 398, 'JVP': 398, 'CDJ': 398, 'BMN': 398, 'BDH': 398, 'YYR': 397, 'YFG': 397, 'PXX': 397, 'QBF': 396, 'PJB': 396, 'LWP': 396, 'KDN': 396, 'JMP': 396, 'IJC': 396, 'HJC': 396, 'FXH': 396, 'FWN': 396, 'FVT': 396, 'BWV': 396, 'RVV': 395, 'LZP': 395, 'EQH': 395, 'PBF': 394, 'MWG': 394, 'HWP': 394, 'MVH': 393, 'IQR': 393, 'GKP': 393, 'XYV': 392, 'QAG': 392, 'OQO': 392, 'FZW': 392, 'DTX': 392, 'RZG': 391, 'JCF': 391, 'IYN': 391, 'BKT': 391, 'PVH': 390, 'LJD': 390, 'KJV': 390, 'FWV': 390, 'YFW': 389, 'WHM': 389, 'SWJ': 389, 'JBT': 389, 'HDZ': 389, 'UFY': 388, 'TWJ': 388, 'MUX': 388, 'GPV': 388, 'SCQ': 387, 'CZR': 387, 'YJL': 386, 'RQS': 386, 'NQV': 386, 'HVH': 386, 'GCV': 386, 'YWL': 385, 'NKX': 385, 'JSN': 385, 'GVM': 385, 'BKL': 385, 'BKC': 385, 'BDJ': 385, 'ZND': 384, 'CVU': 384, 'ZKU': 383, 'TTX': 383, 'PLJ': 383, 'NLK': 383, 'MHK': 383, 'JKW': 383, 'WXB': 382, 'PNV': 382, 'MRX': 382, 'LFZ': 382, 'AZJ': 382, 'KNM': 381, 'ZYY': 380, 'KYZ': 380, 'IMX': 380, 'CJD': 380, 'SQE': 379, 'YXF': 378, 'VGW': 378, 'SQO': 378, 'HXS': 378, 'BLG': 378, 'ZPP': 377, 'IHG': 377, 'GKB': 377, 'VKN': 376, 'KLP': 376, 'YXY': 375, 'SPQ': 375, 'PXS': 375, 'JNG': 375, 'IQL': 375, 'XAY': 374, 'TFX': 374, 'QEA': 374, 'PVM': 374, 'NQC': 374, 'JTC': 374, 'VLK': 373, 'PNJ': 373, 'KSX': 373, 'KDD': 373, 'VHP': 372, 'HJB': 372, 'GBJ': 372, 'WPN': 371, 'PVB': 371, 'PKG': 371, 'FJL': 371, 'TBK': 370, 'QEL': 370, 'FJT': 370, 'DJY': 370, 'BXA': 370, 'SDZ': 369, 'KFW': 369, 'DWJ': 369, 'ZNS': 368, 'YJG': 368, 'WHW': 368, 'QFY': 368, 'LPQ': 368, 'KCK': 368, 'KBD': 368, 'IJF': 368, 'TFJ': 367, 'QMJ': 367, 'EVX': 367, 'BNV': 367, 'XFS': 366, 'UHK': 366, 'TRX': 366, 'FJG': 366, 'YZN': 365, 'JMM': 365, 'GXF': 365, 'GRV': 365, 'YXV': 364, 'VWB': 364, 'MXX': 364, 'LGG': 364, 'KBJ': 364, 'BDN': 364, 'ZXA': 363, 'LGV': 363, 'KVH': 363, 'JCD': 363, 'IXZ': 363, 'FLK': 363, 'CLG': 363, 'XNY': 362, 'QBH': 362, 'FVY': 362, 'FNV': 362, 'YWD': 361, 'VNZ': 361, 'ZYV': 360, 'VNR': 360, 'RHV': 360, 'QEV': 360, 'NQM': 360, 'MXY': 360, 'JEX': 360, 'BWC': 360, 'YVW': 359, 'XBS': 359, 'TXL': 359, 'QJU': 359, 'QCL': 359, 'XLW': 358, 'VNH': 358, 'VGT': 358, 'RXV': 358, 'RQT': 358, 'PVV': 358, 'CUJ': 358, 'ZOJ': 357, 'QRS': 357, 'LZD': 357, 'LHH': 357, 'HQC': 357, 'GZW': 357, 'GPK': 357, 'YGF': 356, 'VNF': 356, 'VLD': 356, 'TWX': 356, 'QGA': 356, 'EQN': 356, 'QER': 355, 'FWG': 355, 'FHG': 355, 'BXS': 355, 'LZF': 354, 'JJJ': 354, 'ABQ': 354, 'WLJ': 353, 'QVA': 353, 'JDT': 353, 'HGG': 353, 'QLT': 352, 'GGK': 352, 'BJH': 352, 'BGN': 352, 'OHZ': 351, 'MJG': 351, 'KTF': 351, 'YJF': 350, 'XXD': 350, 'RLX': 350, 'QVE': 350, 'FVP': 350, 'FKK': 350, 'SUX': 349, 'JGW': 349, 'IBV': 349, 'GVN': 349, 'TDZ': 348, 'LXC': 348, 'DHZ': 348, 'CZF': 348, 'CLK': 348, 'ZLL': 347, 'YXU': 347, 'JCM': 347, 'FXD': 347, 'BKM': 347, 'YXH': 346, 'VRF': 346, 'JGT': 346, 'IYR': 346, 'YZD': 345, 'YYV': 345, 'XMT': 345, 'WBD': 345, 'UVH': 345, 'MPZ': 345, 'CJP': 345, 'XRT': 344, 'UVN': 344, 'QPL': 344, 'OIQ': 344, 'KLH': 344, 'JYE': 344, 'XIY': 343, 'CXS': 343, 'BFK': 343, 'YWG': 342, 'VZA': 342, 'NCQ': 342, 'JJC': 342, 'FVW': 342, 'EGQ': 342, 'ZTL': 341, 'YFH': 341, 'NZZ': 341, 'IQM': 341, 'HHF': 341, 'CMX': 341, 'TQS': 340, 'KWG': 340, 'JMW': 340, 'DBV': 340, 'YYT': 339, 'WXY': 339, 'VCV': 339, 'UVV': 339, 'RJV': 339, 'FHH': 339, 'UPX': 338, 'TJY': 338, 'SGK': 338, 'LCJ': 338, 'KMJ': 338, 'CXT': 338, 'LRK': 337, 'KCV': 337, 'JSG': 337, 'HHK': 337, 'ZGM': 336, 'YWF': 336, 'YKV': 336, 'XLY': 336, 'LWL': 336, 'HFY': 336, 'AXQ': 336, 'YPJ': 335, 'UHG': 335, 'TBV': 335, 'MKX': 335, 'FJJ': 335, 'BJD': 335, 'WQA': 334, 'VXI': 334, 'QBL': 334, 'LHF': 334, 'JFS': 334, 'GVP': 334, 'DZV': 334, 'BKB': 334, 'ZDF': 333, 'CWG': 333, 'CQP': 333, 'YYS': 332, 'RCQ': 332, 'PPX': 332, 'KNL': 332, 'GXB': 332, 'ACX': 332, 'VMD': 331, 'VLL': 331, 'QGR': 331, 'QEE': 331, 'OQS': 331, 'LBV': 331, 'KWV': 331, 'KVW': 331, 'FXL': 331, 'XRH': 330, 'PXT': 330, 'IYB': 330, 'HZV': 330, 'CSZ': 330, 'CBK': 330, 'VZQ': 329, 'SCX': 329, 'OQW': 329, 'JGS': 329, 'XMW': 328, 'PKB': 328, 'KKF': 328, 'HVP': 328, 'TQT': 327, 'MZW': 327, 'LWN': 327, 'KWK': 327, 'IUV': 327, 'YNQ': 326, 'UMX': 326, 'QCI': 326, 'PGY': 326, 'NUQ': 326, 'MQB': 326, 'KWD': 326, 'KKC': 326, 'GWF': 326, 'EBQ': 326, 'BHH': 326, 'YZL': 325, 'YFX': 325, 'VNP': 325, 'PWG': 325, 'KXT': 325, 'IJB': 325, 'HWN': 325, 'VKR': 324, 'MVB': 324, 'LVG': 324, 'BDV': 324, 'XMB': 323, 'IYD': 323, 'CVL': 323, 'CRZ': 323, 'VFF': 322, 'UJD': 322, 'QEM': 322, 'MPX': 322, 'HXB': 322, 'BFD': 322, 'PBN': 321, 'BCZ': 321, 'XCT': 320, 'VHC': 320, 'RCX': 320, 'QSD': 320, 'KNN': 320, 'KGN': 320, 'XMD': 319, 'WVW': 319, 'QMU': 319, 'PYX': 319, 'PVN': 319, 'HJJ': 319, 'GLK': 319, 'FBK': 319, 'DDX': 319, 'VMM': 318, 'QAO': 318, 'OZK': 318, 'KPG': 318, 'HKJ': 318, 'ZIX': 317, 'WXA': 317, 'WHH': 317, 'VNB': 317, 'TKJ': 317, 'SVK': 317, 'PWU': 317, 'KMV': 317, 'JZS': 317, 'HWD': 317, 'FPJ': 317, 'YTG': 316, 'YOQ': 316, 'XUZ': 316, 'VUG': 316, 'TJV': 316, 'PWB': 316, 'YHG': 315, 'WJB': 315, 'SKZ': 315, 'CCX': 315, 'QJO': 314, 'PUX': 314, 'JVG': 314, 'JNJ': 314, 'GVW': 314, 'GRK': 314, 'XVW': 313, 'RJY': 313, 'RFX': 313, 'NBV': 313, 'MDX': 313, 'DYX': 313, 'CQS': 313, 'XZA': 312, 'RXY': 312, 'HWG': 312, 'CZD': 312, 'YUQ': 311, 'XHY': 311, 'VVT': 311, 'QPI': 311, 'LMZ': 311, 'IQC': 311, 'DZC': 311, 'CLV': 311, 'WFN': 310, 'WDK': 310, 'UFG': 310, 'QTW': 310, 'GVH': 310, 'CXX': 310, 'CGN': 310, 'WJM': 309, 'VMP': 309, 'VMH': 309, 'QIZ': 309, 'KJS': 309, 'FGG': 309, 'YZF': 308, 'XNG': 308, 'RQP': 308, 'OJL': 308, 'DGV': 308, 'CVX': 308, 'ZXI': 307, 'XYY': 307, 'PVF': 307, 'PJW': 307, 'MFX': 307, 'MDK': 307, 'LKQ': 307, 'KTK': 307, 'DZN': 307, 'ZTM': 306, 'XUW': 306, 'VTN': 306, 'SZV': 306, 'PTX': 306, 'KKP': 306, 'AGZ': 306, 'IWB': 305, 'HDK': 305, 'DZL': 305, 'VVV': 304, 'VSZ': 304, 'VRL': 304, 'NWX': 304, 'JLU': 304, 'HZY': 304, 'CDK': 304, 'XOH': 303, 'XFC': 302, 'VPJ': 302, 'LXF': 302, 'FJB': 302, 'VXA': 301, 'OVZ': 301, 'MXO': 301, 'HXX': 301, 'EBX': 301, 'PWY': 300, 'JTV': 300, 'DPZ': 300, 'CJF': 300, 'BTQ': 300, 'ZTT': 299, 'WNX': 299, 'UJS': 299, 'TZZ': 299, 'QET': 299, 'JWS': 299, 'IPX': 299, 'AHX': 299, 'SGJ': 298, 'IYL': 298, 'GXX': 298, 'CRJ': 298, 'CMK': 298, 'ZLW': 297, 'ZLT': 297, 'YYK': 297, 'RQC': 297, 'QCS': 297, 'EYX': 297, 'VDY': 296, 'NHZ': 296, 'GJC': 296, 'GGZ': 296, 'YHK': 295, 'VHR': 295, 'OZV': 295, 'IGX': 295, 'HXT': 295, 'HGF': 295, 'BWL': 295, 'LZY': 294, 'KJM': 294, 'IQP': 294, 'HVG': 294, 'AQY': 294, 'TXG': 293, 'QPU': 293, 'PQA': 293, 'PLZ': 293, 'JNW': 293, 'CNV': 293, 'ZNT': 292, 'RQO': 292, 'QES': 292, 'ODX': 292, 'KXP': 292, 'HZG': 292, 'UQB': 291, 'QUP': 291, 'QOV': 291, 'QGS': 291, 'JKL': 291, 'YXL': 290, 'XSJ': 290, 'TQP': 290, 'QTU': 290, 'QJA': 290, 'MZY': 290, 'HXR': 290, 'CJL': 290, 'XIZ': 289, 'UWG': 289, 'SGX': 289, 'FXN': 289, 'SZZ': 287, 'MZS': 287, 'KJT': 287, 'BUV': 287, 'ZGH': 286, 'QBG': 286, 'LWV': 286, 'HWF': 286, 'YXD': 285, 'QRC': 285, 'QCD': 285, 'JUZ': 285, 'JLD': 285, 'HVF': 285, 'YFN': 284, 'XDY': 284, 'PVU': 284, 'IYH': 284, 'HZL': 284, 'FVD': 284, 'ZVS': 283, 'UJH': 283, 'RVK': 283, 'OPX': 283, 'JKN': 283, 'EKX': 283, 'WGD': 282, 'PBJ': 282, 'KGG': 282, 'JPF': 282, 'DXG': 282, 'WXT': 281, 'UUO': 281, 'TVX': 281, 'SQV': 281, 'SLX': 281, 'IYG': 281, 'GFH': 281, 'CGG': 281, 'BWF': 281, 'XNB': 280, 'TQO': 280, 'QDR': 280, 'PCX': 280, 'LHQ': 280, 'HMJ': 280, 'GWD': 280, 'GJS': 280, 'XLB': 279, 'UZV': 279, 'TVQ': 279, 'RZV': 279, 'NVZ': 279, 'NQD': 279, 'MZT': 279, 'KBK': 279, 'GWG': 279, 'QUW': 278, 'PJM': 278, 'FLX': 278, 'VWT': 277, 'VGN': 277, 'LTX': 277, 'LJN': 277, 'KJP': 277, 'JPN': 277, 'FWK': 277, 'FDX': 277, 'CPJ': 277, 'BMJ': 277, 'YHQ': 276, 'SZG': 276, 'RHQ': 276, 'QLC': 276, 'QGE': 276, 'CPK': 276, 'BJM': 276, 'JVB': 275, 'JSY': 275, 'JPB': 275, 'JMR': 275, 'YYP': 274, 'UHV': 274, 'KWN': 274, 'DCX': 274, 'CZL': 274, 'CQB': 274, 'XEK': 273, 'VFM': 273, 'UKZ': 273, 'JFU': 273, 'FKJ': 273, 'FHZ': 273, 'CVF': 273, 'ZNU': 272, 'RBZ': 272, 'QUC': 272, 'PUV': 272, 'NVV': 272, 'KZH': 272, 'JTY': 272, 'DQP': 272, 'XCS': 271, 'WVL': 271, 'UWD': 271, 'KTX': 271, 'JLP': 271, 'FZL': 271, 'XLL': 270, 'VGH': 270, 'EQV': 270, 'DQC': 270, 'CXM': 270, 'BVT': 270, 'BFH': 270, 'XIJ': 269, 'QTS': 269, 'NQE': 269, 'IQD': 269, 'GJD': 269, 'DGJ': 269, 'SWX': 268, 'QLP': 268, 'KTD': 268, 'JDL': 268, 'XDX': 267, 'WMN': 267, 'SVJ': 267, 'SMZ': 267, 'OJG': 267, 'HQM': 267, 'CNJ': 267, 'XPV': 266, 'XKU': 266, 'VBB': 266, 'SFV': 266, 'QAQ': 266, 'PJD': 266, 'JNU': 266, 'GKD': 266, 'FZF': 266, 'CVG': 266, 'BVB': 266, 'BKK': 266, 'ZMS': 265, 'XZE': 265, 'XOO': 265, 'UXY': 265, 'TMX': 265, 'LFX': 265, 'JFP': 265, 'XND': 264, 'WJS': 264, 'WJL': 264, 'VHT': 264, 'KXS': 264, 'JIQ': 264, 'IJW': 264, 'HXF': 264, 'APZ': 264, 'ZDS': 263, 'RRZ': 263, 'PJT': 263, 'KJH': 263, 'JKT': 263, 'IWM': 263, 'HZN': 263, 'FQO': 263, 'XUH': 262, 'XDV': 262, 'WKK': 262, 'TGK': 262, 'SQP': 262, 'KRV': 262, 'JGB': 262, 'VNN': 261, 'UJC': 261, 'KNX': 261, 'JCZ': 261, 'CIY': 261, 'XYK': 260, 'WMK': 260, 'HFG': 260, 'XXN': 259, 'WXW': 259, 'WWZ': 259, 'WIQ': 259, 'VJS': 259, 'UHJ': 259, 'LJL': 259, 'KLG': 259, 'HJW': 259, 'FMX': 259, 'DQO': 259, 'CQC': 259, 'NQP': 258, 'MKK': 258, 'MBQ': 258, 'BCQ': 258, 'YVB': 257, 'VBW': 257, 'HXC': 257, 'HVW': 257, 'DZF': 257, 'CFX': 257, 'WBG': 256, 'VWW': 256, 'VMY': 256, 'VCG': 256, 'QSY': 256, 'MJL': 256, 'LHK': 256, 'KJB': 256, 'JMD': 256, 'BJB': 256, 'XVM': 255, 'WKJ': 255, 'SNX': 255, 'SJY': 255, 'HXU': 255, 'HDX': 255, 'BGF': 255, 'ZLB': 254, 'XDS': 254, 'WGG': 254, 'VGC': 254, 'TLZ': 254, 'RXN': 254, 'PMQ': 254, 'KXO': 254, 'JFM': 254, 'HLQ': 254, 'FZS': 254, 'BSZ': 254, 'BJL': 254, 'ZRH': 253, 'XXU': 253, 'WPY': 253, 'VLB': 253, 'QEW': 253, 'PWP': 253, 'PHQ': 253, 'PGV': 253, 'BMV': 253, 'ZNW': 252, 'YWK': 252, 'RPQ': 252, 'LRJ': 252, 'JWC': 252, 'GVD': 252, 'GFJ': 252, 'FJN': 252, 'DQE': 252, 'DHQ': 252, 'CJG': 252, 'BHF': 252, 'BFP': 252, 'LVV': 251, 'JFF': 251, 'GKF': 251, 'ZLN': 250, 'VZI': 250, 'VLW': 250, 'UCV': 250, 'RQE': 250, 'QKI': 250, 'NRX': 250, 'MXH': 250, 'JWM': 250, 'HVY': 250, 'GVF': 250, 'CFJ': 250, 'AWX': 250, 'UUF': 249, 'RPX': 249, 'QMR': 249, 'MXL': 249, 'KXM': 249, 'ZMD': 248, 'XJS': 248, 'TQC': 248, 'QNX': 248, 'MJK': 248, 'GBK': 248, 'FXV': 248, 'XLF': 247, 'XBC': 247, 'WGF': 247, 'VZE': 247, 'TJX': 247, 'LHG': 247, 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123

py

Python

charms/admin.py

velxundussa/Storyteller

e3c4cc211959bc48efced0c99a1a32e6d003a16d

[ "MIT" ]

3

2017-02-27T05:41:39.000Z

2017-02-28T01:25:30.000Z

charms/admin.py

velxundussa/Storyteller

e3c4cc211959bc48efced0c99a1a32e6d003a16d

[ "MIT" ]

4

2021-06-04T22:43:46.000Z

2022-02-10T10:51:24.000Z

charms/admin.py

velxundussa/Storyteller

e3c4cc211959bc48efced0c99a1a32e6d003a16d

[ "MIT" ]

null

from django.contrib import admin from charms.models import Charm # Register your models here. admin.site.register(Charm)

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py

Python

venv/lib/python3.8/site-packages/pip/_vendor/packaging/__about__.py

Retraces/UkraineBot

3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71

[ "MIT" ]

2

2022-03-13T01:58:52.000Z

2022-03-31T06:07:54.000Z

venv/lib/python3.8/site-packages/pip/_vendor/packaging/__about__.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

19

2021-11-20T04:09:18.000Z

2022-03-23T15:05:55.000Z

venv/lib/python3.8/site-packages/pip/_vendor/packaging/__about__.py

DesmoSearch/Desmobot

b70b45df3485351f471080deb5c785c4bc5c4beb

[ "MIT" ]

null

/home/runner/.cache/pip/pool/a7/f3/90/968a87dac69a75c6d4426584b162bce7b748ebf7dfe44dda4a20aa1850

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8b726458624b3d788aebe58b8819a259295310cf

123

py

Python

Gustavo Guanabara - Python Learning Exercises/ex013 - F String [Exercise] 6.py

TiagoPL/Python-Learning

20855433a8a050647ee9c5039aac1e50807324f8

[ "MIT" ]

null

Gustavo Guanabara - Python Learning Exercises/ex013 - F String [Exercise] 6.py

TiagoPL/Python-Learning

20855433a8a050647ee9c5039aac1e50807324f8

[ "MIT" ]

null

Gustavo Guanabara - Python Learning Exercises/ex013 - F String [Exercise] 6.py

TiagoPL/Python-Learning

20855433a8a050647ee9c5039aac1e50807324f8

[ "MIT" ]

null

n1 = int(input('What is the employee salary? ')) print(f'The new salary with a 15% bonus will be U${(n1 / 100) *115:.2f}')

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8b88a726ce820b3a52f53d6f44cf213378966361

194

py

Python

poseutils/datasets/unprocessed/__init__.py

SaadManzur/PoseUtils

146861eedf6b704118fd38ee6ae996b8781a8741

[ "MIT" ]

null

poseutils/datasets/unprocessed/__init__.py

SaadManzur/PoseUtils

146861eedf6b704118fd38ee6ae996b8781a8741

[ "MIT" ]

null

poseutils/datasets/unprocessed/__init__.py

SaadManzur/PoseUtils

146861eedf6b704118fd38ee6ae996b8781a8741

[ "MIT" ]

null

from .GPADataset import GPADataset from .H36MDataset import H36MDataset from .MPI3DHPDataset import MPI3DHPDataset from .SURREALDataset import SURREALDataset from .TDPWDataset import TDPWDataset

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0

5

8b8a7d2e7edf3a8cc0b3d636e11ea951d3ff5cef

271

py

Python

snmpagent_unity/unity_impl/FanHealthStatus.py

factioninc/snmp-unity-agent

3525dc0fac60d1c784dcdd7c41693544bcbef843

[ "Apache-2.0" ]

2

2019-03-01T11:14:59.000Z

2019-10-02T17:47:59.000Z

snmpagent_unity/unity_impl/FanHealthStatus.py

factioninc/snmp-unity-agent

3525dc0fac60d1c784dcdd7c41693544bcbef843

[ "Apache-2.0" ]

2

2019-03-01T11:26:29.000Z

2019-10-11T18:56:54.000Z

snmpagent_unity/unity_impl/FanHealthStatus.py

factioninc/snmp-unity-agent

3525dc0fac60d1c784dcdd7c41693544bcbef843

[ "Apache-2.0" ]

1

2019-10-03T21:09:17.000Z

class FanHealthStatus(object): def read_get(self, name, idx_name, unity_client): return unity_client.get_fan_health_status(idx_name) class FanHealthStatusColumn(object): def get_idx(self, name, idx, unity_client): return unity_client.get_fans()

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0

5

8b94e9118fd62e1e9e5163f673ca94570643ab43

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py

Python

src/onegov/fsi/utils.py

politbuero-kampagnen/onegov-cloud

20148bf321b71f617b64376fe7249b2b9b9c4aa9

[ "MIT" ]

null

src/onegov/fsi/utils.py

politbuero-kampagnen/onegov-cloud

20148bf321b71f617b64376fe7249b2b9b9c4aa9

[ "MIT" ]

null

src/onegov/fsi/utils.py

politbuero-kampagnen/onegov-cloud

20148bf321b71f617b64376fe7249b2b9b9c4aa9

[ "MIT" ]

null

def handle_empty_p_tags(html): return html if not html == '<p></p>' else ''

26.666667

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0.714286

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8ba60f4e752582975e9fcccf6eadcd8e23012499

132

py

Python

server/app/controllers/__init__.py

Neoteroi/Torino

9bac21735ed4e6bdaed6e8b20e2c6b33d76f938c

[ "MIT" ]

7

2021-12-12T09:14:50.000Z

2022-02-06T15:59:57.000Z

server/app/controllers/__init__.py

Neoteroi/Torino

9bac21735ed4e6bdaed6e8b20e2c6b33d76f938c

[ "MIT" ]

5

2021-12-13T20:27:13.000Z

2021-12-14T08:31:11.000Z

server/app/controllers/__init__.py

Neoteroi/Torino

9bac21735ed4e6bdaed6e8b20e2c6b33d76f938c

[ "MIT" ]

1

2021-12-31T18:52:41.000Z

# flake8: noqa from .albums import AlbumsController from .blobs import BlobsController from .vfs import VirtualFileSystemController

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8be6cf90cca078a5b7a54cc28647b15c13f8e148

438

py

Python

doracle/model.py

baovien/dota-oracle

4541a0d1cfcf54fce9df1b1d853a4e9090262a09

[ "MIT" ]

null

doracle/model.py

baovien/dota-oracle

4541a0d1cfcf54fce9df1b1d853a4e9090262a09

[ "MIT" ]

null

doracle/model.py

baovien/dota-oracle

4541a0d1cfcf54fce9df1b1d853a4e9090262a09

[ "MIT" ]

null

import random class HeroStats: def __init__(self): pass def get_winrate(self, hero_id): return random.random() def get_pickrate(self, hero_id): return random.random() def get_best_paired_with_hero(self, hero_id): return random.randint(0, 120) @staticmethod def load(path_to_model: str): print("loading model from: {}".format(path_to_model)) return HeroStats()

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null

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1

0

1

0

1

0

5

4736ca92aff880e9eea5c31d68f7ac156f3fb3a6

154

py

Python

sync-dropbox.py

sdelcore/home-security

de8164915194c68579327ad25b9221bae8679c6f

[ "MIT" ]

null

sync-dropbox.py

sdelcore/home-security

de8164915194c68579327ad25b9221bae8679c6f

[ "MIT" ]

null

sync-dropbox.py

sdelcore/home-security

de8164915194c68579327ad25b9221bae8679c6f

[ "MIT" ]

null

from subprocess import call photofile = "/home/pi/Dropbox-Uploader/dropbox_uploader.sh -s upload /home/pi/motion /" call ([photofile], shell=True)

30.8

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null

0

1

0

5

4742ef803806a82aee9b4a40603e5b2c48e21957

35,340

py

Python

indiv-metrics/mortality_rate.py

fibanneacci/covid-incarc

9dae392c458a1d9135641e1def517d8719328340

[ "MIT" ]

null

indiv-metrics/mortality_rate.py

fibanneacci/covid-incarc

9dae392c458a1d9135641e1def517d8719328340

[ "MIT" ]

2

2020-08-05T16:17:38.000Z

2021-02-06T19:58:14.000Z

indiv-metrics/mortality_rate.py

fibanneacci/covid-incarc

9dae392c458a1d9135641e1def517d8719328340

[ "MIT" ]

null

import streamlit as st from plotly.subplots import make_subplots import plotly.graph_objects as go import pandas as pd from datetime import datetime # Add data & visualizaions for prevalence, then combine all 3 metrics into one page & animate # Add sidebar for navigation, slider (see how these variables changed with respect to each other over the course # of the outbreak), keep scale same across time (for slider), prob need st.cache PRISON_POP_DATA_URL = ('https://raw.githubusercontent.com/themarshallproject/COVID_prison_data/master/data/prison_populations.csv') prison_pop_data = pd.read_csv(PRISON_POP_DATA_URL, nrows = 50, names = ["name", "abbreviation", "april_pop", "as_of_date"], usecols = ["name", "april_pop", "as_of_date"], skiprows = 1, ) nationwide_prison_pop_data = {"name": "NATIONWIDE", "april_pop": prison_pop_data.sum(0).loc["april_pop"], "as_of_date": "N/A"} prison_pop_data = prison_pop_data.append(nationwide_prison_pop_data, ignore_index = True) COVID_PRISON_DATA_URL = ('https://raw.githubusercontent.com/themarshallproject/COVID_prison_data/master/data/covid_prison_cases.csv') covid_prison_data = pd.read_csv(COVID_PRISON_DATA_URL, nrows = 50, names = ["name", "abbreviation", "staff_tests", "staff_tests_with_multiples", "prisoner_tests", "prisoner_tests_with_multiples", "total_staff_cases", "total_prisoner_cases", "staff_recovered", "prisoners_recovered", "total_staff_deaths","total_prisoner_deaths", "as_of_date", "notes"], usecols = ["name", "total_prisoner_deaths"], skiprows = 1, # Change according to date ) covid_prison_data["Prison_MR"] = covid_prison_data["total_prisoner_deaths"] * 100000 / prison_pop_data["april_pop"] nationwide_covid_prison_data = {"name": "NATIONWIDE", "total_prisoner_deaths": covid_prison_data.sum(0).loc["total_prisoner_deaths"], "Prison_MR": ""} nationwide_covid_prison_data["Prison_MR"] = nationwide_covid_prison_data["total_prisoner_deaths"] * 100000 / prison_pop_data.sum(0).loc["april_pop"] covid_prison_data = covid_prison_data.append(nationwide_covid_prison_data, ignore_index = True) COVID_DATA_URL = ('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports_us/07-21-2020.csv') # Change according to date covid_data = pd.read_csv(COVID_DATA_URL, nrows = 50, names = ["Province_State", "Country_Region", "Last_Update", "Lat", "Long_", "Confirmed", "Deaths", "Recovered", "Active", "FIPS", "Incident_Rate", "People_Tested", "People_Hospitalized", "Mortality_Rate", "UID", "ISO3", "Testing_Rate", "Hospitalization_Rate"], usecols = ["Province_State", "Confirmed", "Deaths", "Incident_Rate"], skiprows = [0, 3, 10, 11, 14, 15, 40, 45, 53], ) covid_data["population"] = (covid_data["Confirmed"] * 100000 / covid_data["Incident_Rate"]).astype(int) covid_data["State_MR"] = covid_data["Deaths"] * 100000 / covid_data["population"] nationwide_covid_data = {"Province_State": "NATIONWIDE", "Confirmed": covid_data.sum(0).loc["Confirmed"], "Deaths": covid_data.sum(0).loc["Deaths"], "Incident_Rate": "", "population": covid_data.sum(0).loc["population"], "State_MR": ""} nationwide_covid_data["Incident_Rate"] = nationwide_covid_data["Confirmed"] * 100000 / nationwide_covid_data["population"] nationwide_covid_data["State_MR"] = nationwide_covid_data["Deaths"] * 100000 / nationwide_covid_data["population"] covid_data = covid_data.append(nationwide_covid_data, ignore_index = True) combined_data = pd.concat([covid_prison_data, covid_data], axis = 1) combined_data = combined_data.drop(columns = ["total_prisoner_deaths", "Province_State", "Confirmed", "Deaths", "Incident_Rate", "population"]) # Based off grid from http://awesome-streamlit.org --> Gallery --> "Layout and Style Experiments" def make_grid(): grid = make_subplots( rows = 9, cols = 12, subplot_titles = ("" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "ME", "WA", "MT", "ND", "MN", "WI", "MI", "" , "" , "NY", "VT", "NH", "MA", "OR", "ID", "WY", "SD", "IA", "IL", "IN", "OH", "PA", "NJ", "CT", "RI", "NV", "UT", "CO", "NB", "KS", "MO", "TN", "KY", "WV", "VA", "MD", "DE", "" , "CA", "AZ", "NM", "OK", "AR", "MS", "AL", "GA", "SC", "NC", "" , "" , "" , "" , "" , "TX", "LA", "" , "" , "FL", "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "" , "AK", "" , "HI", "" , "" , "" , "" , "" , "" , "NAT", "" ,), specs = [ [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], [ {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"}, {"type": "bar"} ], ], ) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Maine']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', name = 'In prisons'), row = 1, col = 12) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Maine']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', name = 'Statewide'), row = 1, col = 12) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Washington']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 1) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Washington']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 1) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Montana']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 2) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Montana']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 2) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'North Dakota']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 3) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'North Dakota']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 3) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Minnesota']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 4) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Minnesota']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 4) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Wisconsin']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 5) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Wisconsin']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 5) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Michigan']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 6) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Michigan']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 6) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'New York']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 9) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'New York']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 9) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Vermont']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 10) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Vermont']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 10) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'New Hampshire']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 11) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'New Hampshire']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 11) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Massachusetts']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 2, col = 12) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Massachusetts']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 2, col = 12) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Oregon']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 1) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Oregon']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 1) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Idaho']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 2) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Idaho']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 2) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Wyoming']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 3) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Wyoming']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 3) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'South Dakota']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 4) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'South Dakota']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 4) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Iowa']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 5) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Iowa']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 5) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Illinois']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 6) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Illinois']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 6) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Indiana']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 7) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Indiana']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 7) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Ohio']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 8) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Ohio']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 8) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Pennsylvania']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 9) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Pennsylvania']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 9) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'New Jersey']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 10) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'New Jersey']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 10) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Connecticut']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 11) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Connecticut']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 11) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Rhode Island']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 3, col = 12) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Rhode Island']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 3, col = 12) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Nevada']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 1) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Nevada']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 1) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Utah']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 2) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Utah']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 2) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Colorado']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 3) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Colorado']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 3) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Nebraska']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 4) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Nebraska']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 4) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Kansas']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 5) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Kansas']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 5) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Missouri']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 6) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Missouri']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 6) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Tennessee']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 7) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Tennessee']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 7) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Kentucky']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 8) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Kentucky']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 8) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'West Virginia']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 9) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'West Virginia']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 9) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Virginia']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 10) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Virginia']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 10) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Maryland']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 11) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Maryland']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 11) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Delaware']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 4, col = 12) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Delaware']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 4, col = 12) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'California']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 2) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'California']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 2) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Arizona']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 3) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Arizona']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 3) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'New Mexico']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 4) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'New Mexico']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 4) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Oklahoma']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 5) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Oklahoma']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 5) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Arkansas']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 6) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Arkansas']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 6) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Mississippi']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 7) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Mississippi']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 7) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Alabama']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 8) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Alabama']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 8) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Georgia']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 9) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Georgia']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 9) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'South Carolina']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 10) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'South Carolina']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 10) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'North Carolina']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 5, col = 11) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'North Carolina']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 5, col = 11) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Texas']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 6, col = 5) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Texas']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 6, col = 5) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Louisiana']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 6, col = 6) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Louisiana']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 6, col = 6) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Florida']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 6, col = 9) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Florida']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 6, col = 9) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Alaska']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 8, col = 2) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Alaska']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 8, col = 2) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'Hawaii']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 8, col = 4) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'Hawaii']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 8, col = 4) grid.add_trace(go.Bar(x = ["In prisons"], y = combined_data.loc[combined_data['name'] == 'NATIONWIDE']['Prison_MR'], width = 0.3, marker_color = '#f13b3b', legendgroup = '1', showlegend = False), row = 8, col = 11) grid.add_trace(go.Bar(x = ["Statewide"], y = combined_data.loc[combined_data['name'] == 'NATIONWIDE']['State_MR'], width = 0.3, marker_color = '#000000', legendgroup = '2', showlegend = False), row = 8, col = 11) grid.update_layout( #width = 1100, #height = 1038, width = 1000, height = 944, #showlegend = False, #legend_itemclick = False, #legend_itemdoubleclick = False, legend = dict ( font = dict ( size = 14, ), ), plot_bgcolor = '#ffffff', font = dict(family = 'IBM Plex Sans', size = 12, color = '#000000'), ) grid.update_xaxes(showticklabels = False, linecolor = '#000000') #grid.update_yaxes(range = [0, max(combined_data["Prison_MR"].max(), combined_data["Mortality_Rate"].max()) + 0.05 * max(combined_data["Prison_MR"].max(), combined_data["State_MR"].max())], visible = False) grid.update_yaxes(range = [0.01 * max(combined_data["Prison_MR"].max(), combined_data["State_MR"].max()), max(combined_data["Prison_MR"].max(), combined_data["State_MR"].max()) + 0.05 * max(combined_data["Prison_MR"].max(), combined_data["State_MR"].max())], visible = False) return grid st.title('COVID-19 in US Prisons, as Told by Data') # CSS trick: https://discuss.streamlit.io/t/are-you-using-html-in-markdown-tell-us-why/96/24, https://discuss.streamlit.io/t/creating-a-nicely-formatted-search-field/1804/2 #with open("style.css") as f: # st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html = True) # Show grid map with Plotly st.markdown('<h3>Map of Mortality</h3>', unsafe_allow_html = True) st.plotly_chart(make_grid()) # Show bar chart with Plotly st.markdown('<h3>Another Visualization</h3>', unsafe_allow_html = True) bar_chart = go.Figure() bar_chart.add_trace(go.Bar( x = combined_data['Prison_MR'], y = combined_data['name'], orientation = 'h', name = 'In prisons', marker_color = '#f13b3b', )) bar_chart.add_trace(go.Bar( x = combined_data['State_MR'], y = combined_data['name'], orientation = 'h', name = 'Statewide', marker_color = '#000000', )) bar_chart.update_layout( xaxis_title = 'COVID-19 Mortality Rate (deaths per 100000 persons)', yaxis_title = 'State', width = 1000, height = 1100, barmode = 'group', bargap = 0.4, plot_bgcolor = '#ffffff', font = dict(family = 'IBM Plex Sans', size = 14, color = '#000000'), ) bar_chart.update_yaxes(autorange = 'reversed') st.write(bar_chart) # Show data with Streamlit st.markdown('<h3>Data</h3>', unsafe_allow_html = True) as_of_date = datetime.strptime(COVID_DATA_URL[115: -4], '%m-%d-%Y').strftime('%B %d, %Y') st.write('As of ' + as_of_date + '.') st.markdown('<h4>COVID-19 in US State Prisons</h4>', unsafe_allow_html = True) st.write(covid_prison_data) st.markdown('[Data](https://github.com/themarshallproject/COVID_prison_data) from The Marshall Project, a nonprofit investigative newsroom dedicated to the U.S. criminal justice system. Here, "total_prisoner_deaths" refers to confirmed deaths due to COVID-19 in US state prisons, while "Prison_MR" refers to estimated mortality rates, calculated using total prisoner deaths and populations (see below).') st.markdown('<h4>US State Prison Populations</h4>', unsafe_allow_html = True) st.write(prison_pop_data) st.markdown('[Data](https://github.com/themarshallproject/COVID_prison_data) from The Marshall Project, a nonprofit investigative newsroom dedicated to the U.S. criminal justice system. Here, "april_pop" refers to state prison populations (retrieved as close to April 15 as possible), while "as_of_date" refers to the actual retrieval date.') st.markdown('<h4>COVID-19 in US States</h4>', unsafe_allow_html = True) st.write(covid_data) st.markdown('[Data](https://github.com/CSSEGISandData/COVID-19) from the COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. Here, "Confirmed" refers to confirmed COVID-19 cases in US states, "Deaths" refers to recorded deaths due to COVID-19, "Incident_Rate" refers to confirmed cases per 100000 persons, and "State_MR" refers to estimated mortality rates, calculated using deaths and populations (found by algebraically manipulating "Incident_Rate").') st.markdown('<h4>Side-by-Side Comparison</h4>', unsafe_allow_html = True) st.write(combined_data) # Explanation of epidemiological terms, potential problems, and other discussion st.markdown('<h3>Epidemiological terms, caveats, discussion</h3>', unsafe_allow_html = True) st.markdown('Mortality rate is an epidemiological measure of the frequency of death in a population due to a disease. A formula for mortality rate is as follows: <i>number of recorded deaths * 100000 / population</i>.', unsafe_allow_html = True) st.write('Some caveats include: (1) underreporting, (2) at any given moment, the instantaneous numbers may not reflect the ultimate numbers (e.g. uncertainty regarding ultimate number of deaths).') st.write('Also note: federal prisons were excluded from these analyses, since the Marshall data placed them in a separate category (rather than grouping them with their state\'s data). The Marshall data did not include D.C. data, so D.C. was also omitted from these analyses. Finally&#8212I\'m assuming due to some sizing or rendering error&#8212some bars of the bar charts inside the map floated just above their zerolines; to fix this, I offset the y-ranges by a tiny amount. The map is only intended to show relative heights, and the scale of each bar chart is small enough that the offset doesn\'t make a discernable difference, but nonetheless, I\'m not sure if this is bad practice? (Feel free to roast me if it is.)') st.write('In addition, prison mortality rates were estimated using population figures retrieved as early as January 2020.') st.markdown('<b>The US has a mass incarceration problem.</b> Of all the prisoners in the world, 20% are held in the US ([Source](https://www.prisonpolicy.org/blog/2020/01/16/percent-incarcerated/)). And over the course of the COVID-19 pandemic, many prisons have failed to take adequate measures to protect prisoners from the disease.', unsafe_allow_html = True)

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5

47a1eb285893e3168ac7729e0382a1bf7d87ad7d

60

py

Python

py/exts/assetimport_maya/importer/__init__.py

ddesmond/assetexchange

0f8133b449b41595e22f27f3970bec7ebeee19c1

[ "MIT" ]

null

py/exts/assetimport_maya/importer/__init__.py

ddesmond/assetexchange

0f8133b449b41595e22f27f3970bec7ebeee19c1

[ "MIT" ]

null

py/exts/assetimport_maya/importer/__init__.py

ddesmond/assetexchange

0f8133b449b41595e22f27f3970bec7ebeee19c1

[ "MIT" ]

null

from .environment_hdri import * from .surface_maps import *

20

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0

1

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5

47bf9b35407609f45b5300c94b488ec713d3c0b2

72

py

Python

app/models/__init__.py

Text-Analysis/doc-gost-api

b89e0181b92334ae40de55b54301e3806c746f91

[ "MIT" ]

null

app/models/__init__.py

Text-Analysis/doc-gost-api

b89e0181b92334ae40de55b54301e3806c746f91

[ "MIT" ]

null

app/models/__init__.py

Text-Analysis/doc-gost-api

b89e0181b92334ae40de55b54301e3806c746f91

[ "MIT" ]

null

from .parserwrapper import ParserWrapper from .database import Database

24

40

0.861111

8

72

7.75

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0.111111

72

2

41

36

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null

0

1

0

1

0

1

0

5

47bfb5fae9bd48c56774ded98f80e809d38275ed

303

py

Python

setup.py

ripper479/Probability_Distributions

66ea1f49786ef81063e80181228cfcee1a2ba16f

[ "MIT" ]

null

setup.py

ripper479/Probability_Distributions

66ea1f49786ef81063e80181228cfcee1a2ba16f

[ "MIT" ]

null

setup.py

ripper479/Probability_Distributions

66ea1f49786ef81063e80181228cfcee1a2ba16f

[ "MIT" ]

null

from setuptools import setup setup(name='probability_distributions_2020_1', version='0.1', description='Probability distributions', author='Sourav Sharma' , author_email = 'sourav.sharma479@gmail.com' , packages=['probability_distributions_2020_1'], zip_safe=False)

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5

47d3bb9855dcc95ac757b3ece2c4b3588b1e8011

33

py

Python

basic_data_structure_01/__init__.py

lhf860/leetcode_python

084d6e39f64271663962589b158f68e90359812a

[ "Apache-2.0" ]

null

basic_data_structure_01/__init__.py

lhf860/leetcode_python

084d6e39f64271663962589b158f68e90359812a

[ "Apache-2.0" ]

null

basic_data_structure_01/__init__.py

lhf860/leetcode_python

084d6e39f64271663962589b158f68e90359812a

[ "Apache-2.0" ]

null

from collections import deque

6.6

29

0.787879

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33

6.5

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33

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8.25

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null

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1

0

1

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5

9a46dde37016f3c838760b6a1abc37e8d8ea6e1e

551

py

Python

reposicao/views.py

Carlosdher/backup

7bd5bf599397b36fd2d2f94053b476ec8a0b6f16

[ "MIT" ]

null

reposicao/views.py

Carlosdher/backup

7bd5bf599397b36fd2d2f94053b476ec8a0b6f16

[ "MIT" ]

null

reposicao/views.py

Carlosdher/backup

7bd5bf599397b36fd2d2f94053b476ec8a0b6f16

[ "MIT" ]

null

from django.shortcuts import render def home(request): template_name = 'home.html' return render(request,template_name) def reposicao(request): template_name = 'formreposicao.html' return render(request,template_name) def historico(request): template_name = 'historico.html' return render(request,template_name) def adiantamento(request): template_name = 'formadiantamento.html' return render(request,template_name) def troca(request): template_name = 'formtroca.html' return render(request,template_name)

25.045455

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551

21

44

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null

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5

9a492a1dcd7255fe646ff01f52928c14b357f595

57

py

Python

rocks_quarry/__main__.py

Agilicus/rocks-quarry

6aad1e45c1185d354409e193f6762177ac9a25b8

[ "Apache-2.0" ]

null

rocks_quarry/__main__.py

Agilicus/rocks-quarry

6aad1e45c1185d354409e193f6762177ac9a25b8

[ "Apache-2.0" ]

null

rocks_quarry/__main__.py

Agilicus/rocks-quarry

6aad1e45c1185d354409e193f6762177ac9a25b8

[ "Apache-2.0" ]

null

from rocks_quarry import server_main server_main.main()

14.25

36

0.842105

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57

5

0.666667

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0

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57

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true

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null

0

1

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5

7bd551a305cbb648268e2c92d3d2ba501f7ebebe

50

py

Python

i learned on py.py

genelorenzSarmiento0408/what-i-learned

5126e257e554438523c59749ca1bbbd8c4145cb8

[ "CC0-1.0" ]

null

i learned on py.py

genelorenzSarmiento0408/what-i-learned

5126e257e554438523c59749ca1bbbd8c4145cb8

[ "CC0-1.0" ]

null

i learned on py.py

genelorenzSarmiento0408/what-i-learned

5126e257e554438523c59749ca1bbbd8c4145cb8

[ "CC0-1.0" ]

null

import tkinker from * print("The more you learm")

16.666667

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d00cc7cd9402989ca7d5ae939a0c597d37e8a97a

250

py

Python

whynot/simulators/world3/__init__.py

yoshavit/whynot

e33e56bae377b65fe87feac5c6246ae38f4586e8

[ "MIT" ]

376

2020-03-20T20:09:16.000Z

2022-03-29T09:53:33.000Z

whynot/simulators/world3/__init__.py

mrtzh/whynot

0668f0a0c1e80defec6e4678f85ed60f45226477

[ "MIT" ]

5

2020-04-20T10:19:34.000Z

2021-11-03T09:36:28.000Z

whynot/simulators/world3/__init__.py

mrtzh/whynot

0668f0a0c1e80defec6e4678f85ed60f45226477

[ "MIT" ]

41

2020-03-20T23:14:38.000Z

2022-03-09T06:02:01.000Z

"""World3 initialization.""" from whynot.simulators.world3.simulator import Config, Intervention, simulate, State from whynot.simulators.world3.experiments import * from whynot.simulators.world3.environments import * SUPPORTS_CAUSAL_GRAPHS = False

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null

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1

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5

d047c1bec1519fe864f5b52eedbdc26bf22c1d80

28

py

Python

users/__init__.py

perrycharlton/forms

4e2d18538a0b08ebdd88a4ddad8fb614f04b1a51

[ "MIT" ]

null

users/__init__.py

perrycharlton/forms

4e2d18538a0b08ebdd88a4ddad8fb614f04b1a51

[ "MIT" ]

null

users/__init__.py

perrycharlton/forms

4e2d18538a0b08ebdd88a4ddad8fb614f04b1a51

[ "MIT" ]

null

from .UserViews import user

14

27

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1

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0.958333

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