ytzi/the-stack-dedup-python-scored · Datasets at Hugging Face

dd1aa8274a7a29ed0c0e03c51dfff1daaec8435e

26

py

Python

data/studio21_generated/introductory/4783/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/introductory/4783/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/introductory/4783/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

def weather_info (temp):

13

24

0.730769

0

dd1d14cad8d7b51f2d3997d8681795f2ed9d4e1a

2,863

py

Python

server/blog/models.py

rafay826/django-react

60bd7dcea8bb5c921f80d064e4d16fa34381ae09

[ "MIT" ]

null

server/blog/models.py

rafay826/django-react

60bd7dcea8bb5c921f80d064e4d16fa34381ae09

[ "MIT" ]

12

2020-06-05T21:17:35.000Z

2022-03-11T23:49:11.000Z

server/blog/models.py

midasdev711/djudo

5717ad63b0ef5dddddfd1d3839fa5231ac21972f

[ "MIT" ]

null

from django.db import models from django.db.models import permalink from django.core.urlresolvers import reverse from comments.models import Comment # Create your models here. class PostManager(models.Manager): def active(self, *args, **kwargs): return super(PostManager, self) def upload_location(instance, filename): #filebase, extension = filename.split(".") #return "%s/%s.%s" %(instance.id, instance.id, extension) PostModel = instance.__class__ """ instance.__class__ gets the model Post. We must use this method because the model is defined below. Then create a queryset ordered by the "id"s of each object, Then we get the last object in the queryset with `.last()` Which will give us the most recently created Model instance We add 1 to it, so we get what should be the same id as the the post we are creating. """ return "static/images/posts/%s" % filename class Post(models.Model): id = models.AutoField(primary_key=True) title = models.CharField(max_length=100, unique=True) slug = models.SlugField(max_length=100, unique=True) image = models.ImageField(upload_to=upload_location, null=True, blank=True, width_field="width_field", height_field="height_field") image_url = models.CharField(max_length=1000, null=True, blank=True) height_field = models.IntegerField(default=0) width_field = models.IntegerField(default=0) description = models.CharField(max_length=255, blank=True) body = models.TextField() published = models.BooleanField(default=True) created = models.DateTimeField(db_index=True, auto_now_add=True) category = models.ForeignKey('blog.Category', related_name='posts', on_delete=models.CASCADE) objects = PostManager() def __unicode__(self): return '%s' % self.title def __str__(self): return self.title def get_absolute_url(self): return reverse("blog.views.post", kwargs={"slug": self.slug}) def get_api_url(self): return reverse("posts-api:detail", kwargs={"slug": self.slug}) @property def comments(self): instance = self qs = Comment.objects.filter_by_instance(instance) return qs class CategoryManager(models.Manager): def active(self, *args, **kwargs): return super(CategoryManager, self) class Category(models.Model): id = models.AutoField(primary_key=True) title = models.CharField(max_length=100, db_index=True) slug = models.SlugField(max_length=100, db_index=True) class Meta: verbose_name = ("Category") verbose_name_plural = ("Categories") objects = CategoryManager() def __unicode__(self): return '%s' % self.title def get_absolute_url(self): return reverse('blog.views.post', args=[self.slug])

35.7875

103

0.691233

2,044

0.713936

0

133

0.046455

0

689

0.240657

dd1d3ef072d0bbe5516060cc303f3f2982632867

305

py

Python

django_obfuscator/testobfuscator/models.py

vishnuc91/obfuscator-date

d4424cb7823dbf20543c5cc2bc0ce48d8d62a69a

[ "Apache-2.0" ]

null

django_obfuscator/testobfuscator/models.py

vishnuc91/obfuscator-date

d4424cb7823dbf20543c5cc2bc0ce48d8d62a69a

[ "Apache-2.0" ]

null

django_obfuscator/testobfuscator/models.py

vishnuc91/obfuscator-date

d4424cb7823dbf20543c5cc2bc0ce48d8d62a69a

[ "Apache-2.0" ]

null

from django.db import models # Create your models here. class MyModel(models.Model): aname = models.CharField(max_length=100, null=True, blank=True) anint = models.IntegerField(default=999) astring = models.CharField(max_length=50) date = models.DateField('Date', null=True, blank=True)

30.5

67

0.734426

246

0.806557

0

32

0.104918

dd1d5f6520079cb76d00ac62e5817128a147acb0

69

py

Python

pyintercept/handlers/print_handler.py

caioariede/pyintercept

19039ce3038521bf32aaafe207024adeb0096749

[ "MIT" ]

32

2015-07-20T21:13:26.000Z

2018-04-05T13:53:28.000Z

pyintercept/handlers/print_handler.py

caioariede/pyintercept

19039ce3038521bf32aaafe207024adeb0096749

[ "MIT" ]

2

2019-07-23T17:38:06.000Z

2020-02-27T13:38:02.000Z

pyintercept/handlers/print_handler.py

caioariede/pyintercept

19039ce3038521bf32aaafe207024adeb0096749

[ "MIT" ]

3

2015-08-09T14:48:38.000Z

2020-02-27T12:58:46.000Z

def print_(origfn, *args, **kwargs): print args print kwargs

17.25

36

0.652174

0

dd1ed841552b8b3a90cb7777b80332b35c886661

7,621

py

Python

PySyft_dev/FL_BC/cryptolib/wrapper_pyca.py

samuelxu999/FederatedLearning_dev

354d951c53ee20eb41bf7980210d61b7a358d341

[ "MIT" ]

null

PySyft_dev/FL_BC/cryptolib/wrapper_pyca.py

samuelxu999/FederatedLearning_dev

354d951c53ee20eb41bf7980210d61b7a358d341

[ "MIT" ]

2

2021-03-17T23:27:00.000Z

2021-03-17T23:27:01.000Z

PySyft_dev/FL_BC/cryptolib/wrapper_pyca.py

samuelxu999/FederatedLearning_dev

354d951c53ee20eb41bf7980210d61b7a358d341

[ "MIT" ]

2

2019-04-23T22:13:18.000Z

2019-08-19T01:39:51.000Z

''' ======================== Wrapper_pyca module ======================== Created on Nov.7, 2017 @author: Xu Ronghua @Email: rxu22@binghamton.edu @TaskDescription: This module provide cryptography function based on pyca API. @Reference:https://cryptography.io/en/latest/ ''' from cryptography.fernet import Fernet from cryptography.hazmat.backends import default_backend from cryptography.hazmat.primitives import hashes from cryptography.hazmat.primitives.asymmetric import ec, dsa from cryptography.hazmat.primitives.serialization import Encoding, PublicFormat, PrivateFormat, BestAvailableEncryption from cryptography.hazmat.primitives import serialization from cryptography.exceptions import InvalidSignature class Crypto_DSA(object): ''' Generate key pairs as json fromat @in: key_size @out: key_pairs={'private_key':x,'public_key':{'y':y,'p':p,'q':q,'g':g}} ''' @staticmethod def generate_key_pairs(key_size=1024): #define key_pairs dictionary key_pairs={} #generate private key private_key = dsa.generate_private_key(key_size=key_size, backend=default_backend()) private_number=private_key.private_numbers() #add private key value - x key_pairs['private_key']=private_number.x #get private key from private_key public_key = private_key.public_key() #get public number public_numbers=public_key.public_numbers() y=public_numbers.y p=public_numbers.parameter_numbers.p q=public_numbers.parameter_numbers.q g=public_numbers.parameter_numbers.g #add public_key_numbers value - y, p, q, g public_keys_numbers={'y':y, 'p':p, 'q':q, 'g':g} key_pairs['public_key']=public_keys_numbers return key_pairs ''' Display out key pairs data on screen @in: key_pairs={'private_key':x,'public_key':{'y':y,'p':p,'q':q,'g':g}} @out: print out key pairs data on screen ''' @staticmethod def display_key_pairs(key_pairs): print("private key value x:%d" %(key_pairs['private_key'])) public_keys_numbers=key_pairs['public_key'] print("public key value y:%d" %(public_keys_numbers['y'])) print("public key value p:%d" %(public_keys_numbers['p'])) print("public key value q:%d" %(public_keys_numbers['q'])) print("public key value g:%d" %(public_keys_numbers['g'])) ''' Get public key object given public key numbers @in: public_key_numbers={'public_key':{'y':y,'p':p,'q':q,'g':g}} @out: public_key object ''' @staticmethod def get_public_key(public_key_numbers): y=public_key_numbers['y'] p=public_key_numbers['p'] q=public_key_numbers['q'] g=public_key_numbers['g'] #construct public key based on public_key_numbers parameter_numbers=dsa.DSAParameterNumbers(p,q,g) publick_number=dsa.DSAPublicNumbers(y,parameter_numbers) public_key=publick_number.public_key(default_backend()) #print(publick_number) return public_key ''' Get private key object given private key numbers @in: private_key_numbers={'publicprivate_key':x} @in: public_key_numbers={'public_key':{'y':y,'p':p,'q':q,'g':g}} @out: private_key object ''' @staticmethod def get_private_key(x, public_key_numbers): #reconstruct private key private_numbers=dsa.DSAPrivateNumbers(x, public_key_numbers) #construct private_key based on private_numbers private_key=private_numbers.private_key(default_backend()) return private_key ''' Generate signature by signing data @in: private_key object @in: sign_data @out: signature ''' @staticmethod def sign(private_key, sign_data): signature=private_key.sign(sign_data,hashes.SHA256()) return signature ''' Verify signature by using public_key @in: public_key object @in: signature @in: sign_data @out: True or False ''' @staticmethod def verify(public_key, signature, sign_data): try: public_key.verify(signature, sign_data, hashes.SHA256()) except InvalidSignature: return False except: return False return True ''' Generate public key bytes @in: public_key object @in: encoding- Encoding.PEM or Encoding.DER @out: public_key_bytes ''' @staticmethod def get_public_key_bytes(public_key, encoding=Encoding.PEM): public_key_bytes=public_key.public_bytes(encoding, PublicFormat.SubjectPublicKeyInfo) return public_key_bytes ''' Generate public_key object by loading public key bytes @in: public_key_bytes @in: encoding- Encoding.PEM or Encoding.DER @out: public_key object ''' @staticmethod def load_public_key_bytes(public_key_bytes,encoding=Encoding.PEM): if(encoding==Encoding.PEM): public_key=serialization.load_pem_public_key(public_key_bytes, default_backend()) elif(encoding==Encoding.DER): public_key=serialization.load_der_public_key(public_key_bytes, default_backend()) else: public_key='' return public_key ''' Generate private key bytes @in: private_key object @in: encryp_pw- password for encryption private_key_bytes @in: encoding- Encoding.PEM or Encoding.DER @in: private_format- PrivateFormat.PKCS8 or PrivateFormat.TraditionalOpenSSL @out: private_key_bytes ''' @staticmethod def get_private_key_bytes(private_key, encryp_pw=b'rootpasswd', encoding=Encoding.PEM, private_format=PrivateFormat.PKCS8): private_key_bytes=private_key.private_bytes(encoding, private_format, BestAvailableEncryption(bytes(encryp_pw))) return private_key_bytes ''' Generate private_key object by loading public key bytes @in: private_key_bytes @in: encryp_pw- password for encryption private_key_bytes @in: encoding- Encoding.PEM or Encoding.DER @out: private_key object ''' @staticmethod def load_private_key_bytes(private_key_bytes, encryp_pw=b'rootpasswd', encoding=Encoding.PEM): if(encoding==Encoding.PEM): private_key=serialization.load_pem_private_key(private_key_bytes, encryp_pw, default_backend()) elif(encoding==Encoding.DER): private_key=serialization.load_der_private_key(private_key_bytes, encryp_pw, default_backend()) else: private_key='' return private_key ''' Save key bytes data in key_file @in: key_bytes @in: key_file ''' @staticmethod def save_key_bytes(key_bytes, key_file): fname = open(key_file, 'w') fname.write("%s" %(key_bytes.decode(encoding='UTF-8'))) fname.close() ''' Load key bytes data from key_file @in: key_file @out: key_bytes ''' @staticmethod def load_key_bytes(key_file): fname = open(key_file, 'r') key_bytes=fname.read().encode(encoding='UTF-8') fname.close() return key_bytes # Message digests (Hashing) related function class Crypto_Hash(object): ''' Generate hash value given input data @in: byte_data @out: hashed_value ''' @staticmethod def generate_hash(byte_data): #new digest hash instance digest = hashes.Hash(hashes.SHA256(), backend=default_backend()) # apply hash function to data block digest.update(byte_data) # Finalize the current context and return the message digest as bytes. hash_block=digest.finalize() return hash_block ''' verify hash value of given input data @in: hash_data @in: byte_data @out: hashed_value ''' @staticmethod def verify_hash(hash_data, byte_data): #new digest hash instance digest = hashes.Hash(hashes.SHA256(), backend=default_backend()) # apply hash function to data block digest.update(byte_data) # Finalize the current context and return the message digest as bytes. hash_block=digest.finalize() return hash_data==hash_block ''' Get all dataset ''' def test_func(): hash_value=Crypto_Hash.generate_hash(b'samuel') print(Crypto_Hash.verify_hash(hash_value, b'samuel')) pass if __name__ == "__main__": test_func() pass

28.543071

124

0.746228

6,650

0.872589

0

4,506

0.591261

0

3,205

0.420548

dd1f85e853fc4ae8cfcfa14f28add26fec35c361

693

py

Python

src/utils/formatter.py

RuhuiCheng/ladybug

fa9e1ea660dd040d3ecfde96ad6c4db67df9bcb9

[ "Apache-2.0" ]

4

2020-03-14T10:43:29.000Z

2020-09-23T11:15:44.000Z

src/utils/formatter.py

RuhuiCheng/ladybug

fa9e1ea660dd040d3ecfde96ad6c4db67df9bcb9

[ "Apache-2.0" ]

null

src/utils/formatter.py

RuhuiCheng/ladybug

fa9e1ea660dd040d3ecfde96ad6c4db67df9bcb9

[ "Apache-2.0" ]

null

import logging import json from src.utils.ucm import app_id, env class JsonLogFormatter(logging.Formatter): def format(self, record): msg = '' if record.exc_text is None: msg = record.message else: msg = record.exc_text data = { 'app_id': ''+app_id+'', 'asctime': ''+record.asctime+'', 'env': ''+env+'', 'file_name': ''+record.filename+'', 'func_name': ''+record.funcName+'', 'level': ''+record.levelname+'', 'line_number': record.lineno, 'message': ''+msg+'' } string_msg = json.dumps(data) return string_msg

26.653846

47

0.506494

625

0.901876

0

103

0.148629

dd21e59c37175256cff1379b7b03b4b83f129381

363

py

Python

afterglow_core/resources/job_plugins/__init__.py

SkynetRTN/afterglow-access-server

3d8d62f622577fdd1ae7b0076cb536251f7bf0cd

[ "Apache-2.0" ]

2

2021-05-24T15:12:07.000Z

2022-02-17T19:58:16.000Z

afterglow_core/resources/job_plugins/__init__.py

SkynetRTN/afterglow-access-server

3d8d62f622577fdd1ae7b0076cb536251f7bf0cd

[ "Apache-2.0" ]

1

2022-02-27T03:01:06.000Z

afterglow_core/resources/job_plugins/__init__.py

SkynetRTN/afterglow-access-server

3d8d62f622577fdd1ae7b0076cb536251f7bf0cd

[ "Apache-2.0" ]

2

2021-06-08T18:16:40.000Z

2021-07-09T14:19:49.000Z

""" Afterglow Core: job plugin package A job plugin must define a custom model subclassing from :class:`afterglow_core.models.jobs.Job`, along with the optional custom result and settings models (subclassing from :class:`afterglow_core.models.jobs.JobResult` and :class:`afterglow_core.schemas.AfterglowSchema`, respectively), and implement :meth:`Job.run`. """

33

78

0.793388

0

362

0.997245

dd2300aac8a3080e89edc939e28aa0516c80f6a3

4,909

py

Python

wotpy/wot/dictionaries/thing.py

JKRhb/wot-py

3eaa780189b686c82b7dbdea404fd8077bd3c9f9

[ "MIT" ]

null

wotpy/wot/dictionaries/thing.py

JKRhb/wot-py

3eaa780189b686c82b7dbdea404fd8077bd3c9f9

[ "MIT" ]

null

wotpy/wot/dictionaries/thing.py

JKRhb/wot-py

3eaa780189b686c82b7dbdea404fd8077bd3c9f9

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ Wrapper class for dictionaries to represent Things. """ import six from wotpy.wot.dictionaries.base import WotBaseDict from wotpy.wot.dictionaries.interaction import PropertyFragmentDict, ActionFragmentDict, EventFragmentDict from wotpy.wot.dictionaries.link import LinkDict from wotpy.wot.dictionaries.security import SecuritySchemeDict from wotpy.utils.utils import to_camel from wotpy.wot.dictionaries.version import VersioningDict from wotpy.wot.enums import SecuritySchemeType class ThingFragment(WotBaseDict): """ThingFragment is a wrapper around a dictionary that contains properties representing semantic metadata and interactions (Properties, Actions and Events). It is used for initializing an internal representation of a Thing Description, and it is also used in ThingFilter.""" class Meta: fields = { "id", "version", "name", "description", "support", "created", "lastModified", "base", "properties", "actions", "events", "links", "security" } required = { "id" } fields_readonly = [ "id" ] fields_str = [ "name", "description", "support", "created", "lastModified", "base" ] fields_dict = [ "properties", "actions", "events" ] fields_list = [ "links", "security" ] fields_instance = [ "version" ] assert set(fields_readonly + fields_str + fields_dict + fields_list + fields_instance) == fields def __setattr__(self, name, value): """Checks to see if the attribute that is being set is a Thing fragment property and updates the internal dict.""" name_camel = to_camel(name) if name_camel not in self.Meta.fields: return super(ThingFragment, self).__setattr__(name, value) if name_camel in self.Meta.fields_readonly: raise AttributeError("Can't set attribute {}".format(name)) if name_camel in self.Meta.fields_str: self._init[name_camel] = value return if name_camel in self.Meta.fields_dict: self._init[name_camel] = {key: val.to_dict() for key, val in six.iteritems(value)} return if name_camel in self.Meta.fields_list: self._init[name_camel] = [item.to_dict() for item in value] return if name_camel in self.Meta.fields_instance: self._init[name_camel] = value.to_dict() return @property def name(self): """The name of the Thing. This property returns the ID if the name is undefined.""" return self._init.get("name", self.id) @property def security(self): """Set of security configurations, provided as an array, that must all be satisfied for access to resources at or below the current level, if not overridden at a lower level. A default nosec security scheme will be provided if none are defined.""" if "security" not in self._init: return [SecuritySchemeDict.build({"scheme": SecuritySchemeType.NOSEC})] return [SecuritySchemeDict.build(item) for item in self._init.get("security")] @property def properties(self): """The properties optional attribute represents a dict with keys that correspond to Property names and values of type PropertyFragment.""" return { key: PropertyFragmentDict(val) for key, val in six.iteritems(self._init.get("properties", {})) } @property def actions(self): """The actions optional attribute represents a dict with keys that correspond to Action names and values of type ActionFragment.""" return { key: ActionFragmentDict(val) for key, val in six.iteritems(self._init.get("actions", {})) } @property def events(self): """The events optional attribute represents a dictionary with keys that correspond to Event names and values of type EventFragment.""" return { key: EventFragmentDict(val) for key, val in six.iteritems(self._init.get("events", {})) } @property def links(self): """The links optional attribute represents an array of Link objects.""" return [LinkDict(item) for item in self._init.get("links", [])] @property def version(self): """Provides version information.""" return VersioningDict(self._init.get("version")) if self._init.get("version") else None

29.932927

106

0.606233

4,371

0.890405

0

2,041

0.415767

0

1,754

0.357303

dd25aadd6a2a27a37d069c617bb272fc239e2c39

1,044

py

Python

MyApp/config.py

muayyad-alsadi/uPyApp

e81fb9d336a843d068ae93c866cf503989ef6a60

[ "Apache-2.0" ]

null

MyApp/config.py

muayyad-alsadi/uPyApp

e81fb9d336a843d068ae93c866cf503989ef6a60

[ "Apache-2.0" ]

null

MyApp/config.py

muayyad-alsadi/uPyApp

e81fb9d336a843d068ae93c866cf503989ef6a60

[ "Apache-2.0" ]

1

2020-03-18T07:27:27.000Z

__all__ = ['app_config'] import sys, os, os.path try: import ConfigParser as configparser except ImportError: import configparser try: import simplejson as json except ImportError: import json from .base_utils import * class AppConfig(configparser.RawConfigParser): config_filename = 'my-app.ini' main_section = 'MyApp' def __init__(self, *args, **kw): configparser.RawConfigParser.__init__(self, *args, **kw) self.base_dir = base_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) self.read(os.path.join(self.base_dir, self.config_filename)) self.log_level = self.opt_string(self.main_section, 'log-level', 'info').strip().upper() self.is_debug = self.log_level=='DEBUG' def opt_string(self, section, key, fallback=None): return self.get(section, key) if self.has_option(section, key) else fallback def opt_int(self, section, key, fallback=0): return try_int(self.opt_string(section, key, str(fallback)), fallback) app_config=AppConfig()

36

97

0.707854

796

0.762452

0

59

0.056513

dd25b254cf6453ad21e303d8fb8dc65ace25ddf6

1,131

py

Python

src/models/losses/corr_loss.py

yewzijian/RegTR

64e5b3f0ccc1e1a11b514eb22734959d32e0cec6

[ "MIT" ]

25

2022-03-28T06:26:16.000Z

2022-03-30T14:21:24.000Z

src/models/losses/corr_loss.py

yewzijian/RegTR

64e5b3f0ccc1e1a11b514eb22734959d32e0cec6

[ "MIT" ]

null

src/models/losses/corr_loss.py

yewzijian/RegTR

64e5b3f0ccc1e1a11b514eb22734959d32e0cec6

[ "MIT" ]

2

2022-03-29T09:37:50.000Z

2022-03-30T06:26:35.000Z

import torch import torch.nn as nn from utils.se3_torch import se3_transform_list _EPS = 1e-6 class CorrCriterion(nn.Module): """Correspondence Loss. """ def __init__(self, metric='mae'): super().__init__() assert metric in ['mse', 'mae'] self.metric = metric def forward(self, kp_before, kp_warped_pred, pose_gt, overlap_weights=None): losses = {} B = pose_gt.shape[0] kp_warped_gt = se3_transform_list(pose_gt, kp_before) corr_err = torch.cat(kp_warped_pred, dim=0) - torch.cat(kp_warped_gt, dim=0) if self.metric == 'mae': corr_err = torch.sum(torch.abs(corr_err), dim=-1) elif self.metric == 'mse': corr_err = torch.sum(torch.square(corr_err), dim=-1) else: raise NotImplementedError if overlap_weights is not None: overlap_weights = torch.cat(overlap_weights) mean_err = torch.sum(overlap_weights * corr_err) / torch.clamp_min(torch.sum(overlap_weights), _EPS) else: mean_err = torch.mean(corr_err, dim=1) return mean_err

27.585366

112

0.625111

1,031

0.911583

0

56

0.049514

dd26b6dd687da7d2ec0ed40d629b6615e9538af8

501

py

Python

application/services/balance_service.py

singnet/token-balances-service

5e32b11bbad46e9df2820132026ab993935f8049

[ "MIT" ]

null

application/services/balance_service.py

singnet/token-balances-service

5e32b11bbad46e9df2820132026ab993935f8049

[ "MIT" ]

1

2021-04-07T14:40:02.000Z

application/services/balance_service.py

singnet/token-balances-service

5e32b11bbad46e9df2820132026ab993935f8049

[ "MIT" ]

3

2021-04-07T14:12:00.000Z

2021-04-27T07:18:34.000Z

from infrastructure.repository.token_snapshot_repo import TokenSnapshotRepo from http import HTTPStatus def get_snapshot_by_address(address): balance = TokenSnapshotRepo().get_token_balance(address) if balance is None: data = None statusCode = HTTPStatus.BAD_REQUEST.value message = "Address not found in snapshot" else: data = balance statusCode = HTTPStatus.OK.value message = HTTPStatus.OK.phrase return statusCode, message, data

27.833333

75

0.718563

0

31

0.061876

dd272efee44a376502bf4522d14dd1625b93c91b

5,015

py

Python

vaccine_allocation/TN_proj.py

COVID-IWG/epimargin-studies

7d4a78e2e6713c6a0aea2cd2440529153e9a635d

[ "MIT" ]

null

vaccine_allocation/TN_proj.py

COVID-IWG/epimargin-studies

7d4a78e2e6713c6a0aea2cd2440529153e9a635d

[ "MIT" ]

null

vaccine_allocation/TN_proj.py

COVID-IWG/epimargin-studies

7d4a78e2e6713c6a0aea2cd2440529153e9a635d

[ "MIT" ]

null

from typing import Callable, Tuple from epimargin.models import SIR import pandas as pd from epimargin.estimators import analytical_MPVS from epimargin.etl.covid19india import data_path, get_time_series, load_all_data import epimargin.plots as plt from epimargin.smoothing import notched_smoothing from epimargin.utils import cwd, weeks from studies.vaccine_allocation.commons import * from studies.vaccine_allocation.epi_simulations import * from tqdm import tqdm # model details CI = 0.95 smoothing = 7 root = cwd() data = root/"data" figs = root/"figs" data.mkdir(exist_ok=True) figs.mkdir(exist_ok=True) # define data versions for api files paths = { "v3": [data_path(i) for i in (1, 2)], "v4": [data_path(i) for i in range(3, 26)] } for target in paths['v3'] + paths['v4']: try: download_data(data, target) except: pass df = load_all_data( v3_paths = [data/filepath for filepath in paths['v3']], v4_paths = [data/filepath for filepath in paths['v4']] ) # cutoff = None # cutoff = "April 7, 2021" cutoff = "April 14, 2021" if cutoff: df = df[df.date_announced <= cutoff] data_recency = str(df["date_announced"].max()).split()[0] run_date = str(pd.Timestamp.now()).split()[0] ts = get_time_series( df[df.detected_state == "Tamil Nadu"], ["detected_state", "detected_district"] )\ .drop(columns = ["date", "time", "delta", "logdelta"])\ .rename(columns = { "Deceased": "dD", "Hospitalized": "dT", "Recovered": "dR" }).droplevel(0)\ .drop(labels = ["Other State", "Railway Quarantine", "Airport Quarantine"]) district_estimates = [] simulation_initial_conditions = pd.read_csv(data/f"all_india_coalesced_initial_conditions{simulation_start.strftime('%b%d')}.csv")\ .drop(columns = ["Unnamed: 0"])\ .set_index(["state", "district"])\ .loc["Tamil Nadu"] def setup(district) -> Tuple[Callable[[str], SIR], pd.DataFrame]: demographics = simulation_initial_conditions.loc[district] dR_conf = ts.loc[district].dR dR_conf = dR_conf.reindex(pd.date_range(dR_conf.index.min(), dR_conf.index.max()), fill_value = 0) dR_conf_smooth = pd.Series(smooth(dR_conf), index = dR_conf.index).clip(0).astype(int) R_conf_smooth = dR_conf_smooth.cumsum().astype(int) R0 = R_conf_smooth[data_recency] dD_conf = ts.loc[district].dD dD_conf = dD_conf.reindex(pd.date_range(dD_conf.index.min(), dD_conf.index.max()), fill_value = 0) dD_conf_smooth = pd.Series(smooth(dD_conf), index = dD_conf.index).clip(0).astype(int) D_conf_smooth = dD_conf_smooth.cumsum().astype(int) D0 = D_conf_smooth[data_recency] dT_conf = ts.loc[district].dT dT_conf = dT_conf.reindex(pd.date_range(dT_conf.index.min(), dT_conf.index.max()), fill_value = 0) ( dates, Rt_pred, Rt_CI_upper, Rt_CI_lower, T_pred, T_CI_upper, T_CI_lower, total_cases, new_cases_ts, *_ ) = analytical_MPVS(ts.loc[district].dT, CI = CI, smoothing = notched_smoothing(window = smoothing), totals = False) Rt_estimates = pd.DataFrame(data = { "dates" : dates, "Rt_pred" : Rt_pred, "Rt_CI_upper" : Rt_CI_upper, "Rt_CI_lower" : Rt_CI_lower, "T_pred" : T_pred, "T_CI_upper" : T_CI_upper, "T_CI_lower" : T_CI_lower, "total_cases" : total_cases[2:], "new_cases_ts": new_cases_ts, }) dT_conf_smooth = pd.Series(smooth(dT_conf), index = dT_conf.index).clip(0).astype(int) T_conf_smooth = dT_conf_smooth.cumsum().astype(int) T0 = T_conf_smooth[data_recency] dT0 = dT_conf_smooth[data_recency] S0 = max(0, demographics.N_tot - T0) I0 = max(0, T0 - R0 - D0) return ( lambda seed = 0: SIR( name = district, mortality = demographics[[f"N_{i}" for i in range(7)]] @ np.array(list(TN_IFRs.values()))/demographics.N_tot, population = demographics.N_tot, random_seed = seed, infectious_period = 10, S0 = S0, I0 = I0, R0 = R0, D0 = D0, dT0 = dT0, Rt0 = Rt_estimates.set_index("dates").loc[data_recency].Rt_pred * demographics.N_tot/S0), Rt_estimates ) district_estimates = [] for district in tqdm(simulation_initial_conditions.index.get_level_values(0).unique()): simulation, Rt_estimates = setup(district) district_estimates.append(Rt_estimates.assign(district = district)) Rt_estimates.to_csv(data/f"TN_Rt_data_{district}_{data_recency}_run{run_date}.csv") projections = pd.DataFrame( np.array( [simulation(_).run(6 * weeks).dT for _ in range(1000)] )).astype(int).T\ .set_index(pd.date_range(start = data_recency, freq = "D", periods = 6*weeks + 1)) print(district, projections.mean(axis = 1)) projections.to_csv(data/f"TN_projections/projections_{district}_data{data_recency}_run{run_date}.csv")

34.586207

131

0.656032

0

710

0.141575

dd27497c195aa372001cc5557855526c81484bc2

263

py

Python

nameyourapp/routes.py

WhereWeCanShare/minipy

485e9c4f122aa56ed8389d0ea7b5c16d59179aed

[ "BSD-3-Clause" ]

null

nameyourapp/routes.py

WhereWeCanShare/minipy

485e9c4f122aa56ed8389d0ea7b5c16d59179aed

[ "BSD-3-Clause" ]

null

nameyourapp/routes.py

WhereWeCanShare/minipy

485e9c4f122aa56ed8389d0ea7b5c16d59179aed

[ "BSD-3-Clause" ]

null

from flask import Blueprint main = Blueprint('main', __name__) @main.route('/') def main_index(): return '<div align="center"><img src="https://source.unsplash.com/1200x800/?technology,matrix,hacker,women"><p>Thanks Unsplash for nice photo</p></div>', 200

29.222222

161

0.714829

0

196

0.745247

0

154

0.585551

dd28575d99501b8ab89e76a54053a882db38d79c

1,514

py

Python

backend/db/test/id_allocator_test.py

xuantan/viewfinder

992209086d01be0ef6506f325cf89b84d374f969

[ "Apache-2.0" ]

645

2015-01-03T02:03:59.000Z

2021-12-03T08:43:16.000Z

backend/db/test/id_allocator_test.py

hoowang/viewfinder

9caf4e75faa8070d85f605c91d4cfb52c4674588

[ "Apache-2.0" ]

null

backend/db/test/id_allocator_test.py

hoowang/viewfinder

9caf4e75faa8070d85f605c91d4cfb52c4674588

[ "Apache-2.0" ]

222

2015-01-07T05:00:52.000Z

2021-12-06T09:54:26.000Z

# Copyright 2011 Viewfinder Inc. All Rights Reserved. """Tests for IdAllocator data object. """ __author__ = 'spencer@emailscrubbed.com (Spencer Kimball)' import unittest from viewfinder.backend.base import util from viewfinder.backend.base.testing import async_test from viewfinder.backend.db.id_allocator import IdAllocator from base_test import DBBaseTestCase class IdAllocatorTestCase(DBBaseTestCase): @async_test def testCreate(self): alloc = IdAllocator('type', 13) num_ids = 3000 def _OnAllocated(ids): id_set = set(ids) assert len(id_set) == num_ids self.stop() with util.ArrayBarrier(_OnAllocated) as b: [alloc.NextId(self._client, callback=b.Callback()) for i in xrange(num_ids)] @async_test def testMultiple(self): """Tests that multiple allocations from the same sequence do not overlap. """ allocs = [IdAllocator('type'), IdAllocator('type')] num_ids = 3000 def _OnAllocated(id_lists): assert len(id_lists) == 2 id_set1 = set(id_lists[0]) id_set2 = set(id_lists[1]) assert len(id_set1) == 3000 assert len(id_set2) == 3000 assert id_set1.isdisjoint(id_set2) self.stop() with util.ArrayBarrier(_OnAllocated) as b: with util.ArrayBarrier(b.Callback()) as b1: [allocs[0].NextId(self._client, b1.Callback()) for i in xrange(num_ids)] with util.ArrayBarrier(b.Callback()) as b2: [allocs[1].NextId(self._client, b2.Callback()) for i in xrange(num_ids)]

30.28

82

0.694188

1,144

0.755614

0

1,095

0.72325

0

242

0.159841

dd2928863b82fbf5dba0596d90335b5ef6bbbb9b

2,429

py

Python

ayame/link.py

hattya/ayame

e8bb2b0ace79cd358b1384270cb9c5e809e12b5d

[ "MIT" ]

1

2022-03-05T03:21:13.000Z

ayame/link.py

hattya/ayame

e8bb2b0ace79cd358b1384270cb9c5e809e12b5d

[ "MIT" ]

1

2021-08-25T13:41:34.000Z

ayame/link.py

hattya/ayame

e8bb2b0ace79cd358b1384270cb9c5e809e12b5d

[ "MIT" ]

1

2018-03-04T21:47:27.000Z

# # ayame.link # # Copyright (c) 2012-2021 Akinori Hattori <hattya@gmail.com> # # SPDX-License-Identifier: MIT # import urllib.parse from . import core, markup, uri, util from . import model as mm from .exception import ComponentError __all__ = ['Link', 'ActionLink', 'PageLink'] # HTML elements _A = markup.QName(markup.XHTML_NS, 'a') _LINK = markup.QName(markup.XHTML_NS, 'link') _AREA = markup.QName(markup.XHTML_NS, 'area') _SCRIPT = markup.QName(markup.XHTML_NS, 'script') _STYLE = markup.QName(markup.XHTML_NS, 'style') # HTML attributes _HREF = markup.QName(markup.XHTML_NS, 'href') _SRC = markup.QName(markup.XHTML_NS, 'src') class Link(core.MarkupContainer): def __init__(self, id, model=None): if isinstance(model, str): model = mm.Model(model) super().__init__(id, model) def on_render(self, element): # modify attribute attr = None if element.qname in (_A, _LINK, _AREA): attr = _HREF elif element.qname in (_SCRIPT, _STYLE): attr = _SRC if attr is not None: uri = self.new_uri(element.attrib.get(attr)) if uri is None: if attr in element.attrib: del element.attrib[attr] else: element.attrib[attr] = uri # replace children by model object body = self.model_object_as_string() if body: element[:] = (body,) # render link return super().on_render(element) def new_uri(self, uri): return uri class ActionLink(Link): def on_fire(self): self.on_click() def new_uri(self, _): query = self.request.query.copy() query[core.AYAME_PATH] = [self.path()] environ = self.environ.copy() environ['QUERY_STRING'] = urllib.parse.urlencode(query, doseq=True) return uri.request_uri(environ, True) def on_click(self): pass class PageLink(Link): def __init__(self, id, page, values=None, anchor=''): super().__init__(id, None) if (not issubclass(page, core.Page) or page is core.Page): raise ComponentError(self, f"'{util.fqon_of(page)}' is not a subclass of Page") self._page = page self._values = values self._anchor = anchor def new_uri(self, uri): return self.uri_for(self._page, self._values, self._anchor)

26.692308

91

0.611774

1,776

0.731165

0

343

0.14121

dd2b17b19b93b0baf9bf8e30437c71d115b7442f

885

py

Python

local/race_sim.py

tractiming/trac-gae

46c4a1fe409a45e8595210a5cf242425d40d4b41

[ "MIT" ]

3

2020-09-13T04:56:31.000Z

2021-05-26T11:46:08.000Z

local/race_sim.py

tractiming/trac-gae

46c4a1fe409a45e8595210a5cf242425d40d4b41

[ "MIT" ]

null

local/race_sim.py

tractiming/trac-gae

46c4a1fe409a45e8595210a5cf242425d40d4b41

[ "MIT" ]

1

2020-05-09T10:05:08.000Z

import requests import datetime import time UPDATE_URL = "http://www.trac-us.appspot.com/api/updates/" #UPDATE_URL = "http://localhost:8000/api/updates/" def post_split(reader_code, tag_code, time): formatted_time = time.strftime("%Y/%m/%d %H:%M:%S.%f") payload = {'r': reader_code, 's': r"[['{0}', '{1}'],]".format(tag_code, formatted_time)} r = requests.post(UPDATE_URL, data=payload) print r.content def main(): tag_str = '12345' reader_str = 'A1010' all_tags = ['test %04d' %i for i in range(1,51)] while True: for tag in all_tags: post_split(reader_str, tag, datetime.datetime.now()) print 'splits posted ------------------------' time.sleep(40) #print all_tags #post_split(reader_str, tag_str, datetime.datetime.utcnow()) if __name__ == "__main__": main()

20.113636

74

0.59661

0

293

0.331073

dd2b8d0943d4247577bcc13dba218fa49f1ddda9

5,775

py

Python

classes.py

mattjoman/deep-RL-snake

c1b48ef3cb7ac0ad068887df1f60bc83a626f9d6

[ "MIT" ]

null

classes.py

mattjoman/deep-RL-snake

c1b48ef3cb7ac0ad068887df1f60bc83a626f9d6

[ "MIT" ]

null

classes.py

mattjoman/deep-RL-snake

c1b48ef3cb7ac0ad068887df1f60bc83a626f9d6

[ "MIT" ]

null

import pygame import numpy as np import random import torch from torch import nn from torch.nn import functional as F class CNN(torch.nn.Module): def __init__(self): super(CNN, self).__init__() torch.manual_seed(50) self.layer1 = nn.Sequential( # input: (1, 1, 10, 10) # output: (1, 8, 18, 18) nn.Conv2d(3, 32, (3, 3), stride=1), nn.ReLU()) self.layer2 = nn.Sequential( # input: (8, 8, 8, 8) # output: (8, 8, 6, 6) nn.Conv2d(32, 64, (3, 3), stride=1), nn.ReLU()) self.layer3 = nn.Sequential( # input: (8, 8, 6, 6) # output: (8, 8, 4, 4) nn.Conv2d(64, 32, (3, 3), stride=1), nn.ReLU()) self.layer4 = nn.Sequential( # input: (32*4*4) nn.Linear(512, 128, bias=True), nn.ReLU()) self.layer5 = nn.Sequential( nn.Linear(128, 4, bias=True)) #self.optimiser = torch.optim.SGD(self.parameters(), lr=1) self.optimiser = torch.optim.Adam(self.parameters(), lr=1) def forward(self, x): out = self.layer1(x.to(torch.float32)) out = self.layer2(out) out = self.layer3(out) out = out.view(out.size(0), -1) # flatten out = self.layer4(out) out = self.layer5(out) #print(out) return out class Snake(): def __init__(self, rows=10, columns=10): self.direction = 3 self.init_body(rows, columns) self.apple = False self.score = 0 self.timestep_counter = 0 def add_to_body(self): if self.direction == 2: new_head = [self.body[0][0] - 1, self.body[0][1]] elif self.direction == 3: new_head = [self.body[0][0] + 1, self.body[0][1]] elif self.direction == 0: new_head = [self.body[0][0], self.body[0][1] - 1] else: new_head = [self.body[0][0], self.body[0][1] + 1] self.body.insert(0, new_head) return def remove_from_body(self): del self.body[-1] return def move(self): self.add_to_body() self.timestep_counter += 1 if not self.apple: self.remove_from_body() else: self.apple = False return def eat_apple(self): self.apple = True self.score += 1 return def init_score(self): self.score = 0 return def init_timestep_counter(self): self.timestep_counter = 0 return def init_body(self, rows, columns): self.body = [[np.random.randint(1, rows-1), np.random.randint(1, columns-1)]] return class Player(Snake): def set_direction(self, keys): if keys[pygame.K_LEFT]: self.direction = 0 # left elif keys[pygame.K_RIGHT]: self.direction = 1 # right elif keys[pygame.K_UP]: self.direction = 2 # up elif keys[pygame.K_DOWN]: self.direction = 3 # down return class AI(Snake): def __init__(self): super().__init__() self.epsilon = 0.1 self.gamma = 0.3 self.Q_net = CNN() self.target_Q_net = self.Q_net self.replay_mem = [] self.replay_mem_limit = 500 self.batch_size = 64 self.game_count = 0 def set_direction(self, state): Q_vals = self.Q_net.forward(torch.from_numpy(state)) self.direction, _ = self.select_action(Q_vals) return def select_action(self, Q_vals): """ Returns the action selected and Q vals for each action """ max_ = Q_vals.max().item() for i in range(4): if Q_vals[0][i].item() == max_: greedy_direction = i random_num = np.random.uniform(0, 1) self.epsilon = 1 / (self.game_count ** (1/2.5)) if random_num > self.epsilon: return greedy_direction, max_ else: return np.random.random_integers(0, 3), Q_vals[0][i].item() def learn_from_mem(self): if self.timestep_counter % 5 == 0: self.target_Q_net = self.Q_net if len(self.replay_mem) < self.batch_size: return for b in range(self.batch_size): mem = self.select_mem() reward = mem[2] Q_0_vals = self.Q_net.forward(torch.from_numpy(mem[0])) Q_1_vals = self.target_Q_net.forward(torch.from_numpy(mem[3])) Q_0 = Q_0_vals[0][mem[1]] # get Q val for the action taken Q_1 = Q_1_vals.max().detach() # get the maximum Q val for the next state loss = F.smooth_l1_loss(Q_0, (self.gamma * Q_1) + reward) self.Q_net.optimiser.zero_grad() loss.backward() for param in self.Q_net.parameters(): param.grad.data.clamp_(-1, 1) # do we need to clamp? self.Q_net.optimiser.step() return def update_replay_mem(self, s0, a0, r, s1): if len(self.replay_mem) >= self.replay_mem_limit: del self.replay_mem[0] self.replay_mem.append([s0, a0, r, s1]) return def select_mem(self): index = np.random.random_integers(0, len(self.replay_mem)-1) return self.replay_mem[index] class Apple(): def __init__(self, rows, columns): self.set_loc(rows, columns) def set_loc(self, rows, columns): self.loc = [random.randint(1, rows-2), random.randint(1, columns-2)] return if __name__ == "__main__": ai = AI() state = np.random.rand(20, 20) ai.set_direction(state) print(ai.direction) print(ai.body[0]) ai.move() print(ai.body[0])

26.612903

86

0.546667

5,435

0.941126

0

419

0.072554

dd2f7e3c6dec1485c37b66c19a901c087ee62101

1,289

py

Python

examples/basic/turnOffLight_fb.py

quangthanh010290/EchoSkills

b90379cddb034a1e379fef77ca48c583bd6e47d5

[ "MIT" ]

null

examples/basic/turnOffLight_fb.py

quangthanh010290/EchoSkills

b90379cddb034a1e379fef77ca48c583bd6e47d5

[ "MIT" ]

null

examples/basic/turnOffLight_fb.py

quangthanh010290/EchoSkills

b90379cddb034a1e379fef77ca48c583bd6e47d5

[ "MIT" ]

null

import logging from random import randint from flask import Flask, render_template from flask_ask import Ask, statement, question, session from firebase import firebase import time firebase = firebase.FirebaseApplication('https://iotdev-6b58b.firebaseio.com', None) app = Flask(__name__) ask = Ask(app, "/") #logging.getLogger("flask_ask").setLevel(logging.DEBUG) @ask.launch def launch(): return question("Which room you want to turn off?") @ask.intent("RoomIntent") def intent_fcn(roomName): msg = "Ligh on {} is turned off".format(roomName) if roomName == "kitchen": print 'Light on kichen room is turned off' firebase.put('/devices/8795002','status',False) if roomName == "living room": print 'Light on living room is turn off' firebase.put('/devices/390650','status',False) if roomName == 'bathroom': print 'Light on bath room is turn off' firebase.put('/devices/390192','status',False) return statement(msg) @ask.intent("AMAZON.YesIntent") def yes_fcn(roomName): msg = "Ligh on {} is turned off".format(roomName) print roomName firebase.put('/123','states/001',False) return statement(msg) def stop(): return statement("Stoped") if __name__ == '__main__': app.run(debug=False,host = '0.0.0.0', port=7000)

22.614035

84

0.703646

0

782

0.606672

0

466

0.361521

dd333037440197eebf8dccb7cbf70627b566e58c

763

py

Python

home_app/migrations/0003_auto_20200412_0206.py

Ymirrp/Home-page

6ac9b5b76cc2b08298086c7e784685dad802c9d6

[ "MIT" ]

null

home_app/migrations/0003_auto_20200412_0206.py

Ymirrp/Home-page

6ac9b5b76cc2b08298086c7e784685dad802c9d6

[ "MIT" ]

7

2020-04-18T04:54:05.000Z

2020-04-29T14:49:46.000Z

home_app/migrations/0003_auto_20200412_0206.py

Ymirrp/Home-page

6ac9b5b76cc2b08298086c7e784685dad802c9d6

[ "MIT" ]

null

# Generated by Django 3.0.5 on 2020-04-12 02:06 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('home_app', '0002_auto_20200408_2205'), ] operations = [ migrations.RemoveField( model_name='topsites', name='order_no', ), migrations.AlterField( model_name='topsites', name='categories', field=models.CharField(choices=[('HOBB', 'Áhugamál'), ('BOOK', 'Bókamerki'), ('NEWS', 'Fréttir'), ('SPOR', 'Íþróttir'), ('GAME', 'Leikir'), ('EDUC', 'Nám'), ('SOCI', 'Samfélagsmiðlar'), ('SHOP', 'Versla'), ('WORK', 'Vinna'), ('FAVO', 'Uppáhalds')], default='FAVO', max_length=4), ), ]

33.173913

292

0.55308

675

0.872093

0

298

0.385013

dd341ee91f7a33f3e372a0311daf89a77f9a9148

349

py

Python

tests/test_license_screening.py

sthagen/python-scaling-tribble

2bb2e41185ae2b0108f341751d0e4a2187909683

[ "MIT" ]

null

tests/test_license_screening.py

sthagen/python-scaling-tribble

2bb2e41185ae2b0108f341751d0e4a2187909683

[ "MIT" ]

18

2021-02-14T15:17:17.000Z

2021-02-14T17:46:27.000Z

tests/test_license_screening.py

sthagen/python-scaling-tribble

2bb2e41185ae2b0108f341751d0e4a2187909683

[ "MIT" ]

null

# -*- coding: utf-8 -*- # pylint: disable=missing-docstring,unused-import,reimported import pytest # type: ignore import tests.context as ctx import license_screening.license_screening as lis def test_parse_ok_empty_string(): assert lis.parse('') is NotImplemented def test_parse_ok_known_tree(): assert lis.main(["tests/data"]) == 0

21.8125

60

0.744986

0

111

0.318052

dd3452c9bed80f5adb210957aa5ef5db051c0f6c

301

py

Python

ml_progress/percent_metric.py

gregrolwes/ml_progress

e352f73847e163993ff9e642973512f070555805

[ "MIT" ]

null

ml_progress/percent_metric.py

gregrolwes/ml_progress

e352f73847e163993ff9e642973512f070555805

[ "MIT" ]

null

ml_progress/percent_metric.py

gregrolwes/ml_progress

e352f73847e163993ff9e642973512f070555805

[ "MIT" ]

null

import sys from .display import Display class PercentMetric(Display): def __init__(self, metric: str): super().__init__() self.metric = metric def update(self, metrics: dict, width=25, height=1): sys.stdout.write("%s: %3d%% \n" % (self.metric, metrics[self.metric]))

27.363636

78

0.644518

259

0.860465

0

14

0.046512

dd34c031db159b934c285da9deacefad0961aecf

762

py

Python

src/server/alembic/versions/6b8cf99be000_add_user_journal_table.py

princessruthie/paws-data-pipeline

6f7095f99b9ad31b0171b256cf18849d63445c91

[ "MIT" ]

27

2019-11-20T20:20:30.000Z

2022-01-31T17:24:55.000Z

src/server/alembic/versions/6b8cf99be000_add_user_journal_table.py

mrcrnkovich/paws-data-pipeline

7c0bd4c5f23276f541611cb564f2f5abbb6b9887

[ "MIT" ]

348

2019-11-26T20:34:02.000Z

2022-02-27T20:28:20.000Z

src/server/alembic/versions/6b8cf99be000_add_user_journal_table.py

mrcrnkovich/paws-data-pipeline

7c0bd4c5f23276f541611cb564f2f5abbb6b9887

[ "MIT" ]

20

2019-12-03T23:50:33.000Z

2022-02-09T18:38:25.000Z

"""Add user journal table Revision ID: 6b8cf99be000 Revises: 36c4ecbfd11a Create Date: 2020-12-21 15:08:07.784568 """ from alembic import op import sqlalchemy as sa from sqlalchemy.sql import func # revision identifiers, used by Alembic. revision = "6b8cf99be000" down_revision = "36c4ecbfd11a" branch_labels = None depends_on = None def upgrade(): op.create_table( "pdp_user_journal", sa.Column("_id", sa.Integer, primary_key=True), sa.Column("stamp", sa.DateTime, nullable=False, server_default=func.now()), sa.Column("username", sa.String(50), nullable=False), sa.Column("event_type", sa.String(50)), sa.Column("detail", sa.String(120)), ) def downgrade(): op.drop_table('pdp_user_journal')

23.090909

83

0.692913

0

265

0.347769

dd368cbbf1f2713371fc20b46be0df6fde83d872

1,906

py

Python

Python/WearherTelegram/weatherbot.py

OnCode-channel/OnCode

4aa7022932bc5aece39121233b34ebea12063717

[ "CC0-1.0" ]

3

2021-11-21T05:09:45.000Z

2021-11-21T09:55:02.000Z

Python/WearherTelegram/weatherbot.py

OnCode-channel/OnCode

4aa7022932bc5aece39121233b34ebea12063717

[ "CC0-1.0" ]

null

Python/WearherTelegram/weatherbot.py

OnCode-channel/OnCode

4aa7022932bc5aece39121233b34ebea12063717

[ "CC0-1.0" ]

1

2022-03-16T20:34:29.000Z

import telebot from pyowm import OWM from pyowm.utils.config import get_default_config bot = telebot.TeleBot("telegram API-key") @bot.message_handler(commands=['start']) def welcome(message): bot.send_message(message.chat.id, 'Добро пожаловать, ' + str(message.from_user.first_name) + ',\n/start - запуск бота\n/help - команды бота\n/credits - автор бота\nЧтобы узнать погоду напишите в чат название города') @bot.message_handler(commands=['help']) def help(message): bot.send_message(message.chat.id, '/start - запуск бота\n/help - команды бота\n/credits - автор бота\nЧтобы узнать погоду напишите в чат название города') @bot.message_handler(content_types=['text']) def test(message): try: place = message.text config_dict = get_default_config() config_dict['language'] = 'ru' owm = OWM('owm api-key', config_dict) mgr = owm.weather_manager() observation = mgr.weather_at_place(place) w = observation.weather t = w.temperature("celsius") t1 = t['temp'] t2 = t['feels_like'] t3 = t['temp_max'] t4 = t['temp_min'] wi = w.wind()['speed'] humi = w.humidity cl = w.clouds st = w.status dt = w.detailed_status ti = w.reference_time('iso') pr = w.pressure['press'] vd = w.visibility_distance bot.send_message(message.chat.id, "В городе " + str(place) + " температура " + str(t1) + " °C" + "\n" + "Максимальная температура " + str(t3) + " °C" +"\n" + "Минимальная температура " + str(t4) + " °C" + "\n" + "Ощущается как" + str(t2) + " °C" + "\n" + "Скорость ветра " + str(wi) + " м/с" + "\n" + "Давление " + str(pr) + " мм.рт.ст" + "\n" + "Влажность " + str(humi) + " %" + "\n" + "Видимость " + str(vd) + " метров" + "\n" + "Описание " + str(st) + "\n\n" + str(dt)) except: bot.send_message(message.chat.id,"Такой город не найден!") print(str(message.text),"- не найден") bot.polling(none_stop=True, interval=0)

32.862069

217

0.64638

0

2,056

0.920734

0

1,001

0.448276

dd37cbcc06fe382942dc56ae1ef81d1193794b23

17

py

Python

appium/version.py

zgq346712481/python-client

1c179d2c84c76bbed33e6333f381cc8a86f3bb82

[ "Apache-2.0" ]

1

2019-03-07T00:53:43.000Z

appium/version.py

zgq346712481/python-client

1c179d2c84c76bbed33e6333f381cc8a86f3bb82

[ "Apache-2.0" ]

null

appium/version.py

zgq346712481/python-client

1c179d2c84c76bbed33e6333f381cc8a86f3bb82

[ "Apache-2.0" ]

null

version = '0.38'

8.5

16

0.588235

0

6

0.352941

dd3bf5910219efb966cd48792f7c68202d3a54a8

130

py

Python

earth_enterprise/src/server/wsgi/serve/push/stream/__init__.py

ezeeyahoo/earthenterprise

b6cac9e6228946f2f17d1edb75e118aeb3e8e8c9

[ "Apache-2.0" ]

2,661

2017-03-20T22:12:50.000Z

2022-03-30T09:43:19.000Z

earth_enterprise/src/server/wsgi/serve/push/stream/__init__.py

ezeeyahoo/earthenterprise

b6cac9e6228946f2f17d1edb75e118aeb3e8e8c9

[ "Apache-2.0" ]

1,531

2017-03-24T17:20:32.000Z

2022-03-16T18:11:14.000Z

earth_enterprise/src/server/wsgi/serve/push/stream/__init__.py

ezeeyahoo/earthenterprise

b6cac9e6228946f2f17d1edb75e118aeb3e8e8c9

[ "Apache-2.0" ]

990

2017-03-24T11:54:28.000Z

2022-03-22T11:51:47.000Z

"""The package indicator for serve.push.stream. Modules for transferring and registering servable stream data on the server. """

26

76

0.784615

0

129

0.992308

dd3c2fd0cab5262a11100e98979113701b2c65bd

2,828

py

Python

Projects_Django/MyPets/tienda_mascotas/models.py

JuanCasanovaQ/Frameworks_8A

353838473b275d366cac8364ef4df72578c0aed8

[ "Apache-2.0" ]

null

Projects_Django/MyPets/tienda_mascotas/models.py

JuanCasanovaQ/Frameworks_8A

353838473b275d366cac8364ef4df72578c0aed8

[ "Apache-2.0" ]

null

Projects_Django/MyPets/tienda_mascotas/models.py

JuanCasanovaQ/Frameworks_8A

353838473b275d366cac8364ef4df72578c0aed8

[ "Apache-2.0" ]

null

from django.db import models from django.db.models.fields.related import ForeignKey # Create your models here. class Country(models.Model): code = models.CharField(max_length=10) name = models.CharField(max_length=150) abrev = models.CharField(max_length=4) status = models.BooleanField() created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField() class User(models.Model): first_name = models.CharField(max_length=200) last_name = models.CharField(max_length=200) id_identification_type = models.IntegerField() number_id = models.CharField(max_length=15) id_city = models.IntegerField() email = models.CharField(max_length=200) password = models.CharField(max_length=200) status = models.BooleanField() created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField() class Session(models.Model): id_user = models.IntegerField() ip = models.CharField(max_length=200) status = models.BooleanField() created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField() class Identification_type(models.Model): type = models.CharField(max_length=150) abrev = models.CharField(max_length=4) created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField() class City(models.Model): code = models.CharField(max_length=10) name = models.CharField(max_length=150) abrev = models.CharField(max_length=4) id_country = models.IntegerField() status = models.BooleanField() created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField() class Pet(models.Model): code = models.CharField(max_length=10) name = models.CharField(max_length=150) id_user = models.IntegerField() id_type = models.IntegerField() id_race = models.IntegerField() status = models.BooleanField() created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField() class Type(models.Model): code = models.CharField(max_length=10) name = models.CharField(max_length=150) abrev = models.CharField(max_length=4) status = models.BooleanField() created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField() class Race(models.Model): code = models.CharField(max_length=10) name = models.CharField(max_length=150) abrev = models.CharField(max_length=4) status = models.BooleanField() created_at = models.DateField(auto_now=True) updatesd_at = models.DateField() deleted_at = models.DateField()

32.883721

54

0.724187

2,691

0.951556

0

26

0.009194

dd3c339456c728831d00962485678bd366a32bd9

34

py

Python

homeassistant/components/limitlessled/__init__.py

domwillcode/home-assistant

f170c80bea70c939c098b5c88320a1c789858958

[ "Apache-2.0" ]

30,023

2016-04-13T10:17:53.000Z

2020-03-02T12:56:31.000Z

homeassistant/components/limitlessled/__init__.py

jagadeeshvenkatesh/core

1bd982668449815fee2105478569f8e4b5670add

[ "Apache-2.0" ]

31,101

2020-03-02T13:00:16.000Z

2022-03-31T23:57:36.000Z

homeassistant/components/limitlessled/__init__.py

jagadeeshvenkatesh/core

1bd982668449815fee2105478569f8e4b5670add

[ "Apache-2.0" ]

11,956

2016-04-13T18:42:31.000Z

2020-03-02T09:32:12.000Z

"""The limitlessled component."""

17

33

0.705882

0

33

0.970588

dd3c5ef2c1c57128342b4cbe674344dc894fe7e9

14,427

py

Python

projectroles/app_settings.py

olgabot/sodar_core

2a012c962c763fe970261839226e848d752d14d5

[ "MIT" ]

null

projectroles/app_settings.py

olgabot/sodar_core

2a012c962c763fe970261839226e848d752d14d5

[ "MIT" ]

null

projectroles/app_settings.py

olgabot/sodar_core

2a012c962c763fe970261839226e848d752d14d5

[ "MIT" ]

null

"""Project and user settings API""" import json from projectroles.models import AppSetting, APP_SETTING_TYPES, SODAR_CONSTANTS from projectroles.plugins import get_app_plugin, get_active_plugins # SODAR constants APP_SETTING_SCOPE_PROJECT = SODAR_CONSTANTS['APP_SETTING_SCOPE_PROJECT'] APP_SETTING_SCOPE_USER = SODAR_CONSTANTS['APP_SETTING_SCOPE_USER'] APP_SETTING_SCOPE_PROJECT_USER = SODAR_CONSTANTS[ 'APP_SETTING_SCOPE_PROJECT_USER' ] # Local constants VALID_SCOPES = [ APP_SETTING_SCOPE_PROJECT, APP_SETTING_SCOPE_USER, APP_SETTING_SCOPE_PROJECT_USER, ] class AppSettingAPI: @classmethod def _check_project_and_user(cls, scope, project, user): """ Ensure one of the project and user parameters is set. :param scope: Scope of Setting (USER, PROJECT, PROJECT_USER) :param project: Project object :param user: User object :raise: ValueError if none or both objects exist """ if scope == APP_SETTING_SCOPE_PROJECT: if not project: raise ValueError('Project unset for setting with project scope') if user: raise ValueError('User set for setting with project scope') elif scope == APP_SETTING_SCOPE_USER: if project: raise ValueError('Project set for setting with user scope') if not user: raise ValueError('User unset for setting with user scope') elif scope == APP_SETTING_SCOPE_PROJECT_USER: if not project: raise ValueError( 'Project unset for setting with project_user scope' ) if not user: raise ValueError( 'User unset for setting with project_user scope' ) @classmethod def _check_scope(cls, scope): """ Ensure the validity of a scope definition. :param scope: String :raise: ValueError if scope is not recognized """ if scope not in VALID_SCOPES: raise ValueError('Invalid scope "{}"'.format(scope)) @classmethod def _get_json_value(cls, value): """ Return JSON value as dict regardless of input type :param value: Original value (string or dict) :raise: json.decoder.JSONDecodeError if string value is not valid JSON :raise: ValueError if value type is not recognized or if value is not valid JSON :return: dict """ if not value: return {} try: if isinstance(value, str): return json.loads(value) else: json.dumps(value) # Ensure this is valid return value except Exception: raise ValueError('Value is not valid JSON: {}'.format(value)) @classmethod def _compare_value(cls, setting_obj, input_value): """ Compare input value to value in an AppSetting object :param setting_obj: AppSetting object :param input_value: Input value (string, int, bool or dict) :return: Bool """ if setting_obj.type == 'JSON': return setting_obj.value_json == cls._get_json_value(input_value) elif setting_obj.type == 'BOOLEAN': # TODO: Also do conversion on input value here if necessary return bool(int(setting_obj.value)) == input_value return setting_obj.value == str(input_value) @classmethod def get_default_setting(cls, app_name, setting_name, post_safe=False): """ Get default setting value from an app plugin. :param app_name: App name (string, must correspond to "name" in app plugin) :param setting_name: Setting name (string) :param post_safe: Whether a POST safe value should be returned (bool) :return: Setting value (string, integer or boolean) :raise: KeyError if nothing is found with setting_name """ app_plugin = get_app_plugin(app_name) if setting_name in app_plugin.app_settings: if ( post_safe and app_plugin.app_settings[setting_name]['type'] == 'JSON' ): return json.dumps( app_plugin.app_settings[setting_name]['default'] ) return app_plugin.app_settings[setting_name]['default'] raise KeyError( 'Setting "{}" not found in app plugin "{}"'.format( setting_name, app_name ) ) @classmethod def get_app_setting( cls, app_name, setting_name, project=None, user=None, post_safe=False ): """ Return app setting value for a project or an user. If not set, return default. :param app_name: App name (string, must correspond to "name" in app plugin) :param setting_name: Setting name (string) :param project: Project object (can be None) :param user: User object (can be None) :param post_safe: Whether a POST safe value should be returned (bool) :return: String or None :raise: KeyError if nothing is found with setting_name """ try: val = AppSetting.objects.get_setting_value( app_name, setting_name, project=project, user=user ) except AppSetting.DoesNotExist: val = cls.get_default_setting(app_name, setting_name, post_safe) # Handle post_safe for dict values (JSON) if post_safe and isinstance(val, dict): return json.dumps(val) return val @classmethod def get_all_settings(cls, project=None, user=None, post_safe=False): """ Return all setting values. If the value is not found, return the default. :param project: Project object (can be None) :param user: User object (can be None) :param post_safe: Whether POST safe values should be returned (bool) :return: Dict :raise: ValueError if neither project nor user are set """ if not project and not user: raise ValueError('Project and user are both unset') ret = {} app_plugins = get_active_plugins() for plugin in app_plugins: p_settings = cls.get_setting_defs( APP_SETTING_SCOPE_PROJECT, plugin=plugin ) for s_key in p_settings: ret[ 'settings.{}.{}'.format(plugin.name, s_key) ] = cls.get_app_setting( plugin.name, s_key, project, user, post_safe ) return ret @classmethod def get_all_defaults(cls, scope, post_safe=False): """ Get all default settings for a scope. :param scope: Setting scope (PROJECT, USER or PROJECT_USER) :param post_safe: Whether POST safe values should be returned (bool) :return: Dict """ cls._check_scope(scope) ret = {} app_plugins = get_active_plugins() for plugin in app_plugins: p_settings = cls.get_setting_defs(scope, plugin=plugin) for s_key in p_settings: ret[ 'settings.{}.{}'.format(plugin.name, s_key) ] = cls.get_default_setting(plugin.name, s_key, post_safe) return ret @classmethod def set_app_setting( cls, app_name, setting_name, value, project=None, user=None, validate=True, ): """ Set value of an existing project or user settings. Creates the object if not found. :param app_name: App name (string, must correspond to "name" in app plugin) :param setting_name: Setting name (string) :param value: Value to be set :param project: Project object (can be None) :param user: User object (can be None) :param validate: Validate value (bool, default=True) :return: True if changed, False if not changed :raise: ValueError if validating and value is not accepted for setting type :raise: ValueError if neither project nor user are set :raise: KeyError if setting name is not found in plugin specification """ if not project and not user: raise ValueError('Project and user are both unset') try: setting = AppSetting.objects.get( app_plugin__name=app_name, name=setting_name, project=project, user=user, ) if cls._compare_value(setting, value): return False if validate: cls.validate_setting(setting.type, value) if setting.type == 'JSON': setting.value_json = cls._get_json_value(value) else: setting.value = value setting.save() return True except AppSetting.DoesNotExist: app_plugin = get_app_plugin(app_name) if setting_name not in app_plugin.app_settings: raise KeyError( 'Setting "{}" not found in app plugin "{}"'.format( setting_name, app_name ) ) s_def = app_plugin.app_settings[setting_name] s_type = s_def['type'] s_mod = ( bool(s_def['user_modifiable']) if 'user_modifiable' in s_def else True ) cls._check_scope(s_def['scope']) cls._check_project_and_user(s_def['scope'], project, user) if validate: v = cls._get_json_value(value) if s_type == 'JSON' else value cls.validate_setting(s_type, v) s_vals = { 'app_plugin': app_plugin.get_model(), 'project': project, 'user': user, 'name': setting_name, 'type': s_type, 'user_modifiable': s_mod, } if s_type == 'JSON': s_vals['value_json'] = cls._get_json_value(value) else: s_vals['value'] = value AppSetting.objects.create(**s_vals) return True @classmethod def validate_setting(cls, setting_type, setting_value): """ Validate setting value according to its type. :param setting_type: Setting type :param setting_value: Setting value :raise: ValueError if setting_type or setting_value is invalid """ if setting_type not in APP_SETTING_TYPES: raise ValueError('Invalid setting type "{}"'.format(setting_type)) elif setting_type == 'BOOLEAN': if not isinstance(setting_value, bool): raise ValueError( 'Please enter a valid boolean value ({})'.format( setting_value ) ) elif setting_type == 'INTEGER': if ( not isinstance(setting_value, int) and not str(setting_value).isdigit() ): raise ValueError( 'Please enter a valid integer value ({})'.format( setting_value ) ) elif setting_type == 'JSON': try: json.dumps(setting_value) except TypeError: raise ValueError( 'Please enter valid JSON ({})'.format(setting_value) ) return True @classmethod def get_setting_def(cls, name, plugin=None, app_name=None): """ Return definition for a single app setting, either based on an app name or the plugin object. :param name: Setting name :param plugin: Plugin object extending ProjectAppPluginPoint :param app_name: Name of the app plugin (string) :return: Dict :raise: ValueError if neither app_name or plugin are set or if setting is not found in plugin """ if not plugin and not app_name: raise ValueError('Plugin and app name both unset') elif not plugin: plugin = get_app_plugin(app_name) if not plugin: raise ValueError( 'Plugin not found with app name "{}"'.format(app_name) ) if name not in plugin.app_settings: raise ValueError( 'App setting not found in app "{}" with name "{}"'.format( plugin.name, name ) ) return plugin.app_settings[name] @classmethod def get_setting_defs( cls, scope, plugin=False, app_name=False, user_modifiable=False ): """ Return app setting definitions of a specific scope from a plugin. :param scope: PROJECT, USER or PROJECT_USER :param plugin: project app plugin object extending ProjectAppPluginPoint :param app_name: Name of the app plugin (string) :param user_modifiable: Only return modifiable settings if True (boolean) :return: Dict :raise: ValueError if scope is invalid or if if neither app_name or plugin are set """ if not plugin and not app_name: raise ValueError('Plugin and app name both unset') if not plugin: plugin = get_app_plugin(app_name) if not plugin: raise ValueError( 'Plugin not found with app name "{}"'.format(app_name) ) cls._check_scope(scope) return { k: v for k, v in plugin.app_settings.items() if ( 'scope' in v and v['scope'] == scope and ( not user_modifiable or ( 'user_modifiable' not in v or v['user_modifiable'] is True ) ) ) }

32.938356

80

0.561932

13,846

0.959728

0

13,755

0.953421

0

5,858

0.406044

dd3d84abfc37890e97980406a58c52b188bedbc3

2,835

py

Python

util/2mass_catalog.py

spake/astrometry.net

12c76f4a44fe90a009eeb962f2ae28b0791829b8

[ "BSD-3-Clause" ]

4

2018-02-13T23:11:40.000Z

2021-09-30T16:02:22.000Z

util/2mass_catalog.py

spake/astrometry.net

12c76f4a44fe90a009eeb962f2ae28b0791829b8

[ "BSD-3-Clause" ]

null

util/2mass_catalog.py

spake/astrometry.net

12c76f4a44fe90a009eeb962f2ae28b0791829b8

[ "BSD-3-Clause" ]

1

2019-02-11T06:56:30.000Z

#! /usr/bin/env python # Licensed under a 3-clause BSD style license - see LICENSE from __future__ import print_function import sys from optparse import OptionParser try: import pyfits except ImportError: try: from astropy.io import fits as pyfits except ImportError: raise ImportError("Cannot import either pyfits or astropy.io.fits") from numpy import * from astrometry.util.fits import * from astrometry.util.healpix import * from astrometry.util.starutil_numpy import * def get_2mass_sources(ra, dec, radius=1, basefn=None): twomass_nside = 9 if basefn is None: twomass_pat = '2mass_hp%03i.fits' else: twomass_pat = basefn hps = healpix_rangesearch(ra, dec, radius, twomass_nside) print('2MASS healpixes in range:', hps) allU = None for hp in hps: fn = twomass_pat % hp print('2MASS filename:', fn) U = fits_table(fn) print(len(U), 'sources') I = (degrees_between(ra, dec, U.ra, U.dec) < radius) print('%i 2MASS stars within range.' % sum(I)) U = U[I] if allU is None: allU = U else: allU.append(U) return allU if __name__ == '__main__': parser = OptionParser(usage='%prog [options] <ra> <dec> <output-filename>') parser.add_option('-r', dest='radius', type='float', help='Search radius, in deg (default 1 deg)') parser.add_option('-b', dest='basefn', help='Base filename of 2MASS FITS files (default: 2mass_hp%03i.fits)') parser.add_option('-B', dest='band', help='Band (J, H, or K) to use for cuts') parser.set_defaults(radius=1.0, basefn=None, band='J') (opt, args) = parser.parse_args() if len(args) != 3: parser.print_help() print() print('Got extra arguments:', args) sys.exit(-1) # parse RA,Dec. ra = float(args[0]) dec = float(args[1]) outfn = args[2] band = opt.band.lower() # ugh! opts = {} for k in ['radius', 'basefn']: opts[k] = getattr(opt, k) X = get_2mass_sources(ra, dec, **opts) print('Got %i 2MASS sources.' % len(X)) #print X.about() print('Applying cuts...') I = logical_not(X.minor_planet) print('not minor planet:', sum(I)) qual = X.get(band + '_quality') # work around dumb bug where it's a single-char column rather than a byte. nobrightness = chr(0) I = logical_and(I, (qual != nobrightness)) print('not NO_BRIGHTNESS', sum(I)) print(len(X)) print(len(X.j_cc)) cc = array(X.getcolumn(band + '_cc')) ccnone = chr(0) #print 'cc shape', cc.shape #print cc[:10] #print ccnone I = logical_and(I, (cc == ccnone)) print('CC_NONE', sum(I)) X = X[I] print('%i pass cuts' % len(X)) print('Writing to', outfn) X.write_to(outfn)

28.35

113

0.610229

0

801

0.28254

dd3f4f79ce1d8a927e706c3ca5d870ec9910cd7c

682

py

Python

models/nicknames.py

Tyson-Chicken-Nuggets/me-discord-leaderboard

d0e04c77e4f7a309cbb6315d24bd47929ba4ec54

[ "MIT" ]

4

2018-12-13T04:15:26.000Z

2021-02-15T21:46:59.000Z

models/nicknames.py

Tyson-Chicken-Nuggets/me-discord-leaderboard

d0e04c77e4f7a309cbb6315d24bd47929ba4ec54

[ "MIT" ]

2

2019-05-17T18:47:18.000Z

2020-09-26T01:31:39.000Z

models/nicknames.py

Tyson-Chicken-Nuggets/me-discord-leaderboard

d0e04c77e4f7a309cbb6315d24bd47929ba4ec54

[ "MIT" ]

1

2018-06-08T17:08:29.000Z

from sqlalchemy import Column, String, Integer, ForeignKey from sqlalchemy.orm import relationship from models.base import Base from models.servers import Server from models.users import User class Nickname(Base): __tablename__ = 'nicknames' id = Column(Integer, primary_key=True) user_id = Column(Integer, ForeignKey('users.id'), nullable=False) server_id = Column(Integer, ForeignKey('servers.id'), nullable=False) user = relationship(User) server = relationship(Server) display_name = Column(String) def __init__(self, user, server, display_name): self.user = user self.server = server self.display_name = display_name

31

73

0.727273

487

0.714076

0

33

0.048387

dd3fd65b348e0bcff47a6b9cda24ca0e585cfa0c

6,749

py

Python

pirates/leveleditor/worldData/tortuga_building_int_10.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

3

2021-02-25T06:38:13.000Z

2022-03-22T07:00:15.000Z

pirates/leveleditor/worldData/tortuga_building_int_10.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

null

pirates/leveleditor/worldData/tortuga_building_int_10.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

1

2021-02-25T06:38:17.000Z

# uncompyle6 version 3.2.0 # Python bytecode 2.4 (62061) # Decompiled from: Python 2.7.14 (v2.7.14:84471935ed, Sep 16 2017, 20:19:30) [MSC v.1500 32 bit (Intel)] # Embedded file name: pirates.leveleditor.worldData.tortuga_building_int_10 from pandac.PandaModules import Point3, VBase3, Vec4, Vec3 objectStruct = {'AmbientColors': {}, 'DirectionalColors': {}, 'FogColors': {}, 'FogRanges': {}, 'Objects': {'1156279496.29dzlu0': {'Type': 'Building Interior', 'Name': '', 'AdditionalData': ['interior_shanty_store_tattoo'], 'Instanced': True, 'Objects': {'1169067906.19mike': {'Type': 'Townsperson', 'Category': 'Commoner', 'AnimSet': 'tatoo', 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'Hpr': VBase3(-102.509, 1.642, 0.0), 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '12.0000', 'Pos': Point3(6.941, -8.134, -0.178), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Villager', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None'}, '1179360000.0dchiappe': {'Type': 'Furniture', 'DisableCollision': False, 'Holiday': '', 'Hpr': VBase3(19.675, 0.0, 0.0), 'Pos': Point3(7.057, -8.171, 0.0), 'Scale': VBase3(1.023, 1.023, 1.023), 'VisSize': '', 'Visual': {'Model': 'models/props/stool_shanty'}}, '1179360000.0dchiappe0': {'Type': 'Furniture', 'DisableCollision': False, 'Holiday': '', 'Hpr': VBase3(-29.781, 0.0, 0.0), 'Objects': {}, 'Pos': Point3(7.771, -4.618, -0.007), 'Scale': VBase3(0.965, 0.965, 0.965), 'VisSize': '', 'Visual': {'Model': 'models/props/stool_shanty'}}, '1179360256.0dchiappe': {'Type': 'Townsperson', 'Category': 'Commoner', 'AnimSet': 'tatoo_receive', 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'HelpID': 'NONE', 'Holiday': '', 'Hpr': VBase3(-125.548, -4.22, -0.497), 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '12.0000', 'Pos': Point3(7.165, -4.221, 0.093), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'PORT_ROYAL_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Villager', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None', 'VisSize': ''}, '1201025152.0dxschafe': {'Type': 'Door Locator Node', 'Name': 'door_locator', 'Hpr': VBase3(-180.0, 0.0, 0.0), 'Pos': Point3(0.044, -4.421, 5.0), 'Scale': VBase3(1.0, 1.0, 1.0)}, '1201025280.0dxschafe': {'Type': 'Townsperson', 'Category': 'Tattoo', 'AnimSet': 'primp', 'CustomModel': 'None', 'GhostColor': 'None', 'GhostFX': 0, 'Greeting Animation': '', 'Hpr': VBase3(-163.551, 0.0, 0.0), 'Level': '37', 'Notice Animation 1': '', 'Notice Animation 2': '', 'Patrol Radius': '1.0000', 'Pos': Point3(16.835, 12.638, 0.0), 'PoseAnim': '', 'PoseFrame': '', 'Private Status': 'All', 'PropLeft': 'None', 'PropRight': 'None', 'Respawns': True, 'Scale': VBase3(1.0, 1.0, 1.0), 'ShopID': 'TORTUGA_DEFAULTS', 'Start State': 'Idle', 'StartFrame': '0', 'Team': 'Villager', 'TrailFX': 'None', 'TrailLeft': 'None', 'TrailRight': 'None'}, '1201122985.55dxschafe': {'Type': 'Light - Dynamic', 'Attenuation': '0.005', 'ConeAngle': '15.0000', 'DropOff': '45.5422', 'FlickRate': '0.5000', 'Flickering': False, 'Hpr': VBase3(170.832, -20.397, 4.921), 'Intensity': '1.0602', 'LightType': 'SPOT', 'Pos': Point3(19.411, 22.344, 13.063), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (1, 1, 1, 1), 'Model': 'models/props/light_tool_bulb'}}, '1201124068.83dxschafe': {'Type': 'Light - Dynamic', 'Attenuation': '0.005', 'ConeAngle': '60.0000', 'DropOff': '29.8193', 'FlickRate': '0.5000', 'Flickering': False, 'Hpr': VBase3(-119.397, -38.379, 0.0), 'Intensity': '0.9639', 'LightType': 'SPOT', 'Pos': Point3(1.086, 14.825, 18.821), 'Scale': VBase3(1.0, 1.0, 1.0), 'Visual': {'Color': (1, 1, 1, 1), 'Model': 'models/props/light_tool_bulb'}}}, 'Visual': {'Model': 'models/buildings/interior_shanty_store'}}}, 'Node Links': [], 'Layers': {'Collisions': ['1184008208.59kmuller', '1184016064.62kmuller', '1184013852.84kmuller', '1185822696.06kmuller', '1184006140.32kmuller', '1184002350.98kmuller', '1184007573.29kmuller', '1184021176.59kmuller', '1184005963.59kmuller', '1188324241.31akelts', '1184006537.34kmuller', '1184006605.81kmuller', '1187139568.33kmuller', '1188324186.98akelts', '1184006730.66kmuller', '1184007538.51kmuller', '1184006188.41kmuller', '1184021084.27kmuller', '1185824396.94kmuller', '1185824250.16kmuller', '1185823630.52kmuller', '1185823760.23kmuller', '1185824497.83kmuller', '1185824751.45kmuller', '1187739103.34akelts', '1188323993.34akelts', '1184016538.29kmuller', '1185822200.97kmuller', '1184016225.99kmuller', '1195241421.34akelts', '1195242796.08akelts', '1184020642.13kmuller', '1195237994.63akelts', '1184020756.88kmuller', '1184020833.4kmuller', '1185820992.97kmuller', '1185821053.83kmuller', '1184015068.54kmuller', '1184014935.82kmuller', '1185821432.88kmuller', '1185821701.86kmuller', '1195240137.55akelts', '1195241539.38akelts', '1195238422.3akelts', '1195238473.22akelts', '1185821453.17kmuller', '1184021269.96kmuller', '1185821310.89kmuller', '1185821165.59kmuller', '1185821199.36kmuller', '1185822035.98kmuller', '1184015806.59kmuller', '1185822059.48kmuller', '1185920461.76kmuller', '1194984449.66akelts', '1185824206.22kmuller', '1184003446.23kmuller', '1184003254.85kmuller', '1184003218.74kmuller', '1184002700.44kmuller', '1186705073.11kmuller', '1187658531.86akelts', '1186705214.3kmuller', '1185824927.28kmuller', '1184014204.54kmuller', '1184014152.84kmuller']}, 'ObjectIds': {'1156279496.29dzlu0': '["Objects"]["1156279496.29dzlu0"]', '1169067906.19mike': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1169067906.19mike"]', '1179360000.0dchiappe': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1179360000.0dchiappe"]', '1179360000.0dchiappe0': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1179360000.0dchiappe0"]', '1179360256.0dchiappe': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1179360256.0dchiappe"]', '1201025152.0dxschafe': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1201025152.0dxschafe"]', '1201025280.0dxschafe': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1201025280.0dxschafe"]', '1201122985.55dxschafe': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1201122985.55dxschafe"]', '1201124068.83dxschafe': '["Objects"]["1156279496.29dzlu0"]["Objects"]["1201124068.83dxschafe"]'}} extraInfo = {'camPos': Point3(295.478, -101.859, 7.30613), 'camHpr': VBase3(66.8195, -6.16144, 0), 'focalLength': 1.39999997616, 'skyState': 2, 'fog': 0}

964.142857

6,298

0.676397

0

5,049

0.748111

dd409f1079701595dd303cbae441bb3663ea68de

755

py

Python

hgtools/managers/library.py

jaraco/hgtools

1090d139e5dbdab864da8f1917a9e674331b6f9b

[ "MIT" ]

1

2017-05-17T15:12:29.000Z

hgtools/managers/library.py

jaraco/hgtools

1090d139e5dbdab864da8f1917a9e674331b6f9b

[ "MIT" ]

12

2016-01-01T14:43:44.000Z

2021-10-03T02:13:19.000Z

hgtools/managers/library.py

jaraco/hgtools

1090d139e5dbdab864da8f1917a9e674331b6f9b

[ "MIT" ]

null

import sys from . import base from . import cmd from . import reentry class MercurialInProcManager(cmd.Mercurial, base.RepoManager): """ A RepoManager implemented by invoking the hg command in-process. """ def _invoke(self, *params): """ Run the self.exe command in-process with the supplied params. """ cmd = [self.exe, '-R', self.location] + list(params) with reentry.in_process_context(cmd) as result: sys.modules['mercurial.dispatch'].run() stdout = result.stdio.stdout.getvalue() stderr = result.stdio.stderr.getvalue() if not result.returncode == 0: raise RuntimeError(stderr.strip() or stdout.strip()) return stdout.decode('utf-8')

30.2

69

0.637086

681

0.901987

0

196

0.259603

dd40a6f098a3b0e41331e54d98f742cb251a3af3

1,882

py

Python

app/core/tests/test_models.py

royandri/attendance

cecb7a91b5e048569299ae6dfb796c20051a16a9

[ "MIT" ]

null

app/core/tests/test_models.py

royandri/attendance

cecb7a91b5e048569299ae6dfb796c20051a16a9

[ "MIT" ]

null

app/core/tests/test_models.py

royandri/attendance

cecb7a91b5e048569299ae6dfb796c20051a16a9

[ "MIT" ]

null

from django.test import TestCase from django.contrib.auth import get_user_model from core import models from django.utils import timezone def sample_user(email='test@mail.com', password='testpass'): # Create a sample user return get_user_model().objects.create_user(email, password) class ModelTests(TestCase): def test_create_user_with_email_successfull(self): # Test creatiing a new user with an email is successfull email = 'royandri.dev@gmail.com' password = 'admin' user = get_user_model().objects.create_user( email=email, password=password ) self.assertEqual(user.email, email) self.assertTrue(user.check_password(password)) def test_new_user_email_normalized(self): # Test the email form a new user is normalized email = 'royandri@GMAIL.COM' user = get_user_model().objects.create_user(email, 'admin') self.assertEqual(user.email, email.lower()) def test_new_user_invalid_email(self): # Test creating user with no email raises error with self.assertRaises(ValueError): get_user_model().objects.create_user(None, 'admin') def test_create_new_superuser(self): # Test creating a new superuser user = get_user_model().objects.create_superuser( 'royandri.dev@gmail.com', 'admin' ) self.assertTrue(user.is_superuser) self.assertTrue(user.is_staff) def test_attendance_str(self): # Test the attendance representation attendance = models.Attendance.objects.create( user=sample_user(), time_in=timezone.localtime(timezone.now()).strftime('%H:%M:%S'), date_in=timezone.localtime(timezone.now()).strftime('%Y-%m-%d') ) self.assertEqual(str(attendance), attendance.date_in)

33.607143

76

0.667906

1,586

0.842721

0

379

0.201382

dd41e5e1e67e9d900eb2ff0bece445448ea41207

1,775

py

Python

controllers/__controller.py

VNCompany/vnforum

770aca3a94ad1ed54628d48867c299d83215f75a

[ "Unlicense" ]

null

controllers/__controller.py

VNCompany/vnforum

770aca3a94ad1ed54628d48867c299d83215f75a

[ "Unlicense" ]

null

controllers/__controller.py

VNCompany/vnforum

770aca3a94ad1ed54628d48867c299d83215f75a

[ "Unlicense" ]

null

from flask import redirect, url_for, render_template from flask_login import current_user from components.pagination import html_pagination from db_session import create_session class Controller: __view__ = None __title__ = "Page" view_includes = {} jquery_enabled = True db_session = None def __init__(self): self.view_includes.clear() self.view_includes["css"] = "" self.css("main.css") self.view_includes["js"] = "" self.javascript("jquery.js", "main.js") self.db_session = create_session() @staticmethod def static(path: str): return url_for('static', filename=path) def view(self, **kwargs): if self.__view__ is None: raise AttributeError elif current_user.is_authenticated and current_user.is_banned(): return redirect("/logout") else: return render_template(str(self.__view__).replace(".", "/") + ".html", **kwargs, **self.view_includes, title=self.__title__) def css(self, *names): if "css" not in self.view_includes.keys(): self.view_includes["css"] = "" for name in names: self.view_includes["css"] += f'<link type="text/css" rel="stylesheet" href="' \ f'{self.static("css/" + name)}">\n' def javascript(self, *names): for name in names: self.view_includes["js"] += f'<script type="text/javascript" src="{self.static("js/" + name)}"></script>\n' def pagination(self, max_page, pos: int, link: str): self.view_includes["pagination_string"] = html_pagination(max_page, pos, link)

34.803922

119

0.580845

1,594

0.898028

0

88

0.049577

0

281

0.15831

dd43d5641662aeed07a7ef83b6967c23588c8ac3

371

py

Python

practice/algos/quick_sort/quick_sort.py

markfranciose/cheat_sheet_of_cheat_sheets

d126bbbb499af43098d3938e35df3381833cecac

[ "MIT" ]

null

practice/algos/quick_sort/quick_sort.py

markfranciose/cheat_sheet_of_cheat_sheets

d126bbbb499af43098d3938e35df3381833cecac

[ "MIT" ]

20

2020-07-21T01:52:53.000Z

2022-02-27T09:44:44.000Z

practice/algos/quick_sort/quick_sort.py

markfranciose/drops_of_knowledge

d126bbbb499af43098d3938e35df3381833cecac

[ "MIT" ]

null

def quick_sort(arr): if len(arr) < 2: return arr pivot = arr.pop() left = [] right = [] for num in arr: if num > pivot: right.append(num) else: left.append(num) return quick_sort(left) + [pivot] + quick_sort(right) arr = [1,2,2,1,2,1,5,23,1,91,2,4,1,] print(quick_sort(arr))

18.55

58

0.490566

0

dd442063bf90797178fddb15d68e9d7b4d342147

157

py

Python

Python/texttospeech.py

Rohit01-pro/All_Program_helper

86b75ecc4ecb095f11e46e6f80c660e27dd22f27

[ "MIT" ]

16

2021-10-03T11:15:49.000Z

2021-10-31T04:40:24.000Z

Python/texttospeech.py

Rohit01-pro/All_Program_helper

86b75ecc4ecb095f11e46e6f80c660e27dd22f27

[ "MIT" ]

232

2021-10-02T14:51:43.000Z

2021-11-14T08:23:27.000Z

Python/texttospeech.py

Rohit01-pro/All_Program_helper

86b75ecc4ecb095f11e46e6f80c660e27dd22f27

[ "MIT" ]

166

2021-10-02T13:56:34.000Z

2021-10-31T17:56:34.000Z

from gtts import gTTS import os f=open("1.txt") x=f.read() language='en' audio=gTTS(text=x,lang=language,slow=False) audio.save("1.wav") os.system("1.wav")

15.7

43

0.707006

0

25

0.159236

dd464fa4b37cf124b28327d6a98fc0f0c806f33d

101

py

Python

code/pyFoamSymlinkToFile.py

sosohungry/pyfoam

b19e40a0ef1f41268930122226660414722178e6

[ "MIT" ]

null

code/pyFoamSymlinkToFile.py

sosohungry/pyfoam

b19e40a0ef1f41268930122226660414722178e6

[ "MIT" ]

null

code/pyFoamSymlinkToFile.py

sosohungry/pyfoam

b19e40a0ef1f41268930122226660414722178e6

[ "MIT" ]

null

#! /usr/bin/env python from PyFoam.Applications.SymlinkToFile import SymlinkToFile SymlinkToFile()

16.833333

59

0.811881

0

22

0.217822

dd468535a193a7786f5ac49b546150a18ebcd261

1,172

py

Python

setup.py

themightyoarfish/svcca

23faa374489067c1c76cee44d92663c120603bdc

[ "Apache-2.0" ]

8

2019-01-17T14:20:07.000Z

2021-07-08T12:16:23.000Z

setup.py

themightyoarfish/svcca

23faa374489067c1c76cee44d92663c120603bdc

[ "Apache-2.0" ]

1

2019-01-30T11:44:25.000Z

2019-02-07T15:02:02.000Z

setup.py

themightyoarfish/svcca-gpu

23faa374489067c1c76cee44d92663c120603bdc

[ "Apache-2.0" ]

null

#!/usr/bin/env python from distutils.core import setup import setuptools import os root_dir = os.path.abspath(os.path.dirname(__file__)) with open(f'{root_dir}/README.md') as f: readme = f.read() with open(f'{root_dir}/requirements.txt') as f: requirements = f.read().split() packages = setuptools.find_packages('.', include='svcca.*') setup(name='svcca', version='0.0.1', description='SVCCA on Numpy, Cupy, and PyTorch', long_description=readme, author='Rasmus Diederichsen', author_email='rasmus@peltarion.com', url='https://github.com/themightyoarfish/svcca-gpu', classifiers=['Intended Audience :: Science/Research', 'Topic :: Scientific/Engineering :: Visualization', 'Programming Language :: Python :: 3.6', 'License :: OSI Approved :: Apache License', 'Intended Audience :: Developers', ], keywords='deep-learning pytorch cupy numpy svcca neural-networks machine-learning'.split(), install_requires=requirements, packages=packages, zip_safe=False, # don't install egg, but source )

33.485714

97

0.636519

0

533

0.454778

dd470b99c72201568c8abe1bba1e9f7add60848f

1,679

py

Python

classmark/ui/home_section.py

mdocekal/ClassMark

e6019f9abeb99e9a6b72365a508d5a6dac13c3c7

[ "Unlicense" ]

null

classmark/ui/home_section.py

mdocekal/ClassMark

e6019f9abeb99e9a6b72365a508d5a6dac13c3c7

[ "Unlicense" ]

2

2021-01-18T12:29:18.000Z

2021-01-18T14:33:31.000Z

classmark/ui/home_section.py

windionleaf/ClassMark

e6019f9abeb99e9a6b72365a508d5a6dac13c3c7

[ "Unlicense" ]

null

""" Created on 19. 12. 2018 Module for home section of the application. :author: Martin Dočekal :contact: xdocek09@stud.fit.vubtr.cz """ from .widget_manager import WidgetManager from .section_router import SectionRouter from functools import partial from .models import ListLastExperiments from PySide2.QtCore import Qt class HomeSection(WidgetManager): """ HomeSection manager class. """ TEMPLATE="home" """Corresponding template name.""" def __init__(self, sectionRouter:SectionRouter, parent=None): """ Initializes home section. :param sectionRouter: Router for in app navigation. :type sectionRouter: SectionRouter :param parent: Parent widget :type parent: QWidget """ super().__init__() self._widget=self._loadTemplate(self.TEMPLATE, parent) self._router=sectionRouter #register click events self._widget.toolNewExperiment.clicked.connect(partial(self._router.goExperiment, None)) self._widget.toolLoadExperiment.clicked.connect(self._router.goLoadExperiment) #self._widget.findChild(QToolButton, 'toolNewExperiment') #last experiements self._widget.lastExpList.setModel(ListLastExperiments()) self._widget.lastExpList.doubleClicked.connect(self.lastExperSel) def lastExperSel(self, index): """ Last experiment was selected. :param index: Index. :type index: QModelIndex """ self._router.goExperiment(self._widget.lastExpList.model().data(index, Qt.DisplayRole))

29.45614

96

0.661108

1,339

0.797024

0

676

0.402381

dd4835795e462053f9d98a0abafa853d67dd9bfc

829

py

Python

urls.py

CodeForPhilly/philly_legislative

5774100325b5374a0510674b4a542171fff3fcd3

[ "BSD-Source-Code" ]

2

2017-08-29T22:27:05.000Z

2019-04-27T20:21:31.000Z

urls.py

CodeForPhilly/philly_legislative

5774100325b5374a0510674b4a542171fff3fcd3

[ "BSD-Source-Code" ]

null

urls.py

CodeForPhilly/philly_legislative

5774100325b5374a0510674b4a542171fff3fcd3

[ "BSD-Source-Code" ]

null

from django.conf.urls.defaults import * # Uncomment the next two lines to enable the admin: from django.contrib import admin admin.autodiscover() urlpatterns = patterns('', # Example: #(r'^philly_legislative/', include('philly_legislative.foo.urls')), # Uncomment the admin/doc line below and add 'django.contrib.admindocs' # to INSTALLED_APPS to enable admin documentation: # (r'^admin/doc/', include('django.contrib.admindocs.urls')), # Uncomment the next line to enable the admin: (r'^admin/(.*)', admin.site.root), (r'^subs/$', 'phillyleg.views.index'), (r'^subs/create/$', 'phillyleg.views.create'), (r'^subs/unsubscribe/$', 'phillyleg.views.unsubscribe'), #(r'^subs/(?P<subscription_id>\d+)/$', 'phillyleg.views.edit'), (r'^subs/delete/$', 'phillyleg.views.delete') )

33.16

76

0.671894

0

602

0.726176

dd486d1d0f1328a725ad7af4079cf4b9fc30ab88

2,510

py

Python

irf/scripts/read_corsika_headers.py

fact-project/irf

d82a3d4ae8b9ef15d9f473cdcd01a5f9c92d42a2

[ "MIT" ]

null

irf/scripts/read_corsika_headers.py

fact-project/irf

d82a3d4ae8b9ef15d9f473cdcd01a5f9c92d42a2

[ "MIT" ]

8

2017-04-25T11:19:32.000Z

2019-05-28T07:24:32.000Z

irf/scripts/read_corsika_headers.py

fact-project/irf

d82a3d4ae8b9ef15d9f473cdcd01a5f9c92d42a2

[ "MIT" ]

null

from corsikaio import CorsikaFile from fact.io import to_h5py from multiprocessing import Pool, cpu_count from tqdm import tqdm import os import click import pandas as pd import numpy as np from glob import glob def get_headers(f): with CorsikaFile(f) as cf: run_header, event_headers, run_end = cf.read_headers() return run_header, event_headers, run_end event_columns = [ 'run_number', 'event_number', 'particle_id', 'total_energy', 'starting_altitude', 'first_target_id', 'first_interaction_height', 'momentum_x', 'momentum_y', 'momentum_minus_z', 'zenith', 'azimuth', ] run_header_columns = [ 'run_number', 'date', 'energy_spectrum_slope', 'energy_min', 'energy_max', ] @click.command() @click.argument('outputfile') @click.argument( 'inputdir', nargs=-1, type=click.Path(exists=True, file_okay=False, dir_okay=True), ) def main(outputfile, inputdir): inputfiles = [] for d in inputdir: inputfiles.extend(glob(os.path.join(d, 'cer*'))) for f in inputfiles[:]: if f + '.gz' in inputfiles: inputfiles.remove(f + '.gz') print('Processing', len(inputfiles), 'files') with Pool(cpu_count()) as pool: results = pool.imap_unordered(get_headers, inputfiles) run_headers = [] run_ends = [] for run_header, event_headers, run_end in tqdm(results, total=len(inputfiles)): run_headers.append(run_header) run_ends.append(run_end) df = pd.DataFrame(event_headers[event_columns]) to_h5py(df, outputfile, key='corsika_events', mode='a') print('saving runwise information') runs = pd.DataFrame(np.array(run_headers)[run_header_columns]) # some runs might have failed and thus no run end block for run_end in run_ends: if run_end is not None: dtype = run_end.dtype break else: raise IOError('All run_end blocks are None, all runs failed.') dummy = np.array([(b'RUNE', np.nan, np.nan)], dtype=dtype)[0] run_ends = [r if r is not None else dummy for r in run_ends] run_ends = np.array(run_ends) print('Number of failed runs:', np.count_nonzero(np.isnan(run_ends['n_events']))) runs['n_events'] = run_ends['n_events'] to_h5py(runs, outputfile, key='corsika_runs', mode='a') print('done') if __name__ == '__main__': main()

25.1

89

0.632669

0

1,704

0.678884

0

539

0.214741

dd489e1ae7bc915c79a5ee9217ee84f8b92fa142

3,101

py

Python

tests/test_maker.py

chfsx/pibooth

4049fb748853ff90e53212336ff7d71bba6c1328

[ "MIT" ]

null

tests/test_maker.py

chfsx/pibooth

4049fb748853ff90e53212336ff7d71bba6c1328

[ "MIT" ]

null

tests/test_maker.py

chfsx/pibooth

4049fb748853ff90e53212336ff7d71bba6c1328

[ "MIT" ]

null

# -*- coding: utf-8 -*- import pytest from pibooth.pictures.factory import PilPictureFactory, OpenCvPictureFactory footer_texts = ('This is the main title', 'Footer text 2', 'Footer text 3') footer_fonts = ('Amatic-Bold', 'DancingScript-Regular', 'Roboto-LightItalic') footer_colors = ((10, 0, 0), (0, 50, 0), (0, 50, 50)) def setup_factory(m, fond, overlay=''): m.add_text(footer_texts[0], footer_fonts[0], footer_colors[0], 'left') m.add_text(footer_texts[1], footer_fonts[1], footer_colors[1], 'center') m.add_text(footer_texts[2], footer_fonts[2], footer_colors[2], 'right') m.set_background(fond) if overlay: m.set_overlay(overlay) def test_benchmark_pil_portrait(benchmark, captures_portrait, fond): factory = PilPictureFactory(2400, 3600, *captures_portrait) setup_factory(factory, fond) benchmark(factory.build) def test_benchmark_pil_landscape(benchmark, captures_landscape, fond): factory = PilPictureFactory(3600, 2400, *captures_landscape) setup_factory(factory, fond) benchmark(factory.build) def test_benchmark_cv2_portrait(benchmark, captures_portrait, fond): factory = OpenCvPictureFactory(2400, 3600, *captures_portrait) setup_factory(factory, fond) benchmark(factory.build) def test_benchmark_cv2_landscape(benchmark, captures_landscape, fond): factory = OpenCvPictureFactory(3600, 2400, *captures_landscape) setup_factory(factory, fond) benchmark(factory.build) @pytest.mark.parametrize('captures_nbr', [1, 2, 3, 4]) def test_save_cv2_portrait(captures_nbr, captures_portrait, fond): factory = OpenCvPictureFactory(2400, 3600, *captures_portrait[:captures_nbr]) setup_factory(factory, fond) factory.save("OpenCV-portrait-{}.jpg".format(captures_nbr)) @pytest.mark.parametrize('captures_nbr', [1, 2, 3, 4]) def test_save_cv2_landscape(captures_nbr, captures_landscape, fond): factory = OpenCvPictureFactory(3600, 2400, *captures_landscape[:captures_nbr]) setup_factory(factory, fond) factory.save("OpenCV-landscape-{}.jpg".format(captures_nbr)) @pytest.mark.parametrize('captures_nbr', [1, 2, 3, 4]) def test_save_pil_portrait(captures_nbr, captures_portrait, fond): factory = PilPictureFactory(2400, 3600, *captures_portrait[:captures_nbr]) setup_factory(factory, fond) factory.save("PIL-portrait-{}.jpg".format(captures_nbr)) @pytest.mark.parametrize('captures_nbr', [1, 2, 3, 4]) def test_save_pil_landscape(captures_nbr, captures_landscape, fond): factory = PilPictureFactory(3600, 2400, *captures_landscape[:captures_nbr]) setup_factory(factory, fond) factory.save("PIL-landscape-{}.jpg".format(captures_nbr)) def test_save_pil_overlay(captures_landscape, fond, overlay): factory = PilPictureFactory(3600, 2400, *captures_landscape) setup_factory(factory, fond, overlay) factory.save("PIL-overlay-4.jpg") def test_save_cv2_overlay(captures_landscape, fond, overlay): factory = OpenCvPictureFactory(3600, 2400, *captures_landscape) setup_factory(factory, fond, overlay) factory.save("OpenCV-overlay-4.jpg")

37.817073

82

0.751048

0

1,196

0.385682

0

345

0.111254

dd491d9bbf97708bde610843ff7316857a2a3334

6,452

py

Python

assignment 1/question3/q3.py

Eunoia1729/soft-computing

d7fc155378d1bb0b914a6f660095653e32d2c0b8

[ "Apache-2.0" ]

1

2021-11-14T15:02:35.000Z

assignment 1/question3/q3.py

Eunoia1729/soft-computing

d7fc155378d1bb0b914a6f660095653e32d2c0b8

[ "Apache-2.0" ]

null

assignment 1/question3/q3.py

Eunoia1729/soft-computing

d7fc155378d1bb0b914a6f660095653e32d2c0b8

[ "Apache-2.0" ]

null

"""## Question 3: Scrap Hotel Data The below code is for India and can be extended to other countries by adding an outer loop given in the last part. The below codes takes several minutes to run. """ import requests import pandas as pd from bs4 import BeautifulSoup hotelname_list = [] city_list = [] countries_list = [] rating_list = [] prince_list = [] Amenities_list = [] HotelDescription_list = [] Review1_list = [] Review2_list = [] hotel_name = "" city_name = "" country_name = "" ratingl = "" pricel = "" amenities = "" descriptionl = "" review1l = "" review2l = "" url = 'https://www.goibibo.com/destinations/all-states-in-india/' data = requests.get(url) html = data.text soup = BeautifulSoup(html, 'html.parser') cards = soup.find_all('div', {'class' : 'col-md-4 col-sm-4 col-xs-12 filtr-item posrel'}) state_urls = [] state_names = [] for card in cards : for a in card.find_all('a', href=True): if a.text.rstrip(): state_urls.append(a['href']) state_names.append(a.text.rstrip()) length = len(state_urls) for i in range(length): url = state_urls[i] country_name = 'India' data = requests.get(url) html = data.text soup = BeautifulSoup(html, 'html.parser') places_to_visit = soup.find('div', {'class' : 'place-to-visit-container'}) if(places_to_visit): card = places_to_visit.find('div', {'class' : 'col-md-12'}) city_urls = {} for a in card.find_all('a', href=True): if a['href']: list = a['href'].split('/') city_urls[list[4]] = 'https://www.goibibo.com/hotels/hotels-in-' + list[4] + '-ct/' for city in city_urls: print(f'Extracting for city : {city}') city_name = city url = city_urls[city] response = requests.get(url) data = BeautifulSoup(response.text, 'html.parser') cards_price_data = data.find_all('p', attrs={'class', 'HotelCardstyles__CurrentPrice-sc-1s80tyk-27 czKsrL'}) cards_url_data = data.find_all('div', attrs={'class', 'HotelCardstyles__HotelNameWrapperDiv-sc-1s80tyk-11 hiiHjq'}) hotel_price = {} hotel_url = {} for i in range(0, len(cards_price_data)): hotel_price[cards_url_data[i].text.rstrip()] = cards_price_data[i].text.rstrip() hotel_url[cards_url_data[i].text.rstrip()] = 'https://www.goibibo.com' + cards_url_data[i].find('a', href = True)['href'] for i in range(0, len(cards_price_data)): url = hotel_url[cards_url_data[i].text.rstrip()] data = requests.get(url) html = data.text hotel_name = cards_url_data[i].text.rstrip() pricel = hotel_price[cards_url_data[i].text.rstrip()] # print('Extracting for hotel : ' + cards_url_data[i].text.rstrip()) soup = BeautifulSoup(html, 'html.parser') div = soup.find('div', { 'id': 'root' }) description = div.find('section', {'class' : 'HotelDetailsMain__HotelDetailsContainer-sc-2p7gdu-0 kpmitu'}) descriptiont = description.find('span', {'itemprop' : 'streetAddress'}) if descriptiont: address = descriptiont.text.rstrip().replace(' View on Map', '') descriptionl = address rating = 'Rating not found' ratingdata = description.find('span', {'itemprop' : 'ratingValue'}) #contains rating if ratingdata: rating = ratingdata.text.rstrip() ratingl = rating review1 = 'Review not found' review2 = 'Review not found' reviews = div.find_all('span', {'class' : 'UserReviewstyles__UserReviewTextStyle-sc-1y05l7z-4 dTkBBw'}) if(len(reviews) > 1): review1 = reviews[0].text.rstrip() if(len(reviews) > 3): review2 = reviews[3].text.rstrip() review1l = review1 review2l = review2 amenities_list = [] #contains all the amenities. amenitiesdiv = div.find('div', {'class' : 'Amenitiesstyles__AmenitiesListBlock-sc-10opy4a-4 cMbIgg'}) if amenitiesdiv: for amenity in amenitiesdiv.find_all('span', {'class':'Amenitiesstyles__AmenityItemText-sc-10opy4a-8 iwRmcg'}) : if amenity: amenities_list.append(amenity.text.rstrip()) else: amenities_list.append('Amenity Not Found') amenities = amenities_list hotelname_list.append(hotel_name) city_list.append(city_name) countries_list.append(country_name) rating_list.append(ratingl) prince_list.append(pricel) Amenities_list.append(amenities) HotelDescription_list.append(descriptionl) Review1_list.append(review1l) Review2_list.append(review2l) print(f'Extracted {len(cards_price_data)} hotels at {city} successfully') dict = {'Hotel_Name': hotelname_list, 'City_Name': city_list, 'country_name': countries_list, 'Rating' : rating_list, 'Price/Night' : prince_list, 'Amenities' : Amenities_list, 'Description' : HotelDescription_list, 'Review1' : Review1_list, 'Review2' : Review2_list} df = pd.DataFrame(dict) df.to_csv('hotels.csv') """To extract for all the countries, we need to use the below code in the outer loop""" hotelname_list = [] city_list = [] countries_list = [] rating_list = [] prince_list = [] Amenities_list = [] HotelDescription_list = [] Review1_list = [] Review2_list = [] hotel_name = "" city_name = "" country_name = "" ratingl = "" pricel = "" amenities = "" descriptionl = "" review1l = "" review2l = "" url = 'https://www.goibibo.com/destinations/intl/all-countries/' data = requests.get(url) html = data.text soup = BeautifulSoup(html, 'html.parser') cards = soup.find_all('div', {'class' : 'col-md-4 col-sm-4 col-xs-12 filtr-item posrel'}) country_urls = [] country_names = [] for card in cards : for a in card.find_all('a', href=True): if a['href']: country_urls.append(a['href']) country_names.append(a.text.rstrip()) length = len(country_urls) for i in range(length): url = country_urls[i] country_name = country_names[i] data = requests.get(url) html = data.text soup = BeautifulSoup(html, 'html.parser') places_to_visit = soup.find('div', {'class' : 'place-to-visit-container'}) if(places_to_visit): card = places_to_visit.find('div', {'class' : 'col-md-12'}) city_urls = {} for a in card.find_all('a', href=True): if a['href']: list = a['href'].split('/') city_urls[list[3]] = 'https://www.goibibo.com/hotels/intl-hotels-in-' + list[3] + '-ct/' print(country_name)

36.451977

160

0.653131

0

1,864

0.288903

dd4965798452f29205244dc8f8464e898af885fa

234

py

Python

groundstation/ROV/OCR/SScrop.py

iturov/rov2018

ca1949806d105a2caddf2cf7a1361e2d3f6a1246

[ "MIT" ]

3

2018-01-26T14:00:50.000Z

2018-08-08T06:44:21.000Z

groundstation/ROV/OCR/SScrop.py

iturov/rov2018

ca1949806d105a2caddf2cf7a1361e2d3f6a1246

[ "MIT" ]

null

groundstation/ROV/OCR/SScrop.py

iturov/rov2018

ca1949806d105a2caddf2cf7a1361e2d3f6a1246

[ "MIT" ]

2

2018-08-08T06:44:23.000Z

2020-10-24T11:36:33.000Z

import pyscreenshot as ImageGrab i=0 src_path ="C:\\Users\\Public\\ROV\OCR\\" if __name__ == "__main__": # part of the screen im=ImageGrab.grab(bbox=(200,100,1100,600)) # X1,Y1,X2,Y2 im.save(src_path + 'init.png')

14.625

60

0.645299

0

83

0.354701

dd4ba76a5fa9e5f97446998ac4f6a5e6ee41ec63

3,008

py

Python

tests/http_client/conftest.py

sjaensch/aiobravado

d3f1eb71883b1f24c4b592917890160eb3d3cbcc

[ "BSD-3-Clause" ]

19

2017-11-20T22:47:12.000Z

2021-12-23T15:56:41.000Z

tests/http_client/conftest.py

sjaensch/aiobravado

d3f1eb71883b1f24c4b592917890160eb3d3cbcc

[ "BSD-3-Clause" ]

10

2018-01-11T12:53:01.000Z

2020-01-27T20:05:51.000Z

tests/http_client/conftest.py

sjaensch/aiobravado

d3f1eb71883b1f24c4b592917890160eb3d3cbcc

[ "BSD-3-Clause" ]

4

2017-11-18T12:37:14.000Z

2021-03-19T14:48:13.000Z

# -*- coding: utf-8 -*- import threading import time import bottle import ephemeral_port_reserve import pytest import umsgpack from bravado_core.content_type import APP_JSON from bravado_core.content_type import APP_MSGPACK from six.moves import urllib ROUTE_1_RESPONSE = b'HEY BUDDY' ROUTE_2_RESPONSE = b'BYE BUDDY' API_RESPONSE = {'answer': 42} SWAGGER_SPEC_DICT = { 'swagger': '2.0', 'info': {'version': '1.0.0', 'title': 'Integration tests'}, 'definitions': { 'api_response': { 'properties': { 'answer': { 'type': 'integer' }, }, 'required': ['answer'], 'type': 'object', 'x-model': 'api_response', 'title': 'api_response', } }, 'basePath': '/', 'paths': { '/json': { 'get': { 'operationId': 'get_json', 'tags': ['json'], 'produces': ['application/json'], 'responses': { '200': { 'description': 'HTTP/200', 'schema': {'$ref': '#/definitions/api_response'}, }, }, }, }, '/msgpack': { 'get': { 'produces': ['application/msgpack'], 'responses': { '200': { 'description': 'HTTP/200', 'schema': {'$ref': '#/definitions/api_response'}, } } } } } } @bottle.get('/swagger.json') def swagger_spec(): return SWAGGER_SPEC_DICT @bottle.get('/json') def api_json(): bottle.response.content_type = APP_JSON return API_RESPONSE @bottle.route('/msgpack') def api_msgpack(): bottle.response.content_type = APP_MSGPACK return umsgpack.packb(API_RESPONSE) @bottle.route('/1') def one(): return ROUTE_1_RESPONSE @bottle.route('/2') def two(): return ROUTE_2_RESPONSE @bottle.post('/double') def double(): x = bottle.request.params['number'] return str(int(x) * 2) @bottle.get('/sleep') def sleep_api(): sec_to_sleep = float(bottle.request.GET.get('sec', '1')) time.sleep(sec_to_sleep) return sec_to_sleep def wait_unit_service_starts(url, timeout=10): start = time.time() while time.time() < start + timeout: try: urllib.request.urlopen(url, timeout=2) except urllib.error.HTTPError: return except urllib.error.URLError: time.sleep(0.1) @pytest.yield_fixture(scope='session') def threaded_http_server(): port = ephemeral_port_reserve.reserve() thread = threading.Thread( target=bottle.run, kwargs={'host': 'localhost', 'port': port}, ) thread.daemon = True thread.start() server_address = 'http://localhost:{port}'.format(port=port) wait_unit_service_starts(server_address) yield server_address

24.064

73

0.539894

0

358

0.119016

1,081

0.359375

0

688

0.228723

dd4bd1dde3eae994bf4970c151cbd96f077c070c

1,479

py

Python

test/test_convvae.py

kejiejiang/UnsupervisedDeepLearning-Pytorch

6ea7b7151ae62bf0130b56cc023f2be068aa87f0

[ "MIT" ]

87

2017-11-22T02:59:24.000Z

2022-01-16T13:08:40.000Z

test/test_convvae.py

CauchyLagrange/UnsupervisedDeepLearning-Pytorch

6ea7b7151ae62bf0130b56cc023f2be068aa87f0

[ "MIT" ]

3

2018-04-24T11:46:51.000Z

2020-01-07T00:01:46.000Z

test/test_convvae.py

CauchyLagrange/UnsupervisedDeepLearning-Pytorch

6ea7b7151ae62bf0130b56cc023f2be068aa87f0

[ "MIT" ]

25

2018-03-15T04:02:21.000Z

2021-12-30T09:24:19.000Z

import torch import torch.utils.data from torchvision import datasets, transforms import numpy as np from udlp.autoencoder.convVAE import ConvVAE import argparse parser = argparse.ArgumentParser(description='VAE MNIST Example') parser.add_argument('--lr', type=float, default=0.0001, metavar='N', help='learning rate for training (default: 0.001)') parser.add_argument('--batch-size', type=int, default=128, metavar='N', help='input batch size for training (default: 128)') parser.add_argument('--epochs', type=int, default=10, metavar='N', help='number of epochs to train (default: 10)') parser.add_argument('--save', type=str, default="", metavar='N', help='number of epochs to train (default: 10)') args = parser.parse_args() train_loader = torch.utils.data.DataLoader( datasets.SVHN('./dataset/svhn', split='train', download=True, transform=transforms.ToTensor()), batch_size=args.batch_size, shuffle=True, num_workers=2) test_loader = torch.utils.data.DataLoader( datasets.SVHN('./dataset/svhn', split='test', download=True, transform=transforms.ToTensor()), batch_size=args.batch_size, shuffle=True, num_workers=2) vae = ConvVAE(width=32, height=32, nChannels=3, hidden_size=500, z_dim=100, binary=True, nFilters=64) vae.fit(train_loader, test_loader, lr=args.lr, num_epochs=args.epochs) if args.save!="": torch.save(vae.state_dict(), args.save)

46.21875

98

0.697769

0

291

0.196755

dd4db1c506d212f1e3f132f918bc8f782cebb18b

673

py

Python

SourceCode/Bayes/bayeslearn.py

xuanyuansen/PyMachineLearning

c5b88c4d9aa2f5d59160d0824f7cee8377e7e16e

[ "Apache-2.0" ]

1

2017-01-17T06:19:33.000Z

SourceCode/Bayes/bayeslearn.py

xuanyuansen/PyMachineLearning

c5b88c4d9aa2f5d59160d0824f7cee8377e7e16e

[ "Apache-2.0" ]

null

SourceCode/Bayes/bayeslearn.py

xuanyuansen/PyMachineLearning

c5b88c4d9aa2f5d59160d0824f7cee8377e7e16e

[ "Apache-2.0" ]

null

#coding=utf-8 ''' Created on 2013年9月20日 @author: Wangliaofan ''' import bayes import feedparser from time import * if __name__== '__main__': listOPosts,listClasses = bayes.loadDataSet() print listOPosts,listClasses myVocabList = bayes.createVocabList(listOPosts) print myVocabList trainMat=[] for postinDoc in listOPosts: trainMat.append(bayes.setOfWords2Vec(myVocabList, postinDoc)) print trainMat p0V,p1V,pAb=bayes.trainNB0(trainMat, listClasses) print p0V print p1V print pAb #ny=feedparser.parse('http://newyork.craigslist.org/stp/index.rss') #sleep(5) #print ny['entries'] bayes.spamTest() pass

24.035714

71

0.708767

0

176

0.259205

dd57860debea07d7b1dee00c8d3f246398e5a1ff

573

py

Python

modules/yats/middleware/header.py

PrathameshBolade/yats

93bb5271255120b7131a3bc416e3386428a4d3ec

[ "MIT" ]

54

2015-01-26T07:56:59.000Z

2022-03-10T18:48:05.000Z

modules/yats/middleware/header.py

PrathameshBolade/yats

93bb5271255120b7131a3bc416e3386428a4d3ec

[ "MIT" ]

8

2015-03-15T18:33:39.000Z

2021-12-21T14:23:11.000Z

modules/yats/middleware/header.py

PrathameshBolade/yats

93bb5271255120b7131a3bc416e3386428a4d3ec

[ "MIT" ]

23

2015-02-19T16:55:35.000Z

2022-03-11T19:49:06.000Z

# -*- coding: utf-8 -*- from socket import gethostname def ResponseInjectHeader(get_response): def middleware(request): setattr(request, '_dont_enforce_csrf_checks', True) response = get_response(request) # response['Access-Control-Allow-Origin'] = '*' # response['Access-Control-Allow-Methods'] = 'GET, POST' response['X-ProcessedBy'] = gethostname() response['Cache-Control'] = 'no-cache, must-revalidate' response['Expires'] = 'Sat, 26 Jul 1997 05:00:00 GMT' return response return middleware

30.157895

64

0.649215

0

250

0.4363

dd58051ac5d7683774d3d6e01bb0dea25252af19

1,334

py

Python

handshake_client/sockets.py

naoki-maeda/handshake-client-py

286884b358e15f84965f3c3224cfabd83e1a1406

[ "MIT" ]

3

2020-12-31T08:29:20.000Z

2021-08-14T14:41:22.000Z

handshake_client/sockets.py

naoki-maeda/handshake-client-py

286884b358e15f84965f3c3224cfabd83e1a1406

[ "MIT" ]

null

handshake_client/sockets.py

naoki-maeda/handshake-client-py

286884b358e15f84965f3c3224cfabd83e1a1406

[ "MIT" ]

1

2020-05-25T14:26:33.000Z

import logging import socketio logger = logging.getLogger("handshake.socket") sio = socketio.AsyncClient(logger=logger) async def get_connection( url: str, api_key: str, watch_chain: bool = True, watch_mempool: bool = True, ) -> socketio.AsyncClient: """ see https://hsd-dev.org/guides/events.html """ assert type(url) == str assert type(api_key) == str assert type(watch_chain) == bool assert type(watch_mempool) == bool if sio.connected is False: await sio.connect(url, transports=["websocket"]) await sio.call("auth", api_key) if watch_chain: await sio.call("watch chain") if watch_mempool: await sio.call("watch mempool") return sio @sio.event async def disconnect() -> None: logger.info("closing socket connection") if sio.connected: await sio.disconnect() async def get_wallet_connection( url: str, api_key: str, wallet_id: str = "*", ) -> socketio.AsyncClient: """ see https://hsd-dev.org/guides/events.html """ assert type(url) == str assert type(api_key) == str assert type(wallet_id) == str if sio.connected is False: await sio.connect(url, transports=["websocket"]) await sio.call("auth", api_key) await sio.call("join", wallet_id) return sio

26.68

81

0.642429

0

140

0.104948

1,192

0.893553

232

0.173913

dd583f7d7e613589a62fb063aca89c71b3483ad8

5,768

py

Python

validation_tests/case_studies/towradgi_simulation/catchment_info.py

samcom12/anuga_core

f4378114dbf02d666fe6423de45798add5c42806

[ "Python-2.0", "OLDAP-2.7" ]

136

2015-05-07T05:47:43.000Z

2022-02-16T03:07:40.000Z

validation_tests/case_studies/towradgi_simulation/catchment_info.py

samcom12/anuga_core

f4378114dbf02d666fe6423de45798add5c42806

[ "Python-2.0", "OLDAP-2.7" ]

184

2015-05-03T09:27:54.000Z

2021-12-20T04:22:48.000Z

validation_tests/case_studies/towradgi_simulation/catchment_info.py

samcom12/anuga_core

f4378114dbf02d666fe6423de45798add5c42806

[ "Python-2.0", "OLDAP-2.7" ]

70

2015-03-18T07:35:22.000Z

2021-11-01T07:07:29.000Z

def create_catchment_list(simulation): from os.path import join channel_manning = simulation.args.channel_manning CatchmentList = [ [join('Model', 'Bdy', 'Catchment.csv'), 100.0], [join('Model', 'Bdy', 'FineCatchment.csv'), 36.0], [join('Model', 'Bdy', 'CreekBanks.csv'), 8.0] ] return CatchmentList def create_manning_list(simulation): from os.path import join channel_manning = simulation.args.channel_manning ## IMPORTANT -- The ORDER in ManningList matters: When there is overlap, ## priority regions at BOTTOM ## FIXME: This setup can be done with fewer lines of code! ManningList = [ [ join('Model', 'Mannings', '1.csv'),0.04], #park [ join('Model', 'Mannings', '2.csv'),0.15], [ join('Model', 'Mannings', '3.csv'),0.15], [ join('Model', 'Mannings', '4.csv'),0.04], [ join('Model', 'Mannings', '5.csv'),0.15], [ join('Model', 'Mannings', '6.csv'),0.15], [ join('Model', 'Mannings', '7.csv'),0.15], [ join('Model', 'Mannings', '8.csv'),0.15], [ join('Model', 'Mannings', '9.csv'),0.04], #park [ join('Model', 'Mannings', '10.csv'), 0.15], [ join('Model', 'Mannings', '11.csv'), 0.15], [ join('Model', 'Mannings', '12.csv'), 0.15], [ join('Model', 'Mannings', '13.csv'), 0.04], [ join('Model', 'Mannings', '14.csv'), 0.15], [ join('Model', 'Mannings', '15.csv'), 0.15], [ join('Model', 'Mannings', '16.csv'), 0.15], [ join('Model', 'Mannings', '17.csv'), 0.15], [ join('Model', 'Mannings', '18.csv'), 0.045], [ join('Model', 'Mannings', '18a.csv'), 0.15], [ join('Model', 'Mannings', '18b.csv'), 0.15], [ join('Model', 'Mannings', '18c.csv'), 0.15], [ join('Model', 'Mannings', '18d.csv'), 0.15], [ join('Model', 'Mannings', '18e.csv'), 0.08], #cokeworks site [ join('Model', 'Mannings', '19.csv'), 0.15], [ join('Model', 'Mannings', '20.csv'), 0.15], [ join('Model', 'Mannings', '21.csv'), 0.15], [ join('Model', 'Mannings', '22.csv'), 0.15], [ join('Model', 'Mannings', '23.csv'), 0.15], [ join('Model', 'Mannings', '24.csv'), 0.05], [ join('Model', 'Mannings', '25.csv'), 0.15], [ join('Model', 'Mannings', '26.csv'), 0.15], [ join('Model', 'Mannings', '27.csv'), 0.15], [ join('Model', 'Mannings', '28.csv'), 0.15], [ join('Model', 'Mannings', '29.csv'), 0.15], [ join('Model', 'Mannings', '30.csv'), 0.15], [ join('Model', 'Mannings', '31.csv'), 0.15], [ join('Model', 'Mannings', '32.csv'), 0.15], [ join('Model', 'Mannings', '33.csv'), 0.15], [ join('Model', 'Mannings', '34.csv'), 0.15], [ join('Model', 'Mannings', '35.csv'), 0.15], [ join('Model', 'Mannings', '36.csv'), 0.05], [ join('Model', 'Mannings', '37.csv'), 0.15], [ join('Model', 'Mannings', '38.csv'), 0.15], [ join('Model', 'Mannings', '39.csv'), 0.15], [ join('Model', 'Mannings', '40.csv'), 0.15], [ join('Model', 'Mannings', '41.csv'), 0.15], [ join('Model', 'Mannings', '42.csv'), 0.15], [ join('Model', 'Mannings', '43.csv'), 0.15], [ join('Model', 'Mannings', '44.csv'), 0.15], [ join('Model', 'Mannings', '45.csv'), 0.15], [ join('Model', 'Mannings', '46.csv'), 0.15], [ join('Model', 'Mannings', '47.csv'), 0.15], [ join('Model', 'Mannings', '48.csv'), 0.15], [ join('Model', 'Mannings', '49.csv'), 0.15], [ join('Model', 'Mannings', '50.csv'), 0.15], [ join('Model', 'Mannings', '51.csv'), 0.15], [ join('Model', 'Mannings', '52.csv'), 0.15], [ join('Model', 'Mannings', '53.csv'), 0.15], [ join('Model', 'Mannings', '54.csv'), 0.15], [ join('Model', 'Mannings', '55.csv'), 0.15], [ join('Model', 'Mannings', '56.csv'), 0.15], [ join('Model', 'Mannings', '57.csv'), 0.15], [ join('Model', 'Mannings', '58.csv'), 0.15], [ join('Model', 'Mannings', '59.csv'), 0.08], [ join('Model', 'Mannings', '60.csv'), 0.15], [ join('Model', 'Mannings', '61.csv'), 0.08], [ join('Model', 'Mannings', '62.csv'), 0.15], [ join('Model', 'Mannings', '63.csv'), 0.08], [ join('Model', 'Mannings', '64.csv'), 0.15], [ join('Model', 'Mannings', '65.csv'), 0.15], [ join('Model', 'Mannings', '66.csv'), 0.15], [ join('Model', 'Mannings', '67.csv'), 0.15], [ join('Model', 'Mannings', '68.csv'), 0.15], [ join('Model', 'Mannings', '69.csv'), 0.15], [ join('Model', 'Mannings', '70.csv'), 0.15], [ join('Model', 'Mannings', '71.csv'), 0.05], [ join('Model', 'Mannings', '72.csv'), 0.15], [ join('Model', 'Mannings', '73.csv'), 0.15], [ join('Model', 'Mannings', '74.csv'), 0.15], [ join('Model', 'Mannings', '75.csv'), 0.15], [ join('Model', 'Mannings', '76.csv'), 0.15], [ join('Model', 'Mannings', '77.csv'), 0.07], [ join('Model', 'Mannings', '78.csv'), 0.15], [ join('Model', 'Mannings', '79.csv'), 0.15], [ join('Model', 'Mannings', '80.csv'), 0.15], [ join('Model', 'Mannings', '81.csv'), 0.15], [ join('Model', 'Mannings', '82.csv'), 0.15], [ join('Model', 'Mannings', '83.csv'), 0.15], [ join('Model', 'Mannings', '84.csv'), 0.15], [ join('Model', 'Mannings', '85.csv'), 0.15], [ join('Model', 'Mannings', '86.csv'), 0.15], [ join('Model', 'Mannings', 'Escarpement.csv'), 0.15], [ join('Model', 'Mannings', 'Railway.csv'), 0.04], [ join('Model', 'Creeks', 'creeks.csv'), channel_manning] ] return ManningList

46.516129

76

0.495319

0

2,645

0.458564

dd586c3a691480974c3b96292cc74640fddadda5

869

py

Python

generator01/testing/test_generator01.py

sku899/World_Travel_Language_Wizard

a9e009336e2f53c5fc0f3e40af51f34335645e5f

[ "MIT" ]

null

generator01/testing/test_generator01.py

sku899/World_Travel_Language_Wizard

a9e009336e2f53c5fc0f3e40af51f34335645e5f

[ "MIT" ]

null

generator01/testing/test_generator01.py

sku899/World_Travel_Language_Wizard

a9e009336e2f53c5fc0f3e40af51f34335645e5f

[ "MIT" ]

null

from unittest.mock import patch from flask import url_for, Response, request from flask_testing import TestCase from random import randint from app import app class TestBase(TestCase): def create_app(self): return app class TestResponse(TestBase): def rand_country(self): countries = ['German', 'Spanish', 'French', 'Russian', 'Chinese', 'Portuguese','Hindi','Arabic','Japanese', 'Korean'] response = self.client.get(url_for("random_generator")) self.assertIn(countries[int(response.data)-1], countries) def test_country(self): with patch("requests.get") as g: g.return_value.text = b"1" response = self.client.get(url_for("random_generator")) random_output = ['1','2','3','4','5','6','7','8','9','10'] self.assertIn(response.data.decode('utf-8'), random_output)

34.76

126

0.653625

705

0.811277

0

180

0.207135

dd5b35b49e23eb6c89bb23b5e7b7a0d158afacb3

14,640

py

Python

assets/arguments.py

YuhangSong/Arena-Baselines-Depreciated

78c33994e67aede7565dda3f68f5cebe0d5ee6e6

[ "Apache-2.0" ]

null

assets/arguments.py

YuhangSong/Arena-Baselines-Depreciated

78c33994e67aede7565dda3f68f5cebe0d5ee6e6

[ "Apache-2.0" ]

null

assets/arguments.py

YuhangSong/Arena-Baselines-Depreciated

78c33994e67aede7565dda3f68f5cebe0d5ee6e6

[ "Apache-2.0" ]

null

import argparse import torch import assets.utils as utils def log_args(args, tf_summary): args_dict = args.__dict__ from pytablewriter import MarkdownTableWriter writer = MarkdownTableWriter() writer.table_name = "Configurations (Args)" writer.headers = ["Parameter", "Value"] print('# INFO: [{} start >>>>]'.format(writer.table_name)) writer.value_matrix = [] for key in args_dict.keys(): print('# INFO: [Config/Args][{} : {}]'.format(key, args_dict[key])) writer.value_matrix += [[str(key), str(args_dict[key])]] print('# INFO: [>>>> {} end]'.format(writer.table_name)) args_markdown_str = writer.dumps() tf_summary.add_text(writer.table_name, args_markdown_str) def generate_env_related_args(args, envs): args.obs_shape = envs.observation_space.shape args.action_space = envs.action_space args.num_agents = envs.unwrapped.num_agents if args.population_number == 1: print('# INFO: baseline: self-play') args.learning_agent_ids = [0] elif args.population_number > 1: print('# INFO: baseline: population-based training') args.learning_agent_ids = range(args.num_agents) if args.population_number < args.num_agents: raise Exception( '# ERROR: population_number should be at least the same as num_agents') else: raise Exception('# ERROR: invalid population_number') return args def get_args(): parser = argparse.ArgumentParser(description='RL') '''general args''' parser.add_argument('--mode', type=str, default='train', help='\ [train: standard training]\ [vis_train: visualize training, using one process and full render]\ [pth2nn: convert pytorch .pth checkpoint to .nn checkpoint that can be used in unity editor]\ [eval_population: evaluate population performance]\ [eval_human: evaluate against human player]\ [eval_round: evaluate agent against agent]\ [scaler2fig: convert scalers logged in tensorboardX to fig]\ ') parser.add_argument('--env-name', help='[general][environment to train on]') parser.add_argument('--obs-type', default='visual', help='[general][observation type: visual, ram]') parser.add_argument('--num-env-steps', type=int, default=10e6, help='[general][number of environment steps to train (default: 10e6)]') parser.add_argument('--store-interval', type=int, default=int(60 * 10), help='[general][save interval (in seconds)') parser.add_argument('--log-dir', default='/tmp/gym/', help='[general][directory to save agent logs (default: /tmp/gym)]') parser.add_argument('--log-episode-every-minutes', type=float, default=20.0, help='[general][log episode every x minutes]') parser.add_argument('--seed', type=int, default=1, help='[general][random seed (default: 1)]') parser.add_argument('--cuda-deterministic', action='store_true', default=False, help="[general][sets flags for determinism when using CUDA (potentially slow!)]") parser.add_argument('--no-cuda', action='store_true', default=False, help='[general][disables CUDA training]') parser.add_argument('--num-eval-episodes', type=int, default=10, help='[general][how many episodes to run for one evaluation]') parser.add_argument('--arena-start-index', type=int, default=2394, help='[general][each arena runs on a port, specify the ports to run the arena]') parser.add_argument('--aux', type=str, default='', help='[general][some aux information you may want to record along with this run]') '''brain args''' parser.add_argument('--add-timestep', action='store_true', default=False, help='[brain][if add timestep to observations]') parser.add_argument('--num-frame-stack', type=int, default=4, help='[brain][num of stacked frames per observation]') parser.add_argument('--recurrent-brain', action='store_true', default=False, help='[brain][if use a recurrent policy]') parser.add_argument('--normalize-obs', action='store_true', default=False, help='[brain][if normalize observation with a running mean and variance]') parser.add_argument('--batch-normalize', action='store_true', default=False, help='[brain][if use batch normalize]') parser.add_argument('--normalize-field', action='store_true', default=False, help='[brain][C4NN][if normalize field]') parser.add_argument('--normalize-kernal', action='store_true', default=False, help='[brain][C4NN][if normalize kernal]') parser.add_argument('--normalize-cross-coefficient', action='store_true', default=False, help='[brain][C4NN][if normalize cross coefficient]') parser.add_argument('--geographical-net', action='store_true', default=False, help='[brain][GN][if use geographical network]') '''trainer args''' parser.add_argument('--trainer-id', default='a2c', help='[trainer][trainer to use: a2c | ppo | acktr]') parser.add_argument('--lr', type=float, default=7e-4, help='[trainer][learning rate (default: 7e-4)]') parser.add_argument('--eps', type=float, default=1e-5, help='[trainer][RMSprop optimizer epsilon (default: 1e-5)]') parser.add_argument('--alpha', type=float, default=0.99, help='[trainer][RMSprop optimizer apha (default: 0.99)]') parser.add_argument('--gamma', type=float, default=0.99, help='[trainer][discount factor for rewards (default: 0.99)]') parser.add_argument('--use-gae', action='store_true', default=False, help='[trainer][use generalized advantage estimation]') parser.add_argument('--tau', type=float, default=0.95, help='[trainer][gae parameter (default: 0.95)]') parser.add_argument('--entropy-coef', type=float, default=0.01, help='[trainer][entropy term coefficient (default: 0.01)]') parser.add_argument('--value-loss-coef', type=float, default=0.5, help='[trainer][value loss coefficient (default: 0.5)]') parser.add_argument('--max-grad-norm', type=float, default=0.5, help='[trainer][max norm of gradients (default: 0.5)]') parser.add_argument('--num-processes', type=int, default=16, help='[trainer][how many training CPU processes to use (default: 16)]') parser.add_argument('--num-steps', type=int, default=5, help='[trainer][number of forward steps in A2C (default: 5)]') parser.add_argument('--ppo-epoch', type=int, default=4, help='[trainer][number of ppo epochs (default: 4)]') parser.add_argument('--num-mini-batch', type=int, default=32, help='[trainer][number of batches for ppo (default: 32)]') parser.add_argument('--clip-param', type=float, default=0.2, help='[trainer][ppo clip parameter (default: 0.2)]') parser.add_argument('--use-linear-lr-decay', action='store_true', default=False, help='[trainer][use a linear schedule on the learning rate]') parser.add_argument('--use-linear-clip-decay', action='store_true', default=False, help='[trainer][use a linear schedule on the ppo clipping parameter]') '''multi-agent args''' parser.add_argument('--population-number', type=int, default=1, help='[multi-agent][number of agents in population train]') parser.add_argument('--reload-agents-interval', type=int, default=(60 * 1), help='[multi-agent][interval to reload agents (in seconds)]') parser.add_argument('--reload-playing-agents-principle', type=str, default='OpenAIFive', help='[multi-agent][principle of choosing a agents from historical checkpoints]\ [\ recent(the most recent checkpoint),\ uniform(uniformly sample from historical checkpoint),\ OpenAIFive(0.8 probability to be recent, 0.2 probability to be uniform)\ ]') parser.add_argument('--playing-agents-deterministic', action='store_false', default=True, help='[eval][if playing agent act deterministically]') '''eval args''' parser.add_argument('--population-eval-start', type=int, default=0, help='[eval][population-eval][when do population eval, start from x checkpoint]') parser.add_argument('--population-eval-skip-interval', type=int, default=4, help='[eval][population-eval][when do population eval, skip every x checkpoints]') parser.add_argument('--learning-agents-deterministic', action='store_true', default=False, help='[eval][if learning agent act deterministically]') parser.add_argument('--record-screen', action='store_true', default=False, help='[eval][if record the screen]') parser.add_argument('--human-controled-agent-ids', type=str, default='', help='set the list of agents (specified by its id) that is controlled by human, example: 1,2,4') args = parser.parse_args() args.log_dir = '../results/' if (args.mode in ['vis_train']) or ('eval' in args.mode): print('# WARNING: set num_processes to 1 for eval purpose') args.num_processes = 1 args.num_mini_batch = 1 def add_to_log_dir(key_, value_): args.log_dir = '{}__{}-{}'.format( args.log_dir, key_, value_, ) '''general''' add_to_log_dir('en', args.env_name) add_to_log_dir('ot', args.obs_type) '''brain''' add_to_log_dir('nfs', args.num_frame_stack) add_to_log_dir('rb', args.recurrent_brain) add_to_log_dir('no', args.normalize_obs) add_to_log_dir('bn', args.batch_normalize) add_to_log_dir('nf', args.normalize_field) add_to_log_dir('nk', args.normalize_kernal) add_to_log_dir('ncc', args.normalize_cross_coefficient) add_to_log_dir('gn', args.geographical_net) '''trainer''' add_to_log_dir('ti', args.trainer_id) '''multi-agent settings''' add_to_log_dir('pn', args.population_number) add_to_log_dir('rpap', args.reload_playing_agents_principle) add_to_log_dir('pad', args.playing_agents_deterministic) '''general''' add_to_log_dir('a', args.aux) '''generated args''' if args.obs_type in ['visual']: args.use_visual = True elif args.obs_type in ['ram']: args.use_visual = False else: raise Exception('# ERROR: obs_type is not supported') if args.mode in ['vis_train']: args.is_envs_train_mode = False else: args.is_envs_train_mode = True if 'NoFrameskip' in args.env_name: args.game_class = 'Atari' else: args.game_class = 'Arena' args.cuda = not args.no_cuda and torch.cuda.is_available() args.device = torch.device("cuda:0" if args.cuda else "cpu") args.num_updates = int( args.num_env_steps) // args.num_steps // args.num_processes args.batch_size = args.num_processes * args.num_steps args.mini_batch_size = args.batch_size // args.num_mini_batch if args.trainer_id in ['ppo']: args.use_clipped_value_loss = True args.human_controled_agent_ids = args.human_controled_agent_ids.split(',') _human_controled_agent_ids = [] for id in args.human_controled_agent_ids: try: _human_controled_agent_ids += [ int(id) ] except Exception as e: pass args.human_controled_agent_ids = _human_controled_agent_ids args.num_human_in_loop = len(args.human_controled_agent_ids) args.is_human_in_loop = (args.num_human_in_loop > 0) if args.is_human_in_loop: input('# WARNING: human in loop, controling agent of id: {}'.format( args.human_controled_agent_ids )) args.is_shuffle_agents = False # check configurations if args.num_processes > 1: input('# WARNING: only process 0 is controlled by human') if (args.game_class in ['Arena']) and (args.is_envs_train_mode in [True]): input('# WARNING: Arena env is running in train mode (faster and smaller), could be unsuitable for human in loop') if args.num_human_in_loop > 1: input('# WARNING: for now, only support one human in loop') # init for human in loop import pygame pygame.init() screen = pygame.display.set_mode((200, 150)) pygame.display.set_caption('Control Window') else: args.is_shuffle_agents = True '''check args''' assert args.trainer_id in ['a2c', 'ppo', 'acktr'] if args.recurrent_brain: assert args.trainer_id in ['a2c', 'ppo'], \ 'Recurrent policy is not implemented for ACKTR' assert args.batch_size >= args.num_mini_batch, ( "PPO requires the number of processes ({}) " "* number of steps ({}) = {} " "to be greater than or equal to the number of PPO mini batches ({})." "".format(args.num_processes, args.num_steps, args.num_processes * args.num_steps, args.num_mini_batch)) if args.recurrent_brain: assert args.num_processes >= args.num_mini_batch, ( "PPO requires the number of processes ({}) " "to be greater than or equal to the number of " "PPO mini batches ({}).".format(args.num_processes, args.num_mini_batch)) '''prepare torch''' torch.set_num_threads(1) torch.manual_seed(args.seed) torch.cuda.manual_seed_all(args.seed) if args.cuda and torch.cuda.is_available() and args.cuda_deterministic: torch.backends.cudnn.benchmark = False torch.backends.cudnn.deterministic = True return args

48.476821

126

0.616189

0

5,950

0.406421

dd5c3b4cdcb7e58a2c1873f564ec41c534d2da13

687

py

Python

khtube/download_ffmpeg.py

KodersHub/khtube

b1a8f96b7ff27cbb7eae615e8aee7d27260f80e8

[ "MIT" ]

1

2021-08-09T14:01:12.000Z

khtube/download_ffmpeg.py

KodersHub/khtube

b1a8f96b7ff27cbb7eae615e8aee7d27260f80e8

[ "MIT" ]

null

khtube/download_ffmpeg.py

KodersHub/khtube

b1a8f96b7ff27cbb7eae615e8aee7d27260f80e8

[ "MIT" ]

null

from google_drive_downloader import GoogleDriveDownloader as gdd import sys import os import requests def get_platform(): platforms = { 'linux1' : 'Linux', 'linux2' : 'Linux', 'darwin' : 'OS X', 'win32' : 'Windows' } if sys.platform not in platforms: return sys.platform return platforms[sys.platform] platform = get_platform() if platform == "linux": print("Nothing needs to install") else: print("Installing ffmpeg") gdd.download_file_from_google_drive(file_id='1Q5zbaXonPEUNQmclp1WMIVVodnUuJdKo', dest_path='./ffmpeg.exe', unzip=False)

25.444444

84

0.604076

0

161

0.234352

dd5ce8afa891dc4561f13cf8c918df7e99c18b1f

1,231

py

Python

climbing (1).py

VamsiKrishna1211/Hacker_rank_solutions

a683a36fcc2f011c120eb4d52aa08468deccc820

[ "Apache-2.0" ]

null

climbing (1).py

VamsiKrishna1211/Hacker_rank_solutions

a683a36fcc2f011c120eb4d52aa08468deccc820

[ "Apache-2.0" ]

null

climbing (1).py

VamsiKrishna1211/Hacker_rank_solutions

a683a36fcc2f011c120eb4d52aa08468deccc820

[ "Apache-2.0" ]

null

#!/bin/python3 import math import os import random import re import sys # Complete the climbingLeaderboard function below. def climbingLeaderboard(scores, alice): li=[] lis=[0 for i in range(len(scores))] lis[0]=1 for i in range(1,len(scores)): #print(i) if scores[i]<scores[i-1]: lis[i]=lis[i-1]+1 else: lis[i]=lis[i-1] #print(lis) num=len(scores)-1 for i in range(len(alice)): lis.append(lis[len(lis)-1]+1) scores.append(alice[i]) for k in range(num,-1,-1): if scores[len(scores)-1]>=scores[k]: lis[len(lis)-1]=lis[k] else: break; num=k+1 li.append(lis[len(lis)-1]) scores.pop(len(scores)-1) lis.pop(len(lis)-1) return li if __name__ == '__main__': fptr = open(os.environ['OUTPUT_PATH'], 'w') scores_count = int(input()) scores = list(map(int, input().rstrip().split())) alice_count = int(input()) alice = list(map(int, input().rstrip().split())) result = climbingLeaderboard(scores, alice) fptr.write('\n'.join(map(str, result))) fptr.write('\n') fptr.close()

20.864407

53

0.541024

0

118

0.095857

dd5d2da4c7eb58adfbaff7779a18bcc9d814e736

25,661

py

Python

game_manager/machine_learning/block_controller_train.py

EndoNrak/tetris

0ce4863348d644b401c53e6c9a50cdc6f7430ed1

[ "MIT" ]

1

2022-01-29T15:23:15.000Z

game_manager/machine_learning/block_controller_train.py

EndoNrak/tetris

0ce4863348d644b401c53e6c9a50cdc6f7430ed1

[ "MIT" ]

null

game_manager/machine_learning/block_controller_train.py

EndoNrak/tetris

0ce4863348d644b401c53e6c9a50cdc6f7430ed1

[ "MIT" ]

null

#!/usr/bin/python3 # -*- coding: utf-8 -*- from datetime import datetime import pprint import random import copy import torch import torch.nn as nn from model.deepqnet import DeepQNetwork,DeepQNetwork_v2 import omegaconf from hydra import compose, initialize import os from tensorboardX import SummaryWriter from collections import deque from random import random, sample,randint import numpy as np import subprocess class Block_Controller(object): # init parameter board_backboard = 0 board_data_width = 0 board_data_height = 0 ShapeNone_index = 0 CurrentShape_class = 0 NextShape_class = 0 def __init__(self,load_weight=None): # init parameter self.mode = None # train self.init_train_parameter_flag = False # predict self.init_predict_parameter_flag = False def set_parameter(self,weight=None): cfg = self.yaml_read() os.makedirs(cfg.common.dir,exist_ok=True) self.saved_path = cfg.common.dir + "/" + cfg.common.weight_path os.makedirs(self.saved_path ,exist_ok=True) subprocess.run("cp config/default.yaml %s/"%(cfg.common.dir), shell=True) self.writer = SummaryWriter(cfg.common.dir+"/"+cfg.common.log_path) self.log = cfg.common.dir+"/log.txt" self.log_score = cfg.common.dir+"/score.txt" self.log_reward = cfg.common.dir+"/reward.txt" self.state_dim = cfg.state.dim with open(self.log,"w") as f: print("start...", file=f) with open(self.log_score,"w") as f: print(0, file=f) with open(self.log_reward,"w") as f: print(0, file=f) #=====Set tetris parameter===== self.height = cfg.tetris.board_height self.width = cfg.tetris.board_width self.max_tetrominoes = cfg.tetris.max_tetrominoes #=====load Deep Q Network===== print("model name: %s"%(cfg.model.name)) if cfg.model.name=="DQN": self.model = DeepQNetwork(self.state_dim) self.initial_state = torch.FloatTensor([0 for i in range(self.state_dim)]) self.get_next_func = self.get_next_states self.reward_func = self.step elif cfg.model.name=="DQNv2": self.model = DeepQNetwork_v2() self.initial_state = torch.FloatTensor([[[0 for i in range(10)] for j in range(22)]]) self.get_next_func = self.get_next_states_v2 self.reward_func = self.step_v2 self.reward_weight = cfg.train.reward_weight self.load_weight = cfg.common.load_weight self.double_dqn = cfg.train.double_dqn self.target_net = cfg.train.target_net if self.double_dqn: self.target_net = True if self.target_net: print("set target network...") self.target_model = copy.deepcopy(self.model) self.target_copy_intarval = cfg.train.target_copy_intarval if self.mode=="predict": if not weight==None: print("load ",weight) self.model = torch.load(weight) self.model.eval() else: if not os.path.exists(self.load_weight): print("%s is not existed!!"%(self.load_weight)) exit() #self.model.load_state_dict(torch.load(self.load_weight)) self.model = torch.load(self.load_weight) self.model.eval() if torch.cuda.is_available(): self.model.cuda() #=====Set hyper parameter===== self.batch_size = cfg.train.batch_size self.lr = cfg.train.lr self.replay_memory_size = cfg.train.replay_memory_size self.replay_memory = deque(maxlen=self.replay_memory_size) self.num_decay_epochs = cfg.train.num_decay_epochs self.num_epochs = cfg.train.num_epoch self.initial_epsilon = cfg.train.initial_epsilon self.final_epsilon = cfg.train.final_epsilon self.save_interval = cfg.train.save_interval #=====Set loss function and optimizer===== if cfg.train.optimizer=="Adam" or cfg.train.optimizer=="ADAM": self.optimizer = torch.optim.Adam(self.model.parameters(), lr=self.lr) self.scheduler = None else: self.momentum =cfg.train.lr_momentum self.optimizer = torch.optim.SGD(self.model.parameters(), lr=self.lr, momentum=self.momentum) self.lr_step_size = cfg.train.lr_step_size self.lr_gamma = cfg.train.lr_gamma self.scheduler = torch.optim.lr_scheduler.StepLR(self.optimizer, step_size=self.lr_step_size , gamma=self.lr_gamma) self.criterion = nn.MSELoss() #=====Initialize parameter===== self.epoch = 0 self.score = 0 self.max_score = -99999 self.epoch_reward = 0 self.cleared_lines = 0 self.iter = 0 self.state = self.initial_state self.tetrominoes = 0 self.gamma = cfg.train.gamma self.reward_clipping = cfg.train.reward_clipping self.score_list = cfg.tetris.score_list self.reward_list = cfg.train.reward_list self.penalty = self.reward_list[5] if self.reward_clipping: self.norm_num =max(max(self.reward_list),abs(self.penalty)) self.reward_list =[r/self.norm_num for r in self.reward_list] self.penalty /= self.norm_num self.penalty = min(cfg.train.max_penalty,self.penalty) #=====Prioritized Experience Replay===== self.prioritized_replay = cfg.train.prioritized_replay if self.prioritized_replay: from machine_learning.qlearning import PRIORITIZED_EXPERIENCE_REPLAY as PER self.PER = PER(self.replay_memory_size,gamma=self.gamma) #更新 def update(self): if self.mode=="train": self.score += self.score_list[5] self.replay_memory[-1][1] += self.penalty self.replay_memory[-1][3] = True #store False to done lists. self.epoch_reward += self.penalty if len(self.replay_memory) < self.replay_memory_size / 10: print("================pass================") print("iter: {} ,meory: {}/{} , score: {}, clear line: {}, block: {} ".format(self.iter, len(self.replay_memory),self.replay_memory_size / 10,self.score,self.cleared_lines ,self.tetrominoes )) else: print("================update================") self.epoch += 1 if self.prioritized_replay: batch,replay_batch_index = self.PER.sampling(self.replay_memory,self.batch_size) else: batch = sample(self.replay_memory, min(len(self.replay_memory),self.batch_size)) state_batch, reward_batch, next_state_batch, done_batch = zip(*batch) state_batch = torch.stack(tuple(state for state in state_batch)) reward_batch = torch.from_numpy(np.array(reward_batch, dtype=np.float32)[:, None]) next_state_batch = torch.stack(tuple(state for state in next_state_batch)) done_batch = torch.from_numpy(np.array(done_batch)[:, None]) #max_next_state_batch = torch.stack(tuple(state for state in max_next_state_batch)) q_values = self.model(state_batch) if self.target_net: if self.epoch %self.target_copy_intarval==0 and self.epoch>0: print("target_net update...") self.target_model = torch.load(self.max_weight) #self.target_model = copy.copy(self.model) #self.max_score = -99999 self.target_model.eval() #======predict Q(S_t+1 max_a Q(s_(t+1),a))====== with torch.no_grad(): next_prediction_batch = self.target_model(next_state_batch) else: self.model.eval() with torch.no_grad(): next_prediction_batch = self.model(next_state_batch) self.model.train() y_batch = torch.cat( tuple(reward if done[0] else reward + self.gamma * prediction for done ,reward, prediction in zip(done_batch,reward_batch, next_prediction_batch)))[:, None] self.optimizer.zero_grad() if self.prioritized_replay: loss_weights = self.PER.update_priority(replay_batch_index,reward_batch,q_values,next_prediction_batch) #print(loss_weights *nn.functional.mse_loss(q_values, y_batch)) loss = (loss_weights *self.criterion(q_values, y_batch)).mean() #loss = self.criterion(q_values, y_batch) loss.backward() else: loss = self.criterion(q_values, y_batch) loss.backward() self.optimizer.step() if self.scheduler!=None: self.scheduler.step() log = "Epoch: {} / {}, Score: {}, block: {}, Reward: {:.1f} Cleared lines: {}".format( self.epoch, self.num_epochs, self.score, self.tetrominoes, self.epoch_reward, self.cleared_lines ) print(log) with open(self.log,"a") as f: print(log, file=f) with open(self.log_score,"a") as f: print(self.score, file=f) with open(self.log_reward,"a") as f: print(self.epoch_reward, file=f) self.writer.add_scalar('Train/Score', self.score, self.epoch - 1) self.writer.add_scalar('Train/Reward', self.epoch_reward, self.epoch - 1) self.writer.add_scalar('Train/block', self.tetrominoes, self.epoch - 1) self.writer.add_scalar('Train/clear lines', self.cleared_lines, self.epoch - 1) if self.epoch > self.num_epochs: with open(self.log,"a") as f: print("finish..", file=f) exit() else: self.epoch += 1 log = "Epoch: {} / {}, Score: {}, block: {}, Reward: {:.1f} Cleared lines: {}".format( self.epoch, self.num_epochs, self.score, self.tetrominoes, self.epoch_reward, self.cleared_lines ) pass #パラメータ読み込み def yaml_read(self): initialize(config_path="../../config", job_name="tetris") cfg = compose(config_name="default") return cfg #累積値の初期化 def reset_state(self): if self.score > self.max_score: torch.save(self.model, "{}/tetris_epoch_{}_score{}".format(self.saved_path,self.epoch,self.score)) self.max_score = self.score self.max_weight = "{}/tetris_epoch_{}_score{}".format(self.saved_path,self.epoch,self.score) self.state = self.initial_state self.score = 0 self.cleared_lines = 0 self.epoch_reward = 0 self.tetrominoes = 0 #削除される列を数える def check_cleared_rows(self,board): board_new = np.copy(board) lines = 0 empty_line = np.array([0 for i in range(self.width)]) for y in range(self.height - 1, -1, -1): blockCount = np.sum(board[y]) if blockCount == self.width: lines += 1 board_new = np.delete(board_new,y,0) board_new = np.vstack([empty_line,board_new ]) return lines,board_new #各列毎の高さの差を計算 def get_bumpiness_and_height(self,board): mask = board != 0 invert_heights = np.where(mask.any(axis=0), np.argmax(mask, axis=0), self.height) heights = self.height - invert_heights total_height = np.sum(heights) currs = heights[:-1] nexts = heights[1:] diffs = np.abs(currs - nexts) total_bumpiness = np.sum(diffs) return total_bumpiness, total_height #各列の穴の個数を数える def get_holes(self, board): num_holes = 0 for i in range(self.width): col = board[:,i] row = 0 while row < self.height and col[row] == 0: row += 1 num_holes += len([x for x in col[row + 1:] if x == 0]) return num_holes # def get_state_properties(self, board): lines_cleared, board = self.check_cleared_rows(board) holes = self.get_holes(board) bumpiness, height = self.get_bumpiness_and_height(board) return torch.FloatTensor([lines_cleared, holes, bumpiness, height]) def get_state_properties_v2(self, board): lines_cleared, board = self.check_cleared_rows(board) holes = self.get_holes(board) bumpiness, height = self.get_bumpiness_and_height(board) max_row = self.get_max_height(board) return torch.FloatTensor([lines_cleared, holes, bumpiness, height,max_row]) def get_max_height(self, board): sum_ = np.sum(board,axis=1) row = 0 while row < self.height and sum_[row] ==0: row += 1 return self.height - row #次の状態を取得(2次元用) def get_next_states_v2(self,curr_backboard,piece_id,CurrentShape_class): states = {} if piece_id == 5: # O piece num_rotations = 1 elif piece_id == 1 or piece_id == 6 or piece_id == 7: num_rotations = 2 else: num_rotations = 4 for direction0 in range(num_rotations): x0Min, x0Max = self.getSearchXRange(CurrentShape_class, direction0) for x0 in range(x0Min, x0Max): # get board data, as if dropdown block board = self.getBoard(curr_backboard, CurrentShape_class, direction0, x0) reshape_backboard = self.get_reshape_backboard(board) reshape_backboard = torch.from_numpy(reshape_backboard[np.newaxis,:,:]).float() states[(x0, direction0)] = reshape_backboard return states #次の状態を取得(1次元用) def get_next_states(self,curr_backboard,piece_id,CurrentShape_class): states = {} if piece_id == 5: # O piece num_rotations = 1 elif piece_id == 1 or piece_id == 6 or piece_id == 7: num_rotations = 2 else: num_rotations = 4 for direction0 in range(num_rotations): x0Min, x0Max = self.getSearchXRange(CurrentShape_class, direction0) for x0 in range(x0Min, x0Max): # get board data, as if dropdown block board = self.getBoard(curr_backboard, CurrentShape_class, direction0, x0) board = self.get_reshape_backboard(board) states[(x0, direction0)] = self.get_state_properties(board) return states #ボードを２次元化 def get_reshape_backboard(self,board): board = np.array(board) reshape_board = board.reshape(self.height,self.width) reshape_board = np.where(reshape_board>0,1,0) return reshape_board #報酬を計算(2次元用) def step_v2(self, curr_backboard,action,curr_shape_class): x0, direction0 = action board = self.getBoard(curr_backboard, curr_shape_class, direction0, x0) board = self.get_reshape_backboard(board) bampiness,height = self.get_bumpiness_and_height(board) max_height = self.get_max_height(board) hole_num = self.get_holes(board) lines_cleared, board = self.check_cleared_rows(board) reward = self.reward_list[lines_cleared] reward -= self.reward_weight[0] *bampiness reward -= self.reward_weight[1] * max(0,max_height-(self.height/2)) reward -= self.reward_weight[2] * hole_num self.epoch_reward += reward self.score += self.score_list[lines_cleared] self.cleared_lines += lines_cleared self.tetrominoes += 1 return reward #報酬を計算(1次元用) def step(self, curr_backboard,action,curr_shape_class): x0, direction0 = action board = self.getBoard(curr_backboard, curr_shape_class, direction0, x0) board = self.get_reshape_backboard(board) lines_cleared, board = self.check_cleared_rows(board) reward = self.reward_list[lines_cleared] self.epoch_reward += reward self.score += self.score_list[lines_cleared] self.cleared_lines += lines_cleared self.tetrominoes += 1 return reward def GetNextMove(self, nextMove, GameStatus,weight=None): t1 = datetime.now() self.mode = GameStatus["judge_info"]["mode"] if self.init_train_parameter_flag == False: self.init_train_parameter_flag = True self.set_parameter(weight=weight) self.ind =GameStatus["block_info"]["currentShape"]["index"] curr_backboard = GameStatus["field_info"]["backboard"] # default board definition self.board_data_width = GameStatus["field_info"]["width"] self.board_data_height = GameStatus["field_info"]["height"] curr_shape_class = GameStatus["block_info"]["currentShape"]["class"] next_shape_class= GameStatus["block_info"]["nextShape"]["class"] # next shape info self.ShapeNone_index = GameStatus["debug_info"]["shape_info"]["shapeNone"]["index"] curr_piece_id =GameStatus["block_info"]["currentShape"]["index"] next_piece_id =GameStatus["block_info"]["nextShape"]["index"] reshape_backboard = self.get_reshape_backboard(curr_backboard) #self.state = reshape_backboard next_steps =self.get_next_func(curr_backboard,curr_piece_id,curr_shape_class) if self.mode == "train": # init parameter epsilon = self.final_epsilon + (max(self.num_decay_epochs - self.epoch, 0) * ( self.initial_epsilon - self.final_epsilon) / self.num_decay_epochs) u = random() random_action = u <= epsilon next_actions, next_states = zip(*next_steps.items()) next_states = torch.stack(next_states) if torch.cuda.is_available(): next_states = next_states.cuda() self.model.train() with torch.no_grad(): predictions = self.model(next_states)[:, 0] if random_action: index = randint(0, len(next_steps) - 1) else: index = torch.argmax(predictions).item() next_state = next_states[index, :] action = next_actions[index] reward = self.reward_func(curr_backboard,action,curr_shape_class) done = False #game over flag #======predict max_a Q(s_(t+1),a)====== #if use double dqn, predicted by main model if self.double_dqn: next_backboard = self.getBoard(curr_backboard, curr_shape_class, action[1], action[0]) next２_steps =self.get_next_func(next_backboard,next_piece_id,next_shape_class) next2_actions, next2_states = zip(*next２_steps.items()) next2_states = torch.stack(next2_states) if torch.cuda.is_available(): next2_states = next2_states.cuda() self.model.train() with torch.no_grad(): next_predictions = self.model(next2_states)[:, 0] next_index = torch.argmax(next_predictions).item() next2_state = next2_states[next_index, :] #if use target net, predicted by target model elif self.target_net: next_backboard = self.getBoard(curr_backboard, curr_shape_class, action[1], action[0]) next２_steps =self.get_next_func(next_backboard,next_piece_id,next_shape_class) next2_actions, next2_states = zip(*next２_steps.items()) next2_states = torch.stack(next2_states) if torch.cuda.is_available(): next2_states = next2_states.cuda() self.target_model.train() with torch.no_grad(): next_predictions = self.target_model(next2_states)[:, 0] next_index = torch.argmax(next_predictions).item() next2_state = next2_states[next_index, :] #if not use target net,predicted by main model else: next_backboard = self.getBoard(curr_backboard, curr_shape_class, action[1], action[0]) next２_steps =self.get_next_func(next_backboard,next_piece_id,next_shape_class) next2_actions, next2_states = zip(*next２_steps.items()) next2_states = torch.stack(next2_states) if torch.cuda.is_available(): next2_states = next2_states.cuda() self.model.train() with torch.no_grad(): next_predictions = self.model(next2_states)[:, 0] epsilon = self.final_epsilon + (max(self.num_decay_epochs - self.epoch, 0) * ( self.initial_epsilon - self.final_epsilon) / self.num_decay_epochs) u = random() random_action = u <= epsilon if random_action: next_index = randint(0, len(next2_steps) - 1) else: next_index = torch.argmax(next_predictions).item() next2_state = next2_states[next_index, :] #======================================= self.replay_memory.append([next_state, reward, next2_state,done]) if self.prioritized_replay: self.PER.store() #self.replay_memory.append([self.state, reward, next_state,done]) nextMove["strategy"]["direction"] = action[1] nextMove["strategy"]["x"] = action[0] nextMove["strategy"]["y_operation"] = 1 nextMove["strategy"]["y_moveblocknum"] = 1 self.state = next_state elif self.mode == "predict": self.model.eval() next_actions, next_states = zip(*next_steps.items()) next_states = torch.stack(next_states) predictions = self.model(next_states)[:, 0] index = torch.argmax(predictions).item() action = next_actions[index] nextMove["strategy"]["direction"] = action[1] nextMove["strategy"]["x"] = action[0] nextMove["strategy"]["y_operation"] = 1 nextMove["strategy"]["y_moveblocknum"] = 1 return nextMove def getSearchXRange(self, Shape_class, direction): # # get x range from shape direction. # minX, maxX, _, _ = Shape_class.getBoundingOffsets(direction) # get shape x offsets[minX,maxX] as relative value. xMin = -1 * minX xMax = self.board_data_width - maxX return xMin, xMax def getShapeCoordArray(self, Shape_class, direction, x, y): # # get coordinate array by given shape. # coordArray = Shape_class.getCoords(direction, x, y) # get array from shape direction, x, y. return coordArray def getBoard(self, board_backboard, Shape_class, direction, x): # # get new board. # # copy backboard data to make new board. # if not, original backboard data will be updated later. board = copy.deepcopy(board_backboard) _board = self.dropDown(board, Shape_class, direction, x) return _board def dropDown(self, board, Shape_class, direction, x): # # internal function of getBoard. # -- drop down the shape on the board. # dy = self.board_data_height - 1 coordArray = self.getShapeCoordArray(Shape_class, direction, x, 0) # update dy for _x, _y in coordArray: _yy = 0 while _yy + _y < self.board_data_height and (_yy + _y < 0 or board[(_y + _yy) * self.board_data_width + _x] == self.ShapeNone_index): _yy += 1 _yy -= 1 if _yy < dy: dy = _yy # get new board _board = self.dropDownWithDy(board, Shape_class, direction, x, dy) return _board def dropDownWithDy(self, board, Shape_class, direction, x, dy): # # internal function of dropDown. # _board = board coordArray = self.getShapeCoordArray(Shape_class, direction, x, 0) for _x, _y in coordArray: _board[(_y + dy) * self.board_data_width + _x] = Shape_class.shape return _board BLOCK_CONTROLLER_TRAIN = Block_Controller()

41.929739

145

0.575465

25,395

0.981981

0

3,018

0.116701

dd5da8896dcd0d60de2ab7a1e52c8732ee3a4ea8

405

py

Python

erp/migrations/0123_auto_20210513_1720.py

bzg/acceslibre

52c7c6990dc132da71a92e856d65f4a983c3b15a

[ "MIT" ]

8

2020-07-23T08:17:28.000Z

2022-03-09T22:31:36.000Z

erp/migrations/0123_auto_20210513_1720.py

bzg/acceslibre

52c7c6990dc132da71a92e856d65f4a983c3b15a

[ "MIT" ]

37

2020-07-01T08:47:33.000Z

2022-02-03T19:50:58.000Z

erp/migrations/0123_auto_20210513_1720.py

bzg/acceslibre

52c7c6990dc132da71a92e856d65f4a983c3b15a

[ "MIT" ]

4

2021-04-08T10:57:18.000Z

2022-01-31T13:16:31.000Z

# Generated by Django 3.2 on 2021-05-13 15:20 import uuid from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ("erp", "0122_auto_20210513_1720"), ] operations = [ migrations.AlterField( model_name="erp", name="uuid", field=models.UUIDField(default=uuid.uuid4, unique=True), ), ]

20.25

68

0.604938

302

0.745679

0

86

0.212346

dd5e767c2f0f3137c08350fa015010541f736e41

290

py

Python

migrations/824-auto-exclude-regions.py

muffinresearch/zamboni

045a6f07c775b99672af6d9857d295ed02fe5dd9

[ "BSD-3-Clause" ]

null

migrations/824-auto-exclude-regions.py

muffinresearch/zamboni

045a6f07c775b99672af6d9857d295ed02fe5dd9

[ "BSD-3-Clause" ]

null

migrations/824-auto-exclude-regions.py

muffinresearch/zamboni

045a6f07c775b99672af6d9857d295ed02fe5dd9

[ "BSD-3-Clause" ]

null

from mkt.constants import regions from mkt.developers.cron import exclude_new_region def run(): exclude_new_region([ regions.CR, regions.EC, regions.FR, regions.GT, regions.IT, regions.NI, regions.PA, regions.SV, ])

18.125

50

0.586207

0

dd5ec06ae412be00165dc082fa38f505f00c44d7

2,959

py

Python

qa/rpc-tests/checkpoint-load.py

ericramos1980/energi

aadc44f714f9d52433ab3595a9f33a61433c60c9

[ "MIT" ]

2

2021-12-28T21:47:07.000Z

2022-02-09T21:04:29.000Z

qa/rpc-tests/checkpoint-load.py

reddragon34/energi

4cc6c426d9d4b6b9053912de9b2197eba071201e

[ "MIT" ]

null

qa/rpc-tests/checkpoint-load.py

reddragon34/energi

4cc6c426d9d4b6b9053912de9b2197eba071201e

[ "MIT" ]

1

2019-10-07T19:17:55.000Z

#!/usr/bin/env python3 # Copyright (c) 2019 The Energi Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. from test_framework.test_framework import BitcoinTestFramework from test_framework.util import * import logging class CheckpointLoadTest(BitcoinTestFramework): def __init__(self): super().__init__() self.setup_clean_chain = True self.num_nodes = 3 node_args = ["-keypool=10", "-debug=stake", "-debug=net", "-addcheckpoint=10:abcdef01234456789", "-checkpoints=0"] self.extra_args = [node_args, node_args, node_args] self.node_args = node_args def setup_network(self, split=False): self.nodes = start_nodes(self.num_nodes, self.options.tmpdir, self.extra_args) connect_nodes_bi(self.nodes, 0, 1) connect_nodes_bi(self.nodes, 0, 2) connect_nodes_bi(self.nodes, 1, 2) self.is_network_split=False def run_test(self): self.sync_all() logging.info("Generating initial blockchain") self.nodes[0].generate(20) self.sync_all() assert_equal(self.nodes[0].getinfo()['blocks'], 20) logging.info("Enabling checkpoints") stop_nodes(self.nodes) node_args = list(self.node_args) node_args[-1] = "-checkpoints=1" self.extra_args[0] = node_args; self.setup_network() sync_blocks(self.nodes[1:]) assert_equal(self.nodes[0].getinfo()['blocks'], 9) assert_equal(self.nodes[1].getinfo()['blocks'], 20) assert_equal(self.nodes[2].getinfo()['blocks'], 20) logging.info("Adding more blocks") self.nodes[1].generate(3) sync_blocks(self.nodes[1:]) assert_equal(self.nodes[0].getinfo()['blocks'], 9) assert_equal(self.nodes[1].getinfo()['blocks'], 23) assert_equal(self.nodes[2].getinfo()['blocks'], 23) logging.info("Adding more block on alt chain") stop_nodes(self.nodes) self.extra_args[0] = self.node_args self.nodes = start_nodes(1, self.options.tmpdir, self.extra_args) self.nodes[0].generate(30) stop_nodes(self.nodes) self.setup_network() self.sync_all() assert_equal(self.nodes[0].getinfo()['blocks'], 39) assert_equal(self.nodes[1].getinfo()['blocks'], 39) assert_equal(self.nodes[2].getinfo()['blocks'], 39) logging.info("Restart to check no issues appear") stop_nodes(self.nodes) self.nodes = start_nodes(self.num_nodes, self.options.tmpdir, self.extra_args) self.sync_all() assert_equal(self.nodes[0].getinfo()['blocks'], 39) assert_equal(self.nodes[1].getinfo()['blocks'], 39) assert_equal(self.nodes[2].getinfo()['blocks'], 39) if __name__ == '__main__': CheckpointLoadTest().main()

37.935897

86

0.639743

2,576

0.870564

0

566

0.191281

dd5ffb792de44849ba525e817187b550fe21e9d9

648

py

Python

python/setup.py

tcolgate/gracetests

552c8113b0554d49cf146e6d7cfd573c8b4cbf8f

[ "MIT" ]

2

2019-07-30T16:50:20.000Z

2021-11-26T22:46:29.000Z

python/setup.py

tcolgate/gracetests

552c8113b0554d49cf146e6d7cfd573c8b4cbf8f

[ "MIT" ]

null

python/setup.py

tcolgate/gracetests

552c8113b0554d49cf146e6d7cfd573c8b4cbf8f

[ "MIT" ]

1

2019-07-30T16:50:54.000Z

import os from setuptools import find_packages, setup DIR = os.path.dirname(os.path.abspath(__file__)) setup( name='graceful', version='1.2.0', description='test of graceful shutdown', url='https://github.com/qubitdigital/graceful/python', author='Infra', author_email='infra@qubit.com', license='All rights reserved.', packages=find_packages(), install_requires=[ 'sanic==0.7.0', 'ujson==1.35', 'python-dotenv==0.8.2', 'cchardet==2.1.1', ], zip_safe=False, entry_points={ 'console_scripts': [ 'graceful=graceful.server:main', ] } )

22.344828

58

0.603395

0

253

0.390432

dd61bcf996578639e6980380d244d98682bbdae6

812

py

Python

src/mylog/logger.py

JoeBuzh/Pm_Composition_Quallity_Control

676c508a37c9a3774bf223e7abd53db04df771d7

[ "MIT" ]

1

2020-07-23T04:13:02.000Z

src/runtime/mylog/mylog.py

JoeBuzh/DeepWeather

2677edc16d9865ec98401aaf121aaabd24974aaf

[ "MIT" ]

null

src/runtime/mylog/mylog.py

JoeBuzh/DeepWeather

2677edc16d9865ec98401aaf121aaabd24974aaf

[ "MIT" ]

null

# -*- coding: utf-8 -*- import os import logging import logging.handlers import time def init_logger(log_file): dir_path = os.path.dirname(log_file) try: if not os.path.exists(dir_path): os.makedirs(dir_path) except Exception as e: pass handler = logging.handlers.RotatingFileHandler(log_file, maxBytes=30 * 1024 * 1024, backupCount=10) fmt = '%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s' formatter = logging.Formatter(fmt) handler.setFormatter(formatter) #logger_instance = logging.getLogger('logs') logger_instance = logging.getLogger(log_file.split("/")[-1]) logger_instance.addHandler(handler) #logger_instance.setLevel(logging.DEBUG) logger_instance.setLevel(logging.INFO) return logger_instance

31.230769

103

0.699507

0

179

0.220443

dd61ede10dd7a8e91db98cff1eeb2bd9cfadde8d

637

py

Python

convert_assets.py

michaelgold/usdzconvert

f4e6e552db4e27a3e088649f19f6bd61977501c1

[ "MIT" ]

null

convert_assets.py

michaelgold/usdzconvert

f4e6e552db4e27a3e088649f19f6bd61977501c1

[ "MIT" ]

null

convert_assets.py

michaelgold/usdzconvert

f4e6e552db4e27a3e088649f19f6bd61977501c1

[ "MIT" ]

null

import glob import os import subprocess import shutil source_file_list = glob.glob("../source/assets/*.glb") for input_file_name in source_file_list: base_file_name = os.path.split(input_file_name)[1] output_file_name = "../dist/assets/{}.usdz".format(os.path.splitext(base_file_name)[0]) print(output_file_name) subprocess.call("python run_usd.py usdzconvert/usdzconvert {} {}".format(input_file_name, output_file_name), shell=True) for glb_file in source_file_list: print(glb_file) destination = "../dist/assets/{}".format(os.path.split(glb_file)[1]) shutil.move(glb_file, destination)

35.388889

125

0.726845

0

116

0.182104

dd6374321202c04d2e14fb1f005b96daccd1a28b

36

py

Python

csv_json/__init__.py

Rerice/Csv_json_converter

54bf0f839d8fff203c1cf96812b96af915449fef

[ "MIT" ]

3

2021-06-02T15:32:45.000Z

2021-12-13T10:12:25.000Z

csv_json/__init__.py

Rerice/Csv_json_converter

54bf0f839d8fff203c1cf96812b96af915449fef

[ "MIT" ]

null

csv_json/__init__.py

Rerice/Csv_json_converter

54bf0f839d8fff203c1cf96812b96af915449fef

[ "MIT" ]

2

2021-06-02T15:30:42.000Z

2021-06-02T17:28:41.000Z

from csv_json.csv_json_conv import *

36

0.861111

0

dd63b219f3cb356db869fd14f9d34da5dd98361a

463

py

Python

Constants.py

HKN-UCSD/HIIT

63f726398ca63c92e82a8052a05608a8537e6e87

[ "MIT" ]

null

Constants.py

HKN-UCSD/HIIT

63f726398ca63c92e82a8052a05608a8537e6e87

[ "MIT" ]

null

Constants.py

HKN-UCSD/HIIT

63f726398ca63c92e82a8052a05608a8537e6e87

[ "MIT" ]

1

2019-08-18T19:23:44.000Z

COLUMNS = ['First Name', 'Last Name', 'Class Standing', 'Cum GPA', 'Major Code', 'Dept', 'Email'] DEPTS = ['CSE', 'ECE', 'MATH', 'BENG'] CLASS_STANDINGS = ['SO', 'JR', 'SR'] DEPTS_MAJORS = dict() # bit of a faux-pas... DEPTS_MAJORS['CSE'] = ['CS25', 'CS26', 'CS27', 'CS28'] DEPTS_MAJORS['ECE'] = ['EC26', 'EC27', 'EC28'] DEPTS_MAJORS['MATH'] = ['MA30'] DEPTS_MAJORS['BENG'] = ['BE25', 'BE26', 'BE27', 'BE28'] CLASS_QUANTILE = {'SO': 0.8, 'JR': 0.75, 'SR': 0.667}

51.444444

97

0.580994

0

235

0.507559

dd6453c36feaa6225a2781434ed2cbc21f1477e2

258

py

Python

app/admin.py

Syilun/aiot-django-dashboard-postgresql

3aa607bd623006a4c99a97da304985eb908741c8

[ "MIT" ]

null

app/admin.py

Syilun/aiot-django-dashboard-postgresql

3aa607bd623006a4c99a97da304985eb908741c8

[ "MIT" ]

null

app/admin.py

Syilun/aiot-django-dashboard-postgresql

3aa607bd623006a4c99a97da304985eb908741c8

[ "MIT" ]

null

# -*- encoding: utf-8 -*- """ License: MIT Copyright (c) 2019 - present AppSeed.us """ from django.contrib import admin from .models import PERSON from .models import FACE # Register your models here. admin.site.register(PERSON) admin.site.register(FACE)

17.2

39

0.728682

0

113

0.437984

dd646968d684c4605ba1ae783d48a3452bbee81d

933

py

Python

Python/python-tutorials/networking/tcp_server.py

zhongyangynag/code-study

5410929554107a384a09d899c6fa3d16ed383d2b

[ "MIT" ]

null

Python/python-tutorials/networking/tcp_server.py

zhongyangynag/code-study

5410929554107a384a09d899c6fa3d16ed383d2b

[ "MIT" ]

null

Python/python-tutorials/networking/tcp_server.py

zhongyangynag/code-study

5410929554107a384a09d899c6fa3d16ed383d2b

[ "MIT" ]

null

#!/usr/bin/env python import re import sys import socket import SocketServer import struct import fcntl import sys def getip(ethname): if ethname=="": ethname="eth0" try: s=socket.socket(socket.AF_INET, socket.SOCK_DGRAM) ip=socket.inet_ntoa(fcntl.ioctl(s.fileno(), 0X8915, struct.pack('256s', ethname[:15]))[20:24]) except: ip="" return ip class MyHandler(SocketServer.BaseRequestHandler): def setup(self): self.allow_reuse_address=True return SocketServer.BaseRequestHandler.setup(self) def finish(self): return SocketServer.BaseRequestHandler.finish(self) def handle(self): #size=self.request.recv(4) buf=self.request.recv(2048).replace('\n','') print "Recv from %s: %s" %(self.client_address[0], buf) # send back message self.request.sendall(buf) if __name__=='__main__': # start server server = SocketServer.ThreadingTCPServer( (getip("eth0"),44444), MyHandler) server.serve_forever()

21.697674

96

0.736334

431

0.461951

0

136

0.145766

dd64daf0644c28687a4705d4e8b356d44e031ab4

2,190

py

Python

tests/test_examples.py

timgates42/goless

3c8742fa0f94d0a365840aae404da4e8eaed9d71

[ "Apache-2.0" ]

266

2015-01-03T04:18:48.000Z

2022-02-16T03:08:38.000Z

tests/test_examples.py

timgates42/goless

3c8742fa0f94d0a365840aae404da4e8eaed9d71

[ "Apache-2.0" ]

19

2015-03-06T11:04:53.000Z

2021-06-09T15:08:57.000Z

tests/test_examples.py

timgates42/goless

3c8742fa0f94d0a365840aae404da4e8eaed9d71

[ "Apache-2.0" ]

20

2015-01-03T03:45:08.000Z

2022-03-05T06:05:32.000Z

""" Idiomatic Go examples converted to use goless. """ from __future__ import print_function import time from . import BaseTests import goless class Examples(BaseTests): def test_select(self): # https://gobyexample.com/select c1 = goless.chan() c2 = goless.chan() def func1(): time.sleep(.1) c1.send('one') goless.go(func1) def func2(): time.sleep(.2) c2.send('two') goless.go(func2) # We don't print since we run this as a test. callbacks = [] for i in range(2): _, val = goless.select([goless.rcase(c1), goless.rcase(c2)]) callbacks.append(val) self.assertEqual(callbacks, ['one', 'two']) def test_range_over_channels(self): # https://gobyexample.com/range-over-channels queue = goless.chan(2) queue.send('one') queue.send('two') queue.close() elements = [elem for elem in queue] self.assertEqual(elements, ['one', 'two']) def test_worker_pool(self): # https://gobyexample.com/worker-pools jobs_done = [] # noinspection PyShadowingNames,PyShadowingBuiltins def worker(id, jobs, results): for j in jobs: jobs_done.append('w %s j %s' % (id, j)) time.sleep(.01) results.send(j * 2) jobs = goless.chan(100) results = goless.chan(100) for w in range(1, 4): goless.go(lambda: worker(w, jobs, results)) for j in range(1, 10): jobs.send(j) jobs.close() for a in range(1, 10): results.recv() self.assertEqual(len(jobs_done), 9) def test_case_switch(self): chan = goless.chan() cases = [goless.rcase(chan), goless.scase(chan, 1), goless.dcase()] chosen, value = goless.select(cases) if chosen is cases[0]: print('Received %s' % value) elif chosen is cases[1]: assert value is None print('Sent.') else: assert chosen is cases[2], chosen print('Default...')

26.071429

75

0.541096

2,042

0.93242

0

348

0.158904

dd67590d08d500fd8ab7568abbfffa79b1097a7f

3,211

py

Python

Utils/Messaging.py

philshams/FC_analysis

cabe2385d5061d206a21b230605bfce9e39ec7f2

[ "MIT" ]

null

Utils/Messaging.py

philshams/FC_analysis

cabe2385d5061d206a21b230605bfce9e39ec7f2

[ "MIT" ]

null

Utils/Messaging.py

philshams/FC_analysis

cabe2385d5061d206a21b230605bfce9e39ec7f2

[ "MIT" ]

null

from slackclient import SlackClient import requests import os from Config import slack_env_var_token, slack_username """ These functions take care of sending slack messages and emails """ def slack_chat_messenger(message): # NEVER LEAVE THE TOKEN IN YOUR CODE ON GITHUB, EVERYBODY WOULD HAVE ACCESS TO THE CHANNEL! slack_token = os.environ.get(slack_env_var_token) slack_client = SlackClient(slack_token) api_call = slack_client.api_call("im.list") user_slack_id = slack_username # You should either know the user_slack_id to send a direct msg to the user if api_call.get('ok'): for im in api_call.get("ims"): if im.get("user") == user_slack_id: im_channel = im.get("id") slack_client.api_call("chat.postMessage", channel=im_channel, text=message, as_user=False) def slack_chat_attachments(filepath): slack_chat_messenger('Trying to send you {}'.format(filepath)) slack_token = os.environ.get(slack_env_var_token) my_file = { 'file': (filepath+'.png', open(filepath+'.png', 'rb'), 'image/png', { 'Expires': '0' }) } payload = { "filename":filepath+'.png', "token":slack_token, "channels": ['@Fede'], "media": my_file } r = requests.post("https://slack.com/api/files.upload", params=payload, files=my_file) print(r.text) def upload_file( filepath ): """Upload file to channel Note: URLs can be constructed from: https://api.slack.com/methods/files.upload/test """ slack_chat_messenger('Trying to send you {}'.format(filepath)) slack_token = os.environ.get(slack_env_var_token) data = {} data['token'] = slack_token data['file'] = filepath data['filename'] = filepath data['channels'] = [slack_username] data['display_as_bot'] = True filepath = data['file'] files = { 'content': (filepath, open(filepath, 'rb'), 'image/png', { 'Expires': '0' }) } data['media'] = files response = requests.post( url='https://slack.com/api/files.upload', data=data, headers={'Accept': 'application/json'}, files=files) print(response.text) def send_email_attachments(filename, filepath): import smtplib from email.mime.image import MIMEImage from email.mime.text import MIMEText from email.mime.multipart import MIMEMultipart # Create the container (outer) email message. msg = MIMEMultipart() msg['Subject'] = filename # me == the sender's email address # family = the list of all recipients' email addresses msg['From'] = 'federicopython@gmail.com' msg['To'] = 'federicoclaudi@gmail.com' body = "Analysis results" msg.attach(MIMEText(body, 'plain')) with open(filepath+'.png', 'rb') as fp: img = MIMEImage(fp.read()) msg.attach(img) # Send the email via our own SMTP server. server = smtplib.SMTP('smtp.gmail.com:587') server.ehlo() server.starttls() server.login('federicopython@gmail.com', '') server.sendmail('federicopython@gmail.com', 'federicoclaudi@gmail.com', msg.as_string()) server.quit()

28.669643

106

0.646528

0

1,135

0.353472

dd67b0be318886c07c1697a2ac8415ae63718592

71,403

py

Python

venv/lib/python3.8/site-packages/spaceone/api/monitoring/v1/alert_pb2.py

choonho/plugin-prometheus-mon-webhook

afa7d65d12715fd0480fb4f92a9c62da2d6128e0

[ "Apache-2.0" ]

null

venv/lib/python3.8/site-packages/spaceone/api/monitoring/v1/alert_pb2.py

choonho/plugin-prometheus-mon-webhook

afa7d65d12715fd0480fb4f92a9c62da2d6128e0

[ "Apache-2.0" ]

null

venv/lib/python3.8/site-packages/spaceone/api/monitoring/v1/alert_pb2.py

choonho/plugin-prometheus-mon-webhook

afa7d65d12715fd0480fb4f92a9c62da2d6128e0

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: spaceone/api/monitoring/v1/alert.proto """Generated protocol buffer code.""" from google.protobuf.internal import enum_type_wrapper from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2 from google.protobuf import struct_pb2 as google_dot_protobuf_dot_struct__pb2 from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2 from spaceone.api.core.v1 import query_pb2 as spaceone_dot_api_dot_core_dot_v1_dot_query__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='spaceone/api/monitoring/v1/alert.proto', package='spaceone.api.monitoring.v1', syntax='proto3', serialized_options=None, create_key=_descriptor._internal_create_key, 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, dependencies=[google_dot_protobuf_dot_empty__pb2.DESCRIPTOR,google_dot_protobuf_dot_struct__pb2.DESCRIPTOR,google_dot_api_dot_annotations__pb2.DESCRIPTOR,spaceone_dot_api_dot_core_dot_v1_dot_query__pb2.DESCRIPTOR,]) _ALERTURGENCY = _descriptor.EnumDescriptor( name='AlertUrgency', full_name='spaceone.api.monitoring.v1.AlertUrgency', filename=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, values=[ _descriptor.EnumValueDescriptor( name='ALERT_URGENCY_NONE', index=0, number=0, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='HIGH', index=1, number=1, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='LOW', index=2, number=2, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), ], containing_type=None, serialized_options=None, serialized_start=2763, serialized_end=2820, ) _sym_db.RegisterEnumDescriptor(_ALERTURGENCY) AlertUrgency = enum_type_wrapper.EnumTypeWrapper(_ALERTURGENCY) _ALERTSTATE = _descriptor.EnumDescriptor( name='AlertState', full_name='spaceone.api.monitoring.v1.AlertState', filename=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, values=[ _descriptor.EnumValueDescriptor( name='ALERT_STATE_NONE', index=0, number=0, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='TRIGGERED', index=1, number=1, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='ACKNOWLEDGED', index=2, number=2, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='RESOLVED', index=3, number=3, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='ERROR', index=4, number=4, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), ], containing_type=None, serialized_options=None, serialized_start=2822, serialized_end=2914, ) _sym_db.RegisterEnumDescriptor(_ALERTSTATE) AlertState = enum_type_wrapper.EnumTypeWrapper(_ALERTSTATE) ALERT_URGENCY_NONE = 0 HIGH = 1 LOW = 2 ALERT_STATE_NONE = 0 TRIGGERED = 1 ACKNOWLEDGED = 2 RESOLVED = 3 ERROR = 4 _ALERTRESOURCE = _descriptor.Descriptor( name='AlertResource', full_name='spaceone.api.monitoring.v1.AlertResource', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='resource_id', full_name='spaceone.api.monitoring.v1.AlertResource.resource_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resource_type', full_name='spaceone.api.monitoring.v1.AlertResource.resource_type', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='spaceone.api.monitoring.v1.AlertResource.name', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=193, serialized_end=266, ) _ALERTRESPONDER = _descriptor.Descriptor( name='AlertResponder', full_name='spaceone.api.monitoring.v1.AlertResponder', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='resource_type', full_name='spaceone.api.monitoring.v1.AlertResponder.resource_type', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resource_id', full_name='spaceone.api.monitoring.v1.AlertResponder.resource_id', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=268, serialized_end=328, ) _CREATEALERTREQUEST = _descriptor.Descriptor( name='CreateAlertRequest', full_name='spaceone.api.monitoring.v1.CreateAlertRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='title', full_name='spaceone.api.monitoring.v1.CreateAlertRequest.title', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='description', full_name='spaceone.api.monitoring.v1.CreateAlertRequest.description', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='assignee', full_name='spaceone.api.monitoring.v1.CreateAlertRequest.assignee', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='urgency', full_name='spaceone.api.monitoring.v1.CreateAlertRequest.urgency', index=3, number=4, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='project_id', full_name='spaceone.api.monitoring.v1.CreateAlertRequest.project_id', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.CreateAlertRequest.domain_id', index=5, number=11, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=331, serialized_end=503, ) _UPDATEALERTREQUEST = _descriptor.Descriptor( name='UpdateAlertRequest', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.alert_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='title', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.title', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='state', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.state', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='status_message', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.status_message', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='description', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.description', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='assignee', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.assignee', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='urgency', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.urgency', index=6, number=7, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='project_id', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.project_id', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='reset_status_message', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.reset_status_message', index=8, number=11, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='reset_description', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.reset_description', index=9, number=12, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='reset_assignee', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.reset_assignee', index=10, number=13, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.UpdateAlertRequest.domain_id', index=11, number=21, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=506, serialized_end=816, ) _UPDATEALERTSTATEREQUEST = _descriptor.Descriptor( name='UpdateAlertStateRequest', full_name='spaceone.api.monitoring.v1.UpdateAlertStateRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.UpdateAlertStateRequest.alert_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='access_key', full_name='spaceone.api.monitoring.v1.UpdateAlertStateRequest.access_key', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='state', full_name='spaceone.api.monitoring.v1.UpdateAlertStateRequest.state', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=818, serialized_end=896, ) _MERGEALERTREQUEST = _descriptor.Descriptor( name='MergeAlertRequest', full_name='spaceone.api.monitoring.v1.MergeAlertRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alerts', full_name='spaceone.api.monitoring.v1.MergeAlertRequest.alerts', index=0, number=1, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='merge_to', full_name='spaceone.api.monitoring.v1.MergeAlertRequest.merge_to', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.MergeAlertRequest.domain_id', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=898, serialized_end=970, ) _SNOOZEALERTREQUEST = _descriptor.Descriptor( name='SnoozeAlertRequest', full_name='spaceone.api.monitoring.v1.SnoozeAlertRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.SnoozeAlertRequest.alert_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='end_time', full_name='spaceone.api.monitoring.v1.SnoozeAlertRequest.end_time', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.SnoozeAlertRequest.domain_id', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=972, serialized_end=1047, ) _ALERTRESPONDERREQUEST = _descriptor.Descriptor( name='AlertResponderRequest', full_name='spaceone.api.monitoring.v1.AlertResponderRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.AlertResponderRequest.alert_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resource_type', full_name='spaceone.api.monitoring.v1.AlertResponderRequest.resource_type', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resource_id', full_name='spaceone.api.monitoring.v1.AlertResponderRequest.resource_id', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.AlertResponderRequest.domain_id', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1049, serialized_end=1153, ) _ALERTPROJECTDEPENDENCYREQUEST = _descriptor.Descriptor( name='AlertProjectDependencyRequest', full_name='spaceone.api.monitoring.v1.AlertProjectDependencyRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.AlertProjectDependencyRequest.alert_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='project_id', full_name='spaceone.api.monitoring.v1.AlertProjectDependencyRequest.project_id', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.AlertProjectDependencyRequest.domain_id', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1155, serialized_end=1243, ) _ALERTREQUEST = _descriptor.Descriptor( name='AlertRequest', full_name='spaceone.api.monitoring.v1.AlertRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.AlertRequest.alert_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.AlertRequest.domain_id', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1245, serialized_end=1296, ) _GETALERTREQUEST = _descriptor.Descriptor( name='GetAlertRequest', full_name='spaceone.api.monitoring.v1.GetAlertRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.GetAlertRequest.alert_id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.GetAlertRequest.domain_id', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='only', full_name='spaceone.api.monitoring.v1.GetAlertRequest.only', index=2, number=3, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1298, serialized_end=1366, ) _ALERTQUERY = _descriptor.Descriptor( name='AlertQuery', full_name='spaceone.api.monitoring.v1.AlertQuery', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='query', full_name='spaceone.api.monitoring.v1.AlertQuery.query', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='alert_number', full_name='spaceone.api.monitoring.v1.AlertQuery.alert_number', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.AlertQuery.alert_id', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='title', full_name='spaceone.api.monitoring.v1.AlertQuery.title', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='state', full_name='spaceone.api.monitoring.v1.AlertQuery.state', index=4, number=5, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='assignee', full_name='spaceone.api.monitoring.v1.AlertQuery.assignee', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='urgency', full_name='spaceone.api.monitoring.v1.AlertQuery.urgency', index=6, number=7, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='severity', full_name='spaceone.api.monitoring.v1.AlertQuery.severity', index=7, number=8, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='is_snoozed', full_name='spaceone.api.monitoring.v1.AlertQuery.is_snoozed', index=8, number=9, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resource_id', full_name='spaceone.api.monitoring.v1.AlertQuery.resource_id', index=9, number=10, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='triggered_by', full_name='spaceone.api.monitoring.v1.AlertQuery.triggered_by', index=10, number=11, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='webhook_id', full_name='spaceone.api.monitoring.v1.AlertQuery.webhook_id', index=11, number=12, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='escalation_policy_id', full_name='spaceone.api.monitoring.v1.AlertQuery.escalation_policy_id', index=12, number=13, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='project_id', full_name='spaceone.api.monitoring.v1.AlertQuery.project_id', index=13, number=14, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.AlertQuery.domain_id', index=14, number=15, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1369, serialized_end=1782, ) _ALERTINFO = _descriptor.Descriptor( name='AlertInfo', full_name='spaceone.api.monitoring.v1.AlertInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='alert_number', full_name='spaceone.api.monitoring.v1.AlertInfo.alert_number', index=0, number=1, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='alert_id', full_name='spaceone.api.monitoring.v1.AlertInfo.alert_id', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='title', full_name='spaceone.api.monitoring.v1.AlertInfo.title', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='state', full_name='spaceone.api.monitoring.v1.AlertInfo.state', index=3, number=4, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='status_message', full_name='spaceone.api.monitoring.v1.AlertInfo.status_message', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='description', full_name='spaceone.api.monitoring.v1.AlertInfo.description', index=5, number=6, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='assignee', full_name='spaceone.api.monitoring.v1.AlertInfo.assignee', index=6, number=7, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='urgency', full_name='spaceone.api.monitoring.v1.AlertInfo.urgency', index=7, number=8, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='severity', full_name='spaceone.api.monitoring.v1.AlertInfo.severity', index=8, number=9, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='rule', full_name='spaceone.api.monitoring.v1.AlertInfo.rule', index=9, number=10, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resource', full_name='spaceone.api.monitoring.v1.AlertInfo.resource', index=10, number=11, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='additional_info', full_name='spaceone.api.monitoring.v1.AlertInfo.additional_info', index=11, number=12, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='is_snoozed', full_name='spaceone.api.monitoring.v1.AlertInfo.is_snoozed', index=12, number=13, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='snoozed_end_time', full_name='spaceone.api.monitoring.v1.AlertInfo.snoozed_end_time', index=13, number=14, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='escalation_step', full_name='spaceone.api.monitoring.v1.AlertInfo.escalation_step', index=14, number=15, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='escalation_ttl', full_name='spaceone.api.monitoring.v1.AlertInfo.escalation_ttl', index=15, number=16, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='responders', full_name='spaceone.api.monitoring.v1.AlertInfo.responders', index=16, number=17, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='project_dependencies', full_name='spaceone.api.monitoring.v1.AlertInfo.project_dependencies', index=17, number=18, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='triggered_by', full_name='spaceone.api.monitoring.v1.AlertInfo.triggered_by', index=18, number=21, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='webhook_id', full_name='spaceone.api.monitoring.v1.AlertInfo.webhook_id', index=19, number=22, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='escalation_policy_id', full_name='spaceone.api.monitoring.v1.AlertInfo.escalation_policy_id', index=20, number=23, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='project_id', full_name='spaceone.api.monitoring.v1.AlertInfo.project_id', index=21, number=24, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.AlertInfo.domain_id', index=22, number=25, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='created_at', full_name='spaceone.api.monitoring.v1.AlertInfo.created_at', index=23, number=31, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='updated_at', full_name='spaceone.api.monitoring.v1.AlertInfo.updated_at', index=24, number=32, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='acknowledged_at', full_name='spaceone.api.monitoring.v1.AlertInfo.acknowledged_at', index=25, number=33, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resolved_at', full_name='spaceone.api.monitoring.v1.AlertInfo.resolved_at', index=26, number=34, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='escalated_at', full_name='spaceone.api.monitoring.v1.AlertInfo.escalated_at', index=27, number=35, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1785, serialized_end=2579, ) _ALERTSINFO = _descriptor.Descriptor( name='AlertsInfo', full_name='spaceone.api.monitoring.v1.AlertsInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='results', full_name='spaceone.api.monitoring.v1.AlertsInfo.results', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='total_count', full_name='spaceone.api.monitoring.v1.AlertsInfo.total_count', index=1, number=2, type=5, cpp_type=1, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2581, serialized_end=2670, ) _ALERTSTATQUERY = _descriptor.Descriptor( name='AlertStatQuery', full_name='spaceone.api.monitoring.v1.AlertStatQuery', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='query', full_name='spaceone.api.monitoring.v1.AlertStatQuery.query', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='domain_id', full_name='spaceone.api.monitoring.v1.AlertStatQuery.domain_id', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2672, serialized_end=2761, ) _CREATEALERTREQUEST.fields_by_name['urgency'].enum_type = _ALERTURGENCY _UPDATEALERTREQUEST.fields_by_name['urgency'].enum_type = _ALERTURGENCY _ALERTQUERY.fields_by_name['query'].message_type = spaceone_dot_api_dot_core_dot_v1_dot_query__pb2._QUERY _ALERTQUERY.fields_by_name['state'].enum_type = _ALERTSTATE _ALERTQUERY.fields_by_name['urgency'].enum_type = _ALERTURGENCY _ALERTINFO.fields_by_name['state'].enum_type = _ALERTSTATE _ALERTINFO.fields_by_name['urgency'].enum_type = _ALERTURGENCY _ALERTINFO.fields_by_name['resource'].message_type = _ALERTRESOURCE _ALERTINFO.fields_by_name['additional_info'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT _ALERTINFO.fields_by_name['responders'].message_type = _ALERTRESPONDER _ALERTSINFO.fields_by_name['results'].message_type = _ALERTINFO _ALERTSTATQUERY.fields_by_name['query'].message_type = spaceone_dot_api_dot_core_dot_v1_dot_query__pb2._STATISTICSQUERY DESCRIPTOR.message_types_by_name['AlertResource'] = _ALERTRESOURCE DESCRIPTOR.message_types_by_name['AlertResponder'] = _ALERTRESPONDER DESCRIPTOR.message_types_by_name['CreateAlertRequest'] = _CREATEALERTREQUEST DESCRIPTOR.message_types_by_name['UpdateAlertRequest'] = _UPDATEALERTREQUEST DESCRIPTOR.message_types_by_name['UpdateAlertStateRequest'] = _UPDATEALERTSTATEREQUEST DESCRIPTOR.message_types_by_name['MergeAlertRequest'] = _MERGEALERTREQUEST DESCRIPTOR.message_types_by_name['SnoozeAlertRequest'] = _SNOOZEALERTREQUEST DESCRIPTOR.message_types_by_name['AlertResponderRequest'] = _ALERTRESPONDERREQUEST DESCRIPTOR.message_types_by_name['AlertProjectDependencyRequest'] = _ALERTPROJECTDEPENDENCYREQUEST DESCRIPTOR.message_types_by_name['AlertRequest'] = _ALERTREQUEST DESCRIPTOR.message_types_by_name['GetAlertRequest'] = _GETALERTREQUEST DESCRIPTOR.message_types_by_name['AlertQuery'] = _ALERTQUERY DESCRIPTOR.message_types_by_name['AlertInfo'] = _ALERTINFO DESCRIPTOR.message_types_by_name['AlertsInfo'] = _ALERTSINFO DESCRIPTOR.message_types_by_name['AlertStatQuery'] = _ALERTSTATQUERY DESCRIPTOR.enum_types_by_name['AlertUrgency'] = _ALERTURGENCY DESCRIPTOR.enum_types_by_name['AlertState'] = _ALERTSTATE _sym_db.RegisterFileDescriptor(DESCRIPTOR) AlertResource = _reflection.GeneratedProtocolMessageType('AlertResource', (_message.Message,), { 'DESCRIPTOR' : _ALERTRESOURCE, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertResource) }) _sym_db.RegisterMessage(AlertResource) AlertResponder = _reflection.GeneratedProtocolMessageType('AlertResponder', (_message.Message,), { 'DESCRIPTOR' : _ALERTRESPONDER, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertResponder) }) _sym_db.RegisterMessage(AlertResponder) CreateAlertRequest = _reflection.GeneratedProtocolMessageType('CreateAlertRequest', (_message.Message,), { 'DESCRIPTOR' : _CREATEALERTREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.CreateAlertRequest) }) _sym_db.RegisterMessage(CreateAlertRequest) UpdateAlertRequest = _reflection.GeneratedProtocolMessageType('UpdateAlertRequest', (_message.Message,), { 'DESCRIPTOR' : _UPDATEALERTREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.UpdateAlertRequest) }) _sym_db.RegisterMessage(UpdateAlertRequest) UpdateAlertStateRequest = _reflection.GeneratedProtocolMessageType('UpdateAlertStateRequest', (_message.Message,), { 'DESCRIPTOR' : _UPDATEALERTSTATEREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.UpdateAlertStateRequest) }) _sym_db.RegisterMessage(UpdateAlertStateRequest) MergeAlertRequest = _reflection.GeneratedProtocolMessageType('MergeAlertRequest', (_message.Message,), { 'DESCRIPTOR' : _MERGEALERTREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.MergeAlertRequest) }) _sym_db.RegisterMessage(MergeAlertRequest) SnoozeAlertRequest = _reflection.GeneratedProtocolMessageType('SnoozeAlertRequest', (_message.Message,), { 'DESCRIPTOR' : _SNOOZEALERTREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.SnoozeAlertRequest) }) _sym_db.RegisterMessage(SnoozeAlertRequest) AlertResponderRequest = _reflection.GeneratedProtocolMessageType('AlertResponderRequest', (_message.Message,), { 'DESCRIPTOR' : _ALERTRESPONDERREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertResponderRequest) }) _sym_db.RegisterMessage(AlertResponderRequest) AlertProjectDependencyRequest = _reflection.GeneratedProtocolMessageType('AlertProjectDependencyRequest', (_message.Message,), { 'DESCRIPTOR' : _ALERTPROJECTDEPENDENCYREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertProjectDependencyRequest) }) _sym_db.RegisterMessage(AlertProjectDependencyRequest) AlertRequest = _reflection.GeneratedProtocolMessageType('AlertRequest', (_message.Message,), { 'DESCRIPTOR' : _ALERTREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertRequest) }) _sym_db.RegisterMessage(AlertRequest) GetAlertRequest = _reflection.GeneratedProtocolMessageType('GetAlertRequest', (_message.Message,), { 'DESCRIPTOR' : _GETALERTREQUEST, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.GetAlertRequest) }) _sym_db.RegisterMessage(GetAlertRequest) AlertQuery = _reflection.GeneratedProtocolMessageType('AlertQuery', (_message.Message,), { 'DESCRIPTOR' : _ALERTQUERY, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertQuery) }) _sym_db.RegisterMessage(AlertQuery) AlertInfo = _reflection.GeneratedProtocolMessageType('AlertInfo', (_message.Message,), { 'DESCRIPTOR' : _ALERTINFO, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertInfo) }) _sym_db.RegisterMessage(AlertInfo) AlertsInfo = _reflection.GeneratedProtocolMessageType('AlertsInfo', (_message.Message,), { 'DESCRIPTOR' : _ALERTSINFO, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertsInfo) }) _sym_db.RegisterMessage(AlertsInfo) AlertStatQuery = _reflection.GeneratedProtocolMessageType('AlertStatQuery', (_message.Message,), { 'DESCRIPTOR' : _ALERTSTATQUERY, '__module__' : 'spaceone.api.monitoring.v1.alert_pb2' # @@protoc_insertion_point(class_scope:spaceone.api.monitoring.v1.AlertStatQuery) }) _sym_db.RegisterMessage(AlertStatQuery) _ALERT = _descriptor.ServiceDescriptor( name='Alert', full_name='spaceone.api.monitoring.v1.Alert', file=DESCRIPTOR, index=0, serialized_options=None, create_key=_descriptor._internal_create_key, serialized_start=2917, serialized_end=4867, methods=[ _descriptor.MethodDescriptor( name='create', full_name='spaceone.api.monitoring.v1.Alert.create', index=0, containing_service=None, input_type=_CREATEALERTREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002\027\"\025/monitoring/v1/alerts', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='update', full_name='spaceone.api.monitoring.v1.Alert.update', index=1, containing_service=None, input_type=_UPDATEALERTREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002!\032\037/monitoring/v1/alert/{alert_id}', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='update_state', full_name='spaceone.api.monitoring.v1.Alert.update_state', index=2, containing_service=None, input_type=_UPDATEALERTSTATEREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\0026\"4/monitoring/v1/alert/{alert_id}/{access_key}/{state}', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='merge', full_name='spaceone.api.monitoring.v1.Alert.merge', index=3, containing_service=None, input_type=_MERGEALERTREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002\035\"\033/monitoring/v1/alerts/merge', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='snooze', full_name='spaceone.api.monitoring.v1.Alert.snooze', index=4, containing_service=None, input_type=_SNOOZEALERTREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002(\"&/monitoring/v1/alert/{alert_id}/snooze', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='add_responder', full_name='spaceone.api.monitoring.v1.Alert.add_responder', index=5, containing_service=None, input_type=_ALERTRESPONDERREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002,\"*/monitoring/v1/alert/{alert_id}/responders', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='remove_responder', full_name='spaceone.api.monitoring.v1.Alert.remove_responder', index=6, containing_service=None, input_type=_ALERTRESPONDERREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002,**/monitoring/v1/alert/{alert_id}/responders', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='add_project_dependency', full_name='spaceone.api.monitoring.v1.Alert.add_project_dependency', index=7, containing_service=None, input_type=_ALERTPROJECTDEPENDENCYREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\0026\"4/monitoring/v1/alert/{alert_id}/project-dependencies', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='remove_project_dependency', full_name='spaceone.api.monitoring.v1.Alert.remove_project_dependency', index=8, containing_service=None, input_type=_ALERTPROJECTDEPENDENCYREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002A*?/monitoring/v1/alert/{alert_id}/project-dependency/{project_id}', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='delete', full_name='spaceone.api.monitoring.v1.Alert.delete', index=9, containing_service=None, input_type=_ALERTREQUEST, output_type=google_dot_protobuf_dot_empty__pb2._EMPTY, serialized_options=b'\202\323\344\223\002!*\037/monitoring/v1/alert/{alert_id}', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='get', full_name='spaceone.api.monitoring.v1.Alert.get', index=10, containing_service=None, input_type=_GETALERTREQUEST, output_type=_ALERTINFO, serialized_options=b'\202\323\344\223\002!\022\037/monitoring/v1/alert/{alert_id}', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='list', full_name='spaceone.api.monitoring.v1.Alert.list', index=11, containing_service=None, input_type=_ALERTQUERY, output_type=_ALERTSINFO, serialized_options=b'\202\323\344\223\0027\022\025/monitoring/v1/alertsZ\036\"\034/monitoring/v1/alerts/search', create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='stat', full_name='spaceone.api.monitoring.v1.Alert.stat', index=12, containing_service=None, input_type=_ALERTSTATQUERY, output_type=google_dot_protobuf_dot_struct__pb2._STRUCT, serialized_options=b'\202\323\344\223\002\034\"\032/monitoring/v1/alerts/stat', create_key=_descriptor._internal_create_key, ), ]) _sym_db.RegisterServiceDescriptor(_ALERT) DESCRIPTOR.services_by_name['Alert'] = _ALERT # @@protoc_insertion_point(module_scope)

50.676366

7,646

0.759086

0

20,365

0.285212

dd67c81828221987d83cf924bc48aff8f98affa6

3,364

py

Python

fluid.py

fomightez/stable-fluids

a7bdbb0960c746022a1dfc216dbfe928ee98947b

[ "Unlicense" ]

1

2020-04-20T12:14:59.000Z

fluid.py

fomightez/stable-fluids

a7bdbb0960c746022a1dfc216dbfe928ee98947b

[ "Unlicense" ]

null

fluid.py

fomightez/stable-fluids

a7bdbb0960c746022a1dfc216dbfe928ee98947b

[ "Unlicense" ]

null

import numpy as np import scipy.sparse as sp from scipy.ndimage import map_coordinates from scipy.sparse.linalg import factorized import operators as ops class Fluid: def __init__(self, shape, viscosity, quantities): self.shape = shape # Defining these here keeps the code somewhat more readable vs. computing them every time they're needed. self.size = np.product(shape) self.dimensions = len(shape) # Variable viscosity, both in time and in space, is easy to set up; but it conflicts with the use of # SciPy's factorized function because the diffusion matrix must be recalculated every frame. # In order to keep the simulation speedy I use fixed viscosity. self.viscosity = viscosity # By dynamically creating advected-diffused quantities as needed prototyping becomes much easier. self.quantities = {} for q in quantities: self.quantities[q] = np.zeros(self.size) self.velocity_field = np.zeros((self.size, self.dimensions)) # The reshaping here corresponds to a partial flattening so that self.indices # has the same shape as self.velocity_field. # This makes calculating the advection map as simple as a single vectorized subtraction each frame. self.indices = np.dstack(np.indices(self.shape)).reshape(self.size, self.dimensions) self.gradient = ops.matrices(shape, ops.differences(1, (1,) * self.dimensions), False) # Both viscosity and pressure equations are just Poisson equations similar to the steady state heat equation. laplacian = ops.matrices(shape, ops.differences(1, (2,) * self.dimensions), True) self.pressure_solver = factorized(laplacian) # Making sure I use the sparse version of the identity function here so I don't cast to a dense matrix. self.viscosity_solver = factorized(sp.identity(self.size) - laplacian * viscosity) def advect_diffuse(self): # Advection is computed backwards in time as described in Jos Stam's Stable Fluids whitepaper. advection_map = np.moveaxis(self.indices - self.velocity_field, -1, 0) def kernel(field): # Credit to Philip Zucker for pointing out the aptness of map_coordinates here. # Initially I was using SciPy's griddata function. # While both of these functions do essentially the same thing, griddata is much slower. advected = map_coordinates(field.reshape(self.shape), advection_map, order=2).flatten() return self.viscosity_solver(advected) if self.viscosity > 0 else advected # Apply viscosity and advection to each axis of the velocity field and each user-defined quantity. for d in range(self.dimensions): self.velocity_field[..., d] = kernel(self.velocity_field[..., d]) for k, q in self.quantities.items(): self.quantities[k] = kernel(q) def project(self): # Pressure is calculated from divergence which is in turn calculated from the gradient of the velocity field. divergence = sum(self.gradient[d].dot(self.velocity_field[..., d]) for d in range(self.dimensions)) pressure = self.pressure_solver(divergence) for d in range(self.dimensions): self.velocity_field[..., d] -= self.gradient[d].dot(pressure)

51.753846

117

0.69352

3,206

0.953032

0

1,406

0.417955

dd69e272fd1cf6715ec8277d234fe3f1835d95b2

879

py

Python

setup.py

ngocjr7/geneticpython

4b4157523ce13b3da56cef61282cb0a984cd317b

[ "MIT" ]

null

setup.py

ngocjr7/geneticpython

4b4157523ce13b3da56cef61282cb0a984cd317b

[ "MIT" ]

null

setup.py

ngocjr7/geneticpython

4b4157523ce13b3da56cef61282cb0a984cd317b

[ "MIT" ]

null

from setuptools import setup, find_packages with open("README.md", "r") as fh: long_description = fh.read() PROJECT_URLS = { 'Bug Tracker': 'https://github.com/ngocjr7/geneticpython/issues', 'Documentation': 'https://github.com/ngocjr7/geneticpython/blob/master/README.md', 'Source Code': 'https://github.com/ngocjr7/geneticpython' } with open('requirements.txt') as f: install_requires = f.read().strip().split('\n') setup(name='geneticpython', description='A simple and friendly Python framework for genetic-based algorithms', author='Ngoc Bui', long_description=long_description, long_description_content_type="text/markdown", author_email='ngocjr7@gmail.com', project_urls=PROJECT_URLS, version='0.0.2', packages=find_packages(), install_requires=install_requires, python_requires='>=3.6')

33.807692

88

0.703072

0

374

0.425484

dd6a3b230c4f4617de43080fbacd944fd76f81a8

182

py

Python

Script Python/Desafios/Desafio-012.py

Hubyratan/Material-Python

3f7910dd10b91cefe7b2f3f6aa49e9f9c522fd32

[ "MIT" ]

1

2020-05-11T04:05:56.000Z

Script Python/Desafios/Desafio-012.py

Hubyratan/Material-Python

3f7910dd10b91cefe7b2f3f6aa49e9f9c522fd32

[ "MIT" ]

null

Script Python/Desafios/Desafio-012.py

Hubyratan/Material-Python

3f7910dd10b91cefe7b2f3f6aa49e9f9c522fd32

[ "MIT" ]

null

v = float(input('Valor do produto? R$')) d = float(input('Porcentagem de desconto: ')) ds = (d*v)/100 p = v-ds print(f'Você recebeu R${ds} de desconto, e pagará somente R${p} reais')

36.4

71

0.659341

0

115

0.625

dd6c3adf785e5f57e8767ea1f8f416eff17606e6

208

py

Python

gavia/__init__.py

brett-hosking/gavia

d771235902b9a949efa92a1954d47dac8b1b527f

[ "MIT" ]

null

gavia/__init__.py

brett-hosking/gavia

d771235902b9a949efa92a1954d47dac8b1b527f

[ "MIT" ]

null

gavia/__init__.py

brett-hosking/gavia

d771235902b9a949efa92a1954d47dac8b1b527f

[ "MIT" ]

null

# Package modules from gavia import camera from gavia import vizualise from gavia import nav from gavia import gps from gavia import log from gavia import time # For nested packages from gavia import image

20.8

27

0.8125

0

39

0.1875

dd6dcaf577bcfeb980245ce8c8087ba55da11a51

1,241

py

Python

pynetester/pynetester/netester.py

zoumingzhe/pynetester

256776491b65d4b5f474754e02537f28a5961888

[ "MIT" ]

null

pynetester/pynetester/netester.py

zoumingzhe/pynetester

256776491b65d4b5f474754e02537f28a5961888

[ "MIT" ]

null

pynetester/pynetester/netester.py

zoumingzhe/pynetester

256776491b65d4b5f474754e02537f28a5961888

[ "MIT" ]

null

#!/usr/bin/env python3 # coding=utf-8 # ---------------------------------------------------------------------------------------------------- import socket import os # ---------------------------------------------------------------------------------------------------- # 类 netester # ---------------------------------------------------------------------------------------------------- # 变更履历： # 2021-05-17 | Zou Mingzhe | Ver0.1 | 初始版本 # ---------------------------------------------------------------------------------------------------- # MAP： # 未开发 | server(self, ...) | 压缩文件 # ---------------------------------------------------------------------------------------------------- class netester: """ netester类操作network io。 """ # ---------------------------------------------------------------------------------------------------- @staticmethod def client(config = {'connect':[{'type':'TCP','host':'127.0.0.1','port':10517}]}): for item in config['connect']: info = netester.encode(item) s = socket.socket(socket.AF_INET, info['type']) s.connect(info['addr']) # ----------------------------------------------------------------------------------------------------

45.962963

102

0.2361

450

0.350195

0

276

0.214786

0

1,009

0.785214

dd6f59dfe10afced9799503fae00bbea231ed3f2

7,121

py

Python

cmepy/solver.py

hegland/cmepy

fa8cdf2fad779badbcb629bf6ee33316724ec4a4

[ "BSD-3-Clause" ]

6

2015-05-21T04:56:26.000Z

2019-12-11T18:23:58.000Z

cmepy/solver.py

fcostin/cmepy

fa8cdf2fad779badbcb629bf6ee33316724ec4a4

[ "BSD-3-Clause" ]

1

2018-11-28T15:45:39.000Z

2019-09-18T23:25:40.000Z

cmepy/solver.py

hegland/cmepy

fa8cdf2fad779badbcb629bf6ee33316724ec4a4

[ "BSD-3-Clause" ]

3

2017-05-13T06:56:08.000Z

2021-09-01T14:20:52.000Z

""" Creates solvers for the Chemical Master Equation (CME). """ import numpy from cmepy import cme_matrix, domain, ode_solver, other_solver, state_enum from cmepy import model as mdl def create_packing_functions(domain_enum): """ create_packing_functions(domain_enum) -> (pack, unpack) where pack((p, p_sink)) -> y unpack(y) -> (p, p_sink) """ def pack((p, p_sink)): """ pack((p, p_sink)) -> y where p : mapping from states to probability p_sink : float, storing probability lost from domain due to truncation of domain states y : array passed to differential equations solver """ d_dense = domain_enum.pack_distribution(p) return numpy.concatenate((d_dense, [p_sink])) def unpack(y): """ unpack(y) -> (p, p_sink) where p : mapping from states to probability p_sink : float, storing probability lost from domain due to truncation of domain states y : array passed to differential equations solver """ p_sparse = domain_enum.unpack_distribution(y[:-1]) p_sink = y[-1] return p_sparse, p_sink return (pack, unpack) def create(model, sink, p_0=None, t_0=None, sink_0=None, time_dependencies=None, domain_states=None, solver=ode_solver.Solver, outflow=False, **solver_args): """ Returns a solver for the Chemical Master Equation of the given model. arguments: model : the CME model to solve sink : If sink is True, the solver will include a 'sink' state used to accumulate any probability that may flow outside the domain. This can be used to measure the error in the solution due to truncation of the domain. If sink is False, the solver will not include a 'sink' state, and probability will be artificially prevented from flowing outside of the domain. p_0 : (optional) mapping from states in the domain to probabilities, for the initial probability distribution. If not specified, and the initial state of the state space is given by the model, defaults to all probability concentrated at the initial state, otherwise, a ValueError will be raised. t_0 : (optional) initial time, defaults to 0.0 sink_0 : (optional) initial sink probability, defaults to 0.0 Only a valid argument if sink is set to True. time_dependencies : (optional) By default, reaction propensities are time independent. If specified, time_dependencies must be of the form { s_1 : phi_1, ..., s_n : phi_n }, where each (s_j, phi_j) item satisifes : s_j : set of reaction indices phi_j : phi_j(t) -> time dependent coefficient The propensities of the reactions with indicies contained in s_j will all be multiplied by the coefficient phi_j(t), at time t. Reactions are indexed according to the ordering of the propensities in the model. The reaction index sets s_j must be *disjoint*. It is not necessary for the union of the s_j to include all the reaction indices. If a reaction's index is not contained in any s_j then the reaction is treated as time-independent. mapping of time dependent coefficient functions keyed by subsets of reaction indices, with respect to the ordering of reactions determined by the order of the propensity functions inside the model. The propensities of the reactions with indices included in each subset are multiplied by the time dependent coefficient function. By default, no time dependent coefficient functions are specified, that is, the CME has time-independent propensities. domain_states : (optional) array of states in the domain. By default, generate the rectangular lattice of states defined by the 'shape' entry of the model. A ValueError is raised if both domain_states and 'shape' are unspecified. """ mdl.validate_model(model) if sink and outflow: raise ValueError('sink and outflow cannot be both True') if sink_0 is not None: if not sink: raise ValueError('sink_0 may not be specified if sink is False') sink_0 = float(sink_0) else: sink_0 = 0.0 # determine states in domain, then construct an enumeration of the # domain states if domain_states is None: if mdl.SHAPE not in model: lament = 'if no states given, model must contain key \'%s\'' raise KeyError(lament % mdl.SHAPE) else: domain_states = domain.from_rect(shape = model.shape) domain_enum = state_enum.create(domain_states) # determine p_0, then construct a dense representation with respect to # the domain enumeration initial_state = model.get(mdl.INITIAL_STATE, None) if p_0 is None: if initial_state is None: lament = 'if no p_0 given, model must contain key \'%s\'' raise ValueError(lament % mdl.INITIAL_STATE) else: p_0 = {initial_state : 1.0} if t_0 is None: t_0 = 0.0 member_flags = domain_enum.contains(domain.from_iter(p_0)) if not numpy.logical_and.reduce(member_flags): raise ValueError('support of p_0 is not a subset of domain_states') # compute reaction matrices and use them to define differential equations gen_matrices = cme_matrix.gen_reaction_matrices( model, domain_enum, sink, cme_matrix.non_neg_states, outflow=outflow ) reaction_matrices = list(gen_matrices) dy_dt = cme_matrix.create_diff_eqs( reaction_matrices, phi = time_dependencies ) if solver_args: solver_args['reaction_matrices'] = reaction_matrices # construct and initialise solver if sink: cme_solver = solver( dy_dt, y_0 = (p_0, sink_0), t_0 = t_0, **solver_args ) pack, unpack = create_packing_functions(domain_enum) cme_solver.set_packing( pack, unpack, transform_dy_dt = False ) else: pack = domain_enum.pack_distribution unpack = domain_enum.unpack_distribution cme_solver = solver( dy_dt, y_0 = p_0, t_0 = t_0, **solver_args ) cme_solver.set_packing( pack, unpack, transform_dy_dt = False ) return cme_solver

35.078818

79

0.602303

0

4,303

0.604269

dd767e6d50fc90c7d830096cddd6903575b2142e

1,290

py

Python

server_common/helpers.py

GustavLero/EPICS-inst_servers

4bcdd6a80f1d9e074de3f0f7c66968d506981988

[ "BSD-3-Clause" ]

null

server_common/helpers.py

GustavLero/EPICS-inst_servers

4bcdd6a80f1d9e074de3f0f7c66968d506981988

[ "BSD-3-Clause" ]

null

server_common/helpers.py

GustavLero/EPICS-inst_servers

4bcdd6a80f1d9e074de3f0f7c66968d506981988

[ "BSD-3-Clause" ]

null

import json import os import sys from server_common.ioc_data_source import IocDataSource from server_common.mysql_abstraction_layer import SQLAbstraction from server_common.utilities import print_and_log, SEVERITY def register_ioc_start(ioc_name, pv_database=None, prefix=None): """ A helper function to register the start of an ioc. Args: ioc_name: name of the ioc to start pv_database: doctionary of pvs in the iov prefix: prefix of pvs in this ioc """ try: exepath = sys.argv[0] if pv_database is None: pv_database = {} if prefix is None: prefix = "none" ioc_data_source = IocDataSource(SQLAbstraction("iocdb", "iocdb", "$iocdb")) ioc_data_source.insert_ioc_start(ioc_name, os.getpid(), exepath, pv_database, prefix) except Exception as e: print_and_log("Error registering ioc start: {}: {}".format(e.__class__.__name__, e), SEVERITY.MAJOR) def get_macro_values(): """ Parse macro environment JSON into dict. To make this work use the icpconfigGetMacros program. Returns: Macro Key:Value pairs as dict """ macros = json.loads(os.environ.get("REFL_MACROS", "")) macros = {key: value for (key, value) in macros.items()} return macros

32.25

108

0.686047

0

444

0.344186

dd782114838d338a027967eb958ee0dd0d6070b0

12,799

py

Python

rman_ui/rman_ui_txmanager.py

ian-hsieh/RenderManForBlender

c827f029f4cbbd1fcc71ed8d3694fc5ac58cc468

[ "MIT" ]

12

2019-05-03T21:58:15.000Z

2022-02-24T07:02:21.000Z

rman_ui/rman_ui_txmanager.py

ian-hsieh/RenderManForBlender

c827f029f4cbbd1fcc71ed8d3694fc5ac58cc468

[ "MIT" ]

4

2019-03-07T18:20:16.000Z

2020-09-24T21:53:15.000Z

rman_ui/rman_ui_txmanager.py

ian-hsieh/RenderManForBlender

c827f029f4cbbd1fcc71ed8d3694fc5ac58cc468

[ "MIT" ]

3

2019-05-25T01:17:09.000Z

2019-09-13T14:43:12.000Z

import bpy from bpy.props import StringProperty, IntProperty, CollectionProperty, EnumProperty, BoolProperty from bpy.types import PropertyGroup, UIList, Operator, Panel from bpy_extras.io_utils import ImportHelper from .rman_ui_base import _RManPanelHeader from ..txmanager3 import txparams from ..rman_utils import texture_utils from .. import txmanager3 as txmngr3 import os import uuid class TxFileItem(PropertyGroup): """UIList item representing a TxFile""" name: StringProperty( name="Name", description="Image name", default="") tooltip: StringProperty( name="tooltip", description="Tool Tip", default="") nodeID: StringProperty( name="nodeID", description="Node ID (hidden)", default="") state: IntProperty( name="state", description="", default=0 ) enable: BoolProperty( name="enable", description="Enable or disable this TxFileItem", default=True ) txsettings = ['texture_type', 'smode', 'tmode', 'texture_format', 'data_type', 'resize'] items = [] for item in txparams.TX_TYPES: items.append((item, item, '')) texture_type: EnumProperty( name="Texture Type", items=items, description="Texture Type", default=txparams.TX_TYPE_REGULAR) items = [] for item in txparams.TX_WRAP_MODES: items.append((item, item, '')) smode: EnumProperty( name="S Wrap", items=items, default=txparams.TX_WRAP_MODE_PERIODIC) tmode: EnumProperty( name="T Wrap", items=items, default=txparams.TX_WRAP_MODE_PERIODIC) items = [] for item in txparams.TX_FORMATS: items.append((item, item, '')) texture_format: EnumProperty( name="Format", default=txparams.TX_FORMAT_PIXAR, items=items, description="Texture format") items = [] items.append(('default', 'default', '')) for item in txparams.TX_DATATYPES: items.append((item, item, '')) data_type: EnumProperty( name="Data Type", default=txparams.TX_DATATYPE_FLOAT, items=items, description="The data storage txmake uses") items = [] for item in txparams.TX_RESIZES: items.append((item, item, '')) resize: EnumProperty( name="Resize", default=txparams.TX_RESIZE_UP_DASH, items=items, description="The type of resizing flag to pass to txmake") class PRMAN_UL_Renderman_txmanager_list(UIList): """RenderMan TxManager UIList.""" def draw_item(self, context, layout, data, item, icon, active_data, active_propname, index): icons_map = {txmngr3.STATE_MISSING: 'ERROR', txmngr3.STATE_EXISTS: 'CHECKBOX_HLT', txmngr3.STATE_IS_TEX: 'TEXTURE', txmngr3.STATE_IN_QUEUE: 'PLUS', txmngr3.STATE_PROCESSING: 'TIME', txmngr3.STATE_ERROR: 'CANCEL', txmngr3.STATE_REPROCESS: 'TIME', txmngr3.STATE_UNKNOWN: 'CANCEL', txmngr3.STATE_INPUT_MISSING: 'ERROR'} txfile = None if item.nodeID != "": txfile = texture_utils.get_txmanager().txmanager.get_txfile_from_id(item.nodeID) else: txfile = texture_utils.get_txmanager().txmanager.get_txfile_from_path(item.name) if txfile: custom_icon = icons_map[txfile.state] else: custom_icon = 'CANCEL' if self.layout_type in {'DEFAULT', 'COMPACT'}: layout.label(text=item.name, icon = custom_icon) elif self.layout_type in {'GRID'}: layout.alignment = 'CENTER' layout.label(text="", icon = custom_icon) class PRMAN_OT_Renderman_txmanager_parse_scene(Operator): """Parse scene for textures to add to to the txmanager""" bl_idname = "rman_txmgr_list.parse_scene" bl_label = "Parse Scene" def execute(self, context): rman_txmgr_list = context.scene.rman_txmgr_list rman_txmgr_list.clear() texture_utils.get_txmanager().txmanager.reset() texture_utils.parse_for_textures(context.scene) texture_utils.get_txmanager().txmake_all(blocking=False) return{'FINISHED'} class PRMAN_OT_Renderman_txmanager_pick_images(Operator, ImportHelper): """Pick images from a directory.""" bl_idname = "rman_txmgr_list.pick_images" bl_label = "Pick Images" filename: StringProperty(maxlen=1024) directory: StringProperty(maxlen=1024) files: CollectionProperty(type=bpy.types.PropertyGroup) def execute(self, context): rman_txmgr_list = context.scene.rman_txmgr_list rman_txmgr_list.clear() texture_utils.get_txmanager().txmanager.reset() if len(self.files) > 0: for f in self.files: img = os.path.join(self.directory, f.name) item = context.scene.rman_txmgr_list.add() item.nodeID = str(uuid.uuid1()) texture_utils.get_txmanager().txmanager.add_texture(item.nodeID, img) item.name = img return{'FINISHED'} class PRMAN_OT_Renderman_txmanager_clear_all_cache(Operator): """Clear RenderMan Texture cache""" bl_idname = "rman_txmgr_list.clear_all_cache" bl_label = "Clear Texture Cache" def execute(self, context): # needs to call InvalidateTexture return{'FINISHED'} class PRMAN_OT_Renderman_txmanager_reconvert_all(Operator): """Clear all .tex files and re-convert.""" bl_idname = "rman_txmgr_list.reconvert_all" bl_label = "RE-Convert All" def execute(self, context): texture_utils.get_txmanager().txmanager.delete_texture_files() texture_utils.get_txmanager().txmake_all(blocking=False) return{'FINISHED'} class PRMAN_OT_Renderman_txmanager_apply_preset(Operator): """Apply current settings to the selected texture.""" bl_idname = "rman_txmgr_list.apply_preset" bl_label = "Apply preset" def execute(self, context): idx = context.scene.rman_txmgr_list_index item = context.scene.rman_txmgr_list[idx] txsettings = dict() for attr in item.txsettings: val = getattr(item, attr) if attr == 'data_type' and val == 'default': val = None txsettings[attr] = val if txsettings: txfile = None if item.nodeID != "": txfile = texture_utils.get_txmanager().txmanager.get_txfile_from_id(item.nodeID) else: txfile = texture_utils.get_txmanager().txmanager.get_txfile_from_path(item.name) txfile.params.set_params_from_dict(txsettings) return{'FINISHED'} class PRMAN_OT_Renderman_txmanager_add_texture(Operator): """Add texture.""" bl_idname = "rman_txmgr_list.add_texture" bl_label = "add_texture" filepath: StringProperty() nodeID: StringProperty() def execute(self, context): txfile = texture_utils.get_txmanager().txmanager.get_txfile_from_path(self.filepath) if not txfile: return{'FINISHED'} item = None # check if nodeID already exists in the list for i in context.scene.rman_txmgr_list: if i.nodeID == self.nodeID: item = i break if not item: item = context.scene.rman_txmgr_list.add() item.nodeID = self.nodeID item.name = txfile.input_image params = txfile.params item.texture_type = params.texture_type item.smode = params.smode item.tmode = params.tmode item.texture_type = params.texture_type if params.data_type is not None: item.data_type = params.data_type item.resize = params.resize item.state = txfile.state if txfile.state == txmngr3.STATE_IS_TEX: item.enable = False item.tooltip = '\n' + txfile.tooltip_text() # FIXME: should also add the nodes that this texture is referenced in return{'FINISHED'} class PRMAN_PT_Renderman_txmanager_list(_RManPanelHeader, Panel): """RenderMan Texture Manager Panel.""" bl_label = "RenderMan Texture Manager" bl_idname = "PRMAN_PT_Renderman_txmanager_list" bl_space_type = 'PROPERTIES' bl_region_type = 'WINDOW' bl_context = "scene" def draw(self, context): layout = self.layout scene = context.scene row = layout.row() row.operator('rman_txmgr_list.parse_scene', text='Parse Scene') # FIXME: not totally working. The done callbacks fail #row.operator('rman_txmgr_list.pick_images', text='Pick Images') row.operator('rman_txmgr_list.reconvert_all', text='Reconvert') row.operator('rman_txmgr_list.clear_all_cache', text='Clear All Cache') if scene.rman_txmgr_list_index >= 0 and scene.rman_txmgr_list: row = layout.row() row.template_list("PRMAN_UL_Renderman_txmanager_list", "The_List", scene, "rman_txmgr_list", scene, "rman_txmgr_list_index", item_dyntip_propname="tooltip") item = scene.rman_txmgr_list[scene.rman_txmgr_list_index] row = layout.row() row.label(text='Texture Settings') row = layout.row() row.enabled = item.enable row.prop(item, "texture_type") row = layout.row() row.enabled = item.enable row.prop(item, "smode") row.prop(item, "tmode") row = layout.row() row.enabled = item.enable row.prop(item, "texture_format") row = layout.row() row.enabled = item.enable row.prop(item, "data_type") row = layout.row() row.enabled = item.enable row.prop(item, "resize") row = layout.row() row.enabled = item.enable row.alignment = 'RIGHT' row.operator('rman_txmgr_list.apply_preset', text='Apply') row = layout.row() row.alignment='CENTER' in_list = len(context.scene.rman_txmgr_list) progress = 'All Converted' qsize = texture_utils.get_txmanager().txmanager.workQueue.qsize() if qsize != 0: progress = 'Converting...%d left to convert' % (qsize) row.label(text=progress) def index_updated(self, context): ''' When the index updates, make sure the texture settings are in sync with the txmanager. ''' idx = context.scene.rman_txmgr_list_index if idx < 0: return item = context.scene.rman_txmgr_list[idx] txfile = None if item.nodeID != "": txfile = texture_utils.get_txmanager().txmanager.get_txfile_from_id(item.nodeID) else: txfile = texture_utils.get_txmanager().txmanager.get_txfile_from_path(item.name) if txfile: params = txfile.params item.texture_type = params.texture_type item.smode = params.smode item.tmode = params.tmode item.texture_type = params.texture_type if params.data_type is not None: item.data_type = params.data_type item.resize = params.resize if txfile.state == txmngr3.STATE_IS_TEX: item.enable = False classes = [ TxFileItem, PRMAN_UL_Renderman_txmanager_list, PRMAN_OT_Renderman_txmanager_parse_scene, PRMAN_OT_Renderman_txmanager_pick_images, PRMAN_OT_Renderman_txmanager_clear_all_cache, PRMAN_OT_Renderman_txmanager_reconvert_all, PRMAN_OT_Renderman_txmanager_apply_preset, PRMAN_OT_Renderman_txmanager_add_texture, PRMAN_PT_Renderman_txmanager_list ] def register(): for cls in classes: bpy.utils.register_class(cls) bpy.types.Scene.rman_txmgr_list = CollectionProperty(type = TxFileItem) bpy.types.Scene.rman_txmgr_list_index = IntProperty(name = "RenderMan Texture Manager", default = 0, update=index_updated) def unregister(): del bpy.types.Scene.rman_txmgr_list del bpy.types.Scene.rman_txmgr_list_index for cls in classes: bpy.utils.unregister_class(cls)

32.734015

110

0.615595

10,539

0.823424

0

2,109

0.164778

dd788c7b5bde6a0a3088e641302680a262892fc0

943

py

Python

cousins-in-binary-tree/cousins-in-binary-tree.py

hyeseonko/LeetCode

48dfc93f1638e13041d8ce1420517a886abbdc77

[ "MIT" ]

2

2021-12-05T14:29:06.000Z

2022-01-01T05:46:13.000Z

cousins-in-binary-tree/cousins-in-binary-tree.py

hyeseonko/LeetCode

48dfc93f1638e13041d8ce1420517a886abbdc77

[ "MIT" ]

null

cousins-in-binary-tree/cousins-in-binary-tree.py

hyeseonko/LeetCode

48dfc93f1638e13041d8ce1420517a886abbdc77

[ "MIT" ]

null

# Definition for a binary tree node. # class TreeNode: # def __init__(self, val=0, left=None, right=None): # self.val = val # self.left = left # self.right = right class Solution: def isCousins(self, root: Optional[TreeNode], x: int, y: int) -> bool: # condition to be cousin: (1) diff.parents (2) same level stack=[(root, 0, -1)] xlevel, ylevel = -1, -1 xparent, yparent = -1, -1 while(stack): cur, depth, parent = stack.pop(0) if cur.val==x: xlevel, xparent = depth, parent if cur.val==y: ylevel, yparent = depth, parent if cur.left: stack.append((cur.left, depth+1, cur.val)) if cur.right: stack.append((cur.right, depth+1, cur.val)) if xlevel==ylevel and xparent!=yparent: return True else: return False

36.269231

74

0.520679

751

0.796394

0

243

0.257688

dd793146f92f3801277eeab8ef75d59d722ca146

5,581

py

Python

rdmo/questions/tests/test_validator_locked_questions.py

berkerY/rdmo

c0500f9b6caff9106a254a05e0d0e8018fc8db28

[ "Apache-2.0" ]

77

2016-08-09T11:40:20.000Z

2022-03-06T11:03:26.000Z

rdmo/questions/tests/test_validator_locked_questions.py

MSpenger/rdmo

c0500f9b6caff9106a254a05e0d0e8018fc8db28

[ "Apache-2.0" ]

377

2016-07-01T13:59:36.000Z

2022-03-30T13:53:19.000Z

rdmo/questions/tests/test_validator_locked_questions.py

MSpenger/rdmo

c0500f9b6caff9106a254a05e0d0e8018fc8db28

[ "Apache-2.0" ]

47

2016-06-23T11:32:19.000Z

2022-03-01T11:34:37.000Z

import pytest from django.core.exceptions import ValidationError from rest_framework.exceptions import \ ValidationError as RestFameworkValidationError from ..models import Question, QuestionSet from ..serializers.v1 import QuestionSerializer from ..validators import QuestionLockedValidator def test_create(db): QuestionLockedValidator()({ 'questionset': QuestionSet.objects.first(), 'locked': False }) def test_create_locked(db): QuestionLockedValidator()({ 'questionset': QuestionSet.objects.first(), 'locked': True }) def test_update(db): question = Question.objects.first() QuestionLockedValidator(question)({ 'questionset': question.questionset, 'locked': False }) def test_update_error(db): question = Question.objects.first() question.locked = True question.save() with pytest.raises(ValidationError): QuestionLockedValidator(question)({ 'questionset': question.questionset, 'locked': True }) def test_update_parent_error(db): question = Question.objects.first() question.questionset.locked = True question.questionset.save() with pytest.raises(ValidationError): QuestionLockedValidator(question)({ 'questionset': question.questionset, 'locked': False }) def test_update_parent_parent_error(db): question = Question.objects.first() question.questionset.section.locked = True question.questionset.section.save() with pytest.raises(ValidationError): QuestionLockedValidator(question)({ 'questionset': question.questionset, 'locked': False }) def test_update_parent_parent_parent_error(db): question = Question.objects.first() question.questionset.section.catalog.locked = True question.questionset.section.catalog.save() with pytest.raises(ValidationError): QuestionLockedValidator(question)({ 'questionset': question.questionset, 'locked': False }) def test_update_lock(db): question = Question.objects.first() QuestionLockedValidator(question)({ 'questionset': question.questionset, 'locked': True }) def test_update_unlock(db): question = Question.objects.first() question.locked = True question.save() QuestionLockedValidator(question)({ 'questionset': question.questionset, 'locked': False }) def test_serializer_create(db): validator = QuestionLockedValidator() validator.set_context(QuestionSerializer()) validator({ 'questionset': QuestionSet.objects.first(), 'locked': False }) def test_serializer_create_locked(db): validator = QuestionLockedValidator() validator.set_context(QuestionSerializer()) validator({ 'questionset': QuestionSet.objects.first(), 'locked': True }) def test_serializer_update(db): question = Question.objects.first() validator = QuestionLockedValidator() validator.set_context(QuestionSerializer(instance=question)) validator({ 'questionset': question.questionset, 'locked': False }) def test_serializer_update_error(db): question = Question.objects.first() question.locked = True question.save() validator = QuestionLockedValidator() validator.set_context(QuestionSerializer(instance=question)) with pytest.raises(RestFameworkValidationError): validator({ 'questionset': question.questionset, 'locked': True }) def test_serializer_update_parent_error(db): question = Question.objects.first() question.questionset.locked = True question.questionset.save() validator = QuestionLockedValidator() validator.set_context(QuestionSerializer(instance=question)) with pytest.raises(RestFameworkValidationError): validator({ 'questionset': question.questionset, 'locked': True }) def test_serializer_update_parent_parent_error(db): question = Question.objects.first() question.questionset.section.locked = True question.questionset.section.save() validator = QuestionLockedValidator() validator.set_context(QuestionSerializer(instance=question)) with pytest.raises(RestFameworkValidationError): validator({ 'questionset': question.questionset, 'locked': True }) def test_serializer_update_parent_parent_parent_error(db): question = Question.objects.first() question.questionset.section.catalog.locked = True question.questionset.section.catalog.save() validator = QuestionLockedValidator() validator.set_context(QuestionSerializer(instance=question)) with pytest.raises(RestFameworkValidationError): validator({ 'questionset': question.questionset, 'locked': True }) def test_serializer_update_lock(db): question = Question.objects.first() validator = QuestionLockedValidator() validator.set_context(QuestionSerializer(instance=question)) validator({ 'questionset': question.questionset, 'locked': True }) def test_serializer_update_unlock(db): question = Question.objects.first() question.locked = True question.save() validator = QuestionLockedValidator() validator.set_context(QuestionSerializer(instance=question)) validator({ 'questionset': question.questionset, 'locked': False })

25.600917

64

0.689124

0

378

0.06773

dd79ddb1ceb718cc4031b1942143fae9a88b3147

80,373

py

Python

samtranslator/model/sam_resources.py

aaythapa/serverless-application-model

1029548db5787845d1a321d7c182aeb3716933ba

[ "Apache-2.0" ]

null

samtranslator/model/sam_resources.py

aaythapa/serverless-application-model

1029548db5787845d1a321d7c182aeb3716933ba

[ "Apache-2.0" ]

null

samtranslator/model/sam_resources.py

aaythapa/serverless-application-model

1029548db5787845d1a321d7c182aeb3716933ba

[ "Apache-2.0" ]

null

""" SAM macro definitions """ from six import string_types import copy import uuid import samtranslator.model.eventsources import samtranslator.model.eventsources.pull import samtranslator.model.eventsources.push import samtranslator.model.eventsources.cloudwatchlogs from .api.api_generator import ApiGenerator from .api.http_api_generator import HttpApiGenerator from .packagetype import ZIP, IMAGE from .s3_utils.uri_parser import construct_s3_location_object, construct_image_code_object from .tags.resource_tagging import get_tag_list from samtranslator.model import PropertyType, SamResourceMacro, ResourceTypeResolver from samtranslator.model.apigateway import ( ApiGatewayDeployment, ApiGatewayStage, ApiGatewayDomainName, ApiGatewayUsagePlan, ApiGatewayUsagePlanKey, ApiGatewayApiKey, ) from samtranslator.model.apigatewayv2 import ApiGatewayV2Stage, ApiGatewayV2DomainName from samtranslator.model.cloudformation import NestedStack from samtranslator.model.s3 import S3Bucket from samtranslator.model.cloudwatch import SyntheticsCanary, CloudWatchAlarm from samtranslator.model.dynamodb import DynamoDBTable from samtranslator.model.exceptions import InvalidEventException, InvalidResourceException from samtranslator.model.resource_policies import ResourcePolicies, PolicyTypes from samtranslator.model.iam import IAMRole, IAMRolePolicies from samtranslator.model.lambda_ import ( LambdaFunction, LambdaVersion, LambdaAlias, LambdaLayerVersion, LambdaEventInvokeConfig, ) from samtranslator.model.types import dict_of, is_str, is_type, list_of, one_of, any_type from samtranslator.translator import logical_id_generator from samtranslator.translator.arn_generator import ArnGenerator from samtranslator.model.intrinsics import ( is_intrinsic_if, is_intrinsic_no_value, ref, make_not_conditional, make_conditional, make_and_condition, ) from samtranslator.model.sqs import SQSQueue from samtranslator.model.sns import SNSTopic from samtranslator.model.stepfunctions import StateMachineGenerator from samtranslator.model.role_utils import construct_role_for_resource from samtranslator.model.xray_utils import get_xray_managed_policy_name # len(prefix) + MAX_CANARY_LOGICAL_ID_LENGTH + MAX_CANARY_UNIQUE_ID_LENGTH + 1 (extra '-' char added) must be less # than or equal to 21 # https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-synthetics-canary.html#cfn-synthetics-canary-name MAX_CANARY_LOGICAL_ID_LENGTH = 11 MAX_CANARY_UNIQUE_ID_LENGTH = 5 CANARY_NAME_PREFIX = "sam-" # The default values for ComparisonOperator, Threshold and Period based on the MetricName provided by the user # These default values were acquired from the Create Canary page in the Synthetics Canary dashboard # https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Synthetics_Canaries_metrics.html DEFAULT_METRIC_VALUES = { "SuccessPercent": {"ComparisonOperator": "LessThanThreshold", "Threshold": 90, "Period": 300}, "Failed": {"ComparisonOperator": "GreaterThanOrEqualToThreshold", "Threshold": 1, "Period": 300}, "Duration": {"ComparisonOperator": "GreaterThanThreshold", "Threshold": 30000, "Period": 900}, } # the main metrics produced by Synthetics Canary # sorted for backwards compatibility (python 2.7 automatically sorts keys) VALID_CANARY_METRICS = list(sorted(DEFAULT_METRIC_VALUES)) class SamFunction(SamResourceMacro): """SAM function macro.""" resource_type = "AWS::Serverless::Function" property_types = { "FunctionName": PropertyType(False, one_of(is_str(), is_type(dict))), "Handler": PropertyType(False, is_str()), "Runtime": PropertyType(False, is_str()), "CodeUri": PropertyType(False, one_of(is_str(), is_type(dict))), "ImageUri": PropertyType(False, is_str()), "PackageType": PropertyType(False, is_str()), "InlineCode": PropertyType(False, one_of(is_str(), is_type(dict))), "DeadLetterQueue": PropertyType(False, is_type(dict)), "Description": PropertyType(False, is_str()), "MemorySize": PropertyType(False, is_type(int)), "Timeout": PropertyType(False, is_type(int)), "VpcConfig": PropertyType(False, is_type(dict)), "Role": PropertyType(False, is_str()), "AssumeRolePolicyDocument": PropertyType(False, is_type(dict)), "Policies": PropertyType(False, one_of(is_str(), is_type(dict), list_of(one_of(is_str(), is_type(dict))))), "PermissionsBoundary": PropertyType(False, is_str()), "Environment": PropertyType(False, dict_of(is_str(), is_type(dict))), "Events": PropertyType(False, dict_of(is_str(), is_type(dict))), "Tags": PropertyType(False, is_type(dict)), "Tracing": PropertyType(False, one_of(is_type(dict), is_str())), "KmsKeyArn": PropertyType(False, one_of(is_type(dict), is_str())), "DeploymentPreference": PropertyType(False, is_type(dict)), "ReservedConcurrentExecutions": PropertyType(False, any_type()), "Layers": PropertyType(False, list_of(one_of(is_str(), is_type(dict)))), "EventInvokeConfig": PropertyType(False, is_type(dict)), # Intrinsic functions in value of Alias property are not supported, yet "AutoPublishAlias": PropertyType(False, one_of(is_str())), "AutoPublishCodeSha256": PropertyType(False, one_of(is_str())), "VersionDescription": PropertyType(False, is_str()), "ProvisionedConcurrencyConfig": PropertyType(False, is_type(dict)), "FileSystemConfigs": PropertyType(False, list_of(is_type(dict))), "ImageConfig": PropertyType(False, is_type(dict)), "CodeSigningConfigArn": PropertyType(False, is_str()), } event_resolver = ResourceTypeResolver( samtranslator.model.eventsources, samtranslator.model.eventsources.pull, samtranslator.model.eventsources.push, samtranslator.model.eventsources.cloudwatchlogs, ) # DeadLetterQueue dead_letter_queue_policy_actions = {"SQS": "sqs:SendMessage", "SNS": "sns:Publish"} # # Conditions conditions = {} # Customers can refer to the following properties of SAM function referable_properties = { "Alias": LambdaAlias.resource_type, "Version": LambdaVersion.resource_type, # EventConfig auto created SQS and SNS "DestinationTopic": SNSTopic.resource_type, "DestinationQueue": SQSQueue.resource_type, } def resources_to_link(self, resources): try: return {"event_resources": self._event_resources_to_link(resources)} except InvalidEventException as e: raise InvalidResourceException(self.logical_id, e.message) def to_cloudformation(self, **kwargs): """Returns the Lambda function, role, and event resources to which this SAM Function corresponds. :param dict kwargs: already-converted resources that may need to be modified when converting this \ macro to pure CloudFormation :returns: a list of vanilla CloudFormation Resources, to which this Function expands :rtype: list """ resources = [] intrinsics_resolver = kwargs["intrinsics_resolver"] mappings_resolver = kwargs.get("mappings_resolver", None) conditions = kwargs.get("conditions", {}) if self.DeadLetterQueue: self._validate_dlq() lambda_function = self._construct_lambda_function() resources.append(lambda_function) if self.ProvisionedConcurrencyConfig: if not self.AutoPublishAlias: raise InvalidResourceException( self.logical_id, "To set ProvisionedConcurrencyConfig " "AutoPublishALias must be defined on the function", ) lambda_alias = None alias_name = "" if self.AutoPublishAlias: alias_name = self._get_resolved_alias_name("AutoPublishAlias", self.AutoPublishAlias, intrinsics_resolver) code_sha256 = None if self.AutoPublishCodeSha256: code_sha256 = intrinsics_resolver.resolve_parameter_refs(self.AutoPublishCodeSha256) lambda_version = self._construct_version( lambda_function, intrinsics_resolver=intrinsics_resolver, code_sha256=code_sha256 ) lambda_alias = self._construct_alias(alias_name, lambda_function, lambda_version) resources.append(lambda_version) resources.append(lambda_alias) if self.DeploymentPreference: self._validate_deployment_preference_and_add_update_policy( kwargs.get("deployment_preference_collection", None), lambda_alias, intrinsics_resolver, mappings_resolver, ) event_invoke_policies = [] if self.EventInvokeConfig: function_name = lambda_function.logical_id event_invoke_resources, event_invoke_policies = self._construct_event_invoke_config( function_name, alias_name, lambda_alias, intrinsics_resolver, conditions ) resources.extend(event_invoke_resources) managed_policy_map = kwargs.get("managed_policy_map", {}) if not managed_policy_map: raise Exception("Managed policy map is empty, but should not be.") execution_role = None if lambda_function.Role is None: execution_role = self._construct_role(managed_policy_map, event_invoke_policies) lambda_function.Role = execution_role.get_runtime_attr("arn") resources.append(execution_role) try: resources += self._generate_event_resources( lambda_function, execution_role, kwargs["event_resources"], intrinsics_resolver, lambda_alias=lambda_alias, ) except InvalidEventException as e: raise InvalidResourceException(self.logical_id, e.message) return resources def _construct_event_invoke_config(self, function_name, alias_name, lambda_alias, intrinsics_resolver, conditions): """ Create a `AWS::Lambda::EventInvokeConfig` based on the input dict `EventInvokeConfig` """ resources = [] policy_document = [] # Try to resolve. resolved_event_invoke_config = intrinsics_resolver.resolve_parameter_refs(self.EventInvokeConfig) logical_id = "{id}EventInvokeConfig".format(id=function_name) if lambda_alias: lambda_event_invoke_config = LambdaEventInvokeConfig( logical_id=logical_id, depends_on=[lambda_alias.logical_id], attributes=self.resource_attributes ) else: lambda_event_invoke_config = LambdaEventInvokeConfig( logical_id=logical_id, attributes=self.resource_attributes ) dest_config = {} input_dest_config = resolved_event_invoke_config.get("DestinationConfig") if input_dest_config and input_dest_config.get("OnSuccess") is not None: resource, on_success, policy = self._validate_and_inject_resource( input_dest_config.get("OnSuccess"), "OnSuccess", logical_id, conditions ) dest_config["OnSuccess"] = on_success self.EventInvokeConfig["DestinationConfig"]["OnSuccess"]["Destination"] = on_success.get("Destination") if resource is not None: resources.extend([resource]) if policy is not None: policy_document.append(policy) if input_dest_config and input_dest_config.get("OnFailure") is not None: resource, on_failure, policy = self._validate_and_inject_resource( input_dest_config.get("OnFailure"), "OnFailure", logical_id, conditions ) dest_config["OnFailure"] = on_failure self.EventInvokeConfig["DestinationConfig"]["OnFailure"]["Destination"] = on_failure.get("Destination") if resource is not None: resources.extend([resource]) if policy is not None: policy_document.append(policy) lambda_event_invoke_config.FunctionName = ref(function_name) if alias_name: lambda_event_invoke_config.Qualifier = alias_name else: lambda_event_invoke_config.Qualifier = "$LATEST" lambda_event_invoke_config.DestinationConfig = dest_config lambda_event_invoke_config.MaximumEventAgeInSeconds = resolved_event_invoke_config.get( "MaximumEventAgeInSeconds" ) lambda_event_invoke_config.MaximumRetryAttempts = resolved_event_invoke_config.get("MaximumRetryAttempts") resources.extend([lambda_event_invoke_config]) return resources, policy_document def _validate_and_inject_resource(self, dest_config, event, logical_id, conditions): """ For Event Invoke Config, if the user has not specified a destination ARN for SQS/SNS, SAM auto creates a SQS and SNS resource with defaults. Intrinsics are supported in the Destination ARN property, so to handle conditional ifs we have to inject if conditions in the auto created SQS/SNS resources as well as in the policy documents. """ accepted_types_list = ["SQS", "SNS", "EventBridge", "Lambda"] auto_inject_list = ["SQS", "SNS"] resource = None policy = {} destination = {} destination["Destination"] = dest_config.get("Destination") resource_logical_id = logical_id + event if dest_config.get("Type") is None or dest_config.get("Type") not in accepted_types_list: raise InvalidResourceException( self.logical_id, "'Type: {}' must be one of {}".format(dest_config.get("Type"), accepted_types_list) ) property_condition, dest_arn = self._get_or_make_condition( dest_config.get("Destination"), logical_id, conditions ) if dest_config.get("Destination") is None or property_condition is not None: combined_condition = self._make_and_conditions( self.get_passthrough_resource_attributes().get("Condition"), property_condition, conditions ) if dest_config.get("Type") in auto_inject_list: if dest_config.get("Type") == "SQS": resource = SQSQueue( resource_logical_id + "Queue", attributes=self.get_passthrough_resource_attributes() ) if dest_config.get("Type") == "SNS": resource = SNSTopic( resource_logical_id + "Topic", attributes=self.get_passthrough_resource_attributes() ) if combined_condition: resource.set_resource_attribute("Condition", combined_condition) if property_condition: destination["Destination"] = make_conditional( property_condition, resource.get_runtime_attr("arn"), dest_arn ) else: destination["Destination"] = resource.get_runtime_attr("arn") policy = self._add_event_invoke_managed_policy( dest_config, resource_logical_id, property_condition, destination["Destination"] ) else: raise InvalidResourceException( self.logical_id, "Destination is required if Type is not {}".format(auto_inject_list) ) if dest_config.get("Destination") is not None and property_condition is None: policy = self._add_event_invoke_managed_policy( dest_config, resource_logical_id, None, dest_config.get("Destination") ) return resource, destination, policy def _make_and_conditions(self, resource_condition, property_condition, conditions): if resource_condition is None: return property_condition if property_condition is None: return resource_condition and_condition = make_and_condition([{"Condition": resource_condition}, {"Condition": property_condition}]) condition_name = self._make_gen_condition_name(resource_condition + "AND" + property_condition, self.logical_id) conditions[condition_name] = and_condition return condition_name def _get_or_make_condition(self, destination, logical_id, conditions): """ This method checks if there is an If condition on Destination property. Since we auto create SQS and SNS if the destination ARN is not provided, we need to make sure that If condition is handled here. True case: Only create the Queue/Topic if the condition is true Destination: !If [SomeCondition, {Ref: AWS::NoValue}, queue-arn] False case : Only create the Queue/Topic if the condition is false. Destination: !If [SomeCondition, queue-arn, {Ref: AWS::NoValue}] For the false case, we need to add a new condition that negates the existing condition, and add that to the top-level Conditions. """ if destination is None: return None, None if is_intrinsic_if(destination): dest_list = destination.get("Fn::If") if is_intrinsic_no_value(dest_list[1]) and is_intrinsic_no_value(dest_list[2]): return None, None if is_intrinsic_no_value(dest_list[1]): return dest_list[0], dest_list[2] if is_intrinsic_no_value(dest_list[2]): condition = dest_list[0] not_condition = self._make_gen_condition_name("NOT" + condition, logical_id) conditions[not_condition] = make_not_conditional(condition) return not_condition, dest_list[1] return None, None def _make_gen_condition_name(self, name, hash_input): # Make sure the property name is not over 255 characters (CFN limit) hash_digest = logical_id_generator.LogicalIdGenerator("", hash_input).gen() condition_name = name + hash_digest if len(condition_name) > 255: return input(condition_name)[:255] return condition_name def _get_resolved_alias_name(self, property_name, original_alias_value, intrinsics_resolver): """ Alias names can be supplied as an intrinsic function. This method tries to extract alias name from a reference to a parameter. If it cannot completely resolve (ie. if a complex intrinsic function was used), then this method raises an exception. If alias name is just a plain string, it will return as is :param dict or string original_alias_value: Value of Alias property as provided by the customer :param samtranslator.intrinsics.resolver.IntrinsicsResolver intrinsics_resolver: Instance of the resolver that knows how to resolve parameter references :return string: Alias name :raises InvalidResourceException: If the value is a complex intrinsic function that cannot be resolved """ # Try to resolve. resolved_alias_name = intrinsics_resolver.resolve_parameter_refs(original_alias_value) if not isinstance(resolved_alias_name, string_types): # This is still a dictionary which means we are not able to completely resolve intrinsics raise InvalidResourceException( self.logical_id, "'{}' must be a string or a Ref to a template parameter".format(property_name) ) return resolved_alias_name def _construct_lambda_function(self): """Constructs and returns the Lambda function. :returns: a list containing the Lambda function and execution role resources :rtype: list """ lambda_function = LambdaFunction( self.logical_id, depends_on=self.depends_on, attributes=self.resource_attributes ) if self.FunctionName: lambda_function.FunctionName = self.FunctionName lambda_function.Handler = self.Handler lambda_function.Runtime = self.Runtime lambda_function.Description = self.Description lambda_function.MemorySize = self.MemorySize lambda_function.Timeout = self.Timeout lambda_function.VpcConfig = self.VpcConfig lambda_function.Role = self.Role lambda_function.Environment = self.Environment lambda_function.Code = self._construct_code_dict() lambda_function.KmsKeyArn = self.KmsKeyArn lambda_function.ReservedConcurrentExecutions = self.ReservedConcurrentExecutions lambda_function.Tags = self._construct_tag_list(self.Tags) lambda_function.Layers = self.Layers lambda_function.FileSystemConfigs = self.FileSystemConfigs lambda_function.ImageConfig = self.ImageConfig lambda_function.PackageType = self.PackageType if self.Tracing: lambda_function.TracingConfig = {"Mode": self.Tracing} if self.DeadLetterQueue: lambda_function.DeadLetterConfig = {"TargetArn": self.DeadLetterQueue["TargetArn"]} lambda_function.CodeSigningConfigArn = self.CodeSigningConfigArn self._validate_package_type(lambda_function) return lambda_function def _add_event_invoke_managed_policy(self, dest_config, logical_id, condition, dest_arn): policy = {} if dest_config and dest_config.get("Type"): if dest_config.get("Type") == "SQS": policy = IAMRolePolicies.sqs_send_message_role_policy(dest_arn, logical_id) if dest_config.get("Type") == "SNS": policy = IAMRolePolicies.sns_publish_role_policy(dest_arn, logical_id) # Event Bridge and Lambda Arns are passthrough. if dest_config.get("Type") == "EventBridge": policy = IAMRolePolicies.event_bus_put_events_role_policy(dest_arn, logical_id) if dest_config.get("Type") == "Lambda": policy = IAMRolePolicies.lambda_invoke_function_role_policy(dest_arn, logical_id) return policy def _construct_role(self, managed_policy_map, event_invoke_policies): """Constructs a Lambda execution role based on this SAM function's Policies property. :returns: the generated IAM Role :rtype: model.iam.IAMRole """ role_attributes = self.get_passthrough_resource_attributes() if self.AssumeRolePolicyDocument is not None: assume_role_policy_document = self.AssumeRolePolicyDocument else: assume_role_policy_document = IAMRolePolicies.lambda_assume_role_policy() managed_policy_arns = [ArnGenerator.generate_aws_managed_policy_arn("service-role/AWSLambdaBasicExecutionRole")] if self.Tracing: managed_policy_name = get_xray_managed_policy_name() managed_policy_arns.append(ArnGenerator.generate_aws_managed_policy_arn(managed_policy_name)) if self.VpcConfig: managed_policy_arns.append( ArnGenerator.generate_aws_managed_policy_arn("service-role/AWSLambdaVPCAccessExecutionRole") ) function_policies = ResourcePolicies( {"Policies": self.Policies}, # No support for policy templates in the "core" policy_template_processor=None, ) policy_documents = [] if self.DeadLetterQueue: policy_documents.append( IAMRolePolicies.dead_letter_queue_policy( self.dead_letter_queue_policy_actions[self.DeadLetterQueue["Type"]], self.DeadLetterQueue["TargetArn"], ) ) if self.EventInvokeConfig: if event_invoke_policies is not None: policy_documents.extend(event_invoke_policies) execution_role = construct_role_for_resource( resource_logical_id=self.logical_id, attributes=role_attributes, managed_policy_map=managed_policy_map, assume_role_policy_document=assume_role_policy_document, resource_policies=function_policies, managed_policy_arns=managed_policy_arns, policy_documents=policy_documents, permissions_boundary=self.PermissionsBoundary, tags=self._construct_tag_list(self.Tags), ) return execution_role def _validate_package_type(self, lambda_function): """ Validates Function based on the existence of Package type """ packagetype = lambda_function.PackageType or ZIP if packagetype not in [ZIP, IMAGE]: raise InvalidResourceException( lambda_function.logical_id, "PackageType needs to be `{zip}` or `{image}`".format(zip=ZIP, image=IMAGE), ) def _validate_package_type_zip(): if not all([lambda_function.Runtime, lambda_function.Handler]): raise InvalidResourceException( lambda_function.logical_id, "Runtime and Handler needs to be present when PackageType is of type `{zip}`".format(zip=ZIP), ) if any([lambda_function.Code.get("ImageUri", False), lambda_function.ImageConfig]): raise InvalidResourceException( lambda_function.logical_id, "ImageUri or ImageConfig cannot be present when PackageType is of type `{zip}`".format(zip=ZIP), ) def _validate_package_type_image(): if any([lambda_function.Handler, lambda_function.Runtime, lambda_function.Layers]): raise InvalidResourceException( lambda_function.logical_id, "Runtime, Handler, Layers cannot be present when PackageType is of type `{image}`".format( image=IMAGE ), ) if not lambda_function.Code.get("ImageUri"): raise InvalidResourceException( lambda_function.logical_id, "ImageUri needs to be present when PackageType is of type `{image}`".format(image=IMAGE), ) _validate_per_package_type = {ZIP: _validate_package_type_zip, IMAGE: _validate_package_type_image} # Call appropriate validation function based on the package type. return _validate_per_package_type[packagetype]() def _validate_dlq(self): """Validates whether the DeadLetterQueue LogicalId is validation :raise: InvalidResourceException """ # Validate required logical ids valid_dlq_types = str(list(self.dead_letter_queue_policy_actions.keys())) if not self.DeadLetterQueue.get("Type") or not self.DeadLetterQueue.get("TargetArn"): raise InvalidResourceException( self.logical_id, "'DeadLetterQueue' requires Type and TargetArn properties to be specified.".format(valid_dlq_types), ) # Validate required Types if not self.DeadLetterQueue["Type"] in self.dead_letter_queue_policy_actions: raise InvalidResourceException( self.logical_id, "'DeadLetterQueue' requires Type of {}".format(valid_dlq_types) ) def _event_resources_to_link(self, resources): event_resources = {} if self.Events: for logical_id, event_dict in self.Events.items(): try: event_source = self.event_resolver.resolve_resource_type(event_dict).from_dict( self.logical_id + logical_id, event_dict, logical_id ) except (TypeError, AttributeError) as e: raise InvalidEventException(logical_id, "{}".format(e)) event_resources[logical_id] = event_source.resources_to_link(resources) return event_resources @staticmethod def order_events(event): """ Helper method for sorting Function Events. Returns a key to use in sorting this event This is mainly used for HttpApi Events, where we need to evaluate the "$default" path (if any) before we evaluate any of the other paths ("/", etc), so we can make sure we don't create any redundant permissions. This sort places "$" before "/" or any alphanumeric characters. :param event: tuple of (logical_id, event_dictionary) that contains event information """ logical_id, event_dict = event if not isinstance(event_dict, dict): return logical_id return event_dict.get("Properties", {}).get("Path", logical_id) def _generate_event_resources( self, lambda_function, execution_role, event_resources, intrinsics_resolver, lambda_alias=None ): """Generates and returns the resources associated with this function's events. :param model.lambda_.LambdaFunction lambda_function: generated Lambda function :param iam.IAMRole execution_role: generated Lambda execution role :param implicit_api: Global Implicit API resource where the implicit APIs get attached to, if necessary :param implicit_api_stage: Global implicit API stage resource where implicit APIs get attached to, if necessary :param event_resources: All the event sources associated with this Lambda function :param model.lambda_.LambdaAlias lambda_alias: Optional Lambda Alias resource if we want to connect the event sources to this alias :returns: a list containing the function's event resources :rtype: list """ resources = [] if self.Events: for logical_id, event_dict in sorted(self.Events.items(), key=SamFunction.order_events): try: eventsource = self.event_resolver.resolve_resource_type(event_dict).from_dict( lambda_function.logical_id + logical_id, event_dict, logical_id ) except TypeError as e: raise InvalidEventException(logical_id, "{}".format(e)) kwargs = { # When Alias is provided, connect all event sources to the alias and *not* the function "function": lambda_alias or lambda_function, "role": execution_role, "intrinsics_resolver": intrinsics_resolver, } for name, resource in event_resources[logical_id].items(): kwargs[name] = resource resources += eventsource.to_cloudformation(**kwargs) return resources def _construct_code_dict(self): """Constructs Lambda Code Dictionary based on the accepted SAM artifact properties such as `InlineCode`, `CodeUri` and `ImageUri` and also raises errors if more than one of them is defined. `PackageType` determines which artifacts are considered. :raises InvalidResourceException when conditions on the SAM artifact properties are not met. """ # list of accepted artifacts packagetype = self.PackageType or ZIP artifacts = {} if packagetype == ZIP: artifacts = {"InlineCode": self.InlineCode, "CodeUri": self.CodeUri} elif packagetype == IMAGE: artifacts = {"ImageUri": self.ImageUri} if packagetype not in [ZIP, IMAGE]: raise InvalidResourceException(self.logical_id, "invalid 'PackageType' : {}".format(packagetype)) # Inline function for transformation of inline code. # It accepts arbitrary argumemnts, because the arguments do not matter for the result. def _construct_inline_code(*args, **kwargs): return {"ZipFile": self.InlineCode} # dispatch mechanism per artifact on how it needs to be transformed. artifact_dispatch = { "InlineCode": _construct_inline_code, "CodeUri": construct_s3_location_object, "ImageUri": construct_image_code_object, } filtered_artifacts = dict(filter(lambda x: x[1] != None, artifacts.items())) # There are more than one allowed artifact types present, raise an Error. # There are no valid artifact types present, also raise an Error. if len(filtered_artifacts) > 1 or len(filtered_artifacts) == 0: if packagetype == ZIP and len(filtered_artifacts) == 0: raise InvalidResourceException(self.logical_id, "Only one of 'InlineCode' or 'CodeUri' can be set.") elif packagetype == IMAGE: raise InvalidResourceException(self.logical_id, "'ImageUri' must be set.") filtered_keys = [key for key in filtered_artifacts.keys()] # NOTE(sriram-mv): This precedence order is important. It is protect against python2 vs python3 # dictionary ordering when getting the key values with .keys() on a dictionary. # Do not change this precedence order. if "InlineCode" in filtered_keys: filtered_key = "InlineCode" elif "CodeUri" in filtered_keys: filtered_key = "CodeUri" elif "ImageUri" in filtered_keys: filtered_key = "ImageUri" else: raise InvalidResourceException(self.logical_id, "Either 'InlineCode' or 'CodeUri' must be set.") dispatch_function = artifact_dispatch[filtered_key] return dispatch_function(artifacts[filtered_key], self.logical_id, filtered_key) def _construct_version(self, function, intrinsics_resolver, code_sha256=None): """Constructs a Lambda Version resource that will be auto-published when CodeUri of the function changes. Old versions will not be deleted without a direct reference from the CloudFormation template. :param model.lambda_.LambdaFunction function: Lambda function object that is being connected to a version :param model.intrinsics.resolver.IntrinsicsResolver intrinsics_resolver: Class that can help resolve references to parameters present in CodeUri. It is a common usecase to set S3Key of Code to be a template parameter. Need to resolve the values otherwise we will never detect a change in Code dict :param str code_sha256: User predefined hash of the Lambda function code :return: Lambda function Version resource """ code_dict = function.Code if not code_dict: raise ValueError("Lambda function code must be a valid non-empty dictionary") if not intrinsics_resolver: raise ValueError("intrinsics_resolver is required for versions creation") # Resolve references to template parameters before creating hash. This will *not* resolve all intrinsics # because we cannot resolve runtime values like Arn of a resource. For purposes of detecting changes, this # is good enough. Here is why: # # When using intrinsic functions there are two cases when has must change: # - Value of the template parameter changes # - (or) LogicalId of a referenced resource changes ie. !GetAtt NewResource.Arn # # Later case will already change the hash because some value in the Code dictionary changes. We handle the # first case by resolving references to template parameters. It is okay even if these references are # present inside another intrinsic such as !Join. The resolver will replace the reference with the parameter's # value and keep all other parts of !Join identical. This will still trigger a change in the hash. code_dict = intrinsics_resolver.resolve_parameter_refs(code_dict) # Construct the LogicalID of Lambda version by appending 10 characters of SHA of CodeUri. This is necessary # to trigger creation of a new version every time code location changes. Since logicalId changes, CloudFormation # will drop the old version and create a new one for us. We set a DeletionPolicy on the version resource to # prevent CloudFormation from actually deleting the underlying version resource # # SHA Collisions: For purposes of triggering a new update, we are concerned about just the difference previous # and next hashes. The chances that two subsequent hashes collide is fairly low. prefix = "{id}Version".format(id=self.logical_id) logical_dict = {} try: logical_dict = code_dict.copy() except (AttributeError, UnboundLocalError): pass else: if function.Environment: logical_dict.update(function.Environment) if function.MemorySize: logical_dict.update({"MemorySize": function.MemorySize}) logical_id = logical_id_generator.LogicalIdGenerator(prefix, logical_dict, code_sha256).gen() attributes = self.get_passthrough_resource_attributes() if attributes is None: attributes = {} if "DeletionPolicy" not in attributes: attributes["DeletionPolicy"] = "Retain" lambda_version = LambdaVersion(logical_id=logical_id, attributes=attributes) lambda_version.FunctionName = function.get_runtime_attr("name") lambda_version.Description = self.VersionDescription return lambda_version def _construct_alias(self, name, function, version): """Constructs a Lambda Alias for the given function and pointing to the given version :param string name: Name of the alias :param model.lambda_.LambdaFunction function: Lambda function object to associate the alias with :param model.lambda_.LambdaVersion version: Lambda version object to associate the alias with :return: Lambda alias object :rtype model.lambda_.LambdaAlias """ if not name: raise InvalidResourceException(self.logical_id, "Alias name is required to create an alias") logical_id = "{id}Alias{suffix}".format(id=function.logical_id, suffix=name) alias = LambdaAlias(logical_id=logical_id, attributes=self.get_passthrough_resource_attributes()) alias.Name = name alias.FunctionName = function.get_runtime_attr("name") alias.FunctionVersion = version.get_runtime_attr("version") if self.ProvisionedConcurrencyConfig: alias.ProvisionedConcurrencyConfig = self.ProvisionedConcurrencyConfig return alias def _validate_deployment_preference_and_add_update_policy( self, deployment_preference_collection, lambda_alias, intrinsics_resolver, mappings_resolver ): if "Enabled" in self.DeploymentPreference: # resolve intrinsics and mappings for Type enabled = self.DeploymentPreference["Enabled"] enabled = intrinsics_resolver.resolve_parameter_refs(enabled) enabled = mappings_resolver.resolve_parameter_refs(enabled) self.DeploymentPreference["Enabled"] = enabled if "Type" in self.DeploymentPreference: # resolve intrinsics and mappings for Type preference_type = self.DeploymentPreference["Type"] preference_type = intrinsics_resolver.resolve_parameter_refs(preference_type) preference_type = mappings_resolver.resolve_parameter_refs(preference_type) self.DeploymentPreference["Type"] = preference_type if deployment_preference_collection is None: raise ValueError("deployment_preference_collection required for parsing the deployment preference") deployment_preference_collection.add(self.logical_id, self.DeploymentPreference) if deployment_preference_collection.get(self.logical_id).enabled: if self.AutoPublishAlias is None: raise InvalidResourceException( self.logical_id, "'DeploymentPreference' requires AutoPublishAlias property to be specified." ) if lambda_alias is None: raise ValueError("lambda_alias expected for updating it with the appropriate update policy") lambda_alias.set_resource_attribute( "UpdatePolicy", deployment_preference_collection.update_policy(self.logical_id).to_dict() ) class SamCanary(SamResourceMacro): """SAM canary macro.""" resource_type = "AWS::Serverless::Canary" property_types = { "FunctionName": PropertyType(False, one_of(is_str(), is_type(dict))), "Handler": PropertyType(True, is_str()), "Runtime": PropertyType(True, is_str()), "CodeUri": PropertyType(False, one_of(is_str(), is_type(dict))), "InlineCode": PropertyType(False, one_of(is_str(), is_type(dict))), "MemorySize": PropertyType(False, is_type(int)), "Tags": PropertyType(False, is_type(dict)), # Easier to pass through as AWS::Synthetics::Canary only accepts a boolean "ActiveTracing": PropertyType(False, is_type(bool)), "AssumeRolePolicyDocument": PropertyType(False, is_type(dict)), "Timeout": PropertyType(False, is_type(int)), "Role": PropertyType(False, is_str()), "Schedule": PropertyType(True, is_type(dict)), "StartCanaryAfterCreation": PropertyType(True, is_type(bool)), "ArtifactS3Location": PropertyType(False, one_of(is_type(dict), is_str())), "FailureRetentionPeriod": PropertyType(False, is_type(int)), "SuccessRetentionPeriod": PropertyType(False, is_type(int)), "VpcConfig": PropertyType(False, is_type(dict)), "Environment": PropertyType(False, dict_of(is_str(), is_type(dict))), "Policies": PropertyType(False, one_of(is_str(), is_type(dict), list_of(one_of(is_str(), is_type(dict))))), "CanaryMetricAlarms": PropertyType(False, list_of(is_type(dict))), } def to_cloudformation(self, **kwargs): """Returns the Synthetics Canary to which this SAM Canary corresponds. :param dict kwargs: already-converted resources that may need to be modified when converting this \ macro to pure CloudFormation :returns: a list of vanilla CloudFormation Resources, to which this Serverless Canary expands :rtype: list """ resources = [] managed_policy_map = kwargs.get("managed_policy_map", {}) synthetics_canary = self._construct_synthetics_canary() resources.append(synthetics_canary) # A S3 Bucket resource will be added to the transformed template if the user doesn't provide an artifact # bucket to store canary results artifact_bucket_name = "" if not self.ArtifactS3Location: s3bucket = self._construct_artifact_bucket() resources.append(s3bucket) synthetics_canary.ArtifactS3Location = {"Fn::Join": ["", ["s3://", {"Ref": s3bucket.logical_id}]]} artifact_bucket_name = {"Ref": s3bucket.logical_id} if not self.Role: role = self._construct_role(artifact_bucket_name, managed_policy_map) resources.append(role) synthetics_canary.ExecutionRoleArn = role.get_runtime_attr("arn") if self.CanaryMetricAlarms: self._validate_cloudwatch_alarms() for alarm_dict in self.CanaryMetricAlarms: resources.append(self._construct_cloudwatch_alarm(alarm_dict)) return resources def _validate_cloudwatch_alarms(self): """Validates the CanaryMetricAlarms property in Serverless Canary The property should follow the following structure CanaryMetricAlarms: - AlarmName: MetricName (required): one of the metrics in VALID_CANARY_METRICS Threshold (optional): any value of type double ComparisonOperator (optional): any of the valid values (https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-cw-alarm.html#cfn-cloudwatch-alarms-comparisonoperator) Period (optional): Integer that is 10, 30, 60, or any multiple of 60 Note: Alarm names are used as logical ids for their respective CloudWatchAlarm property so if user has multiple alarms there should be no duplicate names as we don't want the alarms to override each other without the user's knowledge :raise: InvalidResourceException """ # keeps list of alarm names to make sure there are no duplicates list_of_alarm_names = [] for alarm_dict in self.CanaryMetricAlarms: # Throw an error if there is more than one alarm in the array index, like for example # CanaryMetricAlarms: # - Alarm1: # MetricName: SuccessPercent # Alarm2: # MetricName: SuccessPercent # Threshold: 90 # - Alarm3: # MetricName: Failed # throws an error for Alarm2 since its Alarm1 is already defined in that dict if len(alarm_dict) != 1: raise InvalidResourceException(self.logical_id, "Must have one alarm per array index") # get the alarm name and the properties the user defined for the alarm alarm_name = next(iter(alarm_dict)) alarm_item = alarm_dict[alarm_name] # MetricName property is required if alarm_item is None or "MetricName" not in alarm_item: raise InvalidResourceException( self.logical_id, "CloudWatch alarm '{key}' is missing required property 'MetricName'.".format(key=alarm_name), ) metric_name = alarm_item["MetricName"] # MetricName must be one of the values in VALID_CANARY_METRICS if metric_name not in VALID_CANARY_METRICS: raise InvalidResourceException( self.logical_id, "MetricName needs to be one of {}".format(VALID_CANARY_METRICS), ) # make sure all the alarm names are unique if alarm_name in list_of_alarm_names: raise InvalidResourceException(self.logical_id, "Duplicate CloudWatch alarm names") else: list_of_alarm_names.append(alarm_name) def _construct_cloudwatch_alarm(self, alarm_dict): """Constructs an CloudWatch::Alarm resource if the user specifies the CloudWatchAlarm property in Serverless Canary :param dict alarm_dict: Alarm name and properties as provided by the customer :returns: the generated CloudWatch Alarm :rtype: model.cloudwatch.CloudWatchAlarm """ # gets alarm name and the properties defined by user alarm_name = next(iter(alarm_dict)) alarm_item = alarm_dict[alarm_name] cloudwatch_alarm = CloudWatchAlarm( logical_id=alarm_name, depends_on=self.depends_on, attributes=self.get_passthrough_resource_attributes(), ) # default settings for the CloudWatch alarms # the settings are identical to the Alarms that are made by Synthetics Canary using their dashboard cloudwatch_alarm.MetricName = alarm_item["MetricName"] cloudwatch_alarm.Namespace = "CloudWatchSynthetics" cloudwatch_alarm.EvaluationPeriods = 1 cloudwatch_alarm.Statistic = "Sum" cloudwatch_alarm.TreatMissingData = "notBreaching" # connects the alarm to the metric produced by the Synthetics canary from this Serverless resource cloudwatch_alarm.Dimensions = [{"Name": "CanaryName", "Value": {"Ref": self.logical_id}}] # set the values if user provides them, if not set them to default value based on the MetricName cloudwatch_alarm.ComparisonOperator = alarm_item.get( "ComparisonOperator", DEFAULT_METRIC_VALUES[alarm_item["MetricName"]]["ComparisonOperator"] ) cloudwatch_alarm.Threshold = float( alarm_item.get("Threshold", DEFAULT_METRIC_VALUES[alarm_item["MetricName"]]["Threshold"]) ) cloudwatch_alarm.Period = alarm_item.get("Period", DEFAULT_METRIC_VALUES[alarm_item["MetricName"]]["Period"]) return cloudwatch_alarm def _construct_role(self, artifact_bucket_name, managed_policy_map): """Constructs an IAM:Role resource only if user doesn't specify Role property in Serverless Canary - If the ArtifactS3Location property isn't specified then the the policies to execute the Canary and handle the resulting data will be added - If the Tracing property is enabled then the XRay policy based on the user's region will be added - If the VpcConfig property is specified then the policy to execute VPC will be added - If the Policies property is specified then the that will be appended to the IAM::Role's Policies property :returns: the generated IAM Role :rtype: model.iam.IAMRole """ role_attributes = self.get_passthrough_resource_attributes() if self.AssumeRolePolicyDocument: assume_role_policy_document = self.AssumeRolePolicyDocument else: assume_role_policy_document = IAMRolePolicies.lambda_assume_role_policy() # add AWS managed policies if user has enabled VpcConfig or Tracing managed_policy_arns = [] if self.VpcConfig: managed_policy_arns.append( ArnGenerator.generate_aws_managed_policy_arn("service-role/AWSLambdaVPCAccessExecutionRole") ) if self.ActiveTracing is True: managed_policy_name = get_xray_managed_policy_name() managed_policy_arns.append(ArnGenerator.generate_aws_managed_policy_arn(managed_policy_name)) # if user has defined Policies property, those policies will be appended to this role function_policies = ResourcePolicies( {"Policies": self.Policies}, # No support for policy templates in the "core" policy_template_processor=None, ) # The policy to execute the canary is only added to the role if the user hasn't defined ArtifactS3Location # this emulates CloudWatch Synthetics Canary dashboard's behavior policy_documents = [] if self.ArtifactS3Location is None: policy_documents.extend( ( IAMRolePolicies.canary_put_artifacts_in_s3_policy( logical_id=self.logical_id, result_bucket=artifact_bucket_name ), IAMRolePolicies.canary_put_logs_policy(logical_id=self.logical_id), IAMRolePolicies.canary_put_metric_data_policy(logical_id=self.logical_id), ) ) execution_role = construct_role_for_resource( resource_logical_id=self.logical_id, attributes=role_attributes, managed_policy_map=managed_policy_map, assume_role_policy_document=assume_role_policy_document, resource_policies=function_policies, managed_policy_arns=managed_policy_arns, policy_documents=policy_documents, permissions_boundary=None, tags=self._construct_tag_list(self.Tags), ) return execution_role def _construct_artifact_bucket(self): """Constructs a S3Bucket resource to store canary artifacts. :returns: the generated S3Bucket :rtype: model.s3.S3Bucket """ # Construct the LogicalId of S3Bucket by appending ArtifactBucket to the Canary LogicalId. Once deployed, the # bucket name will be automatically generated by Cloudformation. # https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-name.html logical_id = self.logical_id + "ArtifactBucket" # Set the DeletionPolicy of the S3 resource to Retain to prevent CloudFormation from trying to delete the # bucket when its not empty. This is necessary because if a user creates and runs a serverless canary without # an artifact bucket, then tries to delete/replace that resource, CloudFormation will try to delete the # artifact bucket made by SAM which will throw an error since its not empty. Retaining the bucket will bypass # this error. passthrough_attributes = self.get_passthrough_resource_attributes() if passthrough_attributes is None: passthrough_attributes = {} passthrough_attributes["DeletionPolicy"] = "Retain" s3bucket = S3Bucket( logical_id=logical_id, depends_on=self.depends_on, attributes=passthrough_attributes, ) s3bucket.BucketEncryption = { "ServerSideEncryptionConfiguration": [{"ServerSideEncryptionByDefault": {"SSEAlgorithm": "AES256"}}] } s3bucket.Tags = self._construct_tag_list(self.Tags) return s3bucket def _construct_synthetics_canary(self): """Constructs a AWS::Synthetics::Canary resource.""" canary = SyntheticsCanary( self.logical_id, depends_on=self.depends_on, attributes=self.get_passthrough_resource_attributes() ) canary.ArtifactS3Location = self.ArtifactS3Location canary.Code = self._construct_code_dict canary.ExecutionRoleArn = self.Role canary.FailureRetentionPeriod = self.FailureRetentionPeriod # constructs default name if FunctionName isn't provided because Synthetics Canary resource requires a Name, # also requires it be lower case canary.Name = self.FunctionName if self.FunctionName else self._construct_canary_name() canary.RuntimeVersion = self.Runtime canary.Schedule = self.Schedule canary.StartCanaryAfterCreation = self.StartCanaryAfterCreation canary.SuccessRetentionPeriod = self.SuccessRetentionPeriod canary.Tags = self._construct_tag_list(self.Tags) canary.VPCConfig = self.VpcConfig if self.ActiveTracing or self.Environment or self.MemorySize or self.Timeout: canary.RunConfig = self._construct_run_config() return canary def _construct_canary_name(self): """ Need to construct canary name since the Name property is required in AWS::Synthetics::Canary and CloudFormation doesn't automatically generate one upon deployment Synthetics Canary name is limited to 21 characters https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-synthetics-canary.html#cfn-synthetics-canary-name len(prefix) + MAX_CANARY_LOGICAL_ID_LENGTH + MAX_CANARY_UNIQUE_ID_LENGTH + 1 (extra '-' char added) must be less than or equal to 21 """ logical_id_lowered = self.logical_id.lower()[:MAX_CANARY_LOGICAL_ID_LENGTH] + "-" suffix = uuid.uuid4().hex[:MAX_CANARY_UNIQUE_ID_LENGTH] return CANARY_NAME_PREFIX + logical_id_lowered + suffix @staticmethod def _extract_not_none_properties(d): """ Filters out and returns not None properties """ return {k: v for k, v in d if v is not None} def _construct_run_config(self): """ If the user specifies any of Tracing, MemorySize, Timeout or Environment then the RunConfig resource in the transformed AWS::Synthetics::Canary needs to be added. Note, for Environment property the syntax in AWS::Serverless::Canary is Environment: Variables: Var1: Var2 while in AWS::Synthetics::Canary its EnvironmentVariables: Var1: Var2 so it needs to be transformed accordingly """ runconfig = { "ActiveTracing": self.ActiveTracing, "MemoryInMB": self.MemorySize, "TimeoutInSeconds": self.Timeout, } if self.Environment: runconfig["EnvironmentVariables"] = self.Environment["Variables"] return self._extract_not_none_properties(runconfig.items()) @property def _construct_code_dict(self): """Constructs Synthetics Canary Code Dictionary based on the accepted SAM artifact properties such as `InlineCode` and `CodeUri` :raises InvalidResourceException when conditions on the SAM artifact properties are not met. """ # accepted artifacts artifacts = {"InlineCode": self.InlineCode, "CodeUri": self.CodeUri} filtered_artifacts = self._extract_not_none_properties(artifacts.items()) filtered_artifact_keys = list(filtered_artifacts.keys()) # Note: To emulate the same behavior as SAM Function, if user includes both InlineCode and CodeUri, # InlineCode will take priority if "InlineCode" in filtered_artifact_keys: # Inline function for transformation of inline code. return {"Handler": self.Handler, "Script": self.InlineCode} elif "CodeUri" in filtered_artifact_keys: # extracts Bucket and Key values, adds Handler and extracted values to Code object code = construct_s3_location_object(self.CodeUri, self.logical_id, "CodeUri") code["Handler"] = self.Handler return code else: raise InvalidResourceException(self.logical_id, "Either 'InlineCode' or 'CodeUri' must be set.") class SamApi(SamResourceMacro): """SAM rest API macro.""" resource_type = "AWS::Serverless::Api" property_types = { # Internal property set only by Implicit API plugin. If set to True, the API Event Source code will inject # Lambda Integration URI to the Swagger. To preserve backwards compatibility, this must be set only for # Implicit APIs. For Explicit APIs, customer is expected to set integration URI themselves. # In the future, we might rename and expose this property to customers so they can have SAM manage Explicit APIs # Swagger. "__MANAGE_SWAGGER": PropertyType(False, is_type(bool)), "Name": PropertyType(False, one_of(is_str(), is_type(dict))), "StageName": PropertyType(True, one_of(is_str(), is_type(dict))), "Tags": PropertyType(False, is_type(dict)), "DefinitionBody": PropertyType(False, is_type(dict)), "DefinitionUri": PropertyType(False, one_of(is_str(), is_type(dict))), "CacheClusterEnabled": PropertyType(False, is_type(bool)), "CacheClusterSize": PropertyType(False, is_str()), "Variables": PropertyType(False, is_type(dict)), "EndpointConfiguration": PropertyType(False, one_of(is_str(), is_type(dict))), "MethodSettings": PropertyType(False, is_type(list)), "BinaryMediaTypes": PropertyType(False, is_type(list)), "MinimumCompressionSize": PropertyType(False, is_type(int)), "Cors": PropertyType(False, one_of(is_str(), is_type(dict))), "Auth": PropertyType(False, is_type(dict)), "GatewayResponses": PropertyType(False, is_type(dict)), "AccessLogSetting": PropertyType(False, is_type(dict)), "CanarySetting": PropertyType(False, is_type(dict)), "TracingEnabled": PropertyType(False, is_type(bool)), "OpenApiVersion": PropertyType(False, is_str()), "Models": PropertyType(False, is_type(dict)), "Domain": PropertyType(False, is_type(dict)), "Description": PropertyType(False, is_str()), "Mode": PropertyType(False, is_str()), } referable_properties = { "Stage": ApiGatewayStage.resource_type, "Deployment": ApiGatewayDeployment.resource_type, "DomainName": ApiGatewayDomainName.resource_type, "UsagePlan": ApiGatewayUsagePlan.resource_type, "UsagePlanKey": ApiGatewayUsagePlanKey.resource_type, "ApiKey": ApiGatewayApiKey.resource_type, } def to_cloudformation(self, **kwargs): """Returns the API Gateway RestApi, Deployment, and Stage to which this SAM Api corresponds. :param dict kwargs: already-converted resources that may need to be modified when converting this \ macro to pure CloudFormation :returns: a list of vanilla CloudFormation Resources, to which this Function expands :rtype: list """ resources = [] intrinsics_resolver = kwargs["intrinsics_resolver"] self.BinaryMediaTypes = intrinsics_resolver.resolve_parameter_refs(self.BinaryMediaTypes) self.Domain = intrinsics_resolver.resolve_parameter_refs(self.Domain) self.Auth = intrinsics_resolver.resolve_parameter_refs(self.Auth) redeploy_restapi_parameters = kwargs.get("redeploy_restapi_parameters") shared_api_usage_plan = kwargs.get("shared_api_usage_plan") template_conditions = kwargs.get("conditions") api_generator = ApiGenerator( self.logical_id, self.CacheClusterEnabled, self.CacheClusterSize, self.Variables, self.depends_on, self.DefinitionBody, self.DefinitionUri, self.Name, self.StageName, shared_api_usage_plan, template_conditions, tags=self.Tags, endpoint_configuration=self.EndpointConfiguration, method_settings=self.MethodSettings, binary_media=self.BinaryMediaTypes, minimum_compression_size=self.MinimumCompressionSize, cors=self.Cors, auth=self.Auth, gateway_responses=self.GatewayResponses, access_log_setting=self.AccessLogSetting, canary_setting=self.CanarySetting, tracing_enabled=self.TracingEnabled, resource_attributes=self.resource_attributes, passthrough_resource_attributes=self.get_passthrough_resource_attributes(), open_api_version=self.OpenApiVersion, models=self.Models, domain=self.Domain, description=self.Description, mode=self.Mode, ) ( rest_api, deployment, stage, permissions, domain, basepath_mapping, route53, usage_plan_resources, ) = api_generator.to_cloudformation(redeploy_restapi_parameters) resources.extend([rest_api, deployment, stage]) resources.extend(permissions) if domain: resources.extend([domain]) if basepath_mapping: resources.extend(basepath_mapping) if route53: resources.extend([route53]) # contains usage plan, api key and usageplan key resources if usage_plan_resources: resources.extend(usage_plan_resources) return resources class SamHttpApi(SamResourceMacro): """SAM rest API macro.""" resource_type = "AWS::Serverless::HttpApi" property_types = { # Internal property set only by Implicit HTTP API plugin. If set to True, the API Event Source code will # inject Lambda Integration URI to the OpenAPI. To preserve backwards compatibility, this must be set only for # Implicit APIs. For Explicit APIs, this is managed by the DefaultDefinitionBody Plugin. # In the future, we might rename and expose this property to customers so they can have SAM manage Explicit APIs # Swagger. "__MANAGE_SWAGGER": PropertyType(False, is_type(bool)), "StageName": PropertyType(False, one_of(is_str(), is_type(dict))), "Tags": PropertyType(False, is_type(dict)), "DefinitionBody": PropertyType(False, is_type(dict)), "DefinitionUri": PropertyType(False, one_of(is_str(), is_type(dict))), "StageVariables": PropertyType(False, is_type(dict)), "CorsConfiguration": PropertyType(False, one_of(is_type(bool), is_type(dict))), "AccessLogSettings": PropertyType(False, is_type(dict)), "DefaultRouteSettings": PropertyType(False, is_type(dict)), "Auth": PropertyType(False, is_type(dict)), "RouteSettings": PropertyType(False, is_type(dict)), "Domain": PropertyType(False, is_type(dict)), "FailOnWarnings": PropertyType(False, is_type(bool)), "Description": PropertyType(False, is_str()), "DisableExecuteApiEndpoint": PropertyType(False, is_type(bool)), } referable_properties = { "Stage": ApiGatewayV2Stage.resource_type, "DomainName": ApiGatewayV2DomainName.resource_type, } def to_cloudformation(self, **kwargs): """Returns the API GatewayV2 Api, Deployment, and Stage to which this SAM Api corresponds. :param dict kwargs: already-converted resources that may need to be modified when converting this \ macro to pure CloudFormation :returns: a list of vanilla CloudFormation Resources, to which this Function expands :rtype: list """ resources = [] intrinsics_resolver = kwargs["intrinsics_resolver"] self.CorsConfiguration = intrinsics_resolver.resolve_parameter_refs(self.CorsConfiguration) intrinsics_resolver = kwargs["intrinsics_resolver"] self.Domain = intrinsics_resolver.resolve_parameter_refs(self.Domain) api_generator = HttpApiGenerator( self.logical_id, self.StageVariables, self.depends_on, self.DefinitionBody, self.DefinitionUri, self.StageName, tags=self.Tags, auth=self.Auth, cors_configuration=self.CorsConfiguration, access_log_settings=self.AccessLogSettings, route_settings=self.RouteSettings, default_route_settings=self.DefaultRouteSettings, resource_attributes=self.resource_attributes, passthrough_resource_attributes=self.get_passthrough_resource_attributes(), domain=self.Domain, fail_on_warnings=self.FailOnWarnings, description=self.Description, disable_execute_api_endpoint=self.DisableExecuteApiEndpoint, ) ( http_api, stage, domain, basepath_mapping, route53, ) = api_generator.to_cloudformation() resources.append(http_api) if domain: resources.append(domain) if basepath_mapping: resources.extend(basepath_mapping) if route53: resources.append(route53) # Stage is now optional. Only add it if one is created. if stage: resources.append(stage) return resources class SamSimpleTable(SamResourceMacro): """SAM simple table macro.""" resource_type = "AWS::Serverless::SimpleTable" property_types = { "PrimaryKey": PropertyType(False, dict_of(is_str(), is_str())), "ProvisionedThroughput": PropertyType(False, dict_of(is_str(), one_of(is_type(int), is_type(dict)))), "TableName": PropertyType(False, one_of(is_str(), is_type(dict))), "Tags": PropertyType(False, is_type(dict)), "SSESpecification": PropertyType(False, is_type(dict)), } attribute_type_conversions = {"String": "S", "Number": "N", "Binary": "B"} def to_cloudformation(self, **kwargs): dynamodb_resources = self._construct_dynamodb_table() return [dynamodb_resources] def _construct_dynamodb_table(self): dynamodb_table = DynamoDBTable(self.logical_id, depends_on=self.depends_on, attributes=self.resource_attributes) if self.PrimaryKey: if "Name" not in self.PrimaryKey or "Type" not in self.PrimaryKey: raise InvalidResourceException( self.logical_id, "'PrimaryKey' is missing required Property 'Name' or 'Type'." ) primary_key = { "AttributeName": self.PrimaryKey["Name"], "AttributeType": self._convert_attribute_type(self.PrimaryKey["Type"]), } else: primary_key = {"AttributeName": "id", "AttributeType": "S"} dynamodb_table.AttributeDefinitions = [primary_key] dynamodb_table.KeySchema = [{"AttributeName": primary_key["AttributeName"], "KeyType": "HASH"}] if self.ProvisionedThroughput: dynamodb_table.ProvisionedThroughput = self.ProvisionedThroughput else: dynamodb_table.BillingMode = "PAY_PER_REQUEST" if self.SSESpecification: dynamodb_table.SSESpecification = self.SSESpecification if self.TableName: dynamodb_table.TableName = self.TableName if bool(self.Tags): dynamodb_table.Tags = get_tag_list(self.Tags) return dynamodb_table def _convert_attribute_type(self, attribute_type): if attribute_type in self.attribute_type_conversions: return self.attribute_type_conversions[attribute_type] raise InvalidResourceException(self.logical_id, "Invalid 'Type' \"{actual}\".".format(actual=attribute_type)) class SamApplication(SamResourceMacro): """SAM application macro.""" APPLICATION_ID_KEY = "ApplicationId" SEMANTIC_VERSION_KEY = "SemanticVersion" resource_type = "AWS::Serverless::Application" # The plugin will always insert the TemplateUrl parameter property_types = { "Location": PropertyType(True, one_of(is_str(), is_type(dict))), "TemplateUrl": PropertyType(False, is_str()), "Parameters": PropertyType(False, is_type(dict)), "NotificationARNs": PropertyType(False, list_of(one_of(is_str(), is_type(dict)))), "Tags": PropertyType(False, is_type(dict)), "TimeoutInMinutes": PropertyType(False, is_type(int)), } def to_cloudformation(self, **kwargs): """Returns the stack with the proper parameters for this application""" nested_stack = self._construct_nested_stack() return [nested_stack] def _construct_nested_stack(self): """Constructs a AWS::CloudFormation::Stack resource""" nested_stack = NestedStack( self.logical_id, depends_on=self.depends_on, attributes=self.get_passthrough_resource_attributes() ) nested_stack.Parameters = self.Parameters nested_stack.NotificationARNs = self.NotificationARNs application_tags = self._get_application_tags() nested_stack.Tags = self._construct_tag_list(self.Tags, application_tags) nested_stack.TimeoutInMinutes = self.TimeoutInMinutes nested_stack.TemplateURL = self.TemplateUrl if self.TemplateUrl else "" return nested_stack def _get_application_tags(self): """Adds tags to the stack if this resource is using the serverless app repo""" application_tags = {} if isinstance(self.Location, dict): if self.APPLICATION_ID_KEY in self.Location.keys() and self.Location[self.APPLICATION_ID_KEY] is not None: application_tags[self._SAR_APP_KEY] = self.Location[self.APPLICATION_ID_KEY] if ( self.SEMANTIC_VERSION_KEY in self.Location.keys() and self.Location[self.SEMANTIC_VERSION_KEY] is not None ): application_tags[self._SAR_SEMVER_KEY] = self.Location[self.SEMANTIC_VERSION_KEY] return application_tags class SamLayerVersion(SamResourceMacro): """SAM Layer macro""" resource_type = "AWS::Serverless::LayerVersion" property_types = { "LayerName": PropertyType(False, one_of(is_str(), is_type(dict))), "Description": PropertyType(False, is_str()), "ContentUri": PropertyType(True, one_of(is_str(), is_type(dict))), "CompatibleRuntimes": PropertyType(False, list_of(one_of(is_str(), is_type(dict)))), "LicenseInfo": PropertyType(False, is_str()), "RetentionPolicy": PropertyType(False, is_str()), } RETAIN = "Retain" DELETE = "Delete" retention_policy_options = [RETAIN.lower(), DELETE.lower()] def to_cloudformation(self, **kwargs): """Returns the Lambda layer to which this SAM Layer corresponds. :param dict kwargs: already-converted resources that may need to be modified when converting this \ macro to pure CloudFormation :returns: a list of vanilla CloudFormation Resources, to which this Function expands :rtype: list """ resources = [] # Append any CFN resources: intrinsics_resolver = kwargs["intrinsics_resolver"] resources.append(self._construct_lambda_layer(intrinsics_resolver)) return resources def _construct_lambda_layer(self, intrinsics_resolver): """Constructs and returns the Lambda function. :returns: a list containing the Lambda function and execution role resources :rtype: list """ # Resolve intrinsics if applicable: self.LayerName = self._resolve_string_parameter(intrinsics_resolver, self.LayerName, "LayerName") self.LicenseInfo = self._resolve_string_parameter(intrinsics_resolver, self.LicenseInfo, "LicenseInfo") self.Description = self._resolve_string_parameter(intrinsics_resolver, self.Description, "Description") self.RetentionPolicy = self._resolve_string_parameter( intrinsics_resolver, self.RetentionPolicy, "RetentionPolicy" ) # If nothing defined, this will be set to Retain retention_policy_value = self._get_retention_policy_value() attributes = self.get_passthrough_resource_attributes() if attributes is None: attributes = {} if "DeletionPolicy" not in attributes: attributes["DeletionPolicy"] = self.RETAIN if retention_policy_value is not None: attributes["DeletionPolicy"] = retention_policy_value old_logical_id = self.logical_id # This is to prevent the passthrough resource attributes to be included for hashing hash_dict = copy.deepcopy(self.to_dict()) if "DeletionPolicy" in hash_dict.get(old_logical_id): del hash_dict[old_logical_id]["DeletionPolicy"] if "UpdateReplacePolicy" in hash_dict.get(old_logical_id): del hash_dict[old_logical_id]["UpdateReplacePolicy"] if "Metadata" in hash_dict.get(old_logical_id): del hash_dict[old_logical_id]["Metadata"] new_logical_id = logical_id_generator.LogicalIdGenerator(old_logical_id, hash_dict).gen() self.logical_id = new_logical_id lambda_layer = LambdaLayerVersion(self.logical_id, depends_on=self.depends_on, attributes=attributes) # Changing the LayerName property: when a layer is published, it is given an Arn # example: arn:aws:lambda:us-west-2:123456789012:layer:MyLayer:1 # where MyLayer is the LayerName property if it exists; otherwise, it is the # LogicalId of this resource. Since a LayerVersion is an immutable resource, when # CloudFormation updates this resource, it will ALWAYS create a new version then # delete the old version if the logical ids match. What this does is change the # logical id of every layer (so a `DeletionPolicy: Retain` can work) and set the # LayerName property of the layer so that the Arn will still always be the same # with the exception of an incrementing version number. if not self.LayerName: self.LayerName = old_logical_id lambda_layer.LayerName = self.LayerName lambda_layer.Description = self.Description lambda_layer.Content = construct_s3_location_object(self.ContentUri, self.logical_id, "ContentUri") lambda_layer.CompatibleRuntimes = self.CompatibleRuntimes lambda_layer.LicenseInfo = self.LicenseInfo return lambda_layer def _get_retention_policy_value(self): """ Sets the deletion policy on this resource. The default is 'Retain'. :return: value for the DeletionPolicy attribute. """ if self.RetentionPolicy is None: return None elif self.RetentionPolicy.lower() == self.RETAIN.lower(): return self.RETAIN elif self.RetentionPolicy.lower() == self.DELETE.lower(): return self.DELETE elif self.RetentionPolicy.lower() not in self.retention_policy_options: raise InvalidResourceException( self.logical_id, "'{}' must be one of the following options: {}.".format("RetentionPolicy", [self.RETAIN, self.DELETE]), ) class SamStateMachine(SamResourceMacro): """SAM state machine macro.""" resource_type = "AWS::Serverless::StateMachine" property_types = { "Definition": PropertyType(False, is_type(dict)), "DefinitionUri": PropertyType(False, one_of(is_str(), is_type(dict))), "Logging": PropertyType(False, is_type(dict)), "Role": PropertyType(False, is_str()), "DefinitionSubstitutions": PropertyType(False, is_type(dict)), "Events": PropertyType(False, dict_of(is_str(), is_type(dict))), "Name": PropertyType(False, is_str()), "Type": PropertyType(False, is_str()), "Tags": PropertyType(False, is_type(dict)), "Policies": PropertyType(False, one_of(is_str(), list_of(one_of(is_str(), is_type(dict), is_type(dict))))), "Tracing": PropertyType(False, is_type(dict)), "PermissionsBoundary": PropertyType(False, is_str()), } event_resolver = ResourceTypeResolver( samtranslator.model.stepfunctions.events, ) def to_cloudformation(self, **kwargs): managed_policy_map = kwargs.get("managed_policy_map", {}) intrinsics_resolver = kwargs["intrinsics_resolver"] event_resources = kwargs["event_resources"] state_machine_generator = StateMachineGenerator( logical_id=self.logical_id, depends_on=self.depends_on, managed_policy_map=managed_policy_map, intrinsics_resolver=intrinsics_resolver, definition=self.Definition, definition_uri=self.DefinitionUri, logging=self.Logging, name=self.Name, policies=self.Policies, permissions_boundary=self.PermissionsBoundary, definition_substitutions=self.DefinitionSubstitutions, role=self.Role, state_machine_type=self.Type, tracing=self.Tracing, events=self.Events, event_resources=event_resources, event_resolver=self.event_resolver, tags=self.Tags, resource_attributes=self.resource_attributes, passthrough_resource_attributes=self.get_passthrough_resource_attributes(), ) resources = state_machine_generator.to_cloudformation() return resources def resources_to_link(self, resources): try: return {"event_resources": self._event_resources_to_link(resources)} except InvalidEventException as e: raise InvalidResourceException(self.logical_id, e.message) def _event_resources_to_link(self, resources): event_resources = {} if self.Events: for logical_id, event_dict in self.Events.items(): try: event_source = self.event_resolver.resolve_resource_type(event_dict).from_dict( self.logical_id + logical_id, event_dict, logical_id ) except (TypeError, AttributeError) as e: raise InvalidEventException(logical_id, "{}".format(e)) event_resources[logical_id] = event_source.resources_to_link(resources) return event_resources

47.333922

205

0.674617

76,939

0.95725

0

2,252

0.028019

0

26,146

0.3253

dd7bb92f20393f9e12f7115e84f70223584f154d

928

py

Python

media_logs/urls/audios.py

Akshayvm98/Django-School

723d52db2cd3bc7665680a3adaf8687f97836d48

[ "MIT" ]

26

2015-08-04T00:13:27.000Z

2021-03-19T01:01:14.000Z

media_logs/urls/audios.py

Akshayvm98/Django-School

723d52db2cd3bc7665680a3adaf8687f97836d48

[ "MIT" ]

null

media_logs/urls/audios.py

Akshayvm98/Django-School

723d52db2cd3bc7665680a3adaf8687f97836d48

[ "MIT" ]

28

2015-01-19T15:10:15.000Z

2020-10-27T11:22:21.000Z

from django.conf.urls.defaults import * from media_logs.models import * audio_list = { 'queryset': Audio.objects.all(), } audio_set_list = { 'queryset': AudioSet.objects.all(), } urlpatterns = patterns('', url( regex = '^sets/(?P<slug>[-\w]+)/$', view = 'django.views.generic.list_detail.object_detail', kwargs = audio_set_list, name = 'audio_set_detail', ), url ( regex = '^sets/$', view = 'django.views.generic.list_detail.object_list', kwargs = audio_set_list, name = 'audio_set_list', ), url( regex = '^(?P<user>[-\w]+)/(?P<slug>[-\w]+)/$', #regex = '^(?P<slug>[-\w]+)/$', view = 'views.generic.list_detail.object_detail', kwargs = audio_list, name = 'audio_detail', ), url ( regex = '^$', view = 'django.views.generic.list_detail.object_list', kwargs = audio_list, name = 'audio_list', ), )

23.2

63

0.574353

0

373

0.40194

dd7d61b4fcf318d454a05f755e0919c0dd18ea88

2,964

py

Python

pycalc/MAVProxy/modules/mavproxy_gopro.py

joakimzhang/python-electron

79bc174a14c5286ca739bb7d8ce6522fdc6e9e80

[ "CC0-1.0" ]

null

pycalc/MAVProxy/modules/mavproxy_gopro.py

joakimzhang/python-electron

79bc174a14c5286ca739bb7d8ce6522fdc6e9e80

[ "CC0-1.0" ]

8

2021-01-28T19:26:22.000Z

2022-03-24T18:07:24.000Z

pycalc/MAVProxy/modules/mavproxy_gopro.py

joakimzhang/python-electron

79bc174a14c5286ca739bb7d8ce6522fdc6e9e80

[ "CC0-1.0" ]

null

#!/usr/bin/env python '''gopro control over mavlink for the solo-gimbal To use this module connect to a Solo with a GoPro installed on the gimbal. ''' import time, os from MAVProxy.modules.lib import mp_module from pymavlink import mavutil class GoProModule(mp_module.MPModule): def __init__(self, mpstate): super(GoProModule, self).__init__(mpstate, "gopro", "gopro handling") self.add_command('gopro', self.cmd_gopro, 'gopro control', [ 'status', 'shutter <start|stop>', 'mode <video|camera>', 'power <on|off>']) def cmd_gopro(self, args): '''gopro commands''' usage = "status, shutter <start|stop>, mode <video|camera>, power <on|off>" mav = self.master.mav if args[0] == "status": self.cmd_gopro_status(args[1:]) return if args[0] == "shutter": name = args[1].lower() if name == 'start': mav.gopro_set_request_send(0, mavutil.mavlink.MAV_COMP_ID_GIMBAL, mavutil.mavlink.GOPRO_COMMAND_SHUTTER, 1) return elif name == 'stop': mav.gopro_set_request_send(0, mavutil.mavlink.MAV_COMP_ID_GIMBAL, mavutil.mavlink.GOPRO_COMMAND_SHUTTER, 0) return else: print("unrecognized") return if args[0] == "mode": name = args[1].lower() if name == 'video': mav.gopro_set_request_send(0, mavutil.mavlink.MAV_COMP_ID_GIMBAL, mavutil.mavlink.GOPRO_COMMAND_CAPTURE_MODE, 0) return elif name == 'camera': mav.gopro_set_request_send(0, mavutil.mavlink.MAV_COMP_ID_GIMBAL, mavutil.mavlink.GOPRO_COMMAND_CAPTURE_MODE, 1) return else: print("unrecognized") return if args[0] == "power": name = args[1].lower() if name == 'on': mav.gopro_set_request_send(0, mavutil.mavlink.MAV_COMP_ID_GIMBAL, mavutil.mavlink.GOPRO_COMMAND_POWER, 1) return elif name == 'off': mav.gopro_set_request_send(0, mavutil.mavlink.MAV_COMP_ID_GIMBAL, mavutil.mavlink.GOPRO_COMMAND_POWER, 0) return else: print("unrecognized") return print(usage) def cmd_gopro_status(self, args): '''show gopro status''' master = self.master if 'GOPRO_HEARTBEAT' in master.messages: print(master.messages['GOPRO_HEARTBEAT']) else: print("No GOPRO_HEARTBEAT messages") def init(mpstate): '''initialise module''' return GoProModule(mpstate)

34.068966

83

0.5361

2,639

0.890351

0

567

0.191296

dd7ea8658ced22af8cde597e98ea9827577d3995

343

py

Python

strings.py

aemreb/telegram_paybot

f973ddd9029f2844901508fa983aa37b6ca93089

[ "MIT" ]

2

2021-09-17T10:55:14.000Z

2021-09-17T10:55:38.000Z

strings.py

aemreb/telegram_paybot

f973ddd9029f2844901508fa983aa37b6ca93089

[ "MIT" ]

null

strings.py

aemreb/telegram_paybot

f973ddd9029f2844901508fa983aa37b6ca93089

[ "MIT" ]

1

2021-05-31T18:23:02.000Z

help = '''Hey 👋 \n\n /signup nick: enter your nick and sign up \n\n /atm: see your balance \n\n /send nick amount: send this nick that amount of buxx 💰 \n ''' signup = '''Hi! Type /signup to sign up.''' user_created = '''Created user. Welcome to Paybot 🤑''' user_exists = '''User already exists ☹️''' not_enough_buxx = '''Not enough Buxx 🙄'''

57.166667

158

0.655977

0

291

0.810585

dd7f9dbcfe5bd13ce56beb5ae807d4bb63f3c4df

1,609

py

Python

Program_python/Extractfolderimage.py

pection/MN-furniture

4c796f072662c15b2a263272ef2637e221c42cab

[ "MIT" ]

1

2022-02-22T06:20:56.000Z

Program_python/Extractfolderimage.py

pection/MN-furniture

4c796f072662c15b2a263272ef2637e221c42cab

[ "MIT" ]

null

Program_python/Extractfolderimage.py

pection/MN-furniture

4c796f072662c15b2a263272ef2637e221c42cab

[ "MIT" ]

1

2020-11-24T18:18:42.000Z

import os import sys import numpy as np from PIL import Image num=1 path ="/Users/pection/Documents/mn_furniture/AddwatermarkProgram/Lastday/" #we shall store all the file names in this list filelist=[] for root, dirs, files in os.walk(path): for file in files: if(file.endswith(".jpg")): filelist.append(os.path.join(root,file)) print (filelist) logo=Image.open('logo.png') logo2=Image.open('logo2.png') watermark = Image.open('WatermarkB5.png') watermark2 = Image.open('WatermarkB3.png') logoWidth = watermark.width logoHeight = watermark.height watermarkW=watermark.width watermarkH=watermark.height logo2Width = watermark2.width logo2Height = watermark2.height for filename in filelist: image = Image.open(filename) # imageWidth = image.width # imageHeight = image.height # if imageWidth<500 : # img_w, img_h = image.size # bg_w, bg_h = watermark2.size # offset = ((bg_w - img_w) // 2, (bg_h - img_h) // 2) # image.paste(logo2, (0, 0), logo2) # image2=image.copy() # image2.paste(watermark2,(int((img_w-logo2Width)/2),int((img_h-logo2Height)/2)),watermark2) # else : # img_w, img_h = image.size # bg_w, bg_h = watermark.size # offset = ((bg_w - img_w) // 2, (bg_h - img_h) // 2) # image.paste(logo, (0, 0), logo) # image2=image.copy() # image2.paste(watermark,(int((img_w-logoWidth)/2),int((img_h-logoHeight)/2)),watermark) num += 1 # image.save(filename) image.save('/Users/pection/Documents/mn_furniture/AddwatermarkProgram/Extract/'+str(num)+'.png')

35.755556

100

0.661902

0

912

0.566812

dd7fb45e0f3cff64598edf9ddf119adc6b039b8e

1,986

py

Python

BrainML/__init__.py

bogdan124/DeepML

ad5e904cc9fcd3c499bbca3538525d83fde003f5

[ "Apache-2.0" ]

null

BrainML/__init__.py

bogdan124/DeepML

ad5e904cc9fcd3c499bbca3538525d83fde003f5

[ "Apache-2.0" ]

null

BrainML/__init__.py

bogdan124/DeepML

ad5e904cc9fcd3c499bbca3538525d83fde003f5

[ "Apache-2.0" ]

null

import tensorflow as tf from BrainML.activation import Activator from BrainML.layers import * from BrainML.optimizer import Optimizer from tensorflow.python.util import deprecation ##deprecation._PRINT_DEPRECATION_WARNINGS = False ##tf.compat.v1.disable_eager_execution() import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' class Network: def __init__(self,layers=None, name=None): self.model=None self.output=None self.layers=layers self.compile=None self.name=name newLayers=[] ##if layers[0].shape!=None: ## newLayers.append(tf.keras.Input(input_shape=layers[0].shape)) for i in range(0,len(layers)): newLayers.append(self.layers[i].layer) ##newLayers[i].value_to_feed= self.model=tf.keras.Sequential()##newLayers, name for i in newLayers: self.model.add(i) def train(self,x=None, y=None, batch_size=None, epochs=1, verbose=1, callbacks=None, validation_split=0.0, validation_data=None, shuffle=True, class_weight=None, sample_weight=None, initial_epoch=0, steps_per_epoch=None, validation_steps=None, validation_batch_size=None, validation_freq=1, max_queue_size=10, workers=1, use_multiprocessing=False,optimizer='rmsprop', loss=None, metrics=None, loss_weights=None,weighted_metrics=None, run_eagerly=None): if loss==None: loss="mse" elif metrics==None or metrics[0]=="all": metrics=["mae", "acc"] else: optimizer="rmsprop" self.compile=self.model.compile(optimizer, loss, metrics, loss_weights,weighted_metrics, run_eagerly)##initial_epoch,steps_per_epoch self.output=self.model.fit(x, y, batch_size, epochs, verbose, callbacks,validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing) return self.output def Summary(self): self.model.summary() ## if __name__ == "__main__": ## pass

38.192308

268

0.735146

1,617

0.814199

0

360

0.181269

dd80e90be1c610d2c46bc8b8b02fd6070d94ee6d

2,900

py

Python

detection/pixel_link/util/dec.py

HLIG/HUAWEI_OCR2019

1070d6291072e0223c2624f686766d0f3065e9c6

[ "MIT" ]

211

2020-04-13T02:56:57.000Z

2022-03-30T11:22:46.000Z

detection/pixel_link/util/dec.py

HLIG/HUAWEI_OCR2019

1070d6291072e0223c2624f686766d0f3065e9c6

[ "MIT" ]

41

2020-04-14T20:08:58.000Z

2022-03-28T15:08:30.000Z

detection/pixel_link/util/dec.py

HLIG/HUAWEI_OCR2019

1070d6291072e0223c2624f686766d0f3065e9c6

[ "MIT" ]

47

2020-04-13T10:17:11.000Z

2022-02-21T02:06:16.000Z

#encoding=utf-8 import logging import time def print_calling(fn): def wrapper(*args1, ** args2): s = "calling function %s"%(fn.__name__) logging.info(s) start = time.time() ret = fn(*args1, **args2) end = time.time() # s = "%s. time used = %f seconds"%(s, (end - start)) s = "function [%s] has been called, taking %f seconds"%(fn.__name__, (end - start)) logging.debug(s) return ret return wrapper def print_test(fn): def wrapper(*args1, ** args2): s = "running test: %s..."%(fn.__name__) logging.info(s) ret = fn(*args1, **args2) s = "running test: %s...succeed"%(fn.__name__) logging.debug(s) return ret return wrapper def print_calling_in_short(fn): def wrapper(*args1, ** args2): start = time.time() ret = fn(*args1, **args2) end = time.time() s = "function [%s] has been called, taking %f seconds"%(fn.__name__, (end - start)) logging.debug(s) return ret return wrapper import collections counter = collections.defaultdict(int) count_times =collections.defaultdict(int) def print_calling_in_short_for_tf(fn): import tensorflow as tf import util def wrapper(*args1, ** args2): start = time.time() thread_name = util.thread.get_current_thread_name() ret = fn(*args1, **args2) end = time.time() counter[fn.__name__] = counter[fn.__name__] + (end - start) count_times[fn.__name__] += 1 all_time = sum([counter[name] for name in counter]) * 1.0 for name in counter: # tf.logging.info('\t %s: %f, %f seconds'%(name, counter[name] / all_time, counter[name])) tf.logging.info('\t %s: %d callings, %fsper calling'%(name, count_times[name], counter[name] * 1.0 / count_times[name])) s = "Thread [%s]:function [%s] has been called, taking %f seconds"%(thread_name, fn.__name__, (end - start)) tf.logging.info(s) return ret return wrapper def timeit(fn): import util def wrapper(*args1, ** args2): start = time.time() thread_name = util.thread.get_current_thread_name() ret = fn(*args1, **args2) end = time.time() counter[fn.__name__] = counter[fn.__name__] + (end - start) count_times[fn.__name__] += 1 all_time = sum([counter[name] for name in counter]) * 1.0 for name in counter: logging.info('\t %s: %f, %f seconds'%(name, counter[name] / all_time, counter[name])) logging.info('\t %s: %d callings, %f seconds per calling'%(name, count_times[name], counter[name] * 1.0 / count_times[name])) s = "Thread [%s]:function [%s] has been called, taking %f seconds"%(thread_name, fn.__name__, (end - start)) # logging.info(s) return ret return wrapper

36.708861

137

0.589655

0

600

0.206897

dd8112f277127d953f0d1ded63b446df7043645e

2,955

py

Python

problems/graph-valid-tree.py

sailikhithk/tech-interview-prep

e833764cf98915d56118bddfa0e01871c58de75e

[ "Apache-2.0" ]

null

problems/graph-valid-tree.py

sailikhithk/tech-interview-prep

e833764cf98915d56118bddfa0e01871c58de75e

[ "Apache-2.0" ]

null

problems/graph-valid-tree.py

sailikhithk/tech-interview-prep

e833764cf98915d56118bddfa0e01871c58de75e

[ "Apache-2.0" ]

null

""" First of all a tree of N nodes must have exactly N-1 edges. 2 nodes need 1 edge to connect. 3 nodes need 2 edges to connect... Just draw one or two, you will know it. Valid tree don't have cycles, there are two ways to detect it. DFS. and union find. Union find is more suitable in this sutuation. 1. Union find. We use an array 'markset' to store the root node of each node. [0] So if markset[1]==3, it means node1's root is node3. markset[6]==4, node6's root is node4. we use find() to find the node's root. [1] For example if node1's root is node3. In the recursion, we find out that node3's root is node5. we return and set node5 as node1's real root. If a node don't have root then the root is itselves. Imagine an edge. 1<->6 [2] union()'s mission is to find out if node1 and node6 share the same root before we know 1<->6 exist. If node1 and node6 share the same root before we know the edge 1<->6, There must be a cycle between node1, node6 and their root. A special situation is that 1<->2, 3<->4, 3<->5 (We have two trees that are not connected) 1 and 3 will share -1 as 'root', this means that they are not connected. But a valid tree should be connected and only have one and only root. The time complexity is O(NLogN), becuase we run a loop for every edges. And the number of edges is equal to N-1 for every edge we use find() to find the root of two nodes The recursion takes the height of the tree, which is LogN N is the number of nodes. Space complexity is O(N). 2. DFS We use dfs to find if there are cycles in the tree. If we visit the node that we visited which means there is a cycle. Since this is an undirected map, we have to add both ways to the adjacent list. And everytime we use an edge, we need to remove the counter part of it to avoid repeat. finally, we have to check if we visit all the nodes. because there may be unconnected nodes. The time complexity is O(N+E). Because this is DFS search in adjacent list. Space complexity is O(N). """ class Solution(object): def validTree(self, n, edges): def union(n1, n2): #[2] n1_root = find(n1) n2_root = find(n2) if n1_root==n2_root: return True markset[n2_root] = n1_root return False def find(node): #[1] if markset[node]==-1: return node return find(markset[node]) if len(edges)!=n-1: return False markset = [-1 for _ in xrange(n)] #[0] for edge in edges: if union(edge[0], edge[1]): return False return True def validTree(self, n, edges): if n!=len(edges)+1: return False graph = collections.defaultdict(list) stack = [] visited = set() for edge in edges: graph[edge[0]].append(edge[1]) graph[edge[1]].append(edge[0]) if len(edges)>0: stack.append(edges[0][0]) while stack: node = stack.pop() if node in visited: return False visited.add(node) for nb in graph[node]: stack.append(nb) graph[nb].remove(node) if len(visited)!=n: return False return True

31.105263

99

0.702876

456

0.154315

0

1,998

0.676142

dd81524e1e000d2bbdd8e39c55a281ea1c78ab94

1,336

py

Python

config.py

MGorr/icons_updater

aa9f9177a565fbe590cf959f625f049024e01efb

[ "MIT" ]

1

2021-06-18T06:58:15.000Z

config.py

MGorr/icons_updater

aa9f9177a565fbe590cf959f625f049024e01efb

[ "MIT" ]

null

config.py

MGorr/icons_updater

aa9f9177a565fbe590cf959f625f049024e01efb

[ "MIT" ]

null

"""Configuration class for icons updating.""" import os from configparser import ConfigParser _DESTINATION_NAME = 'dst' _MAGICK_NAME = 'path' _SOURCES_NAME = 'src' class Config: """Configuration class.""" def __init__(self, config_file=None, src=None, dst=None): """Constructor.""" parser = ConfigParser() if config_file: parser.read(config_file) section = parser['settings'] if config_file else None if config_file and _MAGICK_NAME in section: os.environ['PATH'] += os.pathsep + \ os.path.abspath(section[_MAGICK_NAME]) if not src and config_file: src = section[_SOURCES_NAME] elif not src: raise RuntimeError('Source folder should be set!') self._src = os.path.normpath(src) if not dst and config_file: dst = section[_DESTINATION_NAME] elif not dst: raise RuntimeError('Destination folder should be set!') self._dst = os.path.normpath(dst) assert self._dst, 'Destination folder should be set!' assert self._src, 'Sources folder should be set!' def destination(self): """Destination folder.""" return self._dst def sources(self): """Sources folder.""" return self._src

30.363636

72

0.610778

1,166

0.872754

0

298

0.223054

dd820e8c14626563e752d4624969a2315eb254b9

8,831

py

Python

project/settings.py

ziibii88/The_Doe_Agency

2545aeae71c779166bef78941cac36551498ca76

[ "MIT" ]

2

2021-07-16T10:25:15.000Z

2021-08-07T04:44:08.000Z

project/settings.py

ziibii88/The_Doe_Agency

2545aeae71c779166bef78941cac36551498ca76

[ "MIT" ]

null

project/settings.py

ziibii88/The_Doe_Agency

2545aeae71c779166bef78941cac36551498ca76

[ "MIT" ]

null

""" Django settings for project project. Generated by 'django-admin startproject' using Django 3.2.5. For more information on this file, see https://docs.djangoproject.com/en/3.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.2/ref/settings/ """ from datetime import timedelta from pathlib import Path from decouple import config, Csv import sentry_sdk from sentry_sdk.integrations.django import DjangoIntegration from .logging import CONFIG as LOG_CONFIG ENVIRON = config("ENVIRON", default="prod") if ENVIRON == "prod": sentry_sdk.init( dsn="https://ad9a9f987fa949a899c3b890ef4cd112" "@o354850.ingest.sentry.io/5868398", integrations=[DjangoIntegration()], environment=ENVIRON, traces_sample_rate=1.0, send_default_pii=True, release="tda@0.1.0", # change in poetry as well ) LOGGING = LOG_CONFIG PROJECT_NAME = "The Doe Agency" PROJECT_SLUG = "the-doe-agency" PROJECT_CODE = "TDA" # Build paths inside the project like this: BASE_DIR / 'subdir'. BASE_DIR = Path(__file__).resolve().parent.parent # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = config("SECRET_KEY") # SECURITY WARNING: don't run with debug turned on in production! DEBUG = config("DEBUG", default=False, cast=bool) ALLOWED_HOSTS = config("ALLOWED_HOSTS", default=[], cast=Csv()) # https://django-debug-toolbar.readthedocs.io/en/latest/installation.html#configuring-internal-ips INTERNAL_IPS = config("INTERNAL_IPS", default=[], cast=Csv()) # Application definition ---------------------------------------------------- # INSTALLED_APPS = [ # django apps "django.contrib.admin", "django.contrib.auth", "django.contrib.contenttypes", "django.contrib.sessions", "django.contrib.messages", "django.contrib.staticfiles", "django.contrib.sites", "django.contrib.humanize", # 3rd party apps "django_filters", "rest_framework", "rest_framework_simplejwt", "django_celery_results", "django_celery_beat", # health_check "health_check", "health_check.db", "health_check.cache", "health_check.storage", "health_check.contrib.migrations", # 'health_check.contrib.celery', # 'health_check.contrib.celery_ping', "health_check.contrib.psutil", # 'health_check.contrib.s3boto3_storage', # 'health_check.contrib.rabbitmq', # 'health_check.contrib.redis', # project apps "core", "scraper", ] SITE_ID = 1 # Sites framework if ENVIRON == "dev": INSTALLED_APPS.append("debug_toolbar") MIDDLEWARE = [ "debug_toolbar.middleware.DebugToolbarMiddleware", "django.middleware.security.SecurityMiddleware", "django.contrib.sessions.middleware.SessionMiddleware", "django.middleware.common.CommonMiddleware", "django.middleware.csrf.CsrfViewMiddleware", "django.contrib.auth.middleware.AuthenticationMiddleware", "django.contrib.messages.middleware.MessageMiddleware", "django.middleware.clickjacking.XFrameOptionsMiddleware", ] ROOT_URLCONF = "project.urls" TEMPLATES = [ { "BACKEND": "django.template.backends.django.DjangoTemplates", "DIRS": [], "APP_DIRS": True, "OPTIONS": { "context_processors": [ "django.template.context_processors.debug", "django.template.context_processors.request", "django.contrib.auth.context_processors.auth", "django.contrib.messages.context_processors.messages", ], }, }, ] AUTH_USER_MODEL = "core.User" TEST_URL = "http://httpbin.zube.xyz/ip" WSGI_APPLICATION = "project.wsgi.application" # Database ------------------------------------------------------------------ # # https://docs.djangoproject.com/en/3.2/ref/settings/#databases DATABASES = { "default": { "ENGINE": config("DB_ENGINE", default="django.db.backends.postgresql"), "HOST": config("DB_HOST", default="127.0.0.1"), "PORT": config("DB_PORT", default=5432, cast=int), "NAME": config("DB_NAME", default="tda_db"), "USER": config("DB_USER", default="tda_user"), "PASSWORD": config("DB_PASS", default="tda_pass"), } } # Password validation ------------------------------------------------------- # # https://docs.djangoproject.com/en/3.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { "NAME": "django.contrib.auth.password_validation" ".UserAttributeSimilarityValidator" }, { "NAME": "django.contrib.auth.password_validation" ".MinimumLengthValidator" }, { "NAME": "django.contrib.auth.password_validation" ".CommonPasswordValidator" }, { "NAME": "django.contrib.auth.password_validation" ".NumericPasswordValidator" }, ] # Internationalization ------------------------------------------------------ # # https://docs.djangoproject.com/en/3.2/topics/i18n/ LANGUAGE_CODE = "en-us" TIME_ZONE = config("TIME_ZONE", default="UTC") USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) ------------------------------------ # # https://docs.djangoproject.com/en/3.2/howto/static-files/ STATIC_URL = "/static/" STATIC_ROOT = ( BASE_DIR / "static" ) # production, don't forget to run collectstatic STATICFILES_DIRS = [ BASE_DIR / "staticfiles", ] # development environment MEDIA_URL = "/media/" MEDIA_ROOT = BASE_DIR / "media" # Default primary key field type # https://docs.djangoproject.com/en/3.2/ref/settings/#default-auto-field DEFAULT_AUTO_FIELD = "django.db.models.BigAutoField" # Django REST Framework ------------------------------------------------------- # https://www.django-rest-framework.org/api-guide/settings/ REST_FRAMEWORK = { "DEFAULT_AUTHENTICATION_CLASSES": [ # https://django-rest-framework-simplejwt.readthedocs.io/en/latest/getting_started.html#installation "rest_framework_simplejwt.authentication.JWTAuthentication", # "rest_framework.authentication.TokenAuthentication", "rest_framework.authentication.SessionAuthentication", ], "DEFAULT_PERMISSION_CLASSES": [ "rest_framework.permissions.IsAuthenticated" ], "DEFAULT_FILTER_BACKENDS": [ # django-filters # https://www.django-rest-framework.org/api-guide/filtering/ # https://django-filter.readthedocs.io/en/latest/guide/rest_framework.html "django_filters.rest_framework.DjangoFilterBackend", # https://www.django-rest-framework.org/api-guide/filtering/#searchfilter "rest_framework.filters.SearchFilter", # https://www.django-rest-framework.org/api-guide/filtering/#orderingfilter "rest_framework.filters.OrderingFilter", ], "DEFAULT_PAGINATION_CLASS": "rest_framework.pagination" ".PageNumberPagination", "PAGE_SIZE": 100, } # DRF SimpleJWT --------------------------------------------------------------- # https://django-rest-framework-simplejwt.readthedocs.io/en/latest/settings.html SIMPLE_JWT = { "ACCESS_TOKEN_LIFETIME": timedelta(minutes=15), "REFRESH_TOKEN_LIFETIME": timedelta(days=1), "ROTATE_REFRESH_TOKENS": False, "BLACKLIST_AFTER_ROTATION": True, "UPDATE_LAST_LOGIN": True, "ALGORITHM": "HS256", "SIGNING_KEY": SECRET_KEY, "VERIFYING_KEY": None, "AUDIENCE": None, "ISSUER": None, "AUTH_HEADER_TYPES": ("Bearer",), "AUTH_HEADER_NAME": "HTTP_AUTHORIZATION", "USER_ID_FIELD": "id", "USER_ID_CLAIM": "user_id", "USER_AUTHENTICATION_RULE": "rest_framework_simplejwt.authentication" ".default_user_authentication_rule", "AUTH_TOKEN_CLASSES": ("rest_framework_simplejwt.tokens.AccessToken",), "TOKEN_TYPE_CLAIM": "token_type", "JTI_CLAIM": "jti", "SLIDING_TOKEN_REFRESH_EXP_CLAIM": "refresh_exp", "SLIDING_TOKEN_LIFETIME": timedelta(minutes=15), "SLIDING_TOKEN_REFRESH_LIFETIME": timedelta(days=1), } # Celery ---------------------------------------------------------------------- # https://docs.celeryproject.org/en/stable/userguide/configuration.html#configuration-and-defaults CELERY_BROKER_URL = config( "CELERY_BROKER_URL", default="amqp://127.0.0.1:5672/" ) CELERY_RESULT_BACKEND = config("CELERY_RESULT_BACKEND", default="django-db") CELERY_CACHE_BACKEND = config("CELERY_CACHE_BACKEND", default="django-cache") CELERY_TIMEZONE = config("CELERY_TIME_ZONE", default=TIME_ZONE) CELERY_TASK_TRACK_STARTED = config("CELERY_TASK_TRACK_STARTED", default=True) CELERY_TASK_TIME_LIMIT = config("CELERY_TASK_TIME_LIMIT", default=30 * 60)

32.112727

108

0.669347

0

6,005

0.679991

dd837f67ec7177838bf8a526749af097805f6779

15,142

py

Python

CalsCamera/main.py

NoDrones/Imaging

555c8aeced98097379b80f448689f2bf2974c3e9

[ "MIT" ]

1

2019-01-28T21:55:53.000Z

CalsCamera/main.py

NoDrones/Imaging

555c8aeced98097379b80f448689f2bf2974c3e9

[ "MIT" ]

null

CalsCamera/main.py

NoDrones/Imaging

555c8aeced98097379b80f448689f2bf2974c3e9

[ "MIT" ]

null

#Author: Calvin Ryan import sensor, image, time, pyb, ustruct, math, utime def get_gain(): gain_reg_val = sensor.__read_reg(0x00) #print("gain_reg_val: " + str(gain_reg_val)) bitwise_gain_range = (gain_reg_val & 0b11110000) >> 4 #get the highest four bits which correspond to gain range. Depends on the bits set. Can be 0 > 4 for a total of 5 ranges. #print("bitwise_gain_range: " + str(bin(bitwise_gain_range))) gain_range = ((bitwise_gain_range & 0b1000) >> 3) + ((bitwise_gain_range & 0b0100) >> 2) + ((bitwise_gain_range & 0b0010) >> 1) + (bitwise_gain_range & 0b0001) #get an int for the number of bits set #print("read_gain_range: " + str(gain_range)) gain_LSBs = gain_reg_val & 0b00001111 #The 4 lsbs represent the fine tuning gain control. #print("gain_LSBs: " + str(gain_LSBs)) gain_curve_index = 16 * gain_range + gain_LSBs # this gives you an index from 0 > 79 which is the range of points you need to describe every possible gain setting along the new gain curve #print("gain_curve_index: " + str(gain_curve_index)) gain = 10 ** (30 * gain_curve_index / 79 / 20) #10** = 10 ^, calculate the gain along the new exponential gain curve I defined earlier on #print("gain: " + str(gain)) return gain def set_gain(gain_db): # gain_correlation_equation = 20*log(gain_db) = 30*(index)/79 gain_curve_index = (79 * 20 * math.log(gain_db, 10)) / 30 #return an index from the new exponential gain curve... #... Can be 0 > 79 which is the # of points needed to describe every gain setting along the new curve #print("gain_curve_index: " + str(gain_curve_index)) gain_range = int(gain_curve_index/16) #find a 0 > 4 value for the gain range. This range is defined by the 4 msbs. Thus we divide and round down by the LSB of the 4 MSBs (16) #print("gain_range: " + str(gain_range)) gain_LSBs = int(gain_curve_index - 16 * gain_range) & 0b00001111 #Find how many LSBs above the gain range the index is. This is your fine tuning gain control #print("gain_LSBs: " + str(bin(gain_LSBs))) bitwise_gain_range = (0b1111 << gain_range) & 0b11110000 #make the gain range bitwise #print("bitwise_gain_range: " + str(bin(bitwise_gain_range))) gain_reg_val = bitwise_gain_range | gain_LSBs #OR #print("gain to set: " + str(bin(gain_reg_val))) sensor.__write_reg(0x00, gain_reg_val) return gain_reg_val def set_custom_exposure(high_l_mean_thresh = 17, low_l_mean_thresh = 16): try: print("Starting Exposure Adjustment...") b_gain = sensor.__read_reg(0x01) r_gain = sensor.__read_reg(0x02) g_gain = sensor.__read_reg(0x03) r_gain = round(r_gain/4) g_gain = round(g_gain/4) b_gain = round(b_gain/4) sensor.__write_reg(0x01, b_gain) sensor.__write_reg(0x02, r_gain) sensor.__write_reg(0x03, g_gain) img = sensor.snapshot() # Take a picture and return the image. img_stats = img.get_statistics() l_mean = img_stats.l_mean() count = 0 cur_gain = get_gain() while(((l_mean > high_l_mean_thresh) | (l_mean < low_l_mean_thresh))) & (count < 256) & (cur_gain >= 0): img = sensor.snapshot() # Take a picture and return the image. img_stats = img.get_statistics() l_mean = img_stats.l_mean() if ((cur_gain < 1) | (cur_gain > 32)): break if l_mean > high_l_mean_thresh: new_gain = cur_gain - .1 elif l_mean < low_l_mean_thresh: new_gain = cur_gain + .1 else: break #we're in the range now! set_gain(new_gain) cur_gain = new_gain count += 1 if (count < 310) | (cur_gain == 0): print("Exposure Adjustment Complete.") return l_mean else: print("Exposure Adjustment Incomplete.") return -1 except Exception as e: print(e) print("Error occured!") return -2 if __name__ == "__main__": ########### SETUP STUFF sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QVGA) sensor.skip_frames(time = 2000) clock = time.clock() i2c_obj = pyb.I2C(2, pyb.I2C.SLAVE, addr=0x12) i2c_obj.deinit() # Fully reset I2C device... i2c_obj = pyb.I2C(2, pyb.I2C.SLAVE, addr=0x12) #get in focus balance. You have two seconds. t_start = time.ticks() t_elapsed = 0 while(t_elapsed < 1): #ignore bc 1 ms img = sensor.snapshot() t_elapsed = time.ticks() - t_start sensor.set_auto_gain(False) # must be turned off for color tracking sensor.set_auto_whitebal(False) # must be turned off for color tracking sensor.set_auto_exposure(False) sensor.set_contrast(+3) print() pre_adjust_r_gain = sensor.__read_reg(0x02) pre_adjust_g_gain = sensor.__read_reg(0x03) pre_adjust_b_gain = sensor.__read_reg(0x01) pre_adjust_overall_gain = sensor.__read_reg(0x00) pre_adjust_exposure = (sensor.__read_reg(0x08) << 8) + sensor.__read_reg(0x10) print("R gain: " + str(pre_adjust_r_gain)) print("G gain: " + str(pre_adjust_g_gain)) print("B gain: " + str(pre_adjust_b_gain)) print("Overall gain: " + str(pre_adjust_overall_gain)) print("exposure: " + str(pre_adjust_exposure)) print('------------------------------------') set_l_mean = set_custom_exposure() #default thresholds print(set_l_mean) post_adjust_r_gain = sensor.__read_reg(0x02) post_adjust_g_gain = sensor.__read_reg(0x03) post_adjust_b_gain = sensor.__read_reg(0x01) post_adjust_overall_gain = sensor.__read_reg(0x00) post_adjust_exposure = (sensor.__read_reg(0x08) << 8) + sensor.__read_reg(0x10) print("R gain: " + str(post_adjust_r_gain)) print("G gain: " + str(post_adjust_g_gain)) print("B gain: " + str(post_adjust_b_gain)) print("Overall gain: " + str(post_adjust_overall_gain)) print("exposure: " + str(post_adjust_exposure)) print() img = sensor.snapshot() # should pull img_number from a text file and read the plant_id from a qr code or beaglebone # default mode is pyb.usb_mode('VCP+MSC') ''' pyb.usb_mode('VCP+HID') utime.sleep_ms(1000) last_photo_id_path = "last_photo_id.txt" last_photo_id_fd = open(last_photo_id_path, "w+") img_number_str = last_photo_id_fd.read() print(img_number_str) img_number_str = last_photo_id_fd.write("696969") print("Written bytes: " + str(img_number_str)) img_number_str = last_photo_id_fd.read() print(img_number_str) last_photo_id_fd.close() img_number = 1 plant_id = 1 img_id = str(img_number) + "_plant_" + str(plant_id) raw_str = "raw_" + str(img_id) raw_write = image.ImageWriter(raw_str) raw_write.add_frame(img) raw_write.close() img.compress(quality = 100) img.save("img_" + str(img_id)) raw_read = image.ImageReader(raw_str) img = raw_read.next_frame(copy_to_fb = True, loop = False) raw_read.close() ''' ''' L = Lightness where 0 is black and 100 is white A = -127 is green and 128 is red B = -127 is blue and 128 is yellow. ''' img_stats = img.get_statistics() ########### FIND BAD BLOBS unhealthy_full_l_mean = 0 unhealthy_full_a_mean = 0 unhealthy_full_b_mean = 0 unhealthy_centroid_l_mean = 0 unhealthy_centroid_a_mean = 0 unhealthy_centroid_b_mean = 0 unhealthy_blob_l_mean = 0 unhealthy_blob_a_mean = 0 unhealthy_blob_b_mean = 0 healthy_full_l_mean = 0 healthy_full_a_mean = 0 healthy_full_b_mean = 0 healthy_centroid_l_mean = 0 healthy_centroid_a_mean = 0 healthy_centroid_b_mean = 0 healthy_blob_l_mean = 0 healthy_blob_a_mean = 0 healthy_blob_b_mean = 0 blob_index = -1 stage_one_bad_thresholds = [(20, 100, -10, 127, 3, 128)] for blob_index, stage_one_bad_blob in enumerate(img.find_blobs(stage_one_bad_thresholds, pixels_threshold=100, area_threshold=100, merge = False, margin = 15)): rect_stats = img.get_statistics(roi = stage_one_bad_blob.rect()) print("stage_one_bad_blob: " + str(stage_one_bad_blob)) print("density: " + str(stage_one_bad_blob.density())) print("full: " + str(rect_stats)) unhealthy_full_l_mean += rect_stats[0] unhealthy_full_a_mean += rect_stats[8] unhealthy_full_b_mean += rect_stats[16] side_l = stage_one_bad_blob.density() * min(stage_one_bad_blob[2], stage_one_bad_blob[3]) partial_hist = img.get_histogram(roi = (stage_one_bad_blob.cx() - round(side_l/2), stage_one_bad_blob.cy() - round(side_l/2), round(side_l), round(side_l))) partial_stats = partial_hist.get_statistics() print("partial: "+ str(partial_stats)) unhealthy_centroid_l_mean += partial_stats[0] unhealthy_centroid_a_mean += partial_stats[8] unhealthy_centroid_b_mean += partial_stats[16] blob_stats = img.get_statistics(roi = stage_one_bad_blob.rect(), thresholds = stage_one_bad_thresholds) print("blob: "+ str(blob_stats)) print("\n") unhealthy_blob_l_mean += blob_stats[0] unhealthy_blob_a_mean += blob_stats[8] unhealthy_blob_b_mean += blob_stats[16] img.draw_rectangle(stage_one_bad_blob.rect(), color = (255, 255, 255)) #purple #img.draw_rectangle((stage_one_bad_blob.cx() - round(side_l/2), stage_one_bad_blob.cy() - round(side_l/2), round(side_l), round(side_l)), color = (255, 85, 0)) if blob_index != -1: unhealthy_full_l_mean = unhealthy_full_l_mean/(blob_index + 1) unhealthy_full_a_mean = unhealthy_full_a_mean/(blob_index + 1) unhealthy_full_b_mean = unhealthy_full_b_mean/(blob_index + 1) unhealthy_centroid_l_mean = unhealthy_centroid_l_mean/(blob_index + 1) unhealthy_centroid_a_mean = unhealthy_centroid_a_mean/(blob_index + 1) unhealthy_centroid_b_mean = unhealthy_centroid_b_mean/(blob_index + 1) unhealthy_blob_l_mean = unhealthy_blob_l_mean/(blob_index + 1) unhealthy_blob_a_mean = unhealthy_blob_a_mean/(blob_index + 1) unhealthy_blob_b_mean = unhealthy_blob_b_mean/(blob_index + 1) print("------------------------------------------------------------------------") ########### FIND GOOD BLOBS #stage_one_good_thresholds = [(img_stats.l_mean() - 1, 100, -127, img_stats.a_mean() - 4, img_stats.b_mean() - 8, 60)] stage_one_good_thresholds = [(25, 100, -127, -3, -15, 3)] for blob_index, stage_one_good_blob in enumerate(img.find_blobs(stage_one_good_thresholds, pixels_threshold=100, area_threshold=100, merge = False, margin = 15)): rect_stats = img.get_statistics(roi = stage_one_good_blob.rect()) print("stage_one_good_blob: " + str(stage_one_good_blob)) print("density: " + str(stage_one_good_blob.density())) print("full: "+ str(rect_stats)) healthy_full_l_mean += rect_stats[0] healthy_full_a_mean += rect_stats[8] healthy_full_b_mean += rect_stats[16] side_l = stage_one_good_blob.density() * min(stage_one_good_blob[2], stage_one_good_blob[3]) partial_hist = img.get_histogram(roi = (stage_one_good_blob.cx() - round(side_l/2), stage_one_good_blob.cy() - round(side_l/2), round(side_l), round(side_l))) partial_stats = partial_hist.get_statistics() print("partial: "+ str(partial_stats)) healthy_centroid_l_mean += partial_stats[0] healthy_centroid_a_mean += partial_stats[8] healthy_centroid_b_mean += partial_stats[16] blob_stats = img.get_statistics(roi = stage_one_good_blob.rect(), thresholds = stage_one_good_thresholds) print("blob: "+ str(blob_stats)) print("\n") healthy_blob_l_mean += blob_stats[0] healthy_blob_a_mean += blob_stats[8] healthy_blob_b_mean += blob_stats[16] img.draw_rectangle(stage_one_good_blob.rect(), color = (0, 0, 0)) #black #img.draw_rectangle((stage_one_good_blob.cx() - round(side_l/2), stage_one_good_blob.cy() - round(side_l/2), round(side_l), round(side_l)), color = (255, 85, 0)) ########## COLOR IT ALL IN for x in range(stage_one_good_blob[2]): for y in range(stage_one_good_blob[3]): pix_location = (stage_one_good_blob[0] + x, stage_one_good_blob[1] + y) pix_vals = img.get_pixel(pix_location[0], pix_location[1]) lab_pix_vals = image.rgb_to_lab(pix_vals) if ((lab_pix_vals[1] < (blob_stats.a_mean() + 2 * blob_stats.a_stdev())) & (lab_pix_vals[0] >= (blob_stats.l_mean() - .1 * blob_stats.l_stdev()))): #& (abs(lab_pix_vals[2] - lab_pix_vals[1]) > 10) & (lab_pix_vals[0] > (blob_stats.l_mean() - 10)): pass else: pass #img.set_pixel(pix_location[0], pix_location[1], (255, 0, 0)) if blob_index != -1: healthy_full_l_mean = healthy_full_l_mean/(blob_index + 1) healthy_full_a_mean = healthy_full_a_mean/(blob_index + 1) healthy_full_b_mean = healthy_full_b_mean/(blob_index + 1) healthy_centroid_l_mean = healthy_centroid_l_mean/(blob_index + 1) healthy_centroid_a_mean = healthy_centroid_a_mean/(blob_index + 1) healthy_centroid_b_mean = healthy_centroid_b_mean/(blob_index + 1) healthy_blob_l_mean = healthy_blob_l_mean/(blob_index + 1) healthy_blob_a_mean = healthy_blob_a_mean/(blob_index + 1) healthy_blob_b_mean = healthy_blob_b_mean/(blob_index + 1) print(img.compress_for_ide(quality = 100)) print("~~~~~~~~~~~~~~~ RESULTS: ~~~~~~~~~~~~~~~~") print("good thresholds: " + str(stage_one_good_thresholds)) print("bad thresholds: " + str(stage_one_bad_thresholds)) print("unhealthy full l mean: " + str(unhealthy_full_l_mean)) print("unhealthy full a mean: " + str(unhealthy_full_a_mean)) print("unhealthy full b mean: " + str(unhealthy_full_b_mean)) #print("unhealthy centroid l mean: " + str(unhealthy_centroid_l_mean)) #print("unhealthy centroid a mean: " + str(unhealthy_centroid_a_mean)) #print("unhealthy centroid b mean: " + str(unhealthy_centroid_b_mean)) print("unhealthy blob l mean: " + str(unhealthy_blob_l_mean)) print("unhealthy blob a mean: " + str(unhealthy_blob_a_mean)) print("unhealthy blob b mean: " + str(unhealthy_blob_b_mean)) print("healthy full l mean: " + str(healthy_full_l_mean)) print("healthy full a mean: " + str(healthy_full_a_mean)) print("healthy full b mean: " + str(healthy_full_b_mean)) #print("healthy centroid l mean: " + str(healthy_centroid_l_mean)) #print("healthy centroid a mean: " + str(healthy_centroid_a_mean)) #print("healthy centroid b mean: " + str(healthy_centroid_b_mean)) print("healthy blob l mean: " + str(healthy_blob_l_mean)) print("healthy blob a mean: " + str(healthy_blob_a_mean)) print("healthy blob b mean: " + str(healthy_blob_b_mean))

43.636888

262

0.66616

0

4,828

0.318848

dd83de2fe7b5a8905e65a790566a924385cc7b19

297

py

Python

dados/outside/6-JEL_code.py

correia-marcos/Innovation-on-brazilian-economic-research

98bc677618ec2dff062db42cda7279a5e7065a32

[ "MIT" ]

null

dados/outside/6-JEL_code.py

correia-marcos/Innovation-on-brazilian-economic-research

98bc677618ec2dff062db42cda7279a5e7065a32

[ "MIT" ]

null

dados/outside/6-JEL_code.py

correia-marcos/Innovation-on-brazilian-economic-research

98bc677618ec2dff062db42cda7279a5e7065a32

[ "MIT" ]

null

""" This script was made to anaylse the relation between JEL and areas in ANPEC. The idea is that checking the JEL code of each paper, it can be vizualized whether some papers were published in area (from ANPEC meeting) not expected by their JEL code. """ import os import pandas as pd import

22.846154

76

0.767677

0

256

0.861953

dd88982df37b33dce441276837b7773dc3af6b26

1,311

py

Python

tests/garage/tf/spaces/test_dict_space.py

shadiakiki1986/garage

095bb5d25b32df1d44b47e99a78a9b01796941d9

[ "MIT" ]

3

2019-08-11T22:26:55.000Z

2020-11-28T10:23:50.000Z

tests/garage/tf/spaces/test_dict_space.py

shadiakiki1986/garage

095bb5d25b32df1d44b47e99a78a9b01796941d9

[ "MIT" ]

null

tests/garage/tf/spaces/test_dict_space.py

shadiakiki1986/garage

095bb5d25b32df1d44b47e99a78a9b01796941d9

[ "MIT" ]

2

2019-08-11T22:30:14.000Z

2021-03-25T02:57:50.000Z

"""This script tests garage.tf.spaces.dict functionality.""" import unittest from garage.misc import ext from garage.tf.envs import TfEnv from tests.fixtures.envs.dummy import DummyDictEnv class TestDictSpace(unittest.TestCase): def test_dict_space(self): ext.set_seed(0) # A dummy dict env dummy_env = DummyDictEnv() dummy_act = dummy_env.action_space dummy_act_sample = dummy_act.sample() # A dummy dict env wrapped by garage.tf tf_env = TfEnv(dummy_env) tf_act = tf_env.action_space tf_obs = tf_env.observation_space # flat_dim assert tf_act.flat_dim == tf_act.flatten(dummy_act_sample).shape[-1] # flat_dim_with_keys assert tf_obs.flat_dim == tf_obs.flat_dim_with_keys( iter(["achieved_goal", "desired_goal", "observation"])) # un/flatten assert tf_act.unflatten( tf_act.flatten(dummy_act_sample)) == dummy_act_sample # un/flatten_n samples = [dummy_act.sample() for _ in range(10)] assert tf_act.unflatten_n(tf_act.flatten_n(samples)) == samples # un/flatten_with_keys assert tf_act.unflatten_with_keys( tf_act.flatten_with_keys(dummy_act_sample, iter(["action"])), iter(["action"]))

31.214286

76

0.661327

1,118

0.852784

0

253

0.192982

dd8913997853973a6abd55f95d60d2c6a230000b

3,429

py

Python

utils/compare_MRAE.py

Liuhongzhi2018/SSRGAN

b5be922db1600aabb6a06ee52fb1c83ee738d794

[ "Apache-2.0" ]

1

2022-01-21T09:01:48.000Z

utils/compare_MRAE.py

Liuhongzhi2018/SSRGAN

b5be922db1600aabb6a06ee52fb1c83ee738d794

[ "Apache-2.0" ]

1

2021-08-18T11:33:43.000Z

utils/compare_MRAE.py

Liuhongzhi2018/SSRGAN

b5be922db1600aabb6a06ee52fb1c83ee738d794

[ "Apache-2.0" ]

null

import argparse import os import cv2 import numpy as np import hdf5storage as hdf5 from scipy.io import loadmat from matplotlib import pyplot as plt from SpectralUtils import savePNG, projectToRGB from EvalMetrics import computeMRAE BIT_8 = 256 # read path def get_files(path): # read a folder, return the complete path ret = [] for root, dirs, files in os.walk(path): for filespath in files: if filespath[-4:] == '.mat': ret.append(os.path.join(root, filespath)) return ret def get_jpgs(path): # read a folder, return the image name ret = [] for root, dirs, files in os.walk(path): for filespath in files: if filespath[-4:] == '.mat': ret.append(filespath) return ret def check_path(path): if not os.path.exists(path): os.makedirs(path) def demo_track1(filePath, filtersPath): #filePath = "F:\\NTIRE 2020\\spectral reconstruction\\code1\\en4_track1\\ARAD_HS_0451.mat" #filtersPath = "./resources/cie_1964_w_gain.npz" # Load HS image and filters cube = hdf5.loadmat(filePath)['cube'] #cube = loadmat(filePath)['cube'] filters = np.load(filtersPath)['filters'] # Project image to RGB rgbIm = np.true_divide(projectToRGB(cube, filters), BIT_8) # Save image file path = 'temp_clean.png' savePNG(rgbIm, path) # Display RGB image img = cv2.imread(path) img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) plt.imshow(img) plt.title('Example "Clean" Output Image') plt.show() def single_img_mrae(generated_mat_path, groundtruth_mat_path): #generated_mat_path = "F:\\NTIRE 2020\\spectral reconstruction\\code1\\en4_track1\\ARAD_HS_0451.mat" #groundtruth_mat_path = "F:\\NTIRE 2020\\spectral reconstruction\\NTIRE2020_Validation_Spectral\\ARAD_HS_0451.mat" generated_mat = hdf5.loadmat(generated_mat_path)['cube'] # shape: (482, 512, 31) groundtruth_mat = hdf5.loadmat(groundtruth_mat_path)['cube'] # shape: (482, 512, 31) mrae = computeMRAE(generated_mat, groundtruth_mat) print(mrae) return mrae def folder_img_mrae(generated_folder_path, groundtruth_folder_path): #generated_folder_path = "F:\\NTIRE 2020\\spectral reconstruction\\code1\\en4_track1" #groundtruth_folder_path = "F:\\NTIRE 2020\\spectral reconstruction\\NTIRE2020_Validation_Spectral" matlist = get_jpgs(generated_folder_path) avg_mrae = 0 for i, matname in enumerate(matlist): generated_mat_path = os.path.join(generated_folder_path, matname) groundtruth_mat_path = os.path.join(groundtruth_folder_path, matname) generated_mat = hdf5.loadmat(generated_mat_path)['cube'] # shape: (482, 512, 31) groundtruth_mat = hdf5.loadmat(groundtruth_mat_path)['cube'] # shape: (482, 512, 31) mrae = computeMRAE(generated_mat, groundtruth_mat) avg_mrae = avg_mrae + mrae print('The %d-th mat\'s mrae:' % (i + 1), mrae) avg_mrae = avg_mrae / len(matlist) print('The average mrae is:', avg_mrae) return avg_mrae generated_folder_path = "F:\\NTIRE 2020\\spectral reconstruction\\ensemble\\ensemble\\track1" generated_folder_path = "F:\\NTIRE 2020\\spectral reconstruction\\ensemble\\ensemble\\track2" groundtruth_folder_path = "F:\\NTIRE 2020\\spectral reconstruction\\NTIRE2020_Validation_Spectral" avg_mrae = folder_img_mrae(generated_folder_path, groundtruth_folder_path)

36.870968

118

0.706328

0

1,189

0.346748

dd895eff6bdbc6e4f11421a7c77e8c3865e7d03d

2,435

py

Python

board/send_message.py

ben741863140/cfsystem

227e269f16533719251962f4d8caee8b51091d2f

[ "Apache-2.0" ]

4

2018-02-22T01:59:07.000Z

2020-07-09T06:28:46.000Z

board/send_message.py

ben741863140/cfsystem

227e269f16533719251962f4d8caee8b51091d2f

[ "Apache-2.0" ]

null

board/send_message.py

ben741863140/cfsystem

227e269f16533719251962f4d8caee8b51091d2f

[ "Apache-2.0" ]

null

# -*- coding:utf-8 -*- import gzip import re import http.cookiejar import urllib.request import urllib.parse # from logreg.sender import use_sender, sender def send_message(handle, content, captcha): def ungzip(data): return gzip.decompress(data) def get_csrf(data): cer = re.compile('data-csrf=\'(.*?)\'> </span>', re.S) return cer.findall(data)[0] def getOpener(head): # deal with coookie cj = http.cookiejar.CookieJar() pro = urllib.request.HTTPCookieProcessor(cj) opener = urllib.request.build_opener(pro) header = [] for key, value in head.items(): elem = (key, value) header.append(elem) opener.addheaders = header return opener header = { 'Connection': 'Keep-Alive', 'Accept': 'text/html, application/xhtml+xml, */*', 'Accept-Language': 'en-US,en;q=0.8,zh-Hans-CN;q=0.5,zh-Hans;q=0.3', 'User-Agent': 'Mozilla/5.0 (Windows NT 6.3; WOW64; Trident/7.0; rv:11.0) like Gecko', 'Accept-Encoding': 'gzip, deflate', 'Host': 'www.codeforces.com', 'DNT': '1' } url = 'http://codeforces.com/enter' opener = getOpener(header) data = opener.open(url).read() data = ungzip(data) csrf_token = get_csrf(data.decode()) # print(data) # use = str(sender(use_sender())) post_dict = { 'csrf_token': csrf_token, 'action': 'enter', 'ftaa': 'facg0yyl14awvys2jp', 'bfaa': 'd3165a769f306b8a47053d749e2d920a', 'handleOrEmail': 'scau_support', 'password': 'Aa123456', '_tta': '435' } # print(use) # print(handle) # print(data) # if 'scau_support' not in str(data): # return -1 post_data = urllib.parse.urlencode(post_dict).encode() opener.open(url, post_data) url = 'http://codeforces.com/usertalk?other=' + str(handle) data = opener.open(url).read() data = ungzip(data) if 'scau_support' not in str(data): return -1 csrf_token = get_csrf(data.decode()) post_dict = { 'csrf_token': csrf_token, 'action': 'sendMessage', 'content': content, '_tta': '435' } post_data = urllib.parse.urlencode(post_dict).encode() data = opener.open(url, post_data).read() data = ungzip(data) # print(data) if captcha not in str(data): return 1 return 0

29.695122

93

0.588501

0

844

0.346612

dd8f4efcbe0f27065a9ebbb9e0dbf84e6d87fb06

22,725

py

Python

preprocess.py

cheery/pytci

57b526b621da5e6783d15d73bac4ca57b281be70

[ "MIT" ]

148

2015-10-18T04:47:27.000Z

2021-11-09T09:36:43.000Z

preprocess.py

cheery/pytci

57b526b621da5e6783d15d73bac4ca57b281be70

[ "MIT" ]

3

2015-10-21T21:21:38.000Z

2017-04-10T00:16:04.000Z

preprocess.py

cheery/pytci

57b526b621da5e6783d15d73bac4ca57b281be70

[ "MIT" ]

10

2015-10-18T03:29:39.000Z

2018-12-18T12:14:01.000Z

import tokenize, operator macro_list = {} def chomp(state, with_defined=False): token = state.next_expanded_token() while token is not None: if name_of(token) == "macro": for token in run_macro(state): yield token elif state.processing: yield token token = state.next_expanded_token() def run_macro(state): identifier = state.expect('identifier') macro_name = value_of(identifier) if macro_name in macro_list: for token in macro_list[macro_name](state, position_of(identifier)): yield token assert state.macro_end(), "{1}: {0}: macro is expected to end".format(*position_of(identifier)) else: assert False, "Macro {!r} not implemented".format(macro_name) def pump_token(macro_stack, macro_queue, current, passthrough): if isinstance(current, list): # an expansion. for current in current: pump_token(macro_stack, macro_queue, current, passthrough) elif len(macro_stack) > 0: if macro_stack[-1].pump(current): macro_queue.extend(macro_stack.pop(-1).invoke()) else: passthrough.append(current) def pull_identifier(state): token = state.next_token() if token and value_of(token) == '(': token = state.next_token() stop = state.next_token() assert stop and value_of(stop) == ')', "bonked 'defined'" assert token and name_of(token) == 'identifier', "bonked 'defined'" return token class CallBuilder(object): def __init__(self, position, expansion): # at this point '(' has been processed. self.position = position self.expansion = expansion self.bumps = 0 self.bags = [] self.bag = [] self.toco = 0 def pump(self, token): value = value_of(token) if value == ',' and self.bumps == 0: self.bags.append(self.bag) self.bag = [] if value == '(': self.bumps += 1 if value == ')': if self.bumps == 0: return True self.bumps -= 1 self.bag.append(token) return False def invoke(self): if self.toco > 1: # only if there were nonzero arguments. self.bags.append(self.bag) return self.expansion(self.position, self.bags) def process_define(state, position): macro_name = value_of(state.expect('identifier')) macro_func = (state.stream.character == '(') macro_stream = state.macro_stream() if state.processing: if macro_func: # TODO: warn if macro is redefined state.env[macro_name] = parse_macro_function(macro_stream) else: state.env[macro_name] = list(macro_stream) return () def process_undef(state, position): macro_name = value_of(state.expect('identifier')) if state.processing and macro_name in state.env: state.env.pop(macro_name) return () def process_if(state, position): state.stack.append((state.processing, state.processing_inside)) state.processing_inside = 'cond-done' macro_stream = state.hacked_macro_expansion() if state.processing: state.processing = bool(state.macroeval(state, macro_stream)) state.processing_inside = ('cond', 'cond-done')[state.processing] return () def process_elif(state, position): macro_stream = state.hacked_macro_expansion() if state.processing_inside == 'cond': state.processing = state.macroeval(state, macro_stream) state.processing_inside = ('cond', 'cond-done')[state.processing] elif state.processing_inside == 'cond-done': state.processing = False else: assert False, "{1}: {0}: #elif at toplevel".format(*position) return () def process_else(state, position): if state.processing_inside == 'cond': state.processing = True elif state.processing_inside == 'cond-done': state.processing = False else: assert False, "{2}: {1}: #else at {0}".format(state.processing_inside, *position) state.processing_inside = 'else-block' return () def process_ifdef(state, position): state.stack.append((state.processing, state.processing_inside)) state.processing_inside = 'cond-done' macro_name = value_of(state.expect('identifier')) if state.processing: state.processing = macro_name in state.env state.processing_inside = ('cond', 'cond-done')[state.processing] return () def process_ifndef(state, position): state.stack.append((state.processing, state.processing_inside)) state.processing_inside = 'cond-done' macro_name = value_of(state.expect('identifier')) if state.processing: state.processing = macro_name not in state.env state.processing_inside = ('cond', 'cond-done')[state.processing] return () def process_endif(state, position): assert len(state.stack) > 0, "{1}: {0}: excess endif".format(*position) state.processing, state.processing_inside = state.stack.pop(-1) return () # This error handling is bit weird. The idea is # that you could generate stubs instead of halting the compiler. def process_error(state, position): macro_stream = state.macro_stream() if state.processing: message = ' '.join(map(value_of, macro_stream)) return [tokenize.token(position, 'error', message)] return () def process_line(state, position): line = int(value_of(state.expect('number'))) filename = value_of(state.expect('string')) state.stream.skip_spaces() state.stream.line = line state.stream.filename = filename return () def process_include(state, position): if state.macro_end(): assert len(state.stack) > 0, "{1}: {0}: malformed include".format(*position) token = state.next_token() if name_of(token) == 'string': if state.processing: return state.include(state, position, value_of(token), True) else: assert value_of(token) == '<', "{1}: {0}: malformed include".format(*position) string = "" while state.stream.character not in ('>', '', '\n'): string += state.stream.get_next() assert state.stream.get_next() == '>', "{1}: {0}: malformed include".format(*position) if state.processing: return state.include(state, position, string, False) return () def _init_itself(): for name, value in globals().iteritems(): if name.startswith('process_'): macro_name = name.split('_', 1)[1] macro_list[macro_name] = value _init_itself() # ? - badly implemented, ! - no implementation #? Integer constants. #? Character constants, which are interpreted as they would be in normal code. #? Arithmetic operators for addition, subtraction, multiplication, division, #?? bitwise operations, shifts, comparisons, and logical operations (&& and ||). #! The latter two obey the usual short-circuiting rules of standard C. # Macros. All macros in the expression are expanded before # actual computation of the expression's value begins. # Uses of the defined operator, which lets you check whether macros are defined in the middle of an #if. # Identifiers that are not macros, which are all considered to be the number zero. # This allows you to write #if MACRO instead of #ifdef MACRO, if you know that MACRO, # when defined, will always have a nonzero value. Function-like macros used without # their function call parentheses are also treated as zero. def default_macroeval(state, sequence): context = [] value_stack = [] operator_stack = [] def flip(precedence): while len(operator_stack) > 0 and quick_precedence_table[operator_stack[-1]] >= precedence: op = operator_stack.pop(-1) argc, fn = quick_operator_table[op] value_stack[-argc:] = [fn(*value_stack[-argc:])] for token in sequence: if value_of(token) in quick_precedence_table: flip(quick_precedence_table[value_of(token)]) operator_stack.append(value_of(token)) elif value_of(token) == '(': context.append((value_stack, operator_stack)) value_stack = [] operator_stack = [] elif value_of(token) == ')': flip(0) assert len(value_stack) == 1, "lol?" vs, operator_stack = context.pop(-1) value_stack = vs + value_stack elif name_of(token) == 'number': if '.' in value_of(token): value_stack.append(float(value_of(token))) elif value_of(token).startswith('0x') or value_of(token).startswith('0X'): value_stack.append(long(value_of(token).rstrip('L'), 16)) else: value_stack.append(long(value_of(token).rstrip('L'))) flip(150) elif name_of(token) in ('char', 'string'): value_stack.append(value_of(token)) flip(150) elif name_of(token) == 'identifier': value_stack.append(0) else: assert False, "Not sure how to macro-evaluate: {}".format(token) flip(0) if len(value_stack) == 1 and len(context) == 0: return value_stack[0] assert False, (value_stack + list(reversed(operator_stack))) quick_operator_table = { '!':(1, operator.not_), '*':(2, operator.mul), '/':(2, operator.div), '%':(2, operator.mod), '+':(2, operator.add), '-':(2, operator.sub), '<<':(2, operator.lshift), '>>':(2, operator.rshift), '<':(2, operator.lt), '<=':(2, operator.le), '>':(2, operator.gt), '>=':(2, operator.ge), '==':(2, operator.eq), '!=':(2, operator.ne), '&':(2, operator.and_), '^':(2, operator.xor), '|':(2, operator.or_), '&&':(2, (lambda x, y: x and y)), '||':(2, (lambda x, y: x or y)), } quick_precedence_table = { '!':200, '*':100, '/':100, '%':100, '+':80, '-':80, '<<':70, '>>':70, '<':60, '<=':60, '>':60, '>=':60, '==':50, '!=':50, '&':40, '^':35, '|':30, '&&':25, '||':20, } class BaseContext(object): def __init__(self, parent, stream, shadow): self.parent = parent self.stream = stream self.shadow = shadow self.variables = () self.exhausted = False def next_token(self): token = tokenize.chop(self.stream) if token is None: self.exhausted = True return token def macro_concat(self): return False def macro_end(self): self.stream.skip_spaces() return self.stream.character in ('', '\n') def macro_func(self): self.stream.skip_spaces_and_newlines() return self.stream.character == '(' class ExpandContext(object): def __init__(self, parent, stream, shadow, variables=()): self.parent = parent self.stream = stream self.shadow = shadow self.variables = variables try: self.exhausted = False self.lookahead = stream.next() except StopIteration as stop: self.exhausted = True self.lookahead = None def next_token(self): token = self.lookahead try: self.exhausted = False self.lookahead = self.stream.next() except StopIteration as stop: self.exhausted = True self.lookahead = None assert token is not None, "over fetch" return token def macro_concat(self): return self.lookahead and value_of(self.lookahead) == '##' def macro_end(self): return False def macro_func(self): assert not self.exhausted return value_of(self.lookahead) == '(' class ExpandedContext(ExpandContext): pass class PreprocessorState(object): def __init__(self, stream, env, include_chain=(), include=(), macroeval=default_macroeval, processing=True, processing_inside='toplevel'): self.stream = stream self.env = env self.include_chain = include_chain self.include = include self.macroeval = macroeval self.processing = processing self.processing_inside = processing_inside self.stack = [] self.context = BaseContext(None, stream, ()) def pump_context(self): while self.context and self.context.exhausted: self.context = self.context.parent def next_token(self): token = self.context.next_token() self.pump_context() return token def next_expanded_token(self, with_defined=False): context = self.context token = self.next_token() if self.context and self.context.macro_concat(): self.next_token() assert self.context == context, "Catenate should stick within context" other = self.expect('identifier') return catenate_tokens(token, other, context.variables) if isinstance(context, ExpandedContext): return token if with_defined and token and value_of(token) == 'defined': token = self.next_token() if token and value_of(token) == '(': token = self.expect('identifier') rp = self.next_token() assert rp and value_of(rp) == ')', "expected right parenthesis in 'defined'" return tokenize.token(position_of(token), "number", ["0", "1"][value_of(token) in self.env]) if token and value_of(token) == '#' and isinstance(context, ExpandContext) and context == self.context: ntoken = self.next_token() if value_of(ntoken) in context.variables: return tokenize.token(position_of(ntoken), "string", stringify(context.variables[value_of(ntoken)])) else: assert False, "'#' outside proper context" if token and name_of(token) == 'identifier': value = value_of(token) if value in context.shadow: return token if value in context.variables: self.context = ExpandedContext(self.context, iter(context.variables[value]), ()) self.pump_context() return self.next_expanded_token() expansion = self.env.get(value) if expansion is None: return token elif callable(expansion) and self.context and self.context.macro_func(): args = self.next_macro_call() self.context = expansion(self.context, context.shadow + (value,), position_of(token), args) self.pump_context() return self.next_expanded_token() else: self.context = ExpandContext(self.context, iter(expansion), context.shadow + (value,)) self.pump_context() return self.next_expanded_token() return token def next_macro_call(self): begin = self.next_token() assert value_of(begin) == '(', "broken preprocessor" token = self.next_expanded_token() if token and value_of(token) == ')': return [] bag = [] args = [bag] while token and value_of(token) != ')': if value_of(token) == '(': bag.extend(self.grouped_tokens(token)) elif value_of(token) == ',': bag = [] args.append(bag) else: bag.append(token) token = self.next_expanded_token() if token and value_of(token) == ')': return args assert False, "{1}: {0}: nonterminated macro call".format(position_of(begin)) def grouped_tokens(self, token): yield token token = self.next_expanded_token() while token and value_of(token) != ')': if value_of(token) == '(': for subtoken in self.grouped_tokens(token): yield subtoken else: yield token token = self.next_expanded_token() if token and value_of(token) == ')': yield token else: assert False, "{1}: {0}: nonterminated preprocessed group".format(position_of(begin)) def expect(self, name): token = self.next_token() assert name_of(token) == name, "'expected' error message not implemented: {} got {}".format(name, token) return token def macro_end(self): self.pump_context() if self.context is None: return True return self.context.macro_end() def macro_stream(self): sequence = [] while not self.macro_end(): sequence.append(self.next_token()) return MacroStream(iter(sequence)) def hacked_macro_expansion(self): sequence = [] while not self.macro_end(): sequence.append(self.next_token()) original_context = self.context self.context = ExpandContext(None, iter(sequence), original_context.shadow) sequence = [] while self.context is not None: sequence.append(self.next_expanded_token(with_defined=True)) self.context = original_context return MacroStream(iter(sequence)) def fork(self, stream, filename): include_chain = self.include_chain + (filename,) return self.__class__(stream, self.env, include_chain, include=self.include, macroeval=self.macroeval) class MacroStream(object): def __init__(self, generator): self.generator = generator def next_token(self): try: return self.generator.next() except StopIteration as stop: return None def __iter__(self): return self.generator def parse_macro_function(stream): lp = stream.next_token() assert value_of(lp) == '(', "broken preprocessor" bind = [] is_variadic = False current = stream.next_token() while current and value_of(current) != ')': if value_of(current) == '...': is_variadic = True break bind.append(value_of(current)) current = stream.next_token() if not current or value_of(current) != ",": break current = stream.next_token() assert current and value_of(current) == ')', "{1}: {0}: unterminated argument list error".format(position_of(lp)) return MacroFunction(bind, is_variadic, list(stream)) class MacroFunction(object): def __init__(self, bind, is_variadic, body): self.bind = bind self.is_variadic = is_variadic self.body = body def __call__(self, context, shadow, position, args): if self.is_variadic: assert len(args) >= len(self.bind), "argument error, error not implemented. {} -> {} ({})".format(position, self.bind, args) else: assert len(args) == len(self.bind), "argument error, error not implemented. {} -> {} ({})".format(position, self.bind, args) variables = dict(zip(self.bind, args)) if self.is_variadic: variables['...'] = args[len(self.bind):] return ExpandContext(context, iter(self.body), shadow, variables) def position_of(token): return token[0] def name_of(token): return token[1] def value_of(token): return token[2] def stringify(tokens): return ' '.join(map(value_of, tokens)) def catenate_tokens(lhs, rhs, variables): position = position_of(lhs) if value_of(lhs) in variables: lhs = variables[value_of(lhs)] assert len(lhs) <= 1, "rare case for catenation" else: lhs = [lhs] if value_of(rhs) in variables: rhs = variables[value_of(rhs)] assert len(rhs) <= 1, "rare case for catenation" else: rhs = [rhs] return tokenize.token(position, 'identifier', ''.join(map(value_of, lhs + rhs))) if False: import character_stream pull = character_stream.pull def new_pull(x): ch = pull(x) print "read character:", repr(ch) return ch character_stream.pull = new_pull if __name__=='__main__': import trigraphs, traceback, os, sys from character_stream import CharacterStream local_includes = [] global_includes = ['/usr/lib/gcc/x86_64-linux-gnu/4.8/include', '/usr/local/include', '/usr/lib/gcc/x86_64-linux-gnu/4.8/include-fixed', '/usr/include/x86_64-linux-gnu', '/usr/include'] def include_stub(state, position, name, local): if local: includes = [os.path.dirname(state.include_chain[-1])] + local_includes else: includes = global_includes filename = name for dirname in includes: path = os.path.join(dirname, name) if os.path.exists(path): filename = path break else: return [] # incorrect, but lets lol later. if filename in state.include_chain: print "{1}: {0}: cyclic include: ".format(*position) + filename return [] # incorrect again with open(filename, 'r') as fd: contents = fd.read() stream = CharacterStream(trigraphs.translate(contents), 1, filename) return chomp(state.fork(stream, filename)) def advance_position((line0, file0), (line1, file1)): if file0 == file1 and line1 - 9 < line0 < line1: sys.stdout.write("\n" * (line1 - line0)) else: sys.stdout.write("\n#line {!r} \"{!s}\"\n".format(line1, file1)) return (line1, file1) def main(): import sys env = {} if len(sys.argv) < 2: filename = "/usr/include/stdio.h" else: filename = sys.argv[1] with open(filename, 'r') as fd: contents = fd.read() stream = CharacterStream(trigraphs.translate(contents), 1, filename) state = PreprocessorState(stream, env, include_chain=(filename,), include=include_stub) try: position = (1, filename) for token in chomp(state): if position_of(token) != position: position = advance_position(position, position_of(token)) # Token generation. This is still wrong if name_of(token) == 'string': sys.stdout.write('"' + value_of(token) + '" ') elif name_of(token) == 'char': sys.stdout.write("'" + value_of(token) + "' ") else: sys.stdout.write(value_of(token) + ' ') sys.stdout.write('\n') except AssertionError as ass: traceback.print_exc() for x in xrange(5): print tokenize.chop(stream) main()

37.561983

189

0.60374

9,242

0.406689

1,286

0.05659

0

3,001

0.132057

dd8f9e880d1c5b15888f038a47c041322592d1b0

2,177

py

Python

arfit/run_carma_pack.py

farr/arfit

7ff6def331ef98f43f623da2d9867d1ac967448b

[ "MIT" ]

5

2015-04-29T21:46:52.000Z

2021-05-13T04:59:23.000Z

arfit/run_carma_pack.py

afcarl/arfit

7ff6def331ef98f43f623da2d9867d1ac967448b

[ "MIT" ]

null

arfit/run_carma_pack.py

afcarl/arfit

7ff6def331ef98f43f623da2d9867d1ac967448b

[ "MIT" ]

2

2015-12-03T12:08:32.000Z

2018-05-26T16:20:31.000Z

#!/usr/bin/env python from __future__ import print_function import argparse import carmcmc as cm import numpy as np import os import plotutils.autocorr as ac import sys if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--input', required=True, metavar='FILE', help='input file') parser.add_argument('--output', required=True, metavar='FILE', help='chain output') parser.add_argument('--p', default=3, type=int, metavar='P', help='AR order (default: %(default)s)') parser.add_argument('--q', default=2, type=int, metavar='Q', help='MA order (default: %(default)s)') parser.add_argument('--neff', default=1000, type=int, metavar='N', help='number of independent samples (default: %(default)s)') parser.add_argument('--tmax', default=100.0, type=float, metavar='T', help='maximum temperature') parser.add_argument('--ntemp', default=10, type=int, metavar='N', help='number of temperatures') args = parser.parse_args() data = np.loadtxt(args.input) times, tind = np.unique(data[:,0], return_index=True) data = data[tind, :] model = cm.CarmaModel(data[:,0], data[:,1], data[:,2], p=args.p, q=args.q) thin = 1 nsamp = 10*args.neff out, ext = os.path.splitext(args.output) outtemp = out + '.TEMP' + ext while True: sample = model.run_mcmc(nsamp, nthin=thin, nburnin=thin*nsamp/2, tmax=args.tmax, ntemperatures=args.ntemp) np.savetxt(outtemp, np.column_stack((sample.trace, sample.get_samples('loglik'), sample.get_samples('logpost')))) os.rename(outtemp, args.output) taus = [] for j in range(sample.trace.shape[1]): taus.append(ac.autocorrelation_length_estimate(sample.trace[:,j])) taus = np.array(taus) if np.any(np.isnan(taus)): neff_achieved = 0 else: neff_achieved = sample.trace.shape[0] / np.max(taus) print('Ran for ', nsamp*thin, ' steps, achieved ', neff_achieved, ' independent samples') sys.__stdout__.flush() if neff_achieved >= args.neff: break else: thin *= 2

34.015625

131

0.635278

0

378

0.173633

dd90daf3764122311fdf88342d48e04ecb1b9e7d

3,946

py

Python

editquality/feature_lists/wikitext.py

paulkernfeld/editquality

029f21278d89d6e50b0eac7b39d8355f8e4686f4

[ "MIT" ]

18

2015-09-13T10:47:31.000Z

2018-08-20T15:00:35.000Z

editquality/feature_lists/wikitext.py

paulkernfeld/editquality

029f21278d89d6e50b0eac7b39d8355f8e4686f4

[ "MIT" ]

98

2015-12-13T12:18:24.000Z

2018-08-07T21:10:46.000Z

editquality/feature_lists/wikitext.py

paulkernfeld/editquality

029f21278d89d6e50b0eac7b39d8355f8e4686f4

[ "MIT" ]

17

2015-09-29T20:52:12.000Z

2018-08-20T11:33:30.000Z

from revscoring.features import Feature, wikitext from revscoring.features.modifiers import div, log, max, sub def _process_new_longest(p_longest, r_longest): if r_longest > p_longest: return r_longest else: return 1 parent = [ log(wikitext.revision.parent.chars + 1), log(wikitext.revision.parent.tokens + 1), log(wikitext.revision.parent.words + 1), log(wikitext.revision.parent.uppercase_words + 1), log(wikitext.revision.parent.headings + 1), log(wikitext.revision.parent.wikilinks + 1), log(wikitext.revision.parent.external_links + 1), log(wikitext.revision.parent.templates + 1), log(wikitext.revision.parent.ref_tags + 1), div(wikitext.revision.parent.chars, max(wikitext.revision.parent.words, 1), name="revision.parent.chars_per_word"), div(wikitext.revision.parent.words, max(wikitext.revision.parent.tokens, 1), name="revision.parent.words_per_token"), div(wikitext.revision.parent.uppercase_words, max(wikitext.revision.parent.words, 1), name="revision.parent.uppercase_words_per_word"), div(wikitext.revision.parent.markups, max(wikitext.revision.parent.tokens, 1), name="revision.parent.markups_per_token"), ] diff = [ wikitext.revision.diff.markup_delta_sum, wikitext.revision.diff.markup_delta_increase, wikitext.revision.diff.markup_delta_decrease, wikitext.revision.diff.markup_prop_delta_sum, wikitext.revision.diff.markup_prop_delta_increase, wikitext.revision.diff.markup_prop_delta_decrease, wikitext.revision.diff.number_delta_sum, wikitext.revision.diff.number_delta_increase, wikitext.revision.diff.number_delta_decrease, wikitext.revision.diff.number_prop_delta_sum, wikitext.revision.diff.number_prop_delta_increase, wikitext.revision.diff.number_prop_delta_decrease, wikitext.revision.diff.uppercase_word_delta_sum, wikitext.revision.diff.uppercase_word_delta_increase, wikitext.revision.diff.uppercase_word_delta_decrease, wikitext.revision.diff.uppercase_word_prop_delta_sum, wikitext.revision.diff.uppercase_word_prop_delta_increase, wikitext.revision.diff.uppercase_word_prop_delta_decrease, sub(wikitext.revision.chars, wikitext.revision.parent.chars, name="revision.diff.chars_change"), sub(wikitext.revision.tokens, wikitext.revision.parent.tokens, name="revision.diff.tokens_change"), sub(wikitext.revision.words, wikitext.revision.parent.words, name="revision.diff.words_change"), sub(wikitext.revision.markups, wikitext.revision.parent.markups, name="revision.diff.markups_change"), sub(wikitext.revision.headings, wikitext.revision.parent.headings, name="revision.diff.headings_change"), sub(wikitext.revision.external_links, wikitext.revision.parent.external_links, name="revision.diff.external_links_change"), sub(wikitext.revision.wikilinks, wikitext.revision.parent.wikilinks, name="revision.diff.wikilinks_change"), sub(wikitext.revision.templates, wikitext.revision.parent.templates, name="revision.diff.templates_change"), sub(wikitext.revision.tags, wikitext.revision.parent.tags, name="revision.diff.tags_change"), sub(wikitext.revision.ref_tags, wikitext.revision.parent.ref_tags, name="revision.diff.ref_tags_change"), Feature("revision.diff.longest_new_token", _process_new_longest, returns=int, depends_on=[wikitext.revision.parent.longest_token, wikitext.revision.longest_token]), Feature("revision.diff.longest_new_repeated_char", _process_new_longest, returns=int, depends_on=[wikitext.revision.parent.longest_repeated_char, wikitext.revision.longest_repeated_char]) ]

41.978723

71

0.727826

0

521

0.132032

dd9402b8557bc8fee0baeb9f728d3c332668ae1e

2,240

py

Python

test/http2_test/http2_server_health_check.py

miyachu/grpc

a06ea3c3162c10ff90a1578bf82bbbff95dc799d

[ "BSD-3-Clause" ]

2

2021-09-10T00:20:13.000Z

2021-11-16T11:27:19.000Z

test/http2_test/http2_server_health_check.py

miyachu/grpc

a06ea3c3162c10ff90a1578bf82bbbff95dc799d

[ "BSD-3-Clause" ]

null

test/http2_test/http2_server_health_check.py

miyachu/grpc

a06ea3c3162c10ff90a1578bf82bbbff95dc799d

[ "BSD-3-Clause" ]

1

2020-11-04T04:19:45.000Z

# Copyright 2017, Google Inc. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following disclaimer # in the documentation and/or other materials provided with the # distribution. # * Neither the name of Google Inc. nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import argparse import hyper import sys # Utility to healthcheck the http2 server. Used when starting the server to # verify that the server is live before tests begin. if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--server_host', type=str, default='localhost') parser.add_argument('--server_port', type=int, default=8080) args = parser.parse_args() server_host = args.server_host server_port = args.server_port conn = hyper.HTTP20Connection('%s:%d' % (server_host, server_port)) conn.request('POST', '/grpc.testing.TestService/UnaryCall') resp = conn.get_response() if resp.headers.get('grpc-encoding') is None: sys.exit(1) else: sys.exit(0)

44.8

75

0.766964

0

1,743

0.778125

dd9452c189452f40fb4e6f56c43cb761ffc48203

3,494

py

Python

server/droidio/demands/test/test_views.py

lucasOlivio/droid.io

945b1452eaaa73b4d7f9d1d1a35eaa2900e97e96

[ "MIT" ]

null

server/droidio/demands/test/test_views.py

lucasOlivio/droid.io

945b1452eaaa73b4d7f9d1d1a35eaa2900e97e96

[ "MIT" ]

null

server/droidio/demands/test/test_views.py

lucasOlivio/droid.io

945b1452eaaa73b4d7f9d1d1a35eaa2900e97e96

[ "MIT" ]

null

from django.urls import reverse from rest_framework.test import APITestCase from rest_framework import status from nose.tools import eq_ from faker import Faker import factory from ..models import Demand from .factories import DemandFactory from ..serializers import DemandSerializer from droidio.users.test.factories import UserFactory fake = Faker() class TestDemandListTestCase(APITestCase): """ Tests /demands list operations. """ def setUp(self): self.user = UserFactory() self.client.force_authenticate(user=self.user) self.url = reverse("demands-list") self.demand_data = factory.build(dict, FACTORY_CLASS=DemandFactory) def test_post_request_with_no_data_fails(self): response = self.client.post(self.url, {}) eq_(response.status_code, status.HTTP_400_BAD_REQUEST) def test_post_request_with_valid_data_succeeds(self): response = self.client.post(self.url, self.demand_data) eq_(response.status_code, status.HTTP_201_CREATED) demand = Demand.objects.get(pk=response.data.get("id")) eq_(demand.description, self.demand_data.get("description")) def test_get_list_returns_only_my_demands(self): # Set testing demands DemandFactory(user_created=self.user) user2 = UserFactory() DemandFactory(user_created=user2) # Test response and results response = self.client.get(self.url) eq_(response.status_code, status.HTTP_200_OK) demands = Demand.objects.filter(user_created=self.user) serializer = DemandSerializer(demands, many=True) eq_(response.data["count"], 1) eq_(response.data["results"], serializer.data) class TestDemandDetailTestCase(APITestCase): """ Tests /demands detail operations. """ def setUp(self): self.user = UserFactory() self.client.force_authenticate(user=self.user) self.demand = DemandFactory(user_created=self.user) self.url = reverse("demands-detail", kwargs={"pk": self.demand.pk}) def test_get_request_returns_a_given_demand(self): response = self.client.get(self.url) eq_(response.status_code, status.HTTP_200_OK) def test_patch_request_updates_a_demand(self): new_description = fake.text() payload = {"description": new_description} response = self.client.patch(self.url, payload) eq_(response.status_code, status.HTTP_200_OK) demand = Demand.objects.get(pk=self.demand.id) eq_(demand.description, new_description) def test_put_request_updates_a_demand(self): payload = factory.build(dict, FACTORY_CLASS=DemandFactory) response = self.client.put(self.url, payload) eq_(response.status_code, status.HTTP_200_OK) demand = Demand.objects.get(pk=self.demand.id) eq_(demand.description, payload["description"]) def test_set_demand_completed(self): custom_action = reverse("demands-set-completed", kwargs={"pk": self.demand.pk}) response = self.client.post(custom_action) eq_(response.status_code, status.HTTP_200_OK) demand = Demand.objects.get(pk=self.demand.id) eq_(demand.is_completed, True) def test_delete_request_deletes_a_demand(self): response = self.client.delete(self.url) eq_(response.status_code, status.HTTP_204_NO_CONTENT) demand = Demand.objects.filter(pk=self.demand.id).first() eq_(demand, None)

34.94

87

0.704637

3,131

0.896108

0

256

0.073268

dd94f0230de4472e8494e2e5c028fe0a163fe4d9

422

py

Python

leetcode/python/check_in_n_and_its_double_exists.py

subhadig/leetcode

9151ea49c342efa228cf82de72736c3445bbfef2

[ "Unlicense" ]

null

leetcode/python/check_in_n_and_its_double_exists.py

subhadig/leetcode

9151ea49c342efa228cf82de72736c3445bbfef2

[ "Unlicense" ]

null

leetcode/python/check_in_n_and_its_double_exists.py

subhadig/leetcode

9151ea49c342efa228cf82de72736c3445bbfef2

[ "Unlicense" ]

null

# https://leetcode.com/explore/learn/card/fun-with-arrays/527/searching-for-items-in-an-array/3250/ # time: O(n) # space: O(n) class Solution: def checkIfExist(self, arr: List[int]) -> bool: if not arr: return False nums = set() for x in arr: if 2*x in nums or x/2 in nums: return True else: nums.add(x) return False

26.375

99

0.533175

293

0.694313

0

124

0.293839

dd95ba5b789b57d2c18cb6c697a4bed1400af969

2,743

py

Python

cloud_functions/trigger-monitor-dag-function/main_test.py

google/feedloader

f6a25569bc3d7d4ee326961fd3b01e45fc3858e4

[ "Apache-2.0" ]

5

2021-02-15T12:49:12.000Z

2022-01-12T06:28:41.000Z

cloud_functions/trigger-monitor-dag-function/main_test.py

google/feedloader

f6a25569bc3d7d4ee326961fd3b01e45fc3858e4

[ "Apache-2.0" ]

null

cloud_functions/trigger-monitor-dag-function/main_test.py

google/feedloader

f6a25569bc3d7d4ee326961fd3b01e45fc3858e4

[ "Apache-2.0" ]

4

2021-02-16T17:28:00.000Z

2021-06-18T15:27:52.000Z

# coding=utf-8 # Copyright 2021 Google LLC. # # 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. """Unit tests for the Trigger DAG Cloud Function.""" import os from unittest import mock from absl.testing import parameterized import main _TEST_CLIENT_ID = '12345.apps.googleusercontent.com' _TEST_DAG_NAME = 'dag-name' _TEST_WEBSERVER_ID = 'https://12345-tp.appspot.com' @mock.patch.dict( os.environ, { 'CLIENT_ID': _TEST_CLIENT_ID, 'DAG_NAME': _TEST_DAG_NAME, 'WEBSERVER_ID': _TEST_WEBSERVER_ID, }) class TriggerMonitorDagFunctionTest(parameterized.TestCase): def setUp(self): super().setUp() self.event = { 'bucket': 'feed-bucket', 'name': 'filename', 'metageneration': 'test-metageneration', 'timeCreated': '0', 'updated': '0' } self.context = mock.create_autospec('google.cloud.functions.Context') self.context.event_id = '12345' self.context.event_type = 'gcs-event' self.context.timestamp = '2021-06-05T08:16:15.183Z' @mock.patch.object( main, 'make_iap_request', side_effect=Exception('Bad request: JSON body error')) def test_json_body_error(self, _): trigger_event = None with self.assertRaises(Exception) as context: main.trigger_dag(trigger_event, self.context) self.assertIn('Bad request: JSON body error', str(context.exception)) @mock.patch.object( main, 'make_iap_request', side_effect=Exception('Error in IAP response: unauthorized')) def test_iap_response_error(self, _): trigger_event = {'file': 'some-gcs-file'} with self.assertRaises(Exception) as context: main.trigger_dag(trigger_event, self.context) self.assertIn('Error in IAP response', str(context.exception)) @mock.patch.object(main, 'make_iap_request', autospec=True) def test_api_endpoint(self, make_iap_request_mock): main.trigger_dag(self.event, self.context) make_iap_request_mock.assert_called_once_with( 'https://12345-tp.appspot.com/api/experimental/dags/dag-name/dag_runs', '12345.apps.googleusercontent.com', method='POST', json={ 'conf': self.event, 'replace_microseconds': 'false' }, )

31.528736

79

0.696318

1,712

0.624134

0

1,873

0.682829

0

1,255

0.457528