hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c6bbceea046b476c39627d5d6f8b471ec4d99673
| 75
|
py
|
Python
|
tno/mpc/encryption_schemes/templates/test/__init__.py
|
TNO-MPC/encryption_schemes.templates
|
fa2f25ba513d9c00bd79c08af7f6720131ea174f
|
[
"Apache-2.0"
] | null | null | null |
tno/mpc/encryption_schemes/templates/test/__init__.py
|
TNO-MPC/encryption_schemes.templates
|
fa2f25ba513d9c00bd79c08af7f6720131ea174f
|
[
"Apache-2.0"
] | null | null | null |
tno/mpc/encryption_schemes/templates/test/__init__.py
|
TNO-MPC/encryption_schemes.templates
|
fa2f25ba513d9c00bd79c08af7f6720131ea174f
|
[
"Apache-2.0"
] | null | null | null |
"""
Testing module of the tno.mpc.encryption_schemes.templates library
"""
| 18.75
| 66
| 0.773333
| 10
| 75
| 5.7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106667
| 75
| 3
| 67
| 25
| 0.850746
| 0.88
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05b1a8f89a65070bb3fc8824abde9b4efb9f7abf
| 124
|
py
|
Python
|
02_basic_data_types/02_using_variables.py
|
r7asmu7s/art_of_doing_python
|
62a03bcca084046c319976fc308bf3de3a2d412d
|
[
"Unlicense"
] | null | null | null |
02_basic_data_types/02_using_variables.py
|
r7asmu7s/art_of_doing_python
|
62a03bcca084046c319976fc308bf3de3a2d412d
|
[
"Unlicense"
] | null | null | null |
02_basic_data_types/02_using_variables.py
|
r7asmu7s/art_of_doing_python
|
62a03bcca084046c319976fc308bf3de3a2d412d
|
[
"Unlicense"
] | null | null | null |
x = 5
print(5)
print(x)
print('x')
message = 'Hello World!'
print(message)
message = 'Goodbye cruel world...'
print(message)
| 15.5
| 34
| 0.685484
| 19
| 124
| 4.473684
| 0.421053
| 0.141176
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018519
| 0.129032
| 124
| 8
| 35
| 15.5
| 0.768519
| 0
| 0
| 0.25
| 0
| 0
| 0.28
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.625
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
05bacfe8c4886b876a1bd9efa7341550b5a14050
| 175
|
py
|
Python
|
036.py
|
xianlinfeng/project_euler_python3
|
77eca44eb2b1d13bc70d6dc0258b737449d43a23
|
[
"MIT"
] | null | null | null |
036.py
|
xianlinfeng/project_euler_python3
|
77eca44eb2b1d13bc70d6dc0258b737449d43a23
|
[
"MIT"
] | null | null | null |
036.py
|
xianlinfeng/project_euler_python3
|
77eca44eb2b1d13bc70d6dc0258b737449d43a23
|
[
"MIT"
] | null | null | null |
import eulerlib
if __name__ == "__main__":
ans = sum(i for i in range(1, 1000000) if eulerlib.is_palindrome(
i) and eulerlib.is_palindrome(i, 2))
print(ans)
| 21.875
| 69
| 0.662857
| 27
| 175
| 3.925926
| 0.666667
| 0.188679
| 0.377358
| 0.396226
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066176
| 0.222857
| 175
| 7
| 70
| 25
| 0.713235
| 0
| 0
| 0
| 0
| 0
| 0.045714
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0.2
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05bc6fa82c293b18db5024a19838e33a177f9ce6
| 219
|
py
|
Python
|
recommender.py
|
dina-deifallah/dummy_recommender
|
de7d7642187631ccc4cae383968c33554add4e18
|
[
"MIT"
] | null | null | null |
recommender.py
|
dina-deifallah/dummy_recommender
|
de7d7642187631ccc4cae383968c33554add4e18
|
[
"MIT"
] | null | null | null |
recommender.py
|
dina-deifallah/dummy_recommender
|
de7d7642187631ccc4cae383968c33554add4e18
|
[
"MIT"
] | null | null | null |
'''
dummy recommender
'''
def recommend_random(movies, k=10):
"""
Dummy recommender that recommends a list of random movies. Ignores the actual query.
"""
return movies['title'].sample(k).to_list()
| 21.9
| 88
| 0.6621
| 28
| 219
| 5.107143
| 0.75
| 0.223776
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011494
| 0.205479
| 219
| 10
| 89
| 21.9
| 0.810345
| 0.465753
| 0
| 0
| 0
| 0
| 0.052632
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
05c3746b198d717cee8970409e94865d5078ccca
| 192
|
py
|
Python
|
ch6/9 text widget.py
|
PacktPublishing/Learning-Jupyter
|
734ef16ade5f9874e5187e483746524a675bf915
|
[
"MIT"
] | 11
|
2017-02-02T08:47:32.000Z
|
2021-09-15T18:04:01.000Z
|
ch6/9 text widget.py
|
PacktPublishing/Learning-Jupyter
|
734ef16ade5f9874e5187e483746524a675bf915
|
[
"MIT"
] | 2
|
2016-12-02T04:43:11.000Z
|
2016-12-02T04:43:57.000Z
|
ch6/9 text widget.py
|
PacktPublishing/Learning-Jupyter
|
734ef16ade5f9874e5187e483746524a675bf915
|
[
"MIT"
] | 8
|
2016-12-02T04:39:10.000Z
|
2018-04-01T22:58:19.000Z
|
from ipywidgets import widgets
from IPython.display import display
text.on_submit(handle_submit)
display(text)
def handle_submit(sender):
print(text.value)
text.on_submit(handle_submit)
| 19.2
| 35
| 0.817708
| 28
| 192
| 5.428571
| 0.5
| 0.236842
| 0.157895
| 0.236842
| 0.315789
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.104167
| 192
| 9
| 36
| 21.333333
| 0.883721
| 0
| 0
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.285714
| 0
| 0.428571
| 0.142857
| 1
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05dc17a49e0aa924488fd1ddb2e0d45ffd1b80ce
| 1,727
|
py
|
Python
|
weatherstation/mainland/datamanagement/datagatherer.py
|
Risocos/WeatherStation-WEB
|
73a4a55699694b6b639abeb0ddf90c96e382f847
|
[
"MIT"
] | null | null | null |
weatherstation/mainland/datamanagement/datagatherer.py
|
Risocos/WeatherStation-WEB
|
73a4a55699694b6b639abeb0ddf90c96e382f847
|
[
"MIT"
] | null | null | null |
weatherstation/mainland/datamanagement/datagatherer.py
|
Risocos/WeatherStation-WEB
|
73a4a55699694b6b639abeb0ddf90c96e382f847
|
[
"MIT"
] | null | null | null |
import random
class DataGatherer:
def __init__(self):
pass
@staticmethod
def get_temperature_data():
# TODO: read actual data from station folders
# for datefolder in datefolders:
# for stationfolder in datefolder:
# for hourfile in stationfolder:
def data():
""" Temperature between 15 and 30 degrees """
return [round(random.uniform(15, 30), 2) for x in range(7)]
return [data() for x in range(3)]
# measurement_list = []
# for i in range(21):
# measurement = Measurement()
# measurement.temperature = random.randint(0, 40)
# measurement_list.append(measurement.temperature)
#
# chart_list = []
# for measurements in measurement_list:
# chart_list.append(measurements)
#
# return [chart_list]
@staticmethod
def get_wind_data():
# TODO: read actual data from folders
# for datefolder in datefolders:
# for stationfolder in datefolder:
# for hourfile in stationfolder:
def data():
""" Wind is between 25 and 40 """
return [round(random.uniform(25, 40), 2) for x in range(10)]
return [data() for x in range(3)]
@staticmethod
def get_rainfall_data():
# TODO: read actual rainfall data
# for datefolder in datefolders:
# for stationfolder in datefolder:
# for hourfile in stationfolder:
def data():
""" Rainfall between 0 and 5 """
return [round(random.uniform(0, 5), 2) for x in range(10)]
return [data() for x in range(3)]
| 29.271186
| 72
| 0.565142
| 191
| 1,727
| 5.026178
| 0.277487
| 0.051042
| 0.0375
| 0.06875
| 0.451042
| 0.438542
| 0.384375
| 0.361458
| 0.361458
| 0.361458
| 0
| 0.031774
| 0.343949
| 1,727
| 58
| 73
| 29.775862
| 0.815534
| 0.471338
| 0
| 0.473684
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017241
| 0
| 1
| 0.368421
| false
| 0.052632
| 0.052632
| 0
| 0.789474
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
05ddd22e9f2c2783b5628ec7d23ccd67ac71eee5
| 4,084
|
py
|
Python
|
src/tf_ops/nn_distance/tf_nndistance_test.py
|
minghanz/monopsr
|
f3cb31909666012dfcf38e5fe0b0f6feb3801560
|
[
"MIT"
] | 104
|
2019-08-13T01:26:19.000Z
|
2022-03-30T12:08:00.000Z
|
src/tf_ops/nn_distance/tf_nndistance_test.py
|
weidezhang/monopsr
|
e194d2547f10e7ab50d786762dcf9f5619069ce8
|
[
"MIT"
] | 5
|
2020-01-28T22:16:24.000Z
|
2022-02-09T23:33:07.000Z
|
src/tf_ops/nn_distance/tf_nndistance_test.py
|
weidezhang/monopsr
|
e194d2547f10e7ab50d786762dcf9f5619069ce8
|
[
"MIT"
] | 25
|
2019-08-12T23:31:40.000Z
|
2022-02-12T02:27:12.000Z
|
import unittest
import numpy as np
import tensorflow as tf
from tf_ops.nn_distance import tf_nndistance
from monopsr.core import distance_metrics
class NearestNeighborTest(unittest.TestCase):
def test_nn_distance(self):
"""Test for nearest neighbor algorithm where distance should be 0.
"""
# Create test point clouds of shape [batch_size, n_points, 3]
point_cloud_1 = [[[1., 1., 1.], [2., 2., 2.], [3., 3., 3.]]]
point_cloud_2 = [[[1., 1., 1.], [2., 2., 2.], [3., 3., 3.]]]
tf_point_cloud_1 = tf.constant(point_cloud_1)
tf_point_cloud_2 = tf.constant(point_cloud_2)
dist1, idx1, dist2, idx2 = tf_nndistance.nn_distance(tf_point_cloud_1, tf_point_cloud_2)
with tf.Session() as sess:
dist1, idx1 = sess.run([dist1, idx1])
np.testing.assert_almost_equal(np.sum(dist1), 0)
np.testing.assert_equal(idx1, [[0, 1, 2]])
def test_nn_distance_2(self):
"""Test for nearest neighbor algorithm where distance is non-zero.
"""
# Create test point clouds of shape [batch_size, n_points, 3]
point_cloud_1 = [[[1., 1., 1.], [2., 2., 2.], [3., 3., 3.]]]
point_cloud_2 = [[[1., 1., 1.], [2., 2., 2.]]]
tf_point_cloud_1 = tf.constant(point_cloud_1)
tf_point_cloud_2 = tf.constant(point_cloud_2)
dist1, idx1, dist2, idx2 = tf_nndistance.nn_distance(tf_point_cloud_1, tf_point_cloud_2)
with tf.Session() as sess:
dist1, idx1 = sess.run([dist1, idx1])
np.testing.assert_almost_equal(np.sum(dist1), 3.0)
np.testing.assert_equal(idx1, [[0, 1, 1]])
def test_nn_distance_negative(self):
"""Test negative point cloud values for computing nearest neighbor squared distance.
"""
# Create test point clouds of shape [batch_size, n_points, 3]
point_cloud_1 = [[[-2., 2., -2.], [1., 3., 4.]]]
point_cloud_2 = [[[2., 0., 2.], [3., -5., 7.]]]
tf_point_cloud_1 = tf.constant(point_cloud_1)
tf_point_cloud_2 = tf.constant(point_cloud_2)
dist1, idx1, dist2, idx2 = tf_nndistance.nn_distance(tf_point_cloud_1, tf_point_cloud_2)
with tf.Session() as sess:
dist1, idx1 = sess.run([dist1, idx1])
np.testing.assert_almost_equal(np.sum(dist1), 50.0)
def test_nn_distance_batch(self):
"""Tests batches for computing nearest neighbor squared distance.
"""
# Create test point clouds of shape [batch_size, n_points, 3]
point_cloud_1 = [[[1., 1., 1.], [2., 2., 2.], [3., 3., 3.]],
[[1., 1., 1.], [2., 2., 2.], [3., 3., 3.]]]
point_cloud_2 = [[[1., 0., 1.], [2., 0., 2.], [3., 0., 3.]],
[[4., 4., 4.], [2., 2., 2.], [3., 3., 3.]]]
tf_point_cloud_1 = tf.constant(point_cloud_1)
tf_point_cloud_2 = tf.constant(point_cloud_2)
dist1, idx1, dist2, idx2 = tf_nndistance.nn_distance(tf_point_cloud_1, tf_point_cloud_2)
with tf.Session() as sess:
dist1, idx1 = sess.run([dist1, idx1])
np.testing.assert_almost_equal(np.sum(dist1, axis=1), [14.0, 3.0])
def test_sklearn_vs_tf_nn_calc(self):
"""Test to see if our implementation of chamfer distance produces same result as sklearn
"""
# Create test point clouds of shape [batch_size, n_points, 3]
point_cloud_1 = [[[1., 1., 1.], [2., 2., 2.], [1., 5., 7.]]]
point_cloud_2 = [[[1., 5., 7.], [10., 0., 5.]]]
tf_point_cloud_1 = tf.constant(point_cloud_1)
tf_point_cloud_2 = tf.constant(point_cloud_2)
dist1, idx1, dist2, idx2 = tf_nndistance.nn_distance(tf_point_cloud_1, tf_point_cloud_2)
with tf.Session() as sess:
dist1, idx1, dist2, idx2 = sess.run([dist1, idx1, dist2, idx2])
chamfer_dist_calc1 = np.sum(dist1) + np.sum(dist2)
chamfer_dist_calc2 = distance_metrics.calc_chamfer_dist(point_cloud_1[0], point_cloud_2[0])
np.testing.assert_approx_equal(chamfer_dist_calc1, chamfer_dist_calc2)
| 38.168224
| 99
| 0.606024
| 617
| 4,084
| 3.740681
| 0.142626
| 0.186308
| 0.100087
| 0.084489
| 0.707972
| 0.705806
| 0.705806
| 0.705806
| 0.640815
| 0.640815
| 0
| 0.071891
| 0.243879
| 4,084
| 106
| 100
| 38.528302
| 0.675518
| 0.17238
| 0
| 0.45614
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.122807
| 1
| 0.087719
| false
| 0
| 0.087719
| 0
| 0.192982
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05e244ab8d96ba413b68b7a0546e05d7e29fd581
| 190
|
py
|
Python
|
exercises/oops.py
|
jashwanthp/template-python-django
|
627c5df8eb4ea2b92729809c0b678b62c9120b32
|
[
"MIT"
] | null | null | null |
exercises/oops.py
|
jashwanthp/template-python-django
|
627c5df8eb4ea2b92729809c0b678b62c9120b32
|
[
"MIT"
] | null | null | null |
exercises/oops.py
|
jashwanthp/template-python-django
|
627c5df8eb4ea2b92729809c0b678b62c9120b32
|
[
"MIT"
] | null | null | null |
class Vehicle:
def __init__(self, max_speed, mileage):
self.max_speed = max_speed
self.mileage = mileage
modelS = Vehicle(200,20)
print(modelS.max_speed, modelS.mileage)
| 27.142857
| 43
| 0.705263
| 26
| 190
| 4.846154
| 0.461538
| 0.253968
| 0.190476
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.03268
| 0.194737
| 190
| 7
| 44
| 27.142857
| 0.79085
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0
| 0
| 0.333333
| 0.166667
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05fac2d95a89d871466ffb95a3d301130253d727
| 3,143
|
py
|
Python
|
scalpr/database/ticker.py
|
TvanMeer/scalpr
|
c4d2e07da60663f77c3d17875aa61ad9d215a08d
|
[
"MIT"
] | 1
|
2022-02-14T22:48:58.000Z
|
2022-02-14T22:48:58.000Z
|
scalpr/database/ticker.py
|
TvanMeer/scalpr
|
c4d2e07da60663f77c3d17875aa61ad9d215a08d
|
[
"MIT"
] | null | null | null |
scalpr/database/ticker.py
|
TvanMeer/scalpr
|
c4d2e07da60663f77c3d17875aa61ad9d215a08d
|
[
"MIT"
] | 1
|
2022-02-14T22:49:01.000Z
|
2022-02-14T22:49:01.000Z
|
# pylint: disable=no-name-in-module
from datetime import datetime
from pydantic import BaseModel
from pydantic.types import PositiveInt, condecimal
class MiniTicker(BaseModel):
"""24 hour rolling window statistics.
{
"e": "24hrMiniTicker", // Event type
"E": 123456789, // Event time
"s": "BNBBTC", // Symbol
"c": "0.0025", // Close price
"o": "0.0010", // Open price
"h": "0.0025", // High price
"l": "0.0010", // Low price
"v": "10000", // Total traded base asset volume
"q": "18" // Total traded quote asset volume
}
"""
event_time: datetime # E
current_price: condecimal(decimal_places=8) # c
price_24_hours_ago: condecimal(decimal_places=8) # o
high_price_last_24h: condecimal(decimal_places=8) # h
low_price_last_24h: condecimal(decimal_places=8) # l
base_volume_last_24h: condecimal(decimal_places=8) # v
quote_volume_last_24h: condecimal(decimal_places=8) # q
class Ticker(BaseModel):
"""Extended 24 hour rolling window statistics.
{
"e": "24hrTicker", // Event type
"E": 123456789, // Event time
"s": "BNBBTC", // Symbol
"p": "0.0015", // Price change
"P": "250.00", // Price change percent
"w": "0.0018", // Weighted average price
"x": "0.0009", // First trade(F)-1 price (first trade before the 24hr rolling window)
"c": "0.0025", // Last price
"Q": "10", // Last quantity
"b": "0.0024", // Best bid price
"B": "10", // Best bid quantity
"a": "0.0026", // Best ask price
"A": "100", // Best ask quantity
"o": "0.0010", // Open price
"h": "0.0025", // High price
"l": "0.0010", // Low price
"v": "10000", // Total traded base asset volume
"q": "18", // Total traded quote asset volume
"O": 0, // Statistics open time
"C": 86400000, // Statistics close time
"F": 0, // First trade ID
"L": 18150, // Last trade Id
"n": 18151 // Total number of trades
}
"""
event_time: datetime # E
current_price: condecimal(decimal_places=8) # c
price_24_hours_ago: condecimal(decimal_places=8) # o
high_price_last_24h: condecimal(decimal_places=8) # h
low_price_last_24h: condecimal(decimal_places=8) # l
weighted_avg_price_last_24h: condecimal(decimal_places=8) # w
price_change_last_24h: condecimal(decimal_places=8) # p
price_change_last_24h_percent: condecimal(decimal_places=3) # P
base_volume_last_24h: condecimal(decimal_places=8) # v
quote_volume_last_24h: condecimal(decimal_places=8) # q
n_trades_last_24h: PositiveInt # n
| 40.294872
| 98
| 0.526567
| 358
| 3,143
| 4.446927
| 0.284916
| 0.160176
| 0.216709
| 0.211055
| 0.592337
| 0.592337
| 0.535176
| 0.512563
| 0.512563
| 0.461055
| 0
| 0.090281
| 0.355075
| 3,143
| 77
| 99
| 40.818182
| 0.695116
| 0.51384
| 0
| 0.608696
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.130435
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
af03a909a2443bc59aa1f59570756d37269aac99
| 176
|
py
|
Python
|
pages/workshop/Metpy_Introduction/solutions/temperature_change.py
|
zbruick/python-training
|
ba227820accb5849aea8d05ff5cb5c134f56955e
|
[
"BSD-3-Clause"
] | 87
|
2019-08-29T06:54:06.000Z
|
2022-03-14T12:52:59.000Z
|
pages/workshop/Metpy_Introduction/solutions/temperature_change.py
|
zbruick/python-training
|
ba227820accb5849aea8d05ff5cb5c134f56955e
|
[
"BSD-3-Clause"
] | 258
|
2015-02-02T20:49:11.000Z
|
2018-10-04T22:04:47.000Z
|
pages/workshop/Metpy_Introduction/solutions/temperature_change.py
|
zbruick/python-training
|
ba227820accb5849aea8d05ff5cb5c134f56955e
|
[
"BSD-3-Clause"
] | 65
|
2015-02-04T18:48:42.000Z
|
2018-10-03T18:33:39.000Z
|
temperature_change_rate = -2.3 * units.delta_degF / (10 * units.minutes)
temperature = 25 * units.degC
dt = 1.5 * units.hours
print(temperature + temperature_change_rate * dt)
| 35.2
| 72
| 0.744318
| 26
| 176
| 4.846154
| 0.653846
| 0.269841
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052632
| 0.136364
| 176
| 4
| 73
| 44
| 0.776316
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
af1035572c941f93ec9fa5c623462723ec119689
| 167
|
py
|
Python
|
tests/test_cli/model.py
|
csdms/model_metadata
|
62acab7ae2a152bec64bc1f52751f7a8aa1d4184
|
[
"MIT"
] | 1
|
2021-05-25T14:38:10.000Z
|
2021-05-25T14:38:10.000Z
|
tests/test_cli/model.py
|
csdms/model_metadata
|
62acab7ae2a152bec64bc1f52751f7a8aa1d4184
|
[
"MIT"
] | 3
|
2018-04-05T21:50:24.000Z
|
2021-04-02T03:54:04.000Z
|
tests/test_cli/model.py
|
csdms/model_metadata
|
62acab7ae2a152bec64bc1f52751f7a8aa1d4184
|
[
"MIT"
] | null | null | null |
import pathlib
class ModelString:
METADATA = "."
class ModelPath:
METADATA = pathlib.Path(".")
class ModelAbsolutePath:
METADATA = pathlib.Path("/")
| 11.928571
| 32
| 0.664671
| 15
| 167
| 7.4
| 0.533333
| 0.27027
| 0.342342
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.209581
| 167
| 13
| 33
| 12.846154
| 0.840909
| 0
| 0
| 0
| 0
| 0
| 0.017964
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.142857
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
af19ffbdd3e1800a9174efb79812e43ee3c415fb
| 751
|
py
|
Python
|
project/fs/fs_exceptions.py
|
cj8-cheerful-cheetas/project
|
5d9c7cfc2cfec5fca05997bc42d490529cd935ab
|
[
"MIT"
] | null | null | null |
project/fs/fs_exceptions.py
|
cj8-cheerful-cheetas/project
|
5d9c7cfc2cfec5fca05997bc42d490529cd935ab
|
[
"MIT"
] | 3
|
2021-07-17T10:52:21.000Z
|
2021-07-17T10:55:54.000Z
|
project/fs/fs_exceptions.py
|
cj8-cheerful-cheetas/project
|
5d9c7cfc2cfec5fca05997bc42d490529cd935ab
|
[
"MIT"
] | 2
|
2021-07-17T10:54:33.000Z
|
2021-08-30T19:27:49.000Z
|
class NoSuchFileOrDirectory(Exception):
def __init__(self):
super().__init__("no such file or directory")
class FileOrDirectoryAlreadyExist(Exception):
def __init__(self):
super().__init__("file or directory already exist")
class NotAnDirectory(Exception):
def __init__(self):
super().__init__("not an directory")
class NotAnFile(Exception):
def __init__(self):
super().__init__("not an file")
class NotAnIntiger(Exception):
def __init__(self):
super().__init__("not an intiger")
class PermisionDenied(Exception):
def __init__(self):
super().__init__("permision denied")
class NoSuchIndex(Exception):
def __init__(self):
super().__init__("no such index")
| 22.088235
| 59
| 0.681758
| 80
| 751
| 5.7
| 0.325
| 0.184211
| 0.245614
| 0.307018
| 0.504386
| 0.504386
| 0.377193
| 0.377193
| 0
| 0
| 0
| 0
| 0.197071
| 751
| 33
| 60
| 22.757576
| 0.756219
| 0
| 0
| 0.333333
| 0
| 0
| 0.167776
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
af4efe60a883fc6b9b9d86591c97d0706b8abb01
| 113
|
py
|
Python
|
idlib/systems/urn.py
|
tgbugs/idlib
|
4760322b023cc38a8f6800141fe8735d10fa014a
|
[
"MIT"
] | 2
|
2021-11-28T23:52:48.000Z
|
2022-02-17T18:12:32.000Z
|
idlib/systems/urn.py
|
tgbugs/idlib
|
4760322b023cc38a8f6800141fe8735d10fa014a
|
[
"MIT"
] | 2
|
2020-05-22T10:40:58.000Z
|
2022-01-05T22:38:06.000Z
|
idlib/systems/urn.py
|
tgbugs/idlib
|
4760322b023cc38a8f6800141fe8735d10fa014a
|
[
"MIT"
] | null | null | null |
import idlib
from idlib import families
class Urn(idlib.Identifier):
""" """
_family = families.IETF
| 11.3
| 28
| 0.672566
| 13
| 113
| 5.769231
| 0.692308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.221239
| 113
| 9
| 29
| 12.555556
| 0.852273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
af627db44ca4b1c8efa047c6013ab07fdc4ec734
| 171
|
py
|
Python
|
expykit/os/clipboard/__init__.py
|
fakegit/mo-han-toolbox
|
9d5bbc1fe7f12040715d3a0d3f320a1ad617aed8
|
[
"MIT"
] | 24
|
2019-12-08T03:56:32.000Z
|
2021-10-02T13:26:37.000Z
|
expykit/os/clipboard/__init__.py
|
fakegit/mo-han-toolbox
|
9d5bbc1fe7f12040715d3a0d3f320a1ad617aed8
|
[
"MIT"
] | 2
|
2020-04-27T14:20:01.000Z
|
2020-07-17T06:05:33.000Z
|
expykit/os/clipboard/__init__.py
|
fakegit/mo-han-toolbox
|
9d5bbc1fe7f12040715d3a0d3f320a1ad617aed8
|
[
"MIT"
] | 10
|
2019-08-06T01:11:28.000Z
|
2021-07-19T08:45:11.000Z
|
#!/usr/bin/env python3
import os as _os
if _os.name == 'nt':
from .nt import *
elif _os.name == 'posix':
from .posix import *
else:
raise NotImplementedError
| 17.1
| 29
| 0.649123
| 25
| 171
| 4.32
| 0.64
| 0.111111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007519
| 0.222222
| 171
| 9
| 30
| 19
| 0.804511
| 0.122807
| 0
| 0
| 0
| 0
| 0.04698
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.428571
| 0
| 0.428571
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
af70565f0994c219913f2986623ebe387a29747b
| 493
|
py
|
Python
|
adapter_tools/tests/SS2/metadata_analysis/input_data.py
|
broadinstitute/hca-adapter-tools
|
55b69d28fd4c88e5551df46cc67b6596271c2ab6
|
[
"BSD-3-Clause"
] | null | null | null |
adapter_tools/tests/SS2/metadata_analysis/input_data.py
|
broadinstitute/hca-adapter-tools
|
55b69d28fd4c88e5551df46cc67b6596271c2ab6
|
[
"BSD-3-Clause"
] | null | null | null |
adapter_tools/tests/SS2/metadata_analysis/input_data.py
|
broadinstitute/hca-adapter-tools
|
55b69d28fd4c88e5551df46cc67b6596271c2ab6
|
[
"BSD-3-Clause"
] | null | null | null |
# Instead of parsing cromwell metadata we pass the intermediate SS2 files
ANALYSIS_FILE_INPUT = {
"input_uuid": "0244354d-cf37-4483-8db3-425b7e504ca6",
"input_file": "",
"pipeline_type": "SS2",
"workspace_version": "2021-10-19T17:43:52.000000Z",
"ss2_bam_file": "call-HISAT2PairedEnd/cacheCopy/0244354d-cf37-4483-8db3-425b7e504ca6_qc.bam",
"ss2_bai_file": "call-HISAT2PairedEnd/cacheCopy/0244354d-cf37-4483-8db3-425b7e504ca6_qc.bam.bai",
"project_level": False,
}
| 41.083333
| 101
| 0.738337
| 64
| 493
| 5.484375
| 0.609375
| 0.102564
| 0.136752
| 0.17094
| 0.48433
| 0.393162
| 0.393162
| 0.393162
| 0.393162
| 0.393162
| 0
| 0.218894
| 0.119675
| 493
| 11
| 102
| 44.818182
| 0.589862
| 0.144016
| 0
| 0
| 0
| 0
| 0.72619
| 0.511905
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
bb7a2d27e226c204be01f62bd4d1c8fe45d154df
| 130
|
py
|
Python
|
flask/flask_r_interpolaton/run_dev.py
|
andreipreda/py-r-interpolation
|
d7be5799b9cf1da95ce728c00eb0ce1c73bf4c02
|
[
"MIT"
] | null | null | null |
flask/flask_r_interpolaton/run_dev.py
|
andreipreda/py-r-interpolation
|
d7be5799b9cf1da95ce728c00eb0ce1c73bf4c02
|
[
"MIT"
] | 13
|
2019-12-26T17:31:05.000Z
|
2022-02-26T10:36:46.000Z
|
flask/flask_r_interpolaton/run_dev.py
|
andreipreda/py-r-interpolation
|
d7be5799b9cf1da95ce728c00eb0ce1c73bf4c02
|
[
"MIT"
] | null | null | null |
from app import create_app
from config import Config
dev_app = create_app(config=Config)
dev_app.run(host='localhost', port=7000)
| 26
| 40
| 0.807692
| 22
| 130
| 4.590909
| 0.5
| 0.178218
| 0.237624
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.034188
| 0.1
| 130
| 5
| 40
| 26
| 0.82906
| 0
| 0
| 0
| 0
| 0
| 0.068702
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
bb9cf83139e40fc7e3af40c380ee6c897a5f19d7
| 803
|
py
|
Python
|
logos.py
|
Titaniumtown/pyfetch
|
56887709cc0b5235603633cd92286eb0d595ce93
|
[
"MIT"
] | 2
|
2022-02-04T09:44:13.000Z
|
2022-02-10T21:00:09.000Z
|
logos.py
|
Titaniumtown/pyfetch
|
56887709cc0b5235603633cd92286eb0d595ce93
|
[
"MIT"
] | 1
|
2020-05-20T23:05:48.000Z
|
2020-05-25T02:59:39.000Z
|
logos.py
|
Titaniumtown/pyfetch
|
56887709cc0b5235603633cd92286eb0d595ce93
|
[
"MIT"
] | 4
|
2021-09-18T20:55:17.000Z
|
2022-03-30T04:00:03.000Z
|
logo_array = [['--------------------------------------',
'--------------------------------------',
'--------------------------------------',
'---\\\\\\\\\\\\\\\\\\\\\\\\-----------------------',
'----\\\\\\ \\\\\\----------------------',
'-----\\\\\\ \\\\\\---------------------',
'------\\\\\\ \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\------',
'-------\\\\\\ \\\\\\-----',
'--------\\\\\\ \\\\\\----',
'---------\\\\\\ ______ \\\\\\---',
'----------\\\\\\ ///---',
'-----------\\\\\\ ///----',
'------------\\\\\\ ///-----',
'-------------\\\\\\////////////////------',
'--------------------------------------',
'--------------------------------------',
'--------------------------------------']]
| 47.235294
| 61
| 0.019925
| 2
| 803
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.175592
| 803
| 17
| 62
| 47.235294
| 0.013595
| 0
| 0
| 0.235294
| 0
| 0
| 0.895522
| 0.514925
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
bbef613a358fdf050779577fef45484c36d24440
| 271
|
py
|
Python
|
snowflake/router/idservice.py
|
Indexical-Metrics-Measure-Advisory/watchmen-snowflake
|
e55db55f97c4f7509ac99c337fcaac8c7af74891
|
[
"MIT"
] | null | null | null |
snowflake/router/idservice.py
|
Indexical-Metrics-Measure-Advisory/watchmen-snowflake
|
e55db55f97c4f7509ac99c337fcaac8c7af74891
|
[
"MIT"
] | null | null | null |
snowflake/router/idservice.py
|
Indexical-Metrics-Measure-Advisory/watchmen-snowflake
|
e55db55f97c4f7509ac99c337fcaac8c7af74891
|
[
"MIT"
] | null | null | null |
import logging
from fastapi import APIRouter
from snowflake.core.snowflake import get_int_surrogate_key
router = APIRouter()
log = logging.getLogger("app." + __name__)
@router.get("/snowflakeid", tags=["snowflake"])
def next_id():
return get_int_surrogate_key()
| 19.357143
| 58
| 0.763838
| 35
| 271
| 5.6
| 0.628571
| 0.061224
| 0.153061
| 0.183673
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121771
| 271
| 13
| 59
| 20.846154
| 0.823529
| 0
| 0
| 0
| 0
| 0
| 0.092251
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.125
| false
| 0
| 0.375
| 0.125
| 0.625
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
bbf8d9d738b8a7fcb404fb0e52cac086922679f4
| 247
|
py
|
Python
|
FrameApp/flaskApp/module/rainModuleUser.py
|
Rainstyd/rainsty
|
9a0d5f46c20faf909c4194f315fb9960652cffc6
|
[
"Apache-2.0"
] | 1
|
2020-03-25T01:13:35.000Z
|
2020-03-25T01:13:35.000Z
|
FrameApp/flaskApp/module/rainModuleUser.py
|
Rainstyed/rainsty
|
f74e0ccaf16d1871c9d1870bd8a7c8a63243fcf5
|
[
"Apache-2.0"
] | 1
|
2022-01-06T23:49:21.000Z
|
2022-01-06T23:49:21.000Z
|
FrameApp/flaskApp/module/rainModuleUser.py
|
rainstyd/rainsty
|
9a0d5f46c20faf909c4194f315fb9960652cffc6
|
[
"Apache-2.0"
] | 1
|
2020-03-20T08:48:36.000Z
|
2020-03-20T08:48:36.000Z
|
# -*- coding: UTF-8 -*-
import sys
sys.path.append('./lib')
from raindborm import Model
from raindborm import Column
class rainModuleUser(Model):
username = Column('String', 'username', 255)
password = Column('String', 'password', 255)
| 20.583333
| 48
| 0.688259
| 30
| 247
| 5.666667
| 0.6
| 0.152941
| 0.223529
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.033654
| 0.157895
| 247
| 11
| 49
| 22.454545
| 0.783654
| 0.08502
| 0
| 0
| 0
| 0
| 0.147321
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.142857
| 0.428571
| 0
| 0.857143
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
|
0
| 4
|
a5739a8efb8276902638332538e2209a96a4f211
| 902
|
py
|
Python
|
python/origen/origen/timesets.py
|
Origen-SDK/o2
|
5b0f9a6d113ddebc73c7ee224931e8b2d0301794
|
[
"MIT"
] | null | null | null |
python/origen/origen/timesets.py
|
Origen-SDK/o2
|
5b0f9a6d113ddebc73c7ee224931e8b2d0301794
|
[
"MIT"
] | 127
|
2019-11-23T17:09:35.000Z
|
2021-09-02T11:06:20.000Z
|
python/origen/origen/timesets.py
|
Origen-SDK/o2
|
5b0f9a6d113ddebc73c7ee224931e8b2d0301794
|
[
"MIT"
] | null | null | null |
import origen
class Proxy:
def __init__(self, controller):
self.controller = controller
@property
def timesets(self):
return origen.dut.db.timesets(self.controller.model_id)
def add_timeset(self, name, period=None, **kwargs):
return origen.dut.db.add_timeset(self.controller.model_id, name,
period, **kwargs)
def timeset(self, name):
return origen.dut.db.timeset(self.controller.model_id, name)
@classmethod
def api(cls):
return [
'timesets',
'add_timeset',
'timeset',
]
class Loader:
def __init__(self, controller):
self.controller = controller
def Timeset(self, name, **kwargs):
return self.controller.add_timeset(name, **kwargs)
def api(self):
return {
"Timeset": self.Timeset,
}
| 23.128205
| 72
| 0.580931
| 96
| 902
| 5.302083
| 0.260417
| 0.220039
| 0.088409
| 0.100196
| 0.302554
| 0.302554
| 0.176817
| 0
| 0
| 0
| 0
| 0
| 0.31153
| 902
| 38
| 73
| 23.736842
| 0.819646
| 0
| 0
| 0.142857
| 0
| 0
| 0.036585
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.035714
| 0.214286
| 0.607143
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
a5a0f3e5b469211b49cba9178029999db7fd589e
| 262
|
py
|
Python
|
docs/source/examples/loop_2.py
|
astooke/gtimer
|
2146dab459e5d959feb291821733d3d3ba7c523c
|
[
"MIT"
] | 8
|
2016-09-08T05:40:40.000Z
|
2020-04-29T18:17:54.000Z
|
docs/source/examples/loop_2.py
|
astooke/gtimer
|
2146dab459e5d959feb291821733d3d3ba7c523c
|
[
"MIT"
] | 1
|
2022-01-27T13:11:58.000Z
|
2022-01-27T13:11:58.000Z
|
docs/source/examples/loop_2.py
|
astooke/gtimer
|
2146dab459e5d959feb291821733d3d3ba7c523c
|
[
"MIT"
] | null | null | null |
import gtimer as gt
import time
time.sleep(0.1)
gt.stamp('first')
for i in gt.timed_for([1, 2, 3]):
time.sleep(0.1)
gt.stamp('loop_1')
if i > 1:
time.sleep(0.1)
gt.stamp('loop_2')
time.sleep(0.1)
gt.stamp('second')
print gt.report()
| 17.466667
| 33
| 0.603053
| 51
| 262
| 3.039216
| 0.411765
| 0.232258
| 0.258065
| 0.283871
| 0.516129
| 0.516129
| 0.283871
| 0
| 0
| 0
| 0
| 0.067633
| 0.209924
| 262
| 14
| 34
| 18.714286
| 0.681159
| 0
| 0
| 0.307692
| 0
| 0
| 0.087786
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.153846
| null | null | 0.076923
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
a5b5765f695b007b0ced89139a690e0b7fcb7c9d
| 254
|
py
|
Python
|
accounts/models.py
|
veldakarimi/filmreview
|
ef50fc2f43cf87064162cbb43ab5c80cfe24eeb2
|
[
"Apache-2.0"
] | null | null | null |
accounts/models.py
|
veldakarimi/filmreview
|
ef50fc2f43cf87064162cbb43ab5c80cfe24eeb2
|
[
"Apache-2.0"
] | 3
|
2020-07-26T09:27:41.000Z
|
2022-01-13T03:07:25.000Z
|
accounts/models.py
|
veldakarimi/filmreview
|
ef50fc2f43cf87064162cbb43ab5c80cfe24eeb2
|
[
"Apache-2.0"
] | null | null | null |
from django.db import models
from django.contrib.auth.models import AbstractUser
# Create your models here.
class CustomUser(AbstractUser):
class Meta:
pass
def main__str__(self):
return self.username
| 19.538462
| 53
| 0.649606
| 29
| 254
| 5.551724
| 0.724138
| 0.124224
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.295276
| 254
| 13
| 54
| 19.538462
| 0.899441
| 0.094488
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0.142857
| 0.285714
| 0.142857
| 0.857143
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
a5bd34d3b4b5bbbadca338acf6ea18a3b88edbfc
| 2,207
|
py
|
Python
|
static/shapes/const.py
|
marcinbittel/WarsawGTFS
|
5e2d3c6ff2465b06352216e67dbf303e9b69b946
|
[
"MIT"
] | null | null | null |
static/shapes/const.py
|
marcinbittel/WarsawGTFS
|
5e2d3c6ff2465b06352216e67dbf303e9b69b946
|
[
"MIT"
] | null | null | null |
static/shapes/const.py
|
marcinbittel/WarsawGTFS
|
5e2d3c6ff2465b06352216e67dbf303e9b69b946
|
[
"MIT"
] | null | null | null |
from ..const import _BASE_GIST
# Shape-generation external data
GIST_OVERRIDE_RATIOS = _BASE_GIST + "shapes_override_ratios.json"
GIST_FORCE_VIA = _BASE_GIST + "shapes_force_via.json"
# Bus router settings
BUS_ROUTER_SETTINGS = {
"weights": {
"motorway": 1.5, "trunk": 1.5, "primary": 1.4, "secondary": 1.3, "tertiary": 1.3,
"unclassified": 1, "residential": 0.6, "living_street": 0.6, "track": 0.3, "service": 0.3
},
"access": ["access", "vehicle", "motor_vehicle", "psv", "bus", "routing:ztm"],
"name": "bus"
}
# Sources for external graphs
URL_OVERPASS = "https://overpass-api.de/api/interpreter/"
URL_TRAM_TRAIN_GRAPH = "https://mkuran.pl/gtfs/warsaw/tram-rail-shapes.osm"
# Overpass queries
_OVERPASS_QUERY_BOUND_POLY = " ".join([
"52.4455 20.6858", "52.4137 20.622", "52.3609 20.6097", "52.2709 20.5877", "52.274 20.4465",
"52.2599 20.4438", "52.2481 20.5832", "52.2538 20.681", "52.1865 20.6786", "52.1859 20.7129",
"52.1465 20.7895", "52.0966 20.7830", "52.0632 20.7222", "52.0151 20.7617", "51.9873 20.9351",
"51.9269 20.9509", "51.9144 21.0226", "51.9322 21.1987", "51.9569 21.2472", "52.0463 21.2368",
"52.1316 21.4844", "52.1429 21.4404", "52.213 21.3814", "52.2622 21.3141", "52.2652 21.1977",
"52.3038 21.1730", "52.3063 21.2925", "52.3659 21.3515", "52.3829 21.3001", "52.4221 21.1929",
"52.4898 21.1421", "52.4934 20.9234"
])
OVERPASS_BUS_GRAPH = f'''
[bbox:51.9144,20.4438,52.5007,21.4844][out:xml];
(
way["highway"="motorway"];
way["highway"="motorway_link"];
way["highway"="trunk"];
way["highway"="trunk_link"];
way["highway"="primary"];
way["highway"="primary_link"];
way["highway"="secondary"];
way["highway"="secondary_link"];
way["highway"="tertiary"];
way["highway"="tertiary_link"];
way["highway"="unclassified"];
way["highway"="minor"];
way["highway"="residential"];
way["highway"="living_street"];
way["highway"="service"];
);
way._(poly:"{_OVERPASS_QUERY_BOUND_POLY}");
>->.n;
<->.r;
(._;.n;.r;);
out;
'''
OVERPASS_STOPS_JSON = '''
[bbox:51.9144,20.4438,52.5007,21.4844][out:json];
node[public_transport=stop_position][network="ZTM Warszawa"];
out;
'''
| 35.031746
| 98
| 0.637517
| 335
| 2,207
| 4.068657
| 0.456716
| 0.110051
| 0.051357
| 0.032282
| 0.045488
| 0.045488
| 0.045488
| 0.045488
| 0.045488
| 0.045488
| 0
| 0.234646
| 0.136837
| 2,207
| 62
| 99
| 35.596774
| 0.48084
| 0.043045
| 0
| 0.076923
| 0
| 0.038462
| 0.713811
| 0.310394
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.096154
| 0.019231
| 0
| 0.019231
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
a5bdd10106f455dd3e0e5bc80a3bf4bd1bc4ca73
| 115
|
py
|
Python
|
instruction.py
|
bhopkinson/mqtt-TLC5947
|
e0924455b52349d51171ac0ab2c81565542bef8e
|
[
"MIT"
] | null | null | null |
instruction.py
|
bhopkinson/mqtt-TLC5947
|
e0924455b52349d51171ac0ab2c81565542bef8e
|
[
"MIT"
] | null | null | null |
instruction.py
|
bhopkinson/mqtt-TLC5947
|
e0924455b52349d51171ac0ab2c81565542bef8e
|
[
"MIT"
] | null | null | null |
import queue
class instruction:
def __init__(self, addr, pwm):
self.addr = addr
self.pwm = pwm
| 19.166667
| 34
| 0.617391
| 15
| 115
| 4.466667
| 0.6
| 0.238806
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.295652
| 115
| 6
| 35
| 19.166667
| 0.82716
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.2
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
3c16865b949aa032f4da7ec92cced1905dcfe058
| 56
|
py
|
Python
|
tests/test_rotations.py
|
Ceres-Navigation/ceres
|
2ab8431e85e783fcdd21a53ccc62fd09ce687dce
|
[
"MIT"
] | null | null | null |
tests/test_rotations.py
|
Ceres-Navigation/ceres
|
2ab8431e85e783fcdd21a53ccc62fd09ce687dce
|
[
"MIT"
] | null | null | null |
tests/test_rotations.py
|
Ceres-Navigation/ceres
|
2ab8431e85e783fcdd21a53ccc62fd09ce687dce
|
[
"MIT"
] | null | null | null |
from ceres.rotations import Rotation
import numpy as np
| 18.666667
| 36
| 0.839286
| 9
| 56
| 5.222222
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 56
| 2
| 37
| 28
| 0.979167
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
3c3787923a67e552d8ed86e40030b6cc39c7aa3b
| 170
|
py
|
Python
|
openomics/database/disease.py
|
muluayele999/OpenOmics
|
29e3bbc586489c3929ac54d9886627f907aa38b1
|
[
"MIT"
] | null | null | null |
openomics/database/disease.py
|
muluayele999/OpenOmics
|
29e3bbc586489c3929ac54d9886627f907aa38b1
|
[
"MIT"
] | 1
|
2021-12-13T20:51:32.000Z
|
2021-12-13T20:51:32.000Z
|
openomics/database/disease.py
|
muluayele999/OpenOmics
|
29e3bbc586489c3929ac54d9886627f907aa38b1
|
[
"MIT"
] | 1
|
2021-02-18T10:39:00.000Z
|
2021-02-18T10:39:00.000Z
|
from openomics.database.annotation import *
class DiseaseAssociation(Dataset):
@abstractmethod
def get_disease_assocs(self, index): raise NotImplementedError
| 18.888889
| 66
| 0.794118
| 17
| 170
| 7.823529
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141176
| 170
| 8
| 67
| 21.25
| 0.910959
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
3c381d56992d190cfe1228dc7b2d02dd50278b83
| 187
|
py
|
Python
|
setup.py
|
stephen-khan/feature_infection
|
96eb505d17e3b3d540305ae9a6f86be09ceb4974
|
[
"Unlicense"
] | null | null | null |
setup.py
|
stephen-khan/feature_infection
|
96eb505d17e3b3d540305ae9a6f86be09ceb4974
|
[
"Unlicense"
] | null | null | null |
setup.py
|
stephen-khan/feature_infection
|
96eb505d17e3b3d540305ae9a6f86be09ceb4974
|
[
"Unlicense"
] | null | null | null |
from distutils.core import setup
setup(name='Feature Infection',
version='1.0',
description='Assign features to groups of users.',
packages=['feature_infection']
)
| 26.714286
| 56
| 0.679144
| 22
| 187
| 5.727273
| 0.863636
| 0.253968
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.013423
| 0.203209
| 187
| 7
| 57
| 26.714286
| 0.832215
| 0
| 0
| 0
| 0
| 0
| 0.382979
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.166667
| 0
| 0.166667
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3c4c9730441ae9db6146bd976d0a865b07d68a7d
| 708
|
py
|
Python
|
spot_motion_monitor/utils/__init__.py
|
lsst-sitcom/spot_motion_monitor
|
3d0242276198126240667ba13e95b7bdf901d053
|
[
"BSD-3-Clause"
] | null | null | null |
spot_motion_monitor/utils/__init__.py
|
lsst-sitcom/spot_motion_monitor
|
3d0242276198126240667ba13e95b7bdf901d053
|
[
"BSD-3-Clause"
] | 5
|
2020-01-08T23:50:22.000Z
|
2020-02-14T18:15:20.000Z
|
spot_motion_monitor/utils/__init__.py
|
lsst-com/spot_motion_monitor
|
3d0242276198126240667ba13e95b7bdf901d053
|
[
"MIT"
] | null | null | null |
# This file is part of spot_motion_monitor.
#
# Developed for LSST System Integration, Test and Commissioning.
#
# See the LICENSE file at the top-level directory of this distribution
# for details of code ownership.
#
# Use of this source code is governed by a 3-clause BSD-style
# license that can be found in the LICENSE file.
from .config_helpers import *
from .constants import *
from .css import *
from .exceptions import *
from .fft_calculator import *
from .frame_information import *
from .fwhm_calculator import *
from .information_updater import InformationUpdater
from .functions import *
from .time_handler import *
from .parser import *
from .psd_calculator import *
from .yaml_input import *
| 29.5
| 70
| 0.782486
| 103
| 708
| 5.281553
| 0.601942
| 0.202206
| 0.110294
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.001678
| 0.158192
| 708
| 23
| 71
| 30.782609
| 0.911074
| 0.439266
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
3c69e3160ff1023d44ee954cb3530f0458f98d4f
| 154
|
py
|
Python
|
Do-it-first-python/mission/3-01.py
|
siyoon210/Python-Practice
|
778922a8be2faaa564915bcbcab761d39753b1f8
|
[
"MIT"
] | null | null | null |
Do-it-first-python/mission/3-01.py
|
siyoon210/Python-Practice
|
778922a8be2faaa564915bcbcab761d39753b1f8
|
[
"MIT"
] | null | null | null |
Do-it-first-python/mission/3-01.py
|
siyoon210/Python-Practice
|
778922a8be2faaa564915bcbcab761d39753b1f8
|
[
"MIT"
] | null | null | null |
num = int(input())
if num >= 1 and num <= 9:
print('한 자리 숫자입니다')
elif num >= 10 and num <= 99:
print('두 자리 숫자입니다')
else:
print('세 자리 숫자입니다')
| 17.111111
| 29
| 0.545455
| 28
| 154
| 3
| 0.607143
| 0.25
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.053571
| 0.272727
| 154
| 8
| 30
| 19.25
| 0.696429
| 0
| 0
| 0
| 0
| 0
| 0.194805
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.428571
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
3c928821056e65900be167b206aeca158eb32c7a
| 98
|
py
|
Python
|
src/ShowPythonVersion.py
|
bink81/python-tools
|
57f9aa13051a9ac925da293241f4be9cd54e8fb3
|
[
"MIT"
] | null | null | null |
src/ShowPythonVersion.py
|
bink81/python-tools
|
57f9aa13051a9ac925da293241f4be9cd54e8fb3
|
[
"MIT"
] | null | null | null |
src/ShowPythonVersion.py
|
bink81/python-tools
|
57f9aa13051a9ac925da293241f4be9cd54e8fb3
|
[
"MIT"
] | null | null | null |
'''
Created on 27 Mar 2016
'''
import sys
if __name__ == '__main__':
print(sys.version)
| 14
| 27
| 0.612245
| 13
| 98
| 4
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.081081
| 0.244898
| 98
| 6
| 28
| 16.333333
| 0.621622
| 0.22449
| 0
| 0
| 0
| 0
| 0.129032
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0.333333
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
b1bfc66a792603fd76fa2f9c8684603375012e41
| 97
|
py
|
Python
|
src/haydi/base/exception.py
|
Kobzol/haydi
|
4b49230d33ce02edff207b49a5db4ef6e605200c
|
[
"MIT"
] | 5
|
2017-08-09T17:12:31.000Z
|
2020-06-14T13:13:05.000Z
|
src/haydi/base/exception.py
|
Kobzol/haydi
|
4b49230d33ce02edff207b49a5db4ef6e605200c
|
[
"MIT"
] | 13
|
2017-01-31T15:42:13.000Z
|
2017-12-04T11:24:26.000Z
|
src/haydi/base/exception.py
|
Kobzol/haydi
|
4b49230d33ce02edff207b49a5db4ef6e605200c
|
[
"MIT"
] | 2
|
2017-08-21T09:49:10.000Z
|
2021-02-28T13:51:05.000Z
|
class HaydiException(BaseException):
pass
class TimeoutException(HaydiException):
pass
| 13.857143
| 39
| 0.773196
| 8
| 97
| 9.375
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164948
| 97
| 6
| 40
| 16.166667
| 0.925926
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
b1c30971b46bfa8d8a90ce95f5137be9b5ad6950
| 71
|
py
|
Python
|
Dessert.Benchmarks/SimPy3/monitoring.py
|
saboco/Dessert
|
bced609c40f74aeb2c938b754b475f0a79ba92c4
|
[
"MIT"
] | 1
|
2022-03-04T18:03:41.000Z
|
2022-03-04T18:03:41.000Z
|
Dessert.Benchmarks/SimPy3/monitoring.py
|
saboco/Dessert
|
bced609c40f74aeb2c938b754b475f0a79ba92c4
|
[
"MIT"
] | null | null | null |
Dessert.Benchmarks/SimPy3/monitoring.py
|
saboco/Dessert
|
bced609c40f74aeb2c938b754b475f0a79ba92c4
|
[
"MIT"
] | null | null | null |
"""
SimPy's monitoring capabilities will be added in version 3.1.
"""
| 14.2
| 61
| 0.704225
| 11
| 71
| 4.545455
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.033898
| 0.169014
| 71
| 4
| 62
| 17.75
| 0.813559
| 0.859155
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b1cb0c6c49d13a33c28b9d21e1e26e33bd2594f7
| 92
|
py
|
Python
|
nest_apps/old_style/apps.py
|
thinkAmi-sandbox/Django_AppConfig-sample
|
14e2018dcaf31c6a615e615fb4b1ae713ea56416
|
[
"Unlicense"
] | null | null | null |
nest_apps/old_style/apps.py
|
thinkAmi-sandbox/Django_AppConfig-sample
|
14e2018dcaf31c6a615e615fb4b1ae713ea56416
|
[
"Unlicense"
] | null | null | null |
nest_apps/old_style/apps.py
|
thinkAmi-sandbox/Django_AppConfig-sample
|
14e2018dcaf31c6a615e615fb4b1ae713ea56416
|
[
"Unlicense"
] | null | null | null |
from django.apps import AppConfig
class OldStyleConfig(AppConfig):
name = 'old_style'
| 15.333333
| 33
| 0.76087
| 11
| 92
| 6.272727
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.163043
| 92
| 5
| 34
| 18.4
| 0.896104
| 0
| 0
| 0
| 0
| 0
| 0.097826
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
b1f04d77a166513bd6a12c4ea95de49565df889b
| 71
|
py
|
Python
|
src/lamplib/src/tests/__init__.py
|
MikhailShchatko/genny
|
00938dc557ef1ad9b6b2d950447bc0e372e951ef
|
[
"Apache-2.0"
] | 30
|
2019-01-30T17:21:44.000Z
|
2022-01-21T00:05:33.000Z
|
src/lamplib/src/tests/__init__.py
|
MikhailShchatko/genny
|
00938dc557ef1ad9b6b2d950447bc0e372e951ef
|
[
"Apache-2.0"
] | 358
|
2019-01-15T21:51:57.000Z
|
2022-03-30T16:10:42.000Z
|
src/lamplib/src/tests/__init__.py
|
MikhailShchatko/genny
|
00938dc557ef1ad9b6b2d950447bc0e372e951ef
|
[
"Apache-2.0"
] | 50
|
2019-01-15T20:01:15.000Z
|
2022-03-24T16:19:52.000Z
|
# Run tests in this directory with `python3 -m unittest` from lamplib.
| 35.5
| 70
| 0.760563
| 11
| 71
| 4.909091
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016949
| 0.169014
| 71
| 1
| 71
| 71
| 0.898305
| 0.957746
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
591de0335759fbdf4b67e2a6c0d0f0d62a14dfb0
| 139,841
|
py
|
Python
|
tg263/dictionary.py
|
gacou54/tg263
|
dc4efab8937e2edb46d6d994bbbb242bc01f2108
|
[
"MIT"
] | 1
|
2019-10-08T15:51:39.000Z
|
2019-10-08T15:51:39.000Z
|
tg263/dictionary.py
|
gacou54/tg263
|
dc4efab8937e2edb46d6d994bbbb242bc01f2108
|
[
"MIT"
] | null | null | null |
tg263/dictionary.py
|
gacou54/tg263
|
dc4efab8937e2edb46d6d994bbbb242bc01f2108
|
[
"MIT"
] | null | null | null |
# coding: utf-8
# author: Gabriel Couture
import re
from tg263.structure import Structure
ALLOWED_STRUCTURES = [
Structure(re.compile(r'^(A_Aorta~?(\^[\w\d_\+-]+)?)$'), 'A_Aorta', '3734', 'Anatomic', 'Artery', 'Aorta', 'Thorax', 'Aorta'),
Structure(re.compile(r'^(A_Aorta_Asc~?(\^[\w\d_\+-]+)?)$'), 'A_Aorta_Asc', '3736', 'Anatomic', 'Artery', 'Aorta', 'Thorax', 'Ascending Aorta'),
Structure(re.compile(r'^(A_Brachiocephls~?(\^[\w\d_\+-]+)?)$'), 'A_Brachiocephls', '3932', 'Anatomic', 'Artery', 'Brachiocephalic', 'Thorax', 'Brachiocephalic Artery'),
Structure(re.compile(r'^(A_Carotid~?(\^[\w\d_\+-]+)?)$'), 'A_Carotid', '3939', 'Anatomic', 'Artery', 'Carotid', 'Head and Neck', 'Common Carotid Artery'),
Structure(re.compile(r'^(A_Carotid~?_L(\^[\w\d_\+-]+)?)$'), 'A_Carotid_L', '4058', 'Anatomic', 'Artery', 'Carotid', 'Head and Neck', 'Carotid Artery'),
Structure(re.compile(r'^(A_Carotid~?_R(\^[\w\d_\+-]+)?)$'), 'A_Carotid_R', '3941', 'Anatomic', 'Artery', 'Carotid', 'Head and Neck', 'Carotid Artery'),
Structure(re.compile(r'^(A_Celiac~?(\^[\w\d_\+-]+)?)$'), 'A_Celiac', '50737', 'Anatomic', 'Artery', 'Celiac', 'Abdomen', 'Celiac Artery'),
Structure(re.compile(r'^(A_Coronary~?(\^[\w\d_\+-]+)?)$'), 'A_Coronary', '49893', 'Anatomic', 'Artery', 'Coronary', 'Head and Neck', 'Coronary Artery'),
Structure(re.compile(r'^(A_Coronary~?_L(\^[\w\d_\+-]+)?)$'), 'A_Coronary_L', '50040', 'Anatomic', 'Artery', 'Coronary', 'Thorax', 'Coronary Artery Left'),
Structure(re.compile(r'^(A_Coronary~?_R(\^[\w\d_\+-]+)?)$'), 'A_Coronary_R', '50039', 'Anatomic', 'Artery', 'Coronary', 'Thorax', 'Coronary Artery Right'),
Structure(re.compile(r'^(A_Femoral_Cflx~?_L(\^[\w\d_\+-]+)?)$'), 'A_Femoral_Cflx_L', 'nan', 'Anatomic', 'Artery', 'Femoral', 'Limb', 'Circumflex Left Femoral Artery'),
Structure(re.compile(r'^(A_Femoral_Cflx~?_R(\^[\w\d_\+-]+)?)$'), 'A_Femoral_Cflx_R', 'nan', 'Anatomic', 'Artery', 'Femoral', 'Limb', 'Circumflex Right Femoral Artery'),
Structure(re.compile(r'^(A_Femoral~?_L(\^[\w\d_\+-]+)?)$'), 'A_Femoral_L', '70250', 'Anatomic', 'Artery', 'Femoral', 'Limb', 'Femoral Artery Left'),
Structure(re.compile(r'^(A_Femoral~?_R(\^[\w\d_\+-]+)?)$'), 'A_Femoral_R', '70249', 'Anatomic', 'Artery', 'Femoral', 'Limb', 'Femoral Artery Right'),
Structure(re.compile(r'^(A_Humeral_Cflx~?_L(\^[\w\d_\+-]+)?)$'), 'A_Humeral_Cflx_L', 'nan', 'Anatomic', 'Artery', 'Humeral', 'Limb', 'Circumflex Humeral Artery Left'),
Structure(re.compile(r'^(A_Humeral_Cflx~?_R(\^[\w\d_\+-]+)?)$'), 'A_Humeral_Cflx_R', 'nan', 'Anatomic', 'Artery', 'Humeral', 'Limb', 'Circumflex Humeral Artery Right'),
Structure(re.compile(r'^(A_Humeral~?_L(\^[\w\d_\+-]+)?)$'), 'A_Humeral_L', 'nan', 'Anatomic', 'Artery', 'Humeral', 'Limb', 'Humeral Artery Left'),
Structure(re.compile(r'^(A_Humeral~?_R(\^[\w\d_\+-]+)?)$'), 'A_Humeral_R', 'nan', 'Anatomic', 'Artery', 'Humeral', 'Limb', 'Humeral Artery Right'),
Structure(re.compile(r'^(A_Hypophyseal~?_I(\^[\w\d_\+-]+)?)$'), 'A_Hypophyseal_I', '49846', 'Anatomic', 'Artery', 'Hypophyseal', 'Head and Neck', 'Hypophyseal Artery Inferior'),
Structure(re.compile(r'^(A_Hypophyseal~?_S(\^[\w\d_\+-]+)?)$'), 'A_Hypophyseal_S', '49849', 'Anatomic', 'Artery', 'Hypophyseal', 'Head and Neck', 'Hypophyseal Artery Superior'),
Structure(re.compile(r'^(A_Iliac_Cflx~?_L(\^[\w\d_\+-]+)?)$'), 'A_Iliac_Cflx_L', 'nan', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'Circumflex Left Iliac Artery'),
Structure(re.compile(r'^(A_Iliac_Cflx~?_R(\^[\w\d_\+-]+)?)$'), 'A_Iliac_Cflx_R', 'nan', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'Circumflex Right Iliac Artery'),
Structure(re.compile(r'^(A_Iliac_Ext~?_L(\^[\w\d_\+-]+)?)$'), 'A_Iliac_Ext_L', '18807', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'External iliac artery Left'),
Structure(re.compile(r'^(A_Iliac_Ext~?_R(\^[\w\d_\+-]+)?)$'), 'A_Iliac_Ext_R', '18806', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'External iliac artery Right'),
Structure(re.compile(r'^(A_Iliac_Int~?_L(\^[\w\d_\+-]+)?)$'), 'A_Iliac_Int_L', '18810', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'Internal iliac artery Left'),
Structure(re.compile(r'^(A_Iliac_Int~?_R(\^[\w\d_\+-]+)?)$'), 'A_Iliac_Int_R', '18809', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'Internal iliac artery Right'),
Structure(re.compile(r'^(A_Iliac~?_L(\^[\w\d_\+-]+)?)$'), 'A_Iliac_L', '14766', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'Common iliac artery Left'),
Structure(re.compile(r'^(A_Iliac~?_R(\^[\w\d_\+-]+)?)$'), 'A_Iliac_R', '14765', 'Anatomic', 'Artery', 'Iliac', 'Pelvis', 'Common iliac artery Right'),
Structure(re.compile(r'^(A_LAD~?(\^[\w\d_\+-]+)?)$'), 'A_LAD', '3862', 'Anatomic', 'Artery', 'LAD', 'Thorax', 'Anterior interventricular branch of LCA (left anterior descending artery)'),
Structure(re.compile(r'^(A_Mesenteric~?_I(\^[\w\d_\+-]+)?)$'), 'A_Mesenteric_I', '14750', 'Anatomic', 'Artery', 'Mesenteric', 'Abdomen', 'Inferior mesenteric artery '),
Structure(re.compile(r'^(A_Mesenteric~?_S(\^[\w\d_\+-]+)?)$'), 'A_Mesenteric_S', '14749', 'Anatomic', 'Artery', 'Mesenteric', 'Abdomen', 'Superior mesenteric artery '),
Structure(re.compile(r'^(A_Pulmonary~?(\^[\w\d_\+-]+)?)$'), 'A_Pulmonary', '66326', 'Anatomic', 'Artery', 'Pulmonary', 'Thorax', 'Pulmonary Artery'),
Structure(re.compile(r'^(A_Subclavian~?(\^[\w\d_\+-]+)?)$'), 'A_Subclavian', '3951', 'Anatomic', 'Artery', 'Subclavian', 'Thorax', 'Subclavian Artery'),
Structure(re.compile(r'^(A_Subclavian~?_L(\^[\w\d_\+-]+)?)$'), 'A_Subclavian_L', '4694', 'Anatomic', 'Artery', 'Subclavian', 'Thorax', 'Subclavian Artery Left'),
Structure(re.compile(r'^(A_Subclavian~?_R(\^[\w\d_\+-]+)?)$'), 'A_Subclavian_R', '3953', 'Anatomic', 'Artery', 'Subclavian', 'Thorax', 'Subclavian Artery Right'),
Structure(re.compile(r'^(A_Vertebral~?(\^[\w\d_\+-]+)?)$'), 'A_Vertebral', '3956', 'Anatomic', 'Artery', 'Vertebral', 'Thorax', 'Vertebral arteries'),
Structure(re.compile(r'^(A_Vertebral~?_L(\^[\w\d_\+-]+)?)$'), 'A_Vertebral_L', '4066', 'Anatomic', 'Artery', 'Vertebral', 'Thorax', 'Vertebral arteries left'),
Structure(re.compile(r'^(A_Vertebral~?_R(\^[\w\d_\+-]+)?)$'), 'A_Vertebral_R', '3958', 'Anatomic', 'Artery', 'Vertebral', 'Thorax', 'Vertebral arteries right'),
Structure(re.compile(r'^(Acetabulum~?_L(\^[\w\d_\+-]+)?)$'), 'Acetabulum_L', '16599', 'Anatomic', 'Bone', 'Pelvic', 'Pelvis', 'Acetabulum'),
Structure(re.compile(r'^(Acetabulum~?_R(\^[\w\d_\+-]+)?)$'), 'Acetabulum_R', '16598', 'Anatomic', 'Bone', 'Pelvic', 'Pelvis', 'Acetabulum'),
Structure(re.compile(r'^(Acetabulums~?(\^[\w\d_\+-]+)?)$'), 'Acetabulums', '16579', 'Anatomic', 'Bone', 'Pelvic', 'Pelvis', 'Acetabulum'),
Structure(re.compile(r'^(AirWay~?_Dist(\^[\w\d_\+-]+)?)$'), 'AirWay_Dist', 'nan', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Distal Airway'),
Structure(re.compile(r'^(AirWay~?_Prox(\^[\w\d_\+-]+)?)$'), 'AirWay_Prox', 'nan', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Proximal Airway'),
Structure(re.compile(r'^(Anus~?(\^[\w\d_\+-]+)?)$'), 'Anus', '15711', 'Anatomic', 'Bowel', 'Anus', 'Pelvis', 'Anus'),
Structure(re.compile(r'^(Appendix~?(\^[\w\d_\+-]+)?)$'), 'Appendix', '14542', 'Anatomic', 'Bowel', 'Appendix', 'Abdomen', 'Appendix'),
Structure(re.compile(r'^(Arytenoid~?(\^[\w\d_\+-]+)?)$'), 'Arytenoid', '55109', 'Anatomic', 'Cartilage', 'Arytenoid', 'Head and Neck', 'Arytenoid cartilage'),
Structure(re.compile(r'^(Arytenoid~?_L(\^[\w\d_\+-]+)?)$'), 'Arytenoid_L', '55114', 'Anatomic', 'Cartilage', 'Arytenoid', 'Head and Neck', 'Arytenoid cartilage Left'),
Structure(re.compile(r'^(Arytenoid~?_R(\^[\w\d_\+-]+)?)$'), 'Arytenoid_R', '55113', 'Anatomic', 'Cartilage', 'Arytenoid', 'Head and Neck', 'Arytenoid cartilage Right'),
Structure(re.compile(r'^(Atrium~?(\^[\w\d_\+-]+)?)$'), 'Atrium', '7099', 'Anatomic', 'Heart', 'Atrium', 'Thorax', 'Atrium of the heart '),
Structure(re.compile(r'^(Atrium~?_L(\^[\w\d_\+-]+)?)$'), 'Atrium_L', '7097', 'Anatomic', 'Heart', 'Atrium', 'Thorax', 'Atrium of the heart Left'),
Structure(re.compile(r'^(Atrium~?_R(\^[\w\d_\+-]+)?)$'), 'Atrium_R', '7096', 'Anatomic', 'Heart', 'Atrium', 'Thorax', 'Atrium of the heart Right'),
Structure(re.compile(r'^(Bag_Bowel(\^[\w\d_\+-]+)?)$'), 'Bag_Bowel', 'nan', 'Non_Anatomic', 'Bowel', 'nan', 'Abdomen', 'Bowel Bag'),
Structure(re.compile(r'^(Bag_Ostomy(\^[\w\d_\+-]+)?)$'), 'Bag_Ostomy', 'nan', 'Non_Anatomic', 'Devices', 'nan', 'Body', 'Ostomy Bag'),
Structure(re.compile(r'^(BileDuct_Common~?(\^[\w\d_\+-]+)?)$'), 'BileDuct_Common', '14667', 'Anatomic', 'Bowel', 'Bile', 'Abdomen', 'Common bile duct'),
Structure(re.compile(r'^(Bladder~?(\^[\w\d_\+-]+)?)$'), 'Bladder', '15900', 'Anatomic', 'Bladder', 'nan', 'Pelvis', 'Urinary Bladder'),
Structure(re.compile(r'^(Bladder_Wall~?(\^[\w\d_\+-]+)?)$'), 'Bladder_Wall', '15902', 'Anatomic', 'Bladder', 'nan', 'Pelvis', 'Bladder Wall'),
Structure(re.compile(r'^(Bladder-CTV(\^[\w\d_\+-]+)?)$'), 'Bladder-CTV', 'nan', 'Derived', 'Bladder', 'nan', 'Pelvis', 'Bladder minus CTV'),
Structure(re.compile(r'^Body$'), 'Body', '256135', 'Anatomic', 'Body', 'nan', 'Body', 'Only the body'),
Structure(re.compile(r'^(Body-PTV(\^[\w\d_\+-]+)?)$'), 'Body-PTV', 'nan', 'Derived', 'Body', 'nan', 'Body', 'Body minus PTV'),
Structure(re.compile(r'^(Bolus(_\d{2}mm)?(\^[\w\d_\+-]+)?)$'), 'Bolus_xxmm', 'nan', 'Non_Anatomic', 'Bolus', 'nan', 'Body', 'Bolus that is xx millimeters thick e.g. Bolus_03mm, Bolus_10mm'),
Structure(re.compile(r'^(Bone~?(\^[\w\d_\+-]+)?)$'), 'Bone', '30317', 'Anatomic', 'Bone', 'nan', 'Body', 'Bone'),
Structure(re.compile(r'^(Bone_Ethmoid~?(\^[\w\d_\+-]+)?)$'), 'Bone_Ethmoid', '52740', 'Anatomic', 'Bone', 'Ethmoid', 'Head and Neck', 'Ethmoid Bone'),
Structure(re.compile(r'^(Bone_Frontal~?(\^[\w\d_\+-]+)?)$'), 'Bone_Frontal', '52734', 'Anatomic', 'Bone', 'Frontal', 'Head and Neck', 'Frontal Bone'),
Structure(re.compile(r'^(Bone_Hyoid~?(\^[\w\d_\+-]+)?)$'), 'Bone_Hyoid', '52749', 'Anatomic', 'Bone', 'Hyoid', 'Head and Neck', 'Hyoid Bone'),
Structure(re.compile(r'^(Bone_Ilium~?(\^[\w\d_\+-]+)?)$'), 'Bone_Ilium', '42832', 'Anatomic', 'Bone', 'Ilium', 'Pelvis', 'Ilium'),
Structure(re.compile(r'^(Bone_Ilium~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Ilium_L', '16591', 'Anatomic', 'Bone', 'Ilium', 'Pelvis', 'Ilium Left'),
Structure(re.compile(r'^(Bone_Ilium~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Ilium_R', '16590', 'Anatomic', 'Bone', 'Ilium', 'Pelvis', 'Ilium Right'),
Structure(re.compile(r'^(Bone_Incus~?(\^[\w\d_\+-]+)?)$'), 'Bone_Incus', '52752', 'Anatomic', 'Ear', 'Incus', 'Head and Neck', 'Incus'),
Structure(re.compile(r'^(Bone_Incus~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Incus_L', '74051', 'Anatomic', 'Ear', 'Incus', 'Head and Neck', 'Incus Left'),
Structure(re.compile(r'^(Bone_Incus~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Incus_R', '74050', 'Anatomic', 'Ear', 'Incus', 'Head and Neck', 'Incus Right'),
Structure(re.compile(r'^(Bone_Ischium~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Ischium_L', '16594', 'Anatomic', 'Bone', 'Ischium', 'Pelvis', 'Ischium Left'),
Structure(re.compile(r'^(Bone_Ischium~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Ischium_R', '16593', 'Anatomic', 'Bone', 'Ischium', 'Pelvis', 'Ischium Right'),
Structure(re.compile(r'^(Bone_Lacrimal~?(\^[\w\d_\+-]+)?)$'), 'Bone_Lacrimal', '52741', 'Anatomic', 'Bone', 'Lacrimal', 'Head and Neck', 'Lacrimal Bone'),
Structure(re.compile(r'^(Bone_Lacrimal~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Lacrimal_L', '53646', 'Anatomic', 'Bone', 'Lacrimal', 'Head and Neck', 'Lacrimal Bone Left'),
Structure(re.compile(r'^(Bone_Lacrimal~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Lacrimal_R', '53645', 'Anatomic', 'Bone', 'Lacrimal', 'Head and Neck', 'Lacrimal Bone Right'),
Structure(re.compile(r'^(Bone_Mandible~?(\^[\w\d_\+-]+)?)$'), 'Bone_Mandible', '52748', 'Anatomic', 'Bone', 'Mandible', 'Head and Neck', 'Mandible'),
Structure(re.compile(r'^(Bone_Mastoid~?(\^[\w\d_\+-]+)?)$'), 'Bone_Mastoid', '52872', 'Anatomic ', 'Bone', 'Mastoid', 'Head and Neck', 'Both Mastoids'),
Structure(re.compile(r'^(Bone_Mastoid~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Mastoid_L', '52874', 'Anatomic', 'Bone', 'Mastoid', 'Head and Neck', 'Left Mastoid Bone'),
Structure(re.compile(r'^(Bone_Mastoid~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Mastoid_R', '52873', 'Anatomic', 'Bone', 'Mastoid', 'Head and Neck', 'Right Mastoid Bone'),
Structure(re.compile(r'^(Bone_Nasal~?(\^[\w\d_\+-]+)?)$'), 'Bone_Nasal', '52745', 'Anatomic', 'Bone', 'Nasal', 'Head and Neck', 'Nasal Bone'),
Structure(re.compile(r'^(Bone_Nasal~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Nasal_L', '53648', 'Anatomic', 'Bone', 'Nasal', 'Head and Neck', 'Nasal Bone Left'),
Structure(re.compile(r'^(Bone_Nasal~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Nasal_R', '53647', 'Anatomic', 'Bone', 'Nasal', 'Head and Neck', 'Nasal Bone Right'),
Structure(re.compile(r'^(Bone_Occipital~?(\^[\w\d_\+-]+)?)$'), 'Bone_Occipital', '52735', 'Anatomic', 'Bone', 'Occipital ', 'Head and Neck', 'Occipital Bone'),
Structure(re.compile(r'^(Bone_Palatine~?(\^[\w\d_\+-]+)?)$'), 'Bone_Palatine', '52746', 'Anatomic', 'Bone', 'Palatine', 'Head and Neck', 'Palatine bone'),
Structure(re.compile(r'^(Bone_Palatine~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Palatine_L', '53656', 'Anatomic', 'Bone', 'Palatine', 'Head and Neck', 'Palatine bone Left'),
Structure(re.compile(r'^(Bone_Palatine~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Palatine_R', '53655', 'Anatomic', 'Bone', 'Palatine', 'Head and Neck', 'Palatine bone Right'),
Structure(re.compile(r'^(Bone_Parietal~?(\^[\w\d_\+-]+)?)$'), 'Bone_Parietal', '9613', 'Anatomic', 'Bone', 'Parietal', 'Head and Neck', 'Parietal bone'),
Structure(re.compile(r'^(Bone_Parietal~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Parietal_L', '52789', 'Anatomic', 'Bone', 'Parietal', 'Head and Neck', 'Parietal bone Left'),
Structure(re.compile(r'^(Bone_Parietal~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Parietal_R', '52788', 'Anatomic', 'Bone', 'Parietal', 'Head and Neck', 'Parietal bone Right'),
Structure(re.compile(r'^(Bone_Pelvic~?(\^[\w\d_\+-]+)?)$'), 'Bone_Pelvic', '16580', 'Anatomic', 'Bone', 'Pelvic', 'Pelvis', 'Pelvic Bones (Bony Pelvis)'),
Structure(re.compile(r'^(Bone_Pelvic~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Pelvic_L', '20227', 'Anatomic', 'Bone', 'Pelvic', 'Pelvis', 'Bony Pelvis Left'),
Structure(re.compile(r'^(Bone_Pelvic~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Pelvic_R', '20226', 'Anatomic', 'Bone', 'Pelvic', 'Pelvis', 'Bony Pelvis Right'),
Structure(re.compile(r'^(Bone_Sphenoid~?(\^[\w\d_\+-]+)?)$'), 'Bone_Sphenoid', '52736', 'Anatomic', 'Bone', 'Sphenoid', 'Head and Neck', 'Sphenoid Bone'),
Structure(re.compile(r'^(Bone_Temporal~?(\^[\w\d_\+-]+)?)$'), 'Bone_Temporal', '52737', 'Anatomic', 'Bone', 'Temporal', 'Head and Neck', 'Temporal Bone'),
Structure(re.compile(r'^(Bone_Temporal~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Temporal_L', '52739', 'Anatomic', 'Bone', 'Temporal', 'Head and Neck', 'Temporal Bone Left'),
Structure(re.compile(r'^(Bone_Temporal~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Temporal_R', '52738', 'Anatomic', 'Brain', 'Temporal', 'Head and Neck', 'Temporal Bone Right'),
Structure(re.compile(r'^(Bone_Zygomatic~?_L(\^[\w\d_\+-]+)?)$'), 'Bone_Zygomatic_L', '52893', 'Anatomic', 'Bone', 'Zygomatic', 'Head and Neck', 'Zygomatic Bone Left'),
Structure(re.compile(r'^(Bone_Zygomatic~?_R(\^[\w\d_\+-]+)?)$'), 'Bone_Zygomatic_R', '52892', 'Anatomic', 'Bone', 'Zygomatic', 'Head and Neck', 'Zygomatic Bone Right'),
Structure(re.compile(r'^(Bone_Zygomatics~?(\^[\w\d_\+-]+)?)$'), 'Bone_Zygomatics', '52747', 'Anatomic', 'Bone', 'Zygomatic', 'Head and Neck', 'Zygomatic Bone'),
Structure(re.compile(r'^(BoneMarrow~?(\^[\w\d_\+-]+)?)$'), 'BoneMarrow', '9608', 'Anatomic', 'Bone', 'Marrow', 'Body', 'Bone Marrow'),
Structure(re.compile(r'^(BoneMarrow_Act~?(\^[\w\d_\+-]+)?)$'), 'BoneMarrow_Act', 'nan', 'Anatomic', 'Bone', 'Marrow', 'Body', 'Active Bone Marrow'),
Structure(re.compile(r'^(Boost~?(\^[\w\d_\+-]+)?)$'), 'Boost', 'nan', 'Non-Anatomic', 'Body', 'nan', 'Body', 'Boost Volume'),
Structure(re.compile(r'^(Bowel~?(\^[\w\d_\+-]+)?)$'), 'Bowel', '7199', 'Anatomic', 'Bowel', 'nan', 'Abdomen', 'nan'),
Structure(re.compile(r'^(Bowel_Large~?(\^[\w\d_\+-]+)?)$'), 'Bowel_Large', '7201', 'Anatomic', 'Bowel', 'Large', 'Pelvis', 'Large Bowel'),
Structure(re.compile(r'^(Bowel_Small~?(\^[\w\d_\+-]+)?)$'), 'Bowel_Small', '7200', 'Anatomic', 'Bowel', 'nan', 'Abdomen', 'Small Bowel (small intestine)'),
Structure(re.compile(r'^(BrachialPlex~?_L(\^[\w\d_\+-]+)?)$'), 'BrachialPlex_L', '45245', 'Anatomic', 'Nerve', 'Brachial', 'Thorax', 'Brachial plexus Left'),
Structure(re.compile(r'^(BrachialPlex~?_R(\^[\w\d_\+-]+)?)$'), 'BrachialPlex_R', '45244', 'Anatomic', 'Nerve', 'Brachial', 'Thorax', 'Brachial plexus Right'),
Structure(re.compile(r'^(BrachialPlexs~?(\^[\w\d_\+-]+)?)$'), 'BrachialPlexs', '5906', 'Anatomic', 'Nerve', 'Brachial', 'Thorax', 'Brachial plexus'),
Structure(re.compile(r'^(Brain~?(\^[\w\d_\+-]+)?)$'), 'Brain', '50801', 'Anatomic', 'Brain', 'Brain', 'Head and Neck', 'Brain'),
Structure(re.compile(r'^(Brain-CTV(\^[\w\d_\+-]+)?)$'), 'Brain-CTV', 'nan', 'Derived', 'Brain', 'Brain', 'Head and Neck', 'Brain minus the CTV'),
Structure(re.compile(r'^(Brain-GTV(\^[\w\d_\+-]+)?)$'), 'Brain-GTV', 'nan', 'Derived', 'Brain', 'Brain', 'Head and Neck', 'Brain minus the GTV'),
Structure(re.compile(r'^(Brain-PTV(\^[\w\d_\+-]+)?)$'), 'Brain-PTV', 'nan', 'Derived', 'Brain', 'Brain', 'Head and Neck', 'Brain minus the PTV'),
Structure(re.compile(r'^(Brainstem~?(\^[\w\d_\+-]+)?)$'), 'Brainstem', '79876', 'Anatomic', 'Nerve', 'Brainstem', 'Head and Neck', 'Brain Stem'),
Structure(re.compile(r'^(Brainstem_Core~?(\^[\w\d_\+-]+)?)$'), 'Brainstem_Core', 'nan', 'Anatomic', 'Nerve', 'Brainstem', 'Head and Neck', 'Core of the brainstem'),
Structure(re.compile(r'^(Brainstem~?_PRV?\d{0,2}(\^[\w\d_\+-]+)?)$'), 'Brainstem_PRVxx', 'nan', 'PRV', 'Nerve', 'PRV', 'Head and Neck', 'PRV for the Brainstem or PRV margin on the brain stem that is an xx millimeter expansion'),
Structure(re.compile(r'^(Brainstem_Surf~?(\^[\w\d_\+-]+)?)$'), 'Brainstem_Surf', 'nan', 'Anatomic', 'Nerve', 'Brainstem', 'Head and Neck', 'Surface of the brainstem'),
Structure(re.compile(r'^(Breast~?_L(\^[\w\d_\+-]+)?)$'), 'Breast_L', '321497', 'Anatomic', 'Breast', 'nan', 'Thorax', 'Breast Left'),
Structure(re.compile(r'^(Breast~?_R(\^[\w\d_\+-]+)?)$'), 'Breast_R', '321496', 'Anatomic', 'Breast', 'nan', 'Thorax', 'Breast Right'),
Structure(re.compile(r'^(Breasts~?(\^[\w\d_\+-]+)?)$'), 'Breasts', '268893', 'Anatomic', 'Breast', 'nan', 'Thorax', 'Both breasts'),
Structure(re.compile(r'^(Bronchus~?(\^[\w\d_\+-]+)?)$'), 'Bronchus', '26660', 'Anatomic', 'Lung', 'Bronchus', 'Thorax', 'Bronchial tree'),
Structure(re.compile(r'^(Bronchus~?_L(\^[\w\d_\+-]+)?)$'), 'Bronchus_L', '26662', 'Anatomic', 'Lung', 'Bronchus', 'Thorax', 'Bronchial tree Left'),
Structure(re.compile(r'^(Bronchus_Main~?(\^[\w\d_\+-]+)?)$'), 'Bronchus_Main', '7405', 'Anatomic', 'Lung', 'Bronchus', 'Thorax', 'Main Bronchus'),
Structure(re.compile(r'^(Bronchus_Main~?_L(\^[\w\d_\+-]+)?)$'), 'Bronchus_Main_L', '7396', 'Anatomic', 'Lung', 'Bronchus', 'Thorax', 'Main Bronchus Left'),
Structure(re.compile(r'^(Bronchus_Main~?_R(\^[\w\d_\+-]+)?)$'), 'Bronchus_Main_R', '7395', 'Anatomic', 'Lung', 'Bronchus', 'Thorax', 'Main Bronchus Right'),
Structure(re.compile(r'^(Bronchus_PRV?\d{0,2}~?(\^[\w\d_\+-]+)?)$'), 'Bronchus_PRVxx', 'nan', 'Anatomic', 'Lung', 'Bronchus', 'Thorax', 'A PRV expansion on the Bronchus that is xx millimeters thick'),
Structure(re.compile(r'^(Bronchus~?_R(\^[\w\d_\+-]+)?)$'), 'Bronchus_R', '26661', 'Anatomic', 'Lung', 'Bronchus', 'Thorax', 'Bronchial tree Right'),
Structure(re.compile(r'^(Canal_Anal~?(\^[\w\d_\+-]+)?)$'), 'Canal_Anal', '15703', 'Anatomic', 'Bowel', 'Anus', 'Pelvis', 'Anal Canal'),
Structure(re.compile(r'^(Carina~?(\^[\w\d_\+-]+)?)$'), 'Carina', '7465', 'Anatomic', 'Carina', 'nan', 'Thorax', 'Carina'),
Structure(re.compile(r'^(Cartlg_Thyroid~?(\^[\w\d_\+-]+)?)$'), 'Cartlg_Thyroid', '55099', 'Anatomic', 'Cartilage', 'Thyroid', 'Thorax', 'Thyroid cartilage'),
Structure(re.compile(r'^(CaudaEquina~?(\^[\w\d_\+-]+)?)$'), 'CaudaEquina', '52590', 'Anatomic', 'Nerve', 'CaudaEquina', 'Pelvis', 'Cauda equina'),
Structure(re.compile(r'^(Cavernosum~?(\^[\w\d_\+-]+)?)$'), 'Cavernosum', '75189', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Penis Corpus Cavernosum'),
Structure(re.compile(r'^(Cavity_Nasal~?(\^[\w\d_\+-]+)?)$'), 'Cavity_Nasal', '54378', 'Anatomic', 'Nose', 'Nasal', 'Head and Neck', 'Nasal Cavity'),
Structure(re.compile(r'^(Cavity_Oral~?(\^[\w\d_\+-]+)?)$'), 'Cavity_Oral', '20292', 'Anatomic', 'Mouth', 'Oral Cavity', 'Head and Neck', 'Oral cavity'),
Structure(re.compile(r'^(Cecum~?(\^[\w\d_\+-]+)?)$'), 'Cecum', '14541', 'Anatomic', 'Bowel', 'nan', 'Abdomen', 'Large bowel - Cecum'),
Structure(re.compile(r'^(Cerebellum~?(\^[\w\d_\+-]+)?)$'), 'Cerebellum', '67944', 'Anatomic', 'Brain', 'Cerebellum', 'Head and Neck', 'Cerebellum'),
Structure(re.compile(r'^(Cerebrum~?(\^[\w\d_\+-]+)?)$'), 'Cerebrum', '62000', 'Anatomic', 'Brain', 'Cerebrum', 'Head and Neck', 'Cerebrum'),
Structure(re.compile(r'^(Cerebrum~?_L(\^[\w\d_\+-]+)?)$'), 'Cerebrum_L', '61819', 'Anatomic', 'Brain', 'Cerebrum', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Cerebrum~?_R(\^[\w\d_\+-]+)?)$'), 'Cerebrum_R', '67292', 'Anatomic', 'Brain', 'Cerebrum', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Cervix~?(\^[\w\d_\+-]+)?)$'), 'Cervix', '17740', 'Anatomic', 'Cervix', 'nan', 'Pelvis', 'Cervix of uterus'),
Structure(re.compile(r'^(Chestwall~?(\^[\w\d_\+-]+)?)$'), 'Chestwall', '50060', 'Anatomic', 'Chest wall', 'nan', 'Thorax', 'Chest wall'),
Structure(re.compile(r'^(Chestwall~?_L(\^[\w\d_\+-]+)?)$'), 'Chestwall_L', '25559', 'Anatomic', 'Chest wall', 'nan', 'Thorax', 'Left Chest Wall'),
Structure(re.compile(r'^(Chestwall~?_R(\^[\w\d_\+-]+)?)$'), 'Chestwall_R', '25558', 'Anatomic', 'Chest wall', 'nan', 'Thorax', 'Right Chest Wall'),
Structure(re.compile(r'^(Cist_Pontine~?(\^[\w\d_\+-]+)?)$'), 'Cist_Pontine', '83719', 'Anatomic', 'Brain', 'nan', 'Head and Neck', 'Pontine Cistern'),
Structure(re.compile(r'^(Cist_Suprasellar~?(\^[\w\d_\+-]+)?)$'), 'Cist_Suprasellar', 'nan', 'Anatomic', 'Brain', 'nan', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Clavicle~?_L(\^[\w\d_\+-]+)?)$'), 'Clavicle_L', '13323', 'Anatomic', 'Bone', 'Clavicle', 'Thorax', 'Clavicle Left'),
Structure(re.compile(r'^(Clavicle~?_R(\^[\w\d_\+-]+)?)$'), 'Clavicle_R', '13322', 'Anatomic', 'Bone', 'Clavicle', 'Thorax', 'Clavicle Right'),
Structure(re.compile(r'^(CN_III~?(\^[\w\d_\+-]+)?)$'), 'CN_III', '50864', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Third Cranial Nerve (Oculomotor nerve)'),
Structure(re.compile(r'^(CN_III~?_L(\^[\w\d_\+-]+)?)$'), 'CN_III_L', '50880', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Third Cranial Nerve (Oculomotor nerve) Left'),
Structure(re.compile(r'^(CN_III~?_R(\^[\w\d_\+-]+)?)$'), 'CN_III_R', '50879', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Third Cranial Nerve (Oculomotor nerve) Right'),
Structure(re.compile(r'^(CN_IX~?(\^[\w\d_\+-]+)?)$'), 'CN_IX', '50870', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Ninth Cranial Nerve (Glossopharyngeal nerve) '),
Structure(re.compile(r'^(CN_IX~?_L(\^[\w\d_\+-]+)?)$'), 'CN_IX_L', '50892', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Ninth Cranial Nerve (Glossopharyngeal nerve) Left'),
Structure(re.compile(r'^(CN_IX~?_R(\^[\w\d_\+-]+)?)$'), 'CN_IX_R', '50870', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Ninth Cranial Nerve (Glossopharyngeal nerve) Right'),
Structure(re.compile(r'^(CN_V~?(\^[\w\d_\+-]+)?)$'), 'CN_V', '50866', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Fifth Cranial Nerve (Trigeminal nerve)'),
Structure(re.compile(r'^(CN_V~?_L(\^[\w\d_\+-]+)?)$'), 'CN_V_L', '50885', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Fifth Cranial Nerve (Trigeminal nerve) Left'),
Structure(re.compile(r'^(CN_V~?_R(\^[\w\d_\+-]+)?)$'), 'CN_V_R', '50884', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Fifth Cranial Nerve (Trigeminal nerve) Right'),
Structure(re.compile(r'^(CN_VI~?(\^[\w\d_\+-]+)?)$'), 'CN_VI', '50867', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Sixth Cranial Nerve (Abducens nerve)'),
Structure(re.compile(r'^(CN_VI~?_L(\^[\w\d_\+-]+)?)$'), 'CN_VI_L', '50887', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Sixth Cranial Nerve (Abducens nerve) Left'),
Structure(re.compile(r'^(CN_VI~?_R(\^[\w\d_\+-]+)?)$'), 'CN_VI_R', '50886', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Sixth Cranial Nerve (Abducens nerve) Right'),
Structure(re.compile(r'^(CN_VII~?(\^[\w\d_\+-]+)?)$'), 'CN_VII', '50868', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Seventh Cranial Nerve (Facial)'),
Structure(re.compile(r'^(CN_VII~?_L(\^[\w\d_\+-]+)?)$'), 'CN_VII_L', '50889', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Seventh Cranial Nerve (Facial) Left'),
Structure(re.compile(r'^(CN_VII~?_R(\^[\w\d_\+-]+)?)$'), 'CN_VII_R', '50888', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Seventh Cranial Nerve (Facial) Right'),
Structure(re.compile(r'^(CN_VIII~?(\^[\w\d_\+-]+)?)$'), 'CN_VIII', '50869', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Eighth Cranial (Vestibulocochlear) Nerve'),
Structure(re.compile(r'^(CN_VIII~?_L(\^[\w\d_\+-]+)?)$'), 'CN_VIII_L', '50891', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Eighth Cranial (Vestibulocochlear) Nerve Left'),
Structure(re.compile(r'^(CN_VIII~?_R(\^[\w\d_\+-]+)?)$'), 'CN_VIII_R', '50890', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Eighth Cranial (Vestibulocochlear) Nerve Right'),
Structure(re.compile(r'^(CN_XI~?(\^[\w\d_\+-]+)?)$'), 'CN_XI', '6720', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Eleventh Cranial Nerve (Spinal accessory nerve)'),
Structure(re.compile(r'^(CN_XI~?_L(\^[\w\d_\+-]+)?)$'), 'CN_XI_L', '50899', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Eleventh Cranial Nerve (Spinal accessory nerve) Left'),
Structure(re.compile(r'^(CN_XI~?_R(\^[\w\d_\+-]+)?)$'), 'CN_XI_R', '50897', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Eleventh Cranial Nerve (Spinal accessory nerve) Right'),
Structure(re.compile(r'^(CN_XII~?(\^[\w\d_\+-]+)?)$'), 'CN_XII', '50871', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Twelfth Cranial Nerve (Hypoglossal nerve)'),
Structure(re.compile(r'^(CN_XII~?_L(\^[\w\d_\+-]+)?)$'), 'CN_XII_L', '50903', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Twelfth Cranial Nerve (Hypoglossal nerve) Left'),
Structure(re.compile(r'^(CN_XII~?_R(\^[\w\d_\+-]+)?)$'), 'CN_XII_R', '50901', 'Anatomic', 'Nerve', 'Cranial', 'Head and Neck', 'Twelfth Cranial Nerve (Hypoglossal nerve) Right'),
Structure(re.compile(r'^(Cochlea~?(\^[\w\d_\+-]+)?)$'), 'Cochlea', '60201', 'Anatomic', 'Ear', 'Cochlea', 'Head and Neck', 'Cochlea'),
Structure(re.compile(r'^(Cochlea~?_L(\^[\w\d_\+-]+)?)$'), 'Cochlea_L', '60203', 'Anatomic', 'Ear', 'Cochlea', 'Head and Neck', 'Left Cochlea'),
Structure(re.compile(r'^(Cochlea~?_R(\^[\w\d_\+-]+)?)$'), 'Cochlea_R', '60202', 'Anatomic', 'Ear', 'Cochlea', 'Head and Neck', 'Right Cochlea'),
Structure(re.compile(r'^(Colon~?(\^[\w\d_\+-]+)?)$'), 'Colon', '14543', 'Anatomic', 'Bowel', 'Colon', 'Abdomen', 'Colon'),
Structure(re.compile(r'^(Colon_Ascending~?(\^[\w\d_\+-]+)?)$'), 'Colon_Ascending', '14545', 'Anatomic', 'Bowel', 'Colon', 'Abdomen', 'Large bowel - Ascending colon'),
Structure(re.compile(r'^(Colon_Decending~?(\^[\w\d_\+-]+)?)$'), 'Colon_Decending', '14547', 'Anatomic', 'Bowel', 'Colon', 'Abdomen', 'Large bowel - Descending colon'),
Structure(re.compile(r'^(Colon_PTV?\d{0,2}~?(\^[\w\d_\+-]+)?)$'), 'Colon_PTVxx', 'nan', 'Anatomic', 'Bowel', 'nan', 'Abdomen', 'PRV created with xx mm expansion on the left optic nerve'),
Structure(re.compile(r'^(Colon_Sigmoid~?(\^[\w\d_\+-]+)?)$'), 'Colon_Sigmoid', '14548', 'Anatomic', 'Bowel', 'Colon', 'Abdomen', 'Large bowel - Sigmoid colon'),
Structure(re.compile(r'^(Colon_Transverse~?(\^[\w\d_\+-]+)?)$'), 'Colon_Transverse', '14546', 'Anatomic', 'Bowel', 'Colon', 'Abdomen', 'Large bowel -Transverse colon'),
Structure(re.compile(r'^(Cornea~?(\^[\w\d_\+-]+)?)$'), 'Cornea', '58238', 'Anatomic', 'Eye', 'Cornea', 'Head and Neck', 'Cornea'),
Structure(re.compile(r'^(Cornea~?_L(\^[\w\d_\+-]+)?)$'), 'Cornea_L', '58240', 'Anatomic', 'Eye', 'Cornea', 'Head and Neck', 'Cornea Left'),
Structure(re.compile(r'^(Cornea~?_R(\^[\w\d_\+-]+)?)$'), 'Cornea_R', '58239', 'Anatomic', 'Eye', 'Cornea', 'Head and Neck', 'Cornea Right'),
Structure(re.compile(r'^(CribriformPlate~?(\^[\w\d_\+-]+)?)$'), 'CribriformPlate', '52890', 'Anatomic', 'Bone', 'Skull', 'Head and Neck', 'Cribriform Plate'),
Structure(re.compile(r'^(Cricoid~?(\^[\w\d_\+-]+)?)$'), 'Cricoid', '9615', 'Anatomic', 'Cartilage', 'Cricoid', 'Head and Neck', 'Cricoid cartilage'),
Structure(re.compile(r'^(Cricopharyngeus~?(\^[\w\d_\+-]+)?)$'), 'Cricopharyngeus', '46661', 'Anatomic', 'Pharynx', 'Constrictors', 'Head and Neck', 'Cricopharyngeal part of inferior pharyngeal constrictor'),
Structure(re.compile(r'^(I?CTV(p|n|(sb))?\d{0,2}(_((Postop)|(Preop)|(TumorBed)|(Boost)|(Eval)|(A_Aorta)|(A_Aorta_Asc)|(A_Brachiocephls)|(A_Carotid)|(A_Carotid_L)|(A_Carotid_R)|(A_Celiac)|(A_Coronary)|(A_Coronary_L)|(A_Coronary_R)|(A_Femoral_Cflx_L)|(A_Femoral_Cflx_R)|(A_Femoral_L)|(A_Femoral_R)|(A_Humeral_Cflx_L)|(A_Humeral_Cflx_R)|(A_Humeral_L)|(A_Humeral_R)|(A_Hypophyseal_I)|(A_Hypophyseal_S)|(A_Iliac_Cflx_L)|(A_Iliac_Cflx_R)|(A_Iliac_Ext_L)|(A_Iliac_Ext_R)|(A_Iliac_Int_L)|(A_Iliac_Int_R)|(A_Iliac_L)|(A_Iliac_R)|(A_LAD)|(A_Mesenteric_I)|(A_Mesenteric_S)|(A_Pulmonary)|(A_Subclavian)|(A_Subclavian_L)|(A_Subclavian_R)|(A_Vertebral)|(A_Vertebral_L)|(A_Vertebral_R)|(Acetabulum_L)|(Acetabulum_R)|(Acetabulums)|(AirWay_Dist)|(AirWay_Prox)|(Anus)|(Appendix)|(Arytenoid)|(Arytenoid_L)|(Arytenoid_R)|(Atrium)|(Atrium_L)|(Atrium_R)|(BileDuct_Common)|(Bladder)|(Bladder_Wall)|(Body)|(Bone)|(Bone_Ethmoid)|(Bone_Frontal)|(Bone_Hyoid)|(Bone_Ilium)|(Bone_Ilium_L)|(Bone_Ilium_R)|(Bone_Incus)|(Bone_Incus_L)|(Bone_Incus_R)|(Bone_Ischium_L)|(Bone_Ischium_R)|(Bone_Lacrimal)|(Bone_Lacrimal_L)|(Bone_Lacrimal_R)|(Bone_Mandible)|(Bone_Mastoid_L)|(Bone_Mastoid_R)|(Bone_Nasal)|(Bone_Nasal_L)|(Bone_Nasal_R)|(Bone_Occipital)|(Bone_Palatine)|(Bone_Palatine_L)|(Bone_Palatine_R)|(Bone_Parietal)|(Bone_Parietal_L)|(Bone_Parietal_R)|(Bone_Pelvic)|(Bone_Pelvic_L)|(Bone_Pelvic_R)|(Bone_Sphenoid)|(Bone_Temporal)|(Bone_Temporal_L)|(Bone_Temporal_R)|(Bone_Zygomatic_L)|(Bone_Zygomatic_R)|(Bone_Zygomatics)|(BoneMarrow)|(BoneMarrow_Act)|(Bowel)|(Bowel_Large)|(Bowel_Small)|(BrachialPlex_L)|(BrachialPlex_R)|(BrachialPlexs)|(Brain)|(Brainstem)|(Brainstem_Core)|(Brainstem_Surf)|(Breast_L)|(Breast_R)|(Breasts)|(Bronchus)|(Bronchus_L)|(Bronchus_Main)|(Bronchus_Main_L)|(Bronchus_Main_R)|(Bronchus_PRVxx)|(Bronchus_R)|(Canal_Anal)|(Carina)|(Cartlg_Thyroid)|(CaudaEquina)|(Cavernosum)|(Cavity_Nasal)|(Cavity_Oral)|(Cecum)|(Cerebellum)|(Cerebrum)|(Cerebrum_L)|(Cerebrum_R)|(Cervix)|(Chestwall)|(Chestwall_L)|(Chestwall_R)|(Cist_Pontine)|(Cist_Suprasellar)|(Clavicle_L)|(Clavicle_R)|(CN_III)|(CN_III_L)|(CN_III_R)|(CN_IX)|(CN_IX_L)|(CN_IX_R)|(CN_V)|(CN_V_L)|(CN_V_R)|(CN_VI)|(CN_VI_L)|(CN_VI_R)|(CN_VII)|(CN_VII_L)|(CN_VII_R)|(CN_VIII)|(CN_VIII_L)|(CN_VIII_R)|(CN_XI)|(CN_XI_L)|(CN_XI_R)|(CN_XII)|(CN_XII_L)|(CN_XII_R)|(Cochlea)|(Cochlea_L)|(Cochlea_R)|(Colon)|(Colon_Ascending)|(Colon_Decending)|(Colon_PTVxx)|(Colon_Sigmoid)|(Colon_Transverse)|(Cornea)|(Cornea_L)|(Cornea_R)|(CribriformPlate)|(Cricoid)|(Cricopharyngeus)|(Dens)|(Diaphragm)|(Duodenum)|(Ear_External_L)|(Ear_External_R)|(Ear_Externals)|(Ear_Internal_L)|(Ear_Internal_R)|(Ear_Internals)|(Ear_Middle)|(Ear_Middle_L)|(Ear_Middle_R)|(Edema)|(Elbow)|(Elbow_L)|(Elbow_R)|(Esophagus)|(Esophagus_I)|(Esophagus_M)|(Esophagus_NAdj)|(Esophagus_S)|(External)|(Eye_L)|(Eye_R)|(Eyes)|(Femur_Base_L)|(Femur_Base_R)|(Femur_Head_L)|(Femur_Head_R)|(Femur_Joint_L)|(Femur_Joint_R)|(Femur_L)|(Femur_Neck_L)|(Femur_Neck_R)|(Femur_R)|(Femur_Shaft_L)|(Femur_Shaft_R)|(Femurs)|(Fibula)|(Fibula_L)|(Fibula_R)|(Fossa_Jugular)|(Fossa_Posterior)|(Gallbladder)|(Genitals)|(Glnd_Adrenal_L)|(Glnd_Adrenal_R)|(Glnd_Lacrimal)|(Glnd_Lacrimal_L)|(Glnd_Lacrimal_R)|(Glnd_Parathyroid)|(Glnd_Subling_L)|(Glnd_Subling_R)|(Glnd_Sublings)|(Glnd_Submand_L)|(Glnd_Submand_R)|(Glnd_Submands)|(Glnd_Thymus)|(Glnd_Thyroid)|(Glottis)|(GreatVes)|(GreatVes_NAdj)|(GrowthPlate_L)|(GrowthPlate_R)|(Hardpalate)|(Heart)|(Hemisphere_L)|(Hemisphere_R)|(Hemispheres)|(Hippocampi)|(Hippocampus_L)|(Hippocampus_R)|(Humerus_L)|(Humerus_R)|(Hypothalmus)|(Ileum)|(Jejunum)|(Jejunum_Ileum)|(Joint_Elbow)|(Joint_Elbow_L)|(Joint_Elbow_R)|(Joint_Glenohum)|(Joint_Glenohum_L)|(Joint_Glenohum_R)|(Joint_Surface)|(Joint_TM)|(Joint_TM_L)|(Joint_TM_R)|(Kidney_Cortex)|(Kidney_Cortex_L)|(Kidney_Cortex_R)|(Kidney_Hilum_L)|(Kidney_Hilum_R)|(Kidney_Hilums)|(Kidney_L)|(Kidney_Pelvis_L)|(Kidney_Pelvis_R)|(Kidney_R)|(Kidneys)|(Knee)|(Knee_L)|(Knee_R)|(Laryngl_Pharynx)|(Larynx)|(Larynx_SG)|(Lens)|(Lens_L)|(Lens_R)|(Lig_Hepatogastrc)|(Lips)|(Liver)|(LN)|(LN_Ax_Apical)|(LN_Ax_Apical_L)|(LN_Ax_Apical_R)|(LN_Ax_Central_L)|(LN_Ax_Central_R)|(LN_Ax_Centrals)|(LN_Ax_L)|(LN_Ax_L1_L)|(LN_Ax_L1_R)|(LN_Ax_L2_L)|(LN_Ax_L2_R)|(LN_Ax_L3_L)|(LN_Ax_L3_R)|(LN_Ax_Lateral_L)|(LN_Ax_Lateral_R)|(LN_Ax_Laterals)|(LN_Ax_Pectoral_L)|(LN_Ax_Pectoral_R)|(LN_Ax_Pectorals)|(LN_Ax_R)|(LN_Ax_Subscap_L)|(LN_Ax_Subscap_R)|(LN_Ax_Subscaps)|(LN_Brachioceph_L)|(LN_Brachioceph_R)|(LN_Brachiocephs)|(LN_Bronchpulm_L)|(LN_Bronchpulm_R)|(LN_Bronchpulms)|(LN_Diaphragmatic)|(LN_Iliac_Ext_L)|(LN_Iliac_Ext_R)|(LN_Iliac_Int_L)|(LN_Iliac_L)|(LN_Iliac_R)|(LN_IMN_L)|(LN_IMN_R)|(LN_IMNs)|(LN_Inguinofem)|(LN_Inguinofem_L)|(LN_Inguinofem_R)|(LN_Intercostals)|(LN_L)|(LN_Ligamentarter)|(LN_lliac_Int_R)|(LN_Mediastinals)|(LN_Neck_IA_L)|(LN_Neck_IA_R)|(LN_Neck_IB_L)|(LN_Neck_IB_R)|(LN_Neck_II_L)|(LN_Neck_II_R)|(LN_Neck_IIA_L)|(LN_Neck_IIA_R)|(LN_Neck_IIB_L)|(LN_Neck_IIB_R)|(LN_Neck_III_L)|(LN_Neck_III_R)|(LN_Neck_IV_L)|(LN_Neck_IV_R)|(LN_Neck_V_L)|(LN_Neck_V_R)|(LN_Neck_VA_L)|(LN_Neck_VA_R)|(LN_Neck_VB_L)|(LN_Neck_VB_R)|(LN_Neck_VC_L)|(LN_Neck_VC_R)|(LN_Neck_VI_L)|(LN_Neck_VI_R)|(LN_Neck_VII_L)|(LN_Neck_VII_R)|(LN_Obturator_L)|(LN_Obturator_R)|(LN_Paraaortic)|(LN_Paramammary_L)|(LN_Paramammary_R)|(LN_Paramammarys)|(LN_Parasternal_L)|(LN_Parasternal_R)|(LN_Parasternals)|(LN_Pelvic_L)|(LN_Pelvic_R)|(LN_Pelvics)|(LN_Portahepatis)|(LN_Presacral_L)|(LN_Presacral_R)|(LN_Pulmonary_L)|(LN_Pulmonary_R)|(LN_Pulmonarys)|(LN_R)|(LN_Sclav_L)|(LN_Sclav_R)|(LN_Supmammary_L)|(LN_Supmammary_R)|(LN_Supmammarys)|(LN_Trachbrnchs)|(LN_Trachbrnchs_L)|(LN_Trachbrnchs_R)|(Lobe_Frontal)|(Lobe_Frontal_L)|(Lobe_Frontal_R)|(Lobe_Occipital)|(Lobe_Occipital_L)|(Lobe_Occipital_R)|(Lobe_Parietal)|(Lobe_Parietal_L)|(Lobe_Parietal_R)|(Lobe_Temporal)|(Lobe_Temporal_L)|(Lobe_Temporal_R)|(Lung_L)|(Lung_LLL)|(Lung_LUL)|(Lung_R)|(Lung_RLL)|(Lung_RML)|(Lung_RUL)|(Lungs)|(Malleus)|(Malleus_L)|(Malleus_R)|(Maxilla)|(Maxilla_L)|(Maxilla_R)|(Mediastinum)|(Musc)|(Musc_Constrict)|(Musc_Constrict_I)|(Musc_Constrict_M)|(Musc_Constrict_S)|(Musc_Digastric_L)|(Musc_Digastric_R)|(Musc_Masseter)|(Musc_Masseter_L)|(Musc_Masseter_R)|(Musc_Platysma_L)|(Musc_Platysma_R)|(Musc_Pterygoid_L)|(Musc_Pterygoid_R)|(Musc_Sclmast_L)|(Musc_Sclmast_R)|(Musc_Temporal_L)|(Musc_Temporal_R)|(Nasalconcha_LI)|(Nasalconcha_RI)|(Nasopharynx)|(Nose)|(Nrv_Peripheral)|(Nrv_Root)|(OpticChiasm)|(OpticNrv)|(OpticNrv_L)|(OpticNrv_R)|(Orbit_L)|(Orbit_R)|(Oropharynx)|(Ovaries)|(Ovary_L)|(Ovary_R)|(Palate_Soft)|(PancJejuno)|(Pancreas)|(Pancreas_Head)|(Pancreas_Tail)|(Parametrium)|(Parotid_L)|(Parotid_R)|(Parotids)|(PenileBulb)|(Penis)|(Pericardium)|(Perineum)|(Peritoneum)|(Pharynx)|(Pineal)|(Pituitary)|(Pons)|(Proc_Condyloid_L)|(Proc_Condyloid_R)|(Proc_Coronoid_L)|(Proc_Coronoid_R)|(Prostate)|(ProstateBed)|(Prosthesis)|(Pterygoid_Lat_L)|(Pterygoid_Lat_R)|(Pterygoid_Med_L)|(Pterygoid_Med_R)|(PubicSymphys)|(PubicSymphys_L)|(PubicSymphys_R)|(Radius_L)|(Radius_R)|(Rectal_Wall)|(Rectum)|(Retina_L)|(Retina_R)|(Retinas)|(Rib)|(Rib01_L)|(Rib01_R)|(Rib02_L)|(Rib02_R)|(Rib03_L)|(Rib03_R)|(Rib04_L)|(Rib04_R)|(Rib05_L)|(Rib05_R)|(Rib06_L)|(Rib06_R)|(Rib07_L)|(Rib07_R)|(Rib08_L)|(Rib08_R)|(Rib09_L)|(Rib09_R)|(Rib10_L)|(Rib10_R)|(Rib11_L)|(Rib11_R)|(Rib12_L)|(Rib12_R)|(SacralPlex)|(Sacrum)|(Scalp)|(Scapula_L)|(Scapula_R)|(Scar)|(Scar_Boost)|(Scrotum)|(SeminalVes)|(SeminalVes_Dist)|(SeminalVes_Prox)|(Sinus_Ethmoid)|(Sinus_Frontal)|(Sinus_Frontal_L)|(Sinus_Frontal_R)|(Sinus_Maxilry)|(Sinus_Maxilry_L)|(Sinus_Maxilry_R)|(Sinus_Sphenoid)|(Sinus_Sphenoid_L)|(Sinus_Sphenoid_R)|(Skin)|(Skin_Perineum)|(Skin_Peritoneum)|(Skull)|(Spc)|(Spc_Bowel )|(Spc_Bowel_Small)|(Spc_Retrophar_L)|(Spc_Retrophar_R)|(Spc_Retrophars)|(Spc_Retrosty)|(Spc_Retrosty_L)|(Spc_Retrosty_R)|(Spc_Supraclav_L)|(Spc_Supraclav_R)|(Sphincter_Anal)|(SpinalCanal)|(SpinalCord)|(SpinalCord_Cerv)|(SpinalCord_Lum)|(SpinalCord_Sac)|(SpinalCord_Thor)|(Spleen)|(Spleen_Hilum)|(Spongiosum)|(Stapes)|(Stapes_L)|(Stapes_R)|(Stomach)|(Strct )|(Strct_Suprapatel)|(Surf_Eye)|(SurgicalBed)|(Sys_Ventricular)|(Tendon )|(Tendon_Quad)|(Testis)|(Testis_L)|(Testis_R)|(ThecalSac)|(Thoracic_Duct)|(Tongue)|(Tongue_All)|(Tongue_Base)|(Tongue_Base_L)|(Tongue_Base_R)|(Tongue_Oral)|(Tongue_Oral_L)|(Tongue_Oral_R)|(Tonsil)|(Trachea)|(Trachea_NAdj)|(Ureter_L)|(Ureter_R)|(UreterDivert)|(Ureters)|(Urethra)|(Urethra_Prostatc)|(Uterus)|(V_Azygos)|(V_Brachioceph_L)|(V_Brachioceph_R)|(V_Iliac_Ext_L)|(V_Iliac_Ext_R)|(V_Iliac_Int_L)|(V_Iliac_Int_R)|(V_Iliac_L)|(V_Iliac_R)|(V_Jugular)|(V_Jugular_Ext_L)|(V_Jugular_Ext_R)|(V_Jugular_Int_L)|(V_Jugular_Int_R)|(V_Portal)|(V_Pulmonary)|(V_Subclavian_L)|(V_Subclavian_R)|(V_Subclavians)|(V_Venacava_I)|(V_Venacava_S)|(Vagina)|(Vagina_Surf)|(VaginalCuff)|(Valve)|(Valve_Aortic)|(Valve_Mitral)|(Valve_Pulmonic)|(Valve_Tricuspid)|(VB)|(VB_C)|(VB_C1)|(VB_C2)|(VB_C3)|(VB_C4)|(VB_C5)|(VB_C6)|(VB_C7)|(VB_L)|(VB_L1)|(VB_L2)|(VB_L3)|(VB_L4)|(VB_L5)|(VB_S)|(VB_S1)|(VB_S2)|(VB_S3)|(VB_S4)|(VB_S5)|(VB_T)|(VB_T01)|(VB_T02)|(VB_T03)|(VB_T04)|(VB_T05)|(VB_T06)|(VB_T07)|(VB_T08)|(VB_T09)|(VB_T10)|(VB_T11)|(VB_T12)|(VBs)|(Ventricle)|(Ventricle_L)|(Ventricle_R)|(VocalCord_L)|(VocalCord_R)|(VocalCords)|(Vomer)|(Vulva)|(Wall_Vagina)|(Thalami)|(Thalamus_L)|(Thalamus_R)|(Third_Ventricle)|(InternCapsule_L)|(InternCapsule_R)))?(_((High)|(Mid(\d{2})?)|(Low)))?(-\d{2})?(\^[\w\d_\+-]+)?)$'), 'CTV', 'nan', 'Target', 'CTV', 'nan', 'Body', 'Clinical Tumor Volume'),
Structure(re.compile(r'^(Dens~?(\^[\w\d_\+-]+)?)$'), 'Dens', '24043', 'Anatomic', 'Bone', 'Spine', 'Head and Neck', 'Cervical vertebrae - Bony part of dens of axis'),
Structure(re.compile(r'^(Diaphragm~?(\^[\w\d_\+-]+)?)$'), 'Diaphragm', '13295', 'Anatomic', 'Diaphragm', 'nan', 'Thorax', 'Diaphragm'),
Structure(re.compile(r'^(Duodenum~?(\^[\w\d_\+-]+)?)$'), 'Duodenum', '7206', 'Anatomic', 'Gut', 'nan', 'Abdomen', 'Small bowel - Duodenum'),
Structure(re.compile(r'^(Ear_External~?_L(\^[\w\d_\+-]+)?)$'), 'Ear_External_L', '53644', 'Anatomic', 'Ear', 'External', 'Head and Neck', 'External Ear Left'),
Structure(re.compile(r'^(Ear_External~?_R(\^[\w\d_\+-]+)?)$'), 'Ear_External_R', '53643', 'Anatomic', 'Ear', 'External', 'Head and Neck', 'External Ear Right'),
Structure(re.compile(r'^(Ear_Externals~?(\^[\w\d_\+-]+)?)$'), 'Ear_Externals', '52781', 'Anatomic', 'Ear', 'External', 'Head and Neck', 'External Ear'),
Structure(re.compile(r'^(Ear_Internal~?_L(\^[\w\d_\+-]+)?)$'), 'Ear_Internal_L', '61021', 'Anatomic', 'Ear', 'Internal', 'Head and Neck', 'Internal Ear Left'),
Structure(re.compile(r'^(Ear_Internal~?_R(\^[\w\d_\+-]+)?)$'), 'Ear_Internal_R', '61020', 'Anatomic', 'Ear', 'Internal', 'Head and Neck', 'Internal Ear Right'),
Structure(re.compile(r'^(Ear_Internals~?(\^[\w\d_\+-]+)?)$'), 'Ear_Internals', '60909', 'Anatomic', 'Ear', 'Internal', 'Head and Neck', 'Internal Ear'),
Structure(re.compile(r'^(Ear_Middle~?(\^[\w\d_\+-]+)?)$'), 'Ear_Middle', '56513', 'Anatomic', 'Ear', 'Middle', 'Head and Neck', 'Middle Ear'),
Structure(re.compile(r'^(Ear_Middle~?_L(\^[\w\d_\+-]+)?)$'), 'Ear_Middle_L', '56515', 'Anatomic', 'Ear', 'Middle', 'Head and Neck', 'Middle Ear Left'),
Structure(re.compile(r'^(Ear_Middle~?_R(\^[\w\d_\+-]+)?)$'), 'Ear_Middle_R', '56514', 'Anatomic', 'Ear', 'Middle', 'Head and Neck', 'Middle Ear Right'),
Structure(re.compile(r'^(Edema~?(\^[\w\d_\+-]+)?)$'), 'Edema', 'nan', 'Anatomic', 'Skin', 'nan', 'Body', 'Edema'),
Structure(re.compile(r'^(Elbow~?(\^[\w\d_\+-]+)?)$'), 'Elbow', '24901', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Elbow'),
Structure(re.compile(r'^(Elbow~?_L(\^[\w\d_\+-]+)?)$'), 'Elbow_L', '24903', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Elbow Left'),
Structure(re.compile(r'^(Elbow~?_R(\^[\w\d_\+-]+)?)$'), 'Elbow_R', '24902', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Elbow Right'),
Structure(re.compile(r'^(E~?-PTV_Ev05_\d{0,4}(\^[\w\d_\+-]+)?)$'), 'E-PTV_Ev05_xxxx', 'nan', 'Non-Anatomic', 'Body', 'nan', 'Body', 'All tissue excluding the 5 mm expanded PTV. Generated by subtracting the 5 mm expanded PTV receiving a dose of xxxx cGy from the external contour.'),
Structure(re.compile(r'^(E~?-PTV_\d{0,4}(\^[\w\d_\+-]+)?)$'), 'E-PTV_xxxx', 'nan', 'Non-Anatomic', 'Derived', 'nan', 'Body', 'All tissue excluding the PTV. Generated by subtracting the PTV receiving a dose of xxxx cGy from the external contour.'),
Structure(re.compile(r'^(Esophagus~?(\^[\w\d_\+-]+)?)$'), 'Esophagus', '7131', 'Anatomic', 'Esophagus', 'nan', 'Thorax', 'Esophagus'),
Structure(re.compile(r'^(Esophagus~?_I(\^[\w\d_\+-]+)?)$'), 'Esophagus_I', '9397', 'Anatomic', 'Esophagus', 'nan', 'Thorax', 'Lower Esophagus (abdominal)'),
Structure(re.compile(r'^(Esophagus_M~?(\^[\w\d_\+-]+)?)$'), 'Esophagus_M', '9396', 'Anatomic', 'Esophagus', 'nan', 'Thorax', 'Middle Esophagus (thoracic)'),
Structure(re.compile(r'^(Esophagus~?_NAdj(\^[\w\d_\+-]+)?)$'), 'Esophagus_NAdj', 'nan', 'Anatomic', 'Esophagus', 'nan', 'Thorax', 'Non Adjacent Esophagus'),
Structure(re.compile(r'^(Esophagus~?_S(\^[\w\d_\+-]+)?)$'), 'Esophagus_S', 'nan', 'Anatomic', 'Esophagus', 'nan', 'Thorax', 'Upper Esophagus (cervical)'),
Structure(re.compile(r'^(Eval~?(\^[\w\d_\+-]+)?)$'), 'Eval', 'nan', 'Non-Anatomic', 'Body', 'nan', 'Body', 'Evaluation Structure'),
Structure(re.compile(r'^(External~?(\^[\w\d_\+-]+)?)$'), 'External', 'nan', 'Anatomic', 'Body', 'nan', 'Body', 'Contour encompassing body plus other external items '),
Structure(re.compile(r'^(Eye~?_L(\^[\w\d_\+-]+)?)$'), 'Eye_L', '12515', 'Anatomic', 'Eye', 'Eyeball', 'Head and Neck', 'Eyeball Left'),
Structure(re.compile(r'^(Eye~?_R(\^[\w\d_\+-]+)?)$'), 'Eye_R', '12514', 'Anatomic', 'Eye', 'Eyeball', 'Head and Neck', 'Eyeball Right'),
Structure(re.compile(r'^(Eyes~?(\^[\w\d_\+-]+)?)$'), 'Eyes', '268861', 'Anatomic', 'Eye', 'nan', 'Head and Neck', 'Set of eyes'),
Structure(re.compile(r'^(Femur_Base~?_L(\^[\w\d_\+-]+)?)$'), 'Femur_Base_L', '32846', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Base Left'),
Structure(re.compile(r'^(Femur_Base~?_R(\^[\w\d_\+-]+)?)$'), 'Femur_Base_R', '32845', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Base Right'),
Structure(re.compile(r'^(Femur_Head~?_L(\^[\w\d_\+-]+)?)$'), 'Femur_Head_L', '32843', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Head & Neck Left'),
Structure(re.compile(r'^(Femur_Head~?_R(\^[\w\d_\+-]+)?)$'), 'Femur_Head_R', '32842', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Head & Neck Right'),
Structure(re.compile(r'^(Femur_Joint~?_L(\^[\w\d_\+-]+)?)$'), 'Femur_Joint_L', '35180', 'Anatomic', 'Joint', 'Femur', 'Pelvis', 'Femoral Joint Left'),
Structure(re.compile(r'^(Femur_Joint~?_R(\^[\w\d_\+-]+)?)$'), 'Femur_Joint_R', '35179', 'Anatomic', 'Joint', 'Femur', 'Pelvis', 'Femoral Joint Right'),
Structure(re.compile(r'^(Femur~?_L(\^[\w\d_\+-]+)?)$'), 'Femur_L', '24475', 'Anatomic', 'Bone', 'Femur', 'Limb', 'Femur Whole Left'),
Structure(re.compile(r'^(Femur_Neck~?_L(\^[\w\d_\+-]+)?)$'), 'Femur_Neck_L', '42386', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Neck Right'),
Structure(re.compile(r'^(Femur_Neck~?_R(\^[\w\d_\+-]+)?)$'), 'Femur_Neck_R', '42387', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Neck Left'),
Structure(re.compile(r'^(Femur~?_R(\^[\w\d_\+-]+)?)$'), 'Femur_R', '24474', 'Anatomic', 'Bone', 'Femur', 'Limb', 'Femur Whole Right'),
Structure(re.compile(r'^(Femur_Shaft~?_L(\^[\w\d_\+-]+)?)$'), 'Femur_Shaft_L', '32849', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Shaft Left'),
Structure(re.compile(r'^(Femur_Shaft~?_R(\^[\w\d_\+-]+)?)$'), 'Femur_Shaft_R', '32848', 'Anatomic', 'Bone', 'Femur', 'Pelvis', 'Femur Shaft Right'),
Structure(re.compile(r'^(Femurs~?(\^[\w\d_\+-]+)?)$'), 'Femurs', '9611', 'Anatomic', 'Bone', 'Femur', 'Limb', 'Both Femurs'),
Structure(re.compile(r'^(Fibula~?(\^[\w\d_\+-]+)?)$'), 'Fibula', '24479', 'Anatomic', 'Bone', 'Fibula', 'Limbs', 'Fibula'),
Structure(re.compile(r'^(Fibula~?_L(\^[\w\d_\+-]+)?)$'), 'Fibula_L', '24481', 'Anatomic', 'Bone', 'Fibula', 'Limbs', 'Fibula Left'),
Structure(re.compile(r'^(Fibula~?_R(\^[\w\d_\+-]+)?)$'), 'Fibula_R', '24480', 'Anatomic', 'Bone', 'Fibula', 'Limbs', 'Fibula Right'),
Structure(re.compile(r'^(Foley~?(\^[\w\d_\+-]+)?)$'), 'Foley', 'nan', 'Non-Anatomic', 'Bladder', 'nan', 'Pelvis', 'Foley Catheter'),
Structure(re.compile(r'^(Fossa_Jugular~?(\^[\w\d_\+-]+)?)$'), 'Fossa_Jugular', '56429', 'Anatomic', 'Bone', 'Fossa', 'Head and Neck', 'Jugular Fossa'),
Structure(re.compile(r'^(Fossa_Posterior~?(\^[\w\d_\+-]+)?)$'), 'Fossa_Posterior', '54368', 'Anatomic', 'Bone', 'Fossa', 'Head and Neck', 'Posterior Fossa'),
Structure(re.compile(r'^(Gallbladder~?(\^[\w\d_\+-]+)?)$'), 'Gallbladder', '7202', 'Anatomic', 'Gallbladder', 'nan', 'Pelvis', 'Gall bladder'),
Structure(re.compile(r'^(Genitals~?(\^[\w\d_\+-]+)?)$'), 'Genitals', '45643', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Genitals'),
Structure(re.compile(r'^(Glnd_Adrenal~?_L(\^[\w\d_\+-]+)?)$'), 'Glnd_Adrenal_L', '15629', 'Anatomic', 'Gland', 'Adrenal', 'Thorax', 'Adrenal glands left'),
Structure(re.compile(r'^(Glnd_Adrenal~?_R(\^[\w\d_\+-]+)?)$'), 'Glnd_Adrenal_R', '15630', 'Anatomic', 'Gland', 'Adrenal', 'Thorax', 'Adrenal glands right'),
Structure(re.compile(r'^(Glnd_Lacrimal~?(\^[\w\d_\+-]+)?)$'), 'Glnd_Lacrimal', '59101', 'Anatomic', 'Gland', 'Lacrimal', 'Head and Neck', 'Lacrimal Gland'),
Structure(re.compile(r'^(Glnd_Lacrimal~?_L(\^[\w\d_\+-]+)?)$'), 'Glnd_Lacrimal_L', '59103', 'Anatomic', 'Gland', 'Lacrimal', 'Head and Neck', 'Lacrimal Gland Left'),
Structure(re.compile(r'^(Glnd_Lacrimal~?_R(\^[\w\d_\+-]+)?)$'), 'Glnd_Lacrimal_R', '59102', 'Anatomic', 'Gland', 'Lacrimal', 'Head and Neck', 'Lacrimal Gland Right'),
Structure(re.compile(r'^(Glnd_Parathyroid~?(\^[\w\d_\+-]+)?)$'), 'Glnd_Parathyroid', '13890', 'Anatomic', 'Gland', 'nan', 'Thorax', 'Parathyroid gland'),
Structure(re.compile(r'^(Glnd_Subling~?_L(\^[\w\d_\+-]+)?)$'), 'Glnd_Subling_L', '59805', 'Anatomic', 'Gland', 'Sublingual', 'Head and Neck', 'Sublingual gland'),
Structure(re.compile(r'^(Glnd_Subling~?_R(\^[\w\d_\+-]+)?)$'), 'Glnd_Subling_R', '59804', 'Anatomic', 'Gland', 'Sublingual', 'Head and Neck', 'Sublingual gland'),
Structure(re.compile(r'^(Glnd_Sublings~?(\^[\w\d_\+-]+)?)$'), 'Glnd_Sublings', '320440', 'Anatomic', 'Gland', 'Sublingual', 'Head and Neck', 'Sublingual gland'),
Structure(re.compile(r'^(Glnd_Submand~?_L(\^[\w\d_\+-]+)?)$'), 'Glnd_Submand_L', '59803', 'Anatomic', 'Gland', 'Submandibular', 'Head and Neck', 'Submandibular Gland Left'),
Structure(re.compile(r'^(Glnd_Submand~?_R(\^[\w\d_\+-]+)?)$'), 'Glnd_Submand_R', '59802', 'Anatomic', 'Gland', 'Submandibular', 'Head and Neck', 'Submandibular Gland Right'),
Structure(re.compile(r'^(Glnd_Submands~?(\^[\w\d_\+-]+)?)$'), 'Glnd_Submands', '320442', 'Anatomic', 'Gland', 'Submandibular', 'Head and Neck', 'Submandibular Gland'),
Structure(re.compile(r'^(Glnd_Thymus~?(\^[\w\d_\+-]+)?)$'), 'Glnd_Thymus', '9607', 'Anatomic', 'Gland', 'Thymus', 'Thorax', 'Thymus Gland'),
Structure(re.compile(r'^(Glnd_Thyroid~?(\^[\w\d_\+-]+)?)$'), 'Glnd_Thyroid', '9603', 'Anatomic', 'Gland', 'Thyroid', 'Thorax', 'Thyroid Gland'),
Structure(re.compile(r'^(Glottis~?(\^[\w\d_\+-]+)?)$'), 'Glottis', '55414', 'Anatomic', 'Glottis', 'nan', 'Head and Neck', 'Glottis'),
Structure(re.compile(r'^(GreatVes~?(\^[\w\d_\+-]+)?)$'), 'GreatVes', 'nan', 'Anatomic', 'Heart', 'nan', 'Thorax', 'Great Vessels of the heart (aorta, vena cava S&I, pulmonary A&V)'),
Structure(re.compile(r'^(GreatVes~?_NAdj(\^[\w\d_\+-]+)?)$'), 'GreatVes_NAdj', 'nan', 'Anatomic', 'Heart', 'nan', 'Thorax', 'Non Adjacent Great Vessels'),
Structure(re.compile(r'^(GrowthPlate~?_L(\^[\w\d_\+-]+)?)$'), 'GrowthPlate_L', 'nan', 'Anatomic', 'Bone', 'nan', 'Body', 'nan'),
Structure(re.compile(r'^(GrowthPlate~?_R(\^[\w\d_\+-]+)?)$'), 'GrowthPlate_R', 'nan', 'Anatomic', 'Bone', 'nan', 'Body', 'nan'),
Structure(re.compile(r'^(I?GTV(p|n|(sb))?\d{0,2}(_((Postop)|(Preop)|(TumorBed)|(Boost)|(Eval)|(A_Aorta)|(A_Aorta_Asc)|(A_Brachiocephls)|(A_Carotid)|(A_Carotid_L)|(A_Carotid_R)|(A_Celiac)|(A_Coronary)|(A_Coronary_L)|(A_Coronary_R)|(A_Femoral_Cflx_L)|(A_Femoral_Cflx_R)|(A_Femoral_L)|(A_Femoral_R)|(A_Humeral_Cflx_L)|(A_Humeral_Cflx_R)|(A_Humeral_L)|(A_Humeral_R)|(A_Hypophyseal_I)|(A_Hypophyseal_S)|(A_Iliac_Cflx_L)|(A_Iliac_Cflx_R)|(A_Iliac_Ext_L)|(A_Iliac_Ext_R)|(A_Iliac_Int_L)|(A_Iliac_Int_R)|(A_Iliac_L)|(A_Iliac_R)|(A_LAD)|(A_Mesenteric_I)|(A_Mesenteric_S)|(A_Pulmonary)|(A_Subclavian)|(A_Subclavian_L)|(A_Subclavian_R)|(A_Vertebral)|(A_Vertebral_L)|(A_Vertebral_R)|(Acetabulum_L)|(Acetabulum_R)|(Acetabulums)|(AirWay_Dist)|(AirWay_Prox)|(Anus)|(Appendix)|(Arytenoid)|(Arytenoid_L)|(Arytenoid_R)|(Atrium)|(Atrium_L)|(Atrium_R)|(BileDuct_Common)|(Bladder)|(Bladder_Wall)|(Body)|(Bone)|(Bone_Ethmoid)|(Bone_Frontal)|(Bone_Hyoid)|(Bone_Ilium)|(Bone_Ilium_L)|(Bone_Ilium_R)|(Bone_Incus)|(Bone_Incus_L)|(Bone_Incus_R)|(Bone_Ischium_L)|(Bone_Ischium_R)|(Bone_Lacrimal)|(Bone_Lacrimal_L)|(Bone_Lacrimal_R)|(Bone_Mandible)|(Bone_Mastoid_L)|(Bone_Mastoid_R)|(Bone_Nasal)|(Bone_Nasal_L)|(Bone_Nasal_R)|(Bone_Occipital)|(Bone_Palatine)|(Bone_Palatine_L)|(Bone_Palatine_R)|(Bone_Parietal)|(Bone_Parietal_L)|(Bone_Parietal_R)|(Bone_Pelvic)|(Bone_Pelvic_L)|(Bone_Pelvic_R)|(Bone_Sphenoid)|(Bone_Temporal)|(Bone_Temporal_L)|(Bone_Temporal_R)|(Bone_Zygomatic_L)|(Bone_Zygomatic_R)|(Bone_Zygomatics)|(BoneMarrow)|(BoneMarrow_Act)|(Bowel)|(Bowel_Large)|(Bowel_Small)|(BrachialPlex_L)|(BrachialPlex_R)|(BrachialPlexs)|(Brain)|(Brainstem)|(Brainstem_Core)|(Brainstem_Surf)|(Breast_L)|(Breast_R)|(Breasts)|(Bronchus)|(Bronchus_L)|(Bronchus_Main)|(Bronchus_Main_L)|(Bronchus_Main_R)|(Bronchus_PRVxx)|(Bronchus_R)|(Canal_Anal)|(Carina)|(Cartlg_Thyroid)|(CaudaEquina)|(Cavernosum)|(Cavity_Nasal)|(Cavity_Oral)|(Cecum)|(Cerebellum)|(Cerebrum)|(Cerebrum_L)|(Cerebrum_R)|(Cervix)|(Chestwall)|(Chestwall_L)|(Chestwall_R)|(Cist_Pontine)|(Cist_Suprasellar)|(Clavicle_L)|(Clavicle_R)|(CN_III)|(CN_III_L)|(CN_III_R)|(CN_IX)|(CN_IX_L)|(CN_IX_R)|(CN_V)|(CN_V_L)|(CN_V_R)|(CN_VI)|(CN_VI_L)|(CN_VI_R)|(CN_VII)|(CN_VII_L)|(CN_VII_R)|(CN_VIII)|(CN_VIII_L)|(CN_VIII_R)|(CN_XI)|(CN_XI_L)|(CN_XI_R)|(CN_XII)|(CN_XII_L)|(CN_XII_R)|(Cochlea)|(Cochlea_L)|(Cochlea_R)|(Colon)|(Colon_Ascending)|(Colon_Decending)|(Colon_PTVxx)|(Colon_Sigmoid)|(Colon_Transverse)|(Cornea)|(Cornea_L)|(Cornea_R)|(CribriformPlate)|(Cricoid)|(Cricopharyngeus)|(Dens)|(Diaphragm)|(Duodenum)|(Ear_External_L)|(Ear_External_R)|(Ear_Externals)|(Ear_Internal_L)|(Ear_Internal_R)|(Ear_Internals)|(Ear_Middle)|(Ear_Middle_L)|(Ear_Middle_R)|(Edema)|(Elbow)|(Elbow_L)|(Elbow_R)|(Esophagus)|(Esophagus_I)|(Esophagus_M)|(Esophagus_NAdj)|(Esophagus_S)|(External)|(Eye_L)|(Eye_R)|(Eyes)|(Femur_Base_L)|(Femur_Base_R)|(Femur_Head_L)|(Femur_Head_R)|(Femur_Joint_L)|(Femur_Joint_R)|(Femur_L)|(Femur_Neck_L)|(Femur_Neck_R)|(Femur_R)|(Femur_Shaft_L)|(Femur_Shaft_R)|(Femurs)|(Fibula)|(Fibula_L)|(Fibula_R)|(Fossa_Jugular)|(Fossa_Posterior)|(Gallbladder)|(Genitals)|(Glnd_Adrenal_L)|(Glnd_Adrenal_R)|(Glnd_Lacrimal)|(Glnd_Lacrimal_L)|(Glnd_Lacrimal_R)|(Glnd_Parathyroid)|(Glnd_Subling_L)|(Glnd_Subling_R)|(Glnd_Sublings)|(Glnd_Submand_L)|(Glnd_Submand_R)|(Glnd_Submands)|(Glnd_Thymus)|(Glnd_Thyroid)|(Glottis)|(GreatVes)|(GreatVes_NAdj)|(GrowthPlate_L)|(GrowthPlate_R)|(Hardpalate)|(Heart)|(Hemisphere_L)|(Hemisphere_R)|(Hemispheres)|(Hippocampi)|(Hippocampus_L)|(Hippocampus_R)|(Humerus_L)|(Humerus_R)|(Hypothalmus)|(Ileum)|(Jejunum)|(Jejunum_Ileum)|(Joint_Elbow)|(Joint_Elbow_L)|(Joint_Elbow_R)|(Joint_Glenohum)|(Joint_Glenohum_L)|(Joint_Glenohum_R)|(Joint_Surface)|(Joint_TM)|(Joint_TM_L)|(Joint_TM_R)|(Kidney_Cortex)|(Kidney_Cortex_L)|(Kidney_Cortex_R)|(Kidney_Hilum_L)|(Kidney_Hilum_R)|(Kidney_Hilums)|(Kidney_L)|(Kidney_Pelvis_L)|(Kidney_Pelvis_R)|(Kidney_R)|(Kidneys)|(Knee)|(Knee_L)|(Knee_R)|(Laryngl_Pharynx)|(Larynx)|(Larynx_SG)|(Lens)|(Lens_L)|(Lens_R)|(Lig_Hepatogastrc)|(Lips)|(Liver)|(LN)|(LN_Ax_Apical)|(LN_Ax_Apical_L)|(LN_Ax_Apical_R)|(LN_Ax_Central_L)|(LN_Ax_Central_R)|(LN_Ax_Centrals)|(LN_Ax_L)|(LN_Ax_L1_L)|(LN_Ax_L1_R)|(LN_Ax_L2_L)|(LN_Ax_L2_R)|(LN_Ax_L3_L)|(LN_Ax_L3_R)|(LN_Ax_Lateral_L)|(LN_Ax_Lateral_R)|(LN_Ax_Laterals)|(LN_Ax_Pectoral_L)|(LN_Ax_Pectoral_R)|(LN_Ax_Pectorals)|(LN_Ax_R)|(LN_Ax_Subscap_L)|(LN_Ax_Subscap_R)|(LN_Ax_Subscaps)|(LN_Brachioceph_L)|(LN_Brachioceph_R)|(LN_Brachiocephs)|(LN_Bronchpulm_L)|(LN_Bronchpulm_R)|(LN_Bronchpulms)|(LN_Diaphragmatic)|(LN_Iliac_Ext_L)|(LN_Iliac_Ext_R)|(LN_Iliac_Int_L)|(LN_Iliac_L)|(LN_Iliac_R)|(LN_IMN_L)|(LN_IMN_R)|(LN_IMNs)|(LN_Inguinofem)|(LN_Inguinofem_L)|(LN_Inguinofem_R)|(LN_Intercostals)|(LN_L)|(LN_Ligamentarter)|(LN_lliac_Int_R)|(LN_Mediastinals)|(LN_Neck_IA_L)|(LN_Neck_IA_R)|(LN_Neck_IB_L)|(LN_Neck_IB_R)|(LN_Neck_II_L)|(LN_Neck_II_R)|(LN_Neck_IIA_L)|(LN_Neck_IIA_R)|(LN_Neck_IIB_L)|(LN_Neck_IIB_R)|(LN_Neck_III_L)|(LN_Neck_III_R)|(LN_Neck_IV_L)|(LN_Neck_IV_R)|(LN_Neck_V_L)|(LN_Neck_V_R)|(LN_Neck_VA_L)|(LN_Neck_VA_R)|(LN_Neck_VB_L)|(LN_Neck_VB_R)|(LN_Neck_VC_L)|(LN_Neck_VC_R)|(LN_Neck_VI_L)|(LN_Neck_VI_R)|(LN_Neck_VII_L)|(LN_Neck_VII_R)|(LN_Obturator_L)|(LN_Obturator_R)|(LN_Paraaortic)|(LN_Paramammary_L)|(LN_Paramammary_R)|(LN_Paramammarys)|(LN_Parasternal_L)|(LN_Parasternal_R)|(LN_Parasternals)|(LN_Pelvic_L)|(LN_Pelvic_R)|(LN_Pelvics)|(LN_Portahepatis)|(LN_Presacral_L)|(LN_Presacral_R)|(LN_Pulmonary_L)|(LN_Pulmonary_R)|(LN_Pulmonarys)|(LN_R)|(LN_Sclav_L)|(LN_Sclav_R)|(LN_Supmammary_L)|(LN_Supmammary_R)|(LN_Supmammarys)|(LN_Trachbrnchs)|(LN_Trachbrnchs_L)|(LN_Trachbrnchs_R)|(Lobe_Frontal)|(Lobe_Frontal_L)|(Lobe_Frontal_R)|(Lobe_Occipital)|(Lobe_Occipital_L)|(Lobe_Occipital_R)|(Lobe_Parietal)|(Lobe_Parietal_L)|(Lobe_Parietal_R)|(Lobe_Temporal)|(Lobe_Temporal_L)|(Lobe_Temporal_R)|(Lung_L)|(Lung_LLL)|(Lung_LUL)|(Lung_R)|(Lung_RLL)|(Lung_RML)|(Lung_RUL)|(Lungs)|(Malleus)|(Malleus_L)|(Malleus_R)|(Maxilla)|(Maxilla_L)|(Maxilla_R)|(Mediastinum)|(Musc)|(Musc_Constrict)|(Musc_Constrict_I)|(Musc_Constrict_M)|(Musc_Constrict_S)|(Musc_Digastric_L)|(Musc_Digastric_R)|(Musc_Masseter)|(Musc_Masseter_L)|(Musc_Masseter_R)|(Musc_Platysma_L)|(Musc_Platysma_R)|(Musc_Pterygoid_L)|(Musc_Pterygoid_R)|(Musc_Sclmast_L)|(Musc_Sclmast_R)|(Musc_Temporal_L)|(Musc_Temporal_R)|(Nasalconcha_LI)|(Nasalconcha_RI)|(Nasopharynx)|(Nose)|(Nrv_Peripheral)|(Nrv_Root)|(OpticChiasm)|(OpticNrv)|(OpticNrv_L)|(OpticNrv_R)|(Orbit_L)|(Orbit_R)|(Oropharynx)|(Ovaries)|(Ovary_L)|(Ovary_R)|(Palate_Soft)|(PancJejuno)|(Pancreas)|(Pancreas_Head)|(Pancreas_Tail)|(Parametrium)|(Parotid_L)|(Parotid_R)|(Parotids)|(PenileBulb)|(Penis)|(Pericardium)|(Perineum)|(Peritoneum)|(Pharynx)|(Pineal)|(Pituitary)|(Pons)|(Proc_Condyloid_L)|(Proc_Condyloid_R)|(Proc_Coronoid_L)|(Proc_Coronoid_R)|(Prostate)|(ProstateBed)|(Prosthesis)|(Pterygoid_Lat_L)|(Pterygoid_Lat_R)|(Pterygoid_Med_L)|(Pterygoid_Med_R)|(PubicSymphys)|(PubicSymphys_L)|(PubicSymphys_R)|(Radius_L)|(Radius_R)|(Rectal_Wall)|(Rectum)|(Retina_L)|(Retina_R)|(Retinas)|(Rib)|(Rib01_L)|(Rib01_R)|(Rib02_L)|(Rib02_R)|(Rib03_L)|(Rib03_R)|(Rib04_L)|(Rib04_R)|(Rib05_L)|(Rib05_R)|(Rib06_L)|(Rib06_R)|(Rib07_L)|(Rib07_R)|(Rib08_L)|(Rib08_R)|(Rib09_L)|(Rib09_R)|(Rib10_L)|(Rib10_R)|(Rib11_L)|(Rib11_R)|(Rib12_L)|(Rib12_R)|(SacralPlex)|(Sacrum)|(Scalp)|(Scapula_L)|(Scapula_R)|(Scar)|(Scar_Boost)|(Scrotum)|(SeminalVes)|(SeminalVes_Dist)|(SeminalVes_Prox)|(Sinus_Ethmoid)|(Sinus_Frontal)|(Sinus_Frontal_L)|(Sinus_Frontal_R)|(Sinus_Maxilry)|(Sinus_Maxilry_L)|(Sinus_Maxilry_R)|(Sinus_Sphenoid)|(Sinus_Sphenoid_L)|(Sinus_Sphenoid_R)|(Skin)|(Skin_Perineum)|(Skin_Peritoneum)|(Skull)|(Spc)|(Spc_Bowel )|(Spc_Bowel_Small)|(Spc_Retrophar_L)|(Spc_Retrophar_R)|(Spc_Retrophars)|(Spc_Retrosty)|(Spc_Retrosty_L)|(Spc_Retrosty_R)|(Spc_Supraclav_L)|(Spc_Supraclav_R)|(Sphincter_Anal)|(SpinalCanal)|(SpinalCord)|(SpinalCord_Cerv)|(SpinalCord_Lum)|(SpinalCord_Sac)|(SpinalCord_Thor)|(Spleen)|(Spleen_Hilum)|(Spongiosum)|(Stapes)|(Stapes_L)|(Stapes_R)|(Stomach)|(Strct )|(Strct_Suprapatel)|(Surf_Eye)|(SurgicalBed)|(Sys_Ventricular)|(Tendon )|(Tendon_Quad)|(Testis)|(Testis_L)|(Testis_R)|(ThecalSac)|(Thoracic_Duct)|(Tongue)|(Tongue_All)|(Tongue_Base)|(Tongue_Base_L)|(Tongue_Base_R)|(Tongue_Oral)|(Tongue_Oral_L)|(Tongue_Oral_R)|(Tonsil)|(Trachea)|(Trachea_NAdj)|(Ureter_L)|(Ureter_R)|(UreterDivert)|(Ureters)|(Urethra)|(Urethra_Prostatc)|(Uterus)|(V_Azygos)|(V_Brachioceph_L)|(V_Brachioceph_R)|(V_Iliac_Ext_L)|(V_Iliac_Ext_R)|(V_Iliac_Int_L)|(V_Iliac_Int_R)|(V_Iliac_L)|(V_Iliac_R)|(V_Jugular)|(V_Jugular_Ext_L)|(V_Jugular_Ext_R)|(V_Jugular_Int_L)|(V_Jugular_Int_R)|(V_Portal)|(V_Pulmonary)|(V_Subclavian_L)|(V_Subclavian_R)|(V_Subclavians)|(V_Venacava_I)|(V_Venacava_S)|(Vagina)|(Vagina_Surf)|(VaginalCuff)|(Valve)|(Valve_Aortic)|(Valve_Mitral)|(Valve_Pulmonic)|(Valve_Tricuspid)|(VB)|(VB_C)|(VB_C1)|(VB_C2)|(VB_C3)|(VB_C4)|(VB_C5)|(VB_C6)|(VB_C7)|(VB_L)|(VB_L1)|(VB_L2)|(VB_L3)|(VB_L4)|(VB_L5)|(VB_S)|(VB_S1)|(VB_S2)|(VB_S3)|(VB_S4)|(VB_S5)|(VB_T)|(VB_T01)|(VB_T02)|(VB_T03)|(VB_T04)|(VB_T05)|(VB_T06)|(VB_T07)|(VB_T08)|(VB_T09)|(VB_T10)|(VB_T11)|(VB_T12)|(VBs)|(Ventricle)|(Ventricle_L)|(Ventricle_R)|(VocalCord_L)|(VocalCord_R)|(VocalCords)|(Vomer)|(Vulva)|(Wall_Vagina)|(Thalami)|(Thalamus_L)|(Thalamus_R)|(Third_Ventricle)|(InternCapsule_L)|(InternCapsule_R)))?(_((High)|(Mid(\d{2})?)|(Low)))?(-\d{2})?(\^[\w\d_\+-]+)?)$'), 'GTV', 'nan', 'Target', 'GTV', 'nan', 'Body', 'Gross Tumor Volume'),
Structure(re.compile(r'^(Hardpalate~?(\^[\w\d_\+-]+)?)$'), 'Hardpalate', '55023', 'Anatomic', 'Head', 'Mouth', 'Head and Neck', 'Hard palate'),
Structure(re.compile(r'^(Heart~?(\^[\w\d_\+-]+)?)$'), 'Heart', '7088', 'Anatomic', 'Heart', 'nan', 'Thorax', 'Heart'),
Structure(re.compile(r'^(Hemisphere~?_L(\^[\w\d_\+-]+)?)$'), 'Hemisphere_L', '61819', 'Anatomic', 'Brain', 'Hemisphere', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Hemisphere~?_R(\^[\w\d_\+-]+)?)$'), 'Hemisphere_R', '67292', 'Anatomic', 'Brain', 'Hemisphere', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Hemispheres~?(\^[\w\d_\+-]+)?)$'), 'Hemispheres', 'nan', 'Anatomic', 'Brain', 'Hemisphere', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Hippocampi~?(\^[\w\d_\+-]+)?)$'), 'Hippocampi', '275020', 'Anatomic', 'Brain', 'Hippocampus', 'Head and Neck', 'Hippocampus'),
Structure(re.compile(r'^(Hippocampus~?_L(\^[\w\d_\+-]+)?)$'), 'Hippocampus_L', '275024', 'Anatomic', 'Brain', 'Hippocampus', 'Head and Neck', 'Hippocampus Left'),
Structure(re.compile(r'^(Hippocampus~?_R(\^[\w\d_\+-]+)?)$'), 'Hippocampus_R', '275022', 'Anatomic', 'Brain', 'Hippocampus', 'Head and Neck', 'Hippocampus Right'),
Structure(re.compile(r'^(Humerus~?_L(\^[\w\d_\+-]+)?)$'), 'Humerus_L', '23131', 'Anatomic', 'Bone', 'Humerus', 'Limbs', 'Humerus Left'),
Structure(re.compile(r'^(Humerus~?_R(\^[\w\d_\+-]+)?)$'), 'Humerus_R', '23130', 'Anatomic', 'Bone', 'Humerus', 'Limbs', 'Humerus Right'),
Structure(re.compile(r'^(Hypothalmus~?(\^[\w\d_\+-]+)?)$'), 'Hypothalmus', '62008', 'Anatomic', 'Brain', 'Hypothalamus', 'Head and Neck', 'Hypothalamus'),
Structure(re.compile(r'^(Hypothalmus~?_PRV?\d{0,2}(\^[\w\d_\+-]+)?)$'), 'Hypothalmus_PRVxx', 'nan', 'PRV', 'Brain', 'Hypothalamus', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(IDL~?(\^[\w\d_\+-]+)?)$'), 'IDL', 'nan', 'Non-Anatomic', 'Dose', 'nan', 'Body', 'Isodose Line e.g. IDL_5000 isodose line for 50 Gy'),
Structure(re.compile(r'^(Ileum~?(\^[\w\d_\+-]+)?)$'), 'Ileum', '7208', 'Anatomic', 'Gut', 'nan', 'Abdomen', 'Small bowel - Ileum'),
Structure(re.compile(r'^(ITV~?(\^[\w\d_\+-]+)?)$'), 'ITV', 'nan', 'Target', 'ITV', 'nan', 'Body', 'Internal Target Volume'),
Structure(re.compile(r'^(Jejunum~?(\^[\w\d_\+-]+)?)$'), 'Jejunum', '7207', 'Anatomic', 'Gut', 'Small Bowel', 'Abdomen', 'Small bowel - Jejunum'),
Structure(re.compile(r'^(Jejunum_Ileum~?(\^[\w\d_\+-]+)?)$'), 'Jejunum_Ileum', 'nan', 'Anatomic', 'Gut', 'nan', 'Abdomen', 'Both ileum and jejunum'),
Structure(re.compile(r'^(Joint_Elbow~?(\^[\w\d_\+-]+)?)$'), 'Joint_Elbow', '35289', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Elbow joint'),
Structure(re.compile(r'^(Joint_Elbow~?_L(\^[\w\d_\+-]+)?)$'), 'Joint_Elbow_L', '35295', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Left Elbow joint'),
Structure(re.compile(r'^(Joint_Elbow~?_R(\^[\w\d_\+-]+)?)$'), 'Joint_Elbow_R', '35294', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Right Elbow joint'),
Structure(re.compile(r'^(Joint_Glenohum~?(\^[\w\d_\+-]+)?)$'), 'Joint_Glenohum', '25912', 'Anatomic', 'Joint', 'Small Bowel', 'Limbs', 'Glenohumeral Joint'),
Structure(re.compile(r'^(Joint_Glenohum~?_L(\^[\w\d_\+-]+)?)$'), 'Joint_Glenohum_L', '25929', 'Anatomic', 'Joint', 'Small Bowel', 'Limbs', 'Glenohumeral Joint Left'),
Structure(re.compile(r'^(Joint_Glenohum~?_R(\^[\w\d_\+-]+)?)$'), 'Joint_Glenohum_R', '25927', 'Anatomic', 'Joint', 'Glenohumeral', 'Limbs', 'Glenohumeral Joint Right'),
Structure(re.compile(r'^(Joint_Surface~?(\^[\w\d_\+-]+)?)$'), 'Joint_Surface', 'nan', 'Anatomic', 'Joint', 'Glenohumeral', 'Body', 'nan'),
Structure(re.compile(r'^(Joint_TM~?(\^[\w\d_\+-]+)?)$'), 'Joint_TM', '54832', 'Anatomic', 'Joint', 'Glenohumeral', 'Head and Neck', 'Temperomandibular Joint '),
Structure(re.compile(r'^(Joint_TM~?_L(\^[\w\d_\+-]+)?)$'), 'Joint_TM_L', '54834', 'Anatomic', 'Joint', 'Temperomandibular', 'Head and Neck', 'Temperomandibular Joint Left'),
Structure(re.compile(r'^(Joint_TM~?_R(\^[\w\d_\+-]+)?)$'), 'Joint_TM_R', '54833', 'Anatomic', 'Joint', 'Temperomandibular', 'Head and Neck', 'Temperomandibular Joint Right'),
Structure(re.compile(r'^(Kidney_Cortex~?(\^[\w\d_\+-]+)?)$'), 'Kidney_Cortex', '15581', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal cortex for both Kidneys'),
Structure(re.compile(r'^(Kidney_Cortex~?_L(\^[\w\d_\+-]+)?)$'), 'Kidney_Cortex_L', '15584', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal cortex left'),
Structure(re.compile(r'^(Kidney_Cortex~?_R(\^[\w\d_\+-]+)?)$'), 'Kidney_Cortex_R', '15583', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal cortex right'),
Structure(re.compile(r'^(Kidney_Hilum~?_L(\^[\w\d_\+-]+)?)$'), 'Kidney_Hilum_L', '15942', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal Hilum Left'),
Structure(re.compile(r'^(Kidney_Hilum~?_R(\^[\w\d_\+-]+)?)$'), 'Kidney_Hilum_R', '15941', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal Hilum Right'),
Structure(re.compile(r'^(Kidney_Hilums~?(\^[\w\d_\+-]+)?)$'), 'Kidney_Hilums', '15610', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal Hilum for both Kidneys'),
Structure(re.compile(r'^(Kidney~?_L(\^[\w\d_\+-]+)?)$'), 'Kidney_L', '7205', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Kidney Left'),
Structure(re.compile(r'^(Kidney_L-GTV(\^[\w\d_\+-]+)?)$'), 'Kidney_L-GTV', 'nan', 'Derived', 'Urinary', 'Kidney', 'Abdomen', 'nan'),
Structure(re.compile(r'^(Kidney_Pelvis~?_L(\^[\w\d_\+-]+)?)$'), 'Kidney_Pelvis_L', '15579', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal pelvis Left'),
Structure(re.compile(r'^(Kidney_Pelvis~?_R(\^[\w\d_\+-]+)?)$'), 'Kidney_Pelvis_R', '15578', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Renal pelvis Right'),
Structure(re.compile(r'^(Kidney~?_R(\^[\w\d_\+-]+)?)$'), 'Kidney_R', '7204', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Kidney Right'),
Structure(re.compile(r'^(Kidney_R-GTV(\^[\w\d_\+-]+)?)$'), 'Kidney_R-GTV', 'nan', 'Derived', 'Urinary', 'Kidney', 'Abdomen', 'nan'),
Structure(re.compile(r'^(Kidney-GTV(\^[\w\d_\+-]+)?)$'), 'Kidney-GTV', 'nan', 'Derived', 'Urinary', 'Kidney', 'Abdomen', 'nan'),
Structure(re.compile(r'^(Kidneys~?(\^[\w\d_\+-]+)?)$'), 'Kidneys', '264815', 'Anatomic', 'Urinary', 'Kidney', 'Abdomen', 'Both Kidneys'),
Structure(re.compile(r'^(Knee~?(\^[\w\d_\+-]+)?)$'), 'Knee', '24974', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Knee'),
Structure(re.compile(r'^(Knee~?_L(\^[\w\d_\+-]+)?)$'), 'Knee_L', '24978', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Knee Left'),
Structure(re.compile(r'^(Knee~?_R(\^[\w\d_\+-]+)?)$'), 'Knee_R', '24977', 'Anatomic', 'Joint', 'nan', 'Limbs', 'Knee Right'),
Structure(re.compile(r'^(Laryngl_Pharynx~?(\^[\w\d_\+-]+)?)$'), 'Laryngl_Pharynx', '54880', 'Anatomic', 'Tissue', 'Laryngeal pharynx', 'Head and Neck', 'Laryngeal pharynx'),
Structure(re.compile(r'^(Larynx~?(\^[\w\d_\+-]+)?)$'), 'Larynx', '55097', 'Anatomic', 'Larynx', 'nan', 'Head and Neck', 'Larynx'),
Structure(re.compile(r'^(Larynx_SG~?(\^[\w\d_\+-]+)?)$'), 'Larynx_SG', '55476', 'Anatomic', 'Larynx', 'nan', 'Head and Neck', 'Supraglottic Larynx'),
Structure(re.compile(r'^(Leads(\^[\w\d_\+-]+)?)$'), 'Leads', 'nan', 'Non_Anatomic', 'Devices', 'nan', 'Body', 'nan'),
Structure(re.compile(r'^(Lens~?(\^[\w\d_\+-]+)?)$'), 'Lens', '58241', 'Anatomic', 'Eye', 'Lens', 'Head and Neck', 'Eye Lens'),
Structure(re.compile(r'^(Lens~?_L(\^[\w\d_\+-]+)?)$'), 'Lens_L', '58243', 'Anatomic', 'Eye', 'Lens', 'Head and Neck', 'Lens Left'),
Structure(re.compile(r'^(Lens~?_R(\^[\w\d_\+-]+)?)$'), 'Lens_R', '58242', 'Anatomic', 'Eye', 'Lens', 'Head and Neck', 'Lens Right'),
Structure(re.compile(r'^(Lig_Hepatogastrc~?(\^[\w\d_\+-]+)?)$'), 'Lig_Hepatogastrc', '16520', 'Anatomic', 'Ligament', 'Hepatogastric', 'Abdomen', 'Hepatogastric ligament'),
Structure(re.compile(r'^(Lips~?(\^[\w\d_\+-]+)?)$'), 'Lips', '59815', 'Anatomic', 'Feature', 'nan', 'Head and Neck', 'Lips'),
Structure(re.compile(r'^(Liver~?(\^[\w\d_\+-]+)?)$'), 'Liver', '7197', 'Anatomic', 'Liver', 'nan', 'Abdomen', 'Liver'),
Structure(re.compile(r'^(Liver-CTV(\^[\w\d_\+-]+)?)$'), 'Liver-CTV', 'nan', 'Derived', 'Liver', 'nan', 'Abdomen', 'nan'),
Structure(re.compile(r'^(Liver-GTV(\^[\w\d_\+-]+)?)$'), 'Liver-GTV', 'nan', 'Derived', 'Liver', 'nan', 'Abdomen', 'Liver minus GTV'),
Structure(re.compile(r'^(LN~?(\^[\w\d_\+-]+)?)$'), 'LN', '5034', 'Anatomic', 'Lymph Node', 'nan', 'Body', 'Lymph Node'),
Structure(re.compile(r'^(LN_Ax_Apical~?(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Apical', '23394', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Set of apical axillary lymphatic vessels'),
Structure(re.compile(r'^(LN_Ax_Apical~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Apical_L', '73265', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Apical Left'),
Structure(re.compile(r'^(LN_Ax_Apical~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Apical_R', '73264', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Apical Right'),
Structure(re.compile(r'^(LN_Ax_Central~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Central_L', '73263', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Central Left'),
Structure(re.compile(r'^(LN_Ax_Central~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Central_R', '73262', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Central Left'),
Structure(re.compile(r'^(LN_Ax_Centrals~?(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Centrals', '233482', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Set of central axillary lymphatic vessels'),
Structure(re.compile(r'^(LN_Ax~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_L', '73250', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Axillary lymphatic chain Left'),
Structure(re.compile(r'^(LN_Ax_L1~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_L1_L', '276001', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Level 1 Axillary Lymph Node Left'),
Structure(re.compile(r'^(LN_Ax_L1~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_L1_R', '275999', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Level 1 Axillary Lymph Node Right'),
Structure(re.compile(r'^(LN_Ax_L2~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_L2_L', '276005', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Level 2 Axillary Lymph Node Left'),
Structure(re.compile(r'^(LN_Ax_L2~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_L2_R', '276003', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Level 2 Axillary Lymph Node Right'),
Structure(re.compile(r'^(LN_Ax_L3~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_L3_L', '276009', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Level 3 Axillary Lymph Node Left'),
Structure(re.compile(r'^(LN_Ax_L3~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_L3_R', '276007', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Level 3 Axillary Lymph Node Right'),
Structure(re.compile(r'^(LN_Ax_Lateral~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Lateral_L', '73256', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Lateral Left'),
Structure(re.compile(r'^(LN_Ax_Lateral~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Lateral_R', '73255', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Lateral Right'),
Structure(re.compile(r'^(LN_Ax_Laterals~?(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Laterals', '233458', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'pair of Lungs'),
Structure(re.compile(r'^(LN_Ax_Pectoral~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Pectoral_L', '73253', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Pectoral Left'),
Structure(re.compile(r'^(LN_Ax_Pectoral~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Pectoral_R', '73252', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Pectoral Right'),
Structure(re.compile(r'^(LN_Ax_Pectorals~?(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Pectorals', '233446', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Set of pectoral axillary lymphatic vessels'),
Structure(re.compile(r'^(LN_Ax~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_R', '73249', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain Right'),
Structure(re.compile(r'^(LN_Ax_Subscap~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Subscap_L', '73259', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Subscapular Left'),
Structure(re.compile(r'^(LN_Ax_Subscap~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Subscap_R', '73258', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Axillary lymphatic chain - Subscapular Right'),
Structure(re.compile(r'^(LN_Ax_Subscaps~?(\^[\w\d_\+-]+)?)$'), 'LN_Ax_Subscaps', '233470', 'Anatomic', 'Lymph Node', 'Axillary', 'Thorax', 'Set of subscapular axillary lymphatic vessels'),
Structure(re.compile(r'^(LN_Brachioceph~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Brachioceph_L', '5946', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Brachiocephalic Left'),
Structure(re.compile(r'^(LN_Brachioceph~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Brachioceph_R', '5945', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Brachiocephalic Right'),
Structure(re.compile(r'^(LN_Brachiocephs~?(\^[\w\d_\+-]+)?)$'), 'LN_Brachiocephs', '5944', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Brachiocephalic'),
Structure(re.compile(r'^(LN_Bronchpulm~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Bronchpulm_L', '5967', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Bronchopulmonary Left'),
Structure(re.compile(r'^(LN_Bronchpulm~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Bronchpulm_R', '5966', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Bronchopulmonary Right'),
Structure(re.compile(r'^(LN_Bronchpulms~?(\^[\w\d_\+-]+)?)$'), 'LN_Bronchpulms', '5965', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Bronchopulmonary'),
Structure(re.compile(r'^(LN_Diaphragmatic~?(\^[\w\d_\+-]+)?)$'), 'LN_Diaphragmatic', '12773', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Diaphragmatic'),
Structure(re.compile(r'^(LN_Iliac_Ext~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Iliac_Ext_L', '229177', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - external iliac Left'),
Structure(re.compile(r'^(LN_Iliac_Ext~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Iliac_Ext_R', '229177', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - external iliac Right'),
Structure(re.compile(r'^(LN_Iliac_Int~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Iliac_Int_L', '224275', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - internal iliac Left'),
Structure(re.compile(r'^(LN_Iliac~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Iliac_L', '224269', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - common iliac Left'),
Structure(re.compile(r'^(LN_Iliac~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Iliac_R', '224269', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - common iliac Right'),
Structure(re.compile(r'^(LN_IMN~?_L(\^[\w\d_\+-]+)?)$'), 'LN_IMN_L', '5934', 'Anatomic', 'Lymph Node', 'Breast', 'Thorax', 'nan'),
Structure(re.compile(r'^(LN_IMN~?_R(\^[\w\d_\+-]+)?)$'), 'LN_IMN_R', '5933', 'Anatomic', 'Lymph Node', 'Breast', 'Thorax', 'nan'),
Structure(re.compile(r'^(LN_IMNs~?(\^[\w\d_\+-]+)?)$'), 'LN_IMNs', '5849', 'Anatomic', 'Lymph Node', 'Breast', 'Thorax', 'Lymph nodes IMN'),
Structure(re.compile(r'^(LN_Inguinofem~?(\^[\w\d_\+-]+)?)$'), 'LN_Inguinofem', '236337', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - inguinofemoral'),
Structure(re.compile(r'^(LN_Inguinofem~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Inguinofem_L', '236341', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - inguinofemoral'),
Structure(re.compile(r'^(LN_Inguinofem~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Inguinofem_R', '236339', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - inguinofemoral'),
Structure(re.compile(r'^(LN_Intercostals~?(\^[\w\d_\+-]+)?)$'), 'LN_Intercostals', '5932', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Intercostal'),
Structure(re.compile(r'^(LN~?_L(\^[\w\d_\+-]+)?)$'), 'LN_L', 'nan', 'Anatomic', 'Lymph Node', 'Unspecified', 'Body', 'Lymph Node Left'),
Structure(re.compile(r'^(LN_Ligamentarter~?(\^[\w\d_\+-]+)?)$'), 'LN_Ligamentarter', '74033', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Ligamentum arteriosum'),
Structure(re.compile(r'^(LN_lliac_Int~?_R(\^[\w\d_\+-]+)?)$'), 'LN_lliac_Int_R', '224275', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - internal iliac Right'),
Structure(re.compile(r'^(LN_Mediastinals~?(\^[\w\d_\+-]+)?)$'), 'LN_Mediastinals', '12774', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Mediastinal'),
Structure(re.compile(r'^(LN_Neck_IA~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IA_L', '235616', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IA (Submental) neck node Left'),
Structure(re.compile(r'^(LN_Neck_IA~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IA_R', '235614', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IA (Submental) neck node Right'),
Structure(re.compile(r'^(LN_Neck_IB~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IB_L', '232676', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IB (Submandibular) neck node Left'),
Structure(re.compile(r'^(LN_Neck_IB~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IB_R', '232673', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IB (Submandibular) neck node Right'),
Structure(re.compile(r'^(LN_Neck_II~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_II_L', '265660', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IIA & IIB (Upper Jugular) neck nodes Left'),
Structure(re.compile(r'^(LN_Neck_II~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_II_R', '265658', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IIA & IIB (Upper Jugular) neck nodes Left'),
Structure(re.compile(r'^(LN_Neck_IIA~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IIA_L', '241975', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IIA (Upper Jugular) neck node Left'),
Structure(re.compile(r'^(LN_Neck_IIA~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IIA_R', '241973', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IIA (Upper Jugular) neck node Right'),
Structure(re.compile(r'^(LN_Neck_IIB~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IIB_L', '241979', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IIB (Upper Jugular) neck node Left'),
Structure(re.compile(r'^(LN_Neck_IIB~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IIB_R', '241977', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IIB (Upper Jugular) neck node Right'),
Structure(re.compile(r'^(LN_Neck_III~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_III_L', '241953', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level III (Middle Jugular) neck node Left'),
Structure(re.compile(r'^(LN_Neck_III~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_III_R', '241951', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level III (Middle Jugular) neck node Right'),
Structure(re.compile(r'^(LN_Neck_IV~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IV_L', '241959', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IV neck (Lower Jugular) node Left'),
Structure(re.compile(r'^(LN_Neck_IV~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_IV_R', '241957', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level IV (Lower Jugular) neck node Right'),
Structure(re.compile(r'^(LN_Neck_V~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_V_L', '241965', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VA, VB and VC (Posterior Triangle) neck nodes Left'),
Structure(re.compile(r'^(LN_Neck_V~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_V_R', '241963', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VA, VB and VC (Posterior Triangle) neck nodes Right'),
Structure(re.compile(r'^(LN_Neck_VA~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VA_L', '265629', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VA (Posterior Triangle) neck node Left'),
Structure(re.compile(r'^(LN_Neck_VA~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VA_R', '265626', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VA (Posterior Triangle) neck node Right'),
Structure(re.compile(r'^(LN_Neck_VB~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VB_L', 'nan', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VB (Posterior Triangle) neck node Left'),
Structure(re.compile(r'^(LN_Neck_VB~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VB_R', 'nan', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VB (Posterior Triangle) neck node Right'),
Structure(re.compile(r'^(LN_Neck_VC~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VC_L', '232721', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VC (Posterior Triangle) neck node Left'),
Structure(re.compile(r'^(LN_Neck_VC~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VC_R', '232719', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VC (Posterior Triangle) neck node Right'),
Structure(re.compile(r'^(LN_Neck_VI~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VI_L', '241971', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VI (Anterior Triangle) neck node Left'),
Structure(re.compile(r'^(LN_Neck_VI~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VI_R', '241969', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VI (Anterior Triangle) neck node Right'),
Structure(re.compile(r'^(LN_Neck_VII~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VII_L', 'nan', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VII (Upper Mediastinal) neck node Left'),
Structure(re.compile(r'^(LN_Neck_VII~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Neck_VII_R', 'nan', 'Anatomic', 'Lymph Node', 'Neck Nodes', 'Head and Neck', 'Level VII (Upper Mediastinal) neck node Right'),
Structure(re.compile(r'^(LN_Obturator~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Obturator_L', '16676', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - obturator Left'),
Structure(re.compile(r'^(LN_Obturator~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Obturator_R', '16676', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - obturator Right'),
Structure(re.compile(r'^(LN_Paraaortic~?(\^[\w\d_\+-]+)?)$'), 'LN_Paraaortic', '223899', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of abdomen- para-aortic'),
Structure(re.compile(r'^(LN_Paramammary~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Paramammary_L', '232600', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Paramammary Left'),
Structure(re.compile(r'^(LN_Paramammary~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Paramammary_R', '232598', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Paramammary Right'),
Structure(re.compile(r'^(LN_Paramammarys~?(\^[\w\d_\+-]+)?)$'), 'LN_Paramammarys', '44313', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Paramammary'),
Structure(re.compile(r'^(LN_Parasternal~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Parasternal_L', '5934', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Parasternal Left'),
Structure(re.compile(r'^(LN_Parasternal~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Parasternal_R', '5933', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Parasternal Right'),
Structure(re.compile(r'^(LN_Parasternals~?(\^[\w\d_\+-]+)?)$'), 'LN_Parasternals', '5849', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Parasternal'),
Structure(re.compile(r'^(LN_Pelvic~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Pelvic_L', 'nan', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Pelvic Lymph Nodes Left'),
Structure(re.compile(r'^(LN_Pelvic~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Pelvic_R', 'nan', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Pelvic Lymph Nodes Right'),
Structure(re.compile(r'^(LN_Pelvics~?(\^[\w\d_\+-]+)?)$'), 'LN_Pelvics', 'nan', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Pelvic Lymph Nodes'),
Structure(re.compile(r'^(LN_Portahepatis~?(\^[\w\d_\+-]+)?)$'), 'LN_Portahepatis', '15758', 'Anatomic', 'Lymph Node', 'Porta hepatis', 'Abdomen', 'Porta hepatis'),
Structure(re.compile(r'^(LN_Presacral~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Presacral_L', '234280', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - presacral Left'),
Structure(re.compile(r'^(LN_Presacral~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Presacral_R', '234280', 'Anatomic', 'Lymph Node', 'nan', 'Pelvis', 'Lymph nodes of pelvis - presacral Right'),
Structure(re.compile(r'^(LN_Pulmonary~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Pulmonary_L', '5970', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Pulmonary Left'),
Structure(re.compile(r'^(LN_Pulmonary~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Pulmonary_R', '5969', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Pulmonary Right'),
Structure(re.compile(r'^(LN_Pulmonarys~?(\^[\w\d_\+-]+)?)$'), 'LN_Pulmonarys', '5968', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Pulmonary'),
Structure(re.compile(r'^(LN~?_R(\^[\w\d_\+-]+)?)$'), 'LN_R', 'nan', 'Anatomic', 'Lymph Node', 'Unspecified', 'Body', 'Lymph Node Right'),
Structure(re.compile(r'^(LN_Sclav~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Sclav_L', '232719', 'Anatomic', 'Lymph Node', 'Breast', 'Body', 'Supraclavicular Lymph Node Left'),
Structure(re.compile(r'^(LN_Sclav~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Sclav_R', '232721', 'Anatomic', 'Lymph Node', 'Breast', 'Body', 'Supraclavicular Lymph Node Right'),
Structure(re.compile(r'^(LN_Supmammary~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Supmammary_L', '232604', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Supramammary Left'),
Structure(re.compile(r'^(LN_Supmammary~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Supmammary_R', '232602', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Supramammary Right'),
Structure(re.compile(r'^(LN_Supmammarys~?(\^[\w\d_\+-]+)?)$'), 'LN_Supmammarys', '12785', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Supramammary'),
Structure(re.compile(r'^(LN_Trachbrnchs~?(\^[\w\d_\+-]+)?)$'), 'LN_Trachbrnchs', '5950', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Tracheobronchial'),
Structure(re.compile(r'^(LN_Trachbrnchs~?_L(\^[\w\d_\+-]+)?)$'), 'LN_Trachbrnchs_L', '5952', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Tracheobronchial Left'),
Structure(re.compile(r'^(LN_Trachbrnchs~?_R(\^[\w\d_\+-]+)?)$'), 'LN_Trachbrnchs_R', '5951', 'Anatomic', 'Lymph Node', 'nan', 'Thorax', 'Lymph nodes of thorax - Tracheobronchial Right'),
Structure(re.compile(r'^(Lobe_Frontal~?(\^[\w\d_\+-]+)?)$'), 'Lobe_Frontal', '61824', 'Anatomic', 'Brain', 'Lobe', 'Head and Neck', 'Frontal Lobe'),
Structure(re.compile(r'^(Lobe_Frontal~?_L(\^[\w\d_\+-]+)?)$'), 'Lobe_Frontal_L', '72970', 'Anatomic', 'Brain', 'Lobe', 'Head and Neck', 'Frontal Lobe Left'),
Structure(re.compile(r'^(Lobe_Frontal~?_R(\^[\w\d_\+-]+)?)$'), 'Lobe_Frontal_R', '72969', 'Anatomic', 'Brain', 'Lobe', 'Head and Neck', 'Frontal Lobe Left'),
Structure(re.compile(r'^(Lobe_Occipital~?(\^[\w\d_\+-]+)?)$'), 'Lobe_Occipital', '67325', 'Anatomic', 'Brain', 'Occipital Lobe', 'Head and Neck', 'Occipital Lobe'),
Structure(re.compile(r'^(Lobe_Occipital~?_L(\^[\w\d_\+-]+)?)$'), 'Lobe_Occipital_L', '72976', 'Anatomic', 'Brain', 'Occipital Lobe', 'Head and Neck', 'Occipital Lobe Left'),
Structure(re.compile(r'^(Lobe_Occipital~?_R(\^[\w\d_\+-]+)?)$'), 'Lobe_Occipital_R', '72975', 'Anatomic', 'Brain', 'Occipital Lobe', 'Head and Neck', 'Occipital Lobe Right'),
Structure(re.compile(r'^(Lobe_Parietal~?(\^[\w\d_\+-]+)?)$'), 'Lobe_Parietal', '61826', 'Anatomic', 'Brain', 'Lobe', 'Head and Neck', 'Parietal Lobe'),
Structure(re.compile(r'^(Lobe_Parietal~?_L(\^[\w\d_\+-]+)?)$'), 'Lobe_Parietal_L', '72974', 'Anatomic', 'Brain', 'Lobe', 'Head and Neck', 'Parietal Lobe Left'),
Structure(re.compile(r'^(Lobe_Parietal~?_R(\^[\w\d_\+-]+)?)$'), 'Lobe_Parietal_R', '72973', 'Anatomic', 'Brain', 'Lobe', 'Head and Neck', 'Parietal Lobe Right'),
Structure(re.compile(r'^(Lobe_Temporal~?(\^[\w\d_\+-]+)?)$'), 'Lobe_Temporal', '61825', 'Anatomic', 'Brain', 'Temporal', 'Head and Neck', 'Temporal Lobe'),
Structure(re.compile(r'^(Lobe_Temporal~?_L(\^[\w\d_\+-]+)?)$'), 'Lobe_Temporal_L', '72972', 'Anatomic', 'Brain', 'Temporal', 'Head and Neck', 'Temporal Lobe Left'),
Structure(re.compile(r'^(Lobe_Temporal~?_R(\^[\w\d_\+-]+)?)$'), 'Lobe_Temporal_R', '72971', 'Anatomic', 'Brain', 'Temporal', 'Head and Neck', 'Temporal Lobe Right'),
Structure(re.compile(r'^(Lung~?_L(\^[\w\d_\+-]+)?)$'), 'Lung_L', '7310', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Lung Left'),
Structure(re.compile(r'^(Lung~?_LLL(\^[\w\d_\+-]+)?)$'), 'Lung_LLL', '7371', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Lung - lower lobe of left'),
Structure(re.compile(r'^(Lung~?_LUL(\^[\w\d_\+-]+)?)$'), 'Lung_LUL', '7370', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Lung - upper lobe of left'),
Structure(re.compile(r'^(Lung~?_R(\^[\w\d_\+-]+)?)$'), 'Lung_R', '7309', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Lung Right'),
Structure(re.compile(r'^(Lung~?_RLL(\^[\w\d_\+-]+)?)$'), 'Lung_RLL', '7337', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Lung - lower lobe of right'),
Structure(re.compile(r'^(Lung~?_RML(\^[\w\d_\+-]+)?)$'), 'Lung_RML', '7383', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Lung - middle lobe of right'),
Structure(re.compile(r'^(Lung~?_RUL(\^[\w\d_\+-]+)?)$'), 'Lung_RUL', '7333', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Lung - upper lobe of right'),
Structure(re.compile(r'^(Lungs~?(\^[\w\d_\+-]+)?)$'), 'Lungs', '68877', 'Anatomic', 'Lung', 'nan', 'Thorax', 'Pair of Lungs'),
Structure(re.compile(r'^(Lungs-CTV(\^[\w\d_\+-]+)?)$'), 'Lungs-CTV', 'nan', 'Derived', 'Lung', 'nan', 'Thorax', 'Total Lung minus the CTV'),
Structure(re.compile(r'^(Lungs-GTV(\^[\w\d_\+-]+)?)$'), 'Lungs-GTV', 'nan', 'Derived', 'Lung', 'nan', 'Thorax', 'Total Lung minus the GTV'),
Structure(re.compile(r'^(Lungs-ITV(\^[\w\d_\+-]+)?)$'), 'Lungs-ITV', 'nan', 'Derived', 'Lung', 'nan', 'Thorax', 'nan'),
Structure(re.compile(r'^(Lungs-PTV(\^[\w\d_\+-]+)?)$'), 'Lungs-PTV', 'nan', 'Derived', 'Lung', 'nan', 'Thorax', 'Total Lung minus the PTV'),
Structure(re.compile(r'^(Malleus~?(\^[\w\d_\+-]+)?)$'), 'Malleus', '52753', 'Anatomic', 'Bone', 'Ear', 'Head and Neck', 'Malleus'),
Structure(re.compile(r'^(Malleus~?_L(\^[\w\d_\+-]+)?)$'), 'Malleus_L', '74053', 'Anatomic', 'Bone', 'Ear', 'Head and Neck', 'Malleus Left'),
Structure(re.compile(r'^(Malleus~?_R(\^[\w\d_\+-]+)?)$'), 'Malleus_R', '74052', 'Anatomic', 'Bone', 'Ear', 'Head and Neck', 'Malleus Right'),
Structure(re.compile(r'^(Markers~?(\^[\w\d_\+-]+)?)$'), 'Markers', 'nan', 'Non_Anatomic', 'Devices', 'nan', 'Body', 'nan'),
Structure(re.compile(r'^(Maxilla~?(\^[\w\d_\+-]+)?)$'), 'Maxilla', '9711', 'Anatomic', 'Bone', 'Maxilla', 'Head and Neck', 'Maxilla'),
Structure(re.compile(r'^(Maxilla~?_L(\^[\w\d_\+-]+)?)$'), 'Maxilla_L', '53650', 'Anatomic', 'Bone', 'Maxilla', 'Head and Neck', 'Maxilla Left'),
Structure(re.compile(r'^(Maxilla~?_R(\^[\w\d_\+-]+)?)$'), 'Maxilla_R', '53649', 'Anatomic', 'Bone', 'Maxilla', 'Head and Neck', 'Maxilla Right'),
Structure(re.compile(r'^(Mediastinum~?(\^[\w\d_\+-]+)?)$'), 'Mediastinum', '9826', 'Anatomic', 'Heart', 'nan', 'Thorax', 'Mediastinum'),
Structure(re.compile(r'^(Musc~?(\^[\w\d_\+-]+)?)$'), 'Musc', '30316', 'Anatomic', 'Muscle', 'nan', 'Body', 'Muscle'),
Structure(re.compile(r'^(Musc_Constrict~?(\^[\w\d_\+-]+)?)$'), 'Musc_Constrict', '46620', 'Anatomic', 'Muscle', 'Constrictors', 'Head and Neck', 'Constrictor Muscle of Pharynx'),
Structure(re.compile(r'^(Musc_Constrict~?_I(\^[\w\d_\+-]+)?)$'), 'Musc_Constrict_I', '46623', 'Anatomic', 'Muscle', 'Constrictors', 'Head and Neck', 'Pharynx - Inferior pharyngeal constrictor'),
Structure(re.compile(r'^(Musc_Constrict_M~?(\^[\w\d_\+-]+)?)$'), 'Musc_Constrict_M', '46622', 'Anatomic', 'Muscle', 'Constrictors', 'Head and Neck', ' Pharynx - Middle pharyngeal constrictor'),
Structure(re.compile(r'^(Musc_Constrict~?_S(\^[\w\d_\+-]+)?)$'), 'Musc_Constrict_S', '46621', 'Anatomic', 'Muscle', 'Constrictors', 'Head and Neck', 'Pharynx - Superior pharyngeal constrictor'),
Structure(re.compile(r'^(Musc_Digastric~?_L(\^[\w\d_\+-]+)?)$'), 'Musc_Digastric_L', '46293', 'Anatomic', 'Muscle', 'Digastric', 'Abdomen', 'Digastric muscle Left'),
Structure(re.compile(r'^(Musc_Digastric~?_R(\^[\w\d_\+-]+)?)$'), 'Musc_Digastric_R', '46292', 'Anatomic', 'Muscle', 'Digastric', 'Abdomen', 'Digastric muscle Right'),
Structure(re.compile(r'^(Musc_Masseter~?(\^[\w\d_\+-]+)?)$'), 'Musc_Masseter', '48996', 'Anatomic', 'Muscle', 'Masseter', 'Head and Neck', 'Masseter Muscle'),
Structure(re.compile(r'^(Musc_Masseter~?_L(\^[\w\d_\+-]+)?)$'), 'Musc_Masseter_L', '48998', 'Anatomic', 'Muscle', 'Masseter', 'Head and Neck', 'Masseter Muscle Left'),
Structure(re.compile(r'^(Musc_Masseter~?_R(\^[\w\d_\+-]+)?)$'), 'Musc_Masseter_R', '48997', 'Anatomic', 'Muscle', 'Masseter', 'Head and Neck', 'Masseter Muscle Right'),
Structure(re.compile(r'^(Musc_Platysma~?_L(\^[\w\d_\+-]+)?)$'), 'Musc_Platysma_L', '45740', 'Anatomic', 'Muscle', 'Platysma', 'Head and Neck', 'Platysma Left'),
Structure(re.compile(r'^(Musc_Platysma~?_R(\^[\w\d_\+-]+)?)$'), 'Musc_Platysma_R', '45739', 'Anatomic', 'Muscle', 'Platysma', 'Head and Neck', 'Platysma Right'),
Structure(re.compile(r'^(Musc_Pterygoid~?_L(\^[\w\d_\+-]+)?)$'), 'Musc_Pterygoid_L', 'nan', 'Anatomic', 'Muscle', 'Pterygoid', 'Head and Neck', 'Pterygoid muscles - Left'),
Structure(re.compile(r'^(Musc_Pterygoid~?_R(\^[\w\d_\+-]+)?)$'), 'Musc_Pterygoid_R', 'nan', 'Anatomic', 'Muscle', 'Pterygoid', 'Head and Neck', 'Pterygoid muscles - Right'),
Structure(re.compile(r'^(Musc_Sclmast~?_L(\^[\w\d_\+-]+)?)$'), 'Musc_Sclmast_L', '13409', 'Anatomic', 'Muscle', 'Sternocleidomastoid', 'Head and Neck', 'Sternocleidomastoid Left'),
Structure(re.compile(r'^(Musc_Sclmast~?_R(\^[\w\d_\+-]+)?)$'), 'Musc_Sclmast_R', '13408', 'Anatomic', 'Muscle', 'Sternocleidomastoid', 'Head and Neck', 'Sternocleidomastoid Left'),
Structure(re.compile(r'^(Musc_Temporal~?_L(\^[\w\d_\+-]+)?)$'), 'Musc_Temporal_L', '49008', 'Anatomic', 'Muscle', 'Temporal', 'Head and Neck', 'Temporal muscle - Left'),
Structure(re.compile(r'^(Musc_Temporal~?_R(\^[\w\d_\+-]+)?)$'), 'Musc_Temporal_R', '49007', 'Anatomic', 'Muscle', 'Temporal', 'Head and Neck', 'Temporal muscle - Right'),
Structure(re.compile(r'^(Nasalconcha_LI~?(\^[\w\d_\+-]+)?)$'), 'Nasalconcha_LI', '54738', 'Anatomic', 'Nose', 'Nasal', 'Head and Neck', 'Inferior Nasal Concha Left'),
Structure(re.compile(r'^(Nasalconcha_RI~?(\^[\w\d_\+-]+)?)$'), 'Nasalconcha_RI', '54737', 'Anatomic', 'Nose', 'Nasal', 'Head and Neck', 'Inferior Nasal Concha Right'),
Structure(re.compile(r'^(Nasopharynx~?(\^[\w\d_\+-]+)?)$'), 'Nasopharynx', '54878', 'Anatomic', 'Nose', 'Nasal', 'Head and Neck', 'Nasal part of pharynx'),
Structure(re.compile(r'^(Nose~?(\^[\w\d_\+-]+)?)$'), 'Nose', '46472', 'Anatomic', 'Nose', 'Nasal', 'Head and Neck', 'Nose'),
Structure(re.compile(r'^(Nrv_Peripheral~?(\^[\w\d_\+-]+)?)$'), 'Nrv_Peripheral', 'nan', 'Anatomic', 'Nerve', 'nan', 'Body', 'Peripheral Nerve'),
Structure(re.compile(r'^(Nrv_Root~?(\^[\w\d_\+-]+)?)$'), 'Nrv_Root', '5981', 'Anatomic', 'Nerve', 'nan', 'Body', 'Nerve Root'),
Structure(re.compile(r'^(OpticChiasm~?(\^[\w\d_\+-]+)?)$'), 'OpticChiasm', '62045', 'Anatomic', 'Nerve', 'Optic', 'Head and Neck', 'Optic chiasm'),
Structure(re.compile(r'^(OpticChiasm~?_PRV?\d{0,2}(\^[\w\d_\+-]+)?)$'), 'OpticChiasm_PRVxx', 'nan', 'PRV', 'Nerve', 'Optic', 'Head and Neck', 'PRV for Optic Chiasm or PRV expansion of x mm on the optic chiasm'),
Structure(re.compile(r'^(OpticNrv~?(\^[\w\d_\+-]+)?)$'), 'OpticNrv', '50863', 'Anatomic', 'Nerve', 'Optic', 'Head and Neck', 'Optic nerve'),
Structure(re.compile(r'^(OpticNrv~?_L(\^[\w\d_\+-]+)?)$'), 'OpticNrv_L', '50878', 'Anatomic', 'Nerve', 'Optic', 'Head and Neck', 'Optic nerve'),
Structure(re.compile(r'^(OpticNrv~?_PRV?\d{0,2}(\^[\w\d_\+-]+)?)$'), 'OpticNrv_PRVxx', 'nan', 'PRV', 'Nerve', 'Optic', 'Head and Neck', 'PRV for Optic Nerve'),
Structure(re.compile(r'^(OpticNrv~?_PRV?\d{0,2}_L(\^[\w\d_\+-]+)?)$'), 'OpticNrv_PRV_Lxx', 'nan', 'PRV', 'Nerve', 'Optic', 'Head and Neck', 'PRV expansion of xx millimeters on the right optic nerve'),
Structure(re.compile(r'^(OpticNrv~?_PRV?\d{0,2}_R(\^[\w\d_\+-]+)?)$'), 'OpticNrv_PRV_Rxx', 'nan', 'PRV', 'Nerve', 'Optic', 'Head and Neck', 'PRV created with xx mm expansion on the left optic nerve'),
Structure(re.compile(r'^(OpticNrv~?_R(\^[\w\d_\+-]+)?)$'), 'OpticNrv_R', '50875', 'Anatomic', 'Nerve', 'Optic', 'Head and Neck', 'Optic nerve'),
Structure(re.compile(r'^(Orbit~?_L(\^[\w\d_\+-]+)?)$'), 'Orbit_L', '54668', 'Anatomic', 'Eye', 'Orbit', 'Head and Neck', 'Orbit Left'),
Structure(re.compile(r'^(Orbit~?_R(\^[\w\d_\+-]+)?)$'), 'Orbit_R', '54667', 'Anatomic', 'Eye', 'Orbit', 'Head and Neck', 'Orbit Right'),
Structure(re.compile(r'^(Oropharynx~?(\^[\w\d_\+-]+)?)$'), 'Oropharynx', '54879', 'Anatomic', 'Throat', 'Oropharynx', 'Head and Neck', 'Oral part of pharynx'),
Structure(re.compile(r'^(Ovaries~?(\^[\w\d_\+-]+)?)$'), 'Ovaries', '7409', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Ovary'),
Structure(re.compile(r'^(Ovary~?_L(\^[\w\d_\+-]+)?)$'), 'Ovary_L', '7214', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Ovary Left'),
Structure(re.compile(r'^(Ovary~?_R(\^[\w\d_\+-]+)?)$'), 'Ovary_R', '7213', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Ovary Right'),
Structure(re.compile(r'^(Pacemaker(\^[\w\d_\+-]+)?)$'), 'Pacemaker', 'nan', 'Non_Anatomic', 'Devices', 'nan', 'Thorax', 'Pacemaker'),
Structure(re.compile(r'^(Palate_Soft~?(\^[\w\d_\+-]+)?)$'), 'Palate_Soft', '55021', 'Anatomic', 'Muscle', 'Soft Palate', 'Head and Neck', 'Soft palate'),
Structure(re.compile(r'^(PancJejuno~?(\^[\w\d_\+-]+)?)$'), 'PancJejuno', 'nan', 'Surgical', 'Gut', 'nan', 'Abdomen', 'The pancreatic jejuno junction - generated by surgical procedure'),
Structure(re.compile(r'^(Pancreas~?(\^[\w\d_\+-]+)?)$'), 'Pancreas', '7198', 'Anatomic', 'Gland', 'Pancreas', 'Abdomen', 'Pancreas'),
Structure(re.compile(r'^(Pancreas_Head~?(\^[\w\d_\+-]+)?)$'), 'Pancreas_Head', '10468', 'Anatomic', 'Gland', 'Pancreas', 'Abdomen', 'Head of Pancreas'),
Structure(re.compile(r'^(Pancreas_Tail~?(\^[\w\d_\+-]+)?)$'), 'Pancreas_Tail', '14519', 'Anatomic', 'Gland', 'Pancreas', 'Abdomen', 'Tail of Pancreas'),
Structure(re.compile(r'^(Parametrium~?(\^[\w\d_\+-]+)?)$'), 'Parametrium', '77061', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Parametrium'),
Structure(re.compile(r'^(Parotid~?_L(\^[\w\d_\+-]+)?)$'), 'Parotid_L', '59798', 'Anatomic', 'Gland', 'Parotid', 'Head and Neck', 'Parotid Left'),
Structure(re.compile(r'^(Parotid~?_R(\^[\w\d_\+-]+)?)$'), 'Parotid_R', '59797', 'Anatomic', 'Gland', 'Parotid', 'Head and Neck', 'Parotid Right'),
Structure(re.compile(r'^(Parotids~?(\^[\w\d_\+-]+)?)$'), 'Parotids', '320436', 'Anatomic', 'Gland', 'Parotid', 'Head and Neck', 'Pair of Parotid Glands'),
Structure(re.compile(r'^(PenileBulb~?(\^[\w\d_\+-]+)?)$'), 'PenileBulb', '19614', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Penile Bulb'),
Structure(re.compile(r'^(Penis~?(\^[\w\d_\+-]+)?)$'), 'Penis', '9707', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Penis'),
Structure(re.compile(r'^(Pericardium~?(\^[\w\d_\+-]+)?)$'), 'Pericardium', '9869', 'Anatomic', 'Heart', 'Membrane', 'Thorax', 'Pericardium'),
Structure(re.compile(r'^(Perineum~?(\^[\w\d_\+-]+)?)$'), 'Perineum', '9579', 'Anatomic', 'Perineum', 'nan', 'Pelvis', 'Perineum'),
Structure(re.compile(r'^(Peritoneum~?(\^[\w\d_\+-]+)?)$'), 'Peritoneum', '9908', 'Anatomic', 'Membrane', 'Peritoneum', 'Abdomen', 'Peritoneal sac'),
Structure(re.compile(r'^(Pharynx~?(\^[\w\d_\+-]+)?)$'), 'Pharynx', '46688', 'Anatomic', 'Throat', 'Pharynx', 'Head and Neck', 'Pharynx'),
Structure(re.compile(r'^(Pineal~?(\^[\w\d_\+-]+)?)$'), 'Pineal', '62033', 'Anatomic', 'Gland', 'Pineal', 'Head and Neck', 'Pineal gland'),
Structure(re.compile(r'^(Pituitary~?(\^[\w\d_\+-]+)?)$'), 'Pituitary', '13889', 'Anatomic', 'Gland', 'Pituitary', 'Head and Neck', 'Pituitary gland'),
Structure(re.compile(r'^(Pituitary~?_PRV?\d{0,2}~?(\^[\w\d_\+-]+)?)$'), 'Pituitary_PRVxx', 'nan', 'PRV', 'Gland', 'Pituitary', 'Head and Neck', 'PRV constructed as xx millimeter expansion on Pituitary'),
Structure(re.compile(r'^(Pons~?(\^[\w\d_\+-]+)?)$'), 'Pons', '67943', 'Anatomic', 'Brain', 'Brainstem', 'Head and Neck', 'Pons'),
Structure(re.compile(r'^(Postop~?(\^[\w\d_\+-]+)?)$'), 'Postop', 'nan', 'Non_Anatomic', 'Surgery', 'nan', 'Body', 'Post operative volume'),
Structure(re.compile(r'^(Preop~?(\^[\w\d_\+-]+)?)$'), 'Preop', 'nan', 'Non_Anatomic', 'Surgery', 'nan', 'Body', 'Region originally occupied by the gross tumor volume'),
Structure(re.compile(r'^(Proc_Condyloid~?_L(\^[\w\d_\+-]+)?)$'), 'Proc_Condyloid_L', '52838', 'Anatomic', 'Bone', 'Mandible', 'Head and Neck', 'Condyloid process of mandible - Right'),
Structure(re.compile(r'^(Proc_Condyloid~?_R(\^[\w\d_\+-]+)?)$'), 'Proc_Condyloid_R', '52840', 'Anatomic', 'Bone', 'Mandible', 'Head and Neck', 'Condyloid process of mandible - Left'),
Structure(re.compile(r'^(Proc_Coronoid~?_L(\^[\w\d_\+-]+)?)$'), 'Proc_Coronoid_L', '52835', 'Anatomic', 'Bone', 'Mandible', 'Head and Neck', 'Coronoid process of mandible - Left'),
Structure(re.compile(r'^(Proc_Coronoid~?_R(\^[\w\d_\+-]+)?)$'), 'Proc_Coronoid_R', '52834', 'Anatomic', 'Bone', 'Mandible', 'Head and Neck', 'Coronoid process of mandible - Right'),
Structure(re.compile(r'^(Prostate~?(\^[\w\d_\+-]+)?)$'), 'Prostate', '9600', 'Anatomic', 'Gland', 'Prostate', 'Pelvis', 'Prostate'),
Structure(re.compile(r'^(ProstateBed~?(\^[\w\d_\+-]+)?)$'), 'ProstateBed', 'nan', 'Anatomic', 'Surgery', 'Prostate', 'Pelvis', 'Prostate Bed'),
Structure(re.compile(r'^(Prosthesis~?(\^[\w\d_\+-]+)?)$'), 'Prosthesis', 'nan', 'Anatomic', 'Surgery', 'nan', 'Body', 'Prosthesis'),
Structure(re.compile(r'^(Pterygoid_Lat~?_L(\^[\w\d_\+-]+)?)$'), 'Pterygoid_Lat_L', '49017', 'Anatomic', 'Muscle', 'Pterygoid', 'Head and Neck', 'Pterygoid muscles lateral - Left'),
Structure(re.compile(r'^(Pterygoid_Lat~?_R(\^[\w\d_\+-]+)?)$'), 'Pterygoid_Lat_R', '49016', 'Anatomic', 'Muscle', 'Pterygoid', 'Head and Neck', 'Pterygoid muscles lateral - Right'),
Structure(re.compile(r'^(Pterygoid_Med~?_L(\^[\w\d_\+-]+)?)$'), 'Pterygoid_Med_L', '49013', 'Anatomic', 'Muscle', 'Pterygoid', 'Head and Neck', 'Pterygoid muscles medial - Left'),
Structure(re.compile(r'^(Pterygoid_Med~?_R(\^[\w\d_\+-]+)?)$'), 'Pterygoid_Med_R', '49012', 'Anatomic', 'Muscle', 'Pterygoid', 'Head and Neck', 'Pterygoid muscles medial - Right'),
Structure(re.compile(r'^(PTV!?(p|n|(sb))?\d{0,2}(_((Postop)|(Preop)|(TumorBed)|(Boost)|(Eval)|(A_Aorta)|(A_Aorta_Asc)|(A_Brachiocephls)|(A_Carotid)|(A_Carotid_L)|(A_Carotid_R)|(A_Celiac)|(A_Coronary)|(A_Coronary_L)|(A_Coronary_R)|(A_Femoral_Cflx_L)|(A_Femoral_Cflx_R)|(A_Femoral_L)|(A_Femoral_R)|(A_Humeral_Cflx_L)|(A_Humeral_Cflx_R)|(A_Humeral_L)|(A_Humeral_R)|(A_Hypophyseal_I)|(A_Hypophyseal_S)|(A_Iliac_Cflx_L)|(A_Iliac_Cflx_R)|(A_Iliac_Ext_L)|(A_Iliac_Ext_R)|(A_Iliac_Int_L)|(A_Iliac_Int_R)|(A_Iliac_L)|(A_Iliac_R)|(A_LAD)|(A_Mesenteric_I)|(A_Mesenteric_S)|(A_Pulmonary)|(A_Subclavian)|(A_Subclavian_L)|(A_Subclavian_R)|(A_Vertebral)|(A_Vertebral_L)|(A_Vertebral_R)|(Acetabulum_L)|(Acetabulum_R)|(Acetabulums)|(AirWay_Dist)|(AirWay_Prox)|(Anus)|(Appendix)|(Arytenoid)|(Arytenoid_L)|(Arytenoid_R)|(Atrium)|(Atrium_L)|(Atrium_R)|(BileDuct_Common)|(Bladder)|(Bladder_Wall)|(Body)|(Bone)|(Bone_Ethmoid)|(Bone_Frontal)|(Bone_Hyoid)|(Bone_Ilium)|(Bone_Ilium_L)|(Bone_Ilium_R)|(Bone_Incus)|(Bone_Incus_L)|(Bone_Incus_R)|(Bone_Ischium_L)|(Bone_Ischium_R)|(Bone_Lacrimal)|(Bone_Lacrimal_L)|(Bone_Lacrimal_R)|(Bone_Mandible)|(Bone_Mastoid_L)|(Bone_Mastoid_R)|(Bone_Nasal)|(Bone_Nasal_L)|(Bone_Nasal_R)|(Bone_Occipital)|(Bone_Palatine)|(Bone_Palatine_L)|(Bone_Palatine_R)|(Bone_Parietal)|(Bone_Parietal_L)|(Bone_Parietal_R)|(Bone_Pelvic)|(Bone_Pelvic_L)|(Bone_Pelvic_R)|(Bone_Sphenoid)|(Bone_Temporal)|(Bone_Temporal_L)|(Bone_Temporal_R)|(Bone_Zygomatic_L)|(Bone_Zygomatic_R)|(Bone_Zygomatics)|(BoneMarrow)|(BoneMarrow_Act)|(Bowel)|(Bowel_Large)|(Bowel_Small)|(BrachialPlex_L)|(BrachialPlex_R)|(BrachialPlexs)|(Brain)|(Brainstem)|(Brainstem_Core)|(Brainstem_Surf)|(Breast_L)|(Breast_R)|(Breasts)|(Bronchus)|(Bronchus_L)|(Bronchus_Main)|(Bronchus_Main_L)|(Bronchus_Main_R)|(Bronchus_PRVxx)|(Bronchus_R)|(Canal_Anal)|(Carina)|(Cartlg_Thyroid)|(CaudaEquina)|(Cavernosum)|(Cavity_Nasal)|(Cavity_Oral)|(Cecum)|(Cerebellum)|(Cerebrum)|(Cerebrum_L)|(Cerebrum_R)|(Cervix)|(Chestwall)|(Chestwall_L)|(Chestwall_R)|(Cist_Pontine)|(Cist_Suprasellar)|(Clavicle_L)|(Clavicle_R)|(CN_III)|(CN_III_L)|(CN_III_R)|(CN_IX)|(CN_IX_L)|(CN_IX_R)|(CN_V)|(CN_V_L)|(CN_V_R)|(CN_VI)|(CN_VI_L)|(CN_VI_R)|(CN_VII)|(CN_VII_L)|(CN_VII_R)|(CN_VIII)|(CN_VIII_L)|(CN_VIII_R)|(CN_XI)|(CN_XI_L)|(CN_XI_R)|(CN_XII)|(CN_XII_L)|(CN_XII_R)|(Cochlea)|(Cochlea_L)|(Cochlea_R)|(Colon)|(Colon_Ascending)|(Colon_Decending)|(Colon_PTVxx)|(Colon_Sigmoid)|(Colon_Transverse)|(Cornea)|(Cornea_L)|(Cornea_R)|(CribriformPlate)|(Cricoid)|(Cricopharyngeus)|(Dens)|(Diaphragm)|(Duodenum)|(Ear_External_L)|(Ear_External_R)|(Ear_Externals)|(Ear_Internal_L)|(Ear_Internal_R)|(Ear_Internals)|(Ear_Middle)|(Ear_Middle_L)|(Ear_Middle_R)|(Edema)|(Elbow)|(Elbow_L)|(Elbow_R)|(Esophagus)|(Esophagus_I)|(Esophagus_M)|(Esophagus_NAdj)|(Esophagus_S)|(External)|(Eye_L)|(Eye_R)|(Eyes)|(Femur_Base_L)|(Femur_Base_R)|(Femur_Head_L)|(Femur_Head_R)|(Femur_Joint_L)|(Femur_Joint_R)|(Femur_L)|(Femur_Neck_L)|(Femur_Neck_R)|(Femur_R)|(Femur_Shaft_L)|(Femur_Shaft_R)|(Femurs)|(Fibula)|(Fibula_L)|(Fibula_R)|(Fossa_Jugular)|(Fossa_Posterior)|(Gallbladder)|(Genitals)|(Glnd_Adrenal_L)|(Glnd_Adrenal_R)|(Glnd_Lacrimal)|(Glnd_Lacrimal_L)|(Glnd_Lacrimal_R)|(Glnd_Parathyroid)|(Glnd_Subling_L)|(Glnd_Subling_R)|(Glnd_Sublings)|(Glnd_Submand_L)|(Glnd_Submand_R)|(Glnd_Submands)|(Glnd_Thymus)|(Glnd_Thyroid)|(Glottis)|(GreatVes)|(GreatVes_NAdj)|(GrowthPlate_L)|(GrowthPlate_R)|(Hardpalate)|(Heart)|(Hemisphere_L)|(Hemisphere_R)|(Hemispheres)|(Hippocampi)|(Hippocampus_L)|(Hippocampus_R)|(Humerus_L)|(Humerus_R)|(Hypothalmus)|(Ileum)|(Jejunum)|(Jejunum_Ileum)|(Joint_Elbow)|(Joint_Elbow_L)|(Joint_Elbow_R)|(Joint_Glenohum)|(Joint_Glenohum_L)|(Joint_Glenohum_R)|(Joint_Surface)|(Joint_TM)|(Joint_TM_L)|(Joint_TM_R)|(Kidney_Cortex)|(Kidney_Cortex_L)|(Kidney_Cortex_R)|(Kidney_Hilum_L)|(Kidney_Hilum_R)|(Kidney_Hilums)|(Kidney_L)|(Kidney_Pelvis_L)|(Kidney_Pelvis_R)|(Kidney_R)|(Kidneys)|(Knee)|(Knee_L)|(Knee_R)|(Laryngl_Pharynx)|(Larynx)|(Larynx_SG)|(Lens)|(Lens_L)|(Lens_R)|(Lig_Hepatogastrc)|(Lips)|(Liver)|(LN)|(LN_Ax_Apical)|(LN_Ax_Apical_L)|(LN_Ax_Apical_R)|(LN_Ax_Central_L)|(LN_Ax_Central_R)|(LN_Ax_Centrals)|(LN_Ax_L)|(LN_Ax_L1_L)|(LN_Ax_L1_R)|(LN_Ax_L2_L)|(LN_Ax_L2_R)|(LN_Ax_L3_L)|(LN_Ax_L3_R)|(LN_Ax_Lateral_L)|(LN_Ax_Lateral_R)|(LN_Ax_Laterals)|(LN_Ax_Pectoral_L)|(LN_Ax_Pectoral_R)|(LN_Ax_Pectorals)|(LN_Ax_R)|(LN_Ax_Subscap_L)|(LN_Ax_Subscap_R)|(LN_Ax_Subscaps)|(LN_Brachioceph_L)|(LN_Brachioceph_R)|(LN_Brachiocephs)|(LN_Bronchpulm_L)|(LN_Bronchpulm_R)|(LN_Bronchpulms)|(LN_Diaphragmatic)|(LN_Iliac_Ext_L)|(LN_Iliac_Ext_R)|(LN_Iliac_Int_L)|(LN_Iliac_L)|(LN_Iliac_R)|(LN_IMN_L)|(LN_IMN_R)|(LN_IMNs)|(LN_Inguinofem)|(LN_Inguinofem_L)|(LN_Inguinofem_R)|(LN_Intercostals)|(LN_L)|(LN_Ligamentarter)|(LN_lliac_Int_R)|(LN_Mediastinals)|(LN_Neck_IA_L)|(LN_Neck_IA_R)|(LN_Neck_IB_L)|(LN_Neck_IB_R)|(LN_Neck_II_L)|(LN_Neck_II_R)|(LN_Neck_IIA_L)|(LN_Neck_IIA_R)|(LN_Neck_IIB_L)|(LN_Neck_IIB_R)|(LN_Neck_III_L)|(LN_Neck_III_R)|(LN_Neck_IV_L)|(LN_Neck_IV_R)|(LN_Neck_V_L)|(LN_Neck_V_R)|(LN_Neck_VA_L)|(LN_Neck_VA_R)|(LN_Neck_VB_L)|(LN_Neck_VB_R)|(LN_Neck_VC_L)|(LN_Neck_VC_R)|(LN_Neck_VI_L)|(LN_Neck_VI_R)|(LN_Neck_VII_L)|(LN_Neck_VII_R)|(LN_Obturator_L)|(LN_Obturator_R)|(LN_Paraaortic)|(LN_Paramammary_L)|(LN_Paramammary_R)|(LN_Paramammarys)|(LN_Parasternal_L)|(LN_Parasternal_R)|(LN_Parasternals)|(LN_Pelvic_L)|(LN_Pelvic_R)|(LN_Pelvics)|(LN_Portahepatis)|(LN_Presacral_L)|(LN_Presacral_R)|(LN_Pulmonary_L)|(LN_Pulmonary_R)|(LN_Pulmonarys)|(LN_R)|(LN_Sclav_L)|(LN_Sclav_R)|(LN_Supmammary_L)|(LN_Supmammary_R)|(LN_Supmammarys)|(LN_Trachbrnchs)|(LN_Trachbrnchs_L)|(LN_Trachbrnchs_R)|(Lobe_Frontal)|(Lobe_Frontal_L)|(Lobe_Frontal_R)|(Lobe_Occipital)|(Lobe_Occipital_L)|(Lobe_Occipital_R)|(Lobe_Parietal)|(Lobe_Parietal_L)|(Lobe_Parietal_R)|(Lobe_Temporal)|(Lobe_Temporal_L)|(Lobe_Temporal_R)|(Lung_L)|(Lung_LLL)|(Lung_LUL)|(Lung_R)|(Lung_RLL)|(Lung_RML)|(Lung_RUL)|(Lungs)|(Malleus)|(Malleus_L)|(Malleus_R)|(Maxilla)|(Maxilla_L)|(Maxilla_R)|(Mediastinum)|(Musc)|(Musc_Constrict)|(Musc_Constrict_I)|(Musc_Constrict_M)|(Musc_Constrict_S)|(Musc_Digastric_L)|(Musc_Digastric_R)|(Musc_Masseter)|(Musc_Masseter_L)|(Musc_Masseter_R)|(Musc_Platysma_L)|(Musc_Platysma_R)|(Musc_Pterygoid_L)|(Musc_Pterygoid_R)|(Musc_Sclmast_L)|(Musc_Sclmast_R)|(Musc_Temporal_L)|(Musc_Temporal_R)|(Nasalconcha_LI)|(Nasalconcha_RI)|(Nasopharynx)|(Nose)|(Nrv_Peripheral)|(Nrv_Root)|(OpticChiasm)|(OpticNrv)|(OpticNrv_L)|(OpticNrv_R)|(Orbit_L)|(Orbit_R)|(Oropharynx)|(Ovaries)|(Ovary_L)|(Ovary_R)|(Palate_Soft)|(PancJejuno)|(Pancreas)|(Pancreas_Head)|(Pancreas_Tail)|(Parametrium)|(Parotid_L)|(Parotid_R)|(Parotids)|(PenileBulb)|(Penis)|(Pericardium)|(Perineum)|(Peritoneum)|(Pharynx)|(Pineal)|(Pituitary)|(Pons)|(Proc_Condyloid_L)|(Proc_Condyloid_R)|(Proc_Coronoid_L)|(Proc_Coronoid_R)|(Prostate)|(ProstateBed)|(Prosthesis)|(Pterygoid_Lat_L)|(Pterygoid_Lat_R)|(Pterygoid_Med_L)|(Pterygoid_Med_R)|(PubicSymphys)|(PubicSymphys_L)|(PubicSymphys_R)|(Radius_L)|(Radius_R)|(Rectal_Wall)|(Rectum)|(Retina_L)|(Retina_R)|(Retinas)|(Rib)|(Rib01_L)|(Rib01_R)|(Rib02_L)|(Rib02_R)|(Rib03_L)|(Rib03_R)|(Rib04_L)|(Rib04_R)|(Rib05_L)|(Rib05_R)|(Rib06_L)|(Rib06_R)|(Rib07_L)|(Rib07_R)|(Rib08_L)|(Rib08_R)|(Rib09_L)|(Rib09_R)|(Rib10_L)|(Rib10_R)|(Rib11_L)|(Rib11_R)|(Rib12_L)|(Rib12_R)|(SacralPlex)|(Sacrum)|(Scalp)|(Scapula_L)|(Scapula_R)|(Scar)|(Scar_Boost)|(Scrotum)|(SeminalVes)|(SeminalVes_Dist)|(SeminalVes_Prox)|(Sinus_Ethmoid)|(Sinus_Frontal)|(Sinus_Frontal_L)|(Sinus_Frontal_R)|(Sinus_Maxilry)|(Sinus_Maxilry_L)|(Sinus_Maxilry_R)|(Sinus_Sphenoid)|(Sinus_Sphenoid_L)|(Sinus_Sphenoid_R)|(Skin)|(Skin_Perineum)|(Skin_Peritoneum)|(Skull)|(Spc)|(Spc_Bowel )|(Spc_Bowel_Small)|(Spc_Retrophar_L)|(Spc_Retrophar_R)|(Spc_Retrophars)|(Spc_Retrosty)|(Spc_Retrosty_L)|(Spc_Retrosty_R)|(Spc_Supraclav_L)|(Spc_Supraclav_R)|(Sphincter_Anal)|(SpinalCanal)|(SpinalCord)|(SpinalCord_Cerv)|(SpinalCord_Lum)|(SpinalCord_Sac)|(SpinalCord_Thor)|(Spleen)|(Spleen_Hilum)|(Spongiosum)|(Stapes)|(Stapes_L)|(Stapes_R)|(Stomach)|(Strct )|(Strct_Suprapatel)|(Surf_Eye)|(SurgicalBed)|(Sys_Ventricular)|(Tendon )|(Tendon_Quad)|(Testis)|(Testis_L)|(Testis_R)|(ThecalSac)|(Thoracic_Duct)|(Tongue)|(Tongue_All)|(Tongue_Base)|(Tongue_Base_L)|(Tongue_Base_R)|(Tongue_Oral)|(Tongue_Oral_L)|(Tongue_Oral_R)|(Tonsil)|(Trachea)|(Trachea_NAdj)|(Ureter_L)|(Ureter_R)|(UreterDivert)|(Ureters)|(Urethra)|(Urethra_Prostatc)|(Uterus)|(V_Azygos)|(V_Brachioceph_L)|(V_Brachioceph_R)|(V_Iliac_Ext_L)|(V_Iliac_Ext_R)|(V_Iliac_Int_L)|(V_Iliac_Int_R)|(V_Iliac_L)|(V_Iliac_R)|(V_Jugular)|(V_Jugular_Ext_L)|(V_Jugular_Ext_R)|(V_Jugular_Int_L)|(V_Jugular_Int_R)|(V_Portal)|(V_Pulmonary)|(V_Subclavian_L)|(V_Subclavian_R)|(V_Subclavians)|(V_Venacava_I)|(V_Venacava_S)|(Vagina)|(Vagina_Surf)|(VaginalCuff)|(Valve)|(Valve_Aortic)|(Valve_Mitral)|(Valve_Pulmonic)|(Valve_Tricuspid)|(VB)|(VB_C)|(VB_C1)|(VB_C2)|(VB_C3)|(VB_C4)|(VB_C5)|(VB_C6)|(VB_C7)|(VB_L)|(VB_L1)|(VB_L2)|(VB_L3)|(VB_L4)|(VB_L5)|(VB_S)|(VB_S1)|(VB_S2)|(VB_S3)|(VB_S4)|(VB_S5)|(VB_T)|(VB_T01)|(VB_T02)|(VB_T03)|(VB_T04)|(VB_T05)|(VB_T06)|(VB_T07)|(VB_T08)|(VB_T09)|(VB_T10)|(VB_T11)|(VB_T12)|(VBs)|(Ventricle)|(Ventricle_L)|(Ventricle_R)|(VocalCord_L)|(VocalCord_R)|(VocalCords)|(Vomer)|(Vulva)|(Wall_Vagina)|(Thalami)|(Thalamus_L)|(Thalamus_R)|(Third_Ventricle)|(InternCapsule_L)|(InternCapsule_R)))?(_((High)|(Mid(\d{2})?)|(Low)))?(-\d{2})?(\^[\w\d_\+-]+)?)$'), 'PTV', 'nan', 'Target', 'PTV', 'nan', 'Body', 'Planning Target Volume'),
Structure(re.compile(r'^(PubicSymphys~?(\^[\w\d_\+-]+)?)$'), 'PubicSymphys', '16950', 'Anatomic', 'Bone', 'Pubic', 'Pelvis', 'Pubic Symphysis'),
Structure(re.compile(r'^(PubicSymphys~?_L(\^[\w\d_\+-]+)?)$'), 'PubicSymphys_L', '16597', 'Anatomic', 'Bone', 'Pubic', 'Pelvis', 'Pubic bone Left'),
Structure(re.compile(r'^(PubicSymphys~?_R(\^[\w\d_\+-]+)?)$'), 'PubicSymphys_R', '16596', 'Anatomic', 'Bone', 'Pubic', 'Pelvis', 'Pubic bone Right'),
Structure(re.compile(r'^(Radius~?_L(\^[\w\d_\+-]+)?)$'), 'Radius_L', '23465', 'Anatomic', 'Bone', 'Radius', 'Limb', 'Radius Left'),
Structure(re.compile(r'^(Radius~?_R(\^[\w\d_\+-]+)?)$'), 'Radius_R', '23464', 'Anatomic', 'Bone', 'Radius', 'Limb', 'Radius Right'),
Structure(re.compile(r'^(Rectal_Wall~?(\^[\w\d_\+-]+)?)$'), 'Rectal_Wall', '14626', 'Anatomic', 'Rectum', 'nan', 'Pelvis', 'Rectal Wall'),
Structure(re.compile(r'^(Rectum~?(\^[\w\d_\+-]+)?)$'), 'Rectum', '14544', 'Anatomic', 'Rectum', 'nan', 'Pelvis', 'Large bowel - Rectum'),
Structure(re.compile(r'^(Retina~?_L(\^[\w\d_\+-]+)?)$'), 'Retina_L', '58303', 'Anatomic', 'Eye', 'Retina', 'Head and Neck', 'Retina Left'),
Structure(re.compile(r'^(Retina~?_PRV?\d{0,2}_L(\^[\w\d_\+-]+)?)$'), 'Retina_PRVxx_L', 'nan', 'PRV', 'Eye', 'Retina', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Retina~?_PRV?\d{0,2}_R(\^[\w\d_\+-]+)?)$'), 'Retina_PRVxx_R', 'nan', 'PRV', 'Eye', 'Retina', 'Head and Neck', 'PRV constructed as xx millimeter expansion on Retina'),
Structure(re.compile(r'^(Retina~?_R(\^[\w\d_\+-]+)?)$'), 'Retina_R', '58302', 'Anatomic', 'Eye', 'Retina', 'Head and Neck', 'Retina Right'),
Structure(re.compile(r'^(Retinas~?(\^[\w\d_\+-]+)?)$'), 'Retinas', '58301', 'Anatomic', 'Eye', 'Retina', 'Head and Neck', 'Both Retinas'),
Structure(re.compile(r'^(Rib~?(\^[\w\d_\+-]+)?)$'), 'Rib', '7574', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Any Rib volume'),
Structure(re.compile(r'^(Rib01~?_L(\^[\w\d_\+-]+)?)$'), 'Rib01_L', '7987', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'First Rib Left'),
Structure(re.compile(r'^(Rib01~?_R(\^[\w\d_\+-]+)?)$'), 'Rib01_R', '7857', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'First Rib Right'),
Structure(re.compile(r'^(Rib02~?_L(\^[\w\d_\+-]+)?)$'), 'Rib02_L', '8012', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Second rib Left'),
Structure(re.compile(r'^(Rib02~?_R(\^[\w\d_\+-]+)?)$'), 'Rib02_R', '7882', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Second rib Right'),
Structure(re.compile(r'^(Rib03~?_L(\^[\w\d_\+-]+)?)$'), 'Rib03_L', '8039', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Third rib Left'),
Structure(re.compile(r'^(Rib03~?_R(\^[\w\d_\+-]+)?)$'), 'Rib03_R', '7909', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Third rib Right'),
Structure(re.compile(r'^(Rib04~?_L(\^[\w\d_\+-]+)?)$'), 'Rib04_L', '8148', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Fourth rib Left'),
Structure(re.compile(r'^(Rib04~?_R(\^[\w\d_\+-]+)?)$'), 'Rib04_R', '7957', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Fourth rib Right'),
Structure(re.compile(r'^(Rib05~?_L(\^[\w\d_\+-]+)?)$'), 'Rib05_L', '8093', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Fifth rib Left'),
Structure(re.compile(r'^(Rib05~?_R(\^[\w\d_\+-]+)?)$'), 'Rib05_R', '8066', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Fifth rib Right'),
Structure(re.compile(r'^(Rib06~?_L(\^[\w\d_\+-]+)?)$'), 'Rib06_L', '8202', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Sixth rib Left'),
Structure(re.compile(r'^(Rib06~?_R(\^[\w\d_\+-]+)?)$'), 'Rib06_R', '8175', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Sixth rib Right'),
Structure(re.compile(r'^(Rib07~?_L(\^[\w\d_\+-]+)?)$'), 'Rib07_L', '8256', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Seventh rib Left'),
Structure(re.compile(r'^(Rib07~?_R(\^[\w\d_\+-]+)?)$'), 'Rib07_R', '8229', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Seventh rib Right'),
Structure(re.compile(r'^(Rib08~?_L(\^[\w\d_\+-]+)?)$'), 'Rib08_L', '8310', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Eighth rib Left'),
Structure(re.compile(r'^(Rib08~?_R(\^[\w\d_\+-]+)?)$'), 'Rib08_R', '8283', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Eighth rib Right'),
Structure(re.compile(r'^(Rib09~?_L(\^[\w\d_\+-]+)?)$'), 'Rib09_L', '8391', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Ninth rib Left'),
Structure(re.compile(r'^(Rib09~?_R(\^[\w\d_\+-]+)?)$'), 'Rib09_R', '8364', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Ninth rib Right'),
Structure(re.compile(r'^(Rib10~?_L(\^[\w\d_\+-]+)?)$'), 'Rib10_L', '8472', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Tenth rib Left'),
Structure(re.compile(r'^(Rib10~?_R(\^[\w\d_\+-]+)?)$'), 'Rib10_R', '8445', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Tenth rib Right'),
Structure(re.compile(r'^(Rib11~?_L(\^[\w\d_\+-]+)?)$'), 'Rib11_L', '8532', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Eleventh rib Left'),
Structure(re.compile(r'^(Rib11~?_R(\^[\w\d_\+-]+)?)$'), 'Rib11_R', '8531', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Eleventh rib Right'),
Structure(re.compile(r'^(Rib12~?_L(\^[\w\d_\+-]+)?)$'), 'Rib12_L', '8534', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Twelfth rib Left'),
Structure(re.compile(r'^(Rib12~?_R(\^[\w\d_\+-]+)?)$'), 'Rib12_R', '8533', 'Anatomic', 'Bone', 'Rib', 'Thorax', 'Twelfth rib Right'),
Structure(re.compile(r'^(SacralPlex~?(\^[\w\d_\+-]+)?)$'), 'SacralPlex', '5909', 'Anatomic', 'Nerve', 'Sacrum', 'Pelvis', 'Sacral Plexus'),
Structure(re.compile(r'^(Sacrum~?(\^[\w\d_\+-]+)?)$'), 'Sacrum', '16202', 'Anatomic', 'Bone', 'Spine', 'Pelvis', 'Sacrum'),
Structure(re.compile(r'^(Scalp~?(\^[\w\d_\+-]+)?)$'), 'Scalp', '46494', 'Anatomic', 'Skin', 'nan', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Scapula~?_L(\^[\w\d_\+-]+)?)$'), 'Scapula_L', '13396', 'Anatomic', 'Bone', 'Scapula', 'Thorax', 'Scapula Left'),
Structure(re.compile(r'^(Scapula~?_R(\^[\w\d_\+-]+)?)$'), 'Scapula_R', '13395', 'Anatomic', 'Bone', 'Scapula', 'Thorax', 'Scapula Right'),
Structure(re.compile(r'^(Scar~?(\^[\w\d_\+-]+)?)$'), 'Scar', 'nan', 'Anatomic', 'Skin', 'nan', 'Body', 'Scar'),
Structure(re.compile(r'^(Scar_Boost~?(\^[\w\d_\+-]+)?)$'), 'Scar_Boost', 'nan', 'Anatomic', 'Skin', 'nan', 'Body', 'nan'),
Structure(re.compile(r'^(Scrotum~?(\^[\w\d_\+-]+)?)$'), 'Scrotum', '18252', 'Anatomic', 'Skin', 'nan', 'Pelvis', 'Scrotum (skin & cremasteric fascia)'),
Structure(re.compile(r'^(SeminalVes~?(\^[\w\d_\+-]+)?)$'), 'SeminalVes', '19387', 'Anatomic', 'Gland', 'nan', 'Pelvis', 'Seminal vesicle'),
Structure(re.compile(r'^(SeminalVes~?_Dist(\^[\w\d_\+-]+)?)$'), 'SeminalVes_Dist', 'nan', 'Anatomic', 'Gland', 'nan', 'Pelvis', 'Distal Seminal Vesicle'),
Structure(re.compile(r'^(SeminalVes~?_Prox(\^[\w\d_\+-]+)?)$'), 'SeminalVes_Prox', 'nan', 'Anatomic', 'Gland', 'nan', 'Pelvis', 'Proximal Seminal Vesicle'),
Structure(re.compile(r'^(Sinus_Ethmoid~?(\^[\w\d_\+-]+)?)$'), 'Sinus_Ethmoid', '84115', 'Anatomic', 'Sinus', 'Ethmoid', 'Head and Neck', 'Ethmoidal Sinus'),
Structure(re.compile(r'^(Sinus_Frontal~?(\^[\w\d_\+-]+)?)$'), 'Sinus_Frontal', '57417', 'Anatomic', 'Brain', 'Sinus', 'Head and Neck', 'Frontal Sinus'),
Structure(re.compile(r'^(Sinus_Frontal~?_L(\^[\w\d_\+-]+)?)$'), 'Sinus_Frontal_L', '57419', 'Anatomic', 'Brain', 'Sinus', 'Head and Neck', 'Frontal Sinus Left'),
Structure(re.compile(r'^(Sinus_Frontal~?_R(\^[\w\d_\+-]+)?)$'), 'Sinus_Frontal_R', '57418', 'Anatomic', 'Brain', 'Sinus', 'Head and Neck', 'Frontal Sinus Right'),
Structure(re.compile(r'^(Sinus_Maxilry~?(\^[\w\d_\+-]+)?)$'), 'Sinus_Maxilry', '57715', 'Anatomic', 'Sinus', 'Maxillary', 'Head and Neck', 'Maxillary Sinus'),
Structure(re.compile(r'^(Sinus_Maxilry~?_L(\^[\w\d_\+-]+)?)$'), 'Sinus_Maxilry_L', '57717', 'Anatomic', 'Sinus', 'Maxillary', 'Head and Neck', 'Maxillary Sinus'),
Structure(re.compile(r'^(Sinus_Maxilry~?_R(\^[\w\d_\+-]+)?)$'), 'Sinus_Maxilry_R', '57716', 'Anatomic', 'Sinus', 'Maxillary', 'Head and Neck', 'Maxillary Sinus'),
Structure(re.compile(r'^(Sinus_Sphenoid~?(\^[\w\d_\+-]+)?)$'), 'Sinus_Sphenoid', '54683', 'Anatomic', 'Bone', 'Sphenoid', 'Head and Neck', 'Sphenoidal Sinus'),
Structure(re.compile(r'^(Sinus_Sphenoid~?_L(\^[\w\d_\+-]+)?)$'), 'Sinus_Sphenoid_L', '54708', 'Anatomic', 'Bone', 'Sphenoid', 'Head and Neck', 'Sphenoidal Sinus Left'),
Structure(re.compile(r'^(Sinus_Sphenoid~?_R(\^[\w\d_\+-]+)?)$'), 'Sinus_Sphenoid_R', '54707', 'Anatomic', 'Bone', 'Sphenoid', 'Head and Neck', 'Sphenoidal Sinus Right'),
Structure(re.compile(r'^(Skin~?(\^[\w\d_\+-]+)?)$'), 'Skin', '7163', 'Anatomic', 'Skin', 'nan', 'Body', 'Skin'),
Structure(re.compile(r'^(Skin_Perineum~?(\^[\w\d_\+-]+)?)$'), 'Skin_Perineum', '20429', 'Anatomic', 'Skin', 'nan', 'Pelvis', 'nan'),
Structure(re.compile(r'^(Skin_Peritoneum~?(\^[\w\d_\+-]+)?)$'), 'Skin_Peritoneum', 'nan', 'Anatomic', 'Skin', 'nan', 'Abdomen', 'nan'),
Structure(re.compile(r'^(Skull~?(\^[\w\d_\+-]+)?)$'), 'Skull', '46565', 'Anatomic', 'Bone', 'Skull', 'Head and Neck', 'Skeletal system of head'),
Structure(re.compile(r'^(Spc~?(\^[\w\d_\+-]+)?)$'), 'Spc', 'nan', 'Anatomic', 'Space', 'nan', 'Body', 'Space'),
Structure(re.compile(r'^(Spc_Bowel~?(\^[\w\d_\+-]+)?)$'), 'Spc_Bowel', 'nan', 'Anatomic', 'Bowel', 'Space', 'Abdomen', 'Space occupied by bowel'),
Structure(re.compile(r'^(Spc_Bowel_Small~?(\^[\w\d_\+-]+)?)$'), 'Spc_Bowel_Small', 'nan', 'Anatomic', 'Space', 'nan', 'Abdomen', 'nan'),
Structure(re.compile(r'^(Spc_Retrophar~?_L(\^[\w\d_\+-]+)?)$'), 'Spc_Retrophar_L', 'nan', 'Anatomic', 'Space', 'Retropharyngeal', 'Head and Neck', 'Retropharyngeal space Left'),
Structure(re.compile(r'^(Spc_Retrophar~?_R(\^[\w\d_\+-]+)?)$'), 'Spc_Retrophar_R', 'nan', 'Anatomic', 'Space', 'Retropharyngeal', 'Head and Neck', 'Retropharyngeal space Right'),
Structure(re.compile(r'^(Spc_Retrophars~?(\^[\w\d_\+-]+)?)$'), 'Spc_Retrophars', '286702', 'Anatomic', 'Space', 'nan', 'Head and Neck', 'Retropharyngeal space'),
Structure(re.compile(r'^(Spc_Retrosty~?(\^[\w\d_\+-]+)?)$'), 'Spc_Retrosty', 'nan', 'Anatomic', 'Space', 'Retrostyloid', 'Head and Neck', 'Retrostyloid space '),
Structure(re.compile(r'^(Spc_Retrosty~?_L(\^[\w\d_\+-]+)?)$'), 'Spc_Retrosty_L', 'nan', 'Anatomic', 'Space', 'Retrostyloid', 'Head and Neck', 'Retrostyloid space -Left'),
Structure(re.compile(r'^(Spc_Retrosty~?_R(\^[\w\d_\+-]+)?)$'), 'Spc_Retrosty_R', 'nan', 'Anatomic', 'Space', 'Retrostyloid', 'Head and Neck', 'Retrostyloid space -Left'),
Structure(re.compile(r'^(Spc_Supraclav~?_L(\^[\w\d_\+-]+)?)$'), 'Spc_Supraclav_L', '45797', 'Anatomic', 'Space', 'Supraclavicular', 'Thorax', 'Supraclavicular space - Left'),
Structure(re.compile(r'^(Spc_Supraclav~?_R(\^[\w\d_\+-]+)?)$'), 'Spc_Supraclav_R', '45796', 'Anatomic', 'Space', 'Supraclavicular', 'Thorax', 'Supraclavicular space - Right'),
Structure(re.compile(r'^(Sphincter_Anal~?(\^[\w\d_\+-]+)?)$'), 'Sphincter_Anal', '15710', 'Anatomic', 'Bowel', 'Anus', 'Pelvis', 'Internal Anal Sphincter '),
Structure(re.compile(r'^(SpinalCanal~?(\^[\w\d_\+-]+)?)$'), 'SpinalCanal', '9680', 'Anatomic', 'Canal', 'Spinal Cord', 'Body', 'Vertebral canal'),
Structure(re.compile(r'^(SpinalCanal~?_PRV?\d{0,2}(\^[\w\d_\+-]+)?)$'), 'SpinalCanal_PRVxx', 'nan', 'PRV', 'PRV', 'Spinal Canal', 'Body', 'A PRV created with an x millimeter expansion on the spinal canal'),
Structure(re.compile(r'^(SpinalCord~?(\^[\w\d_\+-]+)?)$'), 'SpinalCord', '7647', 'Anatomic', 'Nerve', 'Spinal Cord', 'Body', 'Spinal Cord'),
Structure(re.compile(r'^(SpinalCord_Cerv~?(\^[\w\d_\+-]+)?)$'), 'SpinalCord_Cerv', '71166', 'Anatomic', 'Nerve', 'Spinal Cord', 'Head and Neck', 'Spinal Cord Cervical'),
Structure(re.compile(r'^(SpinalCord_Lum~?(\^[\w\d_\+-]+)?)$'), 'SpinalCord_Lum', '71168', 'Anatomic', 'Nerve', 'Spinal Cord', 'Abdomen', 'Spinal Cord Lumbar'),
Structure(re.compile(r'^(SpinalCord~?_PRV?\d{0,2}(\^[\w\d_\+-]+)?)$'), 'SpinalCord_PRVxx', 'nan', 'PRV', 'PRV', 'Spinal Cord', 'Body', 'A PRV created with an xx millimeter expansion on the spinal cord'),
Structure(re.compile(r'^(SpinalCord_Sac~?(\^[\w\d_\+-]+)?)$'), 'SpinalCord_Sac', '256623', 'Anatomic', 'Nerve', 'Spinal Cord', 'Pelvis', 'Spinal Cord Sacral'),
Structure(re.compile(r'^(SpinalCord_Thor~?(\^[\w\d_\+-]+)?)$'), 'SpinalCord_Thor', '71167', 'Anatomic', 'Nerve', 'Spinal Cord', 'Thorax', 'Spinal Cord Thoracic'),
Structure(re.compile(r'^(Spleen~?(\^[\w\d_\+-]+)?)$'), 'Spleen', '7196', 'Anatomic', 'Lymph Node', 'Spleen', 'Abdomen', 'Spleen'),
Structure(re.compile(r'^(Spleen_Hilum~?(\^[\w\d_\+-]+)?)$'), 'Spleen_Hilum', '15841', 'Anatomic', 'Lymph Node', 'Spleen', 'Abdomen', 'Splenic hilum'),
Structure(re.compile(r'^(Spongiosum~?(\^[\w\d_\+-]+)?)$'), 'Spongiosum', '19617', 'Anatomic', 'Reproductive', 'nan', 'Pelvis', 'Penis Corpus Spongiosum'),
Structure(re.compile(r'^(Stapes~?(\^[\w\d_\+-]+)?)$'), 'Stapes', '52751', 'Anatomic', 'Ear', 'Stapes', 'Head and Neck', 'Stapes'),
Structure(re.compile(r'^(Stapes~?_L(\^[\w\d_\+-]+)?)$'), 'Stapes_L', '74049', 'Anatomic', 'Ear', 'Stapes', 'Head and Neck', 'Stapes Left'),
Structure(re.compile(r'^(Stapes~?_R(\^[\w\d_\+-]+)?)$'), 'Stapes_R', '74048', 'Anatomic', 'Ear', 'Stapes', 'Head and Neck', 'Stapes Right'),
Structure(re.compile(r'^(Stomach~?(\^[\w\d_\+-]+)?)$'), 'Stomach', '7148', 'Anatomic', 'Stomach', 'nan', 'Abdomen', 'Stomach'),
Structure(re.compile(r'^(Stomach~?_PRV?\d{0,2}(\^[\w\d_\+-]+)?)$'), 'Stomach_PRVxx', 'nan', 'PRV', 'Stomach', 'nan', 'Abdomen', 'PRV created with xx mm expansion on the stomach'),
Structure(re.compile(r'^(Strct~?(\^[\w\d_\+-]+)?)$'), 'Strct ', 'nan', 'Anatomic', 'Body', 'nan', 'Body', 'Structure'),
Structure(re.compile(r'^(Strct_Suprapatel~?(\^[\w\d_\+-]+)?)$'), 'Strct_Suprapatel', 'nan', 'Anatomic', 'Joint', 'nan', 'Limb', 'Suprapatellar Structures'),
Structure(re.compile(r'^(Surf_Eye~?(\^[\w\d_\+-]+)?)$'), 'Surf_Eye', 'nan', 'Anatomic', 'Eye', 'nan', 'nan', 'nan'),
Structure(re.compile(r'^(SurgicalBed~?(\^[\w\d_\+-]+)?)$'), 'SurgicalBed', 'nan', 'Anatomic', 'Surgery', 'nan', 'Body', 'nan'),
Structure(re.compile(r'^(Sys_Ventricular~?(\^[\w\d_\+-]+)?)$'), 'Sys_Ventricular', '242787', 'Anatomic', 'Brain', 'nan', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tendon~?(\^[\w\d_\+-]+)?)$'), 'Tendon ', '9721', 'Anatomic', 'Tendon', 'nan', 'Limb', 'nan'),
Structure(re.compile(r'^(Tendon_Quad~?(\^[\w\d_\+-]+)?)$'), 'Tendon_Quad', '46900', 'Anatomic', 'Tendon', 'nan', 'Limb', 'nan'),
Structure(re.compile(r'^(Testis~?(\^[\w\d_\+-]+)?)$'), 'Testis', '7210', 'Anatomic', 'Reproductive', 'Testis', 'Pelvis', 'Testis'),
Structure(re.compile(r'^(Testis~?_L(\^[\w\d_\+-]+)?)$'), 'Testis_L', '7212', 'Anatomic', 'Reproductive', 'Testis', 'Pelvis', 'Testis Left'),
Structure(re.compile(r'^(Testis~?_R(\^[\w\d_\+-]+)?)$'), 'Testis_R', '7211', 'Anatomic', 'Reproductive', 'Testis', 'Pelvis', 'Testis Right'),
Structure(re.compile(r'^(ThecalSac~?(\^[\w\d_\+-]+)?)$'), 'ThecalSac', '83720', 'Anatomic', 'Membrane', 'Thecal Sac', 'Body', 'nan'),
Structure(re.compile(r'^(Thoracic_Duct~?(\^[\w\d_\+-]+)?)$'), 'Thoracic_Duct', '5031', 'Anatomic', 'Duct', 'Thoracic', 'Thorax', 'Thoracic Duct'),
Structure(re.compile(r'^(Tongue~?(\^[\w\d_\+-]+)?)$'), 'Tongue', '54640', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'Tongue'),
Structure(re.compile(r'^(Tongue_All~?(\^[\w\d_\+-]+)?)$'), 'Tongue_All', 'nan', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tongue_Base~?(\^[\w\d_\+-]+)?)$'), 'Tongue_Base', '54645', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tongue_Base~?_L(\^[\w\d_\+-]+)?)$'), 'Tongue_Base_L', 'nan', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tongue_Base~?_R(\^[\w\d_\+-]+)?)$'), 'Tongue_Base_R', 'nan', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tongue_Oral~?(\^[\w\d_\+-]+)?)$'), 'Tongue_Oral', '54644', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tongue_Oral~?_L(\^[\w\d_\+-]+)?)$'), 'Tongue_Oral_L', '281502', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tongue_Oral~?_R(\^[\w\d_\+-]+)?)$'), 'Tongue_Oral_R', '281500', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Tonsil~?(\^[\w\d_\+-]+)?)$'), 'Tonsil', '9609', 'Anatomic', 'Mouth', 'Tongue', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(Trachea~?(\^[\w\d_\+-]+)?)$'), 'Trachea', '7394', 'Anatomic', 'Lung', 'Trachea', 'Thorax', 'Trachea'),
Structure(re.compile(r'^(Trachea~?_NAdj(\^[\w\d_\+-]+)?)$'), 'Trachea_NAdj', 'nan', 'Anatomic', 'Lung', 'Trachea', 'Thorax', 'Trachea non adjacent wall'),
Structure(re.compile(r'^(TumorBed~?(\^[\w\d_\+-]+)?)$'), 'TumorBed', 'nan', 'Non_Anatomic', 'Surgery', 'nan', 'Body', 'Tumor Bed'),
Structure(re.compile(r'^(Ureter~?_L(\^[\w\d_\+-]+)?)$'), 'Ureter_L', '17888', 'Anatomic', 'Urinary', 'Ureter', 'Pelvis', 'Ureter Left'),
Structure(re.compile(r'^(Ureter~?_R(\^[\w\d_\+-]+)?)$'), 'Ureter_R', '17887', 'Anatomic', 'Urinary', 'Ureter', 'Pelvis', 'Ureter Right'),
Structure(re.compile(r'^(UreterDivert~?(\^[\w\d_\+-]+)?)$'), 'UreterDivert', 'nan', 'Anatomic', 'Urinary', 'Ureter', 'Pelvis', 'Urinary Divergence'),
Structure(re.compile(r'^(Ureters~?(\^[\w\d_\+-]+)?)$'), 'Ureters', '264814', 'Anatomic', 'Urinary', 'Ureter', 'Pelvis', 'Both Ureters'),
Structure(re.compile(r'^(Urethra~?(\^[\w\d_\+-]+)?)$'), 'Urethra', '19667', 'Anatomic', 'Urinary', 'Urethra', 'Pelvis', 'Urethra'),
Structure(re.compile(r'^(Urethra_Prostatc~?(\^[\w\d_\+-]+)?)$'), 'Urethra_Prostatc', 'nan', 'Anatomic', 'Urinary', 'Urethra', 'Pelvis', 'Prostatic Urethra'),
Structure(re.compile(r'^(Uterus~?(\^[\w\d_\+-]+)?)$'), 'Uterus', '17558', 'Anatomic', 'Reproductive', 'Uterus', 'Pelvis', 'Uterus'),
Structure(re.compile(r'^(V_Azygos~?(\^[\w\d_\+-]+)?)$'), 'V_Azygos', '4838', 'Anatomic', 'Vein', 'Azygos', 'Thorax', 'Azygos Vein'),
Structure(re.compile(r'^(V_Brachioceph~?_L(\^[\w\d_\+-]+)?)$'), 'V_Brachioceph_L', '4761', 'Anatomic', 'Vein', 'Brachiocephalic', 'Thorax', 'Brachiocephalic vein Left'),
Structure(re.compile(r'^(V_Brachioceph~?_R(\^[\w\d_\+-]+)?)$'), 'V_Brachioceph_R', '4751', 'Anatomic', 'Vein', 'Brachiocephalic', 'Thorax', 'Brachiocephalic vein Right'),
Structure(re.compile(r'^(V_Iliac_Ext~?_L(\^[\w\d_\+-]+)?)$'), 'V_Iliac_Ext_L', '18886', 'Anatomic', 'Vein', 'Iliac', 'Pelvis', 'External iliac vein Left'),
Structure(re.compile(r'^(V_Iliac_Ext~?_R(\^[\w\d_\+-]+)?)$'), 'V_Iliac_Ext_R', '18885', 'Anatomic', 'Vein', 'Iliac', 'Pelvis', 'External iliac vein Right'),
Structure(re.compile(r'^(V_Iliac_Int~?_L(\^[\w\d_\+-]+)?)$'), 'V_Iliac_Int_L', '18810', 'Anatomic', 'Vein', 'Iliac', 'Pelvis', 'Internal iliac vein Left'),
Structure(re.compile(r'^(V_Iliac_Int~?_R(\^[\w\d_\+-]+)?)$'), 'V_Iliac_Int_R', '18809', 'Anatomic', 'Vein', 'Iliac', 'Pelvis', 'Internal iliac vein Right'),
Structure(re.compile(r'^(V_Iliac~?_L(\^[\w\d_\+-]+)?)$'), 'V_Iliac_L', '21387', 'Anatomic', 'Vein', 'Iliac', 'Pelvis', 'Common iliac vein Right'),
Structure(re.compile(r'^(V_Iliac~?_R(\^[\w\d_\+-]+)?)$'), 'V_Iliac_R', '21388', 'Anatomic', 'Vein', 'Iliac', 'Pelvis', 'Common iliac vein Left'),
Structure(re.compile(r'^(V_Jugular~?(\^[\w\d_\+-]+)?)$'), 'V_Jugular', 'nan', 'Anatomic', 'Vein', 'Jugular', 'Head and Neck', 'Any Jugular Vein'),
Structure(re.compile(r'^(V_Jugular_Ext~?_L(\^[\w\d_\+-]+)?)$'), 'V_Jugular_Ext_L', '13112', 'Anatomic', 'Vein', 'Jugular', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(V_Jugular_Ext~?_R(\^[\w\d_\+-]+)?)$'), 'V_Jugular_Ext_R', '13111', 'Anatomic', 'Vein', 'Jugular', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(V_Jugular_Int~?_L(\^[\w\d_\+-]+)?)$'), 'V_Jugular_Int_L', '4754', 'Anatomic', 'Vein', 'Jugular', 'Head and Neck', 'Internal jugular vein Right'),
Structure(re.compile(r'^(V_Jugular_Int~?_R(\^[\w\d_\+-]+)?)$'), 'V_Jugular_Int_R', '4762', 'Anatomic', 'Vein', 'Jugular', 'Head and Neck', 'Internal jugular vein Left'),
Structure(re.compile(r'^(V_Portal~?(\^[\w\d_\+-]+)?)$'), 'V_Portal', '66645', 'Anatomic', 'Vein', 'Portal', 'Abdomen', 'Portal Vein'),
Structure(re.compile(r'^(V_Pulmonary~?(\^[\w\d_\+-]+)?)$'), 'V_Pulmonary', '66643', 'Anatomic', 'Vein', 'Pulmonary', 'Thorax', 'Pulmonary vein'),
Structure(re.compile(r'^(V_Subclavian~?_L(\^[\w\d_\+-]+)?)$'), 'V_Subclavian_L', '4763', 'Anatomic', 'Vein', 'Subclavian', 'Thorax', 'Subclavian Vein Left'),
Structure(re.compile(r'^(V_Subclavian~?_R(\^[\w\d_\+-]+)?)$'), 'V_Subclavian_R', '4755', 'Anatomic', 'Vein', 'Subclavian', 'Thorax', 'Subclavian Vein Right'),
Structure(re.compile(r'^(V_Subclavians~?(\^[\w\d_\+-]+)?)$'), 'V_Subclavians', '4725', 'Anatomic', 'Vein', 'Subclavian', 'Thorax', 'Subclavian Vein'),
Structure(re.compile(r'^(V_Venacava~?_I(\^[\w\d_\+-]+)?)$'), 'V_Venacava_I', '10951', 'Anatomic', 'Vein', 'VenaCava', 'Thorax', 'Inferior vena cava'),
Structure(re.compile(r'^(V_Venacava~?_S(\^[\w\d_\+-]+)?)$'), 'V_Venacava_S', '4720', 'Anatomic', 'Vein', 'VenaCava', 'Thorax', 'Superior vena cava'),
Structure(re.compile(r'^(Vagina~?(\^[\w\d_\+-]+)?)$'), 'Vagina', '19949', 'Anatomic', 'Reproductive', 'Vagina', 'Pelvis', 'Vagina'),
Structure(re.compile(r'^(Vagina_Surf~?(\^[\w\d_\+-]+)?)$'), 'Vagina_Surf', 'nan', 'Anatomic', 'Reproductive', 'Vagina', 'Pelvis', 'nan'),
Structure(re.compile(r'^(VaginalCuff~?(\^[\w\d_\+-]+)?)$'), 'VaginalCuff', 'nan', 'Anatomic', 'Reproductive', 'Vagina', 'Pelvis', 'Vaginal Cuff'),
Structure(re.compile(r'^(Valve~?(\^[\w\d_\+-]+)?)$'), 'Valve', 'nan', 'Anatomic', 'Valve', 'nan', 'Body', 'Valve'),
Structure(re.compile(r'^(Valve_Aortic~?(\^[\w\d_\+-]+)?)$'), 'Valve_Aortic', '7236', 'Anatomic', 'Valve', 'Aorta', 'Thorax', 'Aortic Valve'),
Structure(re.compile(r'^(Valve_Mitral~?(\^[\w\d_\+-]+)?)$'), 'Valve_Mitral', '7235', 'Anatomic', 'Valve', 'Heart', 'Thorax', 'Mitral Valve'),
Structure(re.compile(r'^(Valve_Pulmonic~?(\^[\w\d_\+-]+)?)$'), 'Valve_Pulmonic', '7246', 'Anatomic', 'Valve', 'nan', 'Thorax', 'Pulmonic Valve'),
Structure(re.compile(r'^(Valve_Tricuspid~?(\^[\w\d_\+-]+)?)$'), 'Valve_Tricuspid', '7234', 'Anatomic', 'Valve', 'Heart', 'Thorax', 'Tricuspid Valve'),
Structure(re.compile(r'^(VB~?(\^[\w\d_\+-]+)?)$'), 'VB', 'nan', 'Anatomic', 'Bone', 'Vertebral Body', 'Body', 'Vertebral Body'),
Structure(re.compile(r'^(VB_C~?(\^[\w\d_\+-]+)?)$'), 'VB_C', '72063', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Cervical vertebrae'),
Structure(re.compile(r'^(VB_C1~?(\^[\w\d_\+-]+)?)$'), 'VB_C1', '12519', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Atlas - C1'),
Structure(re.compile(r'^(VB_C2~?(\^[\w\d_\+-]+)?)$'), 'VB_C2', '12520', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Axis - C2'),
Structure(re.compile(r'^(VB_C3~?(\^[\w\d_\+-]+)?)$'), 'VB_C3', '12521', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Cervical vertebra - C3'),
Structure(re.compile(r'^(VB_C4~?(\^[\w\d_\+-]+)?)$'), 'VB_C4', '12522', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Cervical vertebra - C4'),
Structure(re.compile(r'^(VB_C5~?(\^[\w\d_\+-]+)?)$'), 'VB_C5', '12523', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Cervical vertebra - C5'),
Structure(re.compile(r'^(VB_C6~?(\^[\w\d_\+-]+)?)$'), 'VB_C6', '12524', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Cervical vertebra - C6'),
Structure(re.compile(r'^(VB_C7~?(\^[\w\d_\+-]+)?)$'), 'VB_C7', '12525', 'Anatomic', 'Bone', 'Vertebral Body', 'Head and Neck', 'Cervical vertebra - C7'),
Structure(re.compile(r'^(VB~?_L(\^[\w\d_\+-]+)?)$'), 'VB_L', '72065', 'Anatomic', 'Bone', 'Spine', 'Abdomen', 'Lumbar Vertebrae'),
Structure(re.compile(r'^(VB_L1~?(\^[\w\d_\+-]+)?)$'), 'VB_L1', '13072', 'Anatomic', 'Bone', 'Spine', 'Abdomen', 'Lumbar Vertebra L1'),
Structure(re.compile(r'^(VB_L2~?(\^[\w\d_\+-]+)?)$'), 'VB_L2', '13073', 'Anatomic', 'Bone', 'Spine', 'Abdomen', 'Lumbar Vertebra L2'),
Structure(re.compile(r'^(VB_L3~?(\^[\w\d_\+-]+)?)$'), 'VB_L3', '13074', 'Anatomic', 'Bone', 'Spine', 'Abdomen', 'Lumbar Vertebra L3'),
Structure(re.compile(r'^(VB_L4~?(\^[\w\d_\+-]+)?)$'), 'VB_L4', '13075', 'Anatomic', 'Bone', 'Spine', 'Abdomen', 'Lumbar Vertebra L4'),
Structure(re.compile(r'^(VB_L5~?(\^[\w\d_\+-]+)?)$'), 'VB_L5', '13076', 'Anatomic', 'Bone', 'Spine', 'Abdomen', 'Lumbar Vertebra L5'),
Structure(re.compile(r'^(VB~?_S(\^[\w\d_\+-]+)?)$'), 'VB_S', '12526', 'Anatomic', 'Bone', 'Spine', 'Pelvis', 'Sacral Vertebra'),
Structure(re.compile(r'^(VB_S1~?(\^[\w\d_\+-]+)?)$'), 'VB_S1', '13077', 'Anatomic', 'Bone', 'Spine', 'Pelvis', 'Sacral Vertebra S1'),
Structure(re.compile(r'^(VB_S2~?(\^[\w\d_\+-]+)?)$'), 'VB_S2', '13078', 'Anatomic', 'Bone', 'Spine', 'Pelvis', 'Sacral Vertebra S2'),
Structure(re.compile(r'^(VB_S3~?(\^[\w\d_\+-]+)?)$'), 'VB_S3', '13079', 'Anatomic', 'Bone', 'Spine', 'Pelvis', 'Sacral Vertebra S3'),
Structure(re.compile(r'^(VB_S4~?(\^[\w\d_\+-]+)?)$'), 'VB_S4', '13080', 'Anatomic', 'Bone', 'Spine', 'Pelvis', 'Sacral Vertebra S4'),
Structure(re.compile(r'^(VB_S5~?(\^[\w\d_\+-]+)?)$'), 'VB_S5', '13081', 'Anatomic', 'Bone', 'Spine', 'Pelvis', 'Sacral Vertebra S5'),
Structure(re.compile(r'^(VB_T~?(\^[\w\d_\+-]+)?)$'), 'VB_T', '9139', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra'),
Structure(re.compile(r'^(VB_T01~?(\^[\w\d_\+-]+)?)$'), 'VB_T01', '9165', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T1'),
Structure(re.compile(r'^(VB_T02~?(\^[\w\d_\+-]+)?)$'), 'VB_T02', '9187', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T2'),
Structure(re.compile(r'^(VB_T03~?(\^[\w\d_\+-]+)?)$'), 'VB_T03', '9209', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T3'),
Structure(re.compile(r'^(VB_T04~?(\^[\w\d_\+-]+)?)$'), 'VB_T04', '9248', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T4'),
Structure(re.compile(r'^(VB_T05~?(\^[\w\d_\+-]+)?)$'), 'VB_T05', '9922', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T5'),
Structure(re.compile(r'^(VB_T06~?(\^[\w\d_\+-]+)?)$'), 'VB_T06', '9945', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T6'),
Structure(re.compile(r'^(VB_T07~?(\^[\w\d_\+-]+)?)$'), 'VB_T07', '9968', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T7'),
Structure(re.compile(r'^(VB_T08~?(\^[\w\d_\+-]+)?)$'), 'VB_T08', '9991', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T8'),
Structure(re.compile(r'^(VB_T09~?(\^[\w\d_\+-]+)?)$'), 'VB_T09', '10014', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T9'),
Structure(re.compile(r'^(VB_T10~?(\^[\w\d_\+-]+)?)$'), 'VB_T10', '10037', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T10'),
Structure(re.compile(r'^(VB_T11~?(\^[\w\d_\+-]+)?)$'), 'VB_T11', '10059', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T11'),
Structure(re.compile(r'^(VB_T12~?(\^[\w\d_\+-]+)?)$'), 'VB_T12', '10081', 'Anatomic', 'Bone', 'Spine', 'Thorax', 'Thoracic Vertebra T12'),
Structure(re.compile(r'^(VBs~?(\^[\w\d_\+-]+)?)$'), 'VBs', '11945', 'Anatomic', 'Bone', 'Vertebral Body', 'Body', 'Vertebral Bodies'),
Structure(re.compile(r'^(Ventricle~?(\^[\w\d_\+-]+)?)$'), 'Ventricle', '7100', 'Anatomic', 'Heart', 'Ventricle', 'Thorax', 'Ventricle (cardiac)'),
Structure(re.compile(r'^(Ventricle~?_L(\^[\w\d_\+-]+)?)$'), 'Ventricle_L', '7101', 'Anatomic', 'Heart', 'Ventricle', 'Thorax', 'Ventricle (cardiac) Left'),
Structure(re.compile(r'^(Ventricle~?_R(\^[\w\d_\+-]+)?)$'), 'Ventricle_R', '7098', 'Anatomic', 'Heart', 'Ventricle', 'Thorax', 'Ventricle (cardiac) Right'),
Structure(re.compile(r'^(VocalCord~?_L(\^[\w\d_\+-]+)?)$'), 'VocalCord_L', '55459', 'Anatomic', 'Larynx', 'nan', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(VocalCord~?_R(\^[\w\d_\+-]+)?)$'), 'VocalCord_R', '55458', 'Anatomic', 'Larynx', 'nan', 'Head and Neck', 'nan'),
Structure(re.compile(r'^(VocalCords~?(\^[\w\d_\+-]+)?)$'), 'VocalCords', '323919', 'Anatomic', 'Larynx', 'nan', 'Head and Neck', 'Vocal Cords'),
Structure(re.compile(r'^(Vomer~?(\^[\w\d_\+-]+)?)$'), 'Vomer', '9710', 'Anatomic', 'Bone', 'Vomer', 'Head and Neck', 'Vomer'),
Structure(re.compile(r'^(Vulva~?(\^[\w\d_\+-]+)?)$'), 'Vulva', '20462', 'Anatomic', 'Reproductive', 'Vulva', 'Pelvis', 'Vulva'),
Structure(re.compile(r'^(Wall_Vagina~?(\^[\w\d_\+-]+)?)$'), 'Wall_Vagina', '19971', 'Anatomic', 'Reproductive', 'Vagina', 'Pelvis', 'Wall of vagina'),
]
| 194.493741
| 9,419
| 0.631703
| 18,758
| 139,841
| 4.439759
| 0.068291
| 0.093647
| 0.15324
| 0.161754
| 0.775555
| 0.663585
| 0.527575
| 0.447689
| 0.391494
| 0.353358
| 0
| 0.026942
| 0.078461
| 139,841
| 718
| 9,420
| 194.764624
| 0.619303
| 0.000265
| 0
| 0
| 0
| 0.007013
| 0.695152
| 0.365169
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.001403
| 0.002805
| 0
| 0.002805
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
591f0a5345a4e6f604e7e3288869d9abb3cc1c1c
| 121
|
py
|
Python
|
tetris/view/assets/__init__.py
|
TomerHanochi/Tetris
|
5be6c02b27164d0b3897006e5d1476b3e8546533
|
[
"MIT"
] | null | null | null |
tetris/view/assets/__init__.py
|
TomerHanochi/Tetris
|
5be6c02b27164d0b3897006e5d1476b3e8546533
|
[
"MIT"
] | null | null | null |
tetris/view/assets/__init__.py
|
TomerHanochi/Tetris
|
5be6c02b27164d0b3897006e5d1476b3e8546533
|
[
"MIT"
] | null | null | null |
import pygame as pg
pg.mixer.init()
pg.font.init()
from tetris.view.assets.assets import Colors, Images, Fonts, Sounds
| 17.285714
| 67
| 0.760331
| 20
| 121
| 4.6
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.123967
| 121
| 6
| 68
| 20.166667
| 0.867925
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
592454fffc7c03614e2f08e285aca6b36230f4da
| 2,043
|
py
|
Python
|
configs/hibernateconfig.py
|
tshrove/technicaldebtprediction
|
11c5d84b4976cc7e93cf79294403c7615cce81bd
|
[
"MIT"
] | null | null | null |
configs/hibernateconfig.py
|
tshrove/technicaldebtprediction
|
11c5d84b4976cc7e93cf79294403c7615cce81bd
|
[
"MIT"
] | null | null | null |
configs/hibernateconfig.py
|
tshrove/technicaldebtprediction
|
11c5d84b4976cc7e93cf79294403c7615cce81bd
|
[
"MIT"
] | null | null | null |
from .iconfig import IConfig
class HibernateConfig(IConfig):
__priority_val_dict = {
"Blocker": 5,
"Critical": 4,
"Major": 3,
"Minor": 2,
"Trivial": 1
}
__issue_tracker_type = 'jira'
__jira_url = 'https://hibernate.atlassian.net'
__jira_username = ''
__jira_password = ''
__projects = [
{'key': 'HHH', 'start_date': '2003-11-04T00:00:00.000-0500', 'end_date': '2019-02-11T00:00:00.000-0500',
'success': '-1', 'prediction_type': 'train', 'github': 'hibernate/hibernate-orm'},
{'key': 'HSEARCH', 'start_date': '2005-11-21T00:00:00.000-0500', 'end_date': '2019-02-11T00:00:00.000-0500',
'success': '-1', 'prediction_type': 'train', 'github': 'hibernate/hibernate-search'},
{'key': 'OGM', 'start_date': '2011-03-16T00:00:00.000-0500', 'end_date': '2019-02-11T00:00:00.000-0500',
'success': '-1', 'prediction_type': 'train', 'github': 'hibernate/hibernate-ogm'},
{'key': 'HV', 'start_date': '2007-03-06T00:00:00.000-0500', 'end_date': '2019-02-11T00:00:00.000-0500',
'success': '-1', 'prediction_type': 'train', 'github': 'hibernate/hibernate-validator'},
{'key': 'HBX', 'start_date': '2003-06-06T00:00:00.000-0500', 'end_date': '2019-02-11T00:00:00.000-0500',
'success': '-1', 'prediction_type': 'train', 'github': 'hibernate/hibernate-tools'}
]
# __issue_types = ['Bug']
def __init__(self):
super().__init__()
def get_priority_values(self):
return self.__priority_val_dict
def get_jira_url(self):
return self.__jira_url
def get_jira_username(self):
return self.__jira_username
def get_jira_password(self):
return self.__jira_password
def get_resolved_statuses(self):
return self.__resolved_statuses
def get_projects(self):
return self.__projects
def get_issuetypes(self):
return self.__issue_types
def get_issuetrackertype(self):
return self.__issue_tracker_type
| 34.627119
| 116
| 0.621145
| 258
| 2,043
| 4.596899
| 0.29845
| 0.033727
| 0.059022
| 0.092749
| 0.392074
| 0.392074
| 0.392074
| 0.392074
| 0.392074
| 0.392074
| 0
| 0.135385
| 0.204601
| 2,043
| 58
| 117
| 35.224138
| 0.594462
| 0.011258
| 0
| 0
| 0
| 0
| 0.382061
| 0.201189
| 0
| 0
| 0
| 0
| 0
| 1
| 0.209302
| false
| 0.069767
| 0.023256
| 0.186047
| 0.581395
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 4
|
5934925f0ceaff80cd3d86944909e84d5e5cd333
| 50
|
py
|
Python
|
drivers/laserDiodeDrv/__init__.py
|
mv20100/phd_code
|
2262c71c7c35aed5759c4b0e058fe74c44e5266b
|
[
"MIT"
] | null | null | null |
drivers/laserDiodeDrv/__init__.py
|
mv20100/phd_code
|
2262c71c7c35aed5759c4b0e058fe74c44e5266b
|
[
"MIT"
] | null | null | null |
drivers/laserDiodeDrv/__init__.py
|
mv20100/phd_code
|
2262c71c7c35aed5759c4b0e058fe74c44e5266b
|
[
"MIT"
] | null | null | null |
from .np560B import NP560B
__all__ = ['NP560B']
| 16.666667
| 27
| 0.7
| 6
| 50
| 5.166667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.219512
| 0.18
| 50
| 3
| 28
| 16.666667
| 0.536585
| 0
| 0
| 0
| 0
| 0
| 0.122449
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
3ca25a5fe868bb52a7f000d615da2e6761aff14c
| 161
|
py
|
Python
|
ldap2html/ldap2html/config.py
|
nonylene/ldap2html
|
99a0d012e50d1aaa96ebd0ae49240befe6bff858
|
[
"MIT"
] | 4
|
2019-11-02T10:53:56.000Z
|
2021-12-10T14:40:20.000Z
|
ldap2html/ldap2html/config.py
|
nonylene/ldap2html
|
99a0d012e50d1aaa96ebd0ae49240befe6bff858
|
[
"MIT"
] | 1
|
2021-09-03T15:36:53.000Z
|
2021-09-03T15:36:53.000Z
|
ldap2html/ldap2html/config.py
|
nonylene/ldap2html
|
99a0d012e50d1aaa96ebd0ae49240befe6bff858
|
[
"MIT"
] | null | null | null |
from dataclasses import dataclass
@dataclass
class Config:
ldap_uri: str
search_base: str
bind_dn: str
bind_dn_passwd: str
directory: str
| 13.416667
| 33
| 0.708075
| 22
| 161
| 4.954545
| 0.681818
| 0.12844
| 0.165138
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.248447
| 161
| 11
| 34
| 14.636364
| 0.900826
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.125
| 0.125
| 0
| 0.875
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
3caf628abb33ee261ba11a62eb54691417e7c8c5
| 455
|
py
|
Python
|
api/system/mocks/errors.py
|
djzelenak/espa-api
|
ebf347a4dd58008e3e9c368cf6086925e3bf12b7
|
[
"Unlicense"
] | null | null | null |
api/system/mocks/errors.py
|
djzelenak/espa-api
|
ebf347a4dd58008e3e9c368cf6086925e3bf12b7
|
[
"Unlicense"
] | null | null | null |
api/system/mocks/errors.py
|
djzelenak/espa-api
|
ebf347a4dd58008e3e9c368cf6086925e3bf12b7
|
[
"Unlicense"
] | null | null | null |
class MockError(object):
def __init__(self, status, reason):
self.status = status
self.reason = reason
self.extra = {'retry_after': 9, 'retry_limit': 10}
def resolve_submitted(error_message, name):
return MockError('submitted', 'a reason')
def resolve_unavailable(error_message, name):
return MockError('unavailable', 'a reason')
def resolve_retry(error_message, name):
return MockError('retry', 'a reason')
| 23.947368
| 58
| 0.687912
| 55
| 455
| 5.472727
| 0.4
| 0.099668
| 0.159468
| 0.219269
| 0.30897
| 0
| 0
| 0
| 0
| 0
| 0
| 0.00813
| 0.189011
| 455
| 18
| 59
| 25.277778
| 0.807588
| 0
| 0
| 0
| 0
| 0
| 0.157428
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.363636
| false
| 0
| 0
| 0.272727
| 0.727273
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
3cd4fb8af3a2eb3b19279379c4474a84bbf786f3
| 51,246
|
py
|
Python
|
Typing_Test/tests/01.py
|
zetianluo/Data-Science-Portfolio
|
5d568dca73e76d5513c685ffcf42525e8c4f8232
|
[
"MIT"
] | null | null | null |
Typing_Test/tests/01.py
|
zetianluo/Data-Science-Portfolio
|
5d568dca73e76d5513c685ffcf42525e8c4f8232
|
[
"MIT"
] | null | null | null |
Typing_Test/tests/01.py
|
zetianluo/Data-Science-Portfolio
|
5d568dca73e76d5513c685ffcf42525e8c4f8232
|
[
"MIT"
] | null | null | null |
test = {
'name': 'Problem 1',
'points': 1,
'suites': [
{
'cases': [
{
'code': r"""
>>> ps = ['short', 'really long', 'tiny']
>>> s = lambda p: len(p) <= 5
>>> choose(ps, s, 0)
'short'
>>> choose(ps, s, 1)
'tiny'
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
}
],
'scored': True,
'setup': r"""
>>> from typing import choose
""",
'teardown': '',
'type': 'doctest'
},
{
'cases': [
{
'code': r"""
>>> ps = ['d', 'Njtv', 'Kxg', 'ym6bMNxUy', 'Lz']
>>> s = lambda p: p == 'Kxg' or p == 'Lz' or p == 'd'
>>> choose(ps, s, 0)
'd'
>>> choose(ps, s, 1)
'Kxg'
>>> choose(ps, s, 2)
'Lz'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['pVasJy', 'ZD', 'toNG']
>>> s = lambda p: p == 'ZD' or p == 'pVasJy' or p == 'toNG'
>>> choose(ps, s, 0)
'pVasJy'
>>> choose(ps, s, 1)
'ZD'
>>> choose(ps, s, 2)
'toNG'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['JlY3CIaa', '1fMO0', 'pe', 'Q6F4bbNP5J']
>>> s = lambda p: p == '1fMO0' or p == 'pe'
>>> choose(ps, s, 0)
'1fMO0'
>>> choose(ps, s, 1)
'pe'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['o', '1m5Q']
>>> s = lambda p: p == '1m5Q'
>>> choose(ps, s, 0)
'1m5Q'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['eV0dmK0', 'opuJ6xpn1', 'WXfPJa', 'EaXYKI']
>>> s = lambda p: p == 'WXfPJa' or p == 'opuJ6xpn1'
>>> choose(ps, s, 0)
'opuJ6xpn1'
>>> choose(ps, s, 1)
'WXfPJa'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['jakYR6', '7c5IJE7d', 'UJu', 'YB', '6bKkwROlcZ', 'G', 'aMtUQZ4']
>>> s = lambda p: p == 'G' or p == 'UJu'
>>> choose(ps, s, 0)
'UJu'
>>> choose(ps, s, 1)
'G'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['RnW', 'itFiAc40d', 'e']
>>> s = lambda p: p == 'RnW' or p == 'e' or p == 'itFiAc40d'
>>> choose(ps, s, 0)
'RnW'
>>> choose(ps, s, 1)
'itFiAc40d'
>>> choose(ps, s, 2)
'e'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Tl4qyDvUzq', '219tHOGK77', 'gvFnh4ypPs', '2plMVD5bF', 'Sy9ydsV', 'QmMJ']
>>> s = lambda p: p == '2plMVD5bF' or p == 'QmMJ' or p == 'Sy9ydsV' or p == 'gvFnh4ypPs'
>>> choose(ps, s, 0)
'gvFnh4ypPs'
>>> choose(ps, s, 1)
'2plMVD5bF'
>>> choose(ps, s, 2)
'Sy9ydsV'
>>> choose(ps, s, 3)
'QmMJ'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['k2RL9', 'cBtzx1ZUu', 'DdJNjj', 'xdUAYSdFjk', 'N9vHSIIy', 'fO', 'alIf1', 'i']
>>> s = lambda p: p == 'DdJNjj' or p == 'N9vHSIIy' or p == 'alIf1' or p == 'cBtzx1ZUu' or p == 'k2RL9'
>>> choose(ps, s, 0)
'k2RL9'
>>> choose(ps, s, 1)
'cBtzx1ZUu'
>>> choose(ps, s, 2)
'DdJNjj'
>>> choose(ps, s, 3)
'N9vHSIIy'
>>> choose(ps, s, 4)
'alIf1'
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['WzdN8', 'YEDX', 'sr', '9cfLm']
>>> s = lambda p: p == 'YEDX' or p == 'sr'
>>> choose(ps, s, 0)
'YEDX'
>>> choose(ps, s, 1)
'sr'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['NlwErghs', 'XPDU', 'jzYGBj', 'P6', 'w']
>>> s = lambda p: p == 'NlwErghs'
>>> choose(ps, s, 0)
'NlwErghs'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['dZi4B', 'Gtihxn6r', '03alCKzGQ', 'CusewJ6', 'hi9n', 'aipp1l', 'NCTAk', 'UXBZJ']
>>> s = lambda p: p == '03alCKzGQ' or p == 'NCTAk' or p == 'dZi4B' or p == 'hi9n'
>>> choose(ps, s, 0)
'dZi4B'
>>> choose(ps, s, 1)
'03alCKzGQ'
>>> choose(ps, s, 2)
'hi9n'
>>> choose(ps, s, 3)
'NCTAk'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Txb', 'Q1WE7qA', '6XQj', 'gMNin4hq4w', 'pziJgrhuz', '8q4', 'Txy']
>>> s = lambda p: p == 'gMNin4hq4w' or p == 'pziJgrhuz'
>>> choose(ps, s, 0)
'gMNin4hq4w'
>>> choose(ps, s, 1)
'pziJgrhuz'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['HL5xB', 'Z1', 'Zw2hPXj2', 't', 'Kru1WdQbu', 'eqWVk', 'EBRFugj8B', 'tmsX', 'HRd']
>>> s = lambda p: p == 'EBRFugj8B' or p == 'Kru1WdQbu' or p == 't'
>>> choose(ps, s, 0)
't'
>>> choose(ps, s, 1)
'Kru1WdQbu'
>>> choose(ps, s, 2)
'EBRFugj8B'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
>>> choose(ps, s, 10)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['fgdI', 'O8HCeAG4TZ', '1fHh9Ei2uh', 'vBSd']
>>> s = lambda p: p == '1fHh9Ei2uh' or p == 'vBSd'
>>> choose(ps, s, 0)
'1fHh9Ei2uh'
>>> choose(ps, s, 1)
'vBSd'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['thvLCiRUaO', 'MzkZ', '7xG', 'AoGZ', 'HS75YTP']
>>> s = lambda p: p == '7xG' or p == 'AoGZ' or p == 'HS75YTP' or p == 'MzkZ'
>>> choose(ps, s, 0)
'MzkZ'
>>> choose(ps, s, 1)
'7xG'
>>> choose(ps, s, 2)
'AoGZ'
>>> choose(ps, s, 3)
'HS75YTP'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['uT5', 'KPeXYnET', 'IJjA3A2w']
>>> s = lambda p: p == 'KPeXYnET'
>>> choose(ps, s, 0)
'KPeXYnET'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Uq98V6O', 'k', 'EgT1EpPM']
>>> s = lambda p: p == 'Uq98V6O' or p == 'k'
>>> choose(ps, s, 0)
'Uq98V6O'
>>> choose(ps, s, 1)
'k'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Pc', 'CoL', 'KFDY8UD', 'HmG', 'qciZ9kWAB4', 'bafyIpd8U', 'Rtygug']
>>> s = lambda p: p == 'CoL'
>>> choose(ps, s, 0)
'CoL'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['TjK2nv', 'JT', '6izv', 'wqzU3L', 'fg']
>>> s = lambda p: p == 'wqzU3L'
>>> choose(ps, s, 0)
'wqzU3L'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['TfV7QdkY', 'Bzd9osf6er', 'EydfOK', '3y', 'sH', 'h1', '0', 'rD']
>>> s = lambda p: p == '0' or p == 'rD'
>>> choose(ps, s, 0)
'0'
>>> choose(ps, s, 1)
'rD'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['R0P', 'm', 'jsehdWm', '0TWTsZ', 'hA', 'UD', 'kuQb', 'uqQYCAx0', 'c']
>>> s = lambda p: p == 'UD' or p == 'c' or p == 'kuQb' or p == 'm'
>>> choose(ps, s, 0)
'm'
>>> choose(ps, s, 1)
'UD'
>>> choose(ps, s, 2)
'kuQb'
>>> choose(ps, s, 3)
'c'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
>>> choose(ps, s, 10)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['PkmOH', 'NG6HAJ', 'YysuECiszy', 'Q7CysdSt']
>>> s = lambda p: p == 'PkmOH'
>>> choose(ps, s, 0)
'PkmOH'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['BJ5gtIY', 'MuR', 'aKTPcHm']
>>> s = lambda p: p == 'BJ5gtIY' or p == 'aKTPcHm'
>>> choose(ps, s, 0)
'BJ5gtIY'
>>> choose(ps, s, 1)
'aKTPcHm'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Mbkg9g', 'MlYvYYZ', 'mDj', 'if01', 'Rp', '4sznEC', 'vgKWOAEfpL']
>>> s = lambda p: p == 'Mbkg9g' or p == 'MlYvYYZ' or p == 'if01' or p == 'mDj'
>>> choose(ps, s, 0)
'Mbkg9g'
>>> choose(ps, s, 1)
'MlYvYYZ'
>>> choose(ps, s, 2)
'mDj'
>>> choose(ps, s, 3)
'if01'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['tfKtKfC', 'tm', 'h0qDaxp', '9dqW', 'u0L44Wr15j', 'oHeqKhx', '9wIE2qBV']
>>> s = lambda p: p == '9dqW' or p == 'h0qDaxp' or p == 'oHeqKhx' or p == 'tfKtKfC'
>>> choose(ps, s, 0)
'tfKtKfC'
>>> choose(ps, s, 1)
'h0qDaxp'
>>> choose(ps, s, 2)
'9dqW'
>>> choose(ps, s, 3)
'oHeqKhx'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['rJhT7WL', '1nLtR']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['8Kb9Df']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['OwEteuQk7', 'w8L6', 'O8rZO7QEDH', 'yqJND8', 'xi', 'x']
>>> s = lambda p: p == 'O8rZO7QEDH' or p == 'OwEteuQk7' or p == 'w8L6' or p == 'x' or p == 'xi'
>>> choose(ps, s, 0)
'OwEteuQk7'
>>> choose(ps, s, 1)
'w8L6'
>>> choose(ps, s, 2)
'O8rZO7QEDH'
>>> choose(ps, s, 3)
'xi'
>>> choose(ps, s, 4)
'x'
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['3pLPrqWRU', '2tVwTl', 'h3', 'h', 'GKsxvci', 'MMKb17']
>>> s = lambda p: p == '2tVwTl' or p == 'GKsxvci' or p == 'h3'
>>> choose(ps, s, 0)
'2tVwTl'
>>> choose(ps, s, 1)
'h3'
>>> choose(ps, s, 2)
'GKsxvci'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Yj3eX']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['dnln', 'rAgVI']
>>> s = lambda p: p == 'dnln'
>>> choose(ps, s, 0)
'dnln'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Lz', 'v3KeV', 'lIH', 'WlHz', 'FT', 'zyTMZqx', 'AU6D', 'f5h', '0N2h']
>>> s = lambda p: p == '0N2h' or p == 'AU6D' or p == 'FT' or p == 'Lz' or p == 'WlHz' or p == 'f5h' or p == 'lIH' or p == 'zyTMZqx'
>>> choose(ps, s, 0)
'Lz'
>>> choose(ps, s, 1)
'lIH'
>>> choose(ps, s, 2)
'WlHz'
>>> choose(ps, s, 3)
'FT'
>>> choose(ps, s, 4)
'zyTMZqx'
>>> choose(ps, s, 5)
'AU6D'
>>> choose(ps, s, 6)
'f5h'
>>> choose(ps, s, 7)
'0N2h'
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
>>> choose(ps, s, 10)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['784e1Zw5D', 'loszSdL', 'Doljlq87', '7bs1Cavy', 'islC1Zr3pd', 'vC6voVbml', 'NlATIbqbqH']
>>> s = lambda p: p == '784e1Zw5D' or p == 'vC6voVbml'
>>> choose(ps, s, 0)
'784e1Zw5D'
>>> choose(ps, s, 1)
'vC6voVbml'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Gxe', 'aLFptpZ', 'mTk0PqgvEd']
>>> s = lambda p: p == 'mTk0PqgvEd'
>>> choose(ps, s, 0)
'mTk0PqgvEd'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['R', 's5w']
>>> s = lambda p: p == 'R' or p == 's5w'
>>> choose(ps, s, 0)
'R'
>>> choose(ps, s, 1)
's5w'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['56ymnsoou', '3SR1BSp9', 'lnDFUseC', 'XX', '5qPAWcVr', 'MagSw', 'OM2']
>>> s = lambda p: p == '56ymnsoou' or p == 'MagSw' or p == 'lnDFUseC'
>>> choose(ps, s, 0)
'56ymnsoou'
>>> choose(ps, s, 1)
'lnDFUseC'
>>> choose(ps, s, 2)
'MagSw'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['5NB7WkerdL', 'DM7ElcD8', 'Z0jxaWrO']
>>> s = lambda p: p == '5NB7WkerdL' or p == 'DM7ElcD8'
>>> choose(ps, s, 0)
'5NB7WkerdL'
>>> choose(ps, s, 1)
'DM7ElcD8'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['dN']
>>> s = lambda p: p == 'dN'
>>> choose(ps, s, 0)
'dN'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['qIe9AKgG', '32', 'L3BZo7']
>>> s = lambda p: p == '32'
>>> choose(ps, s, 0)
'32'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['6rC', 'i', 'ShmGuRlD', 'auTCnLV9N', 'eUm', '3LWePKqsLE', 'UJWaX5', 'YHWXmg8ZKJ']
>>> s = lambda p: p == 'YHWXmg8ZKJ' or p == 'eUm'
>>> choose(ps, s, 0)
'eUm'
>>> choose(ps, s, 1)
'YHWXmg8ZKJ'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['rdDBdH1Z2', '4vNQk', 'D9']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['7nb', 'ct0', 'vnXAZmXa', 'Kk']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['nt', 'Kh']
>>> s = lambda p: p == 'nt'
>>> choose(ps, s, 0)
'nt'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['D18', 'cDr', '4tqx', 'T4cu', 'rSMQ', 'QOVBeZ', 'LJEhyyV', 'nN4L', 'sh8yGSN0']
>>> s = lambda p: p == '4tqx'
>>> choose(ps, s, 0)
'4tqx'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
>>> choose(ps, s, 10)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['U', 'E', 'xpSt3', 'IBTIrxBn', 'x', '5NHXIC', 'bevi8', 'H2J']
>>> s = lambda p: p == '5NHXIC' or p == 'E' or p == 'H2J' or p == 'IBTIrxBn' or p == 'bevi8' or p == 'x' or p == 'xpSt3'
>>> choose(ps, s, 0)
'E'
>>> choose(ps, s, 1)
'xpSt3'
>>> choose(ps, s, 2)
'IBTIrxBn'
>>> choose(ps, s, 3)
'x'
>>> choose(ps, s, 4)
'5NHXIC'
>>> choose(ps, s, 5)
'bevi8'
>>> choose(ps, s, 6)
'H2J'
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['zKnSYBGR']
>>> s = lambda p: p == 'zKnSYBGR'
>>> choose(ps, s, 0)
'zKnSYBGR'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['qWQ5R', 'itUa']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['vyc99h', 'C2Fb']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['VVfHQc', '3tphSDJHW']
>>> s = lambda p: p == 'VVfHQc'
>>> choose(ps, s, 0)
'VVfHQc'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['6fZ69QtrT', 'w', 'Mj', 'm9Q3q7', 'e8', 'oT91rDgCkf', 'Ku3YY', '1kR7E7o']
>>> s = lambda p: p == '1kR7E7o' or p == '6fZ69QtrT' or p == 'm9Q3q7' or p == 'oT91rDgCkf'
>>> choose(ps, s, 0)
'6fZ69QtrT'
>>> choose(ps, s, 1)
'm9Q3q7'
>>> choose(ps, s, 2)
'oT91rDgCkf'
>>> choose(ps, s, 3)
'1kR7E7o'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['P0GxoIDZ', '1ea7Auf6yr', '4GXri', 'KFEjSWJGo9', 'G4CRHYUS']
>>> s = lambda p: p == '1ea7Auf6yr' or p == 'G4CRHYUS'
>>> choose(ps, s, 0)
'1ea7Auf6yr'
>>> choose(ps, s, 1)
'G4CRHYUS'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['WYDL4w', 'h3X', 'eTzA8ZVto']
>>> s = lambda p: p == 'h3X'
>>> choose(ps, s, 0)
'h3X'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['uSdsnZX', 'sm', 'IhETqbyq', 'YyWmeW']
>>> s = lambda p: p == 'uSdsnZX'
>>> choose(ps, s, 0)
'uSdsnZX'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['newpDoQ']
>>> s = lambda p: p == 'newpDoQ'
>>> choose(ps, s, 0)
'newpDoQ'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['39cz9', 'aF4UgswU7', 'nmLtF3C74t', 'O5zVDC0Qk', 'raNMI', 'Ww']
>>> s = lambda p: p == '39cz9' or p == 'nmLtF3C74t' or p == 'raNMI'
>>> choose(ps, s, 0)
'39cz9'
>>> choose(ps, s, 1)
'nmLtF3C74t'
>>> choose(ps, s, 2)
'raNMI'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['cGYgMJ']
>>> s = lambda p: p == 'cGYgMJ'
>>> choose(ps, s, 0)
'cGYgMJ'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Z6sMzUpX', 'bjZrla', 'd592KutV', 'u9ePqq']
>>> s = lambda p: p == 'Z6sMzUpX' or p == 'bjZrla'
>>> choose(ps, s, 0)
'Z6sMzUpX'
>>> choose(ps, s, 1)
'bjZrla'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['CPkMCFSlI', 'hN', '36fjymO']
>>> s = lambda p: p == 'CPkMCFSlI' or p == 'hN'
>>> choose(ps, s, 0)
'CPkMCFSlI'
>>> choose(ps, s, 1)
'hN'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['0chTifN', 'zwzztDjl9J', 'sibJYXU3', 'FRBno3fxQ']
>>> s = lambda p: p == '0chTifN' or p == 'sibJYXU3' or p == 'zwzztDjl9J'
>>> choose(ps, s, 0)
'0chTifN'
>>> choose(ps, s, 1)
'zwzztDjl9J'
>>> choose(ps, s, 2)
'sibJYXU3'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['RyrvEszDL', 'OX', 'l41oGb51', 'K6', 'miYmytdkh0']
>>> s = lambda p: p == 'miYmytdkh0'
>>> choose(ps, s, 0)
'miYmytdkh0'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['x9', '1mTh6V', 'EtQTYbRs']
>>> s = lambda p: p == '1mTh6V' or p == 'EtQTYbRs'
>>> choose(ps, s, 0)
'1mTh6V'
>>> choose(ps, s, 1)
'EtQTYbRs'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['4iYIAlSlO', 'XmrFk', 'k', 'kmX', 'Wkc5VlUZ']
>>> s = lambda p: p == 'Wkc5VlUZ' or p == 'XmrFk' or p == 'kmX'
>>> choose(ps, s, 0)
'XmrFk'
>>> choose(ps, s, 1)
'kmX'
>>> choose(ps, s, 2)
'Wkc5VlUZ'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['dtrqh', 'lw8BciizM', 'HyveF', 'lLhw', 'jZZsxtz', 'fzTVyZ7SA4']
>>> s = lambda p: p == 'HyveF' or p == 'dtrqh' or p == 'lw8BciizM'
>>> choose(ps, s, 0)
'dtrqh'
>>> choose(ps, s, 1)
'lw8BciizM'
>>> choose(ps, s, 2)
'HyveF'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['9', '2V', 'RApekvN', 'ar6mBR2', 'F0IIQe6', 'tSrWV', 'gWjCn4j']
>>> s = lambda p: p == '9' or p == 'RApekvN'
>>> choose(ps, s, 0)
'9'
>>> choose(ps, s, 1)
'RApekvN'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['k', 'Lhx', 'dV', 'qZs']
>>> s = lambda p: p == 'Lhx'
>>> choose(ps, s, 0)
'Lhx'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['AXNQUf', 'kkjB', 'lGMF']
>>> s = lambda p: p == 'AXNQUf'
>>> choose(ps, s, 0)
'AXNQUf'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['H9SPZR', 'P6x9', '0x6iPT8Vp', 'bELQa', 'gDdF', 'd', 'PLlr39R', 'uB3C', 'J']
>>> s = lambda p: p == 'H9SPZR' or p == 'J' or p == 'P6x9' or p == 'PLlr39R' or p == 'bELQa' or p == 'gDdF'
>>> choose(ps, s, 0)
'H9SPZR'
>>> choose(ps, s, 1)
'P6x9'
>>> choose(ps, s, 2)
'bELQa'
>>> choose(ps, s, 3)
'gDdF'
>>> choose(ps, s, 4)
'PLlr39R'
>>> choose(ps, s, 5)
'J'
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
>>> choose(ps, s, 10)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Gbw', '5eTONy', 'r0AifHw', 'kDl', '6EQvhzS2', 'tzT5Qd0', 'Xt5LH']
>>> s = lambda p: p == 'kDl' or p == 'r0AifHw' or p == 'tzT5Qd0'
>>> choose(ps, s, 0)
'r0AifHw'
>>> choose(ps, s, 1)
'kDl'
>>> choose(ps, s, 2)
'tzT5Qd0'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['T', 'NHHbjxeyg']
>>> s = lambda p: p == 'T'
>>> choose(ps, s, 0)
'T'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['735kD', 'Cydsvguv3', 'aUd1Lh4qll', '2fr', 'orPUSE', 'daD', '9arD', 'YZK']
>>> s = lambda p: p == '735kD' or p == '9arD' or p == 'Cydsvguv3' or p == 'aUd1Lh4qll' or p == 'daD'
>>> choose(ps, s, 0)
'735kD'
>>> choose(ps, s, 1)
'Cydsvguv3'
>>> choose(ps, s, 2)
'aUd1Lh4qll'
>>> choose(ps, s, 3)
'daD'
>>> choose(ps, s, 4)
'9arD'
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['wTrS1wnYVc']
>>> s = lambda p: p == 'wTrS1wnYVc'
>>> choose(ps, s, 0)
'wTrS1wnYVc'
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['O2Z', 'kXg2S', 'iiSLscfD5', 'KQDBr6', 'iy', 'Wl5Y', 'd2K8NvD1d4', 'pTApHl3f', '7GLR9']
>>> s = lambda p: p == 'Wl5Y' or p == 'd2K8NvD1d4' or p == 'iiSLscfD5' or p == 'iy' or p == 'kXg2S' or p == 'pTApHl3f'
>>> choose(ps, s, 0)
'kXg2S'
>>> choose(ps, s, 1)
'iiSLscfD5'
>>> choose(ps, s, 2)
'iy'
>>> choose(ps, s, 3)
'Wl5Y'
>>> choose(ps, s, 4)
'd2K8NvD1d4'
>>> choose(ps, s, 5)
'pTApHl3f'
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
>>> choose(ps, s, 10)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['oM', 'zGYOgEw', 'ueeX', 'D9BVt', 'AAjYFErh4', 'JjCV', '3', '1d7hiLfH']
>>> s = lambda p: p == '1d7hiLfH' or p == 'AAjYFErh4' or p == 'oM'
>>> choose(ps, s, 0)
'oM'
>>> choose(ps, s, 1)
'AAjYFErh4'
>>> choose(ps, s, 2)
'1d7hiLfH'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['9', 'lFk']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['hDfoY', 'Gx5B', 'j4blx8g', '8KmJf6msa', 'un', 'R', 'onOdPr', 'ABRTPn']
>>> s = lambda p: p == 'ABRTPn' or p == 'hDfoY' or p == 'onOdPr' or p == 'un'
>>> choose(ps, s, 0)
'hDfoY'
>>> choose(ps, s, 1)
'un'
>>> choose(ps, s, 2)
'onOdPr'
>>> choose(ps, s, 3)
'ABRTPn'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['eR', 'i6Bgh134A7', 'DXuD34', 'Cx5jaMth', 'Md8', '4Pf7qA', 'zlrFFuA']
>>> s = lambda p: p == 'eR' or p == 'i6Bgh134A7' or p == 'zlrFFuA'
>>> choose(ps, s, 0)
'eR'
>>> choose(ps, s, 1)
'i6Bgh134A7'
>>> choose(ps, s, 2)
'zlrFFuA'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['M7lN', '2', 'slZI6', 'C', 'LirWSCzE7L', '76smbBkd9q', 'ahzd740']
>>> s = lambda p: p == 'C' or p == 'LirWSCzE7L' or p == 'M7lN' or p == 'ahzd740'
>>> choose(ps, s, 0)
'M7lN'
>>> choose(ps, s, 1)
'C'
>>> choose(ps, s, 2)
'LirWSCzE7L'
>>> choose(ps, s, 3)
'ahzd740'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['QHKeBnn', 'igEmIdOqfO', 'D1wLx76K', 'ggy', 'FW', 'akXSeF', 'PW', 'PmSZ']
>>> s = lambda p: p == 'QHKeBnn' or p == 'akXSeF'
>>> choose(ps, s, 0)
'QHKeBnn'
>>> choose(ps, s, 1)
'akXSeF'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
>>> choose(ps, s, 9)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['YVaXL', 'OUqqkf']
>>> s = lambda p: p == 'OUqqkf' or p == 'YVaXL'
>>> choose(ps, s, 0)
'YVaXL'
>>> choose(ps, s, 1)
'OUqqkf'
>>> choose(ps, s, 2)
''
>>> choose(ps, s, 3)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['WsEqFQV', 'H3kSFt', 'tFY']
>>> s = lambda p: p == 'H3kSFt' or p == 'WsEqFQV' or p == 'tFY'
>>> choose(ps, s, 0)
'WsEqFQV'
>>> choose(ps, s, 1)
'H3kSFt'
>>> choose(ps, s, 2)
'tFY'
>>> choose(ps, s, 3)
''
>>> choose(ps, s, 4)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['S2E6N']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = []
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['Tu6Em', 'HAsg4c', 'nB5LTvR4f5', 'zm', 'gV9jk', 'AqFELMW8g']
>>> s = lambda p: p == 'AqFELMW8g' or p == 'gV9jk' or p == 'nB5LTvR4f5' or p == 'zm'
>>> choose(ps, s, 0)
'nB5LTvR4f5'
>>> choose(ps, s, 1)
'zm'
>>> choose(ps, s, 2)
'gV9jk'
>>> choose(ps, s, 3)
'AqFELMW8g'
>>> choose(ps, s, 4)
''
>>> choose(ps, s, 5)
''
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['UawKAu']
>>> s = lambda p: False
>>> choose(ps, s, 0)
''
>>> choose(ps, s, 1)
''
>>> choose(ps, s, 2)
''
""",
'hidden': False,
'locked': False
},
{
'code': r"""
>>> ps = ['XU9', 'ji0ux', 'N', 'V5jBALIgP', 'g6vdlQ', 'ARqJ', 'rqk58']
>>> s = lambda p: p == 'ARqJ' or p == 'N' or p == 'V5jBALIgP' or p == 'XU9' or p == 'ji0ux' or p == 'rqk58'
>>> choose(ps, s, 0)
'XU9'
>>> choose(ps, s, 1)
'ji0ux'
>>> choose(ps, s, 2)
'N'
>>> choose(ps, s, 3)
'V5jBALIgP'
>>> choose(ps, s, 4)
'ARqJ'
>>> choose(ps, s, 5)
'rqk58'
>>> choose(ps, s, 6)
''
>>> choose(ps, s, 7)
''
>>> choose(ps, s, 8)
''
""",
'hidden': False,
'locked': False
}
],
'scored': True,
'setup': r"""
>>> from typing import choose
""",
'teardown': '',
'type': 'doctest'
}
]
}
| 25.059169
| 141
| 0.289623
| 4,594
| 51,246
| 3.230736
| 0.092947
| 0.12532
| 0.366864
| 0.06805
| 0.508894
| 0.505188
| 0.505188
| 0.505188
| 0.504379
| 0.504379
| 0
| 0.049662
| 0.504117
| 51,246
| 2,044
| 142
| 25.071429
| 0.534393
| 0
| 0
| 0.723581
| 0
| 0.03229
| 0.827967
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.000978
| 0
| 0.000978
| 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3ce6a55ed3386e2078fd95c3780559b02064f8e5
| 91
|
py
|
Python
|
metREx/app/main/util/misc_helper.py
|
vijayragava/metREx
|
095ad24680b8351a4ec89744f2ef407ae73795f6
|
[
"Apache-2.0"
] | 8
|
2020-03-13T13:19:25.000Z
|
2021-06-07T15:13:11.000Z
|
metREx/app/main/util/misc_helper.py
|
vijayragava/metREx
|
095ad24680b8351a4ec89744f2ef407ae73795f6
|
[
"Apache-2.0"
] | null | null | null |
metREx/app/main/util/misc_helper.py
|
vijayragava/metREx
|
095ad24680b8351a4ec89744f2ef407ae73795f6
|
[
"Apache-2.0"
] | 2
|
2020-04-27T20:38:16.000Z
|
2021-06-07T15:13:48.000Z
|
def str_to_bool(x):
x = str(x)
return x.lower() in ('true', 't', 'yes', 'y', '1')
| 18.2
| 54
| 0.483516
| 17
| 91
| 2.470588
| 0.764706
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.014493
| 0.241758
| 91
| 4
| 55
| 22.75
| 0.594203
| 0
| 0
| 0
| 0
| 0
| 0.10989
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
3cf25d614747f0a4eb45aa7409790183521d9166
| 113
|
py
|
Python
|
lib/__init__.py
|
ivan1993spb/snake-backend
|
77b115202a8e433ac3fa934b3dae932b5018b9a0
|
[
"MIT"
] | null | null | null |
lib/__init__.py
|
ivan1993spb/snake-backend
|
77b115202a8e433ac3fa934b3dae932b5018b9a0
|
[
"MIT"
] | 3
|
2021-09-08T01:38:22.000Z
|
2022-03-12T00:14:06.000Z
|
lib/__init__.py
|
ivan1993spb/snake-backend
|
77b115202a8e433ac3fa934b3dae932b5018b9a0
|
[
"MIT"
] | null | null | null |
"""The module contains necessary classes, functions and methods to provide
operations with the Snake-Server.
"""
| 28.25
| 74
| 0.787611
| 15
| 113
| 5.933333
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.132743
| 113
| 3
| 75
| 37.666667
| 0.908163
| 0.929204
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
3cff2efdb16dbcc9414b52617014c6ca8ab980fa
| 320
|
py
|
Python
|
app/services/tokyo_commodities_exchange/export_site_to_db/abstract/destinations/tokyo_c_e_historical_db/connection.py
|
Tinitto/crypto-exchange
|
cb61664ff0119d8120315b8c6feb77aeba0ec050
|
[
"MIT"
] | null | null | null |
app/services/tokyo_commodities_exchange/export_site_to_db/abstract/destinations/tokyo_c_e_historical_db/connection.py
|
Tinitto/crypto-exchange
|
cb61664ff0119d8120315b8c6feb77aeba0ec050
|
[
"MIT"
] | null | null | null |
app/services/tokyo_commodities_exchange/export_site_to_db/abstract/destinations/tokyo_c_e_historical_db/connection.py
|
Tinitto/crypto-exchange
|
cb61664ff0119d8120315b8c6feb77aeba0ec050
|
[
"MIT"
] | null | null | null |
"""Module with the connection settings for the Tokyo Commodities Exchange file download service"""
import os
from judah.destinations.database.config import DatabaseConnectionConfig
class TokyoCEHistoricalDbConnectionConfig(DatabaseConnectionConfig):
db_uri: str = os.getenv("TOKYO_COMMODITIES_HISTORICAL_DB_URI")
| 35.555556
| 98
| 0.840625
| 35
| 320
| 7.542857
| 0.771429
| 0.121212
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 320
| 8
| 99
| 40
| 0.916667
| 0.2875
| 0
| 0
| 0
| 0
| 0.157658
| 0.157658
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
a737c58a04b7f20715a418ebd1a9e00255703285
| 155
|
py
|
Python
|
app/wsgi.py
|
vince21/nwapw-condensity-os
|
ddfcdf969d3eee8966d5cbe525242e06445f7e2f
|
[
"MIT"
] | null | null | null |
app/wsgi.py
|
vince21/nwapw-condensity-os
|
ddfcdf969d3eee8966d5cbe525242e06445f7e2f
|
[
"MIT"
] | null | null | null |
app/wsgi.py
|
vince21/nwapw-condensity-os
|
ddfcdf969d3eee8966d5cbe525242e06445f7e2f
|
[
"MIT"
] | null | null | null |
# NWAPW
# Spencer Chang, Toby Ueno, Vincent Wilson
# date: 8/04/20
# description: wsgi file
from app import app
if __name__ == "__main__":
app.run()
| 15.5
| 42
| 0.683871
| 23
| 155
| 4.26087
| 0.913043
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.040323
| 0.2
| 155
| 9
| 43
| 17.222222
| 0.75
| 0.535484
| 0
| 0
| 0
| 0
| 0.119403
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
598e2e363264d6f315feae291c15680c71720bfb
| 415
|
py
|
Python
|
toontown/uberdog/DistributedSecurityMgrAI.py
|
SuperM0use24/TT-CL-Edition
|
fdad8394f0656ae122b687d603f72afafd220c65
|
[
"MIT"
] | 3
|
2020-01-02T08:43:36.000Z
|
2020-07-05T08:59:02.000Z
|
toontown/uberdog/DistributedSecurityMgrAI.py
|
NoraTT/Historical-Commits-Project-Altis-Source
|
fe88e6d07edf418f7de6ad5b3d9ecb3d0d285179
|
[
"Apache-2.0"
] | 1
|
2021-06-08T17:16:48.000Z
|
2021-06-08T17:16:48.000Z
|
toontown/uberdog/DistributedSecurityMgrAI.py
|
NoraTT/Historical-Commits-Project-Altis-Source
|
fe88e6d07edf418f7de6ad5b3d9ecb3d0d285179
|
[
"Apache-2.0"
] | 4
|
2019-06-20T23:45:23.000Z
|
2020-10-14T20:30:15.000Z
|
from direct.directnotify import DirectNotifyGlobal
from direct.distributed.DistributedObjectGlobalAI import DistributedObjectGlobalAI
class DistributedSecurityMgrAI(DistributedObjectGlobalAI):
notify = DirectNotifyGlobal.directNotify.newCategory("DistributedSecurityMgrAI")
def requestAccountId(self, todo0, todo1, todo2):
pass
def requestAccountIdResponse(self, todo0, todo1):
pass
| 31.923077
| 84
| 0.807229
| 32
| 415
| 10.46875
| 0.59375
| 0.059701
| 0.083582
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.013928
| 0.13494
| 415
| 12
| 85
| 34.583333
| 0.91922
| 0
| 0
| 0.25
| 0
| 0
| 0.057971
| 0.057971
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.25
| 0.25
| 0
| 0.75
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
59cdf967829e52140f9a93408e3f0bf4e8e0e808
| 511
|
py
|
Python
|
day05/day05.py
|
RobinRH/advent-of-code-2017
|
8996691abf4d9020294e5b750bef1e35effd5c68
|
[
"MIT"
] | null | null | null |
day05/day05.py
|
RobinRH/advent-of-code-2017
|
8996691abf4d9020294e5b750bef1e35effd5c68
|
[
"MIT"
] | null | null | null |
day05/day05.py
|
RobinRH/advent-of-code-2017
|
8996691abf4d9020294e5b750bef1e35effd5c68
|
[
"MIT"
] | null | null | null |
# answer -> 388611
# answer -> 27763113
import io
# part 1
input = [int(line) for line in open('input05.txt', 'r')]
index = 0
count = 0
while index < len(input):
jump = input[index]
input[index] += 1
index += jump
count += 1
print('part 1: ', count)
# part 2
input = [int(line) for line in open('input05.txt', 'r')]
index = 0
count = 0
while index < len(input):
jump = input[index]
input[index] += -1 if jump >= 3 else 1
index += jump
count += 1
print('part 2: ', count)
| 15.96875
| 56
| 0.58317
| 79
| 511
| 3.772152
| 0.341772
| 0.134228
| 0.080537
| 0.100671
| 0.775168
| 0.775168
| 0.775168
| 0.610738
| 0.610738
| 0.610738
| 0
| 0.08399
| 0.254403
| 511
| 31
| 57
| 16.483871
| 0.698163
| 0.09589
| 0
| 0.736842
| 0
| 0
| 0.087719
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.052632
| 0
| 0.052632
| 0.105263
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ab8b6431e73b0b65448403693bc7faf189e03585
| 89
|
py
|
Python
|
galeria/apps.py
|
JoseDevApps/Pets
|
280e193c5bb293893a2baa547fcde0141f5db010
|
[
"MIT"
] | null | null | null |
galeria/apps.py
|
JoseDevApps/Pets
|
280e193c5bb293893a2baa547fcde0141f5db010
|
[
"MIT"
] | 9
|
2020-06-08T03:31:08.000Z
|
2022-01-13T02:44:42.000Z
|
galeria/apps.py
|
JoseDevApps/Pets
|
280e193c5bb293893a2baa547fcde0141f5db010
|
[
"MIT"
] | 1
|
2020-06-01T17:43:20.000Z
|
2020-06-01T17:43:20.000Z
|
from django.apps import AppConfig
class GaleriaConfig(AppConfig):
name = 'galeria'
| 14.833333
| 33
| 0.752809
| 10
| 89
| 6.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168539
| 89
| 5
| 34
| 17.8
| 0.905405
| 0
| 0
| 0
| 0
| 0
| 0.078652
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
ab971cbe77810088a27561292be60f87c7244231
| 168
|
py
|
Python
|
starlette_context/plugins/user_agent.py
|
adamantike/starlette-context
|
a935fbfc2f58799661c33f72695a42958af92545
|
[
"MIT"
] | 242
|
2019-12-28T15:00:15.000Z
|
2022-03-23T11:40:55.000Z
|
starlette_context/plugins/user_agent.py
|
adamantike/starlette-context
|
a935fbfc2f58799661c33f72695a42958af92545
|
[
"MIT"
] | 37
|
2019-12-31T16:52:43.000Z
|
2022-03-04T02:49:46.000Z
|
starlette_context/plugins/user_agent.py
|
hhamana/starlette-context
|
6638504c4e702578fa23ae4b163a65ffc79d798a
|
[
"MIT"
] | 15
|
2020-03-10T13:13:28.000Z
|
2022-01-31T13:23:10.000Z
|
from starlette_context.header_keys import HeaderKeys
from starlette_context.plugins.base import Plugin
class UserAgentPlugin(Plugin):
key = HeaderKeys.user_agent
| 24
| 52
| 0.839286
| 21
| 168
| 6.52381
| 0.714286
| 0.189781
| 0.291971
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.113095
| 168
| 6
| 53
| 28
| 0.919463
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
abc35ba380794faca22842c672f37f9d33017f19
| 156
|
py
|
Python
|
src/setup.py
|
PejLab/aFC-n
|
5dbaf963b92c41955b36c036eee45b84774ca1a7
|
[
"Apache-2.0"
] | null | null | null |
src/setup.py
|
PejLab/aFC-n
|
5dbaf963b92c41955b36c036eee45b84774ca1a7
|
[
"Apache-2.0"
] | null | null | null |
src/setup.py
|
PejLab/aFC-n
|
5dbaf963b92c41955b36c036eee45b84774ca1a7
|
[
"Apache-2.0"
] | null | null | null |
from setuptools import setup
from Cython.Build import cythonize
setup(
ext_modules = cythonize("*.pyx",compiler_directives={'language_level' : "3"})
)
| 22.285714
| 81
| 0.75
| 19
| 156
| 6
| 0.789474
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007353
| 0.128205
| 156
| 6
| 82
| 26
| 0.830882
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
abc797c4d9d5b0b8133c74e2c3f5159a2afb9b04
| 223
|
py
|
Python
|
remass/tui/forms/__init__.py
|
snototter/remass
|
60494346f676f29a3517bcce30e8aab21cf3d3c6
|
[
"MIT"
] | null | null | null |
remass/tui/forms/__init__.py
|
snototter/remass
|
60494346f676f29a3517bcce30e8aab21cf3d3c6
|
[
"MIT"
] | null | null | null |
remass/tui/forms/__init__.py
|
snototter/remass
|
60494346f676f29a3517bcce30e8aab21cf3d3c6
|
[
"MIT"
] | null | null | null |
from .connection import StartUpForm
from .export import ExportForm
from .screens import ScreenCustomizationForm
from .templates import TemplateSynchronizationForm, TemplateRemovalForm
from .device import DeviceSettingsForm
| 37.166667
| 71
| 0.878924
| 21
| 223
| 9.333333
| 0.619048
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.09417
| 223
| 5
| 72
| 44.6
| 0.970297
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
abd034ee603ee9265f1cbcae49ceec7392305185
| 24
|
py
|
Python
|
tests/__init__.py
|
vb64/bulls_cows
|
dae6c19027c317c475111d35ee18721c563dc22d
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
vb64/bulls_cows
|
dae6c19027c317c475111d35ee18721c563dc22d
|
[
"MIT"
] | 2
|
2019-05-23T19:20:35.000Z
|
2019-05-24T10:51:00.000Z
|
tests/__init__.py
|
vb64/bulls_cows
|
dae6c19027c317c475111d35ee18721c563dc22d
|
[
"MIT"
] | 1
|
2019-06-19T14:32:39.000Z
|
2019-06-19T14:32:39.000Z
|
"""
Run tests stuff
"""
| 6
| 15
| 0.541667
| 3
| 24
| 4.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.208333
| 24
| 3
| 16
| 8
| 0.684211
| 0.625
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
abdce5033ab88016e6d5fcd66c40115ece752c4c
| 34
|
py
|
Python
|
Python_Codes_for_BJ/stage03 for문 사용하기/합.py
|
ch96an/BaekJoonSolution
|
25594fda5ba1c0c4d26ff0828ec8dcf2f6572d33
|
[
"MIT"
] | null | null | null |
Python_Codes_for_BJ/stage03 for문 사용하기/합.py
|
ch96an/BaekJoonSolution
|
25594fda5ba1c0c4d26ff0828ec8dcf2f6572d33
|
[
"MIT"
] | null | null | null |
Python_Codes_for_BJ/stage03 for문 사용하기/합.py
|
ch96an/BaekJoonSolution
|
25594fda5ba1c0c4d26ff0828ec8dcf2f6572d33
|
[
"MIT"
] | null | null | null |
n = int(input())
print(n*(n+1)//2)
| 17
| 17
| 0.529412
| 8
| 34
| 2.25
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.064516
| 0.088235
| 34
| 2
| 17
| 17
| 0.516129
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
abf8b08728d1534e8e835c07c3e299e33de88ca6
| 93
|
py
|
Python
|
anonymous/apps.py
|
ParkHyeonChae/Re-Born-Web
|
95f66600e048b6b10459ed7674d0fa5d3f53dcd5
|
[
"MIT"
] | 23
|
2020-01-22T09:22:46.000Z
|
2022-03-18T08:31:12.000Z
|
anonymous/apps.py
|
ParkHyeonChae/Re-Born-Web
|
95f66600e048b6b10459ed7674d0fa5d3f53dcd5
|
[
"MIT"
] | 9
|
2020-06-05T20:41:34.000Z
|
2022-03-12T00:46:58.000Z
|
anonymous/apps.py
|
ParkHyeonChae/Re-Born-Web
|
95f66600e048b6b10459ed7674d0fa5d3f53dcd5
|
[
"MIT"
] | 15
|
2020-02-09T12:54:25.000Z
|
2022-03-02T00:06:18.000Z
|
from django.apps import AppConfig
class AnonymousConfig(AppConfig):
name = 'anonymous'
| 15.5
| 33
| 0.763441
| 10
| 93
| 7.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 93
| 5
| 34
| 18.6
| 0.910256
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
abfba4a94f9a540df9a4132aa8980ed000925170
| 690
|
py
|
Python
|
unbroke/models.py
|
astar55/unbrokeme
|
a0fb5e59550c7853c866011cc46b8da2dff283b0
|
[
"Apache-2.0"
] | null | null | null |
unbroke/models.py
|
astar55/unbrokeme
|
a0fb5e59550c7853c866011cc46b8da2dff283b0
|
[
"Apache-2.0"
] | null | null | null |
unbroke/models.py
|
astar55/unbrokeme
|
a0fb5e59550c7853c866011cc46b8da2dff283b0
|
[
"Apache-2.0"
] | null | null | null |
from django.db import models
class salary(models.Model):
amount = models.IntegerField()
frequency = models.IntegerField()
monthlysalary = models.IntegerField()
def __str__(self):
return self.id
class income(models.Model):
otherincome = models.IntegerField()
total = models.IntegerField()
def __str__(self):
return self.id
class savings(models.Model):
totalsavings = models.IntegerField()
def __str__(self):
return self.id
class wishlist(models.Model):
prodname = models.CharField(max_length=255)
prodamount = models.DecimalField(decimal_places=2, max_digits=12)
progress = models.IntegerField()
def __str__(self):
return self.id
| 23
| 67
| 0.724638
| 81
| 690
| 5.938272
| 0.444444
| 0.261954
| 0.174636
| 0.199584
| 0.363825
| 0.363825
| 0.363825
| 0.363825
| 0.280665
| 0
| 0
| 0.010471
| 0.169565
| 690
| 30
| 68
| 23
| 0.82897
| 0
| 0
| 0.363636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.181818
| false
| 0
| 0.045455
| 0.181818
| 1
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
abffb9f410bf1001bc549c2c53e223d3d4971b0d
| 1,107
|
py
|
Python
|
tests/test_FIPS.py
|
JohnAndrewTaylor/flowsa
|
21b14b19f08370db574bdd59219a2773983c6f95
|
[
"CC0-1.0"
] | null | null | null |
tests/test_FIPS.py
|
JohnAndrewTaylor/flowsa
|
21b14b19f08370db574bdd59219a2773983c6f95
|
[
"CC0-1.0"
] | null | null | null |
tests/test_FIPS.py
|
JohnAndrewTaylor/flowsa
|
21b14b19f08370db574bdd59219a2773983c6f95
|
[
"CC0-1.0"
] | null | null | null |
# test_FIPS.py (tests)
# !/usr/bin/env python3
# coding=utf-8
# ingwersen.wesley@epa.gov
"""Add docstring in public module.""" # TODO add docstring.
import unittest
from flowsa.common import getFIPS
class TestFIPS(unittest.TestCase):
"""Add docstring in public class.""" # TODO add docstring.
def test_bad_state(self):
"""Add docstring in public method.""" # TODO add docstring.
state = "gibberish"
self.assertIs(getFIPS(state=state), None)
def test_bad_county(self):
"""Add docstring in public method.""" # TODO add docstring.
state = "Wyoming"
county = "Absaroka"
self.assertIs(getFIPS(state=state, county=county), None)
def test_good_state(self):
"""Add docstring in public method.""" # TODO add docstring.
state = "Georgia"
self.assertEqual(getFIPS(state=state), "13000")
def test_good_county(self):
"""Add docstring in public method.""" # TODO add docstring.
state = "IOWA"
county = "Dubuque"
self.assertEqual(getFIPS(state=state, county=county), "19061")
| 30.75
| 70
| 0.64318
| 134
| 1,107
| 5.246269
| 0.358209
| 0.204836
| 0.119488
| 0.170697
| 0.529161
| 0.321479
| 0.321479
| 0.321479
| 0.321479
| 0.321479
| 0
| 0.014068
| 0.229449
| 1,107
| 35
| 71
| 31.628571
| 0.810082
| 0.35411
| 0
| 0
| 0
| 0
| 0.077037
| 0
| 0
| 0
| 0
| 0.028571
| 0.235294
| 1
| 0.235294
| false
| 0
| 0.117647
| 0
| 0.411765
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
f9f7f421259f6693589aa5cdd961133e2e69eb7d
| 563
|
py
|
Python
|
Inheritance/animal.py
|
tatonkoduje/pythonforbegginers
|
1fec11ecd6788c91833d06dfabbb0b1319ff8e68
|
[
"Apache-2.0"
] | null | null | null |
Inheritance/animal.py
|
tatonkoduje/pythonforbegginers
|
1fec11ecd6788c91833d06dfabbb0b1319ff8e68
|
[
"Apache-2.0"
] | null | null | null |
Inheritance/animal.py
|
tatonkoduje/pythonforbegginers
|
1fec11ecd6788c91833d06dfabbb0b1319ff8e68
|
[
"Apache-2.0"
] | null | null | null |
class Animal:
name = "Nieznane"
legs = 4
ears = 2
def __init__(self, name):
self.name = name
def move(self):
print(self.name + " biegnie...")
def stop(self):
print(self.name + " zatrzymuje się.")
def make_noise(self):
print(self.name + " szczeka!")
class Dog(Animal):
def run(self):
print(self.name + " biegnie...")
class Fish(Animal):
def swim(self):
print(self.name + " płynie...")
class Bird(Animal):
def fly(self):
print(self.name + " leci...")
| 17.59375
| 45
| 0.53286
| 68
| 563
| 4.338235
| 0.411765
| 0.216949
| 0.264407
| 0.345763
| 0.162712
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005141
| 0.309059
| 563
| 32
| 46
| 17.59375
| 0.753213
| 0
| 0
| 0.095238
| 0
| 0
| 0.129433
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 0.285714
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e602f677c5c4468ef6f08aef9adbbee72b6c08b1
| 59
|
py
|
Python
|
insurance_charges_model/prediction/__init__.py
|
schmidtbri/regression-model
|
c112949fdb59a947c9f1a6616af9df5d640fe155
|
[
"BSD-3-Clause"
] | null | null | null |
insurance_charges_model/prediction/__init__.py
|
schmidtbri/regression-model
|
c112949fdb59a947c9f1a6616af9df5d640fe155
|
[
"BSD-3-Clause"
] | 2
|
2022-02-26T18:36:16.000Z
|
2022-03-15T12:37:47.000Z
|
insurance_charges_model/prediction/__init__.py
|
schmidtbri/regression-model
|
c112949fdb59a947c9f1a6616af9df5d640fe155
|
[
"BSD-3-Clause"
] | null | null | null |
"""Code for making predictions with a regression model."""
| 29.5
| 58
| 0.745763
| 8
| 59
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135593
| 59
| 1
| 59
| 59
| 0.862745
| 0.881356
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e63b3c39c3c6e8d54be6adcc9322949265f57d91
| 26
|
py
|
Python
|
T02-03/program.py
|
miguelgaoreiss/SSof-Project1920
|
0bf74c264e06966931d6a2e0b42134dfddc32eb4
|
[
"MIT"
] | 2
|
2019-11-20T19:26:07.000Z
|
2019-11-22T00:42:23.000Z
|
T02-03/program.py
|
miguelgaoreiss/SSof-Project1920
|
0bf74c264e06966931d6a2e0b42134dfddc32eb4
|
[
"MIT"
] | 2
|
2019-11-28T05:21:24.000Z
|
2019-11-28T05:21:58.000Z
|
T02-03/program.py
|
miguelgaoreiss/SSof-Project1920
|
0bf74c264e06966931d6a2e0b42134dfddc32eb4
|
[
"MIT"
] | 25
|
2019-11-27T01:40:56.000Z
|
2019-12-04T23:38:59.000Z
|
send_mail_jinja(get(), 2)
| 13
| 25
| 0.730769
| 5
| 26
| 3.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.041667
| 0.076923
| 26
| 1
| 26
| 26
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e645a291fde419fdc95f6166cfe258a5137c2927
| 104
|
py
|
Python
|
surro/__main__.py
|
MatthewScholefield/surro
|
db666a8c5c2fd456b1816562014572ceaabd2b5f
|
[
"MIT"
] | null | null | null |
surro/__main__.py
|
MatthewScholefield/surro
|
db666a8c5c2fd456b1816562014572ceaabd2b5f
|
[
"MIT"
] | null | null | null |
surro/__main__.py
|
MatthewScholefield/surro
|
db666a8c5c2fd456b1816562014572ceaabd2b5f
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
import sys
sys.path += ['.'] # noqa
from surro.game import Game
Game().run()
| 11.555556
| 27
| 0.634615
| 16
| 104
| 4.125
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011628
| 0.173077
| 104
| 8
| 28
| 13
| 0.755814
| 0.25
| 0
| 0
| 0
| 0
| 0.013158
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
0523eccc016d326b432a2a44e523a694aa9f7f34
| 27
|
py
|
Python
|
venv-lib/lib/python3.7/imp.py
|
migmaciasdiaz/venvs
|
bcdbb75931cb27fc4b5b30f12fc44be85952157e
|
[
"MIT"
] | 2
|
2020-03-30T14:17:10.000Z
|
2020-10-04T12:33:00.000Z
|
venv-lib/lib/python3.7/imp.py
|
migmaciasdiaz/venvs
|
bcdbb75931cb27fc4b5b30f12fc44be85952157e
|
[
"MIT"
] | 1
|
2020-11-24T03:31:13.000Z
|
2020-11-24T03:31:13.000Z
|
venv/lib/python3.7/imp.py
|
wensu425/aws-eb-webapp
|
4b149c75c11fe5b33c9a080313ec336fabb45824
|
[
"MIT"
] | 1
|
2021-05-04T09:18:22.000Z
|
2021-05-04T09:18:22.000Z
|
/usr/lib64/python3.7/imp.py
| 27
| 27
| 0.777778
| 6
| 27
| 3.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148148
| 0
| 27
| 1
| 27
| 27
| 0.62963
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05440900ef2c6cd63c982cca941fa868b3b29e1c
| 878
|
py
|
Python
|
oops_fhir/r4/value_set/nutrient_modifier_codes.py
|
Mikuana/oops_fhir
|
77963315d123756b7d21ae881f433778096a1d25
|
[
"MIT"
] | null | null | null |
oops_fhir/r4/value_set/nutrient_modifier_codes.py
|
Mikuana/oops_fhir
|
77963315d123756b7d21ae881f433778096a1d25
|
[
"MIT"
] | null | null | null |
oops_fhir/r4/value_set/nutrient_modifier_codes.py
|
Mikuana/oops_fhir
|
77963315d123756b7d21ae881f433778096a1d25
|
[
"MIT"
] | null | null | null |
from pathlib import Path
from fhir.resources.valueset import ValueSet as _ValueSet
from oops_fhir.utils import ValueSet
from oops_fhir.r4.code_system.snomed_ct import SNOMEDCT
__all__ = ["NutrientModifierCodes"]
_resource = _ValueSet.parse_file(Path(__file__).with_suffix(".json"))
class NutrientModifierCodes(ValueSet):
"""
Nutrient Modifier Codes
NutrientModifier : Codes for types of nutrients that are being modified
such as carbohydrate or sodium. This value set includes codes from
[SNOMED CT](http://snomed.info/sct) where concept is-a 226355009
(Nutrients(substance)), and the concepts for Sodium, Potassium and
Fluid. This is provided as a suggestive example.
Status: draft - Version: 4.0.1
http://hl7.org/fhir/ValueSet/nutrient-code
"""
# TODO: fix this template issue1
pass
class Meta:
resource = _resource
| 24.388889
| 76
| 0.747153
| 117
| 878
| 5.452991
| 0.649573
| 0.043887
| 0.050157
| 0.062696
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.02069
| 0.17426
| 878
| 35
| 77
| 25.085714
| 0.85931
| 0.536446
| 0
| 0
| 0
| 0
| 0.065657
| 0.05303
| 0
| 0
| 0
| 0.028571
| 0
| 1
| 0
| false
| 0.1
| 0.4
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
|
0
| 4
|
054b5c231dfed8abdeafa03df31b71950f5cd52f
| 431
|
py
|
Python
|
src/lib/phdi-transforms/tests/test_basic.py
|
CDCgov/prime-public-health-data-infrastructure
|
7e4849c3a486a84e94765bf0023b80261c510c57
|
[
"Apache-2.0"
] | 3
|
2022-02-24T18:16:39.000Z
|
2022-03-29T20:21:41.000Z
|
src/lib/phdi-transforms/tests/test_basic.py
|
CDCgov/prime-public-health-data-infrastructure
|
7e4849c3a486a84e94765bf0023b80261c510c57
|
[
"Apache-2.0"
] | 17
|
2022-02-08T17:13:55.000Z
|
2022-03-28T16:49:00.000Z
|
src/lib/phdi-transforms/tests/test_basic.py
|
CDCgov/prime-public-health-data-infrastructure
|
7e4849c3a486a84e94765bf0023b80261c510c57
|
[
"Apache-2.0"
] | 3
|
2022-02-27T23:12:50.000Z
|
2022-03-17T04:51:47.000Z
|
from phdi_transforms.basic import transform_name
from phdi_transforms.basic import transform_phone
def test_transform_name():
assert "JOHN DOE" == transform_name(" JOHN DOE ")
assert "JOHN DOE" == transform_name(" John Doe3 ")
def test_transform_phone():
assert "0123456789" == transform_phone("0123456789")
assert "0123456789" == transform_phone("(012)345-6789")
assert transform_phone("345-6789") is None
| 30.785714
| 59
| 0.740139
| 55
| 431
| 5.563636
| 0.363636
| 0.228758
| 0.117647
| 0.150327
| 0.444444
| 0.444444
| 0
| 0
| 0
| 0
| 0
| 0.13079
| 0.148492
| 431
| 13
| 60
| 33.153846
| 0.702997
| 0
| 0
| 0
| 0
| 0
| 0.204176
| 0
| 0
| 0
| 0
| 0
| 0.555556
| 1
| 0.222222
| true
| 0
| 0.222222
| 0
| 0.444444
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05527b69f8cbd606816c8a5a32074c305e9fbb73
| 258
|
py
|
Python
|
aps/admin.py
|
themobilecompany/Bullfrog
|
a13ff0ccaec6887f839cf58435220264fde8df24
|
[
"MIT"
] | 1
|
2017-06-06T07:21:02.000Z
|
2017-06-06T07:21:02.000Z
|
aps/admin.py
|
themobilecompany/Bullfrog
|
a13ff0ccaec6887f839cf58435220264fde8df24
|
[
"MIT"
] | null | null | null |
aps/admin.py
|
themobilecompany/Bullfrog
|
a13ff0ccaec6887f839cf58435220264fde8df24
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Person
from .models import Circle
from .models import Role
from .models import RoleFiller
admin.site.register(Person)
admin.site.register(Circle)
admin.site.register(Role)
admin.site.register(RoleFiller)
| 23.454545
| 32
| 0.821705
| 37
| 258
| 5.72973
| 0.324324
| 0.188679
| 0.301887
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096899
| 258
| 11
| 33
| 23.454545
| 0.909871
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.555556
| 0
| 0.555556
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
0555563c511d848420d5f54b06149304608ec5e9
| 315
|
py
|
Python
|
gvm/language/__init__.py
|
alurin/gvm
|
03feca42c2ab56f26a7167b4a07213ce5c0fbdb4
|
[
"MIT"
] | null | null | null |
gvm/language/__init__.py
|
alurin/gvm
|
03feca42c2ab56f26a7167b4a07213ce5c0fbdb4
|
[
"MIT"
] | null | null | null |
gvm/language/__init__.py
|
alurin/gvm
|
03feca42c2ab56f26a7167b4a07213ce5c0fbdb4
|
[
"MIT"
] | null | null | null |
# Copyright (C) 2019-2020 Vasiliy Sheredeko
#
# This software may be modified and distributed under the terms
# of the MIT license. See the LICENSE file for details.
from gvm.language.grammar import Grammar, SymbolID, TokenID, ParseletID
from gvm.language.scanner import Scanner, DefaultScanner, IndentationScanner
| 45
| 76
| 0.809524
| 43
| 315
| 5.930233
| 0.790698
| 0.054902
| 0.117647
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.029304
| 0.133333
| 315
| 6
| 77
| 52.5
| 0.904762
| 0.498413
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
05688790794410d8d64c49cb76b8e6088947f708
| 5,731
|
py
|
Python
|
src/python/tests/unittests/test_common/test_multiprocessing_logger.py
|
annihilatethee/seedsync
|
7a0ba915cc570bc12916088baa6eb6bee6f291c9
|
[
"Apache-2.0"
] | 255
|
2017-12-25T00:53:40.000Z
|
2022-03-27T10:29:21.000Z
|
src/python/tests/unittests/test_common/test_multiprocessing_logger.py
|
annihilatethee/seedsync
|
7a0ba915cc570bc12916088baa6eb6bee6f291c9
|
[
"Apache-2.0"
] | 111
|
2018-01-04T10:35:49.000Z
|
2022-03-29T15:12:52.000Z
|
src/python/tests/unittests/test_common/test_multiprocessing_logger.py
|
annihilatethee/seedsync
|
7a0ba915cc570bc12916088baa6eb6bee6f291c9
|
[
"Apache-2.0"
] | 53
|
2017-12-25T09:34:19.000Z
|
2022-03-15T17:53:27.000Z
|
# Copyright 2017, Inderpreet Singh, All rights reserved.
import unittest
import logging
import sys
import time
import multiprocessing
from testfixtures import LogCapture
import timeout_decorator
from common import MultiprocessingLogger
class TestMultiprocessingLogger(unittest.TestCase):
def setUp(self):
self.logger = logging.getLogger(TestMultiprocessingLogger.__name__)
handler = logging.StreamHandler(sys.stdout)
self.logger.addHandler(handler)
self.logger.setLevel(logging.DEBUG)
formatter = logging.Formatter("%(asctime)s - %(levelname)s - %(name)s - %(message)s")
handler.setFormatter(formatter)
@timeout_decorator.timeout(5)
def test_main_logger_receives_records(self):
def process_1(_mp_logger: MultiprocessingLogger):
logger = _mp_logger.get_process_safe_logger().getChild("process_1")
logger.debug("Debug line")
time.sleep(0.1)
logger.info("Info line")
time.sleep(0.1)
logger.warning("Warning line")
time.sleep(0.1)
logger.error("Error line")
mp_logger = MultiprocessingLogger(self.logger)
p_1 = multiprocessing.Process(target=process_1,
args=(mp_logger,))
with LogCapture("TestMultiprocessingLogger.MPLogger.process_1") as log_capture:
p_1.start()
mp_logger.start()
time.sleep(1)
p_1.join()
mp_logger.stop()
log_capture.check(
("process_1", "DEBUG", "Debug line"),
("process_1", "INFO", "Info line"),
("process_1", "WARNING", "Warning line"),
("process_1", "ERROR", "Error line")
)
@timeout_decorator.timeout(5)
def test_children_names(self):
def process_1(_mp_logger: MultiprocessingLogger):
logger = _mp_logger.get_process_safe_logger().getChild("process_1")
logger.debug("Debug line")
logger.getChild("child_1").debug("Debug line")
logger.getChild("child_1_1").debug("Debug line")
mp_logger = MultiprocessingLogger(self.logger)
p_1 = multiprocessing.Process(target=process_1,
args=(mp_logger,))
with LogCapture("TestMultiprocessingLogger.MPLogger.process_1") as log_capture:
p_1.start()
mp_logger.start()
time.sleep(1)
p_1.join()
mp_logger.stop()
log_capture.check(
("process_1", "DEBUG", "Debug line"),
("process_1.child_1", "DEBUG", "Debug line"),
("process_1.child_1_1", "DEBUG", "Debug line"),
)
@timeout_decorator.timeout(5)
def test_logger_levels(self):
def process_1(_mp_logger: MultiprocessingLogger):
logger = _mp_logger.get_process_safe_logger().getChild("process_1")
logger.debug("Debug line")
logger.info("Info line")
logger.warning("Warning line")
logger.error("Error line")
# Debug level
self.logger.setLevel(logging.DEBUG)
with LogCapture("TestMultiprocessingLogger.MPLogger.process_1") as log_capture:
mp_logger = MultiprocessingLogger(self.logger)
p_1 = multiprocessing.Process(target=process_1,
args=(mp_logger,))
p_1.start()
mp_logger.start()
time.sleep(0.2)
p_1.join()
mp_logger.stop()
log_capture.check(
("process_1", "DEBUG", "Debug line"),
("process_1", "INFO", "Info line"),
("process_1", "WARNING", "Warning line"),
("process_1", "ERROR", "Error line")
)
# Info level
self.logger.setLevel(logging.INFO)
with LogCapture("TestMultiprocessingLogger.MPLogger.process_1") as log_capture:
mp_logger = MultiprocessingLogger(self.logger)
p_1 = multiprocessing.Process(target=process_1,
args=(mp_logger,))
p_1.start()
mp_logger.start()
time.sleep(0.2)
p_1.join()
mp_logger.stop()
log_capture.check(
("process_1", "INFO", "Info line"),
("process_1", "WARNING", "Warning line"),
("process_1", "ERROR", "Error line")
)
# Warning level
self.logger.setLevel(logging.WARNING)
with LogCapture("TestMultiprocessingLogger.MPLogger.process_1") as log_capture:
mp_logger = MultiprocessingLogger(self.logger)
p_1 = multiprocessing.Process(target=process_1,
args=(mp_logger,))
p_1.start()
mp_logger.start()
time.sleep(0.2)
p_1.join()
mp_logger.stop()
log_capture.check(
("process_1", "WARNING", "Warning line"),
("process_1", "ERROR", "Error line")
)
# Error level
self.logger.setLevel(logging.ERROR)
with LogCapture("TestMultiprocessingLogger.MPLogger.process_1") as log_capture:
mp_logger = MultiprocessingLogger(self.logger)
p_1 = multiprocessing.Process(target=process_1,
args=(mp_logger,))
p_1.start()
mp_logger.start()
time.sleep(0.2)
p_1.join()
mp_logger.stop()
log_capture.check(
("process_1", "ERROR", "Error line")
)
| 36.503185
| 93
| 0.560635
| 583
| 5,731
| 5.284734
| 0.13036
| 0.09088
| 0.042843
| 0.03408
| 0.792924
| 0.738072
| 0.70172
| 0.664719
| 0.653684
| 0.653684
| 0
| 0.021293
| 0.32804
| 5,731
| 156
| 94
| 36.737179
| 0.778759
| 0.017972
| 0
| 0.75969
| 0
| 0
| 0.16133
| 0.046958
| 0
| 0
| 0
| 0
| 0
| 1
| 0.054264
| false
| 0
| 0.062016
| 0
| 0.124031
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
05747c6260b3b281351581caa02c0eb1953c3b48
| 98
|
py
|
Python
|
retweet/wsgi.py
|
adventuringImagineer/estimator-retweet-adventure
|
3c3ea925f38cd50870c6150a804014bfd07ca190
|
[
"MIT"
] | null | null | null |
retweet/wsgi.py
|
adventuringImagineer/estimator-retweet-adventure
|
3c3ea925f38cd50870c6150a804014bfd07ca190
|
[
"MIT"
] | null | null | null |
retweet/wsgi.py
|
adventuringImagineer/estimator-retweet-adventure
|
3c3ea925f38cd50870c6150a804014bfd07ca190
|
[
"MIT"
] | null | null | null |
from .app import app
# do some production specific things to the app
app.config["DEBUG"] = False
| 19.6
| 47
| 0.744898
| 16
| 98
| 4.5625
| 0.8125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173469
| 98
| 4
| 48
| 24.5
| 0.901235
| 0.459184
| 0
| 0
| 0
| 0
| 0.098039
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
557da8a78bcfb8395725531335231579a20c615a
| 128
|
py
|
Python
|
sample_app/actors/apps.py
|
inmagik/django-search-views
|
315cbe8e6cac158884ced02069aa945bc7438dba
|
[
"MIT"
] | 31
|
2016-10-01T15:41:02.000Z
|
2022-02-12T18:44:20.000Z
|
sample_app/actors/apps.py
|
bianchimro/django-search-views
|
315cbe8e6cac158884ced02069aa945bc7438dba
|
[
"MIT"
] | 8
|
2016-10-01T12:19:05.000Z
|
2019-09-30T09:33:47.000Z
|
sample_app/actors/apps.py
|
inmagik/django-search-views
|
315cbe8e6cac158884ced02069aa945bc7438dba
|
[
"MIT"
] | 6
|
2017-09-07T18:39:40.000Z
|
2021-08-30T06:45:20.000Z
|
from __future__ import unicode_literals
from django.apps import AppConfig
class ActorsConfig(AppConfig):
name = 'actors'
| 16
| 39
| 0.789063
| 15
| 128
| 6.4
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15625
| 128
| 7
| 40
| 18.285714
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0.046875
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
558f4b5dfe368365ee39dbd6359d748133a4fbca
| 3,947
|
py
|
Python
|
pong_easy.py
|
Yiluo-pHoton/Pong
|
385d9557759a1e730fc2b41b6a6019d669275399
|
[
"MIT"
] | 1
|
2017-12-31T02:00:59.000Z
|
2017-12-31T02:00:59.000Z
|
pong_easy.py
|
Yiluo-pHoton/Pong
|
385d9557759a1e730fc2b41b6a6019d669275399
|
[
"MIT"
] | 1
|
2017-12-27T17:06:44.000Z
|
2017-12-27T17:06:44.000Z
|
pong_easy.py
|
Yiluo-pHoton/Pong
|
385d9557759a1e730fc2b41b6a6019d669275399
|
[
"MIT"
] | null | null | null |
import Tkinter
import gameStatus
class Handler:
def __init__(self, game):
self.__game = game
# More get and set functions go below here
# WHY USE GET AND SET FUNCTIONS:
# Some fields should remain unaccessible by the user
# therefore unaccessible outside of this class.
# We call this kind of field private field.
# In Python, we can write it as __pos_x
# These fields can be accessed only through get and set functions,
# such as get_pos_x() and set_pos_x(parameter)
def get_game(self):
"stub"
def get_paddle(self, index):
"stub"
def get_ball(self):
"stub"
class Paddle:
# In the easy version of Pong game,
# this class is equivalent to the Player class.
def __init__(self, handler, position):
self.__handler = handler
# All the fields initiated by the constructor go below here
def judge_collision(self):
"stub"
def add_score(self):
"stub"
def move_left(self):
"stub"
def move_right(self):
"stub"
def render(self, canvas):
"stub"
def update(self):
"stub"
# More get and set functions go below here
# WHY USE GET AND SET FUNCTIONS:
# Some fields should remain unaccessible by the user
# therefore unaccessible outside of this class.
# We call this kind of field private field.
# In Python, we can write it as __pos_x
# These fields can be accessed only through get and set functions,
# such as get_pos_x() and set_pos_x(parameter)
def get_canvas_width(self):
"stub"
def get_canvas_height(self):
"stub"
def get_padding(self):
"stub"
def get_pos_y(self):
"stub"
class Ball:
def __init__(self, handler):
self.__handler = handler
# All the fields initiated by the constructor go below here
def judge_score(self):
"stub"
def hit(self):
"stub"
def render(self, canvas):
"stub"
def update(self):
"stub"
def get_canvas_width(self):
"stub"
def get_canvas_height(self):
"stub"
# More get and set functions go below here
# WHY USE GET AND SET FUNCTIONS:
# Some fields should remain unaccessible by the user
# therefore unaccessible outside of this class.
# We call this kind of field private field.
# In Python, we can write it as __pos_x
# These fields can be accessed only through get and set functions,
# such as get_pos_x() and set_pos_x(parameter)
def get_width(self):
return self.__width
def get_velocity_x(self):
return self.__velocity_x
def get_velocity_y(self):
return self.__velocity_y
class Game:
def __init__(self):
self.__handler = handler
# All the fields initiated by the constructor go below here
def start_new_game(self):
"stub"
def key_pressed_handler(self, event):
"stub"
def key_released_handler(self, event):
"stub"
def key_action(self):
"stub"
def render_score(self):
"stub"
def render(self):
"stub"
def update(self):
"stub"
def run(self):
"stub"
# More get and set functions go below here
# WHY USE GET AND SET FUNCTIONS:
# Some fields should remain unaccessible by the user
# therefore unaccessible outside of this class.
# We call this kind of field private field.
# In Python, we can write it as __pos_x
# These fields can be accessed only through get and set functions,
# such as get_pos_x() and set_pos_x(parameter)
def set_game_status(self, game_status):
"stub"
def get_game_status(self):
"stub"
def get_canvas_width(self):
"stub"
def get_canvas_height(self):
"stub"
if __name__ == "__main__":
my_game = Game()
my_game.run()
my_game.frame.mainloop()
| 22.683908
| 70
| 0.633392
| 553
| 3,947
| 4.318264
| 0.177215
| 0.083752
| 0.087521
| 0.090452
| 0.722781
| 0.713987
| 0.682161
| 0.682161
| 0.682161
| 0.682161
| 0
| 0
| 0.292881
| 3,947
| 173
| 71
| 22.815029
| 0.855607
| 0.467444
| 0
| 0.523256
| 0
| 0
| 0.059459
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.44186
| false
| 0
| 0.023256
| 0.034884
| 0.546512
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
559341c75374ea6e3677a1dccde11d84cacca3b3
| 135
|
py
|
Python
|
{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/context_processors.py
|
oddbird/sfdo-template
|
ac128ca5b2db18d3069a1535cb6ac23f83aa987f
|
[
"BSD-3-Clause"
] | 3
|
2018-08-23T18:59:59.000Z
|
2021-05-25T00:05:52.000Z
|
{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/context_processors.py
|
oddbird/sfdo-template
|
ac128ca5b2db18d3069a1535cb6ac23f83aa987f
|
[
"BSD-3-Clause"
] | 9
|
2018-09-28T21:30:35.000Z
|
2020-08-10T20:42:34.000Z
|
{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/context_processors.py
|
oddbird/sfdo-template
|
ac128ca5b2db18d3069a1535cb6ac23f83aa987f
|
[
"BSD-3-Clause"
] | 2
|
2019-03-28T05:03:08.000Z
|
2019-05-05T18:10:30.000Z
|
from django.conf import settings
def env(request):
GLOBALS = {"SENTRY_DSN": settings.SENTRY_DSN}
return {"GLOBALS": GLOBALS}
| 19.285714
| 49
| 0.711111
| 17
| 135
| 5.529412
| 0.705882
| 0.191489
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.17037
| 135
| 6
| 50
| 22.5
| 0.839286
| 0
| 0
| 0
| 0
| 0
| 0.125926
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
e974a8af2a36fd2e6f2f0ee548b8c2b6659b4a2f
| 168
|
py
|
Python
|
factory-ai-vision/OVMSAdaptorEdgeSolution/send_config.py
|
michellechena/azure-intelligent-edge-patterns
|
b1260b962b208880532391e7ef2148d240f489f8
|
[
"MIT"
] | null | null | null |
factory-ai-vision/OVMSAdaptorEdgeSolution/send_config.py
|
michellechena/azure-intelligent-edge-patterns
|
b1260b962b208880532391e7ef2148d240f489f8
|
[
"MIT"
] | null | null | null |
factory-ai-vision/OVMSAdaptorEdgeSolution/send_config.py
|
michellechena/azure-intelligent-edge-patterns
|
b1260b962b208880532391e7ef2148d240f489f8
|
[
"MIT"
] | null | null | null |
import json
import requests
j = json.load(open('voe_config.json'))
js = json.dumps(j)
requests.post('http://YOUR_DEVICE_IP:8585/set_voe_config', json={'config': js})
| 21
| 79
| 0.732143
| 28
| 168
| 4.214286
| 0.607143
| 0.152542
| 0.220339
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026144
| 0.089286
| 168
| 7
| 80
| 24
| 0.745098
| 0
| 0
| 0
| 0
| 0
| 0.369048
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
e98c44929a46d22e081d3db767ec47b015a7a80e
| 348
|
py
|
Python
|
dev/script.py
|
zmoitier/accoster
|
648b9edf7e73848eacb60af0885be4d30fdbbafc
|
[
"MIT"
] | null | null | null |
dev/script.py
|
zmoitier/accoster
|
648b9edf7e73848eacb60af0885be4d30fdbbafc
|
[
"MIT"
] | 5
|
2020-12-04T21:17:00.000Z
|
2020-12-06T19:54:36.000Z
|
dev/script.py
|
zmoitier/accoster
|
648b9edf7e73848eacb60af0885be4d30fdbbafc
|
[
"MIT"
] | 1
|
2020-11-18T17:24:52.000Z
|
2020-11-18T17:24:52.000Z
|
from sys import argv
import matplotlib.pyplot as plt
import numpy as np
import claudius_dev as claudius
obs = claudius.create_obstacle("Disk", "Penetrable", [1, 2], [1, 2], [3, 4])
print(obs)
print(obs.sig_rho[0][0](np.zeros(5)))
print(obs.sig_rho[0][1](np.zeros(5)))
print(obs.sig_rho[1][0](np.zeros(5)))
print(obs.sig_rho[1][1](np.zeros(5)))
| 23.2
| 76
| 0.692529
| 68
| 348
| 3.455882
| 0.397059
| 0.170213
| 0.187234
| 0.238298
| 0.365957
| 0.297872
| 0.297872
| 0.297872
| 0
| 0
| 0
| 0.057508
| 0.100575
| 348
| 14
| 77
| 24.857143
| 0.693291
| 0
| 0
| 0
| 0
| 0
| 0.04023
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0.5
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
|
0
| 4
|
e9bbe4c979028541c6c61168eebf0fa55bb82f8c
| 6,116
|
py
|
Python
|
tests/test_cellpy_cmd.py
|
streamengineer/cellpy
|
59a83065297ce0ba370fc11181085c98f587101e
|
[
"MIT"
] | 38
|
2016-08-16T10:54:56.000Z
|
2022-03-03T04:43:20.000Z
|
tests/test_cellpy_cmd.py
|
Ozzstein/cellpy
|
ee532905741db4cb928303d75426d2a4fa77144a
|
[
"MIT"
] | 88
|
2016-08-16T13:10:27.000Z
|
2022-03-29T10:36:39.000Z
|
tests/test_cellpy_cmd.py
|
Ozzstein/cellpy
|
ee532905741db4cb928303d75426d2a4fa77144a
|
[
"MIT"
] | 13
|
2019-01-02T03:57:52.000Z
|
2022-01-19T08:06:49.000Z
|
import click
from click.testing import CliRunner
import pytest
from cellpy import log
from cellpy import prms
import cellpy
from cellpy import cli, prmreader
NUMBER_OF_DIRS = 9
def test_get_user_name():
u = prmreader.get_user_name()
print(f"\ncurrent username: {u}")
def test_get_user_dir_and_dst():
user_dir, dst_file = prmreader.get_user_dir_and_dst("filename.conf")
print(f"\nuserdir: {user_dir}")
def test_create_custom_init_filename():
u = prmreader.create_custom_init_filename()
print(f"\ncustom config-file-name: {u}")
def test_get_package_prm_dir():
u = cli.get_package_prm_dir()
print(f"\npackage directory: {u}")
def test_info_version():
runner = CliRunner()
result = runner.invoke(cli.cli, ["info", "--version"])
print(result.output)
assert result.exit_code == 0
assert f"[cellpy] version: {cellpy.__version__}" in result.output
def test_info_configloc():
runner = CliRunner()
result = runner.invoke(cli.cli, ["info", "--configloc"])
print()
print(result.output)
assert result.exit_code == 0
assert "conf" in result.output
def test_info_no_option():
runner = CliRunner()
result = runner.invoke(cli.cli, ["info"])
print()
print(result.output)
assert result.exit_code == 0
def test_info_help():
runner = CliRunner()
result = runner.invoke(cli.cli, ["info", "--help"])
print()
print(result.output)
assert result.exit_code == 0
assert "--help" in result.output
def test_info_params():
runner = CliRunner()
result = runner.invoke(cli.cli, ["info", "--params"])
print("\n", result.output)
assert result.exit_code == 0
assert "prms.Paths.outdatadir" in result.output
def test_info_check():
runner = CliRunner()
result = runner.invoke(cli.cli, ["info", "--check"])
print("\n", result.output)
assert result.exit_code == 0
@pytest.mark.slowtest
def test_pull_tests(tmp_path):
runner = CliRunner()
opts = list()
opts.append("pull")
opts.append("--tests")
opts.append("--directory")
opts.append(tmp_path)
opts.append("--password")
opts.append("env")
result = runner.invoke(cli.cli, opts)
print("\n", result.output)
if result.exception:
print(result.exception)
assert result.exception.status == 403
else:
assert result.exit_code == 0
@pytest.mark.slowtest
def test_pull_examples(tmp_path):
import github
runner = CliRunner()
opts = list()
opts.append("pull")
opts.append("--examples")
opts.append("--directory")
opts.append(tmp_path)
opts.append("--password")
opts.append("env")
result = runner.invoke(cli.cli, ["pull", "--examples"])
print("\n", result.output)
if result.exception:
print(result.exception)
assert result.exception.status == 403
else:
assert result.exit_code == 0
@pytest.mark.slowtest
def test_pull_clone():
runner = CliRunner()
result = runner.invoke(cli.cli, ["pull", "--clone"])
print("\n", result.output)
assert result.exit_code == 0
@pytest.mark.slowtest
def test_pull_custom_dir():
runner = CliRunner()
result = runner.invoke(cli.cli, ["pull", "--clone", "--directory", "MyDir"])
print("\n", result.output)
assert result.exit_code == 0
@pytest.mark.slowtest
def test_pull_help():
runner = CliRunner()
result = runner.invoke(cli.cli, ["pull", "--help"])
print("\n", result.output)
assert result.exit_code == 0
def test_run_help():
runner = CliRunner()
result = runner.invoke(cli.cli, ["run", "--help"])
print("\n", result.output)
assert result.exit_code == 0
def test_run_empty():
runner = CliRunner()
result = runner.invoke(cli.cli, ["run"])
print("\n", result.output)
assert result.exit_code != 0
def test_run():
name = "20190210_cell001_cc_01.h5"
runner = CliRunner()
result = runner.invoke(cli.cli, ["run", name])
print("\n", result.output)
assert result.exit_code == 0
def test_run_debug():
name = "20190210_cell001_cc_01.h5"
runner = CliRunner()
result = runner.invoke(cli.cli, ["run", "--debug", name])
print("\n", result.output)
assert result.exit_code == 0
def test_run_journal():
name = "20190210_cell001_cc_01.h5"
runner = CliRunner()
result = runner.invoke(cli.cli, ["run", "--journal", name])
print("\n", result.output)
assert result.exit_code == 0
def test_run_journal_silent():
name = "20190210_cell001_cc_01.h5"
runner = CliRunner()
result = runner.invoke(cli.cli, ["run", "--journal", "--silent", name])
print("\n", result.output)
assert result.exit_code == 0
def test_run_journal_debug():
name = "20190210_cell001_cc_01.h5"
runner = CliRunner()
result = runner.invoke(cli.cli, ["run", "--journal", "--debug", name])
print("\n", result.output)
assert result.exit_code == 0
def test_cli_help():
runner = CliRunner()
result = runner.invoke(cli.cli, ["--help"])
print("\n", result.output)
assert result.exit_code == 0
def test_cli_setup_help():
runner = CliRunner()
result = runner.invoke(cli.cli, ["setup", "--help"])
print("\n", result.output)
assert result.exit_code == 0
def test_cli_setup():
runner = CliRunner()
with runner.isolated_filesystem():
result = runner.invoke(cli.cli, ["setup", "--dry-run"])
print(result.output)
assert result.exit_code == 0
def test_cli_setup_interactive():
runner = CliRunner()
with runner.isolated_filesystem():
result = runner.invoke(
cli.cli, ["setup", "-i", "--dry-run"], input=NUMBER_OF_DIRS * "\n"
)
print(result.output)
assert result.exit_code == 0
def test_cli_setup_custom_dir():
runner = CliRunner()
with runner.isolated_filesystem():
result = runner.invoke(
cli.cli,
["setup", "-i", "--dry-run", "-d", "just_a_dir"],
input=NUMBER_OF_DIRS * "\n",
)
print(result.output)
assert result.exit_code == 0
| 24.861789
| 80
| 0.639143
| 790
| 6,116
| 4.76962
| 0.129114
| 0.050159
| 0.109873
| 0.128185
| 0.811571
| 0.803079
| 0.774151
| 0.774151
| 0.644374
| 0.570594
| 0
| 0.02058
| 0.205526
| 6,116
| 245
| 81
| 24.963265
| 0.754888
| 0
| 0
| 0.576087
| 0
| 0
| 0.113146
| 0.023872
| 0
| 0
| 0
| 0
| 0.157609
| 1
| 0.146739
| false
| 0.01087
| 0.043478
| 0
| 0.190217
| 0.173913
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
e9d0dd010aa6cf5e8e1f824f1424a88378325add
| 62
|
py
|
Python
|
django_covid19/__init__.py
|
zhangguoyuanshuai/Python-Covid19API
|
2c5f69a8eed16df4c04af5137fb5574ea5125ee5
|
[
"MIT"
] | 103
|
2020-05-07T06:13:25.000Z
|
2022-03-27T14:15:35.000Z
|
django_covid19/__init__.py
|
zhangguoyuanshuai/Python-Covid19API
|
2c5f69a8eed16df4c04af5137fb5574ea5125ee5
|
[
"MIT"
] | 13
|
2020-05-14T05:18:41.000Z
|
2022-03-02T14:53:44.000Z
|
django_covid19/__init__.py
|
zhangguoyuanshuai/Python-Covid19API
|
2c5f69a8eed16df4c04af5137fb5574ea5125ee5
|
[
"MIT"
] | 31
|
2020-05-17T13:24:09.000Z
|
2022-03-28T09:22:31.000Z
|
default_app_config = 'django_covid19.apps.DjangoCovid19Config'
| 62
| 62
| 0.887097
| 7
| 62
| 7.428571
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.066667
| 0.032258
| 62
| 1
| 62
| 62
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0.619048
| 0.619048
| 0
| 0
| 0
| 0
| 0
| 1
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| null | 0
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| 1
| 0
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0
| 4
|
758d4a1361d5a80859c87827f5f8df13a263b3ef
| 85,497
|
py
|
Python
|
greekAnalysisTools/shared/getResults.py
|
storey/seniorThesisCode
|
c388bdfe23cf0a25df4f92392bdd4065fb92dc93
|
[
"MIT"
] | 1
|
2017-07-07T04:54:14.000Z
|
2017-07-07T04:54:14.000Z
|
greekAnalysisTools/shared/getResults.py
|
storey/seniorThesisCode
|
c388bdfe23cf0a25df4f92392bdd4065fb92dc93
|
[
"MIT"
] | null | null | null |
greekAnalysisTools/shared/getResults.py
|
storey/seniorThesisCode
|
c388bdfe23cf0a25df4f92392bdd4065fb92dc93
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
# Code for getting the various results
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.backends.backend_pdf import PdfPages
from sklearn import decomposition
from sklearn import datasets
from sklearn import preprocessing
from sklearn.pipeline import make_pipeline
from sklearn.model_selection import cross_val_score
from sklearn.model_selection import ShuffleSplit
from sklearn.model_selection import KFold
from sklearn.feature_selection import SelectFromModel
from sklearn.linear_model import LassoCV
from sklearn import svm
from sklearn import linear_model
from sklearn import neighbors
from sklearn import ensemble
#from utils import getFeatureMatrixFn, getFinalResultsOutputDir
import utils
import json
import copy
# empty class for creating constants
class Constant:
pass
class Dataset:
def __init__(self, data, target):
self.data = data
self.target = target
# a variety of data sets
DATA_SETS = Constant()
# example datasets from scikitlearn
DATA_SETS.DIGITS = "digits" # digits
DATA_SETS.FLOWERS = "flowers" # flowers (iris)
DATA_SETS.FLOWERS_BI = "flowers_2_types" # flowers with only two types
DATA_SETS.ILIAD_ODYSSEY = "iliad_odyssey_only" # only the iliad and the odyssey
DATA_SETS.DIONYSIACA_SPLIT = "dionysiaca_split" # split the dionysiaca into the first and second halves
DATA_SETS.AUTHORS_SPLIT = "authors_split" # look at Cyngetica vs Halieutica
DATA_SETS.ILIAD_ODYSSEY_NO_TARGET = "iliad_odyssey_only_no_target" # the iliad and odyssey with no information about which book is which type.
DATA_SETS.BOOKS_ONLY = "books_only" # only look at the individual books
DATA_SETS.ALL_OVERALLS = "all_overalls" # all the overall texts, no books
DATA_SETS.ALL_OVERALLS_SUB_BOOKS = "all_overalls_test_books" # train on overall books, view data with text books
DATA_SETS.CLOSER_ONLY = "closer_only" # remove dionysiaca, abduciton of helen, hymn 1,
DATA_SETS.CLOSER_ONLY_HERMES_LOOK = "closer_only_hymns" # remove dionysiaca, abduction of helen, hymn 1, plus only show the sub-books of the hymns
DATA_SETS.CLOSER_ONLY_HERMES_LOOK_DIONYSIACA_AS_TEST = "closer_only_hymns_dio_as_test"# look at dionysiaca, moschus, bion, but don't train on it
DATA_SETS.CLOSER_ONLY_HERMES_LOOK_DIONYSIACA_AS_TEST_1 = "closer_only_hymns_dio_as_test_1"# look at dionysiaca, moschus, bion, abduction of helen, taking of ilios but don't train on it
# these train on only overall
DATA_SETS.HOMER_HESIOD_AND_THE_HYMNS = "homer_hesiod_hymns"
DATA_SETS.HOMER_TEST_HESIOD_AND_THE_HYMNS = "homer_test_hesiod_hymns"
DATA_SETS.HOMER_AND_THE_HYMNS = "homer_hymns"
# these train on books as well
DATA_SETS.HOMER_HESIOD_AND_THE_HYMNS_ALL = "homer_hesiod_hymns_all"
DATA_SETS.HOMER_TEST_HESIOD_AND_THE_HYMNS_ALL = "homer_test_hesiod_hymns_all"
DATA_SETS.HOMER_AND_THE_HYMNS_ALL = "homer_hymns_all"
# a variety of subdata sets; for now we only use 3 and 6
# remove some unneeded texts, train on all texts and books, but don't label the books
DATA_SETS.CLASSIFY_3 = "classify_3"
# remove some unneeded texts, train on all texts and books, label the books
DATA_SETS.CLASSIFY_6 = "classify_6"
DATA_SETS.CLASSIFY_1 = "classify_1"
DATA_SETS.CLASSIFY_2 = "classify_2"
DATA_SETS.CLASSIFY_4 = "classify_4"
DATA_SETS.CLASSIFY_5 = "classify_5"
# get the data for a given name
# see explanations of what they are above.
def getData(dataName):
def generalGrab(func):
data = []
target = []
names = []
testData = []
testTarget = []
testNames = []
fName = utils.getFeatureMatrixFn()
matrixStorage = utils.getContent(fName, True)
oldNames = matrixStorage["rowNames"]
matrixData = matrixStorage["matrix"]
for i in range(len(oldNames)):
split = oldNames[i].split(": ")
skip, isTest, includeName, targetVal = func(oldNames[i], split[0], split[1])
if skip:
continue
if isTest:
testData.append(matrixData[i])
testTarget.append(targetVal)
if (includeName):
myName = oldNames[i]
else:
myName = ""
testNames.append(myName)
else:
data.append(matrixData[i])
target.append(targetVal)
if (includeName):
myName = oldNames[i]
else:
myName = ""
names.append(myName)
npData = np.array(data)
npTarget = np.array(target)
res = Dataset(npData, npTarget)
npData = np.array(testData)
npTarget = np.array(testTarget)
testRes = Dataset(npData, npTarget)
return res, names, testRes, testNames
if (dataName == DATA_SETS.DIGITS):
# data, which is the features
# target, which is the target (e.g. the class of the source)
digits = datasets.load_digits()
names = []
for i in range(len(digits.data)):
names.append("Digit " + str(i))
testData = []
testTarget = []
testNames = []
npData = np.array(testData)
npTarget = np.array(testTarget)
testRes = Dataset(npData, npTarget)
return digits, names, testRes, testNames
if (dataName == DATA_SETS.FLOWERS):
# data, which is the features
# target, which is the target (e.g. the class of the source)
iris = datasets.load_iris()
names = []
for i in range(len(iris.data)):
names.append("Flower " + str(i))
testData = []
testTarget = []
testNames = []
npData = np.array(testData)
npTarget = np.array(testTarget)
testRes = Dataset(npData, npTarget)
return iris, names, testRes, testNames
elif (dataName == DATA_SETS.FLOWERS_BI):
# data, which is the features
# target, which is the target (e.g. the class of the source)
iris = datasets.load_iris()
t = iris.target
d = iris.data
data = []
target = []
names = []
testData = []
testTarget = []
testNames = []
for i in range(len(t)):
if (t[i] != 2):
names.append("Flower " + str(i))
data.append(d[i])
target.append(t[i])
npData = np.array(data)
npTarget = np.array(target)
res = Dataset(npData, npTarget)
npData = np.array(testData)
npTarget = np.array(testTarget)
testRes = Dataset(npData, npTarget)
return res, names, testRes, testNames
elif (dataName == DATA_SETS.ILIAD_ODYSSEY):
def func(name, textName, subName):
# skip
if (subName == "Overall") or (textName != "Iliad" and textName != "Odyssey"):
return True, False, False, 0
# non test data
else:
isTestData = False
showNames = True
if (textName == "Iliad"):
targetVal = 0
else: #odyssey
targetVal = 1
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.DIONYSIACA_SPLIT):
def func(name, textName, subName):
# skip
if (subName == "Overall") or (textName != "Dionysiaca"):
return True, False, False, 0
# non test data
else:
isTestData = False
showNames = True
if (int(subName.split("Book ")[1]) <= 24):
targetVal = 0
else: #second half
targetVal = 1
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.AUTHORS_SPLIT):
def func(name, textName, subName):
# skip
if (subName == "Overall") or (textName != "Dionysiaca" and textName != "Fall of Troy"):
return True, False, False, 0
# non test data
else:
isTestData = False
showNames = True
if (textName == "Dionysiaca"):
targetVal = 0
else: #fall of troy
targetVal = 1
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.ILIAD_ODYSSEY_NO_TARGET):
def func(name, textName, subName):
# skip
if (subName == "Overall") or (textName != "Iliad" and textName != "Odyssey"):
return True, False, False, 0
# non test data
else:
isTestData = False
showNames = True
targetVal = 0
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.BOOKS_ONLY):
def func(name, textName, subName):
# skip
if (subName == "Overall"):
return True, False, False, 0
# non test data
else:
isTestData = False
showNames = True
targetVal = 0
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.ALL_OVERALLS):
def func(name, textName, subName):
testStr = "Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (subName != "Overall"):
return True, False, False, 0
# non test data
else:
isTestData = False
showNames = True
targetVal = 2
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.ALL_OVERALLS_SUB_BOOKS):
def func(name, textName, subName):
testStr = "Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1):
return True, False, False, 0
# test data
if (subName != "Overall"):
isTestData = True
showNames = True#False
if textName == "Iliad":
targetVal = 0
return False, isTestData, showNames, targetVal
elif textName == "Odyssey":
targetVal = 1
return False, isTestData, showNames, targetVal
elif textName == "HymnsLong":
targetVal = 2
return False, isTestData, showNames, targetVal
elif textName == "Dionysiaca":
targetVal = 7
return False, isTestData, showNames, targetVal
elif textName == "Argonautica":
targetVal = 5
return False, isTestData, showNames, targetVal
else:
targetVal = 8
return False, isTestData, showNames, targetVal
# non test data
else:
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
targetVal = 3
elif textName == "CallimachusHymns":
targetVal = 5
elif textName == "Idylls_Eidulia":
targetVal = 5
elif textName == "Cynegetica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Halieutica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Fall of Troy":
targetVal = 8 # Quintus was 4th? century ad greco-roman
elif textName == "The Taking of Ilios":
targetVal = 8 # Roman
elif textName == "Dionysiaca":
targetVal = 7
elif textName == "Argonautica":
targetVal = 5 # alexandrian, sure
elif textName == "Phaenomena":
targetVal = 8
elif textName == "Idylls":
targetVal = 5
elif textName == "Works of Bion":
targetVal = 8 # a little after Alexandria, 1/2 bc
elif textName == "Works of Moschus":
targetVal = 8 # a little after Alexandria, 2 bc
isTestData = False
showNames = True
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLOSER_ONLY):
def func(name, textName, subName):
testStr = "Dionysiaca, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (subName != "Overall"):
isTestData = True
showNames = True
if textName == "Iliad":
targetVal = 1
return False, isTestData, showNames, targetVal
elif textName == "Odyssey":
targetVal = 2
return False, isTestData, showNames, targetVal
elif textName == "HymnsLong":
targetVal = 3
return False, isTestData, showNames, targetVal
elif textName == "Dionysiaca":
targetVal = 4
return False, isTestData, showNames, targetVal
elif textName == "Argonautica":
targetVal = 5
return False, isTestData, showNames, targetVal
else:
targetVal = 0
return False, isTestData, showNames, targetVal
# non test data
else:
isTestData = False
showNames = True
targetVal = 2
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLOSER_ONLY_HERMES_LOOK):
def func(name, textName, subName):
testStr = "Dionysiaca, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (subName != "Overall"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
else:
# skip
return True, False, False, 0
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
targetVal = 3
elif textName == "CallimachusHymns":
targetVal = 5
elif textName == "Idylls_Eidulia":
targetVal = 5
elif textName == "Cynegetica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Halieutica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Fall of Troy":
targetVal = 8 # Quintus was 4th? century ad greco-roman
elif textName == "The Taking of Ilios":
targetVal = 8 # Roman
elif textName == "Argonautica":
targetVal = 5 # alexandrian, sure
elif textName == "Phaenomena":
targetVal = 8 # alexandrian, sure
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLOSER_ONLY_HERMES_LOOK_DIONYSIACA_AS_TEST):
def func(name, textName, subName):
testStr = "Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (subName != "Overall" or textName == "Dionysiaca"
or textName == "Works of Moschus" or textName == "Works of Bion"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "Dionysiaca":
showNames = False
targetVal = 7
elif textName == "Abduction of Helen":
showNames = True
targetVal = 8
elif textName == "Cynegetica":
showNames = True
targetVal = 8
elif textName == "Halieutica":
showNames = True
targetVal = 8
elif textName == "Fall of Troy":
showNames = True
targetVal = 8
elif textName == "The Taking of Ilios":
showNames = True
targetVal = 8 # Roman
elif textName == "Works of Bion":
showNames = True
targetVal = 8 # a little after Alexandria, 1/2 bc
elif textName == "Works of Moschus":
showNames = True
targetVal = 8 # a little after Alexandria, 2 bc
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
targetVal = 3
elif textName == "CallimachusHymns":
targetVal = 5
elif textName == "Idylls_Eidulia":
targetVal = 5
elif textName == "Cynegetica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Halieutica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Fall of Troy":
targetVal = 8 # Quintus was 4th? century ad greco-roman
elif textName == "The Taking of Ilios":
targetVal = 8 # Roman
elif textName == "Dionysiaca":
targetVal = 7
elif textName == "Argonautica":
targetVal = 5 # alexandrian, sure
elif textName == "Phaenomena":
targetVal = 8 # alexandrian, sure
elif textName == "Idylls":
targetVal = 5
elif textName == "Works of Bion":
targetVal = 8 # a little after Alexandria, 1/2 bc
elif textName == "Works of Moschus":
targetVal = 8 # a little after Alexandria, 2 bc
elif textName == "Abduction of Helen":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLOSER_ONLY_HERMES_LOOK_DIONYSIACA_AS_TEST_1):
def func(name, textName, subName):
testStr = "Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (subName != "Overall" or textName == "Dionysiaca"
or textName == "Works of Moschus" or textName == "Works of Bion"
or textName == "Abduction of Helen" or textName == "The Taking of Ilios"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "Dionysiaca":
showNames = False
targetVal = 7
elif textName == "Abduction of Helen":
showNames = True
targetVal = 8
elif textName == "Cynegetica":
showNames = True
targetVal = 8
elif textName == "Halieutica":
showNames = True
targetVal = 8
elif textName == "Fall of Troy":
showNames = True
targetVal = 8
elif textName == "The Taking of Ilios":
showNames = True
targetVal = 8 # Roman
elif textName == "Works of Bion":
showNames = True
targetVal = 8 # a little after Alexandria, 1/2 bc
elif textName == "Works of Moschus":
showNames = True
targetVal = 8 # a little after Alexandria, 2 bc
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
targetVal = 3
elif textName == "CallimachusHymns":
targetVal = 5
elif textName == "Idylls_Eidulia":
targetVal = 5
elif textName == "Cynegetica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Halieutica":
targetVal = 8 # oppian was 1st/2nd century ad greco-roman
elif textName == "Fall of Troy":
targetVal = 8 # Quintus was 4th? century ad greco-roman
elif textName == "The Taking of Ilios":
targetVal = 8 # Roman
elif textName == "Dionysiaca":
targetVal = 7
elif textName == "Argonautica":
targetVal = 5 # alexandrian, sure
elif textName == "Phaenomena":
targetVal = 8 # alexandrian, sure
elif textName == "Idylls":
targetVal = 5
elif textName == "Works of Bion":
targetVal = 8 # a little after Alexandria, 1/2 bc
elif textName == "Works of Moschus":
targetVal = 8 # a little after Alexandria, 2 bc
elif textName == "Abduction of Helen":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.HOMER_HESIOD_AND_THE_HYMNS):
def func(name, textName, subName):
testStr = "Cynegetica, Halieutica, Fall of Troy, The Taking of Ilios, Dionysiaca, Argonautica, Phaenomena, Idylls, Works of Bion, Works of Moschus, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (subName != "Overall" or textName == "CallimachusHymns"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "CallimachusHymns":
showNames = True
targetVal = 8
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
targetVal = 3
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "CallimachusHymns":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.HOMER_AND_THE_HYMNS):
def func(name, textName, subName):
testStr = "Cynegetica, Halieutica, Fall of Troy, The Taking of Ilios, Dionysiaca, Argonautica, Phaenomena, Idylls, Works of Bion, Works of Moschus, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (subName != "Overall" or textName == "CallimachusHymns" or textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
showNames = True
targetVal = 3
elif textName == "CallimachusHymns":
showNames = True
targetVal = 8
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "CallimachusHymns":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.HOMER_TEST_HESIOD_AND_THE_HYMNS):
def func(name, textName, subName):
testStr = "Cynegetica, Halieutica, Fall of Troy, The Taking of Ilios, Dionysiaca, Argonautica, Phaenomena, Idylls, Works of Bion, Works of Moschus, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (subName != "Overall" or textName == "CallimachusHymns" or textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony" or textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
showNames = True
targetVal = 3
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "CallimachusHymns":
showNames = True
targetVal = 8
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "CallimachusHymns":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.HOMER_HESIOD_AND_THE_HYMNS_ALL):
def func(name, textName, subName):
testStr = "Cynegetica, Halieutica, Fall of Troy, The Taking of Ilios, Dionysiaca, Argonautica, Phaenomena, Idylls, Works of Bion, Works of Moschus, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (textName == "CallimachusHymns"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "CallimachusHymns":
showNames = True
targetVal = 8
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
targetVal = 3
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "CallimachusHymns":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.HOMER_AND_THE_HYMNS_ALL):
def func(name, textName, subName):
testStr = "Cynegetica, Halieutica, Fall of Troy, The Taking of Ilios, Dionysiaca, Argonautica, Phaenomena, Idylls, Works of Bion, Works of Moschus, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (textName == "CallimachusHymns" or textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
showNames = True
targetVal = 3
elif textName == "CallimachusHymns":
showNames = True
targetVal = 8
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
targetVal = 2
elif textName == "CallimachusHymns":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.HOMER_TEST_HESIOD_AND_THE_HYMNS_ALL):
def func(name, textName, subName):
testStr = "Cynegetica, Halieutica, Fall of Troy, The Taking of Ilios, Dionysiaca, Argonautica, Phaenomena, Idylls, Works of Bion, Works of Moschus, Abduction of Helen, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# test data
if (textName == "CallimachusHymns" or textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony" or textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong"):
isTestData = True
if textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "Iliad":
showNames = False
targetVal = 0
elif textName == "Odyssey":
showNames = False
targetVal = 1
elif textName == "Works and Days" or textName == "Shield of Heracles" or textName == "Theogony":
showNames = True
targetVal = 3
elif textName == "Hymns" or textName == "HymnsShort" or textName == "HymnsLong":
showNames = True
targetVal = 2
elif textName == "CallimachusHymns":
showNames = True
targetVal = 8
else:
# skip
return True, False, False, 8
return False, isTestData, showNames, targetVal
#
else:
isTestData = False
showNames = True
targetVal = 8
# When we have 8:
# 0 is red, 1 is blue, 2 is green, 3 is purple, 4 is orange
# 5 is yellow, six is brown, 7 is pink, 8 is gray
if textName == "Iliad":
targetVal = 0
elif textName == "Odyssey":
targetVal = 1
elif textName == "CallimachusHymns":
targetVal = 8
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLASSIFY_1):
def func(name, textName, subName):
testStr = "Hymns, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# don't include the overall for things we have subdivided
if (textName == "Iliad" or textName == "Odyssey"
or textName == "HymnsLong" or textName == "Dionysiaca"
or textName == "Argonautica") and subName == "Overall":
return True, False, False, 0
if textName == "Iliad" or textName == "Odyssey":
targetVal = 1
else:
targetVal = 0
isTestData = False
showNames = True
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLASSIFY_2):
def func(name, textName, subName):
testStr = "HymnsLong, HymnsShort, Hymns, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# don't include the overall for things we have subdivided
if (textName == "Iliad" or textName == "Odyssey"
or textName == "HymnsLong" or textName == "Dionysiaca"
or textName == "Argonautica") and subName == "Overall":
return True, False, False, 0
if (textName != "Iliad" and textName != "Odyssey"
and textName != "Dionysiaca"):
return True, False, False, 0
if textName == "Iliad" or textName == "Odyssey":
targetVal = 1
else:
targetVal = 0
isTestData = False
showNames = True
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLASSIFY_3):
def func(name, textName, subName):
#Works and Days, Theogony, Shield of Heracles, HymnsLong, HymnsShort,
testStr = "Hymns, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# don't include the overall for things we have subdivided
if ((textName == "Iliad" or textName == "Odyssey"
or textName == "HymnsLong" or textName == "Dionysiaca"
or textName == "Argonautica" or textName == "Cynegetica"
or textName == "Halieutica" or textName == "Fall of Troy")
and subName == "Overall"):
return True, False, False, 0
isTestData = False
showNames = True
if textName == "Dionysiaca":
showNames = False
if textName == "Iliad" or textName == "Odyssey":
showNames = False
targetVal = 1
else:
targetVal = 0
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLASSIFY_4):
def func(name, textName, subName):
#Works and Days, Theogony, Shield of Heracles, HymnsLong, HymnsShort,
testStr = "Hymns, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# don't include the overall for things we have subdivided
if (textName == "Iliad" or textName == "Odyssey"
or textName == "HymnsLong" or textName == "Dionysiaca"
or textName == "Argonautica") and subName == "Overall":
return True, False, False, 0
# skip
if (name == "HymnsLong: Book 5" or name == "HymnsLong: Book 3" or name == "Shield of Heracles: Overall" or name == "Idylls_Eidulia: Overall"):
return True, False, False, 0
if textName == "Iliad" or textName == "Odyssey":
targetVal = 1
else:
targetVal = 0
isTestData = False
showNames = True
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLASSIFY_5):
def func(name, textName, subName):
#Works and Days, Theogony, Shield of Heracles, HymnsLong, HymnsShort,
testStr = "Hymns, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# don't include the overall for things we have subdivided
if (textName == "Iliad" or textName == "Odyssey"
or textName == "HymnsLong" or textName == "Dionysiaca"
or textName == "Argonautica") and subName == "Overall":
return True, False, False, 0
# name == "Idylls_Eidulia: Overall"
if not(textName == "Iliad" or textName == "Odyssey" or name == "HymnsLong: Book 5" or name == "HymnsLong: Book 3" or name == "Shield of Heracles: Overall"):
return True, False, False, 0
isTestData = False
showNames = True
if textName == "Iliad" or textName == "Odyssey":
showNames = False
targetVal = 1
else:
targetVal = 0
return False, isTestData, showNames, targetVal
return generalGrab(func)
elif (dataName == DATA_SETS.CLASSIFY_6): # 3 but with names
def func(name, textName, subName):
#Works and Days, Theogony, Shield of Heracles, HymnsLong, HymnsShort,
testStr = "Hymns, Epitaphius Bios, Eros Drapeta, Europa, Megara, Idylls_Epigrams, Epithalamium Achillis et Deidameiae, Epitaphius Adonis, Fragmenta"
# skip
if (testStr.find(textName) != -1) or (name == "HymnsLong: Book 1"):
return True, False, False, 0
# don't include the overall for things we have subdivided
if ((textName == "Iliad" or textName == "Odyssey"
or textName == "HymnsLong" or textName == "Dionysiaca"
or textName == "Argonautica" or textName == "Cynegetica"
or textName == "Halieutica" or textName == "Fall of Troy")
and subName == "Overall"):
return True, False, False, 0
isTestData = False
showNames = True
if textName == "Iliad" or textName == "Odyssey":
targetVal = 1
else:
targetVal = 0
return False, isTestData, showNames, targetVal
return generalGrab(func)
return {"data": [], "target": []}, [], [], []
# run preprocessing before pca
# adapted from code by Manoj Kumar <mks542@nyu.edu>
def pcaPreprocess(X, X2, y, preprocessType, saveResults, saveDir):
fName = utils.getFeatureMatrixFn()
matrixStorage = utils.getContent(fName, True)
featureNames = matrixStorage["featureNames"]
if preprocessType > 0.0:
clf = LassoCV()
# .15 -> 29
# .25 -> 26
# .4 -> 25
# .6 -> 23
sfm = SelectFromModel(clf, threshold=preprocessType)
sfm.fit(X, y)
n_features = sfm.transform(X).shape[1]
indices = sfm.get_support(True)
newX = X[:,indices]
if len(X2) == 0 or X2.shape[0] == 0:
newX2 = X2
else:
newX2 = X2[:,indices]
newFeatureNames = np.array(featureNames)[indices]
if (saveResults):
output = []
output.append(str(indices.shape))
for nfn in newFeatureNames:
output.append(" " + nfn)
s = "\n".join(output)
filename = saveDir + "featuresChosenByPreprocessing.txt"
utils.safeWrite(filename, s)
return newX, newX2, newFeatureNames
return X, X2, featureNames
# do PCA down to 3 components, then visualize
# Portions of this adapted from code written by Gaël Varoquaux
# dataSet is the list of data to train on, with names as an array of names for those feature vectors
# testSet is the list of data to test on, with testNames as an array of names for those feature vectors
# includeNames is true if we want to print the names in the figure
# saveOutput is true if we want to save the feature to a file rather than view it
# preprocessType refers to the type of preprocessing to do
# (it is a float specifying the lasso feature selection cutoff, or 0 for no selection)
def pca3Viz(dataSet, names, testSet, testNames, includeNames, saveOutput, saveDir, preprocessType):
np.random.seed(5)
X = dataSet.data
y = dataSet.target
X2 = testSet.data
y2 = testSet.target
X, X2, _ = pcaPreprocess(X, X2, y, preprocessType, False, saveDir)
# set figure size
plt.clf()
if saveOutput:
fig = plt.figure()
fig.set_size_inches((11.), (8.5))
else:
fig = plt.figure(1, figsize=(8, 6))
# set 3d axes
ax = Axes3D(fig, rect=[0, 0, .95, 1], elev=48, azim=134)
# train PCA
plt.cla()
pca = decomposition.PCA(n_components=3)
pca.fit(X)
if (False):
for i in range(len(names)):
print names[i]
print pca.transform([X[i]])
print "---"
print pca.explained_variance_
cpts = pca.components_[0]
for i in range(len(cpts)):
if (cpts[i] < -0.014):
print "%d : %f" % (i, cpts[i])
for i in range(len(names)):
print names[i] + ": " + str(X[i][65])
# transform the training and test data
X = pca.transform(X)
if (len(testNames) > 0):
X2 = pca.transform(X2)
# get the final sets to display
if (len(testNames) > 0):
Xfinal = np.append(X, X2, axis=0)
yFinal = np.append(y, y2, axis=0)
namesFinal = np.append(names, testNames, axis=0)
else:
Xfinal = X
yFinal = y
namesFinal = names
# if we include names, print them
if (includeNames):
for i in range(len(Xfinal)):
name = namesFinal[i]
ax.text3D(Xfinal[i, 0], Xfinal[i, 1], (Xfinal[i, 2] + 0.01),
name,
horizontalalignment='center', size=8)
# plot the data.
ax.scatter(Xfinal[:, 0], Xfinal[:, 1], Xfinal[:, 2], c=yFinal, cmap=plt.get_cmap("Set1"))
ax.w_xaxis.set_ticklabels([])
ax.w_yaxis.set_ticklabels([])
ax.w_zaxis.set_ticklabels([])
# save or show the data
if saveOutput:
if includeNames:
labelText = "_labels"
else:
labelText = "_no_labels"
filename = saveDir + "pca3D" + labelText + ".pdf"
utils.check_and_create_path(filename)
pp = PdfPages(filename)
pp.savefig()
pp.close()
else:
plt.show()
# do PCA down to 2 components, then visualize
# Portions of this adapted from code written by Gaël Varoquaux
# dataSet is the list of data to train on, with names as an array of names for those feature vectors
# testSet is the list of data to test on, with testNames as an array of names for those feature vectors
# includeNames is true if we want to print the names in the figure
# saveOutput is true if we want to save the feature to a file rather than view it
# preprocessType refers to the type of preprocessing to do
# (it is a float specifying the lasso feature selection cutoff, or 0 for no selection)
# oneThree is true if we are examining axes 1 and 3 rather than 1 and 2
def pca2Viz(dataSet, names, testSet, testNames, includeNames, saveOutput, saveDir, preprocessType, oneThree):
np.random.seed(5)
X = dataSet.data
y = dataSet.target
X2 = testSet.data
y2 = testSet.target
X, X2, _ = pcaPreprocess(X, X2, y, preprocessType, False, saveDir)
# set figure size
plt.clf()
if saveOutput:
fig = plt.figure()
fig.set_size_inches((11.), (8.5))
else:
fig = plt.figure(1, figsize=(8, 6))
# get the proper axes to examine
if (oneThree):
ax0 = 0
ax1 = 2
numComponents = 3
else:
ax0 = 0
ax1 = 1
numComponents = 2
# train PCA and transform data
pca = decomposition.PCA(n_components=numComponents)
pca.fit(X)
X = pca.transform(X)
if (len(testNames) > 0):
X2 = pca.transform(X2)
# get the final sets to display
if (len(testNames) > 0):
Xfinal = np.append(X, X2, axis=0)
yFinal = np.append(y, y2, axis=0)
namesFinal = np.append(names, testNames, axis=0)
else:
Xfinal = X
yFinal = y
namesFinal = names
# if we include names, print them
if (includeNames):
for i in range(len(Xfinal)):
name = namesFinal[i]
plt.text(Xfinal[i, ax0], (Xfinal[i, ax1] + 0.01),
name,
horizontalalignment='center', size=8)
# plot the data.
plt.scatter(Xfinal[:, ax0], Xfinal[:, ax1], s=49, c=yFinal, cmap=plt.get_cmap("Set1"))
# save or show the data
if saveOutput:
if includeNames:
labelText = "_labels"
else:
labelText = "_no_labels"
if (oneThree):
oneThreeText = "_1_3"
else:
oneThreeText = ""
filename = saveDir + "pca2D" + oneThreeText + labelText + ".pdf"
utils.check_and_create_path(filename)
pp = PdfPages(filename)
pp.savefig()
pp.close()
else:
plt.show()
plt.close()
# do PCA down to 2 components, then visualize
# Portions of this adapted from code written by Gaël Varoquaux
# dataSet is the list of data to train on, with names as an array of names for those feature vectors
# testSet is the list of data to test on, with testNames as an array of names for those feature vectors
# includeNames is true if we want to print the names in the figure
# saveOutput is true if we want to save the feature to a file rather than view it
# preprocessType refers to the type of preprocessing to do
# (it is a float specifying the lasso feature selection cutoff, or 0 for no selection)
def pca4Viz(dataSet, names, testSet, testNames, includeNames, saveOutput, saveDir, preprocessType):
np.random.seed(5)
X = dataSet.data
y = dataSet.target
X2 = testSet.data
y2 = testSet.target
X, X2, _ = pcaPreprocess(X, X2, y, preprocessType, False, saveDir)
# set figure size
plt.clf()
if saveOutput:
fig, axes = plt.subplots(2)
fig.set_size_inches((8.5), (11))
else:
fig, axes = plt.subplots(2)
# train and apply PCA
pca = decomposition.PCA(n_components=4)
pca.fit(X)
X = pca.transform(X)
if (len(testNames) > 0):
X2 = pca.transform(X2)
# get the final sets to display
if (len(testNames) > 0):
Xfinal = np.append(X, X2, axis=0)
yFinal = np.append(y, y2, axis=0)
namesFinal = np.append(names, testNames, axis=0)
else:
Xfinal = X
yFinal = y
namesFinal = names
# make the two plots, with names if we are including names
for k in range(len(axes)):
ax = axes[k]
offset = k*2
secondStartIndex = 1
if (includeNames):
for i in range(len(Xfinal)):
name = namesFinal[i]
ax.text(Xfinal[i, 0+offset], (Xfinal[i, secondStartIndex+offset] + 0.01),
name,
horizontalalignment='center', size=8)
ax.scatter(Xfinal[:, 0+offset], Xfinal[:, secondStartIndex+offset], s=49, c=yFinal, cmap=plt.get_cmap("Set1"))
# save or show the data
if saveOutput:
if includeNames:
labelText = "_labels"
else:
labelText = "_no_labels"
filename = saveDir + "pca4D" + labelText + ".pdf"
utils.check_and_create_path(filename)
pp = PdfPages(filename)
pp.savefig()
pp.close()
else:
plt.show()
plt.close()
# report on the features used in this level of PCA
# same as pcaViz above, but just saves a report rather than printing a graph.
def pcaReport(dataSet, names, dimensions, saveOutput, saveDir, preprocessType):
np.random.seed(5)
X = dataSet.data
y = dataSet.target
X, _, featureNames = pcaPreprocess(X, [], y, preprocessType, True, saveDir)
pca = decomposition.PCA(n_components=dimensions)
pca.fit(X)
output = []
for i in range(len(pca.components_)):
output.append("Component %d" % i)
component = pca.components_[i]
indices = range(len(component))
zipped = np.dstack((component, indices, featureNames))
sortedZipped = sorted(zipped.tolist()[0], key=lambda x: abs(float(x[0])), reverse=True)
for item in sortedZipped:
if (float(item[0]) != 0.0):
output.append(" %s: %s" % (item[0], item[2]))
output.append("===============")
s = "\n".join(output)
if saveOutput:
filename = saveDir + "pcaReport" + str(dimensions) + ".txt"
utils.safeWrite(filename, s)
else:
print s
# Save a large amount of specific data on how the components of the PCA
# apply to each text for closer analysis of what they are picking for components.
def pcaCheck(dataSet, names, dimensions, saveOutput, saveDir, preprocessType):
np.random.seed(5)
X = dataSet.data
y = dataSet.target
X, _, featureNames = pcaPreprocess(X, [], y, preprocessType, True, saveDir)
pca = decomposition.PCA(n_components=dimensions)
pca.fit(X)
X2 = pca.transform(X)
output = []
for i in range(len(names)):
name = names[i]
data = X2[i]
output.append("%s: [%s]" % (name, ", ".join(map(str, data))))
flipped = np.swapaxes(X, 0, 1)
for i in range(len(pca.components_)):
output.append("Component %d" % i)
component = pca.components_[i]
flip = flipped
flipWeighted = []
for text in X:
flipWeighted.append(np.multiply(text, component))
flipWeighted = np.swapaxes(np.array(flipWeighted), 0, 1)
indices = range(len(component))
zipped = np.dstack((component, indices, featureNames))
sortedZipped = sorted(zipped.tolist()[0], key=lambda x: abs(float(x[0])), reverse=True)
runningCounts = []
for name in names:
label = name[0] + name.split(": ")[1].replace("Book ", "")
runningCounts.append([0.0, label])
for item in sortedZipped:
if (float(item[0]) != 0.0):
output.append(" %s: %s" % (item[0], item[2]))
myIndex = int(item[1])
myFlip = flip[myIndex]
myWeighted = flipWeighted[myIndex]
#output.append(" [%s]" % ", ".join(map(str, myFlip)))
#output.append(" [%s]" % ", ".join(map(str, myWeighted)))
for j in range(len(myWeighted)):
runningCounts[j][0] += float(myWeighted[j])
subZipped = np.dstack((myWeighted, names))
sortedWeighted = sorted(subZipped.tolist()[0], key=lambda x: abs(float(x[0])), reverse=True)
s = []
for subItem in sortedWeighted:
val = float(subItem[0])
name = subItem[1]
label = name[0] + name.split(": ")[1].replace("Book ", "")
s.append("%s: %.5f" % (label, val))
output.append(" This Component: [" + ", ".join(s) + "]")
sortedRunning = sorted(copy.deepcopy(runningCounts), key=lambda x: float(x[0]), reverse=True)
s = []
for subItem in sortedRunning:
val = float(subItem[0])
label = subItem[1]
s.append("%s: %.5f" % (label, val))
output.append(" Running Total: [" + ", ".join(s) + "]")
output.append(" ------")
output.append("===============")
s = "\n".join(output)
if saveOutput:
filename = saveDir + "pca" + str(dimensions) + "ReportWithTextResults.txt"
utils.safeWrite(filename, s)
else:
print s
# get the pieces for a classifying pipeline.
def getClassifierPipelinePieces(IncludeAllTypes):
preps = [
["Standard Scaler", lambda: preprocessing.StandardScaler()]
]
for comp in [2, 3, 4]:
name = "PCA %d" % comp
preps.append([name, lambda: decomposition.PCA(n_components=comp)])
featureSelectors = []
# can also include .6, but doesn't add much value for the time cost;
if (IncludeAllTypes):
thresholds = [0.0, .15, .25, .4]
else:
thresholds = [0.0, .25]
#thresholds = [0.0]
for threshold in thresholds:
if (threshold > 0):
name = "Lasso CV, threshold %.2f" % threshold
else:
name = "No Feature Selection"
featureSelectors.append([name, threshold])
#,
#["Linear SVC", lambda: decomposition.PCA(n_components=4)]
#for threshold in [.15, .25, .4, .6]:
#clf = LassoCV()
#sfm = SelectFromModel(clf, threshold=preprocessType)
classifiers = [
["Logistic Regression", lambda: linear_model.LogisticRegression()],
["SVM (Linear)", lambda: svm.SVC(kernel='linear')],
["SVM (RBF)", lambda: svm.SVC(kernel='rbf')],
["Random Forest", lambda: ensemble.RandomForestClassifier()]
]
for i in range(2,6):
classifiers.append(["KNN (" + str(i) + ", By Distance)", lambda: neighbors.KNeighborsClassifier(n_neighbors=i)])
classifiers.append(["KNN (" + str(i) + ")", lambda: neighbors.KNeighborsClassifier(n_neighbors=i, weights='distance')])
return featureSelectors, preps, classifiers
# run crossfold validation for the checkers on the provided data
# dataSet is the list of data to train on, with names as an array of names for those feature vectors
# testSet is the list of data to test on, with testNames as an array of names for those feature vectors
# includeNames is true if we want to print the names in the figure
# saveOutput is true if we want to save the feature to a file rather than view it
# saveDir is the directory in which to save the info
def crossValidateClassifiers(dataSet, names, testSet, testNames, includeNames, saveOutput, saveDir):
data = dataSet.data
target = dataSet.target
if (False):
clf = make_pipeline(preprocessing.StandardScaler(), svm.SVC(C=1))
print cross_val_score(clf, data, target, cv=5)
featureSelectors, preps, classifiers = getClassifierPipelinePieces(False)
#print data.shape
cv = ShuffleSplit(n_splits=5, test_size=.1)
output = []
total = 0
sumAvgs = 0.0
for f in featureSelectors:
data, _, _ = pcaPreprocess(data, [], target, f[1], False, "")
for p in preps:
subTotal = 0
subAvg = 0.0
for c in classifiers:
if ((f[0][0:5] == "Lasso" and p[0].find("PCA") == -1) and (c[0] == "SVM (RBF)")):
continue
pipe = make_pipeline(p[1](), c[1]())
name = "%s -> %s -> %s" % (f[0], p[0], c[0])
print name
scores = cross_val_score(pipe, data, target, cv=cv)
avg = np.mean(scores)
total += 1
subTotal += 1
sumAvgs += avg
subAvg += avg
output.append("%s Scores: [%s] - %f" % (name, ", ".join(map(str, scores)), avg))
output.append("-----")
output.append("Avg for this prep: %f" % (subAvg/subTotal))
output.append("=============")
output.append("Total avg: %f" % (sumAvgs/total))
s = "\n".join(output)
if saveOutput:
fn = saveDir + "CrossValidateClassifiers.txt"
utils.safeWrite(fn, s)
else:
print s
# SVM is about finding a plane to maximize the margin; we sortof have this
# w/ 4 dimensions.
# svc = svm.SVC(kernel='linear')
# or, in 3 dimensions, the RBF kernel (svc = svm.SVC(kernel='rbf'))
# looks good
if (False):
n_samples = len(data)
X_train = data[:.9 * n_samples]
y_train = target[:.9 * n_samples]
X_test = data[.9 * n_samples:]
y_test = target[.9 * n_samples:]
knn = neighbors.KNeighborsClassifier()
logistic = linear_model.LogisticRegression()
print('KNN score: %f' % knn.fit(X_train, y_train).score(X_test, y_test))
print('LogisticRegression score: %f' % logistic.fit(X_train, y_train).score(X_test, y_test))
# run all the classifiers on the data and either print or save the output
def runClassifiers(data, saveOutput, saveName):
# set up classifiers
(X_Train, X_Test, y_Train, y_Test, n_Train, n_Test, names) = data
featureSelectors, preps, classifiers = getClassifierPipelinePieces(True)
results = []
for f in featureSelectors:
for p in preps:
for c in classifiers:
name = "%s -> %s -> %s Scores:" % (f[0], p[0], c[0])
if ((f[0][0:5] == "Lasso" and p[0].find("PCA") == -1) and (c[0] == "SVM (RBF)")):
continue
myRes = []
failures = []
results.append([name, myRes, failures])
# prepare the info per text
resultsByText = []
resultsByTextIndices = {}
for ii in range(len(names)):
name = names[ii]
resultsByText.append([name, 0, []])
resultsByTextIndices[name] = ii
for fold in range(len(X_Train)):
xTr = X_Train[fold]
yTr = y_Train[fold]
xTe = X_Test[fold]
yTe = y_Test[fold]
nTe = n_Test[fold]
k = 0
for f in featureSelectors:
xTrSelected, xTeSelected, _ = pcaPreprocess(xTr, xTe, yTr, f[1], False, "")
for p in preps:
for c in classifiers:
if ((f[0][0:5] == "Lasso" and p[0].find("PCA") == -1) and (c[0] == "SVM (RBF)")):
continue
print str(fold) + ": " + results[k][0]
pipe = make_pipeline(p[1](), c[1]())
pipe.fit(xTrSelected, yTr)
total = 0
success = 0
reports = []
for j in range(len(xTe)):
test = xTeSelected[j]
target = yTe[j]
name = nTe[j]
pred = pipe.predict([test])
total += 1
if (pred != target):
report = " %s: Mismatch. Predicted %d, Actually %d" % (name, pred, target)
# report that this text was misidentified
index = resultsByTextIndices[name]
resultsByText[index][1] = resultsByText[index][1] + 1
resultsByText[index][2].append(results[k][0][:-1])
reports.append(report)
else:
success += 1
acc = (success*1.0)/total
results[k][1].append(acc)
results[k][2].append("\n".join(reports))
k += 1
# report on the classifiers
output = []
total = 0
sumAvgs = 0.0
for res in results:
name = res[0]
accuracy = res[1]
reports = res[2]
output.append(name)
mean = np.mean(accuracy)
total += 1
sumAvgs += mean
output.append("Avg: %f" % (mean))
output.append("[" + ", ".join(map(str, accuracy)) + "]")
output.append(" ----")
for i in range(len(reports)):
rep = reports[i]
if (rep != ""):
output.append(" " + str(accuracy[i]))
output.append(rep)
output.append(" ----")
output.append("=========")
output.append("Overall accuracy: %f" % (sumAvgs/total))
s1 = "\n".join(output)
output = []
tableOutput = []
numClassifiers = k
# report on the texts
for res in resultsByText:
name = res[0]
failures = res[1]
failedOn = res[2]
output.append("Text " + name + ":")
output.append("Failed on %d out of %d." % (failures, numClassifiers))
output.append("(" + ", ".join(failedOn) + ")")
output.append("===========")
tableOutput.append([name, "%.0f\%% (%d/%d)" % (failures*100.0/numClassifiers, failures, numClassifiers)])
s2 = "\n".join(output)
if saveOutput:
fn1 = saveName + "_ByClassifier.txt"
fn2 = saveName + "_ByText.txt"
utils.safeWrite(fn1, s1)
utils.safeWrite(fn2, s2)
else:
print s1
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print "~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~"
print s2
return tableOutput
# run a custom crossfold validation that evenly splits up Homeric,
# Pseudo-Homeric, and Non-Homeric texts.
def classifySpecialCrossfold(dataSet, names, testSet, testNames, includeNames, saveOutput, saveDir):
Homeric = []
hNames = []
hTargets = []
PseudoHomeric = []
phNames = []
phTargets = []
NonHomeric = []
nhNames = []
nhTargets = []
for i in range(len(names)):
split = names[i].split(": ")
if split[0] == "Iliad" or split[0] == "Odyssey":
Homeric.append(dataSet.data[i])
hNames.append(names[i])
hTargets.append(0)
elif split[0][0:5] == "Hymns":
PseudoHomeric.append(dataSet.data[i])
phNames.append(names[i])
phTargets.append(1)
else:
NonHomeric.append(dataSet.data[i])
nhNames.append(names[i])
nhTargets.append(1)
Homeric = np.array(Homeric)
PseudoHomeric = np.array(PseudoHomeric)
NonHomeric = np.array(NonHomeric)
hNames = np.array(hNames)
phNames = np.array(phNames)
nhNames = np.array(nhNames)
hTargets = np.array(hTargets)
phTargets = np.array(phTargets)
nhTargets = np.array(nhTargets)
# set up folds
kf = KFold(n_splits=5, shuffle=True, random_state=10)
hSplit = kf.split(Homeric)
phSplit = kf.split(PseudoHomeric)
nhSplit = kf.split(NonHomeric)
X_Train = []
X_Test = []
y_Train = []
y_Test = []
n_Train = []
n_Test = []
for hTrain, hTest in hSplit:
X1_Train, X1_Test = Homeric[hTrain], Homeric[hTest]
y1_Train, y1_Test = hTargets[hTrain], hTargets[hTest]
n1_Train, n1_Test = hNames[hTrain], hNames[hTest]
X_Train.append(X1_Train)
X_Test.append(X1_Test)
y_Train.append(y1_Train)
y_Test.append(y1_Test)
n_Train.append(n1_Train)
n_Test.append(n1_Test)
j = 0
for phTrain, phTest in phSplit:
X2_Train, X2_Test = PseudoHomeric[phTrain], PseudoHomeric[phTest]
y2_Train, y2_Test = phTargets[phTrain], phTargets[phTest]
n2_Train, n2_Test = phNames[phTrain], phNames[phTest]
X_Train[j] = np.append(X_Train[j], X2_Train, axis=0)
X_Test[j] = np.append(X_Test[j], X2_Test, axis=0)
y_Train[j] = np.append(y_Train[j], y2_Train, axis=0)
y_Test[j] = np.append(y_Test[j], y2_Test, axis=0)
n_Train[j] = np.append(n_Train[j], n2_Train, axis=0)
n_Test[j] = np.append(n_Test[j], n2_Test, axis=0)
j += 1
j = 0
for nhTrain, nhTest in nhSplit:
X3_Train, X3_Test = NonHomeric[nhTrain], NonHomeric[nhTest]
y3_Train, y3_Test = nhTargets[nhTrain], nhTargets[nhTest]
n3_Train, n3_Test = nhNames[nhTrain], nhNames[nhTest]
X_Train[j] = np.append(X_Train[j], X3_Train, axis=0)
X_Test[j] = np.append(X_Test[j], X3_Test, axis=0)
y_Train[j] = np.append(y_Train[j], y3_Train, axis=0)
y_Test[j] = np.append(y_Test[j], y3_Test, axis=0)
n_Train[j] = np.append(n_Train[j], n3_Train, axis=0)
n_Test[j] = np.append(n_Test[j], n3_Test, axis=0)
j += 1
data = (X_Train, X_Test, y_Train, y_Test, n_Train, n_Test, names)
saveName = saveDir + "classifiersKFoldResults"
return runClassifiers(data, saveOutput, saveName)
# check the entire classifier against one text that has been held out
def classifyOneHeldOut(dataSet, names, testSet, testNames, includeNames, saveOutput, saveDir):
data = dataSet.data
targets = dataSet.target
names = np.array(names)
# set up folds
kf = KFold(n_splits=data.shape[0])
X_Train = []
X_Test = []
y_Train = []
y_Test = []
n_Train = []
n_Test = []
for train, test in kf.split(data):
xTr, xTe = data[train], data[test]
yTr, yTe = targets[train], targets[test]
nTr, nTe = names[train], names[test]
X_Train.append(xTr)
X_Test.append(xTe)
y_Train.append(yTr)
y_Test.append(yTe)
n_Train.append(nTr)
n_Test.append(nTe)
data = (X_Train, X_Test, y_Train, y_Test, n_Train, n_Test, names)
saveName = saveDir + "classifiersOneHeldOutResults"
return runClassifiers(data, saveOutput, saveName)
# run a custom crossfold validation where we hold out the books of the
# Iliad/Odyssey for training, then run the classifier on the held out books.
def classifyIOHeldOut(dataSet, names, testSet, testNames, includeNames, saveOutput, saveDir):
X_Train = []
X_Test = []
y_Train = []
y_Test = []
n_Train = []
n_Test = []
for leaveOutName in ["Iliad", "Odyssey"]:
X1_Train = []
X1_Test = []
y1_Train = []
y1_Test = []
n1_Train = []
n1_Test = []
for i in range(len(names)):
split = names[i].split(": ")
if split[0] == leaveOutName:
X1_Test.append(dataSet.data[i])
y1_Test.append(dataSet.target[i])
n1_Test.append(names[i])
else:
X1_Train.append(dataSet.data[i])
y1_Train.append(dataSet.target[i])
n1_Train.append(names[i])
X1_Train = np.array(X1_Train)
X1_Test = np.array(X1_Test)
y1_Train = np.array(y1_Train)
y1_Test = np.array(y1_Test)
n1_Train = np.array(n1_Train)
n1_Test = np.array(n1_Test)
X_Train.append(X1_Train)
X_Test.append(X1_Test)
y_Train.append(y1_Train)
y_Test.append(y1_Test)
n_Train.append(n1_Train)
n_Test.append(n1_Test)
data = (X_Train, X_Test, y_Train, y_Test, n_Train, n_Test, names)
saveName = saveDir + "classifiersIOHeldOutResults"
return runClassifiers(data, saveOutput, saveName)
# build resulting latex tables
def buildResultLatexTables(r1, r2, r3, saveDir):
table1Lines = []
table2Lines = []
table3Lines = []
for ii in range(len(r1)):
name = r1[ii][0]
foldResult = r1[ii][1]
holdResult = r2[ii][1]
ioResult = r3[ii][1]
nameSplit = name.split(": ")
if (nameSplit[1] == "Overall"):
resultName = "\\textit{%s}" % nameSplit[0]
else:
resultName = "\\textit{%s}: %s" % (nameSplit[0], nameSplit[1])
t12Str = "%s & %s & %s" % (name, foldResult, holdResult)
t3Str = "%s & %s" % (name, ioResult)
if (name[0:5] == "Iliad"):
table1Lines.append(t12Str)
table3Lines.append(t3Str)
elif (name[0:7] == "Odyssey"):
oldI = ii - 24
table1Lines[oldI] = table1Lines[oldI] + " & " + t12Str + "\\\\ \\hline"
table3Lines[oldI] = table3Lines[oldI] + " & " + t3Str + "\\\\ \\hline"
elif (name[0:10] != "Dionysiaca"):
table2Lines.append(t12Str + "\\\\ \\hline")
table1Str = "\n".join(table1Lines)
table2Str = "\n".join(table2Lines)
table3Str = "\n".join(table3Lines)
s1 = table1Str + "\n\n\n" + table2Str
s2 = table3Str
fn1 = saveDir + "classifierResultsLatexTablePiece.txt"
fn2 = saveDir + "ioClassifierResultsLatexTablePiece.txt"
utils.safeWrite(fn1, s1)
utils.safeWrite(fn2, s2)
# function for testing a single results grab
def getResults(dataName):
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName);
dataName = DATA_SETS.AUTHORS_SPLIT
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
crossValidateClassifiers(data, names, test, testNames, True, True, saveDir)
if (False):
threshold = 0.6
myDir = saveDir + "0dot" + ("%.2f_" % threshold)[2:]
pca4Viz(data, names, test, testNames, False, True, myDir, threshold)
pca4Viz(data, names, test, testNames, True, True, myDir, threshold)
#pca2Viz(data, names, test, testNames, True, False, saveDir, 0, False)
#pca2Viz(data, names, test, testNames, True, True, saveDir, 0, True)
#pca3Viz(data, names, test, testNames, True, False, saveDir, 0)
#pca4Viz(data, names, test, testNames, True, False, saveDir, 0)
#pcaReport(data, names, 4, True, saveDir, 0)
#pcaCheck(data, names, 3, True, saveDir, 0)
#pcaCheck(data, names, 3, True, saveDir, 1)
#pca3Viz(data, names, test, testNames, True, False, saveDir, 1)
#classifySpecialCrossfold(data, names, test, testNames, True, True, saveDir)
#crossValidateClassifiers(data, names, test, testNames, True, True, saveDir)
# use dataset 6 for the following
#classifySpecialCrossfold(data, names, test, testNames, True, True, saveDir)
#classifyOneHeldOut(data, names, test, testNames, True, True, saveDir)
#classifyIOHeldOut(data, names, test, testNames, True, True, saveDir)
# run all of our results analyses
# skipBlockingSteps is true if we want to skip the 3D graphs that
# block execution
def resultsPipeline(skipBlockingSteps):
verbose = True
if (True):
dataSets = [
DATA_SETS.ALL_OVERALLS_SUB_BOOKS,
DATA_SETS.CLOSER_ONLY_HERMES_LOOK_DIONYSIACA_AS_TEST,
DATA_SETS.CLASSIFY_3,
DATA_SETS.ILIAD_ODYSSEY,
DATA_SETS.HOMER_HESIOD_AND_THE_HYMNS_ALL
]
for dataName in dataSets:
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
pca2Viz(data, names, test, testNames, True, True, saveDir, 0, False)
pca2Viz(data, names, test, testNames, False, True, saveDir, 0, False)
pca2Viz(data, names, test, testNames, True, True, saveDir, 0, True)
pca2Viz(data, names, test, testNames, False, True, saveDir, 0, True)
if not(skipBlockingSteps):
print "PCA3 for data set %s" % (dataName)
# we show this twice so the first time I can grab book names,
# the second time I can take nicer result screenshots
pca3Viz(data, names, test, testNames, True, False, saveDir, 0)
pca3Viz(data, names, test, testNames, False, False, saveDir, 0)
pca4Viz(data, names, test, testNames, True, True, saveDir, 0)
pca4Viz(data, names, test, testNames, False, True, saveDir, 0)
# PCA report
pcaReport(data, names, 4, True, saveDir, 0)
if verbose:
print " Done with visualizations for %s" % dataName
if (True):
dataSets = [
DATA_SETS.CLASSIFY_6,
DATA_SETS.HOMER_HESIOD_AND_THE_HYMNS_ALL
]
for dataName in dataSets:
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
# PCA report to let us know why things end up where they are
#pca3Viz(data, names, test, testNames, True, False, saveDir, 0)
# threshold to features
# .15 -> 29
# .25 -> 26
# .4 -> 25
# .6 -> 23
for threshold in [.15, .25, .4, .6]:
myDir = saveDir + "0dot" + ("%.2f_" % threshold)[2:]
pcaCheck(data, names, 3, True, myDir, threshold)
if not(skipBlockingSteps):
print "PCA3 for data set %s, preprocessing w/ threshold %.2f" % (dataName, threshold)
pca3Viz(data, names, test, testNames, True, False, myDir, threshold)
pca3Viz(data, names, test, testNames, False, False, myDir, threshold)
pca2Viz(data, names, test, testNames, False, True, myDir, threshold, False)
pca2Viz(data, names, test, testNames, True, True, myDir, threshold, False)
# 1/3 versions
pca2Viz(data, names, test, testNames, True, True, myDir, threshold, True)
pca2Viz(data, names, test, testNames, False, True, myDir, threshold, True)
if verbose:
print " Done with visualizations for %s, (threshold %.2f)" % (dataName, threshold)
if verbose:
print "Done with threshold visualizations"
dataSets = [
DATA_SETS.ILIAD_ODYSSEY,
DATA_SETS.CLASSIFY_6,
DATA_SETS.HOMER_HESIOD_AND_THE_HYMNS_ALL
]
for dataName in dataSets:
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
# PCA report to let us know why things end up where they are
pcaCheck(data, names, 3, True, saveDir, 0)
#pca3Viz(data, names, test, testNames, True, False, saveDir, 0)
#pca2Viz(data, names, test, testNames, True, True, saveDir, 0, False)
if verbose:
print "Done with pca rundown for %s" % dataName
if verbose:
print "Done with pca rundowns"
if (True):
# Analyze how good classifiers are at detecting iliad/odyssey stuff
dataName = DATA_SETS.CLASSIFY_6
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
r1 = classifySpecialCrossfold(data, names, test, testNames, True, True, saveDir)
if verbose:
print " Special crossfold done"
r2 = classifyOneHeldOut(data, names, test, testNames, True, True, saveDir)
if verbose:
print " Hold one out done"
r3 = classifyIOHeldOut(data, names, test, testNames, True, True, saveDir)
if verbose:
print " Iliad/Odyssey held out done"
buildResultLatexTables(r1, r2, r3, saveDir)
if verbose:
print " Iliad/Odyssey self compare starting"
dataName = DATA_SETS.ILIAD_ODYSSEY
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
crossValidateClassifiers(data, names, test, testNames, True, True, saveDir)
if verbose:
print " Iliad/Odyssey self compare done."
print " Dionysiaca self compare starting"
dataName = DATA_SETS.DIONYSIACA_SPLIT
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
crossValidateClassifiers(data, names, test, testNames, True, True, saveDir)
if verbose:
print " Dionysiaca self compare done."
print " Dionysiaca/Fall of Troy self compare starting"
dataName = DATA_SETS.AUTHORS_SPLIT
data, names, test, testNames = getData(dataName)
saveDir = utils.getFinalResultsOutputDir(dataName)
crossValidateClassifiers(data, names, test, testNames, True, True, saveDir)
if verbose:
print " Dionysiaca/Fall of Troy self compare done."
| 40.539118
| 310
| 0.547996
| 9,184
| 85,497
| 5.039416
| 0.076002
| 0.033706
| 0.022817
| 0.021391
| 0.754181
| 0.723067
| 0.701612
| 0.679768
| 0.651571
| 0.61538
| 0
| 0.01837
| 0.353755
| 85,497
| 2,108
| 311
| 40.558349
| 0.819283
| 0.125209
| 0
| 0.669951
| 0
| 0.011084
| 0.125074
| 0.007343
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.000616
| 0.012315
| null | null | 0.021552
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
75aa428b3cfcfdfbb975e4d52c3188d992750742
| 87
|
py
|
Python
|
src/hkmeans/c_package/__init__.py
|
IBM/hartigan-kmeans
|
f1a61da4c3123f7f020362c6790caa688f29b932
|
[
"Apache-2.0"
] | 1
|
2021-12-29T00:34:27.000Z
|
2021-12-29T00:34:27.000Z
|
src/hkmeans/c_package/__init__.py
|
IBM/hartigan-kmeans
|
f1a61da4c3123f7f020362c6790caa688f29b932
|
[
"Apache-2.0"
] | 1
|
2021-12-27T10:05:14.000Z
|
2021-12-27T10:05:14.000Z
|
src/hkmeans/c_package/__init__.py
|
IBM/hartigan-kmeans
|
f1a61da4c3123f7f020362c6790caa688f29b932
|
[
"Apache-2.0"
] | null | null | null |
#
# Copyright 2021- IBM Inc. All rights reserved
# SPDX-License-Identifier: Apache2.0
#
| 21.75
| 46
| 0.747126
| 12
| 87
| 5.416667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 0.137931
| 87
| 4
| 47
| 21.75
| 0.786667
| 0.908046
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
75c03822fa95d6bb20bf0a368d362d3abf84300f
| 368
|
py
|
Python
|
problem/10000~19999/15632/15632.pypy3.py
|
njw1204/BOJ-AC
|
1de41685725ae4657a7ff94e413febd97a888567
|
[
"MIT"
] | 1
|
2019-04-19T16:37:44.000Z
|
2019-04-19T16:37:44.000Z
|
problem/10000~19999/15632/15632.pypy3.py
|
njw1204/BOJ-AC
|
1de41685725ae4657a7ff94e413febd97a888567
|
[
"MIT"
] | 1
|
2019-04-20T11:42:44.000Z
|
2019-04-20T11:42:44.000Z
|
problem/10000~19999/15632/15632.pypy3.py
|
njw1204/BOJ-AC
|
1de41685725ae4657a7ff94e413febd97a888567
|
[
"MIT"
] | 3
|
2019-04-19T16:37:47.000Z
|
2021-10-25T00:45:00.000Z
|
ans=0
x1,y1,r1=map(int,input().split())
x2,y2,r2=map(int,input().split())
x3,y3,r3=map(int,input().split())
for i in range(23001):
for j in range(23001):
if (x1-i/230+0.0022)**2+(y1-j/230+0.0022)**2<=r1*r1: ans+=1
elif (x2-i/230+0.0022)**2+(y2-j/230+0.0022)**2<=r2*r2: ans+=1
elif (x3-i/230+0.0022)**2+(y3-j/230+0.0022)**2<=r3*r3: ans+=1
print(ans/52900)
| 36.8
| 65
| 0.600543
| 87
| 368
| 2.54023
| 0.333333
| 0.108597
| 0.217195
| 0.244344
| 0.271493
| 0
| 0
| 0
| 0
| 0
| 0
| 0.282282
| 0.095109
| 368
| 10
| 66
| 36.8
| 0.381381
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.1
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
75d25e4fe0a601a04722de7c5c2111f822146dcc
| 93
|
py
|
Python
|
api/specimens/apps.py
|
fujikawahiroaki/webspecimanager
|
d46a4feec0c695d5231b21e3311f4adbe25435cb
|
[
"BSD-2-Clause"
] | 1
|
2017-06-20T08:09:29.000Z
|
2017-06-20T08:09:29.000Z
|
website/specimens/apps.py
|
BelgianBiodiversityPlatform/Astapor
|
b54f6b8595e90250575e1220802720ab4ac0229d
|
[
"BSD-2-Clause"
] | 31
|
2017-06-20T11:11:29.000Z
|
2018-01-11T15:03:24.000Z
|
website/specimens/apps.py
|
BelgianBiodiversityPlatform/Astapor
|
b54f6b8595e90250575e1220802720ab4ac0229d
|
[
"BSD-2-Clause"
] | null | null | null |
from django.apps import AppConfig
class SpecimensConfig(AppConfig):
name = 'specimens'
| 15.5
| 33
| 0.763441
| 10
| 93
| 7.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16129
| 93
| 5
| 34
| 18.6
| 0.910256
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
75faeb688e84c494c936ae1cc3a4cf0fb0b40809
| 23
|
py
|
Python
|
platzigram_api/users/tests/__init__.py
|
ChekeGT/Platzigram-Api
|
0ab05f1bb325b02563aead2e885194e274013150
|
[
"MIT"
] | null | null | null |
platzigram_api/users/tests/__init__.py
|
ChekeGT/Platzigram-Api
|
0ab05f1bb325b02563aead2e885194e274013150
|
[
"MIT"
] | null | null | null |
platzigram_api/users/tests/__init__.py
|
ChekeGT/Platzigram-Api
|
0ab05f1bb325b02563aead2e885194e274013150
|
[
"MIT"
] | null | null | null |
"""Users app tests."""
| 11.5
| 22
| 0.565217
| 3
| 23
| 4.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130435
| 23
| 1
| 23
| 23
| 0.65
| 0.695652
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
f935dd6236691f10d1a726fbd22121ded1de8d6f
| 268
|
py
|
Python
|
wSelect.py
|
chinmxy/hman
|
bc9c032e3e26fef211c5774d3200143838645357
|
[
"Apache-2.0"
] | null | null | null |
wSelect.py
|
chinmxy/hman
|
bc9c032e3e26fef211c5774d3200143838645357
|
[
"Apache-2.0"
] | null | null | null |
wSelect.py
|
chinmxy/hman
|
bc9c032e3e26fef211c5774d3200143838645357
|
[
"Apache-2.0"
] | null | null | null |
import random
#to generate a random word from .txt file
def generate_the_word(infile):
random_line = random.choice(open(infile).read().split('\n'))
return random_line
def get_word():
infile = "words.txt"
return(generate_the_word(infile))
| 22.333333
| 65
| 0.686567
| 38
| 268
| 4.657895
| 0.552632
| 0.169492
| 0.169492
| 0.237288
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.197761
| 268
| 11
| 66
| 24.363636
| 0.823256
| 0.149254
| 0
| 0
| 1
| 0
| 0.050926
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.142857
| 0
| 0.571429
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
f956f8705d7a28a552c10a8c71304f7242c78c8e
| 144
|
py
|
Python
|
trivial_sudoku/apps.py
|
alexpirine/django-trivial-sudoku
|
75cc2ea7e28ea88e349c01af9fddb34fedd6123c
|
[
"BSD-3-Clause"
] | null | null | null |
trivial_sudoku/apps.py
|
alexpirine/django-trivial-sudoku
|
75cc2ea7e28ea88e349c01af9fddb34fedd6123c
|
[
"BSD-3-Clause"
] | null | null | null |
trivial_sudoku/apps.py
|
alexpirine/django-trivial-sudoku
|
75cc2ea7e28ea88e349c01af9fddb34fedd6123c
|
[
"BSD-3-Clause"
] | null | null | null |
from __future__ import unicode_literals
from django.apps import AppConfig
class TrivialSudoku2Config(AppConfig):
name = 'trivial_sudoku'
| 18
| 39
| 0.8125
| 16
| 144
| 6.9375
| 0.8125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008065
| 0.138889
| 144
| 7
| 40
| 20.571429
| 0.887097
| 0
| 0
| 0
| 0
| 0
| 0.097222
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
f9608dc3f3ad15137b71e947659c6b9c3389688b
| 443
|
py
|
Python
|
utils.py
|
retroinspect/tweetstock
|
cd6e0d5a2c00674d3f9ef2b858bf9001580738aa
|
[
"MIT"
] | null | null | null |
utils.py
|
retroinspect/tweetstock
|
cd6e0d5a2c00674d3f9ef2b858bf9001580738aa
|
[
"MIT"
] | null | null | null |
utils.py
|
retroinspect/tweetstock
|
cd6e0d5a2c00674d3f9ef2b858bf9001580738aa
|
[
"MIT"
] | null | null | null |
from transformers import AutoTokenizer
import pandas as pd
import numpy as np
tokenizer = AutoTokenizer.from_pretrained("vinai/bertweet-base", normalization=True)
def tokenize_function(examples):
return tokenizer(examples["body"], padding="max_length", truncation=True)
def save(tweets, filename, directory="./data"):
tweets.to_csv(f'{directory}/{filename}.csv', sep=',', na_rep='NaN', index=False)
print(f"Saved into {filename}.csv")
| 36.916667
| 84
| 0.76298
| 59
| 443
| 5.644068
| 0.728814
| 0.042042
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.092551
| 443
| 11
| 85
| 40.272727
| 0.828358
| 0
| 0
| 0
| 0
| 0
| 0.21219
| 0.058691
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| false
| 0
| 0.333333
| 0.111111
| 0.666667
| 0.111111
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
f98148f481897546dc2b6297250dc54a615e4967
| 89
|
py
|
Python
|
app/datasci/apps.py
|
sappachok/django-anaconda
|
1ffd33ded759f622b6db23a3550a898b62350403
|
[
"MIT"
] | null | null | null |
app/datasci/apps.py
|
sappachok/django-anaconda
|
1ffd33ded759f622b6db23a3550a898b62350403
|
[
"MIT"
] | 7
|
2019-12-06T05:34:28.000Z
|
2021-06-10T18:25:17.000Z
|
app/datasci/apps.py
|
sappachok/django-datasci
|
1ffd33ded759f622b6db23a3550a898b62350403
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class DatasciConfig(AppConfig):
name = 'datasci'
| 14.833333
| 33
| 0.752809
| 10
| 89
| 6.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168539
| 89
| 5
| 34
| 17.8
| 0.905405
| 0
| 0
| 0
| 0
| 0
| 0.078652
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
f9890fec81e4cae1097c0b77acb0d98a16329696
| 89
|
py
|
Python
|
LunarLight/Solaris/apps.py
|
NafrayuDev/LunarLight
|
130cc1fa6284ed69d922e45e66d4f85a0581cfe0
|
[
"Apache-2.0"
] | null | null | null |
LunarLight/Solaris/apps.py
|
NafrayuDev/LunarLight
|
130cc1fa6284ed69d922e45e66d4f85a0581cfe0
|
[
"Apache-2.0"
] | null | null | null |
LunarLight/Solaris/apps.py
|
NafrayuDev/LunarLight
|
130cc1fa6284ed69d922e45e66d4f85a0581cfe0
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class SolarisConfig(AppConfig):
name = 'Solaris'
| 14.833333
| 33
| 0.752809
| 10
| 89
| 6.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168539
| 89
| 5
| 34
| 17.8
| 0.905405
| 0
| 0
| 0
| 0
| 0
| 0.078652
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
f9c2cdfaec7db5de16dc19ee055c29b102ffe109
| 498
|
py
|
Python
|
experiments/rusentrel/mimlre/model.py
|
nicolay-r/attitude-extraction-with-frames
|
d23d46c426a2321534edb914bfc6a645e7d154a8
|
[
"MIT"
] | null | null | null |
experiments/rusentrel/mimlre/model.py
|
nicolay-r/attitude-extraction-with-frames
|
d23d46c426a2321534edb914bfc6a645e7d154a8
|
[
"MIT"
] | 2
|
2020-12-17T09:23:49.000Z
|
2020-12-17T09:42:08.000Z
|
experiments/rusentrel/mimlre/model.py
|
nicolay-r/attitude-extraction-with-frames
|
d23d46c426a2321534edb914bfc6a645e7d154a8
|
[
"MIT"
] | null | null | null |
from core.networks.multi.training.batch import MultiInstanceBatch
from experiments.rusentrel.context.model import ContextLevelTensorflowModel
from experiments.rusentrel.mimlre.helper.initialization import MIMLREModelInitHelper
class MIMLRETensorflowModel(ContextLevelTensorflowModel):
def create_batch_by_bags_group(self, bags_group):
return MultiInstanceBatch(bags_group)
def create_model_init_helper(self):
return MIMLREModelInitHelper(io=self.IO, config=self.Config)
| 38.307692
| 84
| 0.835341
| 53
| 498
| 7.679245
| 0.54717
| 0.066339
| 0.117936
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.104418
| 498
| 12
| 85
| 41.5
| 0.912556
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.375
| 0.25
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 4
|
ddbf58bbc2c8ff642c67519c2ca970e370f5ac3b
| 295
|
py
|
Python
|
groups/test_apps.py
|
ebaymademepoor/django_milestone_project_myTeam
|
95d503e2c303b9525e9eaff2e08340f6e9f1987b
|
[
"ADSL"
] | null | null | null |
groups/test_apps.py
|
ebaymademepoor/django_milestone_project_myTeam
|
95d503e2c303b9525e9eaff2e08340f6e9f1987b
|
[
"ADSL"
] | 5
|
2020-06-05T19:45:53.000Z
|
2022-03-11T23:41:23.000Z
|
groups/test_apps.py
|
Deirdre18/django_milestone_project_myTeam
|
0555105f65076214087cfed73802470652dd1dcd
|
[
"ADSL"
] | 2
|
2019-04-30T11:08:14.000Z
|
2019-07-24T20:04:50.000Z
|
from django.apps import apps
from django.test import TestCase
from .apps import GroupsConfig
class TestAccountsConfig(TestCase):
def test_app(self):
self.assertEqual("groups", GroupsConfig.name)
self.assertEqual("Groups", apps.get_app_config("groups").verbose_name)
| 32.777778
| 78
| 0.738983
| 36
| 295
| 5.944444
| 0.5
| 0.093458
| 0.196262
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166102
| 295
| 9
| 79
| 32.777778
| 0.869919
| 0
| 0
| 0
| 0
| 0
| 0.060811
| 0
| 0
| 0
| 0
| 0
| 0.285714
| 1
| 0.142857
| false
| 0
| 0.428571
| 0
| 0.714286
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
fb1065aad5d02a31c7434d3cc8b0c742fb92ba0e
| 238
|
py
|
Python
|
treepages/forms.py
|
scotu/django-treepages
|
4c0a3afa6f14244a45c712e1c9b0526804aa90bc
|
[
"MIT"
] | 1
|
2015-11-05T01:38:27.000Z
|
2015-11-05T01:38:27.000Z
|
treepages/forms.py
|
scotu/django-treepages
|
4c0a3afa6f14244a45c712e1c9b0526804aa90bc
|
[
"MIT"
] | null | null | null |
treepages/forms.py
|
scotu/django-treepages
|
4c0a3afa6f14244a45c712e1c9b0526804aa90bc
|
[
"MIT"
] | null | null | null |
from django import forms
from tinymce.widgets import TinyMCE
from treepages.models import Page
class PageAdminModelForm(forms.ModelForm):
body = forms.CharField(required=False, widget=TinyMCE())
class Meta:
model = Page
| 23.8
| 60
| 0.756303
| 29
| 238
| 6.206897
| 0.655172
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172269
| 238
| 9
| 61
| 26.444444
| 0.913706
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.428571
| 0
| 0.857143
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
fb3e8ab98916ffce9fc34d6e2d050966f8496dbf
| 133
|
py
|
Python
|
app.py
|
sinhard/learning-bottle-framework
|
685b1f73e2a0e24b12a5a558668a4b268504097e
|
[
"MIT"
] | null | null | null |
app.py
|
sinhard/learning-bottle-framework
|
685b1f73e2a0e24b12a5a558668a4b268504097e
|
[
"MIT"
] | null | null | null |
app.py
|
sinhard/learning-bottle-framework
|
685b1f73e2a0e24b12a5a558668a4b268504097e
|
[
"MIT"
] | null | null | null |
from bottle import run, route
@route('/')
def index():
return '<h1>Hello, World!</h1>'
run(port=8080, host='localhost')
| 16.625
| 36
| 0.609023
| 18
| 133
| 4.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.056075
| 0.195489
| 133
| 7
| 37
| 19
| 0.700935
| 0
| 0
| 0
| 0
| 0
| 0.253968
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| true
| 0
| 0.2
| 0.2
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
|
0
| 4
|
34946d1644e6652da3e946489e016156cab053ac
| 610
|
py
|
Python
|
proxyclient/hv/trace_all.py
|
Ferdi265/m1n1
|
526cd8a55eedd7f9ea5f5877c47eceb242a422ba
|
[
"MIT"
] | null | null | null |
proxyclient/hv/trace_all.py
|
Ferdi265/m1n1
|
526cd8a55eedd7f9ea5f5877c47eceb242a422ba
|
[
"MIT"
] | null | null | null |
proxyclient/hv/trace_all.py
|
Ferdi265/m1n1
|
526cd8a55eedd7f9ea5f5877c47eceb242a422ba
|
[
"MIT"
] | null | null | null |
# SPDX-License-Identifier: MIT
# Map the entire MMIO range as traceable
map_sw(0x2_00000000,
0x2_00000000 | hv.SPTE_TRACE_READ | hv.SPTE_TRACE_WRITE,
0x5_00000000)
# Skip some noisy devices
try:
trace_device("/arm-io/usb-drd0", False)
except KeyError:
pass
try:
trace_device("/arm-io/usb-drd1", False)
except KeyError:
pass
trace_device("/arm-io/uart2", False)
trace_device("/arm-io/error-handler", False)
trace_device("/arm-io/aic", False)
trace_device("/arm-io/spi1", False)
trace_device("/arm-io/pmgr", False)
# Re-map the vuart, which the first map_sw undid...
map_vuart()
| 24.4
| 63
| 0.716393
| 96
| 610
| 4.375
| 0.479167
| 0.183333
| 0.233333
| 0.266667
| 0.304762
| 0.104762
| 0
| 0
| 0
| 0
| 0
| 0.065134
| 0.144262
| 610
| 24
| 64
| 25.416667
| 0.739464
| 0.231148
| 0
| 0.352941
| 0
| 0
| 0.217672
| 0.045259
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.117647
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
34a2e2d788b6dc02585e952c25a6e4ffa42660fc
| 170
|
py
|
Python
|
runserver.py
|
skakanka/barter_network
|
598ec337682941600704ef293ce415a9c826762d
|
[
"PostgreSQL",
"Unlicense",
"MIT"
] | 1
|
2020-08-30T11:49:46.000Z
|
2020-08-30T11:49:46.000Z
|
runserver.py
|
anka-kondraska/swiftswap
|
598ec337682941600704ef293ce415a9c826762d
|
[
"MIT",
"PostgreSQL",
"Unlicense"
] | null | null | null |
runserver.py
|
anka-kondraska/swiftswap
|
598ec337682941600704ef293ce415a9c826762d
|
[
"MIT",
"PostgreSQL",
"Unlicense"
] | 1
|
2019-06-02T07:55:59.000Z
|
2019-06-02T07:55:59.000Z
|
from flask_debugtoolbar import DebugToolbarExtension
from barter_network import app
# running flask server
app.run(host='0.0.0.0', debug=True)
DebugToolbarExtension(app)
| 28.333333
| 52
| 0.829412
| 24
| 170
| 5.791667
| 0.625
| 0.043165
| 0.043165
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025806
| 0.088235
| 170
| 6
| 53
| 28.333333
| 0.870968
| 0.117647
| 0
| 0
| 0
| 0
| 0.04698
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
34e17293f026a1be678d590691caca3b09594c16
| 687
|
py
|
Python
|
funtest/iface.py
|
duboviy/funtest
|
60a5b768e55d21efb9953479d9a7171a33a896de
|
[
"MIT"
] | 6
|
2017-02-12T22:02:32.000Z
|
2019-04-22T11:43:21.000Z
|
funtest/iface.py
|
duboviy/funtest
|
60a5b768e55d21efb9953479d9a7171a33a896de
|
[
"MIT"
] | null | null | null |
funtest/iface.py
|
duboviy/funtest
|
60a5b768e55d21efb9953479d9a7171a33a896de
|
[
"MIT"
] | null | null | null |
from abc import ABCMeta, abstractmethod
class AbstractCommandExecutor(object):
__metaclass__ = ABCMeta
@abstractmethod
def run(self, cmd, ret_code):
"""For example, run command with args, return stdout merged with stderr. """
pass
@abstractmethod
def cd(self, arg):
pass
@abstractmethod
def get_cwd(self):
pass
@abstractmethod
def mkdir(self, arg):
pass
@abstractmethod
def full_name(self, fname):
pass
@abstractmethod
def rmtree(self):
pass
@abstractmethod
def read(self, fname):
pass
@abstractmethod
def write(self, fname, text):
pass
| 17.615385
| 84
| 0.612809
| 72
| 687
| 5.75
| 0.513889
| 0.328502
| 0.355072
| 0.120773
| 0.280193
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.308588
| 687
| 38
| 85
| 18.078947
| 0.871579
| 0.100437
| 0
| 0.592593
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.296296
| false
| 0.296296
| 0.037037
| 0
| 0.407407
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
34fbbdb543d9abfb883dc28e9fbcd80bd7444d07
| 1,024
|
py
|
Python
|
1_16_Project_4_Advanced_Lane_Lines/CreateVideos.py
|
Alyxion/Udacity_SelfDrivingCarEngineerNd
|
7da27ec7ee86fc65d07c9e1b316088be6975f2d3
|
[
"MIT"
] | 7
|
2018-12-27T00:12:50.000Z
|
2022-03-29T13:13:42.000Z
|
1_16_Project_4_Advanced_Lane_Lines/CreateVideos.py
|
Alyxion/Udacity_SelfDrivingCarEngineerNd
|
7da27ec7ee86fc65d07c9e1b316088be6975f2d3
|
[
"MIT"
] | null | null | null |
1_16_Project_4_Advanced_Lane_Lines/CreateVideos.py
|
Alyxion/Udacity_SelfDrivingCarEngineerNd
|
7da27ec7ee86fc65d07c9e1b316088be6975f2d3
|
[
"MIT"
] | 8
|
2018-10-03T16:46:39.000Z
|
2021-01-11T18:29:42.000Z
|
#####################################################################################################################
# #
# This file is part of the 4th project of Udacity's Self-Driving Car Engineer Nanodegree - Advanced Lane Finding #
# #
# Copyright (c) 2018 by Michael Ikemann #
# #
#####################################################################################################################
import AdvLaneVideoCreator
print("Creating submission video...")
AdvLaneVideoCreator.create_perspective_video()
AdvLaneVideoCreator.create_top_video_photo()
AdvLaneVideoCreator.create_top_video()
| 68.266667
| 117
| 0.285156
| 44
| 1,024
| 6.477273
| 0.772727
| 0.263158
| 0.210526
| 0.231579
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.008977
| 0.456055
| 1,024
| 15
| 118
| 68.266667
| 0.502693
| 0.260742
| 0
| 0
| 0
| 0
| 0.135922
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.2
| 0
| 0.2
| 0.2
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
5503194ce88ada1c3452ab7f045bba23f75e01bf
| 120
|
py
|
Python
|
100.py
|
cwd0204/Python
|
35413d0cfab0d659d710fd3f752dacef00f4a713
|
[
"MIT"
] | 1
|
2022-01-05T05:49:59.000Z
|
2022-01-05T05:49:59.000Z
|
100.py
|
cwd0204/Python
|
35413d0cfab0d659d710fd3f752dacef00f4a713
|
[
"MIT"
] | null | null | null |
100.py
|
cwd0204/Python
|
35413d0cfab0d659d710fd3f752dacef00f4a713
|
[
"MIT"
] | null | null | null |
k_list = [0] * 100
k_list[0] = 1
for i in range(1,100):
k_list[i] = k_list[i-1]+i
print('100 刀最多切 %d块' %k_list[99])
| 13.333333
| 33
| 0.591667
| 29
| 120
| 2.275862
| 0.448276
| 0.378788
| 0.181818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164948
| 0.191667
| 120
| 8
| 34
| 15
| 0.515464
| 0
| 0
| 0
| 0
| 0
| 0.10084
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.2
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
55040345a3d9a38bc15942f1bb4d7dd0dbb11589
| 109
|
py
|
Python
|
Main/handleFileRequest/apps.py
|
mayankkumar2/BulkDataEntryAPI
|
59e65cddbb0a63d3912e75b4b5c40aa3023a5253
|
[
"Apache-2.0"
] | null | null | null |
Main/handleFileRequest/apps.py
|
mayankkumar2/BulkDataEntryAPI
|
59e65cddbb0a63d3912e75b4b5c40aa3023a5253
|
[
"Apache-2.0"
] | 1
|
2021-03-30T12:51:31.000Z
|
2021-03-30T12:51:31.000Z
|
Main/handleFileRequest/apps.py
|
mayankkumar2/BulkDataEntryAPI
|
59e65cddbb0a63d3912e75b4b5c40aa3023a5253
|
[
"Apache-2.0"
] | null | null | null |
from django.apps import AppConfig
class HandlefilerequestConfig(AppConfig):
name = 'handleFileRequest'
| 18.166667
| 41
| 0.798165
| 10
| 109
| 8.7
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137615
| 109
| 5
| 42
| 21.8
| 0.925532
| 0
| 0
| 0
| 0
| 0
| 0.155963
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
9b2f4f5577b89735b08b79bae6c9606945424e39
| 1,657
|
py
|
Python
|
z2/part3/updated_part2_batch/jm/parser_errors_2/725512976.py
|
kozakusek/ipp-2020-testy
|
09aa008fa53d159672cc7cbf969a6b237e15a7b8
|
[
"MIT"
] | 1
|
2020-04-16T12:13:47.000Z
|
2020-04-16T12:13:47.000Z
|
z2/part3/updated_part2_batch/jm/parser_errors_2/725512976.py
|
kozakusek/ipp-2020-testy
|
09aa008fa53d159672cc7cbf969a6b237e15a7b8
|
[
"MIT"
] | 18
|
2020-03-06T17:50:15.000Z
|
2020-05-19T14:58:30.000Z
|
z2/part3/updated_part2_batch/jm/parser_errors_2/725512976.py
|
kozakusek/ipp-2020-testy
|
09aa008fa53d159672cc7cbf969a6b237e15a7b8
|
[
"MIT"
] | 18
|
2020-03-06T17:45:13.000Z
|
2020-06-09T19:18:31.000Z
|
from part1 import (
gamma_board,
gamma_busy_fields,
gamma_delete,
gamma_free_fields,
gamma_golden_move,
gamma_golden_possible,
gamma_move,
gamma_new,
)
"""
scenario: test_random_actions
uuid: 725512976
"""
"""
random actions, total chaos
"""
board = gamma_new(2, 4, 4, 1)
assert board is not None
assert gamma_move(board, 1, 0, 3) == 1
assert gamma_move(board, 1, 1, 0) == 0
assert gamma_move(board, 2, 1, 2) == 1
assert gamma_move(board, 2, 1, 1) == 1
assert gamma_golden_possible(board, 2) == 1
assert gamma_move(board, 3, 1, 0) == 1
assert gamma_move(board, 4, 0, 0) == 1
assert gamma_move(board, 1, 1, 0) == 0
assert gamma_move(board, 2, 3, 1) == 0
assert gamma_move(board, 2, 1, 2) == 0
assert gamma_move(board, 3, 3, 1) == 0
assert gamma_move(board, 4, 1, 0) == 0
assert gamma_move(board, 4, 1, 0) == 0
board845175492 = gamma_board(board)
assert board845175492 is not None
assert board845175492 == ("1.\n"
".2\n"
".2\n"
"43\n")
del board845175492
board845175492 = None
assert gamma_move(board, 1, 3, 1) == 0
assert gamma_free_fields(board, 1) == 2
assert gamma_move(board, 2, 3, 1) == 0
assert gamma_move(board, 3, 0, 2) == 0
assert gamma_free_fields(board, 3) == 0
assert gamma_move(board, 4, 1, 0) == 0
assert gamma_move(board, 1, 2, 0) == 0
assert gamma_move(board, 2, 2, 0) == 0
assert gamma_move(board, 2, 0, 3) == 0
assert gamma_move(board, 3, 1, 0) == 0
board121829258 = gamma_board(board)
assert board121829258 is not None
assert board121829258 == ("1.\n"
".2\n"
".2\n"
"43\n")
del board121829258
board121829258 = None
assert gamma_move(board, 4, 0, 0) == 0
gamma_delete(board)
| 23.671429
| 44
| 0.671092
| 283
| 1,657
| 3.770318
| 0.123675
| 0.247423
| 0.29522
| 0.393627
| 0.550141
| 0.54358
| 0.397376
| 0.309278
| 0.259606
| 0.233365
| 0
| 0.150776
| 0.183464
| 1,657
| 69
| 45
| 24.014493
| 0.637842
| 0
| 0
| 0.245283
| 0
| 0
| 0.020395
| 0
| 0
| 0
| 0
| 0
| 0.54717
| 1
| 0
| false
| 0
| 0.018868
| 0
| 0.018868
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
9b37cc0de8fa35ee844609fda6a00dee81aecdd0
| 1,030
|
py
|
Python
|
clients/oathkeeper/python/test/test_metadata_api.py
|
ALTELMA/sdk
|
a04d56edd0431382dda8a9d10229b8479174aa8e
|
[
"Apache-2.0"
] | null | null | null |
clients/oathkeeper/python/test/test_metadata_api.py
|
ALTELMA/sdk
|
a04d56edd0431382dda8a9d10229b8479174aa8e
|
[
"Apache-2.0"
] | null | null | null |
clients/oathkeeper/python/test/test_metadata_api.py
|
ALTELMA/sdk
|
a04d56edd0431382dda8a9d10229b8479174aa8e
|
[
"Apache-2.0"
] | null | null | null |
"""
Ory Oathkeeper API
Documentation for all of Ory Oathkeeper's APIs. # noqa: E501
The version of the OpenAPI document: v0.38.20-beta.1
Contact: hi@ory.sh
Generated by: https://openapi-generator.tech
"""
import unittest
import ory_oathkeeper_client
from ory_oathkeeper_client.api.metadata_api import MetadataApi # noqa: E501
class TestMetadataApi(unittest.TestCase):
"""MetadataApi unit test stubs"""
def setUp(self):
self.api = MetadataApi() # noqa: E501
def tearDown(self):
pass
def test_get_version(self):
"""Test case for get_version
Return Running Software Version. # noqa: E501
"""
pass
def test_is_alive(self):
"""Test case for is_alive
Check HTTP Server Status # noqa: E501
"""
pass
def test_is_ready(self):
"""Test case for is_ready
Check HTTP Server and Database Status # noqa: E501
"""
pass
if __name__ == '__main__':
unittest.main()
| 20.196078
| 76
| 0.628155
| 129
| 1,030
| 4.844961
| 0.48062
| 0.0768
| 0.0528
| 0.072
| 0.1216
| 0.0672
| 0
| 0
| 0
| 0
| 0
| 0.032476
| 0.282524
| 1,030
| 50
| 77
| 20.6
| 0.813261
| 0.450485
| 0
| 0.25
| 1
| 0
| 0.017167
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3125
| false
| 0.25
| 0.1875
| 0
| 0.5625
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
9b58126b51559db4207624ddec5d37db46b1aac6
| 112
|
py
|
Python
|
utils/__init__.py
|
Gurpreet-Singh121/auto-archiver
|
d76e3bc7ec7c4eb267ec9fe767fabd23102d89f6
|
[
"MIT"
] | null | null | null |
utils/__init__.py
|
Gurpreet-Singh121/auto-archiver
|
d76e3bc7ec7c4eb267ec9fe767fabd23102d89f6
|
[
"MIT"
] | null | null | null |
utils/__init__.py
|
Gurpreet-Singh121/auto-archiver
|
d76e3bc7ec7c4eb267ec9fe767fabd23102d89f6
|
[
"MIT"
] | 1
|
2022-03-06T09:08:12.000Z
|
2022-03-06T09:08:12.000Z
|
# we need to explicitly expose the available imports here
from .gworksheet import GWorksheet
from .misc import *
| 37.333333
| 57
| 0.8125
| 16
| 112
| 5.6875
| 0.8125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.151786
| 112
| 3
| 58
| 37.333333
| 0.957895
| 0.491071
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
9b6f86e81a68737f65a6df5112cb93f40a5d4d65
| 52
|
py
|
Python
|
bridge/__main__.py
|
Paula-Kli/IOT
|
c215a748667265c8da4c00d0473ea17f7da9d21a
|
[
"Apache-2.0"
] | null | null | null |
bridge/__main__.py
|
Paula-Kli/IOT
|
c215a748667265c8da4c00d0473ea17f7da9d21a
|
[
"Apache-2.0"
] | 1
|
2022-02-08T08:55:56.000Z
|
2022-02-08T08:55:56.000Z
|
bridge/__main__.py
|
Paula-Kli/IOT
|
c215a748667265c8da4c00d0473ea17f7da9d21a
|
[
"Apache-2.0"
] | 1
|
2022-02-07T20:26:40.000Z
|
2022-02-07T20:26:40.000Z
|
from .bridge import Bridge
br = Bridge()
br.loop()
| 10.4
| 26
| 0.692308
| 8
| 52
| 4.5
| 0.625
| 0.444444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173077
| 52
| 4
| 27
| 13
| 0.837209
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
32f3aedde05b9caaf0b08bd76d973b0850dd659b
| 27
|
py
|
Python
|
runtimes/xgboost/mlserver_xgboost/version.py
|
shane-breeze/MLServer
|
ebe730211eb7ff0796e5efd1dcd6de0fcb4488d0
|
[
"Apache-2.0"
] | null | null | null |
runtimes/xgboost/mlserver_xgboost/version.py
|
shane-breeze/MLServer
|
ebe730211eb7ff0796e5efd1dcd6de0fcb4488d0
|
[
"Apache-2.0"
] | null | null | null |
runtimes/xgboost/mlserver_xgboost/version.py
|
shane-breeze/MLServer
|
ebe730211eb7ff0796e5efd1dcd6de0fcb4488d0
|
[
"Apache-2.0"
] | null | null | null |
__version__ = "1.1.0.dev3"
| 13.5
| 26
| 0.666667
| 5
| 27
| 2.8
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 0.111111
| 27
| 1
| 27
| 27
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0.37037
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
32fd3be6589d50264cde6fad7f1d03b410451a5c
| 686
|
py
|
Python
|
pybook/ch12/CircleFromGeometicObject.py
|
YanhaoXu/python-learning
|
856687a71635a2ca67dab49d396c238f128e5ec0
|
[
"MIT"
] | 2
|
2021-12-06T13:29:48.000Z
|
2022-01-20T11:39:45.000Z
|
pybook/ch12/CircleFromGeometicObject.py
|
YanhaoXu/python-learning
|
856687a71635a2ca67dab49d396c238f128e5ec0
|
[
"MIT"
] | null | null | null |
pybook/ch12/CircleFromGeometicObject.py
|
YanhaoXu/python-learning
|
856687a71635a2ca67dab49d396c238f128e5ec0
|
[
"MIT"
] | null | null | null |
import math
from GeometricObject import GeometricObject
class Circle(GeometricObject):
def __init__(self, radius):
super().__init__()
self.__radius = radius
def getRadius(self):
return self.__radius
def setRadius(self, raidus):
self.__radius = raidus
def getArea(self):
return math.pi * self.__radius ** 2
def getDiameter(self):
return self.__radius * 2
def getPerimeter(self):
return 2 * self.__radius * math.pi
def printCircle(self):
print(self.__str__() + " radius: " + str(self.__radius))
def __str__(self):
return super().__str__() + " radius: " + str(self.__radius)
| 22.129032
| 67
| 0.626822
| 76
| 686
| 5.184211
| 0.302632
| 0.228426
| 0.071066
| 0.101523
| 0.111675
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005929
| 0.262391
| 686
| 30
| 68
| 22.866667
| 0.772727
| 0
| 0
| 0
| 0
| 0
| 0.026239
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0
| 0.1
| 0.25
| 0.8
| 0.1
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
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