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float64
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int64
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float64
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float64
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float64
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float64
qsc_code_frac_chars_top_4grams_quality_signal
float64
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float64
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float64
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float64
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float64
qsc_code_num_chars_line_mean_quality_signal
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float64
qsc_code_frac_chars_comments_quality_signal
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float64
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float64
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bool
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float64
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float64
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float64
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float64
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int64
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int64
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null
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int64
qsc_code_frac_chars_top_3grams
int64
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int64
qsc_code_frac_chars_hex_words
int64
qsc_code_frac_lines_prompt_comments
int64
qsc_code_frac_lines_assert
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int64
qsc_codepython_frac_lines_func_ratio
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qsc_codepython_cate_var_zero
int64
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int64
qsc_codepython_frac_lines_print
int64
effective
string
hits
int64
6a18a2fc35fca4fa0810d624272b1e9cbf085f8d
108
py
Python
question.py
clash402/quizzer
b1ab6af59e8ebdf3453d19708d366eb2a2fc20da
[ "MIT" ]
3
2021-01-15T15:49:20.000Z
2021-03-17T03:17:41.000Z
question.py
clash402/quizzer
b1ab6af59e8ebdf3453d19708d366eb2a2fc20da
[ "MIT" ]
2
2021-06-10T18:28:21.000Z
2021-09-28T08:26:47.000Z
question.py
clash402/quizzer
b1ab6af59e8ebdf3453d19708d366eb2a2fc20da
[ "MIT" ]
1
2021-07-25T01:55:12.000Z
2021-07-25T01:55:12.000Z
class Question: def __init__(self, text, answer): self.text = text self.answer = answer
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6a3765d6e0c8732d6c84c61c5f319467fe077500
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py
Python
snakeskin_ui/custom_widgets/__init__.py
ewanbarr/snakeskin
b41a5393e9b4ab42fd6245e022dd4923be01815b
[ "Apache-2.0" ]
null
null
null
snakeskin_ui/custom_widgets/__init__.py
ewanbarr/snakeskin
b41a5393e9b4ab42fd6245e022dd4923be01815b
[ "Apache-2.0" ]
null
null
null
snakeskin_ui/custom_widgets/__init__.py
ewanbarr/snakeskin
b41a5393e9b4ab42fd6245e022dd4923be01815b
[ "Apache-2.0" ]
null
null
null
from accordion import Accordion,Chord from drag_drop_listbox import DragDropListBox from dict_controller import DictController from plot_window import PlotWindow
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py
Python
samlab/dashboard/credentials.py
tshead2/samba
1c3dd3a18800e85a6f69ff3a7aa132ee0809a69c
[ "BSD-3-Clause" ]
3
2018-09-04T19:53:20.000Z
2021-07-13T20:26:42.000Z
samlab/dashboard/credentials.py
tshead2/samba
1c3dd3a18800e85a6f69ff3a7aa132ee0809a69c
[ "BSD-3-Clause" ]
15
2018-05-24T19:13:05.000Z
2020-04-21T20:49:31.000Z
samlab/dashboard/credentials.py
tshead2/samba
1c3dd3a18800e85a6f69ff3a7aa132ee0809a69c
[ "BSD-3-Clause" ]
1
2021-07-13T20:26:47.000Z
2021-07-13T20:26:47.000Z
# Copyright 2018, National Technology & Engineering Solutions of Sandia, LLC # (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S. # Government retains certain rights in this software. import logging import traceback log = logging.getLogger(__name__) class LDAP(object): """Check credentials against an LDAP server.""" def __init__(self, server, user_dn, timeout=5): self.server = server self.user_dn = user_dn self.timeout = timeout def __call__(self, authorization): if not authorization: return False try: search_dn = self.user_dn.format(authorization.username) log.info("Checking credentials for %s with %s.", search_dn, self.server) import ldap3 ldap_server = ldap3.Server(self.server, use_ssl=True) connection = ldap3.Connection(ldap_server, user=search_dn, password=authorization.password, receive_timeout=self.timeout) if not connection.bind(): log.warning("Credential check failed.") return False return True except Exception: log.error("%s" % traceback.format_exc()) return False def __repr__(self): return f"{self.__class__.__module__}.{self.__class__.__name__}(server={self.server!r}, user_dn={self.user_dn!r}, timeout={self.timeout!r})" class ExactMatch(object): """Allow credentials that match the given username and password.""" def __init__(self, username="test", password="test"): self.username = username self.password = password def __call__(self, authorization): if not authorization: return False return authorization.username == self.username and authorization.password == self.password def __repr__(self): return f"{self.__class__.__module__}.{self.__class__.__name__}(username={self.username!r}, password={self.password!r})" class ForbidAll(object): """Forbid all credentials.""" def __call__(self, authorization): return False def __repr__(self): return f"{self.__class__.__module__}.{self.__class__.__name__}()" class PermitAll(object): """Permit all non-empty credentials.""" def __call__(self, authorization): return True if authorization else False def __repr__(self): return f"{self.__class__.__module__}.{self.__class__.__name__}()" class PermitAny(object): """Permit any credentials, including empty.""" def __call__(self, authorization): return True def __repr__(self): return f"{self.__class__.__module__}.{self.__class__.__name__}()"
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dbed91716d712c0578f642316e1d5ca206d1a1be
207
py
Python
T.py
Ashokkommi0001/Python-Patterns-Alphabets-Upper_case
0735bb1d7333ea850b91b1a3cf37be659885267b
[ "MIT" ]
null
null
null
T.py
Ashokkommi0001/Python-Patterns-Alphabets-Upper_case
0735bb1d7333ea850b91b1a3cf37be659885267b
[ "MIT" ]
null
null
null
T.py
Ashokkommi0001/Python-Patterns-Alphabets-Upper_case
0735bb1d7333ea850b91b1a3cf37be659885267b
[ "MIT" ]
1
2021-03-08T04:44:56.000Z
2021-03-08T04:44:56.000Z
def T(): for row in range(6): for col in range(5): if (row==0 or col==2): print("*",end=" ") else: print(end=" ") print()
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e002f2850c67afa76f663130b5dd8375150bea7d
170
py
Python
courier/__init__.py
panyam/courier
96a97d454bfc4038d4a9daffbe5a90202ed7bdb3
[ "Apache-2.0" ]
null
null
null
courier/__init__.py
panyam/courier
96a97d454bfc4038d4a9daffbe5a90202ed7bdb3
[ "Apache-2.0" ]
null
null
null
courier/__init__.py
panyam/courier
96a97d454bfc4038d4a9daffbe5a90202ed7bdb3
[ "Apache-2.0" ]
null
null
null
VERSION = (0, 0, 2) def get_version(version = None): version = version or VERSION return ".".join(map(str, list(version))) __version__ = get_version(VERSION)
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4
e00fecd1a3b725cf2e10404b0c3bb1adeba521a1
64
py
Python
k/stdlib/logging/__init__.py
Knewton/k.stdlib
9cf9757721480b845467e37cd6e20e266979412f
[ "Apache-2.0" ]
null
null
null
k/stdlib/logging/__init__.py
Knewton/k.stdlib
9cf9757721480b845467e37cd6e20e266979412f
[ "Apache-2.0" ]
null
null
null
k/stdlib/logging/__init__.py
Knewton/k.stdlib
9cf9757721480b845467e37cd6e20e266979412f
[ "Apache-2.0" ]
null
null
null
"""This module contains improvements to the logging package."""
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1
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0.875
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4
e022eead338624013ac23aadc45d95ba58f02c48
1,122
py
Python
app/grandchallenge/challenges/migrations/0013_auto_20181019_1642.py
Tommos0/grand-challenge.org
187cd857f6a7c9651b7bda8c42c54801f071dd7c
[ "Apache-2.0" ]
1
2021-02-09T10:30:44.000Z
2021-02-09T10:30:44.000Z
app/grandchallenge/challenges/migrations/0013_auto_20181019_1642.py
Tommos0/grand-challenge.org
187cd857f6a7c9651b7bda8c42c54801f071dd7c
[ "Apache-2.0" ]
null
null
null
app/grandchallenge/challenges/migrations/0013_auto_20181019_1642.py
Tommos0/grand-challenge.org
187cd857f6a7c9651b7bda8c42c54801f071dd7c
[ "Apache-2.0" ]
null
null
null
# Generated by Django 2.0.9 on 2018-10-19 16:42 import django.contrib.postgres.fields import django.contrib.postgres.fields.citext from django.db import migrations class Migration(migrations.Migration): dependencies = [("challenges", "0012_auto_20181019_1446")] operations = [ migrations.AlterField( model_name="challenge", name="filter_classes", field=django.contrib.postgres.fields.ArrayField( base_field=django.contrib.postgres.fields.citext.CICharField( max_length=32 ), default=list, editable=False, size=None, ), ), migrations.AlterField( model_name="externalchallenge", name="filter_classes", field=django.contrib.postgres.fields.ArrayField( base_field=django.contrib.postgres.fields.citext.CICharField( max_length=32 ), default=list, editable=False, size=None, ), ), ]
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4
e054ad34a7201de0a8c018bddb342abaa4813ef3
57
py
Python
amazon-sagemaker-pytorch-detectron2/container_training/sku-110k/evaluation/run.py
rodzanto/amazon-sagemaker-pytorch-detectron2
4bdf47705bd949502de0cc8721ba20fb630699c1
[ "MIT-0" ]
22
2021-03-25T14:16:28.000Z
2022-03-29T14:42:23.000Z
amazon-sagemaker-pytorch-detectron2/container_training/sku-110k/evaluation/run.py
rodzanto/amazon-sagemaker-pytorch-detectron2
4bdf47705bd949502de0cc8721ba20fb630699c1
[ "MIT-0" ]
7
2021-04-16T21:00:28.000Z
2022-03-25T08:19:30.000Z
amazon-sagemaker-pytorch-detectron2/container_training/sku-110k/evaluation/run.py
rodzanto/amazon-sagemaker-pytorch-detectron2
4bdf47705bd949502de0cc8721ba20fb630699c1
[ "MIT-0" ]
10
2021-04-03T08:11:28.000Z
2022-03-16T06:35:25.000Z
"""Run COCO evaluation with custom # of max detections"""
57
57
0.736842
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5.25
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0
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1
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57
0.857143
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true
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e063ab33016dc71627fe628f9e136abc7c1ad053
74
py
Python
goal_gen/__init__.py
robotics-4-all/goal-gen
dec88dd9461f6ea0fc972d477fce5675b2a93d8e
[ "MIT" ]
null
null
null
goal_gen/__init__.py
robotics-4-all/goal-gen
dec88dd9461f6ea0fc972d477fce5675b2a93d8e
[ "MIT" ]
null
null
null
goal_gen/__init__.py
robotics-4-all/goal-gen
dec88dd9461f6ea0fc972d477fce5675b2a93d8e
[ "MIT" ]
null
null
null
__version__ = "0.1.0.dev" from .generator import goal_dsl_generate_goalee
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4
e066fbf19a234d02e8aa219f752317105637be32
12,167
py
Python
redis/google/cloud/redis_v1/proto/cloud_redis_pb2_grpc.py
DaveCheez/google-cloud-python
fc03d4d41f13e9d13db7206438163b3a471fdabd
[ "Apache-2.0" ]
2
2021-11-26T07:08:43.000Z
2022-03-07T20:20:04.000Z
redis/google/cloud/redis_v1/proto/cloud_redis_pb2_grpc.py
DaveCheez/google-cloud-python
fc03d4d41f13e9d13db7206438163b3a471fdabd
[ "Apache-2.0" ]
40
2019-07-16T10:04:48.000Z
2020-01-20T09:04:59.000Z
redis/google/cloud/redis_v1/proto/cloud_redis_pb2_grpc.py
DaveCheez/google-cloud-python
fc03d4d41f13e9d13db7206438163b3a471fdabd
[ "Apache-2.0" ]
2
2019-07-18T00:05:31.000Z
2019-11-27T14:17:22.000Z
# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! import grpc from google.cloud.redis_v1.proto import ( cloud_redis_pb2 as google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2, ) from google.longrunning import ( operations_pb2 as google_dot_longrunning_dot_operations__pb2, ) class CloudRedisStub(object): """Configures and manages Cloud Memorystore for Redis instances Google Cloud Memorystore for Redis v1 The `redis.googleapis.com` service implements the Google Cloud Memorystore for Redis API and defines the following resource model for managing Redis instances: * The service works with a collection of cloud projects, named: `/projects/*` * Each project has a collection of available locations, named: `/locations/*` * Each location has a collection of Redis instances, named: `/instances/*` * As such, Redis instances are resources of the form: `/projects/{project_id}/locations/{location_id}/instances/{instance_id}` Note that location_id must be referring to a GCP `region`; for example: * `projects/redpepper-1290/locations/us-central1/instances/my-redis` """ def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.ListInstances = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/ListInstances", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesRequest.SerializeToString, response_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesResponse.FromString, ) self.GetInstance = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/GetInstance", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.GetInstanceRequest.SerializeToString, response_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.Instance.FromString, ) self.CreateInstance = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/CreateInstance", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.CreateInstanceRequest.SerializeToString, response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString, ) self.UpdateInstance = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/UpdateInstance", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.UpdateInstanceRequest.SerializeToString, response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString, ) self.ImportInstance = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/ImportInstance", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ImportInstanceRequest.SerializeToString, response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString, ) self.ExportInstance = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/ExportInstance", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ExportInstanceRequest.SerializeToString, response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString, ) self.FailoverInstance = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/FailoverInstance", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.FailoverInstanceRequest.SerializeToString, response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString, ) self.DeleteInstance = channel.unary_unary( "/google.cloud.redis.v1.CloudRedis/DeleteInstance", request_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.DeleteInstanceRequest.SerializeToString, response_deserializer=google_dot_longrunning_dot_operations__pb2.Operation.FromString, ) class CloudRedisServicer(object): """Configures and manages Cloud Memorystore for Redis instances Google Cloud Memorystore for Redis v1 The `redis.googleapis.com` service implements the Google Cloud Memorystore for Redis API and defines the following resource model for managing Redis instances: * The service works with a collection of cloud projects, named: `/projects/*` * Each project has a collection of available locations, named: `/locations/*` * Each location has a collection of Redis instances, named: `/instances/*` * As such, Redis instances are resources of the form: `/projects/{project_id}/locations/{location_id}/instances/{instance_id}` Note that location_id must be referring to a GCP `region`; for example: * `projects/redpepper-1290/locations/us-central1/instances/my-redis` """ def ListInstances(self, request, context): """Lists all Redis instances owned by a project in either the specified location (region) or all locations. The location should have the following format: * `projects/{project_id}/locations/{location_id}` If `location_id` is specified as `-` (wildcard), then all regions available to the project are queried, and the results are aggregated. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def GetInstance(self, request, context): """Gets the details of a specific Redis instance. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def CreateInstance(self, request, context): """Creates a Redis instance based on the specified tier and memory size. By default, the instance is accessible from the project's [default network](/compute/docs/networks-and-firewalls#networks). The creation is executed asynchronously and callers may check the returned operation to track its progress. Once the operation is completed the Redis instance will be fully functional. Completed longrunning.Operation will contain the new instance object in the response field. The returned operation is automatically deleted after a few hours, so there is no need to call DeleteOperation. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def UpdateInstance(self, request, context): """Updates the metadata and configuration of a specific Redis instance. Completed longrunning.Operation will contain the new instance object in the response field. The returned operation is automatically deleted after a few hours, so there is no need to call DeleteOperation. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def ImportInstance(self, request, context): """Import a Redis RDB snapshot file from Cloud Storage into a Redis instance. Redis may stop serving during this operation. Instance state will be IMPORTING for entire operation. When complete, the instance will contain only data from the imported file. The returned operation is automatically deleted after a few hours, so there is no need to call DeleteOperation. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def ExportInstance(self, request, context): """Export Redis instance data into a Redis RDB format file in Cloud Storage. Redis will continue serving during this operation. The returned operation is automatically deleted after a few hours, so there is no need to call DeleteOperation. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def FailoverInstance(self, request, context): """Initiates a failover of the master node to current replica node for a specific STANDARD tier Cloud Memorystore for Redis instance. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def DeleteInstance(self, request, context): """Deletes a specific Redis instance. Instance stops serving and data is deleted. """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details("Method not implemented!") raise NotImplementedError("Method not implemented!") def add_CloudRedisServicer_to_server(servicer, server): rpc_method_handlers = { "ListInstances": grpc.unary_unary_rpc_method_handler( servicer.ListInstances, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesRequest.FromString, response_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ListInstancesResponse.SerializeToString, ), "GetInstance": grpc.unary_unary_rpc_method_handler( servicer.GetInstance, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.GetInstanceRequest.FromString, response_serializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.Instance.SerializeToString, ), "CreateInstance": grpc.unary_unary_rpc_method_handler( servicer.CreateInstance, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.CreateInstanceRequest.FromString, response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString, ), "UpdateInstance": grpc.unary_unary_rpc_method_handler( servicer.UpdateInstance, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.UpdateInstanceRequest.FromString, response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString, ), "ImportInstance": grpc.unary_unary_rpc_method_handler( servicer.ImportInstance, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ImportInstanceRequest.FromString, response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString, ), "ExportInstance": grpc.unary_unary_rpc_method_handler( servicer.ExportInstance, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.ExportInstanceRequest.FromString, response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString, ), "FailoverInstance": grpc.unary_unary_rpc_method_handler( servicer.FailoverInstance, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.FailoverInstanceRequest.FromString, response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString, ), "DeleteInstance": grpc.unary_unary_rpc_method_handler( servicer.DeleteInstance, request_deserializer=google_dot_cloud_dot_redis__v1_dot_proto_dot_cloud__redis__pb2.DeleteInstanceRequest.FromString, response_serializer=google_dot_longrunning_dot_operations__pb2.Operation.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( "google.cloud.redis.v1.CloudRedis", rpc_method_handlers ) server.add_generic_rpc_handlers((generic_handler,))
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4
0ec11af4715e8154b66219ac91173bbe239bceae
75
py
Python
tests/nutsml/test_viewer.py
maet3608/nuts-ml
2551612a47bc6e9efa534eda0db5d8c5def51887
[ "Apache-2.0" ]
39
2017-02-07T03:22:41.000Z
2021-11-24T20:27:57.000Z
tests/nutsml/test_viewer.py
maet3608/nuts-ml
2551612a47bc6e9efa534eda0db5d8c5def51887
[ "Apache-2.0" ]
19
2017-02-13T22:22:30.000Z
2019-01-31T04:13:39.000Z
tests/nutsml/test_viewer.py
maet3608/nuts-ml
2551612a47bc6e9efa534eda0db5d8c5def51887
[ "Apache-2.0" ]
13
2017-06-01T13:44:54.000Z
2020-09-08T04:51:36.000Z
""" .. module:: test_viewer :synopsis: Unit tests for viewer module """
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4
0ed76e49dae5b7957ad606842a6b2f835a54d450
984
py
Python
Project/spider_middlewares.py
RuanJylf/Scrapy_Frame
fe62dd9c9f6f486114c42b75f3101652e3c8b024
[ "MIT" ]
null
null
null
Project/spider_middlewares.py
RuanJylf/Scrapy_Frame
fe62dd9c9f6f486114c42b75f3101652e3c8b024
[ "MIT" ]
null
null
null
Project/spider_middlewares.py
RuanJylf/Scrapy_Frame
fe62dd9c9f6f486114c42b75f3101652e3c8b024
[ "MIT" ]
null
null
null
# coding=utf-8 class TestSpiderMiddleware1: '''实现爬虫中间件''' def process_request(self, request): ''' 处理请求 :param request:请求 :return: 请求 ''' # print("TestSpiderMiddleware1 -- process_request") return request def process_response(self, response): ''' 处理response :param response:response :return:response ''' # print("TestSpiderMiddleware1 -- process_response") return response class TestSpiderMiddleware2: '''实现爬虫中间件''' def process_request(self, request): ''' 处理请求 :param request:请求 :return: 请求 ''' # print("TestSpiderMiddleware2 -- process_request") return request def process_response(self, response): ''' 处理response :param response:response :return:response ''' # print("TestSpiderMiddleware2 -- process_response") return response
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4
0eda44884ea95f02bed13065b6f0c575d2d2e56f
3,543
py
Python
var/spack/repos/builtin/packages/py-gitpython/package.py
jeanbez/spack
f4e51ce8f366c85bf5aa0eafe078677b42dae1ba
[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]
null
null
null
var/spack/repos/builtin/packages/py-gitpython/package.py
jeanbez/spack
f4e51ce8f366c85bf5aa0eafe078677b42dae1ba
[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]
8
2021-11-09T20:28:40.000Z
2022-03-15T03:26:33.000Z
var/spack/repos/builtin/packages/py-gitpython/package.py
jeanbez/spack
f4e51ce8f366c85bf5aa0eafe078677b42dae1ba
[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]
2
2019-02-08T20:37:20.000Z
2019-03-31T15:19:26.000Z
# Copyright 2013-2022 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from spack.package import * class PyGitpython(PythonPackage): """GitPython is a python library used to interact with Git repositories.""" homepage = "https://gitpython.readthedocs.org" pypi = "GitPython/GitPython-3.1.12.tar.gz" version('3.1.24', sha256='df83fdf5e684fef7c6ee2c02fc68a5ceb7e7e759d08b694088d0cacb4eba59e5') version('3.1.23', sha256='aaae7a3bfdf0a6db30dc1f3aeae47b71cd326d86b936fe2e158aa925fdf1471c') version('3.1.22', sha256='e1589f27c3cd1f33b22db1df194201b5abca6b4cc5450f13f9c371e099c1b24f') version('3.1.20', sha256='df0e072a200703a65387b0cfdf0466e3bab729c0458cf6b7349d0e9877636519') version('3.1.19', sha256='18f4039b96b5567bc4745eb851737ce456a2d499cecd71e84f5c0950e92d0e53') version('3.1.18', sha256='b838a895977b45ab6f0cc926a9045c8d1c44e2b653c1fcc39fe91f42c6e8f05b') version('3.1.17', sha256='ee24bdc93dce357630764db659edaf6b8d664d4ff5447ccfeedd2dc5c253f41e') version('3.1.16', sha256='2bfcd25e6b81fe431fa3ab1f0975986cfddabf7870a323c183f3afbc9447c0c5') version('3.1.15', sha256='05af150f47a5cca3f4b0af289b73aef8cf3c4fe2385015b06220cbcdee48bb6e') version('3.1.14', sha256='be27633e7509e58391f10207cd32b2a6cf5b908f92d9cd30da2e514e1137af61') version('3.1.13', sha256='8621a7e777e276a5ec838b59280ba5272dd144a18169c36c903d8b38b99f750a') version('3.1.12', sha256='42dbefd8d9e2576c496ed0059f3103dcef7125b9ce16f9d5f9c834aed44a1dac') version('3.1.11', sha256='befa4d101f91bad1b632df4308ec64555db684c360bd7d2130b4807d49ce86b8') version('3.1.10', sha256='f488d43600d7299567b59fe41497d313e7c1253a9f2a8ebd2df8af2a1151c71d') version('3.1.9', sha256='a03f728b49ce9597a6655793207c6ab0da55519368ff5961e4a74ae475b9fa8e') version('3.1.8', sha256='080bf8e2cf1a2b907634761c2eaefbe83b69930c94c66ad11b65a8252959f912') version('3.1.7', sha256='2db287d71a284e22e5c2846042d0602465c7434d910406990d5b74df4afb0858') version('3.1.6', sha256='b54969b3262d4647f80ace8e9dd4e3f99ac30cc0f3e766415b349208f810908f') version('3.1.5', sha256='90400ecfa87bac36ac75dfa7b62e83a02017b51759f6eef4494e4de775b2b4be') version('3.1.4', sha256='fa98ce1f05805d59bbc3adb16c0780e5ca43b5ea9422feecf1cd0949a61d947e') version('3.1.3', sha256='e107af4d873daed64648b4f4beb89f89f0cfbe3ef558fc7821ed2331c2f8da1a') version('3.1.2', sha256='864a47472548f3ba716ca202e034c1900f197c0fb3a08f641c20c3cafd15ed94') version('3.1.1', sha256='6d4f10e2aaad1864bb0f17ec06a2c2831534140e5883c350d58b4e85189dab74') version('3.1.0', sha256='e426c3b587bd58c482f0b7fe6145ff4ac7ae6c82673fc656f489719abca6f4cb') version('3.0.9', sha256='7e5df21bfef38505115ad92544fb379e6fedb2753f3b709174c4358cecd0cb97') version('0.3.6', sha256='e6599fcb939cb9b25a015a429702db39de10f2b493655ed5669c49c37707d233') depends_on('python@3.4:', type=('build', 'run')) depends_on('python@3.5:', type=('build', 'run'), when='@3.1.15:') depends_on('python@3.6:', type=('build', 'run'), when='@3.1.18:') depends_on('python@3.7:', type=('build', 'run'), when='@3.1.22:') depends_on('py-setuptools', type='build') depends_on('py-gitdb@4.0.1:4', type=('build', 'run')) depends_on('py-typing-extensions@3.7.4.0:', type=('build', 'run'), when='@3.1.16: ^python@:3.7') depends_on('py-typing-extensions@3.7.4.3:', type=('build', 'run'), when='@3.1.19: ^python@:3.10')
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0ee4739c18627ff1180203a33b555bb38abefc6b
740
py
Python
workout_tracker/exercises/admin.py
e-dang/Workout-Tracker
00a27597ea628cff62b320d616f56b2df4f344a0
[ "MIT" ]
null
null
null
workout_tracker/exercises/admin.py
e-dang/Workout-Tracker
00a27597ea628cff62b320d616f56b2df4f344a0
[ "MIT" ]
null
null
null
workout_tracker/exercises/admin.py
e-dang/Workout-Tracker
00a27597ea628cff62b320d616f56b2df4f344a0
[ "MIT" ]
null
null
null
from django.contrib import admin from .models import ExerciseTemplate, Exercise, WorkloadTemplate, Workload, SetTemplate, Set class ExerciseTemplateAdmin(admin.ModelAdmin): pass class ExerciseAdmin(admin.ModelAdmin): pass class WorkloadTemplateAdmin(admin.ModelAdmin): pass class WorkloadAdmin(admin.ModelAdmin): pass class SetTemplateAdmin(admin.ModelAdmin): pass class SetAdmin(admin.ModelAdmin): pass admin.site.register(ExerciseTemplate, ExerciseTemplateAdmin) admin.site.register(Exercise, ExerciseAdmin) admin.site.register(WorkloadTemplate, WorkloadTemplateAdmin) admin.site.register(Workload, WorkloadAdmin) admin.site.register(SetTemplate, SetTemplateAdmin) admin.site.register(Set, SetAdmin)
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93
21.764706
0.907436
0
0
0.3
0
0
0
0
0
0
0
0
0
1
0
true
0.3
0.1
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0.4
0
0
0
0
null
0
1
1
0
0
0
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0
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0
0
1
1
0
0
0
0
0
4
0efa03064cb2b39b9a66c3e97b004812eacef440
109
py
Python
procuret/errors/error.py
Procuret/procuret-python
2f49cbd3454e33986c84a6c32c0f0ab8f60d4b82
[ "MIT" ]
null
null
null
procuret/errors/error.py
Procuret/procuret-python
2f49cbd3454e33986c84a6c32c0f0ab8f60d4b82
[ "MIT" ]
null
null
null
procuret/errors/error.py
Procuret/procuret-python
2f49cbd3454e33986c84a6c32c0f0ab8f60d4b82
[ "MIT" ]
1
2020-10-28T14:26:21.000Z
2020-10-28T14:26:21.000Z
""" Procuret Python Error Module author: hugh@blinkybeach.com """ class ProcuretError(Exception): pass
10.9
31
0.733945
12
109
6.666667
1
0
0
0
0
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0
0
0
0
0
0.155963
109
9
32
12.111111
0.869565
0.522936
0
0
0
0
0
0
0
0
0
0
0
1
0
true
0.5
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0
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null
0
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null
0
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0
0
0
1
1
0
0
0
0
0
4
1601ae8a693ba138d7b7c1e35c977742c147bfd3
216
py
Python
vol4/191.py
EdisonAlgorithms/ProjectEuler
95025ede2c92dbd3ed2dccc0f8a97e9a3db95ef0
[ "MIT" ]
null
null
null
vol4/191.py
EdisonAlgorithms/ProjectEuler
95025ede2c92dbd3ed2dccc0f8a97e9a3db95ef0
[ "MIT" ]
null
null
null
vol4/191.py
EdisonAlgorithms/ProjectEuler
95025ede2c92dbd3ed2dccc0f8a97e9a3db95ef0
[ "MIT" ]
null
null
null
if __name__ == "__main__": lst = [1, 3, 0, 2, 1, 0, 0, 1] while lst[0] < 30: n, t, a, b, c, d, e, f = lst lst = [n + 1, 2 * t + b - a, c, 2 * b - a + d, t - (a + c), e, f, t] print lst[1]
30.857143
76
0.37037
46
216
1.565217
0.413043
0.111111
0
0
0
0
0
0
0
0
0
0.115385
0.398148
216
6
77
36
0.438462
0
0
0
0
0
0.037037
0
0
0
0
0
0
0
null
null
0
0
null
null
0.166667
0
0
1
null
0
0
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0
0
0
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1
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0
1
0
0
0
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null
0
0
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0
1
0
0
0
0
0
0
0
0
4
16422bad2df1c8e4796f8368f699db522100af5f
142
py
Python
app/models/__init__.py
premanuj/visa-ui
7ee4a6827d1542581a57f2159bb79c666c5157b0
[ "MIT" ]
2
2019-03-10T15:34:24.000Z
2020-06-10T09:34:06.000Z
app/models/__init__.py
premanuj/visa-ui
7ee4a6827d1542581a57f2159bb79c666c5157b0
[ "MIT" ]
1
2018-06-05T15:38:39.000Z
2018-06-05T15:38:39.000Z
app/models/__init__.py
premanuj/visa-ui
7ee4a6827d1542581a57f2159bb79c666c5157b0
[ "MIT" ]
null
null
null
from .base import * from .user import * from .department import * __all__ = ( user.__all__ + base.__all__ + department.__all__ )
14.2
25
0.661972
16
142
4.875
0.375
0.25641
0
0
0
0
0
0
0
0
0
0
0.239437
142
9
26
15.777778
0.722222
0
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0.375
0
0.375
0
1
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0
null
1
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null
0
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0
0
0
0
0
1
0
0
0
0
4
16606fba3a8d5113e0b02672238663e6ab4c647e
121
py
Python
python/testData/inspections/PyTypeCheckerInspection/NewTypeInForeignUnstubbedFile/a.py
alexey-anufriev/intellij-community
ffcd46f14e630acdefcc76e2bfc7c43d2449013a
[ "Apache-2.0" ]
2
2019-04-28T07:48:50.000Z
2020-12-11T14:18:08.000Z
python/testData/inspections/PyTypeCheckerInspection/NewTypeInForeignUnstubbedFile/a.py
alexey-anufriev/intellij-community
ffcd46f14e630acdefcc76e2bfc7c43d2449013a
[ "Apache-2.0" ]
1
2020-07-30T19:04:47.000Z
2020-07-30T19:04:47.000Z
python/testData/inspections/PyTypeCheckerInspection/NewTypeInForeignUnstubbedFile/a.py
bradleesand/intellij-community
750ff9c10333c9c1278c00dbe8d88c877b1b9749
[ "Apache-2.0" ]
1
2020-10-15T05:56:42.000Z
2020-10-15T05:56:42.000Z
from b import ID def func(x: ID): pass func(<warning descr="Expected type 'ID', got 'int' instead">42</warning>)
13.444444
73
0.652893
20
121
3.95
0.8
0
0
0
0
0
0
0
0
0
0
0.020408
0.190083
121
8
74
15.125
0.785714
0
0
0
0
0
0.305785
0
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0
0
null
null
0.25
0.25
null
null
0
1
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null
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0
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1
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0
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null
0
0
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0
1
0
0
1
0
0
0
0
0
4
1661ce160ed44c65a38076e6e70cf5a6d883438c
87
py
Python
2022/Interesting-Libraries/copy-and-paste.py
Muramatsu2602/python-study
c81eb5d2c343817bc29b2763dcdcabed0f6a42c6
[ "MIT" ]
null
null
null
2022/Interesting-Libraries/copy-and-paste.py
Muramatsu2602/python-study
c81eb5d2c343817bc29b2763dcdcabed0f6a42c6
[ "MIT" ]
null
null
null
2022/Interesting-Libraries/copy-and-paste.py
Muramatsu2602/python-study
c81eb5d2c343817bc29b2763dcdcabed0f6a42c6
[ "MIT" ]
null
null
null
import pyperclip pyperclip.copy("This will be on you clipboard...") pyperclip.paste()
17.4
50
0.758621
12
87
5.5
0.833333
0
0
0
0
0
0
0
0
0
0
0
0.114943
87
4
51
21.75
0.857143
0
0
0
0
0
0.367816
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
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null
0
0
0
0
0
0
1
0
1
0
0
0
0
4
16631323fb102edae3a8894779023833ee457448
198
py
Python
src/backend/endpoints/hello.py
PSU-Capstone-Winter-Spring-2021/Eviction-Sponge
cfdc54aeae6d1c76ae6e6c80d5bb8266622f9228
[ "MIT" ]
2
2021-02-11T03:41:27.000Z
2021-03-04T04:05:56.000Z
src/backend/endpoints/hello.py
PSU-Capstone-Winter-Spring-2021/Eviction-Sponge
cfdc54aeae6d1c76ae6e6c80d5bb8266622f9228
[ "MIT" ]
1
2021-04-26T22:10:32.000Z
2021-04-26T22:10:32.000Z
src/backend/endpoints/hello.py
PSU-Capstone-Winter-Spring-2021/Eviction-Sponge
cfdc54aeae6d1c76ae6e6c80d5bb8266622f9228
[ "MIT" ]
null
null
null
from flask.views import MethodView class Hello(MethodView): def get(self): return "Hello, world!" def register(app): app.add_url_rule("/hello", view_func=Hello.as_view("hello"))
18
64
0.686869
28
198
4.714286
0.714286
0
0
0
0
0
0
0
0
0
0
0
0.176768
198
10
65
19.8
0.809816
0
0
0
0
0
0.121212
0
0
0
0
0
0
1
0.333333
false
0
0.166667
0.166667
0.833333
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
1
0
0
0
1
1
0
0
4
166647a57a674201e20f8bc415bb83607a9ab2d3
492
py
Python
src/containment.py
yanstefanovich/rectangles
28cb649328f889167a8f3c5f5279b5bdc5b2d13e
[ "MIT" ]
null
null
null
src/containment.py
yanstefanovich/rectangles
28cb649328f889167a8f3c5f5279b5bdc5b2d13e
[ "MIT" ]
null
null
null
src/containment.py
yanstefanovich/rectangles
28cb649328f889167a8f3c5f5279b5bdc5b2d13e
[ "MIT" ]
null
null
null
def check_line_containment(line_1, line_2): return (line_1[0] <= line_2[0] and line_1[1] >= line_2[1]) def containment(rec_1, rec_2): is__rec_1__in__rec_2 = check_line_containment(rec_1.get('x'), rec_2.get( 'x')) and check_line_containment(rec_1.get('y'), rec_2.get('y')) is__rec_2__in__rec_1 = check_line_containment(rec_2.get('x'), rec_1.get( 'x')) and check_line_containment(rec_2.get('y'), rec_1.get('y')) return is__rec_1__in__rec_2 or is__rec_2__in__rec_1
37.846154
74
0.715447
100
492
2.94
0.16
0.122449
0.340136
0.312925
0.578231
0.578231
0.204082
0
0
0
0
0.065421
0.130081
492
12
75
41
0.621495
0
0
0
0
0
0.01626
0
0
0
0
0
0
1
0.25
false
0
0
0.125
0.5
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
1
0
0
0
4
1666d399a8af367fbd5c9f214310f6b7c31bdc5f
355
py
Python
boilerplate/python/print_module.py
LoLei/design-patterns-examples
213241ab94c8a5e74a3faa9c5f554d557e60b753
[ "MIT" ]
3
2020-02-11T20:37:13.000Z
2020-07-31T14:16:51.000Z
boilerplate/python/print_module.py
LoLei/design-patterns-examples
213241ab94c8a5e74a3faa9c5f554d557e60b753
[ "MIT" ]
null
null
null
boilerplate/python/print_module.py
LoLei/design-patterns-examples
213241ab94c8a5e74a3faa9c5f554d557e60b753
[ "MIT" ]
null
null
null
print('[print_module.py] Begin execution') print('[print_module.py] __name__ is:', __name__) def fancy_module_function(): print('[print_module.py] Running fancy module function') if __name__ == '__main__': import sys if len(sys.argv) == 2 and sys.argv[1] == 'fancy': fancy_module_function() print('[print_module.py] End execution')
27.307692
60
0.695775
49
355
4.55102
0.428571
0.179372
0.286996
0.32287
0.331839
0.331839
0.331839
0
0
0
0
0.006667
0.15493
355
12
61
29.583333
0.736667
0
0
0
0
0
0.433803
0
0
0
0
0
0
1
0.111111
true
0
0.111111
0
0.222222
0.444444
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
0
1
0
4
16832f43b683d0612efb99e27cfe5d2aac740b81
83,112
py
Python
modules/chempy/protein_amber.py
hryknkgw/pymolwin
4a1335e90497dbcbfa789f1285a7c1ad84a051f8
[ "CNRI-Python" ]
2
2019-05-23T22:17:29.000Z
2020-07-03T14:36:22.000Z
Example/feature-3.1.0/tools/bin/protein_amber.py
MukundhMurthy/NucleicNet
fca09d38b9a70d2c402414df7cc06b9dd2824449
[ "BSD-3-Clause" ]
null
null
null
Example/feature-3.1.0/tools/bin/protein_amber.py
MukundhMurthy/NucleicNet
fca09d38b9a70d2c402414df7cc06b9dd2824449
[ "BSD-3-Clause" ]
null
null
null
#A* ------------------------------------------------------------------- #B* This file contains source code for the PyMOL computer program #C* copyright 1998-2000 by Warren Lyford Delano of DeLano Scientific. #D* ------------------------------------------------------------------- #E* It is unlawful to modify or remove this copyright notice. #F* ------------------------------------------------------------------- #G* Please see the accompanying LICENSE file for further information. #H* ------------------------------------------------------------------- #I* Additional authors of this source file include: #-* #-* #-* #Z* ------------------------------------------------------------------- normal = { ('ALA' , '1HB' ) : { 'type' : 'HC' , 'charge' : 0.0603 } , ('ALA' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0603 } , ('ALA' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0603 } , ('ALA' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('ALA' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0337 } , ('ALA' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1825 } , ('ALA' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('ALA' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0823 } , ('ALA' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('ALA' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('CYM' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.2440 } , ('CYM' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.2440 } , ('CYM' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6160 } , ('CYM' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0350 } , ('CYM' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.7360 } , ('CYM' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2520 } , ('CYM' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0480 } , ('CYM' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4630 } , ('CYM' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5040 } , ('CYM' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.7360 } , ('CYS' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1112 } , ('CYS' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1112 } , ('CYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('CYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0213 } , ('CYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1231 } , ('CYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('CYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1124 } , ('CYS' , 'HG' ) : { 'type' : 'HS' , 'charge' : 0.1933 } , ('CYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('CYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('CYS' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.3119 } , ('CYX' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0910 } , ('CYX' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0910 } , ('CYX' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('CYX' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0429 } , ('CYX' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0790 } , ('CYX' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('CYX' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0766 } , ('CYX' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('CYX' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('CYX' , 'SG' ) : { 'type' : 'S' , 'charge' : -0.1081 } , ('ASP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0122 } , ('ASP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0122 } , ('ASP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5366 } , ('ASP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0381 } , ('ASP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0303 } , ('ASP' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.7994 } , ('ASP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2936 } , ('ASP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0880 } , ('ASP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5163 } , ('ASP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5819 } , ('ASP' , 'OD1' ) : { 'type' : 'O2' , 'charge' : -0.8014 } , ('ASP' , 'OD2' ) : { 'type' : 'O2' , 'charge' : -0.8014 } , ('ASH' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0488 } , ('ASH' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0488 } , ('ASH' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('ASH' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0341 } , ('ASH' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0316 } , ('ASH' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.6462 } , ('ASH' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('ASH' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0864 } , ('ASH' , 'HD2' ) : { 'type' : 'HO' , 'charge' : 0.4747 } , ('ASH' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('ASH' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('ASH' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.5554 } , ('ASH' , 'OD2' ) : { 'type' : 'OH' , 'charge' : -0.6376 } , ('GLU' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0173 } , ('GLU' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0425 } , ('GLU' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0173 } , ('GLU' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0425 } , ('GLU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5366 } , ('GLU' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0397 } , ('GLU' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0560 } , ('GLU' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8054 } , ('GLU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0136 } , ('GLU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2936 } , ('GLU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1105 } , ('GLU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5163 } , ('GLU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5819 } , ('GLU' , 'OE1' ) : { 'type' : 'O2' , 'charge' : -0.8188 } , ('GLU' , 'OE2' ) : { 'type' : 'O2' , 'charge' : -0.8188 } , ('GLP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } , ('GLP' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0430 } , ('GLP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } , ('GLP' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0430 } , ('GLP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('GLP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0145 } , ('GLP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0071 } , ('GLP' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.6801 } , ('GLP' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0174 } , ('GLP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('GLP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0779 } , ('GLP' , 'HE2' ) : { 'type' : 'HO' , 'charge' : 0.4641 } , ('GLP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('GLP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('GLP' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.5838 } , ('GLP' , 'OE2' ) : { 'type' : 'OH' , 'charge' : -0.6511 } , ('PHE' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1330 } , ('PHE' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1430 } , ('PHE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } , ('PHE' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1330 } , ('PHE' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1430 } , ('PHE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } , ('PHE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('PHE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0024 } , ('PHE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0343 } , ('PHE' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1256 } , ('PHE' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1256 } , ('PHE' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.1704 } , ('PHE' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.1704 } , ('PHE' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0118 } , ('PHE' , 'CZ' ) : { 'type' : 'CA' , 'charge' : -0.1072 } , ('PHE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('PHE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0978 } , ('PHE' , 'HZ' ) : { 'type' : 'HA' , 'charge' : 0.1297 } , ('PHE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('PHE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('GLY' , '3HA' ) : { 'type' : 'H1' , 'charge' : 0.0698 } , ('GLY' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('GLY' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0252 } , ('GLY' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('GLY' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0698 } , ('GLY' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('GLY' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('HIP' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3866 } , ('HIP' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.2681 } , ('HIP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0810 } , ('HIP' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.2317 } , ('HIP' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3911 } , ('HIP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0810 } , ('HIP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7341 } , ('HIP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1354 } , ('HIP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0414 } , ('HIP' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.1141 } , ('HIP' , 'CE1' ) : { 'type' : 'CR' , 'charge' : -0.0170 } , ('HIP' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0012 } , ('HIP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2747 } , ('HIP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1212 } , ('HIP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3479 } , ('HIP' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.1513 } , ('HIP' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.1718 } , ('HIP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5894 } , ('HIE' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1435 } , ('HIE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0367 } , ('HIE' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1862 } , ('HIE' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3339 } , ('HIE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0367 } , ('HIE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('HIE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0581 } , ('HIE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0074 } , ('HIE' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.2207 } , ('HIE' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1635 } , ('HIE' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.1868 } , ('HIE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('HIE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1360 } , ('HIE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('HIE' , 'ND1' ) : { 'type' : 'NB' , 'charge' : -0.5432 } , ('HIE' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.2795 } , ('HIE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('HID' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3649 } , ('HID' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1392 } , ('HID' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0402 } , ('HID' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1147 } , ('HID' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0402 } , ('HID' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('HID' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0188 } , ('HID' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0462 } , ('HID' , 'CD2' ) : { 'type' : 'CV' , 'charge' : 0.1292 } , ('HID' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.2057 } , ('HID' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0266 } , ('HID' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('HID' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0881 } , ('HID' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('HID' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.3811 } , ('HID' , 'NE2' ) : { 'type' : 'NB' , 'charge' : -0.5727 } , ('HID' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('ILE' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0186 } , ('ILE' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0882 } , ('ILE' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0186 } , ('ILE' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0236 } , ('ILE' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0882 } , ('ILE' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0186 } , ('ILE' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0236 } , ('ILE' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0882 } , ('ILE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('ILE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0597 } , ('ILE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1303 } , ('ILE' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.0660 } , ('ILE' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.0430 } , ('ILE' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3204 } , ('ILE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('ILE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0869 } , ('ILE' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0187 } , ('ILE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('ILE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('LYS' , '1HZ' ) : { 'type' : 'H' , 'charge' : 0.3400 } , ('LYS' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0362 } , ('LYS' , '2HD' ) : { 'type' : 'HC' , 'charge' : 0.0621 } , ('LYS' , '2HE' ) : { 'type' : 'HP' , 'charge' : 0.1135 } , ('LYS' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0103 } , ('LYS' , '2HZ' ) : { 'type' : 'H' , 'charge' : 0.3400 } , ('LYS' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0362 } , ('LYS' , '3HD' ) : { 'type' : 'HC' , 'charge' : 0.0621 } , ('LYS' , '3HE' ) : { 'type' : 'HP' , 'charge' : 0.1135 } , ('LYS' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0103 } , ('LYS' , '3HZ' ) : { 'type' : 'H' , 'charge' : 0.3400 } , ('LYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7341 } , ('LYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2400 } , ('LYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0094 } , ('LYS' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0479 } , ('LYS' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0143 } , ('LYS' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0187 } , ('LYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2747 } , ('LYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1426 } , ('LYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3479 } , ('LYS' , 'NZ' ) : { 'type' : 'N3' , 'charge' : -0.3854 } , ('LYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5894 } , ('LEU' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('LEU' , '1HD2' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('LEU' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0457 } , ('LEU' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('LEU' , '2HD2' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('LEU' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0457 } , ('LEU' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('LEU' , '3HD2' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('LEU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('LEU' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0518 } , ('LEU' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1102 } , ('LEU' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.4121 } , ('LEU' , 'CD2' ) : { 'type' : 'CT' , 'charge' : -0.4121 } , ('LEU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.3531 } , ('LEU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('LEU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0922 } , ('LEU' , 'HG' ) : { 'type' : 'HC' , 'charge' : -0.0361 } , ('LEU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('LEU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('MET' , '1HE' ) : { 'type' : 'H1' , 'charge' : 0.0684 } , ('MET' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0241 } , ('MET' , '2HE' ) : { 'type' : 'H1' , 'charge' : 0.0684 } , ('MET' , '2HG' ) : { 'type' : 'H1' , 'charge' : 0.0440 } , ('MET' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0241 } , ('MET' , '3HE' ) : { 'type' : 'H1' , 'charge' : 0.0684 } , ('MET' , '3HG' ) : { 'type' : 'H1' , 'charge' : 0.0440 } , ('MET' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('MET' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0237 } , ('MET' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0342 } , ('MET' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0536 } , ('MET' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0018 } , ('MET' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('MET' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0880 } , ('MET' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('MET' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('MET' , 'SD' ) : { 'type' : 'S' , 'charge' : -0.2737 } , ('ASN' , '1HD2' ) : { 'type' : 'H' , 'charge' : 0.4196 } , ('ASN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0797 } , ('ASN' , '2HD2' ) : { 'type' : 'H' , 'charge' : 0.4196 } , ('ASN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0797 } , ('ASN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('ASN' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0143 } , ('ASN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2041 } , ('ASN' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.7130 } , ('ASN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('ASN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1048 } , ('ASN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('ASN' , 'ND2' ) : { 'type' : 'N' , 'charge' : -0.9191 } , ('ASN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('ASN' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.5931 } , ('PRO' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0253 } , ('PRO' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0391 } , ('PRO' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0213 } , ('PRO' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0253 } , ('PRO' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0391 } , ('PRO' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0213 } , ('PRO' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5896 } , ('PRO' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0266 } , ('PRO' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0070 } , ('PRO' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0192 } , ('PRO' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0189 } , ('PRO' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0641 } , ('PRO' , 'N' ) : { 'type' : 'N' , 'charge' : -0.2548 } , ('PRO' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5748 } , ('GLN' , '1HE2' ) : { 'type' : 'H' , 'charge' : 0.4251 } , ('GLN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0171 } , ('GLN' , '2HE2' ) : { 'type' : 'H' , 'charge' : 0.4251 } , ('GLN' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0352 } , ('GLN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0171 } , ('GLN' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0352 } , ('GLN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('GLN' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0031 } , ('GLN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0036 } , ('GLN' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.6951 } , ('GLN' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0645 } , ('GLN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('GLN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0850 } , ('GLN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('GLN' , 'NE2' ) : { 'type' : 'N' , 'charge' : -0.9407 } , ('GLN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('GLN' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.6086 } , ('ARG' , '1HH1' ) : { 'type' : 'H' , 'charge' : 0.4478 } , ('ARG' , '1HH2' ) : { 'type' : 'H' , 'charge' : 0.4478 } , ('ARG' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0327 } , ('ARG' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0687 } , ('ARG' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0285 } , ('ARG' , '2HH1' ) : { 'type' : 'H' , 'charge' : 0.4478 } , ('ARG' , '2HH2' ) : { 'type' : 'H' , 'charge' : 0.4478 } , ('ARG' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0327 } , ('ARG' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0687 } , ('ARG' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0285 } , ('ARG' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7341 } , ('ARG' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2637 } , ('ARG' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0007 } , ('ARG' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0486 } , ('ARG' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0390 } , ('ARG' , 'CZ' ) : { 'type' : 'CA' , 'charge' : 0.8076 } , ('ARG' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2747 } , ('ARG' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1560 } , ('ARG' , 'HE' ) : { 'type' : 'H' , 'charge' : 0.3456 } , ('ARG' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3479 } , ('ARG' , 'NE' ) : { 'type' : 'N2' , 'charge' : -0.5295 } , ('ARG' , 'NH1' ) : { 'type' : 'N2' , 'charge' : -0.8627 } , ('ARG' , 'NH2' ) : { 'type' : 'N2' , 'charge' : -0.8627 } , ('ARG' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5894 } , ('SER' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0352 } , ('SER' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0352 } , ('SER' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('SER' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0249 } , ('SER' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.2117 } , ('SER' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('SER' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0843 } , ('SER' , 'HG' ) : { 'type' : 'HO' , 'charge' : 0.4275 } , ('SER' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('SER' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('SER' , 'OG' ) : { 'type' : 'OH' , 'charge' : -0.6546 } , ('THR' , '1HG' ) : { 'type' : 'HO' , 'charge' : 0.4102 } , ('THR' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0642 } , ('THR' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0642 } , ('THR' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0642 } , ('THR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('THR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0389 } , ('THR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.3654 } , ('THR' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.2438 } , ('THR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('THR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1007 } , ('THR' , 'HB' ) : { 'type' : 'H1' , 'charge' : 0.0043 } , ('THR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('THR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('THR' , 'OG1' ) : { 'type' : 'OH' , 'charge' : -0.6761 } , ('VAL' , '1HG1' ) : { 'type' : 'HC' , 'charge' : 0.0791 } , ('VAL' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0791 } , ('VAL' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0791 } , ('VAL' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0791 } , ('VAL' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0791 } , ('VAL' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0791 } , ('VAL' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('VAL' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0875 } , ('VAL' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.2985 } , ('VAL' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.3192 } , ('VAL' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3192 } , ('VAL' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('VAL' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0969 } , ('VAL' , 'HB' ) : { 'type' : 'HC' , 'charge' : -0.0297 } , ('VAL' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('VAL' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('TRP' , '1HD' ) : { 'type' : 'H4' , 'charge' : 0.2062 } , ('TRP' , '1HE' ) : { 'type' : 'H' , 'charge' : 0.3412 } , ('TRP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0339 } , ('TRP' , '2HH' ) : { 'type' : 'HA' , 'charge' : 0.1417 } , ('TRP' , '2HZ' ) : { 'type' : 'HA' , 'charge' : 0.1572 } , ('TRP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0339 } , ('TRP' , '3HE' ) : { 'type' : 'HA' , 'charge' : 0.1700 } , ('TRP' , '3HZ' ) : { 'type' : 'HA' , 'charge' : 0.1447 } , ('TRP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('TRP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0275 } , ('TRP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0050 } , ('TRP' , 'CD1' ) : { 'type' : 'CW' , 'charge' : -0.1638 } , ('TRP' , 'CD2' ) : { 'type' : 'CB' , 'charge' : 0.1243 } , ('TRP' , 'CE2' ) : { 'type' : 'CN' , 'charge' : 0.1380 } , ('TRP' , 'CE3' ) : { 'type' : 'CA' , 'charge' : -0.2387 } , ('TRP' , 'CG' ) : { 'type' : 'C*' , 'charge' : -0.1415 } , ('TRP' , 'CH2' ) : { 'type' : 'CA' , 'charge' : -0.1134 } , ('TRP' , 'CZ2' ) : { 'type' : 'CA' , 'charge' : -0.2601 } , ('TRP' , 'CZ3' ) : { 'type' : 'CA' , 'charge' : -0.1972 } , ('TRP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('TRP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1123 } , ('TRP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('TRP' , 'NE1' ) : { 'type' : 'NA' , 'charge' : -0.3418 } , ('TRP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('TYR' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1699 } , ('TYR' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1656 } , ('TYR' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } , ('TYR' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1699 } , ('TYR' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1656 } , ('TYR' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0295 } , ('TYR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5973 } , ('TYR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0014 } , ('TYR' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0152 } , ('TYR' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1906 } , ('TYR' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1906 } , ('TYR' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.2341 } , ('TYR' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.2341 } , ('TYR' , 'CG' ) : { 'type' : 'CA' , 'charge' : -0.0011 } , ('TYR' , 'CZ' ) : { 'type' : 'C' , 'charge' : 0.3226 } , ('TYR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('TYR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0876 } , ('TYR' , 'HH' ) : { 'type' : 'HO' , 'charge' : 0.3992 } , ('TYR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('TYR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , ('TYR' , 'OH' ) : { 'type' : 'OH' , 'charge' : -0.5579 } , ('NME' , '1HH3' ) : { 'type' : 'H1' , 'charge' : 0.0976 } , ('NME' , '2HH3' ) : { 'type' : 'H1' , 'charge' : 0.0976 } , ('NME' , '3HH3' ) : { 'type' : 'H1' , 'charge' : 0.0976 } , ('NME' , 'CH3' ) : { 'type' : 'CT' , 'charge' : -0.1490 } , ('NME' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2719 } , ('NME' , 'N' ) : { 'type' : 'N' , 'charge' : -0.4157 } , ('ACE' , '1HH3' ) : { 'type' : 'HC' , 'charge' : 0.1123 } , ('ACE' , '2HH3' ) : { 'type' : 'HC' , 'charge' : 0.1123 } , ('ACE' , '3HH3' ) : { 'type' : 'HC' , 'charge' : 0.1123 } , ('ACE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5972 } , ('ACE' , 'CH3' ) : { 'type' : 'CT' , 'charge' : -0.3662 } , ('ACE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5679 } , } n_terminal = { ('ALA' , '1HB' ) : { 'type' : 'HC' , 'charge' : 0.0300 } , ('ALA' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1997 } , ('ALA' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0300 } , ('ALA' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1997 } , ('ALA' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0300 } , ('ALA' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1997 } , ('ALA' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } , ('ALA' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0962 } , ('ALA' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0597 } , ('ALA' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0889 } , ('ALA' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1414 } , ('ALA' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } , ('CYS' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2023 } , ('CYS' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1188 } , ('CYS' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2023 } , ('CYS' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1188 } , ('CYS' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2023 } , ('CYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('CYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0927 } , ('CYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1195 } , ('CYS' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1411 } , ('CYS' , 'HG' ) : { 'type' : 'HS' , 'charge' : 0.1975 } , ('CYS' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1325 } , ('CYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('CYS' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.3298 } , ('CYX' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1815 } , ('CYX' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0680 } , ('CYX' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1815 } , ('CYX' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0680 } , ('CYX' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1815 } , ('CYX' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('CYX' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.1055 } , ('CYX' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0277 } , ('CYX' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0922 } , ('CYX' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.2069 } , ('CYX' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('CYX' , 'SG' ) : { 'type' : 'S' , 'charge' : -0.0984 } , ('ASP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } , ('ASP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } , ('ASP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } , ('ASP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } , ('ASP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } , ('ASP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } , ('ASP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0292 } , ('ASP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0235 } , ('ASP' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8194 } , ('ASP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1141 } , ('ASP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0782 } , ('ASP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } , ('ASP' , 'OD1' ) : { 'type' : 'O2' , 'charge' : -0.8084 } , ('ASP' , 'OD2' ) : { 'type' : 'O2' , 'charge' : -0.8084 } , ('ASH' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } , ('ASH' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } , ('ASH' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } , ('ASH' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0169 } , ('ASH' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2200 } , ('ASH' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } , ('ASH' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0292 } , ('ASH' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0235 } , ('ASH' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8194 } , ('ASH' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1141 } , ('ASH' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0782 } , ('ASH' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } , ('ASH' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.8084 } , ('ASH' , 'OD2' ) : { 'type' : 'OH' , 'charge' : -0.8084 } , ('GLU' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } , ('GLU' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } , ('GLU' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } , ('GLU' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } , ('GLU' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } , ('GLU' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } , ('GLU' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } , ('GLU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } , ('GLU' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0588 } , ('GLU' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0909 } , ('GLU' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8087 } , ('GLU' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0236 } , ('GLU' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1202 } , ('GLU' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0017 } , ('GLU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } , ('GLU' , 'OE1' ) : { 'type' : 'O2' , 'charge' : -0.8189 } , ('GLU' , 'OE2' ) : { 'type' : 'O2' , 'charge' : -0.8189 } , ('GLP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } , ('GLP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } , ('GLP' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } , ('GLP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } , ('GLP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0232 } , ('GLP' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0315 } , ('GLP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2391 } , ('GLP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5621 } , ('GLP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0588 } , ('GLP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0909 } , ('GLP' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8087 } , ('GLP' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0236 } , ('GLP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1202 } , ('GLP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0017 } , ('GLP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5889 } , ('GLP' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.8189 } , ('GLP' , 'OE2' ) : { 'type' : 'OH' , 'charge' : -0.8189 } , ('PHE' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1374 } , ('PHE' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1433 } , ('PHE' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } , ('PHE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0104 } , ('PHE' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1374 } , ('PHE' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1433 } , ('PHE' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } , ('PHE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0104 } , ('PHE' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } , ('PHE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('PHE' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0733 } , ('PHE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0330 } , ('PHE' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1392 } , ('PHE' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1391 } , ('PHE' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.1602 } , ('PHE' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.1603 } , ('PHE' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0031 } , ('PHE' , 'CZ' ) : { 'type' : 'CA' , 'charge' : -0.1208 } , ('PHE' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1041 } , ('PHE' , 'HZ' ) : { 'type' : 'HA' , 'charge' : 0.1329 } , ('PHE' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1737 } , ('PHE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('GLY' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1642 } , ('GLY' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1642 } , ('GLY' , '3HA' ) : { 'type' : 'H1' , 'charge' : 0.0895 } , ('GLY' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1642 } , ('GLY' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } , ('GLY' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0100 } , ('GLY' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0895 } , ('GLY' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.2943 } , ('GLY' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } , ('HIP' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3821 } , ('HIP' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.2645 } , ('HIP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1704 } , ('HIP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0531 } , ('HIP' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.2495 } , ('HIP' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3921 } , ('HIP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1704 } , ('HIP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0531 } , ('HIP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1704 } , ('HIP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7214 } , ('HIP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0581 } , ('HIP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0484 } , ('HIP' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.1433 } , ('HIP' , 'CE1' ) : { 'type' : 'CR' , 'charge' : -0.0011 } , ('HIP' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0236 } , ('HIP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1047 } , ('HIP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.2560 } , ('HIP' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.1510 } , ('HIP' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.1739 } , ('HIP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.6013 } , ('HIE' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1397 } , ('HIE' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2016 } , ('HIE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0223 } , ('HIE' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1963 } , ('HIE' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3324 } , ('HIE' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2016 } , ('HIE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0223 } , ('HIE' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2016 } , ('HIE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('HIE' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0236 } , ('HIE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0489 } , ('HIE' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.2349 } , ('HIE' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1804 } , ('HIE' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.1740 } , ('HIE' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1380 } , ('HIE' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1472 } , ('HIE' , 'ND1' ) : { 'type' : 'NB' , 'charge' : -0.5579 } , ('HIE' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.2781 } , ('HIE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('HID' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3632 } , ('HID' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1385 } , ('HID' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1963 } , ('HID' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0209 } , ('HID' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1299 } , ('HID' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1963 } , ('HID' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0209 } , ('HID' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1963 } , ('HID' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('HID' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0964 } , ('HID' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0259 } , ('HID' , 'CD2' ) : { 'type' : 'CV' , 'charge' : 0.1046 } , ('HID' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.2127 } , ('HID' , 'CG' ) : { 'type' : 'CC' , 'charge' : -0.0399 } , ('HID' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0958 } , ('HID' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1542 } , ('HID' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.3819 } , ('HID' , 'NE2' ) : { 'type' : 'NB' , 'charge' : -0.5711 } , ('HID' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('ILE' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0226 } , ('ILE' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0947 } , ('ILE' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2329 } , ('ILE' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0226 } , ('ILE' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0201 } , ('ILE' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0947 } , ('ILE' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2329 } , ('ILE' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0226 } , ('ILE' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0201 } , ('ILE' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0947 } , ('ILE' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2329 } , ('ILE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('ILE' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0257 } , ('ILE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1885 } , ('ILE' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.0908 } , ('ILE' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.0387 } , ('ILE' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3720 } , ('ILE' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1031 } , ('ILE' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0213 } , ('ILE' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0311 } , ('ILE' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('LYS' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2165 } , ('LYS' , '1HZ' ) : { 'type' : 'H' , 'charge' : 0.3382 } , ('LYS' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0283 } , ('LYS' , '2HD' ) : { 'type' : 'HC' , 'charge' : 0.0633 } , ('LYS' , '2HE' ) : { 'type' : 'HP' , 'charge' : 0.1171 } , ('LYS' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0121 } , ('LYS' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2165 } , ('LYS' , '2HZ' ) : { 'type' : 'H' , 'charge' : 0.3382 } , ('LYS' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0283 } , ('LYS' , '3HD' ) : { 'type' : 'HC' , 'charge' : 0.0633 } , ('LYS' , '3HE' ) : { 'type' : 'HP' , 'charge' : 0.1171 } , ('LYS' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0121 } , ('LYS' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2165 } , ('LYS' , '3HZ' ) : { 'type' : 'H' , 'charge' : 0.3382 } , ('LYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7214 } , ('LYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0015 } , ('LYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0212 } , ('LYS' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0608 } , ('LYS' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0181 } , ('LYS' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0048 } , ('LYS' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1180 } , ('LYS' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0966 } , ('LYS' , 'NZ' ) : { 'type' : 'N3' , 'charge' : -0.3764 } , ('LYS' , 'O' ) : { 'type' : 'O' , 'charge' : -0.6013 } , ('LEU' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0980 } , ('LEU' , '1HD2' ) : { 'type' : 'HC' , 'charge' : 0.0980 } , ('LEU' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2148 } , ('LEU' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } , ('LEU' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0980 } , ('LEU' , '2HD2' ) : { 'type' : 'HC' , 'charge' : 0.0980 } , ('LEU' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2148 } , ('LEU' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0256 } , ('LEU' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0980 } , ('LEU' , '3HD2' ) : { 'type' : 'HC' , 'charge' : 0.0980 } , ('LEU' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2148 } , ('LEU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('LEU' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0104 } , ('LEU' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0244 } , ('LEU' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.4106 } , ('LEU' , 'CD2' ) : { 'type' : 'CT' , 'charge' : -0.4104 } , ('LEU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.3421 } , ('LEU' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1053 } , ('LEU' , 'HG' ) : { 'type' : 'HC' , 'charge' : -0.0380 } , ('LEU' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1010 } , ('LEU' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('MET' , '1HE' ) : { 'type' : 'H1' , 'charge' : 0.0597 } , ('MET' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1984 } , ('MET' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0125 } , ('MET' , '2HE' ) : { 'type' : 'H1' , 'charge' : 0.0597 } , ('MET' , '2HG' ) : { 'type' : 'H1' , 'charge' : 0.0292 } , ('MET' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1984 } , ('MET' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0125 } , ('MET' , '3HE' ) : { 'type' : 'H1' , 'charge' : 0.0597 } , ('MET' , '3HG' ) : { 'type' : 'H1' , 'charge' : 0.0292 } , ('MET' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1984 } , ('MET' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('MET' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0221 } , ('MET' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0865 } , ('MET' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0341 } , ('MET' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0334 } , ('MET' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1116 } , ('MET' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1592 } , ('MET' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('MET' , 'SD' ) : { 'type' : 'S' , 'charge' : -0.2774 } , ('ASN' , '1HD2' ) : { 'type' : 'H' , 'charge' : 0.4097 } , ('ASN' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } , ('ASN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0515 } , ('ASN' , '2HD2' ) : { 'type' : 'H' , 'charge' : 0.4097 } , ('ASN' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } , ('ASN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0515 } , ('ASN' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1921 } , ('ASN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } , ('ASN' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0368 } , ('ASN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0283 } , ('ASN' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.5833 } , ('ASN' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1231 } , ('ASN' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1801 } , ('ASN' , 'ND2' ) : { 'type' : 'N' , 'charge' : -0.8634 } , ('ASN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } , ('ASN' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.5744 } , ('PRO' , '2H' ) : { 'type' : 'H' , 'charge' : 0.3120 } , ('PRO' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('PRO' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.1000 } , ('PRO' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('PRO' , '3H' ) : { 'type' : 'H' , 'charge' : 0.3120 } , ('PRO' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('PRO' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.1000 } , ('PRO' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.1000 } , ('PRO' , 'C' ) : { 'type' : 'C' , 'charge' : 0.5260 } , ('PRO' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.1000 } , ('PRO' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1150 } , ('PRO' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0120 } , ('PRO' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.1210 } , ('PRO' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1000 } , ('PRO' , 'N' ) : { 'type' : 'N3' , 'charge' : -0.2020 } , ('PRO' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5000 } , ('GLN' , '1HE2' ) : { 'type' : 'H' , 'charge' : 0.4429 } , ('GLN' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1996 } , ('GLN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0050 } , ('GLN' , '2HE2' ) : { 'type' : 'H' , 'charge' : 0.4429 } , ('GLN' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0331 } , ('GLN' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1996 } , ('GLN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0050 } , ('GLN' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0331 } , ('GLN' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1996 } , ('GLN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('GLN' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0536 } , ('GLN' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0651 } , ('GLN' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.7354 } , ('GLN' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0903 } , ('GLN' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1015 } , ('GLN' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1493 } , ('GLN' , 'NE2' ) : { 'type' : 'N' , 'charge' : -1.0031 } , ('GLN' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('GLN' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.6133 } , ('ARG' , '1HH1' ) : { 'type' : 'H' , 'charge' : 0.4494 } , ('ARG' , '1HH2' ) : { 'type' : 'H' , 'charge' : 0.4494 } , ('ARG' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2083 } , ('ARG' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0226 } , ('ARG' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0527 } , ('ARG' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0309 } , ('ARG' , '2HH1' ) : { 'type' : 'H' , 'charge' : 0.4494 } , ('ARG' , '2HH2' ) : { 'type' : 'H' , 'charge' : 0.4494 } , ('ARG' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2083 } , ('ARG' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0226 } , ('ARG' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0527 } , ('ARG' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0309 } , ('ARG' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2083 } , ('ARG' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7214 } , ('ARG' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0223 } , ('ARG' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0118 } , ('ARG' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0935 } , ('ARG' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0236 } , ('ARG' , 'CZ' ) : { 'type' : 'CA' , 'charge' : 0.8281 } , ('ARG' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1242 } , ('ARG' , 'HE' ) : { 'type' : 'H' , 'charge' : 0.3592 } , ('ARG' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1305 } , ('ARG' , 'NE' ) : { 'type' : 'N2' , 'charge' : -0.5650 } , ('ARG' , 'NH1' ) : { 'type' : 'N2' , 'charge' : -0.8693 } , ('ARG' , 'NH2' ) : { 'type' : 'N2' , 'charge' : -0.8693 } , ('ARG' , 'O' ) : { 'type' : 'O' , 'charge' : -0.6013 } , ('SER' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1898 } , ('SER' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0273 } , ('SER' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1898 } , ('SER' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0273 } , ('SER' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1898 } , ('SER' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } , ('SER' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0567 } , ('SER' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.2596 } , ('SER' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0782 } , ('SER' , 'HG' ) : { 'type' : 'HO' , 'charge' : 0.4239 } , ('SER' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1849 } , ('SER' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } , ('SER' , 'OG' ) : { 'type' : 'OH' , 'charge' : -0.6714 } , ('THR' , '1HG' ) : { 'type' : 'HO' , 'charge' : 0.4070 } , ('THR' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0627 } , ('THR' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1934 } , ('THR' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0627 } , ('THR' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1934 } , ('THR' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0627 } , ('THR' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1934 } , ('THR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } , ('THR' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0034 } , ('THR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.4514 } , ('THR' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.2554 } , ('THR' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1087 } , ('THR' , 'HB' ) : { 'type' : 'H1' , 'charge' : -0.0323 } , ('THR' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1812 } , ('THR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } , ('THR' , 'OG1' ) : { 'type' : 'OH' , 'charge' : -0.6764 } , ('VAL' , '1HG1' ) : { 'type' : 'HC' , 'charge' : 0.0735 } , ('VAL' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0735 } , ('VAL' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.2272 } , ('VAL' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0735 } , ('VAL' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0735 } , ('VAL' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.2272 } , ('VAL' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0735 } , ('VAL' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0735 } , ('VAL' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.2272 } , ('VAL' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6163 } , ('VAL' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.0054 } , ('VAL' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.3196 } , ('VAL' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.3129 } , ('VAL' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3129 } , ('VAL' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1093 } , ('VAL' , 'HB' ) : { 'type' : 'HC' , 'charge' : -0.0221 } , ('VAL' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.0577 } , ('VAL' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5722 } , ('TRP' , '1HD' ) : { 'type' : 'H4' , 'charge' : 0.2195 } , ('TRP' , '1HE' ) : { 'type' : 'H' , 'charge' : 0.3412 } , ('TRP' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1888 } , ('TRP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0222 } , ('TRP' , '2HH' ) : { 'type' : 'HA' , 'charge' : 0.1411 } , ('TRP' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1888 } , ('TRP' , '2HZ' ) : { 'type' : 'HA' , 'charge' : 0.1589 } , ('TRP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0222 } , ('TRP' , '3HE' ) : { 'type' : 'HA' , 'charge' : 0.1646 } , ('TRP' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1888 } , ('TRP' , '3HZ' ) : { 'type' : 'HA' , 'charge' : 0.1458 } , ('TRP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('TRP' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0421 } , ('TRP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0543 } , ('TRP' , 'CD1' ) : { 'type' : 'CW' , 'charge' : -0.1788 } , ('TRP' , 'CD2' ) : { 'type' : 'CB' , 'charge' : 0.1132 } , ('TRP' , 'CE2' ) : { 'type' : 'CN' , 'charge' : 0.1575 } , ('TRP' , 'CE3' ) : { 'type' : 'CA' , 'charge' : -0.2265 } , ('TRP' , 'CG' ) : { 'type' : 'C*' , 'charge' : -0.1654 } , ('TRP' , 'CH2' ) : { 'type' : 'CA' , 'charge' : -0.1080 } , ('TRP' , 'CZ2' ) : { 'type' : 'CA' , 'charge' : -0.2710 } , ('TRP' , 'CZ3' ) : { 'type' : 'CA' , 'charge' : -0.2034 } , ('TRP' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.1162 } , ('TRP' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1913 } , ('TRP' , 'NE1' ) : { 'type' : 'NA' , 'charge' : -0.3444 } , ('TRP' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('TYR' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1720 } , ('TYR' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1650 } , ('TYR' , '1HT' ) : { 'type' : 'H' , 'charge' : 0.1873 } , ('TYR' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0102 } , ('TYR' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1720 } , ('TYR' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1650 } , ('TYR' , '2HT' ) : { 'type' : 'H' , 'charge' : 0.1873 } , ('TYR' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0102 } , ('TYR' , '3HT' ) : { 'type' : 'H' , 'charge' : 0.1873 } , ('TYR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6123 } , ('TYR' , 'CA' ) : { 'type' : 'CT' , 'charge' : 0.0570 } , ('TYR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0659 } , ('TYR' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.2002 } , ('TYR' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.2002 } , ('TYR' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.2239 } , ('TYR' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.2239 } , ('TYR' , 'CG' ) : { 'type' : 'CA' , 'charge' : -0.0205 } , ('TYR' , 'CZ' ) : { 'type' : 'C' , 'charge' : 0.3139 } , ('TYR' , 'HA' ) : { 'type' : 'HP' , 'charge' : 0.0983 } , ('TYR' , 'HH' ) : { 'type' : 'HO' , 'charge' : 0.4001 } , ('TYR' , 'N' ) : { 'type' : 'N3' , 'charge' : 0.1940 } , ('TYR' , 'O' ) : { 'type' : 'O' , 'charge' : -0.5713 } , ('TYR' , 'OH' ) : { 'type' : 'OH' , 'charge' : -0.5578 } , } c_terminal = { ('ALA' , '1HB' ) : { 'type' : 'HC' , 'charge' : 0.0764 } , ('ALA' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0764 } , ('ALA' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0764 } , ('ALA' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7731 } , ('ALA' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1747 } , ('ALA' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2093 } , ('ALA' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('ALA' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1067 } , ('ALA' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('ALA' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8055 } , ('ALA' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8055 } , ('CYS' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1437 } , ('CYS' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1437 } , ('CYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7497 } , ('CYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1635 } , ('CYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1996 } , ('CYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('CYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1396 } , ('CYS' , 'HG' ) : { 'type' : 'HS' , 'charge' : 0.2068 } , ('CYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('CYS' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7981 } , ('CYS' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7981 } , ('CYS' , 'SG' ) : { 'type' : 'SH' , 'charge' : -0.3102 } , ('CYX' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.1228 } , ('CYX' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.1228 } , ('CYX' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7618 } , ('CYX' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1318 } , ('CYX' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1943 } , ('CYX' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('CYX' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0938 } , ('CYX' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('CYX' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8041 } , ('CYX' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8041 } , ('CYX' , 'SG' ) : { 'type' : 'S' , 'charge' : -0.0529 } , ('ASP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } , ('ASP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } , ('ASP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7256 } , ('ASP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1817 } , ('ASP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0677 } , ('ASP' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8851 } , ('ASP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } , ('ASP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1046 } , ('ASP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } , ('ASP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7887 } , ('ASP' , 'OD1' ) : { 'type' : 'O2' , 'charge' : -0.8162 } , ('ASP' , 'OD2' ) : { 'type' : 'O2' , 'charge' : -0.8162 } , ('ASP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7887 } , ('ASH' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } , ('ASH' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0212 } , ('ASH' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7256 } , ('ASH' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1817 } , ('ASH' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0677 } , ('ASH' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.8851 } , ('ASH' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } , ('ASH' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1046 } , ('ASH' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } , ('ASH' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7887 } , ('ASH' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.8162 } , ('ASH' , 'OD2' ) : { 'type' : 'OH' , 'charge' : -0.8162 } , ('ASH' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7887 } , ('GLU' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } , ('GLU' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } , ('GLU' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } , ('GLU' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } , ('GLU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7420 } , ('GLU' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2059 } , ('GLU' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0071 } , ('GLU' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8183 } , ('GLU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0675 } , ('GLU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } , ('GLU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1399 } , ('GLU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } , ('GLU' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7930 } , ('GLU' , 'OE1' ) : { 'type' : 'O2' , 'charge' : -0.8220 } , ('GLU' , 'OE2' ) : { 'type' : 'O2' , 'charge' : -0.8220 } , ('GLU' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7930 } , ('GLP' , '2HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } , ('GLP' , '2HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } , ('GLP' , '3HB' ) : { 'type' : 'HC' , 'charge' : -0.0078 } , ('GLP' , '3HG' ) : { 'type' : 'HC' , 'charge' : -0.0548 } , ('GLP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7420 } , ('GLP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2059 } , ('GLP' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0071 } , ('GLP' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.8183 } , ('GLP' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0675 } , ('GLP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.3055 } , ('GLP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1399 } , ('GLP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.5192 } , ('GLP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7930 } , ('GLP' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.8220 } , ('GLP' , 'OE2' ) : { 'type' : 'OH' , 'charge' : -0.8220 } , ('GLP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7930 } , ('PHE' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1408 } , ('PHE' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1461 } , ('PHE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0443 } , ('PHE' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1408 } , ('PHE' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1461 } , ('PHE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0443 } , ('PHE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7660 } , ('PHE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1825 } , ('PHE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0959 } , ('PHE' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1300 } , ('PHE' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1300 } , ('PHE' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.1847 } , ('PHE' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.1847 } , ('PHE' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0552 } , ('PHE' , 'CZ' ) : { 'type' : 'CA' , 'charge' : -0.0944 } , ('PHE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('PHE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1098 } , ('PHE' , 'HZ' ) : { 'type' : 'HA' , 'charge' : 0.1280 } , ('PHE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('PHE' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8026 } , ('PHE' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8026 } , ('GLY' , '3HA' ) : { 'type' : 'H1' , 'charge' : 0.1056 } , ('GLY' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7231 } , ('GLY' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2493 } , ('GLY' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('GLY' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1056 } , ('GLY' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('GLY' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7855 } , ('GLY' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7855 } , ('HIP' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3883 } , ('HIP' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.2694 } , ('HIP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0868 } , ('HIP' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.2336 } , ('HIP' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3913 } , ('HIP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0868 } , ('HIP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8032 } , ('HIP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1445 } , ('HIP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0800 } , ('HIP' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.1256 } , ('HIP' , 'CE1' ) : { 'type' : 'CR' , 'charge' : -0.0251 } , ('HIP' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.0298 } , ('HIP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2764 } , ('HIP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1115 } , ('HIP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3481 } , ('HIP' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.1501 } , ('HIP' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.1683 } , ('HIP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8177 } , ('HIP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8177 } , ('HIE' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1448 } , ('HIE' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0620 } , ('HIE' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1957 } , ('HIE' , '2HE' ) : { 'type' : 'H' , 'charge' : 0.3319 } , ('HIE' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0620 } , ('HIE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7916 } , ('HIE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2699 } , ('HIE' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1068 } , ('HIE' , 'CD2' ) : { 'type' : 'CW' , 'charge' : -0.2588 } , ('HIE' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1558 } , ('HIE' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.2724 } , ('HIE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('HIE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1650 } , ('HIE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('HIE' , 'ND1' ) : { 'type' : 'NB' , 'charge' : -0.5517 } , ('HIE' , 'NE2' ) : { 'type' : 'NA' , 'charge' : -0.2670 } , ('HIE' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8065 } , ('HIE' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8065 } , ('HID' , '1HD' ) : { 'type' : 'H' , 'charge' : 0.3755 } , ('HID' , '1HE' ) : { 'type' : 'H5' , 'charge' : 0.1418 } , ('HID' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0565 } , ('HID' , '2HD' ) : { 'type' : 'H4' , 'charge' : 0.1241 } , ('HID' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0565 } , ('HID' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7615 } , ('HID' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1739 } , ('HID' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.1046 } , ('HID' , 'CD2' ) : { 'type' : 'CV' , 'charge' : 0.1001 } , ('HID' , 'CE1' ) : { 'type' : 'CR' , 'charge' : 0.1925 } , ('HID' , 'CG' ) : { 'type' : 'CC' , 'charge' : 0.0293 } , ('HID' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('HID' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1100 } , ('HID' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('HID' , 'ND1' ) : { 'type' : 'NA' , 'charge' : -0.3892 } , ('HID' , 'NE2' ) : { 'type' : 'NB' , 'charge' : -0.5629 } , ('HID' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8016 } , ('HID' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8016 } , ('ILE' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.0196 } , ('ILE' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.1021 } , ('ILE' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.0196 } , ('ILE' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0321 } , ('ILE' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.1021 } , ('ILE' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.0196 } , ('ILE' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0321 } , ('ILE' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.1021 } , ('ILE' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8343 } , ('ILE' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.3100 } , ('ILE' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.0363 } , ('ILE' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.0699 } , ('ILE' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.0323 } , ('ILE' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3498 } , ('ILE' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('ILE' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1375 } , ('ILE' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0766 } , ('ILE' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('ILE' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8190 } , ('ILE' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8190 } , ('LYS' , '1HZ' ) : { 'type' : 'H' , 'charge' : 0.3374 } , ('LYS' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0482 } , ('LYS' , '2HD' ) : { 'type' : 'HC' , 'charge' : 0.0611 } , ('LYS' , '2HE' ) : { 'type' : 'HP' , 'charge' : 0.1121 } , ('LYS' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0134 } , ('LYS' , '2HZ' ) : { 'type' : 'H' , 'charge' : 0.3374 } , ('LYS' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0482 } , ('LYS' , '3HD' ) : { 'type' : 'HC' , 'charge' : 0.0611 } , ('LYS' , '3HE' ) : { 'type' : 'HP' , 'charge' : 0.1121 } , ('LYS' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0134 } , ('LYS' , '3HZ' ) : { 'type' : 'H' , 'charge' : 0.3374 } , ('LYS' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8488 } , ('LYS' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2903 } , ('LYS' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0538 } , ('LYS' , 'CD' ) : { 'type' : 'CT' , 'charge' : -0.0392 } , ('LYS' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0176 } , ('LYS' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0227 } , ('LYS' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2764 } , ('LYS' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1438 } , ('LYS' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3481 } , ('LYS' , 'NZ' ) : { 'type' : 'N3' , 'charge' : -0.3741 } , ('LYS' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8252 } , ('LYS' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8252 } , ('LEU' , '1HD1' ) : { 'type' : 'HC' , 'charge' : 0.1038 } , ('LEU' , '1HD2' ) : { 'type' : 'HC' , 'charge' : 0.1038 } , ('LEU' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0974 } , ('LEU' , '2HD1' ) : { 'type' : 'HC' , 'charge' : 0.1038 } , ('LEU' , '2HD2' ) : { 'type' : 'HC' , 'charge' : 0.1038 } , ('LEU' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0974 } , ('LEU' , '3HD1' ) : { 'type' : 'HC' , 'charge' : 0.1038 } , ('LEU' , '3HD2' ) : { 'type' : 'HC' , 'charge' : 0.1038 } , ('LEU' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8326 } , ('LEU' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2847 } , ('LEU' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2469 } , ('LEU' , 'CD1' ) : { 'type' : 'CT' , 'charge' : -0.4163 } , ('LEU' , 'CD2' ) : { 'type' : 'CT' , 'charge' : -0.4163 } , ('LEU' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.3706 } , ('LEU' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('LEU' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1346 } , ('LEU' , 'HG' ) : { 'type' : 'HC' , 'charge' : -0.0374 } , ('LEU' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('LEU' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8199 } , ('LEU' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8199 } , ('MET' , '1HE' ) : { 'type' : 'H1' , 'charge' : 0.0625 } , ('MET' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0480 } , ('MET' , '2HE' ) : { 'type' : 'H1' , 'charge' : 0.0625 } , ('MET' , '2HG' ) : { 'type' : 'H1' , 'charge' : 0.0317 } , ('MET' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0480 } , ('MET' , '3HE' ) : { 'type' : 'H1' , 'charge' : 0.0625 } , ('MET' , '3HG' ) : { 'type' : 'H1' , 'charge' : 0.0317 } , ('MET' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8013 } , ('MET' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2597 } , ('MET' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0236 } , ('MET' , 'CE' ) : { 'type' : 'CT' , 'charge' : -0.0376 } , ('MET' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0492 } , ('MET' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('MET' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1277 } , ('MET' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('MET' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8105 } , ('MET' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8105 } , ('MET' , 'SD' ) : { 'type' : 'S' , 'charge' : -0.2692 } , ('ASN' , '1HD2' ) : { 'type' : 'H' , 'charge' : 0.4150 } , ('ASN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.1023 } , ('ASN' , '2HD2' ) : { 'type' : 'H' , 'charge' : 0.4150 } , ('ASN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.1023 } , ('ASN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8050 } , ('ASN' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2080 } , ('ASN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.2299 } , ('ASN' , 'CG' ) : { 'type' : 'C' , 'charge' : 0.7153 } , ('ASN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('ASN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1358 } , ('ASN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('ASN' , 'ND2' ) : { 'type' : 'N' , 'charge' : -0.9084 } , ('ASN' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8147 } , ('ASN' , 'OD1' ) : { 'type' : 'O' , 'charge' : -0.6010 } , ('ASN' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8147 } , ('PRO' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0381 } , ('PRO' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0331 } , ('PRO' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0172 } , ('PRO' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0381 } , ('PRO' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0331 } , ('PRO' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0172 } , ('PRO' , 'C' ) : { 'type' : 'C' , 'charge' : 0.6631 } , ('PRO' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.1336 } , ('PRO' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0543 } , ('PRO' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.0434 } , ('PRO' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0466 } , ('PRO' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.0776 } , ('PRO' , 'N' ) : { 'type' : 'N' , 'charge' : -0.2802 } , ('PRO' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.7697 } , ('PRO' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.7697 } , ('GLN' , '1HE2' ) : { 'type' : 'H' , 'charge' : 0.4304 } , ('GLN' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0452 } , ('GLN' , '2HE2' ) : { 'type' : 'H' , 'charge' : 0.4304 } , ('GLN' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0203 } , ('GLN' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0452 } , ('GLN' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0203 } , ('GLN' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7775 } , ('GLN' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2248 } , ('GLN' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0664 } , ('GLN' , 'CD' ) : { 'type' : 'C' , 'charge' : 0.7093 } , ('GLN' , 'CG' ) : { 'type' : 'CT' , 'charge' : -0.0210 } , ('GLN' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('GLN' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1232 } , ('GLN' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('GLN' , 'NE2' ) : { 'type' : 'N' , 'charge' : -0.9574 } , ('GLN' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8042 } , ('GLN' , 'OE1' ) : { 'type' : 'O' , 'charge' : -0.6098 } , ('GLN' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8042 } , ('ARG' , '1HH1' ) : { 'type' : 'H' , 'charge' : 0.4493 } , ('ARG' , '1HH2' ) : { 'type' : 'H' , 'charge' : 0.4493 } , ('ARG' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0371 } , ('ARG' , '2HD' ) : { 'type' : 'H1' , 'charge' : 0.0468 } , ('ARG' , '2HG' ) : { 'type' : 'HC' , 'charge' : 0.0185 } , ('ARG' , '2HH1' ) : { 'type' : 'H' , 'charge' : 0.4493 } , ('ARG' , '2HH2' ) : { 'type' : 'H' , 'charge' : 0.4493 } , ('ARG' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0371 } , ('ARG' , '3HD' ) : { 'type' : 'H1' , 'charge' : 0.0468 } , ('ARG' , '3HG' ) : { 'type' : 'HC' , 'charge' : 0.0185 } , ('ARG' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8557 } , ('ARG' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.3068 } , ('ARG' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0374 } , ('ARG' , 'CD' ) : { 'type' : 'CT' , 'charge' : 0.1114 } , ('ARG' , 'CG' ) : { 'type' : 'CT' , 'charge' : 0.0744 } , ('ARG' , 'CZ' ) : { 'type' : 'CA' , 'charge' : 0.8368 } , ('ARG' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2764 } , ('ARG' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1447 } , ('ARG' , 'HE' ) : { 'type' : 'H' , 'charge' : 0.3479 } , ('ARG' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3481 } , ('ARG' , 'NE' ) : { 'type' : 'N2' , 'charge' : -0.5564 } , ('ARG' , 'NH1' ) : { 'type' : 'N2' , 'charge' : -0.8737 } , ('ARG' , 'NH2' ) : { 'type' : 'N2' , 'charge' : -0.8737 } , ('ARG' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8266 } , ('ARG' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8266 } , ('SER' , '2HB' ) : { 'type' : 'H1' , 'charge' : 0.0813 } , ('SER' , '3HB' ) : { 'type' : 'H1' , 'charge' : 0.0813 } , ('SER' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8113 } , ('SER' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2722 } , ('SER' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1123 } , ('SER' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('SER' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1304 } , ('SER' , 'HG' ) : { 'type' : 'HO' , 'charge' : 0.4474 } , ('SER' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('SER' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8132 } , ('SER' , 'OG' ) : { 'type' : 'OH' , 'charge' : -0.6514 } , ('SER' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8132 } , ('THR' , '1HG' ) : { 'type' : 'HO' , 'charge' : 0.4119 } , ('THR' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0586 } , ('THR' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0586 } , ('THR' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0586 } , ('THR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7810 } , ('THR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2420 } , ('THR' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.3025 } , ('THR' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.1853 } , ('THR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('THR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1207 } , ('THR' , 'HB' ) : { 'type' : 'H1' , 'charge' : 0.0078 } , ('THR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('THR' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8044 } , ('THR' , 'OG1' ) : { 'type' : 'OH' , 'charge' : -0.6496 } , ('THR' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8044 } , ('VAL' , '1HG1' ) : { 'type' : 'HC' , 'charge' : 0.0836 } , ('VAL' , '1HG2' ) : { 'type' : 'HC' , 'charge' : 0.0836 } , ('VAL' , '2HG1' ) : { 'type' : 'HC' , 'charge' : 0.0836 } , ('VAL' , '2HG2' ) : { 'type' : 'HC' , 'charge' : 0.0836 } , ('VAL' , '3HG1' ) : { 'type' : 'HC' , 'charge' : 0.0836 } , ('VAL' , '3HG2' ) : { 'type' : 'HC' , 'charge' : 0.0836 } , ('VAL' , 'C' ) : { 'type' : 'C' , 'charge' : 0.8350 } , ('VAL' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.3438 } , ('VAL' , 'CB' ) : { 'type' : 'CT' , 'charge' : 0.1940 } , ('VAL' , 'CG1' ) : { 'type' : 'CT' , 'charge' : -0.3064 } , ('VAL' , 'CG2' ) : { 'type' : 'CT' , 'charge' : -0.3064 } , ('VAL' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('VAL' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1438 } , ('VAL' , 'HB' ) : { 'type' : 'HC' , 'charge' : 0.0308 } , ('VAL' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('VAL' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8173 } , ('VAL' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8173 } , ('TRP' , '1HD' ) : { 'type' : 'H4' , 'charge' : 0.2043 } , ('TRP' , '1HE' ) : { 'type' : 'H' , 'charge' : 0.3413 } , ('TRP' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0497 } , ('TRP' , '2HH' ) : { 'type' : 'HA' , 'charge' : 0.1401 } , ('TRP' , '2HZ' ) : { 'type' : 'HA' , 'charge' : 0.1567 } , ('TRP' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0497 } , ('TRP' , '3HE' ) : { 'type' : 'HA' , 'charge' : 0.1491 } , ('TRP' , '3HZ' ) : { 'type' : 'HA' , 'charge' : 0.1507 } , ('TRP' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7658 } , ('TRP' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2084 } , ('TRP' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0742 } , ('TRP' , 'CD1' ) : { 'type' : 'CW' , 'charge' : -0.1808 } , ('TRP' , 'CD2' ) : { 'type' : 'CB' , 'charge' : 0.1078 } , ('TRP' , 'CE2' ) : { 'type' : 'CN' , 'charge' : 0.1222 } , ('TRP' , 'CE3' ) : { 'type' : 'CA' , 'charge' : -0.1837 } , ('TRP' , 'CG' ) : { 'type' : 'C*' , 'charge' : -0.0796 } , ('TRP' , 'CH2' ) : { 'type' : 'CA' , 'charge' : -0.1020 } , ('TRP' , 'CZ2' ) : { 'type' : 'CA' , 'charge' : -0.2594 } , ('TRP' , 'CZ3' ) : { 'type' : 'CA' , 'charge' : -0.2287 } , ('TRP' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('TRP' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1272 } , ('TRP' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('TRP' , 'NE1' ) : { 'type' : 'NA' , 'charge' : -0.3316 } , ('TRP' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8011 } , ('TRP' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8011 } , ('TYR' , '1HD' ) : { 'type' : 'HA' , 'charge' : 0.1780 } , ('TYR' , '1HE' ) : { 'type' : 'HA' , 'charge' : 0.1673 } , ('TYR' , '2HB' ) : { 'type' : 'HC' , 'charge' : 0.0490 } , ('TYR' , '2HD' ) : { 'type' : 'HA' , 'charge' : 0.1780 } , ('TYR' , '2HE' ) : { 'type' : 'HA' , 'charge' : 0.1673 } , ('TYR' , '3HB' ) : { 'type' : 'HC' , 'charge' : 0.0490 } , ('TYR' , 'C' ) : { 'type' : 'C' , 'charge' : 0.7817 } , ('TYR' , 'CA' ) : { 'type' : 'CT' , 'charge' : -0.2015 } , ('TYR' , 'CB' ) : { 'type' : 'CT' , 'charge' : -0.0752 } , ('TYR' , 'CD1' ) : { 'type' : 'CA' , 'charge' : -0.1922 } , ('TYR' , 'CD2' ) : { 'type' : 'CA' , 'charge' : -0.1922 } , ('TYR' , 'CE1' ) : { 'type' : 'CA' , 'charge' : -0.2458 } , ('TYR' , 'CE2' ) : { 'type' : 'CA' , 'charge' : -0.2458 } , ('TYR' , 'CG' ) : { 'type' : 'CA' , 'charge' : 0.0243 } , ('TYR' , 'CZ' ) : { 'type' : 'C' , 'charge' : 0.3395 } , ('TYR' , 'H' ) : { 'type' : 'H' , 'charge' : 0.2681 } , ('TYR' , 'HA' ) : { 'type' : 'H1' , 'charge' : 0.1092 } , ('TYR' , 'HH' ) : { 'type' : 'HO' , 'charge' : 0.4017 } , ('TYR' , 'N' ) : { 'type' : 'N' , 'charge' : -0.3821 } , ('TYR' , 'O' ) : { 'type' : 'O2' , 'charge' : -0.8070 } , ('TYR' , 'OH' ) : { 'type' : 'OH' , 'charge' : -0.5643 } , ('TYR' , 'OXT' ) : { 'type' : 'O2' , 'charge' : -0.8070 } , }
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4
168a1d56839afd5c1afd3495075a6a02dc26a4ea
87
py
Python
05 - Result/02 - Rust/run.py
BjoernLange/why-you-should-learn-rust-examples
985d184fc79b77b10628cba81333e9e662f4107b
[ "MIT" ]
null
null
null
05 - Result/02 - Rust/run.py
BjoernLange/why-you-should-learn-rust-examples
985d184fc79b77b10628cba81333e9e662f4107b
[ "MIT" ]
null
null
null
05 - Result/02 - Rust/run.py
BjoernLange/why-you-should-learn-rust-examples
985d184fc79b77b10628cba81333e9e662f4107b
[ "MIT" ]
null
null
null
#!/bin/python3 import os if __name__ == '__main__': exit(os.system('cargo run'))
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0.643678
12
87
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168b5be28e80ad5d47f6d5548a4db14f533f86a3
45
py
Python
yaretry/__init__.py
Aloomaio/yaretry
dabbdab3c91c5ac62ed04a5cf9756b75d2213e5f
[ "Apache-2.0" ]
null
null
null
yaretry/__init__.py
Aloomaio/yaretry
dabbdab3c91c5ac62ed04a5cf9756b75d2213e5f
[ "Apache-2.0" ]
null
null
null
yaretry/__init__.py
Aloomaio/yaretry
dabbdab3c91c5ac62ed04a5cf9756b75d2213e5f
[ "Apache-2.0" ]
1
2020-08-08T21:01:41.000Z
2020-08-08T21:01:41.000Z
from yaretry.retry import * name = "yaretry"
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4
16d07ce6f6163d36be24050a2d53fcf3fde06a46
20
py
Python
tests/__init__.py
trickeydan/j5-dev
ba9e2adcb6d9ed766e4be048cb77cf3fa6592b5f
[ "MIT" ]
10
2019-01-19T13:09:37.000Z
2021-06-18T13:40:10.000Z
tests/__init__.py
trickeydan/j5-dev
ba9e2adcb6d9ed766e4be048cb77cf3fa6592b5f
[ "MIT" ]
681
2019-01-22T18:12:23.000Z
2022-03-25T14:14:31.000Z
tests/__init__.py
trickeydan/j5-dev
ba9e2adcb6d9ed766e4be048cb77cf3fa6592b5f
[ "MIT" ]
8
2019-02-22T21:45:47.000Z
2021-11-17T19:43:33.000Z
"""Tests for j5."""
10
19
0.5
3
20
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4
16d509624c6e9d70153fa1634acb2e9127ea8d95
29
py
Python
tests/__init__.py
abdelq/pybaselines
043aa7875efe1ca01c3e8e9ae7c57a67274aff06
[ "BSD-3-Clause-Clear", "BSD-3-Clause" ]
null
null
null
tests/__init__.py
abdelq/pybaselines
043aa7875efe1ca01c3e8e9ae7c57a67274aff06
[ "BSD-3-Clause-Clear", "BSD-3-Clause" ]
null
null
null
tests/__init__.py
abdelq/pybaselines
043aa7875efe1ca01c3e8e9ae7c57a67274aff06
[ "BSD-3-Clause-Clear", "BSD-3-Clause" ]
null
null
null
"""Tests for pybaselines."""
14.5
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3
29
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4
16ef6a9b8219de1b9bafef9547ff336bf002f425
23
py
Python
agora_identity/__init__.py
agoravoting/agora-identity
a656815207929f3871a6daa67ea7fecc2ec13c83
[ "BSD-3-Clause" ]
null
null
null
agora_identity/__init__.py
agoravoting/agora-identity
a656815207929f3871a6daa67ea7fecc2ec13c83
[ "BSD-3-Clause" ]
null
null
null
agora_identity/__init__.py
agoravoting/agora-identity
a656815207929f3871a6daa67ea7fecc2ec13c83
[ "BSD-3-Clause" ]
null
null
null
""" agora_identity """
11.5
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4
bc57d58e4ff58c7c5a7103af772a3eaf453d2e1e
1,735
py
Python
revscoring/revscoring/languages/__init__.py
yafeunteun/wikipedia-spam-classifier
fca782b39b287fbc0b2dd54f8e2bf33c6d3bc519
[ "MIT" ]
2
2016-10-26T18:58:53.000Z
2017-06-22T20:11:20.000Z
revscoring/revscoring/languages/__init__.py
yafeunteun/wikipedia-spam-classifier
fca782b39b287fbc0b2dd54f8e2bf33c6d3bc519
[ "MIT" ]
null
null
null
revscoring/revscoring/languages/__init__.py
yafeunteun/wikipedia-spam-classifier
fca782b39b287fbc0b2dd54f8e2bf33c6d3bc519
[ "MIT" ]
null
null
null
""" This module implements a set of languages as collections of features that are language specific. feature collections +++++++++++++++++++ Languages implement a subset of feature collections (e.g. :class:`~revscoring.languages.features.Dictionary`, :class:`~revscoring.languages.features.Stopwords`, :class:`~revscoring.languages.features.Stemmed` and :class:`~revscoring.languages.features.RegexMatches`) based on what language assets are available. See :mod:`revscoring.languages.features`. dutch +++++ .. automodule:: revscoring.languages.arabic :members: dutch +++++ .. automodule:: revscoring.languages.dutch :members: english +++++++ .. automodule:: revscoring.languages.english :members: estonian ++++++++ .. automodule:: revscoring.languages.estonian :members: french ++++++ .. automodule:: revscoring.languages.french :members: german ++++++ .. automodule:: revscoring.languages.german :members: hebrew ++++++ .. automodule:: revscoring.languages.hebrew :members: indonesian ++++++++++ .. automodule:: revscoring.languages.indonesian :members: italian +++++++ .. automodule:: revscoring.languages.italian :members: japanese +++++++ .. automodule:: revscoring.languages.japanese :members: persian +++++++ .. automodule:: revscoring.languages.persian :members: portuguese ++++++++++ .. automodule:: revscoring.languages.portuguese :members: spanish +++++++ .. automodule:: revscoring.languages.spanish :members: turkish +++++++ .. automodule:: revscoring.languages.turkish :members: ukrainian +++++++++ .. automodule:: revscoring.languages.ukrainian :members: vietnamese ++++++++++ .. automodule:: revscoring.languages.vietnamese :members: """
18.263158
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1,735
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0.333055
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0.126801
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4
bc682bb20c97a5e3723d2d7082d0107fb8dd5d1f
121
py
Python
config/development.py
joeseggie/fingerprint_api_proxy
e5d81e4de4411e60c925589c5d6a992669f531b4
[ "MIT" ]
null
null
null
config/development.py
joeseggie/fingerprint_api_proxy
e5d81e4de4411e60c925589c5d6a992669f531b4
[ "MIT" ]
2
2021-03-31T18:49:55.000Z
2021-12-13T19:48:31.000Z
config/development.py
joeseggie/fingerprint_api_proxy
e5d81e4de4411e60c925589c5d6a992669f531b4
[ "MIT" ]
null
null
null
from config.default import Config class DevelopmentConfig(Config): """Development configuration""" DEBUG = True
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5
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4
bc703f8b37eb7e122998ca4581d077a1a8eac399
1,267
py
Python
claripy/ast/__init__.py
mborgerson/claripy
45b01c10caa0001b4e210e449ad5618880d1773b
[ "BSD-2-Clause" ]
null
null
null
claripy/ast/__init__.py
mborgerson/claripy
45b01c10caa0001b4e210e449ad5618880d1773b
[ "BSD-2-Clause" ]
null
null
null
claripy/ast/__init__.py
mborgerson/claripy
45b01c10caa0001b4e210e449ad5618880d1773b
[ "BSD-2-Clause" ]
null
null
null
#pylint:disable=redefined-outer-name from typing import TYPE_CHECKING # Mypy is severely confused by this delayed import trickery, but works if we just pretend that the import # happens here already if TYPE_CHECKING: from .bits import Bits from .bv import BV from .vs import VS from .fp import FP from .bool import Bool, true, false from .int import Int from .base import Base from .strings import String from .. import ops as all_operations else: Bits = lambda *args, **kwargs: None BV = lambda *args, **kwargs: None VS = lambda *args, **kwargs: None FP = lambda *args, **kwargs: None Bool = lambda *args, **kwargs: None Int = lambda *args, **kwargs: None Base = lambda *args, **kwargs: None true = lambda *args, **kwargs: None false = lambda *args, **kwargs: None String = lambda *args, **kwargs: None all_operations = None def _import(): global Bits, BV, VS, FP, Bool, Int, Base, String, true, false, all_operations from .bits import Bits from .bv import BV from .vs import VS from .fp import FP from .bool import Bool, true, false from .int import Int from .base import Base from .strings import String from .. import ops as all_operations
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4
bc7fac8fb65ff74f7a3a104b347a3069058466b4
110
py
Python
echopype/analysis/db_diff.py
leewujung/echopype-lfs-test
b76dcf42631d0ac9cef0efeced9be4afdc15e659
[ "Apache-2.0" ]
1
2021-09-04T07:19:35.000Z
2021-09-04T07:19:35.000Z
echopype/analysis/db_diff.py
lsxinh2/echopype
5ed0ea5ec3c872eb2512b045f8585d9225c12bce
[ "Apache-2.0" ]
null
null
null
echopype/analysis/db_diff.py
lsxinh2/echopype
5ed0ea5ec3c872eb2512b045f8585d9225c12bce
[ "Apache-2.0" ]
null
null
null
""" Place holder for frequency-differencing functions. The previous incarnation is in /ref_code/db_diff.py """
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bc84159202c873cc832af26dc05026001f89d59a
317
py
Python
django-server/fras/attendance/views/CapturedFrameAPI.py
ArleneAndrews/Facial-Recognition-Attendance-System
104d17e56af87358974331ef491949b557ab2f01
[ "MIT" ]
52
2019-01-29T14:46:17.000Z
2022-01-14T16:11:37.000Z
django-server/fras/attendance/views/CapturedFrameAPI.py
etrigaen47/Facial-Recognition-Attendance-System
ad0bd18cf9582cc12002baf8c92f6638f632c46e
[ "MIT" ]
13
2018-11-04T12:29:48.000Z
2020-02-11T23:47:35.000Z
django-server/fras/attendance/views/CapturedFrameAPI.py
etrigaen47/Facial-Recognition-Attendance-System
ad0bd18cf9582cc12002baf8c92f6638f632c46e
[ "MIT" ]
16
2019-03-07T11:07:16.000Z
2021-08-13T07:19:28.000Z
from rest_framework import viewsets from attendance.models.CapturedFrame import CapturedFrame from attendance.serializers.CapturedFrameSerializer import CapturedFrameSerializer class CapturedFrameAPI(viewsets.ModelViewSet): queryset = CapturedFrame.objects.all() serializer_class = CapturedFrameSerializer
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bc9005361bcee4811d3abf3f0158f4b1f5d55f2b
257
py
Python
django_presentation/messages/messageBox.py
adamkerz/django-presentation
1e812faa5f682e021fa6580509d8d324cfcc119c
[ "BSD-3-Clause" ]
null
null
null
django_presentation/messages/messageBox.py
adamkerz/django-presentation
1e812faa5f682e021fa6580509d8d324cfcc119c
[ "BSD-3-Clause" ]
null
null
null
django_presentation/messages/messageBox.py
adamkerz/django-presentation
1e812faa5f682e021fa6580509d8d324cfcc119c
[ "BSD-3-Clause" ]
null
null
null
from django.template import Context from django.template.loader import get_template from django.utils.safestring import mark_safe as S def messageBox(messages): return S(get_template('messages/messageBox.html').render(Context({'messages':messages})))
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bc9413fb9a7ab513b3219a6b4baa388b63c06e8a
4,036
py
Python
data.py
andy31lewis/brywidgets
2ff3ffe633cbf226208d7af95cc0eb542173be2b
[ "BSD-3-Clause" ]
1
2020-10-21T12:26:18.000Z
2020-10-21T12:26:18.000Z
data.py
andy31lewis/brywidgets
2ff3ffe633cbf226208d7af95cc0eb542173be2b
[ "BSD-3-Clause" ]
2
2020-04-22T12:04:52.000Z
2021-01-24T15:18:51.000Z
data.py
andy31lewis/brywidgets
2ff3ffe633cbf226208d7af95cc0eb542173be2b
[ "BSD-3-Clause" ]
1
2018-12-10T00:56:39.000Z
2018-12-10T00:56:39.000Z
#!/usr/bin/python # -*- coding: utf-8 -*- artistdict = {"Bohemian Rhapsody":"Queen", "Imagine":"John Lennon", "Angels":"Robbie Williams", "Hey Jude":"Beatles", "Smells Like Teen Spirit":"Nirvana", "Live Forever":"Oasis", "Wonderwall":"Oasis", "One":"U2", "Bitter Sweet Symphony":"Verve", "With Or Without You":"U2", "Penny Lane / Strawberry Fields Forever":"Beatles", "Good Vibrations":"Beach Boys", "Losing My Religion":"REM", "Like A Rolling Stone":"Bob Dylan", "God Only Knows":"Beach Boys", "Everybody Hurts":"REM", "Waterloo Sunset":"Kinks", "Don’t Look Back In Anger":"Oasis", "A Whiter Shade Of Pale":"Procol Harum", "Stairway To Heaven":"Led Zeppelin", "Yesterday":"Beatles", "A Day In The Life":"Beatles", "Hotel California":"Eagles", "Unfinished Sympathy":"Massive Attack", "Dancing Queen":"Abba", "Like A Prayer":"Madonna", "All Along The Watchtower":"Jimi Hendrix Experience", "Creep":"Radiohead", "Billie Jean":"Michael Jackson", "My Generation":"Who", "Wuthering Heights":"Kate Bush", "Paranoid Android":"Radiohead", "Teenage Kicks":"Undertones", "Love Will Tear Us Apart":"Joy Division", "Bridge Over Troubled Water":"Simon And Garfunkel", "Born To Run":"Bruce Springsteen", "No Woman No Cry":"Bob Marley & The Wailers", "Sweet Child O Mine":"Guns N Roses", "Suspicious Minds":"Elvis Presley", "Let It Be":"Beatles", "(I Can’t Get No) Satisfaction":"Rolling Stones", "Bat Out Of Hell":"Meat Loaf", "Common People":"Pulp", "Hero":"Mariah Carey", "I Heard It Through The Grapevine":"Marvin Gaye", "Layla":"Derek And The Dominoes", "American Pie":"Don Mclean", "Mr Brightside":"Killers", "It Must be Love":"Madness", "Paint It Black":"Rolling Stones", "Anarchy In The UK":"Sex Pistols", "Time Of Your Life (Good Riddance)":"Green Day", "Champagne Supernova":"Oasis", "A Town Called Malice / Precious":"Jam", "Wannabe":"Spice Girls", "Street Spirit (Fade Out)":"Radiohead", "All Right Now":"Free", "Fools Gold / What The World Is Waiting For":"Stone Roses", "Yellow":"Coldplay", "Mr. Blue Sky":"Electric Light Orchestra", "Nothing Compares 2 U":"Sinead O’Connor", "This Charming Man":"Smiths", "Careless Whisper":"George Michael", "London Calling":"Clash", "Song 2":"Blur", "That's Entertainment":"Jam", "Under The Bridge":"Red Hot Chili Peppers", "Karma Police":"Radiohead", "God Save The Queen":"Sex Pistols", "(Sittin' On) The Dock Of The Bay":"Ottis Redding", "Wish You Were Here":"Pink Floyd", "In My Life":"Beatles", "Every Breath You Take":"Police", "House Of The Rising Sun":"Animals", "I Am The Resurrection":"Stone Roses", "(Everything I Do) I Do It For You":"Bryan Adams", "Fake Plastic Trees":"Radiohead", "Comfortably Numb":"Pink Floyd", "Brown Eyed Girl":"Van Morrison", "Baker Street":"Gerry Rafferty", "She Loves You":"Beatles", "Romeo And Juliet":"Dire Straits", "Jumping Jack Flash":"Rolling Stones", "My Heart Will Go On":"Celine Dion", "I’ll Be Missing You":"Puff Daddy And Faith Evans", "How Soon Is Now?":"Smiths", "Help!":"Beatles", "Where The Streets Have No Name":"U2", "Space Oddity":"David Bowie", "Heroes":"David Bowie", "Life On Mars":"David Bowie", "There She Goes":"LAs", "Unchained Melody":"Righteous Brothers", "Going Underground / Dreams Of Children":"Jam", "Tracks Of My Tears":"Smokey Robinson & The Miracles", "Come On Eileen":"Dexy's Midnight Runners", "Nights In White Satin":"Moody Blues", "Blue Monday":"New Order", "My Sweet Lord":"George Harrison", "Stan":"Eminem", "Motorcycle Emptiness":"Manic Street Preachers", "The Winner Takes It All":"Abba", "Can't Get You Out Of My Head":"Kylie Minogue", "Fairytale of New York":"Pogues featuring Kirsty MacColl", "Take Your Mama":"Scissor Sisters", "Heartbreak Hotel":"Elvis Presley", "Don't Dream It's Over":"Crowded House", "I’m Not In Love":"10CC", "The Drugs Don’t Work":"Verve", "Lola":"Kinks", "Don’t You Want Me":"Human League", "Without You":"Nilsson", "Believe":"Cher", "Wichita Lineman":"Glen Campbell", "Babylon":"David Gray", "Summer Of ’69":"Bryan Adams", "Wild Wood":"Paul Weller", "Voodoo Chile":"Jimi Hendrix Experience"}
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bcd7b60ca8525e85e1afe8ced67ee42f93dd9dc7
180
py
Python
mwclient/util.py
AdamWill/mwclient
6c8ead656647b811646f60366275f90ecc42a42f
[ "MIT" ]
null
null
null
mwclient/util.py
AdamWill/mwclient
6c8ead656647b811646f60366275f90ecc42a42f
[ "MIT" ]
null
null
null
mwclient/util.py
AdamWill/mwclient
6c8ead656647b811646f60366275f90ecc42a42f
[ "MIT" ]
null
null
null
import time def parse_timestamp(t): if t is None or t == '0000-00-00T00:00:00Z': return (0, 0, 0, 0, 0, 0, 0, 0, 0) return time.strptime(t, '%Y-%m-%dT%H:%M:%SZ')
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4c23d938bd5650c382fcc55770015d0052800bca
395
py
Python
doc/examples/runtime.py
aaronsewall/pytest-dependency
db34c5451891629ad54a18e8a5e6a45b7ec968f8
[ "Apache-2.0" ]
91
2017-01-30T16:05:13.000Z
2022-03-29T12:17:35.000Z
doc/examples/runtime.py
aaronsewall/pytest-dependency
db34c5451891629ad54a18e8a5e6a45b7ec968f8
[ "Apache-2.0" ]
63
2016-04-21T19:30:32.000Z
2022-03-30T13:17:42.000Z
doc/examples/runtime.py
aaronsewall/pytest-dependency
db34c5451891629ad54a18e8a5e6a45b7ec968f8
[ "Apache-2.0" ]
29
2017-09-24T17:22:02.000Z
2022-03-30T20:39:49.000Z
import pytest from pytest_dependency import depends @pytest.mark.dependency() def test_a(): pass @pytest.mark.dependency() @pytest.mark.xfail(reason="deliberate fail") def test_b(): assert False @pytest.mark.dependency() def test_c(request): depends(request, ["test_b"]) pass @pytest.mark.dependency() def test_d(request): depends(request, ["test_a", "test_c"]) pass
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4c4686231662d9771e44fd5ba8bd8ed37776ab5d
82
py
Python
examples/ploty/ploty-01.py
MWTA/Natural-Language-Processing-Python
2cc074f67f6897e802dc239d0c5cdd06a4d24a80
[ "MIT" ]
null
null
null
examples/ploty/ploty-01.py
MWTA/Natural-Language-Processing-Python
2cc074f67f6897e802dc239d0c5cdd06a4d24a80
[ "MIT" ]
null
null
null
examples/ploty/ploty-01.py
MWTA/Natural-Language-Processing-Python
2cc074f67f6897e802dc239d0c5cdd06a4d24a80
[ "MIT" ]
null
null
null
https: // moderndata.plot.ly/generate-html-reports-with-python-pandas-and-plotly/
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4c6382dce1f0c6b8efee87fe1b4984782bdc916a
84
py
Python
detectors/__init__.py
heymarco/ChangeDetectors
03e343a4dd9260328d6d81e01edd7888091b3517
[ "MIT" ]
null
null
null
detectors/__init__.py
heymarco/ChangeDetectors
03e343a4dd9260328d6d81e01edd7888091b3517
[ "MIT" ]
null
null
null
detectors/__init__.py
heymarco/ChangeDetectors
03e343a4dd9260328d6d81e01edd7888091b3517
[ "MIT" ]
null
null
null
from .baselines import * from .abstract import DriftDetector, RegionalDriftDetector
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py
Python
pyqode/python/_forms/pyqode_python_icons_rc.py
haesleinhuepf/pyqode.python
de694278f64cb635c8863d03f3260984fc136b7a
[ "MIT" ]
null
null
null
pyqode/python/_forms/pyqode_python_icons_rc.py
haesleinhuepf/pyqode.python
de694278f64cb635c8863d03f3260984fc136b7a
[ "MIT" ]
null
null
null
pyqode/python/_forms/pyqode_python_icons_rc.py
haesleinhuepf/pyqode.python
de694278f64cb635c8863d03f3260984fc136b7a
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- # Resource object code # # Created by: The Resource Compiler for PyQt5 (Qt v5.5.1) # # WARNING! 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\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x02\ \x00\x00\x00\x2c\x00\x02\x00\x00\x00\x0a\x00\x00\x00\x03\ \x00\x00\x01\x0c\x00\x00\x00\x00\x00\x01\x00\x00\x12\x84\ \x00\x00\x00\x94\x00\x00\x00\x00\x00\x01\x00\x00\x09\x78\ \x00\x00\x00\x4a\x00\x00\x00\x00\x00\x01\x00\x00\x02\x5b\ \x00\x00\x00\xf0\x00\x00\x00\x00\x00\x01\x00\x00\x11\x6b\ \x00\x00\x00\xd2\x00\x00\x00\x00\x00\x01\x00\x00\x0e\xc6\ \x00\x00\x00\xb4\x00\x00\x00\x00\x00\x01\x00\x00\x0c\x2d\ \x00\x00\x00\x7c\x00\x00\x00\x00\x00\x01\x00\x00\x07\x79\ \x00\x00\x00\x66\x00\x00\x00\x00\x00\x01\x00\x00\x05\x00\ \x00\x00\x00\x36\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\ \x00\x00\x01\x2c\x00\x00\x00\x00\x00\x01\x00\x00\x15\x47\ " def qInitResources(): QtCore.qRegisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) def qCleanupResources(): QtCore.qUnregisterResourceData(0x01, qt_resource_struct, qt_resource_name, qt_resource_data) qInitResources()
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4
d5ce206f689f53884df688924e125671fa7ba50d
118
py
Python
crossreceptor_analysis/apps.py
GPCRmd/GPCRmd
7dc75359ace4a00c1597bdb7a86ebee17d51f09c
[ "Apache-2.0" ]
3
2019-03-06T13:35:38.000Z
2020-08-05T15:31:29.000Z
crossreceptor_analysis/apps.py
GPCRmd/GPCRmd
7dc75359ace4a00c1597bdb7a86ebee17d51f09c
[ "Apache-2.0" ]
null
null
null
crossreceptor_analysis/apps.py
GPCRmd/GPCRmd
7dc75359ace4a00c1597bdb7a86ebee17d51f09c
[ "Apache-2.0" ]
null
null
null
from django.apps import AppConfig class CrossreceptorAnalysisConfig(AppConfig): name = 'crossreceptor_analysis'
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4
d5fce18f0b70cb7f0151a5134a3c65c431645438
9,915
py
Python
tests/admin/test_space.py
Harris-Bot/nebula-graph
39411a3b1ec38ce55c670e856138a72f5f8e1721
[ "Apache-2.0" ]
null
null
null
tests/admin/test_space.py
Harris-Bot/nebula-graph
39411a3b1ec38ce55c670e856138a72f5f8e1721
[ "Apache-2.0" ]
2
2021-05-07T09:20:24.000Z
2021-06-22T06:48:55.000Z
tests/admin/test_space.py
Harris-Bot/nebula-graph
39411a3b1ec38ce55c670e856138a72f5f8e1721
[ "Apache-2.0" ]
1
2021-06-22T06:20:03.000Z
2021-06-22T06:20:03.000Z
# --coding:utf-8-- # # Copyright (c) 2020 vesoft inc. All rights reserved. # # This source code is licensed under Apache 2.0 License, # attached with Common Clause Condition 1.0, found in the LICENSES directory. import time from tests.common.nebula_test_suite import NebulaTestSuite, T_EMPTY class TestSpace(NebulaTestSuite): def test_space(self): # not exist resp = self.client.execute('USE not_exist_space') self.check_resp_failed(resp) # with default options resp = self.client.execute('CREATE SPACE space_with_default_options (vid_type=FIXED_STRING(8))') self.check_resp_succeeded(resp) resp = self.client.execute('CREATE SPACE space_on_default_group on default') self.check_resp_failed(resp) # check result resp = self.client.execute('DESC SPACE space_with_default_options') expect_result = [['space_with_default_options', 100, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0}) # drop space resp = self.client.execute('DROP SPACE space_with_default_options') self.check_resp_succeeded(resp) # create space succeeded resp = self.client.execute('CREATE SPACE default_space(partition_num=9, replica_factor=1, vid_type=FIXED_STRING(8))') self.check_resp_succeeded(resp) # show spaces resp = self.client.execute('SHOW SPACES') self.check_resp_succeeded(resp) self.search_result(resp, [['default_space']]) # desc space resp = self.client.execute('DESC SPACE default_space') self.check_resp_succeeded(resp) expect_result = [['default_space', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0}) # show create space # TODO(shylock) need meta cache to permission checking time.sleep(self.delay) resp = self.client.execute('SHOW CREATE SPACE default_space') self.check_resp_succeeded(resp) create_space_str_result = 'CREATE SPACE `default_space` (partition_num = 9, '\ 'replica_factor = 1, '\ 'charset = utf8, '\ 'collate = utf8_bin, '\ 'vid_type = FIXED_STRING(8), '\ 'atomic_edge = false) '\ 'ON default' expect_result = [['default_space', create_space_str_result]] self.check_result(resp, expect_result) # check result from show create resp = self.client.execute('DROP SPACE default_space') self.check_resp_succeeded(resp) create_space_str = 'CREATE SPACE `default_space` (partition_num = 9, '\ 'replica_factor = 1, '\ 'charset = utf8, '\ 'collate = utf8_bin, '\ 'vid_type = FIXED_STRING(8), '\ 'atomic_edge = false)' resp = self.client.execute(create_space_str) self.check_resp_succeeded(resp) resp = self.client.execute('SHOW SPACES') self.check_resp_succeeded(resp) # 2.0 when use space, the validator get from cache time.sleep(self.delay) resp = self.client.execute("USE default_space") self.check_resp_succeeded(resp) def test_charset_collate(self): resp = self.client.execute('CREATE SPACE space_charset_collate (partition_num=9, ' 'replica_factor=1, charset=utf8, collate=utf8_bin, vid_type=FIXED_STRING(8))') self.check_resp_succeeded(resp) resp = self.client.execute('DESC SPACE space_charset_collate') self.check_resp_succeeded(resp) expect_result = [['space_charset_collate', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0}) # drop space resp = self.client.execute('DROP SPACE space_charset_collate') self.check_resp_succeeded(resp) resp = self.client.execute('CREATE SPACE space_charset (partition_num=9, ' 'replica_factor=1, charset=utf8, vid_type=FIXED_STRING(8))') self.check_resp_succeeded(resp) resp = self.client.execute('DESC SPACE space_charset') self.check_resp_succeeded(resp) expect_result = [['space_charset', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0}) # drop space resp = self.client.execute('DROP SPACE space_charset') self.check_resp_succeeded(resp) resp = self.client.execute('CREATE SPACE space_collate (partition_num=9, ' 'replica_factor=1, collate=utf8_bin, vid_type=FIXED_STRING(8))') self.check_resp_succeeded(resp) resp = self.client.execute('DESC SPACE space_collate') self.check_resp_succeeded(resp) expect_result = [['space_collate', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0}) # drop space resp = self.client.execute('DROP SPACE space_collate') self.check_resp_succeeded(resp) # not supported collate resp = self.client.execute('CREATE SPACE space_charset_collate_nomatch (partition_num=9, ' 'replica_factor=1, charset = utf8, collate=gbk_bin, vid_type=FIXED_STRING(8))') self.check_resp_failed(resp) # not supported charset resp = self.client.execute('CREATE SPACE space_charset_collate_nomatch (partition_num=9, ' 'replica_factor=1, charset = gbk, collate=utf8_bin, vid_type=FIXED_STRING(8))') self.check_resp_failed(resp) # not supported charset resp = self.client.execute('CREATE SPACE space_illegal_charset (partition_num=9, ' 'replica_factor=1, charset = gbk, vid_type=FIXED_STRING(8))') self.check_resp_failed(resp) # not supported collate resp = self.client.execute('CREATE SPACE space_illegal_collate (partition_num=9, ' 'replica_factor=1, collate = gbk_bin, vid_type=FIXED_STRING(8))') self.check_resp_failed(resp) resp = self.client.execute('CREATE SPACE space_illegal_collate (partition_num=9, ' 'replica_factor=1, collate = gbk_bin, vid_type=FIXED_STRING(8))') self.check_resp_failed(resp) resp = self.client.execute('CREATE SPACE space_capital (partition_num=9, ' 'replica_factor=1, charset=UTF8, collate=UTF8_bin, vid_type=FIXED_STRING(8))') self.check_resp_succeeded(resp) resp = self.client.execute('DESC SPACE space_capital') self.check_resp_succeeded(resp) expect_result = [['space_capital', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(8)', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0}) # drop space resp = self.client.execute('DROP SPACE space_capital') self.check_resp_succeeded(resp) def test_if_not_exists_and_if_exist(self): # exist then failed resp = self.client.execute('CREATE SPACE default_space') self.check_resp_failed(resp) # exist but success resp = self.client.execute('CREATE SPACE IF NOT EXISTS default_space') self.check_resp_failed(resp) # not exist but success resp = self.client.execute('DROP SPACE IF EXISTS not_exist_space') self.check_resp_succeeded(resp) # not exist then failed resp = self.client.execute('DROP SPACE not_exist_space') self.check_resp_failed(resp) resp = self.client.execute('CREATE SPACE exist_space') self.check_resp_failed(resp) resp = self.client.execute('DROP SPACE IF EXISTS exist_space') self.check_resp_succeeded(resp) def test_drop_space(self): resp = self.client.execute('SHOW SPACES') self.check_resp_succeeded(resp) expect_result = [['default_space']] self.search_result(resp, expect_result) resp = self.client.execute('DROP SPACE default_space') self.check_resp_succeeded(resp) resp = self.client.execute('SHOW SPACES') self.check_resp_succeeded(resp) expect_result = [['default_space']] self.search_not_exist(resp, expect_result) def test_create_space_with_string_vid(self): resp = self.client.execute('CREATE SPACE space_string_vid (partition_num=9, ' 'replica_factor=1, charset=utf8, collate=utf8_bin, ' 'vid_type = fixed_string(30))') self.check_resp_succeeded(resp) resp = self.client.execute('DESC SPACE space_string_vid') self.check_resp_succeeded(resp) expect_result = [['space_string_vid', 9, 1, 'utf8', 'utf8_bin', 'FIXED_STRING(30)', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0}) def test_create_space_with_int_vid(self): resp = self.client.execute('CREATE SPACE space_int_vid (partition_num=9, ' 'replica_factor=1, charset=utf8, collate=utf8_bin, ' 'vid_type = int64)') self.check_resp_succeeded(resp) resp = self.client.execute('DESC SPACE space_int_vid') self.check_resp_succeeded(resp) expect_result = [['space_int_vid', 9, 1, 'utf8', 'utf8_bin', 'INT64', False, 'default', T_EMPTY]] self.check_result(resp, expect_result, {0})
43.486842
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9,915
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4
912c9bec67f638a52259405756d4fda4dc737190
195
py
Python
backend/ohq/pagination.py
pennlabs/Office-Hours-Queue
f73ec90223c43595c9a167162d9d74abfb11ca42
[ "MIT" ]
8
2020-09-05T21:12:25.000Z
2022-01-30T18:25:12.000Z
backend/ohq/pagination.py
pennlabs/Office-Hours-Queue
f73ec90223c43595c9a167162d9d74abfb11ca42
[ "MIT" ]
161
2020-08-05T17:05:56.000Z
2022-03-27T17:44:51.000Z
backend/ohq/pagination.py
pennlabs/office-hours-queue
fce98d3a1b83d1459f61e6d9c3347ef619ee384e
[ "MIT" ]
null
null
null
from rest_framework.pagination import PageNumberPagination class QuestionSearchPagination(PageNumberPagination): """ Custom pagination for QuestionListView. """ page_size = 20
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4
912fcf83b92837a8ee7ae06692c8b883b70e6322
1,577
py
Python
contact/migrations/0006_contactformsuccesspage.py
uktrade/invest
15b84c511839b46e81608fca9762d2df3f6df16c
[ "MIT" ]
1
2019-01-18T03:50:46.000Z
2019-01-18T03:50:46.000Z
contact/migrations/0006_contactformsuccesspage.py
uktrade/invest
15b84c511839b46e81608fca9762d2df3f6df16c
[ "MIT" ]
50
2018-01-24T18:04:08.000Z
2019-01-03T03:30:30.000Z
contact/migrations/0006_contactformsuccesspage.py
uktrade/invest
15b84c511839b46e81608fca9762d2df3f6df16c
[ "MIT" ]
2
2018-02-12T15:20:52.000Z
2019-01-18T03:51:52.000Z
# -*- coding: utf-8 -*- # Generated by Django 1.11.11 on 2018-04-30 10:49 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion import wagtailmarkdown.fields class Migration(migrations.Migration): dependencies = [ ('wagtailcore', '0040_page_draft_title'), ('contact', '0005_auto_20180430_0934'), ] operations = [ migrations.CreateModel( name='ContactFormSuccessPage', fields=[ ('page_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE, parent_link=True, primary_key=True, serialize=False, to='wagtailcore.Page')), ('body_text', wagtailmarkdown.fields.MarkdownField()), ('body_text_en', wagtailmarkdown.fields.MarkdownField(null=True)), ('body_text_de', wagtailmarkdown.fields.MarkdownField(null=True)), ('body_text_es', wagtailmarkdown.fields.MarkdownField(null=True)), ('body_text_fr', wagtailmarkdown.fields.MarkdownField(null=True)), ('body_text_pt', wagtailmarkdown.fields.MarkdownField(null=True)), ('body_text_ar', wagtailmarkdown.fields.MarkdownField(null=True)), ('body_text_ja', wagtailmarkdown.fields.MarkdownField(null=True)), ('body_text_zh_cn', wagtailmarkdown.fields.MarkdownField(null=True)), ], options={ 'abstract': False, }, bases=('wagtailcore.page',), ), ]
41.5
191
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0.361944
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4
9136bfcfa117b4c5680a0980961f5f207e1dd0bf
108
py
Python
packages/python/yap_kernel/yap_ipython/testing/__main__.py
ryandesign/yap
9a50d1a3d985ec559ebfbb8e9f4d4c6b88b30214
[ "Artistic-1.0-Perl", "ClArtistic" ]
90
2015-03-09T01:24:15.000Z
2022-02-24T13:56:25.000Z
packages/python/yap_kernel/yap_ipython/testing/__main__.py
ryandesign/yap
9a50d1a3d985ec559ebfbb8e9f4d4c6b88b30214
[ "Artistic-1.0-Perl", "ClArtistic" ]
52
2016-02-14T08:59:37.000Z
2022-03-14T16:39:35.000Z
packages/python/yap_kernel/yap_ipython/testing/__main__.py
ryandesign/yap
9a50d1a3d985ec559ebfbb8e9f4d4c6b88b30214
[ "Artistic-1.0-Perl", "ClArtistic" ]
27
2015-11-19T02:45:49.000Z
2021-11-25T19:47:58.000Z
if __name__ == '__main__': from yap_ipython.testing import iptestcontroller iptestcontroller.main()
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e67a8860894f989b3e72afd36951546adab63cf8
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py
Python
python3.4Smartforest/lib/python3.4/site-packages/django/contrib/admin/__init__.py
letouriste001/SmartForest_2.0
109b78bf1e8c8404800f377ab969395ccbb617be
[ "MIT" ]
null
null
null
python3.4Smartforest/lib/python3.4/site-packages/django/contrib/admin/__init__.py
letouriste001/SmartForest_2.0
109b78bf1e8c8404800f377ab969395ccbb617be
[ "MIT" ]
null
null
null
python3.4Smartforest/lib/python3.4/site-packages/django/contrib/admin/__init__.py
letouriste001/SmartForest_2.0
109b78bf1e8c8404800f377ab969395ccbb617be
[ "MIT" ]
null
null
null
# ACTION_CHECKBOX_NAME is unused, but should stay since its import from here # has been referenced in documentation. from django.contrib.admin.decorators import register from django.contrib.admin.filters import ( AllValuesFieldListFilter, BooleanFieldListFilter, ChoicesFieldListFilter, DateFieldListFilter, FieldListFilter, ListFilter, RelatedFieldListFilter, RelatedOnlyFieldListFilter, SimpleListFilter, ) from django.contrib.admin.helpers import ACTION_CHECKBOX_NAME from django.contrib.admin.options import ( HORIZONTAL, VERTICAL, ModelAdmin, StackedInline, TabularInline, ) from django.contrib.admin.sites import AdminSite, site from django.utils.module_loading import autodiscover_modules __all__ = [ "register", "ACTION_CHECKBOX_NAME", "ModelAdmin", "HORIZONTAL", "VERTICAL", "StackedInline", "TabularInline", "AdminSite", "site", "ListFilter", "SimpleListFilter", "FieldListFilter", "BooleanFieldListFilter", "RelatedFieldListFilter", "ChoicesFieldListFilter", "DateFieldListFilter", "AllValuesFieldListFilter", "RelatedOnlyFieldListFilter", "autodiscover", ] def autodiscover(): autodiscover_modules('admin', register_to=site) default_app_config = 'django.contrib.admin.apps.AdminConfig'
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4
e680e9adaa7b818851db4beac018c7aee50d1cb7
616
py
Python
EGGS_labrad/clients/__init__.py
EGGS-Experiment/EGGS_labrad
60ff5d6e3c13d3bd42d3127dd4685070b197ea07
[ "MIT" ]
2
2021-12-26T05:00:54.000Z
2021-12-30T17:15:49.000Z
EGGS_labrad/clients/__init__.py
EGGS-Experiment/EGGS_labrad
60ff5d6e3c13d3bd42d3127dd4685070b197ea07
[ "MIT" ]
null
null
null
EGGS_labrad/clients/__init__.py
EGGS-Experiment/EGGS_labrad
60ff5d6e3c13d3bd42d3127dd4685070b197ea07
[ "MIT" ]
null
null
null
""" Contains everything needed to write clients. """ __all__ = [] # utils from EGGS_labrad.clients import utils from EGGS_labrad.clients.utils import * __all__.extend(utils.__all__) # client classes from EGGS_labrad.clients import client from EGGS_labrad.clients.client import * __all__.extend(client.__all__) # connection objects from EGGS_labrad.clients.script_scanner_gui import connect from EGGS_labrad.clients.script_scanner_gui.connect import * __all__.extend(connect.__all__) # widgets from EGGS_labrad.clients import Widgets from EGGS_labrad.clients.Widgets import * __all__.extend(Widgets.__all__)
20.533333
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1
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4
e6a8af56204a16dae94af5f8c0ad8a44032a534f
111
py
Python
nes/processors/ppu/attribute_table.py
Hexadorsimal/pynes
dbb3d40c1240fa27f70fa798bcec09188755eec2
[ "MIT" ]
1
2017-05-13T18:57:09.000Z
2017-05-13T18:57:09.000Z
nes/processors/ppu/attribute_table.py
Hexadorsimal/py6502
dbb3d40c1240fa27f70fa798bcec09188755eec2
[ "MIT" ]
7
2020-10-24T17:16:56.000Z
2020-11-01T14:10:23.000Z
nes/processors/ppu/attribute_table.py
Hexadorsimal/pynes
dbb3d40c1240fa27f70fa798bcec09188755eec2
[ "MIT" ]
null
null
null
class AttributeTable: def __init__(self, start, size): self.start = start self.size = size
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4
e6c066b63a0347107c4c7d042a272ec4e4cf7814
2,283
py
Python
tests/tests.py
RCoff/Smartsheet-DataFrame
598f7f4e4f930d963e62855ab540e66aef350f50
[ "MIT" ]
5
2021-11-25T01:17:02.000Z
2022-02-18T15:58:13.000Z
tests/tests.py
RCoff/Smartsheet-DataFrame
598f7f4e4f930d963e62855ab540e66aef350f50
[ "MIT" ]
null
null
null
tests/tests.py
RCoff/Smartsheet-DataFrame
598f7f4e4f930d963e62855ab540e66aef350f50
[ "MIT" ]
null
null
null
import smartsheet import unittest import config from src.smartsheet_dataframe import get_report_as_df, get_sheet_as_df, get_as_df class SheetTests(unittest.TestCase): def setUp(self): self.token = config.smartsheet_access_token self.sheet_id = config.sheet_id self.report_id = config.report_id self.sheet_client = smartsheet.Smartsheet(self.token) self.sheet_obj = self.sheet_client.Sheets.get_sheet(self.sheet_id, include=['objectValue'], level=1) def test_object_and_request_are_equal(self): df1 = get_sheet_as_df(token=self.token, sheet_id=self.sheet_id) df2 = get_sheet_as_df(sheet_obj=self.sheet_obj) self.assertTrue(df1.to_dict() == df2.to_dict()) def test_generic_vs_specific_requests(self): df1 = get_sheet_as_df(token=self.token, sheet_id=self.sheet_id) df2 = get_as_df(type_='sheet', token=self.token, id_=self.sheet_id) self.assertTrue(df1.to_dict() == df2.to_dict()) def test_generic_vs_specific_object(self): df1 = get_sheet_as_df(sheet_obj=self.sheet_obj) df2 = get_as_df(type_='sheet', obj=self.sheet_obj) self.assertTrue(df1.to_dict() == df2.to_dict()) class ReportTests(unittest.TestCase): def setUp(self): self.token = config.smartsheet_access_token self.report_id = config.report_id self.sheet_client = smartsheet.Smartsheet(self.token) self.report_obj = self.sheet_client.Reports.get_report(self.report_id) def test_report_object_and_request_are_equal(self): df1 = get_report_as_df(token=self.token, report_id=self.report_id) df2 = get_report_as_df(report_obj=self.report_obj) self.assertTrue(df1.to_dict() == df2.to_dict()) def test_generic_vs_specific_requests(self): df1 = get_report_as_df(token=self.token, report_id=self.report_id) df2 = get_as_df(type_='report', token=self.token, id_=self.report_id) self.assertTrue(df1.to_dict() == df2.to_dict()) def test_generic_vs_specific_object(self): df1 = get_report_as_df(report_obj=self.report_obj) df2 = get_as_df(type_='report', obj=self.report_obj) self.assertTrue(df1.to_dict() == df2.to_dict()) if __name__ == "__main__": unittest.main()
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4
e6d621eeef540a2461f7929b43d7a6e12d421ce6
240
py
Python
agent/__init__.py
eric8607242/OSNASLib
43908ab454fb78f835f8a015935205179b9acec4
[ "MIT" ]
3
2021-06-14T11:00:21.000Z
2021-10-18T02:59:54.000Z
agent/__init__.py
eric8607242/OneShot_NAS_example
2e758a9e5d9e03eecb9c4cc0e2e6a8ec38cf7052
[ "MIT" ]
1
2021-12-04T07:42:25.000Z
2021-12-04T15:14:12.000Z
agent/__init__.py
eric8607242/OneShot_NAS_example
2e758a9e5d9e03eecb9c4cc0e2e6a8ec38cf7052
[ "MIT" ]
null
null
null
import sys def get_agent_cls(name): return getattr(sys.modules[__name__], name) # Importing customizing modules from .classification_agent import CFSearchAgent, CFEvaluateAgent from .face_agent import FRSearchAgent, FREvaluateAgent
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4
e6e14f923671c7fde994222291155054f0ade282
43
py
Python
src/tools/generator/__init__.py
technote-space/genetic-algorithms-py
a37e0a34c5970987d76fda6b14a48d9ab0579e33
[ "MIT" ]
3
2020-09-03T18:02:30.000Z
2020-09-08T18:09:38.000Z
src/tools/generator/__init__.py
Amplil/genetic-algorithms-py
4788c73b1b9d57eac904e8eb99d9140457201e6b
[ "MIT" ]
7
2020-09-08T16:57:19.000Z
2022-03-12T00:51:26.000Z
src/tools/generator/__init__.py
Amplil/genetic-algorithms-py
4788c73b1b9d57eac904e8eb99d9140457201e6b
[ "MIT" ]
1
2021-04-14T11:10:50.000Z
2021-04-14T11:10:50.000Z
from .make import Make __all__ = ['Make']
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4
e6f5abd6175dd600d7260c994f23b6321bcc673d
120
py
Python
uniname.py
Rosuav/shed
ea161a50cf3695da6e68c0f15c2c63d4996d4c26
[ "MIT" ]
12
2015-01-12T15:44:46.000Z
2020-07-10T06:35:36.000Z
uniname.py
Rosuav/shed
ea161a50cf3695da6e68c0f15c2c63d4996d4c26
[ "MIT" ]
2
2021-11-06T02:09:30.000Z
2022-01-23T07:22:09.000Z
uniname.py
Rosuav/shed
ea161a50cf3695da6e68c0f15c2c63d4996d4c26
[ "MIT" ]
8
2016-10-12T20:17:10.000Z
2022-03-26T08:18:34.000Z
#!/usr/bin/env python3 import sys, unicodedata for ch in " ".join(sys.argv[1:]): print(ascii(ch), unicodedata.name(ch))
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1
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4
fc129dca5d24dfa514c25f7d1d28d1ba66574430
7,748
py
Python
tests/test_remote_serialize.py
KarenImmanuel/hangar-py
2a5caff259ad699db56676f14a70cb94e75d8a5b
[ "Apache-2.0" ]
null
null
null
tests/test_remote_serialize.py
KarenImmanuel/hangar-py
2a5caff259ad699db56676f14a70cb94e75d8a5b
[ "Apache-2.0" ]
null
null
null
tests/test_remote_serialize.py
KarenImmanuel/hangar-py
2a5caff259ad699db56676f14a70cb94e75d8a5b
[ "Apache-2.0" ]
1
2019-10-25T06:11:46.000Z
2019-10-25T06:11:46.000Z
import pytest import numpy as np param_shapes = [(1,), (1000,), (1, 1), (623, 3, 5), (2, 4, 5, 6, 1, 3)] param_dtypes = [np.uint8, np.float32, np.float64, np.int32] param_digest = ['digesta', 'digestaaaaaa', 'digestaaaaaaaaaaaaaaaaaaaaaaaaaa'] param_schema = ['schemaa', 'schemaaaaaaaaa', 'schemaaaaaaaaaaaaaaaa'] def assert_equal(arr, arr2): assert np.array_equal(arr, arr2) assert arr.dtype == arr2.dtype @pytest.fixture(scope='module', params=param_shapes) def arr_shape(request): return request.param @pytest.fixture(scope='module', params=param_dtypes) def arr_dtype(request): return request.param @pytest.fixture(scope='module', params=param_digest) def ident_digest(request): return request.param @pytest.fixture(scope='module', params=param_schema) def ident_schema(request): return request.param @pytest.fixture(scope='module') def array_testcase(arr_shape, arr_dtype): arr = 200 * np.random.random_sample(arr_shape) - 100 return arr.astype(arr_dtype) @pytest.fixture(scope='module') def ident_testcase(ident_digest, ident_schema): return (ident_digest, ident_schema) def test_serialize_deserialize_array(array_testcase): from hangar.remote.chunks import serialize_arr from hangar.remote.chunks import deserialize_arr raw = serialize_arr(array_testcase) res = deserialize_arr(raw) assert_equal(array_testcase, res) def test_serialize_deserialize_ident(ident_testcase): from hangar.remote.chunks import serialize_ident from hangar.remote.chunks import deserialize_ident from hangar.remote.chunks import ArrayIdent digest, schema = ident_testcase raw = serialize_ident(digest, schema) res = deserialize_ident(raw) assert isinstance(res, ArrayIdent) assert res.digest == digest assert res.schema == schema def test_serialize_deserialize_record(array_testcase, ident_testcase): from hangar.remote.chunks import serialize_record from hangar.remote.chunks import deserialize_record from hangar.remote.chunks import ArrayRecord digest, schema = ident_testcase raw = serialize_record(array_testcase, digest, schema) res = deserialize_record(raw) assert isinstance(res, ArrayRecord) assert_equal(res.array, array_testcase) assert res.digest == digest assert res.schema == schema @pytest.mark.parametrize('nrecords', [1, 25]) def test_serialize_deserialize_record_pack(ident_testcase, nrecords): from hangar.remote.chunks import serialize_record from hangar.remote.chunks import serialize_record_pack from hangar.remote.chunks import deserialize_record from hangar.remote.chunks import deserialize_record_pack from hangar.remote.chunks import ArrayRecord idx = 0 ArrList, RecList = [], [] digest, schema = ident_testcase for shape in param_shapes: for dtype in param_dtypes: arr = 200 * np.random.random_sample(shape) + 100 arr = arr.astype(dtype) digest = f'digest{str(idx)*len(digest)}' schema = f'schema{str(idx)*len(schema)}' idx += 1 ArrList.append((arr, digest, schema)) RecList.append(serialize_record(arr, digest, schema)) rawpack = serialize_record_pack(RecList) reslist = deserialize_record_pack(rawpack) assert reslist == RecList for rawres, origRec in zip(reslist, ArrList): resRec = deserialize_record(rawres) assert isinstance(resRec, ArrayRecord) assert_equal(resRec.array, origRec[0]) assert resRec.digest == origRec[1] assert resRec.schema == origRec[2] def test_serialize_deserialize_ident_digest_field_only(ident_testcase): from hangar.remote.chunks import serialize_ident from hangar.remote.chunks import deserialize_ident from hangar.remote.chunks import ArrayIdent digest, schema = ident_testcase raw = serialize_ident(digest, '') res = deserialize_ident(raw) assert isinstance(res, ArrayIdent) assert res.digest == digest assert res.schema == '' def test_serialize_deserialize_ident_schema_field_only(ident_testcase): from hangar.remote.chunks import serialize_ident from hangar.remote.chunks import deserialize_ident from hangar.remote.chunks import ArrayIdent digest, schema = ident_testcase raw = serialize_ident('', schema) res = deserialize_ident(raw) assert isinstance(res, ArrayIdent) assert res.digest == '' assert res.schema == schema @pytest.mark.parametrize('nrecords', [1, 25]) def test_serialize_deserialize_ident_only_record_pack(ident_testcase, nrecords): from hangar.remote.chunks import serialize_ident from hangar.remote.chunks import deserialize_ident from hangar.remote.chunks import serialize_record_pack from hangar.remote.chunks import deserialize_record_pack from hangar.remote.chunks import ArrayIdent idx = 0 IdentList, RawList = [], [] digest, schema = ident_testcase for idx in range(nrecords): digest = f'digest{str(idx)*len(digest)}' schema = f'schema{str(idx)*len(schema)}' IdentList.append((digest, schema)) RawList.append(serialize_ident(digest, schema)) packed_raw = serialize_record_pack(RawList) unpacked_raw = deserialize_record_pack(packed_raw) assert unpacked_raw == RawList for raw, origIdent in zip(unpacked_raw, IdentList): resIdent = deserialize_ident(raw) assert isinstance(resIdent, ArrayIdent) assert resIdent.digest == origIdent[0] assert resIdent.schema == origIdent[1] @pytest.mark.parametrize('nrecords', [1, 25]) def test_serialize_deserialize_ident_only_digest_only_record_pack(ident_testcase, nrecords): from hangar.remote.chunks import serialize_ident from hangar.remote.chunks import deserialize_ident from hangar.remote.chunks import serialize_record_pack from hangar.remote.chunks import deserialize_record_pack from hangar.remote.chunks import ArrayIdent idx = 0 IdentList, RawList = [], [] digest, schema = ident_testcase for idx in range(nrecords): digest = f'digest{str(idx)*len(digest)}' schema = f'' IdentList.append((digest, schema)) RawList.append(serialize_ident(digest, schema)) packed_raw = serialize_record_pack(RawList) unpacked_raw = deserialize_record_pack(packed_raw) assert unpacked_raw == RawList for raw, origIdent in zip(unpacked_raw, IdentList): resIdent = deserialize_ident(raw) assert isinstance(resIdent, ArrayIdent) assert resIdent.digest == origIdent[0] assert resIdent.schema == origIdent[1] @pytest.mark.parametrize('nrecords', [1, 25]) def test_serialize_deserialize_ident_only_schema_only_record_pack(ident_testcase, nrecords): from hangar.remote.chunks import serialize_ident from hangar.remote.chunks import deserialize_ident from hangar.remote.chunks import serialize_record_pack from hangar.remote.chunks import deserialize_record_pack from hangar.remote.chunks import ArrayIdent idx = 0 IdentList, RawList = [], [] digest, schema = ident_testcase for idx in range(nrecords): digest = f'' schema = f'schema{str(idx)*len(schema)}' IdentList.append((digest, schema)) RawList.append(serialize_ident(digest, schema)) packed_raw = serialize_record_pack(RawList) unpacked_raw = deserialize_record_pack(packed_raw) assert unpacked_raw == RawList for raw, origIdent in zip(unpacked_raw, IdentList): resIdent = deserialize_ident(raw) assert isinstance(resIdent, ArrayIdent) assert resIdent.digest == origIdent[0] assert resIdent.schema == origIdent[1]
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4
fc1d1836fe2ca7576472394f54f6cf39919affc1
1,404
py
Python
src/data/data_extractor.py
ElenaVasylenko/titanic
4256d18354466de2e3d3af1da283959c25bb22f9
[ "MIT" ]
null
null
null
src/data/data_extractor.py
ElenaVasylenko/titanic
4256d18354466de2e3d3af1da283959c25bb22f9
[ "MIT" ]
null
null
null
src/data/data_extractor.py
ElenaVasylenko/titanic
4256d18354466de2e3d3af1da283959c25bb22f9
[ "MIT" ]
null
null
null
import pandas as pd from config import PROJECT_DIR_PATH, PROCESSED_FILES_DIR class DataExtractor(): def __init__(self): self.train_file_path = PROJECT_DIR_PATH + "\\data_files\\train.csv" self.test_file_path = PROJECT_DIR_PATH + "\\data_files\\test.csv" self.processed_train_file_path = PROCESSED_FILES_DIR + "\\train.csv" self.processed_test_file_path = PROCESSED_FILES_DIR + "\\test.csv" self.train_df = pd.read_csv(self.train_file_path, index_col='PassengerId') self.test_df = pd.read_csv(self.test_file_path, index_col='PassengerId') self.processed_train_df = pd.read_csv(self.processed_train_file_path, index_col='PassengerId') self.processed_test_df = pd.read_csv(self.processed_test_file_path, index_col='PassengerId') #print(self.train_df.info()) self.test_df['Survived'] = -888 # Add Survived column for prediction self.df = pd.concat((self.train_df, self.test_df), axis=0) #print(self.df.info()) def get_df(self): return self.df def get_train_df(self): return self.train_df def get_test_df(self): return self.test_df def get_processed_test_df(self): return self.processed_test_df def get_processed_train_df(self): return self.processed_train_df data_extractor = DataExtractor() data_extractor_df = data_extractor.get_df()
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4
fc31ede07249e87a601e1df74acfd0461999064d
113
py
Python
developer/lab/ipython/notebooks/sacred.utils.SacredInterrupt.py
arXiv-research/DevLab-III
fdb3f4fd1abf1beafdc84fecca016db169c5f923
[ "MIT" ]
1
2021-04-17T04:38:57.000Z
2021-04-17T04:38:57.000Z
developer/lab/ipython/notebooks/sacred.utils.SacredInterrupt.py
arXiv-research/DevLab-III
fdb3f4fd1abf1beafdc84fecca016db169c5f923
[ "MIT" ]
null
null
null
developer/lab/ipython/notebooks/sacred.utils.SacredInterrupt.py
arXiv-research/DevLab-III
fdb3f4fd1abf1beafdc84fecca016db169c5f923
[ "MIT" ]
null
null
null
from sacred.utils import SacredInterrupt class CustomInterrupt(SacredInterrupt) STATUS = 'MY_CUSTOM_STATUS'
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4
fc6b63ee85841ca211ad643f80e86a4cb4354017
232
py
Python
tests/app/apps.py
systemallica/django-snitch
557ae2a0e01184ffc552536507782fff39785457
[ "MIT" ]
16
2019-08-14T13:21:46.000Z
2021-09-03T10:35:23.000Z
tests/app/apps.py
systemallica/django-snitch
557ae2a0e01184ffc552536507782fff39785457
[ "MIT" ]
5
2020-03-24T17:48:35.000Z
2021-05-12T10:02:53.000Z
tests/app/apps.py
systemallica/django-snitch
557ae2a0e01184ffc552536507782fff39785457
[ "MIT" ]
4
2019-09-30T11:18:14.000Z
2021-01-05T12:26:22.000Z
from django.apps import AppConfig class TestAppConfig(AppConfig): """Testing app.""" name = "tests.app" def ready(self): try: import tests.app.signals except ImportError: pass
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4
fc787937f43a9b120ec47eb8b90af12a5f6f2496
216
py
Python
project_simple/tests/dags/test_cli.py
KostyaEsmukov/airflow-docker
abf7c50cec71f5153148738d13401546cef9f60c
[ "MIT" ]
null
null
null
project_simple/tests/dags/test_cli.py
KostyaEsmukov/airflow-docker
abf7c50cec71f5153148738d13401546cef9f60c
[ "MIT" ]
null
null
null
project_simple/tests/dags/test_cli.py
KostyaEsmukov/airflow-docker
abf7c50cec71f5153148738d13401546cef9f60c
[ "MIT" ]
null
null
null
from pathlib import Path import pytest from project_common.testing_cli import * # noqa import project_simple @pytest.fixture(scope="session") def src_root_path(): return Path(project_simple.__file__).parent
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4
fc7928940c86b3c2442bdcb7ff98f8aafb19b9c3
2,376
py
Python
test/PR_test/integration_test/dataset/test_batch_dataset.py
DwijayDS/fastestimator
9b288cb2bd870f971ec4cee09d0b3205e1316a94
[ "Apache-2.0" ]
null
null
null
test/PR_test/integration_test/dataset/test_batch_dataset.py
DwijayDS/fastestimator
9b288cb2bd870f971ec4cee09d0b3205e1316a94
[ "Apache-2.0" ]
null
null
null
test/PR_test/integration_test/dataset/test_batch_dataset.py
DwijayDS/fastestimator
9b288cb2bd870f971ec4cee09d0b3205e1316a94
[ "Apache-2.0" ]
null
null
null
import tempfile import unittest import numpy as np import fastestimator as fe from fastestimator.dataset import NumpyDataset from fastestimator.test.unittest_util import sample_system_object, sample_system_object_torch class TestDataset(NumpyDataset): def __init__(self, data, var): super().__init__(data) self.var = var class TestBatchDataset(unittest.TestCase): def test_save_and_load_state_with_batch_dataset_tf(self): def instantiate_system(): system = sample_system_object() x_train = np.ones((2, 28, 28, 3)) y_train = np.ones((2, )) ds = TestDataset(data={'x': x_train, 'y': y_train}, var=1) train_data = fe.dataset.BatchDataset(datasets=[ds, ds], num_samples=[1, 1]) system.pipeline = fe.Pipeline(train_data=train_data, batch_size=2) return system system = instantiate_system() # make some change new_var = 2 system.pipeline.data["train"][''].datasets[0].var = new_var # save the state save_path = tempfile.mkdtemp() system.save_state(save_path) # reinstantiate system and load the state system = instantiate_system() system.load_state(save_path) loaded_var = system.pipeline.data["train"][''].datasets[0].var self.assertEqual(loaded_var, new_var) def test_save_and_load_state_with_batch_dataset_torch(self): def instantiate_system(): system = sample_system_object_torch() x_train = np.ones((2, 3, 28, 28)) y_train = np.ones((2, )) ds = TestDataset(data={'x': x_train, 'y': y_train}, var=1) train_data = fe.dataset.BatchDataset(datasets=[ds, ds], num_samples=[1, 1]) system.pipeline = fe.Pipeline(train_data=train_data, batch_size=2) return system system = instantiate_system() # make some change new_var = 2 system.pipeline.data["train"][''].datasets[0].var = new_var # save the state save_path = tempfile.mkdtemp() system.save_state(save_path) # reinstantiate system and load the state system = instantiate_system() system.load_state(save_path) loaded_var = system.pipeline.data["train"][''].datasets[0].var self.assertEqual(loaded_var, new_var)
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4
fc869b5f7105a377ede40951b7f4d0943933af5d
70
py
Python
unit_tests/__init__.py
LandRegistry/digital-street-title-ui
3477c51be8806289da02c758ca5f0732d0444a8f
[ "MIT" ]
null
null
null
unit_tests/__init__.py
LandRegistry/digital-street-title-ui
3477c51be8806289da02c758ca5f0732d0444a8f
[ "MIT" ]
null
null
null
unit_tests/__init__.py
LandRegistry/digital-street-title-ui
3477c51be8806289da02c758ca5f0732d0444a8f
[ "MIT" ]
3
2019-04-26T06:38:12.000Z
2021-04-11T05:22:21.000Z
from title_ui import config config.STATIC_ASSETS_MODE = 'production'
17.5
40
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3
41
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0
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4
fca1c7cf8beca479553355ac23daddc572c4fcfa
92
py
Python
2014/09/aircraft-over-time/graphic_config.py
nprapps/graphics-archive
97b0ef326b46a959df930f5522d325e537f7a655
[ "FSFAP" ]
14
2015-05-08T13:41:51.000Z
2021-02-24T12:34:55.000Z
2014/09/aircraft-over-time/graphic_config.py
nprapps/graphics-archive
97b0ef326b46a959df930f5522d325e537f7a655
[ "FSFAP" ]
null
null
null
2014/09/aircraft-over-time/graphic_config.py
nprapps/graphics-archive
97b0ef326b46a959df930f5522d325e537f7a655
[ "FSFAP" ]
7
2015-04-04T04:45:54.000Z
2021-02-18T11:12:48.000Z
#!/usr/bin/env python COPY_GOOGLE_DOC_KEY = '0AqjLQISCZzBkdDF6dTlNdC00Q2NPMVEtQ3FYeUh1amc'
23
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4
5da06f1df419cd10c931e58a98ac166973beac93
143
py
Python
bp/pecan/__init__.py
JAlvarezJarreta/pecan
9b630655d6490a013542fca86251d4869dd47bc3
[ "MIT" ]
5
2016-06-30T18:10:57.000Z
2021-03-30T12:31:05.000Z
bp/pecan/__init__.py
JAlvarezJarreta/pecan
9b630655d6490a013542fca86251d4869dd47bc3
[ "MIT" ]
1
2016-08-16T23:10:42.000Z
2016-08-16T23:10:42.000Z
bp/pecan/__init__.py
benedictpaten/pecan
9b630655d6490a013542fca86251d4869dd47bc3
[ "MIT" ]
3
2018-10-24T15:58:48.000Z
2019-12-18T13:44:33.000Z
#!/usr/bin/env python #Copyright (C) 2006-2011 by Benedict Paten (benedictpaten@gmail.com) # #Released under the MIT license, see LICENSE.txt
23.833333
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4
5dd99d5f099ec31fbb441416221e01a104b0ce13
5,816
py
Python
rankfromsets/gridsearch/run-rankfromsets-train.py
rohanbansal12/extended_essay
03848a1c9f4dafe8db0a9ad263e8776681139659
[ "MIT" ]
5
2020-09-17T17:56:21.000Z
2021-11-03T02:40:27.000Z
rankfromsets/gridsearch/run-rankfromsets-train.py
rohanbansal12/extended_essay
03848a1c9f4dafe8db0a9ad263e8776681139659
[ "MIT" ]
null
null
null
rankfromsets/gridsearch/run-rankfromsets-train.py
rohanbansal12/extended_essay
03848a1c9f4dafe8db0a9ad263e8776681139659
[ "MIT" ]
1
2020-11-01T11:37:38.000Z
2020-11-01T11:37:38.000Z
import copy import jobs import pathlib import addict def get_slurm_script_gpu(output_dir, command): """Returns contents of SLURM script for a gpu job.""" return """#!/bin/bash #SBATCH -N 1 #SBATCH --ntasks-per-node=1 #SBATCH --ntasks-per-socket=1 #SBATCH --gres=gpu:tesla_p100:1 #SBATCH --cpus-per-task=4 #SBATCH --mem=64000 #SBATCH --output={}/slurm_%j.out #SBATCH -t 05:59:00 #module load anaconda3 cudatoolkit/10.0 cudnn/cuda-10.0/7.3.1 #source activate yumi {} """.format( output_dir, command ) if __name__ == "__main__": commands = [ "PYTHONPATH=. python train-rankfromsets.py --train_path /scratch/gpfs/altosaar/dat/longform-data/main/combined-data/train.json --test_path /scratch/gpfs/altosaar/dat/longform-data/main/combined-data/test.json --eval_path /scratch/gpfs/altosaar/dat/longform-data/main/combined-data/evaluation.json " ] experiment_name = "news-rankfromsets" log_dir = ( pathlib.Path(pathlib.os.environ["LOG"]) / "news-classification-inner-product" ) base_grid = addict.Dict() base_grid.create_dicts = False base_grid.map_items = False base_grid.emb_size = [10, 25, 50, 100] base_grid.recall_max = 100 base_grid.tokenize = False base_grid.target_publication = 0 base_grid.batch_size = 2000 base_grid.training_steps = 1500 base_grid.momentum = 0.9 base_grid.use_sparse = False base_grid.use_gpu = True base_grid.frequency = 50 base_grid.dict_dir = pathlib.Path( "/scratch/gpfs/altosaar/dat/longform-data/main/dictionaries" ) base_grid.tokenizer_file = ( "/scratch/gpfs/altosaar/dat/longform-data/main/bert-base-uncased.txt" ) base_grid.index_file_path = ( "/scratch/gpfs/altosaar/dat/longform-data/BERT/eval_indices_list.txt" ) # RMS with all words grid = copy.deepcopy(base_grid) grid["optimizer_type"] = "RMS" grid["use_all_words"] = True grid["learning_rate"] = [1e-1, 1e-3, 1e-4, 1e-5] grid["word_embedding_type"] = ["sum", "mean"] keys_for_dir_name = jobs.get_keys_for_dir_name(grid) keys_for_dir_name.insert(0, "optimizer_type") keys_for_dir_name.insert(1, "use_all_words") for cfg in jobs.param_grid(grid): cfg["output_dir"] = jobs.make_output_dir( log_dir, experiment_name, cfg, keys_for_dir_name ) jobs.submit(commands, cfg, get_slurm_script_gpu) # RMS with only unique from first 500 words grid = copy.deepcopy(base_grid) grid["optimizer_type"] = "RMS" grid["use_all_words"] = False grid["words_to_use"] = 500 grid["learning_rate"] = [1e-1, 1e-3, 1e-4, 1e-5] grid["word_embedding_type"] = ["sum", "mean"] keys_for_dir_name = jobs.get_keys_for_dir_name(grid) keys_for_dir_name.insert(0, "optimizer_type") keys_for_dir_name.insert(1, "use_all_words") for cfg in jobs.param_grid(grid): cfg["output_dir"] = jobs.make_output_dir( log_dir, experiment_name, cfg, keys_for_dir_name ) jobs.submit(commands, cfg, get_slurm_script_gpu) # SGD with all words and sum grid = copy.deepcopy(base_grid) grid["optimizer_type"] = "SGD" grid["use_all_words"] = True grid["learning_rate"] = [0.1, 1, 5, 10, 15] grid["word_embedding_type"] = "sum" keys_for_dir_name = jobs.get_keys_for_dir_name(grid) keys_for_dir_name.insert(0, "optimizer_type") keys_for_dir_name.insert(1, "use_all_words") keys_for_dir_name.insert(2, "word_embedding_type") for cfg in jobs.param_grid(grid): cfg["output_dir"] = jobs.make_output_dir( log_dir, experiment_name, cfg, keys_for_dir_name ) jobs.submit(commands, cfg, get_slurm_script_gpu) # SGD with all words and mean grid = copy.deepcopy(base_grid) grid["optimizer_type"] = "SGD" grid["use_all_words"] = True grid["learning_rate"] = [60, 600, 3000, 6000, 9000] grid["word_embedding_type"] = "mean" keys_for_dir_name = jobs.get_keys_for_dir_name(grid) keys_for_dir_name.insert(0, "optimizer_type") keys_for_dir_name.insert(1, "use_all_words") keys_for_dir_name.insert(2, "word_embedding_type") for cfg in jobs.param_grid(grid): cfg["output_dir"] = jobs.make_output_dir( log_dir, experiment_name, cfg, keys_for_dir_name ) jobs.submit(commands, cfg, get_slurm_script_gpu) # SGD with only unique from first 500 words and sum grid = copy.deepcopy(base_grid) grid["optimizer_type"] = "SGD" grid["use_all_words"] = False grid["words_to_use"] = 500 grid["learning_rate"] = [0.1, 1, 5, 10, 15] grid["word_embedding_type"] = "mean" keys_for_dir_name = jobs.get_keys_for_dir_name(grid) keys_for_dir_name.insert(0, "optimizer_type") keys_for_dir_name.insert(1, "use_all_words") keys_for_dir_name.insert(2, "word_embedding_type") for cfg in jobs.param_grid(grid): cfg["output_dir"] = jobs.make_output_dir( log_dir, experiment_name, cfg, keys_for_dir_name ) jobs.submit(commands, cfg, get_slurm_script_gpu) # SGD with only unique from first 500 words and sum grid = copy.deepcopy(base_grid) grid["optimizer_type"] = "SGD" grid["use_all_words"] = False grid["words_to_use"] = 500 grid["learning_rate"] = [30, 300, 1500, 3000, 4500] grid["word_embedding_type"] = "mean" keys_for_dir_name = jobs.get_keys_for_dir_name(grid) keys_for_dir_name.insert(0, "optimizer_type") keys_for_dir_name.insert(1, "use_all_words") keys_for_dir_name.insert(2, "word_embedding_type") for cfg in jobs.param_grid(grid): cfg["output_dir"] = jobs.make_output_dir( log_dir, experiment_name, cfg, keys_for_dir_name ) jobs.submit(commands, cfg, get_slurm_script_gpu)
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5ddf40af4fc99ba634808aa7f934bdcdc424ad0b
7,425
py
Python
Push2/parameter_mapping_sensitivities.py
phatblat/AbletonLiveMIDIRemoteScripts
ef6e87237a9dcea1046fb6836b18af01b160736a
[ "MIT" ]
4
2015-12-31T19:13:32.000Z
2017-04-23T19:52:16.000Z
Push2/parameter_mapping_sensitivities.py
phatblat/AbletonLiveMIDIRemoteScripts
ef6e87237a9dcea1046fb6836b18af01b160736a
[ "MIT" ]
1
2015-12-23T09:59:18.000Z
2015-12-23T18:53:01.000Z
Push2/parameter_mapping_sensitivities.py
phatblat/AbletonLiveMIDIRemoteScripts
ef6e87237a9dcea1046fb6836b18af01b160736a
[ "MIT" ]
null
null
null
# Source Generated with Decompyle++ # File: parameter_mapping_sensitivities.pyc (Python 2.5) from pushbase import consts DEFAULT_SENSITIVITY_KEY = 'normal_sensitivity' FINE_GRAINED_SENSITIVITY_KEY = 'fine_grained_sensitivity' DEFAULT_SENSITIVITY = consts.CONTINUOUS_MAPPING_SENSITIVITY DEFAULT_FG_SENSITIVITY = consts.FINE_GRAINED_CONTINUOUS_MAPPING_SENSITIVITY PARAMETER_SENSITIVITIES = { 'Analog': { 'OSC1 Octave': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'OSC2 Octave': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'OSC1 Semi': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'OSC1 Detune': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'OSC2 Semi': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'OSC2 Detune': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'LoungeLizard': { 'Noise Pitch': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Damp Balance': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'P Amp < Key': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Semitone': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'Collision': { 'Res 1 Decay': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'Impulse': { '1 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '2 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '3 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '4 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '5 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '6 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '7 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '8 Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'OriginalSimpler': { 'Zoom': { DEFAULT_SENSITIVITY_KEY: 1 }, 'Mode': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Playback': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Start': { DEFAULT_SENSITIVITY_KEY: 0.2 }, 'End': { DEFAULT_SENSITIVITY_KEY: 0.2 }, 'Sensitivity': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'S Start': { DEFAULT_SENSITIVITY_KEY: 0.2 }, 'S Length': { DEFAULT_SENSITIVITY_KEY: 0.2 }, 'S Loop Length': { DEFAULT_SENSITIVITY_KEY: 0.2 }, 'Transpose': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Detune': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Gain': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Env. Type': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Filter Freq': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Filt < Vel': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Filt < Key': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Filt < LFO': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'FE < ENV': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'LR < Key': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Vol < LFO': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Pan < RND': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Pan < LFO': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'L Sync Rate': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'Operator': { 'Oscillator': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'A Coarse': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'B Coarse': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'C Coarse': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'D Coarse': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'LFO Sync': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'MidiArpeggiator': { 'Style': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Synced Rate': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Offset': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Transp. Steps': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Transp. Dist.': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Repeats': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Ret. Interval': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Groove': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Retrigger Mode': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'MidiNoteLength': { 'Synced Length': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'MidiScale': { 'Base': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Transpose': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'Amp': { 'Bass': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Middle': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Treble': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Presence': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Gain': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Volume': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'Dry/Wet': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'AutoFilter': { 'Frequency': { DEFAULT_SENSITIVITY_KEY: 1 }, 'Env. Modulation': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'LFO Sync Rate': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'LFO Phase': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'LFO Offset': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'AutoPan': { 'Sync Rate': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'BeatRepeat': { 'Grid': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Interval': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Offset': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Gate': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Pitch': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Variation': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Mix Type': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Grid': { DEFAULT_SENSITIVITY_KEY: 0.1 }, 'Variation Type': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'Corpus': { 'LFO Sync Rate': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'Eq8': { 'Band': { DEFAULT_SENSITIVITY_KEY: 0.5 }, '1 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 }, '2 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 }, '3 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 }, '4 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 }, '5 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 }, '6 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 }, '7 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 }, '8 Frequency A': { DEFAULT_SENSITIVITY_KEY: 0.4 } }, 'Flanger': { 'Sync Rate': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'GrainDelay': { 'Pitch': { DEFAULT_SENSITIVITY_KEY: 0.5 } }, 'Phaser': { 'LFO Sync Rate': { DEFAULT_SENSITIVITY_KEY: 0.1 } }, 'Resonator': { 'II Pitch': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'III Pitch': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'IV Pitch': { DEFAULT_SENSITIVITY_KEY: 0.5 }, 'V Pitch': { DEFAULT_SENSITIVITY_KEY: 0.5 } } }
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4
b90ae3301efb79ab37e54874071cd29717d8a21a
241
py
Python
A/B/C/D/E/F/G/H/3/static/templatetags/email_tags.py
FrancesMaffyValor/DownGit
997d32e9e5d8a30fa0ec0ae0f4734f4c80ece5b1
[ "MIT" ]
1
2019-09-19T07:35:23.000Z
2019-09-19T07:35:23.000Z
A/B/C/D/E/F/G/H/3/static/templatetags/email_tags.py
FrancesMaffyValor/DownGit
997d32e9e5d8a30fa0ec0ae0f4734f4c80ece5b1
[ "MIT" ]
null
null
null
A/B/C/D/E/F/G/H/3/static/templatetags/email_tags.py
FrancesMaffyValor/DownGit
997d32e9e5d8a30fa0ec0ae0f4734f4c80ece5b1
[ "MIT" ]
null
null
null
from django import template from healingcirclemassage.static.forms import EmailForm register = template.Library() @register.filter @register.inclusion_tag("email_form.html") def display_email_form(): return {"email_form": EmailForm()}
24.1
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4
f8f29b00a0bb66e2fcf3ddaaa9271a539ff99468
10,594
py
Python
home-assignments/HA3/gridworld_mdp.py
JulianoLagana/deep-machine-learning
0135a84067be357c8bc3d3a4298b60dcaf7d53d5
[ "MIT" ]
49
2017-09-07T19:56:45.000Z
2022-02-17T11:19:14.000Z
home-assignments/HA3/gridworld_mdp.py
JulianoLagana/deep-machine-learning
0135a84067be357c8bc3d3a4298b60dcaf7d53d5
[ "MIT" ]
16
2018-09-05T08:10:21.000Z
2021-09-06T11:47:54.000Z
home-assignments/HA3/gridworld_mdp.py
JulianoLagana/deep-machine-learning
0135a84067be357c8bc3d3a4298b60dcaf7d53d5
[ "MIT" ]
103
2017-09-19T13:37:32.000Z
2021-11-03T14:09:59.000Z
from collections import namedtuple import numpy as np def test_policy(pi): pi[4] = 0 # green state pi[9] = 0 # red state pi[6] = 0 # unreachable state pi[7] = 0 # unreachable state pi_star = np.array([ 3., 3., 3., 3., 0., 0., 0., 0., 1., 0., 0., 1., 1., 1., 2., 0.]) assert np.array_equal(pi, pi_star), "Failed, policy is not optimal" print('Passed: policy test, for gamma=.99') def test_state_values(V): v_star = np.array([ 0.93861973, 0.95193393, 0.9639533, 0.97612443, 1., 0.92691625, 0., 0., 0.88371826, -1., 0.91395196, 0.90255605, 0.89130223, 0.88057656, 0.79978972, 0]) assert (sum(abs(V - v_star)) < 1e-4), "Failed, not correct state-values" print('Passed: state-value test, for gamma=.99') def test_value_iteration(V, pi): test_state_values(V) test_policy(pi) def test_q_learning(Q): pi = [np.argmax(Q[i]) for i in range(len(Q[:]))] test_policy(pi) class GridWorldMDP(object): def __init__(self, trans_prob=.8): ''' Initializes an instance of the GridWorldMDP class :param trans_prob: transition probabilities (e.g. =1 for deterministic MDP) ''' assert 0 <= trans_prob and trans_prob <= 1., "Not a valid transition probability" # actions {0=N, 1=W, 2=S, 3} # available actions: North, West, South, East self.__actions_to_char = {i: char for i, char in enumerate(['↑', '←', '↓', '→'])} self.__num_actions = 4 self.__actions = np.arange(self.__num_actions) self._transition_model = self.__transition_model(trans_prob) self._num_states = np.shape(self._transition_model)[1] self._init_state = 10 # init state in lower left corner self._state = self._init_state self._states = np.arange(self._num_states) def get_states(self): ''' Returns complete set of states for the MDP :return: numpy array of shape [num states,] ''' return self._states def get_actions(self): ''' Returns complete set of actions for the MDP :return: numpy array of shape [num actions,] ''' return self.__actions @property def act_to_char_dict(self): ''' Returns dictionary that points action to char, i,e. N, W, S, E ''' return self.__actions_to_char def reset(self): ''' Resets the environment and the agent is positioned in the initial state in the bottom left corner. :return: state, reward, terminal ''' self._state = self._init_state return self._state, 0, False def step(self, action): ''' Takes one step in the environment using the selected action :param action: action to execute, integer :return: state, reward, terminal ''' trans_prob = self.state_transition_func(self._state, action) new_state = np.random.choice(self._num_states, p=trans_prob) reward = 0 terminal = self._state == 15 reward = self.reward_function(self._state, action) self._state = new_state return new_state, reward, terminal def __transition_model(self, p=.8): p_ = (1-p) / 2 return np.array([ #NORTH [[p + p_, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state [p, 0, 0, 0, 0, 2 * p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # ureachable [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # ureachable [0, 0, 0, p, 0, 0, 0,0 , p_, p_, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state [0, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, p_, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, p, 0, 0, 0, p_, 0, p_, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, p, 0, 0, 0, p_, p_, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop ], # WEST [[p + p_, 0, 0, 0, 0, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [p, 2 * p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, p, 2 * p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, p, 2* p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state [p_, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable [0, 0, 0, p_, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state [0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p + p_, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p, 2 * p_, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p, 2 * p_, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, p, p_, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, p, p_, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop ], # SOUTH [[p_, p_, 0, 0, 0, p, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, p_, p, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, p_, 0, p_, 0, 0, 0, p, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state [0, 0, 0, 0, 0, 2 * p_, 0, 0, 0, 0, p, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state [0, 0, 0, 0, 0, 0, 0, 0, p_, p_, 0, 0, 0, p, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p + p_, p_, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p, p_, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, p_, p + p_, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop ], # EAST [[p_, p, 0, 0, 0, p_, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 2*p_, p, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 2*p_, p, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, p_, p, 0, 0, 0, p_, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # green state [p_, 0, 0, 0, 0, p, 0, 0, 0, 0, p_, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0], # unreachable state [0, 0, 0, p_, 0, 0, 0, 0, 0, p, 0, 0, 0, p_, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], # red state [0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p_, p, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2 * p_, p, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2 * p_, p, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p_, p, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, p_, 0, 0, 0, 0, p + p_, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1] # terminal state loop ]]) def state_transition_func(self, s, a): ''' Returns the transition probabilities to all states given current state and action :param state: current state as integer :param action: selected action as integer :return: state-transition probabilities, i.e. [P[S_0| S=s, A_t=a], P[S_1| S=s, A=a], ..., P[S_14| S=s, A=a]] ''' return np.array(self._transition_model[a, s]) def reward_function(self, s, a): ''' Returns the reward r(s,a) :param state: current state as integer :param action: selected action as integer :return: r(s,a) ''' if s ==4: return 1 # green state elif s==9: return -1 # red state else: return 0
51.427184
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0.360204
1,658
10,594
2.199035
0.095296
0.439934
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4
f8f86e9a97a4f38d785079dd743a351edabd6c6f
3,681
py
Python
Code/queue.py
alexbarksdale/CS-1.3-Core-Data-Structures
43e9d71d90dce5d3fa06fd00c3e174bfcfdbe5af
[ "MIT" ]
null
null
null
Code/queue.py
alexbarksdale/CS-1.3-Core-Data-Structures
43e9d71d90dce5d3fa06fd00c3e174bfcfdbe5af
[ "MIT" ]
6
2020-02-15T17:40:00.000Z
2020-03-09T22:32:05.000Z
Code/queue.py
alexbarksdale/CS-1.3-Core-Data-Structures
43e9d71d90dce5d3fa06fd00c3e174bfcfdbe5af
[ "MIT" ]
null
null
null
#!python from linkedlist import LinkedList # Implement LinkedQueue below, then change the assignment at the bottom # to use this Queue implementation to verify it passes all tests class LinkedQueue(object): def __init__(self, iterable=None): """Initialize this queue and enqueue the given items, if any.""" # Initialize a new linked list to store the items self.list = LinkedList() if iterable is not None: for item in iterable: self.enqueue(item) def __repr__(self): """Return a string representation of this queue.""" return 'Queue({} items, front={})'.format(self.length(), self.front()) def is_empty(self): """Return True if this queue is empty, or False otherwise.""" return self.list.is_empty() def length(self): """Return the number of items in this queue.""" return self.list.length() def enqueue(self, item): """Insert the given item at the back of this queue. Running time: O(1) because the LL append() executes once in constant time. """ self.list.append(item) def front(self): """Return the item at the front of this queue without removing it, or None if this queue is empty.""" return None if self.is_empty() else self.list.head.data def dequeue(self): """Remove and return the item at the front of this queue, or raise ValueError if this queue is empty. Running time: O(1) because the item being removed is the first item which executes once in constant time. """ if self.is_empty(): raise ValueError("Queue is empty") top_item = self.list.head.data self.list.delete(top_item) return top_item # Implement ArrayQueue below, then change the assignment at the bottom # to use this Queue implementation to verify it passes all tests class ArrayQueue(object): def __init__(self, iterable=None): """Initialize this queue and enqueue the given items, if any.""" # Initialize a new list (dynamic array) to store the items self.list = list() if iterable is not None: for item in iterable: self.enqueue(item) def __repr__(self): """Return a string representation of this queue.""" return 'Queue({} items, front={})'.format(self.length(), self.front()) def is_empty(self): """Return True if this queue is empty, or False otherwise.""" return len(self.list) == 0 def length(self): """Return the number of items in this queue.""" return len(self.list) def enqueue(self, item): """Insert the given item at the back of this queue. Running time: O(n) because you need to shift everything over by one after you insert""" self.list.insert(0, item) def front(self): """Return the item at the front of this queue without removing it, or None if this queue is empty.""" return None if self.is_empty() else self.list[len(self.list) - 1] def dequeue(self): """Remove and return the item at the front of this queue, or raise ValueError if this queue is empty. Running time: O(1) because you're removing the last item and requires no shifting.""" if self.is_empty(): raise ValueError("Queue is empty") return self.list.pop(len(self.list) - 1) # Implement LinkedQueue and ArrayQueue above, then change the assignment below # to use each of your Queue implementations to verify they each pass all tests # Queue = LinkedQueue Queue = ArrayQueue
35.394231
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0.037833
0.033534
0.730868
0.708512
0.682717
0.682717
0.682717
0.648323
0
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3,681
103
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0.865622
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false
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0
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0
4
5d331867511d8c49bfb46ebaa6ee797755b94009
11,141
py
Python
tests/test_korean_tokenizer.py
bage79/python-nori
f7824cecea7a498a01736d6caf8dd14faeebd8b7
[ "Apache-2.0" ]
1
2020-07-13T15:23:07.000Z
2020-07-13T15:23:07.000Z
tests/test_korean_tokenizer.py
bage79/python-nori
f7824cecea7a498a01736d6caf8dd14faeebd8b7
[ "Apache-2.0" ]
null
null
null
tests/test_korean_tokenizer.py
bage79/python-nori
f7824cecea7a498a01736d6caf8dd14faeebd8b7
[ "Apache-2.0" ]
null
null
null
""" Reference: https://github.com/apache/lucene-solr/blob/master/lucene/analysis/nori/src/test/org/apache/lucene/analysis/ko/TestKoreanTokenizer.java TODO Test List. - test_reading - test_random_strings - test_random_huge_strings - test_random_huge_string_mock_graph_after - test_combining """ import os import unittest from configparser import ConfigParser from pynori.korean_tokenizer import KoreanTokenizer, DcpdMode from pynori.pos import POS cfg = ConfigParser() PATH_CUR = os.getcwd() + '/pynori' cfg.read(PATH_CUR + '/config.ini') # PATH PATH_USER_DICT = cfg['PATH']['USER_DICT'] ## Initization print('KoreanTokenizer Initializing...') tokenizer = KoreanTokenizer(verbose=False, path_userdict=PATH_USER_DICT, decompound_mode=DcpdMode.NONE, infl_decompound_mode=DcpdMode.NONE, output_unknown_unigrams=False, discard_punctuation=True) tokenizer_with_punctuation = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.NONE, DcpdMode.DISCARD, False, False) tokenizer_unigram = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.NONE, DcpdMode.DISCARD, True, True) tokenizer_decompound = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.DISCARD, DcpdMode.DISCARD, False, True) tokenizer_decompound_keep = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.MIXED, DcpdMode.MIXED, False, True) tokenizer_infl_decompound_none = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.DISCARD, DcpdMode.NONE, False, True) tokenizer_infl_decompound_mixed = KoreanTokenizer(False, PATH_USER_DICT, DcpdMode.DISCARD, DcpdMode.MIXED, False, True) # analyzer_reading => test_korean_analyzer class TestKoreanTokenizer(unittest.TestCase): def setUp(self): pass def do(self, kor_tokenizer, token_attr, in_string): kor_tokenizer.set_input(in_string) while kor_tokenizer.increment_token(): pass tkn_attr_obj = kor_tokenizer.tkn_attr_obj return tkn_attr_obj.__dict__[token_attr] def test_spaces(self): self.assertEqual(self.do(tokenizer, 'termAtt', "화학 이외의 것"), ["화학", "이외", "의", "것"]) self.assertEqual(self.do(tokenizer, 'offsetAtt', "화학 이외의 것"), [(0, 2), (10, 12), (12, 13), (22, 23)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "화학 이외의 것"), [1, 1, 1, 1]) self.assertEqual(self.do(tokenizer, 'termAtt', "화학 이외의 것"), ["화학", "이외", "의", "것"]) self.assertEqual(self.do(tokenizer, 'offsetAtt', "화학 이외의 것"), [(0, 2), (3, 5), (5, 6), (7, 8)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "화학 이외의 것"), [1, 1, 1, 1]) def test_part_of_speechs(self): self.assertEqual(self.do(tokenizer, 'posTagAtt', "화학 이외의 것"), ['NNG', 'NNG', 'JKG', 'NNB']) def test_part_of_speechs_with_punc(self): self.assertEqual(self.do(tokenizer_with_punctuation, 'termAtt', "화학 이외의 것!"), ['화학', ' ', '이외', '의', ' ', '것', '!']) self.assertEqual(self.do(tokenizer_with_punctuation, 'posTagAtt', "화학 이외의 것!"), ['NNG', 'SP', 'NNG', 'JKG', 'SP', 'NNB', 'SF']) def test_floating_point_number(self): self.assertEqual(self.do(tokenizer_with_punctuation, 'termAtt', "10.1 인치 모니터"), ['10', '.', '1', ' ', '인치', ' ', '모니터']) self.assertEqual(self.do(tokenizer_with_punctuation, 'offsetAtt', "10.1 인치 모니터"), [(0, 2), (2, 3), (3, 4), (4, 5), (5, 7), (7, 8), (8, 11)]) self.assertEqual(self.do(tokenizer_with_punctuation, 'posLengthAtt', "10.1 인치 모니터"), [1, 1, 1, 1, 1, 1, 1]) self.assertEqual(self.do(tokenizer, 'termAtt', "10.1 인치 모니터"), ['10', '1', '인치', '모니터']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "10.1 인치 모니터"), [(0, 2), (3, 4), (5, 7), (8, 11)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "10.1 인치 모니터"), [1, 1, 1, 1]) def test_part_of_speechs_with_compound(self): self.assertEqual(self.do(tokenizer, 'termAtt', "가락지나물은 한국, 중국, 일본"), ['가락지나물', '은', '한국', '중국', '일본']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "가락지나물은 한국, 중국, 일본"), [(0, 5), (5, 6), (7, 9), (11, 13), (15, 17)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "가락지나물은 한국, 중국, 일본"), [1, 1, 1, 1, 1]) self.assertEqual(self.do(tokenizer, 'posTagAtt', "가락지나물은 한국, 중국, 일본"), ['NNG', 'JX', 'NNP', 'NNP', 'NNP']) self.assertEqual(self.do(tokenizer_decompound, 'termAtt', "가락지나물은 한국, 중국, 일본"), ['가락지', '나물', '은', '한국', '중국', '일본']) self.assertEqual(self.do(tokenizer_decompound, 'offsetAtt', "가락지나물은 한국, 중국, 일본"), [(0, 3), (3, 5), (5, 6), (7, 9), (11, 13), (15, 17)]) self.assertEqual(self.do(tokenizer_decompound, 'posLengthAtt', "가락지나물은 한국, 중국, 일본"), [1, 1, 1, 1, 1, 1]) self.assertEqual(self.do(tokenizer_decompound, 'posTagAtt', "가락지나물은 한국, 중국, 일본"), ['NNG', 'NNG', 'JX', 'NNP', 'NNP', 'NNP']) self.assertEqual(self.do(tokenizer_decompound_keep, 'termAtt', "가락지나물은 한국, 중국, 일본"), ['가락지나물', '가락지', '나물', '은', '한국', '중국', '일본']) self.assertEqual(self.do(tokenizer_decompound_keep, 'offsetAtt', "가락지나물은 한국, 중국, 일본"), [(0, 5), (0, 3), (3, 5), (5, 6), (7, 9), (11, 13), (15, 17)]) self.assertEqual(self.do(tokenizer_decompound_keep, 'posLengthAtt', "가락지나물은 한국, 중국, 일본"), [2, 1, 1, 1, 1, 1, 1]) self.assertEqual(self.do(tokenizer_decompound_keep, 'posTagAtt', "가락지나물은 한국, 중국, 일본"), ['NNG', 'NNG', 'NNG', 'JX', 'NNP', 'NNP', 'NNP']) def test_part_of_speechs_with_inflects(self): self.assertEqual(self.do(tokenizer, 'termAtt', "감싸여"), ['감싸여']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "감싸여"), [(0, 3)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "감싸여"), [1]) self.assertEqual(self.do(tokenizer, 'posTypeAtt', "감싸여"), [POS.Type.INFLECT]) self.assertEqual(self.do(tokenizer, 'posTagAtt', "감싸여"), ['VV+EC']) self.assertEqual(self.do(tokenizer_decompound, 'termAtt', "감싸여"), ['감싸이', '어']) self.assertEqual(self.do(tokenizer_decompound, 'offsetAtt', "감싸여"), [(0, 3), (0, 3)]) self.assertEqual(self.do(tokenizer_decompound, 'posLengthAtt', "감싸여"), [1, 1]) self.assertEqual(self.do(tokenizer_decompound, 'posTypeAtt', "감싸여"), [POS.Type.MORPHEME, POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer_decompound, 'posTagAtt', "감싸여"), ['VV', 'EC']) self.assertEqual(self.do(tokenizer_decompound_keep, 'termAtt', "감싸여"), ['감싸여', '감싸이', '어']) self.assertEqual(self.do(tokenizer_decompound_keep, 'offsetAtt', "감싸여"), [(0, 3), (0, 3), (0, 3)]) self.assertEqual(self.do(tokenizer_decompound_keep, 'posLengthAtt', "감싸여"), [2, 1, 1]) self.assertEqual(self.do(tokenizer_decompound_keep, 'posTypeAtt', "감싸여"), [POS.Type.INFLECT, POS.Type.MORPHEME, POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer_decompound_keep, 'posTagAtt', "감싸여"), ['VV+EC', 'VV', 'EC']) def test_unknown_word(self): self.assertEqual(self.do(tokenizer, 'termAtt', "2018 평창 동계올림픽대회"), ['2018', '평창', '동계', '올림픽', '대회']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "2018 평창 동계올림픽대회"), [(0, 4), (5, 7), (8, 10), (10, 13), (13, 15)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "2018 평창 동계올림픽대회"), [1, 1, 1, 1, 1]) self.assertEqual(self.do(tokenizer, 'posTypeAtt', "2018 평창 동계올림픽대회"), [POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer, 'posTagAtt', "2018 평창 동계올림픽대회"), ['SN', 'NNP', 'NNP', 'NNP', 'NNG']) self.assertEqual(self.do(tokenizer_unigram, 'termAtt', "2018 평창 동계올림픽대회"), ['2', '0', '1', '8', '평창', '동계', '올림픽', '대회']) self.assertEqual(self.do(tokenizer_unigram, 'offsetAtt', "2018 평창 동계올림픽대회"), [(0, 1), (1, 2), (2, 3), (3, 4), (5, 7), (8, 10), (10, 13), (13, 15)]) self.assertEqual(self.do(tokenizer_unigram, 'posLengthAtt', "2018 평창 동계올림픽대회"), [1, 1, 1, 1, 1, 1, 1, 1]) self.assertEqual(self.do(tokenizer_unigram, 'posTypeAtt', "2018 평창 동계올림픽대회"), [POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer_unigram, 'posTagAtt', "2018 평창 동계올림픽대회"), ['SN', 'SN', 'SN', 'SN', 'NNP', 'NNP', 'NNP', 'NNG']) # def test_reading(self): # pass def test_userdict(self): self.assertEqual(self.do(tokenizer, 'termAtt', "c++ 프로그래밍 언어"), ['c++', '프로그래밍', '언어']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "c++ 프로그래밍 언어"), [(0, 3), (4, 9), (10, 12)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "c++ 프로그래밍 언어"), [1, 1, 1]) self.assertEqual(self.do(tokenizer, 'posTypeAtt', "c++ 프로그래밍 언어"), [POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer, 'posTagAtt', "c++ 프로그래밍 언어"), ['NNG', 'NNG', 'NNG']) self.assertEqual(self.do(tokenizer_decompound, 'termAtt', "정부세종청사"), ['정부', '세종', '청사']) self.assertEqual(self.do(tokenizer_decompound, 'offsetAtt', "정부세종청사"), [(0, 2), (2, 4), (4, 6)]) self.assertEqual(self.do(tokenizer_decompound, 'posLengthAtt', "정부세종청사"), [1, 1, 1]) self.assertEqual(self.do(tokenizer_decompound, 'posTypeAtt', "정부세종청사"), [POS.Type.MORPHEME, POS.Type.MORPHEME, POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer_decompound, 'posTagAtt', "정부세종청사"), ['NNG', 'NNG', 'NNG']) self.assertEqual(self.do(tokenizer, 'termAtt', "대한민국날씨"), ['대한민국날씨']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "대한민국날씨"), [(0, 6)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "대한민국날씨"), [1]) self.assertEqual(self.do(tokenizer, 'posTypeAtt', "대한민국날씨"), [POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer, 'posTagAtt', "대한민국날씨"), ['NNG']) self.assertEqual(self.do(tokenizer, 'termAtt', "21세기대한민국"), ['21세기대한민국']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "21세기대한민국"), [(0, 8)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "21세기대한민국"), [1]) self.assertEqual(self.do(tokenizer, 'posTypeAtt', "21세기대한민국"), [POS.Type.MORPHEME]) self.assertEqual(self.do(tokenizer, 'posTagAtt', "21세기대한민국"), ['NNG']) def test_inter_punct(self): self.assertEqual(self.do(tokenizer, 'termAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), ['도로', '지반', '수자원', '건설', '환경', '건축', '화재', '설비', '연구']) self.assertEqual(self.do(tokenizer, 'offsetAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), [(0, 2), (3, 5), (6, 9), (10, 12), (12, 14), (15, 17), (18, 20), (20, 22), (22, 24)]) self.assertEqual(self.do(tokenizer, 'posLengthAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), [1, 1, 1, 1, 1, 1, 1, 1, 1]) self.assertEqual(self.do(tokenizer, 'posTagAtt', "도로ㆍ지반ㆍ수자원ㆍ건설환경ㆍ건축ㆍ화재설비연구"), ['NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG', 'NNG']) def test_infl_mode(self): self.assertEqual(self.do(tokenizer_infl_decompound_none, 'termAtt', "가벼운 냉장고"), ['가벼운', '냉장', '고']) self.assertEqual(self.do(tokenizer_infl_decompound_mixed, 'termAtt', "가벼운 냉장고"), ['가벼운', '가볍', 'ᆫ', '냉장', '고']) def tearDown(self): pass if __name__ == '__main__': unittest.main()
69.198758
196
0.638363
1,470
11,141
4.72517
0.131973
0.168442
0.21336
0.235819
0.745897
0.706306
0.611143
0.476965
0.423265
0.298733
0
0.036986
0.157885
11,141
160
197
69.63125
0.703368
0.034018
0
0.058824
0
0
0.188204
0.008931
0
0
0
0.00625
0.655462
1
0.109244
false
0.02521
0.042017
0
0.168067
0.008403
0
0
0
null
0
1
1
0
1
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0
0
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null
0
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1
0
0
0
0
0
0
0
0
0
4
5d5ab7923cc1d778fa28786e250f7753d3f2c17a
268
py
Python
comprehemd/blocks/__init__.py
cariad/comprehemd
668c9cb5b757f0fd09ffb8e73f70d432294ad394
[ "MIT" ]
null
null
null
comprehemd/blocks/__init__.py
cariad/comprehemd
668c9cb5b757f0fd09ffb8e73f70d432294ad394
[ "MIT" ]
4
2021-11-27T09:00:53.000Z
2021-11-30T16:25:45.000Z
comprehemd/blocks/__init__.py
cariad/comprehemd
668c9cb5b757f0fd09ffb8e73f70d432294ad394
[ "MIT" ]
null
null
null
from comprehemd.blocks.block import Block from comprehemd.blocks.code import CodeBlock from comprehemd.blocks.empty import EmptyBlock from comprehemd.blocks.heading import HeadingBlock __all__ = [ "Block", "CodeBlock", "EmptyBlock", "HeadingBlock", ]
22.333333
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0.761194
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268
6.896552
0.413793
0.28
0.4
0
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0.152985
268
11
51
24.363636
0.881057
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0.134328
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false
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0.4
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0
0
0
1
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0
0
0
4
5d5b9654991ce6515bbfd1b4fff11e08ccb3fa29
177
py
Python
diffpriv_laplace/global_sensitivity/median.py
aleph-research/diff-priv-laplace-python
74233931a0edc1503c332d731d9aa2784ec04189
[ "MIT" ]
6
2020-04-13T01:09:38.000Z
2020-11-11T08:01:18.000Z
diffpriv_laplace/global_sensitivity/median.py
aleph-research/diff-priv-laplace-python
74233931a0edc1503c332d731d9aa2784ec04189
[ "MIT" ]
null
null
null
diffpriv_laplace/global_sensitivity/median.py
aleph-research/diff-priv-laplace-python
74233931a0edc1503c332d731d9aa2784ec04189
[ "MIT" ]
null
null
null
from diffpriv_laplace.global_sensitivity.base import GlobalSensitivity class MedianGlobalSensitivity(GlobalSensitivity): def __init__(self): super().__init__(1.0)
25.285714
70
0.79096
18
177
7.222222
0.888889
0
0
0
0
0
0
0
0
0
0
0.012987
0.129944
177
6
71
29.5
0.831169
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
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0
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0
0
0
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0
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0
0
null
0
0
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0
0
1
0
0
0
0
1
0
0
4
536fdb152dcef8fd304b30ccecb4f8b2be6a4616
553
py
Python
ultra/learning_algorithm/__init__.py
rowedenny/ULTRA_pytorch
4c7bcbe0e3afb9c1abf627b002f90b85c1c7c3ff
[ "Apache-2.0" ]
46
2021-07-01T04:02:35.000Z
2022-03-31T02:29:20.000Z
ultra/learning_algorithm/__init__.py
rowedenny/ULTRA_pytorch
4c7bcbe0e3afb9c1abf627b002f90b85c1c7c3ff
[ "Apache-2.0" ]
5
2021-08-12T21:20:56.000Z
2022-02-01T22:41:34.000Z
ultra/learning_algorithm/__init__.py
rowedenny/ULTRA_pytorch
4c7bcbe0e3afb9c1abf627b002f90b85c1c7c3ff
[ "Apache-2.0" ]
9
2021-08-14T12:42:26.000Z
2022-02-22T08:29:17.000Z
# note: from __future__ import absolute_import from .base_algorithm import * from .dla import * from .ipw_rank import * from .regression_EM import * from .pdgd import * from .dbgd import * from .pairwise_debias import * from .navie_algorithm import * from .mgd import * from .nsgd import * from .lambda_rank import * from .prs_rank import * def list_available() -> list: from .base_algorithm import BaseAlgorithm from ultra.utils.sys_tools import list_recursive_concrete_subclasses return list_recursive_concrete_subclasses(BaseAlgorithm)
26.333333
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0.786618
74
553
5.594595
0.445946
0.289855
0.082126
0.111111
0
0
0
0
0
0
0
0
0.148282
553
20
73
27.65
0.878981
0.009042
0
0
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0
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0
0
1
0.058824
true
0
0.882353
0
1
0
0
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0
null
1
0
0
0
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0
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0
0
0
0
0
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0
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0
0
0
0
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0
0
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null
0
0
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0
0
0
1
0
1
0
1
0
0
4
5377f1a511bcd75f7920708582f914adc64c9275
257
py
Python
kfdata/transformer.py
kylef-archive/KFData.py
685d58255c9f8518834e395d94d3b75d3dd3eceb
[ "BSD-3-Clause" ]
1
2015-11-08T13:23:39.000Z
2015-11-08T13:23:39.000Z
kfdata/transformer.py
kylef/KFData.py
685d58255c9f8518834e395d94d3b75d3dd3eceb
[ "BSD-3-Clause" ]
null
null
null
kfdata/transformer.py
kylef/KFData.py
685d58255c9f8518834e395d94d3b75d3dd3eceb
[ "BSD-3-Clause" ]
null
null
null
class ValueTransformer(object): ATTRIBUTE_TYPE = 'Transformable' def __init__(self, name): self.name = name def __str__(self): return self.name def __repr__(self): return '<ValueTransformer {}>'.format(self.name)
19.769231
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257
12
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21.416667
0.782383
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false
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0.25
0.875
0
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null
1
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1
0
0
0
1
0
0
0
4
53b94283c6cec76206879bdce8c22f3c6912330b
15
py
Python
stac_api/__init__.py
lossyrob/arturo-stac-api
3cd885639caaefd521d354a7f70ce86eea4e36e5
[ "MIT" ]
1
2021-03-25T11:39:59.000Z
2021-03-25T11:39:59.000Z
stac_api/__init__.py
lossyrob/arturo-stac-api
3cd885639caaefd521d354a7f70ce86eea4e36e5
[ "MIT" ]
null
null
null
stac_api/__init__.py
lossyrob/arturo-stac-api
3cd885639caaefd521d354a7f70ce86eea4e36e5
[ "MIT" ]
null
null
null
"""stac_api"""
7.5
14
0.533333
2
15
3.5
1
0
0
0
0
0
0
0
0
0
0
0
0.066667
15
1
15
15
0.5
0.533333
0
null
0
null
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null
0
0
0
null
1
null
true
0
0
null
null
null
1
1
0
null
0
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null
0
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0
0
0
1
0
0
0
0
0
0
4
53c8c77d0b7fef8cffd80512448706672cc52e99
94
py
Python
energenie/Devices/MIHO059.py
klattimer/pyenergenie
1677bd2ac2bda9d0cd6960b5fb537a2d097eda4e
[ "MIT" ]
null
null
null
energenie/Devices/MIHO059.py
klattimer/pyenergenie
1677bd2ac2bda9d0cd6960b5fb537a2d097eda4e
[ "MIT" ]
15
2020-03-22T13:55:00.000Z
2021-12-14T09:07:56.000Z
energenie/Devices/MIHO059.py
klattimer/pyenergenie
1677bd2ac2bda9d0cd6960b5fb537a2d097eda4e
[ "MIT" ]
null
null
null
# Smart 6mm double socket brushed steel # https://energenie4u.co.uk/catalogue/product/MIHO059
31.333333
53
0.797872
13
94
5.769231
1
0
0
0
0
0
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0.058824
0.095745
94
2
54
47
0.823529
0.946809
0
null
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null
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null
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null
true
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null
null
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0
0
1
0
0
0
0
0
0
4
53f46a9cf190ba251ed836c3a7269b1eb9271ccc
2,923
py
Python
python/lvmdatasimulator/wavecoords.py
sdss/lvmdatasimulator
3857fe0794970a51ca70baab9edc04b780b9f3bf
[ "BSD-3-Clause" ]
null
null
null
python/lvmdatasimulator/wavecoords.py
sdss/lvmdatasimulator
3857fe0794970a51ca70baab9edc04b780b9f3bf
[ "BSD-3-Clause" ]
null
null
null
python/lvmdatasimulator/wavecoords.py
sdss/lvmdatasimulator
3857fe0794970a51ca70baab9edc04b780b9f3bf
[ "BSD-3-Clause" ]
null
null
null
# encoding: utf-8 # # @Author: Oleg Egorov, Enrico Congiu # @Date: Nov 12, 2021 # @Filename: field.py # @License: BSD 3-Clause # @Copyright: Oleg Egorov, Enrico Congiu import numpy as np import astropy.units as u from dataclasses import dataclass from abc import ABC, abstractmethod import sys if (sys.version_info[0]+sys.version_info[1]/10.) < 3.8: from backports.cached_property import cached_property else: from functools import cached_property from lvmdatasimulator import ROOT_DIR @dataclass class WaveCoord(ABC): """ Abstract class describing the main properties of a WaveCoord object """ @abstractmethod def wave(self): """Build the wavelength axis""" pass @abstractmethod def start(self): """ get the starting wavelength """ pass @abstractmethod def end(self): """ Get the end wavelength""" pass @abstractmethod def step(self): """ Get the step """ pass @abstractmethod def npix(self): """ Get the step """ pass @dataclass class LinearWave(WaveCoord): """ Linear wavelength axis, most for preliminary tests purposes """ @cached_property def wave(self): filename = f'{ROOT_DIR}/data/instrument/linear_wave.dat' data = np.genfromtxt(filename, skip_header=1, unpack=True) return np.arange(data[0], data[1] + data[2], data[2]) * u.AA @cached_property def start(self): return self.wave[0] @cached_property def end(self): return self.wave[-1] @cached_property def step(self): delta = self.wave[1: -1] - self.wave[0: -2] return delta.mean() / u.pix @cached_property def npix(self): return len(self.wave) @dataclass class BlueWave(WaveCoord): """ Wavelength axis of the blue spectrograph """ @cached_property def wave(self): pass @cached_property def start(self): pass @cached_property def end(self): pass @cached_property def step(self): pass @cached_property def npix(self): return len(self.wave) @dataclass class RedWave(WaveCoord): """ wavelength axis of the red spectrograph """ @cached_property def wave(self): pass @cached_property def start(self): pass @cached_property def end(self): pass @cached_property def step(self): pass @cached_property def npix(self): return len(self.wave) @dataclass class IRWave(WaveCoord): """ wavelength axis of the IR spectrograph """ @cached_property def wave(self): pass @cached_property def start(self): pass @cached_property def end(self): pass @cached_property def step(self): pass @cached_property def npix(self): return len(self.wave)
18.26875
71
0.618543
354
2,923
5.025424
0.285311
0.181001
0.191119
0.148398
0.45756
0.333895
0.333895
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0.333895
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0
0.011905
0.28156
2,923
159
72
18.383648
0.835238
0.175163
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0.77551
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0.255102
false
0.173469
0.081633
0.061224
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1
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0
0
0
0
4
53ffdca66e9b9bb80a45fd070ef4a0a79e14cc60
449
py
Python
tests/mock_input_provider.py
wllmsash/yget
cb3828c62afc00655d8a3e72987c6c563c437580
[ "MIT" ]
null
null
null
tests/mock_input_provider.py
wllmsash/yget
cb3828c62afc00655d8a3e72987c6c563c437580
[ "MIT" ]
null
null
null
tests/mock_input_provider.py
wllmsash/yget
cb3828c62afc00655d8a3e72987c6c563c437580
[ "MIT" ]
null
null
null
from yget.input_provider import InputProvider class MockInputProvider(InputProvider): def __init__(self, input_delegate, password_delegate): super(MockInputProvider, self).__init__() self.input_delegate = input_delegate self.password_delegate = password_delegate def get_input(self, label): return self.input_delegate(label) def get_password(self, label): return self.password_delegate(label)
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58
0.739421
50
449
6.26
0.34
0.166134
0.162939
0.134185
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0.187082
449
14
59
32.071429
0.857534
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0.3
false
0.4
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0.2
0.7
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null
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1
0
1
0
1
1
0
0
4
54d63f6db8f4103d4ed1c7c6a8665715371b458c
114
py
Python
python/lvmnps/switch/exceptions.py
treetopper/lvmnps
9c2b9a7ce9a8025804d4154c8bde8b8a2be42471
[ "BSD-3-Clause" ]
null
null
null
python/lvmnps/switch/exceptions.py
treetopper/lvmnps
9c2b9a7ce9a8025804d4154c8bde8b8a2be42471
[ "BSD-3-Clause" ]
null
null
null
python/lvmnps/switch/exceptions.py
treetopper/lvmnps
9c2b9a7ce9a8025804d4154c8bde8b8a2be42471
[ "BSD-3-Clause" ]
null
null
null
class PowerException(Exception): """ An error occurred talking the the DLI Power switch """ pass
16.285714
54
0.649123
13
114
5.692308
0.923077
0
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0.27193
114
6
55
19
0.891566
0.438596
0
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true
0.5
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null
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1
1
0
0
0
0
0
4
07145334e4282e48797ab4b53e715d2c4c9fbae0
401
py
Python
datatype_tools/lib/List.py
edmundpf/datatype_tools
903094fe3aa76cf6714a8f2e53d24afcca244a39
[ "MIT" ]
null
null
null
datatype_tools/lib/List.py
edmundpf/datatype_tools
903094fe3aa76cf6714a8f2e53d24afcca244a39
[ "MIT" ]
null
null
null
datatype_tools/lib/List.py
edmundpf/datatype_tools
903094fe3aa76cf6714a8f2e53d24afcca244a39
[ "MIT" ]
null
null
null
from forbiddenfruit import curse from datatype_tools.utils.type_functions import (list_sort_by_val, list_sort_by_key, list_sort_by_key_val, list_nested_sort_by_val) #: List Curses curse(list, 'sort_by_val', list_sort_by_val) curse(list, 'sort_by_key', list_sort_by_key) curse(list, 'sort_by_key_val', list_sort_by_key_val) curse(list, 'nested_sort', list_nested_sort_by_val) #::: END PROGRAM :::
28.642857
66
0.812968
71
401
4.056338
0.253521
0.229167
0.3125
0.270833
0.59375
0.399306
0.305556
0.180556
0
0
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0.087282
401
13
67
30.846154
0.786885
0.079801
0
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0
0
0
0
1
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true
0
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null
1
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1
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0
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1
0
0
0
0
0
0
4
0717cbfa412a283a310e6a75bc6fea33accac60c
49
py
Python
ptdt/__init__.py
tanimutomo/ptdt
ab3a48a39871729ac4485a9aba843670ae6a4edc
[ "MIT" ]
null
null
null
ptdt/__init__.py
tanimutomo/ptdt
ab3a48a39871729ac4485a9aba843670ae6a4edc
[ "MIT" ]
null
null
null
ptdt/__init__.py
tanimutomo/ptdt
ab3a48a39871729ac4485a9aba843670ae6a4edc
[ "MIT" ]
null
null
null
from ptdt.ptdt import ( image, tensor, )
9.8
23
0.591837
6
49
4.833333
0.833333
0
0
0
0
0
0
0
0
0
0
0
0.306122
49
4
24
12.25
0.852941
0
0
0
0
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0
0
0
0
0
0
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1
0
true
0
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0
1
1
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null
0
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0
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1
0
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null
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0
0
0
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4
071bea025cb6690d37513a4ae985c93d91b78af7
209
py
Python
mods/mcpython/Item/Grass.py
uuk0/mcpython-a-minecraft-clone-in-python
c16cd66f319efdeec4130e1a43f5a857caf1ea13
[ "MIT" ]
2
2020-04-23T16:25:51.000Z
2020-08-27T17:56:16.000Z
mods/mcpython/Item/Grass.py
uuk0/mcpython-a-minecraft-clone-in-python
c16cd66f319efdeec4130e1a43f5a857caf1ea13
[ "MIT" ]
null
null
null
mods/mcpython/Item/Grass.py
uuk0/mcpython-a-minecraft-clone-in-python
c16cd66f319efdeec4130e1a43f5a857caf1ea13
[ "MIT" ]
null
null
null
from .Item import * class Grass(Item): def getName(self): return "minecraft:grass" def getTexturFile(self): return "./assets/textures/items/grass_item.png" handler.register(Grass)
16.076923
55
0.669856
25
209
5.56
0.68
0.129496
0
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0.210526
209
12
56
17.416667
0.842424
0
0
0
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0
0.253589
0.181818
0
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0
0
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0.285714
false
0
0.142857
0.285714
0.857143
0
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null
0
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0
1
0
0
0
1
1
0
0
4
0722310c97d54251c5976b5219db35faf74a7bc8
232
py
Python
project_name/urls.py
codyparker/django-project-template-cp
4f4d0bcae827c11b0676cc79615948920b435d4e
[ "MIT" ]
null
null
null
project_name/urls.py
codyparker/django-project-template-cp
4f4d0bcae827c11b0676cc79615948920b435d4e
[ "MIT" ]
null
null
null
project_name/urls.py
codyparker/django-project-template-cp
4f4d0bcae827c11b0676cc79615948920b435d4e
[ "MIT" ]
null
null
null
from django.conf.urls import url from django.contrib import admin from django.contrib.staticfiles.urls import staticfiles_urlpatterns urlpatterns = [ url(r'^admin/', admin.site.urls), ] urlpatterns += staticfiles_urlpatterns()
25.777778
67
0.788793
29
232
6.241379
0.413793
0.165746
0.187845
0
0
0
0
0
0
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0
0
0.112069
232
9
68
25.777778
0.878641
0
0
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0
0
0.030043
0
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0
0
0
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false
0
0.428571
0
0.428571
0
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null
0
1
0
0
0
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0
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1
0
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0
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0
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null
0
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0
0
0
0
0
1
0
0
0
0
4
07334babd4baa88cf28456f7c7b7083c252ad074
95
py
Python
spa/singlepage/apps.py
shrinks25002/Harvard-CS50
a27cd57d5dde7a06d9127fbf278b536fa8d90df0
[ "MIT" ]
2
2021-04-05T15:29:08.000Z
2022-03-08T11:07:21.000Z
Lecture 6 : User Interfaces/src6/singlepage2/singlepage/apps.py
Sumanth-Talluri/CS50-Web-Programming-with-Python-and-JavaScript
8d5f83f4354f1f27138a2a9c40317d358f3b2f9a
[ "MIT" ]
null
null
null
Lecture 6 : User Interfaces/src6/singlepage2/singlepage/apps.py
Sumanth-Talluri/CS50-Web-Programming-with-Python-and-JavaScript
8d5f83f4354f1f27138a2a9c40317d358f3b2f9a
[ "MIT" ]
null
null
null
from django.apps import AppConfig class SinglepageConfig(AppConfig): name = 'singlepage'
15.833333
34
0.768421
10
95
7.3
0.9
0
0
0
0
0
0
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0
0
0
0
0.157895
95
5
35
19
0.9125
0
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0.105263
0
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1
0
false
0
0.333333
0
1
0
1
0
0
null
0
0
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0
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0
0
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null
0
0
0
0
0
0
0
0
1
0
1
0
0
4
07464d7d9f68e728acc2d4b00825b5b3379b78cb
59,946
py
Python
sdk/datafactory/azure-mgmt-datafactory/azure/mgmt/datafactory/models/__init__.py
NateLehman/azure-sdk-for-python
82fcc5a5e9e01c3b7f6ab24fccbafad19149e400
[ "MIT" ]
1
2022-03-09T08:59:13.000Z
2022-03-09T08:59:13.000Z
sdk/datafactory/azure-mgmt-datafactory/azure/mgmt/datafactory/models/__init__.py
NateLehman/azure-sdk-for-python
82fcc5a5e9e01c3b7f6ab24fccbafad19149e400
[ "MIT" ]
null
null
null
sdk/datafactory/azure-mgmt-datafactory/azure/mgmt/datafactory/models/__init__.py
NateLehman/azure-sdk-for-python
82fcc5a5e9e01c3b7f6ab24fccbafad19149e400
[ "MIT" ]
null
null
null
# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from ._models_py3 import AccessPolicyResponse from ._models_py3 import Activity from ._models_py3 import ActivityDependency from ._models_py3 import ActivityPolicy from ._models_py3 import ActivityRun from ._models_py3 import ActivityRunsQueryResponse from ._models_py3 import AddDataFlowToDebugSessionResponse from ._models_py3 import AdditionalColumns from ._models_py3 import AmazonMWSLinkedService from ._models_py3 import AmazonMWSObjectDataset from ._models_py3 import AmazonMWSSource from ._models_py3 import AmazonRdsForOracleLinkedService from ._models_py3 import AmazonRdsForOraclePartitionSettings from ._models_py3 import AmazonRdsForOracleSource from ._models_py3 import AmazonRdsForOracleTableDataset from ._models_py3 import AmazonRdsForSqlServerLinkedService from ._models_py3 import AmazonRdsForSqlServerSource from ._models_py3 import AmazonRdsForSqlServerTableDataset from ._models_py3 import AmazonRedshiftLinkedService from ._models_py3 import AmazonRedshiftSource from ._models_py3 import AmazonRedshiftTableDataset from ._models_py3 import AmazonS3CompatibleLinkedService from ._models_py3 import AmazonS3CompatibleLocation from ._models_py3 import AmazonS3CompatibleReadSettings from ._models_py3 import AmazonS3Dataset from ._models_py3 import AmazonS3LinkedService from ._models_py3 import AmazonS3Location from ._models_py3 import AmazonS3ReadSettings from ._models_py3 import AppendVariableActivity from ._models_py3 import ArmIdWrapper from ._models_py3 import AvroDataset from ._models_py3 import AvroFormat from ._models_py3 import AvroSink from ._models_py3 import AvroSource from ._models_py3 import AvroWriteSettings from ._models_py3 import AzPowerShellSetup from ._models_py3 import AzureBatchLinkedService from ._models_py3 import AzureBlobDataset from ._models_py3 import AzureBlobFSDataset from ._models_py3 import AzureBlobFSLinkedService from ._models_py3 import AzureBlobFSLocation from ._models_py3 import AzureBlobFSReadSettings from ._models_py3 import AzureBlobFSSink from ._models_py3 import AzureBlobFSSource from ._models_py3 import AzureBlobFSWriteSettings from ._models_py3 import AzureBlobStorageLinkedService from ._models_py3 import AzureBlobStorageLocation from ._models_py3 import AzureBlobStorageReadSettings from ._models_py3 import AzureBlobStorageWriteSettings from ._models_py3 import AzureDataExplorerCommandActivity from ._models_py3 import AzureDataExplorerLinkedService from ._models_py3 import AzureDataExplorerSink from ._models_py3 import AzureDataExplorerSource from ._models_py3 import AzureDataExplorerTableDataset from ._models_py3 import AzureDataLakeAnalyticsLinkedService from ._models_py3 import AzureDataLakeStoreDataset from ._models_py3 import AzureDataLakeStoreLinkedService from ._models_py3 import AzureDataLakeStoreLocation from ._models_py3 import AzureDataLakeStoreReadSettings from ._models_py3 import AzureDataLakeStoreSink from ._models_py3 import AzureDataLakeStoreSource from ._models_py3 import AzureDataLakeStoreWriteSettings from ._models_py3 import AzureDatabricksDeltaLakeDataset from ._models_py3 import AzureDatabricksDeltaLakeExportCommand from ._models_py3 import AzureDatabricksDeltaLakeImportCommand from ._models_py3 import AzureDatabricksDeltaLakeLinkedService from ._models_py3 import AzureDatabricksDeltaLakeSink from ._models_py3 import AzureDatabricksDeltaLakeSource from ._models_py3 import AzureDatabricksLinkedService from ._models_py3 import AzureFileStorageLinkedService from ._models_py3 import AzureFileStorageLocation from ._models_py3 import AzureFileStorageReadSettings from ._models_py3 import AzureFileStorageWriteSettings from ._models_py3 import AzureFunctionActivity from ._models_py3 import AzureFunctionLinkedService from ._models_py3 import AzureKeyVaultLinkedService from ._models_py3 import AzureKeyVaultSecretReference from ._models_py3 import AzureMLBatchExecutionActivity from ._models_py3 import AzureMLExecutePipelineActivity from ._models_py3 import AzureMLLinkedService from ._models_py3 import AzureMLServiceLinkedService from ._models_py3 import AzureMLUpdateResourceActivity from ._models_py3 import AzureMLWebServiceFile from ._models_py3 import AzureMariaDBLinkedService from ._models_py3 import AzureMariaDBSource from ._models_py3 import AzureMariaDBTableDataset from ._models_py3 import AzureMySqlLinkedService from ._models_py3 import AzureMySqlSink from ._models_py3 import AzureMySqlSource from ._models_py3 import AzureMySqlTableDataset from ._models_py3 import AzurePostgreSqlLinkedService from ._models_py3 import AzurePostgreSqlSink from ._models_py3 import AzurePostgreSqlSource from ._models_py3 import AzurePostgreSqlTableDataset from ._models_py3 import AzureQueueSink from ._models_py3 import AzureSearchIndexDataset from ._models_py3 import AzureSearchIndexSink from ._models_py3 import AzureSearchLinkedService from ._models_py3 import AzureSqlDWLinkedService from ._models_py3 import AzureSqlDWTableDataset from ._models_py3 import AzureSqlDatabaseLinkedService from ._models_py3 import AzureSqlMILinkedService from ._models_py3 import AzureSqlMITableDataset from ._models_py3 import AzureSqlSink from ._models_py3 import AzureSqlSource from ._models_py3 import AzureSqlTableDataset from ._models_py3 import AzureStorageLinkedService from ._models_py3 import AzureTableDataset from ._models_py3 import AzureTableSink from ._models_py3 import AzureTableSource from ._models_py3 import AzureTableStorageLinkedService from ._models_py3 import BinaryDataset from ._models_py3 import BinaryReadSettings from ._models_py3 import BinarySink from ._models_py3 import BinarySource from ._models_py3 import BlobEventsTrigger from ._models_py3 import BlobSink from ._models_py3 import BlobSource from ._models_py3 import BlobTrigger from ._models_py3 import CMKIdentityDefinition from ._models_py3 import CassandraLinkedService from ._models_py3 import CassandraSource from ._models_py3 import CassandraTableDataset from ._models_py3 import ChainingTrigger from ._models_py3 import CloudError from ._models_py3 import CmdkeySetup from ._models_py3 import CommonDataServiceForAppsEntityDataset from ._models_py3 import CommonDataServiceForAppsLinkedService from ._models_py3 import CommonDataServiceForAppsSink from ._models_py3 import CommonDataServiceForAppsSource from ._models_py3 import ComponentSetup from ._models_py3 import CompressionReadSettings from ._models_py3 import ConcurLinkedService from ._models_py3 import ConcurObjectDataset from ._models_py3 import ConcurSource from ._models_py3 import ConnectionStateProperties from ._models_py3 import ControlActivity from ._models_py3 import CopyActivity from ._models_py3 import CopyActivityLogSettings from ._models_py3 import CopySink from ._models_py3 import CopySource from ._models_py3 import CopyTranslator from ._models_py3 import CosmosDbLinkedService from ._models_py3 import CosmosDbMongoDbApiCollectionDataset from ._models_py3 import CosmosDbMongoDbApiLinkedService from ._models_py3 import CosmosDbMongoDbApiSink from ._models_py3 import CosmosDbMongoDbApiSource from ._models_py3 import CosmosDbSqlApiCollectionDataset from ._models_py3 import CosmosDbSqlApiSink from ._models_py3 import CosmosDbSqlApiSource from ._models_py3 import CouchbaseLinkedService from ._models_py3 import CouchbaseSource from ._models_py3 import CouchbaseTableDataset from ._models_py3 import CreateDataFlowDebugSessionRequest from ._models_py3 import CreateDataFlowDebugSessionResponse from ._models_py3 import CreateLinkedIntegrationRuntimeRequest from ._models_py3 import CreateRunResponse from ._models_py3 import Credential from ._models_py3 import CredentialReference from ._models_py3 import CredentialResource from ._models_py3 import CustomActivity from ._models_py3 import CustomActivityReferenceObject from ._models_py3 import CustomDataSourceLinkedService from ._models_py3 import CustomDataset from ._models_py3 import CustomEventsTrigger from ._models_py3 import CustomSetupBase from ._models_py3 import DWCopyCommandDefaultValue from ._models_py3 import DWCopyCommandSettings from ._models_py3 import DataFlow from ._models_py3 import DataFlowDebugCommandPayload from ._models_py3 import DataFlowDebugCommandRequest from ._models_py3 import DataFlowDebugCommandResponse from ._models_py3 import DataFlowDebugPackage from ._models_py3 import DataFlowDebugPackageDebugSettings from ._models_py3 import DataFlowDebugResource from ._models_py3 import DataFlowDebugSessionInfo from ._models_py3 import DataFlowFolder from ._models_py3 import DataFlowListResponse from ._models_py3 import DataFlowReference from ._models_py3 import DataFlowResource from ._models_py3 import DataFlowSink from ._models_py3 import DataFlowSource from ._models_py3 import DataFlowSourceSetting from ._models_py3 import DataFlowStagingInfo from ._models_py3 import DataLakeAnalyticsUSQLActivity from ._models_py3 import DatabricksNotebookActivity from ._models_py3 import DatabricksSparkJarActivity from ._models_py3 import DatabricksSparkPythonActivity from ._models_py3 import Dataset from ._models_py3 import DatasetCompression from ._models_py3 import DatasetDataElement from ._models_py3 import DatasetDebugResource from ._models_py3 import DatasetFolder from ._models_py3 import DatasetListResponse from ._models_py3 import DatasetLocation from ._models_py3 import DatasetReference from ._models_py3 import DatasetResource from ._models_py3 import DatasetSchemaDataElement from ._models_py3 import DatasetStorageFormat from ._models_py3 import Db2LinkedService from ._models_py3 import Db2Source from ._models_py3 import Db2TableDataset from ._models_py3 import DeleteActivity from ._models_py3 import DeleteDataFlowDebugSessionRequest from ._models_py3 import DelimitedTextDataset from ._models_py3 import DelimitedTextReadSettings from ._models_py3 import DelimitedTextSink from ._models_py3 import DelimitedTextSource from ._models_py3 import DelimitedTextWriteSettings from ._models_py3 import DependencyReference from ._models_py3 import DistcpSettings from ._models_py3 import DocumentDbCollectionDataset from ._models_py3 import DocumentDbCollectionSink from ._models_py3 import DocumentDbCollectionSource from ._models_py3 import DrillLinkedService from ._models_py3 import DrillSource from ._models_py3 import DrillTableDataset from ._models_py3 import DynamicsAXLinkedService from ._models_py3 import DynamicsAXResourceDataset from ._models_py3 import DynamicsAXSource from ._models_py3 import DynamicsCrmEntityDataset from ._models_py3 import DynamicsCrmLinkedService from ._models_py3 import DynamicsCrmSink from ._models_py3 import DynamicsCrmSource from ._models_py3 import DynamicsEntityDataset from ._models_py3 import DynamicsLinkedService from ._models_py3 import DynamicsSink from ._models_py3 import DynamicsSource from ._models_py3 import EloquaLinkedService from ._models_py3 import EloquaObjectDataset from ._models_py3 import EloquaSource from ._models_py3 import EncryptionConfiguration from ._models_py3 import EntityReference from ._models_py3 import EnvironmentVariableSetup from ._models_py3 import ExcelDataset from ._models_py3 import ExcelSource from ._models_py3 import ExecuteDataFlowActivity from ._models_py3 import ExecuteDataFlowActivityTypeProperties from ._models_py3 import ExecuteDataFlowActivityTypePropertiesCompute from ._models_py3 import ExecutePipelineActivity from ._models_py3 import ExecutePowerQueryActivityTypeProperties from ._models_py3 import ExecuteSSISPackageActivity from ._models_py3 import ExecuteWranglingDataflowActivity from ._models_py3 import ExecutionActivity from ._models_py3 import ExportSettings from ._models_py3 import ExposureControlBatchRequest from ._models_py3 import ExposureControlBatchResponse from ._models_py3 import ExposureControlRequest from ._models_py3 import ExposureControlResponse from ._models_py3 import Expression from ._models_py3 import Factory from ._models_py3 import FactoryGitHubConfiguration from ._models_py3 import FactoryIdentity from ._models_py3 import FactoryListResponse from ._models_py3 import FactoryRepoConfiguration from ._models_py3 import FactoryRepoUpdate from ._models_py3 import FactoryUpdateParameters from ._models_py3 import FactoryVSTSConfiguration from ._models_py3 import FailActivity from ._models_py3 import FileServerLinkedService from ._models_py3 import FileServerLocation from ._models_py3 import FileServerReadSettings from ._models_py3 import FileServerWriteSettings from ._models_py3 import FileShareDataset from ._models_py3 import FileSystemSink from ._models_py3 import FileSystemSource from ._models_py3 import FilterActivity from ._models_py3 import Flowlet from ._models_py3 import ForEachActivity from ._models_py3 import FormatReadSettings from ._models_py3 import FormatWriteSettings from ._models_py3 import FtpReadSettings from ._models_py3 import FtpServerLinkedService from ._models_py3 import FtpServerLocation from ._models_py3 import GetDataFactoryOperationStatusResponse from ._models_py3 import GetMetadataActivity from ._models_py3 import GetSsisObjectMetadataRequest from ._models_py3 import GitHubAccessTokenRequest from ._models_py3 import GitHubAccessTokenResponse from ._models_py3 import GitHubClientSecret from ._models_py3 import GlobalParameterSpecification from ._models_py3 import GoogleAdWordsLinkedService from ._models_py3 import GoogleAdWordsObjectDataset from ._models_py3 import GoogleAdWordsSource from ._models_py3 import GoogleBigQueryLinkedService from ._models_py3 import GoogleBigQueryObjectDataset from ._models_py3 import GoogleBigQuerySource from ._models_py3 import GoogleCloudStorageLinkedService from ._models_py3 import GoogleCloudStorageLocation from ._models_py3 import GoogleCloudStorageReadSettings from ._models_py3 import GreenplumLinkedService from ._models_py3 import GreenplumSource from ._models_py3 import GreenplumTableDataset from ._models_py3 import HBaseLinkedService from ._models_py3 import HBaseObjectDataset from ._models_py3 import HBaseSource from ._models_py3 import HDInsightHiveActivity from ._models_py3 import HDInsightLinkedService from ._models_py3 import HDInsightMapReduceActivity from ._models_py3 import HDInsightOnDemandLinkedService from ._models_py3 import HDInsightPigActivity from ._models_py3 import HDInsightSparkActivity from ._models_py3 import HDInsightStreamingActivity from ._models_py3 import HdfsLinkedService from ._models_py3 import HdfsLocation from ._models_py3 import HdfsReadSettings from ._models_py3 import HdfsSource from ._models_py3 import HiveLinkedService from ._models_py3 import HiveObjectDataset from ._models_py3 import HiveSource from ._models_py3 import HttpDataset from ._models_py3 import HttpLinkedService from ._models_py3 import HttpReadSettings from ._models_py3 import HttpServerLocation from ._models_py3 import HttpSource from ._models_py3 import HubspotLinkedService from ._models_py3 import HubspotObjectDataset from ._models_py3 import HubspotSource from ._models_py3 import IfConditionActivity from ._models_py3 import ImpalaLinkedService from ._models_py3 import ImpalaObjectDataset from ._models_py3 import ImpalaSource from ._models_py3 import ImportSettings from ._models_py3 import InformixLinkedService from ._models_py3 import InformixSink from ._models_py3 import InformixSource from ._models_py3 import InformixTableDataset from ._models_py3 import IntegrationRuntime from ._models_py3 import IntegrationRuntimeAuthKeys from ._models_py3 import IntegrationRuntimeComputeProperties from ._models_py3 import IntegrationRuntimeConnectionInfo from ._models_py3 import IntegrationRuntimeCustomSetupScriptProperties from ._models_py3 import IntegrationRuntimeCustomerVirtualNetwork from ._models_py3 import IntegrationRuntimeDataFlowProperties from ._models_py3 import IntegrationRuntimeDataProxyProperties from ._models_py3 import IntegrationRuntimeDebugResource from ._models_py3 import IntegrationRuntimeListResponse from ._models_py3 import IntegrationRuntimeMonitoringData from ._models_py3 import IntegrationRuntimeNodeIpAddress from ._models_py3 import IntegrationRuntimeNodeMonitoringData from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesCategoryEndpoint from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesEndpoint from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesEndpointDetails from ._models_py3 import IntegrationRuntimeOutboundNetworkDependenciesEndpointsResponse from ._models_py3 import IntegrationRuntimeReference from ._models_py3 import IntegrationRuntimeRegenerateKeyParameters from ._models_py3 import IntegrationRuntimeResource from ._models_py3 import IntegrationRuntimeSsisCatalogInfo from ._models_py3 import IntegrationRuntimeSsisProperties from ._models_py3 import IntegrationRuntimeStatus from ._models_py3 import IntegrationRuntimeStatusListResponse from ._models_py3 import IntegrationRuntimeStatusResponse from ._models_py3 import IntegrationRuntimeVNetProperties from ._models_py3 import JiraLinkedService from ._models_py3 import JiraObjectDataset from ._models_py3 import JiraSource from ._models_py3 import JsonDataset from ._models_py3 import JsonFormat from ._models_py3 import JsonReadSettings from ._models_py3 import JsonSink from ._models_py3 import JsonSource from ._models_py3 import JsonWriteSettings from ._models_py3 import LinkedIntegrationRuntime from ._models_py3 import LinkedIntegrationRuntimeKeyAuthorization from ._models_py3 import LinkedIntegrationRuntimeRbacAuthorization from ._models_py3 import LinkedIntegrationRuntimeRequest from ._models_py3 import LinkedIntegrationRuntimeType from ._models_py3 import LinkedService from ._models_py3 import LinkedServiceDebugResource from ._models_py3 import LinkedServiceListResponse from ._models_py3 import LinkedServiceReference from ._models_py3 import LinkedServiceResource from ._models_py3 import LogLocationSettings from ._models_py3 import LogSettings from ._models_py3 import LogStorageSettings from ._models_py3 import LookupActivity from ._models_py3 import MagentoLinkedService from ._models_py3 import MagentoObjectDataset from ._models_py3 import MagentoSource from ._models_py3 import ManagedIdentityCredential from ._models_py3 import ManagedIntegrationRuntime from ._models_py3 import ManagedIntegrationRuntimeError from ._models_py3 import ManagedIntegrationRuntimeNode from ._models_py3 import ManagedIntegrationRuntimeOperationResult from ._models_py3 import ManagedIntegrationRuntimeStatus from ._models_py3 import ManagedPrivateEndpoint from ._models_py3 import ManagedPrivateEndpointListResponse from ._models_py3 import ManagedPrivateEndpointResource from ._models_py3 import ManagedVirtualNetwork from ._models_py3 import ManagedVirtualNetworkListResponse from ._models_py3 import ManagedVirtualNetworkReference from ._models_py3 import ManagedVirtualNetworkResource from ._models_py3 import MappingDataFlow from ._models_py3 import MariaDBLinkedService from ._models_py3 import MariaDBSource from ._models_py3 import MariaDBTableDataset from ._models_py3 import MarketoLinkedService from ._models_py3 import MarketoObjectDataset from ._models_py3 import MarketoSource from ._models_py3 import MetadataItem from ._models_py3 import MicrosoftAccessLinkedService from ._models_py3 import MicrosoftAccessSink from ._models_py3 import MicrosoftAccessSource from ._models_py3 import MicrosoftAccessTableDataset from ._models_py3 import MongoDbAtlasCollectionDataset from ._models_py3 import MongoDbAtlasLinkedService from ._models_py3 import MongoDbAtlasSink from ._models_py3 import MongoDbAtlasSource from ._models_py3 import MongoDbCollectionDataset from ._models_py3 import MongoDbCursorMethodsProperties from ._models_py3 import MongoDbLinkedService from ._models_py3 import MongoDbSource from ._models_py3 import MongoDbV2CollectionDataset from ._models_py3 import MongoDbV2LinkedService from ._models_py3 import MongoDbV2Sink from ._models_py3 import MongoDbV2Source from ._models_py3 import MultiplePipelineTrigger from ._models_py3 import MySqlLinkedService from ._models_py3 import MySqlSource from ._models_py3 import MySqlTableDataset from ._models_py3 import NetezzaLinkedService from ._models_py3 import NetezzaPartitionSettings from ._models_py3 import NetezzaSource from ._models_py3 import NetezzaTableDataset from ._models_py3 import ODataLinkedService from ._models_py3 import ODataResourceDataset from ._models_py3 import ODataSource from ._models_py3 import OdbcLinkedService from ._models_py3 import OdbcSink from ._models_py3 import OdbcSource from ._models_py3 import OdbcTableDataset from ._models_py3 import Office365Dataset from ._models_py3 import Office365LinkedService from ._models_py3 import Office365Source from ._models_py3 import Operation from ._models_py3 import OperationDisplay from ._models_py3 import OperationListResponse from ._models_py3 import OperationLogSpecification from ._models_py3 import OperationMetricAvailability from ._models_py3 import OperationMetricDimension from ._models_py3 import OperationMetricSpecification from ._models_py3 import OperationServiceSpecification from ._models_py3 import OracleCloudStorageLinkedService from ._models_py3 import OracleCloudStorageLocation from ._models_py3 import OracleCloudStorageReadSettings from ._models_py3 import OracleLinkedService from ._models_py3 import OraclePartitionSettings from ._models_py3 import OracleServiceCloudLinkedService from ._models_py3 import OracleServiceCloudObjectDataset from ._models_py3 import OracleServiceCloudSource from ._models_py3 import OracleSink from ._models_py3 import OracleSource from ._models_py3 import OracleTableDataset from ._models_py3 import OrcDataset from ._models_py3 import OrcFormat from ._models_py3 import OrcSink from ._models_py3 import OrcSource from ._models_py3 import OrcWriteSettings from ._models_py3 import PackageStore from ._models_py3 import ParameterSpecification from ._models_py3 import ParquetDataset from ._models_py3 import ParquetFormat from ._models_py3 import ParquetSink from ._models_py3 import ParquetSource from ._models_py3 import ParquetWriteSettings from ._models_py3 import PaypalLinkedService from ._models_py3 import PaypalObjectDataset from ._models_py3 import PaypalSource from ._models_py3 import PhoenixLinkedService from ._models_py3 import PhoenixObjectDataset from ._models_py3 import PhoenixSource from ._models_py3 import PipelineElapsedTimeMetricPolicy from ._models_py3 import PipelineFolder from ._models_py3 import PipelineListResponse from ._models_py3 import PipelinePolicy from ._models_py3 import PipelineReference from ._models_py3 import PipelineResource from ._models_py3 import PipelineRun from ._models_py3 import PipelineRunInvokedBy from ._models_py3 import PipelineRunsQueryResponse from ._models_py3 import PolybaseSettings from ._models_py3 import PostgreSqlLinkedService from ._models_py3 import PostgreSqlSource from ._models_py3 import PostgreSqlTableDataset from ._models_py3 import PowerQuerySink from ._models_py3 import PowerQuerySinkMapping from ._models_py3 import PowerQuerySource from ._models_py3 import PrestoLinkedService from ._models_py3 import PrestoObjectDataset from ._models_py3 import PrestoSource from ._models_py3 import PrivateEndpointConnectionListResponse from ._models_py3 import PrivateEndpointConnectionResource from ._models_py3 import PrivateLinkConnectionApprovalRequest from ._models_py3 import PrivateLinkConnectionApprovalRequestResource from ._models_py3 import PrivateLinkConnectionState from ._models_py3 import PrivateLinkResource from ._models_py3 import PrivateLinkResourceProperties from ._models_py3 import PrivateLinkResourcesWrapper from ._models_py3 import QueryDataFlowDebugSessionsResponse from ._models_py3 import QuickBooksLinkedService from ._models_py3 import QuickBooksObjectDataset from ._models_py3 import QuickBooksSource from ._models_py3 import QuickbaseLinkedService from ._models_py3 import RecurrenceSchedule from ._models_py3 import RecurrenceScheduleOccurrence from ._models_py3 import RedirectIncompatibleRowSettings from ._models_py3 import RedshiftUnloadSettings from ._models_py3 import RelationalSource from ._models_py3 import RelationalTableDataset from ._models_py3 import RemotePrivateEndpointConnection from ._models_py3 import RerunTumblingWindowTrigger from ._models_py3 import Resource from ._models_py3 import ResponsysLinkedService from ._models_py3 import ResponsysObjectDataset from ._models_py3 import ResponsysSource from ._models_py3 import RestResourceDataset from ._models_py3 import RestServiceLinkedService from ._models_py3 import RestSink from ._models_py3 import RestSource from ._models_py3 import RetryPolicy from ._models_py3 import RunFilterParameters from ._models_py3 import RunQueryFilter from ._models_py3 import RunQueryOrderBy from ._models_py3 import SSISAccessCredential from ._models_py3 import SSISChildPackage from ._models_py3 import SSISExecutionCredential from ._models_py3 import SSISExecutionParameter from ._models_py3 import SSISLogLocation from ._models_py3 import SSISPackageLocation from ._models_py3 import SSISPropertyOverride from ._models_py3 import SalesforceLinkedService from ._models_py3 import SalesforceMarketingCloudLinkedService from ._models_py3 import SalesforceMarketingCloudObjectDataset from ._models_py3 import SalesforceMarketingCloudSource from ._models_py3 import SalesforceObjectDataset from ._models_py3 import SalesforceServiceCloudLinkedService from ._models_py3 import SalesforceServiceCloudObjectDataset from ._models_py3 import SalesforceServiceCloudSink from ._models_py3 import SalesforceServiceCloudSource from ._models_py3 import SalesforceSink from ._models_py3 import SalesforceSource from ._models_py3 import SapBWLinkedService from ._models_py3 import SapBwCubeDataset from ._models_py3 import SapBwSource from ._models_py3 import SapCloudForCustomerLinkedService from ._models_py3 import SapCloudForCustomerResourceDataset from ._models_py3 import SapCloudForCustomerSink from ._models_py3 import SapCloudForCustomerSource from ._models_py3 import SapEccLinkedService from ._models_py3 import SapEccResourceDataset from ._models_py3 import SapEccSource from ._models_py3 import SapHanaLinkedService from ._models_py3 import SapHanaPartitionSettings from ._models_py3 import SapHanaSource from ._models_py3 import SapHanaTableDataset from ._models_py3 import SapOpenHubLinkedService from ._models_py3 import SapOpenHubSource from ._models_py3 import SapOpenHubTableDataset from ._models_py3 import SapTableLinkedService from ._models_py3 import SapTablePartitionSettings from ._models_py3 import SapTableResourceDataset from ._models_py3 import SapTableSource from ._models_py3 import ScheduleTrigger from ._models_py3 import ScheduleTriggerRecurrence from ._models_py3 import ScriptAction from ._models_py3 import ScriptActivity from ._models_py3 import ScriptActivityParameter from ._models_py3 import ScriptActivityScriptBlock from ._models_py3 import ScriptActivityTypePropertiesLogSettings from ._models_py3 import SecretBase from ._models_py3 import SecureString from ._models_py3 import SelfDependencyTumblingWindowTriggerReference from ._models_py3 import SelfHostedIntegrationRuntime from ._models_py3 import SelfHostedIntegrationRuntimeNode from ._models_py3 import SelfHostedIntegrationRuntimeStatus from ._models_py3 import ServiceNowLinkedService from ._models_py3 import ServiceNowObjectDataset from ._models_py3 import ServiceNowSource from ._models_py3 import ServicePrincipalCredential from ._models_py3 import SetVariableActivity from ._models_py3 import SftpLocation from ._models_py3 import SftpReadSettings from ._models_py3 import SftpServerLinkedService from ._models_py3 import SftpWriteSettings from ._models_py3 import SharePointOnlineListLinkedService from ._models_py3 import SharePointOnlineListResourceDataset from ._models_py3 import SharePointOnlineListSource from ._models_py3 import ShopifyLinkedService from ._models_py3 import ShopifyObjectDataset from ._models_py3 import ShopifySource from ._models_py3 import SkipErrorFile from ._models_py3 import SmartsheetLinkedService from ._models_py3 import SnowflakeDataset from ._models_py3 import SnowflakeExportCopyCommand from ._models_py3 import SnowflakeImportCopyCommand from ._models_py3 import SnowflakeLinkedService from ._models_py3 import SnowflakeSink from ._models_py3 import SnowflakeSource from ._models_py3 import SparkLinkedService from ._models_py3 import SparkObjectDataset from ._models_py3 import SparkSource from ._models_py3 import SqlAlwaysEncryptedProperties from ._models_py3 import SqlDWSink from ._models_py3 import SqlDWSource from ._models_py3 import SqlDWUpsertSettings from ._models_py3 import SqlMISink from ._models_py3 import SqlMISource from ._models_py3 import SqlPartitionSettings from ._models_py3 import SqlServerLinkedService from ._models_py3 import SqlServerSink from ._models_py3 import SqlServerSource from ._models_py3 import SqlServerStoredProcedureActivity from ._models_py3 import SqlServerTableDataset from ._models_py3 import SqlSink from ._models_py3 import SqlSource from ._models_py3 import SqlUpsertSettings from ._models_py3 import SquareLinkedService from ._models_py3 import SquareObjectDataset from ._models_py3 import SquareSource from ._models_py3 import SsisEnvironment from ._models_py3 import SsisEnvironmentReference from ._models_py3 import SsisFolder from ._models_py3 import SsisObjectMetadata from ._models_py3 import SsisObjectMetadataListResponse from ._models_py3 import SsisObjectMetadataStatusResponse from ._models_py3 import SsisPackage from ._models_py3 import SsisParameter from ._models_py3 import SsisProject from ._models_py3 import SsisVariable from ._models_py3 import StagingSettings from ._models_py3 import StoreReadSettings from ._models_py3 import StoreWriteSettings from ._models_py3 import StoredProcedureParameter from ._models_py3 import SubResource from ._models_py3 import SubResourceDebugResource from ._models_py3 import SwitchActivity from ._models_py3 import SwitchCase from ._models_py3 import SybaseLinkedService from ._models_py3 import SybaseSource from ._models_py3 import SybaseTableDataset from ._models_py3 import TabularSource from ._models_py3 import TabularTranslator from ._models_py3 import TarGZipReadSettings from ._models_py3 import TarReadSettings from ._models_py3 import TeamDeskLinkedService from ._models_py3 import TeradataLinkedService from ._models_py3 import TeradataPartitionSettings from ._models_py3 import TeradataSource from ._models_py3 import TeradataTableDataset from ._models_py3 import TextFormat from ._models_py3 import Transformation from ._models_py3 import Trigger from ._models_py3 import TriggerDependencyReference from ._models_py3 import TriggerFilterParameters from ._models_py3 import TriggerListResponse from ._models_py3 import TriggerPipelineReference from ._models_py3 import TriggerQueryResponse from ._models_py3 import TriggerReference from ._models_py3 import TriggerResource from ._models_py3 import TriggerRun from ._models_py3 import TriggerRunsQueryResponse from ._models_py3 import TriggerSubscriptionOperationStatus from ._models_py3 import TumblingWindowTrigger from ._models_py3 import TumblingWindowTriggerDependencyReference from ._models_py3 import TypeConversionSettings from ._models_py3 import UntilActivity from ._models_py3 import UpdateIntegrationRuntimeNodeRequest from ._models_py3 import UpdateIntegrationRuntimeRequest from ._models_py3 import UserAccessPolicy from ._models_py3 import UserProperty from ._models_py3 import ValidationActivity from ._models_py3 import VariableSpecification from ._models_py3 import VerticaLinkedService from ._models_py3 import VerticaSource from ._models_py3 import VerticaTableDataset from ._models_py3 import WaitActivity from ._models_py3 import WebActivity from ._models_py3 import WebActivityAuthentication from ._models_py3 import WebAnonymousAuthentication from ._models_py3 import WebBasicAuthentication from ._models_py3 import WebClientCertificateAuthentication from ._models_py3 import WebHookActivity from ._models_py3 import WebLinkedService from ._models_py3 import WebLinkedServiceTypeProperties from ._models_py3 import WebSource from ._models_py3 import WebTableDataset from ._models_py3 import WranglingDataFlow from ._models_py3 import XeroLinkedService from ._models_py3 import XeroObjectDataset from ._models_py3 import XeroSource from ._models_py3 import XmlDataset from ._models_py3 import XmlReadSettings from ._models_py3 import XmlSource from ._models_py3 import ZendeskLinkedService from ._models_py3 import ZipDeflateReadSettings from ._models_py3 import ZohoLinkedService from ._models_py3 import ZohoObjectDataset from ._models_py3 import ZohoSource from ._data_factory_management_client_enums import ( AmazonRdsForOraclePartitionOption, AvroCompressionCodec, AzureFunctionActivityMethod, AzureSearchIndexWriteBehaviorType, BlobEventTypes, CassandraSourceReadConsistencyLevels, CompressionCodec, CopyBehaviorType, CosmosDbConnectionMode, CosmosDbServicePrincipalCredentialType, DataFlowComputeType, DataFlowDebugCommandType, DatasetCompressionLevel, DayOfWeek, DaysOfWeek, Db2AuthenticationType, DependencyCondition, DynamicsAuthenticationType, DynamicsDeploymentType, DynamicsSinkWriteBehavior, EventSubscriptionStatus, FactoryIdentityType, FtpAuthenticationType, GlobalParameterType, GoogleAdWordsAuthenticationType, GoogleBigQueryAuthenticationType, HBaseAuthenticationType, HDInsightActivityDebugInfoOption, HdiNodeTypes, HiveAuthenticationType, HiveServerType, HiveThriftTransportProtocol, HttpAuthenticationType, ImpalaAuthenticationType, IntegrationRuntimeAuthKeyName, IntegrationRuntimeAutoUpdate, IntegrationRuntimeEdition, IntegrationRuntimeEntityReferenceType, IntegrationRuntimeInternalChannelEncryptionMode, IntegrationRuntimeLicenseType, IntegrationRuntimeSsisCatalogPricingTier, IntegrationRuntimeState, IntegrationRuntimeType, IntegrationRuntimeUpdateResult, JsonFormatFilePattern, JsonWriteFilePattern, ManagedIntegrationRuntimeNodeStatus, MongoDbAuthenticationType, NetezzaPartitionOption, ODataAadServicePrincipalCredentialType, ODataAuthenticationType, OraclePartitionOption, OrcCompressionCodec, ParameterType, PhoenixAuthenticationType, PolybaseSettingsRejectType, PrestoAuthenticationType, PublicNetworkAccess, RecurrenceFrequency, RestServiceAuthenticationType, RunQueryFilterOperand, RunQueryFilterOperator, RunQueryOrder, RunQueryOrderByField, SalesforceSinkWriteBehavior, SalesforceSourceReadBehavior, SapCloudForCustomerSinkWriteBehavior, SapHanaAuthenticationType, SapHanaPartitionOption, SapTablePartitionOption, ScriptActivityLogDestination, ScriptActivityParameterDirection, ScriptActivityParameterType, ScriptType, SelfHostedIntegrationRuntimeNodeStatus, ServiceNowAuthenticationType, ServicePrincipalCredentialType, SftpAuthenticationType, SparkAuthenticationType, SparkServerType, SparkThriftTransportProtocol, SqlAlwaysEncryptedAkvAuthType, SqlDWWriteBehaviorEnum, SqlPartitionOption, SqlWriteBehaviorEnum, SsisLogLocationType, SsisObjectMetadataType, SsisPackageLocationType, StoredProcedureParameterType, SybaseAuthenticationType, TeamDeskAuthenticationType, TeradataAuthenticationType, TeradataPartitionOption, TriggerRunStatus, TriggerRuntimeState, TumblingWindowFrequency, VariableType, WebActivityMethod, WebAuthenticationType, WebHookActivityMethod, ZendeskAuthenticationType, ) __all__ = [ 'AccessPolicyResponse', 'Activity', 'ActivityDependency', 'ActivityPolicy', 'ActivityRun', 'ActivityRunsQueryResponse', 'AddDataFlowToDebugSessionResponse', 'AdditionalColumns', 'AmazonMWSLinkedService', 'AmazonMWSObjectDataset', 'AmazonMWSSource', 'AmazonRdsForOracleLinkedService', 'AmazonRdsForOraclePartitionSettings', 'AmazonRdsForOracleSource', 'AmazonRdsForOracleTableDataset', 'AmazonRdsForSqlServerLinkedService', 'AmazonRdsForSqlServerSource', 'AmazonRdsForSqlServerTableDataset', 'AmazonRedshiftLinkedService', 'AmazonRedshiftSource', 'AmazonRedshiftTableDataset', 'AmazonS3CompatibleLinkedService', 'AmazonS3CompatibleLocation', 'AmazonS3CompatibleReadSettings', 'AmazonS3Dataset', 'AmazonS3LinkedService', 'AmazonS3Location', 'AmazonS3ReadSettings', 'AppendVariableActivity', 'ArmIdWrapper', 'AvroDataset', 'AvroFormat', 'AvroSink', 'AvroSource', 'AvroWriteSettings', 'AzPowerShellSetup', 'AzureBatchLinkedService', 'AzureBlobDataset', 'AzureBlobFSDataset', 'AzureBlobFSLinkedService', 'AzureBlobFSLocation', 'AzureBlobFSReadSettings', 'AzureBlobFSSink', 'AzureBlobFSSource', 'AzureBlobFSWriteSettings', 'AzureBlobStorageLinkedService', 'AzureBlobStorageLocation', 'AzureBlobStorageReadSettings', 'AzureBlobStorageWriteSettings', 'AzureDataExplorerCommandActivity', 'AzureDataExplorerLinkedService', 'AzureDataExplorerSink', 'AzureDataExplorerSource', 'AzureDataExplorerTableDataset', 'AzureDataLakeAnalyticsLinkedService', 'AzureDataLakeStoreDataset', 'AzureDataLakeStoreLinkedService', 'AzureDataLakeStoreLocation', 'AzureDataLakeStoreReadSettings', 'AzureDataLakeStoreSink', 'AzureDataLakeStoreSource', 'AzureDataLakeStoreWriteSettings', 'AzureDatabricksDeltaLakeDataset', 'AzureDatabricksDeltaLakeExportCommand', 'AzureDatabricksDeltaLakeImportCommand', 'AzureDatabricksDeltaLakeLinkedService', 'AzureDatabricksDeltaLakeSink', 'AzureDatabricksDeltaLakeSource', 'AzureDatabricksLinkedService', 'AzureFileStorageLinkedService', 'AzureFileStorageLocation', 'AzureFileStorageReadSettings', 'AzureFileStorageWriteSettings', 'AzureFunctionActivity', 'AzureFunctionLinkedService', 'AzureKeyVaultLinkedService', 'AzureKeyVaultSecretReference', 'AzureMLBatchExecutionActivity', 'AzureMLExecutePipelineActivity', 'AzureMLLinkedService', 'AzureMLServiceLinkedService', 'AzureMLUpdateResourceActivity', 'AzureMLWebServiceFile', 'AzureMariaDBLinkedService', 'AzureMariaDBSource', 'AzureMariaDBTableDataset', 'AzureMySqlLinkedService', 'AzureMySqlSink', 'AzureMySqlSource', 'AzureMySqlTableDataset', 'AzurePostgreSqlLinkedService', 'AzurePostgreSqlSink', 'AzurePostgreSqlSource', 'AzurePostgreSqlTableDataset', 'AzureQueueSink', 'AzureSearchIndexDataset', 'AzureSearchIndexSink', 'AzureSearchLinkedService', 'AzureSqlDWLinkedService', 'AzureSqlDWTableDataset', 'AzureSqlDatabaseLinkedService', 'AzureSqlMILinkedService', 'AzureSqlMITableDataset', 'AzureSqlSink', 'AzureSqlSource', 'AzureSqlTableDataset', 'AzureStorageLinkedService', 'AzureTableDataset', 'AzureTableSink', 'AzureTableSource', 'AzureTableStorageLinkedService', 'BinaryDataset', 'BinaryReadSettings', 'BinarySink', 'BinarySource', 'BlobEventsTrigger', 'BlobSink', 'BlobSource', 'BlobTrigger', 'CMKIdentityDefinition', 'CassandraLinkedService', 'CassandraSource', 'CassandraTableDataset', 'ChainingTrigger', 'CloudError', 'CmdkeySetup', 'CommonDataServiceForAppsEntityDataset', 'CommonDataServiceForAppsLinkedService', 'CommonDataServiceForAppsSink', 'CommonDataServiceForAppsSource', 'ComponentSetup', 'CompressionReadSettings', 'ConcurLinkedService', 'ConcurObjectDataset', 'ConcurSource', 'ConnectionStateProperties', 'ControlActivity', 'CopyActivity', 'CopyActivityLogSettings', 'CopySink', 'CopySource', 'CopyTranslator', 'CosmosDbLinkedService', 'CosmosDbMongoDbApiCollectionDataset', 'CosmosDbMongoDbApiLinkedService', 'CosmosDbMongoDbApiSink', 'CosmosDbMongoDbApiSource', 'CosmosDbSqlApiCollectionDataset', 'CosmosDbSqlApiSink', 'CosmosDbSqlApiSource', 'CouchbaseLinkedService', 'CouchbaseSource', 'CouchbaseTableDataset', 'CreateDataFlowDebugSessionRequest', 'CreateDataFlowDebugSessionResponse', 'CreateLinkedIntegrationRuntimeRequest', 'CreateRunResponse', 'Credential', 'CredentialReference', 'CredentialResource', 'CustomActivity', 'CustomActivityReferenceObject', 'CustomDataSourceLinkedService', 'CustomDataset', 'CustomEventsTrigger', 'CustomSetupBase', 'DWCopyCommandDefaultValue', 'DWCopyCommandSettings', 'DataFlow', 'DataFlowDebugCommandPayload', 'DataFlowDebugCommandRequest', 'DataFlowDebugCommandResponse', 'DataFlowDebugPackage', 'DataFlowDebugPackageDebugSettings', 'DataFlowDebugResource', 'DataFlowDebugSessionInfo', 'DataFlowFolder', 'DataFlowListResponse', 'DataFlowReference', 'DataFlowResource', 'DataFlowSink', 'DataFlowSource', 'DataFlowSourceSetting', 'DataFlowStagingInfo', 'DataLakeAnalyticsUSQLActivity', 'DatabricksNotebookActivity', 'DatabricksSparkJarActivity', 'DatabricksSparkPythonActivity', 'Dataset', 'DatasetCompression', 'DatasetDataElement', 'DatasetDebugResource', 'DatasetFolder', 'DatasetListResponse', 'DatasetLocation', 'DatasetReference', 'DatasetResource', 'DatasetSchemaDataElement', 'DatasetStorageFormat', 'Db2LinkedService', 'Db2Source', 'Db2TableDataset', 'DeleteActivity', 'DeleteDataFlowDebugSessionRequest', 'DelimitedTextDataset', 'DelimitedTextReadSettings', 'DelimitedTextSink', 'DelimitedTextSource', 'DelimitedTextWriteSettings', 'DependencyReference', 'DistcpSettings', 'DocumentDbCollectionDataset', 'DocumentDbCollectionSink', 'DocumentDbCollectionSource', 'DrillLinkedService', 'DrillSource', 'DrillTableDataset', 'DynamicsAXLinkedService', 'DynamicsAXResourceDataset', 'DynamicsAXSource', 'DynamicsCrmEntityDataset', 'DynamicsCrmLinkedService', 'DynamicsCrmSink', 'DynamicsCrmSource', 'DynamicsEntityDataset', 'DynamicsLinkedService', 'DynamicsSink', 'DynamicsSource', 'EloquaLinkedService', 'EloquaObjectDataset', 'EloquaSource', 'EncryptionConfiguration', 'EntityReference', 'EnvironmentVariableSetup', 'ExcelDataset', 'ExcelSource', 'ExecuteDataFlowActivity', 'ExecuteDataFlowActivityTypeProperties', 'ExecuteDataFlowActivityTypePropertiesCompute', 'ExecutePipelineActivity', 'ExecutePowerQueryActivityTypeProperties', 'ExecuteSSISPackageActivity', 'ExecuteWranglingDataflowActivity', 'ExecutionActivity', 'ExportSettings', 'ExposureControlBatchRequest', 'ExposureControlBatchResponse', 'ExposureControlRequest', 'ExposureControlResponse', 'Expression', 'Factory', 'FactoryGitHubConfiguration', 'FactoryIdentity', 'FactoryListResponse', 'FactoryRepoConfiguration', 'FactoryRepoUpdate', 'FactoryUpdateParameters', 'FactoryVSTSConfiguration', 'FailActivity', 'FileServerLinkedService', 'FileServerLocation', 'FileServerReadSettings', 'FileServerWriteSettings', 'FileShareDataset', 'FileSystemSink', 'FileSystemSource', 'FilterActivity', 'Flowlet', 'ForEachActivity', 'FormatReadSettings', 'FormatWriteSettings', 'FtpReadSettings', 'FtpServerLinkedService', 'FtpServerLocation', 'GetDataFactoryOperationStatusResponse', 'GetMetadataActivity', 'GetSsisObjectMetadataRequest', 'GitHubAccessTokenRequest', 'GitHubAccessTokenResponse', 'GitHubClientSecret', 'GlobalParameterSpecification', 'GoogleAdWordsLinkedService', 'GoogleAdWordsObjectDataset', 'GoogleAdWordsSource', 'GoogleBigQueryLinkedService', 'GoogleBigQueryObjectDataset', 'GoogleBigQuerySource', 'GoogleCloudStorageLinkedService', 'GoogleCloudStorageLocation', 'GoogleCloudStorageReadSettings', 'GreenplumLinkedService', 'GreenplumSource', 'GreenplumTableDataset', 'HBaseLinkedService', 'HBaseObjectDataset', 'HBaseSource', 'HDInsightHiveActivity', 'HDInsightLinkedService', 'HDInsightMapReduceActivity', 'HDInsightOnDemandLinkedService', 'HDInsightPigActivity', 'HDInsightSparkActivity', 'HDInsightStreamingActivity', 'HdfsLinkedService', 'HdfsLocation', 'HdfsReadSettings', 'HdfsSource', 'HiveLinkedService', 'HiveObjectDataset', 'HiveSource', 'HttpDataset', 'HttpLinkedService', 'HttpReadSettings', 'HttpServerLocation', 'HttpSource', 'HubspotLinkedService', 'HubspotObjectDataset', 'HubspotSource', 'IfConditionActivity', 'ImpalaLinkedService', 'ImpalaObjectDataset', 'ImpalaSource', 'ImportSettings', 'InformixLinkedService', 'InformixSink', 'InformixSource', 'InformixTableDataset', 'IntegrationRuntime', 'IntegrationRuntimeAuthKeys', 'IntegrationRuntimeComputeProperties', 'IntegrationRuntimeConnectionInfo', 'IntegrationRuntimeCustomSetupScriptProperties', 'IntegrationRuntimeCustomerVirtualNetwork', 'IntegrationRuntimeDataFlowProperties', 'IntegrationRuntimeDataProxyProperties', 'IntegrationRuntimeDebugResource', 'IntegrationRuntimeListResponse', 'IntegrationRuntimeMonitoringData', 'IntegrationRuntimeNodeIpAddress', 'IntegrationRuntimeNodeMonitoringData', 'IntegrationRuntimeOutboundNetworkDependenciesCategoryEndpoint', 'IntegrationRuntimeOutboundNetworkDependenciesEndpoint', 'IntegrationRuntimeOutboundNetworkDependenciesEndpointDetails', 'IntegrationRuntimeOutboundNetworkDependenciesEndpointsResponse', 'IntegrationRuntimeReference', 'IntegrationRuntimeRegenerateKeyParameters', 'IntegrationRuntimeResource', 'IntegrationRuntimeSsisCatalogInfo', 'IntegrationRuntimeSsisProperties', 'IntegrationRuntimeStatus', 'IntegrationRuntimeStatusListResponse', 'IntegrationRuntimeStatusResponse', 'IntegrationRuntimeVNetProperties', 'JiraLinkedService', 'JiraObjectDataset', 'JiraSource', 'JsonDataset', 'JsonFormat', 'JsonReadSettings', 'JsonSink', 'JsonSource', 'JsonWriteSettings', 'LinkedIntegrationRuntime', 'LinkedIntegrationRuntimeKeyAuthorization', 'LinkedIntegrationRuntimeRbacAuthorization', 'LinkedIntegrationRuntimeRequest', 'LinkedIntegrationRuntimeType', 'LinkedService', 'LinkedServiceDebugResource', 'LinkedServiceListResponse', 'LinkedServiceReference', 'LinkedServiceResource', 'LogLocationSettings', 'LogSettings', 'LogStorageSettings', 'LookupActivity', 'MagentoLinkedService', 'MagentoObjectDataset', 'MagentoSource', 'ManagedIdentityCredential', 'ManagedIntegrationRuntime', 'ManagedIntegrationRuntimeError', 'ManagedIntegrationRuntimeNode', 'ManagedIntegrationRuntimeOperationResult', 'ManagedIntegrationRuntimeStatus', 'ManagedPrivateEndpoint', 'ManagedPrivateEndpointListResponse', 'ManagedPrivateEndpointResource', 'ManagedVirtualNetwork', 'ManagedVirtualNetworkListResponse', 'ManagedVirtualNetworkReference', 'ManagedVirtualNetworkResource', 'MappingDataFlow', 'MariaDBLinkedService', 'MariaDBSource', 'MariaDBTableDataset', 'MarketoLinkedService', 'MarketoObjectDataset', 'MarketoSource', 'MetadataItem', 'MicrosoftAccessLinkedService', 'MicrosoftAccessSink', 'MicrosoftAccessSource', 'MicrosoftAccessTableDataset', 'MongoDbAtlasCollectionDataset', 'MongoDbAtlasLinkedService', 'MongoDbAtlasSink', 'MongoDbAtlasSource', 'MongoDbCollectionDataset', 'MongoDbCursorMethodsProperties', 'MongoDbLinkedService', 'MongoDbSource', 'MongoDbV2CollectionDataset', 'MongoDbV2LinkedService', 'MongoDbV2Sink', 'MongoDbV2Source', 'MultiplePipelineTrigger', 'MySqlLinkedService', 'MySqlSource', 'MySqlTableDataset', 'NetezzaLinkedService', 'NetezzaPartitionSettings', 'NetezzaSource', 'NetezzaTableDataset', 'ODataLinkedService', 'ODataResourceDataset', 'ODataSource', 'OdbcLinkedService', 'OdbcSink', 'OdbcSource', 'OdbcTableDataset', 'Office365Dataset', 'Office365LinkedService', 'Office365Source', 'Operation', 'OperationDisplay', 'OperationListResponse', 'OperationLogSpecification', 'OperationMetricAvailability', 'OperationMetricDimension', 'OperationMetricSpecification', 'OperationServiceSpecification', 'OracleCloudStorageLinkedService', 'OracleCloudStorageLocation', 'OracleCloudStorageReadSettings', 'OracleLinkedService', 'OraclePartitionSettings', 'OracleServiceCloudLinkedService', 'OracleServiceCloudObjectDataset', 'OracleServiceCloudSource', 'OracleSink', 'OracleSource', 'OracleTableDataset', 'OrcDataset', 'OrcFormat', 'OrcSink', 'OrcSource', 'OrcWriteSettings', 'PackageStore', 'ParameterSpecification', 'ParquetDataset', 'ParquetFormat', 'ParquetSink', 'ParquetSource', 'ParquetWriteSettings', 'PaypalLinkedService', 'PaypalObjectDataset', 'PaypalSource', 'PhoenixLinkedService', 'PhoenixObjectDataset', 'PhoenixSource', 'PipelineElapsedTimeMetricPolicy', 'PipelineFolder', 'PipelineListResponse', 'PipelinePolicy', 'PipelineReference', 'PipelineResource', 'PipelineRun', 'PipelineRunInvokedBy', 'PipelineRunsQueryResponse', 'PolybaseSettings', 'PostgreSqlLinkedService', 'PostgreSqlSource', 'PostgreSqlTableDataset', 'PowerQuerySink', 'PowerQuerySinkMapping', 'PowerQuerySource', 'PrestoLinkedService', 'PrestoObjectDataset', 'PrestoSource', 'PrivateEndpointConnectionListResponse', 'PrivateEndpointConnectionResource', 'PrivateLinkConnectionApprovalRequest', 'PrivateLinkConnectionApprovalRequestResource', 'PrivateLinkConnectionState', 'PrivateLinkResource', 'PrivateLinkResourceProperties', 'PrivateLinkResourcesWrapper', 'QueryDataFlowDebugSessionsResponse', 'QuickBooksLinkedService', 'QuickBooksObjectDataset', 'QuickBooksSource', 'QuickbaseLinkedService', 'RecurrenceSchedule', 'RecurrenceScheduleOccurrence', 'RedirectIncompatibleRowSettings', 'RedshiftUnloadSettings', 'RelationalSource', 'RelationalTableDataset', 'RemotePrivateEndpointConnection', 'RerunTumblingWindowTrigger', 'Resource', 'ResponsysLinkedService', 'ResponsysObjectDataset', 'ResponsysSource', 'RestResourceDataset', 'RestServiceLinkedService', 'RestSink', 'RestSource', 'RetryPolicy', 'RunFilterParameters', 'RunQueryFilter', 'RunQueryOrderBy', 'SSISAccessCredential', 'SSISChildPackage', 'SSISExecutionCredential', 'SSISExecutionParameter', 'SSISLogLocation', 'SSISPackageLocation', 'SSISPropertyOverride', 'SalesforceLinkedService', 'SalesforceMarketingCloudLinkedService', 'SalesforceMarketingCloudObjectDataset', 'SalesforceMarketingCloudSource', 'SalesforceObjectDataset', 'SalesforceServiceCloudLinkedService', 'SalesforceServiceCloudObjectDataset', 'SalesforceServiceCloudSink', 'SalesforceServiceCloudSource', 'SalesforceSink', 'SalesforceSource', 'SapBWLinkedService', 'SapBwCubeDataset', 'SapBwSource', 'SapCloudForCustomerLinkedService', 'SapCloudForCustomerResourceDataset', 'SapCloudForCustomerSink', 'SapCloudForCustomerSource', 'SapEccLinkedService', 'SapEccResourceDataset', 'SapEccSource', 'SapHanaLinkedService', 'SapHanaPartitionSettings', 'SapHanaSource', 'SapHanaTableDataset', 'SapOpenHubLinkedService', 'SapOpenHubSource', 'SapOpenHubTableDataset', 'SapTableLinkedService', 'SapTablePartitionSettings', 'SapTableResourceDataset', 'SapTableSource', 'ScheduleTrigger', 'ScheduleTriggerRecurrence', 'ScriptAction', 'ScriptActivity', 'ScriptActivityParameter', 'ScriptActivityScriptBlock', 'ScriptActivityTypePropertiesLogSettings', 'SecretBase', 'SecureString', 'SelfDependencyTumblingWindowTriggerReference', 'SelfHostedIntegrationRuntime', 'SelfHostedIntegrationRuntimeNode', 'SelfHostedIntegrationRuntimeStatus', 'ServiceNowLinkedService', 'ServiceNowObjectDataset', 'ServiceNowSource', 'ServicePrincipalCredential', 'SetVariableActivity', 'SftpLocation', 'SftpReadSettings', 'SftpServerLinkedService', 'SftpWriteSettings', 'SharePointOnlineListLinkedService', 'SharePointOnlineListResourceDataset', 'SharePointOnlineListSource', 'ShopifyLinkedService', 'ShopifyObjectDataset', 'ShopifySource', 'SkipErrorFile', 'SmartsheetLinkedService', 'SnowflakeDataset', 'SnowflakeExportCopyCommand', 'SnowflakeImportCopyCommand', 'SnowflakeLinkedService', 'SnowflakeSink', 'SnowflakeSource', 'SparkLinkedService', 'SparkObjectDataset', 'SparkSource', 'SqlAlwaysEncryptedProperties', 'SqlDWSink', 'SqlDWSource', 'SqlDWUpsertSettings', 'SqlMISink', 'SqlMISource', 'SqlPartitionSettings', 'SqlServerLinkedService', 'SqlServerSink', 'SqlServerSource', 'SqlServerStoredProcedureActivity', 'SqlServerTableDataset', 'SqlSink', 'SqlSource', 'SqlUpsertSettings', 'SquareLinkedService', 'SquareObjectDataset', 'SquareSource', 'SsisEnvironment', 'SsisEnvironmentReference', 'SsisFolder', 'SsisObjectMetadata', 'SsisObjectMetadataListResponse', 'SsisObjectMetadataStatusResponse', 'SsisPackage', 'SsisParameter', 'SsisProject', 'SsisVariable', 'StagingSettings', 'StoreReadSettings', 'StoreWriteSettings', 'StoredProcedureParameter', 'SubResource', 'SubResourceDebugResource', 'SwitchActivity', 'SwitchCase', 'SybaseLinkedService', 'SybaseSource', 'SybaseTableDataset', 'TabularSource', 'TabularTranslator', 'TarGZipReadSettings', 'TarReadSettings', 'TeamDeskLinkedService', 'TeradataLinkedService', 'TeradataPartitionSettings', 'TeradataSource', 'TeradataTableDataset', 'TextFormat', 'Transformation', 'Trigger', 'TriggerDependencyReference', 'TriggerFilterParameters', 'TriggerListResponse', 'TriggerPipelineReference', 'TriggerQueryResponse', 'TriggerReference', 'TriggerResource', 'TriggerRun', 'TriggerRunsQueryResponse', 'TriggerSubscriptionOperationStatus', 'TumblingWindowTrigger', 'TumblingWindowTriggerDependencyReference', 'TypeConversionSettings', 'UntilActivity', 'UpdateIntegrationRuntimeNodeRequest', 'UpdateIntegrationRuntimeRequest', 'UserAccessPolicy', 'UserProperty', 'ValidationActivity', 'VariableSpecification', 'VerticaLinkedService', 'VerticaSource', 'VerticaTableDataset', 'WaitActivity', 'WebActivity', 'WebActivityAuthentication', 'WebAnonymousAuthentication', 'WebBasicAuthentication', 'WebClientCertificateAuthentication', 'WebHookActivity', 'WebLinkedService', 'WebLinkedServiceTypeProperties', 'WebSource', 'WebTableDataset', 'WranglingDataFlow', 'XeroLinkedService', 'XeroObjectDataset', 'XeroSource', 'XmlDataset', 'XmlReadSettings', 'XmlSource', 'ZendeskLinkedService', 'ZipDeflateReadSettings', 'ZohoLinkedService', 'ZohoObjectDataset', 'ZohoSource', 'AmazonRdsForOraclePartitionOption', 'AvroCompressionCodec', 'AzureFunctionActivityMethod', 'AzureSearchIndexWriteBehaviorType', 'BlobEventTypes', 'CassandraSourceReadConsistencyLevels', 'CompressionCodec', 'CopyBehaviorType', 'CosmosDbConnectionMode', 'CosmosDbServicePrincipalCredentialType', 'DataFlowComputeType', 'DataFlowDebugCommandType', 'DatasetCompressionLevel', 'DayOfWeek', 'DaysOfWeek', 'Db2AuthenticationType', 'DependencyCondition', 'DynamicsAuthenticationType', 'DynamicsDeploymentType', 'DynamicsSinkWriteBehavior', 'EventSubscriptionStatus', 'FactoryIdentityType', 'FtpAuthenticationType', 'GlobalParameterType', 'GoogleAdWordsAuthenticationType', 'GoogleBigQueryAuthenticationType', 'HBaseAuthenticationType', 'HDInsightActivityDebugInfoOption', 'HdiNodeTypes', 'HiveAuthenticationType', 'HiveServerType', 'HiveThriftTransportProtocol', 'HttpAuthenticationType', 'ImpalaAuthenticationType', 'IntegrationRuntimeAuthKeyName', 'IntegrationRuntimeAutoUpdate', 'IntegrationRuntimeEdition', 'IntegrationRuntimeEntityReferenceType', 'IntegrationRuntimeInternalChannelEncryptionMode', 'IntegrationRuntimeLicenseType', 'IntegrationRuntimeSsisCatalogPricingTier', 'IntegrationRuntimeState', 'IntegrationRuntimeType', 'IntegrationRuntimeUpdateResult', 'JsonFormatFilePattern', 'JsonWriteFilePattern', 'ManagedIntegrationRuntimeNodeStatus', 'MongoDbAuthenticationType', 'NetezzaPartitionOption', 'ODataAadServicePrincipalCredentialType', 'ODataAuthenticationType', 'OraclePartitionOption', 'OrcCompressionCodec', 'ParameterType', 'PhoenixAuthenticationType', 'PolybaseSettingsRejectType', 'PrestoAuthenticationType', 'PublicNetworkAccess', 'RecurrenceFrequency', 'RestServiceAuthenticationType', 'RunQueryFilterOperand', 'RunQueryFilterOperator', 'RunQueryOrder', 'RunQueryOrderByField', 'SalesforceSinkWriteBehavior', 'SalesforceSourceReadBehavior', 'SapCloudForCustomerSinkWriteBehavior', 'SapHanaAuthenticationType', 'SapHanaPartitionOption', 'SapTablePartitionOption', 'ScriptActivityLogDestination', 'ScriptActivityParameterDirection', 'ScriptActivityParameterType', 'ScriptType', 'SelfHostedIntegrationRuntimeNodeStatus', 'ServiceNowAuthenticationType', 'ServicePrincipalCredentialType', 'SftpAuthenticationType', 'SparkAuthenticationType', 'SparkServerType', 'SparkThriftTransportProtocol', 'SqlAlwaysEncryptedAkvAuthType', 'SqlDWWriteBehaviorEnum', 'SqlPartitionOption', 'SqlWriteBehaviorEnum', 'SsisLogLocationType', 'SsisObjectMetadataType', 'SsisPackageLocationType', 'StoredProcedureParameterType', 'SybaseAuthenticationType', 'TeamDeskAuthenticationType', 'TeradataAuthenticationType', 'TeradataPartitionOption', 'TriggerRunStatus', 'TriggerRuntimeState', 'TumblingWindowFrequency', 'VariableType', 'WebActivityMethod', 'WebAuthenticationType', 'WebHookActivityMethod', 'ZendeskAuthenticationType', ]
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075af4946cc5d91cfc403188506045ecbdebe51b
60,590
py
Python
benchmark/generate_graphs.py
zanderhavgaard/thesis-code
d9f193e622b8b98ec88c33006f8e0e1dbb3d17fc
[ "MIT" ]
null
null
null
benchmark/generate_graphs.py
zanderhavgaard/thesis-code
d9f193e622b8b98ec88c33006f8e0e1dbb3d17fc
[ "MIT" ]
2
2020-04-28T07:59:30.000Z
2020-05-17T15:36:04.000Z
benchmark/generate_graphs.py
zanderhavgaard/thesis-code
d9f193e622b8b98ec88c33006f8e0e1dbb3d17fc
[ "MIT" ]
null
null
null
import sys import json import time from pprint import pprint from mysql_interface import SQL_Interface as database from graph_generater import GraphGenerater import function_lib as lib from datetime import datetime from os.path import expanduser from functools import reduce import pandas as pd import numpy as np import seaborn as sns import warnings warnings.filterwarnings("ignore") # change 'report' to your default value name_of_report = sys.argv[1] if len(sys.argv) > 1 else 'report' dev_mode = eval(sys.argv[2]) if len(sys.argv) > 2 else False # TODO change dev_mode db = database(True) gg = GraphGenerater(name_of_report, dev_mode) # meta coloring and order for produced graphs hue_order = ['openfaas','aws_lambda','azure_functions'] provider_color_dict = {'openfaas': '#2316deff', 'aws_lambda':'#ff8c00ff', 'azure_functions': '#ffd700ff', } colors = { 'light_gray': '#708090ff', 'blue': '#191970ff' } # name sub-directories for the different categories by changing stringvalues in below list # comment line out of graphs for that category is not wanted category_of_graphs = [ lambda : cold_start('cold_starts',dev_mode), lambda : function_lifetime('Function_lifetime', dev_mode), lambda : large_function('Large_function',dev_mode), lambda : throughput_graphs( 'Throughput', dev_mode), lambda : coldtimes_graphs('Coldtimes', dev_mode), # lambda : test( 'test', dev_mode), ] # aux function for getting latest uuids from a experiment name def get_uuids(experiment_name:str): return { x[0]: x[1] for x in db.get_latest_metadata_by_experiment(experiment_name) } def cold_start(ldir:str, devmode): print('cold_start') # metadata directory = ldir experiment_uuids = get_uuids('simple-cold-function') def get_table_all(uuid): return f"""select cl_provider as provider, name, minutes, seconds, granularity, threads as requests, benchmark, cold, final from Coldstart c left join Experiment e on e.uuid=c.exp_id where e.uuid = '{uuid}';""" def get_table_final(uuid): return f"""select cl_provider as provider, name, minutes, seconds, granularity, threads as requests, benchmark, cold from Coldstart c left join Experiment e on e.uuid=c.exp_id where final = True and e.uuid = '{uuid}';""" # coldstart-identifier # coldstart-identifier-nested # simple-cold-function # simple-cold-function-nested # simple-cold-function-threaded-twelve aws_final_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda'])) aws_all_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda'])) open_final_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas'])) open_all_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas'])) azure_final_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions'])) azure_all_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions'])) experiment_uuids = get_uuids('simple-cold-function-nested') print('NESTED', experiment_uuids) aws_final_nested_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda'])) aws_all_nested_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda'])) open_final_nested_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas'])) open_all_nested_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas'])) azure_final_nested_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions'])) azure_all_nested_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions'])) experiment_uuids = get_uuids('simple-cold-function-threaded-twelve') print('CONCURRENT', experiment_uuids) aws_final_con_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda'])) aws_all_con_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda'])) open_final_con_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas'])) open_all_con_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas'])) azure_final_con_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions'])) azure_all_con_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions'])) experiment_uuids = get_uuids('coldstart-identifier') print('identifier', experiment_uuids) aws_final_iden_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda'])) aws_all_iden_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda'])) open_final_iden_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas'])) open_all_iden_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas'])) azure_final_iden_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions'])) azure_all_iden_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions'])) experiment_uuids = get_uuids('coldstart-identifier-nested') print('identifier', experiment_uuids) aws_final_iden_nest_df = db.get_raw_query(get_table_final(experiment_uuids['aws_lambda'])) aws_all_iden_nest_df = db.get_raw_query(get_table_all(experiment_uuids['aws_lambda'])) open_final_iden_nest_df = db.get_raw_query(get_table_final(experiment_uuids['openfaas'])) open_all_iden_nest_df = db.get_raw_query(get_table_all(experiment_uuids['openfaas'])) azure_final_iden_nest_df = db.get_raw_query(get_table_final(experiment_uuids['azure_functions'])) azure_all_iden_nest_df = db.get_raw_query(get_table_all(experiment_uuids['azure_functions'])) all_finals = [aws_final_df, open_final_df, azure_final_df, aws_final_nested_df, open_final_nested_df, azure_final_nested_df, aws_final_con_df, open_final_con_df, azure_final_con_df, aws_final_iden_df, open_final_iden_df, azure_final_iden_df, aws_final_iden_nest_df, open_final_iden_nest_df, azure_final_iden_nest_df] table_df = pd.concat(all_finals) gg.save_table(table_df,'All final results',directory) gg.save_table(aws_all_df,'AWS all simple-cold-function',directory) gg.save_table(open_all_df,'OpenFaaS all simple-cold-function',directory) gg.save_table(azure_all_df,'Azure all simple-cold-function',directory) gg.save_table(aws_all_nested_df,'AWS all simple-cold-function-nested',directory) gg.save_table(open_all_nested_df,'OpenFaaS all simple-cold-function-nested',directory) gg.save_table(azure_all_nested_df,'Azure all simple-cold-function-nested',directory) gg.save_table(aws_all_con_df,'AWS all simple-cold-function-concurrent',directory) gg.save_table(open_all_con_df,'OpenFaaS all simple-cold-function-concurrent',directory) gg.save_table(azure_all_con_df,'Azure all simple-cold-function-concurrent',directory) gg.save_table(aws_all_iden_df,'AWS all coldstart-identifier',directory) gg.save_table(open_all_iden_df,'OpenFaaS all coldstart-identifier',directory) gg.save_table(azure_all_iden_df,'Azure all coldstart-identifier',directory) gg.save_table(aws_all_iden_nest_df,'AWS all coldstart-identifier-nested',directory) gg.save_table(open_all_iden_nest_df,'OpenFaaS all coldstart-identifier-nested',directory) gg.save_table(azure_all_iden_nest_df,'Azure all coldstart-identifier-nested',directory) def function_lifetime(ldir:str, devmode:bool): print('function_lifetime') # metadata directory = ldir experiment_uuids = get_uuids('function-lifetime') def get_table(uuid): return f"""select cl_provider as provider,instance_identifier as first_invoked, orig_identifier as last_invoked, hours,minutes,seconds,sleep_time,reclaimed from Function_lifetime f left join Experiment e on e.uuid=f.exp_id where e.uuid = '{uuid}';""" def get_invocations(uuid): return f"""select execution_start-invocation_start as latency, instance_identifier, cl_provider as provider from Invocation i left join Experiment e on e.uuid=i.exp_id where e.uuid = '{uuid}';""" aws_table_df = db.get_raw_query(get_table(experiment_uuids['aws_lambda'])) open_table_df = db.get_raw_query(get_table(experiment_uuids['openfaas'])) azure_table_df = db.get_raw_query(get_table(experiment_uuids['azure_functions'])) table_df = pd.concat([aws_table_df,open_table_df,azure_table_df]) aws_df = db.get_raw_query(get_invocations(experiment_uuids['aws_lambda'])) open_df = db.get_raw_query(get_invocations(experiment_uuids['openfaas'])) open_df.loc[(open_df.latency > 5.0),'latency']= 5.0 azure_df = db.get_raw_query(get_invocations(experiment_uuids['azure_functions'])) joint_df = pd.concat([aws_df,open_df,azure_df]) config = { 'x': 'provider', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'markers': ['o','s','v'], 'ylabel': ('Latency in seconds',12), 'xlabel': ('Cloud provider',12), 'markers': ['o','s','v'], 'jitter': 0.25, 'alpha': 0.5, # 'height': 4, # 'aspect': 0.8, } gg.strip_plot(joint_df, config, 'Latency by provider', directory) gg.save_table(table_df, 'Function lifetime values',directory) def large_function(ldir:str, devmode:bool): # metadata directory = ldir experiment_uuids = get_uuids('coldtime-large-functions ') # queries def query_by_provider(uuid): return f"""select execution_start-invocation_start as latency, execution_total, function_name, instance_identifier as instance_id, throughput,cl_provider as provider from Invocation i left join Experiment e on i.exp_id=e.uuid where e.uuid ='{uuid}';""" # dataframes aws_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'])) open_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'])) azure_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'])) joint_df = pd.concat([aws_df,open_df,azure_df]) config = { 'x': 'function_name', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Latency in seconds',12), 'xlabel': ('Function name',12), 'markers': ['o','s','v'], 'jitter': 0.1, 'x_strip': 'instance_id', 'y_strip': 'latency', 'strip': True, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } # NOT INT USE ---------------------------------------------------------- # aws_avg = aws_df.groupby('function_name')['latency'].sum() # avg_reg = aws_avg[0]/len(aws_df) # avg_mono = aws_avg[1]/len(aws_df) # warm_times = aws_df.map(lambda x: x.latency if x.latency < ) # aws_mono = aws_df[aws_df['function_name'== 'monolith'] ] # aws_mono = aws_df.loc[aws_df['function_name'] == 'monolith'] # aws_reg = aws_df.loc[aws_df['function_name'] != 'monolith'] # aws_mono_cutoff = aws_mono *2 # aws_avg_mono = aws_mono.sum().latency / len(aws_mono) # print(aws_avg_mono) # aws_avg_reg = aws_reg.sum().latency / len(aws_reg) # aws_mono_warm = aws_mono.loc[aws_mono['latency'] < aws_mono_cutoff] # pprint(aws_mono) # aws_reg = aws_df.query("function_name == monolith") # pprint(aws_reg) # aws_reg = aws_df.query(f"function_name == monolith")['*'] # open_avg = open_df.groupby('function_name')['latency'].sum() # azure_avg = azure_df.groupby('function_name')['latency'].sum() # data = {'provider': ['aws_lambda','openfaas','azure_functions'], # 'reg_func': [aws_avg[0]/len(aws_df),open_avg[0]/len(open_df),azure_avg[0]/len(azure_df)], # 'monolith': [aws_avg[1]/len(aws_df),open_avg[1]/len(open_df),azure_avg[1]/len(azure_df)]} # df = pd.DataFrame(data) # pprint(df) # aws_sum = aws_df.sum() # avg_latency = aws_df.sum().latency / len(aws_df) # print(avg_latency) # pprint(aws_sum) # ------------------------------------------------------------------------------------------ config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['hue_order'] = ['aws_lambda'] config['markers'] = ['s'] gg.swarm_plot(aws_df, config, 'AWS latency small vs large function',directory) config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['hue_order'] = ['openfaas'] config['markers'] = ['o'] gg.swarm_plot(open_df, config, 'OpenFaaS latency small vs large function',directory) config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['hue_order'] = ['azure_functions'] config['markers'] = ['v'] gg.swarm_plot(azure_df, config, 'Azure latency small vs large function',directory) config = { 'x': 'throughput', 'y': 'latency', 'hue': 'function_name', 'palette': {'function1': 'red', 'monolith': 'black'}, 'ylabel': ('Latency in seconds',12), 'xlabel': ('Number of operations',12), 'markers': ['s'], 'jitter': 0.1, 'x_strip': 'instance_id', 'y_strip': 'latency', 'strip': True, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } aws_throughput = aws_df.loc[aws_df['throughput'] != 0.0] gg.line_plot(aws_throughput,config,'AWS throughput by function type',directory) open_throughput = open_df.loc[open_df['throughput'] != 0.0] gg.line_plot(open_throughput,config,'OpenFaaS throughput by function type',directory) azure_throughput = azure_df.loc[azure_df['throughput'] != 0.0] gg.line_plot(azure_throughput,config,'Azure throughput by function type',directory) def coldtimes_graphs(ldir:str, devmode:bool): print('coldtimes_graphs') # metadata directory = ldir experiment_uuids = get_uuids('linear-invocation') # queries def query_by_provider(uuid, level:int,pyramid:bool=False): return f"""select latency,instance_id, total, thread_id, multi, provider, if(latency > if(coldtime > 1,{2.0 if pyramid else 1.0},coldtime), 'cold','warm') as cold, invocation_start from (SELECT instance_identifier as instance_id, execution_total as total, thread_id, if(numb_threads > 1,0,1) as multi, cl_provider as provider, coldtime, execution_start-invocation_start as latency, level, invocation_start from Experiment e left join Invocation i on i.exp_id=e.uuid left join (select avg(execution_start-invocation_start)*3 as coldtime,exp_id as xexp_id from Invocation where exp_id ='{uuid}') x on e.uuid=x.xexp_id where exp_id ='{uuid}') y where level = {level};""" def error_by_provider(uuid): return f"""select count(*) as number, cl_provider as provider from Error r left join Experiment e on e.uuid=r.exp_id where e.uuid = '{uuid}';""" # dataframes aws_linear_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 0)) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_linear_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 0)) if 'openfaas' in experiment_uuids else np.DataFrame() azure_linear_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 0)) if 'azure_functions' in experiment_uuids else np.DataFrame() joint_linear_df = pd.concat([aws_linear_df,open_linear_df,azure_linear_df],ignore_index=True) experiment_uuids = get_uuids('linear-invocation-nested') aws_linear_nested_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 1)) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_linear_nested_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 1)) if 'openfaas' in experiment_uuids else np.DataFrame() azure_linear_nested_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 1)) if 'azure_functions' in experiment_uuids else np.DataFrame() joint_linear_nested_df = pd.concat([aws_linear_nested_df,open_linear_nested_df,azure_linear_nested_df],ignore_index=True) experiment_uuids = get_uuids('scenario-pyramid') print('pyramid',experiment_uuids) aws_pyramid_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 0, True)) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_pyramid_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 0, True)) if 'openfaas' in experiment_uuids else np.DataFrame() azure_pyramid_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 0, True)) if 'azure_functions' in experiment_uuids else np.DataFrame() joint_pyramid_df = pd.concat([aws_pyramid_df,open_pyramid_df,azure_pyramid_df],ignore_index=True) aws_error_df = db.get_raw_query(error_by_provider(experiment_uuids['aws_lambda'])) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_error_df = db.get_raw_query(error_by_provider(experiment_uuids['openfaas'])) if 'openfaas' in experiment_uuids else np.DataFrame() azure_error_df = db.get_raw_query(error_by_provider(experiment_uuids['azure_functions'])) if 'azure_functions' in experiment_uuids else np.DataFrame() joint_error_df = pd.concat([aws_error_df,open_error_df,azure_error_df],ignore_index=True) experiment_uuids = get_uuids('growing-load-spikes') aws_spike_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], 0)) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_spike_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], 0)) if 'openfaas' in experiment_uuids else np.DataFrame() azure_spike_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], 0)) if 'azure_functions' in experiment_uuids else np.DataFrame() joint_spike_df = pd.concat([aws_spike_df,open_spike_df,azure_spike_df],ignore_index=True) aws_error_spike_df = db.get_raw_query(error_by_provider(experiment_uuids['aws_lambda'])) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_error_spike_df = db.get_raw_query(error_by_provider(experiment_uuids['openfaas'])) if 'openfaas' in experiment_uuids else np.DataFrame() azure_error_spike_df = db.get_raw_query(error_by_provider(experiment_uuids['azure_functions'])) if 'azure_functions' in experiment_uuids else np.DataFrame() joint_error_spike_df = pd.concat([aws_error_spike_df,open_error_spike_df,azure_error_spike_df],ignore_index=True) ######### # PLOTS # ######### # appendix stuff for showing graph of pyramid - get back to it # config = { # 'x': 'invocations_start', # 'y': 'latency', # 'hue': 'provider', # 'palette': provider_color_dict, # 'hue_order': hue_order, # 'ylabel': ('operations (1000)',14), # 'xlabel': ('time in seconds',14), # 'markers': ['o','s','v'], # 'hist':True, # 'kde': False, # # 'height': 4, # # 'aspect': 0.8, # 'line_kws':{'color':colors['light_gray']}, # } # plist = np.array(aws_pyramid_df.loc[ : , 'invocation_start' ]).tolist() # gg.dist_plot(plist,config,'pyramid invocation starts',directory) config = { 'x': 'cold', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': ['aws_lambda'], 'ylabel': ('latency in seconds',12), 'xlabel': ('Cold time vs warm time',12), 'markers': ['s'], 'jitter': 0.1, 'x_strip': 'cold', 'y_strip': 'latency', 'strip': True, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.box_plot(aws_linear_df, config, 'AWS cold times distribution',directory) config['hue_order'] = ['openfaas'] config['markers'] = ['o'] gg.box_plot(open_linear_df, config, 'OpenFaaS cold times distribution',directory) config['hue_order'] = ['azure_functions'] config['markers'] = ['v'] gg.box_plot(azure_linear_df, config, 'Azure cold times distribution',directory) config = { 'x': 'invocation_start', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Latency in seconds',12), 'xlabel': ('Invocation start (unix time)',12), 'markers': ['o','s','v'], 'alpha': 0.5, # 'jitter': 0.25, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.scatter_plot(joint_linear_df,config,'Latency relative to invocation start:appendix',directory,18) joint_linear_df.loc[(joint_linear_df.latency > 10.0 ),'latency']=8.00 gg.scatter_plot(joint_linear_df,config,'Latency relative to invocation start',directory,18) open_linear_df.loc[(open_linear_df.latency > 10.0 ),'latency']=3.00 config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.scatter_plot(aws_linear_df,config,' AWS latency relative to invocation start',directory,18) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.scatter_plot(open_linear_df,config,' OpenFaaS latency relative to invocation start',directory,18) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.scatter_plot(azure_linear_df,config,'Azure latency relative to invocation start',directory,18) config = { 'x': 'provider', 'y': 'cold', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Number of cold times',12), 'xlabel': ('Cloud provider',12), 'markers': ['o','s','v'], 'jitter': 0.1, 'alpha': 0.5, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } aws = np.array(aws_linear_df['cold'].value_counts()).tolist()+['aws_lambda'] openf = np.array(open_linear_df['cold'].value_counts()).tolist()+['openfaas'] azure = np.array(azure_linear_df['cold'].value_counts()).tolist()+['azure_functions'] zipped = list(zip(aws,openf,azure)) data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]} df = pd.DataFrame(data) gg.bar_plot(df, config,'Cold times by provider: linear-invocation',directory) config['y'] = 'warm' config['ylabel'] = ('Number of warm times',12) gg.bar_plot(df, config,'Warm times by provider: linear-invocation',directory) config['x'] = 'instance_id' config['y'] = 'latency' config['xlabel'] = ('Function instance',12) config['ylabel'] = ('Latency in seconds',12) config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] copy_aws_linear_df = aws_linear_df.copy(deep=True) copy_aws_linear_df['instance_id'] = copy_aws_linear_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000)) gg.strip_plot(copy_aws_linear_df,config,' AWS latency per function instance',directory) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] copy_open_linear_df = open_linear_df.copy(deep=True) copy_open_linear_df['instance_id'] = copy_open_linear_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000)) gg.strip_plot(copy_open_linear_df,config,'OpenFaaS latency per function instance',directory) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] copy_azure_linear_df = azure_linear_df.copy(deep=True) copy_azure_linear_df['instance_id'] = copy_azure_linear_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000)) gg.strip_plot(copy_azure_linear_df,config,'Azure latency per function instance',directory) ################################### # --> linear-invocation-nested <--# ################################### directory = directory.split('/')[0] directory += '/nested' config = { 'x': 'cold', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'ylabel': ('cold times',12), 'markers': ['s'], 'jitter': 0.1, 'x_strip': 'cold', 'y_strip': 'latency', 'strip': True, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.box_plot(aws_linear_nested_df, config, 'AWS cold times distribution: nested',directory) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.box_plot(open_linear_nested_df, config, 'OpenFaaS cold times distribution: nested',directory) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.box_plot(azure_linear_nested_df, config, 'Azure cold times distribution: nested',directory) config = { 'x': 'invocation_start', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('latency in seconds',12), 'xlabel': ('invocation start (unix time)',12), 'markers': ['o','s','v'], 'alpha': 0.9, # 'jitter': 0.25, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.scatter_plot(joint_linear_nested_df,config,'appendix:latency relative to invocation start: nested',directory,18) joint_linear_nested_df.loc[(joint_linear_nested_df.latency > 8.0 ),'latency']=8.00 gg.scatter_plot(joint_linear_nested_df,config,'latency relative to invocation start: nested',directory,18) open_linear_nested_df.loc[(open_linear_nested_df.latency > 3.0 ),'latency']=3.00 config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.scatter_plot(aws_linear_nested_df,config,' AWS latency relative to invocation start: nested',directory,18) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.scatter_plot(open_linear_nested_df,config,' OpenFaaS latency relative to invocation start: nested',directory,18) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.scatter_plot(azure_linear_nested_df,config,'Azure latency relative to invocation start: nested',directory,18) config = { 'x': 'provider', 'y': 'cold', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Number of cold times',12), 'markers': ['o','s','v'], 'jitter': 0.1, 'alpha': 0.5, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } aws = np.array(aws_linear_nested_df['cold'].value_counts()).tolist()+['aws_lambda'] openf = np.array(open_linear_nested_df['cold'].value_counts()).tolist()+['openfaas'] azure = np.array(azure_linear_nested_df['cold'].value_counts()).tolist()+['azure_functions'] zipped = list(zip(aws,openf,azure)) data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]} df = pd.DataFrame(data) gg.bar_plot(df, config,'Cold times: linear-invocation: nested',directory) config['y'] = 'warm' config['ylabel'] = ('Number of warm times',12) gg.bar_plot(df, config,'Warm times: linear-invocation: nested',directory) config['x'] = 'instance_id' config['y'] = 'latency' config['xlabel'] = ('Function id',12) config['ylabel'] = ('Latency in seconds',12) copy_aws_linear_nested_df = aws_linear_nested_df.copy(deep=True) copy_aws_linear_nested_df['instance_id'] = copy_aws_linear_nested_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000)) config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.strip_plot(copy_aws_linear_nested_df,config,' AWS latency per function instance: nested',directory) copy_open_linear_nested_df = open_linear_nested_df.copy(deep=True) open_linear_nested_df['instance_id'] = copy_open_linear_nested_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000)) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.strip_plot(copy_open_linear_nested_df,config,'OpenFaaS latency per function instance: nested',directory) copy_azure_linear_nested_df = azure_linear_nested_df.copy(deep=True) copy_azure_linear_nested_df['instance_id'] = copy_azure_linear_nested_df.instance_id.map(lambda x: int(abs(int(hash(x)))/10000000000000000)) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.strip_plot(copy_azure_linear_nested_df,config,'Azure latency per function instance: nested',directory) ######################### # --> load-scenario <-- # ######################### directory = directory.split('/')[0] directory += '/pyramid' config = { 'x': 'provider', 'y': 'number', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('number of errors',12), 'xlabel': ('Cloud Provider',12), 'markers': ['o','s','v'], 'hist':True, 'kde': False, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.bar_plot(joint_error_df,config,'error by provider for load-scenario: pyramid',directory,18) aws = np.array(aws_pyramid_df['cold'].value_counts()).tolist()+['aws_lambda'] openf = np.array(open_pyramid_df['cold'].value_counts()).tolist()+['openfaas'] azure = np.array(azure_pyramid_df['cold'].value_counts()).tolist()+['azure_functions'] zipped = list(zip(aws,openf,azure)) data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]} df = pd.DataFrame(data) config = { 'x': 'provider', 'y': 'cold', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('number of cold times',12), 'markers': ['o','s','v'], 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.bar_plot(df, config,'Cold times: load-scenario: pyramid',directory) config['y'] = 'warm' config['ylabel'] = ('number of warm times',12) gg.bar_plot(df, config,'Warm times: load-scenario: pyramid',directory) config = { 'x': 'provider', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('cold times',12), 'markers': ['o','s','v'], 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.boxen_plot(joint_pyramid_df, config, 'Cold times distribution: pyramid',directory) config['x'] = 'multi' gg.boxen_plot(joint_pyramid_df, config, 'Cold times concurrent vs sequential: pyramid',directory) config = { 'x': 'invocation_start', 'y': 'latency', 'hue': 'provider', 'ylabel': ('Latency in seconds',12), 'xlabel': ('Invocation start time',12), 'fit_reg': False, # 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.lm_plot(aws_pyramid_df, config, 'AWS latency: pyramid', directory) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.lm_plot(open_pyramid_df, config, 'OpenFaaS latency: pyramid', directory) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.lm_plot(azure_pyramid_df, config, 'Azure latency: pyramid', directory) config = { 'x': 'invocation_start', 'y': 'latency', 'ylabel': ('Latency in seconds',12), 'xlabel': ('Invocation start time',12), 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'markers': ['o','s','v'], 'fit_reg': False, # 'hist':True, # 'kde': False, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.lm_plot(joint_pyramid_df, config, 'Latency by provider: pyramid', directory) def find_cold_times(df): cold_times = {} for row in df.itertuples(index=True, name='Pandas'): if row.cold == 'cold': if row.instance_id not in cold_times: cold_times[row.instance_id] = 0 else: cold_times[row.instance_id] += 1 return cold_times aws_count = find_cold_times(aws_pyramid_df) aws_cold_starts = len(aws_count) aws_cold_times = reduce(lambda x,y: x+y[1],[0]+list(aws_count.items())) open_count = find_cold_times(open_pyramid_df) open_cold_starts = len(open_count) open_cold_times = reduce(lambda x,y: x+y[1],[0]+list(open_count.items())) # print(open_count,'\n') azure_count = find_cold_times(azure_pyramid_df) azure_cold_starts = len(azure_count) azure_cold_times = reduce(lambda x,y: x+y[1],[0]+list(azure_count.items())) # print(azure_count,'\n') data = {'provider': ['aws_lambda','openfaas','azure_functions'], 'cold_start': [aws_cold_starts,open_cold_starts,azure_cold_starts], 'cold_times': [aws_cold_times,open_cold_times,azure_cold_times]} df = pd.DataFrame(data) config = { 'x': 'provider', 'y': 'cold_start', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Number of cold starts',12), 'xlabel': ('Provider',12), 'markers': ['o','s','v'], # 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.bar_plot(df, config,'Cold starts: load-scenario-pyramid',directory) config['y'] = 'cold_times' config['ylabel'] = ('Number of cold times',12) gg.bar_plot(df, config,'Cold times: load scenario-pyramid',directory) ############################### # growing-load-spike scenario # ############################### directory = directory.split('/')[0] directory += '/spikes' config = { 'x': 'provider', 'y': 'number', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('number of errors',12), 'xlabel': ('Cloud Provider',12), 'markers': ['o','s','v'], 'hist':True, 'kde': False, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.bar_plot(joint_error_spike_df,config,'Error by provider for load-scenario: spikes',directory,18) aws = np.array(aws_spike_df['cold'].value_counts()).tolist()+['aws_lambda'] openf = np.array(open_spike_df['cold'].value_counts()).tolist()+['openfaas'] azure = np.array(azure_spike_df['cold'].value_counts()).tolist()+['azure_functions'] zipped = list(zip(aws,openf,azure)) data = {'provider': zipped[2], 'cold': zipped[1],'warm': zipped[0]} df = pd.DataFrame(data) config = { 'x': 'provider', 'y': 'cold', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('number of cold times',12), 'markers': ['o','s','v'], 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.bar_plot(df, config,'Cold times: load-scenario: spikes',directory) config['y'] = 'warm' config['ylabel'] = ('number of warm times',12) gg.bar_plot(df, config,'Warm times: load-scenario: spikes',directory) config = { 'x': 'provider', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('cold times',12), 'markers': ['o','s','v'], 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.boxen_plot(joint_spike_df, config, 'Cold times distribution: spikes',directory) config['x'] = 'multi' gg.boxen_plot(joint_spike_df, config, 'Cold times concurrent vs sequential: spikes',directory) config = { 'x': 'invocation_start', 'y': 'latency', 'hue': 'provider', 'ylabel': ('Latency in seconds',12), 'xlabel': ('Invocation start time',12), 'fit_reg': False, # 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.lm_plot(aws_spike_df, config, 'AWS latency: spikes', directory) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.lm_plot(open_spike_df, config, 'OpenFaaS latency: spikes', directory) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.lm_plot(azure_spike_df, config, 'Azure latency: spikes', directory) config['hue_order'] = hue_order config['palette'] = provider_color_dict config = { 'x': 'invocation_start', 'y': 'latency', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Latency in seconds',12), 'xlabel': ('Invocation start time',12), 'markers': ['o','s','v'], 'jitter': 0.1, 'fit_reg': False, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.lm_plot(joint_spike_df, config, 'Latency by provider: spikes', directory) def find_cold_times(df): cold_times = {} for row in df.itertuples(index=True, name='Pandas'): if row.cold == 'cold': if row.instance_id not in cold_times: cold_times[row.instance_id] = 0 else: cold_times[row.instance_id] += 1 return cold_times aws_count = find_cold_times(aws_spike_df) aws_cold_starts = len(aws_count) aws_cold_times = reduce(lambda x,y: x+y[1],[0]+list(aws_count.items())) open_count = find_cold_times(open_spike_df) open_cold_starts = len(open_count) open_cold_times = reduce(lambda x,y: x+y[1],[0]+list(open_count.items())) # print(open_count,'\n') azure_count = find_cold_times(azure_spike_df) azure_cold_starts = len(azure_count) azure_cold_times = reduce(lambda x,y: x+y[1],[0]+list(azure_count.items())) # print(azure_count,'\n') data = {'provider': ['aws_lambda','openfaas','azure_functions'], 'cold_start': [aws_cold_starts,open_cold_starts,azure_cold_starts], 'cold_times': [aws_cold_times,open_cold_times,azure_cold_times]} df = pd.DataFrame(data) config = { 'x': 'provider', 'y': 'cold_start', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Number of cold starts',12), 'xlabel': ('Provider',12), 'markers': ['o','s','v'], # 'jitter': 0.1, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.bar_plot(df, config,'Cold starts: load-scenario-spikes',directory) config['y'] = 'cold_times' config['ylabel'] = ('Number of cold times',12) gg.bar_plot(df, config,'Cold times: load scenario-spikes',directory) def throughput_graphs(directory:str, devmode:bool ): print('throughput_graphs') # metadata directory = 'Throughput' experiment_uuids = get_uuids('throughput-benchmarking') # queries def query_by_provider(uuid, multi): return f"""SELECT throughput/1000 as operations_milli, throughput_time, throughput_process_time,(throughput_process_time/throughput_time)*100 as process_fraction, execution_start-invocation_start as latency, thread_id, if(numb_threads > 1,1,0) as multi, cl_provider as provider from Experiment e left join Invocation i on i.exp_id=e.uuid where throughput != 0 and numb_threads {'> 1' if multi else '= 1'} and exp_id ='{uuid}';""" def monolith_by_provider(uuid,multi): return f"""select function_argument,process_time_matrix,running_time_matrix,monolith_result,(process_time_matrix/running_time_matrix)*100 as process_fraction, execution_start-invocation_start as latency, thread_id, numb_threads, if(numb_threads > 1,0,1) as multi, cl_provider as provider from (Monolith m left join Experiment e on m.exp_id=e.uuid) join Invocation i on m.invo_id=i.identifier where numb_threads {'> 1' if multi else '= 1'} and m.exp_id ='{uuid}';""" # dataframes aws_invo_single_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], False)) if 'aws_lambda' in experiment_uuids else np.DataFrame() azure_invo_single_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], False)) if 'azure_functions' in experiment_uuids else np.DataFrame() open_invo_single_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], False)) if 'openfaas' in experiment_uuids else np.DataFrame() aws_invo_multi_df = db.get_raw_query(query_by_provider(experiment_uuids['aws_lambda'], True)) if 'aws_lambda' in experiment_uuids else np.DataFrame() azure_invo_multi_df = db.get_raw_query(query_by_provider(experiment_uuids['azure_functions'], True)) if 'azure_functions' in experiment_uuids else np.DataFrame() open_invo_multi_df = db.get_raw_query(query_by_provider(experiment_uuids['openfaas'], True)) if 'openfaas' in experiment_uuids else np.DataFrame() joined_single_df = pd.concat([aws_invo_single_df,azure_invo_single_df,open_invo_single_df],ignore_index=True) joined_multi_df = pd.concat([aws_invo_multi_df,azure_invo_multi_df,open_invo_multi_df],ignore_index=True) all_invo_df = pd.concat([joined_single_df,joined_multi_df],ignore_index=True) # from monolith table aws_monolith_df = db.get_raw_query(monolith_by_provider(experiment_uuids['aws_lambda'], False)) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_monolith_df = db.get_raw_query(monolith_by_provider(experiment_uuids['azure_functions'], False)) if 'azure_functions' in experiment_uuids else np.DataFrame() azure_monolith_df = db.get_raw_query(monolith_by_provider(experiment_uuids['openfaas'], False)) if 'openfaas' in experiment_uuids else np.DataFrame() aws_monolith_multi_df = db.get_raw_query(monolith_by_provider(experiment_uuids['aws_lambda'], True)) if 'aws_lambda' in experiment_uuids else np.DataFrame() open_monolith_multi_df = db.get_raw_query(monolith_by_provider(experiment_uuids['azure_functions'], True)) if 'azure_functions' in experiment_uuids else np.DataFrame() azure_monolith_multi_df = db.get_raw_query(monolith_by_provider(experiment_uuids['openfaas'], True)) if 'openfaas' in experiment_uuids else np.DataFrame() monolith_single_df = pd.concat([aws_monolith_df, azure_monolith_df,open_monolith_df],ignore_index=True) monolith_multi_df = pd.concat([aws_monolith_multi_df,azure_monolith_multi_df,open_monolith_multi_df],ignore_index=True) monolith_all_invo_df = pd.concat([monolith_single_df,monolith_multi_df],ignore_index=True) # Throughput time and operations perfomed in that time config = { 'x': 'throughput_time', 'y': 'operations_milli', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('operations (1000)',12), 'xlabel': ('time in seconds',12), 'markers': ['o','s','v'], # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } gg.lm_plot(joined_single_df,config,'Ops per second: sequential ',directory) gg.line_plot(joined_single_df,config,'Ops per second: sequential',directory) gg.lm_plot(joined_multi_df,config,'Ops per second: concurrent',directory) gg.line_plot(joined_multi_df,config,'Ops per second: concurrent',directory) gg.lm_plot(all_invo_df,config,'Ops per second: all',directory) # for appendix config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.lm_plot(pd.concat([aws_invo_single_df,aws_invo_multi_df]),config,'AWS ops per second: all',directory ) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.lm_plot(pd.concat([open_invo_single_df,open_invo_multi_df]),config,'OpenFaaS ops per second: all',directory ) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.lm_plot(pd.concat([azure_invo_single_df,azure_invo_multi_df]),config,'Azure ops per second: all',directory ) config['x'] = 'latency' config['hue_order'] = hue_order config['palette'] = provider_color_dict config['markers'] = ['o','s','v'] gg.lm_plot(joined_single_df,config,'Ops per second mapped to latency: sequential ',directory) gg.lm_plot(joined_multi_df,config,'Ops per second mapped to latency: concurrent',directory) gg.lm_plot(all_invo_df,config,'Ops per second mapped to latency: all',directory) config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.lm_plot(pd.concat([aws_invo_single_df,aws_invo_multi_df]),config,'AWS ops per second mapped to latency: all',directory) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.lm_plot(pd.concat([open_invo_single_df,open_invo_multi_df]),config,'OpenFaaS ops per second mapped to latency: all',directory) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['v'] gg.lm_plot(pd.concat([azure_invo_single_df,azure_invo_multi_df]),config,'Azure ops per second mapped to latency: all',directory) # for appendix - no correlation found for latency copy_all_invo = all_invo_df.copy(deep=True) indexNames = copy_all_invo[ copy_all_invo['latency'] > 10.0 ].index # Delete these row indexes from dataFrame copy_all_invo.drop(indexNames , inplace=True) config['kind']='scatter' config['x_vars'] = ['operations_milli','throughput_process_time','process_fraction'] config['y_vars'] = ['latency'] gg.pair_plot(copy_all_invo, config,'Process fraction: sequential',directory) config = { 'x': 'throughput_time', 'y': 'process_fraction', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Percentage of time in CPU ',12), 'xlabel': ('Time in seconds',12), 'markers': ['o','s','v'], # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } # single gg.bar_plot(joined_single_df,config,'Process fraction: sequential',directory) # multi gg.bar_plot(joined_multi_df, config,'Process fraction: concurrent',directory) # all gg.bar_plot(all_invo_df, config,'Process fraction: all',directory) config['x'] = 'provider' # plots per provider gg.violin_plot(joined_single_df,config,'Process fraction by provider: sequential',directory) # multi gg.violin_plot(joined_multi_df, config,'Process fraction: concurrent',directory) # all gg.violin_plot(all_invo_df, config,'Process fraction: all',directory) # --> Monolith plots <-- directory += '/monolith' config = { 'x': 'function_argument', 'y': 'running_time_matrix', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'xlabel': ('Size of matrix',12), 'ylabel': ('Running time in seconds',12), 'markers': ['o','s','v'], 'jitter':0.15, # 'height': 4, # 'aspect': 0.8, } gg.lm_plot(monolith_all_invo_df,config,'Time for matrix calculation: all',directory) gg.line_plot(monolith_all_invo_df,config,'Time for matrix calculation: all',directory) gg.swarm_plot(monolith_all_invo_df,config,'Time for matrix calculation: all',directory) config = { 'x': 'multi', 'y': 'running_time_matrix', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('Time in seconds',12), 'xlabel': ('Sequential vs concurrent',12), 'markers': ['o','s','v'], 'hist':True, 'kde': False, # 'height': 4, # 'aspect': 0.8, 'line_kws':{'color':colors['light_gray']}, } # config['x']='multi' config['strip'] = True config['x_strip'] = 'multi' config['y_strip'] = 'running_time_matrix' config['bins'] = 30 config['hue_order'] = ['aws_lambda'] config['palette'] = {'aws_lambda':provider_color_dict['aws_lambda']} config['markers'] = ['s'] gg.box_plot(pd.concat([aws_monolith_df,aws_monolith_multi_df]),config,'AWS Time for matrix calc: all',directory) config['hue_order'] = ['openfaas'] config['palette'] = {'openfaas':provider_color_dict['openfaas']} config['markers'] = ['o'] gg.box_plot(pd.concat([open_monolith_df,open_monolith_multi_df]),config,'OpenFaaS Time for matrix calc: all',directory) config['hue_order'] = ['azure_functions'] config['palette'] = {'azure_functions':provider_color_dict['azure_functions']} config['markers'] = ['s'] gg.box_plot(pd.concat([azure_monolith_df,azure_monolith_multi_df]),config,'azure Time for matrix calc: all',directory) config['hue_order'] = hue_order config['palette'] = provider_color_dict config['markers'] = ['o','s','v'] gg.box_plot(monolith_all_invo_df,config,'Time for matrix calc for all providers',directory) config = { 'x': 'function_argument', 'y': 'process_fraction', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'xlabel': ('Size of matrix',12), 'ylabel': ('Process time in seconds',12), 'markers': ['o','s','v'], 'jitter':0.15, # 'height': 4, # 'aspect': 0.8, } gg.swarm_plot(monolith_all_invo_df,config,'Process fraction by function argument: all',directory) gg.bar_plot(monolith_all_invo_df,config,'Process fraction by function argument: all',directory) gg.scatter_plot(monolith_all_invo_df,config,'Process fraction by function argument: all',directory) config = { 'x': 'running_time_matrix', 'y': 'process_fraction', 'hue': 'provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'xlabel': ('Running time seconds',14), 'ylabel': ('Process time in seconds',14), 'markers': ['o','s','v'], 'jitter':0.15, # 'height': 4, # 'aspect': 0.8, } gg.scatter_plot(monolith_all_invo_df,config,'Matrix calculation: all',directory) # delete when done def test(directory:str, dev_mode:bool): db = database(True) gg = GraphGenerater('report',dev_mode) hue_order = ['openfaas','aws_lambda','azure_functions'] provider_color_dict = dict({'aws_lambda':'#ff8c00ff', 'azure_functions': '#ffd700ff', 'openfaas': '#2316deff', }) query_throughput = """SELECT floor(throughput/1000) as operations_milli,throughput_time,(throughput_process_time/throughput_time)*100 as process_fraction, cl_provider from (select name, cl_provider, total_time, uuid as experiment_uuid from Experiment where name = 'throughput-benchmarking') x left join Invocation i on i.exp_id=x.experiment_uuid where throughput != 0 and throughput_time < 2.0 and floor(throughput/1000) < 1000 order by throughput_time;""" throughput_dataframe = db.get_raw_query(query_throughput) # print(throughput_dataframe.head(10).to_latex(index=False)) # print(throughput_dataframe.head(10).to_html(index=False)) # basic_throughput = throughput_dataframe.copy(deep=True) # lineplot - throughput per second all providers config = { 'x': 'throughput_time', 'y': 'operations_milli', 'hue': 'cl_provider', 'palette': provider_color_dict, 'hue_order': hue_order, 'ylabel': ('operations (100)',14), 'xlabel': ('time in seconds',18), # 'markers': ['o','s','v'], # 'height': 3, # 'aspect':0.8, # 'kind': 'scatter', # 'x_jitter':0.25, # 'y_jitter': 0.25, # 'row':'cl_provider', # 'line_kws':{'color':'#191970ff'}, # 'color':'purple' } # gg.joint_plot(throughput_dataframe,config,'jointplot',directory) list_query = """select execution_start-invocation_start as latency from Invocation where exp_id in (select uuid from Experiment where name='linear-invocation-nested' and cl_provider='aws_lambda') and execution_start-invocation_start > 0.5;""" res_list = db.get_raw_query(list_query,False) flatten = reduce(lambda x,y: x+y,res_list) # config['hist']=True # config['kde']= False # config['bins'] = 30 # config['height'] = 0.5 # config.pop('x') # config['color']='#ff8c00ff' # gg.rug_plot(flatten,config,'rug plot',directory) # gg.dist_plot(flatten,config,'dist plot',directory) # gg.bar_plot(throughput_dataframe,config,'operations (1000) per second',directory) # config.pop('y') # gg.count_plot(throughput_dataframe,config,'operations (1000) per second',directory) # gg.line_plot(throughput_dataframe,config,'operations (1000) per second',directory,12) # config['col'] = 'cl_provider' # config['jitter'] = 0.25 # config['aspect'] = 1.2 # config['height'] = 3 # config.pop('hue') # config['palette'] = 'bright' # gg.cat_plot(throughput_dataframe,config,'cat plot',directory) # gg.violin_plot(throughput_dataframe,config,'Violin plot',directory) # config['y'] = 'process_fraction' # gg.strip_plot(throughput_dataframe,config,'strip plot',directory) gg.dynamic_multi_plot(throughput_dataframe,config,'line + scatter',directory,[lambda l: sns.lineplot( x=l[0], y=l[1], hue=l[2], style=None, palette=l[3], hue_order=l[4], data=l[5]), lambda l: sns.scatterplot( x=l[0], y=l[1], hue=l[2], style=None, palette=l[3], hue_order=l[4], data=l[5], )],12,) gg.scatter_plot(throughput_dataframe,config,'scatterplot',directory,12) # swarmplot - process_fraction per throughput_time config = { 'x': 'throughput_time', 'y': 'process_fraction', 'hue': 'cl_provider', 'palette': provider_color_dict } # gg.swarm_plot(throughput_dataframe,config,'process fraction',directory) config['x'] = 'cl_provider' gg.box_plot(throughput_dataframe,config,'process fraction',directory) # query_avg_process_fraction = """SELECT floor(throughput/1000) as operations_milli,throughput_time,throughput_process_time, avg((throughput_process_time/throughput_time)*100) as process_fraction, cl_provider from (select name, cl_provider, total_time, uuid as experiment_uuid from Experiment where name = 'throughput-benchmarking') x left join Invocation i on i.exp_id=x.experiment_uuid where throughput != 0 group by throughput_time,cl_provider order by cl_provider;""" avg_process_fraction_df = db.get_raw_query(query_avg_process_fraction) config = { 'x': 'throughput_time', 'y': 'process_fraction', 'hue': 'cl_provider', 'palette': provider_color_dict } gg.lineplot_graph(avg_process_fraction_df, config, 'lineplot process fraction', directory) gg.relplot(avg_process_fraction_df, config, 'relplot process fraction', directory) # Produce the graphs by calling chosen graph methos for category in category_of_graphs: category()
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4
4ae2d2cfd811bec92e12e8dd7ce4576495f72360
181
py
Python
race/serializers.py
scottBowles/dnd
a1ef333f1a865d51b5426dc4b3493e8437584565
[ "MIT" ]
null
null
null
race/serializers.py
scottBowles/dnd
a1ef333f1a865d51b5426dc4b3493e8437584565
[ "MIT" ]
null
null
null
race/serializers.py
scottBowles/dnd
a1ef333f1a865d51b5426dc4b3493e8437584565
[ "MIT" ]
null
null
null
from rest_framework import serializers from .models import Race class RaceSerializer(serializers.ModelSerializer): class Meta: model = Race fields = "__all__"
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4
ab19bff99a2e03b4fd2fd7845b69a57f4bc8c45b
91
py
Python
design_System/design_System/apps/__init__.py
Dante-max/Design_System
dcc837588eb72542c6a3ee213b184d49b685bc59
[ "MIT" ]
null
null
null
design_System/design_System/apps/__init__.py
Dante-max/Design_System
dcc837588eb72542c6a3ee213b184d49b685bc59
[ "MIT" ]
null
null
null
design_System/design_System/apps/__init__.py
Dante-max/Design_System
dcc837588eb72542c6a3ee213b184d49b685bc59
[ "MIT" ]
null
null
null
# 最是人间留不住,朱颜辞镜花辞树 # -*- coding:utf-8 -*- # http://127.0.0.1:8000/static/Navimage/Nav1.png
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4
ab1db84947b6628898cbbd425acb1dc1db41a5dd
144
py
Python
django_gotolong/broker/icidir/isum/admin.py
ParikhKadam/gotolong
839beb8aa37055a2078eaa289b8ae05b62e8905e
[ "BSD-2-Clause", "BSD-3-Clause" ]
15
2019-12-06T16:19:45.000Z
2021-08-20T13:22:22.000Z
django_gotolong/broker/icidir/isum/admin.py
ParikhKadam/gotolong
839beb8aa37055a2078eaa289b8ae05b62e8905e
[ "BSD-2-Clause", "BSD-3-Clause" ]
14
2020-12-08T10:45:05.000Z
2021-09-21T17:23:45.000Z
django_gotolong/broker/icidir/isum/admin.py
ParikhKadam/gotolong
839beb8aa37055a2078eaa289b8ae05b62e8905e
[ "BSD-2-Clause", "BSD-3-Clause" ]
9
2020-01-01T03:04:29.000Z
2021-04-18T08:42:30.000Z
from django.contrib import admin # Register your models here. from .models import BrokerIcidirSum # ... admin.site.register(BrokerIcidirSum)
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4
ab1dea57c847afb7221339493a273801da7cf334
586
py
Python
students/views/professors.py
ovod88/studentsdb
ade2cff0eea7a13644a0f708133901457352ff5c
[ "MIT" ]
null
null
null
students/views/professors.py
ovod88/studentsdb
ade2cff0eea7a13644a0f708133901457352ff5c
[ "MIT" ]
null
null
null
students/views/professors.py
ovod88/studentsdb
ade2cff0eea7a13644a0f708133901457352ff5c
[ "MIT" ]
null
null
null
from django.shortcuts import render from django.http import HttpResponse from django.template import RequestContext, loader from django.core.paginator import Paginator, EmptyPage, PageNotAnInteger from ..models.groups import Group def professors_list(request): return render(request, 'students/professors_list.html', {}) # def examins_add(request): # return HttpResponse('<h1>Examin Add Form</h1>') def professors_edit(request, pid): return HttpResponse(f'<h1>Edit Professor {pid}</h1>') # def groups_delete(request, gid): # return HttpResponse(f'<h1>Delete Group {gid}</h1>')
30.842105
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4
ab211c1ec3d66d22156a37f9389218b48c6b2876
29,739
py
Python
analyzer/tmp.py
GPrathap/OpenBCIPython
0f5be167fb09d31c15885003eeafec8cdc08dbfa
[ "MIT" ]
1
2021-11-07T12:01:08.000Z
2021-11-07T12:01:08.000Z
analyzer/tmp.py
GPrathap/OpenBCIPython
0f5be167fb09d31c15885003eeafec8cdc08dbfa
[ "MIT" ]
null
null
null
analyzer/tmp.py
GPrathap/OpenBCIPython
0f5be167fb09d31c15885003eeafec8cdc08dbfa
[ "MIT" ]
1
2020-10-15T08:35:01.000Z
2020-10-15T08:35:01.000Z
# Visualize an STFT power spectrum import librosa.display import matplotlib.pyplot as plt import numpy as np # y, sr = librosa.load(librosa.util.example_audio_file()) # plt.figure(figsize=(12, 8)) # number_of_columns = 5 # number_of_rows = 2 # # D = librosa.stft(y) # plt.subplot(number_of_columns, number_of_rows, 1) # librosa.display.specshow(D, y_axis='log') # plt.colorbar() # plt.title('Log-frequency power spectrogram') # # # Or on a logarithmic scale # D = np.array(librosa.zero_crossings(y)) # D = np.where(D == True, 10, D) # D = np.where(D == False, -10, D) # F=[] # F.append(D.tolist()) # # plt.subplot(number_of_columns, number_of_rows, 2) # librosa.display.specshow(np.array(F)) # plt.colorbar() # plt.title('Zero-Crossing-Rate') # # # Or use a CQT scale # # CQT = librosa.cqt(y, sr=sr) # plt.subplot(number_of_columns, number_of_rows, 3) # librosa.display.specshow(CQT, y_axis='cqt_note') # plt.colorbar() # plt.title('Constant-Q power spectrogram (note)') # # plt.subplot(number_of_columns, number_of_rows, 4) # librosa.display.specshow(CQT, y_axis='cqt_hz') # plt.colorbar() # plt.title('Constant-Q power spectrogram (Hz)') # # # Draw a chromagram with pitch classes # # tonnetz = librosa.feature.tonnetz(y=y, sr=sr) # plt.subplot(number_of_columns, number_of_rows, 5) # librosa.display.specshow(tonnetz, y_axis='tonnetz') # plt.colorbar() # plt.title('Tonal Centroids (Tonnetz)') # # rms = librosa.feature.rmse(y=y) # plt.subplot(number_of_columns, number_of_rows, 6) # plt.semilogy(rms.T, label='RMS Energy') # plt.colorbar() # plt.title('Root Mean Square Energy') # # # Draw time markers automatically # cent = librosa.feature.spectral_centroid(y=y, sr=sr) # plt.subplot(number_of_columns, number_of_rows, 7) # plt.semilogy(cent.T, label='Spectral centroid') # plt.ylabel('Hz') # plt.xticks([]) # plt.xlim([0, cent.shape[-1]]) # plt.colorbar() # plt.title('Spectral centroid') # # # Draw a tempogram with BPM markers # plt.subplot(number_of_columns, number_of_rows, 8) # Tgram = librosa.feature.tempogram(y=y, sr=sr) # librosa.display.specshow(Tgram, x_axis='time', y_axis='tempo') # plt.colorbar() # plt.title('Tempogram') # plt.tight_layout() # # # plt.show() distance = np.array([0.43535290045236669, 0.42654141461933315, 0.41773000255681991, 0.40891999695557635, 0.40011370175151184, 0.39131343663359758, 0.38252154303566893, 0.37374034300584275, 0.36497215917263209, 0.35621801267585679, 0.34747593421300349, 0.33874262441059977, 0.33001335524476083, 0.3212808090951445, 0.31253415076299623, 0.30375467571545162, 0.29279413332463616, 0.28066950263846913, 0.26748473568315551, 0.25329508095999298, 0.23816238276517113, 0.22257064085487269, 0.20686783041366305, 0.19137636417560147, 0.17619725667101774, 0.1613130873077859, 0.14692619820926339, 0.13302604230193524, 0.11948229124115357, 0.10618926662385368, 0.093221416544688129, 0.080759511753566646, 0.068909841268586389, 0.057741789191314258, 0.047528297400111059, 0.038377661783666583, 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0.29084310546334524, 0.28987632769887078, 0.28697612648899906, 0.27849302709726087, 0.27040182687763575, 0.26313598066475358, 0.25736953519198241, 0.25390598541742998, 0.25252011424599741, 0.25158379281330517, 0.25087691546326274, 0.25016368106446818, 0.24916780826531498, 0.24757336510865122, 0.24533318976705304, 0.24241758801732174, 0.2389234940494453, 0.23500048496638054, 0.22517230687318487, 0.20968403325682883, 0.1954168931013287, 0.18653916776633384, 0.18331583090627679, 0.18215909901887159, 0.18145950323339111, 0.18111948230345445, 0.18111924333514509, 0.1814137460697513, 0.1818535851353055, 0.18229296467977235, 0.18262723505235368, 0.1827770738594422, 0.18265681180591548, 0.1821994799425449, 0.17608807141805072, 0.16872983107947212, 0.16240144702190812, 0.15776702584744981, 0.15464840228225418, 0.15237019406976063, 0.15069387855224797, 0.14957855280129848, 0.14887084600985745, 0.14944410780100323, 0.15119699571390499, 0.1536553381027834, 0.15630072203410425, 0.15934025175622293, 0.16403903814992299, 0.16937677296024786, 0.17377070391008656, 0.17912562063261195, 0.18733224310885299, 0.19879874326035937, 0.21231634467295796, 0.22825017488658014, 0.24753159238992894, 0.25631758902797996, 0.25757325062304964, 0.25869443202710857, 0.25978688224240926, 0.26099281158466298, 0.26238203918045533, 0.26398376588674261, 0.26574486564100647, 0.26766362036726948, 0.26971398165645072, 0.27181052886496732, 0.27387207451181622, 0.27594100769380986, 0.27798838385600128, 0.28017436118818662, 0.2824514682885908, 0.28474846618476674, 0.28705095901637745, 0.28919778908299615, 0.29114421238617272, 0.29274340523878489, 0.2939492708455681]) possion = np.array([3000, 3005, 3010, 3015, 3020, 3025, 3030, 3035, 3040, 3045, 3050, 3055, 3060, 3065, 3070, 3075, 3080, 3085, 3090, 3095, 3100, 3105, 3110, 3115, 3120, 3125, 3130, 3135, 3140, 3145, 3150, 3155, 3160, 3165, 3170, 3175, 3180, 3185, 3190, 3195, 3200, 3205, 3210, 3215, 3220, 3225, 3230, 3235, 3240, 3245, 3250, 3255, 3260, 3265, 3270, 3275, 3280, 3285, 3290, 3295, 3300, 3305, 3310, 3315, 3320, 3325, 3330, 3335, 3340, 3345, 3350, 3355, 3360, 3365, 3370, 3375, 3380, 3385, 3390, 3395, 3400, 3405, 3410, 3415, 3420, 3425, 3430, 3435, 3440, 3445, 3450, 3455, 3460, 3465, 3470, 3475, 3480, 3485, 3490, 3495, 3500, 3505, 3510, 3515, 3520, 3525, 3530, 3535, 3540, 3545, 3550, 3555, 3560, 3565, 3570, 3575, 3580, 3585, 3590, 3595, 3600, 3605, 3610, 3615, 3620, 3625, 3630, 3635, 3640, 3645, 3650, 3655, 3660, 3665, 3670, 3675, 3680, 3685, 3690, 3695, 3700, 3705, 3710, 3715, 3720, 3725, 3730, 3735, 3740, 3745, 3750, 3755, 3760, 3765, 3770, 3775, 3780, 3785, 3790, 3795, 3800, 3805, 3810, 3815, 3820, 3825, 3830, 3835, 3840, 3845, 3850, 3855, 3860, 3865, 3870, 3875, 3880, 3885, 3890, 3895, 3900, 3905, 3910, 3915, 3920, 3925, 3930, 3935, 3940, 3945, 3950, 3955, 3960, 3965, 3970, 3975, 3980, 3985, 3990, 3995, 4000, 4005, 4010, 4015, 4020, 4025, 4030, 4035, 4040, 4045, 4050, 4055, 4060, 4065, 4070, 4075, 4080, 4085, 4090, 4095, 4100, 4105, 4110, 4115, 4120, 4125, 4130, 4135, 4140, 4145, 4150, 4155, 4160, 4165, 4170, 4175, 4180, 4185, 4190, 4195, 4200, 4205, 4210, 4215, 4220, 4225, 4230, 4235, 4240, 4245, 4250, 4255, 4260, 4265, 4270, 4275, 4280, 4285, 4290, 4295, 4300, 4305, 4310, 4315, 4320, 4325, 4330, 4335, 4340, 4345, 4350, 4355, 4360, 4365, 4370, 4375, 4380, 4385, 4390, 4395, 4400, 4405, 4410, 4415, 4420, 4425, 4430, 4435, 4440, 4445, 4450, 4455, 4460, 4465, 4470, 4475, 4480, 4485, 4490, 4495, 4500, 4505, 4510, 4515, 4520, 4525, 4530, 4535, 4540, 4545, 4550, 4555, 4560, 4565, 4570, 4575, 4580, 4585, 4590, 4595, 4600, 4605, 4610, 4615, 4620, 4625, 4630, 4635, 4640, 4645, 4650, 4655, 4660, 4665, 4670, 4675, 4680, 4685, 4690, 4695, 4700, 4705, 4710, 4715, 4720, 4725, 4730, 4735, 4740, 4745, 4750, 4755, 4760, 4765, 4770, 4775, 4780, 4785, 4790, 4795, 4800, 4805, 4810, 4815, 4820, 4825, 4830, 4835, 4840, 4845, 4850, 4855, 4860, 4865, 4870, 4875, 4880, 4885, 4890, 4895, 4900, 4905, 4910, 4915, 4920, 4925, 4930, 4935, 4940, 4945, 4950, 4955, 4960, 4965, 4970, 4975, 4980, 4985, 4990, 4995, 5000, 5005, 5010, 5015, 5020, 5025, 5030, 5035, 5040, 5045, 5050, 5055, 5060, 5065, 5070, 5075, 5080, 5085, 5090, 5095, 5100, 5105, 5110, 5115, 5120, 5125, 5130, 5135, 5140, 5145, 5150, 5155, 5160, 5165, 5170, 5175, 5180, 5185, 5190, 5195, 5200, 5205, 5210, 5215, 5220, 5225, 5230, 5235, 5240, 5245, 5250, 5255, 5260, 5265, 5270, 5275, 5280, 5285, 5290, 5295, 5300, 5305, 5310, 5315, 5320, 5325, 5330, 5335, 5340, 5345, 5350, 5355, 5360, 5365, 5370, 5375, 5380, 5385, 5390, 5395, 5400, 5405, 5410, 5415, 5420, 5425, 5430, 5435, 5440, 5445, 5450, 5455, 5460, 5465, 5470, 5475, 5480, 5485, 5490, 5495, 5500, 5505, 5510, 5515, 5520, 5525, 5530, 5535, 5540, 5545, 5550, 5555, 5560, 5565, 5570, 5575, 5580, 5585, 5590, 5595, 5600, 5605, 5610, 5615, 5620, 5625, 5630, 5635, 5640, 5645, 5650, 5655, 5660, 5665, 5670, 5675, 5680, 5685, 5690, 5695, 5700, 5705, 5710, 5715, 5720, 5725, 5730, 5735, 5740, 5745, 5750, 5755, 5760, 5765, 5770, 5775, 5780, 5785, 5790, 5795, 5800, 5805, 5810, 5815, 5820, 5825, 5830, 5835, 5840, 5845, 5850, 5855, 5860, 5865, 5870, 5875, 5880, 5885, 5890, 5895, 5900, 5905, 5910, 5915, 5920, 5925, 5930, 5935, 5940, 5945, 5950, 5955, 5960, 5965, 5970, 5975, 5980, 5985, 5990, 5995, 6000, 6005, 6010, 6015, 6020, 6025, 6030, 6035, 6040, 6045, 6050, 6055, 6060, 6065, 6070, 6075, 6080, 6085, 6090, 6095, 6100, 6105, 6110, 6115, 6120, 6125, 6130, 6135, 6140, 6145, 6150, 6155, 6160, 6165, 6170, 6175, 6180, 6185, 6190, 6195, 6200, 6205, 6210, 6215, 6220, 6225, 6230, 6235, 6240, 6245, 6250, 6255, 6260, 6265, 6270, 6275, 6280, 6285, 6290, 6295, 6300, 6305, 6310, 6315, 6320, 6325, 6330, 6335, 6340, 6345, 6350, 6355, 6360, 6365, 6370, 6375, 6380, 6385, 6390, 6395, 6400, 6405, 6410, 6415, 6420, 6425, 6430, 6435, 6440, 6445, 6450, 6455, 6460, 6465, 6470, 6475, 6480, 6485, 6490, 6495, 6500, 6505, 6510, 6515, 6520, 6525, 6530, 6535, 6540, 6545, 6550, 6555, 6560, 6565, 6570, 6575, 6580, 6585, 6590, 6595, 6600, 6605, 6610, 6615, 6620, 6625, 6630, 6635, 6640, 6645, 6650, 6655, 6660, 6665, 6670, 6675, 6680, 6685, 6690, 6695, 6700, 6705, 6710, 6715, 6720, 6725, 6730, 6735, 6740, 6745, 6750, 6755, 6760, 6765, 6770, 6775, 6780, 6785, 6790, 6795, 6800, 6805, 6810, 6815, 6820, 6825, 6830, 6835, 6840, 6845, 6850, 6855, 6860, 6865, 6870, 6875, 6880, 6885, 6890, 6895, 6900, 6905, 6910, 6915, 6920, 6925, 6930, 6935, 6940, 6945, 6950, 6955, 6960, 6965, 6970, 6975, 6980, 6985, 6990, 6995, 7000, 7005, 7010, 7015, 7020, 7025, 7030, 7035, 7040, 7045, 7050, 7055, 7060, 7065, 7070, 7075, 7080, 7085, 7090, 7095, 7100, 7105, 7110, 7115, 7120, 7125, 7130, 7135, 7140, 7145, 7150, 7155, 7160, 7165, 7170, 7175, 7180, 7185, 7190, 7195, 7200, 7205, 7210, 7215, 7220, 7225, 7230, 7235, 7240, 7245, 7250, 7255, 7260, 7265, 7270, 7275, 7280, 7285, 7290, 7295, 7300, 7305, 7310, 7315, 7320, 7325, 7330, 7335, 7340, 7345, 7350, 7355, 7360, 7365, 7370, 7375, 7380, 7385, 7390, 7395, 7400, 7405, 7410, 7415, 7420, 7425, 7430, 7435, 7440, 7445, 7450, 7455, 7460, 7465, 7470, 7475, 7480, 7485, 7490, 7495, 7500, 7505, 7510, 7515, 7520, 7525, 7530, 7535, 7540, 7545, 7550, 7555, 7560, 7565, 7570, 7575, 7580, 7585, 7590, 7595, 7600, 7605, 7610, 7615, 7620, 7625, 7630, 7635, 7640, 7645, 7650, 7655, 7660, 7665, 7670, 7675, 7680, 7685, 7690, 7695, 7700, 7705, 7710, 7715, 7720, 7725, 7730, 7735, 7740, 7745, 7750, 7755, 7760, 7765, 7770, 7775, 7780, 7785, 7790, 7795, 7800, 7805, 7810, 7815, 7820, 7825, 7830, 7835, 7840, 7845, 7850, 7855, 7860, 7865, 7870, 7875, 7880, 7885, 7890, 7895, 7900, 7905, 7910, 7915, 7920, 7925, 7930, 7935, 7940, 7945, 7950, 7955, 7960, 7965, 7970, 7975, 7980, 7985, 7990, 7995]) plt.plot(possion, distance) plt.show() 0.0881659076708 0.0749462847822 0.0625061816364 0.0512740922866 0.0414091664901 0.0330504482696 0.0261112501876 0.0203759258579 0.0156153477831 0.0115580054158 0.00806045469524 0.00516485884949 0.00287576153205 0.00126080586026 0.000319452887888 0.0 0.000302155880928
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21,221
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4
ab270fdecd61a98f26007cb051d00aa309341018
194
py
Python
main/CompuCellPythonTutorial/CellDistance/Simulation/CellDistance.py
JulianoGianlupi/nh-cc3d-4x-base-tool
c0f4aceebd4c5bf3ec39e831ef851e419b161259
[ "CC0-1.0" ]
null
null
null
main/CompuCellPythonTutorial/CellDistance/Simulation/CellDistance.py
JulianoGianlupi/nh-cc3d-4x-base-tool
c0f4aceebd4c5bf3ec39e831ef851e419b161259
[ "CC0-1.0" ]
null
null
null
main/CompuCellPythonTutorial/CellDistance/Simulation/CellDistance.py
JulianoGianlupi/nh-cc3d-4x-base-tool
c0f4aceebd4c5bf3ec39e831ef851e419b161259
[ "CC0-1.0" ]
1
2021-02-26T21:50:29.000Z
2021-02-26T21:50:29.000Z
from cc3d import CompuCellSetup from .CellDistanceSteppables import CellDistanceSteppable CompuCellSetup.register_steppable(steppable=CellDistanceSteppable(frequency=1)) CompuCellSetup.run()
24.25
79
0.876289
17
194
9.941176
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0.01105
0.06701
194
7
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1
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4
ab31e6d9af6c7a8a6fd6dc55027a525fee820e24
228
py
Python
serif/theory/segment.py
BBN-E/ZS4IE
357965f3068cfe5098422d8cb0ca4b0f99c99fd4
[ "Apache-2.0" ]
7
2022-03-24T11:04:08.000Z
2022-03-31T17:12:46.000Z
serif/theory/segment.py
BBN-E/ZS4IE
357965f3068cfe5098422d8cb0ca4b0f99c99fd4
[ "Apache-2.0" ]
null
null
null
serif/theory/segment.py
BBN-E/ZS4IE
357965f3068cfe5098422d8cb0ca4b0f99c99fd4
[ "Apache-2.0" ]
null
null
null
from serif.theory.serif_theory import SerifTheory from serif.xmlio import _ChildTheoryElementList class Segment(SerifTheory): attributes = _ChildTheoryElementList('Attribute') fields = _ChildTheoryElementList('Field')
28.5
53
0.815789
21
228
8.666667
0.619048
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228
7
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32.571429
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4
ab3574c21161f36bbc075ea698a34b4a95d0ebab
397
py
Python
srcs/interpretator/context.py
pomponchik/computor_v2
742b3f3b47c8d46806b2f733b4ec07ae63a23f00
[ "MIT" ]
null
null
null
srcs/interpretator/context.py
pomponchik/computor_v2
742b3f3b47c8d46806b2f733b4ec07ae63a23f00
[ "MIT" ]
2
2022-01-28T07:02:15.000Z
2022-01-28T07:04:33.000Z
srcs/interpretator/context.py
pomponchik/expert_system
47d183c36474869dd1beccde8f2b6d509b5a8bcc
[ "MIT" ]
null
null
null
class Context: def __init__(self): self.data = {} def __getitem__(self, key): return self.data.get(self.convert_key(key), None) def __setitem__(self, key, value): self.data[self.convert_key(key)] = value def get(self, key, default): return self.data.get(self.convert_key(key), default) def convert_key(self, key): return key.lower()
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0
0
4
db59f047a069feaef47cc2e1dd9486af6e1a4a55
444
py
Python
mysite/MCQ/models.py
PUNITKUMARGAUTAM/mydjango
5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc
[ "MIT" ]
null
null
null
mysite/MCQ/models.py
PUNITKUMARGAUTAM/mydjango
5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc
[ "MIT" ]
null
null
null
mysite/MCQ/models.py
PUNITKUMARGAUTAM/mydjango
5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc
[ "MIT" ]
null
null
null
from django.db import models # Create your models here. class Quiz(models.Model): Qustno=models.CharField(max_length = 300) Qustn = models.CharField(max_length = 200) OptA = models.CharField(max_length = 200) optB = models.CharField(max_length = 200) OptC = models.CharField(max_length = 200) OptD = models.CharField(max_length = 200) RightAns=models.IntegerField() class Meta: db_table="questions"
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4
db5b682a834f3daffca8d2d1292a349c02e706f6
6,230
py
Python
tests/test_utility.py
ccarocean/python-rads
fec1cfccbdafb7e372b66a76132c59f3d2a6beb3
[ "MIT" ]
null
null
null
tests/test_utility.py
ccarocean/python-rads
fec1cfccbdafb7e372b66a76132c59f3d2a6beb3
[ "MIT" ]
3
2019-06-27T19:00:35.000Z
2020-03-07T09:43:24.000Z
tests/test_utility.py
ccarocean/python-rads
fec1cfccbdafb7e372b66a76132c59f3d2a6beb3
[ "MIT" ]
1
2019-05-31T01:04:26.000Z
2019-05-31T01:04:26.000Z
import io from datetime import datetime import pytest # type: ignore from rads.constants import EPOCH from rads.utility import ( contains_sublist, datetime_to_timestamp, delete_sublist, ensure_open, fortran_float, isio, merge_sublist, timestamp_to_datetime, xor, ) def test_ensure_open_closeio_default(): file = io.StringIO("content") with ensure_open(file) as f: assert not f.closed assert not f.closed def test_ensure_open_closeio_true(): file = io.StringIO("content") with ensure_open(file, closeio=True) as f: assert not f.closed assert f.closed def test_ensure_open_closeio_false(): file = io.StringIO("content") with ensure_open(file, closeio=False) as f: assert not f.closed assert not f.closed def test_isio(mocker): assert isio(io.StringIO("content")) assert not isio("string is not io") m = mocker.Mock() m.read.return_value = "duck typing not accepted" assert not isio(m) def test_isio_read(mocker): assert isio(io.StringIO("content"), read=True) assert not isio("string is not io", read=True) m = mocker.Mock(spec=["read"]) m.read.return_value = "duck typing is accepted" assert isio(m, read=True) m = mocker.Mock(spec=["write"]) m.write.return_value = "duck typing is accepted" assert not isio(m, read=True) def test_isio_write(mocker): assert isio(io.StringIO("content"), write=True) assert not isio("string is not io", write=True) m = mocker.Mock(spec=["read"]) m.read.return_value = "duck typing is accepted" assert not isio(m, write=True) m = mocker.Mock(spec=["write"]) m.write.return_value = "duck typing is accepted" assert isio(m, write=True) def test_xor(): assert not xor(True, True) assert xor(True, False) assert xor(False, True) assert not xor(False, False) def test_contains_sublist(): assert contains_sublist([1, 2, 3, 4], [1, 2]) assert contains_sublist([1, 2, 3, 4], [2, 3]) assert contains_sublist([1, 2, 3, 4], [3, 4]) assert contains_sublist([1, 2, 3, 4], [1, 2, 3, 4]) assert not contains_sublist([1, 2, 3, 4], [2, 1]) assert not contains_sublist([1, 2, 3, 4], [3, 2]) assert not contains_sublist([1, 2, 3, 4], [4, 3]) # while the empty list is technically a sublist of any list for this # function [] is never a sublist assert not contains_sublist([1, 2, 3, 4], []) def test_merge_sublist(): assert merge_sublist([1, 2, 3, 4], []) == [1, 2, 3, 4] assert merge_sublist([1, 2, 3, 4], [1, 2]) == [1, 2, 3, 4] assert merge_sublist([1, 2, 3, 4], [2, 3]) == [1, 2, 3, 4] assert merge_sublist([1, 2, 3, 4], [3, 4]) == [1, 2, 3, 4] assert merge_sublist([1, 2, 3, 4], [0, 1]) == [1, 2, 3, 4, 0, 1] assert merge_sublist([1, 2, 3, 4], [4, 5]) == [1, 2, 3, 4, 4, 5] assert merge_sublist([1, 2, 3, 4], [1, 1]) == [1, 2, 3, 4, 1, 1] def test_delete_sublist(): assert delete_sublist([1, 2, 3, 4], []) == [1, 2, 3, 4] assert delete_sublist([1, 2, 3, 4], [1, 2]) == [3, 4] assert delete_sublist([1, 2, 3, 4], [2, 3]) == [1, 4] assert delete_sublist([1, 2, 3, 4], [3, 4]) == [1, 2] assert delete_sublist([1, 2, 3, 4], [0, 1]) == [1, 2, 3, 4] assert delete_sublist([1, 2, 3, 4], [4, 5]) == [1, 2, 3, 4] assert delete_sublist([1, 2, 3, 4], [1, 1]) == [1, 2, 3, 4] def test_fortran_float(): assert fortran_float("3.14e10") == pytest.approx(3.14e10) assert fortran_float("3.14E10") == pytest.approx(3.14e10) assert fortran_float("3.14d10") == pytest.approx(3.14e10) assert fortran_float("3.14D10") == pytest.approx(3.14e10) assert fortran_float("3.14e+10") == pytest.approx(3.14e10) assert fortran_float("3.14E+10") == pytest.approx(3.14e10) assert fortran_float("3.14d+10") == pytest.approx(3.14e10) assert fortran_float("3.14D+10") == pytest.approx(3.14e10) assert fortran_float("3.14e-10") == pytest.approx(3.14e-10) assert fortran_float("3.14E-10") == pytest.approx(3.14e-10) assert fortran_float("3.14d-10") == pytest.approx(3.14e-10) assert fortran_float("3.14D-10") == pytest.approx(3.14e-10) assert fortran_float("3.14+100") == pytest.approx(3.14e100) assert fortran_float("3.14-100") == pytest.approx(3.14e-100) with pytest.raises(ValueError): fortran_float("not a float") def test_datetime_to_epoch(): epoch = datetime(2000, 1, 1, 0, 0, 0) assert datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 0), epoch=epoch) == 0.0 assert datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 1), epoch=epoch) == 1.0 assert datetime_to_timestamp(datetime(2000, 1, 1, 0, 1, 0), epoch=epoch) == 60.0 assert datetime_to_timestamp(datetime(2000, 1, 1, 1, 0, 0), epoch=epoch) == 3600.0 def test_datetime_to_epoch_with_default_epoch(): assert datetime_to_timestamp( datetime(2000, 1, 1, 0, 0, 0) ) == datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 0), epoch=EPOCH) assert datetime_to_timestamp( datetime(2000, 1, 1, 0, 0, 1) ) == datetime_to_timestamp(datetime(2000, 1, 1, 0, 0, 1), epoch=EPOCH) assert datetime_to_timestamp( datetime(2000, 1, 1, 0, 1, 0) ) == datetime_to_timestamp(datetime(2000, 1, 1, 0, 1, 0), epoch=EPOCH) assert datetime_to_timestamp( datetime(2000, 1, 1, 1, 0, 0) ) == datetime_to_timestamp(datetime(2000, 1, 1, 1, 0, 0), epoch=EPOCH) def test_epoch_to_datetime(): epoch = datetime(2000, 1, 1, 0, 0, 0) assert timestamp_to_datetime(0.0, epoch=epoch) == datetime(2000, 1, 1, 0, 0, 0) assert timestamp_to_datetime(1.0, epoch=epoch) == datetime(2000, 1, 1, 0, 0, 1) assert timestamp_to_datetime(60.0, epoch=epoch) == datetime(2000, 1, 1, 0, 1, 0) assert timestamp_to_datetime(3600.0, epoch=epoch) == datetime(2000, 1, 1, 1, 0, 0) def test_epoch_to_datetime_with_default_epoch(): assert timestamp_to_datetime(0.0) == timestamp_to_datetime(0.0, epoch=EPOCH) assert timestamp_to_datetime(1.0) == timestamp_to_datetime(1.0, epoch=EPOCH) assert timestamp_to_datetime(60.0) == timestamp_to_datetime(60.0, epoch=EPOCH) assert timestamp_to_datetime(3600.0) == timestamp_to_datetime(3600.0, epoch=EPOCH)
37.53012
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4
db63d7ed6fba86eb8197753f23124f154ca4fa78
250
py
Python
slickqaweb/model/resultReference.py
slickqa/slickqaweb
3d8ec25d9febc573e67eb4e91f7b6015d7ad6a68
[ "Apache-2.0" ]
null
null
null
slickqaweb/model/resultReference.py
slickqa/slickqaweb
3d8ec25d9febc573e67eb4e91f7b6015d7ad6a68
[ "Apache-2.0" ]
9
2015-12-17T18:24:17.000Z
2018-09-28T16:00:30.000Z
slickqaweb/model/resultReference.py
slickqa/slickqaweb
3d8ec25d9febc573e67eb4e91f7b6015d7ad6a68
[ "Apache-2.0" ]
2
2015-12-17T18:45:20.000Z
2018-02-01T21:05:13.000Z
from mongoengine import * from .buildReference import BuildReference class ResultReference(EmbeddedDocument): resultId = ObjectIdField() status = StringField() recorded = DateTimeField() build = EmbeddedDocumentField(BuildReference)
27.777778
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4
db916c5f423bccd241aa08c3611f223d862ad934
7,010
py
Python
pysnmp-with-texts/DELL-WLAN-MIB.py
agustinhenze/mibs.snmplabs.com
1fc5c07860542b89212f4c8ab807057d9a9206c7
[ "Apache-2.0" ]
8
2019-05-09T17:04:00.000Z
2021-06-09T06:50:51.000Z
pysnmp-with-texts/DELL-WLAN-MIB.py
agustinhenze/mibs.snmplabs.com
1fc5c07860542b89212f4c8ab807057d9a9206c7
[ "Apache-2.0" ]
4
2019-05-31T16:42:59.000Z
2020-01-31T21:57:17.000Z
pysnmp-with-texts/DELL-WLAN-MIB.py
agustinhenze/mibs.snmplabs.com
1fc5c07860542b89212f4c8ab807057d9a9206c7
[ "Apache-2.0" ]
10
2019-04-30T05:51:36.000Z
2022-02-16T03:33:41.000Z
# # PySNMP MIB module DELL-WLAN-MIB (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/DELL-WLAN-MIB # Produced by pysmi-0.3.4 at Wed May 1 12:38:17 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # OctetString, ObjectIdentifier, Integer = mibBuilder.importSymbols("ASN1", "OctetString", "ObjectIdentifier", "Integer") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ValueSizeConstraint, ValueRangeConstraint, ConstraintsUnion, SingleValueConstraint, ConstraintsIntersection = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueSizeConstraint", "ValueRangeConstraint", "ConstraintsUnion", "SingleValueConstraint", "ConstraintsIntersection") ModuleCompliance, ObjectGroup, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ModuleCompliance", "ObjectGroup", "NotificationGroup") Counter64, MibScalar, MibTable, MibTableRow, MibTableColumn, snmpModules, TimeTicks, ObjectIdentity, ModuleIdentity, Unsigned32, iso, enterprises, Integer32, IpAddress, NotificationType, MibIdentifier, Counter32, Gauge32, Bits = mibBuilder.importSymbols("SNMPv2-SMI", "Counter64", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "snmpModules", "TimeTicks", "ObjectIdentity", "ModuleIdentity", "Unsigned32", "iso", "enterprises", "Integer32", "IpAddress", "NotificationType", "MibIdentifier", "Counter32", "Gauge32", "Bits") DisplayString, TextualConvention = mibBuilder.importSymbols("SNMPv2-TC", "DisplayString", "TextualConvention") dell = MibIdentifier((1, 3, 6, 1, 4, 1, 674)) powerConnect = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895)) w_650 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5001)).setLabel("w-650") w_651 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5002)).setLabel("w-651") w_3200 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5003)).setLabel("w-3200") w_3400 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5004)).setLabel("w-3400") w_3600 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5005)).setLabel("w-3600") w_AP92 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5006)).setLabel("w-AP92") w_AP93 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5007)).setLabel("w-AP93") w_AP105 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5008)).setLabel("w-AP105") w_AP124 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5009)).setLabel("w-AP124") w_AP125 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5010)).setLabel("w-AP125") w_RAP5 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5011)).setLabel("w-RAP5") w_RAP5WN = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5012)).setLabel("w-RAP5WN") w_RAP2 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5013)).setLabel("w-RAP2") w_620 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5014)).setLabel("w-620") w_6000M3 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5015)).setLabel("w-6000M3") w_7210 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5027)).setLabel("w-7210") w_7220 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5028)).setLabel("w-7220") w_7240 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5029)).setLabel("w-7240") w_7005 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5043)).setLabel("w-7005") w_7010 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5044)).setLabel("w-7010") w_7030 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5049)).setLabel("w-7030") w_7205 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5050)).setLabel("w-7205") w_7024 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5051)).setLabel("w-7024") w_AP68 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5016)).setLabel("w-AP68") w_AP68P = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5017)).setLabel("w-AP68P") w_AP175P = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5018)).setLabel("w-AP175P") w_AP175AC = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5019)).setLabel("w-AP175AC") w_AP175DC = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5020)).setLabel("w-AP175DC") w_AP134 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5021)).setLabel("w-AP134") w_AP135 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5022)).setLabel("w-AP135") w_AP93H = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5023)).setLabel("w-AP93H") w_AP104 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5024)).setLabel("w-AP104") w_IAP3WN = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5025)).setLabel("w-IAP3WN") w_IAP3WNP = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5026)).setLabel("w-IAP3WNP") w_IAP108 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5031)).setLabel("w-IAP108") w_IAP109 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5032)).setLabel("w-IAP109") w_AP224 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5033)).setLabel("w-AP224") w_AP225 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5034)).setLabel("w-AP225") w_IAP155 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5035)).setLabel("w-IAP155") w_IAP155P = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5036)).setLabel("w-IAP155P") w_AP114 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5037)).setLabel("w-AP114") w_AP115 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5038)).setLabel("w-AP115") w_AP274 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5039)).setLabel("w-AP274") w_AP275 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5040)).setLabel("w-AP275") w_AP277 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5052)).setLabel("w-AP277") w_AP228 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5054)).setLabel("w-AP228") w_AP103 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5045)).setLabel("w-AP103") w_AP103H = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5046)).setLabel("w-AP103H") w_AP204 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5047)).setLabel("w-AP204") w_AP205 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5048)).setLabel("w-AP205") w_AP205H = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5055)).setLabel("w-AP205H") w_AP214 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5041)).setLabel("w-AP214") w_AP215 = MibIdentifier((1, 3, 6, 1, 4, 1, 674, 10895, 5042)).setLabel("w-AP215") mibBuilder.exportSymbols("DELL-WLAN-MIB", w_AP175P=w_AP175P, w_AP68P=w_AP68P, w_AP205=w_AP205, w_7240=w_7240, w_AP225=w_AP225, powerConnect=powerConnect, w_6000M3=w_6000M3, w_7030=w_7030, w_7024=w_7024, w_AP224=w_AP224, w_3200=w_3200, w_AP134=w_AP134, w_7220=w_7220, w_AP124=w_AP124, w_AP204=w_AP204, w_3600=w_3600, w_AP215=w_AP215, w_AP92=w_AP92, w_7005=w_7005, w_AP93H=w_AP93H, w_AP105=w_AP105, w_AP103H=w_AP103H, w_620=w_620, w_AP104=w_AP104, w_IAP155=w_IAP155, w_RAP2=w_RAP2, w_AP115=w_AP115, w_RAP5=w_RAP5, w_AP125=w_AP125, w_IAP109=w_IAP109, w_IAP155P=w_IAP155P, w_AP214=w_AP214, w_AP135=w_AP135, w_AP228=w_AP228, w_IAP108=w_IAP108, w_7210=w_7210, w_IAP3WN=w_IAP3WN, w_AP93=w_AP93, dell=dell, w_IAP3WNP=w_IAP3WNP, w_650=w_650, w_AP68=w_AP68, w_651=w_651, w_AP277=w_AP277, w_AP274=w_AP274, w_AP205H=w_AP205H, w_AP275=w_AP275, w_3400=w_3400, w_7010=w_7010, w_AP175AC=w_AP175AC, w_AP175DC=w_AP175DC, w_AP114=w_AP114, w_RAP5WN=w_RAP5WN, w_7205=w_7205, w_AP103=w_AP103)
100.142857
970
0.694294
1,189
7,010
3.95963
0.170732
0.163551
0.175234
0.186916
0.437128
0.395072
0.395072
0.395072
0.390399
0.080714
0
0.268582
0.111412
7,010
69
971
101.594203
0.487237
0.045649
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0.127526
0.006586
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false
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0.096774
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0.096774
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null
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0
0
0
0
0
0
4
db92df0d69a2d192ad0f19f8107908c80e36c29e
149
py
Python
example/models.py
hbielenia/csv-mapper
1f39bb2f02395be2ca66654030cffe2c5790808e
[ "Unlicense" ]
null
null
null
example/models.py
hbielenia/csv-mapper
1f39bb2f02395be2ca66654030cffe2c5790808e
[ "Unlicense" ]
null
null
null
example/models.py
hbielenia/csv-mapper
1f39bb2f02395be2ca66654030cffe2c5790808e
[ "Unlicense" ]
null
null
null
from .fields import * from .mapper import Model class Person(Model): name = StringField() height_cm = IntegerField() salary = DecimalField()
16.555556
28
0.718121
17
149
6.235294
0.823529
0
0
0
0
0
0
0
0
0
0
0
0.181208
149
8
29
18.625
0.868852
0
0
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0
0
0
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0
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1
0
false
0
0.333333
0
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1
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null
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0
0
1
0
1
0
0
4
db9c76e4cba1c2f10f2b00a27b67c15c23397f9a
649
py
Python
2017/day01/test_captcha.py
kgaughan/aoc
ffd1d8f28adb3b5b61da15402fb6ca489b9025b0
[ "BSD-3-Clause" ]
null
null
null
2017/day01/test_captcha.py
kgaughan/aoc
ffd1d8f28adb3b5b61da15402fb6ca489b9025b0
[ "BSD-3-Clause" ]
null
null
null
2017/day01/test_captcha.py
kgaughan/aoc
ffd1d8f28adb3b5b61da15402fb6ca489b9025b0
[ "BSD-3-Clause" ]
null
null
null
#!/usr/bin/env python3 import unittest import captcha class CaptchaTests(unittest.TestCase): def test_part1(self): self.assertEqual(captcha.captcha1('1122'), 3) self.assertEqual(captcha.captcha1('1111'), 4) self.assertEqual(captcha.captcha1('1234'), 0) self.assertEqual(captcha.captcha1('91212129'), 9) def test_part2(self): self.assertEqual(captcha.captcha2('1212'), 6) self.assertEqual(captcha.captcha2('1221'), 0) self.assertEqual(captcha.captcha2('123425'), 4) self.assertEqual(captcha.captcha2('123123'), 12) self.assertEqual(captcha.captcha2('12131415'), 4)
30.904762
57
0.674884
74
649
5.891892
0.445946
0.309633
0.454128
0.344037
0
0
0
0
0
0
0
0.131086
0.177196
649
20
58
32.45
0.685393
0.032357
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0.076555
0
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0
0.642857
1
0.142857
false
0
0.142857
0
0.357143
0
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null
1
1
1
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null
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0
0
0
0
0
0
0
4
918a513549337d8cbfd0e41813480d00a393f8d5
217
py
Python
Files/Python/puntajes_03/puntajes_03.py
Souto751/isft151-base-de-datos
639e2d2f32e5d1cdb8308d1e67e37967a45759a5
[ "MIT" ]
null
null
null
Files/Python/puntajes_03/puntajes_03.py
Souto751/isft151-base-de-datos
639e2d2f32e5d1cdb8308d1e67e37967a45759a5
[ "MIT" ]
null
null
null
Files/Python/puntajes_03/puntajes_03.py
Souto751/isft151-base-de-datos
639e2d2f32e5d1cdb8308d1e67e37967a45759a5
[ "MIT" ]
null
null
null
import puntajes_csv valores = [("Pepe", 108, "4:16"), ("Juana", 2315, "8:42")] puntajes_csv.guardar_puntajes("puntajes.dat", valores) recuperado = puntajes_csv.recuperar_puntajes("puntajes.dat") print(recuperado)
36.166667
60
0.732719
28
217
5.5
0.607143
0.214286
0.246753
0
0
0
0
0
0
0
0
0.06599
0.092166
217
6
61
36.166667
0.715736
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0.188073
0
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null
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0
0
0
0
0
0
0
0
4
91bd074c51494e76a866a7ffdbc55fc0f1c0f09b
68
py
Python
phonon_tools_VASP/__init__.py
benwmcdowell/phonon_tools_VASP
c31d12b59d838a9078b0bbd2e284b48c45d27dc9
[ "MIT" ]
2
2021-03-19T16:03:52.000Z
2021-03-24T03:24:16.000Z
phonon_tools_VASP/__init__.py
benwmcdowell/phonon_tools_VASP
c31d12b59d838a9078b0bbd2e284b48c45d27dc9
[ "MIT" ]
null
null
null
phonon_tools_VASP/__init__.py
benwmcdowell/phonon_tools_VASP
c31d12b59d838a9078b0bbd2e284b48c45d27dc9
[ "MIT" ]
null
null
null
### methods for analyzing and manipulating phonon modes in VASP ###
34
67
0.75
9
68
5.666667
1
0
0
0
0
0
0
0
0
0
0
0
0.161765
68
1
68
68
0.894737
0.867647
0
null
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null
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null
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null
1
null
true
0
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null
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0
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1
0
0
0
0
0
0
4
91cceba0c7b32fb937b692f79ad3461f1cfed8d7
68
py
Python
testping.py
operationzombie/apache-base
d1fe8edd665728ab4437f162236a3e865a94942c
[ "MIT" ]
null
null
null
testping.py
operationzombie/apache-base
d1fe8edd665728ab4437f162236a3e865a94942c
[ "MIT" ]
null
null
null
testping.py
operationzombie/apache-base
d1fe8edd665728ab4437f162236a3e865a94942c
[ "MIT" ]
null
null
null
import serial, time ser2 = serial.Serial('COM2') print ser2.read(5)
17
28
0.735294
11
68
4.545455
0.727273
0
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0.066667
0.117647
68
4
29
17
0.766667
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