xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

2c50ed4e48f58d35c3ae963dcdc2c5876f1cb1b6

64

py

Python

neuro_pypes/convert/__init__.py

Neurita/pypes

e88d27ebba842e8fa1f36b52ca12a0b9d5777e89

[ "Apache-2.0" ]

14

2015-11-30T19:32:08.000Z

2021-11-16T05:35:20.000Z

neuro_pypes/convert/__init__.py

Neurita/pypes

e88d27ebba842e8fa1f36b52ca12a0b9d5777e89

[ "Apache-2.0" ]

42

2015-11-28T23:18:42.000Z

2021-02-23T01:45:02.000Z

neuro_pypes/convert/__init__.py

Neurita/pypes

e88d27ebba842e8fa1f36b52ca12a0b9d5777e89

[ "Apache-2.0" ]

9

2015-12-09T17:10:59.000Z

2022-01-03T17:26:40.000Z

from neuro_pypes.convert.dicom_to_nifti import attach_dcm2niix

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2c5ffc02ab03d463d3c11e15028765df29c0732c

154

py

Python

learning-python/src/comments.py

learning-software-development/packt-publishing-tutorials

625618d9eff8d108645e1f4035ef1b00869d12af

[ "Unlicense" ]

null

learning-python/src/comments.py

learning-software-development/packt-publishing-tutorials

625618d9eff8d108645e1f4035ef1b00869d12af

[ "Unlicense" ]

null

learning-python/src/comments.py

learning-software-development/packt-publishing-tutorials

625618d9eff8d108645e1f4035ef1b00869d12af

[ "Unlicense" ]

null

# This is a single line comment in Python print("Hello World!") # This is a single comment """ For multi-line comments use three double quotes ... """

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92,333

py

Python

boto3_type_annotations_with_docs/boto3_type_annotations/opsworkscm/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

119

2018-12-01T18:20:57.000Z

2022-02-02T10:31:29.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/opsworkscm/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

15

2018-11-16T00:16:44.000Z

2021-11-13T03:44:18.000Z

boto3_type_annotations_with_docs/boto3_type_annotations/opsworkscm/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

11

2019-05-06T05:26:51.000Z

2021-09-28T15:27:59.000Z

from typing import Optional from botocore.client import BaseClient from typing import Dict from botocore.paginate import Paginator from botocore.waiter import Waiter from typing import Union from typing import List class Client(BaseClient): def associate_node(self, ServerName: str, NodeName: str, EngineAttributes: List) -> Dict: """ Associates a new node with the server. For more information about how to disassociate a node, see DisassociateNode . On a Chef server: This command is an alternative to ``knife bootstrap`` . Example (Chef): ``aws opsworks-cm associate-node --server-name *MyServer* --node-name *MyManagedNode* --engine-attributes "Name=*CHEF_ORGANIZATION* ,Value=default" "Name=*CHEF_NODE_PUBLIC_KEY* ,Value=*public-key-pem* "`` On a Puppet server, this command is an alternative to the ``puppet cert sign`` command that signs a Puppet node CSR. Example (Chef): ``aws opsworks-cm associate-node --server-name *MyServer* --node-name *MyManagedNode* --engine-attributes "Name=*PUPPET_NODE_CSR* ,Value=*csr-pem* "`` A node can can only be associated with servers that are in a ``HEALTHY`` state. Otherwise, an ``InvalidStateException`` is thrown. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. The AssociateNode API call can be integrated into Auto Scaling configurations, AWS Cloudformation templates, or the user data of a server's instance. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/AssociateNode>`_ **Request Syntax** :: response = client.associate_node( ServerName='string', NodeName='string', EngineAttributes=[ { 'Name': 'string', 'Value': 'string' }, ] ) **Response Syntax** :: { 'NodeAssociationStatusToken': 'string' } **Response Structure** - *(dict) --* - **NodeAssociationStatusToken** *(string) --* Contains a token which can be passed to the ``DescribeNodeAssociationStatus`` API call to get the status of the association request. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server with which to associate the node. :type NodeName: string :param NodeName: **[REQUIRED]** The name of the node. :type EngineAttributes: list :param EngineAttributes: **[REQUIRED]** Engine attributes used for associating the node. **Attributes accepted in a AssociateNode request for Chef** * ``CHEF_ORGANIZATION`` : The Chef organization with which the node is associated. By default only one organization named ``default`` can exist. * ``CHEF_NODE_PUBLIC_KEY`` : A PEM-formatted public key. This key is required for the ``chef-client`` agent to access the Chef API. **Attributes accepted in a AssociateNode request for Puppet** * ``PUPPET_NODE_CSR`` : A PEM-formatted certificate-signing request (CSR) that is created by the node. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. :rtype: dict :returns: """ pass def can_paginate(self, operation_name: str = None): """ Check if an operation can be paginated. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :return: ``True`` if the operation can be paginated, ``False`` otherwise. """ pass def create_backup(self, ServerName: str, Description: str = None) -> Dict: """ Creates an application-level backup of a server. While the server is in the ``BACKING_UP`` state, the server cannot be changed, and no additional backup can be created. Backups can be created for servers in ``RUNNING`` , ``HEALTHY`` , and ``UNHEALTHY`` states. By default, you can create a maximum of 50 manual backups. This operation is asynchronous. A ``LimitExceededException`` is thrown when the maximum number of manual backups is reached. An ``InvalidStateException`` is thrown when the server is not in any of the following states: RUNNING, HEALTHY, or UNHEALTHY. A ``ResourceNotFoundException`` is thrown when the server is not found. A ``ValidationException`` is thrown when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/CreateBackup>`_ **Request Syntax** :: response = client.create_backup( ServerName='string', Description='string' ) **Response Syntax** :: { 'Backup': { 'BackupArn': 'string', 'BackupId': 'string', 'BackupType': 'AUTOMATED'|'MANUAL', 'CreatedAt': datetime(2015, 1, 1), 'Description': 'string', 'Engine': 'string', 'EngineModel': 'string', 'EngineVersion': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'KeyPair': 'string', 'PreferredBackupWindow': 'string', 'PreferredMaintenanceWindow': 'string', 'S3DataSize': 123, 'S3DataUrl': 'string', 'S3LogUrl': 'string', 'SecurityGroupIds': [ 'string', ], 'ServerName': 'string', 'ServiceRoleArn': 'string', 'Status': 'IN_PROGRESS'|'OK'|'FAILED'|'DELETING', 'StatusDescription': 'string', 'SubnetIds': [ 'string', ], 'ToolsVersion': 'string', 'UserArn': 'string' } } **Response Structure** - *(dict) --* - **Backup** *(dict) --* Backup created by request. - **BackupArn** *(string) --* The ARN of the backup. - **BackupId** *(string) --* The generated ID of the backup. Example: ``myServerName-yyyyMMddHHmmssSSS`` - **BackupType** *(string) --* The backup type. Valid values are ``automated`` or ``manual`` . - **CreatedAt** *(datetime) --* The time stamp when the backup was created in the database. Example: ``2016-07-29T13:38:47.520Z`` - **Description** *(string) --* A user-provided description for a manual backup. This field is empty for automated backups. - **Engine** *(string) --* The engine type that is obtained from the server when the backup is created. - **EngineModel** *(string) --* The engine model that is obtained from the server when the backup is created. - **EngineVersion** *(string) --* The engine version that is obtained from the server when the backup is created. - **InstanceProfileArn** *(string) --* The EC2 instance profile ARN that is obtained from the server when the backup is created. Because this value is stored, you are not required to provide the InstanceProfileArn again if you restore a backup. - **InstanceType** *(string) --* The instance type that is obtained from the server when the backup is created. - **KeyPair** *(string) --* The key pair that is obtained from the server when the backup is created. - **PreferredBackupWindow** *(string) --* The preferred backup period that is obtained from the server when the backup is created. - **PreferredMaintenanceWindow** *(string) --* The preferred maintenance period that is obtained from the server when the backup is created. - **S3DataSize** *(integer) --* This field is deprecated and is no longer used. - **S3DataUrl** *(string) --* This field is deprecated and is no longer used. - **S3LogUrl** *(string) --* The Amazon S3 URL of the backup's log file. - **SecurityGroupIds** *(list) --* The security group IDs that are obtained from the server when the backup is created. - *(string) --* - **ServerName** *(string) --* The name of the server from which the backup was made. - **ServiceRoleArn** *(string) --* The service role ARN that is obtained from the server when the backup is created. - **Status** *(string) --* The status of a backup while in progress. - **StatusDescription** *(string) --* An informational message about backup status. - **SubnetIds** *(list) --* The subnet IDs that are obtained from the server when the backup is created. - *(string) --* - **ToolsVersion** *(string) --* The version of AWS OpsWorks CM-specific tools that is obtained from the server when the backup is created. - **UserArn** *(string) --* The IAM user ARN of the requester for manual backups. This field is empty for automated backups. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server that you want to back up. :type Description: string :param Description: A user-defined description of the backup. :rtype: dict :returns: """ pass def create_server(self, ServerName: str, InstanceProfileArn: str, InstanceType: str, ServiceRoleArn: str, AssociatePublicIpAddress: bool = None, DisableAutomatedBackup: bool = None, Engine: str = None, EngineModel: str = None, EngineVersion: str = None, EngineAttributes: List = None, BackupRetentionCount: int = None, KeyPair: str = None, PreferredMaintenanceWindow: str = None, PreferredBackupWindow: str = None, SecurityGroupIds: List = None, SubnetIds: List = None, BackupId: str = None) -> Dict: """ Creates and immedately starts a new server. The server is ready to use when it is in the ``HEALTHY`` state. By default, you can create a maximum of 10 servers. This operation is asynchronous. A ``LimitExceededException`` is thrown when you have created the maximum number of servers (10). A ``ResourceAlreadyExistsException`` is thrown when a server with the same name already exists in the account. A ``ResourceNotFoundException`` is thrown when you specify a backup ID that is not valid or is for a backup that does not exist. A ``ValidationException`` is thrown when parameters of the request are not valid. If you do not specify a security group by adding the ``SecurityGroupIds`` parameter, AWS OpsWorks creates a new security group. *Chef Automate:* The default security group opens the Chef server to the world on TCP port 443. If a KeyName is present, AWS OpsWorks enables SSH access. SSH is also open to the world on TCP port 22. *Puppet Enterprise:* The default security group opens TCP ports 22, 443, 4433, 8140, 8142, 8143, and 8170. If a KeyName is present, AWS OpsWorks enables SSH access. SSH is also open to the world on TCP port 22. By default, your server is accessible from any IP address. We recommend that you update your security group rules to allow access from known IP addresses and address ranges only. To edit security group rules, open Security Groups in the navigation pane of the EC2 management console. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/CreateServer>`_ **Request Syntax** :: response = client.create_server( AssociatePublicIpAddress=True|False, DisableAutomatedBackup=True|False, Engine='string', EngineModel='string', EngineVersion='string', EngineAttributes=[ { 'Name': 'string', 'Value': 'string' }, ], BackupRetentionCount=123, ServerName='string', InstanceProfileArn='string', InstanceType='string', KeyPair='string', PreferredMaintenanceWindow='string', PreferredBackupWindow='string', SecurityGroupIds=[ 'string', ], ServiceRoleArn='string', SubnetIds=[ 'string', ], BackupId='string' ) **Response Syntax** :: { 'Server': { 'AssociatePublicIpAddress': True|False, 'BackupRetentionCount': 123, 'ServerName': 'string', 'CreatedAt': datetime(2015, 1, 1), 'CloudFormationStackArn': 'string', 'DisableAutomatedBackup': True|False, 'Endpoint': 'string', 'Engine': 'string', 'EngineModel': 'string', 'EngineAttributes': [ { 'Name': 'string', 'Value': 'string' }, ], 'EngineVersion': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'KeyPair': 'string', 'MaintenanceStatus': 'SUCCESS'|'FAILED', 'PreferredMaintenanceWindow': 'string', 'PreferredBackupWindow': 'string', 'SecurityGroupIds': [ 'string', ], 'ServiceRoleArn': 'string', 'Status': 'BACKING_UP'|'CONNECTION_LOST'|'CREATING'|'DELETING'|'MODIFYING'|'FAILED'|'HEALTHY'|'RUNNING'|'RESTORING'|'SETUP'|'UNDER_MAINTENANCE'|'UNHEALTHY'|'TERMINATED', 'StatusReason': 'string', 'SubnetIds': [ 'string', ], 'ServerArn': 'string' } } **Response Structure** - *(dict) --* - **Server** *(dict) --* The server that is created by the request. - **AssociatePublicIpAddress** *(boolean) --* Associate a public IP address with a server that you are launching. - **BackupRetentionCount** *(integer) --* The number of automated backups to keep. - **ServerName** *(string) --* The name of the server. - **CreatedAt** *(datetime) --* Time stamp of server creation. Example ``2016-07-29T13:38:47.520Z`` - **CloudFormationStackArn** *(string) --* The ARN of the CloudFormation stack that was used to create the server. - **DisableAutomatedBackup** *(boolean) --* Disables automated backups. The number of stored backups is dependent on the value of PreferredBackupCount. - **Endpoint** *(string) --* A DNS name that can be used to access the engine. Example: ``myserver-asdfghjkl.us-east-1.opsworks.io`` - **Engine** *(string) --* The engine type of the server. Valid values in this release include ``Chef`` and ``Puppet`` . - **EngineModel** *(string) --* The engine model of the server. Valid values in this release include ``Monolithic`` for Puppet and ``Single`` for Chef. - **EngineAttributes** *(list) --* The response of a createServer() request returns the master credential to access the server in EngineAttributes. These credentials are not stored by AWS OpsWorks CM; they are returned only as part of the result of createServer(). **Attributes returned in a createServer response for Chef** * ``CHEF_PIVOTAL_KEY`` : A base64-encoded RSA private key that is generated by AWS OpsWorks for Chef Automate. This private key is required to access the Chef API. * ``CHEF_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Chef starter kit, which includes a README, a configuration file, and the required RSA private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. From this directory, you can run Knife commands. **Attributes returned in a createServer response for Puppet** * ``PUPPET_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Puppet starter kit, including a README and a required private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. * ``PUPPET_ADMIN_PASSWORD`` : An administrator password that you can use to sign in to the Puppet Enterprise console after the server is online. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. - **EngineVersion** *(string) --* The engine version of the server. For a Chef server, the valid value for EngineVersion is currently ``12`` . For a Puppet server, the valid value is ``2017`` . - **InstanceProfileArn** *(string) --* The instance profile ARN of the server. - **InstanceType** *(string) --* The instance type for the server, as specified in the CloudFormation stack. This might not be the same instance type that is shown in the EC2 console. - **KeyPair** *(string) --* The key pair associated with the server. - **MaintenanceStatus** *(string) --* The status of the most recent server maintenance run. Shows ``SUCCESS`` or ``FAILED`` . - **PreferredMaintenanceWindow** *(string) --* The preferred maintenance period specified for the server. - **PreferredBackupWindow** *(string) --* The preferred backup period specified for the server. - **SecurityGroupIds** *(list) --* The security group IDs for the server, as specified in the CloudFormation stack. These might not be the same security groups that are shown in the EC2 console. - *(string) --* - **ServiceRoleArn** *(string) --* The service role ARN used to create the server. - **Status** *(string) --* The server's status. This field displays the states of actions in progress, such as creating, running, or backing up the server, as well as the server's health state. - **StatusReason** *(string) --* Depending on the server status, this field has either a human-readable message (such as a create or backup error), or an escaped block of JSON (used for health check results). - **SubnetIds** *(list) --* The subnet IDs specified in a CreateServer request. - *(string) --* - **ServerArn** *(string) --* The ARN of the server. :type AssociatePublicIpAddress: boolean :param AssociatePublicIpAddress: Associate a public IP address with a server that you are launching. Valid values are ``true`` or ``false`` . The default value is ``true`` . :type DisableAutomatedBackup: boolean :param DisableAutomatedBackup: Enable or disable scheduled backups. Valid values are ``true`` or ``false`` . The default value is ``true`` . :type Engine: string :param Engine: The configuration management engine to use. Valid values include ``Chef`` and ``Puppet`` . :type EngineModel: string :param EngineModel: The engine model of the server. Valid values in this release include ``Monolithic`` for Puppet and ``Single`` for Chef. :type EngineVersion: string :param EngineVersion: The major release version of the engine that you want to use. For a Chef server, the valid value for EngineVersion is currently ``12`` . For a Puppet server, the valid value is ``2017`` . :type EngineAttributes: list :param EngineAttributes: Optional engine attributes on a specified server. **Attributes accepted in a Chef createServer request:** * ``CHEF_PIVOTAL_KEY`` : A base64-encoded RSA public key. The corresponding private key is required to access the Chef API. When no CHEF_PIVOTAL_KEY is set, a private key is generated and returned in the response. * ``CHEF_DELIVERY_ADMIN_PASSWORD`` : The password for the administrative user in the Chef Automate GUI. The password length is a minimum of eight characters, and a maximum of 32. The password can contain letters, numbers, and special characters (!/@#$%^&+=_). The password must contain at least one lower case letter, one upper case letter, one number, and one special character. When no CHEF_DELIVERY_ADMIN_PASSWORD is set, one is generated and returned in the response. **Attributes accepted in a Puppet createServer request:** * ``PUPPET_ADMIN_PASSWORD`` : To work with the Puppet Enterprise console, a password must use ASCII characters. * ``PUPPET_R10K_REMOTE`` : The r10k remote is the URL of your control repository (for example, ssh://git@your.git-repo.com:user/control-repo.git). Specifying an r10k remote opens TCP port 8170. * ``PUPPET_R10K_PRIVATE_KEY`` : If you are using a private Git repository, add PUPPET_R10K_PRIVATE_KEY to specify an SSH URL and a PEM-encoded private SSH key. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. :type BackupRetentionCount: integer :param BackupRetentionCount: The number of automated backups that you want to keep. Whenever a new backup is created, AWS OpsWorks CM deletes the oldest backups if this number is exceeded. The default value is ``1`` . :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server. The server name must be unique within your AWS account, within each region. Server names must start with a letter; then letters, numbers, or hyphens (-) are allowed, up to a maximum of 40 characters. :type InstanceProfileArn: string :param InstanceProfileArn: **[REQUIRED]** The ARN of the instance profile that your Amazon EC2 instances use. Although the AWS OpsWorks console typically creates the instance profile for you, if you are using API commands instead, run the service-role-creation.yaml AWS CloudFormation template, located at https://s3.amazonaws.com/opsworks-cm-us-east-1-prod-default-assets/misc/opsworks-cm-roles.yaml. This template creates a CloudFormation stack that includes the instance profile you need. :type InstanceType: string :param InstanceType: **[REQUIRED]** The Amazon EC2 instance type to use. For example, ``m4.large`` . Recommended instance types include ``t2.medium`` and greater, ``m4.*`` , or ``c4.xlarge`` and greater. :type KeyPair: string :param KeyPair: The Amazon EC2 key pair to set for the instance. This parameter is optional; if desired, you may specify this parameter to connect to your instances by using SSH. :type PreferredMaintenanceWindow: string :param PreferredMaintenanceWindow: The start time for a one-hour period each week during which AWS OpsWorks CM performs maintenance on the instance. Valid values must be specified in the following format: ``DDD:HH:MM`` . The specified time is in coordinated universal time (UTC). The default value is a random one-hour period on Tuesday, Wednesday, or Friday. See ``TimeWindowDefinition`` for more information. **Example:** ``Mon:08:00`` , which represents a start time of every Monday at 08:00 UTC. (8:00 a.m.) :type PreferredBackupWindow: string :param PreferredBackupWindow: The start time for a one-hour period during which AWS OpsWorks CM backs up application-level data on your server if automated backups are enabled. Valid values must be specified in one of the following formats: * ``HH:MM`` for daily backups * ``DDD:HH:MM`` for weekly backups The specified time is in coordinated universal time (UTC). The default value is a random, daily start time. **Example:** ``08:00`` , which represents a daily start time of 08:00 UTC. **Example:** ``Mon:08:00`` , which represents a start time of every Monday at 08:00 UTC. (8:00 a.m.) :type SecurityGroupIds: list :param SecurityGroupIds: A list of security group IDs to attach to the Amazon EC2 instance. If you add this parameter, the specified security groups must be within the VPC that is specified by ``SubnetIds`` . If you do not specify this parameter, AWS OpsWorks CM creates one new security group that uses TCP ports 22 and 443, open to 0.0.0.0/0 (everyone). - *(string) --* :type ServiceRoleArn: string :param ServiceRoleArn: **[REQUIRED]** The service role that the AWS OpsWorks CM service backend uses to work with your account. Although the AWS OpsWorks management console typically creates the service role for you, if you are using the AWS CLI or API commands, run the service-role-creation.yaml AWS CloudFormation template, located at https://s3.amazonaws.com/opsworks-cm-us-east-1-prod-default-assets/misc/opsworks-cm-roles.yaml. This template creates a CloudFormation stack that includes the service role and instance profile that you need. :type SubnetIds: list :param SubnetIds: The IDs of subnets in which to launch the server EC2 instance. Amazon EC2-Classic customers: This field is required. All servers must run within a VPC. The VPC must have \"Auto Assign Public IP\" enabled. EC2-VPC customers: This field is optional. If you do not specify subnet IDs, your EC2 instances are created in a default subnet that is selected by Amazon EC2. If you specify subnet IDs, the VPC must have \"Auto Assign Public IP\" enabled. For more information about supported Amazon EC2 platforms, see `Supported Platforms <https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-supported-platforms.html>`__ . - *(string) --* :type BackupId: string :param BackupId: If you specify this field, AWS OpsWorks CM creates the server by using the backup represented by BackupId. :rtype: dict :returns: """ pass def delete_backup(self, BackupId: str) -> Dict: """ Deletes a backup. You can delete both manual and automated backups. This operation is asynchronous. An ``InvalidStateException`` is thrown when a backup deletion is already in progress. A ``ResourceNotFoundException`` is thrown when the backup does not exist. A ``ValidationException`` is thrown when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DeleteBackup>`_ **Request Syntax** :: response = client.delete_backup( BackupId='string' ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type BackupId: string :param BackupId: **[REQUIRED]** The ID of the backup to delete. Run the DescribeBackups command to get a list of backup IDs. Backup IDs are in the format ``ServerName-yyyyMMddHHmmssSSS`` . :rtype: dict :returns: """ pass def delete_server(self, ServerName: str) -> Dict: """ Deletes the server and the underlying AWS CloudFormation stacks (including the server's EC2 instance). When you run this command, the server state is updated to ``DELETING`` . After the server is deleted, it is no longer returned by ``DescribeServer`` requests. If the AWS CloudFormation stack cannot be deleted, the server cannot be deleted. This operation is asynchronous. An ``InvalidStateException`` is thrown when a server deletion is already in progress. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DeleteServer>`_ **Request Syntax** :: response = client.delete_server( ServerName='string' ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type ServerName: string :param ServerName: **[REQUIRED]** The ID of the server to delete. :rtype: dict :returns: """ pass def describe_account_attributes(self) -> Dict: """ Describes your account attributes, and creates requests to increase limits before they are reached or exceeded. This operation is synchronous. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DescribeAccountAttributes>`_ **Request Syntax** :: response = client.describe_account_attributes() **Response Syntax** :: { 'Attributes': [ { 'Name': 'string', 'Maximum': 123, 'Used': 123 }, ] } **Response Structure** - *(dict) --* - **Attributes** *(list) --* The attributes that are currently set for the account. - *(dict) --* Stores account attributes. - **Name** *(string) --* The attribute name. The following are supported attribute names. * *ServerLimit:* The number of current servers/maximum number of servers allowed. By default, you can have a maximum of 10 servers. * *ManualBackupLimit:* The number of current manual backups/maximum number of backups allowed. By default, you can have a maximum of 50 manual backups saved. - **Maximum** *(integer) --* The maximum allowed value. - **Used** *(integer) --* The current usage, such as the current number of servers that are associated with the account. :rtype: dict :returns: """ pass def describe_backups(self, BackupId: str = None, ServerName: str = None, NextToken: str = None, MaxResults: int = None) -> Dict: """ Describes backups. The results are ordered by time, with newest backups first. If you do not specify a BackupId or ServerName, the command returns all backups. This operation is synchronous. A ``ResourceNotFoundException`` is thrown when the backup does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DescribeBackups>`_ **Request Syntax** :: response = client.describe_backups( BackupId='string', ServerName='string', NextToken='string', MaxResults=123 ) **Response Syntax** :: { 'Backups': [ { 'BackupArn': 'string', 'BackupId': 'string', 'BackupType': 'AUTOMATED'|'MANUAL', 'CreatedAt': datetime(2015, 1, 1), 'Description': 'string', 'Engine': 'string', 'EngineModel': 'string', 'EngineVersion': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'KeyPair': 'string', 'PreferredBackupWindow': 'string', 'PreferredMaintenanceWindow': 'string', 'S3DataSize': 123, 'S3DataUrl': 'string', 'S3LogUrl': 'string', 'SecurityGroupIds': [ 'string', ], 'ServerName': 'string', 'ServiceRoleArn': 'string', 'Status': 'IN_PROGRESS'|'OK'|'FAILED'|'DELETING', 'StatusDescription': 'string', 'SubnetIds': [ 'string', ], 'ToolsVersion': 'string', 'UserArn': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **Backups** *(list) --* Contains the response to a ``DescribeBackups`` request. - *(dict) --* Describes a single backup. - **BackupArn** *(string) --* The ARN of the backup. - **BackupId** *(string) --* The generated ID of the backup. Example: ``myServerName-yyyyMMddHHmmssSSS`` - **BackupType** *(string) --* The backup type. Valid values are ``automated`` or ``manual`` . - **CreatedAt** *(datetime) --* The time stamp when the backup was created in the database. Example: ``2016-07-29T13:38:47.520Z`` - **Description** *(string) --* A user-provided description for a manual backup. This field is empty for automated backups. - **Engine** *(string) --* The engine type that is obtained from the server when the backup is created. - **EngineModel** *(string) --* The engine model that is obtained from the server when the backup is created. - **EngineVersion** *(string) --* The engine version that is obtained from the server when the backup is created. - **InstanceProfileArn** *(string) --* The EC2 instance profile ARN that is obtained from the server when the backup is created. Because this value is stored, you are not required to provide the InstanceProfileArn again if you restore a backup. - **InstanceType** *(string) --* The instance type that is obtained from the server when the backup is created. - **KeyPair** *(string) --* The key pair that is obtained from the server when the backup is created. - **PreferredBackupWindow** *(string) --* The preferred backup period that is obtained from the server when the backup is created. - **PreferredMaintenanceWindow** *(string) --* The preferred maintenance period that is obtained from the server when the backup is created. - **S3DataSize** *(integer) --* This field is deprecated and is no longer used. - **S3DataUrl** *(string) --* This field is deprecated and is no longer used. - **S3LogUrl** *(string) --* The Amazon S3 URL of the backup's log file. - **SecurityGroupIds** *(list) --* The security group IDs that are obtained from the server when the backup is created. - *(string) --* - **ServerName** *(string) --* The name of the server from which the backup was made. - **ServiceRoleArn** *(string) --* The service role ARN that is obtained from the server when the backup is created. - **Status** *(string) --* The status of a backup while in progress. - **StatusDescription** *(string) --* An informational message about backup status. - **SubnetIds** *(list) --* The subnet IDs that are obtained from the server when the backup is created. - *(string) --* - **ToolsVersion** *(string) --* The version of AWS OpsWorks CM-specific tools that is obtained from the server when the backup is created. - **UserArn** *(string) --* The IAM user ARN of the requester for manual backups. This field is empty for automated backups. - **NextToken** *(string) --* This is not currently implemented for ``DescribeBackups`` requests. :type BackupId: string :param BackupId: Describes a single backup. :type ServerName: string :param ServerName: Returns backups for the server with the specified ServerName. :type NextToken: string :param NextToken: This is not currently implemented for ``DescribeBackups`` requests. :type MaxResults: integer :param MaxResults: This is not currently implemented for ``DescribeBackups`` requests. :rtype: dict :returns: """ pass def describe_events(self, ServerName: str, NextToken: str = None, MaxResults: int = None) -> Dict: """ Describes events for a specified server. Results are ordered by time, with newest events first. This operation is synchronous. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DescribeEvents>`_ **Request Syntax** :: response = client.describe_events( ServerName='string', NextToken='string', MaxResults=123 ) **Response Syntax** :: { 'ServerEvents': [ { 'CreatedAt': datetime(2015, 1, 1), 'ServerName': 'string', 'Message': 'string', 'LogUrl': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **ServerEvents** *(list) --* Contains the response to a ``DescribeEvents`` request. - *(dict) --* An event that is related to the server, such as the start of maintenance or backup. - **CreatedAt** *(datetime) --* The time when the event occurred. - **ServerName** *(string) --* The name of the server on or for which the event occurred. - **Message** *(string) --* A human-readable informational or status message. - **LogUrl** *(string) --* The Amazon S3 URL of the event's log file. - **NextToken** *(string) --* NextToken is a string that is returned in some command responses. It indicates that not all entries have been returned, and that you must run at least one more request to get remaining items. To get remaining results, call ``DescribeEvents`` again, and assign the token from the previous results as the value of the ``nextToken`` parameter. If there are no more results, the response object's ``nextToken`` parameter value is ``null`` . Setting a ``nextToken`` value that was not returned in your previous results causes an ``InvalidNextTokenException`` to occur. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server for which you want to view events. :type NextToken: string :param NextToken: NextToken is a string that is returned in some command responses. It indicates that not all entries have been returned, and that you must run at least one more request to get remaining items. To get remaining results, call ``DescribeEvents`` again, and assign the token from the previous results as the value of the ``nextToken`` parameter. If there are no more results, the response object\'s ``nextToken`` parameter value is ``null`` . Setting a ``nextToken`` value that was not returned in your previous results causes an ``InvalidNextTokenException`` to occur. :type MaxResults: integer :param MaxResults: To receive a paginated response, use this parameter to specify the maximum number of results to be returned with a single call. If the number of available results exceeds this maximum, the response includes a ``NextToken`` value that you can assign to the ``NextToken`` request parameter to get the next set of results. :rtype: dict :returns: """ pass def describe_node_association_status(self, NodeAssociationStatusToken: str, ServerName: str) -> Dict: """ Returns the current status of an existing association or disassociation request. A ``ResourceNotFoundException`` is thrown when no recent association or disassociation request with the specified token is found, or when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DescribeNodeAssociationStatus>`_ **Request Syntax** :: response = client.describe_node_association_status( NodeAssociationStatusToken='string', ServerName='string' ) **Response Syntax** :: { 'NodeAssociationStatus': 'SUCCESS'|'FAILED'|'IN_PROGRESS', 'EngineAttributes': [ { 'Name': 'string', 'Value': 'string' }, ] } **Response Structure** - *(dict) --* - **NodeAssociationStatus** *(string) --* The status of the association or disassociation request. **Possible values:** * ``SUCCESS`` : The association or disassociation succeeded. * ``FAILED`` : The association or disassociation failed. * ``IN_PROGRESS`` : The association or disassociation is still in progress. - **EngineAttributes** *(list) --* Attributes specific to the node association. In Puppet, the attibute PUPPET_NODE_CERT contains the signed certificate (the result of the CSR). - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. :type NodeAssociationStatusToken: string :param NodeAssociationStatusToken: **[REQUIRED]** The token returned in either the AssociateNodeResponse or the DisassociateNodeResponse. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server from which to disassociate the node. :rtype: dict :returns: """ pass def describe_servers(self, ServerName: str = None, NextToken: str = None, MaxResults: int = None) -> Dict: """ Lists all configuration management servers that are identified with your account. Only the stored results from Amazon DynamoDB are returned. AWS OpsWorks CM does not query other services. This operation is synchronous. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DescribeServers>`_ **Request Syntax** :: response = client.describe_servers( ServerName='string', NextToken='string', MaxResults=123 ) **Response Syntax** :: { 'Servers': [ { 'AssociatePublicIpAddress': True|False, 'BackupRetentionCount': 123, 'ServerName': 'string', 'CreatedAt': datetime(2015, 1, 1), 'CloudFormationStackArn': 'string', 'DisableAutomatedBackup': True|False, 'Endpoint': 'string', 'Engine': 'string', 'EngineModel': 'string', 'EngineAttributes': [ { 'Name': 'string', 'Value': 'string' }, ], 'EngineVersion': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'KeyPair': 'string', 'MaintenanceStatus': 'SUCCESS'|'FAILED', 'PreferredMaintenanceWindow': 'string', 'PreferredBackupWindow': 'string', 'SecurityGroupIds': [ 'string', ], 'ServiceRoleArn': 'string', 'Status': 'BACKING_UP'|'CONNECTION_LOST'|'CREATING'|'DELETING'|'MODIFYING'|'FAILED'|'HEALTHY'|'RUNNING'|'RESTORING'|'SETUP'|'UNDER_MAINTENANCE'|'UNHEALTHY'|'TERMINATED', 'StatusReason': 'string', 'SubnetIds': [ 'string', ], 'ServerArn': 'string' }, ], 'NextToken': 'string' } **Response Structure** - *(dict) --* - **Servers** *(list) --* Contains the response to a ``DescribeServers`` request. *For Puppet Server:* ``DescribeServersResponse$Servers$EngineAttributes`` contains PUPPET_API_CA_CERT. This is the PEM-encoded CA certificate that is used by the Puppet API over TCP port number 8140. The CA certificate is also used to sign node certificates. - *(dict) --* Describes a configuration management server. - **AssociatePublicIpAddress** *(boolean) --* Associate a public IP address with a server that you are launching. - **BackupRetentionCount** *(integer) --* The number of automated backups to keep. - **ServerName** *(string) --* The name of the server. - **CreatedAt** *(datetime) --* Time stamp of server creation. Example ``2016-07-29T13:38:47.520Z`` - **CloudFormationStackArn** *(string) --* The ARN of the CloudFormation stack that was used to create the server. - **DisableAutomatedBackup** *(boolean) --* Disables automated backups. The number of stored backups is dependent on the value of PreferredBackupCount. - **Endpoint** *(string) --* A DNS name that can be used to access the engine. Example: ``myserver-asdfghjkl.us-east-1.opsworks.io`` - **Engine** *(string) --* The engine type of the server. Valid values in this release include ``Chef`` and ``Puppet`` . - **EngineModel** *(string) --* The engine model of the server. Valid values in this release include ``Monolithic`` for Puppet and ``Single`` for Chef. - **EngineAttributes** *(list) --* The response of a createServer() request returns the master credential to access the server in EngineAttributes. These credentials are not stored by AWS OpsWorks CM; they are returned only as part of the result of createServer(). **Attributes returned in a createServer response for Chef** * ``CHEF_PIVOTAL_KEY`` : A base64-encoded RSA private key that is generated by AWS OpsWorks for Chef Automate. This private key is required to access the Chef API. * ``CHEF_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Chef starter kit, which includes a README, a configuration file, and the required RSA private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. From this directory, you can run Knife commands. **Attributes returned in a createServer response for Puppet** * ``PUPPET_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Puppet starter kit, including a README and a required private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. * ``PUPPET_ADMIN_PASSWORD`` : An administrator password that you can use to sign in to the Puppet Enterprise console after the server is online. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. - **EngineVersion** *(string) --* The engine version of the server. For a Chef server, the valid value for EngineVersion is currently ``12`` . For a Puppet server, the valid value is ``2017`` . - **InstanceProfileArn** *(string) --* The instance profile ARN of the server. - **InstanceType** *(string) --* The instance type for the server, as specified in the CloudFormation stack. This might not be the same instance type that is shown in the EC2 console. - **KeyPair** *(string) --* The key pair associated with the server. - **MaintenanceStatus** *(string) --* The status of the most recent server maintenance run. Shows ``SUCCESS`` or ``FAILED`` . - **PreferredMaintenanceWindow** *(string) --* The preferred maintenance period specified for the server. - **PreferredBackupWindow** *(string) --* The preferred backup period specified for the server. - **SecurityGroupIds** *(list) --* The security group IDs for the server, as specified in the CloudFormation stack. These might not be the same security groups that are shown in the EC2 console. - *(string) --* - **ServiceRoleArn** *(string) --* The service role ARN used to create the server. - **Status** *(string) --* The server's status. This field displays the states of actions in progress, such as creating, running, or backing up the server, as well as the server's health state. - **StatusReason** *(string) --* Depending on the server status, this field has either a human-readable message (such as a create or backup error), or an escaped block of JSON (used for health check results). - **SubnetIds** *(list) --* The subnet IDs specified in a CreateServer request. - *(string) --* - **ServerArn** *(string) --* The ARN of the server. - **NextToken** *(string) --* This is not currently implemented for ``DescribeServers`` requests. :type ServerName: string :param ServerName: Describes the server with the specified ServerName. :type NextToken: string :param NextToken: This is not currently implemented for ``DescribeServers`` requests. :type MaxResults: integer :param MaxResults: This is not currently implemented for ``DescribeServers`` requests. :rtype: dict :returns: """ pass def disassociate_node(self, ServerName: str, NodeName: str, EngineAttributes: List = None) -> Dict: """ Disassociates a node from an AWS OpsWorks CM server, and removes the node from the server's managed nodes. After a node is disassociated, the node key pair is no longer valid for accessing the configuration manager's API. For more information about how to associate a node, see AssociateNode . A node can can only be disassociated from a server that is in a ``HEALTHY`` state. Otherwise, an ``InvalidStateException`` is thrown. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/DisassociateNode>`_ **Request Syntax** :: response = client.disassociate_node( ServerName='string', NodeName='string', EngineAttributes=[ { 'Name': 'string', 'Value': 'string' }, ] ) **Response Syntax** :: { 'NodeAssociationStatusToken': 'string' } **Response Structure** - *(dict) --* - **NodeAssociationStatusToken** *(string) --* Contains a token which can be passed to the ``DescribeNodeAssociationStatus`` API call to get the status of the disassociation request. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server from which to disassociate the node. :type NodeName: string :param NodeName: **[REQUIRED]** The name of the client node. :type EngineAttributes: list :param EngineAttributes: Engine attributes that are used for disassociating the node. No attributes are required for Puppet. **Attributes required in a DisassociateNode request for Chef** * ``CHEF_ORGANIZATION`` : The Chef organization with which the node was associated. By default only one organization named ``default`` can exist. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. :rtype: dict :returns: """ pass def export_server_engine_attribute(self, ExportAttributeName: str, ServerName: str, InputAttributes: List = None) -> Dict: """ Exports a specified server engine attribute as a base64-encoded string. For example, you can export user data that you can use in EC2 to associate nodes with a server. This operation is synchronous. A ``ValidationException`` is raised when parameters of the request are not valid. A ``ResourceNotFoundException`` is thrown when the server does not exist. An ``InvalidStateException`` is thrown when the server is in any of the following states: CREATING, TERMINATED, FAILED or DELETING. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/ExportServerEngineAttribute>`_ **Request Syntax** :: response = client.export_server_engine_attribute( ExportAttributeName='string', ServerName='string', InputAttributes=[ { 'Name': 'string', 'Value': 'string' }, ] ) **Response Syntax** :: { 'EngineAttribute': { 'Name': 'string', 'Value': 'string' }, 'ServerName': 'string' } **Response Structure** - *(dict) --* - **EngineAttribute** *(dict) --* The requested engine attribute pair with attribute name and value. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. - **ServerName** *(string) --* The server name used in the request. :type ExportAttributeName: string :param ExportAttributeName: **[REQUIRED]** The name of the export attribute. Currently, the supported export attribute is ``Userdata`` . This exports a user data script that includes parameters and values provided in the ``InputAttributes`` list. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server from which you are exporting the attribute. :type InputAttributes: list :param InputAttributes: The list of engine attributes. The list type is ``EngineAttribute`` . An ``EngineAttribute`` list item is a pair that includes an attribute name and its value. For the ``Userdata`` ExportAttributeName, the following are supported engine attribute names. * **RunList** In Chef, a list of roles or recipes that are run in the specified order. In Puppet, this parameter is ignored. * **OrganizationName** In Chef, an organization name. AWS OpsWorks for Chef Automate always creates the organization ``default`` . In Puppet, this parameter is ignored. * **NodeEnvironment** In Chef, a node environment (for example, development, staging, or one-box). In Puppet, this parameter is ignored. * **NodeClientVersion** In Chef, the version of the Chef engine (three numbers separated by dots, such as 13.8.5). If this attribute is empty, OpsWorks for Chef Automate uses the most current version. In Puppet, this parameter is ignored. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. :rtype: dict :returns: """ pass def generate_presigned_url(self, ClientMethod: str = None, Params: Dict = None, ExpiresIn: int = None, HttpMethod: str = None): """ Generate a presigned url given a client, its method, and arguments :type ClientMethod: string :param ClientMethod: The client method to presign for :type Params: dict :param Params: The parameters normally passed to ``ClientMethod``. :type ExpiresIn: int :param ExpiresIn: The number of seconds the presigned url is valid for. By default it expires in an hour (3600 seconds) :type HttpMethod: string :param HttpMethod: The http method to use on the generated url. By default, the http method is whatever is used in the method\'s model. :returns: The presigned url """ pass def get_paginator(self, operation_name: str = None) -> Paginator: """ Create a paginator for an operation. :type operation_name: string :param operation_name: The operation name. This is the same name as the method name on the client. For example, if the method name is ``create_foo``, and you\'d normally invoke the operation as ``client.create_foo(**kwargs)``, if the ``create_foo`` operation can be paginated, you can use the call ``client.get_paginator(\"create_foo\")``. :raise OperationNotPageableError: Raised if the operation is not pageable. You can use the ``client.can_paginate`` method to check if an operation is pageable. :rtype: L{botocore.paginate.Paginator} :return: A paginator object. """ pass def get_waiter(self, waiter_name: str = None) -> Waiter: """ Returns an object that can wait for some condition. :type waiter_name: str :param waiter_name: The name of the waiter to get. See the waiters section of the service docs for a list of available waiters. :returns: The specified waiter object. :rtype: botocore.waiter.Waiter """ pass def restore_server(self, BackupId: str, ServerName: str, InstanceType: str = None, KeyPair: str = None) -> Dict: """ Restores a backup to a server that is in a ``CONNECTION_LOST`` , ``HEALTHY`` , ``RUNNING`` , ``UNHEALTHY`` , or ``TERMINATED`` state. When you run RestoreServer, the server's EC2 instance is deleted, and a new EC2 instance is configured. RestoreServer maintains the existing server endpoint, so configuration management of the server's client devices (nodes) should continue to work. This operation is asynchronous. An ``InvalidStateException`` is thrown when the server is not in a valid state. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/RestoreServer>`_ **Request Syntax** :: response = client.restore_server( BackupId='string', ServerName='string', InstanceType='string', KeyPair='string' ) **Response Syntax** :: {} **Response Structure** - *(dict) --* :type BackupId: string :param BackupId: **[REQUIRED]** The ID of the backup that you want to use to restore a server. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server that you want to restore. :type InstanceType: string :param InstanceType: The type of the instance to create. Valid values must be specified in the following format: ``^([cm][34]|t2).*`` For example, ``m4.large`` . Valid values are ``t2.medium`` , ``m4.large`` , and ``m4.2xlarge`` . If you do not specify this parameter, RestoreServer uses the instance type from the specified backup. :type KeyPair: string :param KeyPair: The name of the key pair to set on the new EC2 instance. This can be helpful if the administrator no longer has the SSH key. :rtype: dict :returns: """ pass def start_maintenance(self, ServerName: str, EngineAttributes: List = None) -> Dict: """ Manually starts server maintenance. This command can be useful if an earlier maintenance attempt failed, and the underlying cause of maintenance failure has been resolved. The server is in an ``UNDER_MAINTENANCE`` state while maintenance is in progress. Maintenance can only be started on servers in ``HEALTHY`` and ``UNHEALTHY`` states. Otherwise, an ``InvalidStateException`` is thrown. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/StartMaintenance>`_ **Request Syntax** :: response = client.start_maintenance( ServerName='string', EngineAttributes=[ { 'Name': 'string', 'Value': 'string' }, ] ) **Response Syntax** :: { 'Server': { 'AssociatePublicIpAddress': True|False, 'BackupRetentionCount': 123, 'ServerName': 'string', 'CreatedAt': datetime(2015, 1, 1), 'CloudFormationStackArn': 'string', 'DisableAutomatedBackup': True|False, 'Endpoint': 'string', 'Engine': 'string', 'EngineModel': 'string', 'EngineAttributes': [ { 'Name': 'string', 'Value': 'string' }, ], 'EngineVersion': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'KeyPair': 'string', 'MaintenanceStatus': 'SUCCESS'|'FAILED', 'PreferredMaintenanceWindow': 'string', 'PreferredBackupWindow': 'string', 'SecurityGroupIds': [ 'string', ], 'ServiceRoleArn': 'string', 'Status': 'BACKING_UP'|'CONNECTION_LOST'|'CREATING'|'DELETING'|'MODIFYING'|'FAILED'|'HEALTHY'|'RUNNING'|'RESTORING'|'SETUP'|'UNDER_MAINTENANCE'|'UNHEALTHY'|'TERMINATED', 'StatusReason': 'string', 'SubnetIds': [ 'string', ], 'ServerArn': 'string' } } **Response Structure** - *(dict) --* - **Server** *(dict) --* Contains the response to a ``StartMaintenance`` request. - **AssociatePublicIpAddress** *(boolean) --* Associate a public IP address with a server that you are launching. - **BackupRetentionCount** *(integer) --* The number of automated backups to keep. - **ServerName** *(string) --* The name of the server. - **CreatedAt** *(datetime) --* Time stamp of server creation. Example ``2016-07-29T13:38:47.520Z`` - **CloudFormationStackArn** *(string) --* The ARN of the CloudFormation stack that was used to create the server. - **DisableAutomatedBackup** *(boolean) --* Disables automated backups. The number of stored backups is dependent on the value of PreferredBackupCount. - **Endpoint** *(string) --* A DNS name that can be used to access the engine. Example: ``myserver-asdfghjkl.us-east-1.opsworks.io`` - **Engine** *(string) --* The engine type of the server. Valid values in this release include ``Chef`` and ``Puppet`` . - **EngineModel** *(string) --* The engine model of the server. Valid values in this release include ``Monolithic`` for Puppet and ``Single`` for Chef. - **EngineAttributes** *(list) --* The response of a createServer() request returns the master credential to access the server in EngineAttributes. These credentials are not stored by AWS OpsWorks CM; they are returned only as part of the result of createServer(). **Attributes returned in a createServer response for Chef** * ``CHEF_PIVOTAL_KEY`` : A base64-encoded RSA private key that is generated by AWS OpsWorks for Chef Automate. This private key is required to access the Chef API. * ``CHEF_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Chef starter kit, which includes a README, a configuration file, and the required RSA private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. From this directory, you can run Knife commands. **Attributes returned in a createServer response for Puppet** * ``PUPPET_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Puppet starter kit, including a README and a required private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. * ``PUPPET_ADMIN_PASSWORD`` : An administrator password that you can use to sign in to the Puppet Enterprise console after the server is online. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. - **EngineVersion** *(string) --* The engine version of the server. For a Chef server, the valid value for EngineVersion is currently ``12`` . For a Puppet server, the valid value is ``2017`` . - **InstanceProfileArn** *(string) --* The instance profile ARN of the server. - **InstanceType** *(string) --* The instance type for the server, as specified in the CloudFormation stack. This might not be the same instance type that is shown in the EC2 console. - **KeyPair** *(string) --* The key pair associated with the server. - **MaintenanceStatus** *(string) --* The status of the most recent server maintenance run. Shows ``SUCCESS`` or ``FAILED`` . - **PreferredMaintenanceWindow** *(string) --* The preferred maintenance period specified for the server. - **PreferredBackupWindow** *(string) --* The preferred backup period specified for the server. - **SecurityGroupIds** *(list) --* The security group IDs for the server, as specified in the CloudFormation stack. These might not be the same security groups that are shown in the EC2 console. - *(string) --* - **ServiceRoleArn** *(string) --* The service role ARN used to create the server. - **Status** *(string) --* The server's status. This field displays the states of actions in progress, such as creating, running, or backing up the server, as well as the server's health state. - **StatusReason** *(string) --* Depending on the server status, this field has either a human-readable message (such as a create or backup error), or an escaped block of JSON (used for health check results). - **SubnetIds** *(list) --* The subnet IDs specified in a CreateServer request. - *(string) --* - **ServerArn** *(string) --* The ARN of the server. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server on which to run maintenance. :type EngineAttributes: list :param EngineAttributes: Engine attributes that are specific to the server on which you want to run maintenance. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. :rtype: dict :returns: """ pass def update_server(self, ServerName: str, DisableAutomatedBackup: bool = None, BackupRetentionCount: int = None, PreferredMaintenanceWindow: str = None, PreferredBackupWindow: str = None) -> Dict: """ Updates settings for a server. This operation is synchronous. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/UpdateServer>`_ **Request Syntax** :: response = client.update_server( DisableAutomatedBackup=True|False, BackupRetentionCount=123, ServerName='string', PreferredMaintenanceWindow='string', PreferredBackupWindow='string' ) **Response Syntax** :: { 'Server': { 'AssociatePublicIpAddress': True|False, 'BackupRetentionCount': 123, 'ServerName': 'string', 'CreatedAt': datetime(2015, 1, 1), 'CloudFormationStackArn': 'string', 'DisableAutomatedBackup': True|False, 'Endpoint': 'string', 'Engine': 'string', 'EngineModel': 'string', 'EngineAttributes': [ { 'Name': 'string', 'Value': 'string' }, ], 'EngineVersion': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'KeyPair': 'string', 'MaintenanceStatus': 'SUCCESS'|'FAILED', 'PreferredMaintenanceWindow': 'string', 'PreferredBackupWindow': 'string', 'SecurityGroupIds': [ 'string', ], 'ServiceRoleArn': 'string', 'Status': 'BACKING_UP'|'CONNECTION_LOST'|'CREATING'|'DELETING'|'MODIFYING'|'FAILED'|'HEALTHY'|'RUNNING'|'RESTORING'|'SETUP'|'UNDER_MAINTENANCE'|'UNHEALTHY'|'TERMINATED', 'StatusReason': 'string', 'SubnetIds': [ 'string', ], 'ServerArn': 'string' } } **Response Structure** - *(dict) --* - **Server** *(dict) --* Contains the response to a ``UpdateServer`` request. - **AssociatePublicIpAddress** *(boolean) --* Associate a public IP address with a server that you are launching. - **BackupRetentionCount** *(integer) --* The number of automated backups to keep. - **ServerName** *(string) --* The name of the server. - **CreatedAt** *(datetime) --* Time stamp of server creation. Example ``2016-07-29T13:38:47.520Z`` - **CloudFormationStackArn** *(string) --* The ARN of the CloudFormation stack that was used to create the server. - **DisableAutomatedBackup** *(boolean) --* Disables automated backups. The number of stored backups is dependent on the value of PreferredBackupCount. - **Endpoint** *(string) --* A DNS name that can be used to access the engine. Example: ``myserver-asdfghjkl.us-east-1.opsworks.io`` - **Engine** *(string) --* The engine type of the server. Valid values in this release include ``Chef`` and ``Puppet`` . - **EngineModel** *(string) --* The engine model of the server. Valid values in this release include ``Monolithic`` for Puppet and ``Single`` for Chef. - **EngineAttributes** *(list) --* The response of a createServer() request returns the master credential to access the server in EngineAttributes. These credentials are not stored by AWS OpsWorks CM; they are returned only as part of the result of createServer(). **Attributes returned in a createServer response for Chef** * ``CHEF_PIVOTAL_KEY`` : A base64-encoded RSA private key that is generated by AWS OpsWorks for Chef Automate. This private key is required to access the Chef API. * ``CHEF_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Chef starter kit, which includes a README, a configuration file, and the required RSA private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. From this directory, you can run Knife commands. **Attributes returned in a createServer response for Puppet** * ``PUPPET_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Puppet starter kit, including a README and a required private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. * ``PUPPET_ADMIN_PASSWORD`` : An administrator password that you can use to sign in to the Puppet Enterprise console after the server is online. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. - **EngineVersion** *(string) --* The engine version of the server. For a Chef server, the valid value for EngineVersion is currently ``12`` . For a Puppet server, the valid value is ``2017`` . - **InstanceProfileArn** *(string) --* The instance profile ARN of the server. - **InstanceType** *(string) --* The instance type for the server, as specified in the CloudFormation stack. This might not be the same instance type that is shown in the EC2 console. - **KeyPair** *(string) --* The key pair associated with the server. - **MaintenanceStatus** *(string) --* The status of the most recent server maintenance run. Shows ``SUCCESS`` or ``FAILED`` . - **PreferredMaintenanceWindow** *(string) --* The preferred maintenance period specified for the server. - **PreferredBackupWindow** *(string) --* The preferred backup period specified for the server. - **SecurityGroupIds** *(list) --* The security group IDs for the server, as specified in the CloudFormation stack. These might not be the same security groups that are shown in the EC2 console. - *(string) --* - **ServiceRoleArn** *(string) --* The service role ARN used to create the server. - **Status** *(string) --* The server's status. This field displays the states of actions in progress, such as creating, running, or backing up the server, as well as the server's health state. - **StatusReason** *(string) --* Depending on the server status, this field has either a human-readable message (such as a create or backup error), or an escaped block of JSON (used for health check results). - **SubnetIds** *(list) --* The subnet IDs specified in a CreateServer request. - *(string) --* - **ServerArn** *(string) --* The ARN of the server. :type DisableAutomatedBackup: boolean :param DisableAutomatedBackup: Setting DisableAutomatedBackup to ``true`` disables automated or scheduled backups. Automated backups are enabled by default. :type BackupRetentionCount: integer :param BackupRetentionCount: Sets the number of automated backups that you want to keep. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server to update. :type PreferredMaintenanceWindow: string :param PreferredMaintenanceWindow: ``DDD:HH:MM`` (weekly start time) or ``HH:MM`` (daily start time). Time windows always use coordinated universal time (UTC). Valid strings for day of week (``DDD`` ) are: ``Mon`` , ``Tue`` , ``Wed`` , ``Thr`` , ``Fri`` , ``Sat`` , or ``Sun`` . :type PreferredBackupWindow: string :param PreferredBackupWindow: ``DDD:HH:MM`` (weekly start time) or ``HH:MM`` (daily start time). Time windows always use coordinated universal time (UTC). Valid strings for day of week (``DDD`` ) are: ``Mon`` , ``Tue`` , ``Wed`` , ``Thr`` , ``Fri`` , ``Sat`` , or ``Sun`` . :rtype: dict :returns: """ pass def update_server_engine_attributes(self, ServerName: str, AttributeName: str, AttributeValue: str = None) -> Dict: """ Updates engine-specific attributes on a specified server. The server enters the ``MODIFYING`` state when this operation is in progress. Only one update can occur at a time. You can use this command to reset a Chef server's public key (``CHEF_PIVOTAL_KEY`` ) or a Puppet server's admin password (``PUPPET_ADMIN_PASSWORD`` ). This operation is asynchronous. This operation can only be called for servers in ``HEALTHY`` or ``UNHEALTHY`` states. Otherwise, an ``InvalidStateException`` is raised. A ``ResourceNotFoundException`` is thrown when the server does not exist. A ``ValidationException`` is raised when parameters of the request are not valid. See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/opsworkscm-2016-11-01/UpdateServerEngineAttributes>`_ **Request Syntax** :: response = client.update_server_engine_attributes( ServerName='string', AttributeName='string', AttributeValue='string' ) **Response Syntax** :: { 'Server': { 'AssociatePublicIpAddress': True|False, 'BackupRetentionCount': 123, 'ServerName': 'string', 'CreatedAt': datetime(2015, 1, 1), 'CloudFormationStackArn': 'string', 'DisableAutomatedBackup': True|False, 'Endpoint': 'string', 'Engine': 'string', 'EngineModel': 'string', 'EngineAttributes': [ { 'Name': 'string', 'Value': 'string' }, ], 'EngineVersion': 'string', 'InstanceProfileArn': 'string', 'InstanceType': 'string', 'KeyPair': 'string', 'MaintenanceStatus': 'SUCCESS'|'FAILED', 'PreferredMaintenanceWindow': 'string', 'PreferredBackupWindow': 'string', 'SecurityGroupIds': [ 'string', ], 'ServiceRoleArn': 'string', 'Status': 'BACKING_UP'|'CONNECTION_LOST'|'CREATING'|'DELETING'|'MODIFYING'|'FAILED'|'HEALTHY'|'RUNNING'|'RESTORING'|'SETUP'|'UNDER_MAINTENANCE'|'UNHEALTHY'|'TERMINATED', 'StatusReason': 'string', 'SubnetIds': [ 'string', ], 'ServerArn': 'string' } } **Response Structure** - *(dict) --* - **Server** *(dict) --* Contains the response to an ``UpdateServerEngineAttributes`` request. - **AssociatePublicIpAddress** *(boolean) --* Associate a public IP address with a server that you are launching. - **BackupRetentionCount** *(integer) --* The number of automated backups to keep. - **ServerName** *(string) --* The name of the server. - **CreatedAt** *(datetime) --* Time stamp of server creation. Example ``2016-07-29T13:38:47.520Z`` - **CloudFormationStackArn** *(string) --* The ARN of the CloudFormation stack that was used to create the server. - **DisableAutomatedBackup** *(boolean) --* Disables automated backups. The number of stored backups is dependent on the value of PreferredBackupCount. - **Endpoint** *(string) --* A DNS name that can be used to access the engine. Example: ``myserver-asdfghjkl.us-east-1.opsworks.io`` - **Engine** *(string) --* The engine type of the server. Valid values in this release include ``Chef`` and ``Puppet`` . - **EngineModel** *(string) --* The engine model of the server. Valid values in this release include ``Monolithic`` for Puppet and ``Single`` for Chef. - **EngineAttributes** *(list) --* The response of a createServer() request returns the master credential to access the server in EngineAttributes. These credentials are not stored by AWS OpsWorks CM; they are returned only as part of the result of createServer(). **Attributes returned in a createServer response for Chef** * ``CHEF_PIVOTAL_KEY`` : A base64-encoded RSA private key that is generated by AWS OpsWorks for Chef Automate. This private key is required to access the Chef API. * ``CHEF_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Chef starter kit, which includes a README, a configuration file, and the required RSA private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. From this directory, you can run Knife commands. **Attributes returned in a createServer response for Puppet** * ``PUPPET_STARTER_KIT`` : A base64-encoded ZIP file. The ZIP file contains a Puppet starter kit, including a README and a required private key. Save this file, unzip it, and then change to the directory where you've unzipped the file contents. * ``PUPPET_ADMIN_PASSWORD`` : An administrator password that you can use to sign in to the Puppet Enterprise console after the server is online. - *(dict) --* A name and value pair that is specific to the engine of the server. - **Name** *(string) --* The name of the engine attribute. - **Value** *(string) --* The value of the engine attribute. - **EngineVersion** *(string) --* The engine version of the server. For a Chef server, the valid value for EngineVersion is currently ``12`` . For a Puppet server, the valid value is ``2017`` . - **InstanceProfileArn** *(string) --* The instance profile ARN of the server. - **InstanceType** *(string) --* The instance type for the server, as specified in the CloudFormation stack. This might not be the same instance type that is shown in the EC2 console. - **KeyPair** *(string) --* The key pair associated with the server. - **MaintenanceStatus** *(string) --* The status of the most recent server maintenance run. Shows ``SUCCESS`` or ``FAILED`` . - **PreferredMaintenanceWindow** *(string) --* The preferred maintenance period specified for the server. - **PreferredBackupWindow** *(string) --* The preferred backup period specified for the server. - **SecurityGroupIds** *(list) --* The security group IDs for the server, as specified in the CloudFormation stack. These might not be the same security groups that are shown in the EC2 console. - *(string) --* - **ServiceRoleArn** *(string) --* The service role ARN used to create the server. - **Status** *(string) --* The server's status. This field displays the states of actions in progress, such as creating, running, or backing up the server, as well as the server's health state. - **StatusReason** *(string) --* Depending on the server status, this field has either a human-readable message (such as a create or backup error), or an escaped block of JSON (used for health check results). - **SubnetIds** *(list) --* The subnet IDs specified in a CreateServer request. - *(string) --* - **ServerArn** *(string) --* The ARN of the server. :type ServerName: string :param ServerName: **[REQUIRED]** The name of the server to update. :type AttributeName: string :param AttributeName: **[REQUIRED]** The name of the engine attribute to update. :type AttributeValue: string :param AttributeValue: The value to set for the attribute. :rtype: dict :returns: """ pass

60.705457

578

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0.031087

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92,333

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0.416667

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null

0

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1

0

1

0

5

2c90ad6a01ed4c30472559a80a16e50ff4269a3c

3,971

py

Python

test/test_modify_contact.py

GennadyBarchenkov/python_training

fd3da53ee3da9f9e043c08d648f7ea20197dbb78

[ "Apache-2.0" ]

null

test/test_modify_contact.py

GennadyBarchenkov/python_training

fd3da53ee3da9f9e043c08d648f7ea20197dbb78

[ "Apache-2.0" ]

null

test/test_modify_contact.py

GennadyBarchenkov/python_training

fd3da53ee3da9f9e043c08d648f7ea20197dbb78

[ "Apache-2.0" ]

null

from model.contact import Contact import random def test_full_edit_contact(app, db, check_ui): if len(db.get_contact_list()) == 0: app.contact.create(Contact(firstname="test", middlename="test", lastname="test", nickname="test", title="test", company="test", address="test", home_telephone="test", mobile_telephone="test", work_telephone="test", fax="test", email="test", email2="test", email3="test", homepage="test", bday="7", bmonth="May", byear="1900", aday="7", amonth="May", ayear="1900", address2="test", phone2="test")) old_contacts = db.get_contact_list() contact = Contact(firstname="edit1", middlename="edit2", lastname="edit3", nickname="edit4", title="edit5", company="edit6", address="edit7", home_telephone="edit8", mobile_telephone="edit9", work_telephone="edit10", fax="edit11", email="edit12", email2="edit13", email3="edit14", homepage="edit15", bday="13", bmonth="December", byear="2000", aday="13", amonth="January", ayear="2000", address2="edit16", phone2="edit17") select_contact = random.choice(old_contacts) contact.id = select_contact.id app.contact.modify_contact_by_id(select_contact.id, contact) new_contacts = db.get_contact_list() old_contacts.remove(select_contact) old_contacts.append(contact) assert sorted(old_contacts, key=Contact.id_or_max) == sorted(new_contacts, key=Contact.id_or_max) if check_ui: assert sorted(new_contacts, key=Contact.id_or_max) == sorted(app.contact.get_contact_list(), key=Contact.id_or_max) def test_modify_contact_firstname(app, db, check_ui): if len(db.get_contact_list()) == 0: app.contact.create(Contact(firstname="test")) old_contacts = db.get_contact_list() contact = Contact(firstname="New_firstname") select_contact = random.choice(old_contacts) contact.id = select_contact.id app.contact.modify_contact_by_id(select_contact.id, contact) new_contacts = db.get_contact_list() old_contacts.remove(select_contact) old_contacts.append(contact) assert sorted(old_contacts, key=Contact.id_or_max) == sorted(new_contacts, key=Contact.id_or_max) if check_ui: assert sorted(new_contacts, key=Contact.id_or_max) == sorted(app.contact.get_contact_list(), key=Contact.id_or_max) def test_modify_contact_lastname(app, db, check_ui): if len(db.get_contact_list()) == 0: app.contact.create(Contact(lastname="test")) old_contacts = db.get_contact_list() contact = Contact(lastname="New_lastname") select_contact = random.choice(old_contacts) contact.id = select_contact.id app.contact.modify_contact_by_id(select_contact.id, contact) new_contacts = db.get_contact_list() old_contacts.remove(select_contact) old_contacts.append(contact) assert sorted(old_contacts, key=Contact.id_or_max) == sorted(new_contacts, key=Contact.id_or_max) if check_ui: assert sorted(new_contacts, key=Contact.id_or_max) == sorted(app.contact.get_contact_list(), key=Contact.id_or_max) def test_modify_contact_bday(app, db, check_ui): if len(db.get_contact_list()) == 0: app.contact.create(Contact(bday="7")) old_contacts = db.get_contact_list() contact = Contact(bday="30") select_contact = random.choice(old_contacts) contact.id = select_contact.id app.contact.modify_contact_by_id(select_contact.id, contact) new_contacts = db.get_contact_list() old_contacts.remove(select_contact) old_contacts.append(contact) assert sorted(old_contacts, key=Contact.id_or_max) == sorted(new_contacts, key=Contact.id_or_max) if check_ui: assert sorted(new_contacts, key=Contact.id_or_max) == sorted(app.contact.get_contact_list(), key=Contact.id_or_max)

52.25

123

0.690506

535

3,971

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0.086486

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0.734749

0.717375

0

0.019048

0.180307

3,971

75

124

52.946667

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0

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0

0.060438

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0.059701

false

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0.029851

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0.089552

0

null

0

1

0

null

0

5

2c99571a87f5306bad72f333639fb2a57c2dc504

143

py

Python

src/resources.py

ieuan-jones/pytafl

731b9ec771074ccd3b2a6341bd823e6789b752ad

[ "MIT" ]

null

src/resources.py

ieuan-jones/pytafl

731b9ec771074ccd3b2a6341bd823e6789b752ad

[ "MIT" ]

null

src/resources.py

ieuan-jones/pytafl

731b9ec771074ccd3b2a6341bd823e6789b752ad

[ "MIT" ]

null

import pygame,os IMAGES = {} #for i in os.listdir(os.path.join("../","art")): # IMAGES[i] = pygame.image.load(os.path.join("../","art",i))

23.833333

63

0.587413

23

143

3.652174

0.565217

0.142857

0.238095

0.309524

0

0.118881

143

6

63

23.833333

0.666667

0.762238

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

5

2ca67e2d45ce703f751f36a8ee085d13f62a643c

215

py

Python

simulator/utime.py

ondiiik/meteoink

9bc7af929de12ed5eb2fafd64fcfe447f07b6eeb

[ "MIT" ]

2

2021-05-27T13:32:16.000Z

2022-03-30T01:23:34.000Z

simulator/utime.py

ondiiik/meteoink

9bc7af929de12ed5eb2fafd64fcfe447f07b6eeb

[ "MIT" ]

null

simulator/utime.py

ondiiik/meteoink

9bc7af929de12ed5eb2fafd64fcfe447f07b6eeb

[ "MIT" ]

null

def localtime(sec): import time return time.localtime(sec + 946677600) def sleep_ms(ms): import time time.sleep(0.001 * ms) def ticks_ms(): import time return int(round(time.time() * 1000))

19.545455

42

0.655814

32

215

4.34375

0.46875

0.215827

0.230216

0

0.101796

0.223256

215

11

43

19.545455

0.730539

0

0.333333

0

1

0.333333

false

0

0.333333

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0.888889

0

null

1

0

null

0

1

0

1

0

1

0

5

e2efd616a17ace90e828905e2a36cbf6e0fd2e0f

5,536

py

Python

steering-models/community-models/autumn/autumn/data_reader.py

vaibhav-s/self-driving-car

eb5865d50499f90b3eeace869c1f8a65cf9e2c46

[ "MIT" ]

null

steering-models/community-models/autumn/autumn/data_reader.py

vaibhav-s/self-driving-car

eb5865d50499f90b3eeace869c1f8a65cf9e2c46

[ "MIT" ]

null

steering-models/community-models/autumn/autumn/data_reader.py

vaibhav-s/self-driving-car

eb5865d50499f90b3eeace869c1f8a65cf9e2c46

[ "MIT" ]

null

import scipy.misc import random import csv DATA_DIR = '/vol/data/' FILE_EXT = '.png' class DataReader(object): def __init__(self, data_dir=DATA_DIR, file_ext=FILE_EXT, sequential=False): self.load() def load(self): xs = [] ys = [] self.train_batch_pointer = 0 self.val_batch_pointer = 0 total = 0 count01 = count005 = count002 = count0 = 0 with open('interpolated_center.csv') as f: reader = csv.DictReader(f) for row in reader: angle = float(row['steering_angle']) if angle > 0.1 or angle < -0.1 and random.random() > 0.2: xs.append(DATA_DIR + 'training/center/flow_7_cart/' + row['frame_id'] + FILE_EXT) ys.append(row['steering_angle']) count01 += 1 elif (angle > 0.05 or angle < -0.5) and random.random() > 0.2: xs.append(DATA_DIR + 'training/center/flow_7_cart/' + row['frame_id'] + FILE_EXT) ys.append(row['steering_angle']) count005 += 1 elif (angle > 0.02 or angle < -0.02) and random.random() > 0.7: xs.append(DATA_DIR + 'training/center/flow_7_cart/' + row['frame_id'] + FILE_EXT) ys.append(row['steering_angle']) count002 += 1 elif random.random() > 0.8: xs.append(DATA_DIR + 'training/center/flow_7_cart/' + row['frame_id'] + FILE_EXT) ys.append(row['steering_angle']) count0 += 1 total += 1 with open('train_center.csv') as f: reader = csv.DictReader(f) for row in reader: angle = float(row['steering_angle']) xs.append(DATA_DIR + 'Ch2_Train/center/flow_7_local/' + row['frame_id'] + FILE_EXT) ys.append(row['steering_angle']) total += 1 print('> 0.1 or < -0.1: ' + str(count01)) print('> 0.05 or < -0.05: ' + str(count005)) print('> 0.02 or < -0.02: ' + str(count002)) print('~0: ' + str(count0)) print('Total data: ' + str(total)) self.num_images = len(xs) c = list(zip(xs, ys)) random.shuffle(c) xs, ys = zip(*c) self.train_xs = xs[:int(len(xs) * 0.8)] self.train_ys = ys[:int(len(xs) * 0.8)] self.val_xs = xs[-int(len(xs) * 0.2):] self.val_ys = ys[-int(len(xs) * 0.2):] self.num_train_images = len(self.train_xs) self.num_val_images = len(self.val_xs) def load_train_batch(self, batch_size): x_out = [] y_out = [] for i in range(0, batch_size): image = scipy.misc.imread(self.train_xs[(self.train_batch_pointer + i) % self.num_train_images]) x_out.append(scipy.misc.imresize(image[-400:], [66, 200]) / 255.0) y_out.append([self.train_ys[(self.train_batch_pointer + i) % self.num_train_images]]) self.train_batch_pointer += batch_size return x_out, y_out def load_val_batch(self, batch_size): x_out = [] y_out = [] for i in range(0, batch_size): image = scipy.misc.imread(self.val_xs[(self.val_batch_pointer + i) % self.num_val_images]) x_out.append(scipy.misc.imresize(image[-400:], [66, 200]) / 255.0) y_out.append([self.val_ys[(self.val_batch_pointer + i) % self.num_val_images]]) self.val_batch_pointer += batch_size return x_out, y_out def load_seq(self): xs = [] ys = [] self.train_batch_pointer = 0 self.val_batch_pointer = 0 print('LSTM Data') with open('train_center.csv') as f: reader = csv.DictReader(f) for row in reader: xs.append(DATA_DIR + 'Ch2_Train/center/flow_7_local/' + row['frame_id'] + FILE_EXT) ys.append(row['steering_angle']) c = list(zip(xs, ys)) xs, ys = zip(*c) self.train_xs = xs[:int(len(xs) * 1.0)] self.train_ys = ys[:int(len(xs) * 1.0)] self.num_images = len(self.train_xs) print('total: ' + str(self.num_images)) self.num_train_images = len(self.train_xs) def load_seq_2(self): xs = [] ys = [] self.train_batch_pointer = 0 print('LSTM Data') with open('interpolated_center.csv') as f: reader = csv.DictReader(f) for row in reader: xs.append(DATA_DIR + 'output/left/flow_7_cart/' + row['frame_id'] + FILE_EXT) ys.append(row['steering_angle']) c = list(zip(xs, ys)) xs, ys = zip(*c) self.train_xs = xs[:int(len(xs) * 1.0)] self.train_ys = ys[:int(len(xs) * 1.0)] self.num_images = len(self.train_xs) print('total: ' + str(self.num_images)) self.num_train_images = len(self.train_xs) def skip(self, num): self.train_batch_pointer += num def load_seq_batch(self, batch_size): x_out = [] y_out = [] for i in range(0, batch_size): image = scipy.misc.imread(self.train_xs[(self.train_batch_pointer + i) % self.num_train_images]) x_out.append(scipy.misc.imresize(image[-400:], [66, 200]) / 255.0) y_out.append([self.train_ys[(self.train_batch_pointer + i) % self.num_train_images]]) self.train_batch_pointer += batch_size return x_out, y_out

35.487179

108

0.546785

772

5,536

3.699482

0.121762

0.078782

0.04902

0.073529

0.790966

0.786765

0.772759

0.765406

0.734594

0.711485

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0.038158

0.313584

5,536

155

109

35.716129

0.713421

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0.655738

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0.065574

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0.02459

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0.07377

0

null

0

1

0

null

0

5

393750d050c1374278df07824bc8029f2c95e31e

123

py

Python

SimPEG/utils/curvutils.py

jcapriot/simpeg

e88e653673c6b818592b6c075f76ee9215fe82b7

[ "MIT" ]

1

2021-08-07T13:50:54.000Z

SimPEG/utils/curvutils.py

jcapriot/simpeg

e88e653673c6b818592b6c075f76ee9215fe82b7

[ "MIT" ]

null

SimPEG/utils/curvutils.py

jcapriot/simpeg

e88e653673c6b818592b6c075f76ee9215fe82b7

[ "MIT" ]

1

2021-01-05T18:16:54.000Z

from .code_utils import deprecate_module deprecate_module("curvutils", "curv_utils", "0.15.0") from .curv_utils import *

20.5

53

0.772358

18

123

5

0.555556

0.244444

0

0.036364

0.105691

123

5

54

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0.781818

0

0.203252

0

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true

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1

0

null

0

1

0

1

0

5

1a4e88144b4567b8dcbb6da0e0cb53ad8bae94a2

140

py

Python

search.py

FelixVicis/Google-EmailScraper

3c22116e28eb0ddef406c1d865ab147fc55d9738

[ "MIT" ]

4

2017-10-13T20:03:35.000Z

2018-10-10T20:21:22.000Z

search.py

FelixVicis/Google-EmailScraper

3c22116e28eb0ddef406c1d865ab147fc55d9738

[ "MIT" ]

4

2017-12-28T18:34:37.000Z

2019-12-29T09:06:55.000Z

search.py

FelixVicis/Google-EmailScraper

3c22116e28eb0ddef406c1d865ab147fc55d9738

[ "MIT" ]

1

2018-08-07T10:31:33.000Z

import google def websites(query, start=0, stop=None, per_page=10): return google.search(query, start=start, stop=stop, num=per_page)

23.333333

69

0.742857

23

140

4.434783

0.652174

0.196078

0

0.02459

0.128571

140

5

70

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0.811475

0

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0.333333

false

0

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null

0

1

0

null

0

1

0

1

0

5

1a5c87f18b01822ec32c651c5da44c45ac9c69b4

146

py

Python

consul_lib/__init__.py

syseleven/consul_lib

b85fdc71c98cd5b0dc4e93260e4b4b065a07604d

[ "MIT" ]

2

2018-12-03T12:50:49.000Z

2020-03-12T16:44:23.000Z

consul_lib/__init__.py

syseleven/consul_lib

b85fdc71c98cd5b0dc4e93260e4b4b065a07604d

[ "MIT" ]

3

2018-11-13T10:43:48.000Z

2019-07-31T13:13:27.000Z

consul_lib/__init__.py

syseleven/consul_lib

b85fdc71c98cd5b0dc4e93260e4b4b065a07604d

[ "MIT" ]

null

from .lock import Lock # noqa from .semaphore import Semaphore # noqa from .services import get_local_checks, get_failed_cluster_checks # noqa

36.5

73

0.80137

21

146

5.333333

0.52381

0.142857

0

0.150685

146

3

74

48.666667

0.903226

0.09589

0

1

0

true

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0

1

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0

null

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1

0

null

0

1

0

1

0

1

0

5

1a72c016bb19e89b2c979630892e0fbf61386de5

113

py

Python

sliding_window/__init__.py

gmum/ProtoPNet

d538c99a09f965d048ad094ebbdb24edab3472f5

[ "MIT" ]

1

2022-02-26T17:10:05.000Z

sliding_window/__init__.py

gmum/ProtoPNet

d538c99a09f965d048ad094ebbdb24edab3472f5

[ "MIT" ]

null

sliding_window/__init__.py

gmum/ProtoPNet

d538c99a09f965d048ad094ebbdb24edab3472f5

[ "MIT" ]

null

""" Code for training prototype segmentation model on Cityscapes dataset https://www.cityscapes-dataset.com/ """

22.6

68

0.778761

14

113

6.285714

0.857143

0.386364

0

0.106195

113

4

69

28.25

0.871287

0.920354

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

1

0

1

0

1

0

null

0

1

0

5

1a8688850d729e21715344bc820916f60681aa00

274

py

Python

aaaaa/test02.py

manlucas/atom

94963fc6fdfd0568473ee68e9d1631f421265359

[ "Apache-2.0" ]

null

aaaaa/test02.py

manlucas/atom

94963fc6fdfd0568473ee68e9d1631f421265359

[ "Apache-2.0" ]

8

2020-06-06T00:34:57.000Z

2021-06-10T22:30:24.000Z

aaaaa/test02.py

manlucas/atom

94963fc6fdfd0568473ee68e9d1631f421265359

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- if __name__ == '__main__': a = u'\u5f53\u524d\u4e91\u533a\u57df\u6ca1\u6709\u53ef\u7528\u7684' # PROXY\uff0c\u8bf7\u5148\u68c0\u67e5\u5e76\u5b89\u88c5', u'\u76f4\u8fde\u533a\u57df\uff0c\u4e0d\u80fd\u5b89\u88c5PROXY\u548cPAGENT' print(a)

39.142857

136

0.70438

40

274

4.625

0.85

0.108108

0

0.310204

0.105839

274

7

137

39.142857

0.444898

0.554745

0

0.566667

0.5

0

1

0

1

0

false

0

0.333333

0

null

0

1

0

1

0

1

0

1

null

1

0

5

1abe9a089db4e56bba9779688db8bcb6f171fcfb

163

py

Python

sports_manager/views/__init__.py

hbuyse/dj-sports-manager

7e32cc41347b968b4ede9ea6846de14d9504c3f9

[ "MIT" ]

null

sports_manager/views/__init__.py

hbuyse/dj-sports-manager

7e32cc41347b968b4ede9ea6846de14d9504c3f9

[ "MIT" ]

null

sports_manager/views/__init__.py

hbuyse/dj-sports-manager

7e32cc41347b968b4ede9ea6846de14d9504c3f9

[ "MIT" ]

null

# -*- coding utf-8 -*- from sports_manager.views.category import CategoryCreateView, CategoryDeleteView, CategoryDetailView, CategoryListView, CategoryUpdateView

40.75

138

0.828221

14

163

9.571429

1

0

0.006711

0.08589

163

3

139

54.333333

0.892617

0.122699

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

46e10c746d20624afbafc45ce519980f72c0b3f5

155

py

Python

tests/web_platform/css_flexbox_1/test_percentage_heights.py

jonboland/colosseum

cbf974be54fd7f6fddbe7285704cfaf7a866c5c5

[ "BSD-3-Clause" ]

71

2015-04-13T09:44:14.000Z

2019-03-24T01:03:02.000Z

tests/web_platform/css_flexbox_1/test_percentage_heights.py

jonboland/colosseum

cbf974be54fd7f6fddbe7285704cfaf7a866c5c5

[ "BSD-3-Clause" ]

35

2019-05-06T15:26:09.000Z

2022-03-28T06:30:33.000Z

tests/web_platform/css_flexbox_1/test_percentage_heights.py

jonboland/colosseum

cbf974be54fd7f6fddbe7285704cfaf7a866c5c5

[ "BSD-3-Clause" ]

139

2015-05-30T18:37:43.000Z

2019-03-27T17:14:05.000Z

from tests.utils import W3CTestCase class TestPercentageHeights(W3CTestCase): vars().update(W3CTestCase.find_tests(__file__, 'percentage-heights-'))

25.833333

74

0.8

16

155

7.4375

0.8125

0

0.021277

0.090323

155

5

75

31

0.822695

0

0.122581

0

1

0

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

46e5abf2c897e11f51534fa681ed917bd91f65c4

59

py

Python

tests/test_cnn2.py

CooperComputationalCaucus/BOML

c78ddea7261143522a7b10bc076ac03ca577d455

[ "MIT" ]

null

tests/test_cnn2.py

CooperComputationalCaucus/BOML

c78ddea7261143522a7b10bc076ac03ca577d455

[ "MIT" ]

null

tests/test_cnn2.py

CooperComputationalCaucus/BOML

c78ddea7261143522a7b10bc076ac03ca577d455

[ "MIT" ]

null

#TODO: Write and run tests of regression and classification

59

0.830508

9

59

5.444444

0.888889

0

0.135593

59

1

59

0.960784

0.983051

0

null

0

null

0

null

0

1

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

203c21bb68a40c77664d8d5c76387387cc2a4d12

174

py

Python

exercisio74.py

bruno194/EXERCICIOS

cf7f00020515731031275a9b8d2696d7bf3bb5dc

[ "MIT" ]

1

2022-02-25T13:28:46.000Z

exercisio74.py

bruno194/EXERCICIOS

cf7f00020515731031275a9b8d2696d7bf3bb5dc

[ "MIT" ]

null

exercisio74.py

bruno194/EXERCICIOS

cf7f00020515731031275a9b8d2696d7bf3bb5dc

[ "MIT" ]

null

from random import randint a = randint(1 , 10) , randint(1 , 10) ,randint(1 , 10) ,randint(1 , 10) ,randint(1 , 10) for i in a: print(f'{a}') print(max(a)) print(min(a))

29

88

0.609195

33

174

3.212121

0.424242

0.377358

0.471698

0.641509

0.471698

0

0.106383

0.189655

174

6

89

29

0.64539

0

0.017143

0

1

0

false

0

0.166667

0

0.166667

0.5

0

null

1

0

1

0

null

0

1

0

5

6461490d4488676a7dfeb5fcbbae145aee864858

2,905

py

Python

agency/python/src/reputation_api.py

nejc9921/reputation

fd232cffc182d045d3e0a202dcbc979b240cdafb

[ "MIT" ]

null

agency/python/src/reputation_api.py

nejc9921/reputation

fd232cffc182d045d3e0a202dcbc979b240cdafb

[ "MIT" ]

null

agency/python/src/reputation_api.py

nejc9921/reputation

fd232cffc182d045d3e0a202dcbc979b240cdafb

[ "MIT" ]

null

# MIT License # # Copyright (c) 2018 Stichting SingularityNET # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # Reputation Service API, including Rating Service and Ranking Service import abc #TODO @anton provide proper parameters for the methods """ Reputation Rating Service interface definition """ class RatingService(abc.ABC): @abc.abstractmethod def put_ratings(self): pass @abc.abstractmethod def get_ratings(self): pass @abc.abstractmethod def clear_ratings(self): pass """ Reputation Ranking Service interface definition """ class RankingService(abc.ABC): @abc.abstractmethod def update_ranks(self): pass @abc.abstractmethod def put_ranks(self): pass @abc.abstractmethod def get_ranks(self): pass @abc.abstractmethod def clear_ranks(self): pass #TODO @anton take this out to separate file and implement """ Reputation Service wrapper around Aigents Java-based implementation """ class AigentsReputationService(RatingService,RankingService): def clear_ratings(self): return("clear_ratings") def put_ratings(self): return("put_ratings") def get_ratings(self): return("get_ratings") def clear_ranks(self): return("clear_ranks") def put_ranks(self): return("put_ranks") def get_ranks(self): return("get_ranks") def update_ranks(self): return("update_ranks") #TODO @neic take this out to separate file and implement """ Reputation Service native implementation in Python """ class PythonReputationService(RatingService,RankingService): def clear_ratings(self): return("clear_ratings") def put_ratings(self): return("put_ratings") def get_ratings(self): return("get_ratings") def clear_ranks(self): return("clear_ranks") def put_ranks(self): return("put_ranks") def get_ranks(self): return("get_ranks") def update_ranks(self): return("update_ranks")

23.427419

80

0.752151

396

2,905

5.429293

0.356061

0.065116

0.055814

0.05814

0.398605

0.374419

0.288372

0

0.001651

0.165921

2,905

123

81

23.617886

0.885679

0.450947

0

0.907407

0

0.11463

0

0.02439

0

1

0.388889

false

0.12963

0.018519

0.259259

0.481481

0

null

0

1

0

null

0

1

0

1

0

1

0

1

0

5

6475f35b18566075f63cf68bd9b9d1206fda4f93

37

py

Python

trac/Lib/site-packages/codeexamplemacro-1.0_r11766-py2.7-patched.egg/codeexample/__init__.py

thinkbase/PortableTrac

9ea0210f6b88f135ef73f370b48127af0495b2d7

[ "BSD-3-Clause" ]

2

2015-08-06T04:19:21.000Z

2020-04-29T23:52:10.000Z

trac/Lib/site-packages/codeexamplemacro-1.0_r11766-py2.7-patched.egg/codeexample/__init__.py

thinkbase/PortableTrac

9ea0210f6b88f135ef73f370b48127af0495b2d7

[ "BSD-3-Clause" ]

null

trac/Lib/site-packages/codeexamplemacro-1.0_r11766-py2.7-patched.egg/codeexample/__init__.py

thinkbase/PortableTrac

9ea0210f6b88f135ef73f370b48127af0495b2d7

[ "BSD-3-Clause" ]

null

from code_example_processor import *

18.5

36

0.864865

5

37

6

1

0

0.108108

37

1

37

0.909091

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

649581e4786fc5717fab7476c5e42d5b9ddc0aa2

16,491

py

Python

Code/Train_cLapIRN.py

S-HuaBomb/Conditional_LapIRN

2afe563a796768406bd7e8c244696245ce74b57a

[ "MIT" ]

null

Code/Train_cLapIRN.py

S-HuaBomb/Conditional_LapIRN

2afe563a796768406bd7e8c244696245ce74b57a

[ "MIT" ]

null

Code/Train_cLapIRN.py

S-HuaBomb/Conditional_LapIRN

2afe563a796768406bd7e8c244696245ce74b57a

[ "MIT" ]

null

import glob import os import sys from argparse import ArgumentParser from datetime import datetime import numpy as np import torch import torch.utils.data as Data from Functions import generate_grid, Dataset_epoch, Predict_dataset, transform_unit_flow_to_flow_cuda, \ generate_grid_unit from miccai2021_model import Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl1, \ Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl2, Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl3, \ SpatialTransform_unit, SpatialTransformNearest_unit, smoothloss, \ neg_Jdet_loss, NCC, multi_resolution_NCC parser = ArgumentParser() parser.add_argument("--lr", type=float, dest="lr", default=1e-4, help="learning rate") parser.add_argument("--iteration_lvl1", type=int, dest="iteration_lvl1", default=30001, help="number of lvl1 iterations") parser.add_argument("--iteration_lvl2", type=int, dest="iteration_lvl2", default=30001, help="number of lvl2 iterations") parser.add_argument("--iteration_lvl3", type=int, dest="iteration_lvl3", default=60001, help="number of lvl3 iterations") parser.add_argument("--antifold", type=float, dest="antifold", default=0., help="Anti-fold loss: suggested range 1 to 10000") parser.add_argument("--checkpoint", type=int, dest="checkpoint", default=5000, help="frequency of saving models") parser.add_argument("--start_channel", type=int, dest="start_channel", default=7, # default:8, 7 for stage help="number of start channels") parser.add_argument("--datapath", type=str, dest="datapath", default='../Dataset/Brain_dataset/OASIS/crop_min_max/norm', help="data path for training images") parser.add_argument("--freeze_step", type=int, dest="freeze_step", default=3000, help="Number of step to freeze the previous level") opt = parser.parse_args() lr = opt.lr start_channel = opt.start_channel antifold = opt.antifold n_checkpoint = opt.checkpoint datapath = opt.datapath freeze_step = opt.freeze_step iteration_lvl1 = opt.iteration_lvl1 iteration_lvl2 = opt.iteration_lvl2 iteration_lvl3 = opt.iteration_lvl3 model_name = "LDR_OASIS_NCC_unit_disp_add_fea7_reg01_10_testing_" def train_lvl1(): print("Training lvl1...") model = Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl1(2, 3, start_channel, is_train=True, imgshape=imgshape_4, range_flow=range_flow).cuda() loss_similarity = NCC(win=3) loss_smooth = smoothloss loss_Jdet = neg_Jdet_loss transform = SpatialTransform_unit().cuda() for param in transform.parameters(): param.requires_grad = False param.volatile = True # OASIS names = sorted(glob.glob(datapath + '/*.nii')) grid_4 = generate_grid(imgshape_4) grid_4 = torch.from_numpy(np.reshape(grid_4, (1,) + grid_4.shape)).cuda().float() optimizer = torch.optim.Adam(model.parameters(), lr=lr) # optimizer = torch.optim.SGD(model.parameters(), lr=lr, momentum=0.9) model_dir = '../Model/Stage' if not os.path.isdir(model_dir): os.mkdir(model_dir) lossall = np.zeros((4, iteration_lvl1 + 1)) training_generator = Data.DataLoader(Dataset_epoch(names, norm=False), batch_size=1, shuffle=True, num_workers=2) step = 0 load_model = False if load_model is True: model_path = "../Model/LDR_LPBA_NCC_lap_share_preact_1_05_3000.pth" print("Loading weight: ", model_path) step = 3000 model.load_state_dict(torch.load(model_path)) temp_lossall = np.load("../Model/loss_LDR_LPBA_NCC_lap_share_preact_1_05_3000.npy") lossall[:, 0:3000] = temp_lossall[:, 0:3000] while step <= iteration_lvl1: for X, Y in training_generator: X = X.cuda().float() Y = Y.cuda().float() reg_code = torch.rand(1, dtype=X.dtype, device=X.device).unsqueeze(dim=0) F_X_Y, X_Y, Y_4x, F_xy, _ = model(X, Y, reg_code) loss_multiNCC = loss_similarity(X_Y, Y_4x) F_X_Y_norm = transform_unit_flow_to_flow_cuda(F_X_Y.permute(0, 2, 3, 4, 1).clone()) loss_Jacobian = loss_Jdet(F_X_Y_norm, grid_4) _, _, x, y, z = F_X_Y.shape norm_vector = torch.zeros((1, 3, 1, 1, 1), dtype=F_X_Y.dtype, device=F_X_Y.device) norm_vector[0, 0, 0, 0, 0] = (z - 1) norm_vector[0, 1, 0, 0, 0] = (y - 1) norm_vector[0, 2, 0, 0, 0] = (x - 1) loss_regulation = loss_smooth(F_X_Y * norm_vector) smo_weight = reg_code * max_smooth loss = loss_multiNCC + antifold * loss_Jacobian + smo_weight * loss_regulation optimizer.zero_grad() # clear gradients for this training step loss.backward() # backpropagation, compute gradients optimizer.step() # apply gradients lossall[:, step] = np.array( [loss.item(), loss_multiNCC.item(), loss_Jacobian.item(), loss_regulation.item()]) sys.stdout.write( "\r" + 'step "{0}" -> training loss "{1:.4f}" - sim_NCC "{2:4f}" - Jdet "{3:.10f}" -smo "{4:.4f} -reg_c "{5:.4f}"'.format( step, loss.item(), loss_multiNCC.item(), loss_Jacobian.item(), loss_regulation.item(), reg_code[0].item())) sys.stdout.flush() # with lr 1e-3 + with bias if step % n_checkpoint == 0: modelname = model_dir + '/' + model_name + "stagelvl1_" + str(step) + '.pth' torch.save(model.state_dict(), modelname) np.save(model_dir + '/loss' + model_name + "stagelvl1_" + str(step) + '.npy', lossall) step += 1 if step > iteration_lvl1: break print("one epoch pass") np.save(model_dir + '/loss' + model_name + 'stagelvl1.npy', lossall) def train_lvl2(): print("Training lvl2...") model_lvl1 = Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl1(2, 3, start_channel, is_train=True, imgshape=imgshape_4, range_flow=range_flow).cuda() model_path = sorted(glob.glob("../Model/Stage/" + model_name + "stagelvl1_?????.pth"))[-1] model_lvl1.load_state_dict(torch.load(model_path)) print("Loading weight for model_lvl1...", model_path) # Freeze model_lvl1 weight for param in model_lvl1.parameters(): param.requires_grad = False model = Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl2(2, 3, start_channel, is_train=True, imgshape=imgshape_2, range_flow=range_flow, model_lvl1=model_lvl1).cuda() loss_similarity = multi_resolution_NCC(win=5, scale=2) loss_smooth = smoothloss loss_Jdet = neg_Jdet_loss transform = SpatialTransform_unit().cuda() for param in transform.parameters(): param.requires_grad = False param.volatile = True # OASIS names = sorted(glob.glob(datapath + '/*.nii')) grid_2 = generate_grid(imgshape_2) grid_2 = torch.from_numpy(np.reshape(grid_2, (1,) + grid_2.shape)).cuda().float() optimizer = torch.optim.Adam(model.parameters(), lr=lr) # optimizer = torch.optim.SGD(model.parameters(), lr=lr, momentum=0.9) model_dir = '../Model/Stage' if not os.path.isdir(model_dir): os.mkdir(model_dir) lossall = np.zeros((4, iteration_lvl2 + 1)) training_generator = Data.DataLoader(Dataset_epoch(names, norm=False), batch_size=1, shuffle=True, num_workers=2) step = 0 load_model = False if load_model is True: model_path = "../Model/LDR_LPBA_NCC_lap_share_preact_1_05_3000.pth" print("Loading weight: ", model_path) step = 3000 model.load_state_dict(torch.load(model_path)) temp_lossall = np.load("../Model/loss_LDR_LPBA_NCC_lap_share_preact_1_05_3000.npy") lossall[:, 0:3000] = temp_lossall[:, 0:3000] while step <= iteration_lvl2: for X, Y in training_generator: X = X.cuda().float() Y = Y.cuda().float() reg_code = torch.rand(1, dtype=X.dtype, device=X.device).unsqueeze(dim=0) F_X_Y, X_Y, Y_4x, F_xy, F_xy_lvl1, _ = model(X, Y, reg_code) loss_multiNCC = loss_similarity(X_Y, Y_4x) F_X_Y_norm = transform_unit_flow_to_flow_cuda(F_X_Y.permute(0, 2, 3, 4, 1).clone()) loss_Jacobian = loss_Jdet(F_X_Y_norm, grid_2) _, _, x, y, z = F_X_Y.shape norm_vector = torch.zeros((1, 3, 1, 1, 1), dtype=F_X_Y.dtype, device=F_X_Y.device) norm_vector[0, 0, 0, 0, 0] = (z - 1) norm_vector[0, 1, 0, 0, 0] = (y - 1) norm_vector[0, 2, 0, 0, 0] = (x - 1) loss_regulation = loss_smooth(F_X_Y * norm_vector) smo_weight = reg_code * max_smooth loss = loss_multiNCC + antifold * loss_Jacobian + smo_weight * loss_regulation optimizer.zero_grad() # clear gradients for this training step loss.backward() # backpropagation, compute gradients optimizer.step() # apply gradients lossall[:, step] = np.array( [loss.item(), loss_multiNCC.item(), loss_Jacobian.item(), loss_regulation.item()]) sys.stdout.write( "\r" + 'step "{0}" -> training loss "{1:.4f}" - sim_NCC "{2:4f}" - Jdet "{3:.10f}" -smo "{4:.4f} -reg_c "{5:.4f}"'.format( step, loss.item(), loss_multiNCC.item(), loss_Jacobian.item(), loss_regulation.item(), reg_code[0].item())) sys.stdout.flush() # with lr 1e-3 + with bias if (step % n_checkpoint == 0): modelname = model_dir + '/' + model_name + "stagelvl2_" + str(step) + '.pth' torch.save(model.state_dict(), modelname) np.save(model_dir + '/loss' + model_name + "stagelvl2_" + str(step) + '.npy', lossall) if step == freeze_step: model.unfreeze_modellvl1() step += 1 if step > iteration_lvl2: break print("one epoch pass") np.save(model_dir + '/loss' + model_name + 'stagelvl2.npy', lossall) def train_lvl3(): print("Training lvl3...") model_lvl1 = Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl1(2, 3, start_channel, is_train=True, imgshape=imgshape_4, range_flow=range_flow).cuda() model_lvl2 = Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl2(2, 3, start_channel, is_train=True, imgshape=imgshape_2, range_flow=range_flow, model_lvl1=model_lvl1).cuda() model_path = sorted(glob.glob("../Model/Stage/" + model_name + "stagelvl2_?????.pth"))[-1] model_lvl2.load_state_dict(torch.load(model_path)) print("Loading weight for model_lvl2...", model_path) # Freeze model_lvl1 weight for param in model_lvl2.parameters(): param.requires_grad = False model = Miccai2021_LDR_conditional_laplacian_unit_disp_add_lvl3(2, 3, start_channel, is_train=True, imgshape=imgshape, range_flow=range_flow, model_lvl2=model_lvl2).cuda() loss_similarity = multi_resolution_NCC(win=7, scale=3) loss_smooth = smoothloss loss_Jdet = neg_Jdet_loss transform = SpatialTransform_unit().cuda() transform_nearest = SpatialTransformNearest_unit().cuda() for param in transform.parameters(): param.requires_grad = False param.volatile = True # OASIS names = sorted(glob.glob(datapath + '/*.nii')) grid = generate_grid(imgshape) grid = torch.from_numpy(np.reshape(grid, (1,) + grid.shape)).cuda().float() grid_unit = generate_grid_unit(imgshape) grid_unit = torch.from_numpy(np.reshape(grid_unit, (1,) + grid_unit.shape)).cuda().float() optimizer = torch.optim.Adam(model.parameters(), lr=lr) # optimizer = torch.optim.SGD(model.parameters(), lr=lr, momentum=0.9) model_dir = '../Model' if not os.path.isdir(model_dir): os.mkdir(model_dir) lossall = np.zeros((4, iteration_lvl3 + 1)) training_generator = Data.DataLoader(Dataset_epoch(names, norm=False), batch_size=1, shuffle=True, num_workers=2) step = 0 load_model = False if load_model is True: model_path = "../Model/LDR_LPBA_NCC_lap_share_preact_1_05_3000.pth" print("Loading weight: ", model_path) step = 3000 model.load_state_dict(torch.load(model_path)) temp_lossall = np.load("../Model/loss_LDR_LPBA_NCC_lap_share_preact_1_05_3000.npy") lossall[:, 0:3000] = temp_lossall[:, 0:3000] while step <= iteration_lvl3: for X, Y in training_generator: X = X.cuda().float() Y = Y.cuda().float() reg_code = torch.rand(1, dtype=X.dtype, device=X.device).unsqueeze(dim=0) F_X_Y, X_Y, Y_4x, F_xy, F_xy_lvl1, F_xy_lvl2, _ = model(X, Y, reg_code) loss_multiNCC = loss_similarity(X_Y, Y_4x) F_X_Y_norm = transform_unit_flow_to_flow_cuda(F_X_Y.permute(0, 2, 3, 4, 1).clone()) loss_Jacobian = loss_Jdet(F_X_Y_norm, grid) _, _, x, y, z = F_X_Y.shape norm_vector = torch.zeros((1, 3, 1, 1, 1), dtype=F_X_Y.dtype, device=F_X_Y.device) norm_vector[0, 0, 0, 0, 0] = (z - 1) norm_vector[0, 1, 0, 0, 0] = (y - 1) norm_vector[0, 2, 0, 0, 0] = (x - 1) loss_regulation = loss_smooth(F_X_Y * norm_vector) smo_weight = reg_code * max_smooth loss = loss_multiNCC + antifold * loss_Jacobian + smo_weight * loss_regulation optimizer.zero_grad() # clear gradients for this training step loss.backward() # backpropagation, compute gradients optimizer.step() # apply gradients lossall[:, step] = np.array( [loss.item(), loss_multiNCC.item(), loss_Jacobian.item(), loss_regulation.item()]) sys.stdout.write( "\r" + 'step "{0}" -> training loss "{1:.4f}" - sim_NCC "{2:4f}" - Jdet "{3:.10f}" -smo "{4:.4f} -reg_c "{5:.4f}"'.format( step, loss.item(), loss_multiNCC.item(), loss_Jacobian.item(), loss_regulation.item(), reg_code[0].item())) sys.stdout.flush() # with lr 1e-3 + with bias if step % n_checkpoint == 0: modelname = model_dir + '/' + model_name + "stagelvl3_" + str(step) + '.pth' torch.save(model.state_dict(), modelname) np.save(model_dir + '/loss' + model_name + "stagelvl3_" + str(step) + '.npy', lossall) # Put your validation code here # --------------------------------------- if step == freeze_step: model.unfreeze_modellvl2() step += 1 if step > iteration_lvl3: break print("one epoch pass") np.save(model_dir + '/loss' + model_name + 'stagelvl3.npy', lossall) imgshape = (160, 192, 144) imgshape_4 = (160 / 4, 192 / 4, 144 / 4) imgshape_2 = (160 / 2, 192 / 2, 144 / 2) range_flow = 0.4 max_smooth = 10. start_t = datetime.now() train_lvl1() train_lvl2() train_lvl3() # time end_t = datetime.now() total_t = end_t - start_t print("Time: ", total_t.total_seconds())

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0.007945

0.032774

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0.744869

0.723571

0.715405

0.692121

0.687597

0

0.041688

0.293069

16,491

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139

41.434673

0.735632

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0

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1

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0.107308

0.026986

0

1

0.010239

false

0.010239

0.03413

0

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null

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1

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null

0

5

b3bbea3ceef6d735318b5142e23764578478fe0a

21,276

py

Python

src/python_pachyderm/proto/auth/auth_pb2_grpc.py

barretthinson/python-pachyderm

82cea22d1105d70833a5522ccac750ca521694ff

[ "Apache-2.0" ]

null

src/python_pachyderm/proto/auth/auth_pb2_grpc.py

barretthinson/python-pachyderm

82cea22d1105d70833a5522ccac750ca521694ff

[ "Apache-2.0" ]

null

src/python_pachyderm/proto/auth/auth_pb2_grpc.py

barretthinson/python-pachyderm

82cea22d1105d70833a5522ccac750ca521694ff

[ "Apache-2.0" ]

null

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT! import grpc from python_pachyderm.proto.auth import auth_pb2 as client_dot_auth_dot_auth__pb2 class APIStub(object): # missing associated documentation comment in .proto file pass def __init__(self, channel): """Constructor. Args: channel: A grpc.Channel. """ self.Activate = channel.unary_unary( '/auth.API/Activate', request_serializer=client_dot_auth_dot_auth__pb2.ActivateRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.ActivateResponse.FromString, ) self.Deactivate = channel.unary_unary( '/auth.API/Deactivate', request_serializer=client_dot_auth_dot_auth__pb2.DeactivateRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.DeactivateResponse.FromString, ) self.GetConfiguration = channel.unary_unary( '/auth.API/GetConfiguration', request_serializer=client_dot_auth_dot_auth__pb2.GetConfigurationRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetConfigurationResponse.FromString, ) self.SetConfiguration = channel.unary_unary( '/auth.API/SetConfiguration', request_serializer=client_dot_auth_dot_auth__pb2.SetConfigurationRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.SetConfigurationResponse.FromString, ) self.GetAdmins = channel.unary_unary( '/auth.API/GetAdmins', request_serializer=client_dot_auth_dot_auth__pb2.GetAdminsRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetAdminsResponse.FromString, ) self.ModifyAdmins = channel.unary_unary( '/auth.API/ModifyAdmins', request_serializer=client_dot_auth_dot_auth__pb2.ModifyAdminsRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.ModifyAdminsResponse.FromString, ) self.GetClusterRoleBindings = channel.unary_unary( '/auth.API/GetClusterRoleBindings', request_serializer=client_dot_auth_dot_auth__pb2.GetClusterRoleBindingsRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetClusterRoleBindingsResponse.FromString, ) self.ModifyClusterRoleBinding = channel.unary_unary( '/auth.API/ModifyClusterRoleBinding', request_serializer=client_dot_auth_dot_auth__pb2.ModifyClusterRoleBindingRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.ModifyClusterRoleBindingResponse.FromString, ) self.Authenticate = channel.unary_unary( '/auth.API/Authenticate', request_serializer=client_dot_auth_dot_auth__pb2.AuthenticateRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.AuthenticateResponse.FromString, ) self.Authorize = channel.unary_unary( '/auth.API/Authorize', request_serializer=client_dot_auth_dot_auth__pb2.AuthorizeRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.AuthorizeResponse.FromString, ) self.WhoAmI = channel.unary_unary( '/auth.API/WhoAmI', request_serializer=client_dot_auth_dot_auth__pb2.WhoAmIRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.WhoAmIResponse.FromString, ) self.GetScope = channel.unary_unary( '/auth.API/GetScope', request_serializer=client_dot_auth_dot_auth__pb2.GetScopeRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetScopeResponse.FromString, ) self.SetScope = channel.unary_unary( '/auth.API/SetScope', request_serializer=client_dot_auth_dot_auth__pb2.SetScopeRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.SetScopeResponse.FromString, ) self.GetACL = channel.unary_unary( '/auth.API/GetACL', request_serializer=client_dot_auth_dot_auth__pb2.GetACLRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetACLResponse.FromString, ) self.SetACL = channel.unary_unary( '/auth.API/SetACL', request_serializer=client_dot_auth_dot_auth__pb2.SetACLRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.SetACLResponse.FromString, ) self.GetOIDCLogin = channel.unary_unary( '/auth.API/GetOIDCLogin', request_serializer=client_dot_auth_dot_auth__pb2.GetOIDCLoginRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetOIDCLoginResponse.FromString, ) self.GetAuthToken = channel.unary_unary( '/auth.API/GetAuthToken', request_serializer=client_dot_auth_dot_auth__pb2.GetAuthTokenRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetAuthTokenResponse.FromString, ) self.ExtendAuthToken = channel.unary_unary( '/auth.API/ExtendAuthToken', request_serializer=client_dot_auth_dot_auth__pb2.ExtendAuthTokenRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.ExtendAuthTokenResponse.FromString, ) self.RevokeAuthToken = channel.unary_unary( '/auth.API/RevokeAuthToken', request_serializer=client_dot_auth_dot_auth__pb2.RevokeAuthTokenRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.RevokeAuthTokenResponse.FromString, ) self.SetGroupsForUser = channel.unary_unary( '/auth.API/SetGroupsForUser', request_serializer=client_dot_auth_dot_auth__pb2.SetGroupsForUserRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.SetGroupsForUserResponse.FromString, ) self.ModifyMembers = channel.unary_unary( '/auth.API/ModifyMembers', request_serializer=client_dot_auth_dot_auth__pb2.ModifyMembersRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.ModifyMembersResponse.FromString, ) self.GetGroups = channel.unary_unary( '/auth.API/GetGroups', request_serializer=client_dot_auth_dot_auth__pb2.GetGroupsRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetGroupsResponse.FromString, ) self.GetUsers = channel.unary_unary( '/auth.API/GetUsers', request_serializer=client_dot_auth_dot_auth__pb2.GetUsersRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetUsersResponse.FromString, ) self.GetOneTimePassword = channel.unary_unary( '/auth.API/GetOneTimePassword', request_serializer=client_dot_auth_dot_auth__pb2.GetOneTimePasswordRequest.SerializeToString, response_deserializer=client_dot_auth_dot_auth__pb2.GetOneTimePasswordResponse.FromString, ) class APIServicer(object): # missing associated documentation comment in .proto file pass def Activate(self, request, context): """Activate/Deactivate the auth API. 'Activate' sets an initial set of admins for the Pachyderm cluster, and 'Deactivate' removes all ACLs, tokens, and admins from the Pachyderm cluster, making all data publicly accessable """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Deactivate(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetConfiguration(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def SetConfiguration(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetAdmins(self, request, context): """Deprecated. GetAdmins returns the current list of cluster super admins """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ModifyAdmins(self, request, context): """Deprecated. ModifyAdmins adds or removes super admins from the cluster """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetClusterRoleBindings(self, request, context): """GetClusterRoleBindings returns the current set of cluster role bindings """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ModifyClusterRoleBinding(self, request, context): """ModifyAdmin sets the list of admin roles for a principal """ context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Authenticate(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def Authorize(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def WhoAmI(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetScope(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def SetScope(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetACL(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def SetACL(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetOIDCLogin(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetAuthToken(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ExtendAuthToken(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def RevokeAuthToken(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def SetGroupsForUser(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def ModifyMembers(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetGroups(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetUsers(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def GetOneTimePassword(self, request, context): # missing associated documentation comment in .proto file pass context.set_code(grpc.StatusCode.UNIMPLEMENTED) context.set_details('Method not implemented!') raise NotImplementedError('Method not implemented!') def add_APIServicer_to_server(servicer, server): rpc_method_handlers = { 'Activate': grpc.unary_unary_rpc_method_handler( servicer.Activate, request_deserializer=client_dot_auth_dot_auth__pb2.ActivateRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.ActivateResponse.SerializeToString, ), 'Deactivate': grpc.unary_unary_rpc_method_handler( servicer.Deactivate, request_deserializer=client_dot_auth_dot_auth__pb2.DeactivateRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.DeactivateResponse.SerializeToString, ), 'GetConfiguration': grpc.unary_unary_rpc_method_handler( servicer.GetConfiguration, request_deserializer=client_dot_auth_dot_auth__pb2.GetConfigurationRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetConfigurationResponse.SerializeToString, ), 'SetConfiguration': grpc.unary_unary_rpc_method_handler( servicer.SetConfiguration, request_deserializer=client_dot_auth_dot_auth__pb2.SetConfigurationRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.SetConfigurationResponse.SerializeToString, ), 'GetAdmins': grpc.unary_unary_rpc_method_handler( servicer.GetAdmins, request_deserializer=client_dot_auth_dot_auth__pb2.GetAdminsRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetAdminsResponse.SerializeToString, ), 'ModifyAdmins': grpc.unary_unary_rpc_method_handler( servicer.ModifyAdmins, request_deserializer=client_dot_auth_dot_auth__pb2.ModifyAdminsRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.ModifyAdminsResponse.SerializeToString, ), 'GetClusterRoleBindings': grpc.unary_unary_rpc_method_handler( servicer.GetClusterRoleBindings, request_deserializer=client_dot_auth_dot_auth__pb2.GetClusterRoleBindingsRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetClusterRoleBindingsResponse.SerializeToString, ), 'ModifyClusterRoleBinding': grpc.unary_unary_rpc_method_handler( servicer.ModifyClusterRoleBinding, request_deserializer=client_dot_auth_dot_auth__pb2.ModifyClusterRoleBindingRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.ModifyClusterRoleBindingResponse.SerializeToString, ), 'Authenticate': grpc.unary_unary_rpc_method_handler( servicer.Authenticate, request_deserializer=client_dot_auth_dot_auth__pb2.AuthenticateRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.AuthenticateResponse.SerializeToString, ), 'Authorize': grpc.unary_unary_rpc_method_handler( servicer.Authorize, request_deserializer=client_dot_auth_dot_auth__pb2.AuthorizeRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.AuthorizeResponse.SerializeToString, ), 'WhoAmI': grpc.unary_unary_rpc_method_handler( servicer.WhoAmI, request_deserializer=client_dot_auth_dot_auth__pb2.WhoAmIRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.WhoAmIResponse.SerializeToString, ), 'GetScope': grpc.unary_unary_rpc_method_handler( servicer.GetScope, request_deserializer=client_dot_auth_dot_auth__pb2.GetScopeRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetScopeResponse.SerializeToString, ), 'SetScope': grpc.unary_unary_rpc_method_handler( servicer.SetScope, request_deserializer=client_dot_auth_dot_auth__pb2.SetScopeRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.SetScopeResponse.SerializeToString, ), 'GetACL': grpc.unary_unary_rpc_method_handler( servicer.GetACL, request_deserializer=client_dot_auth_dot_auth__pb2.GetACLRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetACLResponse.SerializeToString, ), 'SetACL': grpc.unary_unary_rpc_method_handler( servicer.SetACL, request_deserializer=client_dot_auth_dot_auth__pb2.SetACLRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.SetACLResponse.SerializeToString, ), 'GetOIDCLogin': grpc.unary_unary_rpc_method_handler( servicer.GetOIDCLogin, request_deserializer=client_dot_auth_dot_auth__pb2.GetOIDCLoginRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetOIDCLoginResponse.SerializeToString, ), 'GetAuthToken': grpc.unary_unary_rpc_method_handler( servicer.GetAuthToken, request_deserializer=client_dot_auth_dot_auth__pb2.GetAuthTokenRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetAuthTokenResponse.SerializeToString, ), 'ExtendAuthToken': grpc.unary_unary_rpc_method_handler( servicer.ExtendAuthToken, request_deserializer=client_dot_auth_dot_auth__pb2.ExtendAuthTokenRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.ExtendAuthTokenResponse.SerializeToString, ), 'RevokeAuthToken': grpc.unary_unary_rpc_method_handler( servicer.RevokeAuthToken, request_deserializer=client_dot_auth_dot_auth__pb2.RevokeAuthTokenRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.RevokeAuthTokenResponse.SerializeToString, ), 'SetGroupsForUser': grpc.unary_unary_rpc_method_handler( servicer.SetGroupsForUser, request_deserializer=client_dot_auth_dot_auth__pb2.SetGroupsForUserRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.SetGroupsForUserResponse.SerializeToString, ), 'ModifyMembers': grpc.unary_unary_rpc_method_handler( servicer.ModifyMembers, request_deserializer=client_dot_auth_dot_auth__pb2.ModifyMembersRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.ModifyMembersResponse.SerializeToString, ), 'GetGroups': grpc.unary_unary_rpc_method_handler( servicer.GetGroups, request_deserializer=client_dot_auth_dot_auth__pb2.GetGroupsRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetGroupsResponse.SerializeToString, ), 'GetUsers': grpc.unary_unary_rpc_method_handler( servicer.GetUsers, request_deserializer=client_dot_auth_dot_auth__pb2.GetUsersRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetUsersResponse.SerializeToString, ), 'GetOneTimePassword': grpc.unary_unary_rpc_method_handler( servicer.GetOneTimePassword, request_deserializer=client_dot_auth_dot_auth__pb2.GetOneTimePasswordRequest.FromString, response_serializer=client_dot_auth_dot_auth__pb2.GetOneTimePasswordResponse.SerializeToString, ), } generic_handler = grpc.method_handlers_generic_handler( 'auth.API', rpc_method_handlers) server.add_generic_rpc_handlers((generic_handler,))

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null

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5

b3fa0782717a39fa918b7977539bdb3b3c1c4471

20

py

Python

version.py

Dranion/s3am

1100b794eee98d4985df3b295e396de797ba4d61

[ "Apache-2.0" ]

12

2015-04-09T03:09:46.000Z

2021-10-10T22:16:40.000Z

version.py

BD2KGenomics/s3am

d0e26e89fcd7d0e9e51aef75d4f29f5c5a5ac14c

[ "Apache-2.0" ]

57

2015-02-18T07:21:38.000Z

2017-04-24T04:59:52.000Z

version.py

Dranion/s3am

1100b794eee98d4985df3b295e396de797ba4d61

[ "Apache-2.0" ]

8

2015-09-25T06:57:51.000Z

2021-10-10T22:16:31.000Z

version = '2.1.0a1'

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19

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null

0

5

b3ffd50808c3ea5f3c56c8b84912e34ca2ae1d8d

31

py

Python

bitirmetezi/venv/Lib/site-packages/plot/matplotlibConfig/__init__.py

busraltun/IMPLEMENTATIONOFEYECONTROLLEDVIRTUALKEYBOARD

fa3a9b150419a17aa82f41b068a5d69d0ff0d0f3

[ "MIT" ]

1

2020-04-10T08:14:43.000Z

bitirmetezi/venv/Lib/site-packages/plot/matplotlibConfig/__init__.py

busraltun/IMPLEMENTATIONOFEYECONTROLLEDVIRTUALKEYBOARD

fa3a9b150419a17aa82f41b068a5d69d0ff0d0f3

[ "MIT" ]

1

2016-11-30T20:37:27.000Z

2016-12-12T11:55:50.000Z

bitirmetezi/venv/Lib/site-packages/plot/matplotlibConfig/__init__.py

busraltun/IMPLEMENTATIONOFEYECONTROLLEDVIRTUALKEYBOARD

fa3a9b150419a17aa82f41b068a5d69d0ff0d0f3

[ "MIT" ]

1

2019-12-18T07:56:00.000Z

from .rcParams import rcParams

15.5

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6.5

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null

0

1

0

1

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5

37725063ebccd75358f5bee40f22b65f3b415c00

94

py

Python

bookstone/exceptions.py

Timtam/bookstone

fe06e35ad18c51e452d400a5e679aa2824931557

[ "MIT" ]

null

bookstone/exceptions.py

Timtam/bookstone

fe06e35ad18c51e452d400a5e679aa2824931557

[ "MIT" ]

3

2020-10-29T23:55:17.000Z

2021-04-16T20:41:46.000Z

bookstone/exceptions.py

Timtam/bookstone

fe06e35ad18c51e452d400a5e679aa2824931557

[ "MIT" ]

null

class BackendError(Exception): pass class ThreadStoppedError(Exception): pass

13.428571

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0.234043

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1

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true

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1

0

null

1

0

1

0

null

0

1

0

5

377a8619fcd7a43bc299016c5c4b7a5fd7e37030

313

py

Python

errpred/__init__.py

Ithric/keras-error-predictor

c8272ee27c5c64ba12b10dd0bb94e58513edf429

[ "MIT" ]

null

errpred/__init__.py

Ithric/keras-error-predictor

c8272ee27c5c64ba12b10dd0bb94e58513edf429

[ "MIT" ]

null

errpred/__init__.py

Ithric/keras-error-predictor

c8272ee27c5c64ba12b10dd0bb94e58513edf429

[ "MIT" ]

null

from errpred.errutils import copy_model, normalize_data, split_train_validation, to_shape, fit_model, print_summary, split_train_test from errpred.aleatoric_error import create_error_model, train_error_model, predict_error from errpred.epistemic_error import create_epistemic_error_model, estimate_epistemic_error

104.333333

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0.897764

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104.333333

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true

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0.333333

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null

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1

0

null

0

1

0

1

0

1

0

5

37ca709962d19336868ab8cda93251e3f64b9b0b

732

py

Python

soni_f110_ws/build/f110-skeletons-spring2020/system/vesc/vesc_driver/catkin_generated/pkg.develspace.context.pc.py

4-legends/Paresh-Soni-F110-2020

24b8d6ee654d4b0f78dc2bf643f0f850e5c0ca85

[ "MIT" ]

null

soni_f110_ws/build/f110-skeletons-spring2020/system/vesc/vesc_driver/catkin_generated/pkg.develspace.context.pc.py

4-legends/Paresh-Soni-F110-2020

24b8d6ee654d4b0f78dc2bf643f0f850e5c0ca85

[ "MIT" ]

null

soni_f110_ws/build/f110-skeletons-spring2020/system/vesc/vesc_driver/catkin_generated/pkg.develspace.context.pc.py

4-legends/Paresh-Soni-F110-2020

24b8d6ee654d4b0f78dc2bf643f0f850e5c0ca85

[ "MIT" ]

null

# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "/home/graspinglab/carla-ros-bridge/Paresh-Soni-F110-2020/soni_f110_ws/src/f110-skeletons-spring2020/system/vesc/vesc_driver/include".split(';') if "/home/graspinglab/carla-ros-bridge/Paresh-Soni-F110-2020/soni_f110_ws/src/f110-skeletons-spring2020/system/vesc/vesc_driver/include" != "" else [] PROJECT_CATKIN_DEPENDS = "nodelet;pluginlib;roscpp;std_msgs;vesc_msgs;serial".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "vesc_driver" PROJECT_SPACE_DIR = "/home/graspinglab/carla-ros-bridge/Paresh-Soni-F110-2020/soni_f110_ws/devel" PROJECT_VERSION = "0.0.1"

81.333333

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732

8

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91.5

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false

0

null

0

1

0

1

null

0

5

37ccaf97e53097669cba52e77bbfd2e944194f9d

110

py

Python

examples/theworldfoundry/theworldfoundry/components/important.py

vreon/figment

03696ee1c2288805d2a041f4116813d2f81640f8

[ "MIT" ]

12

2016-12-01T19:30:54.000Z

2020-12-15T13:16:52.000Z

examples/theworldfoundry/theworldfoundry/components/important.py

vreon/figment

03696ee1c2288805d2a041f4116813d2f81640f8

[ "MIT" ]

null

examples/theworldfoundry/theworldfoundry/components/important.py

vreon/figment

03696ee1c2288805d2a041f4116813d2f81640f8

[ "MIT" ]

1

2020-09-15T18:56:34.000Z

from figment import Component class Important(Component): """An item that can't be dropped or taken."""

18.333333

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16

110

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0.9375

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0.181818

110

5

50

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0.877778

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0

1

0

true

0

1

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1.5

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1

0

null

0

1

0

1

0

1

0

5

807aed00017a263819144c0b01346494f6e037c6

148

py

Python

tizza/pizza/admin.py

RicardoMorato/DesignOfMicroservices

539ac040ffad729957dd923d0c3124d255c2bc5a

[ "MIT" ]

null

tizza/pizza/admin.py

RicardoMorato/DesignOfMicroservices

539ac040ffad729957dd923d0c3124d255c2bc5a

[ "MIT" ]

null

tizza/pizza/admin.py

RicardoMorato/DesignOfMicroservices

539ac040ffad729957dd923d0c3124d255c2bc5a

[ "MIT" ]

null

from django.contrib import admin from .models import Pizza class PizzaAdmin(admin.ModelAdmin): pass admin.site.register(Pizza, PizzaAdmin)

13.454545

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0.777027

19

148

6.052632

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10

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14.8

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true

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1

0

null

0

null

0

1

0

1

0

5

80abdbe778467ffb6b03846c21f8641b8f7a9856

128

py

Python

Python/AWS_Search_Private_IP.py

Blue-Comet/AWS-CD

fe32ae0c992b9906b97eae444e09851bbf115d75

[ "Apache-2.0" ]

null

Python/AWS_Search_Private_IP.py

Blue-Comet/AWS-CD

fe32ae0c992b9906b97eae444e09851bbf115d75

[ "Apache-2.0" ]

null

Python/AWS_Search_Private_IP.py

Blue-Comet/AWS-CD

fe32ae0c992b9906b97eae444e09851bbf115d75

[ "Apache-2.0" ]

null

version https://git-lfs.github.com/spec/v1 oid sha256:e0de201cc6d4630bd3cdb656ecbb417301e87061aae5be10fdc65ec64d826a2f size 811

32

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128

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42.666667

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1

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1

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null

1

0

1

0

5

80ac068ca5610741b60acd39b8a1fe0bde98049c

32

py

Python

python/Legacy/micro.py

LostLucidity/lucid_ai

0811fd7169015d7ba61d5ee54ce01f60129aeb61

[ "MIT" ]

2

2020-08-13T01:25:20.000Z

2020-11-22T19:00:06.000Z

python/Legacy/micro.py

LostLucidity/lucid_ai

0811fd7169015d7ba61d5ee54ce01f60129aeb61

[ "MIT" ]

null

python/Legacy/micro.py

LostLucidity/lucid_ai

0811fd7169015d7ba61d5ee54ce01f60129aeb61

[ "MIT" ]

null

# adjust iteration when microing

32

0.84375

4

32

6.75

1

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32

1

32

0.964286

0.9375

0

null

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true

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1

0

null

0

1

0

5

80eaf021e113ff89511e921e4eacab7c9c0d4050

218

py

Python

common/models.py

farhad0085/django-money-management

d4622192d6b9df3f785abd5f4ef1bfcbf465d045

[ "MIT" ]

null

common/models.py

farhad0085/django-money-management

d4622192d6b9df3f785abd5f4ef1bfcbf465d045

[ "MIT" ]

null

common/models.py

farhad0085/django-money-management

d4622192d6b9df3f785abd5f4ef1bfcbf465d045

[ "MIT" ]

null

from django.db import models class TrackingModel(models.Model): created_utc = models.DateTimeField(auto_now_add=True) updated_utc = models.DateTimeField(auto_now=True) class Meta: abstract = True

24.222222

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80edc45454e2a0198d7bd443b563414116a934f4

183

py

Python

aio_geojson_nsw_transport_incidents/__init__.py

Fred-Ch/python-aio-geojson-nsw-transport-incidents-master

aea1e5e0a4a90c5aa8aa277e936ac8ba09f11ec5

[ "Apache-2.0" ]

null

aio_geojson_nsw_transport_incidents/__init__.py

Fred-Ch/python-aio-geojson-nsw-transport-incidents-master

aea1e5e0a4a90c5aa8aa277e936ac8ba09f11ec5

[ "Apache-2.0" ]

null

aio_geojson_nsw_transport_incidents/__init__.py

Fred-Ch/python-aio-geojson-nsw-transport-incidents-master

aea1e5e0a4a90c5aa8aa277e936ac8ba09f11ec5

[ "Apache-2.0" ]

null

"""NSW Transport Service Incidents library.""" from .feed import NswTransportServiceIncidentsFeed # noqa from .feed_manager import NswTransportServiceIncidentsFeedManager # noqa

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py

Python

kopf_entrypoint.py

MridulS/amalthea

c88cfa4c819c8ab539f470ff56c00a0caf489101

[ "Apache-2.0" ]

18

2021-09-29T09:37:52.000Z

2022-03-04T07:52:18.000Z

kopf_entrypoint.py

MridulS/amalthea

c88cfa4c819c8ab539f470ff56c00a0caf489101

[ "Apache-2.0" ]

45

2021-08-22T10:24:39.000Z

2022-03-31T09:12:48.000Z

kopf_entrypoint.py

MridulS/amalthea

c88cfa4c819c8ab539f470ff56c00a0caf489101

[ "Apache-2.0" ]

1

2021-09-21T12:14:52.000Z

# The the logic of the script expected by kopf is # in a module inside the controller package. from controller import server_controller

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py

Python

yomitai/__main__.py

noxowl/yomitai

912f180e3a8100cb167d0aa9a45a770ecc47f4ca

[ "MIT" ]

null

yomitai/__main__.py

noxowl/yomitai

912f180e3a8100cb167d0aa9a45a770ecc47f4ca

[ "MIT" ]

null

yomitai/__main__.py

noxowl/yomitai

912f180e3a8100cb167d0aa9a45a770ecc47f4ca

[ "MIT" ]

null

from .main import app app(prog_name='yomitai')

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47

py

Python

enthought/pyface/ui/qt4/gui.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/pyface/ui/qt4/gui.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/pyface/ui/qt4/gui.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from pyface.ui.qt4.gui import *

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227

py

Python

apps/reader/admin.py

starsep/NewsBlur

6c59416ca82377ca1bbc7d044890bdead3eba904

[ "MIT" ]

3,073

2015-01-01T07:20:18.000Z

2022-03-31T20:33:41.000Z

apps/reader/admin.py

starsep/NewsBlur

6c59416ca82377ca1bbc7d044890bdead3eba904

[ "MIT" ]

1,054

2015-01-02T13:32:35.000Z

2022-03-30T04:21:21.000Z

apps/reader/admin.py

starsep/NewsBlur

6c59416ca82377ca1bbc7d044890bdead3eba904

[ "MIT" ]

676

2015-01-03T16:40:29.000Z

2022-03-30T14:00:40.000Z

from apps.reader.models import UserSubscription, UserSubscriptionFolders, Feature from django.contrib import admin admin.site.register(UserSubscription) admin.site.register(UserSubscriptionFolders) admin.site.register(Feature)

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ff17f34f86bac6006d3feb5cdfbe4babafa7f15d

12,660

py

Python

src/explorepy/cli.py

hacklschorsch/explorepy

407435c5e3948bdf150b412001b7f48854e846e5

[ "MIT" ]

null

src/explorepy/cli.py

hacklschorsch/explorepy

407435c5e3948bdf150b412001b7f48854e846e5

[ "MIT" ]

null

src/explorepy/cli.py

hacklschorsch/explorepy

407435c5e3948bdf150b412001b7f48854e846e5

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Command Line Interface module for explorepy""" import click import explorepy from sys import platform as _platform CONTEXT_SETTINGS = dict(help_option_names=['-h', '--help']) if _platform == 'darwin': default_bt_backend = 'sdk' else: default_bt_backend = 'pybluez' @click.group(context_settings=CONTEXT_SETTINGS, invoke_without_command=True) @click.option("--version", "-V", help="Print explorepy version", is_flag=True) @click.pass_context def cli(ctx, version, args=None): """Python API for Mentalab biosignal aquisition devices""" if ctx.invoked_subcommand is None: if version: click.echo(explorepy.__version__) else: click.echo(ctx.get_help()) @cli.command() @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface (default: pybluez)", default=default_bt_backend) def find_device(bluetooth): """List available Explore devices.""" explorepy.set_bt_interface(bluetooth) explorepy.tools.bt_scan() @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-d", "--duration", type=int, help="Duration in seconds", metavar="<integer>") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface (default: pybluez)", default=default_bt_backend) def acquire(name, address, duration, bluetooth): """Connect to a device with selected name or address. Only one input is necessary""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.acquire(duration) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-f", "--filename", help="Name of the file.", required=True, type=click.Path(file_okay=True, dir_okay=True, resolve_path=True)) @click.option("-ow", "--overwrite", is_flag=True, help="Overwrite existing file") @click.option("-d", "--duration", type=int, help="Recording duration in seconds", metavar="<integer>") @click.option("--edf", 'file_type', flag_value='edf', help="Write in EDF file (default type)", default=True) @click.option("--csv", 'file_type', flag_value='csv', help="Write in csv file") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface (default: pybluez)", default=default_bt_backend) def record_data(address, name, filename, overwrite, duration, file_type, bluetooth): """Record data from Explore to a file """ if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.record_data(file_name=filename, file_type=file_type, do_overwrite=overwrite, duration=duration, block=True) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-d", "--duration", type=int, help="Streaming duration in seconds", metavar="<integer>") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface (default: pybluez)", default=default_bt_backend) def push2lsl(address, name, duration, bluetooth): """Push data to lsl""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.push2lsl(duration) @cli.command() @click.option("-f", "--filename", help="Name of (and path to) the binary file.", required=True, type=click.Path(exists=True, file_okay=True, dir_okay=True, resolve_path=True)) @click.option("-ow", "--overwrite", is_flag=True, help="Overwrite existing file") def bin2csv(filename, overwrite): """Convert a binary file to CSV""" explore = explorepy.explore.Explore() explore.convert_bin(bin_file=filename, do_overwrite=overwrite, file_type='csv') @cli.command() @click.option("-f", "--filename", help="Name of (and path to) the binary file.", required=True, type=click.Path(exists=True, file_okay=True, dir_okay=True, resolve_path=True)) @click.option("-ow", "--overwrite", is_flag=True, help="Overwrite existing file") def bin2edf(filename, overwrite): """Convert a binary file to EDF (BDF+)""" explore = explorepy.explore.Explore() explore.convert_bin(bin_file=filename, do_overwrite=overwrite, file_type='edf') @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-nf", "--notchfreq", type=click.Choice(['50', '60']), help="Frequency of notch filter.", default='50') @click.option("-lf", "--lowfreq", type=float, help="Low cutoff frequency of bandpass/highpass filter.") @click.option("-hf", "--highfreq", type=float, help="High cutoff frequency of bandpass/lowpass filter.") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def visualize(address, name, notchfreq, lowfreq, highfreq, bluetooth): """Visualizing signal in a browser-based dashboard""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.visualize(notch_freq=int(notchfreq), bp_freq=(lowfreq, highfreq)) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-nf", "--notchfreq", type=click.Choice(['50', '60']), help="Frequency of notch filter.", default='50') @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def impedance(address, name, notchfreq, bluetooth): """Impedance measurement in a browser-based dashboard""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.measure_imp(notch_freq=int(notchfreq)) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def format_memory(address, name, bluetooth): """format the memory of Explore device""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.format_memory() @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-sr", "--sampling-rate", help="Sampling rate of ExG channels, it can be 250 or 500", type=click.Choice(['250', '500', '1000']), required=True) @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def set_sampling_rate(address, name, sampling_rate, bluetooth): """Change sampling rate of the Explore device""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.set_sampling_rate(int(sampling_rate)) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def soft_reset(address, name, bluetooth): """Software reset of Explore device""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) """Reset the selected explore device (current session will be terminated).""" explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.reset_soft() @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-m", "--channel-mask", type=click.IntRange(min=1, max=255), required=True, help="Channel mask, it should be an integer between 1 and 255, the binary representation will be " "interpreted as mask.") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def set_channels(address, name, channel_mask, bluetooth): """Mask the channels of selected explore device""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.set_channels(channel_mask) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-m", "--module", required=True, type=str, help="Module name to be disabled, options: ORN, ENV, EXG") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def disable_module(address, name, module, bluetooth): """Disable a module of Explore device""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.disable_module(module) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-m", "--module", required=True, type=str, help="Module name to be enabled, options: ORN, ENV, EXG") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def enable_module(address, name, module, bluetooth): """Enable a module of Explore device""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.enable_module(module) @cli.command() @click.option("--address", "-a", type=str, help="Explore device's MAC address") @click.option("--name", "-n", type=str, help="Name of the device") @click.option("-ow", "--overwrite", is_flag=True, help="Overwrite existing file") @click.option("--bluetooth", "-bt", type=click.Choice(['sdk', 'pybluez']), help="Select the Bluetooth interface", default=default_bt_backend) def calibrate_orn(address, name, overwrite, bluetooth): """Calibrate the orientation module of the specified device""" if name is None and address is None: raise ValueError("Either name or address must be given!") explorepy.set_bt_interface(bluetooth) explore = explorepy.explore.Explore() explore.connect(mac_address=address, device_name=name) explore.calibrate_orn(do_overwrite=overwrite)

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5

205b81a4d5936ec8eb2be40238df34f42cf74f7e

176

py

Python

pyprac/movie_search_console_ui.py

manojbhargavan/python_practice

599d47af7798345db9543b05e5da4ac8930fa412

[ "MIT" ]

null

pyprac/movie_search_console_ui.py

manojbhargavan/python_practice

599d47af7798345db9543b05e5da4ac8930fa412

[ "MIT" ]

null

pyprac/movie_search_console_ui.py

manojbhargavan/python_practice

599d47af7798345db9543b05e5da4ac8930fa412

[ "MIT" ]

null

from movies_search import MoviesSearch movie_to_search = input('Enter a movie name or part of it: ') search = MoviesSearch(movie_to_search) search.get_formatted_result()

29.333333

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1

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null

0

5

20f587d4841bfc1eb4ee255e77ccd96851c5aebe

204

py

Python

mmfashion/utils/__init__.py

lijiancheng0614/mmfashion

f67b6ebc45252356d9f40a185c40894429f43a13

[ "Apache-2.0" ]

2

2020-05-26T03:14:24.000Z

2021-01-31T18:23:47.000Z

mmfashion/utils/__init__.py

ceciliaAI/mmfashion

0161ec8717f129433271a796a3d3a6b540b005a3

[ "Apache-2.0" ]

null

mmfashion/utils/__init__.py

ceciliaAI/mmfashion

0161ec8717f129433271a796a3d3a6b540b005a3

[ "Apache-2.0" ]

null

from .checkpoint import init_weights_from from .image import get_img_tensor from .registry import Registry, build_from_cfg __all__ = ['Registry', 'build_from_cfg', 'get_img_tensor', 'init_weights_from']

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5

4561ec0c7487642899455ccc3ff726120ddf3e2e

4,761

py

Python

tests/test_adb.py

RakhithJK/andriller

be94bc5aff84069395c333bdf472f39b550bdba7

[ "MIT" ]

883

2019-12-14T10:47:48.000Z

2022-03-30T12:35:19.000Z

tests/test_adb.py

RakhithJK/andriller

be94bc5aff84069395c333bdf472f39b550bdba7

[ "MIT" ]

40

2019-12-18T03:04:28.000Z

2022-03-30T03:07:05.000Z

tests/test_adb.py

RakhithJK/andriller

be94bc5aff84069395c333bdf472f39b550bdba7

[ "MIT" ]

169

2019-12-15T17:08:41.000Z

2022-03-25T12:52:12.000Z

import sys import pytest import tempfile import subprocess from unittest import mock from andriller import adb_conn fake_adb = tempfile.NamedTemporaryFile() @pytest.fixture def ADB(mocker): mocker.patch('andriller.adb_conn.ADBConn.kill') mocker.patch('andriller.adb_conn.ADBConn._opt_use_capture', return_value=True) with mock.patch('andriller.adb_conn.ADBConn._get_adb_bin', return_value=fake_adb.name): with mock.patch('andriller.adb_conn.ADBConn._adb_has_exec', return_value=True): adb = adb_conn.ADBConn() adb_cmd = adb.adb.__func__ setattr(adb, 'adb', lambda *args, **kwargs: adb_cmd(adb, *args, **kwargs)) return adb @pytest.fixture def ADB_alt(mocker): mocker.patch('andriller.adb_conn.ADBConn.kill') mocker.patch('andriller.adb_conn.ADBConn._opt_use_capture', return_value=False) with mock.patch('andriller.adb_conn.ADBConn._get_adb_bin', return_value=fake_adb.name): with mock.patch('andriller.adb_conn.ADBConn._adb_has_exec', return_value=False): adb = adb_conn.ADBConn() adb_cmd = adb.adb.__func__ setattr(adb, 'adb', lambda *args, **kwargs: adb_cmd(adb, *args, **kwargs)) return adb @pytest.fixture def ADB_win(mocker): mock_sub = mocker.patch('andriller.adb_conn.subprocess', autospec=True) mock_sub.STARTUPINFO = mock.MagicMock() mock_sub.STARTF_USESHOWWINDOW = mock.MagicMock() mocker.patch('andriller.adb_conn.ADBConn.kill') mocker.patch('andriller.adb_conn.ADBConn._opt_use_capture', return_value=True) with mock.patch('sys.platform', return_value='win32'): with mock.patch('andriller.adb_conn.ADBConn._get_adb_bin', return_value=fake_adb.name): with mock.patch('andriller.adb_conn.ADBConn._adb_has_exec', return_value=True): adb = adb_conn.ADBConn() return adb def test_init_windows(ADB_win): assert ADB_win.startupinfo is not None assert ADB_win.rmr == b'\r\r\n' @pytest.mark.parametrize('file_path, result', [ ('/some/file.txt', '/some/file.txt\n'), ('/some/my file.txt', '/some/my file.txt\n'), ('some/file.txt', 'some/file.txt\n'), ]) def test_file_regex(file_path, result): assert adb_conn.ADBConn._file_regex(file_path).match(result) def test_adb_simple(ADB, mocker): output = mock.Mock(stdout=b'lala', returncode=0) mock_run = mocker.patch('andriller.adb_conn.subprocess.run', return_value=output) res = ADB('hello') assert res == 'lala' mock_run.assert_called_with([fake_adb.name, 'hello'], capture_output=True, shell=False, startupinfo=None) def test_adb_simple_su(ADB, mocker): output = mock.Mock(stdout=b'lala', returncode=0) mock_run = mocker.patch('andriller.adb_conn.subprocess.run', return_value=output) res = ADB('hello', su=True) assert res == 'lala' mock_run.assert_called_with([fake_adb.name, 'su -c', 'hello'], capture_output=True, shell=False, startupinfo=None) def test_adb_binary(ADB, mocker): output = mock.Mock(stdout=b'lala', returncode=0) mock_run = mocker.patch('andriller.adb_conn.subprocess.run', return_value=output) res = ADB('hello', binary=True) assert res == b'lala' mock_run.assert_called_with([fake_adb.name, 'hello'], capture_output=True, shell=False, startupinfo=None) def test_adb_out(ADB, mocker): output = mock.Mock(stdout=b'uid(1000)', returncode=0) mock_run = mocker.patch('andriller.adb_conn.subprocess.run', return_value=output) res = ADB.adb_out('id', binary=False) assert res == 'uid(1000)' mock_run.assert_called_with([fake_adb.name, 'shell', 'id'], capture_output=True, shell=False, startupinfo=None) def test_adb_out_alt(ADB_alt, mocker): output = mock.Mock(stdout=b'uid(1000)', returncode=0) mock_run = mocker.patch('andriller.adb_conn.subprocess.run', return_value=output) res = ADB_alt.adb_out('id', binary=True) assert res == b'uid(1000)' mock_run.assert_called_with([fake_adb.name, 'shell', 'id'], stdout=subprocess.PIPE, shell=False, startupinfo=None) def test_adb_out_win(ADB_win, mocker): output = mock.Mock(stdout=b'uid(1000)\r\r\n', returncode=0) mock_run = mocker.patch('andriller.adb_conn.subprocess.run', return_value=output) res = ADB_win.adb_out('id', binary=True) assert res == b'uid(1000)\n' def test_adb_out_uses_exec(ADB, mocker): ADB._is_adb_out_post_v5 = True output = mock.Mock(stdout=b'uid(1000)', returncode=0) mock_run = mocker.patch('andriller.adb_conn.subprocess.run', return_value=output) res = ADB.adb_out('id', binary=False) assert res == 'uid(1000)' mock_run.assert_called_with([fake_adb.name, 'exec-out', 'id'], capture_output=True, shell=False, startupinfo=None)

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0.216495

0

null

0

1

0

null

0

5

456c7876c9e495052b4d059448fc14036e36379f

93

py

Python

peco/parser/read_end_for.py

Tikubonn/peco

c77fc163ad31d3c271d299747914ce4ef3386987

[ "MIT" ]

null

peco/parser/read_end_for.py

Tikubonn/peco

c77fc163ad31d3c271d299747914ce4ef3386987

[ "MIT" ]

null

peco/parser/read_end_for.py

Tikubonn/peco

c77fc163ad31d3c271d299747914ce4ef3386987

[ "MIT" ]

null

from .end_for import EndFor def read_end_for(preread, stream, parser): raise EndFor()

13.285714

42

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93

4.642857

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null

0

1

0

1

0

1

0

5

456e3af2e6de3bd6d92f5b1c4f27afbb637bd3de

126

py

Python

boa3_test/test_sc/interop_test/storage/StorageDeleteStrKey.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

25

2020-07-22T19:37:43.000Z

2022-03-08T03:23:55.000Z

boa3_test/test_sc/interop_test/storage/StorageDeleteStrKey.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

419

2020-04-23T17:48:14.000Z

2022-03-31T13:17:45.000Z

boa3_test/test_sc/interop_test/storage/StorageDeleteStrKey.py

hal0x2328/neo3-boa

6825a3533384cb01660773050719402a9703065b

[ "Apache-2.0" ]

15

2020-05-21T21:54:24.000Z

2021-11-18T06:17:24.000Z

from boa3.builtin import public from boa3.builtin.interop.storage import delete @public def Main(key: str): delete(key)

15.75

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5

4576de23e37082e2dea8e638cef12f85c2f2f63b

5,442

py

Python

test/unit2/usersignup/validation_test.py

cdoremus/udacity-python_web_development-cs253

87cf5dd5d0e06ee745d3aba058d96fa46f2aeb6b

[ "Apache-2.0" ]

null

test/unit2/usersignup/validation_test.py

cdoremus/udacity-python_web_development-cs253

87cf5dd5d0e06ee745d3aba058d96fa46f2aeb6b

[ "Apache-2.0" ]

null

test/unit2/usersignup/validation_test.py

cdoremus/udacity-python_web_development-cs253

87cf5dd5d0e06ee745d3aba058d96fa46f2aeb6b

[ "Apache-2.0" ]

null

''' Created on Apr 25, 2012 @author: h87966 ''' import unittest from unit2.usersignup.validation import UserSignupValidation from unit2.usersignup.validation import VERIFICATION_MESSAGES from unit2.usersignup.validation import VERIFICATION_MESSAGES_KEYS from unit2.usersignup.validation import MISMATCHED_PASSWORDS_MESSAGE class Test(unittest.TestCase): def setUp(self): self.validation = UserSignupValidation() pass def tearDown(self): pass def testIsValidUsername(self): self.assertTrue(self.validation.is_valid_username("Crag")) self.assertTrue(self.validation.is_valid_username("Crag-Doremus")) self.assertTrue(self.validation.is_valid_username("Crag_Doremus")) self.assertTrue(self.validation.is_valid_username("Cra")) self.assertFalse(self.validation.is_valid_username("ca")) self.assertFalse(self.validation.is_valid_username("cat!")) self.assertTrue(self.validation.is_valid_username("abcdefghijklmnopqrst")) self.assertFalse(self.validation.is_valid_username("abcdefghijklmnopqrstu")) pass def testIsValidPassword(self): self.assertTrue(self.validation.is_valid_password("Craig")) self.assertTrue(self.validation.is_valid_password("abcdefghijklmnopqrst")) self.assertFalse(self.validation.is_valid_password("abcdefghijklmnopqrstu")) pass def testIsValidEmail(self): self.assertTrue(self.validation.is_valid_email("Craig@foo.com")) self.assertTrue(self.validation.is_valid_email("Craig@foo.com.com")) self.assertFalse(self.validation.is_valid_email("Craigfoocom")) pass def testValid(self): username = "Craig" password = "craig1" verify = "craig1" email = "craig@foo.com" validMsgs, isValid = self.validation.validate(username, password, verify, email) self.assertTrue(isValid) self.assertEmptyMessage([VERIFICATION_MESSAGES_KEYS[0],VERIFICATION_MESSAGES_KEYS[1],VERIFICATION_MESSAGES_KEYS[2],VERIFICATION_MESSAGES_KEYS[3]], validMsgs) def testValid_BadUsername(self): username = "Craigasdfasdfasdfasdfadfadfs" password = "craig1" verify = "craig1" email = "craig@foo.com" validMsgs, isValid = self.validation.validate(username, password, verify, email) self.assertFalse(isValid) self.assertEquals(VERIFICATION_MESSAGES[VERIFICATION_MESSAGES_KEYS[0]], validMsgs[VERIFICATION_MESSAGES_KEYS[0]]) self.assertEmptyMessage([VERIFICATION_MESSAGES_KEYS[1],VERIFICATION_MESSAGES_KEYS[2],VERIFICATION_MESSAGES_KEYS[3]], validMsgs) def testValid_BadPassword(self): username = "Craig" password = "c1" verify = "c1" email = "craig@foo.com" validMsgs, isValid = self.validation.validate(username, password, verify, email) self.assertFalse(isValid) self.assertEquals(VERIFICATION_MESSAGES[VERIFICATION_MESSAGES_KEYS[1]], validMsgs[VERIFICATION_MESSAGES_KEYS[1]]) self.assertEquals(VERIFICATION_MESSAGES[VERIFICATION_MESSAGES_KEYS[2]], validMsgs[VERIFICATION_MESSAGES_KEYS[2]]) self.assertEmptyMessage([VERIFICATION_MESSAGES_KEYS[0],VERIFICATION_MESSAGES_KEYS[3]], validMsgs) # def testValid_BadVerifyPassword(self): # username = "Craig" # password = "c1" # verify = "c1" # email = "craig@foo.com" # validMsgs, isValid = self.validation.validate(username, password, verify, email) # self.assertFalse(isValid) # self.assertEquals(VERIFICATION_MESSAGES[VERIFICATION_MESSAGES_KEYS[2]], validMsgs[VERIFICATION_MESSAGES_KEYS[2]]) # self.assertEmptyMessage([VERIFICATION_MESSAGES_KEYS[0],VERIFICATION_MESSAGES_KEYS[1],VERIFICATION_MESSAGES_KEYS[3]], validMsgs) def testValid_BadEmail(self): username = "Craig" password = "craig1" verify = "craig1" email = "craigfoo.com" validMsgs, isValid = self.validation.validate(username, password, verify, email) self.assertFalse(isValid) self.assertEquals(VERIFICATION_MESSAGES[VERIFICATION_MESSAGES_KEYS[3]], validMsgs[VERIFICATION_MESSAGES_KEYS[3]]) self.assertEmptyMessage([VERIFICATION_MESSAGES_KEYS[0],VERIFICATION_MESSAGES_KEYS[2],VERIFICATION_MESSAGES_KEYS[1]], validMsgs) def testValid_PasswordsDontMatch(self): username = "Craig" password = "craig1" verify = "craig" email = "craig@foo.com" validMsgs, isValid = self.validation.validate(username, password, verify, email) self.assertFalse(isValid) self.assertEquals(MISMATCHED_PASSWORDS_MESSAGE, validMsgs[VERIFICATION_MESSAGES_KEYS[1]]) self.assertEquals(MISMATCHED_PASSWORDS_MESSAGE, validMsgs[VERIFICATION_MESSAGES_KEYS[2]]) self.assertEmptyMessage([VERIFICATION_MESSAGES_KEYS[0],VERIFICATION_MESSAGES_KEYS[3]], validMsgs) def test_is_password_and_verify_equals(self): self.assertTrue(self.validation.is_password_and_verify_equals("craig", "craig")) self.assertFalse(self.validation.is_password_and_verify_equals("craig", "craig1")) def assertEmptyMessage(self, key_list, messages): for key in key_list: self.assertEquals('', messages[key], "Message with key " + key + " is not empty") if __name__ == "__main__": #import sys;sys.argv = ['', 'Test.testValidateUsername'] unittest.main()

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null

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1

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null

0

1

0

5

afe714cf033f9bba57daf8d57ed54029b8f6ecd6

127

py

Python

ankidict/pagemodel/__init__.py

wojtex/millandict

6601873a1541ef7aaf938ac1a6b7aecb5f82cbf8

[ "MIT" ]

1

2015-10-15T19:04:05.000Z

ankidict/pagemodel/__init__.py

wojtex/ankidict

6601873a1541ef7aaf938ac1a6b7aecb5f82cbf8

[ "MIT" ]

9

2015-03-24T08:06:51.000Z

2015-05-21T13:44:10.000Z

ankidict/pagemodel/__init__.py

wojtex/ankidict

6601873a1541ef7aaf938ac1a6b7aecb5f82cbf8

[ "MIT" ]

null

from . import html from .html import (Node, StrictNode, Text, ShallowText, Html, StrictHtml, ThisClass)

31.75

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127

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1

0

1

0

1

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5

b311266d18257e334be798593bb7cf2011a43b16

157

py

Python

webactivities/default_settings.py

lukegb/ehacktivities

bc04d02eaf36a106b943ce0cb8395e85a780f6fc

[ "MIT" ]

1

2016-04-30T00:19:13.000Z

webactivities/default_settings.py

lukegb/ehacktivities

bc04d02eaf36a106b943ce0cb8395e85a780f6fc

[ "MIT" ]

null

webactivities/default_settings.py

lukegb/ehacktivities

bc04d02eaf36a106b943ce0cb8395e85a780f6fc

[ "MIT" ]

null

FERNET_KEY = 'uyflUICClYw0n7OVjtyEsGDiiyLqzsSqaLQJZtGigf0=' SECRET_KEY = "=8wGX26:{mKZVRo0@0`i<RLMq(eHt~Nh8P6|LX'WHlN5S6n/eZ52>s4182G6$f1" FERNET_TTL = 3600

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1

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null

0

1

0

1

null

0

5

b31c0364d3b3c6f0e6157e9a4d623e77515058ce

26

py

Python

yaraa/__init__.py

Te-k/yaraa

b5a1be88419fbd4ea5e0a1f5e6dbedca8ff77b36

[ "MIT" ]

3

2019-12-18T03:14:56.000Z

2021-01-15T13:23:09.000Z

yaraa/__init__.py

Te-k/yaraa

b5a1be88419fbd4ea5e0a1f5e6dbedca8ff77b36

[ "MIT" ]

1

2019-12-17T15:13:39.000Z

yaraa/__init__.py

Te-k/yaraa

b5a1be88419fbd4ea5e0a1f5e6dbedca8ff77b36

[ "MIT" ]

null

from .yaraa import lookup

13

25

0.807692

4

26

5.25

1

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0.153846

26

1

26

0.954545

0

1

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true

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0

1

0

1

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null

0

1

0

null

0

1

0

1

0

5

b32d0934431628f5bfdb30a0016bef13ddfa7e5b

138

py

Python

example/blueprints/bptest/__init__.py

Mitalee/Flask-SocketIO-Celery-Electron

78e89e91c63f3ee7b1d2deb4ee14cd76cadb8fbc

[ "MIT" ]

3

2020-03-10T20:30:22.000Z

2021-11-04T15:40:28.000Z

example/blueprints/bptest/__init__.py

Mitalee/Flask-SocketIO-Celery-Electron

78e89e91c63f3ee7b1d2deb4ee14cd76cadb8fbc

[ "MIT" ]

null

example/blueprints/bptest/__init__.py

Mitalee/Flask-SocketIO-Celery-Electron

78e89e91c63f3ee7b1d2deb4ee14cd76cadb8fbc

[ "MIT" ]

1

2020-06-10T05:43:52.000Z

from flask import Blueprint #from example.app import create_celery_app bptest = Blueprint('bptest', __name__) from . import views, tasks

23

42

0.797101

19

138

5.473684

0.631579

0

0.130435

138

6

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23

0.866667

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0

0.061856

0

1

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false

0

0.666667

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0.666667

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null

0

1

0

null

0

1

0

1

0

5

b362debb9fa5a8b0ab65b654e6ac42df50871e93

197

py

Python

playproject/migrator_settings.py

sellonen/django-security-tips

b6d52fee5db7ff221cf7fd12e2e3abd862bca8c0

[ "CC0-1.0" ]

66

2016-03-16T15:49:39.000Z

2022-03-07T16:40:22.000Z

playproject/migrator_settings.py

sellonen/django-security-tips

b6d52fee5db7ff221cf7fd12e2e3abd862bca8c0

[ "CC0-1.0" ]

2

2017-12-15T23:02:19.000Z

2020-03-30T14:56:09.000Z

playproject/migrator_settings.py

sellonen/django-security-tips

b6d52fee5db7ff221cf7fd12e2e3abd862bca8c0

[ "CC0-1.0" ]

7

2016-03-17T07:33:36.000Z

2020-07-09T01:17:59.000Z

from .settings import * DATABASES['default']['USER'] = 'djangomigrator' with open(BASE_DIR + '/_etc_passwords_djangomigrator.txt') as fp: DATABASES['default']['PASSWORD'] = fp.read().strip()

28.142857

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197

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true

0.5

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null

1

0

1

0

null

0

1

0

5

2fbb1d608df09af1e79eb18a2c5740454c56f01c

274

py

Python

tests/parts/clock.py

ycwn/pyhdl

6440cc40193b789e281eb10f12580f2b6df17d1a

[ "MIT" ]

null

tests/parts/clock.py

ycwn/pyhdl

6440cc40193b789e281eb10f12580f2b6df17d1a

[ "MIT" ]

null

tests/parts/clock.py

ycwn/pyhdl

6440cc40193b789e281eb10f12580f2b6df17d1a

[ "MIT" ]

null

import pyhdl.core as core import pyhdl.parts.clock as clk from ..common import * test_component(clk.clock.create(), [ [], [], [], [], [], [], [], [] ], [ [ True ], [ False ], [ True ], [ False ], [ True ], [ False ], [ True ], [ False ] ] )

10.538462

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4.666667

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0.309524

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0.285714

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0.30292

274

25

35

10.96

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0

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true

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1

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null

1

0

null

0

1

0

5

2fbb813247c72ac96b54ffa884030f958a75f82b

130

py

Python

src/udsxmlrpc/__init__.py

daizhaolin/udsxmlrpc

1f16ce8029e0bd68b08ad02119ca5bcec61971dd

[ "BSD-3-Clause" ]

1

2020-01-15T08:53:53.000Z

src/udsxmlrpc/__init__.py

daizhaolin/udsxmlrpc

1f16ce8029e0bd68b08ad02119ca5bcec61971dd

[ "BSD-3-Clause" ]

null

src/udsxmlrpc/__init__.py

daizhaolin/udsxmlrpc

1f16ce8029e0bd68b08ad02119ca5bcec61971dd

[ "BSD-3-Clause" ]

null

# -*- coding: UTF-8 -*- ''' Created on 2020-01-13 @author: daizhaolin ''' from .server import Server from .client import Client

13

26

0.669231

18

130

4.833333

0.777778

0

0.083333

0.169231

130

9

27

14.444444

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0.5

0

1

0

true

0

1

0

1

0

1

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null

0

1

0

null

0

1

0

1

0

1

0

5

2fbda503d81cca79faf80b5f81ca18d295fda31d

128

py

Python

tinkoff/invest/market_data_stream/typevars.py

forked-group/invest-python

3398391f5bb4a52020c312855de175cfe8cdc021

[ "Apache-2.0" ]

41

2022-01-21T05:38:57.000Z

2022-03-30T03:54:41.000Z

tinkoff/invest/market_data_stream/typevars.py

forked-group/invest-python

3398391f5bb4a52020c312855de175cfe8cdc021

[ "Apache-2.0" ]

20

2022-01-24T05:46:02.000Z

2022-03-31T16:54:04.000Z

tinkoff/invest/market_data_stream/typevars.py

forked-group/invest-python

3398391f5bb4a52020c312855de175cfe8cdc021

[ "Apache-2.0" ]

15

2022-01-25T06:53:27.000Z

2022-03-30T03:49:07.000Z

from typing import TypeVar TMarketDataStreamManager = TypeVar("TMarketDataStreamManager") TInstrument = TypeVar("TInstrument")

25.6

62

0.835938

10

128

10.7

0.6

0.579439

0

0.085938

128

4

63

32

0.91453

0

0.273438

0.1875

0

1

0

false

0

0.333333

0

0.333333

0

1

0

1

null

1

0

1

0

null

0

1

0

5

2fc751a07689597eb520fe0eb4337776e6ff00df

16

py

Python

python/coursera_python/MICHIGAN/DataStructures/test/range.py

SayanGhoshBDA/code-backup

8b6135facc0e598e9686b2e8eb2d69dd68198b80

[ "MIT" ]

16

2018-11-26T08:39:42.000Z

2019-05-08T10:09:52.000Z

python/coursera_python/MICHIGAN/DataStructures/test/range.py

SayanGhoshBDA/code-backup

8b6135facc0e598e9686b2e8eb2d69dd68198b80

[ "MIT" ]

8

2020-05-04T06:29:26.000Z

2022-02-12T05:33:16.000Z

python/coursera_python/MICHIGAN/DataStructures/test/range.py

SayanGhoshBDA/code-backup

8b6135facc0e598e9686b2e8eb2d69dd68198b80

[ "MIT" ]

5

2020-02-11T16:02:21.000Z

2021-02-05T07:48:30.000Z

print(range(4))

8

15

0.6875

3

16

3.666667

1

0

0.066667

0.0625

16

1

16

0.666667

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

2fe408f5037fc3a7255b1b32266159ee20a4cdbd

113

py

Python

DeepAlignmentNetwork/menpofit/aps/__init__.py

chiawei-liu/DeepAlignmentNetwork

52621cd2f697abe372b88c9ea0ee08f0d93b43d8

[ "MIT" ]

220

2019-09-01T01:52:04.000Z

2022-03-28T12:52:07.000Z

DeepAlignmentNetwork/menpofit/aps/__init__.py

chiawei-liu/DeepAlignmentNetwork

52621cd2f697abe372b88c9ea0ee08f0d93b43d8

[ "MIT" ]

80

2015-01-05T16:17:39.000Z

2020-11-22T13:42:00.000Z

DeepAlignmentNetwork/menpofit/aps/__init__.py

chiawei-liu/DeepAlignmentNetwork

52621cd2f697abe372b88c9ea0ee08f0d93b43d8

[ "MIT" ]

64

2015-02-02T15:11:38.000Z

2022-02-28T06:19:31.000Z

from .base import GenerativeAPS from .fitter import GaussNewtonAPSFitter from .algorithm import Inverse, Forward

28.25

40

0.849558

13

113

7.384615

0.692308

0

0.115044

113

3

41

37.666667

0.96

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

642a99074d38d44f874c56c53e73970eec03b88e

231

py

Python

scripts/item/consume_2433828.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

54

2019-04-16T23:24:48.000Z

2021-12-18T11:41:50.000Z

scripts/item/consume_2433828.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

3

2019-05-19T15:19:41.000Z

2020-04-27T16:29:16.000Z

scripts/item/consume_2433828.py

G00dBye/YYMS

1de816fc842b6598d5b4b7896b6ab0ee8f7cdcfb

[ "MIT" ]

49

2020-11-25T23:29:16.000Z

2022-03-26T16:20:24.000Z

# Created by MechAviv # White Heaven Sun Damage Skin | (2433828) if sm.addDamageSkin(2433828): sm.chat("'White Heaven Sun Damage Skin' Damage Skin has been added to your account's damage skin collection.") sm.consumeItem()

46.2

115

0.74026

34

231

5.029412

0.647059

0.233918

0.163743

0.233918

0.280702

0

0.072917

0.168831

231

5

116

46.2

0.817708

0.25974

0

0.333333

0.591716

0

1

0

true

0

null

1

0

1

0

1

0

1

0

null

0

1

0

5

643d957019a052f5c4aadcbde260636fc78a6929

101

py

Python

game/user.py

luiszun/scrambled

4293a90e50678b38ecc0d69f2299ba487dbe0c27

[ "Apache-2.0" ]

null

game/user.py

luiszun/scrambled

4293a90e50678b38ecc0d69f2299ba487dbe0c27

[ "Apache-2.0" ]

null

game/user.py

luiszun/scrambled

4293a90e50678b38ecc0d69f2299ba487dbe0c27

[ "Apache-2.0" ]

null

from match import Match class User: def __init__(self, userId): self.userId = userId

20.2

32

0.653465

13

101

4.769231

0.692308

0.322581

0

0.277228

101

5

33

20.2

0.849315

0

1

0.25

false

0

0.25

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

ff273b3c41062828dc8b00d45f6bc998a94b3159

117

py

Python

sample.py

j-tesla/androidframer

7d9efe22fbb25b1801603c542794b5016bc11543

[ "Apache-2.0" ]

80

2019-08-03T12:26:22.000Z

2020-06-13T11:43:55.000Z

sample.py

j-tesla/androidframer

7d9efe22fbb25b1801603c542794b5016bc11543

[ "Apache-2.0" ]

7

2019-08-03T09:50:28.000Z

2020-07-01T17:10:10.000Z

sample.py

j-tesla/androidframer

7d9efe22fbb25b1801603c542794b5016bc11543

[ "Apache-2.0" ]

7

2020-07-06T11:27:08.000Z

2021-02-24T11:45:47.000Z

from androidframer import Framer Framer("resources/framer.json","resources/strings.json","resources/images").start()

39

83

0.803419

14

117

6.714286

0.642857

0.276596

0

0.042735

117

3

83

39

0.839286

0

0.5

0.364407

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

ff4229df98b5ee7702a83095e8df3a16f97d6205

55

py

Python

crypto_native/__init__.py

dkushche/Crypto

75919d6df2084aee1de76c9999ac4e361c4efd48

[ "MIT" ]

3

2020-05-07T22:03:48.000Z

2021-03-11T16:36:56.000Z

crypto_native/__init__.py

dkushche/Crypto

75919d6df2084aee1de76c9999ac4e361c4efd48

[ "MIT" ]

null

crypto_native/__init__.py

dkushche/Crypto

75919d6df2084aee1de76c9999ac4e361c4efd48

[ "MIT" ]

null

from .openssl_api import * from .ms_cryptoapi import *

18.333333

27

0.781818

8

55

5.125

0.75

0

0.145455

55

2

28

27.5

0.87234

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ff5f2604767219fd7aefda98b68f39ceb0404a95

7,990

py

Python

release/stubs.min/System/Windows/Forms/__init___parts/Screen.py

htlcnn/ironpython-stubs

780d829e2104b2789d5f4d6f32b0ec9f2930ca03

[ "MIT" ]

182

2017-06-27T02:26:15.000Z

2022-03-30T18:53:43.000Z

release/stubs.min/System/Windows/Forms/__init___parts/Screen.py

htlcnn/ironpython-stubs

780d829e2104b2789d5f4d6f32b0ec9f2930ca03

[ "MIT" ]

28

2017-06-27T13:38:23.000Z

2022-03-15T11:19:44.000Z

release/stubs.min/System/Windows/Forms/__init___parts/Screen.py

htlcnn/ironpython-stubs

780d829e2104b2789d5f4d6f32b0ec9f2930ca03

[ "MIT" ]

67

2017-06-28T09:43:59.000Z

2022-03-20T21:17:10.000Z

class Screen(object): """ Represents a display device or multiple display devices on a single system. """ def Equals(self,obj): """ Equals(self: Screen,obj: object) -> bool Gets or sets a value indicating whether the specified object is equal to this Screen. obj: The object to compare to this System.Windows.Forms.Screen. Returns: true if the specified object is equal to this System.Windows.Forms.Screen; otherwise,false. """ pass @staticmethod def FromControl(control): """ FromControl(control: Control) -> Screen Retrieves a System.Windows.Forms.Screen for the display that contains the largest portion of the specified control. control: A System.Windows.Forms.Control for which to retrieve a System.Windows.Forms.Screen. Returns: A System.Windows.Forms.Screen for the display that contains the largest region of the specified control. In multiple display environments where no display contains the control,the display closest to the specified control is returned. """ pass @staticmethod def FromHandle(hwnd): """ FromHandle(hwnd: IntPtr) -> Screen Retrieves a System.Windows.Forms.Screen for the display that contains the largest portion of the object referred to by the specified handle. hwnd: The window handle for which to retrieve the System.Windows.Forms.Screen. Returns: A System.Windows.Forms.Screen for the display that contains the largest region of the object. In multiple display environments where no display contains any portion of the specified window,the display closest to the object is returned. """ pass @staticmethod def FromPoint(point): """ FromPoint(point: Point) -> Screen Retrieves a System.Windows.Forms.Screen for the display that contains the specified point. point: A System.Drawing.Point that specifies the location for which to retrieve a System.Windows.Forms.Screen. Returns: A System.Windows.Forms.Screen for the display that contains the point. In multiple display environments where no display contains the point,the display closest to the specified point is returned. """ pass @staticmethod def FromRectangle(rect): """ FromRectangle(rect: Rectangle) -> Screen Retrieves a System.Windows.Forms.Screen for the display that contains the largest portion of the rectangle. rect: A System.Drawing.Rectangle that specifies the area for which to retrieve the display. Returns: A System.Windows.Forms.Screen for the display that contains the largest region of the specified rectangle. In multiple display environments where no display contains the rectangle,the display closest to the rectangle is returned. """ pass @staticmethod def GetBounds(*__args): """ GetBounds(ctl: Control) -> Rectangle Retrieves the bounds of the display that contains the largest portion of the specified control. ctl: The System.Windows.Forms.Control for which to retrieve the display bounds. Returns: A System.Drawing.Rectangle that specifies the bounds of the display that contains the specified control. In multiple display environments where no display contains the specified control,the display closest to the control is returned. GetBounds(rect: Rectangle) -> Rectangle Retrieves the bounds of the display that contains the largest portion of the specified rectangle. rect: A System.Drawing.Rectangle that specifies the area for which to retrieve the display bounds. Returns: A System.Drawing.Rectangle that specifies the bounds of the display that contains the specified rectangle. In multiple display environments where no monitor contains the specified rectangle, the monitor closest to the rectangle is returned. GetBounds(pt: Point) -> Rectangle Retrieves the bounds of the display that contains the specified point. pt: A System.Drawing.Point that specifies the coordinates for which to retrieve the display bounds. Returns: A System.Drawing.Rectangle that specifies the bounds of the display that contains the specified point. In multiple display environments where no display contains the specified point,the display closest to the point is returned. """ pass def GetHashCode(self): """ GetHashCode(self: Screen) -> int Computes and retrieves a hash code for an object. Returns: A hash code for an object. """ pass @staticmethod def GetWorkingArea(*__args): """ GetWorkingArea(ctl: Control) -> Rectangle Retrieves the working area for the display that contains the largest region of the specified control. The working area is the desktop area of the display,excluding taskbars,docked windows,and docked tool bars. ctl: The System.Windows.Forms.Control for which to retrieve the working area. Returns: A System.Drawing.Rectangle that specifies the working area. In multiple display environments where no display contains the specified control,the display closest to the control is returned. GetWorkingArea(rect: Rectangle) -> Rectangle Retrieves the working area for the display that contains the largest portion of the specified rectangle. The working area is the desktop area of the display,excluding taskbars,docked windows,and docked tool bars. rect: The System.Drawing.Rectangle that specifies the area for which to retrieve the working area. Returns: A System.Drawing.Rectangle that specifies the working area. In multiple display environments where no display contains the specified rectangle,the display closest to the rectangle is returned. GetWorkingArea(pt: Point) -> Rectangle Retrieves the working area closest to the specified point. The working area is the desktop area of the display,excluding taskbars,docked windows,and docked tool bars. pt: A System.Drawing.Point that specifies the coordinates for which to retrieve the working area. Returns: A System.Drawing.Rectangle that specifies the working area. In multiple display environments where no display contains the specified point,the display closest to the point is returned. """ pass def ToString(self): """ ToString(self: Screen) -> str Retrieves a string representing this object. Returns: A string representation of the object. """ pass def __eq__(self,*args): """ x.__eq__(y) <==> x==y """ pass def __ne__(self,*args): pass BitsPerPixel=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the number of bits of memory,associated with one pixel of data. Get: BitsPerPixel(self: Screen) -> int """ Bounds=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the bounds of the display. Get: Bounds(self: Screen) -> Rectangle """ DeviceName=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the device name associated with a display. Get: DeviceName(self: Screen) -> str """ Primary=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets a value indicating whether a particular display is the primary device. Get: Primary(self: Screen) -> bool """ WorkingArea=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the working area of the display. The working area is the desktop area of the display,excluding taskbars,docked windows,and docked tool bars. Get: WorkingArea(self: Screen) -> Rectangle """ AllScreens=None PrimaryScreen=None

24.660494

150

0.705757

1,049

7,990

5.360343

0.120114

0.062244

0.051218

0.0626

0.779477

0.720967

0.685577

0.665837

0.652321

0.61533

0

0.233417

7,990

323

151

24.736842

0.918041

0.722153

0

0.472222

0

1

0.305556

false

0.305556

0

0.527778

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

5

ff651f22bfd2a2fd73774e38cfb2fad6847e9eaa

15,329

py

Python

spoonacular/com.spoonacular.client.model/__init__.py

Lowe-Man/spoonacular-python-api

c5522abdc2ef48258434e22b4f2038d64bcebd86

[ "MIT" ]

21

2019-08-09T18:53:26.000Z

2022-03-14T22:10:10.000Z

spoonacular/com.spoonacular.client.model/__init__.py

Lowe-Man/spoonacular-python-api

c5522abdc2ef48258434e22b4f2038d64bcebd86

[ "MIT" ]

null

spoonacular/com.spoonacular.client.model/__init__.py

Lowe-Man/spoonacular-python-api

c5522abdc2ef48258434e22b4f2038d64bcebd86

[ "MIT" ]

55

2019-08-13T17:52:47.000Z

2022-03-27T04:29:34.000Z

# coding: utf-8 # flake8: noqa """ spoonacular API The spoonacular Nutrition, Recipe, and Food API allows you to access over 380,000 recipes, thousands of ingredients, 800,000 food products, and 100,000 menu items. Our food ontology and semantic recipe search engine makes it possible to search for recipes using natural language queries, such as \"gluten free brownies without sugar\" or \"low fat vegan cupcakes.\" You can automatically calculate the nutritional information for any recipe, analyze recipe costs, visualize ingredient lists, find recipes for what's in your fridge, find recipes based on special diets, nutritional requirements, or favorite ingredients, classify recipes into types and cuisines, convert ingredient amounts, or even compute an entire meal plan. With our powerful API, you can create many kinds of food and especially nutrition apps. Special diets/dietary requirements currently available include: vegan, vegetarian, pescetarian, gluten free, grain free, dairy free, high protein, whole 30, low sodium, low carb, Paleo, ketogenic, FODMAP, and Primal. # noqa: E501 The version of the OpenAPI document: 1.0 Contact: mail@spoonacular.com Generated by: https://openapi-generator.tech """ from __future__ import absolute_import # import models into model package from spoonacular.com.spoonacular.client.model.food_ingredients_map_products import FoodIngredientsMapProducts from spoonacular.com.spoonacular.client.model.inline_object import InlineObject from spoonacular.com.spoonacular.client.model.inline_object1 import InlineObject1 from spoonacular.com.spoonacular.client.model.inline_object10 import InlineObject10 from spoonacular.com.spoonacular.client.model.inline_object2 import InlineObject2 from spoonacular.com.spoonacular.client.model.inline_object3 import InlineObject3 from spoonacular.com.spoonacular.client.model.inline_object4 import InlineObject4 from spoonacular.com.spoonacular.client.model.inline_object5 import InlineObject5 from spoonacular.com.spoonacular.client.model.inline_object6 import InlineObject6 from spoonacular.com.spoonacular.client.model.inline_object7 import InlineObject7 from spoonacular.com.spoonacular.client.model.inline_object8 import InlineObject8 from spoonacular.com.spoonacular.client.model.inline_object9 import InlineObject9 from spoonacular.com.spoonacular.client.model.inline_response200 import InlineResponse200 from spoonacular.com.spoonacular.client.model.inline_response2001 import InlineResponse2001 from spoonacular.com.spoonacular.client.model.inline_response20010 import InlineResponse20010 from spoonacular.com.spoonacular.client.model.inline_response20010_amount import InlineResponse20010Amount from spoonacular.com.spoonacular.client.model.inline_response20010_amount_metric import InlineResponse20010AmountMetric from spoonacular.com.spoonacular.client.model.inline_response20010_ingredients import InlineResponse20010Ingredients from spoonacular.com.spoonacular.client.model.inline_response20011 import InlineResponse20011 from spoonacular.com.spoonacular.client.model.inline_response20011_ingredients import InlineResponse20011Ingredients from spoonacular.com.spoonacular.client.model.inline_response20012 import InlineResponse20012 from spoonacular.com.spoonacular.client.model.inline_response20013 import InlineResponse20013 from spoonacular.com.spoonacular.client.model.inline_response20013_ingredients import InlineResponse20013Ingredients from spoonacular.com.spoonacular.client.model.inline_response20013_ingredients1 import InlineResponse20013Ingredients1 from spoonacular.com.spoonacular.client.model.inline_response20013_parsed_instructions import InlineResponse20013ParsedInstructions from spoonacular.com.spoonacular.client.model.inline_response20013_steps import InlineResponse20013Steps from spoonacular.com.spoonacular.client.model.inline_response20014 import InlineResponse20014 from spoonacular.com.spoonacular.client.model.inline_response20015 import InlineResponse20015 from spoonacular.com.spoonacular.client.model.inline_response20016 import InlineResponse20016 from spoonacular.com.spoonacular.client.model.inline_response20017 import InlineResponse20017 from spoonacular.com.spoonacular.client.model.inline_response20018 import InlineResponse20018 from spoonacular.com.spoonacular.client.model.inline_response20018_dishes import InlineResponse20018Dishes from spoonacular.com.spoonacular.client.model.inline_response20018_ingredients import InlineResponse20018Ingredients from spoonacular.com.spoonacular.client.model.inline_response20019 import InlineResponse20019 from spoonacular.com.spoonacular.client.model.inline_response2002 import InlineResponse2002 from spoonacular.com.spoonacular.client.model.inline_response20020 import InlineResponse20020 from spoonacular.com.spoonacular.client.model.inline_response20021 import InlineResponse20021 from spoonacular.com.spoonacular.client.model.inline_response20021_calories import InlineResponse20021Calories from spoonacular.com.spoonacular.client.model.inline_response20021_calories_confidence_range95_percent import InlineResponse20021CaloriesConfidenceRange95Percent from spoonacular.com.spoonacular.client.model.inline_response20022 import InlineResponse20022 from spoonacular.com.spoonacular.client.model.inline_response20022_nutrition import InlineResponse20022Nutrition from spoonacular.com.spoonacular.client.model.inline_response20023 import InlineResponse20023 from spoonacular.com.spoonacular.client.model.inline_response20023_ingredients import InlineResponse20023Ingredients from spoonacular.com.spoonacular.client.model.inline_response20024 import InlineResponse20024 from spoonacular.com.spoonacular.client.model.inline_response20025 import InlineResponse20025 from spoonacular.com.spoonacular.client.model.inline_response20025_results import InlineResponse20025Results from spoonacular.com.spoonacular.client.model.inline_response20026 import InlineResponse20026 from spoonacular.com.spoonacular.client.model.inline_response20027 import InlineResponse20027 from spoonacular.com.spoonacular.client.model.inline_response20028 import InlineResponse20028 from spoonacular.com.spoonacular.client.model.inline_response20028_ingredients import InlineResponse20028Ingredients from spoonacular.com.spoonacular.client.model.inline_response20028_nutrition import InlineResponse20028Nutrition from spoonacular.com.spoonacular.client.model.inline_response20028_servings import InlineResponse20028Servings from spoonacular.com.spoonacular.client.model.inline_response20029 import InlineResponse20029 from spoonacular.com.spoonacular.client.model.inline_response20029_custom_foods import InlineResponse20029CustomFoods from spoonacular.com.spoonacular.client.model.inline_response2003 import InlineResponse2003 from spoonacular.com.spoonacular.client.model.inline_response20030 import InlineResponse20030 from spoonacular.com.spoonacular.client.model.inline_response20030_ingredients import InlineResponse20030Ingredients from spoonacular.com.spoonacular.client.model.inline_response20031 import InlineResponse20031 from spoonacular.com.spoonacular.client.model.inline_response20031_comparable_products import InlineResponse20031ComparableProducts from spoonacular.com.spoonacular.client.model.inline_response20031_comparable_products_protein import InlineResponse20031ComparableProductsProtein from spoonacular.com.spoonacular.client.model.inline_response20032 import InlineResponse20032 from spoonacular.com.spoonacular.client.model.inline_response20032_results import InlineResponse20032Results from spoonacular.com.spoonacular.client.model.inline_response20033 import InlineResponse20033 from spoonacular.com.spoonacular.client.model.inline_response20034 import InlineResponse20034 from spoonacular.com.spoonacular.client.model.inline_response20035 import InlineResponse20035 from spoonacular.com.spoonacular.client.model.inline_response20035_menu_items import InlineResponse20035MenuItems from spoonacular.com.spoonacular.client.model.inline_response20036 import InlineResponse20036 from spoonacular.com.spoonacular.client.model.inline_response20037 import InlineResponse20037 from spoonacular.com.spoonacular.client.model.inline_response20037_nutrients import InlineResponse20037Nutrients from spoonacular.com.spoonacular.client.model.inline_response20038 import InlineResponse20038 from spoonacular.com.spoonacular.client.model.inline_response20038_days import InlineResponse20038Days from spoonacular.com.spoonacular.client.model.inline_response20038_items import InlineResponse20038Items from spoonacular.com.spoonacular.client.model.inline_response20038_nutrition_summary import InlineResponse20038NutritionSummary from spoonacular.com.spoonacular.client.model.inline_response20038_nutrition_summary_nutrients import InlineResponse20038NutritionSummaryNutrients from spoonacular.com.spoonacular.client.model.inline_response20038_value import InlineResponse20038Value from spoonacular.com.spoonacular.client.model.inline_response20039 import InlineResponse20039 from spoonacular.com.spoonacular.client.model.inline_response2003_extended_ingredients import InlineResponse2003ExtendedIngredients from spoonacular.com.spoonacular.client.model.inline_response2003_measures import InlineResponse2003Measures from spoonacular.com.spoonacular.client.model.inline_response2003_measures_metric import InlineResponse2003MeasuresMetric from spoonacular.com.spoonacular.client.model.inline_response2003_wine_pairing import InlineResponse2003WinePairing from spoonacular.com.spoonacular.client.model.inline_response2003_wine_pairing_product_matches import InlineResponse2003WinePairingProductMatches from spoonacular.com.spoonacular.client.model.inline_response2004 import InlineResponse2004 from spoonacular.com.spoonacular.client.model.inline_response20040 import InlineResponse20040 from spoonacular.com.spoonacular.client.model.inline_response20040_items import InlineResponse20040Items from spoonacular.com.spoonacular.client.model.inline_response20040_value import InlineResponse20040Value from spoonacular.com.spoonacular.client.model.inline_response20041 import InlineResponse20041 from spoonacular.com.spoonacular.client.model.inline_response20041_days import InlineResponse20041Days from spoonacular.com.spoonacular.client.model.inline_response20041_items import InlineResponse20041Items from spoonacular.com.spoonacular.client.model.inline_response20041_value import InlineResponse20041Value from spoonacular.com.spoonacular.client.model.inline_response20042 import InlineResponse20042 from spoonacular.com.spoonacular.client.model.inline_response20042_aisles import InlineResponse20042Aisles from spoonacular.com.spoonacular.client.model.inline_response20042_items import InlineResponse20042Items from spoonacular.com.spoonacular.client.model.inline_response20042_measures import InlineResponse20042Measures from spoonacular.com.spoonacular.client.model.inline_response20043 import InlineResponse20043 from spoonacular.com.spoonacular.client.model.inline_response20044 import InlineResponse20044 from spoonacular.com.spoonacular.client.model.inline_response20045 import InlineResponse20045 from spoonacular.com.spoonacular.client.model.inline_response20045_product_matches import InlineResponse20045ProductMatches from spoonacular.com.spoonacular.client.model.inline_response20046 import InlineResponse20046 from spoonacular.com.spoonacular.client.model.inline_response20047 import InlineResponse20047 from spoonacular.com.spoonacular.client.model.inline_response20047_recommended_wines import InlineResponse20047RecommendedWines from spoonacular.com.spoonacular.client.model.inline_response20048 import InlineResponse20048 from spoonacular.com.spoonacular.client.model.inline_response20049 import InlineResponse20049 from spoonacular.com.spoonacular.client.model.inline_response20049_category import InlineResponse20049Category from spoonacular.com.spoonacular.client.model.inline_response20049_nutrition import InlineResponse20049Nutrition from spoonacular.com.spoonacular.client.model.inline_response20049_nutrition_calories import InlineResponse20049NutritionCalories from spoonacular.com.spoonacular.client.model.inline_response20049_nutrition_calories_confidence_range95_percent import InlineResponse20049NutritionCaloriesConfidenceRange95Percent from spoonacular.com.spoonacular.client.model.inline_response20049_recipes import InlineResponse20049Recipes from spoonacular.com.spoonacular.client.model.inline_response2005 import InlineResponse2005 from spoonacular.com.spoonacular.client.model.inline_response20050 import InlineResponse20050 from spoonacular.com.spoonacular.client.model.inline_response20051 import InlineResponse20051 from spoonacular.com.spoonacular.client.model.inline_response20052 import InlineResponse20052 from spoonacular.com.spoonacular.client.model.inline_response20053 import InlineResponse20053 from spoonacular.com.spoonacular.client.model.inline_response20053_results import InlineResponse20053Results from spoonacular.com.spoonacular.client.model.inline_response20053_search_results import InlineResponse20053SearchResults from spoonacular.com.spoonacular.client.model.inline_response20054 import InlineResponse20054 from spoonacular.com.spoonacular.client.model.inline_response20054_videos import InlineResponse20054Videos from spoonacular.com.spoonacular.client.model.inline_response20055 import InlineResponse20055 from spoonacular.com.spoonacular.client.model.inline_response20056 import InlineResponse20056 from spoonacular.com.spoonacular.client.model.inline_response20057 import InlineResponse20057 from spoonacular.com.spoonacular.client.model.inline_response20057_suggests import InlineResponse20057Suggests from spoonacular.com.spoonacular.client.model.inline_response2006 import InlineResponse2006 from spoonacular.com.spoonacular.client.model.inline_response2006_recipes import InlineResponse2006Recipes from spoonacular.com.spoonacular.client.model.inline_response2007 import InlineResponse2007 from spoonacular.com.spoonacular.client.model.inline_response2008 import InlineResponse2008 from spoonacular.com.spoonacular.client.model.inline_response2009 import InlineResponse2009 from spoonacular.com.spoonacular.client.model.inline_response200_results import InlineResponse200Results from spoonacular.com.spoonacular.client.model.recipes_find_by_ingredients_missed_ingredients import RecipesFindByIngredientsMissedIngredients from spoonacular.com.spoonacular.client.model.recipes_parse_ingredients_estimated_cost import RecipesParseIngredientsEstimatedCost from spoonacular.com.spoonacular.client.model.recipes_parse_ingredients_nutrition import RecipesParseIngredientsNutrition from spoonacular.com.spoonacular.client.model.recipes_parse_ingredients_nutrition_caloric_breakdown import RecipesParseIngredientsNutritionCaloricBreakdown from spoonacular.com.spoonacular.client.model.recipes_parse_ingredients_nutrition_nutrients import RecipesParseIngredientsNutritionNutrients from spoonacular.com.spoonacular.client.model.recipes_parse_ingredients_nutrition_properties import RecipesParseIngredientsNutritionProperties from spoonacular.com.spoonacular.client.model.recipes_parse_ingredients_nutrition_weight_per_serving import RecipesParseIngredientsNutritionWeightPerServing

101.516556

1,050

0.903386

1,629

15,329

8.349294

0.233886

0.137931

0.176016

0.283582

0.557091

0.55268

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0.407617

0.108889

0.070142

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0.079597

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15,329

150

1,051

102.193333

0.852873

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1

0

null

0

1

0

1

0

5

ff73f9177c9f2dd2b1e19e713669fdd3ecf27baf

316

py

Python

Aulas/Mundo 1/030.py

JoaoEmanuell/Meus-Estudos-Python

f6f6eeb6016919e594613785ffe7136d74241ada

[ "MIT" ]

2

2021-07-29T18:58:02.000Z

2021-10-29T21:11:22.000Z

Aulas/Mundo 1/030.py

JoaoEmanuell/Meus-Estudos-Python

f6f6eeb6016919e594613785ffe7136d74241ada

[ "MIT" ]

null

Aulas/Mundo 1/030.py

JoaoEmanuell/Meus-Estudos-Python

f6f6eeb6016919e594613785ffe7136d74241ada

[ "MIT" ]

null

num = int(input('\033[1;31mMe diga um número \033[m')) resultado = num % 2 par = (0) impar = (1) if resultado == impar: print('\033[1;32mO número\033[m \033[1;31m{}\033[m \033[1;34mé impar\033[m'.format(num)) else: print('\033[1;33mO número\033[m \033[1;31m{}\033[m \033[1;34mé par\033[m'.format(num))

39.5

93

0.623418

62

316

3.177419

0.370968

0.142132

0.162437

0.294416

0

0.245353

0.148734

316

8

94

39.5

0.486989

0

0.25

0.535484

0

1

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false

0

0.25

0

null

0

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0

1

0

1

0

1

0

null

0

5

ff846ba2c62e7e2834b9c4c6ce9421ed288620f9

4,585

py

Python

resources/dot_PyCharm/system/python_stubs/-762174762/PySide/QtGui/QFormLayout.py

basepipe/developer_onboarding

05b6a776f8974c89517868131b201f11c6c2a5ad

[ "MIT" ]

1

2020-04-20T02:27:20.000Z

resources/dot_PyCharm/system/python_stubs/cache/8cdc475d469a13122bc4bc6c3ac1c215d93d5f120f5cc1ef33a8f3088ee54d8e/PySide/QtGui/QFormLayout.py

basepipe/developer_onboarding

05b6a776f8974c89517868131b201f11c6c2a5ad

[ "MIT" ]

null

resources/dot_PyCharm/system/python_stubs/cache/8cdc475d469a13122bc4bc6c3ac1c215d93d5f120f5cc1ef33a8f3088ee54d8e/PySide/QtGui/QFormLayout.py

basepipe/developer_onboarding

05b6a776f8974c89517868131b201f11c6c2a5ad

[ "MIT" ]

null

# encoding: utf-8 # module PySide.QtGui # from C:\Python27\lib\site-packages\PySide\QtGui.pyd # by generator 1.147 # no doc # imports import PySide.QtCore as __PySide_QtCore import Shiboken as __Shiboken from QLayout import QLayout class QFormLayout(QLayout): # no doc def addItem(self, *args, **kwargs): # real signature unknown pass def addRow(self, *args, **kwargs): # real signature unknown pass def count(self, *args, **kwargs): # real signature unknown pass def expandingDirections(self, *args, **kwargs): # real signature unknown pass def fieldGrowthPolicy(self, *args, **kwargs): # real signature unknown pass def formAlignment(self, *args, **kwargs): # real signature unknown pass def getItemPosition(self, *args, **kwargs): # real signature unknown pass def getLayoutPosition(self, *args, **kwargs): # real signature unknown pass def getWidgetPosition(self, *args, **kwargs): # real signature unknown pass def hasHeightForWidth(self, *args, **kwargs): # real signature unknown pass def heightForWidth(self, *args, **kwargs): # real signature unknown pass def horizontalSpacing(self, *args, **kwargs): # real signature unknown pass def insertRow(self, *args, **kwargs): # real signature unknown pass def invalidate(self, *args, **kwargs): # real signature unknown pass def itemAt(self, *args, **kwargs): # real signature unknown pass def labelAlignment(self, *args, **kwargs): # real signature unknown pass def labelForField(self, *args, **kwargs): # real signature unknown pass def minimumSize(self, *args, **kwargs): # real signature unknown pass def rowCount(self, *args, **kwargs): # real signature unknown pass def rowWrapPolicy(self, *args, **kwargs): # real signature unknown pass def setFieldGrowthPolicy(self, *args, **kwargs): # real signature unknown pass def setFormAlignment(self, *args, **kwargs): # real signature unknown pass def setGeometry(self, *args, **kwargs): # real signature unknown pass def setHorizontalSpacing(self, *args, **kwargs): # real signature unknown pass def setItem(self, *args, **kwargs): # real signature unknown pass def setLabelAlignment(self, *args, **kwargs): # real signature unknown pass def setLayout(self, *args, **kwargs): # real signature unknown pass def setRowWrapPolicy(self, *args, **kwargs): # real signature unknown pass def setSpacing(self, *args, **kwargs): # real signature unknown pass def setVerticalSpacing(self, *args, **kwargs): # real signature unknown pass def setWidget(self, *args, **kwargs): # real signature unknown pass def sizeHint(self, *args, **kwargs): # real signature unknown pass def spacing(self, *args, **kwargs): # real signature unknown pass def takeAt(self, *args, **kwargs): # real signature unknown pass def verticalSpacing(self, *args, **kwargs): # real signature unknown pass def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(S, *more): # real signature unknown; restored from __doc__ """ T.__new__(S, ...) -> a new object with type S, a subtype of T """ pass AllNonFixedFieldsGrow = PySide.QtGui.QFormLayout.FieldGrowthPolicy.AllNonFixedFieldsGrow DontWrapRows = PySide.QtGui.QFormLayout.RowWrapPolicy.DontWrapRows ExpandingFieldsGrow = PySide.QtGui.QFormLayout.FieldGrowthPolicy.ExpandingFieldsGrow FieldGrowthPolicy = None # (!) real value is "<type 'PySide.QtGui.QFormLayout.FieldGrowthPolicy'>" FieldRole = PySide.QtGui.QFormLayout.ItemRole.FieldRole FieldsStayAtSizeHint = PySide.QtGui.QFormLayout.FieldGrowthPolicy.FieldsStayAtSizeHint ItemRole = None # (!) real value is "<type 'PySide.QtGui.QFormLayout.ItemRole'>" LabelRole = PySide.QtGui.QFormLayout.ItemRole.LabelRole RowWrapPolicy = None # (!) real value is "<type 'PySide.QtGui.QFormLayout.RowWrapPolicy'>" SpanningRole = PySide.QtGui.QFormLayout.ItemRole.SpanningRole staticMetaObject = None # (!) real value is '<PySide.QtCore.QMetaObject object at 0x0000000003F48208>' WrapAllRows = PySide.QtGui.QFormLayout.RowWrapPolicy.WrapAllRows WrapLongRows = PySide.QtGui.QFormLayout.RowWrapPolicy.WrapLongRows

31.840278

106

0.676118

489

4,585

6.288344

0.208589

0.156423

0.24065

0.210732

0.537236

0.519024

0.506667

0

0.006443

0.221374

4,585

143

107

32.062937

0.854902

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0

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0

1

0.402174

false

0.402174

0.032609

0

0.586957

0

null

0

1

0

null

0

1

0

1

0

1

0

5

4410e87e6117bc5dfe33cf6364f7ca605cbea611

4,412

py

Python

function/python/brightics/function/classification/test/classification_test.py

GSByeon/studio

782cf484541c6d68e1451ff6a0d3b5dc80172664

[ "Apache-2.0" ]

null

function/python/brightics/function/classification/test/classification_test.py

GSByeon/studio

782cf484541c6d68e1451ff6a0d3b5dc80172664

[ "Apache-2.0" ]

null

function/python/brightics/function/classification/test/classification_test.py

GSByeon/studio

782cf484541c6d68e1451ff6a0d3b5dc80172664

[ "Apache-2.0" ]

1

2020-11-19T06:44:15.000Z

import unittest from brightics.function.classification import svm_classification_train, svm_classification_predict from brightics.function.transform import split_data from brightics.common.datasets import load_iris import pandas as pd import random from brightics.function.classification.decision_tree_classification import decision_tree_classification_train, \ decision_tree_classification_predict from brightics.function.classification.logistic_regression import logistic_regression_train, \ logistic_regression_predict from brightics.function.classification.xgb_classification import xgb_classification_train, \ xgb_classification_predict class SVMTest(unittest.TestCase): def test1(self): iris = load_iris() df_splitted = split_data(table=iris, train_ratio=0.7, test_ratio=0.3) train_df = df_splitted['train_table'] test_df = df_splitted['test_table'] train_out = svm_classification_train(table=train_df, feature_cols=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'], label_col='species') # print(train_out['model']['svc_model']) predict_out = svm_classification_predict(table=test_df, model=train_out['model']) print(predict_out['out_table'][['species', 'prediction']]) def test_predict_thresholds(self): iris = load_iris() df_splitted = split_data(table=iris, train_ratio=0.7, test_ratio=0.3) train_df = df_splitted['train_table'] test_df = df_splitted['test_table'] train_out = svm_classification_train(table=train_df, feature_cols=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'], label_col='species') # print(train_out['model']['svc_model']) predict_out = svm_classification_predict(table=test_df, model=train_out['model'], thresholds=[0.1, 0.2, 0.3]) print(predict_out['out_table'][['species', 'prediction']]) def test_groupby1(self): df = load_iris() random_group = [] for i in range(len(df)): random_group.append(random.randint(1, 2)) df['random_group'] = random_group train_out = svm_classification_train(table=df, feature_cols=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'], label_col='species', group_by=['random_group']) predict_out = svm_classification_predict(table=df, model=train_out['model']) print(predict_out['out_table'][['species', 'prediction']]) class DecisionTreeClassificationTest(unittest.TestCase): def test_groupby1(self): df = load_iris() random_group = [] for i in range(len(df)): random_group.append(random.randint(1, 2)) df['random_group'] = random_group train_out = decision_tree_classification_train(table=df, feature_cols=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'], label_col='species', group_by=['random_group']) predict_out = decision_tree_classification_predict(table=df, model=train_out['model']) print(predict_out['out_table'][['species', 'prediction']]) class LogisticRegressionTest(unittest.TestCase): def test_groupby1(self): df = load_iris() random_group = [] for i in range(len(df)): random_group.append(random.randint(1, 2)) df['random_group'] = random_group train_out = logistic_regression_train(table=df, feature_cols=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'], label_col='species', group_by=['random_group']) predict_out = logistic_regression_predict(table=df, model=train_out['model']) print(predict_out['out_table'][['species', 'prediction']]) class XGBClassificationTest(unittest.TestCase): def test_groupby1(self): df = load_iris() random_group = [] for i in range(len(df)): random_group.append(random.randint(1, 2)) df['random_group'] = random_group train_out = xgb_classification_train(table=df, feature_cols=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'], label_col='species', group_by=['random_group']) predict_out = xgb_classification_predict(table=df, model=train_out['model']) print(predict_out['out_table'][['species', 'prediction']])

46.442105

189

0.684723

534

4,412

5.320225

0.129213

0.077438

0.036607

0.038015

0.780007

0.730729

0.728617

0.712073

0

0.007589

0.193563

4,412

94

190

46.93617

0.790894

0.017452

0

0.588235

0

0.148199

0

1

0.088235

false

0

0.132353

0

0.279412

0.088235

0

null

0

1

0

null

0

5

441df44b23a1317552d5a8d14ec3a46c96c346fa

200

py

Python

py_reportit/shared/repository/crawl.py

fedus/py_reportit

46422cabb652571d8cce6c8e91a229009dcca141

[ "MIT" ]

1

2021-12-05T19:16:16.000Z

py_reportit/shared/repository/crawl.py

fedus/py_reportit

46422cabb652571d8cce6c8e91a229009dcca141

[ "MIT" ]

null

py_reportit/shared/repository/crawl.py

fedus/py_reportit

46422cabb652571d8cce6c8e91a229009dcca141

[ "MIT" ]

null

from py_reportit.shared.repository.abstract_repository import AbstractRepository from py_reportit.shared.model.crawl import Crawl class CrawlRepository(AbstractRepository[Crawl]): model = Crawl

28.571429

80

0.845

23

200

7.217391

0.521739

0.072289

0.168675

0.240964

0

0.095

200

6

81

33.333333

0.917127

0

1

0

false

0

0.5

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

444ab8aade30730cc88a7df30405f132f9e800cb

679

py

Python

twitch_uninstall_services.py

europaYuu/RaspiTwitchONAIR

8fa7a5f457a297e9b06fb946e89c33a0d49e335f

[ "MIT" ]

null

twitch_uninstall_services.py

europaYuu/RaspiTwitchONAIR

8fa7a5f457a297e9b06fb946e89c33a0d49e335f

[ "MIT" ]

null

twitch_uninstall_services.py

europaYuu/RaspiTwitchONAIR

8fa7a5f457a297e9b06fb946e89c33a0d49e335f

[ "MIT" ]

null

import os os.system('sudo systemctl disable twitch_onair_webserver_service') os.system('sudo systemctl disable twitch_onair_neopixel_service') os.system('sudo systemctl disable powerButton') os.system('sudo systemctl disable functionButton') os.system('sudo systemctl disable oled_service') os.system('sudo rm /lib/systemd/system/twitch_onair_webserver_service.service') os.system('sudo rm /lib/systemd/system/twitch_onair_neopixel_service.service') os.system('sudo rm /lib/systemd/system/powerButton.service') os.system('sudo rm /lib/systemd/system/functionButton.service') os.system('sudo rm /lib/systemd/system/oled_service.service') os.system('sudo systemctl daemon-reload')

52.230769

79

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97

679

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0.161765

0.242647

0.279412

0.794118

0.626838

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0.40625

0.270221

0.176471

0

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679

13

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0

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true

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0.083333

0

null

0

1

0

1

null

0

1

0

5

444c276fed8a2f52c4bfc671803cb99f075b3a78

171

py

Python

butter_cms/feed.py

ButterCMS/buttercms-python

46892eff36f20829b130684a85994e7178eb4ef2

[ "MIT" ]

33

2017-03-28T03:11:23.000Z

2020-12-21T16:13:59.000Z

butter_cms/feed.py

skroys/buttercms-python

6797e2a5f1ded6112e7d2b2f60561798ca4e2731

[ "MIT" ]

4

2017-09-16T05:08:20.000Z

2022-03-11T15:19:53.000Z

butter_cms/feed.py

skroys/buttercms-python

6797e2a5f1ded6112e7d2b2f60561798ca4e2731

[ "MIT" ]

9

2017-11-03T12:51:48.000Z

2021-11-09T08:40:13.000Z

from .client import Client class Feed(Client): """Feed""" def __init__(self, auth_token): Client.__init__(self, auth_token) self.path = 'feeds/'

19

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4.619048

0.571429

0.164948

0.247423

0.350515

0

0.239766

171

8

42

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0

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false

0

0.2

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0.6

0

1

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null

0

1

0

1

0

null

0

1

0

5

445a4e53843ac50d8ed751c8e4f20b3ed3bc6e5d

4,731

py

Python

python/fcdd/models/fcdd_vark.py

kyungmin96/myfcdd

eb3062105e0b345f0abc4aebcbc48247bc9fcda0

[ "MIT" ]

152

2020-07-08T05:44:40.000Z

2022-03-29T07:10:22.000Z

python/fcdd/models/fcdd_vark.py

kyungmin96/myfcdd

eb3062105e0b345f0abc4aebcbc48247bc9fcda0

[ "MIT" ]

21

2020-07-07T12:00:02.000Z

2022-03-23T03:50:23.000Z

python/fcdd/models/fcdd_vark.py

kyungmin96/myfcdd

eb3062105e0b345f0abc4aebcbc48247bc9fcda0

[ "MIT" ]

39

2020-09-14T05:45:08.000Z

2022-03-25T09:53:30.000Z

import torch.nn as nn import torch.nn.functional as F from fcdd.models.bases import FCDDNet class FCDD_CNN224_VARK(FCDDNet): def __init__(self, in_shape, k=3, **kwargs): assert k % 2 == 1, 'kernel size needs to be uneven' p = (k - 1) // 2 super().__init__(in_shape, **kwargs) self.conv1 = self._create_conv2d(in_shape[0], 32, k, bias=self.bias, padding=p) self.bn2d1 = nn.BatchNorm2d(32, eps=1e-04, affine=self.bias) self.pool1 = self._create_maxpool2d(3, 2, 1) # 32 x 112 x 112 self.conv2 = self._create_conv2d(32, 128, k, bias=self.bias, padding=p) self.bn2d2 = nn.BatchNorm2d(128, eps=1e-04, affine=self.bias) self.pool2 = self._create_maxpool2d(3, 2, 1) # 128 x 56 x 56 self.conv3 = self._create_conv2d(128, 256, k, bias=self.bias, padding=p) self.bn2d3 = nn.BatchNorm2d(256, eps=1e-04, affine=self.bias) self.conv4 = self._create_conv2d(256, 256, k, bias=self.bias, padding=p) self.bn2d4 = nn.BatchNorm2d(256, eps=1e-04, affine=self.bias) self.pool3 = self._create_maxpool2d(3, 2, 1) # 256 x 28 x 28 self.conv5 = self._create_conv2d(256, 128, k, bias=self.bias, padding=p) self.encoder_out_shape = (128, 28, 28) self.conv_final = self._create_conv2d(128, 1, 1, bias=self.bias) def forward(self, x, ad=True): x = self.conv1(x) x = F.leaky_relu(self.bn2d1(x)) x = self.pool1(x) x = self.conv2(x) x = F.leaky_relu(self.bn2d2(x)) x = self.pool2(x) x = self.conv3(x) x = F.leaky_relu(self.bn2d3(x)) x = self.conv4(x) x = F.leaky_relu(self.bn2d4(x)) x = self.pool3(x) x = self.conv5(x) if ad: x = self.conv_final(x) # n x heads x h' x w' return x class FCDD_CNN224_3K(FCDD_CNN224_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=3, **kwargs) class FCDD_CNN224_5K(FCDD_CNN224_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=5, **kwargs) class FCDD_CNN224_7K(FCDD_CNN224_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=7, **kwargs) class FCDD_CNN224_9K(FCDD_CNN224_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=9, **kwargs) class FCDD_CNN224_11K(FCDD_CNN224_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=11, **kwargs) class FCDD_CNN224_13K(FCDD_CNN224_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=13, **kwargs) class FCDD_CNN32_VARK(FCDDNet): def __init__(self, in_shape, k=3, **kwargs): assert k % 2 == 1, 'kernel size needs to be uneven' p = (k - 1) // 2 super().__init__(in_shape, **kwargs) self.conv1 = self._create_conv2d(in_shape[0], 128, k, bias=self.bias, padding=p) self.bn2d1 = nn.BatchNorm2d(128, eps=1e-04, affine=self.bias) self.pool1 = self._create_maxpool2d(2, 2) self.conv2 = self._create_conv2d(128, 256, 3, bias=self.bias, padding=1) self.bn2d2 = nn.BatchNorm2d(256, eps=1e-04, affine=self.bias) self.pool2 = self._create_maxpool2d(2, 2) self.conv3 = self._create_conv2d(256, 128, 3, bias=self.bias, padding=1) self.conv_final = self._create_conv2d(128, 1, 1, bias=self.bias) def forward(self, x, ad=True): x = self.conv1(x) x = self.pool1(F.leaky_relu(self.bn2d1(x))) x = self.conv2(x) x = self.pool2(F.leaky_relu(self.bn2d2(x))) x = self.conv3(x) if ad: x = self.conv_final(x) # n x heads x h' x w' return x class FCDD_CNN32_3K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=3, **kwargs) class FCDD_CNN32_5K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=5, **kwargs) class FCDD_CNN32_7K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=7, **kwargs) class FCDD_CNN32_9K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=9, **kwargs) class FCDD_CNN32_11K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=11, **kwargs) class FCDD_CNN32_13K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=13, **kwargs) class FCDD_CNN32_15K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=15, **kwargs) class FCDD_CNN32_17K(FCDD_CNN32_VARK): def __init__(self, *args, **kwargs): super().__init__(*args, k=17, **kwargs)

32.40411

88

0.619531

725

4,731

3.717241

0.131034

0.056772

0.065306

0.077922

0.849722

0.797032

0.762894

0.745826

0.666048

0

0.089442

0.227225

4,731

145

89

32.627586

0.647702

0.017332

0

0.490196

0

0.012923

0

0.019608

1

0.176471

false

0

0.029412

0

0.382353

0

null

0

1

0

1

0

null

0

5

446b6bdff4d4aac132485087c94178da817f52aa

47

py

Python

AtCoder/ABC107/A.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

1

2018-11-25T04:15:45.000Z

AtCoder/ABC107/A.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

null

AtCoder/ABC107/A.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

2

2018-08-08T13:01:14.000Z

2018-11-25T12:38:36.000Z

N, i = map(int, input().split()) print(N-i+1)

11.75

32

0.553191

10

47

2.6

0.8

0.153846

0

0.025

0.148936

47

3

33

15.666667

0.625

0

1

0

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

5

92407e50b2c8faa8d671f4096450ed2ebf548e1c

71

py

Python

quaesit/__init__.py

jgregoriods/quaesit

3846f5084ea4d6c1cbd9a93176ee9dee25e12105

[ "MIT" ]

null

quaesit/__init__.py

jgregoriods/quaesit

3846f5084ea4d6c1cbd9a93176ee9dee25e12105

[ "MIT" ]

null

quaesit/__init__.py

jgregoriods/quaesit

3846f5084ea4d6c1cbd9a93176ee9dee25e12105

[ "MIT" ]

null

from .agent import Agent from .gui import GUI from .world import World

17.75

24

0.788732

12

71

4.666667

0.416667

0

0.169014

71

3

25

23.666667

0.949153

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

925ff3c1a99f975c4fe57081c6a973d5ce11a7b8

166

py

Python

tests/cases/shell/reasonable_output_if_unknown_cmd/test_reasonable_output_for_unknown_cmd.py

WilliamMayor/vantage

05cda557cfc27cbf8aaf80a472a023a896e98546

[ "MIT" ]

1

2018-02-21T09:50:53.000Z

tests/cases/shell/reasonable_output_if_unknown_cmd/test_reasonable_output_for_unknown_cmd.py

WilliamMayor/vantage

05cda557cfc27cbf8aaf80a472a023a896e98546

[ "MIT" ]

15

2015-04-30T15:19:29.000Z

2021-07-28T14:34:46.000Z

tests/cases/shell/reasonable_output_if_unknown_cmd/test_reasonable_output_for_unknown_cmd.py

WilliamMayor/vantage

05cda557cfc27cbf8aaf80a472a023a896e98546

[ "MIT" ]

null

def test_reasonable_output_for_unknown_cmd(result): assert result.exit_code == 1 assert result.stderr_ == "vantage: error: Command 'not-a-command' not found"

41.5

80

0.759036

24

166

4.958333

0.791667

0.201681

0

0.006993

0.138554

166

3

81

55.333333

0.825175

0

0.295181

0

0.666667

1

0.333333

false

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

2bbbac086320598591f7393fda6bc51c191a10c9

239

py

Python

applications/views/admin/context_processor.py

solitary-sen/pear-admin-flask

c2ce10bb2a51fd7376ca1d211e30380fca119a19

[ "MIT" ]

1

2021-12-06T06:13:30.000Z

applications/views/admin/context_processor.py

solitary-sen/pear-admin-flask

c2ce10bb2a51fd7376ca1d211e30380fca119a19

[ "MIT" ]

null

applications/views/admin/context_processor.py

solitary-sen/pear-admin-flask

c2ce10bb2a51fd7376ca1d211e30380fca119a19

[ "MIT" ]

null

from flask import session def init_template_global(app): @app.template_global() def authorize(power): # print(power) # print(session.get('permissions')) return bool(power in session.get('permissions'))

19.916667

57

0.656904

28

239

5.5

0.607143

0.181818

0.272727

0

0.225941

239

11

58

21.727273

0.832432

0.192469

0

0.058511

0

1

0.4

false

0

0.2

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

5

2bc3f8ba47df2192458a929f8124a9753c4dd674

359

py

Python

creatures/animals/Fox.py

stasgora/python-world-simulator

f574c8791de4d8045e1ebcbe48e6e66c3f2ff256

[ "MIT" ]

null

creatures/animals/Fox.py

stasgora/python-world-simulator

f574c8791de4d8045e1ebcbe48e6e66c3f2ff256

[ "MIT" ]

null

creatures/animals/Fox.py

stasgora/python-world-simulator

f574c8791de4d8045e1ebcbe48e6e66c3f2ff256

[ "MIT" ]

null

from ..Animal import Animal class Fox(Animal): def __init__(self, strength, initiative, symbol, position, world, color): super(Fox, self).__init__(strength, initiative, symbol, position, world, color) def get_move_pos(self): return self._world.get_map().get_pos_nearby(self._position, False, self._range, self._strength)

32.636364

104

0.70195

46

359

5.108696

0.5

0.102128

0.204255

0.27234

0.357447

0

0.183844

359

10

105

35.9

0.802048

0

1

0.333333

false

0

0.166667

0.833333

0

null

0

1

0

null

0

1

0

1

0

5

920aa4e0f853887c83492d931ac2dc41d89e4a50

133

py

Python

python/benchmark/utils/fst.py

jkomyno/lattice-submodular-maximization

e03c8bcc5fcf5bf79a6ae81f145757cf3fdff7cb

[ "MIT" ]

1

2021-11-16T18:16:42.000Z

python/benchmark/utils/fst.py

jkomyno/lattice-submodular-maximization

e03c8bcc5fcf5bf79a6ae81f145757cf3fdff7cb

[ "MIT" ]

null

python/benchmark/utils/fst.py

jkomyno/lattice-submodular-maximization

e03c8bcc5fcf5bf79a6ae81f145757cf3fdff7cb

[ "MIT" ]

null

from typing import Tuple, TypeVar, Set, Any T = TypeVar('T', int, float, Set[int]) def fst(x: Tuple[T, Any]) -> T: return x[0]

19

43

0.616541

24

133

3.416667

0.625

0.097561

0

0.009434

0.203008

133

6

44

22.166667

0.764151

0

0.007519

0

1

0.25

false

0

0.25

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

5

920aec40f0cae2a5d71edc12932c140b48f49637

66

py

Python

PVGPpy/macros/__init__.py

aashish24/ParaViewGeophysics

d9a71ffd21a57fa0eb704c5f6893ec9b1ddf6da6

[ "BSD-3-Clause" ]

null

PVGPpy/macros/__init__.py

aashish24/ParaViewGeophysics

d9a71ffd21a57fa0eb704c5f6893ec9b1ddf6da6

[ "BSD-3-Clause" ]

null

PVGPpy/macros/__init__.py

aashish24/ParaViewGeophysics

d9a71ffd21a57fa0eb704c5f6893ec9b1ddf6da6

[ "BSD-3-Clause" ]

null

from norm_slices_along_points import * from clip_through import *

22

38

0.848485

10

66

5.2

0.8

0

0.121212

66

2

39

33

0.896552

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

a64474a8af7279131eae2c696e2c0ae67d09425a

132

py

Python

training_api/shared/helpers/classes_helper.py

BMW-InnovationLab/BMW-Semantic-Segmentation-Training-GUI

902f35a7e367e635898f687b16a830db892fbaa5

[ "Apache-2.0" ]

20

2021-07-13T13:08:57.000Z

2022-03-29T09:38:00.000Z

training_api/shared/helpers/classes_helper.py

BMW-InnovationLab/BMW-Semantic-Segmentation-Training-GUI

902f35a7e367e635898f687b16a830db892fbaa5

[ "Apache-2.0" ]

null

training_api/shared/helpers/classes_helper.py

BMW-InnovationLab/BMW-Semantic-Segmentation-Training-GUI

902f35a7e367e635898f687b16a830db892fbaa5

[ "Apache-2.0" ]

2

2021-07-12T08:42:53.000Z

2022-03-04T18:41:25.000Z

def get_num_classes(classes_path: str) -> int: classes: str = open(classes_path, 'r').read() return len(classes.split(','))

33

49

0.666667

19

132

4.421053

0.684211

0.261905

0

0.151515

132

3

50

44

0.75

0

0.015152

0

1

0.333333

false

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

a64d6ff3c492525cc51f24edec3f80d93d04ea33

16

py

Python

tests/test-recipes/metadata/_compile-test/f3.py

DerThorsten/conda-build

729c0cea03677dae0e2e15b7ec6d98619b5d4401

[ "BSD-3-Clause" ]

5

2016-05-10T23:36:56.000Z

2021-04-21T17:09:18.000Z

tests/test-recipes/metadata/_compile-test/f3.py

DerThorsten/conda-build

729c0cea03677dae0e2e15b7ec6d98619b5d4401

[ "BSD-3-Clause" ]

6

2016-07-05T19:08:39.000Z

2017-10-23T10:59:14.000Z

tests/test-recipes/metadata/_compile-test/f3.py

DerThorsten/conda-build

729c0cea03677dae0e2e15b7ec6d98619b5d4401

[ "BSD-3-Clause" ]

5

2016-10-08T19:31:55.000Z

2021-10-10T18:24:42.000Z

print("File 3")

8

15

0.625

3

16

3.333333

1

0

0.071429

0.125

16

1

16

0.642857

0

0.375

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

a6c5115b5bd0ba232b4a04dcb2362d77e7e7a8e2

184

py

Python

src/lib/centipede/TaskWrapper/aux/gafferRunSerializedTask.py

ramgopal99/centipede

0b1dc1f17b025f6b37c9a3cf5753a46cbbcd36ba

[ "MIT" ]

3

2018-05-28T20:56:19.000Z

2018-06-02T15:58:10.000Z

src/lib/centipede/TaskWrapper/aux/gafferRunSerializedTask.py

ramgopal99/centipede

0b1dc1f17b025f6b37c9a3cf5753a46cbbcd36ba

[ "MIT" ]

2

2018-07-01T07:45:38.000Z

2018-07-11T03:15:35.000Z

src/lib/centipede/TaskWrapper/aux/gafferRunSerializedTask.py

ramgopal99/centipede

0b1dc1f17b025f6b37c9a3cf5753a46cbbcd36ba

[ "MIT" ]

3

2018-07-10T14:51:13.000Z

2022-03-17T00:39:58.000Z

# gaffer needs to be imported at top-most import Gaffer # now we can import centipede import centipede # running serialized task centipede.TaskWrapper.Subprocess.runSerializedTask()

20.444444

52

0.815217

24

184

6.25

0.791667

0.2

0

0.13587

184

8

53

23

0.943396

0.494565

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

a6f8f825d0e13375be4fccd5f52201df9949c4ac

28

py

Python

rest/settings.py

engleandro/Portifolio-WhatsAppAutomation

f01d181697215aee3d105e3ad94e2593b7732e5c

[ "Apache-2.0" ]

null

rest/settings.py

engleandro/Portifolio-WhatsAppAutomation

f01d181697215aee3d105e3ad94e2593b7732e5c

[ "Apache-2.0" ]

null

rest/settings.py

engleandro/Portifolio-WhatsAppAutomation

f01d181697215aee3d105e3ad94e2593b7732e5c

[ "Apache-2.0" ]

null

class MySettings(): pass

14

19

0.678571

3

28

6.333333

1

0

0.214286

28

2

20

14

0.863636

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

5b34a2e04283b1e77743c79f4c17e7e4e64f15f2

234

py

Python

closed/FuriosaAI/code/quantization/furiosa_sdk_quantizer/frontend/onnx/transformer/experimental/__init__.py

ctuning/inference_results_v1.1

d9176eca28fcf6d7a05ccb97994362a76a1eb5ab

[ "Apache-2.0" ]

12

2021-09-23T08:05:57.000Z

2022-03-21T03:52:11.000Z

closed/FuriosaAI/code/quantization/furiosa_sdk_quantizer/frontend/onnx/transformer/experimental/__init__.py

ctuning/inference_results_v1.1

d9176eca28fcf6d7a05ccb97994362a76a1eb5ab

[ "Apache-2.0" ]

11

2021-09-23T20:34:06.000Z

2022-01-22T07:58:02.000Z

closed/FuriosaAI/code/quantization/furiosa_sdk_quantizer/frontend/onnx/transformer/experimental/__init__.py

ctuning/inference_results_v1.1

d9176eca28fcf6d7a05ccb97994362a76a1eb5ab

[ "Apache-2.0" ]

16

2021-09-23T20:26:38.000Z

2022-03-09T12:59:56.000Z

from furiosa_sdk_quantizer.frontend.onnx.transformer.experimental.fuse_div_for_bert import ( FuseDivForBert, ) from furiosa_sdk_quantizer.frontend.onnx.transformer.experimental.reify_conv_for_bert import ( ReifyConvForBert, )

33.428571

94

0.846154

28

234

6.714286

0.607143

0.117021

0.148936

0.244681

0.617021

0

0.08547

234

6

95

39

0.878505

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

5b567a8055799d331ce1797e3fb8316f98ff8b25

342

py

Python

tests/ReLGetExpNums.py

nelmiux/CS347-Data_Management

1e9d87097b5a373f9312b0d6b413198e495fd6c0

[ "CNRI-Jython" ]

null

tests/ReLGetExpNums.py

nelmiux/CS347-Data_Management

1e9d87097b5a373f9312b0d6b413198e495fd6c0

[ "CNRI-Jython" ]

null

tests/ReLGetExpNums.py

nelmiux/CS347-Data_Management

1e9d87097b5a373f9312b0d6b413198e495fd6c0

[ "CNRI-Jython" ]

null

connectTo 'jdbc:oracle:thin:@ib-perfdb.us.oracle.com:1525:perfdb' 'cannata' 'orcl' 'remote'; for i in range(1,65) : SQL """ insert into ibexperiment(name, exp_date, tool, protocol, published) values ('BM on cloud-mwm-15 -> cloud-mwm-16 S12b23 1 stream only, multi-parts """ i """/ 64', to_char(sysdate), 'rds-stress', 'IPoIB', 'Yes');"""

85.5

225

0.678363

54

342

4.259259

0.888889

0.069565

0

0.06

0.122807

342

3

226

114

0.706667

0

0.333333

0.798246

0.154971

0

null

0

null

0

null

0

1

0

1

0

1

0

null

0

1

0

5

5babf059a2a80e85471f8189b5df1ed0af9bc5e5

42

py

Python

pasta para baixar/netcha/benvindo.py

vany-oss/python

f687d9cd798af7038d9ce963e5e7ba167010331a

[ "MIT" ]

null

pasta para baixar/netcha/benvindo.py

vany-oss/python

f687d9cd798af7038d9ce963e5e7ba167010331a

[ "MIT" ]

null

pasta para baixar/netcha/benvindo.py

vany-oss/python

f687d9cd798af7038d9ce963e5e7ba167010331a

[ "MIT" ]

null

print('ola mundo ') # esse e o primeiro pg

21

22

0.690476

8

42

3.625

1

0

0.190476

42

2

22

21

0.852941

0.47619

0

0.47619

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

5bb03870924d828da4926eca7596f02cc199d949

277

py

Python

django_fieldbustier/fieldbustier_config.py

OmenApps/django-fieldbustier

4189f419eafa67648d65ed50195a7bb5d9ee159c

[ "MIT" ]

null

django_fieldbustier/fieldbustier_config.py

OmenApps/django-fieldbustier

4189f419eafa67648d65ed50195a7bb5d9ee159c

[ "MIT" ]

null

django_fieldbustier/fieldbustier_config.py

OmenApps/django-fieldbustier

4189f419eafa67648d65ed50195a7bb5d9ee159c

[ "MIT" ]

null

from collections import namedtuple FieldBustierConfig = namedtuple( "FieldBustierConfig", ["app_name", "model_klass", "field_name", "field_klass", "args", "kwargs"] ) DeleteFieldBustierConfig = namedtuple("FieldBustierConfig", ["app_name", "model_klass", "field_name"])

30.777778

102

0.750903

26

277

7.730769

0.5

0.41791

0.308458

0.348259

0.537313

0

0.101083

277

8

103

34.625

0.807229

0

0.415162

0

1

0

false

0

0.2

0

0.2

0

1

0

null

1

0

1

0

null

0

5

5bba66d584bb5e5550bf6d8970af0ac56bdabd1f

80

py

Python

vedastr/models/bodies/sequences/transformer/__init__.py

csmasters/vedastr

7513384ab503f15dc574c7d92b75ff2092354757

[ "Apache-2.0" ]

475

2020-03-17T01:46:32.000Z

2022-03-29T23:30:15.000Z

vedastr/models/bodies/sequences/transformer/__init__.py

csmasters/vedastr

7513384ab503f15dc574c7d92b75ff2092354757

[ "Apache-2.0" ]

71

2020-04-01T04:17:47.000Z

2021-11-18T06:55:14.000Z

vedastr/models/bodies/sequences/transformer/__init__.py

csmasters/vedastr

7513384ab503f15dc574c7d92b75ff2092354757

[ "Apache-2.0" ]

108

2020-02-21T10:30:37.000Z

2022-03-21T12:03:30.000Z

from .encoder import TransformerEncoder from .decoder import TransformerDecoder

26.666667

39

0.875

8

80

8.75

0.75

0

0.1

80

2

40

0.972222

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

5bfb1fe5ab623887900be4a20461e870f5fd685a

30

py

Python

validator/user/user_validator.py

JadenChoi2k/python-csv-http-db

0947d42717723bb3887522c8b36379f67cc673b2

[ "MIT" ]

null

validator/user/user_validator.py

JadenChoi2k/python-csv-http-db

0947d42717723bb3887522c8b36379f67cc673b2

[ "MIT" ]

null

validator/user/user_validator.py

JadenChoi2k/python-csv-http-db

0947d42717723bb3887522c8b36379f67cc673b2

[ "MIT" ]

null

class UserValidator: pass

10

20

0.733333

3

30

7.333333

1

0

0.233333

30

2

21

15

0.956522

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

5

753f2f59734f6b5c0094f78b08c9279198b9daf0

5,044

py

Python

src/tests.py

simoncrowe/bookchain-validator

2ce4091f1ad297f667fdedbc6c97c0ec2e3903c8

[ "MIT" ]

null

src/tests.py

simoncrowe/bookchain-validator

2ce4091f1ad297f667fdedbc6c97c0ec2e3903c8

[ "MIT" ]

null

src/tests.py

simoncrowe/bookchain-validator

2ce4091f1ad297f667fdedbc6c97c0ec2e3903c8

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """Quick and dirty "unit" tests for API. Too complex but do the job.""" from multiprocessing import Process import unittest import time import requests from app import app class CallLocalApiTestCase(unittest.TestCase): @classmethod def setUpClass(cls): cls.test_server = Process(target=app.run) cls.test_server.start() # Wait for the test server to start time.sleep(1) @classmethod def tearDownClass(cls): cls.test_server.terminate() cls.test_server.join() def test_greeting_without_latest_text(self): response = requests.post('http://127.0.0.1:5000/greeting') self.assertEqual(response.status_code, 200) self.assertEqual( response.json(), app.config['GREETING_NO_REQUIRED_STRING'] ) def test_greeting_with_latest_block_text_containing_stop_word(self): response = requests.post( 'http://127.0.0.1:5000/greeting', data={'latest_block_text': 'Almost'} ) self.assertEqual(response.status_code, 200) self.assertEqual( response.json(), app.config['GREETING_NO_REQUIRED_STRING'] ) def test_greeting_with_latest_block_text_containing_verbs(self): response = requests.post( 'http://127.0.0.1:5000/greeting', data={'latest_block_text': 'subsist exist.'} ) self.assertEqual(response.status_code, 200) self.assertEqual( response.json(), app.config['GREETING_TEMPLATE_WITH_REQUIRED_STRING'].replace( '{{ required_string }}', 'exist' ) ) def test_greeting_with_latest_block_text_containing_noun_phrases(self): response = requests.post( 'http://127.0.0.1:5000/greeting', data={'latest_block_text': 'The quick brown fox jumps over the lazy dog.'} ) self.assertEqual(response.status_code, 200) self.assertEqual( response.json(), app.config['GREETING_TEMPLATE_WITH_REQUIRED_STRING'].replace( '{{ required_string }}', 'the lazy dog' ) ) def test_validate_with_no_latest_text_and_no_matching_pattern(self): response = requests.post( 'http://127.0.0.1:5000/validate', data={'proposed_block_text': 'I am a the lazy dog.'} ) self.assertEqual(response.status_code, 200) self.assertDictEqual( response.json(), { 'valid': False, 'message': app.config['PROPOSAL_INVALID_MESSAGE'] } ) def test_validate_with_latest_text_and_no_matching_pattern(self): response = requests.post( 'http://127.0.0.1:5000/validate', data={ 'latest_block_text': 'I once was a spoon.', 'proposed_block_text': 'I am a the lazy dog.' } ) self.assertEqual(response.status_code, 200) self.assertDictEqual( response.json(), { 'valid': False, 'message': app.config['PROPOSAL_INVALID_MESSAGE'] } ) def test_validate_with_latest_text_and_matching_pattern(self): response = requests.post( 'http://127.0.0.1:5000/validate', data={ 'latest_block_text': 'I paid £1 for my spoon.', 'proposed_block_text': 'I did not earn my $1,000,000,000.' } ) self.assertEqual(response.status_code, 200) self.assertDictEqual( response.json(), { 'valid': True, 'message': app.config['PROPOSAL_VALID_MESSAGE'] } ) def test_validate_with_latest_text_and_matching_phrase(self): response = requests.post( 'http://127.0.0.1:5000/validate', data={ 'latest_block_text': 'I hated her.', 'proposed_block_text': 'I loved her.' } ) self.assertEqual(response.status_code, 200) self.assertDictEqual( response.json(), { 'valid': True, 'message': app.config['PROPOSAL_VALID_MESSAGE'] } ) def test_validate_with_latest_text_matching_phrase_and_pattern(self): response = requests.post( 'http://127.0.0.1:5000/validate', data={ 'latest_block_text': 'I hated her £500 shoes.', 'proposed_block_text': 'I loved her £500 shoes.' } ) self.assertEqual(response.status_code, 200) self.assertDictEqual( response.json(), { 'valid': True, 'message': app.config['PROPOSAL_VALID_MESSAGE'] } ) if __name__ == '__main__': unittest.main()

30.569697

86

0.560468

536

5,044

5.024254

0.223881

0.05013

0.111029

0.080208

0.768288

0.757891

0.738582

0.722243

0.718158

0

0.040509

0.3295

5,044

165

87

30.569697

0.754879

0.028351

0

0.474453

0

0.225582

0.049857

0

0.131387

1

0.080292

false

0

0.036496

0

0.124088

0

null

0

1

0

null

0

5

7552c07346e47dadf936ebc70a4725f342c0497c

37

py

Python

routes/index.py

felipe2323/habi-test-api

0dd1c84b3b816dcaaf324261620c11768ea56b63

[ "MIT" ]

null

routes/index.py

felipe2323/habi-test-api

0dd1c84b3b816dcaaf324261620c11768ea56b63

[ "MIT" ]

null

routes/index.py

felipe2323/habi-test-api

0dd1c84b3b816dcaaf324261620c11768ea56b63

[ "MIT" ]

null

from routes.property import property_

37

0.891892

5

37

6.4

0.8

0

0.081081

37

1

37

0.941176

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

755a8398bd049fc90f65a949727f10b4e33f81a2

268

py

Python

examples/print_cur_tb.py

cclauss/traceback_with_variables

a2bbeb0629535a81f68e1c60a04a7db0ca7470ba

[ "MIT" ]

550

2020-10-31T18:19:24.000Z

2022-03-31T17:40:07.000Z

examples/print_cur_tb.py

cclauss/traceback_with_variables

a2bbeb0629535a81f68e1c60a04a7db0ca7470ba

[ "MIT" ]

20

2020-10-29T15:20:35.000Z

2021-12-06T00:00:08.000Z

examples/print_cur_tb.py

cclauss/traceback_with_variables

a2bbeb0629535a81f68e1c60a04a7db0ca7470ba

[ "MIT" ]

24

2020-11-04T05:12:36.000Z

2022-03-18T05:38:59.000Z

from traceback_with_variables import print_cur_tb # , format_cur_tb, iter_cur_tb_lines def f(n): print_cur_tb() # cur_tb_str = format_cur_tb() # cur_tb_lines = list(iter_cur_tb_lines()) return n + 1 def main(): f(10) main()

15.764706

88

0.63806

43

268

3.511628

0.465116

0.264901

0.198676

0.18543

0

0.015228

0.264925

268

16

89

16.75

0.751269

0.38806

0

1

0.285714

false

0

0.142857

0

0.571429

0.285714

0

null

1

0

null

0

1

0

1

0

5

755dd9140247198cd698a9c435a540d43ab0990c

153

py

Python

server/umoveapp/admin.py

tekishahammock/Backend-Capstone-uMove

12feb7b778e7abeed428bcef00e417a028db9bf3

[ "MIT" ]

null

server/umoveapp/admin.py

tekishahammock/Backend-Capstone-uMove

12feb7b778e7abeed428bcef00e417a028db9bf3

[ "MIT" ]

null

server/umoveapp/admin.py

tekishahammock/Backend-Capstone-uMove

12feb7b778e7abeed428bcef00e417a028db9bf3

[ "MIT" ]

null

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

19.125

33

0.797386

22

153

5.545455

0.545455

0.147541

0.278689

0

0.117647

153

7

34

21.857143

0.903704

0.169935

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

f3b1b5347b70350c2e3a4be5b38c17cc13ebe59f

101

py

Python

htchirp/__main__.py

BrunoCoimbra/htchirp

e75492a00d3acd3233c9bf57fb0a194cb8fbfa5d

[ "Apache-2.0" ]

null

htchirp/__main__.py

BrunoCoimbra/htchirp

e75492a00d3acd3233c9bf57fb0a194cb8fbfa5d

[ "Apache-2.0" ]

null

htchirp/__main__.py

BrunoCoimbra/htchirp

e75492a00d3acd3233c9bf57fb0a194cb8fbfa5d

[ "Apache-2.0" ]

null

from __future__ import absolute_import from htchirp import client import sys sys.exit(client.main())

20.2

38

0.831683

15

101

5.266667

0.6

0

0.108911

101

5

39

20.2

0.877778

0

1

0

true

0

0.75

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

45fd7034fb94aa5ef1498eff38bac2c729701fac

157

py

Python

src/installer/_compat/typing.py

FFY00/installer

86c028799437bea9ff1996d4c4d463897102b266

[ "MIT" ]

null

src/installer/_compat/typing.py

FFY00/installer

86c028799437bea9ff1996d4c4d463897102b266

[ "MIT" ]

null

src/installer/_compat/typing.py

FFY00/installer

86c028799437bea9ff1996d4c4d463897102b266

[ "MIT" ]

null

try: # pragma: no cover from typing import TYPE_CHECKING except ImportError: # pragma: no cover TYPE_CHECKING = False __all__ = ["TYPE_CHECKING"]

22.428571

39

0.719745

20

157

5.3

0.65

0.339623

0.245283

0

0.203822

157

6

40

26.166667

0.848

0.210191

0

0.107438

0

1

0

false

0

0.4

0

0.4

0

1

0

null

1

0

1

0

null

0

1

0

5

3418a4fcd57ffcafd919952d1df26391e8d69b44

259

py

Python

facturador/stock/admin.py

crodriguezud/Facturador

1a1e08072ae1d54f3f7963cdd202444618a0fa2e

[ "Apache-2.0" ]

null

facturador/stock/admin.py

crodriguezud/Facturador

1a1e08072ae1d54f3f7963cdd202444618a0fa2e

[ "Apache-2.0" ]

9

2020-06-05T17:25:18.000Z

2022-03-11T23:15:36.000Z

facturador/stock/admin.py

crodriguezud/Facturador

1a1e08072ae1d54f3f7963cdd202444618a0fa2e

[ "Apache-2.0" ]

null

from django.contrib import admin from .models import TipoProducto, TipoEstampado, Color, Producto, Talla admin.site.register(TipoProducto) admin.site.register(TipoEstampado) admin.site.register(Talla) admin.site.register(Color) admin.site.register(Producto)

28.777778

71

0.830116

33

259

6.515152

0.393939

0.209302

0.395349

0.204651

0

0.069498

259

9

72

28.777778

0.892116

0

1

0

true

0

0.285714

0

0.285714

0

null

1

0

1

0

null

0

1

0

5

caa7a4df4fa79a24bbd9807eb4a18b8c265ce749

110

py

Python

neuralnet_pytorch/extensions/bpd.py

justanhduc/neuralnet-pytorch

cbb0c5a540a0ba91cb4dd20684bb00692305d193

[ "MIT" ]

28

2019-01-07T04:07:55.000Z

2021-11-09T15:16:11.000Z

neuralnet_pytorch/extensions/bpd.py

justanhduc/neuralnet-pytorch

cbb0c5a540a0ba91cb4dd20684bb00692305d193

[ "MIT" ]

9

2019-12-25T08:00:33.000Z

2021-11-23T09:02:34.000Z

neuralnet_pytorch/extensions/bpd.py

justanhduc/neuralnet-pytorch

cbb0c5a540a0ba91cb4dd20684bb00692305d193

[ "MIT" ]

3

2020-08-07T12:49:05.000Z

2022-03-07T21:32:39.000Z

import neuralnet_pytorch.ext as ext __all__ = ['batch_pairwise_dist'] batch_pairwise_dist = ext.bpd_forward

18.333333

37

0.818182

16

110

5

0.6875

0.325

0.425

0

0.109091

110

5

38

22

0.816327

0

0.172727

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

5

cafbcbcb1b27c0c95b0d75f7c43b3108b68c5153

23

py

Python

Python/test.py

vvpn9/Handy-Tools

5b8e59e80832985c352b7f6e578462e61fcbc300

[ "MIT" ]

null

Python/test.py

vvpn9/Handy-Tools

5b8e59e80832985c352b7f6e578462e61fcbc300

[ "MIT" ]

null

Python/test.py

vvpn9/Handy-Tools

5b8e59e80832985c352b7f6e578462e61fcbc300

[ "MIT" ]

null

v1 = 1 and 3 print(v1)

11.5

13

0.608696

6

23

2.333333

0.833333

0

0.235294

0.26087

23

2

14

11.5

0.588235

0

1

0

false

0

0.5

1

0

null

0

1

0

1

0

null

0

1

0

5

1b08ed9193ffee461d8fdf9e75fca713b1df4e60

79

py

Python

openeo_driver/app.py

vconrado/openeo-python-driver

35dd46ed40b02d147a66fa3199b94f2798e03467

[ "Apache-2.0" ]

null

openeo_driver/app.py

vconrado/openeo-python-driver

35dd46ed40b02d147a66fa3199b94f2798e03467

[ "Apache-2.0" ]

null

openeo_driver/app.py

vconrado/openeo-python-driver

35dd46ed40b02d147a66fa3199b94f2798e03467

[ "Apache-2.0" ]

null

from openeo_driver.views import build_app app = build_app() app.run(port=9007)

19.75

41

0.797468

14

79

4.285714

0.714286

0.266667

0.366667

0

0.056338

0.101266

79

4

42

19.75

0.788732

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

5

1badf4d21d0b627944aec7d94627fe9544f7919c

151

py

Python

database/__init__.py

TioDexty/someone-bot

2598766f61ce81d934793c85158060bd8f3a4143

[ "MIT" ]

2

2020-10-19T11:27:57.000Z

2021-05-29T19:03:49.000Z

database/__init__.py

AVBotz-TG/someone-bot

a6ccfac50455e56cb7f980f2d207f3fde0ed49ad

[ "MIT" ]

null

database/__init__.py

AVBotz-TG/someone-bot

a6ccfac50455e56cb7f980f2d207f3fde0ed49ad

[ "MIT" ]

9

2019-07-05T12:36:27.000Z

2021-08-01T18:44:03.000Z

from .models import db from .models import User, Member def create_tables(): with db: db.create_tables([User, Member]) create_tables()

13.727273

40

0.688742

21

151

4.809524

0.47619

0.356436

0.316832

0

0.211921

151

10

41

15.1

0.84874

0

1

0.166667

true

0

0.333333

0

0.5

0

1

0

null

1

0

null

0

1

0

1

0

5

1bb268ea6110c4abae676565e21b48024b072817

196

py

Python

chatbot/views.py

gcivil-nyu-org/spring2021-cs-gy-9223-class

97121291c2a79dfec87c8b50e5f7e002a6020bfd

[ "MIT" ]

1

2021-02-25T23:17:27.000Z

chatbot/views.py

xiaodan-tang/sprint2021-team-1-repo

cb3595d808e47bb9ff77b432213ffa5d45593dff

[ "MIT" ]

102

2021-03-01T21:57:35.000Z

2021-04-28T21:36:57.000Z

chatbot/views.py

gcivil-nyu-org/spring2021-cs-gy-9223-class

97121291c2a79dfec87c8b50e5f7e002a6020bfd

[ "MIT" ]

5

2021-02-25T22:31:41.000Z

2021-11-21T21:56:30.000Z

from django.shortcuts import render from django.contrib.auth.decorators import login_required @login_required def chatbot(request): return render(request=request, template_name="chat.html")

24.5

61

0.816327

26

196

6.038462

0.692308

0.127389

0

0.102041

196

7

62

28

0.892045

0

0.045918

0

1

0.2

false

0

0.4

0.2

0.8

0

1

0

null

0

1

0

null

0

1

0

5

1bcf7632bf943df480a9e7a759ecf479d324fed0

124

py

Python

simple_machine_learning_models/models/gradient_boost/__init__.py

lnblanke/OCR

b235faa85fedd9f764f71ea592e8693a2a7ac42a

[ "MIT" ]

null

simple_machine_learning_models/models/gradient_boost/__init__.py

lnblanke/OCR

b235faa85fedd9f764f71ea592e8693a2a7ac42a

[ "MIT" ]

null

simple_machine_learning_models/models/gradient_boost/__init__.py

lnblanke/OCR

b235faa85fedd9f764f71ea592e8693a2a7ac42a

[ "MIT" ]

null

# @Time: 10/28/2021 # @Author: lnblanke # @Email: fjh314.84@gmail.com # @File: __init__.py from .GradBoost import GradBoost

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59fb545588e6c7f8d2fb083222ada37424d1c3f0

133

py

Python

flow_storage/flow_io_utils_impl/__init__.py

ekarpovs/flow_storage

8b0e7131eb3244a559a951b77541a0b6dc8908bd

[ "MIT" ]

null

flow_storage/flow_io_utils_impl/__init__.py

ekarpovs/flow_storage

8b0e7131eb3244a559a951b77541a0b6dc8908bd

[ "MIT" ]

null

flow_storage/flow_io_utils_impl/__init__.py

ekarpovs/flow_storage

8b0e7131eb3244a559a951b77541a0b6dc8908bd

[ "MIT" ]

null

from .flowioutilsimpl import FlowIOUtilsImpl from .flowioutils_fs import FlowIOUtilsFs from .flowioutils_h5py import FlowIOUtilsH5Py

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null

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9425b5c796ccb6672fcf37f3ebc17f70a608fb9f

312

py

Python

loca/__init__.py

julievano/LOCA_Downscaling_Analysis

7c18cd7ad4af09161b35c7f5c0c8a1335088c48c

[ "Apache-2.0" ]

5

2018-02-08T02:06:35.000Z

2021-03-19T02:28:20.000Z

loca/__init__.py

julievano/LOCA_Downscaling_Analysis

7c18cd7ad4af09161b35c7f5c0c8a1335088c48c

[ "Apache-2.0" ]

null

loca/__init__.py

julievano/LOCA_Downscaling_Analysis

7c18cd7ad4af09161b35c7f5c0c8a1335088c48c

[ "Apache-2.0" ]

7

2018-07-10T00:38:53.000Z

2022-03-31T03:08:19.000Z

def print_date(): '''Helper function to print current licencse and time''' from datetime import datetime import getpass import socket print('Last executed: %s by %s on %s' % (datetime.now(), getpass.getuser(), socket.gethostname()), flush=True)

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5

942f6abcf113413e01a6d2df7dc48c67135e12e5

47

py

Python

jupyter_remote/version.py

aaronkollasch/jupyter-remote

556328c9b220c5913d031bb0f2752b3672b75da8

[ "MIT" ]

null

jupyter_remote/version.py

aaronkollasch/jupyter-remote

556328c9b220c5913d031bb0f2752b3672b75da8

[ "MIT" ]

null

jupyter_remote/version.py

aaronkollasch/jupyter-remote

556328c9b220c5913d031bb0f2752b3672b75da8

[ "MIT" ]

null

__version__ = "0.9.4" version_info = [0, 9, 4]

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null

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5

945bf3c930d55e887198a935ca0b1f2a2bf6a92b

28,751

py

Python

graph.py

Tony031218/manim-projects

b243dec0f0a007649a92938e90d60eccb4c7dd15

[ "Apache-2.0" ]

45

2019-10-08T23:58:20.000Z

2020-05-20T03:49:15.000Z

graph.py

Tony031218/manim-projects

b243dec0f0a007649a92938e90d60eccb4c7dd15

[ "Apache-2.0" ]

null

graph.py

Tony031218/manim-projects

b243dec0f0a007649a92938e90d60eccb4c7dd15

[ "Apache-2.0" ]

12

2019-08-15T08:07:22.000Z

2020-05-09T12:34:14.000Z

from manimlib.imports import * class Scene_(Scene): CONFIG = { "camera_config": { "background_color": WHITE } } class NF24P3358(Scene_): def construct(self): line = Line(LEFT*3, RIGHT*3, color=BLACK) nodes = VGroup( *[ Circle(radius=0.25, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK) for _ in range(7) ] ).arrange(RIGHT, buff=0.5) names = VGroup( *[ TextMobject(str(i), color=BLACK).scale(0.7) for i in range(1, 8) ] ) edges = VGroup( *[ Arrow(nodes[i].get_center(), nodes[i + 1].get_center(), buff=0.25, color=BLACK) for i in range(6) ] ) infs = VGroup( *[ TextMobject("inf", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).next_to(edges[i], UP, buff=0.1) for i in range(6) ] ) costs = VGroup( *[ TextMobject("0", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.6).next_to(edges[i], DOWN, buff=0.1) for i in range(6) ] ) for i in range(7): names[i].move_to(nodes[i]) s = VGroup( Circle(radius=0.25, fill_color=WHITE, fill_opacity=1, stroke_color=RED), TextMobject("s", color=RED, background_stroke_width=0).scale(0.75) ).move_to(np.array([-4.5, -1.5, 0])) s.add(Arrow(s.get_center(), nodes[0].get_center(), color=RED, buff=0.25)) s.add(TextMobject("k", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).next_to(s[-1], UL, buff=-0.5)) s.add(TextMobject("0", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.6).next_to(s[-2], DR, buff=-0.5)) t = VGroup( Circle(radius=0.25, fill_color=WHITE, fill_opacity=1, stroke_color=RED), TextMobject("t", color=RED, background_stroke_width=0).scale(0.75) ).move_to(np.array([4.5, -1.5, 0])) t.add(Arrow(nodes[-1].get_center(), t.get_center(), color=RED, buff=0.25)) t.add(TextMobject("inf", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).next_to(t[-1], UR, buff=-0.5)) t.add(TextMobject("0", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.6).next_to(t[-2], DL, buff=-0.5)) braces = VGroup( Brace(VGroup(Dot(nodes[0].get_center(), radius=0.01), Dot(nodes[2].get_center(), radius=0.01)), UP, color=GRAY, buff=0.52), Brace(VGroup(Dot(nodes[2].get_center(), radius=0.01), Dot(nodes[5].get_center(), radius=0.01)), UP, color=GRAY, buff=0.52), Brace(VGroup(Dot(nodes[1].get_center(), radius=0.01), Dot(nodes[3].get_center(), radius=0.01)), DOWN, color=GRAY, buff=0.52), Brace(VGroup(Dot(nodes[4].get_center(), radius=0.01), Dot(nodes[6].get_center(), radius=0.01)), DOWN, color=GRAY, buff=0.52), ) edges2 = VGroup( CurvedArrow(nodes[0].get_center(), nodes[2].get_center(), buff=0.25, color=BLACK, angle=-TAU / 4).shift(UP*1), CurvedArrow(nodes[2].get_center(), nodes[5].get_center(), buff=0.25, color=BLACK, angle=-TAU / 4).shift(UP*1), CurvedArrow(nodes[1].get_center(), nodes[3].get_center(), buff=0.25, color=BLACK, angle= TAU / 4).shift(DOWN*1), CurvedArrow(nodes[4].get_center(), nodes[6].get_center(), buff=0.25, color=BLACK, angle= TAU / 4).shift(DOWN*1), ) caps2 = VGroup( TextMobject("1", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).next_to(edges2[0], UP, buff=0.1), TextMobject("1", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).next_to(edges2[1], UP, buff=0.1), TextMobject("1", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).next_to(edges2[2], UP, buff=-0.4), TextMobject("1", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).next_to(edges2[3], UP, buff=-0.4) ) costs2 = VGroup( TextMobject("6", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.6).next_to(edges2[0], DOWN, buff=-0.4), TextMobject("3", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.6).next_to(edges2[1], DOWN, buff=-0.6), TextMobject("2", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.6).next_to(edges2[2], DOWN, buff=0.1), TextMobject("4", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.6).next_to(edges2[3], DOWN, buff=0.1), ) old_num = VGroup( TextMobject("1", color=GRAY, background_stroke_color=GRAY).scale(0.45), TextMobject("6", color=GRAY, background_stroke_color=GRAY).scale(0.45), TextMobject("7", color=GRAY, background_stroke_color=GRAY).scale(0.45), TextMobject("8", color=GRAY, background_stroke_color=GRAY).scale(0.45), TextMobject("9", color=GRAY, background_stroke_color=GRAY).scale(0.45), TextMobject("10", color=GRAY, background_stroke_color=GRAY).scale(0.45), TextMobject("13", color=GRAY, background_stroke_color=GRAY).scale(0.45), ) for i in range(7): old_num[i].next_to(nodes[i], DOWN, buff=0.08) comments = VGroup( TextMobject("蓝-容量", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.7), TextMobject("橙-费用", color=GOLD_D, background_stroke_color=GOLD_D).scale(0.7), ).arrange(DOWN, aligned_edge=LEFT, buff=0.2).next_to(nodes[0], DOWN, buff=1.3) rec = SurroundingRectangle(comments, color=GRAY, buff=0.2) problem = TextMobject("最长$k$可重区间集问题", color=WHITE, background_stroke_color=WHITE) problem.add_background_rectangle(color=GOLD_D, opacity=1, buff=0.15).next_to(nodes[0], UP, buff=1.8).shift(RIGHT*0.2) author = TextMobject("by @鹤翔万里", background_stroke_color=ORANGE, opacity=0.8).scale(0.7).set_color(ORANGE).next_to(t[0], DOWN, buff=0.4).shift(LEFT*0.8) self.add(line, nodes, names, s, edges, infs, costs, t, braces, edges2, caps2, costs2, old_num, comments, rec, problem, author) class NF24P2762(Scene_): def construct(self): rad = 0.3 s = VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=RED), TextMobject("s", color=RED, background_stroke_width=0).scale(0.75) ).move_to(np.array([-4.5, 0, 0])) t = VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=RED), TextMobject("t", color=RED, background_stroke_width=0).scale(0.75) ).move_to(np.array([4.5, 0, 0])) nodes = VGroup( VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=BLACK), TextMobject("1\ 实验", color=BLACK, background_stroke_color=BLACK).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([-1.6, 1, 0])), VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=BLACK), TextMobject("2\ 实验", color=BLACK, background_stroke_color=BLACK).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([-1.6, -1, 0])), VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=BLACK, fill_opacity=1), TextMobject("1\ 仪器", color=WHITE, background_stroke_color=WHITE).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([1.5, 2, 0])), VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=BLACK, fill_opacity=1), TextMobject("2\ 仪器", color=WHITE, background_stroke_color=WHITE).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([1.5, 0, 0])), VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=BLACK, fill_opacity=1), TextMobject("3\ 仪器", color=WHITE, background_stroke_color=WHITE).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([1.5, -2, 0])), ) edges_s = VGroup( Arrow(s[0].get_center(), nodes[0][0].get_center(), color=RED, buff=rad), Arrow(s[0].get_center(), nodes[1][0].get_center(), color=RED, buff=rad), ) edges_s.add(TextMobject("10", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_s[0], UP, buff=-0.3).shift(LEFT*0.3)) edges_s.add(TextMobject("25", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_s[1], DOWN, buff=-0.3).shift(LEFT*0.3)) edges_n = VGroup( Arrow(nodes[0][-1].get_center(), nodes[2][0].get_center(), color=BLACK, buff=rad), Arrow(nodes[0][-1].get_center(), nodes[3][0].get_center(), color=BLACK, buff=rad), Arrow(nodes[1][-1].get_center(), nodes[3][0].get_center(), color=BLACK, buff=rad), Arrow(nodes[1][-1].get_center(), nodes[4][0].get_center(), color=BLACK, buff=rad), ) edges_n.add(TextMobject("inf", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_n[0], UP, buff=-0.35).shift(LEFT*0.3)) edges_n.add(TextMobject("inf", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_n[1], UP, buff=-0.25).shift(LEFT*-0.1)) edges_n.add(TextMobject("inf", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_n[2], UP, buff=-0.35).shift(LEFT*0.3)) edges_n.add(TextMobject("inf", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_n[3], UP, buff=-0.25).shift(LEFT*-0.1)) edges_t = VGroup( Arrow(nodes[2][-1].get_center(), t[0].get_center(), color=RED, buff=rad), Arrow(nodes[3][-1].get_center(), t[0].get_center(), color=RED, buff=rad), Arrow(nodes[4][-1].get_center(), t[0].get_center(), color=RED, buff=rad), ) edges_t.add(TextMobject("5", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_t[0], UP, buff=-0.5).shift(LEFT*0.15)) edges_t.add(TextMobject("6", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_t[1], UP, buff=-0.1).shift(LEFT*0.2)) edges_t.add(TextMobject("7", color=BLUE_D, background_stroke_color=BLUE_D).next_to(edges_t[2], DOWN, buff=-0.5).shift(LEFT*0.15)) min_cut = DashedLine(np.array([2.5, 3, 0]), np.array([2.5, -3, 0]), color=DARK_GRAY) comment = VGroup( TextMobject("蓝-容量", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.7), TextMobject("灰-最小割(最大流)", color=DARK_GRAY, background_stroke_color=DARK_GRAY).scale(0.7) ).arrange(DOWN, aligned_edge=LEFT).next_to(edges_s[3], DOWN, buff=0.8) rec = SurroundingRectangle(comment, color=GRAY, buff=0.2) problem = TextMobject("太空飞行计划问题", color=WHITE, background_stroke_color=WHITE) problem.add_background_rectangle(color=GOLD_D, opacity=1, buff=0.15).next_to(edges_s[2], UP, buff=1) author = TextMobject("by @鹤翔万里", background_stroke_color=ORANGE, opacity=0.8).scale(0.7).set_color(ORANGE).next_to(t[0], DOWN, buff=2) label = VGroup( TextMobject("报酬", color=GREEN, background_stroke_color=GREEN).scale(0.6).next_to(edges_s[2], UL, buff=0.1), TextMobject("费用", color=GREEN, background_stroke_color=GREEN).scale(0.6).next_to(edges_t[3], UR, buff=0.1), ) self.add(s, t, edges_s, edges_n, edges_t, nodes, min_cut, comment, rec, problem, author, label) class NF24P3357(Scene_): def construct(self): axes = Axes(x_min=-0.5, x_max=8, y_min=-0.5, y_max=4, number_line_config={"color": BLACK}).center().shift(DOWN*0.5) axes.add_coordinates(number_config={"color": BLACK}) line1 = Line(axes.c2p(1, 1), axes.c2p(1, 3), color=BLUE_D) line1_ = Line(axes.c2p(2, 1), axes.c2p(3, 3), color=BLUE_D) line2 = Line(axes.c2p(1, 1), axes.c2p(3, 3), color=GREEN_D) line2_ = Line(axes.c2p(3, 1), axes.c2p(6, 3), color=GREEN_D) dots = VGroup( SmallDot(axes.c2p(1, 1), color=GRAY), SmallDot(axes.c2p(1, 3), color=GRAY), SmallDot(axes.c2p(2, 1), color=GRAY), SmallDot(axes.c2p(3, 3), color=GRAY), SmallDot(axes.c2p(3, 1), color=GRAY), SmallDot(axes.c2p(6, 3), color=GRAY), ) arrows = VGroup( CurvedArrow(line1.get_center(), line1_.get_center(), color=RED, angle=-TAU/4).scale(0.9), CurvedArrow(line2.get_center(), line2_.get_center(), color=RED).scale(0.9).shift(DL*0.2+LEFT*0.1), ) changes = VGroup( TexMobject("(x_1,x_1)\\rightarrow(2x_1, 2x_1+1)", color=MAROON, background_stroke_color=MAROON).scale(0.85), TexMobject("(x_1,x_2)\\rightarrow(2x_1+1, 2x_2)", color=MAROON, background_stroke_color=MAROON).scale(0.85) ).arrange(DOWN, aligned_edge=LEFT).next_to(axes, UP, buff=-0.5) dls = VGroup( DashedLine(axes.c2p(2, 0), axes.c2p(2, 1), color=PURPLE), DashedLine(axes.c2p(3, 0), axes.c2p(3, 3), color=PURPLE), DashedLine(axes.c2p(6, 0), axes.c2p(6, 3), color=PURPLE), ) braces = VGroup( Brace(VGroup(Dot(axes.c2p(2, 0), radius=0.01), Dot(axes.c2p(3, 0), radius=0.01)), UP, color=DARK_GRAY), Brace(VGroup(Dot(axes.c2p(3, 0), radius=0.01), Dot(axes.c2p(6, 0), radius=0.01)), UP, color=DARK_GRAY), ) problem = TextMobject("最长$k$可重线段集问题", color=WHITE, background_stroke_color=WHITE) problem.add_background_rectangle(color=GOLD_D, opacity=1, buff=0.15).move_to(np.array([-3, 3, 0])) author = TextMobject("by @鹤翔万里", background_stroke_color=ORANGE, opacity=0.8).scale(0.7).set_color(ORANGE) author.move_to(np.array([4, -1.5, 0])) comment = TextMobject("化为开区间", color=DARK_GRAY, background_stroke_color=DARK_GRAY).scale(0.6).next_to(braces[-1], UP, buff=0.2) dots2 = VGroup( Dot(axes.c2p(2, 0), color=BLACK, radius=0.1), Dot(axes.c2p(3, 0), color=BLACK, radius=0.1), Dot(axes.c2p(6, 0), color=BLACK, radius=0.1), ) self.add(axes, line1, line1_, line2, line2_, dls, dots, arrows, changes, braces, problem, author, comment, dots2) class NF24P2754(Scene_): def construct(self): self.camera.set_frame_height(9) self.camera.resize_frame_shape(1) rad = 0.3 lis = [3, 1.8, 0.6, -0.6, -1.8, -3] times = VGroup( *[ VGroup( TextMobject("time={}".format(i), color=GRAY, background_stroke_color=GRAY).scale(0.6), DashedLine(np.array([-5, lis[i], 0]), np.array([5, lis[i], 0]), color=GRAY) ) for i in range(6) ] ).shift(DL+UP*0.5) for i in range(6): times[i][0].next_to(times[i][1], LEFT) nodes_0 = VGroup( *[ VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=BLACK, fill_color=WHITE, fill_opacity=1), TextMobject("0\ 地", color=BLACK, background_stroke_color=BLACK).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([-3.6, i, 0])) for i in lis ] ) nodes_1 = VGroup( *[ VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=ORANGE, fill_color=WHITE, fill_opacity=1), TextMobject("1\ 站", color=ORANGE, background_stroke_color=ORANGE).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([-1.2, i, 0])) for i in lis ] ) nodes_2 = VGroup( *[ VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=ORANGE, fill_color=WHITE, fill_opacity=1), TextMobject("2\ 站", color=ORANGE, background_stroke_color=ORANGE).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([1.2, i, 0])) for i in lis ] ) nodes_3 = VGroup( *[ VGroup( Circle(radius=rad, fill_color=BLACK, fill_opacity=1, stroke_color=BLACK).shift(LEFT*0.4).set_opacity(0), RoundedRectangle(height=rad*2, width=1.4, corner_radius=rad, color=BLACK, fill_opacity=1), TextMobject("-1\ 月", color=WHITE, background_stroke_color=WHITE).scale(0.75), Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=BLACK).shift(RIGHT*0.4).set_opacity(0) ).move_to(np.array([3.6, i, 0])) for i in lis ] ) nodes = VGroup(nodes_0, nodes_1, nodes_2, nodes_3).shift(DL+UP*0.5) sw = 6 edges_0 = VGroup( *[ Arrow(nodes_0[i][1].get_center(), nodes_0[i + 1][1].get_center(), color=BLACK, buff=rad, stroke_width=sw) for i in range(5) ] ) edges_1 = VGroup( *[ Arrow(nodes_1[i][1].get_center(), nodes_1[i + 1][1].get_center(), color=ORANGE, buff=rad, stroke_width=sw) for i in range(5) ] ) edges_2 = VGroup( *[ Arrow(nodes_2[i][1].get_center(), nodes_2[i + 1][1].get_center(), color=ORANGE, buff=rad, stroke_width=sw) for i in range(5) ] ) edges_3 = VGroup( *[ Arrow(nodes_3[i + 1][1].get_center(), nodes_3[i][1].get_center(), color=BLACK, buff=rad, stroke_width=sw) for i in range(5) ] ) car_1 = VGroup( Arrow(nodes[0][0][-1].get_center(), nodes[1][1][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), Arrow(nodes[1][1][-1].get_center(), nodes[2][2][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), Arrow(nodes[2][2][0].get_center(), nodes[0][3][-1].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.05).set_stroke(width=4), Arrow(nodes[0][3][-1].get_center(), nodes[1][4][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), Arrow(nodes[1][4][-1].get_center(), nodes[2][5][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), ) car_2 = VGroup( Arrow(nodes[1][0][-1].get_center(), nodes[2][1][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), Arrow(nodes[2][1][-1].get_center(), nodes[3][2][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), Arrow(nodes[3][2][0].get_center(), nodes[1][3][-1].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.05).set_stroke(width=4), Arrow(nodes[1][3][-1].get_center(), nodes[2][4][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), Arrow(nodes[2][4][-1].get_center(), nodes[3][5][0].get_center(), buff=rad+0.03, color=BLUE_D, max_tip_length_to_length_ratio=0.1).set_stroke(width=4), ) cars = VGroup(car_1, car_2) labels = VGroup( *[ TextMobject("1", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).add_background_rectangle(color=WHITE, opacity=0.8, buff=0.1)\ .move_to(car_1[i]) for i in range(5) ], *[ TextMobject("1", color=BLUE_D, background_stroke_color=BLUE_D).scale(0.6).add_background_rectangle(color=WHITE, opacity=0.8, buff=0.1)\ .move_to(car_2[i]) for i in range(5) ], ) s = VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=RED), TextMobject("s", color=RED, background_stroke_width=0).scale(0.75) ).move_to(np.array([-6, 3.5, 0])) t = VGroup( Circle(radius=rad, fill_color=WHITE, fill_opacity=1, stroke_color=RED), TextMobject("t", color=RED, background_stroke_width=0).scale(0.75) ).move_to(np.array([4, 3.5, 0])) edge_s = Arrow(s[0].get_center() , nodes[0][0][0].get_center(), color=RED, buff=rad) edge_t = Arrow(nodes[3][0][-1].get_center(), t[0].get_center(), color=RED, buff=rad) problem = TextMobject("星际转移问题", color=WHITE, background_stroke_color=WHITE).scale(1.3) problem.add_background_rectangle(color=GOLD_D, opacity=1, buff=0.15).next_to(nodes[1][0], UP, buff=0.5) comment = VGroup( TextMobject("未标记的边", color=GRAY, background_stroke_color=GRAY).scale(0.75), TextMobject("容量为inf", color=BLUE, background_stroke_color=BLUE).scale(0.75) ).arrange(DOWN, aligned_edge=LEFT).move_to(np.array([5.5, -0.5, 0])) rec = SurroundingRectangle(comment, color=GRAY, buff=0.2) author = TextMobject("by @鹤翔万里", background_stroke_color=ORANGE, opacity=0.8).scale(0.7).set_color(ORANGE) author.move_to(np.array([5.5, -2.5, 0])) vdots = VGroup( *[TexMobject("\\vdots", color=BLACK).scale(0.8) for i in range(4)] ) for i in range(4): vdots[i].next_to(nodes[i][-1], DOWN, buff=0.2) edges = VGroup(edges_0, edges_1, edges_2, edges_3) self.add(times, edges, cars, labels, edge_s, edge_t, nodes, s, t, problem, comment, rec, vdots, author) class MosAlgoCompare1(Scene_): def construct(self): line = [ [-3.8, [-3, -1.8, -0.2, 0.2, 1.8, 2.2, 3.8]], [-1.8, [-1, 0.2, 1.8, 2.2, 3.8]], [0.2, [1.8, 2.2, 3.8]], [2.2, [3, 3.8]] ] lines = VGroup( *[ VGroup( *[ VGroup( Line(i * RIGHT, j * RIGHT, color=BLACK), Dot(i * RIGHT, color=DARK_GRAY, radius=0.05), Dot(j * RIGHT, color=DARK_GRAY, radius=0.05), ) for j in k ] ).arrange(DOWN, False, buff=0.3, coor_mask=np.array([0, 1, 0])) for i, k in line ] ).arrange(DOWN, buff=0.45, coor_mask=np.array([0, 1, 0])) back = VGroup( *[ DashedLine(np.array([i, 3.8, 0]), np.array([i, -3.8, 0]), color=GRAY) for i in [-4, -2, 0, 2, 4] ] ) lines1 = VGroup() for group in lines: for i, j in enumerate(group): if j != group[-1]: lines1.add(Line(j[-1].get_center(), group[i+1][-1].get_center(), color=RED).add_tip(0.15)) lines2 = VGroup() for i, j in enumerate(lines): if j != lines[-1]: lines2.add(Line(j[-1][-1].get_center(), lines[i+1][0][-1].get_center(), color=BLUE_D).add_tip(0.15)) self.add(back, lines, lines1, lines2) class MosAlgoCompare2(Scene_): def construct(self): line = [ [-3.8, [-3, -1.8, -0.2, 0.2, 1.8, 2.2, 3.8]], [-1.8, [3.8, 2.2, 1.8, 0.2, -1]], [0.2, [1.8, 2.2, 3.8]], [2.2, [3.8, 3]] ] lines = VGroup( *[ VGroup( *[ VGroup( Line(i * RIGHT, j * RIGHT, color=BLACK), Dot(i * RIGHT, color=DARK_GRAY, radius=0.05), Dot(j * RIGHT, color=DARK_GRAY, radius=0.05), ) for j in k ] ).arrange(DOWN, False, buff=0.3, coor_mask=np.array([0, 1, 0])) for i, k in line ] ).arrange(DOWN, buff=0.45, coor_mask=np.array([0, 1, 0])) back = VGroup( *[ DashedLine(np.array([i, 3.8, 0]), np.array([i, -3.8, 0]), color=GRAY) for i in [-4, -2, 0, 2, 4] ] ) lines1 = VGroup() for group in lines: for i, j in enumerate(group): if j != group[-1]: lines1.add(Line(j[-1].get_center(), group[i+1][-1].get_center(), color=RED).add_tip(0.15)) lines2 = VGroup() for i, j in enumerate(lines): if j != lines[-1]: lines2.add(Line(j[-1][-1].get_center(), lines[i+1][0][-1].get_center(), color=BLUE_D).add_tip(0.15)) self.add(back, lines, lines1, lines2) class RollBackMosAlgo(Scene_): def construct(self): line = [ [-3.6, -0.4], [-2.4, 0.4], [-3.6, 2.4], [-2.4, 3.6] ] lines = VGroup( *[ VGroup( Line(i * RIGHT, j * RIGHT, color=BLACK), Dot(i * RIGHT, color=DARK_GRAY, radius=0.05), Dot(j * RIGHT, color=DARK_GRAY, radius=0.05), ) for i, j in line ] ).arrange(DOWN, buff=0.5, coor_mask=np.array([0, 1, 0])) back = VGroup( *[ DashedLine(np.array([i, 3.8, 0]), np.array([i, -3.8, 0]), color=GRAY) for i in [-4, -2, 0, 2, 4] ] ) s = np.array([-2, 1.5, 0]) # self.add(Dot(s, color=BLACK)) l = VGroup( Line(s, lines[0][1].get_center(), color=ORANGE), Line(lines[0][1].get_center(), np.array([-2, lines[0][1].get_center()[1], 0]), color=ORANGE), Line(np.array([-2, lines[0][1].get_center()[1], 0]), lines[1][1].get_center(), color=ORANGE), Line(lines[1][1].get_center(), np.array([-2, lines[1][1].get_center()[1], 0]), color=ORANGE), Line(np.array([-2, lines[1][1].get_center()[1], 0]), lines[2][1].get_center(), color=ORANGE), Line(lines[2][1].get_center(), np.array([-2, lines[2][1].get_center()[1], 0]), color=ORANGE), Line(np.array([-2, lines[2][1].get_center()[1], 0]), lines[3][1].get_center(), color=ORANGE), Line(lines[3][1].get_center(), np.array([-2, lines[3][1].get_center()[1], 0]), color=ORANGE), ) for each in l: each.add_tip(0.2) r = VGroup( Line(s, lines[0][2].get_center(), color=BLUE_D), Line(lines[0][2].get_center(), lines[1][2].get_center(), color=BLUE_D), Line(lines[1][2].get_center(), lines[2][2].get_center(), color=BLUE_D), Line(lines[2][2].get_center(), lines[3][2].get_center(), color=BLUE_D), ) for each in r: each.add_tip(0.2) self.add(lines, back, l, r)

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Python

Coursera/Google_IT_Automation_with_Python/01_Crash_Course_on_Python/Week_3/wk3_mod1_pquiz.py

ssolomon2020/Self_Study_Python_Training

b253093b185f4a0d98cb8565f5fcf2b0e4a99556

[ "MIT" ]

null

Coursera/Google_IT_Automation_with_Python/01_Crash_Course_on_Python/Week_3/wk3_mod1_pquiz.py

ssolomon2020/Self_Study_Python_Training

b253093b185f4a0d98cb8565f5fcf2b0e4a99556

[ "MIT" ]

null

Coursera/Google_IT_Automation_with_Python/01_Crash_Course_on_Python/Week_3/wk3_mod1_pquiz.py

ssolomon2020/Self_Study_Python_Training

b253093b185f4a0d98cb8565f5fcf2b0e4a99556

[ "MIT" ]

null

# Specialization: Google IT Automation with Python # Course 01: Crash Course with Python # Week 3 Module Part 1 - Practice Quiz # Student: Shawn Solomon # Learning Platform: Coursera.org # Scripting examples encountered during the Module Part 1 Practice Quiz: # 02. Fill in the blanks to make the print_prime_factors function print all the prime factors of a number. # A prime factor is a number that is prime and divides another without a remainder. # def print_prime_factors(number): # # Start with two, which is the first prime # factor = ___ # # Keep going until the factor is larger than the number # while factor <= number: # # Check if factor is a divisor of number # if number % factor == ___: # # If it is, print it and divide the original number # print(factor) # number = number / factor # else: # # If it's not, increment the factor by one # ___ # return "Done" # # print_prime_factors(100) # # Should print 2,2,5,5 # # DO NOT DELETE THIS COMMENT def print_prime_factors(number): # Start with two, which is the first prime factor = 2 # Keep going until the factor is larger than the number while factor <= number: # Check if factor is a divisor of number if number % factor == 0: # If it is, print it and divide the original number print(factor) number = number / factor else: # If it's not, increment the factor by one factor += 1 return "Done" print_prime_factors(100) # Should print 2,2,5,5 # DO NOT DELETE THIS COMMENT # 03. The following code can lead to an infinite loop. Fix the code so that it can finish successfully for all numbers. # Note: Try running your function with the number 0 as the input, and see what you get! # def is_power_of_two(n): # # Check if the number can be divided by two without a remainder # while n % 2 == 0: # n = n / 2 # # If after dividing by two the number is 1, it's a power of two # if n == 1: # return True # return False # # # print(is_power_of_two(0)) # Should be False # print(is_power_of_two(1)) # Should be True # print(is_power_of_two(8)) # Should be True # print(is_power_of_two(9)) # Should be False def is_power_of_two(n): # Check if the number can be divided by two without a remainder while n % 2 == 0: if n == 0: return False n = n / 2 # If after dividing by two the number is 1, it's a power of two if n == 1: return True return False print(is_power_of_two(0)) # Should be False print(is_power_of_two(1)) # Should be True print(is_power_of_two(8)) # Should be True print(is_power_of_two(9)) # Should be False # 04. Fill in the empty function so that it returns the sum of all the divisors of a number, without including it. # A divisor is a number that divides into another without a remainder. # def sum_divisors(n): # sum = 0 # # Return the sum of all divisors of n, not including n # return sum # # print(sum_divisors(0)) # # 0 # print(sum_divisors(3)) # Should sum of 1 # # 1 # print(sum_divisors(36)) # Should sum of 1+2+3+4+6+9+12+18 # # 55 # print(sum_divisors(102)) # Should be sum of 2+3+6+17+34+51 # # 114 def sum_divisors(number): sum = 0 divs = 1 while divs < number: # Check if factor is a divisor of number if number == 0: return 0 if number % divs == 0: # If it is, print it and divide the original number sum = sum + divs divs = divs + 1 else: divs += 1 # Return the sum of all divisors of n, not including n return sum print(sum_divisors(0)) # 0 print(sum_divisors(3)) # Should sum of 1 # 1 print(sum_divisors(36)) # Should sum of 1+2+3+4+6+9+12+18 # 55 print(sum_divisors(102)) # Should be sum of 2+3+6+17+34+51 # 114 # 05. The multiplication_table function prints the results of a number passed to it multiplied by 1 through 5. # An additional requirement is that the result is not to exceed 25, which is done with the break statement. # Fill in the blanks to complete the function to satisfy these conditions. # def multiplication_table(number): # # Initialize the starting point of the multiplication table # multiplier = 1 # # Only want to loop through 5 # while multiplier <= 5: # result = ___ # # What is the additional condition to exit out of the loop? # if ___ : # break # print(str(number) + "x" + str(multiplier) + "=" + str(result)) # # Increment the variable for the loop # ___ += 1 # # multiplication_table(3) # # Should print: 3x1=3 3x2=6 3x3=9 3x4=12 3x5=15 # # multiplication_table(5) # # Should print: 5x1=5 5x2=10 5x3=15 5x4=20 5x5=25 # # multiplication_table(8) # # Should print: 8x1=8 8x2=16 8x3=24 def multiplication_table(number): # Initialize the starting point of the multiplication table multiplier = 1 # Only want to loop through 5 while multiplier <= 5: result = number * multiplier # What is the additional condition to exit out of the loop? if result > 25 : break print(str(number) + "x" + str(multiplier) + "=" + str(result)) # Increment the variable for the loop multiplier += 1 multiplication_table(3) # Should print: 3x1=3 3x2=6 3x3=9 3x4=12 3x5=15 multiplication_table(5) # Should print: 5x1=5 5x2=10 5x3=15 5x4=20 5x5=25 multiplication_table(8) # Should print: 8x1=8 8x2=16 8x3=24

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