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

542ed8915929d9082655f10271231d6e8237f5b5

2,848

py

Python

bin/models_vs_uniprot_check/ViPhOG_chunks_rank_summ.py

alexcorm/emg-viral-pipeline

f367002f0e1e375840e5696323bde65f7accb31f

[ "Apache-2.0" ]

30

2020-05-18T14:02:34.000Z

2022-03-16T20:04:25.000Z

bin/models_vs_uniprot_check/ViPhOG_chunks_rank_summ.py

lynceuslq/emg-viral-pipeline

53a99b84ed93428ee88d61e529bcf6799f5eec94

[ "Apache-2.0" ]

45

2020-04-30T09:45:03.000Z

2022-03-21T09:10:21.000Z

bin/models_vs_uniprot_check/ViPhOG_chunks_rank_summ.py

lynceuslq/emg-viral-pipeline

53a99b84ed93428ee88d61e529bcf6799f5eec94

[ "Apache-2.0" ]

12

2020-06-02T12:43:49.000Z

2022-02-22T13:09:13.000Z

#!/usr/bin/env python3 import os import re import glob import sys import operator import ast import argparse ############################################################################################### # This script was written as part of the analysis conducted on the output generated by # # hmmsearch, when the ViPhOG database was searched against UniProtKB. The ViPhOG profile HMM # # files were stored in different directories, each containing maximum 2000 files and named # # using a sequential number from 1 to 16 (hmm1...hmm16). For each one of these a corresponding# # output directory was generated, each containing a domtbl output file for each of the files # # stored in the hmm directories. The output directories were named using the same sequential # # numbers as the directories storing the hmm files (hmm1domtbl...hmm16domtbl). # ############################################################################################### parser = argparse.ArgumentParser(description = "Step 3: Generate summary tables for each taxonomic rank. Make sure to run the script from within the directory containing the domtbl output directories (check comment block for guidance) and following the scripts that execute Step 1 and Step 2") parser.add_argument("-i", "--input", dest = "input_file", help = "Path to summary chunk file", required = True) if len(sys.argv) == 1: parser.print_help() else: args = parser.parse_args() summ_file = args.input_file with open(summ_file) as input_file: header_line = input_file.readline().rstrip() taxa_ranks = [] for x,y in enumerate(header_line.split("\t")): if x >= 2: taxa_ranks.append((x, y)) for x,y in taxa_ranks: input_file.seek(0) next(input_file) with open(f"{os.path.splitext(summ_file)[0]}_{y}.tsv", "w") as output_file: output_file.write("ViPhOG\t#_taxons\tMost_significant\tMax_min_score\tOverlapping_taxons\tNext_max_score\n") for line in input_file: line = line.rstrip() viphog_id = line.split("\t")[0] rank_hits = ast.literal_eval(line.split("\t")[x]) total_hits = len(rank_hits) most_significant = "" score_range = "" overlap = "" next_max_score = "" if total_hits > 0: rank_hits_sorted = sorted(rank_hits, key = operator.itemgetter(2), reverse = True) most_significant = rank_hits_sorted[0][0] score_range = (rank_hits_sorted[0][2], rank_hits_sorted[0][3]) if total_hits > 1: overlap = [] for elem in rank_hits_sorted[1:]: if elem[2] >= score_range[1]: overlap.append((elem[0], elem[2])) if len(overlap) < 1: overlap = "" next_max_score = rank_hits_sorted[1][2] output_file.write("{}\t{}\t{}\t{}\t{}\t{}\n".format(viphog_id, total_hits, most_significant, score_range, overlap, next_max_score))

45.935484

293

0.652388

0

1,358

0.476826

54318f46c52690013bfe7cc4791a2d7dcc84bf04

6,349

py

Python

bika/lims/permissions.py

hocinebendou/bika.gsoc

85bc0c587de7f52073ae0e89bddbc77bf875f295

[ "MIT" ]

null

bika/lims/permissions.py

hocinebendou/bika.gsoc

85bc0c587de7f52073ae0e89bddbc77bf875f295

[ "MIT" ]

null

bika/lims/permissions.py

hocinebendou/bika.gsoc

85bc0c587de7f52073ae0e89bddbc77bf875f295

[ "MIT" ]

null

""" All permissions are defined here. They are also defined in permissions.zcml. The two files must be kept in sync. bika.lims.__init__ imports * from this file, so bika.lims.PermName or bika.lims.permissions.PermName are both valid. """ from Products.CMFCore.permissions import AddPortalContent # Add Permissions: # ---------------- AddAnalysis = 'BIKA: Add Analysis' AddAnalysisProfile = 'BIKA: Add AnalysisProfile' AddAnalysisRequest = 'BIKA: Add Analysis Request' AddAnalysisSpec = 'BIKA: Add AnalysisSpec' AddAttachment = 'BIKA: Add Attachment' AddARTemplate = 'BIKA: Add ARTemplate' AddBatch = 'BIKA: Add Batch' AddClient = 'BIKA: Add Client' AddClientFolder = 'BIKA: Add ClientFolder' AddInvoice = 'BIKA: Add Invoice' AddMethod = 'BIKA: Add Method' AddMultifile = 'BIKA: Add Multifile' AddPricelist = 'BIKA: Add Pricelist' AddProduct = 'BIKA: Add Product' AddProductCategory = 'BIKA: Add ProductCategory' AddStockItem = 'BIKA: Add StockItem' AddSupplyOrder = 'BIKA: Add SupplyOrder' AddInventoryOrder = 'BIKA: Add Inventory Order' AddSample = 'BIKA: Add Sample' AddSampleMatrix = 'BIKA: Add SampleMatrix' AddSamplePartition = 'BIKA: Add SamplePartition' AddSamplePoint = 'BIKA: Add SamplePoint' AddStorageLocation = 'BIKA: Add StorageLocation' AddSamplingDeviation = 'BIKA: Add SamplingDeviation' AddSamplingRound = 'BIKA: Add SamplingRound' AddSRTemplate = 'BIKA: Add SRTemplate' AddStorageLevel = 'BIKA: Add StorageLevel' AddStorageUnit = 'BIKA: Add StorageUnit' AddSubGroup = 'BIKA: Add Sub-group' # Default Archetypes Add Permission ADD_CONTENT_PERMISSION = AddPortalContent # Add Permissions for specific types, if required ADD_CONTENT_PERMISSIONS = { 'ARAnalysisSpec': AddAnalysisSpec, 'AnalysisProfile': AddAnalysisProfile, 'Analysis': AddAnalysis, 'AnalysisRequest': AddAnalysisRequest, 'Attachment': AddAttachment, 'Batch': AddBatch, 'Client': AddClient, 'Invoice': AddInvoice, 'Method': AddMethod, 'Multifile': AddMultifile, 'SupplyOrder': AddSupplyOrder, 'Order': AddInventoryOrder, 'Sample': AddSample, 'SampleMatrix': AddSampleMatrix, 'SamplePartition': AddSamplePartition, 'SamplingDeviation': AddSamplingDeviation, 'SamplingRound': AddSamplingRound, 'SubGroup': AddSubGroup, 'StorageLevel': AddStorageLevel, 'StorageUnit': AddStorageUnit, } # Very Old permissions: # --------------------- ManageBika = 'BIKA: Manage Bika' DispatchOrder = 'BIKA: Dispatch Order' ManageAnalysisRequests = 'BIKA: Manage Analysis Requests' ManageSamples = 'BIKA: Manage Samples' ManageSuppliers = 'BIKA: Manage Reference Suppliers' ManageReference = 'BIKA: Manage Reference' PostInvoiceBatch = 'BIKA: Post Invoice batch' ManagePricelists = 'BIKA: Manage Pricelists' # This allows to edit all client fields, and perform admin tasks on Clients. ManageClients = 'BIKA: Manage Clients' # this is for creating and transitioning worksheets ManageWorksheets = 'BIKA: Manage Worksheets' # this is for adding/editing/exporting analyses on worksheets EditWorksheet = 'BIKA: Edit Worksheet' RejectWorksheet = 'BIKA: Reject Worksheet' ImportInstrumentResults = "BIKA: Import Instrument Results" AccessJSONAPI = 'BIKA: Access JSON API' # New or changed permissions: # --------------------------- DispatchInventoryOrder = 'BIKA: Dispatch Inventory Order' ReceiveInventoryOrder = 'BIKA: Receive Inventory Order' StoreInventoryOrder = 'BIKA: Store Inventory Order' SampleSample = 'BIKA: Sample Sample' PreserveSample = 'BIKA: Preserve Sample' ReceiveSample = 'BIKA: Receive Sample' ExpireSample = 'BIKA: Expire Sample' DisposeSample = 'BIKA: Dispose Sample' ImportAnalysis = 'BIKA: Import Analysis' Retract = "BIKA: Retract" Verify = 'BIKA: Verify' VerifyOwnResults = 'BIKA: Verify own results' Publish = 'BIKA: Publish' EditSample = 'BIKA: Edit Sample' EditAR = 'BIKA: Edit AR' ResultsNotRequested = 'BIKA: Results not requested' ManageInvoices = 'BIKA: Manage Invoices' ViewResults = 'BIKA: View Results' EditResults = 'BIKA: Edit Results' EditFieldResults = 'BIKA: Edit Field Results' ViewRetractedAnalyses = 'BIKA: View Retracted Analyses' CancelAndReinstate = 'BIKA: Cancel and reinstate' # For adding login credentials to Contacts. ManageLoginDetails = 'BIKA: Manage Login Details' Assign = 'BIKA: Assign analyses' Unassign = 'BIKA: Unassign analyses' # Field permissions EditARContact = "BIKA: Edit AR Contact" ViewLogTab = 'BIKA: View Log Tab' # Edit AR # ----------------------------------------------------------------------------- # Allows to set values for AR fields in AR view # # Only takes effect if: # - The AR's 'cancellation_state' is 'active' # - The AR's 'review_state' is in: # 'sample_registered', 'to_be_sampled', 'sampled', 'to_be_preserved', # 'sample_due', 'sample_received', 'to_be_verified', 'attachment_due' EditAR = 'BIKA: Edit AR' # Edit Sample Partition # ----------------------------------------------------------------------------- # Allows to set a Container and/or Preserver for a Sample Partition. # See AR view: Sample Partitions table and Sample Partitions tab # # Only takes effect if: # - The Sample's 'cancellation_state' is 'active' # - The Sample's 'review_state' is in: # 'sample_registered', 'to_be_sampled', 'sampled', 'to_be_preserved', # 'sample_due', 'sample_received', 'to_be_verified', 'attachment_due' EditSamplePartition = 'BIKA: Edit Sample Partition' # Edit Client # ---------------------------------------------- # Allows access to 'Edit' and 'Contacts' tabs from Client View EditClient = 'BIKA: Edit Client' # Manage Supply Orders # ---------------------------------------------- # Allows access to 'Supply Orders' tab in Client context ManageSupplyOrders = 'BIKA: Manage Supply Orders' # Batch-specific permissions # ---------------------------------------------- EditBatch = 'BIKA: Edit Batch' CloseBatch = 'BIKA: Close Batch' ReopenBatch = 'BIKA: Reopen Batch' # Sampling Round permissions # -------------------------- CloseSamplingRound = 'BIKA: Close SamplingRound' ReopenSamplingRound = 'BIKA: Reopen SamplingRound' # Manage AR Imports # ---------------------------------------------- ManageARImport = 'BIKA: Manage ARImport' # Manage AR Priorities # ---------------------------------------------- ManageARPriority = 'BIKA: Manage ARPriority'

34.505435

79

0.695228

0

4,276

0.673492

5431f5aaf571f8d48be62c018da65e8a8b984c28

5,140

py

Python

python/venv/lib/python2.7/site-packages/openstack/tests/unit/telemetry/v2/test_sample.py

sjsucohort6/openstack

8471e6e599c3f52319926a582358358ef84cbadb

[ "MIT" ]

null

python/venv/lib/python2.7/site-packages/openstack/tests/unit/telemetry/v2/test_sample.py

sjsucohort6/openstack

8471e6e599c3f52319926a582358358ef84cbadb

[ "MIT" ]

null

python/venv/lib/python2.7/site-packages/openstack/tests/unit/telemetry/v2/test_sample.py

sjsucohort6/openstack

8471e6e599c3f52319926a582358358ef84cbadb

[ "MIT" ]

null

# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import mock import testtools from openstack.telemetry.v2 import sample SAMPLE = { 'id': None, 'metadata': {'1': 'one'}, 'meter': '2', 'project_id': '3', 'recorded_at': '4', 'resource_id': '5', 'source': '6', 'timestamp': '7', 'type': '8', 'unit': '9', 'user_id': '10', 'volume': '11.1', } OLD_SAMPLE = { 'counter_name': '1', 'counter_type': '2', 'counter_unit': '3', 'counter_volume': '4', 'message_id': None, 'project_id': '5', 'recorded_at': '6', 'resource_id': '7', 'resource_metadata': '8', 'source': '9', 'timestamp': '10', 'user_id': '11', } class TestSample(testtools.TestCase): def test_basic(self): sot = sample.Sample(SAMPLE) self.assertIsNone(sot.resource_key) self.assertIsNone(sot.resources_key) self.assertEqual('/meters/%(meter)s', sot.base_path) self.assertEqual('metering', sot.service.service_type) self.assertTrue(sot.allow_create) self.assertFalse(sot.allow_retrieve) self.assertFalse(sot.allow_update) self.assertFalse(sot.allow_delete) self.assertTrue(sot.allow_list) def test_make_new(self): sot = sample.Sample(SAMPLE) self.assertIsNone(sot.id) self.assertEqual(SAMPLE['metadata'], sot.metadata) self.assertEqual(SAMPLE['meter'], sot.meter) self.assertEqual(SAMPLE['project_id'], sot.project_id) self.assertEqual(SAMPLE['recorded_at'], sot.recorded_at) self.assertEqual(SAMPLE['resource_id'], sot.resource_id) self.assertIsNone(sot.sample_id) self.assertEqual(SAMPLE['source'], sot.source) self.assertEqual(SAMPLE['timestamp'], sot.generated_at) self.assertEqual(SAMPLE['type'], sot.type) self.assertEqual(SAMPLE['unit'], sot.unit) self.assertEqual(SAMPLE['user_id'], sot.user_id) self.assertEqual(SAMPLE['volume'], sot.volume) def test_make_old(self): sot = sample.Sample(OLD_SAMPLE) self.assertIsNone(sot.id) self.assertIsNone(sot.sample_id), self.assertEqual(OLD_SAMPLE['counter_name'], sot.meter) self.assertEqual(OLD_SAMPLE['counter_type'], sot.type) self.assertEqual(OLD_SAMPLE['counter_unit'], sot.unit) self.assertEqual(OLD_SAMPLE['counter_volume'], sot.volume) self.assertEqual(OLD_SAMPLE['project_id'], sot.project_id) self.assertEqual(OLD_SAMPLE['recorded_at'], sot.recorded_at) self.assertEqual(OLD_SAMPLE['resource_id'], sot.resource_id) self.assertEqual(OLD_SAMPLE['resource_metadata'], sot.metadata) self.assertEqual(OLD_SAMPLE['source'], sot.source) self.assertEqual(OLD_SAMPLE['timestamp'], sot.generated_at) self.assertEqual(OLD_SAMPLE['user_id'], sot.user_id) def test_list(self): sess = mock.Mock() resp = mock.Mock() resp.body = [SAMPLE, OLD_SAMPLE] sess.get = mock.Mock(return_value=resp) path_args = {'meter': 'name_of_meter'} found = sample.Sample.list(sess, path_args=path_args) self.assertEqual(2, len(found)) first = found[0] self.assertIsNone(first.id) self.assertIsNone(first.sample_id) self.assertEqual(SAMPLE['metadata'], first.metadata) self.assertEqual(SAMPLE['meter'], first.meter) self.assertEqual(SAMPLE['project_id'], first.project_id) self.assertEqual(SAMPLE['recorded_at'], first.recorded_at) self.assertEqual(SAMPLE['resource_id'], first.resource_id) self.assertEqual(SAMPLE['source'], first.source) self.assertEqual(SAMPLE['timestamp'], first.generated_at) self.assertEqual(SAMPLE['type'], first.type) self.assertEqual(SAMPLE['unit'], first.unit) self.assertEqual(SAMPLE['user_id'], first.user_id) self.assertEqual(SAMPLE['volume'], first.volume) def test_create(self): sess = mock.Mock() resp = mock.Mock() resp.body = [SAMPLE] sess.post = mock.Mock(return_value=resp) data = {'id': None, 'meter': 'temperature', 'project_id': 'project', 'resource_id': 'resource', 'type': 'gauge', 'unit': 'instance', 'volume': '98.6'} new_sample = sample.Sample.new(**data) new_sample.create(sess) url = '/meters/temperature' sess.post.assert_called_with(url, service=new_sample.service, json=[data]) self.assertIsNone(new_sample.id)

36.978417

75

0.637743

3,949

0.768288

0

1,400

0.272374

54324dc90f9df188cfe21f89b7c0b9336f381fe0

7,645

py

Python

data_convert/convert_text_to_tree.py

wlof-2/Text2Relation

a1321e3627fee4714d2c39c964d93d12d0802467

[ "MIT" ]

null

data_convert/convert_text_to_tree.py

wlof-2/Text2Relation

a1321e3627fee4714d2c39c964d93d12d0802467

[ "MIT" ]

null

data_convert/convert_text_to_tree.py

wlof-2/Text2Relation

a1321e3627fee4714d2c39c964d93d12d0802467

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding:utf-8 -*- import os import json from collections import Counter, defaultdict from data_convert.format.text2tree import Entity_Type, Text2Tree from data_convert.task_format.event_extraction import Event, DyIEPP, Conll04 from data_convert.utils import read_file, check_output, data_counter_to_table, get_schema, output_schema from nltk.corpus import stopwords Ace_Entity_Type = {"ORG": "<ORG>", "VEH": "<VEH>", "WEA": "<WEA>", "LOC": "<LOC>", "FAC": "<FAC>", "PER": "<PER>", "GPE": "<GPE>"} Sci_Entity_Type = {'Metric': '<Metric>', 'Task': '<Task>', 'OtherScientificTerm': '<OtherScientificTerm>', 'Generic': '<Generic>', 'Material': '<Material>', 'Method': '<Method>'} Conll04_Type = {'Org': '<Org>', 'Peop': '<Peop>', 'Other': '<Other>', 'Loc': '<Loc>'} english_stopwords = set(stopwords.words('english') + ["'s", "'re", "%"]) def convert_file_tuple(file_tuple, data_class=Event, target_class=Text2Tree, output_folder='data/text2tree/framenet', entity_Type = dict(), ignore_nonevent=False, zh=False, mark_tree=False, type_format='subtype'): counter = defaultdict(Counter) data_counter = defaultdict(Counter) relation_schema_set = set() span_output_folder = output_folder + '_span' if not os.path.exists(span_output_folder): os.makedirs(span_output_folder) # in_filename a example is "data/raw_data/dyiepp_ace2005/train.json" # out_filename a example is 'data/text2tree/ace2005_event/train' for in_filename, output_filename in file_tuple(output_folder): span_output_filename = output_filename.replace( output_folder, span_output_folder) relation_output = open(output_filename + '.json', 'w') span_relation_output = open(span_output_filename + '.json', 'w') for line in read_file(in_filename): document = data_class(json.loads(line.strip())) for sentence in document.generate_relations(): if ignore_nonevent and len(sentence['relations']) == 0: continue # souce is the sentence text tokens # target is the corresponding relations annotations source, target = target_class.annotate_predicate_arguments( tokens=sentence['tokens'], predicate_arguments=sentence['relations'], entities=sentence['entities'], Entity_Type = entity_Type, zh=zh ) # Test if we only consider there are relations in the sentence # if target == "<Temp_S> <Temp_E>": # continue # The event knowledge schema, used in constrained decoder # sentence['tokens'] is the sentence schema information, event['tokens'] # is the event trigger text span index for relation in sentence['relations']: relation_schema_set.add(relation['type']) sep = '' if zh else ' ' counter['type'].update([relation['type']]) data_counter[in_filename].update(['relation']) for argument in relation['arguments']: data_counter[in_filename].update(['argument']) data_counter[in_filename].update(['sentence']) relation_output.write(json.dumps( {'text': source, 'relation': target}, ensure_ascii=False) + '\n') # for tokens and entities in one sentence span_source, span_target = target_class.annotate_predicate_entities( tokens=sentence['tokens'], entities=sentence['entities'], Entity_Type = entity_Type, zh=zh, mark_tree=mark_tree ) # write the span format data, name entity format span_relation_output.write( json.dumps({'text': span_source, 'relation': span_target}, ensure_ascii=False) + '\n') relation_output.close() span_relation_output.close() check_output(output_filename) check_output(span_output_filename) print('\n') relation_type_list = list(set([schema for schema in relation_schema_set])) schema_output_file=os.path.join(output_folder, 'relation.schema') with open(schema_output_file, 'w') as output: output.write(json.dumps(relation_type_list) + '\n') # output_schema(event_schema_set, output_file=os.path.join( # span_output_folder, 'event.schema')) print('Pred:', len(counter['pred']), counter['pred'].most_common(10)) print('Type:', len(counter['type']), counter['type'].most_common(10)) print('Role:', len(counter['role']), counter['role'].most_common(10)) print(data_counter_to_table(data_counter)) print('\n\n\n') def convert_ace2005_event(output_folder='data/new_text2tree/ace2005_event', type_format='subtype', ignore_nonevent=False, mark_tree=False): from data_convert.task_format.event_extraction import ace2005_en_file_tuple convert_file_tuple(file_tuple=ace2005_en_file_tuple, output_folder=output_folder, ignore_nonevent=ignore_nonevent, mark_tree=mark_tree, type_format=type_format, entity_Type=Ace_Entity_Type, ) def convert_sci_event(output_folder='data/new_text2tree/sci_relastion_', type_format='subtype', ignore_nonevent=False, mark_tree=False): from data_convert.task_format.event_extraction import sci_file_tuple convert_file_tuple(file_tuple=sci_file_tuple, output_folder=output_folder, ignore_nonevent=ignore_nonevent, entity_Type= Sci_Entity_Type, mark_tree=mark_tree, type_format=type_format, data_class=DyIEPP, ) def convert_conll04_relation(output_folder='data/new_text2tree/conll04_relation_', type_format='subtype', ignore_nonevent=False, mark_tree=False): from data_convert.task_format.event_extraction import conll04_file_tuple convert_file_tuple(file_tuple=conll04_file_tuple, output_folder=output_folder, ignore_nonevent=ignore_nonevent, entity_Type=Conll04_Type, mark_tree=mark_tree, type_format=type_format, data_class=Conll04, ) if __name__ == "__main__": type_format_name = 'subtype' convert_ace2005_event("data/new_text2tree/one_ie_ace2005_%s" % type_format_name, type_format=type_format_name, ignore_nonevent=False, mark_tree=False ) # """ # convert_sci_event("data/new_text2tree/sci_relation_%s" % type_format_name, # type_format=type_format_name, # ignore_nonevent=False, # mark_tree=False) # """ # convert_conll04_relation("data/new_text2tree/conll04_relation_%s" % type_format_name, # type_format=type_format_name, # ignore_nonevent=False, # mark_tree=False)

45.778443

138

0.597515

0

1,970

0.257685

5432a871244c2f1064853af01dd1344e9304f2e3

1,246

py

Python

arachnado/utils/spiders.py

wigginzz/arachnado

8de92625262958e886263b4ccb189f4fc62d7400

[ "MIT" ]

2

2017-12-26T14:50:14.000Z

2018-06-12T07:04:08.000Z

arachnado/utils/spiders.py

wigginzz/arachnado

8de92625262958e886263b4ccb189f4fc62d7400

[ "MIT" ]

null

arachnado/utils/spiders.py

wigginzz/arachnado

8de92625262958e886263b4ccb189f4fc62d7400

[ "MIT" ]

null

from scrapy.utils.misc import walk_modules from scrapy.utils.spider import iter_spider_classes def get_spider_cls(url, spider_packages, default): """ Return spider class based on provided url. :param url: if it looks like `spider://spidername` it tries to load spider named `spidername`, otherwise it returns default spider class :param spider_packages: a list of package names that will be searched for spider classes :param default: the class that is returned when `url` doesn't start with `spider://` """ if url.startswith('spider://'): spider_name = url[len('spider://'):] return find_spider_cls(spider_name, spider_packages) return default def find_spider_cls(spider_name, spider_packages): """ Find spider class which name is equal to `spider_name` argument :param spider_name: spider name to look for :param spider_packages: a list of package names that will be searched for spider classes """ for package_name in spider_packages: for module in walk_modules(package_name): for spider_cls in iter_spider_classes(module): if spider_cls.name == spider_name: return spider_cls

35.6

78

0.690209

0

657

0.527287

543307112090d54acedcff9238e2cea7185b6c19

1,165

py

Python

Social_Encoders.py

Haroon96/GraphRec-WWW19

fc28eee70fad927d761c15cab97de52f5955dcfd

[ "MIT" ]

null

Social_Encoders.py

Haroon96/GraphRec-WWW19

fc28eee70fad927d761c15cab97de52f5955dcfd

[ "MIT" ]

null

Social_Encoders.py

Haroon96/GraphRec-WWW19

fc28eee70fad927d761c15cab97de52f5955dcfd

[ "MIT" ]

null

import torch import torch.nn as nn from torch.nn import init import torch.nn.functional as F class Social_Encoder(nn.Module): def __init__(self, features, embed_dim, social_adj_lists, aggregator, base_model=None, cuda="cpu"): super(Social_Encoder, self).__init__() self.features = features self.social_adj_lists = social_adj_lists self.aggregator = aggregator if base_model != None: self.base_model = base_model self.embed_dim = embed_dim self.device = cuda self.linear1 = nn.Linear(2 * self.embed_dim, self.embed_dim) # def forward(self, nodes): to_neighs = [] for node in nodes: to_neighs.append(self.social_adj_lists.get(int(node), {})) neigh_feats = self.aggregator.forward(nodes, to_neighs) # user-user network self_feats = self.features(torch.LongTensor(nodes.cpu().numpy())).to(self.device) self_feats = self_feats.t() # self-connection could be considered. combined = torch.cat([self_feats, neigh_feats], dim=1) combined = F.relu(self.linear1(combined)) return combined

32.361111

103

0.654936

1,069

0.917597

0

63

0.054077

5433996009680b5160e896f44a3bff1c9d65a2bb

3,280

py

Python

deephub/utils/__main__.py

deeplab-ai/deephub

b1d271436fab69cdfad14f19fa2e29c5338f18d6

[ "Apache-2.0" ]

8

2019-10-17T12:46:13.000Z

2020-03-12T08:09:40.000Z

deephub/utils/__main__.py

deeplab-ai/deephub

b1d271436fab69cdfad14f19fa2e29c5338f18d6

[ "Apache-2.0" ]

12

2019-10-22T13:11:56.000Z

2022-02-10T00:23:30.000Z

deephub/utils/__main__.py

deeplab-ai/deephub

b1d271436fab69cdfad14f19fa2e29c5338f18d6

[ "Apache-2.0" ]

1

2019-10-17T13:21:27.000Z

import click import time from deephub.common.io import resolve_glob_pattern from deephub.models.feeders.tfrecords.meta import generate_fileinfo, get_fileinfo, TFRecordValidationError, \ TFRecordInfoMissingError @click.group() def cli(): """ General purpose CLI utils. """ pass @cli.command() @click.argument('pattern', type=str) @click.option('--force', is_flag=True, default=False, help='It will forcefully regenerate meta data even for tfrecords that' 'have not changed.') @click.option('--compression_type', type=str, default='', help="""Compression type of the tfrecord file. Options: '' for no compression 'GZIP' for gzip compression""") def generate_metadata(pattern, force, compression_type): """ Generate metadata for tfrecord files. With this util you can generate metadata from tfrecords based on a matching glob pattern. Example: Generate metadata for training dataset deep utils generate-metadata 'dataset/train-*' """ files = resolve_glob_pattern(pattern) click.echo(f"{len(files)} files matched with the pattern.") with click.progressbar(files) as files: for fpath in files: try: generate_fileinfo(fpath, compression_type=compression_type) except Exception as e: click.echo(f'Skipping file {fpath} because of: {e!s}') click.echo('Finished generating metadata') @cli.command() @click.argument('pattern', type=str) def total_examples(pattern) -> int: """ Get total examples for all the files matched with the given input file pattern. """ files = resolve_glob_pattern(pattern) click.echo(f"{len(files)} files matched with the pattern.") total_rows = 0 for file in files: try: total_rows += get_fileinfo(file).total_records except Exception: pass click.echo(f"Total number of examples: {total_rows}") @cli.command() @click.argument('pattern', type=str) @click.option('--shallow-check/--deep-check', default=True, help='Flag in order to control shallow or deep md5 hash check. With shallow-check only the size of' 'each file will be validated, while with deep-check both size and md5 hash of each file will be' 'validated.') def validate(pattern: str, shallow_check: bool): """ Validate each one of the files matched using the input file pattern. """ start = time.time() files = resolve_glob_pattern(pattern) click.echo(f"{len(files)} files matched with the pattern.") with click.progressbar(files) as files: for file in files: try: get_fileinfo(file, shallow_check) # inside here happens the validation step too except TFRecordValidationError: raise except TFRecordInfoMissingError: raise except Exception as e: # Probably not a valid tfrecords file click.echo(f'Probably not a valid tf_record file {e}') end = time.time() click.echo(f"Total execution time: {end - start}")

33.814433

115

0.633232

0

3,052

0.930488

0

1,502

0.457927

543471083e8ed6e6fd0d08082e7de83061292ab1

10,072

py

Python

utils_mit_im.py

putama/visualcomposition

ada3d8e71b79a5f3e239718f3cdac58eca5e1327

[ "MIT" ]

null

utils_mit_im.py

putama/visualcomposition

ada3d8e71b79a5f3e239718f3cdac58eca5e1327

[ "MIT" ]

null

utils_mit_im.py

putama/visualcomposition

ada3d8e71b79a5f3e239718f3cdac58eca5e1327

[ "MIT" ]

null

import numpy as np import cPickle import os from scipy.io import loadmat import time import h5py import json import copy import bz2 def unique_rows(a): b = np.ascontiguousarray(a).view(np.dtype((np.void, a.dtype.itemsize * a.shape[1]))) _, idx = np.unique(b, return_index=True) return a[idx], idx; def setdiff2d(a1, a2): assert a1.dtype == a2.dtype; #only works with numpy >= 1.7 versplit = [int(x) for x in np.__version__.split('.')]; assert versplit[0]>=1 and versplit[1]>=7; a1_rows = a1.view([('', a1.dtype)] * a1.shape[1]) a2_rows = a2.view([('', a2.dtype)] * a2.shape[1]) return np.setdiff1d(a1_rows, a2_rows).view(a1.dtype).reshape(-1, a1.shape[1]) def argtopk(a, k): ind = np.argpartition(a,-k)[-k:] srtind = ind[np.argsort(a[ind])[::-1]]; return srtind; def get_dir_list(dirPath, extension = None): onlydirs = [ os.path.join(dirPath,f) for f in os.listdir(dirPath) if os.path.isdir(os.path.join(dirPath,f)) ]; if extension!= None: onlydirs = [f for f in onlydirs if os.path.splitext(f)[1]==extension]; onlydirs.sort(); return onlydirs; #extension with "." e.g. .jpg def get_file_list(dirPath, extension = None): onlyfiles = [ os.path.join(dirPath,f) for f in os.listdir(dirPath) if os.path.isfile(os.path.join(dirPath,f)) ]; if extension!= None: onlyfiles = [f for f in onlyfiles if os.path.splitext(f)[1]==extension]; onlyfiles.sort(); return onlyfiles; def get_file_list_prefix(dirPath, prefix, extension=None): onlyfiles = [ os.path.join(dirPath,f) for f in os.listdir(dirPath) if os.path.isfile(os.path.join(dirPath,f)) and f.startswith(prefix) ]; if extension!= None: onlyfiles = [f for f in onlyfiles if os.path.splitext(f)[1]==extension]; onlyfiles.sort(); return onlyfiles; def list_to_indexed_dict(lvar): dvar = {}; for ind, item in enumerate(lvar): dvar[item]=ind; return dvar; def tic_toc_print(interval, string): global tic_toc_print_time_old if 'tic_toc_print_time_old' not in globals(): tic_toc_print_time_old = time.time() print string else: new_time = time.time() if new_time - tic_toc_print_time_old > interval: tic_toc_print_time_old = new_time; print string def mkdir(output_dir): return mkdir_if_missing(output_dir); def mkdir_if_missing(output_dir): """ def mkdir_if_missing(output_dir) """ if not os.path.exists(output_dir): try: os.makedirs(output_dir) return True; except: #generally happens when many processes try to make this dir return False; def recurse_get_mat_struct(v, curr_field=None): accum_dict = {}; if type(v).__name__ != 'mat_struct': if type(v).__name__ == 'ndarray': #sometimes we have nested mat_structs ... numel = v.size; found_nested_structs = False; for x in range(numel): if type(v.item(x)).__name__ == 'mat_struct': if found_nested_structs == False: accum_dict[curr_field]=[]; found_nested_structs = True; if found_nested_structs: newdict = recurse_get_mat_struct(v.item(x), curr_field); accum_dict[curr_field].append(newdict); if found_nested_structs == False: accum_dict[curr_field] = v; else: accum_dict[curr_field] = v; else: for field in v._fieldnames: local_dict = recurse_get_mat_struct( getattr(v, field), field ); if field not in local_dict: accum_dict[field] = copy.deepcopy(local_dict); else: accum_dict[field] = copy.deepcopy(local_dict[field]); if curr_field not in accum_dict: ret_dict = {}; ret_dict[curr_field] = copy.deepcopy(accum_dict); accum_dict = ret_dict; return accum_dict; def mat_to_dict(mat_name): matfile = loadmat(mat_name, squeeze_me=True, struct_as_record=False); var_keys = matfile.keys(); allVarDict = {}; for v in var_keys: if v.startswith('__') == True: continue; dictData = {}; for field in matfile[v]._fieldnames: localDict = recurse_get_mat_struct( getattr(matfile[v], field), field ); if field not in localDict: dictData[field] = copy.deepcopy(localDict); else: dictData[field] = copy.deepcopy(localDict[field]); allVarDict[v] = dictData; return allVarDict; def save_variables_h5(h5_file_name, var, info, overwrite = False): if info is None: return save_variables_h5_dict(h5_file_name, var, overwrite) if os.path.exists(h5_file_name) and overwrite == False: raise Exception('{:s} exists and over write is false.'.format(h5_file_name)) # Construct the dictionary assert(type(var) == list); assert(type(info) == list); with h5py.File(h5_file_name, 'w') as f: for i in range(len(info)): d = f.create_dataset(info[i], data=var[i], chunks=True, compression="gzip", compression_opts=9); def rec_get_keys(fh, src, keyList): if src!='' and type(fh[src]).__name__ == 'Dataset': keyList.append(src); return keyList; if src!='': moreSrcs = fh[src].keys(); else: moreSrcs = fh.keys(); for kk in moreSrcs: if src=='': keyList = rec_get_keys(fh, kk, keyList); else: keyList = rec_get_keys(fh, src+'/'+kk, keyList); return keyList; def get_h5_keys(h5_file_name): if os.path.exists(h5_file_name): with h5py.File(h5_file_name,'r') as f: keyList = rec_get_keys(f, '', []); return keyList; else: raise Exception('{:s} does not exists.'.format(h5_file_name)) def save_variables_h5_dict(h5_file_name, dictVar, overwrite = False): if os.path.exists(h5_file_name) and overwrite == False: raise Exception('{:s} exists and over write is false.'.format(h5_file_name)) # Construct the dictionary assert(type(dictVar) == dict); with h5py.File(h5_file_name, 'w') as f: for key in dictVar: d = f.create_dataset(key, data=dictVar[key], chunks=True, compression="gzip", compression_opts=9); def load_variablesh5(h5_file_name): if os.path.exists(h5_file_name): with h5py.File(h5_file_name,'r') as f: d = {}; h5keys = get_h5_keys(h5_file_name); for key in h5keys: d[key] = f[key].value; return d else: raise Exception('{:s} does not exists.'.format(h5_file_name)) def save_variables(pickle_file_name, var, info, overwrite = False): """ def save_variables(pickle_file_name, var, info, overwrite = False) """ fext = os.path.splitext(pickle_file_name)[1] if fext =='.h5': return save_variables_h5(pickle_file_name, var, info, overwrite); elif fext == '.pkl' or fext == '.pklz': if os.path.exists(pickle_file_name) and overwrite == False: raise Exception('{:s} exists and over write is false.'.format(pickle_file_name)) if info is not None: # Construct the dictionary assert(type(var) == list); assert(type(info) == list); d = {} for i in xrange(len(var)): d[info[i]] = var[i] else: #we have the dictionary in var d = var; if fext == '.pkl': with open(pickle_file_name, 'wb') as f: cPickle.dump(d, f, cPickle.HIGHEST_PROTOCOL) else: with bz2.BZ2File(pickle_file_name, 'w') as f: cPickle.dump(d, f, cPickle.HIGHEST_PROTOCOL) else: raise Exception('{:s}: extension unknown'.format(fext)) def load_variables(pickle_file_name): """ d = load_variables(pickle_file_name) Output: d is a dictionary of variables stored in the pickle file. """ fext = os.path.splitext(pickle_file_name)[1] if fext =='.h5': return load_variablesh5(pickle_file_name); elif fext == '.pkl' or fext == '.pklz': if os.path.exists(pickle_file_name): if fext == '.pkl': with open(pickle_file_name, 'rb') as f: d = cPickle.load(f) else: with bz2.BZ2File(pickle_file_name, 'r') as f: d = cPickle.load(f) return d else: raise Exception('{:s} does not exists.'.format(pickle_file_name)) elif fext == '.json': with open(pickle_file_name, 'r') as fh: data = json.load(fh) return data else: raise Exception('{:s}: extension unknown'.format(fext)) #wrappers for load_variables and save_variables def load(pickle_file_name): return load_variables(pickle_file_name); def save(pickle_file_name, var, info, overwrite = False): return save_variables(pickle_file_name, var, info, overwrite); def calc_pr_ovr_noref(counts, out): """ [P, R, score, ap] = calc_pr_ovr(counts, out, K) Input : counts : number of occurrences of this word in the ith image out : score for this image Output : P, R : precision and recall score : score which corresponds to the particular precision and recall ap : average precision """ #binarize counts out = out.astype(np.float64) counts = np.array(counts > 0, dtype=np.float32); tog = np.hstack((counts[:,np.newaxis].astype(np.float64), out[:, np.newaxis].astype(np.float64))) ind = np.argsort(out) ind = ind[::-1] score = np.array([tog[i,1] for i in ind]) sortcounts = np.array([tog[i,0] for i in ind]) tp = sortcounts; fp = sortcounts.copy(); for i in xrange(sortcounts.shape[0]): if sortcounts[i] >= 1: fp[i] = 0.; elif sortcounts[i] < 1: fp[i] = 1.; tp = np.cumsum(tp) fp = np.cumsum(fp) # P = np.cumsum(tp)/(np.cumsum(tp) + np.cumsum(fp)); P = tp / np.maximum(tp + fp, np.finfo(np.float64).eps) numinst = np.sum(counts); R = tp/numinst ap = voc_ap(R,P) return P, R, score, ap def voc_ap(rec, prec): # correct AP calculation # first append sentinel values at the end mrec = np.concatenate(([0.], rec, [1.])) mpre = np.concatenate(([0.], prec, [0.])) # compute the precision envelope for i in range(mpre.size - 1, 0, -1): mpre[i - 1] = np.maximum(mpre[i - 1], mpre[i]) # to calculate area under PR curve, look for points # where X axis (recall) changes value i = np.where(mrec[1:] != mrec[:-1])[0] # and sum (\Delta recall) * prec ap = np.sum((mrec[i + 1] - mrec[i]) * mpre[i + 1]) return ap

32.807818

141

0.652502

0

1,588

0.157665

5435607e763096b9e0e81fbf68d44b9c31b6852e

1,085

py

Python

python_teste/python_aulas/aula_94.py

BrunoDantasMoreira/projectsPython

bd73ab0b3c067456407f227ed2ece42e7f21ddfc

[ "MIT" ]

1

2020-07-27T14:18:08.000Z

python_teste/python_aulas/aula_94.py

BrunoDantasMoreira/projectsPython

bd73ab0b3c067456407f227ed2ece42e7f21ddfc

[ "MIT" ]

null

python_teste/python_aulas/aula_94.py

BrunoDantasMoreira/projectsPython

bd73ab0b3c067456407f227ed2ece42e7f21ddfc

[ "MIT" ]

null

dict = {} lista = [] soma = 0 while True: dict['nome'] = str(input('Nome: ')).capitalize() dict['sexo'] = str(input('Sexo: ')).strip().upper()[0] while dict['sexo'] not in 'MF': print('ERRO! Por favor, digite apenas M ou F') dict['sexo'] = str(input('Sexo: ')).strip().upper()[0] dict['idade'] = int(input('Idade: ')) soma += dict['idade'] lista.append(dict.copy()) opção = str(input('Quer continuar? ')).strip().upper()[0] while opção not in 'SN': print('ERRO! Responda apenas S ou N.') opção = str(input('Quer continuar? ')).strip().upper()[0] if opção == 'N': break print('-='*30) print(f'A) Ao todo temos {len(lista)} pessoas cadastradas.') media = soma / len(lista) print(f'B) A media de idade é de {media:5.2f} anos') print('C) As mulheres cadastradas foram ', end='') for p in lista: if p['sexo'] == 'F': print(f'{p["nome"]}', end=' ') print() print('D) As pessoas com idade maior que a média são ', end='') for c in lista: if c['idade'] > media: print(f'{c["nome"]}', end=' ')

33.90625

65

0.562212

0

430

0.392336

543805ee596eba6c41f93710a63dc5eaf28196da

7,894

py

Python

nlp/layers/linears.py

zhihao-chen/NLP-experiments

c7512276050f5b8489adb4c745fa970ea8119646

[ "MIT" ]

4

2021-11-10T03:49:28.000Z

2022-03-24T02:18:44.000Z

nlp/layers/linears.py

zhihao-chen/NLP-experiments

c7512276050f5b8489adb4c745fa970ea8119646

[ "MIT" ]

null

nlp/layers/linears.py

zhihao-chen/NLP-experiments

c7512276050f5b8489adb4c745fa970ea8119646

[ "MIT" ]

1

2021-11-14T18:01:18.000Z

# -*- coding: utf8 -*- """ ====================================== Project Name: NLP File Name: linears Author: czh Create Date: 2021/11/15 -------------------------------------- Change Activity: ====================================== """ import math import torch import torch.nn as nn import torch.nn.functional as func from torch.nn.parameter import Parameter class Linears(nn.Module): def __init__(self, input_dim: int, output_dim: int = 1, bias: bool = True): super().__init__() self.fn1 = nn.Linear(input_dim, input_dim) self.fn2 = nn.Linear(input_dim, input_dim) self.fn3 = nn.Linear(input_dim, output_dim, bias=bias) nn.init.orthogonal_(self.fn1.weight, gain=1) nn.init.orthogonal_(self.fn2.weight, gain=1) nn.init.orthogonal_(self.fn3.weight, gain=1) def forward(self, hidden_states: torch.Tensor, encoder_hidden_states: torch.Tensor): logits = self.fn3(torch.tanh( self.fn1(hidden_states).unsqueeze(2) + self.fn2(encoder_hidden_states).unsqueeze(1) )).squeeze() return logits class EntityLinears(nn.Module): def __init__(self, input_dim: int, output_dim: int = 1, bias: bool = True): super().__init__() self.head = Linears(input_dim=input_dim, output_dim=output_dim, bias=bias) self.tail = Linears(input_dim=input_dim, output_dim=output_dim, bias=bias) def forward(self, hidden_states: torch.Tensor, encoder_hidden_states: torch.Tensor): # [bsz, num_triples, seq_len, output_dim] return self.head(hidden_states, encoder_hidden_states), self.tail(hidden_states, encoder_hidden_states) class FeedForwardNetwork(nn.Module): def __init__(self, input_size, hidden_size, output_size, dropout_rate=0): super(FeedForwardNetwork, self).__init__() self.dropout_rate = dropout_rate self.linear1 = nn.Linear(input_size, hidden_size) self.linear2 = nn.Linear(hidden_size, output_size) def forward(self, x): x_proj = func.dropout(func.relu(self.linear1(x)), p=self.dropout_rate, training=self.training) x_proj = self.linear2(x_proj) return x_proj class PoolerStartLogits(nn.Module): """ bert_ner_span """ def __init__(self, hidden_size, num_classes): super(PoolerStartLogits, self).__init__() self.dense = nn.Linear(hidden_size, num_classes) def forward(self, hidden_states): x = self.dense(hidden_states) return x class PoolerEndLogits(nn.Module): """ bert_ner_span """ def __init__(self, hidden_size, num_classes): super(PoolerEndLogits, self).__init__() self.dense_0 = nn.Linear(hidden_size, hidden_size) self.activation = nn.Tanh() self.LayerNorm = nn.LayerNorm(hidden_size) self.dense_1 = nn.Linear(hidden_size, num_classes) def forward(self, hidden_states, start_positions=None): x = self.dense_0(torch.cat([hidden_states, start_positions], dim=-1)) x = self.activation(x) x = self.LayerNorm(x) x = self.dense_1(x) return x class MultiNonLinearClassifier(nn.Module): def __init__(self, hidden_size, num_label, dropout_rate, act_func="gelu", intermediate_hidden_size=None): super(MultiNonLinearClassifier, self).__init__() self.num_label = num_label self.intermediate_hidden_size = hidden_size if intermediate_hidden_size is None else intermediate_hidden_size self.classifier1 = nn.Linear(hidden_size, self.intermediate_hidden_size) self.classifier2 = nn.Linear(self.intermediate_hidden_size, self.num_label) self.dropout = nn.Dropout(dropout_rate) self.act_func = act_func def forward(self, input_features): features_output1 = self.classifier1(input_features) if self.act_func == "gelu": features_output1 = func.gelu(features_output1) elif self.act_func == "relu": features_output1 = func.relu(features_output1) elif self.act_func == "tanh": features_output1 = func.tanh(features_output1) else: raise ValueError features_output1 = self.dropout(features_output1) features_output2 = self.classifier2(features_output1) return features_output2 class SingleLinearClassifier(nn.Module): def __init__(self, hidden_size, num_label): super(SingleLinearClassifier, self).__init__() self.num_label = num_label self.classifier = nn.Linear(hidden_size, num_label) def forward(self, input_features): features_output = self.classifier(input_features) return features_output class BERTTaggerClassifier(nn.Module): def __init__(self, hidden_size, num_label, dropout_rate, act_func="gelu", intermediate_hidden_size=None): super(BERTTaggerClassifier, self).__init__() self.num_label = num_label self.intermediate_hidden_size = hidden_size if intermediate_hidden_size is None else intermediate_hidden_size self.classifier1 = nn.Linear(hidden_size, self.intermediate_hidden_size) self.classifier2 = nn.Linear(self.intermediate_hidden_size, self.num_label) self.dropout = nn.Dropout(dropout_rate) self.act_func = act_func def forward(self, input_features): features_output1 = self.classifier1(input_features) if self.act_func == "gelu": features_output1 = func.gelu(features_output1) elif self.act_func == "relu": features_output1 = func.relu(features_output1) elif self.act_func == "tanh": features_output1 = func.tanh(features_output1) else: raise ValueError features_output1 = self.dropout(features_output1) features_output2 = self.classifier2(features_output1) return features_output2 class ClassifierLayer(nn.Module): # https://github.com/Akeepers/LEAR/blob/master/utils/model_utils.py def __init__(self, class_num, out_features, bias=True): super(ClassifierLayer, self).__init__() self.class_num = class_num self.out_features = out_features self.weight = Parameter(torch.Tensor(class_num, out_features)) if bias: self.bias = Parameter(torch.Tensor(class_num)) else: self.register_parameter('bias', None) self.reset_parameters() def reset_parameters(self) -> None: nn.init.kaiming_uniform_(self.weight, a=math.sqrt(5)) if self.bias is not None: fan_in, _ = nn.init._calculate_fan_in_and_fan_out(self.weight) bound = 1 / math.sqrt(fan_in) nn.init.uniform_(self.bias, -bound, bound) def forward(self, inputs): x = torch.mul(inputs, self.weight) # (class_num, 1) x = torch.sum(x, -1) # [-1, class_num] if self.bias is not None: x = x + self.bias return x def extra_repr(self): return 'class_num={}, out_features={}, bias={}'.format( self.class_num, self.out_features, self.bias is not None) class MultiNonLinearClassifierForMultiLabel(nn.Module): # https://github.com/Akeepers/LEAR/blob/master/utils/model_utils.py def __init__(self, hidden_size, num_label, dropout_rate): super(MultiNonLinearClassifierForMultiLabel, self).__init__() self.num_label = num_label self.classifier1 = nn.Linear(hidden_size, hidden_size) self.classifier2 = ClassifierLayer(num_label, hidden_size) self.dropout = nn.Dropout(dropout_rate) def forward(self, input_features): features_output1 = self.classifier1(input_features) features_output1 = func.gelu(features_output1) features_output1 = self.dropout(features_output1) features_output2 = self.classifier2(features_output1) return features_output2

38.8867

117

0.673676

7,481

0.947682

0

617

0.078161

5438824c4ced393aa643d5e74bfabb01555d5d5c

2,037

py

Python

components/siren.py

TalaoDAO/ecole42

2236f24527966195c953f222f9715ee967348b0f

[ "Apache-2.0" ]

1

2021-09-22T16:30:57.000Z

components/siren.py

TalaoDAO/credential-repository

d36c694d9e90ead8a35bd8cc5be47c6d951474ba

[ "Apache-2.0" ]

null

components/siren.py

TalaoDAO/credential-repository

d36c694d9e90ead8a35bd8cc5be47c6d951474ba

[ "Apache-2.0" ]

null

import requests def company(SIREN): r = requests.get('https://entreprise.data.gouv.fr/api/sirene/v2/siren/'+SIREN+'') json_object = r.json() settings = dict() if json_object['sirene']['status'] == 404: return None if json_object['sirene']['data']['siege_social']['nom_raison_sociale'] != None : settings['name'] = json_object['sirene']['data']['siege_social']['nom_raison_sociale'] else : settings['name'] = '' try : settings['address'] = json_object['sirene']['data']['siege_social']['numero_voie'] + ' ' + json_object['sirene']['data']['siege_social']['type_voie'] + ' ' + json_object['sirene']['data']['siege_social']['libelle_voie'] + ' ' + json_object['sirene']['data']['siege_social']['code_postal'] + ' ' + json_object['sirene']['data']['siege_social']['libelle_commune'] except : settings['address'] = '' if json_object['sirene']['data']['total_results'] != None : settings['group'] = json_object['sirene']['data']['total_results'] else : settings['group'] = '' Dictionnaire_effectifs = {'NN': "No staff members", '00': '0', '01': "1-2", '02': "3-5", '03': "6-9", '11': "10-19", '12': "20-49", '21': "50-99", '22': "100-199", '31': "200-249", '32': "250-499", '41': "500-999", '42': "1000-1999", '51': "2000-4999", '52': "5000-9999", '53': "+10 000"} if json_object['sirene']['data']['siege_social']['tranche_effectif_salarie'] != None : settings['staff'] = Dictionnaire_effectifs[json_object['sirene']['data']['siege_social']['tranche_effectif_salarie']] else : settings['staff'] = '' if json_object['sirene']['data']['siege_social']['libelle_activite_principale_entreprise'] != None : settings['activity'] = json_object['sirene']['data']['siege_social']['libelle_activite_principale_entreprise'] else : settings['activity'] = '' return settings

55.054054

370

0.571919

0

977

0.479627

5438db8d908a649df431fff16b0d49559bcdf6d6

2,036

py

Python

Week 2/medt_opdracht_9.py

zowie93/ISCRIPT

fa3e5122be8ef47b23c23554ec9e1c04b37da562

[ "MIT" ]

null

Week 2/medt_opdracht_9.py

zowie93/ISCRIPT

fa3e5122be8ef47b23c23554ec9e1c04b37da562

[ "MIT" ]

null

Week 2/medt_opdracht_9.py

zowie93/ISCRIPT

fa3e5122be8ef47b23c23554ec9e1c04b37da562

[ "MIT" ]

null

""" Opdracht 9 - Loonbrief https://dodona.ugent.be/nl/exercises/990750894/ """ # functie voor start amount def get_start_amount(): # return start amount return int(input("Start bedrag: ")) # functie voor salaris def get_salary(): # array van salaris maken salary = [] # count op nul zetten count = 0 # wanneer de loop niet wordt afgebroken while True: # counter bijhouden voor werknemer id count += 1 # input voor het salaris betreffende werknemer input_salary = input("Werknemer " + str(count) + ": ") # lengte controleren en controleren op het woordje stop if len(salary) > 3 and input_salary.lower() == "stop": break # salaris toevoegen aan de array salary.append(int(input_salary)) # returnen van salaris return salary # functie voor gemiddeld salaris def get_average_salary(salary): # totaal aantal salaris total = sum(salary) # aantal werknemmers contributors = len(salary) # gemiddeld salaris per werknemer average = total / contributors # returnen van gemiddelde return average def print_salary(start_amount, salary, average): # count op nul zetten count = 0 # begin salaris of opgegeven bedrag total = start_amount # for loop die door het salaris heen gaat for amount in salary: # telkens 1tje optellen count += 1 # loon erbij optellen total = total + amount # uitprinten van totaal bedrag werknemer print("Werknemer #" + str(count) + " fluistert €" + str(total)) # uitprinten gemiddelde loon print("Gemiddeld loon: €" + str("{0:.2f}".format(average))) def main(): # begin bedrag verkrijgen start_amount = get_start_amount() # salaris verkrijgen salary = get_salary() # gemiddelde verkrijgen average = get_average_salary(salary) # printen van alle benodigde dingen print_salary(start_amount, salary, average) if __name__ == '__main__': main()

24.238095

71

0.651768

0

978

0.479412

543993f4662d66952cafe8284d07a22ac01ccee7

1,845

py

Python

4.1.1-simple-object-tracking-video.py

CleverYh/opencv_py

20b28e8ef20fa3015f4f7c20ed69fed954c16805

[ "MIT" ]

2

2020-04-05T13:44:13.000Z

2020-07-06T08:53:58.000Z

4.1.1-simple-object-tracking-video.py

CleverYh/opencv_py

20b28e8ef20fa3015f4f7c20ed69fed954c16805

[ "MIT" ]

null

4.1.1-simple-object-tracking-video.py

CleverYh/opencv_py

20b28e8ef20fa3015f4f7c20ed69fed954c16805

[ "MIT" ]

null

# coding: utf-8 from cv2 import cv2 import numpy as np cap = cv2.VideoCapture(0) while(1): # Take each frame _, frame = cap.read() # Convert BGR to HSV hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # define range of blue color in HSV lower_blue = np.array([110,50,50]) upper_blue = np.array([130,255,255]) # Threshold the HSV image to get only blue colors mask = cv2.inRange(hsv, lower_blue, upper_blue) # Bitwise-AND mask and original image res = cv2.bitwise_and(frame,frame, mask= mask) cv2.imshow('frame',frame) cv2.imshow('mask',mask) cv2.imshow('res',res) k = cv2.waitKey(5) & 0xFF if k == 27: break cv2.destroyAllWindows() # OBJECT TRACKING # Take each frame of the video # Convert from BGR to HSV color-space # We threshold the HSV image for a range of blue color # Now extract the blue object alone, we can do whatever on that image we want. # HOW TO FINDHSV VALUES TO TRACK? # It is very simple and you can use the same function, cv2.cvtColor(). Instead of passing an image, you just pass the BGR values you want. For example, to find the HSV value of Green, try following commands in Python terminal: # >>> green = np.uint8([[[0,255,0 ]]]) # >>> hsv_green = cv2.cvtColor(green,cv2.COLOR_BGR2HSV) # >>> print hsv_green # [[[ 60 255 255]]] # Now you take [H-10, 100,100] and [H+10, 255, 255] as lower bound and upper bound respectively. Apart from this method, you can use any image editing tools like GIMP or any online converters to find these values, but don’t forget to adjust the HSV ranges. # Now you take [H-10, 100,100] and [H+10, 255, 255] as lower bound and upper bound respectively. Apart from this method, you can use any image editing tools like GIMP or any online converters to find these values, but don’t forget to adjust the HSV ranges.

37.653061

256

0.701897

0

1,315

0.711195

5439f19ce894429f825edd092b433b960bae49d4

9,411

py

Python

src/peering/azext_peering/custom.py

michimune/azure-cli-extensions

697e2c674e5c0825d44c72d714542fe01331e107

[ "MIT" ]

1

2022-03-22T15:02:32.000Z

src/peering/azext_peering/custom.py

michimune/azure-cli-extensions

697e2c674e5c0825d44c72d714542fe01331e107

[ "MIT" ]

1

2021-02-10T22:04:59.000Z

src/peering/azext_peering/custom.py

michimune/azure-cli-extensions

697e2c674e5c0825d44c72d714542fe01331e107

[ "MIT" ]

1

2021-06-03T19:31:10.000Z

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- # pylint: disable=line-too-long # pylint: disable=too-many-statements # pylint: disable=too-many-lines # pylint: disable=too-many-locals # pylint: disable=unused-argument import json def list_peering_legacy(cmd, client, peering_location=None, kind=None): return client.list(peering_location=peering_location, kind=kind) def create_peering_asn(cmd, client, name, peer_asn=None, emails=None, phone=None, peer_name=None, validation_state=None): body = {} body['peer_asn'] = peer_asn # number body.setdefault('peer_contact_info', {})['emails'] = None if emails is None else emails.split(',') body.setdefault('peer_contact_info', {})['phone'] = None if phone is None else phone.split(',') body['peer_name'] = peer_name # str body['validation_state'] = validation_state # str return client.create_or_update(peer_asn_name=name, peer_asn=body) def update_peering_asn(cmd, client, name, peer_asn=None, emails=None, phone=None, peer_name=None, validation_state=None): body = client.get(peer_asn_name=name).as_dict() body.peer_asn = peer_asn # number body.peer_contact_info.emails = None if emails is None else emails.split(',') body.peer_contact_info.phone = None if phone is None else phone.split(',') body.peer_name = peer_name # str body.validation_state = validation_state # str return client.create_or_update(peer_asn_name=name, peer_asn=body) def delete_peering_asn(cmd, client, name): return client.delete(peer_asn_name=name) def list_peering_asn(cmd, client): return client.list_by_subscription() def list_peering_location(cmd, client, kind=None, direct_peering_type=None): return client.list(kind=kind, direct_peering_type=direct_peering_type) def create_peering(cmd, client, resource_group, name, kind, location, sku_name=None, sku_tier=None, sku_family=None, sku_size=None, direct_connections=None, direct_peer_asn=None, direct_direct_peering_type=None, exchange_connections=None, exchange_peer_asn=None, peering_location=None, tags=None): body = {} body.setdefault('sku', {})['name'] = sku_name # str body.setdefault('sku', {})['tier'] = sku_tier # str body.setdefault('sku', {})['family'] = sku_family # str body.setdefault('sku', {})['size'] = sku_size # str body['kind'] = kind # str body.setdefault('direct', {})['connections'] = json.loads(direct_connections) if isinstance(direct_connections, str) else direct_connections body.setdefault('direct', {}).setdefault('peer_asn', {})['id'] = direct_peer_asn body.setdefault('direct', {})['direct_peering_type'] = direct_direct_peering_type # str # body.setdefault('exchange', {})['connections'] = json.loads(exchange_connections) if isinstance(exchange_connections, str) else exchange_connections # body.setdefault('exchange', {}).setdefault('peer_asn', {})['id'] = exchange_peer_asn body['peering_location'] = peering_location # str body['location'] = location # str body['tags'] = tags # dictionary return client.create_or_update(resource_group_name=resource_group, peering_name=name, peering=body) def update_peering(cmd, client, resource_group, name, sku_name=None, sku_tier=None, sku_family=None, sku_size=None, kind=None, direct_connections=None, direct_peer_asn=None, direct_direct_peering_type=None, exchange_connections=None, exchange_peer_asn=None, peering_location=None, location=None, tags=None): body = client.get(resource_group_name=resource_group, peering_name=name).as_dict() body.sku.name = sku_name # str body.sku.tier = sku_tier # str body.sku.family = sku_family # str body.sku.size = sku_size # str body.kind = kind # str body.direct.connections = json.loads(direct_connections) if isinstance(direct_connections, str) else direct_connections body.direct.peer_asn = direct_peer_asn body.direct.direct_peering_type = direct_direct_peering_type # str body.exchange.connections = json.loads(exchange_connections) if isinstance(exchange_connections, str) else exchange_connections body.exchange.peer_asn = exchange_peer_asn body.peering_location = peering_location # str body.location = location # str body.tags = tags # dictionary return client.create_or_update(resource_group_name=resource_group, peering_name=name, peering=body) def delete_peering(cmd, client, resource_group, name): return client.delete(resource_group_name=resource_group, peering_name=name) def list_peering(cmd, client, resource_group): if resource_group is not None: return client.list_by_resource_group(resource_group_name=resource_group) return client.list_by_subscription() def list_peering_service_location(cmd, client): return client.list() def create_peering_service_prefix(cmd, client, resource_group, peering_service_name, name, prefix=None): return client.create_or_update(resource_group_name=resource_group, peering_service_name=peering_service_name, prefix_name=name, prefix=prefix) def update_peering_service_prefix(cmd, client, resource_group, peering_service_name, name, prefix=None): return client.create_or_update(resource_group_name=resource_group, peering_service_name=peering_service_name, prefix_name=name, prefix=prefix) def delete_peering_service_prefix(cmd, client, resource_group, peering_service_name, name): return client.delete(resource_group_name=resource_group, peering_service_name=peering_service_name, prefix_name=name) def list_peering_service_prefix(cmd, client, resource_group, peering_service_name): return client.list_by_peering_service(resource_group_name=resource_group, peering_service_name=peering_service_name) def list_peering_service_provider(cmd, client): return client.list() def create_peering_service(cmd, client, resource_group, name, location, peering_service_location=None, peering_service_provider=None, tags=None): body = {} body['peering_service_location'] = peering_service_location # str body['peering_service_provider'] = peering_service_provider # str body['location'] = location # str body['tags'] = tags # dictionary return client.create_or_update(resource_group_name=resource_group, peering_service_name=name, peering_service=body) def update_peering_service(cmd, client, resource_group, name, peering_service_location=None, peering_service_provider=None, location=None, tags=None): body = client.get(resource_group_name=resource_group, peering_service_name=name).as_dict() body.peering_service_location = peering_service_location # str body.peering_service_provider = peering_service_provider # str body.location = location # str body.tags = tags # dictionary return client.create_or_update(resource_group_name=resource_group, peering_service_name=name, peering_service=body) def delete_peering_service(cmd, client, resource_group, name): return client.delete(resource_group_name=resource_group, peering_service_name=name) def list_peering_service(cmd, client, resource_group): if resource_group is not None: return client.list_by_resource_group(resource_group_name=resource_group) return client.list_by_subscription()

42.013393

154

0.604824

0

1,267

0.13463

543ac48e108696b4125575c0e8b5fa9098b4ddb3

830

py

Python

votes/migrations/0004_team.py

aiventimptner/horizon

6e2436bfa81cad55fefd4c0bb67df3c36a9b6deb

[ "MIT" ]

null

votes/migrations/0004_team.py

aiventimptner/horizon

6e2436bfa81cad55fefd4c0bb67df3c36a9b6deb

[ "MIT" ]

1

2021-06-10T19:59:07.000Z

votes/migrations/0004_team.py

aiventimptner/horizon

6e2436bfa81cad55fefd4c0bb67df3c36a9b6deb

[ "MIT" ]

null

# Generated by Django 3.1.4 on 2020-12-30 00:27 from django.conf import settings from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ('votes', '0003_auto_20201229_1301'), ] operations = [ migrations.CreateModel( name='Team', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=150)), ('slug', models.SlugField()), ('created', models.DateTimeField(auto_now_add=True)), ('members', models.ManyToManyField(related_name='teams', to=settings.AUTH_USER_MODEL)), ], ), ]

31.923077

114

0.609639

704

0.848193

0

130

0.156627

543ac83c6ae50796c548f885ed09b3775131b174

576

py

Python

Python/Day 21/score.py

Aswinpkrishnan94/Fabulous-Python

bafba6d5b3889008299c012625b4a9e1b63b1d44

[ "MIT" ]

null

Python/Day 21/score.py

Aswinpkrishnan94/Fabulous-Python

bafba6d5b3889008299c012625b4a9e1b63b1d44

[ "MIT" ]

null

Python/Day 21/score.py

Aswinpkrishnan94/Fabulous-Python

bafba6d5b3889008299c012625b4a9e1b63b1d44

[ "MIT" ]

null

from turtle import Turtle FONT = ("Arial", 10, "normal") ALIGN = "center" class Score(Turtle): def __init__(self): super().__init__() self.score = 0 self.color("White") self.penup() self.goto(0, 270) self.update() self.hideturtle() def update(self): self.write(f"Score : {self.score}", align=ALIGN, font=FONT) def game_over(self): self.goto(0,0) self.write(f"GAME OVER", align=ALIGN, font=FONT) def inc(self): self.score += 1 self.clear() self.update()

23.04

67

0.553819

500

0.868056

0

65

0.112847

543c4f51f177e890cbcf4f4101beb26f2ee15486

81

py

Python

tests/integration/testdata/buildcmd/PyLayerMake/layer.py

renanmontebelo/aws-sam-cli

b5cfc46aa9726b5cd006df8ecc08d1b4eedeb9ea

[ "BSD-2-Clause", "Apache-2.0" ]

2,959

2018-05-08T21:48:56.000Z

2020-08-24T14:35:39.000Z

tests/integration/testdata/buildcmd/PyLayerMake/layer.py

renanmontebelo/aws-sam-cli

b5cfc46aa9726b5cd006df8ecc08d1b4eedeb9ea

[ "BSD-2-Clause", "Apache-2.0" ]

1,469

2018-05-08T22:44:28.000Z

2020-08-24T20:19:24.000Z

tests/integration/testdata/buildcmd/PyLayerMake/layer.py

renanmontebelo/aws-sam-cli

b5cfc46aa9726b5cd006df8ecc08d1b4eedeb9ea

[ "BSD-2-Clause", "Apache-2.0" ]

642

2018-05-08T22:09:19.000Z

2020-08-17T09:04:37.000Z

import numpy def layer_method(): return {"pi": "{0:.2f}".format(numpy.pi)}

13.5

45

0.617284

0

13

0.160494

543cd354a10448d8c328281db21e317c63dd0072

5,520

py

Python

bcbio/qc/coverage.py

markdunning/bcbio-nextgen

37b69efcc5b2b3713b8d5cd207cece4cb343380d

[ "MIT" ]

null

bcbio/qc/coverage.py

markdunning/bcbio-nextgen

37b69efcc5b2b3713b8d5cd207cece4cb343380d

[ "MIT" ]

null

bcbio/qc/coverage.py

markdunning/bcbio-nextgen

37b69efcc5b2b3713b8d5cd207cece4cb343380d

[ "MIT" ]

null

"""Coverage based QC calculations. """ import glob import os import subprocess from bcbio.bam import ref, readstats, utils from bcbio.distributed import transaction from bcbio.heterogeneity import chromhacks import bcbio.pipeline.datadict as dd from bcbio.provenance import do from bcbio.variation import coverage as cov from bcbio.variation import bedutils def run(bam_file, data, out_dir): """Run coverage QC analysis """ out = dict() out_dir = utils.safe_makedir(out_dir) if dd.get_coverage(data) and dd.get_coverage(data) not in ["None"]: merged_bed_file = bedutils.clean_file(dd.get_coverage_merged(data), data, prefix="cov-", simple=True) target_name = "coverage" elif dd.get_coverage_interval(data) != "genome": merged_bed_file = dd.get_variant_regions_merged(data) target_name = "variant_regions" else: merged_bed_file = None target_name = "genome" avg_depth = cov.get_average_coverage(target_name, merged_bed_file, data) if target_name == "coverage": out_files = cov.coverage_region_detailed_stats(target_name, merged_bed_file, data, out_dir) else: out_files = [] out['Avg_coverage'] = avg_depth samtools_stats_dir = os.path.join(out_dir, os.path.pardir, 'samtools') from bcbio.qc import samtools samtools_stats = samtools.run(bam_file, data, samtools_stats_dir)["metrics"] out["Total_reads"] = total_reads = int(samtools_stats["Total_reads"]) out["Mapped_reads"] = mapped = int(samtools_stats["Mapped_reads"]) out["Mapped_paired_reads"] = int(samtools_stats["Mapped_paired_reads"]) out['Duplicates'] = dups = int(samtools_stats["Duplicates"]) if total_reads: out["Mapped_reads_pct"] = 100.0 * mapped / total_reads if mapped: out['Duplicates_pct'] = 100.0 * dups / mapped if dd.get_coverage_interval(data) == "genome": mapped_unique = mapped - dups else: mapped_unique = readstats.number_of_mapped_reads(data, bam_file, keep_dups=False) out['Mapped_unique_reads'] = mapped_unique if merged_bed_file: ontarget = readstats.number_of_mapped_reads( data, bam_file, keep_dups=False, bed_file=merged_bed_file, target_name=target_name) out["Ontarget_unique_reads"] = ontarget if mapped_unique: out["Ontarget_pct"] = 100.0 * ontarget / mapped_unique out['Offtarget_pct'] = 100.0 * (mapped_unique - ontarget) / mapped_unique if dd.get_coverage_interval(data) != "genome": # Skip padded calculation for WGS even if the "coverage" file is specified # the padded statistic makes only sense for exomes and panels padded_bed_file = bedutils.get_padded_bed_file(out_dir, merged_bed_file, 200, data) ontarget_padded = readstats.number_of_mapped_reads( data, bam_file, keep_dups=False, bed_file=padded_bed_file, target_name=target_name + "_padded") out["Ontarget_padded_pct"] = 100.0 * ontarget_padded / mapped_unique if total_reads: out['Usable_pct'] = 100.0 * ontarget / total_reads indexcov_files = _goleft_indexcov(bam_file, data, out_dir) out_files += [x for x in indexcov_files if x and utils.file_exists(x)] out = {"metrics": out} if len(out_files) > 0: out["base"] = out_files[0] out["secondary"] = out_files[1:] return out def _goleft_indexcov(bam_file, data, out_dir): """Use goleft indexcov to estimate coverage distributions using BAM index. Only used for whole genome runs as captures typically don't have enough data to be useful for index-only summaries. """ if not dd.get_coverage_interval(data) == "genome": return [] out_dir = utils.safe_makedir(os.path.join(out_dir, "indexcov")) out_files = [os.path.join(out_dir, "%s-indexcov.%s" % (dd.get_sample_name(data), ext)) for ext in ["roc", "ped", "bed.gz"]] if not utils.file_uptodate(out_files[-1], bam_file): with transaction.tx_tmpdir(data) as tmp_dir: tmp_dir = utils.safe_makedir(os.path.join(tmp_dir, dd.get_sample_name(data))) gender_chroms = [x.name for x in ref.file_contigs(dd.get_ref_file(data)) if chromhacks.is_sex(x.name)] gender_args = "--sex %s" % (",".join(gender_chroms)) if gender_chroms else "" cmd = "goleft indexcov --directory {tmp_dir} {gender_args} -- {bam_file}" try: do.run(cmd.format(**locals()), "QC: goleft indexcov") except subprocess.CalledProcessError as msg: if not ("indexcov: no usable" in str(msg) or ("indexcov: expected" in str(msg) and "sex chromosomes, found:" in str(msg))): raise for out_file in out_files: orig_file = os.path.join(tmp_dir, os.path.basename(out_file)) if utils.file_exists(orig_file): utils.copy_plus(orig_file, out_file) # MultiQC needs non-gzipped/BED inputs so unpack the file out_bed = out_files[-1].replace(".bed.gz", ".tsv") if utils.file_exists(out_files[-1]) and not utils.file_exists(out_bed): with transaction.file_transaction(data, out_bed) as tx_out_bed: cmd = "gunzip -c %s > %s" % (out_files[-1], tx_out_bed) do.run(cmd, "Unpack indexcov BED file") out_files[-1] = out_bed return [x for x in out_files if utils.file_exists(x)]

46.386555

115

0.664312

0

1,162

0.210507

543cef330851534694d86f1be5bca5d7e8614e34

1,210

py

Python

shrike-examples/contoso/utils/arg_utils.py

lynochka/azure-ml-problem-sets

e7e69de763444c5603e4455e35e69e917081a4cc

[ "MIT" ]

3

2021-07-27T16:28:51.000Z

2021-11-15T18:29:02.000Z

shrike-examples/contoso/utils/arg_utils.py

lynochka/azure-ml-problem-sets

e7e69de763444c5603e4455e35e69e917081a4cc

[ "MIT" ]

null

shrike-examples/contoso/utils/arg_utils.py

lynochka/azure-ml-problem-sets

e7e69de763444c5603e4455e35e69e917081a4cc

[ "MIT" ]

7

2021-08-09T15:04:03.000Z

2022-03-09T05:48:56.000Z

""" Utility functions for argument parsing """ import argparse def str2bool(val): """ Resolving boolean arguments if they are not given in the standard format Arguments: val (bool or string): boolean argument type Returns: bool: the desired value {True, False} """ if isinstance(val, bool): return val if isinstance(val, str): if val.lower() in ("yes", "true", "t", "y", "1"): return True elif val.lower() in ("no", "false", "f", "n", "0"): return False else: raise argparse.ArgumentTypeError("Boolean value expected.") def str2intlist(val): """Converts comma separated string of integers into list of integers Args: val (str): comma separate string of integers """ return commastring2list(int)(val) def commastring2list(output_type=str): """Returns a lambda function which converts a comma separated string into a list of a given type Args: output_type (function, optional): string type conversion function. Defaults to str. Returns: function: lambda function """ return lambda input_str: list(map(output_type, input_str.split(",")))

25.744681

100

0.638017

0

725

0.599174

543dd03030508ee683df7a6d3985dc5051235db5

277

py

Python

tests/test_learner.py

luksurious/faster-teaching

1493311d5b723ca3f216f537bda8db5907196443

[ "MIT" ]

2

2020-08-06T13:21:51.000Z

2021-04-15T04:29:03.000Z

tests/test_learner.py

luksurious/faster-teaching

1493311d5b723ca3f216f537bda8db5907196443

[ "MIT" ]

null

tests/test_learner.py

luksurious/faster-teaching

1493311d5b723ca3f216f537bda8db5907196443

[ "MIT" ]

null

from concepts.letter_addition import LetterAddition from learners.sim_memoryless_learner import SimMemorylessLearner def test_see_example(): concept = LetterAddition(6) learner = SimMemorylessLearner(concept, list(range(0, 7))) learner.see_example(((0, 1), 10))

27.7

64

0.776173

0

543dded51722ade60b4b464e9cde6ba374678fe4

2,536

py

Python

piper/jde.py

miketarpey/piper

d1620727889228d61fbe448f4747cef9351ede59

[ "BSD-2-Clause-FreeBSD" ]

null

piper/jde.py

miketarpey/piper

d1620727889228d61fbe448f4747cef9351ede59

[ "BSD-2-Clause-FreeBSD" ]

24

2021-02-03T17:06:13.000Z

2021-04-02T13:09:13.000Z

piper/jde.py

miketarpey/piper

d1620727889228d61fbe448f4747cef9351ede59

[ "BSD-2-Clause-FreeBSD" ]

null

import logging import pandas as pd from datetime import datetime from typing import ( Any, Callable, Dict, Hashable, Iterable, List, NamedTuple, Optional, Pattern, Set, Tuple, Union, ) logger = logging.getLogger(__name__) # add_jde_batch() {{{1 def add_jde_batch(df: pd.DataFrame, col_prefix: str = 'ed', userid: str = 'userid', batch: str = 'ABC', start: int = 100, step: int = 100) -> pd.DataFrame: ''' Add 'standard' JDE timestamp/default columns. For given dataframe, adds the following standard Z-file columns. User ID (edus) Batch Number (edbt) Transaction Number (edtn) Line Number (edln) Examples -------- from piper.defaults import * from piper.jde import * .. code-block: %%piper sample_sales() >> select('-target_profit', '-location', '-month') >> reset_index(drop=True) >> add_jde_batch(start=3) >> head(tablefmt='plain') edus edbt edtn edln product target_sales actual_sales actual_profit 0 userid ABC_20210331 1 3 Beachwear 31749 29209 1753 1 userid ABC_20210331 1 103 Beachwear 37833 34050 5448 2 userid ABC_20210331 1 203 Jeans 29485 31549 4417 3 userid ABC_20210331 1 303 Jeans 37524 40901 4090 Parameters ---------- df : the pandas dataframe object col_prefix : 2 character (e.g. 'ed') column name prefix to be applied to the added columns userid : default userid text value batch : 2 character prefix to concatenated to current timestamp trans_no : start number in xxln column step : step increment in xxln column Returns ------- A pandas dataframe ''' timestamp = datetime.now().strftime('_%Y%m%d') start_position = 0 range_seq = range(start, (df.shape[0]+1)*step, step) df.insert(start_position, f'{col_prefix}us', userid) df.insert(start_position+1, f'{col_prefix}bt', batch + timestamp) df.insert(start_position+2, f'{col_prefix}tn', 1) df.insert(start_position+3, f'{col_prefix}ln', pd.Series(range_seq)) return df

27.868132

109

0.542587

0

1,658

0.653785

543e07ad4f4ef4e280a96b2a4575d3e61db5448a

2,159

py

Python

codes/utils.py

epfml/byzantine-robust-noniid-optimizer

0e27349ac99235251110d54dd102fda0091bf274

[ "MIT" ]

7

2021-06-22T03:12:15.000Z

2022-01-06T16:11:14.000Z

codes/utils.py

epfml/byzantine-robust-noniid-optimizer

0e27349ac99235251110d54dd102fda0091bf274

[ "MIT" ]

null

codes/utils.py

epfml/byzantine-robust-noniid-optimizer

0e27349ac99235251110d54dd102fda0091bf274

[ "MIT" ]

2

2021-12-12T13:28:02.000Z

2022-02-18T13:22:20.000Z

import os import shutil import logging class BColors(object): HEADER = "\033[95m" OK_BLUE = "\033[94m" OK_CYAN = "\033[96m" OK_GREEN = "\033[92m" WARNING = "\033[93m" FAIL = "\033[91m" END_C = "\033[0m" BOLD = "\033[1m" UNDERLINE = "\033[4m" def touch(fname: str, times=None, create_dirs: bool = False): if create_dirs: base_dir = os.path.dirname(fname) if not os.path.exists(base_dir): os.makedirs(base_dir) with open(fname, "a"): os.utime(fname, times) def touch_dir(base_dir: str) -> None: if not os.path.exists(base_dir): os.makedirs(base_dir) def accuracy(output, target, topk=(1,)): """Computes the precision@k for the specified values of k""" maxk = max(topk) batch_size = target.size(0) _, pred = output.topk(maxk, 1, True, True) pred = pred.t() correct = pred.eq(target.view(1, -1).expand_as(pred)) res = [] for k in topk: correct_k = correct[:k].view(-1).float().sum(0) res.append(correct_k.mul_(100.0 / batch_size)) return res def top1_accuracy(output, target): return accuracy(output, target, topk=(1,))[0].item() def log(*args, **kwargs): pass def log_dict(*args, **kwargs): pass def initialize_logger(log_root): if not os.path.exists(log_root): os.makedirs(log_root) else: shutil.rmtree(log_root) os.makedirs(log_root) print(f"Logging files to {log_root}") # Only to file; One dict per line; Easy to process json_logger = logging.getLogger("stats") json_logger.setLevel(logging.INFO) fh = logging.FileHandler(os.path.join(log_root, "stats")) fh.setLevel(logging.INFO) fh.setFormatter(logging.Formatter("%(message)s")) json_logger.addHandler(fh) debug_logger = logging.getLogger("debug") debug_logger.setLevel(logging.INFO) ch = logging.StreamHandler() ch.setLevel(logging.INFO) ch.setFormatter(logging.Formatter("%(message)s")) debug_logger.addHandler(ch) fh = logging.FileHandler(os.path.join(log_root, "debug")) fh.setLevel(logging.INFO) debug_logger.addHandler(fh)

25.104651

64

0.642427

238

0.110236

0

284

0.131542

543e913c7932efd8a58e4692b8be276e0e6a692e

2,090

py

Python

setup.py

robertjanes/drawbot

5a0a2ce55cda3f87624ae8c028d9d59aceee3897

[ "BSD-2-Clause" ]

null

setup.py

robertjanes/drawbot

5a0a2ce55cda3f87624ae8c028d9d59aceee3897

[ "BSD-2-Clause" ]

null

setup.py

robertjanes/drawbot

5a0a2ce55cda3f87624ae8c028d9d59aceee3897

[ "BSD-2-Clause" ]

null

#!/usr/bin/env python from __future__ import division, absolute_import, print_function from setuptools import setup import os import re import shutil _versionRE = re.compile(r'__version__\s*=\s*\"([^\"]+)\"') # read the version number for the settings file with open('drawBot/drawBotSettings.py', "r") as settings: code = settings.read() found = _versionRE.search(code) assert found is not None, "drawBot __version__ not found" __version__ = found.group(1) externalTools = ("ffmpeg", "gifsicle", "mkbitmap", "potrace") externalToolsSourceRoot = os.path.join(os.path.dirname(__file__), "Resources", "externalTools") externalToolsDestRoot = os.path.join(os.path.dirname(__file__), "drawBot", "context", "tools") # copy all external tools into drawBot.context.tools folder for externalTool in externalTools: source = os.path.join(externalToolsSourceRoot, externalTool) dest = os.path.join(externalToolsDestRoot, externalTool) shutil.copyfile(source, dest) os.chmod(dest, 0o775) setup(name="drawBot", version=__version__, description="DrawBot is a powerful tool that invites you to write simple Python scripts to generate two-dimensional graphics. The builtin graphics primitives support rectangles, ovals, (bezier) paths, polygons, text objects and transparency.", author="Just van Rossum, Erik van Blokland, Frederik Berlaen", author_email="frederik@typemytype.com", url="http://drawbot.com", license="BSD", packages=[ "drawBot", "drawBot.context", "drawBot.context.tools", "drawBot.ui" ], package_data={ "drawBot": [ "context/tools/ffmpeg", "context/tools/gifsicle", "context/tools/mkbitmap", "context/tools/potrace" ] }, install_requires=[ "pyobjc", "fontTools", "booleanOperations", "pillow" ], include_package_data=True, ) # remove all external tools for externalTool in externalTools: dest = os.path.join(externalToolsDestRoot, externalTool) os.remove(dest)

32.65625

247

0.688517

0

890

0.425837

543ed68a45e19a13dd2f2c914498c100fd410df9

784

py

Python

src/homework/i_dictionaries_sets/dictionary.py

acc-cosc-1336-spring-2022/acc-cosc-1336-spring-2022-WillCapo

426db13aa4d5f6005d7079007ff5fdf114ef649e

[ "MIT" ]

null

src/homework/i_dictionaries_sets/dictionary.py

acc-cosc-1336-spring-2022/acc-cosc-1336-spring-2022-WillCapo

426db13aa4d5f6005d7079007ff5fdf114ef649e

[ "MIT" ]

null

src/homework/i_dictionaries_sets/dictionary.py

acc-cosc-1336-spring-2022/acc-cosc-1336-spring-2022-WillCapo

426db13aa4d5f6005d7079007ff5fdf114ef649e

[ "MIT" ]

1

2022-02-09T02:28:56.000Z

def get_p_distance(list1, list2): count = 0 i = 0 while i < len(list1): if (list1[i] != list2[i]): count += .1 i += 1 return count def get_p_distance_matrix(list1, list2, list3, list4): dna1 = get_p_distance(list1, list1), get_p_distance(list1, list2), get_p_distance(list1, list3), get_p_distance(list1, list4) dna2 = get_p_distance(list2, list1), get_p_distance(list2, list2), get_p_distance(list2, list3), get_p_distance(list2, list4) dna3 = get_p_distance(list3, list1), get_p_distance(list3, list2), get_p_distance(list3, list3), get_p_distance(list3, list4) dna4 = get_p_distance(list4, list1), get_p_distance(list4, list2), get_p_distance(list4, list3), get_p_distance(list4, list4) return dna1, dna2, dna3, dna4

52.266667

129

0.69898

0

543fd7e53080b049a8ec4e7ace7dac2f370068e8

38,634

py

Python

pysnmp-with-texts/ZHONE-COM-IP-FILTER-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

8

2019-05-09T17:04:00.000Z

2021-06-09T06:50:51.000Z

pysnmp-with-texts/ZHONE-COM-IP-FILTER-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

4

2019-05-31T16:42:59.000Z

2020-01-31T21:57:17.000Z

pysnmp-with-texts/ZHONE-COM-IP-FILTER-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

10

2019-04-30T05:51:36.000Z

2022-02-16T03:33:41.000Z

# # PySNMP MIB module ZHONE-COM-IP-FILTER-MIB (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/ZHONE-COM-IP-FILTER-MIB # Produced by pysmi-0.3.4 at Wed May 1 15:47:04 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # Integer, OctetString, ObjectIdentifier = mibBuilder.importSymbols("ASN1", "Integer", "OctetString", "ObjectIdentifier") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ValueSizeConstraint, SingleValueConstraint, ValueRangeConstraint, ConstraintsUnion, ConstraintsIntersection = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueSizeConstraint", "SingleValueConstraint", "ValueRangeConstraint", "ConstraintsUnion", "ConstraintsIntersection") ifIndex, = mibBuilder.importSymbols("IF-MIB", "ifIndex") SnmpAdminString, = mibBuilder.importSymbols("SNMP-FRAMEWORK-MIB", "SnmpAdminString") ModuleCompliance, NotificationGroup = mibBuilder.importSymbols("SNMPv2-CONF", "ModuleCompliance", "NotificationGroup") Gauge32, Counter64, iso, Integer32, ModuleIdentity, ObjectIdentity, IpAddress, Unsigned32, MibIdentifier, TimeTicks, MibScalar, MibTable, MibTableRow, MibTableColumn, Bits, NotificationType, Counter32 = mibBuilder.importSymbols("SNMPv2-SMI", "Gauge32", "Counter64", "iso", "Integer32", "ModuleIdentity", "ObjectIdentity", "IpAddress", "Unsigned32", "MibIdentifier", "TimeTicks", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "Bits", "NotificationType", "Counter32") DisplayString, TextualConvention = mibBuilder.importSymbols("SNMPv2-TC", "DisplayString", "TextualConvention") zhoneModules, zhoneIp = mibBuilder.importSymbols("Zhone", "zhoneModules", "zhoneIp") ZhoneRowStatus, ZhoneAdminString = mibBuilder.importSymbols("Zhone-TC", "ZhoneRowStatus", "ZhoneAdminString") comIpFilter = ModuleIdentity((1, 3, 6, 1, 4, 1, 5504, 6, 58)) comIpFilter.setRevisions(('2005-01-10 10:16', '2005-01-03 09:24', '2004-12-21 09:25', '2004-08-30 11:00', '2004-04-06 00:17', '2001-01-17 08:48', '2000-09-11 16:22',)) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): if mibBuilder.loadTexts: comIpFilter.setRevisionsDescriptions(('changed portAccessArg1, portAccessArg2 to more intuitive names.', 'changed portArg1, portArg2 to IP addresses', 'added Port_Access', 'V01.01.02 - Add type field to mcastControlList.', 'V01.01.01 - Implementation of multicast-control-list.', 'V01.01.00 - Added keyword markup, updated SMI, Added the filterStmtRenumTable and filterStatsTable', 'V01.00.00 - Initial Release',)) if mibBuilder.loadTexts: comIpFilter.setLastUpdated('200501100015Z') if mibBuilder.loadTexts: comIpFilter.setOrganization('Zhone Technologies, Inc.') if mibBuilder.loadTexts: comIpFilter.setContactInfo(' Postal: Zhone Technologies, Inc. @ Zhone Way 7001 Oakport Street Oakland, CA 94621 USA Toll-Free: +1 877-ZHONE20 (+1 877-946-6320) Tel: +1-510-777-7000 Fax: +1-510-777-7001 E-mail: support@zhone.com') if mibBuilder.loadTexts: comIpFilter.setDescription('Zhone IP Filter MIB Module. IP Software Minneapolis, MN') filter = ObjectIdentity((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8)) if mibBuilder.loadTexts: filter.setStatus('current') if mibBuilder.loadTexts: filter.setDescription('The MIB module representing IP filter specifications in Zhone Technologies products. IP filtering is typically performed to enhance network security by limiting what access is allowed between two networks. Filtering is also effective in eliminating certain denial-of-service attacks. Packet filtering also provides a framework for sanity checking packet headers, and rejecting packets that are unlikely (or that should be impossible). In this way, packet filtering can prevent certain unfortunate mistakes from shutting a network down.') if mibBuilder.loadTexts: filter.setReference("RFC1812, 'Requirements for IP Version 4 Routers,' ftp://ftp.isi.edu/in-notes/rfc1812.txt. RFC2267, 'Network Ingress Filtering: Defeating Denial of Service Attacks which employ IP Source Address Spoofing,' ftp://ftp.isi.edu/in-notes/rfc2267.txt. RFC2474, 'Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers', ftp://ftp.isi.edu/in-notes/rfc2474.txt. D. Brent Chapman, 'Network (In)Security Through IP Packet Filtering,' Proceedings of the 3rd USENIX Security Symposium, Sept. 1992. Andrew Molitor, 'An Architecture for Advanced Packet Filtering,' Proceedings of the 5th USENIX Security Symposium, June. 1995. Paul Russell, 'Linux IPCHAINS-HOWTO,' http://www.rustcorp.com/linux/ipchains/HOWTO.html, v1.0.7, Mar. 1999.") filterGlobal = ObjectIdentity((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 1)) if mibBuilder.loadTexts: filterGlobal.setStatus('current') if mibBuilder.loadTexts: filterGlobal.setDescription('Global filter provisioning information.') fltGlobalIndexNext = MibScalar((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))).setMaxAccess("readonly") if mibBuilder.loadTexts: fltGlobalIndexNext.setStatus('current') if mibBuilder.loadTexts: fltGlobalIndexNext.setDescription('The next available filter spec table index (filterSpecIndex). A GET on this object increments the value by one. A GETNEXT on this object will always return zero.') fltGlobalTimeout = MibScalar((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 1, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))).setUnits('seconds').setMaxAccess("readwrite") if mibBuilder.loadTexts: fltGlobalTimeout.setStatus('current') if mibBuilder.loadTexts: fltGlobalTimeout.setDescription('Filter inconsistency timeout in seconds. A filter spec is considered to be in an inconsistent state when the value of the objects fltSpecVersion1 and fltSpecVersion2 are not equal. This timeout indicates the minimum number of seconds a filter may be in an inconsistent state before the filter spec becomes invalid and the default action for a filter is used as the filter. Provided fltGlobalTimeout is long enough, it should ensure that both an old modification is permanently stalled (ensuring exclusive access) as well as enough time to repair a filter. Default is five seconds.') filterSpecTable = MibTable((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2), ) if mibBuilder.loadTexts: filterSpecTable.setStatus('current') if mibBuilder.loadTexts: filterSpecTable.setDescription("The filter specification table contains specifications for the IP filtering module. Rows are indexed by a single integer index (filterSpecIndex). The fltGlobalIndexNext object is used to determine the next index value. Each row points to a sequence of rows (statements) in the filterStatementTable. When any row in that sequence is modified, created, or removed, the fltSpecVersion1 and fltSpecVersion2 objects must be incremented. Rows are created by assigning fltSpecIndex and setting fltSpecRowStatus to 'createAndGo'. All columnar objects in this table have default values, so no objects other than the index value need be set to create a row. Rows are removed by setting fltSpecRowStatus to 'destroy'. When a row is removed, each row in filterStatementTable with the same fltSpecIndex is automatically removed.") filterSpecEntry = MibTableRow((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1), ).setIndexNames((0, "ZHONE-COM-IP-FILTER-MIB", "fltSpecIndex")) if mibBuilder.loadTexts: filterSpecEntry.setStatus('current') if mibBuilder.loadTexts: filterSpecEntry.setDescription('An entry in the filterSpecTable.') fltSpecIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))) if mibBuilder.loadTexts: fltSpecIndex.setStatus('current') if mibBuilder.loadTexts: fltSpecIndex.setDescription('The index that identifies an entry in the filterSpecTable. The fltGlobalIndexNext object is used to determine the next value of this object.') fltSpecName = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1, 2), ZhoneAdminString()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltSpecName.setStatus('current') if mibBuilder.loadTexts: fltSpecName.setDescription('The filter name associated with this filter specification. This name should indicate the nature of the filter. The default value is an empty string.') fltSpecDesc = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1, 3), SnmpAdminString()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltSpecDesc.setStatus('current') if mibBuilder.loadTexts: fltSpecDesc.setDescription('Textual description of the filter specification. This should briefly describe the nature of the filter defined by the associated filter statements. The default value is an empty string.') fltSpecVersion1 = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1, 4), Unsigned32()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltSpecVersion1.setStatus('current') if mibBuilder.loadTexts: fltSpecVersion1.setDescription('The version number of the filter specification. This is used to flag any changes in the statements that comprise a filter. Each time a modification occurs to an object in a filter spec (including the the list of filter statements of the same fltSpecIndex in filterStatementTable), the value of this object, and fltSpecVersion2 must be incremented. The manager adding, deleting, or modifying a filter statement or statements must increment this version number in the following manner. A read of fltSpecVersion1 returns its current value. A write to fltSpecVersion1 must be one greater than its current value. A successful write of this object transfers ownership to the manager, where the manager must subsequently perform any desired modifications to the filter spec and then write the new value of fltSpecVersion1 to the fltSpecVersion2 object to release ownership. When fltSpecVersion1 does not equal to fltSpecVersion2, the filter spec is in an inconsistent state. If the filter spec remains in an inconsistent state longer than the time specified in fltGlobalTimeout, the filter spec is declared invalid and the filter spec does not become active. The previously provisioned filter spec will remain active. If no previous filter spec was provisioned for this interface, a default action is used. It is up to the manager to fix the invalid filter spec and bring it into a consistent state.') fltSpecVersion2 = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1, 5), Unsigned32()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltSpecVersion2.setStatus('current') if mibBuilder.loadTexts: fltSpecVersion2.setDescription('The version number of the filter specification. The value of this object must be equal to fltSpecVersion1, otherwise the filter spec is inconsistent. See fltSpecVersion1 for details.') fltSpecLanguageVersion = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1, 6), Unsigned32()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltSpecLanguageVersion.setStatus('current') if mibBuilder.loadTexts: fltSpecLanguageVersion.setDescription('The language version of the filter. The language version further details the meaning and use of the objects in filterStatmentTable. The definitions of the filter languages is beyond the scope of this description.') fltSpecRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 2, 1, 7), ZhoneRowStatus()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltSpecRowStatus.setStatus('current') if mibBuilder.loadTexts: fltSpecRowStatus.setDescription('Zhone convention to support row creation and deletion. This is the only object required to create or destroy a row in this table.') filterStatementTable = MibTable((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3), ) if mibBuilder.loadTexts: filterStatementTable.setStatus('current') if mibBuilder.loadTexts: filterStatementTable.setDescription("This table contains the filter specification statements for the IP filtering module. A complete filter specification is comprised of all the linked statements (rows) that are pointed to by an entry in the filterSpecTable. Filter statements are linked together by fltSpecIndex, and are ordered within the comprised filter using fltStmtIndex. A statement can only be owned by one filter spec. Rows are created by assigning fltSpecIndex and fltStmtIndex, and setting fltStmtRowStatus to 'createAndGo'. All columnar objects in this table have default values, so no objects other than the index values need be set to create a row. Rows are destroyed by setting fltStmtRowStatus to 'delete'. When rows are created or destroyed, the version of the corresponding filter spec row is incremented.") filterStatementEntry = MibTableRow((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1), ).setIndexNames((0, "ZHONE-COM-IP-FILTER-MIB", "fltSpecIndex"), (0, "ZHONE-COM-IP-FILTER-MIB", "fltStmtIndex")) if mibBuilder.loadTexts: filterStatementEntry.setStatus('current') if mibBuilder.loadTexts: filterStatementEntry.setDescription('An entry in the filterStatement table. Each entry represents one of a sequence of statements that comprise a filter. Each filter statement consists of an index, specific packet header fields, and arbitrary packet offsets and values. Some objects in this entry define ranges for specific packet header fields. These objects define comparison operations on the field they share in the following manner: Low High Compare Method for field f --- ---- ------------------------------------------- 0 0 no comparison on the field 0 H less than or equal to High (f <= H) L 0 exact match (L == f) L H inclusive between comparison (L <= f <= H) ') fltStmtIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))) if mibBuilder.loadTexts: fltStmtIndex.setStatus('current') if mibBuilder.loadTexts: fltStmtIndex.setDescription('The table index that identifies a filter statement. These indicies should be sparse to allow for insertion into the list.') fltStmtIpSrcAddrLow = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 2), IpAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtIpSrcAddrLow.setStatus('current') if mibBuilder.loadTexts: fltStmtIpSrcAddrLow.setDescription('The inclusive lower bound for the source IP address range. See the filterStatementEntry description for details.') fltStmtIpSrcAddrHigh = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 3), IpAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtIpSrcAddrHigh.setStatus('current') if mibBuilder.loadTexts: fltStmtIpSrcAddrHigh.setDescription('The inclusive upper bound for the source IP address range. See the filterStatementEntry description for details.') fltStmtSrcPortLow = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 4), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 65535))).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtSrcPortLow.setStatus('current') if mibBuilder.loadTexts: fltStmtSrcPortLow.setDescription('The inclusive lower bound for the transport layer source port range. See the filterStatementEntry description for details.') fltStmtSrcPortHigh = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 5), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 65535))).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtSrcPortHigh.setStatus('current') if mibBuilder.loadTexts: fltStmtSrcPortHigh.setDescription('The inclusive upper bound for the transport layer source port range. See the filterStatementEntry description for details.') fltStmtIpDstAddrLow = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 6), IpAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtIpDstAddrLow.setStatus('current') if mibBuilder.loadTexts: fltStmtIpDstAddrLow.setDescription('The inclusive lower bound for the destination IP address range. See the filterStatementEntry description for details.') fltStmtIpDstAddrHigh = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 7), IpAddress().clone(hexValue="00000000")).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtIpDstAddrHigh.setStatus('current') if mibBuilder.loadTexts: fltStmtIpDstAddrHigh.setDescription('The inclusive upper bound for the destination IP address range. See the filterStatementEntry description for details.') fltStmtDstPortLow = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 8), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 65535))).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtDstPortLow.setStatus('current') if mibBuilder.loadTexts: fltStmtDstPortLow.setDescription('The inclusive lower bound for the transport layer destination port range. See the filterStatementEntry description for details.') fltStmtDstPortHigh = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 9), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 65535))).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtDstPortHigh.setStatus('current') if mibBuilder.loadTexts: fltStmtDstPortHigh.setDescription('The inclusive upper bound for the transport layer destination port range. See the filterStatementEntry description for details.') fltStmtIpProtocol = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 10), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("any", 1), ("ip", 2), ("tcp", 3), ("udp", 4), ("icmp", 5))).clone('any')).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtIpProtocol.setStatus('current') if mibBuilder.loadTexts: fltStmtIpProtocol.setDescription('The IP protocol value that is to be matched. The enum values are as follows: any(1) : any protocol type is a match (wildcard) ip(2) : raw IP packet tcp(3) : TCP packet udp(4) : UDP packet icmp(5) : ICMP packet The default value is any(1).') fltStmtArbValueBase = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 11), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5, 6, 7))).clone(namedValues=NamedValues(("none", 1), ("ip", 2), ("udp", 3), ("tcp", 4), ("icmp", 5), ("ipOptions", 6), ("tcpOptions", 7))).clone('none')).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtArbValueBase.setStatus('current') if mibBuilder.loadTexts: fltStmtArbValueBase.setDescription('This field identifies the protocol header to which the arbitrary value comparison applies. The enum values are as follows: none(1) : no arbitrary value comparison ip(2) : base is IP header udp(3) : base is UDP header tcp(4) : base is TCP header icmp(5) : base is ICMP header ipOptions(6) : base is IP options header tcpOptions(7) : base is TCP options header The default value is none(1).') fltStmtArbOffset = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 12), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 64))).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtArbOffset.setStatus('current') if mibBuilder.loadTexts: fltStmtArbOffset.setDescription('The offset, in octets, from the beginning of the header to the most significant octet for the arbitrary value comparison.') fltStmtArbMask = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 13), Unsigned32()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtArbMask.setStatus('current') if mibBuilder.loadTexts: fltStmtArbMask.setDescription('This object is mask for for arbitrary value comparisons. The non-zero bits in this field determine the size of the arbitrary field.') fltStmtArbValueLow = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 14), Unsigned32()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtArbValueLow.setStatus('current') if mibBuilder.loadTexts: fltStmtArbValueLow.setDescription('This object is the inclusive lower bound for arbitrary value comparison. See the filterStatementEntry description for details.') fltStmtArbValueHigh = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 15), Unsigned32()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtArbValueHigh.setStatus('current') if mibBuilder.loadTexts: fltStmtArbValueHigh.setDescription('This object is the inclusive upper bound for arbitrary value comparison. See the filterStatementEntry description for details.') fltStmtModifier = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 16), Bits().clone(namedValues=NamedValues(("notIpSrc", 0), ("notSrcPort", 1), ("notDstIp", 2), ("notPortDst", 3), ("notProtocol", 4), ("notArbitrary", 5), ("notStatement", 6)))).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtModifier.setStatus('current') if mibBuilder.loadTexts: fltStmtModifier.setDescription('Filter statement modifier. The bits set in this object logically negate the results of the comparisons made on their respecive fields as shown : notIpSrcAddr(1) : fltStmtIpSrcAddrLow, fltStmtIpSrcAddrHigh notSrcPort(2) : fltStmtSrcPortLow, fltStmtSrcPortHigh notIpDstAddr(3) : fltStmtIpDstAddrLow, fltStmtIpDstAddrHigh notDstPort(4) : fltStmtDstPortLow, fltStmtDstPortHigh notIpProtocol(5) : fltStmtIpProtocol notArbitrary(6) : fltStmtArbValueLow, fltStmtArbValueHigh notStatement(7) : negate outcome of the entire statement No bits set (the default) specifies to use all outcomes as is.') fltStmtAction = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 17), Bits().clone(namedValues=NamedValues(("reset", 0), ("permit", 1), ("deny", 2), ("forward", 3), ("reject", 4), ("log", 5))).clone(namedValues=NamedValues(("deny", 2)))).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtAction.setStatus('current') if mibBuilder.loadTexts: fltStmtAction.setDescription('Filter statement action. The bits set in this object specify actions to take on packets matching this statement. Supported actions are: reset(0) : Return a TCP reset packet to the packet sender and drop the packet. This cannot be specified with permit. permit(1) : Stop filtering the packet and allow it to be sent on the associated interface. This cannot be specified with deny. deny(2) : Stop filtering the packet and discard it. This cannot be specified with permit. forward(3) : Forward the packet the IP address specified in fltStmtActionArg. reject(4) : Return an ICMP destination unreachable packet (type 3) to the packet sender with code 13 (communication administratively prohibited). This cannot be specified permit. log(5) : Write the packet to the log stream. There are some mutually exclusive bits: reset(0) and permit(1), permit(1) and deny(2), permit(1) and reject(4). No bits set implies to continue filtering on the packet.') fltStmtActionArg = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 18), Integer32()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtActionArg.setStatus('current') if mibBuilder.loadTexts: fltStmtActionArg.setDescription('Filter statement action argument. The meaning of this object depends on the value of fltStmtAction: forward(3) : An IP address to forward the packet to. The value of this object must be non-zero. All other values of fltStmtAction have no relation to this object. The default is zero.') fltStmtRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 3, 1, 19), ZhoneRowStatus()).setMaxAccess("readcreate") if mibBuilder.loadTexts: fltStmtRowStatus.setStatus('current') if mibBuilder.loadTexts: fltStmtRowStatus.setDescription('Zhone convention to support row creation and deletion. This is the only object required to create or destroy a row in this table.') filterStmtRenumTable = MibTable((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 4), ) if mibBuilder.loadTexts: filterStmtRenumTable.setStatus('current') if mibBuilder.loadTexts: filterStmtRenumTable.setDescription('This table provides a mechanism for renumbering individual filter statments within their particular filter spec.') filterStmtRenumEntry = MibTableRow((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 4, 1), ) filterStatementEntry.registerAugmentions(("ZHONE-COM-IP-FILTER-MIB", "filterStmtRenumEntry")) filterStmtRenumEntry.setIndexNames(*filterStatementEntry.getIndexNames()) if mibBuilder.loadTexts: filterStmtRenumEntry.setStatus('current') if mibBuilder.loadTexts: filterStmtRenumEntry.setDescription('An entry in the filterStmtRenumTable.') fltStmtIndexNew = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 4, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))).setMaxAccess("readwrite") if mibBuilder.loadTexts: fltStmtIndexNew.setStatus('current') if mibBuilder.loadTexts: fltStmtIndexNew.setDescription("The new statement index for the filter statement. Reading this object will return the same value as the 'fltStmtIndex' portion of its index. Writing to this object will cause the corresponding filter statement to be relocated to the position identified by the value written here. If no statement exists at the current index, 'no such instance' will be returned. If a statement already exists at the new index then 'inconsistent value' is returned. For example, to move the second statement of filter #4 to the third position (e.g. to make room for a new statement #2), the following SNMP set-request would be issued: fltStmtIndexNew.4.2 = 3 There is no default value for this object as it is derived from the fltStmtIndex.") filterStatsTable = MibTable((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5), ) if mibBuilder.loadTexts: filterStatsTable.setStatus('current') if mibBuilder.loadTexts: filterStatsTable.setDescription('This table provides ingress and egress IP filter statistics for each interface. This table is indexed by the ifIndex of the interface and the direction (ingress or egress) of traffic being filtered. This is a read-only table.') filterStatsEntry = MibTableRow((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1), ).setIndexNames((0, "IF-MIB", "ifIndex"), (0, "ZHONE-COM-IP-FILTER-MIB", "fltStatDirection")) if mibBuilder.loadTexts: filterStatsEntry.setStatus('current') if mibBuilder.loadTexts: filterStatsEntry.setDescription('An entry in the filterStatsTable. There will be an entry for each filter provisioned on an interface. There can be, at most, two filters provisioned per interface; one for ingress filtering and the other for egress filtering.') fltStatDirection = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("ingress", 1), ("egress", 2)))) if mibBuilder.loadTexts: fltStatDirection.setStatus('current') if mibBuilder.loadTexts: fltStatDirection.setDescription('The direction for which this set of statistics is kept: ingress or egress.') fltStatResetPkts = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 2), Counter32()).setUnits('packets').setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatResetPkts.setStatus('current') if mibBuilder.loadTexts: fltStatResetPkts.setDescription('The number of discarded packets for which a TCP reset packet was sent.') fltStatPermitPkts = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 3), Counter32()).setUnits('packets').setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatPermitPkts.setStatus('current') if mibBuilder.loadTexts: fltStatPermitPkts.setDescription('The number of permitted packets.') fltStatDenyPkts = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 4), Counter32()).setUnits('packets').setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatDenyPkts.setStatus('current') if mibBuilder.loadTexts: fltStatDenyPkts.setDescription('The number of discarded packets.') fltStatForwardPkts = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 5), Counter32()).setUnits('packets').setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatForwardPkts.setStatus('current') if mibBuilder.loadTexts: fltStatForwardPkts.setDescription('The number of packets forwarded to the IP address specified in the filter.') fltStatRejectPkts = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 6), Counter32()).setUnits('packets').setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatRejectPkts.setStatus('current') if mibBuilder.loadTexts: fltStatRejectPkts.setDescription('The number of discarded packets for which an ICMP destination unreachable packet with code 13 was sent.') fltStatLogPkts = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 7), Counter32()).setUnits('packets').setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatLogPkts.setStatus('current') if mibBuilder.loadTexts: fltStatLogPkts.setDescription('The number of logged packets.') fltStatDefaultPkts = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 8), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatDefaultPkts.setStatus('current') if mibBuilder.loadTexts: fltStatDefaultPkts.setDescription('The number of packets that pass through the filter without matching upon which the default action is used.') fltStatSpecVersion = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 9), Unsigned32()).setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatSpecVersion.setStatus('current') if mibBuilder.loadTexts: fltStatSpecVersion.setDescription('The version of the filter being used on this interface.') fltStatSpecIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 5, 1, 10), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))).setMaxAccess("readonly") if mibBuilder.loadTexts: fltStatSpecIndex.setStatus('current') if mibBuilder.loadTexts: fltStatSpecIndex.setDescription('The index of the filter specification being used on this interface. If there is no filter configured for an interface, the entry will not exist in this table.') mcastControl = ObjectIdentity((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6)) if mibBuilder.loadTexts: mcastControl.setStatus('current') if mibBuilder.loadTexts: mcastControl.setDescription('The MIB module representing Multicast control list specifications in Zhone Technologies products. The First application of multicast control list is to accept of deny a IGMP request to join or leave a IGMP group. Any IGMP request to join a group is accepted only if the group address is available in the Multicast Control list pointed by a field in the ip-interface-record.') mcastControlListTable = MibTable((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6, 1), ) if mibBuilder.loadTexts: mcastControlListTable.setStatus('current') if mibBuilder.loadTexts: mcastControlListTable.setDescription('Multicast control list table conatins the one of the IP Address that can be allowed to join to by a IGMP join request from IP interface that has the the multicast control list in its ip-interfce-profile. The address to the table is the multicast control list ID and the precedence. The Row status in the table contains indication of whether the row is being created or destroyed. ') mcastControlListEntry = MibTableRow((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6, 1, 1), ).setIndexNames((0, "ZHONE-COM-IP-FILTER-MIB", "mcastControlListControlId"), (0, "ZHONE-COM-IP-FILTER-MIB", "mcastControlListControlPrecedence")) if mibBuilder.loadTexts: mcastControlListEntry.setStatus('current') if mibBuilder.loadTexts: mcastControlListEntry.setDescription('An entry in the Multicast Control List.') mcastControlListControlId = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6, 1, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))) if mibBuilder.loadTexts: mcastControlListControlId.setStatus('current') if mibBuilder.loadTexts: mcastControlListControlId.setDescription('Description.') mcastControlListControlPrecedence = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6, 1, 1, 2), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 2147483647))) if mibBuilder.loadTexts: mcastControlListControlPrecedence.setStatus('current') if mibBuilder.loadTexts: mcastControlListControlPrecedence.setDescription('Description.') mcastControlListRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6, 1, 1, 3), ZhoneRowStatus()).setMaxAccess("readcreate") if mibBuilder.loadTexts: mcastControlListRowStatus.setStatus('current') if mibBuilder.loadTexts: mcastControlListRowStatus.setDescription('Description.') mcastControlListIpAddress = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6, 1, 1, 4), IpAddress()).setMaxAccess("readcreate") if mibBuilder.loadTexts: mcastControlListIpAddress.setStatus('current') if mibBuilder.loadTexts: mcastControlListIpAddress.setDescription('multicast ip address.') mcastControlListType = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 6, 1, 1, 5), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3))).clone(namedValues=NamedValues(("normal", 1), ("always-on", 2), ("periodic", 3))).clone('normal')).setMaxAccess("readcreate") if mibBuilder.loadTexts: mcastControlListType.setStatus('current') if mibBuilder.loadTexts: mcastControlListType.setDescription('Defines the video stream type. normal - join and leave when desired. Used for video. always-on - always joined. Meant for EBS, not video. periodic - will join and leave after task complete. Not meant for video. Used to download the tv guide.') portAccessControl = ObjectIdentity((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7)) if mibBuilder.loadTexts: portAccessControl.setStatus('current') if mibBuilder.loadTexts: portAccessControl.setDescription('This MIB represents the port access control list in Zhone products. It is used to control access to internal ports. Initially it is used just for TELNET (23) , but in theory could be used for other ports as well.') portAccessNextIndex = MibScalar((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 1), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: portAccessNextIndex.setStatus('current') if mibBuilder.loadTexts: portAccessNextIndex.setDescription('Description: A hint for the next free index should the manager want to create a new entry.') portAccessTable = MibTable((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 2), ) if mibBuilder.loadTexts: portAccessTable.setStatus('current') if mibBuilder.loadTexts: portAccessTable.setDescription('Contains the list of entries that control port access on this device.') portAccessEntry = MibTableRow((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 2, 1), ).setIndexNames((0, "ZHONE-COM-IP-FILTER-MIB", "portAccessIndex")) if mibBuilder.loadTexts: portAccessEntry.setStatus('current') if mibBuilder.loadTexts: portAccessEntry.setDescription('This contains the entry that is to be accepted. Currently only used to control access to port 23. arg1, arg2 provide IP Address/mask to allow in.') portAccessIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 2, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 100))) if mibBuilder.loadTexts: portAccessIndex.setStatus('current') if mibBuilder.loadTexts: portAccessIndex.setDescription('The index of this entry in table. 100 entries should be more than enough.') portAccessRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 2, 1, 2), ZhoneRowStatus()).setMaxAccess("readcreate") if mibBuilder.loadTexts: portAccessRowStatus.setStatus('current') if mibBuilder.loadTexts: portAccessRowStatus.setDescription('Description.: used to create/delete entries in the table.') portAccessNumber = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 2, 1, 3), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 1023))).setMaxAccess("readcreate") if mibBuilder.loadTexts: portAccessNumber.setStatus('current') if mibBuilder.loadTexts: portAccessNumber.setDescription('PortNumber that this applies to, 1..1023 supported.') portAccessSrcAddr = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 2, 1, 4), IpAddress()).setMaxAccess("readcreate") if mibBuilder.loadTexts: portAccessSrcAddr.setStatus('current') if mibBuilder.loadTexts: portAccessSrcAddr.setDescription('The IP address that we will accept packets from.') portAccessNetMask = MibTableColumn((1, 3, 6, 1, 4, 1, 5504, 4, 1, 8, 7, 2, 1, 5), IpAddress()).setMaxAccess("readcreate") if mibBuilder.loadTexts: portAccessNetMask.setStatus('current') if mibBuilder.loadTexts: portAccessNetMask.setDescription('portAccessNetMask - used to pass the range that we will accept with regards to portAccessSrcAddr.') mibBuilder.exportSymbols("ZHONE-COM-IP-FILTER-MIB", fltStmtIpDstAddrLow=fltStmtIpDstAddrLow, fltStmtIpSrcAddrHigh=fltStmtIpSrcAddrHigh, mcastControlListIpAddress=mcastControlListIpAddress, fltSpecVersion1=fltSpecVersion1, fltStatSpecIndex=fltStatSpecIndex, portAccessSrcAddr=portAccessSrcAddr, fltStatSpecVersion=fltStatSpecVersion, portAccessNumber=portAccessNumber, fltStmtIpProtocol=fltStmtIpProtocol, fltStmtModifier=fltStmtModifier, fltSpecLanguageVersion=fltSpecLanguageVersion, fltStmtSrcPortLow=fltStmtSrcPortLow, mcastControlListControlPrecedence=mcastControlListControlPrecedence, fltStmtActionArg=fltStmtActionArg, fltSpecVersion2=fltSpecVersion2, filterStmtRenumEntry=filterStmtRenumEntry, filterStmtRenumTable=filterStmtRenumTable, portAccessTable=portAccessTable, mcastControlListControlId=mcastControlListControlId, fltStmtIpDstAddrHigh=fltStmtIpDstAddrHigh, fltStmtRowStatus=fltStmtRowStatus, comIpFilter=comIpFilter, portAccessControl=portAccessControl, fltStatDirection=fltStatDirection, mcastControl=mcastControl, fltStmtArbValueLow=fltStmtArbValueLow, mcastControlListTable=mcastControlListTable, filterGlobal=filterGlobal, fltSpecIndex=fltSpecIndex, PYSNMP_MODULE_ID=comIpFilter, fltStmtSrcPortHigh=fltStmtSrcPortHigh, filterStatsTable=filterStatsTable, fltStmtArbMask=fltStmtArbMask, fltGlobalIndexNext=fltGlobalIndexNext, fltStmtIndexNew=fltStmtIndexNew, mcastControlListRowStatus=mcastControlListRowStatus, filterStatsEntry=filterStatsEntry, fltStmtArbValueBase=fltStmtArbValueBase, fltStatLogPkts=fltStatLogPkts, fltStatResetPkts=fltStatResetPkts, fltStatPermitPkts=fltStatPermitPkts, mcastControlListType=mcastControlListType, portAccessIndex=portAccessIndex, fltStmtDstPortLow=fltStmtDstPortLow, fltGlobalTimeout=fltGlobalTimeout, filterStatementTable=filterStatementTable, fltStatDefaultPkts=fltStatDefaultPkts, filter=filter, fltStmtArbOffset=fltStmtArbOffset, portAccessEntry=portAccessEntry, portAccessNextIndex=portAccessNextIndex, fltStatRejectPkts=fltStatRejectPkts, mcastControlListEntry=mcastControlListEntry, filterStatementEntry=filterStatementEntry, fltStmtIndex=fltStmtIndex, filterSpecTable=filterSpecTable, fltSpecRowStatus=fltSpecRowStatus, fltStmtArbValueHigh=fltStmtArbValueHigh, portAccessNetMask=portAccessNetMask, portAccessRowStatus=portAccessRowStatus, fltStmtAction=fltStmtAction, fltStmtIpSrcAddrLow=fltStmtIpSrcAddrLow, filterSpecEntry=filterSpecEntry, fltStatDenyPkts=fltStatDenyPkts, fltSpecDesc=fltSpecDesc, fltSpecName=fltSpecName, fltStmtDstPortHigh=fltStmtDstPortHigh, fltStatForwardPkts=fltStatForwardPkts)

168.707424

2,566

0.786354

0

18,647

0.482658

5442d7409922b392e57d7544f376052f8505514b

11,160

py

Python

watertap/examples/flowsheets/case_studies/municipal_treatment/municipal_treatment.py

avdudchenko/watertap

ac8d59e015688ff175a8087d2d52272e4f1fe84f

[ "BSD-3-Clause-LBNL" ]

4

2021-11-06T01:13:22.000Z

2022-02-08T21:16:38.000Z

watertap/examples/flowsheets/case_studies/municipal_treatment/municipal_treatment.py

avdudchenko/watertap

ac8d59e015688ff175a8087d2d52272e4f1fe84f

[ "BSD-3-Clause-LBNL" ]

233

2021-10-13T12:53:44.000Z

2022-03-31T21:59:50.000Z

watertap/examples/flowsheets/case_studies/municipal_treatment/municipal_treatment.py

avdudchenko/watertap

ac8d59e015688ff175a8087d2d52272e4f1fe84f

[ "BSD-3-Clause-LBNL" ]

12

2021-11-01T19:11:03.000Z

2022-03-08T22:20:58.000Z

############################################################################### # WaterTAP Copyright (c) 2021, The Regents of the University of California, # through Lawrence Berkeley National Laboratory, Oak Ridge National # Laboratory, National Renewable Energy Laboratory, and National Energy # Technology Laboratory (subject to receipt of any required approvals from # the U.S. Dept. of Energy). All rights reserved. # # Please see the files COPYRIGHT.md and LICENSE.md for full copyright and license # information, respectively. These files are also available online at the URL # "https://github.com/watertap-org/watertap/" # ############################################################################### from pyomo.environ import ( ConcreteModel, value, TransformationFactory, units as pyunits, assert_optimal_termination, ) from pyomo.network import Arc, SequentialDecomposition from pyomo.util.check_units import assert_units_consistent from idaes.core import FlowsheetBlock from idaes.core.util import get_solver from idaes.generic_models.unit_models import Product import idaes.core.util.scaling as iscale from idaes.generic_models.costing import UnitModelCostingBlock from watertap.core.util.initialization import assert_degrees_of_freedom from watertap.core.wt_database import Database import watertap.core.zero_order_properties as prop_ZO from watertap.unit_models.zero_order import ( FeedZO, MunicipalDrinkingZO, WaterPumpingStationZO, PumpZO, CoagulationFlocculationZO, SedimentationZO, OzoneZO, FixedBedZO, GACZO, UVZO, IonExchangeZO, ChlorinationZO, StorageTankZO, BackwashSolidsHandlingZO, ) from watertap.core.zero_order_costing import ZeroOrderCosting def main(): m = build() set_operating_conditions(m) assert_degrees_of_freedom(m, 0) initialize_system(m) # initialization needed for ozone unit results = solve(m) display_results(m) add_costing(m) initialize_costing(m) assert_degrees_of_freedom(m, 0) assert_units_consistent(m) results = solve(m) display_costing(m) return m, results def build(): # flowsheet set up m = ConcreteModel() m.db = Database() m.fs = FlowsheetBlock(default={"dynamic": False}) m.fs.prop = prop_ZO.WaterParameterBlock( default={"solute_list": ["tds", "tss", "toc"]} ) # unit models m.fs.feed = FeedZO(default={"property_package": m.fs.prop}) m.fs.intake_pump = WaterPumpingStationZO( default={ "property_package": m.fs.prop, "database": m.db, "process_subtype": "raw", } ) m.fs.coag_and_floc = CoagulationFlocculationZO( default={"property_package": m.fs.prop, "database": m.db} ) m.fs.sedimentation = SedimentationZO( default={"property_package": m.fs.prop, "database": m.db} ) m.fs.ozonation = OzoneZO(default={"property_package": m.fs.prop, "database": m.db}) m.fs.gravity_basin = FixedBedZO( default={ "property_package": m.fs.prop, "database": m.db, "process_subtype": "gravity_basin", } ) m.fs.gac = GACZO( default={ "property_package": m.fs.prop, "database": m.db, "process_subtype": "pressure_vessel", } ) m.fs.backwash_pump = WaterPumpingStationZO( default={ "property_package": m.fs.prop, "database": m.db, "process_subtype": "treated", } ) m.fs.uv = UVZO(default={"property_package": m.fs.prop, "database": m.db}) m.fs.anion_exchange = IonExchangeZO( default={ "property_package": m.fs.prop, "database": m.db, "process_subtype": "anion_exchange", } ) m.fs.chlorination = ChlorinationZO( default={"property_package": m.fs.prop, "database": m.db} ) m.fs.storage = StorageTankZO( default={"property_package": m.fs.prop, "database": m.db} ) m.fs.recharge_pump = WaterPumpingStationZO( default={ "property_package": m.fs.prop, "database": m.db, "process_subtype": "treated", } ) m.fs.product = Product(default={"property_package": m.fs.prop}) # connections m.fs.s01 = Arc(source=m.fs.feed.outlet, destination=m.fs.intake_pump.inlet) m.fs.s02 = Arc(source=m.fs.intake_pump.outlet, destination=m.fs.coag_and_floc.inlet) m.fs.s03 = Arc( source=m.fs.coag_and_floc.outlet, destination=m.fs.sedimentation.inlet ) m.fs.s04 = Arc(source=m.fs.sedimentation.treated, destination=m.fs.ozonation.inlet) m.fs.s05 = Arc(source=m.fs.ozonation.treated, destination=m.fs.gravity_basin.inlet) m.fs.s06 = Arc(source=m.fs.gravity_basin.treated, destination=m.fs.gac.inlet) m.fs.s07 = Arc(source=m.fs.gac.treated, destination=m.fs.uv.inlet) m.fs.s08 = Arc(source=m.fs.gac.byproduct, destination=m.fs.backwash_pump.inlet) m.fs.s09 = Arc(source=m.fs.uv.treated, destination=m.fs.anion_exchange.inlet) m.fs.s10 = Arc( source=m.fs.anion_exchange.treated, destination=m.fs.chlorination.inlet ) m.fs.s11 = Arc(source=m.fs.chlorination.treated, destination=m.fs.storage.inlet) m.fs.s12 = Arc(source=m.fs.storage.outlet, destination=m.fs.recharge_pump.inlet) m.fs.s13 = Arc(source=m.fs.recharge_pump.outlet, destination=m.fs.product.inlet) TransformationFactory("network.expand_arcs").apply_to(m) # scaling iscale.calculate_scaling_factors(m) return m def set_operating_conditions(m): # ---specifications--- # feed flow_vol = 0.9224 * pyunits.m**3 / pyunits.s conc_mass_tds = 0.63 * pyunits.kg / pyunits.m**3 conc_mass_tss = 0.006525 * pyunits.kg / pyunits.m**3 conc_mass_toc = 0.004 * pyunits.kg / pyunits.m**3 m.fs.feed.flow_vol[0].fix(flow_vol) m.fs.feed.conc_mass_comp[0, "tds"].fix(conc_mass_tds) m.fs.feed.conc_mass_comp[0, "tss"].fix(conc_mass_tss) m.fs.feed.conc_mass_comp[0, "toc"].fix(conc_mass_toc) solve(m.fs.feed) # intake pump m.fs.intake_pump.load_parameters_from_database() m.fs.intake_pump.electricity.fix(93.2) # coagulation and flocculation m.fs.coag_and_floc.load_parameters_from_database(use_default_removal=True) # sedimentation m.fs.sedimentation.load_parameters_from_database(use_default_removal=True) # # ozonation m.fs.ozonation.load_parameters_from_database(use_default_removal=True) # fixed bed gravity basin m.fs.gravity_basin.load_parameters_from_database(use_default_removal=True) # granular activated carbon m.fs.gac.load_parameters_from_database(use_default_removal=True) # backwash pump m.fs.backwash_pump.load_parameters_from_database() m.fs.backwash_pump.electricity.fix(37.3) # uv aop m.fs.uv.load_parameters_from_database(use_default_removal=True) m.fs.uv.uv_reduced_equivalent_dose.fix(200) m.fs.uv.uv_transmittance_in.fix(0.90) # anion exchange m.fs.anion_exchange.load_parameters_from_database(use_default_removal=True) # chlorination m.fs.chlorination.load_parameters_from_database(use_default_removal=True) # storage m.fs.storage.load_parameters_from_database(use_default_removal=True) m.fs.storage.storage_time.fix(6) # recharge pump m.fs.recharge_pump.load_parameters_from_database() m.fs.recharge_pump.electricity.fix(186.4) def initialize_system(m): seq = SequentialDecomposition() seq.options.tear_set = [] seq.options.iterLim = 1 seq.run(m, lambda u: u.initialize()) def solve(blk, solver=None, tee=False, check_termination=True): if solver is None: solver = get_solver() results = solver.solve(blk, tee=tee) if check_termination: assert_optimal_termination(results) return results def display_results(m): unit_list = [ "feed", "intake_pump", "coag_and_floc", "sedimentation", "ozonation", "gravity_basin", "gac", "backwash_pump", "uv", "anion_exchange", "chlorination", "storage", "recharge_pump", "product", ] for u in unit_list: m.fs.component(u).report() def add_costing(m): m.fs.costing = ZeroOrderCosting() # typing aid costing_kwargs = {"default": {"flowsheet_costing_block": m.fs.costing}} m.fs.intake_pump.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.coag_and_floc.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.sedimentation.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.ozonation.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.gravity_basin.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.gac.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.backwash_pump.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.uv.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.anion_exchange.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.chlorination.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.storage.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.recharge_pump.costing = UnitModelCostingBlock(**costing_kwargs) m.fs.costing.cost_process() m.fs.costing.add_electricity_intensity(m.fs.product.properties[0].flow_vol) m.fs.costing.add_LCOW(m.fs.product.properties[0].flow_vol) def initialize_costing(m): m.fs.costing.initialize() def display_costing(m): m.fs.costing.total_capital_cost.display() m.fs.costing.total_operating_cost.display() m.fs.costing.LCOW.display() print("\nUnit Capital Costs\n") for u in m.fs.costing._registered_unit_costing: print( u.name, " : ", value(pyunits.convert(u.capital_cost, to_units=pyunits.USD_2018)), ) print("\nUtility Costs\n") for f in m.fs.costing.flow_types: print( f, " : ", value( pyunits.convert( m.fs.costing.aggregate_flow_costs[f], to_units=pyunits.USD_2018 / pyunits.year, ) ), ) print("") total_capital_cost = value( pyunits.convert(m.fs.costing.total_capital_cost, to_units=pyunits.MUSD_2018) ) print(f"Total Capital Costs: {total_capital_cost:.2f} M$") total_operating_cost = value( pyunits.convert( m.fs.costing.total_operating_cost, to_units=pyunits.MUSD_2018 / pyunits.year ) ) print(f"Total Operating Costs: {total_operating_cost:.2f} M$/year") electricity_intensity = value( pyunits.convert( m.fs.costing.electricity_intensity, to_units=pyunits.kWh / pyunits.m**3 ) ) print(f"Electricity Intensity: {electricity_intensity:.4f} kWh/m^3") LCOW = value( pyunits.convert(m.fs.costing.LCOW, to_units=pyunits.USD_2018 / pyunits.m**3) ) print(f"Levelized Cost of Water: {LCOW:.4f} $/m^3") if __name__ == "__main__": m, results = main()

32.631579

88

0.66819

0

2,129

0.190771

54439c9a0c52b928b7dce1ab1fcc8ffac580ad8b

2,680

py

Python

lib/googlecloudsdk/sql/tools/instances/delete.py

IsaacHuang/google-cloud-sdk

52afa5d1a75dff08f4f5380c5cccc015bf796ca5

[ "Apache-2.0" ]

null

lib/googlecloudsdk/sql/tools/instances/delete.py

IsaacHuang/google-cloud-sdk

52afa5d1a75dff08f4f5380c5cccc015bf796ca5

[ "Apache-2.0" ]

null

lib/googlecloudsdk/sql/tools/instances/delete.py

IsaacHuang/google-cloud-sdk

52afa5d1a75dff08f4f5380c5cccc015bf796ca5

[ "Apache-2.0" ]

null

# Copyright 2013 Google Inc. All Rights Reserved. """Deletes a Cloud SQL instance.""" from googlecloudapis.apitools.base import py as apitools_base from googlecloudsdk.calliope import base from googlecloudsdk.calliope import exceptions from googlecloudsdk.core import log from googlecloudsdk.core.util import console_io from googlecloudsdk.sql import util class Delete(base.Command): """Deletes a Cloud SQL instance.""" @staticmethod def Args(parser): """Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed. """ parser.add_argument( 'instance', help='Cloud SQL instance ID.') def Run(self, args): """Deletes a Cloud SQL instance. Args: args: argparse.Namespace, The arguments that this command was invoked with. Returns: A dict object representing the operations resource describing the delete operation if the delete was successful. Raises: HttpException: A http error response was received while executing api request. ToolException: An error other than http error occured while executing the command. """ sql_client = self.context['sql_client'] sql_messages = self.context['sql_messages'] resources = self.context['registry'] util.ValidateInstanceName(args.instance) instance_ref = resources.Parse(args.instance, collection='sql.instances') if not console_io.PromptContinue( 'All of the instance data will be lost when the instance is deleted.'): return None try: result = sql_client.instances.Delete( sql_messages.SqlInstancesDeleteRequest( instance=instance_ref.instance, project=instance_ref.project)) operation_ref = resources.Create( 'sql.operations', operation=result.operation, project=instance_ref.project, instance=instance_ref.instance, ) unused_operation = sql_client.operations.Get(operation_ref.Request()) log.DeletedResource(instance_ref) except apitools_base.HttpError as error: raise exceptions.HttpException(util.GetErrorMessage(error)) def Display(self, unused_args, result): """Display prints information about what just happened to stdout. Args: unused_args: The same as the args in Run. result: A dict object representing the operations resource describing the delete operation if the delete was successful. """ self.format(result)

31.904762

79

0.701493

2,319

0.865299

0

377

0.140672

0

1,301

0.485448

5445ab0135e0f3ff0f80b808bab631bc81bb1f98

804

py

Python

nsapiwrapper/exceptions.py

DolphDev/nsapiwrapper

cd67be445cfc4845f822ff815f3fb265f75061c9

[ "MIT" ]

null

nsapiwrapper/exceptions.py

DolphDev/nsapiwrapper

cd67be445cfc4845f822ff815f3fb265f75061c9

[ "MIT" ]

null

nsapiwrapper/exceptions.py

DolphDev/nsapiwrapper

cd67be445cfc4845f822ff815f3fb265f75061c9

[ "MIT" ]

null

"""Exceptions for this library""" class NSBaseError(Exception): """Base Error for all custom exceptions""" pass class RateLimitReached(NSBaseError): """Rate Limit was reached""" class NSServerBaseException(NSBaseError): """Exceptions that the server returns""" pass class APIError(NSServerBaseException): """General API Error""" pass class Forbidden(APIError): pass class ConflictError(APIError): """ConflictError from Server""" pass class NotFound(APIError): """Nation/Region Not Found""" pass class APIRateLimitBan(APIError): """Server has banned your IP""" pass class APIUsageError(APIError): pass class InternalServerError(APIError): pass class CloudflareServerError(APIError): pass class BadRequest(APIError): pass

18.272727

46

0.705224

746

0.927861

0

257

0.319652

544703b0ead742e49b1d2aa2223e76a2cd97299b

62,639

py

Python

src.py

edbezci/mapOverlayHumanoid

95d5e16fb983a7384abea6f51599483274ff0f62

[ "MIT" ]

null

src.py

edbezci/mapOverlayHumanoid

95d5e16fb983a7384abea6f51599483274ff0f62

[ "MIT" ]

null

src.py

edbezci/mapOverlayHumanoid

95d5e16fb983a7384abea6f51599483274ff0f62

[ "MIT" ]

null

# lines 1-4 imports the necessary libraries import pygame import os import random import math import sys import hlp import intro import dsb # this is the last module with the description files ''' declaring some global variables beacause in Python, we can set global variables that can be used in future functions setting the variables false allows us to activate them in the game loop, or vice versa creating empty lists as global variables allows us to access them outside of the functions they are being used ''' cursor = False randomLine = False randomTimer = True run = False stop = False start = False clear = False lines = [] colours = [] brutecolours = [] points = [] line_name = [] intersect_name = [] orderList = [] # initialise Pygame library, it is necessary in Programs using Pygame pygame.init() line_colour = pygame.Color(50, 50, 120) # initialise window size at 800 * 550 with a caption display = pygame.display.set_mode((1280, 550), pygame.FULLSCREEN | pygame.DOUBLEBUF | pygame.HWSURFACE) pygame.display.set_caption("Line Segment Intersection Visualisation Tool") # frames per second determines how many frames should be refreshed per second clock = pygame.time.Clock() # load cursor image for inserting line, os.path method points to the path of the cursor image file pointer = pygame.image.load(os.path.join("resources", "pointer.png")) # BitterFont text used throughout the program bitterfont = os.path.abspath("resources/bitterfont.otf") def AddPoints(p): ''' this function takes a point as an argument, then append the 'points' list by using iteration over every item in the points list if that point is already in the list, the function does nothing if not, the function appends the points list object with the argument p. ''' # make sure we're referring to the points object outside of this function global points # step through all the current items in points list for point in points: # is p the same as the current item if point == p: # if so, stop stepping through and drop out of this function without doing anything return # if we get here, we've gone through the whole list without a match # add the new point to the list points.append(p) def TransValue(OldValue, oldMax, oldMin): ''' scales the data ''' newMax = 350 newMin = 0 OldRange = (oldMax - oldMin) NewRange = (newMax - newMin) NewValue = int((((OldValue - oldMin) * NewRange) / OldRange) + newMin) return NewValue def GenerateRandomLine(): ''' generates random lines ''' x1 = random.randrange(51, 450) # randomly choses between 51 and 450 y1 = random.randrange(50, 450) # randomly choses between 50 and 450 x2 = random.randrange(51, 450) # randomly choses between 51 and 450 y2 = random.randrange(50, 450) # randomly choses between 50 and 450 # calls for the AddNewLine function to create new lines AddNewLine([(x1, y1), (x2, y2)]) def CheckIntersect(p1, p2, q1, q2): ''' this function determines if two lines intersect p1,p2, q1, q2 are start and end points of the lines it uses Cramer's rule of linear algebra to determine whether lines intersect ''' # getting the distance between end points by accessing the second index of the p1 and p2 list items and appointing it to variable a1 a1 = p2[1] - p1[1] b1 = p1[0] - p2[0] # same as above but accessing to the first index c1 = a1 * p1[0] + b1 * p1[1] a2 = q2[1] - q1[1] # same as a1 but for q instead of p b2 = q1[0] - q2[0] # same as b1 but for q instead of p c2 = a2 * q1[0] + b2 * q1[1] d = (a1 * b2 - a2 * b1) # finding the determinant if d == 0: # paralel or same line, determinant is zero return x = int((c1 * b2 - c2 * b1) / d) # solving for x y = int((a1 * c2 - a2 * c1) / d) # solving for y if min(p1[0], p2[0]) <= x <= max(p1[0], p2[0]) and min(p1[1], p2[1]) <= y <= max(p1[1], p2[1]): if min(q1[0], q2[0]) <= x <= max(q1[0], q2[0]) and min(q1[1], q2[1]) <= y <= max(q1[1], q2[1]): # found the intersection by checking solution of x and y for existing points AddPoints((x, y)) return True # returns true return False def BruteForceMain(): ''' this function is the Brute-Force Algorithm function with main display loop ''' # acessing the global variables global cursor, lines, brutecolours, points, randomLine, randomTimer, run, stop, clear, intersect_name # first the lines are accessing necessary global variables global display, line_name, orderList pygame.display.set_caption("Brute-Force Algorithm") # adding a caption # setting the display for the algorithm display = pygame.display.set_mode((1280, 550), pygame.FULLSCREEN) cursor = False # until while true line, which is the main loop, lines below creating the default values randomLine = False # again the default placeholder for the randomline clickedPos = [] # default place holder value for position orderList = [] # same for the order list, empty now all these values will be appended during the game loop efficiency = 0 # default place holder value for algorithm efficieny eventQueue = [] # event queue place holder, empty now back = 0 # if this becomes one, you go back while True: # starting the game loop # pygame method to fill the screen, takes colours and a display object display.fill((0, 0, 0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting # Here is to tell the computer to recognise if a keybord key is pressed. if event.type == pygame.KEYUP: if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. ''' if mouse clicked on the below coordinates, create a line pygame GUI property detecting when mouse click is on MOUSEBUTTONDOWN and MOUSEBUTTONUP should be used as a small loops so that the computer can understand when that instance of the mouse movement is over ''' if cursor == True and event.type == pygame.MOUSEBUTTONDOWN: if event.button == 1: # pygame method defining the button in the GUI mouse_pos = pygame.mouse.get_pos() # displays the mouse position on the screen # pygame property pos[0] is the mouse cursor in the X axis and pos[1] is the Y axis if 50 < pos[0] < 450 and 50 < pos[1] < 450: # here it adds the clicked postion corresponding to the positon of the mouse clickedPos.append(pos) if event.type == pygame.MOUSEBUTTONUP: randomTimer = True # turning the random from false to true so the timer can activate for i in range(0, 41): # choosing coordinates for drawing, exiting the previous iteration, range (0,41) goes between 0 and 40 # for the pygame method of drawing below, we need to determine the position on the screen as a tuple object pos = i * 10 + 50 # pygame method, takes display, colour, and positions of where the lines start and end. i.e, starts in (50,pos) ends in (450,pos), 1 at the end is the width of the line pygame.draw.line(display, line_colour, (50, pos), (450, pos), 1) # same as above but takes pos as y, by doing so and iterating through the range, you cover all the plane pygame.draw.line(display, line_colour, (pos, 50), (pos, 450), 1) i = 0 # index determining for data structure, taking it back to zero for line in lines: # iterating through lines which is a global variable for the priority queue aka eventQueue ''' having [i] next to colour allows me to colour each line differently each line has tuple object in the global variable line[0] accesses the nth item's first coordinates in the iteration and drawing ends in the line[1], nth item's second object ''' pygame.draw.line(display, brutecolours[i], line[0], line[1], 1) # calling the hlp.AddText function that was created before in the script hlp.AddText(line_name[i], line[0]) i += 1 # remember, need to increase the index. orderList = [] # creating the placeholder list object to secure future items i = 50 while i < 450: # this is the start of the brute force algorithm, it uses a try and error methods by iterating through all existing points j = 0 # that's why it enumarates through all possible points on the screen to go through, thus, I have the second while loop here for point in points: # 450 is the max number of points on the display, therefore, indexing goes until 450 i < 450 if point[0] == i: # while trying all the points, if the x value of the selected point intersects with the given index # then add it to the orderList orderList.append(intersect_name[j]) j += 1 # as before, increse indexing values by one i += 1 # as before in the previous function, increase the index by one n = len(lines) # finding out how many lines are drawn already for point in points: # iterating over the points # use this pygame method to draw a small circle where the lines intersect pygame.draw.circle(display, hlp.red, point, 3) efficiency = n * n # this is the efficieny formula for the brute-force algorithm if cursor == True: # arrange the mouse cursors pygame.mouse.set_visible(False) pos = pygame.mouse.get_pos() # this is a pygame method for mouse cursor # the cursor with the existing pointer image, pygame method called display.blit which adds a spirit to the screen display.blit(pointer, pos) # if you clicked on the screen, this checks the number of clicks and starts drawing if len(clickedPos) > 0: # again pygame method to draw, if clicked then draw this pygame.draw.circle(display, hlp.white, clickedPos[0], 2) # if clicked then draw this pygame.draw.line(display, hlp.white, clickedPos[0], pos, 1) if len(clickedPos) >= 2: # if the cursor is in a positon which is longer than 2 that can draw lines, if you clicked on more or equal to 2 times, which means begining and end for the lines # then add lines according to the points saved in the clickedPos object. [0] is the begining index and clickedPos[1] is the ending index. AddNewLine([clickedPos[0], clickedPos[1]]) cursor = False # disable the cursor after drawing clickedPos = [] # empty the placeholder after drawing the line else: # now you are entering into the scene of mouse action # again pygame GUI method enabling mouse action on the screen to interact pygame.mouse.set_visible(True) if randomLine == True: # if mouse clicked on the randomline GenerateRandomLine() # then create a random line, calling the existing function randomLine = False # turn it off after drawing so it would not keep drawing forever randomTimer = False # and stop the timer so it won't go forever if clear == True: # clear action is enabled, clear back all the placeholders to default lines = [] # everything is back to the default value colours = [] # everything is back to the default value brutecolours = [] # everything is back to the default value points = [] # everything is back to the default value orderList = [] # everything is back to the default value efficiency = 0 # everything is back to the default value eventQueue = [] # everything is back to the default value intersect_name = [] # everything is back to the default value line_name = [] # everything is back to the default value clear = False ''' adding text positions and texts for the frame calling existing functions, giving text, position and when applicable the action my helper functions are button and addtext that help me in my larger script. ''' # adding the texts and buttons as above function hlp.AddText("(0,0)", (30, 25)) hlp.AddText("(50,0)", (430, 25)) hlp.AddText("(0,50)", (30, 450)) hlp.AddText("(50,50)", (430, 450)) hlp.Button("Clear", 200, 5, 100, 30, ClearActive) hlp.Button("Random Segment", 50, 500, 180, 30, RandomActive) hlp.Button("Insert Segment", 280, 500, 180, 35, CursorActive) hlp.Button("Exit", 500, 5, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 900, 5, 100, 30, 1) if back > 0: # if back has a value, which means it has been clicked, stop the bigger loop that we started, i.e. the game loop, and break the game loop break # calls the helper function nxt = hlp.ButtonWithReturn("Next", 700, 5, 100, 30, 1) if nxt > 0: # so if the next button is clicked # calls for the description function hlp.Description(dsb.bf_desc) # pygame method to draw an object pygame.draw.rect(display, line_colour, [500, 50, 750, 490], 2) # adding the text on the given location hlp.AddText("Brute-Force Algorithm", (520, 70)) # adding the text on the given location. hlp.AddText("Order List:", (520, 120)) # creating indexing i and x, y positions to display on the GUI, this is an important way to assign values to a tuplae object i, o_x, o_y = 0, 540, 150 ''' iterating through the existing values in the orderList. because we don't want the texts to overlap on the screen most of the numbers below are finetuning to prevent overlapping of the texts for the order list and the eventqueue list. ''' for val in orderList: # going through the items in the orderList # calling the helper function to add the text of the values in the orderList hlp.AddText(val, (o_x, o_y), (255, 255, 255)) o_x += 50 # moving 50 pix on the x axis for each item i += 1 # going to next item by increasing the index if i % 14 == 0: # check if the line ends o_x = 540 # text is on the edge, there no more horizontol space o_y += 20 # # go to the next line by adding 20 to the y axis # adding the text on the given location hlp.AddText("Efficiency O(n*n):", (520, 480)) # adding the text on the given location hlp.AddText(str(efficiency), (540, 505), (255, 255, 255)) # updates the screen every turn pygame.display.flip() # will not run more than 30 frames per second clock.tick(90) intro.Introduction2() # calls back the introduction function def BentleyMain(): ''' this function is the Bentley-Ottmann Algorithm function with main display loop ''' global cursor, lines, colours, points, randomLine, randomTimer, run, stop, clear, intersect_name # first the lines are accessing necessary global variables global display, line_name, orderList pygame.display.set_caption("Bentley-Ottmann Algorithm") # adding a caption # setting the display for the algorithm display = pygame.display.set_mode((1280, 550), pygame.FULLSCREEN) cursor = False # until while true line, which is the main loop, lines below creating the default values randomLine = False # again the default placeholder for the randomline clickedPos = [] # default place holder value for position efficiency = 0 # default place holder value for algorithm efficieny eventQueue = [] # event queue place holder, empty now orderList = [] # same for the order list, empty now all these values will be appended during the game loop x = 50 # location of the x value on the screen back = 0 # if this becomes one, you go back while True: # starting the game loop # pygame method to fill the screen. takes colours and a display object display.fill((0, 0, 0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting # Here is to tell the computer to recognise if a keybord key is pressed. if event.type == pygame.KEYUP: if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. ''' if mouse clicked on the below coordinates, create a line pygame GUI property detecting when mouse click is on MOUSEBUTTONDOWN and MOUSEBUTTONUP should be used as a small loops so that the computer can understand when that instance of the mouse movement is over ''' if cursor == True and event.type == pygame.MOUSEBUTTONDOWN: if event.button == 1: # pygame method defining the button in the GUI mouse_pos = pygame.mouse.get_pos() # displays the mouse position on the screen # pygame property pos[0] is the mouse cursor in the X axis and pos[1] is the Y axis if 50 < pos[0] < 450 and 50 < pos[1] < 450: # here it adds the clicked postion corresponding to the positon of the mouse clickedPos.append(pos) if event.type == pygame.MOUSEBUTTONUP: randomTimer = True # turning the random from false to true so the timer can activate for i in range(0, 41): # choosing coordinates for drawing, exiting the previous iteration, range (0,41) goes between 0 and 40 # for the pygame method of drawing below, we need to determine the position on the screen as a tuple object pos = i * 10 + 50 # pygame method, takes display, colour, and positions of where the lines start and end. i.e, starts in (50,pos) ends in (450,pos), 1 at the end is the width of the line pygame.draw.line(display, line_colour, (50, pos), (450, pos), 1) # same as above but takes pos as y, by doing so and iterating through the range, you cover all the plane pygame.draw.line(display, line_colour, (pos, 50), (pos, 450), 1) i = 0 # index determining for data structure, taking it back to zero for line in lines: # iterating through lines which is a global variable for the priority queue aka eventQueue ''' having [i] next to colour allows me to colour each line differently each line has tuple object in the global variable line[0] accesses the nth item's first coordinates in the iteration and drawing ends in the line[1], nth item's second object ''' pygame.draw.line(display, colours[i], line[0], line[1], 1) # calling the addText function that was created before in the script hlp.AddText(line_name[i], line[0]) ''' nested indexing, as I am accessing the first item of the first item in the line object which is in the lines global variable result of this nested indexing should access a point of x- coordinated saved in a tuple ''' if x == line[0][0]: # if that begining point of the line's x coordinates equals to the preset x, then append the queue list with the name of this line eventQueue.append(line_name[i]) if x == line[1][0]: # again the nested indexing # removes the line from the queue if the end of the line's x coordinates equals to x variable eventQueue.remove(line_name[i]) # increasing the index number at the end of the iteration loop so I can access the other items saved i += 1 if stop == True: # tells to stop if stop is clicked run = False # turns off the run, if it is stop, then run must be false x = 50 # set x to default # if I don't make the stop false at the end of this clause, there would be a logic error as stop must be false after it was used otherwise, it will be true forever stop = False if run == True: # tells it to start if run is clicked cursor = False # when it is running cursor can't draw any newlines randomLine = False # again no new random lines too x += 1 # since I am scanning, the x value should scan the screen pixel after pixel, thus, adding 1 to the x value # this draws the scan line on the screen pygame.draw.line(display, hlp.red, (x, 50), (x, 450), 1) # j and k are placeholders to keep track of the index j = 0 k = 0 # iterating through points to draw the intersection circle in the run for point in points: # if the first item's x value is smaller or equal to the present x variable if point[0] <= x: # use this pygame method to draw a small circle where the lines intersect pygame.draw.circle(display, hlp.white, point, 3) k += 1 # increase the placeholders value if point[0] == x: # if x value is already equal to the preset x # then append the orderList with the name of the intersection orderList.append(intersect_name[j]) j += 1 # increase the j once more if k > 0: # so it means there is already an intersection n = len(lines) # check how many lines were drawn already if n > 0: # if the number of lines are more than 0, it means that there are existing lines # measure the algorithm's speed efficiency = (n + k) * math.log10(n) ''' since the display stars from 50th pixel, I substract 50 from that, and the script uses //8 as divide without remainers to convert the x values pixel to coordinates this is so it can be used to name the incident of intersection ''' c = (x - 50) // 8 # adding the text as well for the intersection hlp.AddText("(X, Y) = (" + str(c) + ", 0)", (200, 470), (255, 255, 255)) if cursor == True: # arrange the mouse cursors pygame.mouse.set_visible(False) pos = pygame.mouse.get_pos() # this is a pygame method for mouse cursor # the cursor with the existing pointer image, pygame method called display.blit which adds a spirit to the screen display.blit(pointer, pos) # if you clicked on the screen, this checks the number of clicks and starts drawing if len(clickedPos) > 0: # again pygame method to draw, if clicked then draw this pygame.draw.circle(display, hlp.white, clickedPos[0], 2) # if clicked then draw this pygame.draw.line(display, hlp.white, clickedPos[0], pos, 1) if len(clickedPos) >= 2: # if the cursor is in a positon which is longer than 2 that can draw lines, if you clicked on more or equal to 2 times, which means begining and end for the lines # then add lines according to the points saved in the clickedPos object. [0] is the begining index and clickedPos[1] is the ending index. AddNewLine([clickedPos[0], clickedPos[1]]) cursor = False # disable the cursor after drawing clickedPos = [] # empty the placeholder after drawing the line else: # now you are entering into the scene of mouse action # again pygame GUI method enabling mouse action on the screen to interact pygame.mouse.set_visible(True) if randomLine == True: # if mouse clicked on the randomline GenerateRandomLine() # then create a random line, calling the existing function randomLine = False # turn it off after drawing so it would not keep drawing forever randomTimer = False # and stop the timer so it won't go forever if run == True and x > 450: # if run function is enabled however the x value is out of the screen x = 50 # put x back to the default of 50 run = False # and disable the run if clear == True: # clear action is enabled, clear back all the placeholders to default lines = [] # everything is back to the default value colours = [] # everything is back to the default value points = [] # everything is back to the default value orderList = [] # everything is back to the default value efficiency = 0 # everything is back to the default value eventQueue = [] # everything is back to the default value intersect_name = [] # everything is back to the default value line_name = [] # everything is back to the default value x = 50 # everything is back to the default value run = False # everything is back to the default value clear = False # everything is back to the default value ''' adding text positions and texts for the frame calling existing functions, giving text, position and when applicable the action my helper functions are button and addtext that help me in my larger script ''' # adding text positions and texts for the frame hlp.AddText("(0,0)", (30, 25)) hlp.AddText("(50,0)", (430, 25)) hlp.AddText("(0,50)", (30, 450)) hlp.AddText("(50,50)", (430, 450)) # drawing buttons and determining positions hlp.Button("Run", 80, 5, 100, 35, RunActive) hlp.Button("Stop", 200, 5, 100, 35, StopActive) hlp.Button("Clear", 320, 5, 100, 30, ClearActive) hlp.Button("Random Segment", 50, 500, 180, 30, RandomActive) hlp.Button("Insert Segment", 280, 500, 180, 35, CursorActive) hlp.Button("Exit", 500, 5, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 900, 5, 100, 30, 1) if back > 0: # if back has a value, which means it has been clicked, stop the bigger loop that we started, i.e. the game loop, and break the game loop break # calls the helper function nxt = hlp.ButtonWithReturn("Next", 700, 5, 100, 30, 1) if nxt > 0: # so if the next button is clicked # calls for the description function hlp.Description(dsb.bo_desc) text = ["If you are learning to play, it is recommended", # and displays this text "you chose your own starting area."] # pygame method to draw an object pygame.draw.rect(display, line_colour, [500, 50, 750, 490], 2) # adding the text on the given location hlp.AddText("Bentley-Ottmann Algorithm", (520, 70)) # adding the text on the given location hlp.AddText("Event Queue:", (520, 120)) # creating indexing i and x, y positions to display on the GUI, this is an important way to assign values to a tuplae object i, o_x, o_y = 0, 540, 150 ''' iterating through the existing values in the eventQueue because we don't want the texts to overlap on the screen most of the numbers below are finetuning to prevent overlapping of the texts for the order list and the eventqueue list ''' for val in eventQueue: # val is each text saved in the eventQueue, and these values are not to overlap on the screen hlp.AddText(val, (o_x, o_y), (255, 255, 255)) o_x += 30 # therefore for each value, I'm adding +30 for each one i += 1 # adding one to the index to access to the next item if i % 23 == 0: # 23rd item appears on the righest point on the screen so for the next one you need to go on the y axis o_x = 540 # text is on the edge, there no more horizontol space # text needs to appear on the next line, so adding 20 onto the y axis, vertical move o_y += 20 hlp.AddText("Order List:", (520, 200)) # adding the text i, o_x, o_y = 0, 540, 230 for val in orderList: # same as above iteration but for the order list this time hlp.AddText(val, (o_x, o_y), (255, 255, 255)) o_x += 50 # adding to x axis i += 1 # increasing the index if i % 14 == 0: # this is 14, because the text has less horizontal space to appear. o_x = 540 # reached the end of the line o_y += 20 # go to the next line, move vertical, thus adding to the y value # adding the text on the given location hlp.AddText("Efficiency O((n+k)logn):", (520, 480)) # adding the text on the given location hlp.AddText(str(efficiency), (540, 505), (255, 255, 255)) # updates the screen every turn pygame.display.flip() # will not run more than 30 frames per second clock.tick(30) intro.Introduction2() # calls back the introduction function def ShamosHoeyMain(): ''' this function is the Shamos-Hoey Algorithm function with main display loop ''' global cursor, lines, colours, points, randomLine, randomTimer, run, stop, clear, intersect_name global display, line_name # first the lines are accessing necessary global variables pygame.display.set_caption("Shamos-Hoey Algorithm") # adding a caption # setting the display for the algorithm display = pygame.display.set_mode((1280, 550), pygame.FULLSCREEN) cursor = False # until while true line, which is the main loop, lines below creating the default values randomLine = False # again the default placeholder for the randomline clickedPos = [] # default place holder value for position firstPoint = None # first intersection point identified efficiency = 0 # default place holder value for algorithm efficieny eventQueue = [] # event queue place holder, empty now run = False x = 50 # location of the x value on the screen back = 0 # if this becomes one, you go back while True: # starting the game loop # pygame method to fill the screen, takes colours and a display object display.fill((0, 0, 0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting # Here is to tell the computer to recognise if a keybord key is pressed. if event.type == pygame.KEYUP: if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. ''' if mouse clicked on the below coordinates, create a line pygame GUI property detecting when mouse click is on MOUSEBUTTONDOWN and MOUSEBUTTONUP should be used as a small loops so that the computer can understand when that instance of the mouse movement is over ''' if cursor == True and event.type == pygame.MOUSEBUTTONDOWN: if event.button == 1: # pygame method defining the button in the GUI mouse_pos = pygame.mouse.get_pos() # displays the mouse position on the screen # pygame property pos[0] is the mouse cursor in the X axis and pos[1] is the Y axis if 50 < pos[0] < 450 and 50 < pos[1] < 450: # here it adds the clicked postion corresponding to the positon of the mouse clickedPos.append(pos) if event.type == pygame.MOUSEBUTTONUP: randomTimer = True # turning the random from false to true so the timer can activate for i in range(0, 41): # choosing coordinates for drawing, exiting the previous iteration, range (0,41) goes between 0 and 40 # for the pygame method of drawing below, we need to determine the position on the screen as a tuple object pos = i * 10 + 50 # pygame method, takes display, colour, and positions of where the lines start and end. i.e, starts in (50,pos) ends in (450,pos), 1 at the end is the width of the line pygame.draw.line(display, line_colour, (50, pos), (450, pos), 1) # same as above but takes pos as y, by doing so and iterating through the range, you cover all the plane pygame.draw.line(display, line_colour, (pos, 50), (pos, 450), 1) i = 0 # index determining for data structure, taking it back to zero for line in lines: # iterating through lines which is a global variable for the priority queue aka eventQueue ''' having [i] next to colour allows me to colour each line differently each line has tuple object in the global variable line[0] accesses the nth item's first coordinates in the iteration and drawing ends in the line[1], nth item's second object ''' pygame.draw.line(display, colours[i], line[0], line[1], 1) # calling the addText function that was created before in the script hlp.AddText(line_name[i], line[0]) ''' nested indexing, as I am accessing the first item of the first item in the line object which is in the lines global variable result of this nested indexing should access a point of x- coordinated saved in a tuple ' ''' if x == line[0][0]: # if that begining point of the line's x coordinates equals to the preset x, then append the queue list with the name of this line eventQueue.append(line_name[i]) if x == line[1][0]: # again the nested indexing # removes the line from the queue if the end of the line's x coordinates equals to x variable eventQueue.remove(line_name[i]) # increasing the index number at the end of the iteration loop so I can access the other items saved i += 1 if stop == True: # tells to stop if stop is clicked run = False # turns off the run, if it is stop, then run must be false x = 50 # set x to default # if I don't make the stop false at the end of this clause, there would be a logic error as stop must be false after it was used otherwise, it will be true forever stop = False eventQueue = [] # empties the eventQueue if run == True: # tells it to start if run is clicked cursor = False # when it is running cursor can't draw any newlines randomLine = False # again no new random lines too x += 1 # since I am scanning, the x value should scan the screen pixel after pixel, thus, adding 1 to the x value # this draws the scan line on the screen pygame.draw.line(display, hlp.red, (x, 50), (x, 450), 1) # iterating through points to draw the intersection circle in the run for point in points: # if the first item's x value is smaller or equal to the present x variable if point[0] == x: firstPoint = point # having a designated first point variable run = False # setting variables to default. x = 50 # setting variables to default. eventQueue = [] # setting variables to default. efficiency = 0 # setting variables to default. break # break the loop n = len(lines) # number of existing lines if n > 0: # if the number of lines are more than 0, it means that there are existing lines efficiency = n * math.log10(n) # measure the algorithm's speed ''' since the display stars from 50th pixel, I substract 50 from that, and the script uses //8 as divide without remainers to convert the x values pixel to coordinates this is so it can be used to name the incident of intersection ''' c = (x - 50) // 8 # adding the text as well for the intersection hlp.AddText("(X, Y) = (" + str(c) + ", 0)", (200, 470), hlp.white) # adding the intersection if firstPoint != None: # if there is a first point # use this pygame method of drawing a circle. pygame.draw.circle(display, hlp.white, firstPoint, 3) if cursor == True: # arrange the mouse cursors pygame.mouse.set_visible(False) pos = pygame.mouse.get_pos() # this is a pygame method for mouse cursor # the cursor with the existing pointer image, pygame method called display.blit which adds a spirit to the screen display.blit(pointer, pos) # if you clicked on the screen, this checks the number of clicks and starts drawing if len(clickedPos) > 0: pygame.draw.circle(display, hlp.white, clickedPos[0], 2) # if clicked then draw this pygame.draw.line(display, hlp.white, clickedPos[0], pos, 1) if len(clickedPos) >= 2: # if the cursor is in a positon which is longer than 2 that can draw lines, if you clicked on more or equal to 2 times, which means begining and end for the lines # then add lines according to the points saved in the clickedPos object. [0] is the begining index and clickedPos[1] is the ending index. AddNewLine([clickedPos[0], clickedPos[1]]) cursor = False # disable the cursor after drawing clickedPos = [] # empty the placeholder after drawing the line else: # now you are entering into the scene of mouse action # again pygame GUI method enabling mouse action on the screen to interact pygame.mouse.set_visible(True) if randomLine == True: # if mouse clicked on the randomline GenerateRandomLine() # then create a random line, calling the existing function randomLine = False # turn it off after drawing so it would not keep drawing forever randomTimer = False # and stop the timer so it won't go forever if run == True and x > 450: # if run function is enabled however the x value is out of the screen x = 50 # put x back to the default of 50 run = False # and disable the run if clear == True: # clear action is enabled, clear back all the placeholders to default lines = [] # everything is back to the default value colours = [] # everything is back to the default value points = [] # everything is back to the default value efficiency = 0 # everything is back to the default value firstPoint = None # everything is back to the default value eventQueue = [] # everything is back to the default value intersect_name = [] # everything is back to the default value line_name = [] # everything is back to the default value x = 50 # everything is back to the default value run = False # everything is back to the default value clear = False # everything is back to the default value ''' adding text positions and texts for the frame calling existing functions, giving text, position and when applicable the action my helper functions are button and addtext that help me in my larger script. ''' # adding text positions and texts for the frame hlp.AddText("(0,0)", (30, 25)) hlp.AddText("(50,0)", (430, 25)) hlp.AddText("(0,50)", (30, 450)) hlp.AddText("(50,50)", (430, 450)) # drawing buttons and determining positions hlp.Button("Run", 80, 5, 100, 35, RunActive) hlp.Button("Stop", 200, 5, 100, 35, StopActive) hlp.Button("Clear", 320, 5, 100, 30, ClearActive) hlp.Button("Random Segment", 50, 500, 180, 30, RandomActive) hlp.Button("Insert Segment", 280, 500, 180, 35, CursorActive) hlp.Button("Exit", 500, 5, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 900, 5, 100, 30, 1) if back > 0: # if back has a value, which means it has been clicked, stop the bigger loop that we started, i.e. the game loop, and break the game loop break # calls the helper function nxt = hlp.ButtonWithReturn("Next", 700, 5, 100, 30, 1) if nxt > 0: # so if the next button is clicked # calls for the description function hlp.Description(dsb.sh_desc) # pygame method to draw an object pygame.draw.rect(display, line_colour, [500, 50, 750, 490], 2) # adding caption, frame size, texts, buttons and their positions # adding the text on the given location hlp.AddText("Shamos-Hoey Algorithm", (520, 70)) # adding the text on the given location hlp.AddText("Event Queue:", (520, 120)) # creating indexing i and x, y positions to display on the GUI, this is an important way to assign values to a tuplae object i, o_x, o_y = 0, 540, 150 ''' iterating through the existing values in the eventQueue. because we don't want the texts to overlap on the screen most of the numbers below are finetuning to prevent overlapping of the texts for the order list and the eventqueue list. ''' for val in eventQueue: # val is each text saved in the eventQueue, and these values are not to overlap on the screen # calling the helper function. hlp.AddText(val, (o_x, o_y), hlp.white) o_x += 30 # adding 30 to the x-axis for each item. i += 1 # adding one to the index to access to the next item if i % 23 == 0: # 23rd item appears on the righest point on the screen so for the next one you need to go on the y axis o_x = 540 # text is on the edge, there no more horizontol space # text needs to appear on the next line, so adding 20 onto the y axis, vertical move o_y += 20 # go to the next line by adding 20 to the y axis # adding the text on the given location hlp.AddText("Efficiency O(nlogn):", (520, 200)) # adding the text on the given location hlp.AddText(str(efficiency), (540, 230), hlp.white) # updates the screen every turn pygame.display.flip() # will not run more than 30 frames per second clock.tick(30) intro.Introduction2() # calls back the introduction function def Efficiency(): ''' this function compares the efficiency of the algorithms ''' pygame.display.set_caption("Efficiency Comparison") display = pygame.display.set_mode( (1280, 550), pygame.FULLSCREEN | pygame.DOUBLEBUF) n = 0 # number segment k = 0 # intersection posX1 = 180 # position to appear posX2 = 400 # position to appear posY = 20 # position to appear bPos = 450 # position to appear bo = 0 # bentley-ottmann placeholders bf = 0 # brute-force placeholders sh = 0 # shamos-hoey placeholders bog = 0 # bentley-Ottman placeholders bfg = 0 # brute-force placeholders shg = 0 # shamos-hoey placeholders while True: # starting the initial loop with first game events, ie. quit and mouse button # starting the initial loop with first game events, ie. quit and mouse button display.fill((0, 0, 0)) # display.blit(hlp.dscbg,(0,0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event # again iterating as an important pygame method to set the features. for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting # Here is to tell the computer to recognise if a keybord key is pressed. if event.type == pygame.KEYUP: if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. # starting the initial loop with first game events, i.e. quit and mouse button if event.type == pygame.MOUSEBUTTONDOWN: if event.button == 1: # pygame method defining the button in the GUI pos = pygame.mouse.get_pos() # displays the mouse position on the screen # starting the initial loop with first game events, ie. quit and mouse button if posX1 < pos[0] < posX1 + 130 and posY < pos[1] < posY + 60: # getting the number of lines lineTxt = hlp.InsertNumber("Line Number:") if lineTxt != "": # if the string is not empty try: # input gives string so this one turns it into an integer n = int(lineTxt) except: # if that is not happening n = 0 # make n equals to zero, this is a error-handling method by managing the possible error by wrong input, i.e. linetxt can't be converted to an integer # same as above but for the intersect number elif posX2 < pos[0] < posX2 + 170 and posY < pos[1] < posY + 60: intersectTxt = hlp.InsertNumber("Intersect Number :") if intersectTxt != "": try: k = int(intersectTxt) except: k = 0 if n > 0: # using established algorithm efficiency calculation for every algorithm bo = int((n + k) * math.log10(n)) bog = bo # number to be used in the graph string # using established algorithm efficiency calculation for every algorithm bf = int(n * n) bfg = bf # number to be used in the graph string # using established algorithm efficiency calculation for every algorithm sh = int(n * math.log10(n)) shg = sh # number to be used in the graph string if bo > 350 or bf > 350 or sh > 350: # multiply by 350 for later on to use for rectangle object below m = max(bo, bf, sh) bo = int((bo / m) * 350) bf = int((bf / m) * 350) sh = int((sh / m) * 350) if bo == 0: # handling zeros for graphs below bo = 1 # handling zeros for graphs below if bf == 0: # handling zeros for graphs below bf = 1 # handling zeros for graphs below if sh == 0: # handling zeros for graphs below sh = 1 # handling zeros for graphs below # setting the texts and buttons hlp.Button("Insert Line", posX1, posY, 130, 30, None) hlp.Button("Insert Intersect", posX2, posY, 160, 30, None) hlp.AddText("Line: " + str(n), (600, 20), hlp.white) hlp.AddText("Intersect: " + str(k), (600, 50), hlp.white) hlp.AddText("BF", (180, 460), hlp.white) hlp.AddText("BO", (330, 460), hlp.white) hlp.AddText("SH", (480, 460), hlp.white) # pygame method, takes display, colour, and positions of where the lines start and end pygame.draw.line(display, line_colour, (100, 100), (100, 500), 2) # pygame method, takes display, colour, and positions of where the lines start and end pygame.draw.line(display, line_colour, (50, 450), (650, 450), 2) if bf > 0: # comparing here which one is better, if bf exists # comparing here which one is better hlp.AddText(str(bfg), (165, bPos - bf - 30), hlp.white) pygame.draw.rect(display, hlp.button_colour, (165, bPos - bf, 50, bf) ) # drawing a rectangular bar on the screen if bo > 0: # comparing here which one is better, if bo exists # comparing here which one is better hlp.AddText(str(bog), (315, bPos - bo - 30), hlp.white) pygame.draw.rect(display, hlp.button_colour, (315, bPos - bo, 50, bo) ) # drawing a rectangular bar on the screen if sh > 0: # comparing here which one is better, if sh exists # comparing here which one is better hlp.AddText(str(shg), (465, bPos - sh - 30), hlp.white) # drawing a rectangular bar on the screen. # bPos- algorithm name determines the rectangle's dimensions pygame.draw.rect(display, hlp.button_colour, (465, bPos - sh, 50, sh)) # setting and drawing the next/back buttons hlp.Button("Exit", 350, 500, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 650, 500, 100, 30, 1) if back > 0: break nxt = hlp.ButtonWithReturn("Next", 500, 500, 100, 30, 1) if nxt > 0: hlp.Description(dsb.effic_desc) pygame.display.flip() # updates the screen every turn clock.tick(60) # will not run more than 15 frames per second intro.Introduction2() # calls back the introduction function def Efficiency2(): ''' this function compares the efficiency of the algorithms ''' pygame.display.set_caption("Efficiency Comparison") display = pygame.display.set_mode( (1280, 550), pygame.FULLSCREEN | pygame.DOUBLEBUF) n = range(10, 1001) # number segment bet = False posX1 = 180 # position to appear posX2 = 400 # position to appear posY = 20 # position to appear bPos = 450 # position to appear sheffc = [i * math.log10(i) for i in n] # it is a list comprehension method for sh algoritm efficiency. bfeffc = [i**2 for i in n] # it is a list comprehension method for bf algoritm efficiency. boeffc = [((i + (((i**2) - i) / 2)) * math.log10(i)) for i in n] # it is a list comprehension method for bo algoritm efficiency. topalg = sheffc + bfeffc + boeffc # here compiles all efficency into one list mx = max(topalg) # getting the max value from the list mn = min(topalg) # getting the min value from the list transsheffc = [TransValue(i, mx, mn) for i in sheffc] #here it starts a list comprehension to normalize the values for across three efficiencies transshefc2 = random.sample(transsheffc, 550) #then getting 550 values to represent equally across the pixels transshefc2.sort() # sorting in descending order shno = 0 #starting an index for iteration shpoints = [] #placeholder value for i in transshefc2[:200]: #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. shpoints.append((100 + shno, 450 - int(i))) #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. shno += 1 #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. for i in transshefc2[200:349]: #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. shpoints.append((100 + shno, 450 - (int(i + 2)))) #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. shno += 1 #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. for i in transshefc2[349:]: #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. shpoints.append((100 + shno, 450 - (int(i + 4)))) #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. shno += 1 #here it uses indexing and iteration for creating display pixel points for sh algoritm. First one is the x value, other one is y value. transbfeffc = [TransValue(i, mx, mn) for i in bfeffc] # between lines 910 and 917, same as above but for bf algoritm transbfeffc2 = random.sample(transbfeffc, 550) transbfeffc2.sort() bfno = 0 bfpoints = [] for i in(transbfeffc2): bfpoints.append((100 + bfno, 450 - int(i))) bfno += 1 transboeffc = [TransValue(i, mx, mn) for i in boeffc] # between lines 919 and 926, same as above but for bo algoritm transboeffc2 = random.sample(transboeffc, 550) transboeffc2.sort() bono = 0 bopoints = [] for i in(transboeffc2): bopoints.append((100 + bono, 450 - int(i))) bono += 1 while True: # starting the initial loop with first game events, ie. quit and mouse button # starting the initial loop with first game events, ie. quit and mouse button display.fill((0, 0, 0)) # display.blit(hlp.dscbg,(0,0)) # pygame method, iterates over the events in pygame to determine what we are doing with every event # again iterating as an important pygame method to set the features. for event in pygame.event.get(): if event.type == pygame.QUIT: # this one quits pygame.quit() # putting the quit pygame method exit() # takes the user from GUI to the script for exiting # Here is to tell the computer to recognise if a keybord key is pressed. if event.type == pygame.KEYUP: if event.key == pygame.K_ESCAPE: # if that keyboard key is ESC exit() # call for the exit function. # starting the initial loop with first game events, i.e. quit and mouse button if event.type == pygame.MOUSEBUTTONDOWN: if event.button == 1: # pygame method defining the button in the GUI pos = pygame.mouse.get_pos() # displays the mouse position on the screen # starting the initial loop with first game events, ie. quit and mouse button if posX2 < pos[0] < posX2 + 170 and posY < pos[1] < posY + 60: bet = True hlp.Button("Start", posX2, posY, 160, 30, None) hlp.AddText("Lines: 10, 100, 1000", (600, 20), hlp.white) hlp.AddText("10", (115, 460), hlp.white) hlp.AddText("100", (350, 460), hlp.white) hlp.AddText("1000", (650, 460), hlp.white) hlp.AddText("max", (50, 100), hlp.white) hlp.AddText("0", (50, 460), hlp.white) sidefont = pygame.font.Font(bitterfont, 16) sidetext = sidefont.render("Algorithm Efficiency", True, hlp.white) sidetext = pygame.transform.rotate(sidetext, 90) display.blit(sidetext, (70, 235)) # pygame method, takes display, colour, and positions of where the lines start and end pygame.draw.line(display, line_colour, (100, 100), (100, 500), 2) # pygame method, takes display, colour, and positions of where the lines start and end pygame.draw.line(display, line_colour, (50, 450), (650, 450), 2) if bet: pygame.draw.lines(display, (62, 150, 81), False, bfpoints, 4) pygame.draw.lines(display, (255, 255, 0), False, shpoints, 4) pygame.draw.lines(display, (255, 0, 0), False, bopoints, 4) hlp.AddText("Brute Force", (750, 150), hlp.white) hlp.AddText("Bentley-Ottmann", (750, 250), hlp.white) hlp.AddText("Shamos-Hoey", (750, 350), hlp.white) pygame.draw.line(display, (62, 150, 81), (720, 160), (740, 160), 4) pygame.draw.line(display, (255, 0, 0), (720, 260), (740, 260), 4) pygame.draw.line(display, (255, 255, 0), (720, 360), (740, 360), 4) hlp.AddText("n=10;100;1000", (720, 390), hlp.white) hlp.AddText("Brute Force = " + str(round(bfeffc[9])) + "; " + str( round(bfeffc[499])) + "; " + str(round(bfeffc[989])), (720, 405), hlp.white) hlp.AddText("Bentley-Ottmann = " + str(round(boeffc[9])) + "; " + str( round(boeffc[499])) + "; " + str(round(boeffc[989])), (720, 420), hlp.white) hlp.AddText("Shamos-Hoey = " + str(round(sheffc[9])) + "; " + str( round(sheffc[499])) + "; " + str(round(sheffc[989])), (720, 435), hlp.white) hlp.Button("Exit", 350, 500, 100, 30, sys.exit) back = hlp.ButtonWithReturn("Back", 650, 500, 100, 30, 1) if back > 0: break nxt = hlp.ButtonWithReturn("Next", 500, 500, 100, 30, 1) if nxt > 0: hlp.Description(dsb.effic_desc) pygame.display.flip() # updates the screen every turn clock.tick(60) # will not run more than 15 frames per second intro.Introduction2() # calls back the introduction function def AddNewColour(): ''' this function selects random colours and appends the global colours variable used for adding random colour to each line ''' global colours # accessing the variable r = random.randrange(1, 255) # choosing the red tone g = random.randrange(1, 255) # choosing the green tone b = random.randrange(1, 255) # choosing the blue tone randomColour = pygame.Color(r, g, b) # appointing the colour colours.append(randomColour) # appending the global variable def AddNewLine(newLine): ''' this function adds a new line to the list it iterates through the lines list item and checks whether they intersect if so, it appoints a name for the intersecting lines and appends the intersect lines list ''' global lines, line_name, intersect_name name = str(1 + len(lines)) # appointing a name i = 0 # appointing default index for the coming iteration below for line in lines: # checking whether new line and existing line intersect status = CheckIntersect(newLine[0], newLine[1], line[0], line[1]) if status: intsec_name = line_name[i] + "." + name # appointing a name intersect_name.append(intsec_name) # appending the list i += 1 # increasing the index by one l = newLine # indexing the newline's points and sorting from start to end in the next line if(newLine[0][0] > newLine[1][0]): l = [newLine[1], newLine[0]] lines.append(l) # appending the new line line_name.append(name) # appending the name of the new line. AddNewColour() ChangeColour() def ChangeColour(): ''' this function changes the line colours to white for the brute force algorithm it iterates through the different lines and appoints a new colour for each line ''' global intersect_name, colours, brutecolours brutecolours = colours[:] # copies the colours variable for name in intersect_name: # iterates through the items sp = name.split(".") # splits the string object # appoints each splitted names to converted integer objects n1 = int(sp[0]) n2 = int(sp[1]) brutecolours[n1 - 1] = hlp.white # making them white brutecolours[n2 - 1] = hlp.white # making them white def CursorActive(): ''' acessing and activating the cursor image to be used this is for when the user wishes to draw their own line segments ''' global cursor cursor = True # activating the cursor def RandomActive(): ''' accessing the existing global variables of random timer and lines if random timer is on create random lines this activates the action for the button, i.e. it gives the action to the button ''' global randomLine, randomTimer if randomTimer == True: # if random timer is on randomLine = True # create the random lines def RunActive(): ''' empities the orderlist and runs the system with the button click ''' global run, orderList run = True orderList = [] # empties the list object def StopActive(): ''' stops the system when stop button is clicked ''' global stop stop = True def ClearActive(): ''' clears existing system ''' global clear clear = True # activate flag for introduction menu def StartGame(): global start # access the global variable start = True # enable it

56.279425

200

0.61765

0

34,756

0.554862

544732e628a00b56caac8c9cd412468f1e74169a

8,514

py

Python

iologik/e2210.py

shannon-jia/iologik

bda254ee1cdb3f4d724fbb9d6fe993257f1cce52

[ "MIT" ]

null

iologik/e2210.py

shannon-jia/iologik

bda254ee1cdb3f4d724fbb9d6fe993257f1cce52

[ "MIT" ]

null

iologik/e2210.py

shannon-jia/iologik

bda254ee1cdb3f4d724fbb9d6fe993257f1cce52

[ "MIT" ]

null

import aiohttp import asyncio import async_timeout import logging from collections import namedtuple, deque from .events import Events from html.parser import HTMLParser log = logging.getLogger(__name__) class Parser(HTMLParser): def handle_starttag(self, tag, attrs): log.debug("Encountered a start tag: {}".format(tag)) def handle_endtag(self, tag): log.debug("Encountered an end tag : {}".format(tag)) def handle_data(self, data): log.debug("Encountered some data : {}".format(data)) if self.callback: self.callback(data) def set_callback(self, callback): self.callback = callback class E2210(object): ''' Moxa iologik E2210 module 12 inputs and 8 outputs ''' MAX_INPUTS = 12 MAX_OUTPUTS = 8 GET_PATH = 'getParam.cgi' SET_PATH = 'setParam.cgi' SYS_INFO = ['DATE', 'TIME', 'IP', 'LOC', 'DESC', 'FWR_V', 'MOD_NAME', 'SN_NUM', 'MAC_ADDR'] def __init__(self, loop, url=None, events=None, line=0, addr=1, handle_events=None): self.loop = loop or None self.url = url self.line = line self.addr = addr self.events = events or Events() self.parser = Parser() self.parser.set_callback(self.received) self.handle_events = handle_events self.connection = None self.changed = True self.fail = True self.command = namedtuple('Command', 'name method params completed') self.setting = {'System': {}, 'DIMode': ['DI' for i in range(self.MAX_INPUTS)], 'DIStatus': [0 for i in range(self.MAX_INPUTS)], 'DIFilter': [200 for i in range(self.MAX_INPUTS)], 'DOMode': ['DO' for i in range(self.MAX_OUTPUTS)], 'DOStatus': [1 for i in range(self.MAX_OUTPUTS)] } self.CMDS = { 'get_sys_info': ('get', '&'.join(['{}=?'.format(i) for i in self.SYS_INFO])), 'get_di_mode': ('get', '&'.join(['DIMode_{:02d}=?'.format(i) for i in range(self.MAX_INPUTS)])), 'set_di_mode': ('set', '&'.join(['DIMode_{:02d}=0'.format(i) for i in range(self.MAX_INPUTS)])), 'get_di_status': ('get', '&'.join(['DIStatus_{:02d}=?'.format(i) for i in range(self.MAX_INPUTS)])), 'set_di_filter_low': ('set', '&'.join(['DIFilter_{:02d}={}'.format(i, self.setting['DIFilter'][i]) for i in range(0, self.MAX_OUTPUTS//2)])), 'set_di_filter_high': ('set', '&'.join(['DIFilter_{:02d}={}'.format(i, self.setting['DIFilter'][i]) for i in range(self.MAX_OUTPUTS//2, self.MAX_OUTPUTS)])), 'get_do_mode': ('get', '&'.join(['DOMode_{:02d}=?'.format(i) for i in range(self.MAX_OUTPUTS)])), 'set_do_mode': ('set', '&'.join(['DOMode_{:02d}=0'.format(i) for i in range(self.MAX_OUTPUTS)])), 'get_do_status': ('get', '&'.join(['DOStatus_{:02d}=?'.format(i) for i in range(self.MAX_OUTPUTS)])), 'set_do_status': ('set', '&'.join(['DOStatus_{:02d}=1'.format(i) for i in range(self.MAX_OUTPUTS)])), } self.cmd_deque = deque() for name in self.CMDS: self.append_cmd(name) # start to poll http server self.restart_poll() def poll(self): pass def do_output(self, addr, which, action, deadtime): if which >= self.MAX_OUTPUTS or which < 0: return status = (action == 'Activate' and 0 or 1) params = 'DOStatus_{:02d}={}'.format(which, status) self.cmd_deque.appendleft(self.command('do_outputs', 'set', params, False)) def append_cmd(self, cmd_name=None): cmd = self.CMDS.get(cmd_name) if cmd: self.cmd_deque.append(self.command(cmd_name, cmd[0], cmd[1], False)) def received(self, data): log.debug("Encountered some data : {}".format(data)) l = data.split('=') if len(l) != 2: return reg = l[0] val = l[1] if reg in self.SYS_INFO: self.setting['System'][reg] = val elif reg.startswith('DIMode'): n = int(reg.split('_')[1]) if n < 0 or n >= self.MAX_INPUTS: return self.setting['DIMode'][n] = (val == '0' and 'DI' or 'COUNTER') elif reg.startswith('DIStatus'): n = int(reg.split('_')[1]) if n < 0 or n >= self.MAX_INPUTS: return self.setting['DIStatus'][n] = (val == '0' and 'ALARM' or 'NORMAL') event_type = 'Auxiliary Input' event = 'MXI_{}_{}_{}'.format(self.line, self.addr, n) condition = (val == '0' and True or False) self.events.append(event, event_type, condition) elif reg.startswith('DIFilter'): n = int(reg.split('_')[1]) if n < 0 or n >= self.MAX_INPUTS: return self.setting['DIFilter'][n] = int(val) elif reg.startswith('DOMode'): n = int(reg.split('_')[1]) if n < 0 or n >= self.MAX_OUTPUTS: return self.setting['DOMode'][n] = (val == '0' and 'DO' or 'PULSE') elif reg.startswith('DOStatus'): n = int(reg.split('_')[1]) if n < 0 or n >= self.MAX_OUTPUTS: return self.setting['DOStatus'][n] = (val == '0' and 'OFF' or 'ON') else: log.warn("Do not care it: {}".format(data)) def processor(self): if not self.events: return if callable(self.handle_events): return self.handle_events(self.events) else: log.warn('No master to processor {}'.format(self.events)) def restart_poll(self): asyncio.ensure_future(self.loop_polling()) async def _fetch(self, params, method='get'): endpoint = (method == 'get' and self.GET_PATH or self.SET_PATH) async with aiohttp.ClientSession() as session: with async_timeout.timeout(20): async with session.get('{}/{}?{}'.format(self.url, endpoint, params)) as response: if response.status >= 200 and response.status <= 300: self.parser.feed(await response.text()) async def _request(self): try: self.cmd = self.cmd_deque.popleft() except IndexError: self.append_cmd('get_di_status') self.append_cmd('get_do_status') self.cmd = self.cmd_deque.popleft() log.debug('Request: {}'.format(self.cmd.name)) x = await self._fetch(self.cmd.params, method=self.cmd.method) async def loop_polling(self): try: while True: try: await self._request() self.connection = True self.processor() except Exception as err: log.error("Cmd {} failed, with Error: {} " "Will retry in {} seconds" .format(self.cmd.name, err, 10)) self.connection = False if self.connection is not True: self.changed = True self.cmd_deque.append(self.cmd) self.fail = True await asyncio.sleep(10) else: self.changed = False self.fail = False log.info("{} Successfully requested. ".format(self.cmd.name)) # poll connection state every 1s await asyncio.sleep(0.5) except asyncio.CancelledError: self.connection = False except Exception as err: log.error("Failed to access http server with Error: {}".format(err)) self.connection = False

38.7

161

0.499765

8,301

0.974982

0

2,171

0.254992

1,355

0.15915

5448e80da68c244752c3380cbc4f039308ae3d65

7,009

py

Python

apps/cmdb/verify/operate.py

yanshicheng/super-ops

dd39fe971bfd0f912cab155b82e41a09aaa47892

[ "Apache-2.0" ]

null

apps/cmdb/verify/operate.py

yanshicheng/super-ops

dd39fe971bfd0f912cab155b82e41a09aaa47892

[ "Apache-2.0" ]

1

2022-01-17T09:34:14.000Z

2022-01-18T13:32:20.000Z

apps/cmdb/verify/operate.py

yanshicheng/super_ops

dd39fe971bfd0f912cab155b82e41a09aaa47892

[ "Apache-2.0" ]

null

from ..models import Classify, Fields, Asset, AssetBind, ClassifyBind from django.db.models import Q from collections import OrderedDict from django.forms.models import model_to_dict class OperateInstance: @staticmethod def get_classify(id): """通过ID 查找指定分类表""" return Classify.objects.filter(id=id).first() # 获取类型表的子表 @staticmethod def get_children_classify(p_tid): """通过主表ID 查找子分类表 pid=id""" children_classify = Classify.objects.filter(pid=p_tid) if children_classify: return children_classify return None @staticmethod def get_parent_classify_classify(pid): parent_classify_classify_obj = Classify.objects.filter(id=pid).first() if parent_classify_classify_obj: return parent_classify_classify_obj return None # parent_classify @staticmethod def get_parent_classify_bind(pid): """通过分类表主ID 查找关系绑定表数据""" parent_bind_obj = ClassifyBind.objects.filter(parent_classify_id=pid) if parent_bind_obj: return parent_bind_obj return None @staticmethod def get_child_classify_bind(cid): """通过 child_classify_id 获取表关系记录""" child_classify_obj = ClassifyBind.objects.filter(child_classify_id=cid) if child_classify_obj: return child_classify_obj return None @staticmethod def get_classify_bind(pid, cid): """根据 parent_classify_id 和 child_classify_id 返回分类关系表""" classify_bind_obj = ClassifyBind.objects.filter( parent_classify_id=pid, child_classify_id=cid ).first() if classify_bind_obj: return classify_bind_obj return None @staticmethod def get_abs_asset_bind(p_id, c_id): """根据 parent_asset_id child_asset_id 查询 asset_bind 记录""" asset_bind = AssetBind.objects.filter( parent_asset_id=p_id, child_asset_id=c_id ).first() if asset_bind: return asset_bind return None @staticmethod def get_asset_bind(t_id): """ 根据 classify_bind_id 查找资产绑定记录 """ asset_bind = AssetBind.objects.filter(classify_bind_id=t_id) if asset_bind: return asset_bind return None @staticmethod def get_parent_asset_bind(t_id, p_id): """根据表关系ID 主资产ID, 获取资产数据""" asset_bind = AssetBind.objects.filter( classify_bind=t_id, parent_asset_id=p_id ) if asset_bind: return asset_bind return None @staticmethod def get_child_asset_bind(t_id, c_id): """根据表关系ID 子资产ID 获取资产数据""" asset_bind = AssetBind.objects.filter( classify_bind_id=t_id, child_asset_id=c_id ) if asset_bind: return asset_bind return None @staticmethod def get_c_asset_bind(c_id): """根据子资产ID 获取资产数据""" asset_bind = AssetBind.objects.filter(child_asset_id=c_id) if asset_bind: return asset_bind return None # @staticmethod # def create_asset(c_id, *args): # asset_obj = Asset.objects.create(asset_key=get_md5(*args), classify_id_id=c_id) # asset_obj.save() # return asset_obj @staticmethod def get_asset(id): """根据 ID 获取资产记录""" asset_obj = Asset.objects.filter(id=id).first() if asset_obj: return asset_obj return None @staticmethod def get_classify_asset(id, cid): """根据分类表ID 资产表 ID 获取资产数据""" asset_obj = Asset.objects.filter(id=id, classify_classify_id=cid).first() if asset_obj: return asset_obj return None @staticmethod def get_all_asset(s_id): asset_all_obj = Asset.objects.filter(classify_id=s_id) if asset_all_obj: return asset_all_obj return None @staticmethod def get_classify_field(c_id): """根据分类表ID返回 fields 字段表""" field_obj = Fields.objects.filter(classify_id=c_id).first() if field_obj: return field_obj return None @staticmethod def get_all_field_map(c_id): field_all = Classify.objects.filter(id=c_id).values() if field_all: return field_all return None @staticmethod def get_asset_bind_exists(c_id): """查询 parent_asset_id 或者 child_asset_id 等于指定id的资产""" field_all = AssetBind.objects.filter( Q(parent_asset_id=c_id) | Q(child_asset_id=c_id) ) if field_all: return field_all return None @staticmethod def get_p_bind_asset(id, pid): """通过主资产ID 和分类ID 查询关联下所有的数据""" # 获取关联数据类型 classify_bind = OperateInstance.get_parent_classify_bind(pid) l_c = [] if classify_bind: for t_r in classify_bind: data = OrderedDict() asset_re_all = OperateInstance.get_parent_asset_bind(t_r.id, id) data['classify_name'] = t_r.child_classify.name data['classify_id'] = t_r.child_classify.id data['parent_classify_name'] = t_r.child_classify.pid.name data['fields'] = t_r.child_classify.fields.fields if asset_re_all: data['data'] = [model_to_dict(i.child_asset) for i in asset_re_all] else: data['data'] = [] l_c.append(data) return l_c return [] def get_c_bind_asset(id, cid): """通过子资产ID 和分类ID 查询关联下所有的数据""" # 查询到所有的关联表记录 classify_bind = OperateInstance.get_child_classify_bind(cid) l_c = [] if classify_bind: # 循环关联表记录 for t_r in classify_bind: asset_re_all = OperateInstance.get_child_asset_bind(t_r.id, id) if not asset_re_all: continue data = OrderedDict() data['classify_name'] = t_r.parent_classify.name data['classify_id'] = t_r.parent_classify.id data['parent_classify_name'] = t_r.parent_classify.pid.name data['fields'] = t_r.parent_classify.fields.fields if asset_re_all: data['data'] = [model_to_dict(i.parent_asset) for i in asset_re_all] else: data['data'] = [] l_c.append(data) return l_c return [] @staticmethod def get_p_classify_bind(pid): """ 根据主 classify_id 返回所有关联数据 """ parent_bind_obj = ClassifyBind.objects.filter(parent_classify_id=pid) if parent_bind_obj: return parent_bind_obj return [] def get_c_classify_bind(cid): """ 根据子 classify_id 返回所有关联数据 """ parent_bind_obj = ClassifyBind.objects.filter(child_classify_id=cid) if parent_bind_obj: return parent_bind_obj return []

31.859091

89

0.610786

7,309

0.975183

0

5,608

0.748232

0

1,465

0.195464

544b2254aa27aedc58e9f1dae64e313ac23e420d

525

py

Python

glass/mirror.py

fwcd/glass

eba5321753a41e4ebb28f6933ec554c104cb0f4c

[ "MIT" ]

2

2021-02-01T23:06:35.000Z

2022-01-12T15:39:30.000Z

glass/mirror.py

fwcd/glass

eba5321753a41e4ebb28f6933ec554c104cb0f4c

[ "MIT" ]

1

2022-03-18T04:07:58.000Z

2022-03-19T18:00:08.000Z

glass/mirror.py

fwcd/glass

eba5321753a41e4ebb28f6933ec554c104cb0f4c

[ "MIT" ]

null

import subprocess from pathlib import Path from urllib.parse import urlparse def mirror_repo(repo_url, target_dir): repo_dir = Path(str(target_dir) + urlparse(repo_url).path) repo_dir.parent.mkdir(parents=True, exist_ok=True) if repo_dir.exists(): print(f'Updating from {repo_url}...') subprocess.run(['git', 'remote', 'update'], cwd=str(repo_dir)) else: print(f'Mirroring from {repo_url}...') subprocess.run(['git', 'clone', repo_url, '--mirror'], cwd=str(repo_dir.parent))

35

88

0.67619

0

104

0.198095

544bbee47e78ee286a199342f8cffdd22f773ed2

3,880

py

Python

modeling/__init__.py

WinstonHuTiger/BOEMD-UNet

f81a0506b8b8a90fd783afcda61f28acb113fc77

[ "MIT" ]

2

2021-10-03T11:49:32.000Z

2021-12-15T11:40:52.000Z

modeling/__init__.py

WinstonHuTiger/BOEMD-UNet

f81a0506b8b8a90fd783afcda61f28acb113fc77

[ "MIT" ]

null

modeling/__init__.py

WinstonHuTiger/BOEMD-UNet

f81a0506b8b8a90fd783afcda61f28acb113fc77

[ "MIT" ]

null

import os import torch from modeling.unet import * from modeling.bAttenUnet import MDecoderUNet, MMultiBAUNet, MMultiBUNet def build_model(args, nchannels, nclass, model='unet'): if model == 'unet': return UNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p ) elif model == "batten-unet": return MDecoderUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, attention="attn" ) elif model == 'prob-unet': return ProbUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p ) elif model == 'multi-unet': return MultiUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p ) elif model == 'decoder-unet': return DecoderUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p ) elif model == "multi-bunet": return MMultiBUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p ) elif model == "multi-atten-bunet": return MMultiBAUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p ) elif model == 'attn-unet': return DecoderUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p, attention='attn' ) elif model == 'pattn-unet': return DecoderUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p, attention='prob', ) elif model == 'pattn-unet-al': return DecoderUNet( n_channels=nchannels, n_classes=nclass, bilinear=True, dropout=args.dropout, dropp=args.drop_p, attention='prob-al', ) elif model == 'battn-unet-one': return MDecoderUNet( n_channels=nchannels, # one head output n_classes=1, bilinear=True, attention="attn" ) else: raise NotImplementedError def build_transfer_learning_model(args, nchannels, nclass, pretrained, model='unet'): """ param args: param nclass: number of classes param pretrained: path to the pretrained model parameters """ # hard coded class number for pretained UNet on BraTS pre_model = UNet( n_channels=args.nchannels, n_classes=3, bilinear=True, dropout=args.dropout, dropp=args.drop_p ) if not os.path.isfile(pretrained): raise RuntimeError("no checkpoint found at {}".format(pretrained)) params = torch.load(pretrained) pre_model.load_state_dict(params['state_dict']) m = UNet( n_channels=args.nchannels, n_classes=nclass, bilinear=pre_model.bilinear, dropout=args.dropout, dropp=args.drop_p ) assert args.nchannels == pre_model.n_channels m.inc = pre_model.inc m.down1 = pre_model.down1 m.down2 = pre_model.down2 m.down3 = pre_model.down3 m.down4 = pre_model.down4 m.up1 = pre_model.up1 m.up2 = pre_model.up2 m.up3 = pre_model.up3 m.up4 = pre_model.up4 return m

27.51773

85

0.559794

0

422

0.108763

544c328461515102957fb6ba2f7ecaadd80e93ff

1,356

py

Python

A.py

JK-Incorporated/EYN-DOS

6dc331655b5fd04e6d37651ea79ac4e204bfd52e

[ "BSD-3-Clause" ]

null

A.py

JK-Incorporated/EYN-DOS

6dc331655b5fd04e6d37651ea79ac4e204bfd52e

[ "BSD-3-Clause" ]

null

A.py

JK-Incorporated/EYN-DOS

6dc331655b5fd04e6d37651ea79ac4e204bfd52e

[ "BSD-3-Clause" ]

null

import os from os import listdir from os.path import isfile, join dir_path = os.path.dirname(os.path.realpath(__file__)) filesys = [f for f in listdir(dir_path) if isfile(join(dir_path, f))] def get_dir_size(path=dir_path): total = 0 with os.scandir(dir_path) as it: for entry in it: if entry.is_file(): total += entry.stat().st_size elif entry.is_dir(): total += get_dir_size(entry.path) return total/1024 size=0 for path, dirs, files in os.walk(dir_path): for f in files: fp = os.path.join(path, f) size += os.path.getsize(fp) while True: command_lineA=input("A:\> ") if command_lineA==("B:"): print("") os.system("python3 B.py") print("") if command_lineA==("C:"): print("") os.system("python3 C.py") print("") if command_lineA==("D:"): print("") os.system("python3 D.py") print("") if command_lineA==("E:"): print("") os.system("python3 E.py") print("") if command_lineA==("dir"): print("") print("ERROR EYN_A1") print("") if command_lineA==("listdir"): print("") print("ERROR EYN_A1") print("") if command_lineA==("end"): print("") exit()

22.229508

69

0.526549

0

152

0.112094

544ec34dfb38023e11066f7adf551926d37772c9

3,111

py

Python

api_site/src/api_x/application/entry/bankcard_views.py

webee/pay

b48c6892686bf3f9014bb67ed119506e41050d45

[ "W3C" ]

1

2019-10-14T11:51:49.000Z

api_site/src/api_x/application/entry/bankcard_views.py

webee/pay

b48c6892686bf3f9014bb67ed119506e41050d45

[ "W3C" ]

null

api_site/src/api_x/application/entry/bankcard_views.py

webee/pay

b48c6892686bf3f9014bb67ed119506e41050d45

[ "W3C" ]

null

# coding=utf-8 from __future__ import unicode_literals from api_x.utils import response from api_x.utils.entry_auth import verify_request from flask import request from . import application_mod as mod from .. import dba from .. import bankcard from api_x.utils.parser import to_bool from pytoolbox.util.log import get_logger logger = get_logger(__name__) @mod.route('/bankcard/<card_no>/bin', methods=['GET']) @verify_request('app_query_bin') def query_bin(card_no): try: bankcard_bin = bankcard.query_bin_cache(card_no) card_bin_info = bankcard_bin.to_dict() return response.success(data=card_bin_info) except Exception as e: logger.exception(e) return response.bad_request(msg=e.message) @mod.route('/users/<user_id>/bankcards/bind', methods=['POST']) @verify_request('app_bind_bankcard') def bind_bankcard(user_id): data = request.params channel = request.channel card_no = data['card_no'] acct_name = data['account_name'] is_corporate_account = to_bool(data['is_corporate_account']) province_code = data['province_code'] city_code = data['city_code'] brabank_name = data['branch_bank_name'] user_map = channel.get_user_map(user_id) if user_map is None: return response.bad_request(msg='user not exists: [{0}]'.format(user_id)) account_user_id = user_map.account_user_id bankcard_id = bankcard.bind_bankcard(account_user_id, card_no, acct_name, is_corporate_account, province_code, city_code, brabank_name) return response.success(id=bankcard_id) @mod.route('/users/<user_id>/bankcards/<int:bankcard_id>/unbind', methods=['POST']) @verify_request('app_unbind_bankcard') def unbind_bankcard(user_id, bankcard_id): try: bankcard.unbind_bankcard(user_id, bankcard_id) response.success() except Exception as e: logger.exception(e) response.fail() @mod.route('/users/<user_id>/bankcards', methods=['GET']) @verify_request('app_list_user_bankcards') def list_user_bankcards(user_id): channel = request.channel user_map = channel.get_user_map(user_id) if user_map is None: return response.bad_request(msg='user not exists: [{0}]'.format(user_id)) account_user_id = user_map.account_user_id bankcards = dba.query_all_bankcards(account_user_id) bankcards = [bc.to_dict() for bc in bankcards] return response.success(data=bankcards) @mod.route('/users/<user_id>/bankcards/<int:bankcard_id>', methods=['GET']) @verify_request('app_get_user_bankcard') def get_user_bankcard(user_id, bankcard_id): channel = request.channel user_map = channel.get_user_map(user_id) if user_map is None: return response.bad_request(msg='user not exists: [{0}]'.format(user_id)) account_user_id = user_map.account_user_id bc = dba.query_bankcard_by_id(bankcard_id) if bc is None or bc.user_id != account_user_id: return response.bad_request(msg='user [{0}] has no bankcard [{1}]'.format(user_id, bankcard_id)) return response.success(data=bc.to_dict())

34.566667

104

0.724204

0

2,739

0.880424

0

524

0.168435

544eed2f5a6fd341973e64324b8db14d8a1824d5

2,928

py

Python

httpd/httpd.py

protocollabs/dmprd

c39e75532ae73458b8239b2d21ca69e42b68929f

[ "MIT" ]

1

2018-09-05T08:16:00.000Z

httpd/httpd.py

protocollabs/dmprd

c39e75532ae73458b8239b2d21ca69e42b68929f

[ "MIT" ]

8

2017-01-08T19:11:16.000Z

2018-09-24T12:20:40.000Z

httpd/httpd.py

protocollabs/dmprd

c39e75532ae73458b8239b2d21ca69e42b68929f

[ "MIT" ]

2

2017-08-23T12:41:02.000Z

2018-08-17T08:11:35.000Z

import asyncio import os try: from aiohttp import web except ImportError: web = None class Httpd(object): def __init__(self): if not web: print('httpd is specified in conf but aiohttp not available') return self.app = web.Application() self._setup_routes() self._run_app() def _run_app(self): loop = asyncio.get_event_loop() handler = self.app.make_handler() f = loop.create_server(handler, '0.0.0.0', 9000) srv = loop.run_until_complete(f) print('serving on', srv.sockets[0].getsockname()) async def handler_index(self, request): data = ''' <!doctype html> <html> <head> <meta charset="utf-8"> <meta content="width=device-width" name="viewport"> <meta content="yes" name="apple-mobile-web-app-capable"> <meta content="IE=edge,chrome=1" http-equiv="X-UA-Compatible"> <title>DMPR</title> <script type="text/javascript" src="static/js/vis.min.js"></script> <script type="text/javascript" src="static/js/script.js"></script> <link href="static/css/bootstrap-3.3.6.css" rel="stylesheet" /> <link href="static/css/style.css" rel="stylesheet" /> <link href="static/css/vis.min.css" rel="stylesheet" type="text/css" /> <link href="static/css/style.css" rel="stylesheet" type="text/css" /> </head> <body> <div class="container-fluid"> <div class="row"> <div class="col-sm-3 col-lg-2"> <nav class="navbar navbar-default navbar-fixed-side"> <div class="container"> <div class="navbar-header"> <button class="navbar-toggle" data-target=".navbar-collapse" data-toggle="collapse"> <span class="sr-only">Toggle navigation</span> <span class="icon-bar"></span> <span class="icon-bar"></span> <span class="icon-bar"></span> </button> <a class="navbar-brand" href="./">DMPR</a> </div> <div class="collapse navbar-collapse"> <ul class="nav navbar-nav"> <li class="active"><a href="#">Topology</a></li> <li class=""><a href="#">Logging</a></li> </ul> </div> </div> </nav> </div> <div class="col-sm-9 col-lg-10 content"> <div id="mynetwork"></div> </div> </div> </div> <script src="static/js/bootstrap-3.3.6.js"></script> </body> </html> ''' data = str.encode(data) return web.Response(body=data, content_type='text/html') def _setup_routes(self): absdir = os.path.dirname(os.path.realpath(__file__)) app_path = os.path.join(absdir, 'www', 'static') self.app.router.add_get('/', self.handler_index) self.app.router.add_static('/static', app_path, show_index=True)

34.046512

100

0.565574

2,831

0.966872

0

2,036

0.695355

1,995

0.681352

5451d6245307e0c41240f5d6be7ea9013b165899

196

py

Python

SImple-Number.py

TonikaHristova/Loops

55b3f1608cf81d185fe98366450b527350d86f3b

[ "MIT" ]

null

SImple-Number.py

TonikaHristova/Loops

55b3f1608cf81d185fe98366450b527350d86f3b

[ "MIT" ]

null

SImple-Number.py

TonikaHristova/Loops

55b3f1608cf81d185fe98366450b527350d86f3b

[ "MIT" ]

null

import math num = int(input()) is_prime = True if num < 2: print("Not prime") for i in range(2, int(math.sqrt(num)+1)): if num / i == 0: is_prime = False print(is_prime)

9.8

41

0.571429

0

11

0.056122

54520f95709f73e2e760152d29139cc05ba229e9

218

py

Python

badgify/apps.py

BrendanBerkley/django-badgify

61203e92cb76982f778caf168d371a72a401db10

[ "MIT" ]

null

badgify/apps.py

BrendanBerkley/django-badgify

61203e92cb76982f778caf168d371a72a401db10

[ "MIT" ]

null

badgify/apps.py

BrendanBerkley/django-badgify

61203e92cb76982f778caf168d371a72a401db10

[ "MIT" ]

null

from django.apps import AppConfig class BadgifyConfig(AppConfig): name = 'badgify' verbose_name = 'Badgify' def ready(self): super(BadgifyConfig, self).ready() self.module.autodiscover()

19.818182

42

0.674312

181

0.830275

0

18

0.082569

545268aad6cd438a8b86741579655c5f5b28ba41

249

py

Python

test/test_i18n.py

timgates42/uliweb

80c0459c5e5d257b665eb2e1d0b5f68ad55c42f1

[ "BSD-2-Clause" ]

202

2015-01-12T08:10:48.000Z

2021-11-08T09:04:32.000Z

test/test_i18n.py

timgates42/uliweb

80c0459c5e5d257b665eb2e1d0b5f68ad55c42f1

[ "BSD-2-Clause" ]

30

2015-01-01T09:07:17.000Z

2021-06-03T12:58:45.000Z

test/test_i18n.py

timgates42/uliweb

80c0459c5e5d257b665eb2e1d0b5f68ad55c42f1

[ "BSD-2-Clause" ]

58

2015-01-12T03:28:54.000Z

2022-01-14T01:58:08.000Z

from uliweb.i18n import ugettext_lazy as _ def test_1(): """ >>> x = _('Hello') >>> print repr(x) ugettext_lazy('Hello') """ def test_1(): """ >>> x = _('Hello {0}') >>> print x.format('name') Hello name """

16.6

42

0.48996

0

167

0.670683

545316d49d38f35bdeec6536c47e60475a119d98

1,041

py

Python

KeyBoardControlImageCaptue.py

Prashant-1305/Tello-Drone

11c3f845a9887c66ac7e52e042dfd28f23555d2e

[ "MIT" ]

null

KeyBoardControlImageCaptue.py

Prashant-1305/Tello-Drone

11c3f845a9887c66ac7e52e042dfd28f23555d2e

[ "MIT" ]

null

KeyBoardControlImageCaptue.py

Prashant-1305/Tello-Drone

11c3f845a9887c66ac7e52e042dfd28f23555d2e

[ "MIT" ]

null

import KeyPressModule as kp from djitellopy import tello import time import cv2 global img kp.init() skynet = tello.Tello() skynet.connect() print(skynet.get_battery()) skynet.streamon() def getKeyboardInput(): lr, fb, ud, yv = 0, 0, 0, 0 speed = 50 if kp.getKey("LEFT"): lr = -speed elif kp.getKey("RIGHT"): lr = speed if kp.getKey("UP"): fb = speed elif kp.getKey("DOWN"): fb = -speed if kp.getKey("u"): ud = speed elif kp.getKey("d"): ud = -speed if kp.getKey("c"): yv = speed elif kp.getKey("a"): yv = -speed if kp.getKey("t"): skynet.takeoff() if kp.getKey("l"): skynet.land(); time.sleep(3) if kp.getKey('s'): cv2.imwrite(f'Resources/Images/{time.time()}.jpg',img) time.sleep(1) return [lr, fb, ud, yv] while True: keyVals = getKeyboardInput() skynet.send_rc_control(keyVals[0], keyVals[1], keyVals[2], keyVals[3]) img = skynet.get_frame_read().frame #timg = cv2.resize(img, (360, 240)) cv2.imshow("Image", img) cv2.waitKey(1)

22.148936

74

0.616715

0

123

0.118156

545376512fee3de8e6da4487e774ee09c7ad912d

1,479

py

Python

cnns/foolbox/foolbox_2_3_0/tests/test_model_zoo.py

anonymous-user-commits/perturb-net

66fc7c4a1234fa34b92bcc85751f0a6e23d80a23

[ "MIT" ]

12

2021-07-27T07:18:24.000Z

2022-03-09T13:52:20.000Z

cnns/foolbox/foolbox_2_3_0/tests/test_model_zoo.py

anonymous-user-commits/perturb-net

66fc7c4a1234fa34b92bcc85751f0a6e23d80a23

[ "MIT" ]

2

2021-08-03T09:21:33.000Z

2021-12-29T14:25:30.000Z

cnns/foolbox/foolbox_2_3_0/tests/test_model_zoo.py

anonymous-user-commits/perturb-net

66fc7c4a1234fa34b92bcc85751f0a6e23d80a23

[ "MIT" ]

3

2021-11-18T14:46:40.000Z

2022-01-03T15:47:23.000Z

from foolbox import zoo import numpy as np import foolbox import sys import pytest from foolbox.zoo.model_loader import ModelLoader from os.path import join, dirname @pytest.fixture(autouse=True) def unload_foolbox_model_module(): # reload foolbox_model from scratch for every run # to ensure atomic tests without side effects module_names = ["foolbox_model", "model"] for module_name in module_names: if module_name in sys.modules: del sys.modules[module_name] test_data = [ # private repo won't work on travis # ('https://github.com/bethgelab/AnalysisBySynthesis.git', (1, 28, 28)), # ('https://github.com/bethgelab/convex_adversarial.git', (1, 28, 28)), # ('https://github.com/bethgelab/mnist_challenge.git', 784) (join("file://", dirname(__file__), "data/model_repo"), (3, 224, 224)) ] @pytest.mark.parametrize("url, dim", test_data) def test_loading_model(url, dim): # download model model = zoo.get_model(url) # create a dummy image x = np.zeros(dim, dtype=np.float32) x[:] = np.random.randn(*x.shape) # run the model logits = model.forward_one(x) probabilities = foolbox.utils.softmax(logits) predicted_class = np.argmax(logits) # sanity check assert predicted_class >= 0 assert np.sum(probabilities) >= 0.9999 # TODO: delete fmodel def test_non_default_module_throws_error(): with pytest.raises(RuntimeError): ModelLoader.get(key="other")

27.90566

76

0.694388

0

836

0.565247

0

484

0.327248

54538684df9453f633582e0d87edd283242082a7

8,464

py

Python

tests/unit/nistbeacon/test_nistbeacon.py

urda/py_nist_beacon

0251970ec31bc370c326c4c3c3b93a5513bdc028

[ "Apache-2.0" ]

11

2017-05-06T02:42:34.000Z

2021-02-11T10:13:09.000Z

tests/unit/nistbeacon/test_nistbeacon.py

urda/nistbeacon

0251970ec31bc370c326c4c3c3b93a5513bdc028

[ "Apache-2.0" ]

31

2015-12-13T12:04:10.000Z

2021-01-27T02:34:34.000Z

tests/unit/nistbeacon/test_nistbeacon.py

urda/py_nist_beacon

0251970ec31bc370c326c4c3c3b93a5513bdc028

[ "Apache-2.0" ]

1

2015-12-25T03:50:25.000Z

""" Copyright 2015-2017 Peter Urda 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. """ from unittest import TestCase from unittest.mock import ( Mock, patch, ) import requests.exceptions from requests import Response from nistbeacon import ( NistBeacon, NistBeaconValue, ) from tests.test_data.nist_records import local_record_json_db class TestNistBeacon(TestCase): @classmethod def setUpClass(cls): cls.init_timestamp = 1378395540 cls.expected_first = local_record_json_db[cls.init_timestamp] cls.expected_first_next = local_record_json_db[cls.init_timestamp + 60] cls.reference_previous = 1447872960 cls.reference_timestamp = 1447873020 cls.reference_next = 1447873080 cls.expected_current = local_record_json_db[cls.reference_timestamp] cls.expected_next = local_record_json_db[cls.reference_next] cls.expected_previous = local_record_json_db[cls.reference_previous] # Perform conversions from json data to record objects cls.expected_first = NistBeaconValue.from_json(cls.expected_first) cls.expected_first_next = NistBeaconValue.from_json( cls.expected_first_next ) cls.expected_current = NistBeaconValue.from_json(cls.expected_current) cls.expected_next = NistBeaconValue.from_json(cls.expected_next) cls.expected_previous = NistBeaconValue.from_json( cls.expected_previous ) @patch('requests.get') def test_get_first_record(self, requests_get_patched): mock_response = Mock(spec=Response) mock_response.status_code = 200 mock_response.text = self.expected_first.xml requests_get_patched.return_value = mock_response expected = self.expected_first actual_download_false = NistBeacon.get_first_record(download=False) actual_download_true = NistBeacon.get_first_record(download=True) self.assertEqual(expected, actual_download_false) self.assertEqual(expected, actual_download_true) self.assertIsNot(expected, actual_download_false) self.assertIsNot(expected, actual_download_true) self.assertIsNot(actual_download_false, actual_download_true) @patch('requests.get') def test_get_next(self, requests_get_patched): mock_response = Mock(spec=Response) mock_response.status_code = 200 mock_response.text = self.expected_next.xml requests_get_patched.return_value = mock_response next_record = NistBeacon.get_next(self.reference_timestamp) self.assertEqual(self.expected_next, next_record) @patch('requests.get') def test_get_previous(self, requests_get_patched): mock_response = Mock(spec=Response) mock_response.status_code = 200 mock_response.text = self.expected_previous.xml requests_get_patched.return_value = mock_response previous_record = NistBeacon.get_previous( self.reference_timestamp ) self.assertEqual(self.expected_previous, previous_record) @patch('requests.get') def test_get_record(self, requests_get_patched): mock_response = Mock(spec=Response) mock_response.status_code = 200 mock_response.text = self.expected_current.xml requests_get_patched.return_value = mock_response record = NistBeacon.get_record(self.reference_timestamp) self.assertEqual(self.expected_current, record) @patch('requests.get') def test_get_last_record(self, requests_get_patched): mock_response = Mock(spec=Response) mock_response.status_code = 200 mock_response.text = self.expected_current.xml requests_get_patched.return_value = mock_response last_record = NistBeacon.get_last_record() self.assertIsInstance(last_record, NistBeaconValue) @patch('requests.get') def test_get_last_record_404(self, requests_get_patched): mock_response = Mock(spec=Response) mock_response.status_code = 404 requests_get_patched.return_value = mock_response self.assertIsNone(NistBeacon.get_last_record()) @patch('requests.get') def test_get_last_record_exceptions(self, requests_get_patched): exceptions_to_test = [ requests.exceptions.RequestException(), requests.exceptions.ConnectionError(), requests.exceptions.HTTPError(), requests.exceptions.URLRequired(), requests.exceptions.TooManyRedirects(), requests.exceptions.Timeout(), ] for exception_to_test in exceptions_to_test: requests_get_patched.side_effect = exception_to_test self.assertIsNone(NistBeacon.get_last_record()) @patch('requests.get') def test_chain_check_empty_input(self, requests_get_patched): mock_response = Mock(spec=Response) mock_response.status_code = 404 requests_get_patched.return_value = mock_response # noinspection PyTypeChecker self.assertFalse(NistBeacon.chain_check(None)) @patch('requests.get') def test_chain_check_majority(self, requests_get_patched): first_response = Mock(spec=Response) first_response.status_code = 200 first_response.text = self.expected_current.xml previous_response = Mock(spec=Response) previous_response.status_code = 200 previous_response.text = self.expected_previous.xml next_response = Mock(spec=Response) next_response.status_code = 200 next_response.text = self.expected_next.xml requests_get_patched.side_effect = [ first_response, previous_response, next_response, ] self.assertTrue( NistBeacon.chain_check( self.expected_current.timestamp ) ) @patch('requests.get') def test_chain_check_init(self, requests_get_patched): first_response = Mock(spec=Response) first_response.status_code = 200 first_response.text = self.expected_first.xml previous_response = Mock(spec=Response) previous_response.status_code = 404 next_response = Mock(spec=Response) next_response.status_code = 200 next_response.text = self.expected_first_next.xml requests_get_patched.side_effect = [ first_response, previous_response, next_response, ] self.assertTrue( NistBeacon.chain_check( self.init_timestamp, ) ) @patch('requests.get') def test_chain_check_last(self, requests_get_patched): first_response = Mock(spec=Response) first_response.status_code = 200 first_response.text = self.expected_current.xml previous_response = Mock(spec=Response) previous_response.status_code = 200 previous_response.text = self.expected_previous.xml next_response = Mock(spec=Response) next_response.status_code = 404 requests_get_patched.side_effect = [ first_response, previous_response, next_response, ] self.assertTrue( NistBeacon.chain_check( self.expected_current.timestamp, ) ) @patch('requests.get') def test_chain_check_no_records_around(self, requests_get_patched): first_response = Mock(spec=Response) first_response.status_code = 200 first_response.text = self.expected_current.xml none_response = Mock(spec=Response) none_response.status_code = 404 requests_get_patched.side_effect = [ first_response, none_response, none_response, ] self.assertFalse( NistBeacon.chain_check( self.expected_current.timestamp ) )

34.129032

79

0.69258

7,630

0.901465

0

7,522

0.888705

0

813

0.096054

54539ddc987a464c0db1b706648667e1f538fd7a

5,417

py

Python

aae/auto_pose/visualization/render_pose.py

shbe-aau/multi-pose-estimation

0425ed9dcc7969f0281cb435615abc33c640e157

[ "MIT" ]

4

2021-12-28T09:25:06.000Z

2022-01-13T12:55:44.000Z

aae/auto_pose/visualization/render_pose.py

shbe-aau/multi-view-pose-estimation

22cea6cd09684fe655fb2214bc14856f589048e1

[ "MIT" ]

null

aae/auto_pose/visualization/render_pose.py

shbe-aau/multi-view-pose-estimation

22cea6cd09684fe655fb2214bc14856f589048e1

[ "MIT" ]

1

2022-01-13T13:00:15.000Z

import cv2 import numpy as np import os from auto_pose.meshrenderer import meshrenderer from auto_pose.ae.utils import lazy_property class PoseVisualizer: def __init__(self, mp_pose_estimator, downsample=1, vertex_scale=False): self.downsample = downsample self.vertex_scale = [mp_pose_estimator.train_args.getint('Dataset', 'VERTEX_SCALE')] if not vertex_scale else [1.] if hasattr(mp_pose_estimator, 'class_2_objpath'): self.classes, self.ply_model_paths = zip(*mp_pose_estimator.class_2_objpath.items()) else: # For BOP evaluation (sry!): self.classes = mp_pose_estimator.class_2_codebook.keys() all_model_paths = eval(mp_pose_estimator.train_args.get('Paths', 'MODEL_PATH')) base_path = '/'.join(all_model_paths[0].split('/')[:-3]) itodd_paths = [os.path.join(base_path, 'itodd/models/obj_0000{: 02d}.ply'.format(i)) for i in range(29)] all_model_paths = all_model_paths + itodd_paths all_model_paths = [model_p.replace('YCB_VideoDataset/original2sixd/bop_models/', 'bop/original/ycbv/models_eval/') for model_p in all_model_paths] self.ply_model_paths = [] for cb_name in mp_pose_estimator.class_2_codebook.values(): for model_path in all_model_paths: bop_dataset = cb_name.split('_')[0] bop_dataset = 'ycbv' if bop_dataset == 'original2sixd' else bop_dataset model_type, obj, obj_id = cb_name.split('_')[-3:] model_name = obj + '_' + obj_id if bop_dataset in model_path and model_name in model_path: self.ply_model_paths.append(model_path) print(('renderer', 'Model paths: ', self.ply_model_paths)) @lazy_property def renderer(self): return meshrenderer.Renderer(self.ply_model_paths, samples=1, vertex_tmp_store_folder='.', vertex_scale=float(self.vertex_scale[0])) # 1000 for models in meters def render_poses(self, image, camK, pose_ests, dets, vis_bbs=True, vis_mask=False, all_pose_estimates_rgb=None, depth_image=None, waitKey=True): W_d = image.shape[1] / self.downsample H_d = image.shape[0] / self.downsample print( [self.classes.index(pose_est.name) for pose_est in pose_ests]) bgr, depth,_ = self.renderer.render_many(obj_ids = [self.classes.index(pose_est.name) for pose_est in pose_ests], W = W_d, H = H_d, K = camK.copy(), Rs = [pose_est.trafo[:3,:3] for pose_est in pose_ests], ts = [pose_est.trafo[:3,3] for pose_est in pose_ests], near = 10, far = 10000) image_show = cv2.resize(image,(W_d,H_d)) if all_pose_estimates_rgb is not None: image_show_rgb = image_show.copy() g_y = np.zeros_like(bgr) g_y[:,:,1]= bgr[:,:,1] image_show[bgr > 0] = g_y[bgr > 0]*2./3. + image_show[bgr > 0]*1./3. if all_pose_estimates_rgb is not None: bgr, depth,_ = self.renderer.render_many(obj_ids = [clas_idx for clas_idx in all_class_idcs], W = W_d, H = H_d, K = camK.copy(), Rs = [pose_est.trafo[:3,:3] for pose_est in pose_ests], ts = [pose_est.trafo[:3,3] for pose_est in pose_ests], near = 10, far = 10000) bgr = cv2.resize(bgr,(W_d,H_d)) b_y = np.zeros_like(bgr) b_y[:,:,0]= bgr[:,:,0] image_show_rgb[bgr > 0] = b_y[bgr > 0]*2./3. + image_show_rgb[bgr > 0]*1./3. if np.any(depth_image): depth_show = depth_image.copy() depth_show = np.dstack((depth_show,depth_show,depth_show)) depth_show[bgr[:,:,0] > 0] = g_y[bgr[:,:,0] > 0]*2./3. + depth_show[bgr[:,:,0] > 0]*1./3. cv2.imshow('depth_refined_pose', depth_show) if vis_bbs: # for label,box,score in zip(labels,boxes,scores): for det in dets: # box = box.astype(np.int32) / self.downsample # xmin, ymin, xmax, ymax = box[0], box[1], box[0] + box[2], box[1] + box[3] xmin, ymin, xmax, ymax = int(det.xmin * W_d), int(det.ymin * H_d), int(det.xmax * W_d), int(det.ymax * H_d) label, score = list(det.classes.items())[0] try: cv2.putText(image_show, '%s : %1.3f' % (label,score), (xmin, ymax+20), cv2.FONT_ITALIC, .5, (0,0,255), 2) cv2.rectangle(image_show,(xmin,ymin),(xmax,ymax),(255,0,0),2) if all_pose_estimates_rgb is not None: cv2.putText(image_show_rgb, '%s : %1.3f' % (label,score), (xmin, ymax+20), cv2.FONT_ITALIC, .5, (0,0,255), 2) cv2.rectangle(image_show_rgb,(xmin,ymin),(xmax,ymax),(255,0,0),2) except: print('failed to plot boxes') if all_pose_estimates_rgb is not None: cv2.imshow('rgb_pose', image_show_rgb) cv2.imshow('refined_pose', image_show) if waitKey: cv2.waitKey(0) else: cv2.waitKey(1) return (image_show)

47.517544

158

0.567288

5,269

0.972679

0

281

0.051874

0

549

0.101348

5454b8f602a3ea5235a7102af61b547b5c4c3b31

1,128

py

Python

client/nodes/common/docker_subsriber.py

CanboYe/BusEdge

2e53e1d1d82559fc3e9f0029b2f0faf4e356b210

[ "MIT", "Apache-2.0", "BSD-2-Clause", "BSD-3-Clause" ]

2

2021-08-17T14:14:28.000Z

2022-02-02T02:09:33.000Z

client/nodes/common/docker_subsriber.py

cmusatyalab/gabriel-BusEdge

528a6ee337882c6e709375ecd7ec7e201083c825

[ "MIT", "Apache-2.0", "BSD-2-Clause", "BSD-3-Clause" ]

null

client/nodes/common/docker_subsriber.py

cmusatyalab/gabriel-BusEdge

528a6ee337882c6e709375ecd7ec7e201083c825

[ "MIT", "Apache-2.0", "BSD-2-Clause", "BSD-3-Clause" ]

1

2021-09-01T16:18:29.000Z

# SPDX-FileCopyrightText: 2021 Carnegie Mellon University # # SPDX-License-Identifier: Apache-2.0 import cv2 import numpy as np import rospy from gabriel_protocol import gabriel_pb2 from std_msgs.msg import UInt8MultiArray def run_node(client_filter, source_name): rospy.init_node(source_name + "_subscriber_node") rospy.loginfo("Initialized subscriber node for " + source_name) sub = rospy.Subscriber( source_name, UInt8MultiArray, callback, callback_args=(client_filter,), queue_size=1, buff_size=2 ** 24, ) # spin() simply keeps python from exiting until this node is stopped rospy.spin() def callback(data, args): client_filter = args[0] serialized_message = data.data # client_filter.send_serialized(serialized_message) # TODO: this is inefficient becuase we deserialize the binary data, # need to either modify the gabriel library or change the way # we save the extra fields. input_frame = gabriel_pb2.InputFrame() input_frame.ParseFromString(serialized_message) client_filter.send(input_frame)

29.684211

72

0.720745

0

433

0.383865

54562608a59ce9476a71d70e032f5d5bf8f6d75b

138

py

Python

datx/base_station.py

ipipdotnet/datx-python

68d6e99363abc6ae48714be38aa90a5ae6e20fd4

[ "Apache-2.0" ]

39

2018-03-13T02:48:36.000Z

2021-03-18T07:51:54.000Z

datx/base_station.py

ipipdotnet/datx-python

68d6e99363abc6ae48714be38aa90a5ae6e20fd4

[ "Apache-2.0" ]

1

2018-11-06T08:30:31.000Z

datx/base_station.py

ipipdotnet/datx-python

68d6e99363abc6ae48714be38aa90a5ae6e20fd4

[ "Apache-2.0" ]

10

2018-04-28T02:07:08.000Z

2020-11-09T04:26:47.000Z

15.333333

33

0.623188

37

0.266187

0

67

0.482014

5456722cbb51619ad54be3201718c3cfa01f24c7

13,034

py

Python

cogs/user.py

billydevyt/RoboBilly

6d79ab9626a6d6b487dd73688ad7187212e7864c

[ "MIT" ]

6

2020-11-07T16:46:18.000Z

2021-01-03T11:52:39.000Z

cogs/user.py

billyeatcookies/RoboBilly

6d79ab9626a6d6b487dd73688ad7187212e7864c

[ "MIT" ]

3

2020-11-30T01:52:41.000Z

2021-01-03T11:53:18.000Z

cogs/user.py

billyeatcookies/RoboBilly

6d79ab9626a6d6b487dd73688ad7187212e7864c

[ "MIT" ]

7

2021-04-17T07:27:58.000Z

2021-08-31T15:21:42.000Z

""" User module """ import discord import random import asyncio from discord.ext import commands from discord.ext.commands import has_permissions, MissingPermissions, BadArgument import requests, json, pyfiglet from datetime import timedelta, datetime class User(commands.Cog): api_key = "bbde6a19c33fb4c3962e36b8187abbf8" base_url = "http://api.openweathermap.org/data/2.5/weather?" def __init__(self, bot): self.bot = bot def get_embed(self, _title, _description, icon): embed = discord.Embed(title=_title, description=_description, color= discord.Color.dark_theme()) embed.set_thumbnail(url=icon) return embed def get_weather(self, city_name): complete_url = self.base_url + "appid=" + self.api_key + "&q=" + city_name response = requests.get(complete_url) x = response.json() if x["cod"] != "404": # store the value of "main" # key in variable y y = x["main"] # store the value corresponding # to the "temp" key of y current_temperature = y["temp"] # store the value corresponding # to the "pressure" key of y current_pressure = y["pressure"] # store the value corresponding # to the "humidity" key of y current_humidiy = y["humidity"] # store the value of "weather" # key in variable z z = x["weather"] # store the value corresponding # to the "description" key at # the 0th index of z weather_description = z[0]["description"] # print following values result = ("Temperature (in kelvin unit) = " + str(current_temperature) + "\natmospheric pressure (in hPa unit) = " + str(current_pressure) + "\nhumidity (in percentage) = " + str(current_humidiy) + "\ndescription = " + str(weather_description)) return result else: print(" City Not Found : " + city_name) return "That city might be in moon" @commands.command() async def say(self, ctx, *, arg): async with ctx.channel.typing(): thing = arg await (ctx.channel).send(thing) print("Event: Repeated {ctx.author.name}: ", arg) @commands.command() async def hi(self, ctx): async with ctx.channel.typing(): thing = "hello human!" await (ctx.channel).send(thing) print("Event: I said Hi to ", ctx.author.name) @commands.command() async def info(self, ctx, *, member: discord.Member): async with ctx.channel.typing(): await asyncio.sleep(2) avatar = member.avatar_url fmt = 'Joined basement on {0.joined_at} \njoined Discord on {0.created_at} \nThis member has {1} roles.' msg = self.get_embed("Info of {0.display_name}".format(member), fmt.format(member, len(member.roles)), avatar) await ctx.send(embed=msg) print(ctx.author.name, " checked info of ", member.name) @info.error async def info_error(self, ctx, error): if isinstance(error, commands.BadArgument): await ctx.send('I could not find that member...') @commands.command(pass_context=True) async def weather(self, ctx, a: str): async with ctx.channel.typing(): msg = self.get_weather(a) await asyncio.sleep(2) await ctx.send(embed=discord.Embed(title=f"Weather status at {a}", description=msg, color=discord.Color.dark_theme())) print("Event. weather checked on user's command: ", ctx.author.name, ", location: ", a) @commands.command() async def bing(self, ctx): async with ctx.channel.typing(): thing = discord.Embed(title="Bong!", description="Sounds like something " + "https://www.bing.com/"+" would know!", color=discord.Color.dark_theme()) await (ctx.channel).send(embed=thing) print("Event. I binged, bong! : ", ctx.author.name) @commands.command() async def google(self, ctx): await ctx.send("It is quite important that you **google your problems before asking** someone. Most of your questions have already been answered at least once online because you are definitely not the only one with this particular question. Additionally, each programming language, API, or program should be well documented in its official documentation. \nRefer to this page: https://duck-dev.github.io/general/how-to-google/") print("Event. how to google! : ", ctx.author.name) @commands.command() async def dontasktoask(self, ctx): async with ctx.channel.typing(): thing = discord.Embed(title="Don't ask to ask, Just ask!", description="Ask your question, instead of asking to help \nhttps://dontasktoask.com/", color=discord.Color.dark_theme()) await (ctx.channel).send(embed = thing) print("Event. ", ctx.author.name, " did ask to ask!") @commands.command(name='goodnight', aliases=['night', 'gn']) async def goodnight(self, ctx, *, args = "nothing"): async with ctx.channel.typing(): thing = discord.Embed(title="Good Night", description="Sleep tight", color= discord.Color.dark_theme()) await (ctx.channel).send(embed=thing) print(f"Event. {ctx.author.name} said good night") @commands.command(name='goodmorning', aliases=['morning', 'gm']) async def goodmorning(self, ctx, *, args = "nothing"): async with ctx.channel.typing(): thing = discord.Embed(title="Good Morning", description="Wishing you a good day", color= discord.Color.dark_theme()) await (ctx.channel).send(embed=thing) print(f"Event. {ctx.author.name} said good morning") @commands.group() async def git(self, ctx): """ A set of funny ~~useful~~ git commands. """ if ctx.invoked_subcommand is None: await ctx.send('> See: `[]help git`') @git.command() async def push(self, ctx, remote: str, branch: str): await ctx.send('Pushing {} to {}'.format(remote, branch)) @git.command() async def blame(self, ctx, branch: str): await ctx.send('#blame{}'.format(branch)) @git.command() async def lick(self, ctx, user): if random.choice([True, False]): await ctx.send('*licks {}, Mmm tastes good*'.format(user)) else: await ctx.send('*licks {}, euh tastes kinda bad*'.format(user)) @git.command() async def commit(self, ctx, *, message: str): await ctx.send('Commiting {}'.format(message)) @git.command() async def pull(self, ctx, branch: str): await ctx.send('Pulling {}'.format(branch)) @git.command() async def status(self, ctx, user: discord.Member=None): if user: await ctx.send("On branch {0}\nYour branch is up to date with 'origin/main'. \nstatus: {1}".format(user.display_name, user.status)) else: await ctx.send("On branch main\nYour branch is up to date with 'origin/main'. \nstatus: {}".format(ctx.author.status)) @git.command() async def merge(self, ctx, thing, anotherthing): await ctx.send('Merging {0} to {1}'.format(thing, anotherthing)) @git.command() async def add(self, ctx, *, thing): msg = await ctx.send('Adding {0}...'.format(thing)) await asyncio.sleep(2) await msg.edit(content='Added {0} to changes.\n`{1} additions and {2} deletions.`'.format(thing, random.randint(10, 1000), random.randint(10, 1000))) @git.command() async def out(self, ctx, *, thing): await ctx.send('https://tenor.com/view/the-office-steve-carell-please-leave-get-out-move-gif-3579774') @commands.command(name='codeblocks', aliases=['codeblock', 'cb', 'myst']) async def codeblocks(self, ctx, *args): async with ctx.channel.typing(): thing = discord.Embed(title="Code Blocks", description="""**__Use codeblocks to send code in a message!__** To make a codeblock, surround your code with \`\`\` \`\`\`cs // your code here \`\`\` `In order use C# syntax highlighting add cs after the three back ticks` To send lengthy code, paste it into <https://paste.myst.rs/> and send the link of the paste into chat.""", color=discord.Color.dark_theme()) await (ctx.channel).send(embed=thing) print(f"Event: {ctx.author.name} used codeblocks") @commands.command(name='example', aliases=['Example', 'eg', 'eg.']) async def example(self, ctx, *args): async with ctx.channel.typing(): thing = discord.Embed(title="Example", description="""**__How to create a Minimal, Reproducible Example__** When asking a question, people will be better able to provide help if you provide code that they can easily understand and use to reproduce the problem. This is referred to by community members as creating a minimal, reproducible example (**reprex**), a minimal, complete and verifiable example (**mcve**), or a minimal, workable example (**mwe**). Regardless of how it's communicated to you, it boils down to ensuring your code that reproduces the problem follows the following guidelines: **__Your code examples should be…__** » **Minimal** – Use as little code as possible that still produces the same problem » **Complete** – Provide all parts someone else needs to reproduce your problem in the question itself » **Reproducible** – Test the code you're about to provide to make sure it reproduces the problem """, color=discord.Color.dark_theme()) await (ctx.channel).send(embed=thing) print(f"Event: {ctx.author.name} used example") @commands.command(name='pastemyst', aliases=['pm', 'pastebin', 'PasteMyst', 'paste']) async def pastemyst(self, ctx, *, args = "nothing"): async with ctx.channel.typing(): thing = discord.Embed(title="How to use PasteMyst", description="> 1. paste your code in https://paste.myst.rs/\n> 2. copy the link of the website completely\n> 3. send the link into chat.", color=discord.Color.dark_theme()) await (ctx.channel).send(embed=thing) print(f"Event: {ctx.author.name} used how to use pastemyst") @commands.group(name="ascii") async def ascii(self, ctx): if ctx.invoked_subcommand is None: await ctx.trigger_typing() embed = discord.Embed(title="Ascii Modules", description="use []ascii <module>", color = discord.Color.dark_theme()) embed.add_field(name="Word", value="Shows ascii art of given text.", inline=False) embed.add_field(name="Fonts", value="See available Fonts.", inline=False) embed.set_footer(text="use []ascii <module> <args>") await ctx.send(embed=embed) @ascii.command(name="word", aliases=["w", "Word", "W"]) async def word(self, ctx, word:str = "hey", font:str = "standard"): try: result = pyfiglet.figlet_format(word, font = font) except: result = f"There is no font called {font}." await ctx.send("```\n" + result + "\n```") @ascii.command(name="fonts", aliases=["font", "f"]) async def fonts(self, ctx, page:int=1): total_pages = 4 with open('./cogs/fonts.json', 'r') as f: try: data = json.load(f) if page == 1: page_data = data['fonts1'] page_no = 1 elif page == 2: page_data = data['fonts2'] page_no = 2 elif page == 3: page_data = data['fonts3'] page_no = 3 elif page == 4: page_data = data['fonts4'] page_no = 4 elif page is None: page_data = data['fonts1'] page_no = 1 else: page_data = "more fonts will be added in future" page_no = 0 except: print("fonts.json loading error") if page_data is not None: Separator = "\n" fields = Separator.join(page_data) #embeding embed = discord.Embed(color = discord.Color.dark_theme()) embed.set_author(name='Ascii Art') embed.add_field(name='Fonts page', value=fields, inline=False) if page_no != 0: embed.set_footer(text=f"page: {page_no}/{total_pages}") else: embed.set_footer(text="use []ascii fonts <page_no>") await ctx.send(embed=embed) else: print("looks like there's a problem with page_data") #===================================== ADD COG ======================================# def setup(bot): bot.add_cog(User(bot))

43.15894

490

0.603192

12,655

0.970103

0

10,583

0.811269

9,665

0.740897

4,701

0.360368

5459131a00c531976bbf1bad787c4cbce19610f5

622

py

Python

wsu/tools/simx/simx/python/simx/protomap/util.py

tinyos-io/tinyos-3.x-contrib

3aaf036722a2afc0c0aad588459a5c3e00bd3c01

[ "BSD-3-Clause", "MIT" ]

1

2020-02-28T20:35:09.000Z

wsu/tools/simx/simx/python/simx/protomap/util.py

tinyos-io/tinyos-3.x-contrib

3aaf036722a2afc0c0aad588459a5c3e00bd3c01

[ "BSD-3-Clause", "MIT" ]

null

wsu/tools/simx/simx/python/simx/protomap/util.py

tinyos-io/tinyos-3.x-contrib

3aaf036722a2afc0c0aad588459a5c3e00bd3c01

[ "BSD-3-Clause", "MIT" ]

null

def sync_read(socket, size): """ Perform a (temporary) blocking read. The amount read may be smaller than the amount requested if a timeout occurs. """ timeout = socket.gettimeout() socket.settimeout(None) try: return socket.recv(size) finally: socket.settimeout(timeout) def sync_write(socket, data): """ Perform a (temporary) blocking write. """ timeout = socket.gettimeout() socket.settimeout(None) try: while data: sent = socket.send(data) data = data[sent:] finally: socket.settimeout(timeout)

22.214286

65

0.607717

0

192

0.308682

545b4ee6fb3b667ccf9bf2aadc9dfb4077e4dee6

976

py

Python

mergeKsortedlist.py

ZhouLihua/leetcode

7a711e450756fb7b5648e938879d690e583f5957

[ "MIT" ]

2

2019-05-16T03:11:44.000Z

2019-10-25T03:20:05.000Z

mergeKsortedlist.py

ZhouLihua/leetcode

7a711e450756fb7b5648e938879d690e583f5957

[ "MIT" ]

null

mergeKsortedlist.py

ZhouLihua/leetcode

7a711e450756fb7b5648e938879d690e583f5957

[ "MIT" ]

null

#Definition for singly-linked list. class ListNode(object): def __init__(self, x): self.val = x self.next = None import sys class Solution(object): def mergeKLists(self, lists): """ :type lists: List[ListNode] :rtype: ListNode """ temp = ListNode(-1) result = temp null_lists = 0 while lists: while null_lists > 0: lists.remove(None) null_lists -= 1 min_node = ListNode(sys.maxint) order = -1 for index, node in enumerate(lists): if not node: null_lists += 1 continue if node.val < min_node.val: order, min_node = index, node if order != -1: temp.next = ListNode(min_node.val) temp = temp.next lists[order] = lists[order].next return result.next

27.885714

50

0.482582

926

0.94877

0

111

0.11373

545c039475e437fcfe31a7978e08b358e2864ddd

1,334

py

Python

f5/bigip/tm/vcmp/test/unit/test_virtual_disk.py

nghia-tran/f5-common-python

acb23a6e5830a119b460c19a578654113419f5c3

[ "Apache-2.0" ]

272

2016-02-23T06:05:44.000Z

2022-02-20T02:09:32.000Z

f5/bigip/tm/vcmp/test/unit/test_virtual_disk.py

nghia-tran/f5-common-python

acb23a6e5830a119b460c19a578654113419f5c3

[ "Apache-2.0" ]

1,103

2016-02-11T17:48:03.000Z

2022-02-15T17:13:37.000Z

f5/bigip/tm/vcmp/test/unit/test_virtual_disk.py

nghia-tran/f5-common-python

acb23a6e5830a119b460c19a578654113419f5c3

[ "Apache-2.0" ]

167

2016-02-11T17:48:21.000Z

2022-01-17T20:13:05.000Z

# Copyright 2017 F5 Networks Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import mock import pytest from f5.bigip.tm.vcmp.virtual_disk import Virtual_Disk from f5.sdk_exception import UnsupportedMethod @pytest.fixture def FakeResource(): mo = mock.MagicMock() return Virtual_Disk(mo) def test_create(FakeResource): with pytest.raises(UnsupportedMethod) as ex: FakeResource.create() assert "does not support the create method" in str(ex.value) def test_update(FakeResource): with pytest.raises(UnsupportedMethod) as ex: FakeResource.update() assert "does not support the update method" in str(ex.value) def test_modify(FakeResource): with pytest.raises(UnsupportedMethod) as ex: FakeResource.modify() assert "does not support the modify method" in str(ex.value)

29.644444

74

0.749625

0

89

0.066717

0

675

0.505997

545c6c254ab620127f5ce9a6e6a0f63adc08b458

1,281

py

Python

tinylinks/admin.py

lavindiuss/django-shorter

50bc018e762b396cd9bc71991f6ea1329aaceddd

[ "MIT" ]

null

tinylinks/admin.py

lavindiuss/django-shorter

50bc018e762b396cd9bc71991f6ea1329aaceddd

[ "MIT" ]

null

tinylinks/admin.py

lavindiuss/django-shorter

50bc018e762b396cd9bc71991f6ea1329aaceddd

[ "MIT" ]

null

"""Admin sites for the ``django-tinylinks`` app.""" from django.contrib import admin from django.template.defaultfilters import truncatechars from django.utils.translation import ugettext_lazy as _ from django.template.loader import render_to_string from tinylinks.forms import TinylinkAdminForm from tinylinks.models import Tinylink, TinylinkLog class TinylinkAdmin(admin.ModelAdmin): list_display = ('short_url', 'url_truncated', 'amount_of_views', 'user', 'last_checked', 'status', 'validation_error',) search_fields = ['short_url', 'long_url'] form = TinylinkAdminForm fieldsets = [ ('Tinylink', {'fields': ['user', 'long_url', 'short_url', ]}), ] def url_truncated(self, obj): return truncatechars(obj.long_url, 60) url_truncated.short_description = _('Long URL') def status(self, obj): if not obj.is_broken: return _('OK') return _('Link broken') status.short_description = _('Status') admin.site.register(Tinylink, TinylinkAdmin) class TinylinkLogAdmin(admin.ModelAdmin): list_display = ('tinylink', 'datetime', 'remote_ip', 'tracked') readonly_fields = ('datetime',) date_hierarchy = 'datetime' admin.site.register(TinylinkLog, TinylinkLogAdmin)

28.466667

76

0.699454

826

0.644809

0

301

0.234973

545c8aae9bf713a7f6422a8269de2049905dd92f

562

py

Python

wk11frontend.py

alvaro-root/pa2_2021

fee3931f9e10a7d39af9bf2ce5f033e41621bbda

[ "MIT" ]

null

wk11frontend.py

alvaro-root/pa2_2021

fee3931f9e10a7d39af9bf2ce5f033e41621bbda

[ "MIT" ]

null

wk11frontend.py

alvaro-root/pa2_2021

fee3931f9e10a7d39af9bf2ce5f033e41621bbda

[ "MIT" ]

null

import requests import json def main(): host = "http://localhost:5006" urlpattern = "/user/" response = requests.post(f"{host}{urlpattern}", json={'key1': 'random value'}) if 199 < response.status_code < 300: for k, v in response.headers.items(): print(f"{k} -> {v}") print(f"{'=' * 50}") body = json.loads(response.text) for k, v in body.items(): print(f"{k} -> {v}") else: print(f"Something bad happened: {response.status_code}") if __name__ == "__main__": main()

21.615385

82

0.551601

0

170

0.302491

545fd8631d933f37ee5ed9022359f6f1a7a06f4b

73

py

Python

software/python/XilinxKcu1500Pgp3/__init__.py

ejangelico/cryo-on-epix-hr-dev

354bf205a67d3c43b4e815823dd78cec85d3b672

[ "BSD-3-Clause-LBNL" ]

1

2021-05-24T22:01:54.000Z

software/python/XilinxKcu1500Pgp3/__init__.py

ejangelico/cryo-on-epix-hr-dev

354bf205a67d3c43b4e815823dd78cec85d3b672

[ "BSD-3-Clause-LBNL" ]

1

2021-02-25T20:27:36.000Z

2021-03-31T17:55:08.000Z

software/python/XilinxKcu1500Pgp3/__init__.py

ejangelico/cryo-on-epix-hr-dev

354bf205a67d3c43b4e815823dd78cec85d3b672

[ "BSD-3-Clause-LBNL" ]

4

2020-10-21T21:39:37.000Z

2021-07-24T02:19:34.000Z

#!/usr/bin/env python from XilinxKcu1500Pgp3.XilinxKcu1500Pgp3 import *

18.25

49

0.808219

0

21

0.287671

545fe80c1b80eb166756266947e1f74465ae48f6

2,517

py

Python

files/files.py

StevenKangWei/tools

f0de7d2202dbe979b06ba8344addad6df6e96320

[ "MIT" ]

15

2021-07-06T13:03:09.000Z

2022-03-05T04:18:13.000Z

files/files.py

StevenKangWei/tools

f0de7d2202dbe979b06ba8344addad6df6e96320

[ "MIT" ]

1

2021-12-03T05:39:24.000Z

files/files.py

StevenKangWei/tools

f0de7d2202dbe979b06ba8344addad6df6e96320

[ "MIT" ]

5

2021-07-30T09:31:31.000Z

2022-01-03T06:30:25.000Z

#!/usr/bin/python import os import glob import traceback import datetime import dandan from flask import Flask from flask import abort from flask import send_file from flask import send_from_directory from flask import render_template from werkzeug.routing import BaseConverter import config __VERSION__ = "0.0.1.1" dirname = os.path.dirname(os.path.abspath(__file__)) favicon = os.path.join(dirname, "static/images/favicon.ico") class RegexConverter(BaseConverter): def __init__(self, map, *args): self.map = map self.regex = args[0] server = Flask(__name__) server.url_map.converters['regex'] = RegexConverter def get_data(): data = dandan.value.AttrDict() data.info.name = "Files" data.info.current_time = datetime.datetime.now() return data def get_info(filepath): info = dandan.value.AttrDict() info.filepath = filepath info.basename = os.path.basename(filepath) info.size = os.path.getsize(filepath) info.mtime = datetime.datetime.fromtimestamp(os.path.getmtime(filepath)) if os.path.isfile(filepath): info.type = "file" elif os.path.isdir(filepath): info.type = 'dir' return info def get_response(filename=""): basket = os.path.join(dirname, "basket") if not os.path.exists(basket): return "basket not exists." # abort(404) filepath = os.path.join(basket, filename) if not os.path.exists(filepath): return "file not exists {}".format(filepath) # abort(404) if os.path.isfile(filepath): return send_file(filepath) children = os.listdir(filepath) data = get_data() data.filename = filename if filename: data.title = '/{}/'.format(filename) else: data.title = "/" data.items = [get_info(os.path.join(filepath, child)) for child in children] return render_template("index.html", **data) @server.route('/') @server.route("/<regex('.+'):filename>") def index(filename=""): if filename == "favicon.ico" and os.path.exists(favicon): return send_file(favicon) else: return get_response(filename) def main(): try: print("run server {}:{}".format(config.host, config.port)) server.run(host=config.host, port=config.port, debug=config.debug, threaded=True) except Exception: traceback.print_exc() return if __name__ == "__main__": main()

25.683673

90

0.642034

127

0.050457

0

233

0.092571

0

247

0.098133

546042473af828587af78168aa3e36324191b2db

2,961

py

Python

jdcloud_sdk/services/iotcore/models/DeviceVO.py

Tanc009/jdcloud-sdk-python

8b045c99bc5b73ca7348e950b6f01e03a27982f5

[ "Apache-2.0" ]

14

2018-04-19T09:53:56.000Z

2022-01-27T06:05:48.000Z

jdcloud_sdk/services/iotcore/models/DeviceVO.py

Tanc009/jdcloud-sdk-python

8b045c99bc5b73ca7348e950b6f01e03a27982f5

[ "Apache-2.0" ]

15

2018-09-11T05:39:54.000Z

2021-07-02T12:38:02.000Z

jdcloud_sdk/services/iotcore/models/DeviceVO.py

Tanc009/jdcloud-sdk-python

8b045c99bc5b73ca7348e950b6f01e03a27982f5

[ "Apache-2.0" ]

33

2018-04-20T05:29:16.000Z

2022-02-17T09:10:05.000Z

# coding=utf8 # Copyright 2018 JDCLOUD.COM # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # NOTE: This class is auto generated by the jdcloud code generator program. class DeviceVO(object): def __init__(self, deviceId=None, deviceName=None, parentId=None, deviceType=None, status=None, identifier=None, secret=None, description=None, activatedTime=None, lastConnectedTime=None, createdTime=None, updatedTime=None, productKey=None, productName=None, productSecret=None, model=None, manufacturer=None, dynamicRegister=None, deviceCollectorType=None, lastDisconnectTime=None, orderId=None): """ :param deviceId: (Optional) 设备ID :param deviceName: (Optional) 设备名称 :param parentId: (Optional) 父级设备Id :param deviceType: (Optional) 设备类型，同产品类型，0-普通设备，1-网关，2-Edge :param status: (Optional) 设备状态，0-未激活，1-激活离线，2-激活在线 :param identifier: (Optional) 设备标识符 :param secret: (Optional) 设备秘钥 :param description: (Optional) 设备描述 :param activatedTime: (Optional) 激活时间 :param lastConnectedTime: (Optional) 最后连接时间 :param createdTime: (Optional) 注册时间 :param updatedTime: (Optional) 修改时间 :param productKey: (Optional) 产品Key :param productName: (Optional) 产品名称 :param productSecret: (Optional) 产品秘钥 :param model: (Optional) 设备型号 :param manufacturer: (Optional) 设备厂商 :param dynamicRegister: (Optional) 是否开启动态注册,0:关闭,1:开启，开启动态注册的设备认证类型为一型一密，否则为一机一密 :param deviceCollectorType: (Optional) 设备采集器类型 :param lastDisconnectTime: (Optional) 最后离线时间 :param orderId: (Optional) 订单号 """ self.deviceId = deviceId self.deviceName = deviceName self.parentId = parentId self.deviceType = deviceType self.status = status self.identifier = identifier self.secret = secret self.description = description self.activatedTime = activatedTime self.lastConnectedTime = lastConnectedTime self.createdTime = createdTime self.updatedTime = updatedTime self.productKey = productKey self.productName = productName self.productSecret = productSecret self.model = model self.manufacturer = manufacturer self.dynamicRegister = dynamicRegister self.deviceCollectorType = deviceCollectorType self.lastDisconnectTime = lastDisconnectTime self.orderId = orderId

43.544118

401

0.69875

2,592

0.794361

0

1,988

0.609255

54607def7c2c2dd5026968fee33155a24a8770a7

155

py

Python

satyrus/sat/types/__init__.py

lucasvg/Satyrus3-FinalProject-EspTopsOTM

024785752abdc46e3463d8c94df7c3da873c354d

[ "MIT" ]

null

satyrus/sat/types/__init__.py

lucasvg/Satyrus3-FinalProject-EspTopsOTM

024785752abdc46e3463d8c94df7c3da873c354d

[ "MIT" ]

null

satyrus/sat/types/__init__.py

lucasvg/Satyrus3-FinalProject-EspTopsOTM

024785752abdc46e3463d8c94df7c3da873c354d

[ "MIT" ]

null

from .array import Array from .string import String from .problem import Constraint, Loop from .main import SatType, Var, Number from .expr import Expr

31

39

0.780645

0

54615497a597809e722b75e586e88b607f457119

470

py

Python

magma/backend/util.py

Kuree/magma

be2439aa897768c5810be72e3a55a6f772ac83cf

[ "MIT" ]

null

magma/backend/util.py

Kuree/magma

be2439aa897768c5810be72e3a55a6f772ac83cf

[ "MIT" ]

null

magma/backend/util.py

Kuree/magma

be2439aa897768c5810be72e3a55a6f772ac83cf

[ "MIT" ]

null

import os __magma_codegen_debug_info = False if os.environ.get("MAGMA_CODEGEN_DEBUG_INFO", False): __magma_codegen_debug_info = True def set_codegen_debug_info(val): global __magma_codegen_debug_info __magma_codegen_debug_info = val def get_codegen_debug_info(): return __magma_codegen_debug_info def make_relative(path): cwd = os.getcwd() common_prefix = os.path.commonprefix([cwd, path]) return os.path.relpath(path, common_prefix)

21.363636

53

0.77234

0

26

0.055319

546277ddd1038ab1b79d6538508e871a2186c14c

3,560

py

Python

src/backend/main.py

tuimac/servertools

ceda2685a248d700f48aea4f93887b0f89a264a8

[ "MIT" ]

null

src/backend/main.py

tuimac/servertools

ceda2685a248d700f48aea4f93887b0f89a264a8

[ "MIT" ]

null

src/backend/main.py

tuimac/servertools

ceda2685a248d700f48aea4f93887b0f89a264a8

[ "MIT" ]

null

#!/usr/bin/env python3 from subprocess import Popen, PIPE, DEVNULL, run import socket import sys import traceback import argparse import time import logging import os logger = logging.getLogger("django") def startProcess(command, port): try: sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) result = sock.connect_ex((socket.gethostbyname(socket.gethostname()), int(port))) if result == 0: raise OSError("[Errno 98] Address already in use") sock.close() #popen = Popen(command, stdout=DEVNULL, stderr=PIPE) popen = os.popen(' '.join(command)) time.sleep(3) print("Start httptracker is sucess.") except OSError as e: raise e except Exception as e: raise e except PermissionError as e: raise e def stopProcess(command): try: killCommand = ['pkill', '-f', ' '.join(command)] run(killCommand) time.sleep(2) print("Stop httptracker is sucess.") except OSError as e: raise e except Exception as e: raise e except PermissionError as e: raise e class CustomArgparse(argparse.ArgumentParser): def error(self, message): if message == "": print("[Error] Argument is wrong...<(^^;)\n", file=sys.stderr) else: print("[Error] " + message + "\n", file=sys.stderr) self.print_help() sys.exit(2) def main(): try: parser = CustomArgparse( prog = "httptracker", description = "Track HTTP request to the end of the host.\nex) httptracker --mode start -p 80", add_help = True ) parser.add_argument( "-m", "--mode", dest = "mode", nargs = 1, required = True, help = "[Required]Select modes which are 'start', 'restart', 'stop' to execute httptracker.", ) parser.add_argument( "-p", "--port", dest = "port", nargs = 1, type = int, default = 8000, required = False, help = "[Optional]Direct port which httptracker process use. Default is 8000/tcp." ) parser.add_argument( "-i", "--ipaddress", dest = "ipaddress", nargs = 1, type = str, default = "0.0.0.0", required = False, help = "[Optional]Direct listen ip address which httptracker process use. Default is 0.0.0.0 .", ) args = parser.parse_args() ipaddress = "" port = "" if args.ipaddress != "0.0.0.0": ipaddress= args.ipaddress[0] else: ipaddress = args.ipaddress if args.port != 8000: port = str(args.port[0]) else: port = str(args.port) command = ["python3", os.path.dirname(__file__) + "/manage.py", "runserver", ipaddress + ":" + port] if args.mode: mode = args.mode[0] if mode == "start": startProcess(command, port) elif mode == "restart": stopProcess(command) startProcess(command, port) elif mode == "stop": stopProcess(command) else: parser.error('Argument "--mode" need only "start", "restart", "stop".') except SystemExit: pass except: print("[Error] " + traceback.format_exc().splitlines()[-1], file=sys.stderr) if __name__ == '__main__': main()

30.169492

108

0.538202

301

0.084551

0

808

0.226966

5463fe7521a3910ac70e77bb4ec4fc1c354e171b

35

py

Python

pyble/const/characteristic/sensor_location.py

bgromov/PyBLEWrapper

8a5d016e65b3c259391ddc97c371ab4b1b5c61b5

[ "MIT" ]

14

2015-03-30T23:11:36.000Z

2020-04-07T00:57:12.000Z

pyble/const/characteristic/sensor_location.py

bgromov/PyBLEWrapper

8a5d016e65b3c259391ddc97c371ab4b1b5c61b5

[ "MIT" ]

3

2016-05-17T06:11:07.000Z

2017-05-15T16:43:09.000Z

pyble/const/characteristic/sensor_location.py

bgromov/PyBLEWrapper

8a5d016e65b3c259391ddc97c371ab4b1b5c61b5

[ "MIT" ]

11

2016-03-11T08:53:03.000Z

2019-03-11T21:32:13.000Z

NAME="Sensor Location" UUID=0x2A5D

11.666667

22

0.8

0

17

0.485714

546484ce8b5ed762d88a0033bf3308f52967f631

296

py

Python

active-learning/seq_data.py

ansunsujoe/ml-research

7ab529a5ec1d420385e64b9eebf87e0847b85afd

[ "MIT" ]

null

active-learning/seq_data.py

ansunsujoe/ml-research

7ab529a5ec1d420385e64b9eebf87e0847b85afd

[ "MIT" ]

null

active-learning/seq_data.py

ansunsujoe/ml-research

7ab529a5ec1d420385e64b9eebf87e0847b85afd

[ "MIT" ]

null

import random from tqdm import tqdm def random_seq(): return [str(random.randint(1, 9)) for x in range(random.randint(2, 15))] if __name__ == "__main__": with open("sequences-1-train.txt", "w") as f: for i in tqdm(range(5000)): f.write(",".join(random_seq()) + "\n")

29.6

76

0.614865

0

43

0.14527

546488ac5fe6da6a714985e1c5c6692b62df9032

3,585

py

Python

datatest/main.py

ajhynes7/datatest

78742e98de992807286655f5685a2dc33a7b452e

[ "Apache-2.0" ]

277

2016-05-12T13:22:49.000Z

2022-03-11T00:18:32.000Z

datatest/main.py

ajhynes7/datatest

78742e98de992807286655f5685a2dc33a7b452e

[ "Apache-2.0" ]

57

2016-05-18T01:03:32.000Z

2022-02-17T13:48:43.000Z

datatest/main.py

ajhynes7/datatest

78742e98de992807286655f5685a2dc33a7b452e

[ "Apache-2.0" ]

16

2016-05-22T11:35:19.000Z

2021-12-01T19:41:42.000Z

"""Datatest main program""" import sys as _sys from unittest import TestProgram as _TestProgram from unittest import defaultTestLoader as _defaultTestLoader try: from unittest.signals import installHandler except ImportError: installHandler = None from datatest import DataTestRunner __unittest = True __datatest = True class DataTestProgram(_TestProgram): def __init__(self, module='__main__', defaultTest=None, argv=None, testRunner=DataTestRunner, testLoader=_defaultTestLoader, exit=True, verbosity=1, failfast=None, catchbreak=None, buffer=None, ignore=False): self.ignore = ignore _TestProgram.__init__(self, module=module, defaultTest=defaultTest, argv=argv, testRunner=testRunner, testLoader=testLoader, exit=exit, verbosity=verbosity, failfast=failfast, catchbreak=catchbreak, buffer=buffer) def runTests(self): try: if self.catchbreak and installHandler: installHandler() except AttributeError: pass # does not have catchbreak attribute if self.testRunner is None: self.testRunner = DataTestRunner if isinstance(self.testRunner, type): try: kwds = ['verbosity', 'failfast', 'buffer', 'warnings', 'ignore'] kwds = [attr for attr in kwds if hasattr(self, attr)] kwds = dict((attr, getattr(self, attr)) for attr in kwds) testRunner = self.testRunner(**kwds) except TypeError: if 'warnings' in kwds: del kwds['warnings'] testRunner = self.testRunner(**kwds) else: # assumed to be a TestRunner instance testRunner = self.testRunner self.result = testRunner.run(self.test) if self.exit: _sys.exit(not self.result.wasSuccessful()) if _sys.version_info[:2] == (3, 1): # Patch methods for Python 3.1. def __init__(self, module='__main__', defaultTest=None, argv=None, testRunner=DataTestRunner, testLoader=_defaultTestLoader, exit=True, ignore=False): self.ignore = ignore _TestProgram.__init__(self, module=module, defaultTest=defaultTest, argv=argv, testRunner=testRunner, testLoader=testLoader, exit=exit) DataTestProgram.__init__ = __init__ elif _sys.version_info[:2] == (2, 6): # Patch runTests() for Python 2.6. def __init__(self, module='__main__', defaultTest=None, argv=None, testRunner=DataTestRunner, testLoader=_defaultTestLoader, exit=True, ignore=False): self.exit = exit # <- 2.6 does not handle exit argument. self.ignore = ignore _TestProgram.__init__(self, module=module, defaultTest=defaultTest, argv=argv, testRunner=testRunner, testLoader=testLoader) DataTestProgram.__init__ = __init__ main = DataTestProgram

38.138298

80

0.538633

1,883

0.525244

0

301

0.083961

54655fd5e9013ea6eec439615853e317aa7b100b

17,503

py

Python

zvmsdk/vmops.py

jasealpers/python-zvm-sdk

feb19dd40915b1a6cad74e7ccda17bc76d015ea5

[ "Apache-2.0" ]

9

2017-06-13T17:46:33.000Z

2019-01-08T03:00:00.000Z

zvmsdk/vmops.py

jasealpers/python-zvm-sdk

feb19dd40915b1a6cad74e7ccda17bc76d015ea5

[ "Apache-2.0" ]

4

2018-07-18T21:41:21.000Z

2019-01-07T06:05:15.000Z

zvmsdk/vmops.py

jasealpers/python-zvm-sdk

feb19dd40915b1a6cad74e7ccda17bc76d015ea5

[ "Apache-2.0" ]

20

2017-02-27T09:46:13.000Z

2019-05-29T23:17:52.000Z

# Copyright 2017 IBM Corp. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import os import six from zvmsdk import config from zvmsdk import dist from zvmsdk import exception from zvmsdk import log from zvmsdk import smtclient from zvmsdk import database from zvmsdk import utils as zvmutils _VMOPS = None CONF = config.CONF LOG = log.LOG def get_vmops(): global _VMOPS if _VMOPS is None: _VMOPS = VMOps() return _VMOPS class VMOps(object): def __init__(self): self._smtclient = smtclient.get_smtclient() self._dist_manager = dist.LinuxDistManager() self._pathutils = zvmutils.PathUtils() self._namelist = zvmutils.get_namelist() self._GuestDbOperator = database.GuestDbOperator() self._ImageDbOperator = database.ImageDbOperator() def get_power_state(self, userid): """Get power status of a z/VM instance.""" return self._smtclient.get_power_state(userid) def _get_cpu_num_from_user_dict(self, dict_info): cpu_num = 0 for inf in dict_info: if 'CPU ' in inf: cpu_num += 1 return cpu_num def _get_max_memory_from_user_dict(self, dict_info): with zvmutils.expect_invalid_resp_data(): mem = dict_info[0].split(' ')[4] return zvmutils.convert_to_mb(mem) * 1024 def get_info(self, userid): power_stat = self.get_power_state(userid) perf_info = self._smtclient.get_image_performance_info(userid) if perf_info: try: max_mem_kb = int(perf_info['max_memory'].split()[0]) mem_kb = int(perf_info['used_memory'].split()[0]) num_cpu = int(perf_info['guest_cpus']) cpu_time_us = int(perf_info['used_cpu_time'].split()[0]) except (ValueError, TypeError, IndexError, AttributeError, KeyError) as err: LOG.error('Parse performance_info encounter error: %s', str(perf_info)) raise exception.SDKInternalError(msg=str(err), modID='guest') return {'power_state': power_stat, 'max_mem_kb': max_mem_kb, 'mem_kb': mem_kb, 'num_cpu': num_cpu, 'cpu_time_us': cpu_time_us} else: # virtual machine in shutdown state or not exists dict_info = self._smtclient.get_user_direct(userid) return { 'power_state': power_stat, 'max_mem_kb': self._get_max_memory_from_user_dict(dict_info), 'mem_kb': 0, 'num_cpu': self._get_cpu_num_from_user_dict(dict_info), 'cpu_time_us': 0} def instance_metadata(self, instance, content, extra_md): pass def add_instance_metadata(self): pass def is_reachable(self, userid): """Reachable through IUCV communication channel.""" return self._smtclient.get_guest_connection_status(userid) def guest_start(self, userid): """"Power on z/VM instance.""" LOG.info("Begin to power on vm %s", userid) self._smtclient.guest_start(userid) LOG.info("Complete power on vm %s", userid) def guest_stop(self, userid, **kwargs): LOG.info("Begin to power off vm %s", userid) self._smtclient.guest_stop(userid, **kwargs) LOG.info("Complete power off vm %s", userid) def guest_softstop(self, userid, **kwargs): LOG.info("Begin to soft power off vm %s", userid) self._smtclient.guest_softstop(userid, **kwargs) LOG.info("Complete soft power off vm %s", userid) def guest_pause(self, userid): LOG.info("Begin to pause vm %s", userid) self._smtclient.guest_pause(userid) LOG.info("Complete pause vm %s", userid) def guest_unpause(self, userid): LOG.info("Begin to unpause vm %s", userid) self._smtclient.guest_unpause(userid) LOG.info("Complete unpause vm %s", userid) def guest_reboot(self, userid): """Reboot a guest vm.""" LOG.info("Begin to reboot vm %s", userid) self._smtclient.guest_reboot(userid) LOG.info("Complete reboot vm %s", userid) def guest_reset(self, userid): """Reset z/VM instance.""" LOG.info("Begin to reset vm %s", userid) self._smtclient.guest_reset(userid) LOG.info("Complete reset vm %s", userid) def live_migrate_vm(self, userid, destination, parms, action): """Move an eligible, running z/VM(R) virtual machine transparently from one z/VM system to another within an SSI cluster.""" # Check guest state is 'on' state = self.get_power_state(userid) if state != 'on': LOG.error("Failed to live migrate guest %s, error: " "guest is inactive, cann't perform live migrate." % userid) raise exception.SDKConflictError(modID='guest', rs=1, userid=userid) # Do live migrate if action.lower() == 'move': LOG.info("Moving the specific vm %s", userid) self._smtclient.live_migrate_move(userid, destination, parms) LOG.info("Complete move vm %s", userid) if action.lower() == 'test': LOG.info("Testing the eligiblity of specific vm %s", userid) self._smtclient.live_migrate_test(userid, destination) def create_vm(self, userid, cpu, memory, disk_list, user_profile, max_cpu, max_mem, ipl_from, ipl_param, ipl_loadparam): """Create z/VM userid into user directory for a z/VM instance.""" LOG.info("Creating the user directory for vm %s", userid) info = self._smtclient.create_vm(userid, cpu, memory, disk_list, user_profile, max_cpu, max_mem, ipl_from, ipl_param, ipl_loadparam) # add userid into smapi namelist self._smtclient.namelist_add(self._namelist, userid) return info def create_disks(self, userid, disk_list): LOG.info("Beging to create disks for vm: %(userid)s, list: %(list)s", {'userid': userid, 'list': disk_list}) user_direct = self._smtclient.get_user_direct(userid) exist_disks = [] for ent in user_direct: if ent.strip().startswith('MDISK'): md_vdev = ent.split()[1].strip() exist_disks.append(md_vdev) if exist_disks: start_vdev = hex(int(max(exist_disks), 16) + 1)[2:].rjust(4, '0') else: start_vdev = None info = self._smtclient.add_mdisks(userid, disk_list, start_vdev) LOG.info("Complete create disks for vm: %s", userid) return info def delete_disks(self, userid, vdev_list): LOG.info("Begin to delete disk on vm: %(userid), vdev list: %(list)s", {'userid': userid, 'list': vdev_list}) # not support delete disks when guest is active if self._smtclient.get_power_state(userid) == 'on': func = 'delete disks when guest is active' raise exception.SDKFunctionNotImplementError(func) self._smtclient.remove_mdisks(userid, vdev_list) LOG.info("Complete delete disks for vm: %s", userid) def guest_config_minidisks(self, userid, disk_info): LOG.info("Begin to configure disks on vm: %(userid), info: %(info)s", {'userid': userid, 'info': disk_info}) if disk_info != []: self._smtclient.process_additional_minidisks(userid, disk_info) LOG.info("Complete configure disks for vm: %s", userid) else: LOG.info("No disk to handle on %s." % userid) def is_powered_off(self, instance_name): """Return True if the instance is powered off.""" return self._smtclient.get_power_state(instance_name) == 'off' def delete_vm(self, userid): """Delete z/VM userid for the instance.""" LOG.info("Begin to delete vm %s", userid) self._smtclient.delete_vm(userid) # remove userid from smapi namelist self._smtclient.namelist_remove(self._namelist, userid) LOG.info("Complete delete vm %s", userid) def execute_cmd(self, userid, cmdStr): """Execute commands on the guest vm.""" LOG.debug("executing cmd: %s", cmdStr) return self._smtclient.execute_cmd(userid, cmdStr) def set_hostname(self, userid, hostname, os_version): """Punch a script that used to set the hostname of the guest. :param str guest: the user id of the guest :param str hostname: the hostname of the guest :param str os_version: version of guest operation system """ tmp_path = self._pathutils.get_guest_temp_path(userid) if not os.path.exists(tmp_path): os.makedirs(tmp_path) tmp_file = tmp_path + '/hostname.sh' lnxdist = self._dist_manager.get_linux_dist(os_version)() lines = lnxdist.generate_set_hostname_script(hostname) with open(tmp_file, 'w') as f: f.writelines(lines) requestData = "ChangeVM " + userid + " punchfile " + \ tmp_file + " --class x" LOG.debug("Punch script to guest %s to set hostname" % userid) try: self._smtclient._request(requestData) except exception.SDKSMTRequestFailed as err: msg = ("Failed to punch set_hostname script to userid '%s'. SMT " "error: %s" % (userid, err.format_message())) LOG.error(msg) raise exception.SDKSMTRequestFailed(err.results, msg) finally: self._pathutils.clean_temp_folder(tmp_path) def guest_deploy(self, userid, image_name, transportfiles=None, remotehost=None, vdev=None, hostname=None): LOG.info("Begin to deploy image on vm %s", userid) self._smtclient.guest_deploy(userid, image_name, transportfiles, remotehost, vdev) # punch scripts to set hostname if (transportfiles is None) and hostname: image_info = self._ImageDbOperator.image_query_record(image_name) os_version = image_info[0]['imageosdistro'] self.set_hostname(userid, hostname, os_version) def guest_capture(self, userid, image_name, capture_type='rootonly', compress_level=6): LOG.info("Begin to capture vm %(userid), image name is %(name)s", {'userid': userid, 'name': image_name}) self._smtclient.guest_capture(userid, image_name, capture_type=capture_type, compress_level=compress_level) LOG.info("Complete capture image on vm %s", userid) def guest_list(self): return self._smtclient.get_vm_list() def get_definition_info(self, userid, **kwargs): check_command = ["nic_coupled"] direct_info = self._smtclient.get_user_direct(userid) info = {} info['user_direct'] = direct_info for k, v in kwargs.items(): if k in check_command: if (k == 'nic_coupled'): info['nic_coupled'] = False nstr = "NICDEF %s TYPE QDIO LAN SYSTEM" % v for inf in direct_info: if nstr in inf: info['nic_coupled'] = True break else: raise exception.SDKInvalidInputFormat( msg=("invalid check option for user direct: %s") % k) return info def get_console_output(self, userid): def append_to_log(log_data, log_path): LOG.debug('log_data: %(log_data)r, log_path: %(log_path)r', {'log_data': log_data, 'log_path': log_path}) with open(log_path, 'a+') as fp: fp.write(log_data) return log_path LOG.info("Begin to capture console log on vm %s", userid) log_size = CONF.guest.console_log_size * 1024 console_log = self._smtclient.get_user_console_output(userid) log_path = self._pathutils.get_console_log_path(userid) # TODO: need consider shrink log file size append_to_log(console_log, log_path) log_fp = open(log_path, 'rb') try: log_data, remaining = zvmutils.last_bytes(log_fp, log_size) except Exception as err: msg = ("Failed to truncate console log, error: %s" % six.text_type(err)) LOG.error(msg) raise exception.SDKInternalError(msg) if remaining > 0: LOG.info('Truncated console log returned, %d bytes ignored' % remaining) LOG.info("Complete get console output on vm %s", userid) return log_data def check_guests_exist_in_db(self, userids, raise_exc=True): if not isinstance(userids, list): # convert userid string to list userids = [userids] all_userids = self.guest_list() userids_not_in_db = list(set(userids) - set(all_userids)) if userids_not_in_db: if raise_exc: # log and raise exception userids_not_in_db = ' '.join(userids_not_in_db) LOG.error("Guest '%s' does not exist in guests database" % userids_not_in_db) raise exception.SDKObjectNotExistError( obj_desc=("Guest '%s'" % userids_not_in_db), modID='guest') else: return False else: userids_migrated = self._GuestDbOperator.get_migrated_guest_list() userids_in_migrated = list(set(userids) & set(userids_migrated)) # case1 userid has been migrated. if userids_in_migrated: if raise_exc: migrated_userids = ' '.join(userids_in_migrated) LOG.error("Guest(s) '%s' has been migrated." % migrated_userids) raise exception.SDKObjectNotExistError( obj_desc=("Guest(s) '%s'" % migrated_userids), modID='guest') else: return False flag = True for uid in userids: # case2 userid has been shudown and started on other host. if zvmutils.check_userid_on_others(uid): flag = False comment = self._GuestDbOperator.get_comments_by_userid(uid) comment['migrated'] = 1 action = "update guest '%s' in database" % uid with zvmutils.log_and_reraise_sdkbase_error(action): self._GuestDbOperator.update_guest_by_userid( uid, comments=comment) return flag def live_resize_cpus(self, userid, count): # Check power state is 'on' state = self.get_power_state(userid) if state != 'on': LOG.error("Failed to live resize cpus of guest %s, error: " "guest is inactive, cann't perform live resize." % userid) raise exception.SDKConflictError(modID='guest', rs=1, userid=userid) # Do live resize self._smtclient.live_resize_cpus(userid, count) LOG.info("Complete live resize cpu on vm %s", userid) def resize_cpus(self, userid, count): LOG.info("Begin to resize cpu on vm %s", userid) # Do resize self._smtclient.resize_cpus(userid, count) LOG.info("Complete resize cpu on vm %s", userid) def live_resize_memory(self, userid, memory): # Check power state is 'on' state = self.get_power_state(userid) if state != 'on': LOG.error("Failed to live resize memory of guest %s, error: " "guest is inactive, cann't perform live resize." % userid) raise exception.SDKConflictError(modID='guest', rs=1, userid=userid) # Do live resize self._smtclient.live_resize_memory(userid, memory) LOG.info("Complete live resize memory on vm %s", userid) def resize_memory(self, userid, memory): LOG.info("Begin to resize memory on vm %s", userid) # Do resize self._smtclient.resize_memory(userid, memory) LOG.info("Complete resize memory on vm %s", userid)

40.144495

79

0.588642

16,527

0.944238

0

4,442

0.253785

546685a1cd267c088cdbed690f4354973078c4ca

3,481

py

Python

Q146.py

Linchin/python_leetcode_git

3d08ab04bbdbd2ce268f33c501fbb149662872c7

[ "MIT" ]

null

Q146.py

Linchin/python_leetcode_git

3d08ab04bbdbd2ce268f33c501fbb149662872c7

[ "MIT" ]

null

Q146.py

Linchin/python_leetcode_git

3d08ab04bbdbd2ce268f33c501fbb149662872c7

[ "MIT" ]

null

""" Q146 LRU Cache Medium Author: Lingqing Gan Date: 08/06/2019 Question: Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put. get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1. put(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item. The cache is initialized with a positive capacity. Follow up: Could you do both operations in O(1) time complexity? notes: linked list + dict(hash map) 12/24/2019 Merry Xmas~~ Now the code I wrote is working correctly. Just not very efficient. Time to learn how the tutorial did it. """ class LRUCache: class Node: def __init__(self, key, val): self.key = key self.val = val self.next = None self.prev = None def __init__(self, capacity: int): self.cap = capacity self.size = 0 self.hash = {} self.head = None self.tail = None def get(self, key: int) -> int: if key not in self.hash: return -1 # if the inquired node is the last/only node if self.hash[key].next is None: return self.hash[key].val # AT LEAST 2 NODES # move the inquired node to the end of the linked list # handle head and tail of the linked list if self.head == self.hash[key]: self.head = self.head.next last = self.tail.key self.tail.next = self.hash[key] self.tail = self.hash[key] # connect the nodes before and after the inquired node if self.hash[key].prev is not None: self.hash[key].prev.next = self.hash[key].next if self.hash[key].next is not None: self.hash[key].next.prev = self.hash[key].prev # update the prev/next node of the inquired node self.hash[key].prev = self.hash[last] self.hash[key].next = None return self.hash[key].val def put(self, key: int, value: int) -> None: # if the key exists if key in self.hash: self.hash[key].val = value self.get(key) return 0 # if key is new self.hash[key] = self.Node(key, value) if self.size == 0: # first node self.head = self.tail = self.hash[key] self.size = 1 elif self.size < self.cap: # capacity not reached, just add new node to the end self.tail.next = self.hash[key] self.hash[key].prev = self.tail self.tail = self.hash[key] self.size += 1 else: # capacity reached, need to remove LRU node self.tail.next = self.hash[key] self.hash[key].prev = self.tail self.tail = self.hash[key] first = self.head.key self.head = self.head.next self.head.prev = None del self.hash[first] # Your LRUCache object will be instantiated and called as such: # obj = LRUCache(capacity) # param_1 = obj.get(key) # obj.put(key,value) capacity = 2 cache = LRUCache(capacity) cache.put(1,1) cache.put(2,2) print(cache.get(1)) cache.put(3,3) print(cache.get(2)) cache.put(4,4) print(cache.get(1)) print(cache.get(3)) print(cache.get(4))

26.172932

76

0.600402

2,325

0.667912

0

1,341

0.385234

54670eac7c97edca8f6b8dd01151c748a6156511

9,940

py

Python

bin/genparams.py

neonkingfr/VizBench

e41f559cb6e761d717f2f5b202482d5d8dacd2d8

[ "MIT" ]

7

2015-01-05T06:32:49.000Z

2020-10-30T19:29:07.000Z

bin/genparams.py

neonkingfr/VizBench

e41f559cb6e761d717f2f5b202482d5d8dacd2d8

[ "MIT" ]

null

bin/genparams.py

neonkingfr/VizBench

e41f559cb6e761d717f2f5b202482d5d8dacd2d8

[ "MIT" ]

4

2016-03-09T22:29:26.000Z

2021-04-07T13:52:28.000Z

# This script reads *VizParams.list files that define Vizlet parameters # and generates .h files for them, making runtime access to them much faster. # This allows new parameters to be added just by editing one file. import sys import os import re types={"bool":"BOOL","int":"INT","double":"DBL","string":"STR"} realtypes={"bool":"bool","int":"int","double":"double","string":"std::string"} paramtypes={"bool":"BoolParam","int":"IntParam","double":"DoubleParam","string":"StringParam"} def readparams(listfile): try: f = open(listfile) except: print(sys.stderr,"Unable to open "+listfile) sys.exit(1) lines = f.readlines() params = [] for ln in lines: if len(ln) == 0: continue if ln[0] == '#': continue if ln[0] == ':': # These lines are used to define string values vals = ln.split(None,5) (name,typ,mn,mx,default,comment) = vals continue vals = ln.split(None,5) (name,typ,mn,mx,default,comment) = vals params.append( { "name": name, "type": typ, "min": mn, "max": mx, "default": default, "comment": comment } ) params = sorted(params, key=lambda dct: dct['name']) return params def writeln(line): sys.stdout.write(line+"\n") def write(line): sys.stdout.write(line) def genparamcpp(paramclass): writeln("#include \"VizParams.h\"") writeln("#include \""+paramclass+".h\"") writeln("char* "+paramclass+"Names[] = { "+paramclass+"Names_INIT };") ## utility to make sure floating-point values are printed with a decimal point ## so function calls/etc get disambiguated between double and int. def s2d(d): return "%f" % float(d); def genparamheader(params,classname): uptype = classname.upper() tab = "\t" tab2 = "\t\t" tab3 = "\t\t\t" writeln("#ifndef _"+uptype+"_H") writeln("#define _"+uptype+"_H") writeln("#include \"VizParams.h\"") writeln("#include \"VizJSON.h\"") writeln("") ### Generate a declaration for the array of parameter names. ### The actual storage for it needs to be declared in a non-header file. writeln("extern char* "+paramnames+"[];") writeln("") ### Generate a macro which is all the parameter names, used to initialize that array writeln("#define "+paramnames+"_INIT \\") for p in params: name = p["name"] writeln(tab+"\"%s\",\\"%(name)) writeln(tab+"NULL") writeln("") ### Start the class writeln("class "+classname+" : public VizParams {") writeln("public:") ### Generate the class constructor writeln(tab+classname+"() {") writeln(tab2+"loadDefaults();") writeln(tab+"}") writeln(tab+"char **ListOfNames() { return "+paramnames+"; }"); writeln(tab+"// std::string JsonListOfValues() { return _JsonListOfValues("+paramnames+"); }"); writeln(tab+"// std::string JsonListOfParams() { return _JsonListOfParams("+paramnames+"); }"); writeln(tab+"std::string JsonListOfStringValues(std::string type) { return _JsonListOfStringValues(type); }"); ### Generate the method that loads JSON writeln(tab+"void loadJson(cJSON* json) {") writeln(tab2+"cJSON* j;") for p in params: name = p["name"] typ = p["type"] writeln(tab2+"j = cJSON_GetObjectItem(json,\""+name+"\");") writeln(tab2+"if (j) { "+name+".set(j); }") writeln(tab+"}") ### Generate the method that loads default values writeln(tab+"void loadDefaults() {") for p in params: name = p["name"] typ = p["type"] defaultvalue = p["default"] if typ == "double": defaultvalue = s2d(defaultvalue) writeln(tab2+name+".set("+defaultvalue+");") writeln(tab+"}") ### Generate the method that applies one params to another writeln(tab+"void applyVizParamsFrom("+classname+"* p) {") writeln(tab2+"if ( ! p ) { return; }"); for p in params: name = p["name"] typ = p["type"] writeln(tab2+"if ( p->"+name+".isset() ) { this->"+name+".set(p->"+name+".get()); }"); writeln(tab+"}") ### Generate the Set method writeln(tab+"void Set(std::string nm, std::string val) {") writeln(tab2+"bool stringval = false;") estr = "" for p in params: name = p["name"] writeln(tab2+estr+"if ( nm == \""+name+"\" ) {") typ = p["type"] if typ == "double": writeln(tab3+name+".set(string2double(val));") elif typ == "int": writeln(tab3+name+".set(string2int(val));") elif typ == "bool": writeln(tab3+name+".set(string2bool(val));") elif typ == "string": writeln(tab3+name+".set(val);") writeln(tab3+"stringval = true;") estr = "} else " writeln(tab2+"}") writeln("") writeln(tab2+"if ( ! stringval ) {") writeln(tab3+"Increment(nm,0.0); // abide by limits, using code in Increment") writeln(tab2+"}") writeln(tab+"}") ### Generate the Increment method writeln(tab+"void Increment(std::string nm, double amount) {") estr = "" for p in params: name = p["name"] typ = p["type"] mn = p["min"] mx = p["max"] writeln(tab2+estr+"if ( nm == \""+name+"\" ) {") if typ == "double": writeln(tab3+name+".set(adjust("+name+".get(),amount,"+s2d(mn)+","+s2d(mx)+"));") elif typ == "int": writeln(tab3+name+".set(adjust("+name+".get(),amount,"+mn+","+mx+"));") elif typ == "bool": writeln(tab3+name+".set(adjust("+name+".get(),amount));") elif typ == "string": vals = p["min"] if vals == "*": writeln(tab3+"// '*' means the value can be anything"); else: writeln(tab3+name+".set(adjust("+name+".get(),amount,VizParams::StringVals[\""+vals+"\"]));") estr = "} else " writeln(tab2+"}") writeln("") writeln(tab+"}") ### Generate the DefaultValue method writeln(tab+"std::string DefaultValue(std::string nm) {") estr = "" for p in params: name = p["name"] typ = p["type"] default = p["default"] if default[0] != "\"": default = "\"" + default + "\"" writeln(tab2+estr+"if ( nm == \""+name+"\" ) { return "+default+"; }"); writeln(tab2+"return \"\";"); writeln(tab+"}") ### Generate the MinValue method writeln(tab+"std::string MinValue(std::string nm) {") estr = "" for p in params: name = p["name"] typ = p["type"] mn = p["min"] write(tab2+estr+"if ( nm == \""+name+"\" ) { ") if typ == "double": write("return \""+mn+"\";"); elif typ == "int": write("return \""+mn+"\";"); elif typ == "bool": write("return \"false\";"); elif typ == "string": write("return \""+mn+"\";"); writeln(" }"); writeln(tab2+"return \"\";"); writeln(tab+"}") ### Generate the MaxValue method writeln(tab+"std::string MaxValue(std::string nm) {") estr = "" for p in params: name = p["name"] typ = p["type"] mx = p["max"] write(tab2+estr+"if ( nm == \""+name+"\" ) { ") if typ == "double": write("return \""+mx+"\";"); elif typ == "int": write("return \""+mx+"\";"); elif typ == "bool": write("return \"true\";"); elif typ == "string": write("return \""+mx+"\";"); writeln(" }"); writeln(tab2+"return \"\";"); writeln(tab+"}") ### Generate the Toggle method writeln(tab+"void Toggle(std::string nm) {") writeln(tab2+"bool stringval = false;") estr = "" for p in params: name = p["name"] typ = p["type"] if typ == "bool": writeln(tab2+estr+"if ( nm == \""+name+"\" ) {") writeln(tab3+name+".set( ! "+name+".get());") writeln(tab2+"}") estr = "else " writeln(tab+"}") ### Generate the Get method writeln(tab+"std::string GetAsString(std::string nm) {") estr = "" for p in params: name = p["name"] typ = p["type"] writeln(tab2+estr+"if ( nm == \""+name+"\" ) {") if typ == "double": writeln(tab3+"return DoubleString("+name+".get());") elif typ == "int": writeln(tab3+"return IntString("+name+".get());") elif typ == "bool": writeln(tab3+"return BoolString("+name+".get());") elif typ == "string": writeln(tab3+"return "+name+".get();") estr = "} else " writeln(tab2+"}") writeln(tab2+"return \"\";") writeln(tab+"}") ### Generate the GetType method writeln(tab+"std::string GetType(std::string nm) {") for p in params: name = p["name"] typ = p["type"] writeln(tab2+"if ( nm == \""+name+"\" ) { return \""+typ+"\"; }") writeln(tab2+"return \"\";") writeln(tab+"}") ### Generate the member declarations writeln("") for p in params: name = p["name"] typ = p["type"] paramtype = paramtypes[typ] writeln(tab+paramtype+" "+name+";") writeln("};") writeln("") writeln("#endif") def modtime(file): try: return os.path.getmtime(file) except: return -1 if __name__ != "__main__": print "This code needs to be invoked as a main program." sys.exit(1) if len(sys.argv) < 2: print("Usage: %s {paramlist}" % sys.argv[0]) sys.exit(1) # We expect this program to be invoked from the VizBench/bin directory # so everything can be full paths without depending on environment variables paramdir = "../src/params" if not os.path.isdir(paramdir): print("No directory "+paramdir+" !?") sys.exit(1) os.chdir(paramdir) force = False if len(sys.argv) > 2 and sys.argv[1] == "-f": force = True parambase = sys.argv[2] else: parambase = sys.argv[1] paramclass = parambase+"VizParams" paramlist = parambase+"VizParams.list" paramtouch = parambase+"VizParams.touch" paramnames = parambase+"VizParamsNames" file_h = parambase + "VizParams.h" file_cpp = parambase + "VizParams.cpp" changed = force or (modtime(paramlist) > modtime(paramtouch) ) or not os.path.exists(file_h) or not os.path.exists(file_cpp) if not changed: print "No change in "+paramlist sys.exit(0) do_not_edit = "/************************************************\n" \ " *\n" \ " * This file is generated from '"+paramlist+"' by genparams.py\n" \ " *\n" \ " * DO NOT EDIT!\n" \ " *\n" \ " ************************************************/\n"; f = open(file_h,"w") f.write(do_not_edit) sys.stdout = f params = readparams(paramlist) genparamheader(params,paramclass) f.close() f = open(file_cpp,"w") f.write(do_not_edit); sys.stdout = f genparamcpp(paramclass) f.close() def touch(filename): f = open(filename,"w") f.write("# This file exists to record the last build time\n"); f.close() touch(paramtouch)

27.458564

124

0.609557

0

4,639

0.466606

54685a8741677f7fae5e8b83b5e24b77c1c400f9

712

py

Python

notebooks/session_4/s3-sobelAndmatplotlib.py

bigmpc/cv-spring-2021

81d9384f74f5411804cdbb26be5b7ced0d0f5958

[ "Apache-2.0" ]

3

2021-03-09T10:00:50.000Z

2021-12-26T07:19:09.000Z

notebooks/session_4/s3-sobelAndmatplotlib.py

bigmpc/cv-spring-2021

81d9384f74f5411804cdbb26be5b7ced0d0f5958

[ "Apache-2.0" ]

null

notebooks/session_4/s3-sobelAndmatplotlib.py

bigmpc/cv-spring-2021

81d9384f74f5411804cdbb26be5b7ced0d0f5958

[ "Apache-2.0" ]

1

2021-02-27T16:09:30.000Z

import cv2 import numpy as np import matplotlib.pyplot as plt #Read the image as grayscale: image = cv2.imread('building.jpg', 0) #Compute the gradient approximations using the Sobel operator: dx = cv2.Sobel(image, cv2.CV_32F, 1, 0) dy = cv2.Sobel(image, cv2.CV_32F, 0, 1) #Visualize the results: plt.figure() plt.subplot(141) plt.axis('off') plt.title('image') plt.imshow(image, cmap='gray') plt.subplot(142) plt.axis('off') plt.imshow(dx, cmap='gray') plt.title('dx') plt.subplot(143) plt.axis('off') plt.imshow(dy, cmap='gray') plt.title('dx') plt.subplot(144) plt.axis('off') plt.title('dy + dx') plt.imshow(np.absolute(dx)+np.absolute(dy), cmap='gray') plt.show()

19.777778

63

0.671348

0

199

0.279494

5468626a4d8739106b686cc86e072541eeccc86e

956

py

Python

reporter-cli/sql-pdf/python/src/reporterprimary/__init__.py

rgolubtsov/reporter-multilang

6d7e04bbd57342ea80e1beccea3c4de1b1c4e203

[ "Unlicense" ]

3

2017-04-28T16:40:22.000Z

2019-02-22T16:57:12.000Z

reporter-cli/sql-pdf/python/src/reporterprimary/__init__.py

rgolubtsov/reporter-multilang

6d7e04bbd57342ea80e1beccea3c4de1b1c4e203

[ "Unlicense" ]

46

2017-01-17T01:10:15.000Z

2019-06-13T20:45:12.000Z

reporter-cli/sql-pdf/python/src/reporterprimary/__init__.py

rgolubtsov/reporter-multilang

6d7e04bbd57342ea80e1beccea3c4de1b1c4e203

[ "Unlicense" ]

1

2017-07-06T14:18:55.000Z

# -*- coding: utf-8 -*- # reporter-cli/sql-pdf/python/src/reporterprimary/__init__.py # ============================================================================= # Reporter Multilang. Version 0.5.9 # ============================================================================= # A tool to generate human-readable reports based on data from various sources # with the focus on its implementation using a series of programming languages. # ============================================================================= # Written by Radislav (Radicchio) Golubtsov, 2016-2021 # # This is free and unencumbered software released into the public domain. # # Anyone is free to copy, modify, publish, use, compile, sell, or # distribute this software, either in source code form or as a compiled # binary, for any purpose, commercial or non-commercial, and by any # means. # # (See the LICENSE file at the top of the source tree.) # # vim:set nu et ts=4 sw=4:

45.52381

79

0.561715

0

936

0.979079

5468c394ce1fe6e2cc2dd6fce2fd7d4c6e567c44

3,494

py

Python

bem/teq_planet.py

DanielAndreasen/bem

c4cca79322f08b5e9a3f3d39749c11d9f6296aae

[ "MIT" ]

null

bem/teq_planet.py

DanielAndreasen/bem

c4cca79322f08b5e9a3f3d39749c11d9f6296aae

[ "MIT" ]

null

bem/teq_planet.py

DanielAndreasen/bem

c4cca79322f08b5e9a3f3d39749c11d9f6296aae

[ "MIT" ]

null

import numpy as np from uncertainties import umath as um def getTeqpl(Teffst, aR, ecc, A=0, f=1/4.): """Return the planet equilibrium temperature. Relation adapted from equation 4 page 4 in http://www.mpia.de/homes/ppvi/chapter/madhusudhan.pdf and https://en.wikipedia.org/wiki/Stefan%E2%80%93Boltzmann_law and later updated to include the effect of excentricity on the average stellar planet distance according to equation 5 p 25 of Laughlin & Lissauer 2015arXiv150105685L (1501.05685) Plus Exoplanet atmospheres, physical processes, Sara Seager, p30 eq 3.9 for f contribution. :param float/np.ndarray Teffst: Effective temperature of the star :param float/np.ndarray aR: Ration of the planetary orbital semi-major axis over the stellar radius (without unit) :param float/np.ndarray A: Bond albedo (should be between 0 and 1) :param float/np.ndarray f: Redistribution factor. If 1/4 the energy is uniformly redistributed over the planetary surface. If f = 2/3, no redistribution at all, the atmosphere immediately reradiate whithout advection. :return float/np.ndarray Teqpl: Equilibrium temperature of the planet """ return Teffst * (f * (1 - A))**(1 / 4.) * np.sqrt(1 / aR) / (1 - ecc**2)**(1/8.) def getTeqpl_error(Teffst, aR, ecc, A=0, f=1/4.): """Return the planet equilibrium temperature. Relation adapted from equation 4 page 4 in http://www.mpia.de/homes/ppvi/chapter/madhusudhan.pdf and https://en.wikipedia.org/wiki/Stefan%E2%80%93Boltzmann_law and later updated to include the effect of excentricity on the average stellar planet distance according to equation 5 p 25 of Laughlin & Lissauer 2015arXiv150105685L (1501.05685) Plus Exoplanet atmospheres, physical processes, Sara Seager, p30 eq 3.9 for f contribution. :param float/np.ndarray Teffst: Effective temperature of the star :param float/np.ndarray aR: Ration of the planetary orbital semi-major axis over the stellar radius (without unit) :param float/np.ndarray A: Bond albedo (should be between 0 and 1) :param float/np.ndarray f: Redistribution factor. If 1/4 the energy is uniformly redistributed over the planetary surface. If f = 2/3, no redistribution at all, the atmosphere immediately reradiate whithout advection. :return float/np.ndarray Teqpl: Equilibrium temperature of the planet """ return Teffst * (f * (1 - A))**(1 / 4.) * um.sqrt(1 / aR) / (1 - ecc**2)**(1/8.) def getHtidal(Ms, Rp, a, e): # a -- in AU, semi major axis # Teq -- in Kelvins, planetary equilibrium temperature # M -- in Jupiter masses, planetary mass # Z -- [Fe/H], stellar metallicity # Rp -- radius planet # Ms -- stellar mass # e -- eccentricity # G -- gravitational constant # # G = 6.67408 * 10**(-11) # m3 kg-1 s-2 # Equation from Enoch et al. 2012 # Q = 10**5 # Tidal dissipation factor for high mass planets ...? # k = 0.51 # Love number # H_tidal = (63/4) * ((G * Ms)**(3/2) * Ms * Rp**5 * a**(-15/2)*e**2) / ((3*Q) / (2*k)) # Equation from Jackson 2008 # Qp' = (3*Qp) / (2*k) Qp = 500 # with Love number 0.3 for terrestrial planets H_tidal = (63 / 16*np.pi) * (((G*Ms)**(3/2) * Ms * Rp**3) / (Qp)) * a**(-15/2) * e**2 return H_tidal def safronov_nb(Mp, Ms, Rp, a): # Ozturk 2018, Safronov 1972 return (Mp/Ms) * (a/Rp)

48.527778

100

0.660561

0

2,811

0.804522

5469add1bc5b0732388dfd9a2adc569e52915599

1,656

py

Python

poppy/data_preprocess.py

phanxuanphucnd/BertTextClassification

c9a0500f07d831f924f56cc8211569b035c6e47a

[ "MIT" ]

1

2021-06-14T21:03:04.000Z

poppy/data_preprocess.py

phanxuanphucnd/BertTextClassification

c9a0500f07d831f924f56cc8211569b035c6e47a

[ "MIT" ]

null

poppy/data_preprocess.py

phanxuanphucnd/BertTextClassification

c9a0500f07d831f924f56cc8211569b035c6e47a

[ "MIT" ]

null

import pandas as pd import re import os from tqdm import tqdm ## Cleaning train raw dataset train = open('./data/raw/train.crash').readlines() train_ids = [] train_texts = [] train_labels = [] for id, line in tqdm(enumerate(train)): line = line.strip() if line.startswith("train_"): train_ids.append(id) elif line == "0" or line == "1": train_labels.append(id) for id, lb in tqdm(zip(train_ids, train_labels)): line_id = train[id].strip() label = train[lb].strip() text = ' '.join(train[id + 1: lb]) text = re.sub('\s+', ' ', text).strip()[1: -1].strip() train_texts.append(text) train_df = pd.DataFrame({ 'id': train_ids, 'text': train_texts, 'label': train_labels }) if not os.path.exists('./data'): os.makedirs('./data') train_df.to_csv('./data/train.csv', encoding='utf-8', index=False) ## Clean test raw dataset test = open("./data/raw/test.crash").readlines() test_ids = [] test_texts = [] for id, line in tqdm(enumerate(test)): line = line.strip() if line.startswith("test_"): test_ids.append(id) for i, id in tqdm(enumerate(test_ids)): if i >= len(test_ids) - 1: end = len(test) else: end = test_ids[i + 1] line_id = test[id].strip() text = re.sub('\s+', ' ', ' '.join(test[id + 1: end])).strip()[1:-1].strip() test_texts.append(text) test_df = pd.DataFrame({ 'id': test_ids, 'text': test_texts }) submission = pd.read_csv('./data/raw/sample_submission.csv', encoding='utf-8') result = pd.concat([test_df, submission], axis=1, sort=False) result.to_csv('./data/test.csv', encoding='utf-8', index=False)

23.323944

80

0.618357

0

277

0.167271

546a32ceac58022d2ad2cfb8c9d2804371eb31f5

6,456

py

Python

websaw/core/app.py

valq7711/websaw

fb5718ad3ecd011d7fbb3f24fa007d84951bd58c

[ "MIT" ]

1

2022-02-25T15:02:25.000Z

websaw/core/app.py

valq7711/websaw

fb5718ad3ecd011d7fbb3f24fa007d84951bd58c

[ "MIT" ]

null

websaw/core/app.py

valq7711/websaw

fb5718ad3ecd011d7fbb3f24fa007d84951bd58c

[ "MIT" ]

null

import functools from types import SimpleNamespace from typing import List from . import globs from .context import BaseContext from .exceptions import FixtureProcessError from .reloader import Reloader from .static_registry import static_registry def _dummy_exception_handler(ctx: BaseContext, exc: Exception): raise exc class Fixtured: def __init__(self, h, fixt: List[str]): if isinstance(h, self.__class__): fixt = [*fixt, *h.fixt] h = h.h self.h = h self.fixt = fixt functools.update_wrapper(self, h) def __call__(self, *a, **kw): return self.h(*a, **kw) class BaseApp: static_registry = static_registry add_route = staticmethod(globs.app.add_route) reloader = Reloader def __init__( self, default_config, default_ctx: BaseContext, ): self.default_config = default_config self.default_ctx = default_ctx self._registered = {} self._mixins: List['BaseApp'] = [] def mixin(self, *mixins): self._mixins.extend(mixins) self.default_ctx.extend(*[m.default_ctx for m in mixins]) def _register(self, fun, route_args, fixtures=None): meta = self._registered.setdefault( fun, SimpleNamespace(routes_args=[], fixtures=[]) ) meta.routes_args.append(route_args) if fixtures is not None: meta.fixtures.extend(fixtures) def route(self, rule, method='GET', name=None, **kw): args = (rule, method, name) def decorator(h): fixt = None if isinstance(h, Fixtured): fixt = h.fixt h = h.h self._register(h, (args, kw), fixt) return h return decorator def use(self, *fixt): fixt = [self.default_ctx.get_or_make_fixture_key(f) for f in fixt] def decorator(h): if isinstance(h, Fixtured): h.fixt[:] = [*fixt, *h.fixt] return h return Fixtured(h, fixt) return decorator def mount( self, config: dict = None, context: BaseContext = None, render_map: dict = None, exception_handler=None ): if context is None: context = self.default_ctx if config is None: config = self.default_config render_map: dict = config.get('render_map') exception_handler = config.get('exception_handler') context = context.clone() app_data = context.app_data = SimpleNamespace( routes=[], named_routes={}, **config ) for raw_h, meta, mixin_data in self._iter_registered(): h = self.make_handler(raw_h, meta.fixtures, context, render_map, exception_handler, mixin_data) for route_args, route_kw in meta.routes_args: self._mount_route(context.app_data, h, route_args, route_kw) # mount app static static_rule, static_h = self.static_registry.make_rule_and_handler( f'{app_data.static_base_url}/static', app_data.static_folder, app_data.app_name ) if static_rule is not None: self._mount_route(context.app_data, static_h, (static_rule, 'GET', None), {}) # mount mixins static as /{app_name}/static/{mixin_name}/ for m in self._mixins: m_cfg = m.default_config m_name = m_cfg['app_name'] static_base_url = f'{app_data.base_url}/static/mxn/{m_name}' static_rule, static_h = self.static_registry.make_rule_and_handler( static_base_url, m_cfg['static_folder'], app_data.app_name ) if static_rule is not None: self._mount_route(context.app_data, static_h, (static_rule, 'GET', None), {}) # register self.reloader.register_app_data(context.app_data) context.app_mounted() return context def _iter_registered(self): for m in reversed(self._mixins): for raw_h, meta in m._registered.items(): yield raw_h, meta, SimpleNamespace(**m.default_config) for raw_h, meta in self._registered.items(): yield raw_h, meta, None @staticmethod def make_handler(h, fixtures, ctx: BaseContext, render_map: dict = None, exception_handler=None, mixin_data=None): hooks = False if fixtures: hooks = { fkey: fobj for fkey, fobj in ([fkey, getattr(ctx, fkey)] for fkey in fixtures) if fobj.is_hook } or False else: fixtures = False if exception_handler is None: exception_handler = _dummy_exception_handler @functools.wraps(h) def handler(**kw): exc = None ctx.initialize() ctx.mixin_data = mixin_data try: if fixtures: ctx.use_fixtures(fixtures, hooks) ctx.output = h(ctx, **kw) except FixtureProcessError: pass except Exception as exc_: exc = exc_ ctx.finalize(exc) if ctx.exception is not None: exception_handler(ctx, ctx.exception) if render_map: output = ctx.output render = render_map.get(type(output), False) if render: ctx.output = render(ctx, output) return ctx.output return handler @staticmethod def _get_abs_url(base_url, path): if not path: return base_url if path[0] != '/': path = f'{base_url}/{path}' return path def _mount_route(self, app_data, fun, route_args, route_kw): path, method, name = route_args is_index = path == 'index' path = self._get_abs_url(app_data.base_url, path) route = self.add_route(path, method, fun, **route_kw) app_data.routes.append(route) if name: if name in app_data.named_routes: raise KeyError(f'The route name already in use: {name}') app_data.named_routes[name] = route if is_index: route = self.add_route( path[:-len('/index')] or '/', method, fun, **route_kw ) app_data.routes.append(route)

31.960396

118

0.577912

6,121

0.94811

283

0.043835

1,490

0.230793

0

324

0.050186

546beba67c891d71b93c4df6d7f37c550d736d00

1,772

py

Python

observations/r/chest_sizes.py

hajime9652/observations

2c8b1ac31025938cb17762e540f2f592e302d5de

[ "Apache-2.0" ]

199

2017-07-24T01:34:27.000Z

2022-01-29T00:50:55.000Z

observations/r/chest_sizes.py

hajime9652/observations

2c8b1ac31025938cb17762e540f2f592e302d5de

[ "Apache-2.0" ]

46

2017-09-05T19:27:20.000Z

2019-01-07T09:47:26.000Z

observations/r/chest_sizes.py

hajime9652/observations

2c8b1ac31025938cb17762e540f2f592e302d5de

[ "Apache-2.0" ]

45

2017-07-26T00:10:44.000Z

2022-03-16T20:44:59.000Z

# -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import print_function import csv import numpy as np import os import sys from observations.util import maybe_download_and_extract def chest_sizes(path): """Chest measurements of 5738 Scottish Militiamen Quetelet's data on chest measurements of 5738 Scottish Militiamen. Quetelet (1846) used this data as a demonstration of the normal distribution of physical characteristics. A data frame with 16 observations on the following 2 variables. `chest` Chest size (in inches) `count` Number of soldiers with this chest size Velleman, P. F. and Hoaglin, D. C. (1981). *Applications, Basics, and Computing of Exploratory Data Analysis*. Belmont. CA: Wadsworth. Retrieved from Statlib: `https://www.stat.cmu.edu/StatDat/Datafiles/MilitiamenChests.html` Args: path: str. Path to directory which either stores file or otherwise file will be downloaded and extracted there. Filename is `chest_sizes.csv`. Returns: Tuple of np.ndarray `x_train` with 16 rows and 2 columns and dictionary `metadata` of column headers (feature names). """ import pandas as pd path = os.path.expanduser(path) filename = 'chest_sizes.csv' if not os.path.exists(os.path.join(path, filename)): url = 'http://dustintran.com/data/r/HistData/ChestSizes.csv' maybe_download_and_extract(path, url, save_file_name='chest_sizes.csv', resume=False) data = pd.read_csv(os.path.join(path, filename), index_col=0, parse_dates=True) x_train = data.values metadata = {'columns': data.columns} return x_train, metadata

29.533333

71

0.705418

0

1,068

0.602709

546e4ec20d3fdf8c1c5f8ed657bb3f80549f9803

1,365

py

Python

setup.py

google/ads-api-reports-fetcher

de0bacc3ab520b020cf19985284b7e3dbc9778b0

[ "Apache-2.0" ]

4

2022-02-16T12:42:26.000Z

2022-03-30T17:14:32.000Z

setup.py

google/ads-api-reports-fetcher

de0bacc3ab520b020cf19985284b7e3dbc9778b0

[ "Apache-2.0" ]

null

setup.py

google/ads-api-reports-fetcher

de0bacc3ab520b020cf19985284b7e3dbc9778b0

[ "Apache-2.0" ]

1

2022-03-28T05:51:57.000Z

import pathlib from setuptools import setup, find_packages HERE = pathlib.Path(__file__).parent README = (HERE / "README.md").read_text() setup(name="google-ads-api-report-fetcher", version="0.1", description="Library for fetching reports from Google Ads API and saving them locally / BigQuery.", long_description=README, long_description_content_type="text/markdown", url="https://github.com/google/ads-api-reports-fetcher", author="Google Inc. (gTech gPS CSE team)", author_email="no-reply@google.com", license="Apache 2.0", classifiers=[ "Programming Language :: Python :: 3", "Intended Audience :: Developers", "Topic :: Software Development :: Libraries :: Python Modules", "Operating System :: OS Independent", "License :: OSI Approved :: Apache Software License" ], packages=find_packages(include=["runner", "runner.*"]), install_requires=[ "google-ads==14.1.0", "google-cloud-bigquery==2.26.0", "pandas==1.3.4", "pyarrow==6.0.1", "tabulate" ], setup_requires=["pytest-runner"], tests_requires=["pytest"], entry_points={ "console_scripts": [ "fetch-reports=runner.fetcher:main", "post-process-queries=runner.post_processor:main", ] })

36.891892

105

0.621245

0

720

0.527473

546e73d201a7995e9aa7205db669d55b27e2e940

2,880

py

Python

scan_service/scan_service/utils/stats.py

kkkkv/tgnms

a3b8fd8a69b647a614f9856933f05e50a4affadf

[ "MIT" ]

12

2021-04-06T06:27:18.000Z

2022-03-18T10:52:29.000Z

scan_service/scan_service/utils/stats.py

kkkkv/tgnms

a3b8fd8a69b647a614f9856933f05e50a4affadf

[ "MIT" ]

6

2022-01-04T13:32:16.000Z

2022-03-28T21:13:59.000Z

scan_service/scan_service/utils/stats.py

kkkkv/tgnms

a3b8fd8a69b647a614f9856933f05e50a4affadf

[ "MIT" ]

7

2021-09-27T13:14:42.000Z

2022-03-28T16:24:15.000Z

#!/usr/bin/env python3 # Copyright 2004-present Facebook. All Rights Reserved. import asyncio import logging import time from collections import defaultdict from typing import DefaultDict, Dict, List from tglib.clients.prometheus_client import PrometheusClient, consts from tglib.exceptions import ClientRuntimeError from .topology import Topology def reshape_values(network_name: str, values: Dict) -> DefaultDict: """Reshape the Prometheus results and map to other node's MAC address.""" node_metrics: DefaultDict = defaultdict(dict) other_node: str for metric, result in values.items(): for link_result in result: node_pair = Topology.link_name_to_mac.get(network_name, {}).get( link_result["metric"]["linkName"] ) if node_pair is None: logging.error( f"Missing node_mac mapping for {link_result['metric']['linkName']}" ) continue if link_result["metric"]["radioMac"] == node_pair[0]: other_node = node_pair[1] elif link_result["metric"]["radioMac"] == node_pair[1]: other_node = node_pair[0] else: logging.error( "Incorrect node_mac mapping for " f"{link_result['metric']['linkName']}" ) continue if link_result["values"]: node_metrics[other_node][metric] = link_result["values"][-1][1] return node_metrics async def get_latest_stats( network_name: str, radio_mac: str, metrics: List[str], sample_period: int = 300, hold_period: int = 30, ) -> DefaultDict: """Fetch latest metric values for specific links in the network.""" client = PrometheusClient(timeout=2) coros = [] curr_time = int(time.time()) for metric in metrics: coros.append( client.query_range( client.format_query( metric, {consts.network: network_name, consts.radio_mac: radio_mac} ), step=f"{hold_period+1}s", start=curr_time - sample_period, end=curr_time, ) ) values: Dict = {} for metric_name, response in zip( metrics, await asyncio.gather(*coros, return_exceptions=True) ): if isinstance(response, ClientRuntimeError): logging.error(response) continue if response["status"] != "success": logging.error(f"Failed to fetch {metric_name} data for {radio_mac}") continue result = response["data"]["result"] if not result: logging.error(f"Found no results for {metric}") else: values[metric_name] = result return reshape_values(network_name, values)

32.727273

87

0.594097

0

1,329

0.461458

560

0.194444

547084a7679711993b0e3d30495458fce0c7f40b

1,866

py

Python

multithread_pipeline.py

kapitsa2811/smartOCR

6ecca79b29778778b1458ea28763a39920a3d58a

[ "MIT" ]

null

multithread_pipeline.py

kapitsa2811/smartOCR

6ecca79b29778778b1458ea28763a39920a3d58a

[ "MIT" ]

null

multithread_pipeline.py

kapitsa2811/smartOCR

6ecca79b29778778b1458ea28763a39920a3d58a

[ "MIT" ]

null

import glob import os from io import StringIO from threading import Thread import logging from logger import TimeHandler from costants import THREADS, INFERENCE_GRAPH from pipeline import pipeline logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) logger.addHandler(TimeHandler().handler) class MyThread(Thread): def __init__(self, name, file_path): Thread.__init__(self) self.name = name self.path = file_path def run(self): for file_path in self.path: file_path = os.path.join(file_path) fp = StringIO() pipeline( pdf_path=file_path, inference_graph_path=INFERENCE_GRAPH, thread_name=self.name ) logger.info(fp.getvalue()) fp.close() if __name__ == '__main__': path_list = [] for path in glob.iglob("..\\Polizze\\" + '/**/*.pdf', recursive=True): path_list.append(path) el_per_list = int(len(path_list) / THREADS) thread_list = [] i = 0 path_list_per_thread = [] if len(path_list) == 1: new_thread = MyThread('Thread_{}'.format(0), path_list) new_thread.start() new_thread.join() else: for i in range(0, THREADS): if i < THREADS - 2: path_list_per_thread = path_list[el_per_list * i:el_per_list * (i + 1) - 1] else: path_list_per_thread = path_list[ el_per_list * i:len(path_list) - 1] # lista vuota se c'e' un solo elemento new_thread = MyThread('Thread_{}'.format(i), path_list_per_thread) new_thread.start() thread_list.append(new_thread) for new_thread in thread_list: new_thread.join()

29.619048

115

0.576099

523

0.280279

0

97

0.051983

5470a342899892808b0ad450ef5da5a2f9cf5b36

12,319

py

Python

src/keys_server/GMO/GMOKeysLookup.py

OasisLMF/gem

95c755a1cb76a2bbc41e5dd7bc503c59123ca3ac

[ "BSD-2-Clause" ]

null

src/keys_server/GMO/GMOKeysLookup.py

OasisLMF/gem

95c755a1cb76a2bbc41e5dd7bc503c59123ca3ac

[ "BSD-2-Clause" ]

null

src/keys_server/GMO/GMOKeysLookup.py

OasisLMF/gem

95c755a1cb76a2bbc41e5dd7bc503c59123ca3ac

[ "BSD-2-Clause" ]

null

# -*- coding: utf-8 -*- # Python 2 standard library imports import csv import io import logging import os # Python 2 non-standard library imports import pandas as pd # Imports from Oasis core repos + subpackages or modules within keys_server from oasislmf.utils.coverages import COVERAGE_TYPES from oasislmf.utils.peril import PERILS from oasislmf.utils.status import OASIS_KEYS_STATUS KEYS_STATUS_FAIL = OASIS_KEYS_STATUS['fail'] KEYS_STATUS_NOMATCH = OASIS_KEYS_STATUS['nomatch'] KEYS_STATUS_SUCCESS = OASIS_KEYS_STATUS['success'] from oasislmf.model_preparation.lookup import OasisBaseKeysLookup from oasislmf.utils.log import oasis_log KEYS_STATUS_FAIL = OASIS_KEYS_STATUS['fail']['id'] KEYS_STATUS_NOMATCH = OASIS_KEYS_STATUS['nomatch']['id'] KEYS_STATUS_SUCCESS = OASIS_KEYS_STATUS['success']['id'] from .utils import ( AreaPerilLookup, VulnerabilityLookup, ) # # Public entry point # __all__ = [ 'GMOKeysLookup' ] # # START - deprecated oasislmf.utils.values # from datetime import datetime import pytz NULL_VALUES = [None, '', 'n/a', 'N/A', 'null', 'Null', 'NULL'] def get_timestamp(thedate=None, fmt='%Y%m%d%H%M%S'): """ Get a timestamp """ d = thedate if thedate else datetime.now() return d.strftime(fmt) def get_utctimestamp(thedate=None, fmt='%Y-%b-%d %H:%M:%S'): """ Returns a UTC timestamp for a given ``datetime.datetime`` in the specified string format - the default format is:: YYYY-MMM-DD HH:MM:SS """ d = thedate.astimezone(pytz.utc) if thedate else datetime.utcnow() return d.strftime(fmt) def to_string(val): """ Converts value to string, with possible additional formatting. """ return '' if val is None else str(val) def to_int(val): """ Parse a string to int """ return None if val in NULL_VALUES else int(val) def to_float(val): """ Parse a string to float """ return None if val in NULL_VALUES else float(val) # # END - deprecated oasislmf.utils.values # """ ---- Implementation note ---- In the original lookup implementation each location can map to multiple vulnerability ids, each with difference levels of ductility and or material type. Note from Malcolm: Ductility is largely a product of materials, with unreinforced masonry being the worst and wood the best. The reason it’s probably not explicitly included in commercial cat models is likely that the ductility for a given material is largely a function of age, since better construction codes usually leads to more ductile structures. Age usually is explicitly included in cat models wheres the GEM functions capture this through the construction itself. Original taxonomy: gem_taxonomy_by_oed_occupancy_and_number_of_storeys_df = pd.DataFrame.from_dict({ 'constructioncode': ['5156', '5150', '5150', '5150', '5150', '5150', '5150', '5109', '5109', '5109', '5109', '5109', '5109', '5109', '5105', '5105', '5105', '5105', '5105', '5105', '5105', '5105', '5101', '5103', '5103', '5103', '5000', '5050', '5050', '5050', '5050', '5050'], 'numberofstoreys': [1, 2, 2, 3, 2, 3, 1, 2, 3, 2, 3, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 2, 1, 2, 1, 1, 1, 2, 1, -1], 'taxonomy': ['CR-PC_LWAL-DNO_H1', 'CR_LFINF-DNO_H2', 'CR_LFINF-DUH_H2', 'CR_LFINF-DUH_H3', 'CR_LFINF-DUM_H2', 'CR_LFINF-DUM_H3', 'CR_LFM-DNO_H1', 'MCF_LWAL-DNO_H2', 'MCF_LWAL-DNO_H3', 'MCF_LWAL-DUH_H2', 'MCF_LWAL-DUH_H3', 'MCF_LWAL-DUM_H2','MCF_LWAL-DUM_H3', 'MR_LWAL-DNO_H1','MR_LWAL-DNO_H2', 'MR_LWAL-DNO_H3','MR_LWAL-DUH_H1', 'MR_LWAL-DUH_H2', 'MR_LWAL-DUH_H3', 'MR_LWAL-DUM_H1', 'MR_LWAL-DUM_H2', 'MR_LWAL-DUM_H3', 'MUR-ADO_LWAL-DNO_H2', 'MUR-ST_LWAL-DNO_H2', 'MUR_LWAL-DNO_H1', 'MUR_LWAL-DNO_H2', 'UNK_H1', 'W-WBB_LPB-DNO_H1', 'W-WLI_LWAL-DNO_H1', 'W-WLI_LWAL-DNO_H2', 'W-WS_LPB-DNO_H1', 'W-'] }) The below was changed so that each unique combination of ('constructioncode', 'numberofstoreys') maps to a single 'taxonomy' code """ gem_taxonomy_by_oed_occupancy_and_number_of_storeys_df = pd.DataFrame.from_dict({ 'constructioncode': ['5156', '5150', '5150', '5150', '5109', '5109', '5109', '5105', '5105', '5105', '5101', '5103', '5103', '5000', '5050', '5050', '5050'], 'numberofstoreys': [1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 2, 1, 2, 1, 1, 2, -1], 'taxonomy': ['CR-PC_LWAL-DNO_H1', 'CR_LFINF-DUM_H2', 'CR_LFINF-DUM_H3', 'CR_LFM-DNO_H1', 'MCF_LWAL-DNO_H2', 'MCF_LWAL-DNO_H3', 'MR_LWAL-DNO_H1', 'MR_LWAL-DUM_H1', 'MR_LWAL-DUM_H2', 'MR_LWAL-DUM_H3', 'MUR-ADO_LWAL-DNO_H2', 'MUR_LWAL-DNO_H1', 'MUR_LWAL-DNO_H2', 'UNK_H1', 'W-WLI_LWAL-DNO_H1', 'W-WLI_LWAL-DNO_H2', 'W-'] }) class GMOKeysLookup(OasisBaseKeysLookup): """ GMO keys lookup. """ _LOCATION_RECORD_META = { 'id': { 'source_header': 'loc_id', 'csv_data_type': int, 'validator': to_int, 'desc': 'Location ID' }, 'lon': { 'source_header': 'Longitude', 'csv_data_type': float, 'validator': to_float, 'desc': 'Longitude' }, 'lat': { 'source_header': 'Latitude', 'csv_data_type': float, 'validator': to_float, 'desc': 'Latitude' }, 'county': { 'source_header': 'GeogName1', 'csv_data_type': str, 'validator': to_string, 'desc': 'County' }, 'state': { 'source_header': 'AreaName1', 'csv_data_type': str, 'validator': to_string, 'desc': 'State' }, 'country': { 'source_header': 'CountryCode', 'csv_data_type': str, 'validator': to_string, 'desc': 'Country' }, 'coverage': { 'source_header': 'BuildingTIV', 'csv_data_type': int, 'validator': to_int, 'desc': 'Coverage' }, 'taxonomy': { 'source_header': 'taxonomy', 'csv_data_type': str, 'validator': to_string, 'desc': 'Class #1' }, 'occupancy': { 'source_header': 'OccupancyCode', 'csv_data_type': str, 'validator': to_string, 'desc': 'Class #2' }, 'imt': { 'source_header': 'type', 'csv_data_type': str, 'validator': to_string, 'desc': 'Intensity Measure' } } @oasis_log() def __init__(self, keys_data_directory=None, supplier='GEMFoundation', model_name='GMO', model_version=None, complex_lookup_config_fp=None, output_directory=None): """ Initialise the static data required for the lookup. """ super(self.__class__, self).__init__( keys_data_directory, supplier, model_name, model_version ) # join IMTs with locs self.vulnDict = pd.read_csv(os.path.join(self.keys_data_directory, 'vulnerability_dict.csv')) self.area_peril_lookup = AreaPerilLookup( areas_file=os.path.join( self.keys_data_directory, 'areaperil_dict.csv') ) if keys_data_directory else AreaPerilLookup() self.vulnerability_lookup = VulnerabilityLookup( vulnerabilities_file=os.path.join( self.keys_data_directory, 'vulnerability_dict.csv') ) if keys_data_directory else VulnerabilityLookup() @oasis_log() def process_locations(self, loc_df): """ Process location rows - passed in as a pandas dataframe. """ # Mapping to OED set_dtype = {'constructioncode': 'int', 'numberofstoreys': 'int'} loc_df = loc_df.astype(set_dtype).merge( gem_taxonomy_by_oed_occupancy_and_number_of_storeys_df.astype(set_dtype), on=['constructioncode', 'numberofstoreys']) loc_df = loc_df.merge(self.vulnDict, on="taxonomy") pd.set_option('display.max_columns', 500) # Enforce single taxonomy per location row (Safe guard) loc_df.drop_duplicates(subset=['locperilscovered', 'loc_id'], keep='first', inplace=True) for i in range(len(loc_df)): record = self._get_location_record(loc_df.iloc[i]) area_peril_rec = self.area_peril_lookup.do_lookup_location(record) vuln_peril_rec = \ self.vulnerability_lookup.do_lookup_location(record) status = message = '' # print(area_peril_rec) # print(vuln_peril_rec) # print(KEYS_STATUS_SUCCESS) if area_peril_rec['status'] == \ vuln_peril_rec['status'] == KEYS_STATUS_SUCCESS: status = KEYS_STATUS_SUCCESS elif ( area_peril_rec['status'] == KEYS_STATUS_FAIL or vuln_peril_rec['status'] == KEYS_STATUS_FAIL ): status = KEYS_STATUS_FAIL message = '{}, {}'.format( area_peril_rec['message'], vuln_peril_rec['message'] ) else: status = KEYS_STATUS_NOMATCH message = 'No area peril or vulnerability match' record = { "loc_id": record['id'], "peril_id": PERILS['earthquake']['id'], "coverage_type": COVERAGE_TYPES['buildings']['id'], "area_peril_id": area_peril_rec['area_peril_id'], "vulnerability_id": vuln_peril_rec['vulnerability_id'], "message": message, "status": status } yield(record) def process_locations_multiproc(self, locations): """ Process location rows - passed in as a pandas dataframe. """ # Mapping to OED set_dtype = {'constructioncode': 'int', 'numberofstoreys': 'int'} loc_df = locations.astype(set_dtype).merge( gem_taxonomy_by_oed_occupancy_and_number_of_storeys_df.astype(set_dtype), on=['constructioncode', 'numberofstoreys']) loc_df = loc_df.merge(self.vulnDict, on="taxonomy") pd.set_option('display.max_columns', 500) # Enforce single taxonomy per location row (Safe guard) loc_df.drop_duplicates(subset=['locperilscovered', 'loc_id'], keep='first', inplace=True) results = [] for i in range(len(loc_df)): record = self._get_location_record(loc_df.iloc[i]) area_peril_rec = self.area_peril_lookup.do_lookup_location(record) vuln_peril_rec = \ self.vulnerability_lookup.do_lookup_location(record) status = message = '' if area_peril_rec['status'] == \ vuln_peril_rec['status'] == KEYS_STATUS_SUCCESS: status = KEYS_STATUS_SUCCESS elif ( area_peril_rec['status'] == KEYS_STATUS_FAIL or vuln_peril_rec['status'] == KEYS_STATUS_FAIL ): status = KEYS_STATUS_FAIL message = '{}, {}'.format( area_peril_rec['message'], vuln_peril_rec['message'] ) else: status = KEYS_STATUS_NOMATCH message = 'No area peril or vulnerability match' record = { "loc_id": record['id'], "peril_id": PERILS['earthquake']['id'], "coverage_type": COVERAGE_TYPES['buildings']['id'], "area_peril_id": area_peril_rec['area_peril_id'], "vulnerability_id": vuln_peril_rec['vulnerability_id'], "message": message, "status": status } results.append(record) return(results) def _get_location_record(self, loc_item): """ Construct a location record (dict) from the location item, which in this case is a row in a Pandas dataframe. """ # print("!! _get_location_record: {0}".format(loc_item)) meta = self._LOCATION_RECORD_META return dict(( k, meta[k]['validator'](loc_item[meta[k]['source_header'].lower()]) ) for k in meta )

36.554896

606

0.596396

7,708

0.625599

2,218

0.180018

3,336

0.270757

0

5,492

0.445743

5470aea747a6878071245059e1de2776baa03338

18,485

py

Python

pandemic_eval.py

aypan17/value_learning

240a67ecf99b178fe0c4ced2bfd1dd50453fbdfe

[ "MIT" ]

null

pandemic_eval.py

aypan17/value_learning

240a67ecf99b178fe0c4ced2bfd1dd50453fbdfe

[ "MIT" ]

null

pandemic_eval.py

aypan17/value_learning

240a67ecf99b178fe0c4ced2bfd1dd50453fbdfe

[ "MIT" ]

null

import time import sys import json import argparse from tqdm import trange from typing import Any, Callable, Dict, List, Optional, Tuple, Union import torch import numpy as np from scipy.spatial.distance import jensenshannon import gym import matplotlib.pyplot as plt from matplotlib.axes import Axes from matplotlib.ticker import MaxNLocator from matplotlib.lines import Line2D import pandemic_simulator as ps from pandemic_simulator.environment.reward import RewardFunction, SumReward, RewardFunctionFactory, RewardFunctionType from pandemic_simulator.environment.interfaces import InfectionSummary from pandemic_simulator.viz import PandemicViz from pandemic_simulator.environment import PandemicSimOpts from stable_baselines3.common import base_class from stable_baselines3.common.vec_env import DummyVecEnv, VecEnv def hellinger(p, q): # distance between p and q # p and q are np array probability distributions return (1.0 / np.sqrt(2.0)) * np.sqrt(np.sum(np.square(np.sqrt(p) - np.sqrt(q)), axis=1)) def evaluate_policy( name: str, model: "base_class.BaseAlgorithm", base_model: "base_class.BaseAlgorithm", env: Union[gym.Env, VecEnv], n_eval_episodes: int = 32, deterministic: bool = True, render: bool = False, viz: Optional[PandemicViz] = None, reward_threshold: Optional[float] = None, return_episode_rewards: bool = False, warn: bool = True, ) -> Union[Tuple[float, float], Tuple[List[float], List[int]]]: """ Runs policy for ``n_eval_episodes`` episodes and returns average reward. If a vector env is passed in, this divides the episodes to evaluate onto the different elements of the vector env. This static division of work is done to remove bias. See https://github.com/DLR-RM/stable-baselines3/issues/402 for more details and discussion. .. note:: If environment has not been wrapped with ``Monitor`` wrapper, reward and episode lengths are counted as it appears with ``env.step`` calls. If the environment contains wrappers that modify rewards or episode lengths (e.g. reward scaling, early episode reset), these will affect the evaluation results as well. You can avoid this by wrapping environment with ``Monitor`` wrapper before anything else. :param model: The RL agent you want to evaluate. :param env: The gym environment or ``VecEnv`` environment. :param n_eval_episodes: Number of episode to evaluate the agent :param deterministic: Whether to use deterministic or stochastic actions :param render: Whether to render the environment or not :param callback: callback function to do additional checks, called after each step. Gets locals() and globals() passed as parameters. :param reward_threshold: Minimum expected reward per episode, this will raise an error if the performance is not met :param return_episode_rewards: If True, a list of rewards and episode lengths per episode will be returned instead of the mean. :param warn: If True (default), warns user about lack of a Monitor wrapper in the evaluation environment. :return: Mean reward per episode, std of reward per episode. Returns ([float], [int]) when ``return_episode_rewards`` is True, first list containing per-episode rewards and second containing per-episode lengths (in number of steps). """ if not isinstance(env, VecEnv): env = DummyVecEnv([lambda: env]) episode_rewards = [] reward_std = [] episode_true_rewards = [] true_reward_std = [] episode_true_rewards2 = [] true_reward_std2 = [] vfs = [] log_probs = [] ents = [] base_vfs = [] base_log_probs = [] base_ents = [] kls = [] js = [] h = [] numpy_obs = env.reset() states = None for t in range(200): actions, states = model.predict(numpy_obs, state=states, deterministic=True) vf, logp, ent = model.policy.evaluate_actions(torch.as_tensor(numpy_obs), torch.as_tensor(actions)) base_vf, base_logp, base_ent = base_model.policy.evaluate_actions(torch.as_tensor(numpy_obs), torch.as_tensor(actions)) vfs.append(torch.mean(vf).detach().item()) log_probs.append(torch.mean(logp).detach().item()) ents.append(torch.mean(ent).detach().item()) base_vfs.append(torch.mean(base_vf).detach().item()) base_log_probs.append(torch.mean(base_logp).detach().item()) base_ents.append(torch.mean(base_ent).detach().item()) # Distances log_ratio = logp - base_logp # Estimator of KL from http://joschu.net/blog/kl-approx.html kls.append(torch.mean(torch.exp(log_ratio) - 1 - log_ratio).item()) latent_pi, _, latent_sde = model.policy._get_latent(torch.as_tensor(numpy_obs)) model_dist = model.policy._get_action_dist_from_latent(latent_pi, latent_sde=latent_sde).distribution.probs.detach().numpy() latent_pi, _, latent_sde = base_model.policy._get_latent(torch.as_tensor(numpy_obs)) base_dist = base_model.policy._get_action_dist_from_latent(latent_pi, latent_sde=latent_sde).distribution.probs.detach().numpy() js.append(np.mean(jensenshannon(model_dist, base_dist, axis=1)).item()) h.append(np.mean(hellinger(model_dist, base_dist)).item()) numpy_obs, _, done, info = env.step(actions) rew = env.get_attr("last_reward") true_rew = env.get_attr("get_true_reward") true_rew2 = env.get_attr("get_true_reward2") episode_rewards.append(np.mean(rew)) reward_std.append(rew) episode_true_rewards.append(np.mean(true_rew)) true_reward_std.append(true_rew) episode_true_rewards2.append(np.mean(true_rew2)) true_reward_std2.append(true_rew2) obs = env.get_attr("observation") infection_data = np.zeros((1, 5)) threshold_data = np.zeros(len(obs)) for o in obs: infection_data += o.global_infection_summary[-1] gis = np.array([o.global_infection_summary[-1] for o in obs]).squeeze(1) gts = np.array([o.global_testing_summary[-1] for o in obs]).squeeze(1) stage = np.array([o.stage[-1].item() for o in obs]) if viz: viz.record_list(obs[0], gis, gts, stage, rew, true_rew, true_rew2=true_rew2) reward = np.sum(episode_rewards).item() true_reward = np.sum(episode_true_rewards).item() true_reward2 = np.sum(episode_true_rewards2).item() #if viz: # viz.plot(name=name, evaluate=True, plots_to_show=['critical_summary', 'stages', 'cumulative_reward', 'cumulative_true_reward2']) # viz.reset() return reward, np.std(np.sum(np.array(reward_std), axis=0)).item(), \ true_reward, np.std(np.sum(np.array(true_reward_std), axis=0)).item(), \ true_reward2, np.std(np.sum(np.array(true_reward_std2), axis=0)).item(), \ kls, js, h, log_probs, base_log_probs, vfs, base_vfs def plot_critical_summary(ax, viz, color, sty, m): gis = np.vstack(viz._gis).squeeze() gis_std = np.vstack(viz._gis_std).squeeze() ax.plot(viz._num_persons * gis[:, viz._critical_index], color='black', linestyle=sty, linewidth=1, label='_nolegend_') #ax.fill_between(np.arange(len(gis)), viz._num_persons * (gis-gis_std)[:, viz._critical_index], viz._num_persons * (gis+gis_std)[:, viz._critical_index], alpha=0.1, color=color) ax.plot(np.arange(gis.shape[0]), np.ones(gis.shape[0]) * viz._max_hospital_capacity, 'y') ax.legend(['Max hospital capacity'], loc='upper left') ax.set_ylim(-0.1, viz._max_hospital_capacity * 3) ax.set_title('ICU Usage', fontsize=16) ax.set_xlabel('time (days)', fontsize=16) ax.set_ylabel('persons', fontsize=16) ax.yaxis.set_major_locator(MaxNLocator(integer=True)) height = viz._num_persons * gis[m, viz._critical_index] ax.plot([m, m], [-0.1, height], color=color, linestyle=sty, linewidth=2) ax.plot([0, m], [height, height], color=color, linestyle=sty, linewidth=2) def plot_stages(ax, viz, color, sty): days = np.arange(len(viz._stages)) stages = np.array(viz._stages) stages_std = np.array(viz._stages_std) ax.plot(days, stages, color='black', linestyle=sty, linewidth=1) #ax.fill_between(days, stages - stages_std, stages + stages_std, alpha=0.1, color=color) ax.set_ylim(-0.1, 5) # This assumes at most 5 stages!! ax.set_title('Regulation Stage', fontsize=16) ax.set_xlabel('time (days)', fontsize=16) ax.yaxis.set_major_locator(MaxNLocator(integer=True)) m = np.argmax(stages[50:]) + 50 ax.plot([m, m], [-0.1, stages[m]], color=color, linestyle=sty, linewidth=2) p1 = Line2D([0,1],[0,1],linestyle='-', color='black') p2 = Line2D([0,1],[0,1],linestyle='--', color='black') ax.legend([p1, p2], ['smaller policy', 'larger policy'], loc='upper right') return m def plot(v1, v2): fig, (ax1, ax2) = plt.subplots(1, 2) c1 = 'red' c2 = 'blue' s1 = '-' s2 = '--' m1 = plot_stages(ax2, v1, c1, s1) plot_critical_summary(ax1, v1, c1, s1, m1) m2 = plot_stages(ax2, v2, c2, s2) plot_critical_summary(ax1, v2, c2, s2, m2) ax1.figure.set_size_inches(4, 3) ax2.figure.set_size_inches(4, 3) fig.set_size_inches(8, 3) plt.savefig('test.svg',dpi=120, bbox_inches='tight', pad_inches = 0, format='svg') def make_cfg(): # cfg = ps.sh.small_town_config # cfg.delta_start_lo = int(sys.argv[6]) # cfg.delta_start_hi = int(sys.argv[7]) # return cfg sim_config = ps.env.PandemicSimConfig( num_persons=500, location_configs=[ ps.env.LocationConfig(ps.env.Home, num=150), ps.env.LocationConfig(ps.env.GroceryStore, num=2, num_assignees=5, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.Office, num=2, num_assignees=150, state_opts=dict(visitor_capacity=0)), ps.env.LocationConfig(ps.env.School, num=10, num_assignees=2, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.Hospital, num=1, num_assignees=15, state_opts=dict(patient_capacity=5)), ps.env.LocationConfig(ps.env.RetailStore, num=2, num_assignees=5, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.HairSalon, num=2, num_assignees=3, state_opts=dict(visitor_capacity=5)), ps.env.LocationConfig(ps.env.Restaurant, num=1, num_assignees=6, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.Bar, num=1, num_assignees=3, state_opts=dict(visitor_capacity=30)) ], person_routine_assignment=ps.sh.DefaultPersonRoutineAssignment(), delta_start_lo = 95, delta_start_hi = 105 ) sim_config_med = ps.env.PandemicSimConfig( num_persons=2000, location_configs=[ ps.env.LocationConfig(ps.env.Home, num=600), ps.env.LocationConfig(ps.env.GroceryStore, num=4, num_assignees=10, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.Office, num=4, num_assignees=300, state_opts=dict(visitor_capacity=0)), ps.env.LocationConfig(ps.env.School, num=20, num_assignees=4, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.Hospital, num=2, num_assignees=30, state_opts=dict(patient_capacity=5)), ps.env.LocationConfig(ps.env.RetailStore, num=4, num_assignees=10, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.HairSalon, num=4, num_assignees=6, state_opts=dict(visitor_capacity=5)), ps.env.LocationConfig(ps.env.Restaurant, num=2, num_assignees=12, state_opts=dict(visitor_capacity=30)), ps.env.LocationConfig(ps.env.Bar, num=2, num_assignees=6, state_opts=dict(visitor_capacity=30)) ], person_routine_assignment=ps.sh.DefaultPersonRoutineAssignment(), delta_start_lo = 95, delta_start_hi = 105 ) return sim_config def make_reg(): return ps.sh.austin_regulations def make_sim(sim_config, noise): sim_opt = PandemicSimOpts() sim_opt.spontaneous_testing_rate = noise return ps.env.PandemicSim.from_config(sim_config=sim_config, sim_opts=sim_opt) def make_viz(sim_config): return ps.viz.GymViz.from_config(sim_config=sim_config) def load_model(env, model_path, width, depth): agent = ps.model.StageModel(env = env) d_model = width n_layers = depth net_arch = [d_model] * n_layers if n_layers != 0 else [] policy_kwargs = { "net_arch": [dict(pi=net_arch, vf=net_arch)], } model = agent.get_model("ppo", policy_kwargs = policy_kwargs, verbose = 0) return model.load(model_path) def init(args, noise): n_cpus = args.n_cpus ps.init_globals(seed=args.seed) sim_config = make_cfg() regulations = make_reg() viz = make_viz(sim_config) done_fn = ps.env.DoneFunctionFactory.default(ps.env.DoneFunctionType.TIME_LIMIT, horizon=200) reward_fn = SumReward( reward_fns=[ RewardFunctionFactory.default(RewardFunctionType.INFECTION_SUMMARY_ABOVE_THRESHOLD, summary_type=InfectionSummary.CRITICAL, threshold=sim_config.max_hospital_capacity / sim_config.num_persons), RewardFunctionFactory.default(RewardFunctionType.INFECTION_SUMMARY_ABSOLUTE, summary_type=InfectionSummary.CRITICAL), RewardFunctionFactory.default(RewardFunctionType.LOWER_STAGE, num_stages=len(regulations)), RewardFunctionFactory.default(RewardFunctionType.SMOOTH_STAGE_CHANGES, num_stages=len(regulations)) ], weights=[0, 10, 0.1, 0.01] ) gym = ps.env.PandemicPolicyGymEnv.from_config( sim_config=sim_config, sim_opts = PandemicSimOpts(spontaneous_testing_rate=noise), pandemic_regulations=regulations, done_fn=done_fn, reward_fn=reward_fn, constrain=True, four_start=False, obs_history_size=3, num_days_in_obs=8 ) env = gym.get_multi_env(n=n_cpus) if n_cpus > 1 else gym.get_single_env() return env, viz def evaluate(env, model_path, width, depth, base_model, viz): model = load_model(env, model_path, width, depth) model_parameters = filter(lambda p: p.requires_grad, model.policy.mlp_extractor.parameters()) params = sum([np.prod(p.size()) for p in model_parameters]) params = int(params) print(f"Evaluating {model_path+str(width)}...") reward, rstd, true_reward, trstd, true_reward2, tr2std, kl, js, h, log_probs, base_log_probs, vfs, base_vfs = evaluate_policy(model_path, model, base_model, env, viz=viz) env.close() print(f"Model: {model_path}. Proxy: {reward}. Objective: {true_reward}.") return params, reward, rstd, true_reward, trstd, true_reward2, tr2std, kl, js, h, log_probs, base_log_probs, vfs, base_vfs def main(): parser = argparse.ArgumentParser() parser.add_argument('model_path') parser.add_argument('base_model_path') parser.add_argument('base_width', type=int) parser.add_argument('base_depth', type=int) parser.add_argument('--seed', type=int, default=17) parser.add_argument('--n_cpus', type=int, default=32) parser.add_argument('--n_episodes', type=int, default=32) parser.add_argument('--epoch', type=int, default=0) parser.add_argument('--width', type=int, default=0) #parser.add_argument('--noise', type=str, default="") args = parser.parse_known_args(sys.argv[1:])[0] vs = [] for w in [16, 112]: env, viz = init(args, 0.02) base_model = load_model(env, args.base_model_path, args.base_width, args.base_depth) evaluate(env, args.model_path+str(w), w, 2, base_model, viz) vs.append(viz) plot(vs[0], vs[1]) # params, reward, reward_std, true_reward, true_reward_std, true_reward2, true_reward2_std, kls, js, h, log_probs, base_log_probs, vfs, base_vfs, e, noises = \ # [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [] # #widths = [4, 8, 12, 16, 20, 24, 28, 32] if args.width == 0 else [40, 48, 56, 64, 80, 96, 112, 128] # for w in [args.width]: # for noise in ['01', '02', '003', '005', '03', '04', '05', '06', '07', '08', '09', '095', '1']: # n2n = {'01':0.1, '02':0.2, '003':0.03, '005':0.05, '03':0.3, '04':0.4, '05':0.5, '06':0.6, '07':0.7, '08':0.8, '09':0.9, '095':0.95, '1':1} # env, viz = init(args, n2n[noise]) # base_model = load_model(env, args.base_model_path, args.base_width, args.base_depth) # p, r, rs, tr, trs, tr2, tr2s, kl, j_s, h_, logp, blogp, vf, bvf = evaluate(env, args.model_path+noise+"_"+str(w), w, 2, base_model, viz) # noises.append(n2n[noise]) # params.append(p) # reward.append(r) # reward_std.append(rs) # true_reward.append(tr) # true_reward_std.append(trs) # true_reward2.append(tr2) # true_reward2_std.append(tr2s) # kls.append(kl) # js.append(j_s) # h.append(h_) # log_probs.append(logp) # base_log_probs.append(blogp) # vfs.append(vf) # base_vfs.append(bvf) # e.append(args.epoch) # f = open(f"pandemic_{args.epoch}_{args.width}_noise.json", "w") # json.dump({'params':params, 'noise':noises, 'rew': reward, 'rew_std': reward_std, 'true_rew': true_reward, 'true_rew_std': true_reward_std, 'true_rew2': true_reward2, # 'true_rew2_std': true_reward2_std, 'kls': kls, 'js': js, 'h': h, 'log_probs': log_probs, 'base_log_probs': base_log_probs, 'vfs': vfs, 'base_vfs': base_vfs, 'e': e}, f) # f.close() if __name__ == '__main__': main()

47.51928

182

0.648526

0

5,161

0.279199

5471ef5e2041074700733cd254f4357bec345d93

3,289

py

Python

WagerBrain/odds.py

sedemmler/WagerBrain

b1cc33f5eb7a6130106bf8251b554718e2d22172

[ "MIT" ]

83

2020-03-26T22:14:24.000Z

2022-03-22T19:00:48.000Z

website.py

rax-v/XSS

ff70b89c9fb94a19caaf84e81eddeeca052344ea

[ "MIT" ]

2

2020-03-26T19:34:03.000Z

2020-03-27T19:56:14.000Z

website.py

rax-v/XSS

ff70b89c9fb94a19caaf84e81eddeeca052344ea

[ "MIT" ]

19

2020-04-06T10:47:30.000Z

2022-03-30T19:16:42.000Z

from fractions import Fraction from math import gcd import numpy as np """ Convert the style of gambling odds to Function Name (Decimal, American, Fractional). TO DO: Fix edge case related to Fraction module that causes weird rounding / slightly off output """ def american_odds(odds): """ :param odds: Float (e.g., 2.25) or String (e.g., '3/1' or '5/4'). :return: Integer. Odds expressed in American terms. """ if isinstance(odds, int): return odds elif isinstance(odds, float): if odds > 2.0: return round((odds - 1) * 100, 0) else: return round(-100 / (odds - 1), 0) elif "/" in odds: odds = Fraction(odds) if odds.numerator > odds.denominator: return (odds.numerator / odds.denominator) * 100 else: return -100 / (odds.numerator / odds.denominator) def decimal_odds(odds): """ :param odds: Integer (e.g., -350) or String (e.g., '3/1' or '5/4'). :return: Float. Odds expressed in Decimal terms. """ if isinstance(odds, float): return odds elif isinstance(odds, int): if odds >= 100: return abs(1 + (odds / 100)) elif odds <= -101 : return 100 / abs(odds) + 1 else: return float(odds) elif "/" in odds: odds = Fraction(odds) return round((odds.numerator / odds.denominator) + 1, 2) def fractional_odds(odds): """ :param odds: Numeric. (e.g., 2.25 or -350). :return: Fraction Class. Odds expressed in Fractional terms. """ if isinstance(odds, str): return Fraction(odds) elif isinstance(odds, int): if odds > 0: denom = 100 g_cd = gcd(odds, denom) num = int(odds / g_cd) denom = int(denom / g_cd) return Fraction(num, denom) else: num = 100 g_cd = gcd(num, odds) num = int(num / g_cd) denom = int(odds / g_cd) return -Fraction(num, denom) elif isinstance(odds, float): new_odds = int((odds - 1) * 100) g_cd = gcd(new_odds, 100) return Fraction(int(new_odds/g_cd), int(100/g_cd)) def parlay_odds(odds): """ :param odds: List. A list of odds for wagers to be included in parlay :return: Parlay odds in Decimal terms """ return np.prod(np.array([decimal_odds(x) for x in odds])) def convert_odds(odds, odds_style='a'): """ :param odds: Stated odds from bookmaker (American, Decimal, or Fractional) :param odds_style: American ('a', 'amer', 'american'), Decimal ('d', dec','decimal) Fractional ('f','frac','fractional) :return: Numeric. Odds converted to selected style. """ try: if odds_style.lower() == "american" or odds_style.lower() == 'amer' or odds_style.lower() == 'a': return american_odds(odds) elif odds_style.lower() == "decimal" or odds_style.lower() == 'dec' or odds_style.lower() == 'd': return decimal_odds(odds) elif odds_style.lower() == "fractional" or odds_style.lower() == 'frac' or odds_style.lower() == 'f': return fractional_odds(odds) except (ValueError, KeyError, NameError): return None

28.850877

123

0.578291

0

1,054

0.320462

5472180161d7e60f43fc9232da207e59fa3cb086

16,438

py

Python

GANs/jsigan/ops.py

JonathanLehner/nnabla-examples

2971b987484945e12fb171594181908789485a0f

[ "Apache-2.0" ]

null

GANs/jsigan/ops.py

JonathanLehner/nnabla-examples

2971b987484945e12fb171594181908789485a0f

[ "Apache-2.0" ]

null

GANs/jsigan/ops.py

JonathanLehner/nnabla-examples

2971b987484945e12fb171594181908789485a0f

[ "Apache-2.0" ]

null

# Copyright (c) 2017 Sony Corporation. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from collections import namedtuple import nnabla as nn import nnabla.functions as F import nnabla.parametric_functions as PF import nnabla.initializer as I import numpy as np from utils import depth_to_space def box_filter(x, szf): """ Box filter """ y = F.identity(x) szy = list(y.shape) b_filt = nn.Variable((szf, szf, 1, 1)) b_filt.data.fill(1.) b_filt = b_filt / (szf ** 2) # 5,5,1,1 b_filt = F.tile(b_filt, [1, 1, szy[3], 1]) b_filt = F.transpose(b_filt, (3, 2, 0, 1)) b_filt = F.reshape(b_filt, (6, 5, 5)) pp = int((szf - 1) / 2) y = F.pad(y, (0, 0, pp, pp, pp, pp, 0, 0), mode='reflect') y_chw = F.transpose(y, (0, 3, 1, 2)) y_chw = F.depthwise_convolution(y_chw, b_filt, multiplier=1, stride=(1, 1)) y_hwc = F.transpose(y_chw, (0, 2, 3, 1)) return y_hwc def guided_filter(img, r, eps): """ Edge preserving filter """ img2 = F.concatenate(img, img * img, axis=3) img2 = box_filter(img2, r) mean = F.split(img2, axis=3) mean_i = F.stack(mean[0], mean[1], mean[2], axis=3) mean_ii = F.stack(mean[3], mean[4], mean[5], axis=3) var_i = mean_ii - mean_i * mean_i a = var_i / (var_i + eps) b = mean_i - a * mean_i ab = F.concatenate(a, b, axis=3) ab = box_filter(ab, r) mean_ab = F.split(ab, axis=3) mean_a = F.stack(mean_ab[0], mean_ab[1], mean_ab[2], axis=3) mean_b = F.stack(mean_ab[3], mean_ab[4], mean_ab[5], axis=3) q = mean_a * img + mean_b return q def conv_2d(x, o_ch, kernel, name=None): """ Convolution for JSInet """ b = I.ConstantInitializer(0.) h = PF.convolution(x, o_ch, kernel=kernel, stride=(1, 1), pad=(1, 1), channel_last=True, b_init=b, name=name) return h def res_block(x, out_ch, name): """ Create residual block """ with nn.parameter_scope(name): h = conv_2d(F.relu(x), out_ch, kernel=(3, 3), name='conv/0') h = conv_2d(F.relu(h), out_ch, kernel=(3, 3), name='conv/1') h = x + h return h def dyn_2d_filter(x, lf_2d, k_sz): """ Dynamic 2d filtering """ with nn.parameter_scope('Dynamic_2D_Filtering'): f_localexpand = nn.Variable.from_numpy_array( np.eye(k_sz[0] * k_sz[1], k_sz[0] * k_sz[1])) f_localexpand = F.reshape(f_localexpand, (k_sz[0], k_sz[1], 1, k_sz[0] * k_sz[1])) # (9,9,1,81)) f_localexpand = F.transpose(f_localexpand, (3, 0, 1, 2)) # (81,9,9,1)) x_sz = x.shape x = F.reshape(x, (x_sz[0], x_sz[1], x_sz[2], 1)) # (1,100,170,1) x_localexpand = F.convolution(x, f_localexpand, stride=(1, 1), pad=(4, 4), channel_last=True) # (1,100,170,81) x_le_sz = x_localexpand.shape x_localexpand = F.reshape(x_localexpand, (x_le_sz[0], x_le_sz[1], x_le_sz[2], 1, x_le_sz[3])) y = F.batch_matmul(x_localexpand, lf_2d) y_sz = y.shape y = F.reshape(y, (y_sz[0], y_sz[1], y_sz[2], y_sz[4])) return y def dyn_2d_up_operation(x, lf_2d, k_sz, sf=2): """ Dynamic 2d upsampling """ with nn.parameter_scope("Dynamic_2D_Upsampling"): y = [] sz = lf_2d.shape lf_2d_new = F.reshape( lf_2d, (sz[0], sz[1], sz[2], k_sz[0] * k_sz[0], sf ** 2)) lf_2d_new = F.softmax(lf_2d_new, axis=3) for ch in range(3): # loop over YUV channels # apply dynamic filtering operation temp = dyn_2d_filter(x[:, :, :, ch], lf_2d_new, k_sz) temp = depth_to_space(temp, sf) y += [temp] y = F.concatenate(*y, axis=3) return y def dyn_sep_up_operation(x, dr_k_v, dr_k_h, k_sz, sf): """ Dynamic separable upsampling operation with 1D separable local kernels. x: [B, H, W, C], dr_k_v: [B, H, W, 41*sf*sf], dr_k_h: [B, H, W, 41*sf*sf] out: [B, H*sf, W*sf, C] """ sz = x.shape pad = k_sz // 2 # local filter pad size # [B, H, W, C*sf*sf] out_v = nn.Variable((sz[0], sz[1], sz[2], sz[3] * sf ** 2)) out_v.data.zero() # [B, H, W, C*sf*sf] out_h = nn.Variable((sz[0], sz[1], sz[2], sz[3] * sf ** 2)) out_h.data.zero() img_pad = F.pad(x, (0, 0, pad, pad, 0, 0, 0, 0)) img_pad_y = F.reshape(img_pad[:, :, :, 0], (img_pad.shape[0], img_pad.shape[1], img_pad.shape[2], 1)) img_pad_y = F.tile(img_pad_y, [1, 1, 1, sf ** 2]) img_pad_u = F.reshape(img_pad[:, :, :, 1], (img_pad.shape[0], img_pad.shape[1], img_pad.shape[2], 1)) img_pad_u = F.tile(img_pad_u, [1, 1, 1, sf ** 2]) img_pad_v = F.reshape(img_pad[:, :, :, 2], (img_pad.shape[0], img_pad.shape[1], img_pad.shape[2], 1)) img_pad_v = F.tile(img_pad_v, [1, 1, 1, sf ** 2]) img_pad = F.concatenate(img_pad_y, img_pad_u, img_pad_v, axis=3) # vertical 1D filter for i in range(k_sz): out_v = out_v + img_pad[:, i:i + sz[1], :, :] * F.tile( dr_k_v[:, :, :, i:k_sz * sf ** 2:k_sz], [1, 1, 1, 3]) img_pad = F.pad(out_v, (0, 0, 0, 0, pad, pad, 0, 0)) # horizontal 1D filter for i in range(k_sz): out_h = out_h + img_pad[:, :, i:i + sz[2], :] * F.tile( dr_k_h[:, :, :, i:k_sz * sf ** 2:k_sz], [1, 1, 1, 3]) # depth to space upsampling (YUV) out = depth_to_space(out_h[:, :, :, 0:sf ** 2], sf) out = F.concatenate(out, depth_to_space( out_h[:, :, :, sf ** 2:2 * sf ** 2], sf), axis=3) out = F.concatenate(out, depth_to_space( out_h[:, :, :, 2 * sf ** 2:3 * sf ** 2], sf), axis=3) return out def res_block_concat(x, out_ch, name): """ Basic residual block -> [conv-relu | conv-relu] + input """ with nn.parameter_scope(name): h = conv_2d(F.relu(x), out_ch, kernel=(3, 3), name='conv/0') h = conv_2d(F.relu(h), out_ch, kernel=(3, 3), name='conv/1') h = x[:, :, :, :out_ch] + h return h def model(img, sf): """ Define JSInet model """ with nn.parameter_scope('Network'): with nn.parameter_scope('local_contrast_enhancement'): ## ================= Local Contrast Enhancement Subnet ============================ ## ch = 64 b = guided_filter(img, 5, 0.01) n1 = conv_2d(b, ch, kernel=(3, 3), name='conv/0') for i in range(4): n1 = res_block(n1, ch, 'res_block/%d' % i) n1 = F.relu(n1, inplace=True) local_filter_2d = conv_2d(n1, (9 ** 2) * (sf ** 2), kernel=(3, 3), name='conv_k') # [B, H, W, (9x9)*(sfxsf)] # dynamic 2D upsampling with 2D local filters pred_C = dyn_2d_up_operation(b, local_filter_2d, (9, 9), sf) # local contrast mask pred_C = 2 * F.sigmoid(pred_C) ## ================= Detail Restoration Subnet ============================ ## ch = 64 d = F.div2(img, b + 1e-15) with nn.parameter_scope('detail_restoration'): n3 = conv_2d(d, ch, kernel=(3, 3), name='conv/0') for i in range(4): n3 = res_block(n3, ch, 'res_block/%d' % i) if i == 0: d_feature = n3 n3 = F.relu(n3, inplace=True) # separable 1D filters dr_k_h = conv_2d(n3, 41 * sf ** 2, kernel=(3, 3), name='conv_k_h') dr_k_v = conv_2d(n3, 41 * sf ** 2, kernel=(3, 3), name='conv_k_v') # dynamic separable upsampling with with separable 1D local filters pred_D = dyn_sep_up_operation(d, dr_k_v, dr_k_h, 41, sf) ## ================= Image Reconstruction Subnet ============================ ## with nn.parameter_scope('image_reconstruction'): n4 = conv_2d(img, ch, kernel=(3, 3), name='conv/0') for i in range(4): if i == 1: n4 = F.concatenate(n4, d_feature, axis=3) n4 = res_block_concat(n4, ch, 'res_block/%d' % i) else: n4 = res_block(n4, ch, 'res_block/%d' % i) n4 = F.relu(n4, inplace=True) n4 = F.relu(conv_2d(n4, ch * sf * sf, kernel=(3, 3), name='conv/1'), inplace=True) # (1,100,170,1024) -> (1,100,170,4,4,64) -> (1,100,4,170,4,64) # pixel shuffle n4 = depth_to_space(n4, sf) pred_I = conv_2d(n4, 3, kernel=(3, 3), name='conv/2') pred = F.add2(pred_I, pred_D, inplace=True) * pred_C jsinet = namedtuple('jsinet', ['pred']) return jsinet(pred) def truncated_normal(w_shape, mean, std): """ Numpy truncated normal """ init = I.NormalInitializer() tmp = init(w_shape + (4,)) valid = np.logical_and((np.less(tmp, 2)), (np.greater(tmp, -2))) ind = np.argmax(valid, axis=-1) ind1 = (np.expand_dims(ind, -1)) trunc_norm = np.take_along_axis(tmp, ind1, axis=4).squeeze(-1) trunc_norm = trunc_norm * std + mean return trunc_norm def conv(x, channels, kernel=4, stride=2, pad=0, pad_type='zero', use_bias=True, scope='conv_0'): """ Convolution for discriminator """ w_n_shape = (channels, kernel, kernel, x.shape[-1]) w_init = truncated_normal(w_n_shape, mean=0.0, std=0.02) b_init = I.ConstantInitializer(0.) with nn.parameter_scope(scope): if pad > 0: h = x.shape[1] if h % stride == 0: pad = pad * 2 else: pad = max(kernel - (h % stride), 0) pad_top = pad // 2 pad_bottom = pad - pad_top pad_left = pad // 2 pad_right = pad - pad_left if pad_type == 'zero': x = F.pad(x, (0, 0, pad_top, pad_bottom, pad_left, pad_right, 0, 0)) if pad_type == 'reflect': x = F.pad(x, (0, 0, pad_top, pad_bottom, pad_left, pad_right, 0, 0), mode='reflect') def apply_w(w): return PF.spectral_norm(w, dim=0) x = PF.convolution(x, channels, kernel=(kernel, kernel), stride=( stride, stride), apply_w=apply_w, w_init=w_init, b_init=b_init, with_bias=use_bias, channel_last=True) return x def dis_block(n, c, i, train=True): """ Discriminator conv_bn_relu block """ out = conv(n, channels=c, kernel=4, stride=2, pad=1, use_bias=False, scope='d_conv/' + str(2 * i + 2)) out_fm = F.leaky_relu( PF.batch_normalization( out, axes=[3], batch_stat=train, name='d_bn/' + str(2 * i + 1)), alpha=0.2) out = conv(out_fm, channels=c * 2, kernel=3, stride=1, pad=1, use_bias=False, scope='d_conv/' + str(2 * i + 3)) out = F.leaky_relu( PF.batch_normalization( out, axes=[3], batch_stat=train, name='d_bn/' + str(2 * i + 2)), alpha=0.2) return out, out_fm def discriminator_fm(x, sf, scope="Discriminator_FM"): """ Feature matching discriminator """ with nn.parameter_scope(scope): fm_list = [] ch = 32 n = F.leaky_relu(conv(x, ch, 3, 1, 1, scope='d_conv/1'), alpha=0.2) for i in range(4): n, out_fm = dis_block(n, ch, i, train=True) ch = ch * 2 fm_list.append(out_fm) n = F.leaky_relu(PF.batch_normalization( conv(n, channels=ch, kernel=4, stride=2, pad=1, use_bias=False, scope='d_conv/10'), axes=[3], batch_stat=True, name='d_bn/9'), alpha=0.2, inplace=True) if sf == 1: n = F.leaky_relu(PF.batch_normalization( conv(n, channels=ch, kernel=5, stride=1, pad=1, use_bias=False, scope='d_conv/11'), axes=[3], batch_stat=True, name='d_bn/10'), alpha=0.2, inplace=True) else: n = F.leaky_relu(PF.batch_normalization( conv(n, channels=ch, kernel=5, stride=1, use_bias=False, scope='d_conv/11'), axes=[3], batch_stat=True, name='d_bn/10'), alpha=0.2, inplace=True) n = PF.batch_normalization( conv(n, channels=1, kernel=1, stride=1, use_bias=False, scope='d_conv/12'), axes=[3], batch_stat=True, name='d_bn/11') out_logit = n out = F.sigmoid(out_logit) # [B,1] return out, out_logit, fm_list def discriminator_loss(real, fake): """ Calculate discriminator loss """ real_loss = F.mean( F.relu(1.0 - (real - F.reshape(F.mean(fake), (1, 1, 1, 1))))) fake_loss = F.mean( F.relu(1.0 + (fake - F.reshape(F.mean(real), (1, 1, 1, 1))))) l_d = real_loss + fake_loss return l_d def generator_loss(real, fake): """ Calculate generator loss """ real_loss = F.mean( F.relu(1.0 + (real - F.reshape(F.mean(fake), (1, 1, 1, 1))))) fake_loss = F.mean( F.relu(1.0 - (fake - F.reshape(F.mean(real), (1, 1, 1, 1))))) l_g = real_loss + fake_loss return l_g def feature_matching_loss(x, y, num=4): """ Calculate feature matching loss """ fm_loss = 0.0 for i in range(num): fm_loss += F.mean(F.squared_error(x[i], y[i])) return fm_loss def gan_model(label_ph, pred, conf): """ Define GAN model with adversarial and discriminator losses and their orchestration """ # Define Discriminator _, d_real_logits, d_real_fm_list = discriminator_fm( label_ph, conf.scaling_factor, scope="Discriminator_FM") # output of D for fake images _, d_fake_logits, d_fake_fm_list = discriminator_fm( pred, conf.scaling_factor, scope="Discriminator_FM") # Define Detail Discriminator # compute the detail layers for the dicriminator (reuse) base_gt = guided_filter(label_ph, 5, 0.01) detail_gt = F.div2(label_ph, base_gt + 1e-15) base_pred = guided_filter(pred, 5, 0.01) detail_pred = F.div2(pred, base_pred + 1e-15) # detail layer output of D for real images _, d_detail_real_logits, d_detail_real_fm_list = \ discriminator_fm(detail_gt, conf.scaling_factor, scope="Discriminator_Detail") # detail layer output of D for fake images _, d_detail_fake_logits, d_detail_fake_fm_list = \ discriminator_fm(detail_pred, conf.scaling_factor, scope="Discriminator_Detail") # Loss # original GAN (hinge GAN) d_adv_loss = discriminator_loss(d_real_logits, d_fake_logits) d_adv_loss.persistent = True g_adv_loss = generator_loss(d_real_logits, d_fake_logits) g_adv_loss.persistent = True # detail GAN (hinge GAN) d_detail_adv_loss = conf.detail_lambda * \ discriminator_loss(d_detail_real_logits, d_detail_fake_logits) d_detail_adv_loss.persistent = True g_detail_adv_loss = conf.detail_lambda * \ generator_loss(d_detail_real_logits, d_detail_fake_logits) g_detail_adv_loss.persistent = True # feature matching (FM) loss fm_loss = feature_matching_loss(d_real_fm_list, d_fake_fm_list, 4) fm_loss.persistent = True fm_detail_loss = conf.detail_lambda * feature_matching_loss(d_detail_real_fm_list, d_detail_fake_fm_list, 4) fm_detail_loss.persistent = True jsigan = namedtuple('jsigan', ['d_adv_loss', 'd_detail_adv_loss', 'g_adv_loss', 'g_detail_adv_loss', 'fm_loss', 'fm_detail_loss']) return jsigan(d_adv_loss, d_detail_adv_loss, g_adv_loss, g_detail_adv_loss, fm_loss, fm_detail_loss)

37.359091

98

0.55828

0

3,241

0.197165

5475f0c326a3f8de3e388b70e03c71cc3faf4139

2,973

py

Python

neptune/internal/hardware/gpu/gpu_monitor.py

neptune-ml/neptune-client

7aea63160b5149c3fec40f62d3b0da7381a35748

[ "Apache-2.0" ]

13

2019-02-11T13:18:38.000Z

2019-12-26T06:26:07.000Z

neptune/internal/hardware/gpu/gpu_monitor.py

neptune-ml/neptune-client

7aea63160b5149c3fec40f62d3b0da7381a35748

[ "Apache-2.0" ]

39

2019-03-07T13:40:10.000Z

2020-01-07T17:19:24.000Z

neptune/internal/hardware/gpu/gpu_monitor.py

neptune-ml/neptune-client

7aea63160b5149c3fec40f62d3b0da7381a35748

[ "Apache-2.0" ]

4

2019-02-11T13:07:23.000Z

2019-11-26T08:20:24.000Z

# # Copyright (c) 2019, Neptune Labs Sp. z o.o. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import logging from neptune.vendor.pynvml import ( NVMLError, nvmlDeviceGetCount, nvmlDeviceGetHandleByIndex, nvmlDeviceGetMemoryInfo, nvmlDeviceGetUtilizationRates, nvmlInit, ) _logger = logging.getLogger(__name__) class GPUMonitor(object): nvml_error_printed = False def get_card_count(self): return self.__nvml_get_or_else(nvmlDeviceGetCount, default=0) def get_card_usage_percent(self, card_index): # pylint: disable=no-member # pylint incorrectly detects that function nvmlDeviceGetUtilizationRates returns str return self.__nvml_get_or_else( lambda: float(nvmlDeviceGetUtilizationRates(nvmlDeviceGetHandleByIndex(card_index)).gpu) ) def get_card_used_memory_in_bytes(self, card_index): # pylint: disable=no-member # pylint incorrectly detects that function nvmlDeviceGetMemoryInfo returns str return self.__nvml_get_or_else( lambda: nvmlDeviceGetMemoryInfo(nvmlDeviceGetHandleByIndex(card_index)).used ) def get_top_card_memory_in_bytes(self): def read_top_card_memory_in_bytes(): # pylint: disable=no-member # pylint incorrectly detects that function nvmlDeviceGetMemoryInfo returns str return self.__nvml_get_or_else( lambda: [ nvmlDeviceGetMemoryInfo(nvmlDeviceGetHandleByIndex(card_index)).total for card_index in range(nvmlDeviceGetCount()) ], default=0, ) memory_per_card = read_top_card_memory_in_bytes() if not memory_per_card: return 0 return max(memory_per_card) def __nvml_get_or_else(self, getter, default=None): try: nvmlInit() return getter() except NVMLError as e: if not GPUMonitor.nvml_error_printed: warning = ( "Info (NVML): %s. GPU usage metrics may not be reported. For more information, " "see https://docs-legacy.neptune.ai/logging-and-managing-experiment-results" "/logging-experiment" "-data.html#hardware-consumption " ) _logger.warning(warning, e) GPUMonitor.nvml_error_printed = True return default

35.392857

100

0.664649

2,131

0.716784

0

1,113

0.374369

54768720b8a58a3c4d1cf1c8c265ceea8f6fc111

5,219

py

Python

tests/redis_map.py

jaredlunde/redis_structures

b9cce5f5c85db5e12c292633ff8d04e3ae053294

[ "MIT" ]

2

2016-04-05T08:40:47.000Z

2016-06-27T14:03:26.000Z

tests/redis_map.py

jaredLunde/redis_structures

b9cce5f5c85db5e12c292633ff8d04e3ae053294

[ "MIT" ]

1

2015-10-27T14:30:53.000Z

2015-11-09T17:54:33.000Z

tests/redis_map.py

jaredlunde/redis_structures

b9cce5f5c85db5e12c292633ff8d04e3ae053294

[ "MIT" ]

null

#!/usr/bin/python3 -S # -*- coding: utf-8 -*- """ `Redis Map Tests` --·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·--·-- 2015 Jared Lunde © The MIT License (MIT) http://github.com/jaredlunde """ import datetime import time import pickle import unittest from redis_structures.debug import RandData, gen_rand_str from redis_structures import StrictRedis, RedisMap class TestJSONRedisMap(unittest.TestCase): map = RedisMap("json_map", prefix="rs:unit_tests:", serialize=True) is_str = False def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self.addCleanup(self.map.clear) def cast(self, obj): return str(obj) if self.is_str else obj def reset(self, count=10, type=int): self.map.clear() self.data = RandData(type).dict(count, 1) self.data_count = count self.map.update(self.data) def test_prefix(self): self.assertEqual(self.map.prefix, 'rs:unit_tests') self.assertEqual(self.map.name, 'json_map') self.assertEqual(self.map.key_prefix, 'rs:unit_tests:json_map') def test_incr_decr(self): self.reset() self.map.incr('views', 1) self.assertEqual(self.map['views'], self.cast(1)) self.map.incr('views', 3) self.assertEqual(self.map['views'], self.cast(4)) self.map.decr('views', 1) self.assertEqual(self.map['views'], self.cast(3)) def test_get(self): self.reset() self.map["hello"] = "world" self.assertEqual(self.map.get("hello"), 'world') self.assertEqual(self.map.get('world', 'hello'), 'hello') def test_get_key(self): self.assertEqual( self.map.get_key('views'), "{}:{}:{}".format(self.map.prefix, self.map.name, 'views')) def test_items(self): self.reset() self.assertDictEqual( {k: v for k, v in self.map.items()}, {k: self.cast(v) for k, v in self.data.items()}) def test_values(self): self.reset() self.assertSetEqual( set(self.map.values()), set(map(self.cast, self.data.values()))) def test_iter(self): self.reset() self.assertSetEqual( set(k for k in self.map.iter()), set(self.cast(k) for k in self.data.keys())) def test_iter_match(self): self.reset(count=10) self.assertSetEqual( set(k for k in self.map.iter("a*")), set(self.cast(k) for k in self.data.keys() if k.startswith('a'))) def test_mget(self): self.reset(0) self.map.update({ 'test1': 1, 'test2': 2, 'test3': 3, 'test4': 4, 'test5': 5}) self.assertListEqual( self.map.mget('test2', 'test3', 'test4'), [self.cast(2), self.cast(3), self.cast(4)]) def test_pop(self): self.reset() self.map['hello'] = 'world' self.assertEqual(self.map.pop('hello'), 'world') self.assertNotIn('hello', self.map) def test_delete(self): self.reset() self.map['hello'] = 'world' self.assertEqual(self.map['hello'], 'world') del self.map['hello'] self.assertNotIn('hello', self.map) def test_scan(self): self.reset() new_keys = [] cursor = '0' while cursor: cursor, keys = self.map.scan(count=1, cursor=int(cursor)) if keys: new_keys.extend(keys) self.assertSetEqual( set(self.map.get_key(k) for k in self.data.keys()), set(new_keys)) def test_set(self): self.reset() self.map.set("hello", "world") self.assertIn("hello", self.map) def test_setex(self): self.reset() self.map.setex("hello", "world", 1) self.assertIn("hello", self.map) time.sleep(1.25) self.assertNotIn("hello", self.map) self.map.psetex("hello", "world", 1000) self.assertIn("hello", self.map) time.sleep(1.25) self.assertNotIn("hello", self.map) class TestPickledRedisMap(TestJSONRedisMap): map = RedisMap("pickled_map", prefix="rs:unit_tests:", serializer=pickle) def test_prefix(self): self.assertEqual(self.map.prefix, 'rs:unit_tests') self.assertEqual(self.map.name, 'pickled_map') self.assertEqual(self.map.key_prefix, 'rs:unit_tests:pickled_map') def test_incr_decr(self): self.reset() self.map.incr('views', 1) self.assertEqual(self.map['views'], str(1)) self.map.incr('views', 3) self.assertEqual(self.map['views'], str(4)) self.map.decr('views', 1) self.assertEqual(self.map['views'], str(3)) class TestUnserializedRedisMap(TestJSONRedisMap): map = RedisMap("unserialized_map", prefix="rs:unit_tests:") is_str = True def test_prefix(self): self.assertEqual(self.map.prefix, 'rs:unit_tests') self.assertEqual(self.map.name, 'unserialized_map') self.assertEqual( self.map.key_prefix, 'rs:unit_tests:unserialized_map') if __name__ == '__main__': unittest.main()

30.881657

80

0.57923

4,760

0.907358

0

902

0.171941

5477f31f091eaba6d081dd15b6e4e452029c17e6

4,480

py

Python

examples/parser_example.py

pibico/beacontools

513e1c7ff2aaf74b6c7d7b10805c2f6ca4384e3d

[ "MIT" ]

139

2017-06-09T17:15:23.000Z

2022-03-15T03:02:17.000Z

examples/parser_example.py

pibico/beacontools

513e1c7ff2aaf74b6c7d7b10805c2f6ca4384e3d

[ "MIT" ]

71

2017-06-20T03:20:56.000Z

2022-02-13T22:47:53.000Z

examples/parser_example.py

pibico/beacontools

513e1c7ff2aaf74b6c7d7b10805c2f6ca4384e3d

[ "MIT" ]

59

2017-06-20T03:10:00.000Z

2022-03-15T23:54:44.000Z

# -*- coding: utf-8 -*- from beacontools import parse_packet # Eddystone UID packet uid_packet = b"\x02\x01\x06\x03\x03\xaa\xfe\x17\x16\xaa\xfe\x00\xe3\x12\x34\x56\x78\x90\x12" \ b"\x34\x67\x89\x01\x00\x00\x00\x00\x00\x01\x00\x00" uid_frame = parse_packet(uid_packet) print("Namespace: %s" % uid_frame.namespace) print("Instance: %s" % uid_frame.instance) print("TX Power: %s" % uid_frame.tx_power) print("-----") # Eddystone URL packet url_packet = b"\x03\x03\xAA\xFE\x13\x16\xAA\xFE\x10\xF8\x03github\x00citruz" url_frame = parse_packet(url_packet) print("TX Power: %d" % url_frame.tx_power) print("URL: %s" % url_frame.url) print("-----") # Eddystone TLM packet (unencrypted) tlm_packet = b"\x02\x01\x06\x03\x03\xaa\xfe\x11\x16\xaa\xfe\x20\x00\x0b\x18\x13\x00\x00\x00" \ b"\x14\x67\x00\x00\x2a\xc4\xe4" tlm_frame = parse_packet(tlm_packet) print("Voltage: %d mV" % tlm_frame.voltage) print("Temperature: %f °C" % tlm_frame.temperature) print("Advertising count: %d" % tlm_frame.advertising_count) print("Seconds since boot: %d" % tlm_frame.seconds_since_boot) print("-----") # Eddystone TLM packet (encrypted) enc_tlm_packet = b"\x02\x01\x06\x03\x03\xaa\xfe\x11\x16\xaa\xfe\x20\x01\x41\x41\x41\x41\x41" \ b"\x41\x41\x41\x41\x41\x41\x41\xDE\xAD\xBE\xFF" enc_tlm_frame = parse_packet(enc_tlm_packet) print("Data: %s" % enc_tlm_frame.encrypted_data) print("Salt: %d" % enc_tlm_frame.salt) print("Mic: %d" % enc_tlm_frame.mic) print("-----") # iBeacon Advertisement ibeacon_packet = b"\x02\x01\x06\x1a\xff\x4c\x00\x02\x15\x41\x41\x41\x41\x41\x41\x41\x41\x41" \ b"\x41\x41\x41\x41\x41\x41\x41\x00\x01\x00\x01\xf8" adv = parse_packet(ibeacon_packet) print("UUID: %s" % adv.uuid) print("Major: %d" % adv.major) print("Minor: %d" % adv.minor) print("TX Power: %d" % adv.tx_power) print("-----") # Cypress iBeacon Sensor cypress_packet = b"\x02\x01\x04\x1a\xff\x4c\x00\x02\x15\x00\x05\x00\x01\x00\x00\x10\x00\x80" \ b"\x00\x00\x80\x5f\x9b\x01\x31\x00\x02\x6c\x66\xc3" sensor = parse_packet(cypress_packet) print("UUID: %s" % sensor.uuid) print("Major: %d" % sensor.major) print("Temperature: %d °C" % sensor.cypress_temperature) print("Humidity: %d %%" % sensor.cypress_humidity) print("TX Power: %d" % sensor.tx_power) print("-----") # Estimote Telemetry Packet (Subframe A) telemetry_a_packet = b"\x02\x01\x04\x03\x03\x9a\xfe\x17\x16\x9a\xfe\x22\x47\xa0\x38\xd5"\ b"\xeb\x03\x26\x40\x00\x00\x01\x41\x44\x47\xfa\xff\xff\xff\xff" telemetry = parse_packet(telemetry_a_packet) print("Identifier: %s" % telemetry.identifier) print("Protocol Version: %d" % telemetry.protocol_version) print("Acceleration (g): (%f, %f, %f)" % telemetry.acceleration) print("Is moving: %s" % telemetry.is_moving) # ... see packet_types/estimote.py for all available attributes and units print("-----") # Estimote Telemetry Packet (Subframe B) telemetry_b_packet = b"\x02\x01\x04\x03\x03\x9a\xfe\x17\x16\x9a\xfe\x22\x47\xa0\x38\xd5"\ b"\xeb\x03\x26\x40\x01\xd8\x42\xed\x73\x49\x25\x66\xbc\x2e\x50" telemetry_b = parse_packet(telemetry_b_packet) print("Identifier: %s" % telemetry_b.identifier) print("Protocol Version: %d" % telemetry_b.protocol_version) print("Magnetic field: (%f, %f, %f)" % telemetry_b.magnetic_field) print("Temperature: %f °C" % telemetry_b.temperature) # ... see packet_types/estimote.py for all available attributes and units # Estimote Nearable Advertisement nearable_packet = b"\x02\x01\x04\x03\x03\x0f\x18\x17\xff\x5d" \ b"\x01\x01\x1e\xfe\x42\x7e\xb6\xf4\xbc\x2f" \ b"\x04\x01\x68\xa1\xaa\xfe\x05\xc1\x45\x25" \ b"\x53\xb5" nearable_adv = parse_packet(nearable_packet) print("Identifier: %s" % nearable_adv.identifier) print("Hardware_version: %d" % nearable_adv.hardware_version) print("Firmware_version: %d" % nearable_adv.firmware_version) print("Temperature: %d" % nearable_adv.temperature) print("Is moving: %i" % nearable_adv.is_moving) print("-----") # CJ Monitor packet cj_monitor_packet = b"\x02\x01\x06\x05\x02\x1A\x18\x00\x18" \ b"\x09\xFF\x72\x04\xFE\x10\xD1\x0C\x33\x61" \ b"\x09\x09\x4D\x6F\x6E\x20\x35\x36\x34\x33" cj_monitor = parse_packet(cj_monitor_packet) print("Name: %s" % cj_monitor.name) print("Temperature: %f °C" % cj_monitor.temperature) print("Humidity: %d %%" % cj_monitor.humidity) print("Light: %f" % cj_monitor.light)

40

94

0.690625

0

2,343

0.522525

547c48103894763c6518d10f40329e0d7d4eaefd

1,228

py

Python

mlsurvey/sl/workflows/multiple_learning_workflow.py

jlaumonier/mlsurvey

373598d067c7f0930ba13fe8da9756ce26eecbaf

[ "MIT" ]

null

mlsurvey/sl/workflows/multiple_learning_workflow.py

jlaumonier/mlsurvey

373598d067c7f0930ba13fe8da9756ce26eecbaf

[ "MIT" ]

null

mlsurvey/sl/workflows/multiple_learning_workflow.py

jlaumonier/mlsurvey

373598d067c7f0930ba13fe8da9756ce26eecbaf

[ "MIT" ]

null

from kedro.io import DataCatalog, MemoryDataSet from kedro.pipeline import Pipeline from kedro.runner import SequentialRunner import mlsurvey as mls from mlsurvey.workflows.learning_workflow import LearningWorkflow class MultipleLearningWorkflow(LearningWorkflow): def run(self): """ Run the workflow : run each config """ # data data_catalog = DataCatalog({'config': MemoryDataSet(), 'log': MemoryDataSet(), 'base_directory': MemoryDataSet()}) data_catalog.save('config', self.config) data_catalog.save('log', self.log) data_catalog.save('base_directory', self.base_directory) expand_config_node = mls.sl.workflows.tasks.ExpandConfigTask.get_node() multiple_learning_node = mls.sl.workflows.tasks.MultipleLearningTask.get_node() # Assemble nodes into a pipeline pipeline = Pipeline([expand_config_node, multiple_learning_node]) # Create a runner to run the pipeline runner = SequentialRunner() # Run the pipeline result = runner.run(pipeline, data_catalog) if len(result) == 0: self.terminate()

34.111111

87

0.653094

1,007

0.820033

0

209

0.170195

547cd68f734cef8dede708252277b864855b2580

2,542

py

Python

backend/apps/cmdb/migrations/0001_initial.py

renmcc/SA2

a524124c140ae0b291b10dafc11d38744dd93bd9

[ "MIT" ]

4

2020-06-25T05:57:39.000Z

2021-06-26T04:58:16.000Z

backend/apps/cmdb/migrations/0001_initial.py

renmcc/SA2

a524124c140ae0b291b10dafc11d38744dd93bd9

[ "MIT" ]

null

backend/apps/cmdb/migrations/0001_initial.py

renmcc/SA2

a524124c140ae0b291b10dafc11d38744dd93bd9

[ "MIT" ]

1

2020-12-10T15:12:11.000Z

# Generated by Django 2.2.12 on 2020-06-15 16:55 import datetime from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): initial = True dependencies = [ ('project', '0001_initial'), ] operations = [ migrations.CreateModel( name='server', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('hostname', models.CharField(blank=True, help_text='主机名', max_length=200, verbose_name='主机名')), ('public_ip', models.GenericIPAddressField(blank=True, help_text='外网IP', null=True, verbose_name='外网IP')), ('private_ip', models.GenericIPAddressField(help_text='内网IP', unique=True, verbose_name='内网IP')), ('os', models.CharField(blank=True, default=None, help_text='操作系统', max_length=100, verbose_name='操作系统')), ('cpu', models.CharField(blank=True, default=None, help_text='CPU信息', max_length=250, verbose_name='CPU信息')), ('memory', models.CharField(blank=True, default=None, help_text='内存信息', max_length=100, verbose_name='内存信息')), ('disk', models.CharField(blank=True, help_text='硬盘信息', max_length=300, null=True, verbose_name='硬盘信息')), ('status', models.BooleanField(default=True, help_text='是否启用', verbose_name='启用')), ('remark', models.TextField(blank=True, help_text='备注', null=True, verbose_name='备注')), ('add_time', models.DateTimeField(default=datetime.datetime.now, help_text='添加时间', verbose_name='添加时间')), ('update_time', models.DateTimeField(auto_now=True, help_text='更新时间', verbose_name='更新时间')), ('area', models.ForeignKey(blank=True, help_text='所属大区', null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='server_area', to='project.ProjectArea', verbose_name='大区')), ('project', models.ForeignKey(blank=True, default=1, help_text='项目', null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='server_project', to='project.Project', verbose_name='项目')), ('role', models.ManyToManyField(blank=True, help_text='功能', null=True, related_name='server_role', to='project.ProjectRole', verbose_name='功能')), ], options={ 'verbose_name': '服务器列表', 'verbose_name_plural': '服务器列表', 'ordering': ('id',), }, ), ]

59.116279

215

0.632179

2,583

0.947542

0

703

0.257887

547d39324fd1deeba259dcc2ee665fe787ad6b6c

1,055

py

Python

sphecius/ciphers/base.py

douglasdaly/sphecius

df8fc8dd2add157c6360c2b66cb22ac6f0241051

[ "MIT" ]

1

2019-09-26T01:08:20.000Z

sphecius/ciphers/base.py

douglasdaly/sphecius

df8fc8dd2add157c6360c2b66cb22ac6f0241051

[ "MIT" ]

null

sphecius/ciphers/base.py

douglasdaly/sphecius

df8fc8dd2add157c6360c2b66cb22ac6f0241051

[ "MIT" ]

1

2019-09-26T01:08:19.000Z

# -*- coding: utf-8 -*- """ base.py Base Cipher Object class @author: Douglas Daly @date: 1/12/2017 """ # # Imports # from abc import ABCMeta, abstractmethod from ..alphabets import English # # Classes # class Cipher(object, metaclass=ABCMeta): """ Base Cipher Class """ def __init__(self, alphabet=English): """ Default Constructor """ self._alphabet = alphabet self._key = None def set_key(self, key): """ Sets the Key for this Cipher object :param str key: Key for this Cipher object """ self._key = key.upper() @abstractmethod def encrypt(self, plaintext): """ Abstract Encrypt Method :param str plaintext: Text to encrypt :returns: Encrypted text :rtype: str """ pass @abstractmethod def decrypt(self, ciphertext): """ Abstract Decrypt Method :param str ciphertext: Text to decrypt :returns: Decrypted text :rtype: str """ pass

16.484375

50

0.57346

836

0.792417

0

426

0.403791

0

589

0.558294

547ee9e4da4b047390b557dc16580a853bcc3c8e

281

py

Python

setup.py

codewars/python-unittest

5a6cc27a51a9d91ce997c953099515c701b76057

[ "MIT" ]

4

2020-06-20T12:36:09.000Z

2021-10-31T22:04:48.000Z

setup.py

codewars/python-unittest

5a6cc27a51a9d91ce997c953099515c701b76057

[ "MIT" ]

null

setup.py

codewars/python-unittest

5a6cc27a51a9d91ce997c953099515c701b76057

[ "MIT" ]

3

2020-07-11T13:46:24.000Z

2022-02-23T20:55:19.000Z

from setuptools import setup setup( name="codewars_unittest", version="0.1.0", packages=["codewars_unittest"], license="MIT", description="unittest runner with Codewars output", install_requires=[], url="https://github.com/Codewars/python-unittest", )

23.416667

55

0.690391

0

133

0.47331

547f16545ac590cbce83d8fc70ff6fbb32f028e2

16,628

py

Python

code/python/FactSetFunds/v1/fds/sdk/FactSetFunds/model/classifications.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

6

2022-02-07T16:34:18.000Z

2022-03-30T08:04:57.000Z

code/python/FactSetFunds/v1/fds/sdk/FactSetFunds/model/classifications.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

2

2022-02-07T05:25:57.000Z

2022-03-07T14:18:04.000Z

code/python/FactSetFunds/v1/fds/sdk/FactSetFunds/model/classifications.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

[ "Apache-2.0" ]

null

""" FactSet Funds API FactSet Mutual Funds data offers over 50 fund- and share class-specific data points for mutual funds listed in the United States. <p>FactSet Mutual Funds Reference provides fund-specific reference information as well as FactSet's proprietary classification system. It includes but is not limited to the following coverage * Fund descriptions * A seven-tier classification system * Leverage information * Fees and expenses * Portfolio managers FactSet Mutual Funds Time Series provides quantitative data items on a historical basis. It includes but is not limited to the following coverage * Net asset value * Fund flows * Assets under management * Total return # noqa: E501 The version of the OpenAPI document: 1.0.0 Contact: api@factset.com Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from fds.sdk.FactSetFunds.model_utils import ( # noqa: F401 ApiTypeError, ModelComposed, ModelNormal, ModelSimple, cached_property, change_keys_js_to_python, convert_js_args_to_python_args, date, datetime, file_type, none_type, validate_get_composed_info, OpenApiModel ) from fds.sdk.FactSetFunds.exceptions import ApiAttributeError class Classifications(ModelNormal): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. Attributes: allowed_values (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict with a capitalized key describing the allowed value and an allowed value. These dicts store the allowed enum values. attribute_map (dict): The key is attribute name and the value is json key in definition. discriminator_value_class_map (dict): A dict to go from the discriminator variable value to the discriminator class name. validations (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict that stores validations for max_length, min_length, max_items, min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum, inclusive_minimum, and regex. additional_properties_type (tuple): A tuple of classes accepted as additional properties values. """ allowed_values = { } validations = { } @cached_property def additional_properties_type(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded """ return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501 _nullable = False @cached_property def openapi_types(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded Returns openapi_types (dict): The key is attribute name and the value is attribute type. """ return { 'fsym_id': (str,), # noqa: E501 'request_id': (str,), # noqa: E501 'asset_class': (str,), # noqa: E501 'category_class': (str,), # noqa: E501 'economic_development_class': (str,), # noqa: E501 'focus_class': (str,), # noqa: E501 'geographic_class': (str,), # noqa: E501 'niche_class': (str,), # noqa: E501 'region_class': (str,), # noqa: E501 } @cached_property def discriminator(): return None attribute_map = { 'fsym_id': 'fsymId', # noqa: E501 'request_id': 'requestId', # noqa: E501 'asset_class': 'assetClass', # noqa: E501 'category_class': 'categoryClass', # noqa: E501 'economic_development_class': 'economicDevelopmentClass', # noqa: E501 'focus_class': 'focusClass', # noqa: E501 'geographic_class': 'geographicClass', # noqa: E501 'niche_class': 'nicheClass', # noqa: E501 'region_class': 'regionClass', # noqa: E501 } read_only_vars = { } _composed_schemas = {} @classmethod @convert_js_args_to_python_args def _from_openapi_data(cls, *args, **kwargs): # noqa: E501 """Classifications - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) fsym_id (str): FactSet Security Identifier. Six alpha-numeric characters, excluding vowels, with a -S suffix (XXXXXX-S), resolved from the requestId of the Fund requested.. [optional] # noqa: E501 request_id (str): The requested Id sent as input.. [optional] # noqa: E501 asset_class (str): Returns the asset class description from FactSet's fund classification system. Asset class designates the fund's underlying holding type, e.g. equity, fixed-income, etc.. [optional] # noqa: E501 category_class (str): Returns the asset class category description from FactSet's fund classification system. The asset class category is the first-tier subcategory within the fund's asset class, e.g. size & style, sector, precious metals, etc.. [optional] # noqa: E501 economic_development_class (str): Returns the fund's economic development description from FactSet's fund classification system. This description refers to the development level for the fund's geographic region of focus, e.g. developed, emerging, etc.. [optional] # noqa: E501 focus_class (str): Returns the fund's focus description from FactSet's fund classification system. The fund's focus is the second-tier subcategory within the fund's asset class, e.g. small cap, energy, etc.. [optional] # noqa: E501 geographic_class (str): Returns the fund's specific geography description from FactSet's fund classification system. Specific geography refers to the fund's particular geographic focus within the region, e.g. Chile, BRICs, etc.. [optional] # noqa: E501 niche_class (str): Returns the fund's niche description from FactSet's fund classification system. The fund's niche is the third-tier subcategory with the fund's asset class, e.g. growth, coal, etc.. [optional] # noqa: E501 region_class (str): Returns the fund's region description from FactSet's fund classification system. Refers to the broad regional exposure of the fund's holdings, e.g. Latin America, Asia-Pacific, etc.. [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) self = super(OpenApiModel, cls).__new__(cls) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) return self required_properties = set([ '_data_store', '_check_type', '_spec_property_naming', '_path_to_item', '_configuration', '_visited_composed_classes', ]) @convert_js_args_to_python_args def __init__(self, *args, **kwargs): # noqa: E501 """Classifications - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) fsym_id (str): FactSet Security Identifier. Six alpha-numeric characters, excluding vowels, with a -S suffix (XXXXXX-S), resolved from the requestId of the Fund requested.. [optional] # noqa: E501 request_id (str): The requested Id sent as input.. [optional] # noqa: E501 asset_class (str): Returns the asset class description from FactSet's fund classification system. Asset class designates the fund's underlying holding type, e.g. equity, fixed-income, etc.. [optional] # noqa: E501 category_class (str): Returns the asset class category description from FactSet's fund classification system. The asset class category is the first-tier subcategory within the fund's asset class, e.g. size & style, sector, precious metals, etc.. [optional] # noqa: E501 economic_development_class (str): Returns the fund's economic development description from FactSet's fund classification system. This description refers to the development level for the fund's geographic region of focus, e.g. developed, emerging, etc.. [optional] # noqa: E501 focus_class (str): Returns the fund's focus description from FactSet's fund classification system. The fund's focus is the second-tier subcategory within the fund's asset class, e.g. small cap, energy, etc.. [optional] # noqa: E501 geographic_class (str): Returns the fund's specific geography description from FactSet's fund classification system. Specific geography refers to the fund's particular geographic focus within the region, e.g. Chile, BRICs, etc.. [optional] # noqa: E501 niche_class (str): Returns the fund's niche description from FactSet's fund classification system. The fund's niche is the third-tier subcategory with the fund's asset class, e.g. growth, coal, etc.. [optional] # noqa: E501 region_class (str): Returns the fund's region description from FactSet's fund classification system. Refers to the broad regional exposure of the fund's holdings, e.g. Latin America, Asia-Pacific, etc.. [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) if var_name in self.read_only_vars: raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate " f"class with read only attributes.")

57.536332

709

0.619016

15,319

0.921277

0

13,248

0.796728

0

12,467

0.749759

547ff536693b82874299f521ef54379c7a3ee663

1,637

py

Python

tests/test_drc.py

atait/lymask

a047bee386e7c9c7f04030277cdfaf7b3c731d14

[ "MIT" ]

3

2020-12-01T07:55:50.000Z

2022-03-16T22:18:07.000Z

tests/test_drc.py

atait/lymask

a047bee386e7c9c7f04030277cdfaf7b3c731d14

[ "MIT" ]

null

tests/test_drc.py

atait/lymask

a047bee386e7c9c7f04030277cdfaf7b3c731d14

[ "MIT" ]

2

2020-12-01T22:56:35.000Z

2021-05-03T09:30:09.000Z

import os, sys import subprocess import xmltodict import lymask from lymask import batch_drc_main from conftest import test_dir drc_file = os.path.join(test_dir, 'tech', 'lymask_example_tech', 'drc', 'default.yml') layout_file = os.path.join(test_dir, '2_drc_src.oas') outfile = os.path.join(test_dir, '2_drc_run.lyrdb') reffile = os.path.join(test_dir, '2_drc_answer.lyrdb') class DRC_difference(Exception): pass def assert_equal(rdb_file1, rdb_file2): ''' Errors if the rdbs are different. This is done with dictionaries not the XML text itself Note, ordering of lists matters currently (although it shouldn't). Dict key order does not (appropriately). ''' with open(rdb_file1, 'r') as fx: rdbspec1 = xmltodict.parse(fx.read(), process_namespaces=True) with open(rdb_file2, 'r') as fx: rdbspec2 = xmltodict.parse(fx.read(), process_namespaces=True) if rdbspec1 != rdbspec2: raise DRC_difference() # This one need Technology working def test_api(): lymask.set_active_technology('lymask_example_tech') batch_drc_main(layout_file, ymlspec=drc_file, outfile=outfile) assert_equal(outfile, reffile) def test_from_technology(): batch_drc_main(layout_file, ymlspec='default', outfile=outfile, technology='lymask_example_tech') assert_equal(outfile, reffile) def test_cm_from_tech(): # this also checks that it defaults to default.yml command = ['lymask', 'drc'] command += [layout_file] command += ['-o', outfile] command += ['-t', 'lymask_example_tech'] subprocess.check_call(command) assert_equal(outfile, reffile)

30.886792

115

0.722053

41

0.025046

0

504

0.30788

5480da3b737fa2ac8f9665bf668142513e4bbaba

1,731

py

Python

graphviz/parameters/formatters.py

boeddeker/graphviz

acf79bca4518781cad02c102e89ec4e9ce757088

[ "MIT" ]

1

2022-01-19T04:02:46.000Z

graphviz/parameters/formatters.py

boeddeker/graphviz

acf79bca4518781cad02c102e89ec4e9ce757088

[ "MIT" ]

1

2021-11-19T07:21:48.000Z

graphviz/parameters/formatters.py

boeddeker/graphviz

acf79bca4518781cad02c102e89ec4e9ce757088

[ "MIT" ]

1

2022-01-14T17:15:38.000Z

"""Rendering formatter parameter handling.""" import typing from . import base __all__ = ['FORMATTERS', 'verify_formatter', 'Formatter'] FORMATTERS = {'cairo', 'core', 'gd', 'gdiplus', 'gdwbmp', 'xlib'} REQUIRED = False def verify_formatter(formatter: typing.Optional[str], *, required: bool = REQUIRED) -> None: if formatter is None: if required: raise ValueError('missing formatter') elif formatter.lower() not in FORMATTERS: raise ValueError(f'unknown formatter: {formatter!r}') class Formatter(base.ParameterBase): """Rendering engine parameter (no default).""" _formatter = None _verify_formatter = staticmethod(verify_formatter) def __init__(self, *, formatter: typing.Optional[str] = None, **kwargs) -> None: super().__init__(**kwargs) self.formatter = formatter def _copy_kwargs(self, **kwargs): """Return the kwargs to create a copy of the instance.""" formatter = self._getattr_from_dict('_formatter') if formatter is not None: kwargs['formatter'] = formatter return super()._copy_kwargs(**kwargs) @property def formatter(self) -> typing.Optional[str]: """The output formatter used for rendering (``'cairo'``, ``'gd'``, ...).""" return self._formatter @formatter.setter def formatter(self, formatter: typing.Optional[str]) -> None: if formatter is None: self.__dict__.pop('_formatter', None) else: formatter = formatter.lower() self._verify_formatter(formatter) self._formatter = formatter

28.377049

84

0.60312

1,112

0.642403

0

490

0.283073

0

405

0.233969

5480e17b073b3d2de7a418823c0645c307bf4d95

183

py

Python

reward/utils/device.py

lgvaz/torchrl

cfff8acaf70d1fec72169162b95ab5ad3547d17a

[ "MIT" ]

5

2018-06-21T14:33:40.000Z

2018-08-18T02:26:03.000Z

reward/utils/device.py

lgvaz/reward

cfff8acaf70d1fec72169162b95ab5ad3547d17a

[ "MIT" ]

null

reward/utils/device.py

lgvaz/reward

cfff8acaf70d1fec72169162b95ab5ad3547d17a

[ "MIT" ]

2

2018-05-08T03:34:49.000Z

2018-06-22T15:04:17.000Z

import torch CONFIG = {"device": torch.device("cuda" if torch.cuda.is_available() else "cpu")} def get(): return CONFIG["device"] def set_device(device): CONFIG["device"] = device

22.875

81

0.704918

0

35

0.191257

548192ff87fcf5b59d3f5cc728048383ca680545

5,727

py

Python

Source/Functions/RPSLS.Python.Api/NextMove/next_move.py

ivan-b-ivanov/RockPaperScissorsLizardSpock

9167bcbe5ad2937e834408475c2ec66cf92fef84

[ "MIT" ]

null

Source/Functions/RPSLS.Python.Api/NextMove/next_move.py

ivan-b-ivanov/RockPaperScissorsLizardSpock

9167bcbe5ad2937e834408475c2ec66cf92fef84

[ "MIT" ]

null

Source/Functions/RPSLS.Python.Api/NextMove/next_move.py

ivan-b-ivanov/RockPaperScissorsLizardSpock

9167bcbe5ad2937e834408475c2ec66cf92fef84

[ "MIT" ]

null

import logging import random import os import json from typing import Tuple, List import requests def predict(player_name: str) -> str: next_move = _predict_next_move(*_get_player_games(player_name)) return _convert_game_to_json(next_move) R_rock, P_paper, S_scissors, V_spock, L_lizard = ('R', 'P', 'S', 'V', 'L') INTERNAL_MOVES_ENCODING = [R_rock, P_paper, S_scissors, V_spock, L_lizard] def _get_player_games(player_name: str) -> Tuple[str, str]: game_manager_uri = os.getenv("GAME_MANAGER_URI", None) url = f'{game_manager_uri}/game-manager/api/games?player={player_name}' logging.info(f'requesting human moves: {url}') req = requests.get(url) data = req.json() return _convert_games_to_str(data["challengerGames"]), _convert_games_to_str(data["humanGames"]) def _convert_games_to_str(games) -> str: SOURCE_MOVES_ENCODING = [R_rock, P_paper, S_scissors, L_lizard, V_spock] return "".join([SOURCE_MOVES_ENCODING[game] for game in games]) def _convert_game_to_json(game: str) -> str: JSON_MOVES_ENCODING = {R_rock: "rock", P_paper: "paper", S_scissors: "scissors", L_lizard: "lizard", V_spock: "spock"} return json.dumps({"prediction": JSON_MOVES_ENCODING[game]}) def _zip_moves(challenger_moves: List[str], human_moves: List[str]) -> List[Tuple[str, str]]: move_encoding_dict = {value: index for index, value in enumerate(INTERNAL_MOVES_ENCODING)} history = [(move_encoding_dict[i], move_encoding_dict[j]) for i, j in zip(challenger_moves, human_moves)] return history def _predict_next_move(challenger_moves: str, human_moves: str) -> str: history = _zip_moves(challenger_moves, human_moves) # what would have been predicted in the last rounds? pred_hist = [_best_next_moves_for_game( history[:i]) for i in range(2, len(history)+1)] # if no history prediction, then returns random if not pred_hist: return random.choice(INTERNAL_MOVES_ENCODING) # how would the different predictions have scored? # we have the pred_hist from moves i=2 to len(history) so we can check # check https://i.stack.imgur.com/jILea.png for game rules n_pred = len(pred_hist[0]) scores = [[0]*5 for i in range(n_pred)] for pred, real in zip(pred_hist[:-1], history[2:]): for i in range(n_pred): # %5: When an int is negative it returns the count to the move # to beat another, in (reverse order) counterclockwise # i.e -1%5=4, -2%5=3 scores[i][(real[1]-pred[i]+1) % 5] += 1 scores[i][(real[1]-pred[i]+3) % 5] += 1 # 1 & 3 move to the other "moves" that beat another # for example Rock is beaten with Paper and Spock, # which are 1 & 3 positions away scores[i][(real[1]-pred[i]+2) % 5] -= 1 scores[i][(real[1]-pred[i]+4) % 5] -= 1 # depending in predicted strategies, select best one with less risks # return best counter move best_scores = [list(max(enumerate(s), key=lambda x: x[1])) for s in scores] best_scores[-1][1] *= 1.001 # bias towards the simplest strategy if best_scores[-1][1] < 0.4*len(history): best_scores[-1][1] *= 1.4 strat, (shift, _) = max(enumerate(best_scores), key=lambda x: x[1][1]) return INTERNAL_MOVES_ENCODING[(pred_hist[-1][strat]+shift) % 5] def _best_next_moves_for_game(hist: List[str]) -> List[List[str]]: N = len(hist) # find longest match of the preceding moves in the earlier history cand_m = cand_o = cand_b = range(N-1) for l in range(1, min(N, 20)): ref = hist[N-l] # l = 1 # Looks for previous occurrences of the last move in my_moves, since hist[N-l] == hist[-1] # l = 2 # it checks which of the possible candidates was preceded by the move previous to the last # and so on... i.e loos for longest chain matching last moves to use the next move cand_m_tmp = [] for c in cand_m: if c >= l and hist[c-l+1][0] == ref[0]: cand_m_tmp.append(c) if not cand_m_tmp: cand_m = cand_m[-1:] else: cand_m = cand_m_tmp[:] # same for op_moves cand_o_tmp = [] for c in cand_o: if c >= l and hist[c-l+1][1] == ref[1]: cand_o_tmp.append(c) if not cand_o_tmp: cand_o = cand_o[-1:] else: cand_o = cand_o_tmp[:] # same for both_moves i.e directly the zipped tuples cand_b_tmp = [] for c in cand_b: if c >= l and hist[c-l+1] == ref: cand_b_tmp.append(c) if not cand_b_tmp: cand_b = cand_b[-1:] else: cand_b = cand_b_tmp[:] # analyze which moves were used how often, i.e a np.bincount freq_m, freq_o = [0]*5, [0]*5 for m in hist: freq_m[m[0]] += 1 freq_o[m[1]] += 1 # return predictions (or possible "good" strategies) last_2_moves = [j for i in hist[:-3:-1] for j in i] return (last_2_moves + # repeat last moves [hist[cand_m[-1]+1][0], # history matching of my own moves # history matching of opponent's moves hist[cand_o[-1]+1][1], hist[cand_b[-1]+1][0], # history matching of both hist[cand_b[-1]+1][1], freq_m.index(max(freq_m)), # my most frequent move freq_o.index(max(freq_o)), # opponent's most frequent move 0])

39.226027

101

0.596124

0

1,613

0.281648

5481ba7b076cad5057871b2955d0e7140c538c8a

5,410

py

Python

examples/trials/nas_cifar10/src/cifar10/nni_child_cifar10.py

runauto/nni

30152b04c4739f5b4f95087dee5f1e66ee893078

[ "MIT" ]

2

2019-12-30T20:42:17.000Z

2021-01-24T16:51:56.000Z

examples/trials/nas_cifar10/src/cifar10/nni_child_cifar10.py

runauto/nni

30152b04c4739f5b4f95087dee5f1e66ee893078

[ "MIT" ]

null

examples/trials/nas_cifar10/src/cifar10/nni_child_cifar10.py

runauto/nni

30152b04c4739f5b4f95087dee5f1e66ee893078

[ "MIT" ]

1

2020-01-11T13:19:26.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import shutil import logging import tensorflow as tf from src.cifar10.data_utils import read_data from src.cifar10.general_child import GeneralChild import src.cifar10_flags from src.cifar10_flags import FLAGS def build_logger(log_name): logger = logging.getLogger(log_name) logger.setLevel(logging.DEBUG) fh = logging.FileHandler(log_name+'.log') fh.setLevel(logging.DEBUG) logger.addHandler(fh) return logger logger = build_logger("nni_child_cifar10") def build_trial(images, labels, ChildClass): '''Build child class''' child_model = ChildClass( images, labels, use_aux_heads=FLAGS.child_use_aux_heads, cutout_size=FLAGS.child_cutout_size, num_layers=FLAGS.child_num_layers, num_cells=FLAGS.child_num_cells, num_branches=FLAGS.child_num_branches, fixed_arc=FLAGS.child_fixed_arc, out_filters_scale=FLAGS.child_out_filters_scale, out_filters=FLAGS.child_out_filters, keep_prob=FLAGS.child_keep_prob, drop_path_keep_prob=FLAGS.child_drop_path_keep_prob, num_epochs=FLAGS.num_epochs, l2_reg=FLAGS.child_l2_reg, data_format=FLAGS.data_format, batch_size=FLAGS.batch_size, clip_mode="norm", grad_bound=FLAGS.child_grad_bound, lr_init=FLAGS.child_lr, lr_dec_every=FLAGS.child_lr_dec_every, lr_dec_rate=FLAGS.child_lr_dec_rate, lr_cosine=FLAGS.child_lr_cosine, lr_max=FLAGS.child_lr_max, lr_min=FLAGS.child_lr_min, lr_T_0=FLAGS.child_lr_T_0, lr_T_mul=FLAGS.child_lr_T_mul, optim_algo="momentum", sync_replicas=FLAGS.child_sync_replicas, num_aggregate=FLAGS.child_num_aggregate, num_replicas=FLAGS.child_num_replicas ) return child_model def get_child_ops(child_model): '''Assemble child op to a dict''' child_ops = { "global_step": child_model.global_step, "loss": child_model.loss, "train_op": child_model.train_op, "lr": child_model.lr, "grad_norm": child_model.grad_norm, "train_acc": child_model.train_acc, "optimizer": child_model.optimizer, "num_train_batches": child_model.num_train_batches, "eval_every": child_model.num_train_batches * FLAGS.eval_every_epochs, "eval_func": child_model.eval_once, } return child_ops class NASTrial(): def __init__(self): images, labels = read_data(FLAGS.data_path, num_valids=0) self.output_dir = os.path.join(os.getenv('NNI_OUTPUT_DIR'), '../..') self.file_path = os.path.join( self.output_dir, 'trainable_variable.txt') self.graph = tf.Graph() with self.graph.as_default(): self.child_model = build_trial(images, labels, GeneralChild) self.total_data = {} self.child_model.build_model() self.child_ops = get_child_ops(self.child_model) config = tf.ConfigProto( intra_op_parallelism_threads=0, inter_op_parallelism_threads=0, allow_soft_placement=True) self.sess = tf.train.SingularMonitoredSession(config=config) logger.debug('initlize NASTrial done.') def run_one_step(self): '''Run this model on a batch of data''' run_ops = [ self.child_ops["loss"], self.child_ops["lr"], self.child_ops["grad_norm"], self.child_ops["train_acc"], self.child_ops["train_op"], ] loss, lr, gn, tr_acc, _ = self.sess.run(run_ops) global_step = self.sess.run(self.child_ops["global_step"]) log_string = "" log_string += "ch_step={:<6d}".format(global_step) log_string += " loss={:<8.6f}".format(loss) log_string += " lr={:<8.4f}".format(lr) log_string += " |g|={:<8.4f}".format(gn) log_string += " tr_acc={:<3d}/{:>3d}".format(tr_acc, FLAGS.batch_size) if int(global_step) % FLAGS.log_every == 0: logger.debug(log_string) return loss, global_step def run(self): '''Run this model according to the `epoch` set in FALGS''' max_acc = 0 while True: _, global_step = self.run_one_step() if global_step % self.child_ops['num_train_batches'] == 0: acc = self.child_ops["eval_func"]( self.sess, "test", self.child_model) max_acc = max(max_acc, acc) '''@nni.report_intermediate_result(acc)''' if global_step / self.child_ops['num_train_batches'] >= FLAGS.num_epochs: '''@nni.report_final_result(max_acc)''' break def main(_): logger.debug("-" * 80) if not os.path.isdir(FLAGS.output_dir): logger.debug( "Path {} does not exist. Creating.".format(FLAGS.output_dir)) os.makedirs(FLAGS.output_dir) elif FLAGS.reset_output_dir: logger.debug( "Path {} exists. Remove and remake.".format(FLAGS.output_dir)) shutil.rmtree(FLAGS.output_dir) os.makedirs(FLAGS.output_dir) logger.debug("-" * 80) trial = NASTrial() trial.run() if __name__ == "__main__": tf.app.run()

33.190184

85

0.64085

2,340

0.432532

0

738

0.136414

5481d023ae1cb5111f38843d186a6cb4876d216a

175

py

Python

apps/oper/apps.py

dryprojects/MyBlog

ec04ba2bc658e96cddeb1d4766047ca8e89ff656

[ "BSD-3-Clause" ]

2

2021-08-17T13:29:21.000Z

2021-09-04T05:00:01.000Z

apps/oper/apps.py

dryprojects/MyBlog

ec04ba2bc658e96cddeb1d4766047ca8e89ff656

[ "BSD-3-Clause" ]

1

2020-07-16T11:22:32.000Z

apps/oper/apps.py

dryprojects/MyBlog

ec04ba2bc658e96cddeb1d4766047ca8e89ff656

[ "BSD-3-Clause" ]

1

2020-09-18T10:41:59.000Z

from django.apps import AppConfig class OperConfig(AppConfig): name = 'oper' verbose_name = '用户操作管理' def ready(self): from oper import signals

17.5

34

0.64

146

0.780749

0

26

0.139037

5481e05c5889a5fab05aff46f53912b82371d733

1,952

py

Python

stella/core/interpreter/lexer.py

xabinapal/stella

ae02055749f997323390d642c99a37b80aa5df68

[ "MIT" ]

null

stella/core/interpreter/lexer.py

xabinapal/stella

ae02055749f997323390d642c99a37b80aa5df68

[ "MIT" ]

null

stella/core/interpreter/lexer.py

xabinapal/stella

ae02055749f997323390d642c99a37b80aa5df68

[ "MIT" ]

null

# -*- coding: utf-8 -*- import io import collections from stella.core.utils import RewindableIterator from stella.core.interpreter.productions import Token __all__ = ['Tokenizer', 'Lexer'] ################################################################################ ### Tokenizer ################################################################################ class Tokenizer(object): def __init__(self, tokens): self.tokens = tokens def get_token(self, value): return next((x for x in self.tokens if x.match(value)), None) ################################################################################ ### Lexer ################################################################################ class Lexer(object): def __init__(self, stream, tokenizer): iterator = iter(stream) self.iterator = RewindableIterator(iterator) self.tokenizer = tokenizer def __iter__(self): return RewindableIterator(self) def __next__(self): token = None tmp_value = next(self.iterator) tmp_token = self.tokenizer.get_token(tmp_value) token_found = False while tmp_token or not token_found: if tmp_token: token_found = True value = tmp_value token = tmp_token try: char = self.iterator.peek() tmp_token = self.tokenizer.get_token(tmp_value + char) if not token and not tmp_token and self.tokenizer.get_token(char): token_found = True value = tmp_value if tmp_token or not token_found: tmp_value = tmp_value + char next(self.iterator) except StopIteration: value = tmp_value token = tmp_token break self.iterator.commit() return Token(token, value)

29.134328

82

0.483607

1,406

0.720287

0

383

0.196209

548332d9c8a9e409da8648383e49cb1b1c4dbca5

12,628

py

Python

tensorflow_v1/10_-_Sequence-to-sequence/03_-_Dynamic_attention_with_par-inject.py

mtanti/deeplearningtutorial

a6fef37c77216e4f98dba2bde7c62d6aa6292476

[ "MIT" ]

5

2019-05-31T08:30:28.000Z

2020-02-13T20:17:13.000Z

tensorflow_v1/10_-_Sequence-to-sequence/03_-_Dynamic_attention_with_par-inject.py

mtanti/deeplearningtutorial

a6fef37c77216e4f98dba2bde7c62d6aa6292476

[ "MIT" ]

null

tensorflow_v1/10_-_Sequence-to-sequence/03_-_Dynamic_attention_with_par-inject.py

mtanti/deeplearningtutorial

a6fef37c77216e4f98dba2bde7c62d6aa6292476

[ "MIT" ]

6

2019-04-12T15:34:05.000Z

2019-10-01T16:57:39.000Z

import matplotlib.pyplot as plt import numpy as np import tensorflow as tf tf.logging.set_verbosity(tf.logging.ERROR) max_epochs = 6000 init_stddev = 0.0001 source_embedding_size = 2 target_embedding_size = 2 source_state_size = 2 preattention_size = 2 target_state_size = 2 max_seq_len = 10 source_tokens = [ 'i like it'.split(' '), 'i hate it'.split(' '), 'i don\'t hate it'.split(' '), 'i don\'t like it'.split(' '), ] target_tokens = [ 'i don\'t like it'.split(' '), 'i don\'t hate it'.split(' '), 'i hate it'.split(' '), 'i like it'.split(' '), ] source_vocab = [ 'EDGE' ] + sorted({ token for sent in source_tokens for token in sent }) source_token2index = { token: index for (index, token) in enumerate(source_vocab) } source_index2token = { index: token for (index, token) in enumerate(source_vocab) } source_max_len = max(len(sent) for sent in source_tokens) index_source_indexes = [] index_source_lens = [] for sent in source_tokens: source_lens = len(sent) source_index = [ source_token2index[token] for token in sent ] + [ 0 for _ in range(source_max_len - source_lens) ] index_source_lens.append(source_lens) index_source_indexes.append(source_index) target_vocab = [ 'EDGE' ] + sorted({ token for sent in target_tokens for token in sent }) target_token2index = { token: index for (index, token) in enumerate(target_vocab) } target_index2token = { index: token for (index, token) in enumerate(target_vocab) } target_max_len = max(len(sent) for sent in target_tokens) + 1 #Plus edge token index_target_prefixes = [] index_target_lens = [] index_target_targets = [] for sent in target_tokens: target_len = len(sent) + 1 #Plus edge token target_index = [ target_token2index[token] for token in sent ] target_prefix = [ target_token2index['EDGE'] ] + target_index + [ 0 for _ in range(target_max_len - target_len) ] target_target = target_index + [ target_token2index['EDGE'] ] + [ 0 for _ in range(target_max_len - target_len) ] index_target_prefixes.append(target_prefix) index_target_lens.append(target_len) index_target_targets.append(target_target) g = tf.Graph() with g.as_default(): source_indexes = tf.placeholder(tf.int32, [None, None], 'source_indexes') source_lens = tf.placeholder(tf.int32, [None], 'source_lens') target_prefixes = tf.placeholder(tf.int32, [None, None], 'target_prefixes') target_lens = tf.placeholder(tf.int32, [None], 'target_lens') target_targets = tf.placeholder(tf.int32, [None, None], 'target_targets') batch_size = tf.shape(source_indexes)[0] source_seq_width = tf.shape(source_indexes)[1] target_seq_width = tf.shape(target_prefixes)[1] with tf.variable_scope('source'): with tf.variable_scope('embedding'): embedding_matrix = tf.get_variable('embedding_matrix', [len(source_vocab), source_embedding_size], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) embedded = tf.nn.embedding_lookup(embedding_matrix, source_indexes) with tf.variable_scope('init_state'): init_state_fw = tf.get_variable('init_state_fw', [source_state_size], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) batch_init_fw = tf.tile(tf.reshape(init_state_fw, [1, source_state_size]), [batch_size, 1]) init_state_bw = tf.get_variable('init_state_bw', [source_state_size], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) batch_init_bw = tf.tile(tf.reshape(init_state_bw, [1, source_state_size]), [batch_size, 1]) with tf.variable_scope('rnn'): cell_fw = tf.contrib.rnn.GRUCell(source_state_size) cell_bw = tf.contrib.rnn.GRUCell(source_state_size) ((outputs_fw, outputs_bw), _) = tf.nn.bidirectional_dynamic_rnn(cell_fw, cell_bw, embedded, sequence_length=source_lens, initial_state_fw=batch_init_fw, initial_state_bw=batch_init_bw) outputs_ = tf.concat([ outputs_fw, outputs_bw ], axis=2) outputs_2d_ = tf.reshape(outputs_, [batch_size*source_seq_width, 2*source_state_size]) W = tf.get_variable('W', [2*source_state_size, source_state_size], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) b = tf.get_variable('b', [source_state_size], tf.float32, tf.zeros_initializer()) source_outputs_2d = tf.matmul(outputs_2d_, W) + b source_outputs = tf.reshape(source_outputs_2d, [batch_size, source_seq_width, source_state_size]) with tf.variable_scope('targets'): with tf.variable_scope('embedding'): embedding_matrix = tf.get_variable('embedding_matrix', [len(target_vocab), target_embedding_size], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) embedded = tf.nn.embedding_lookup(embedding_matrix, target_prefixes) with tf.variable_scope('init_state'): init_state = tf.get_variable('init_state', [target_state_size], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) batch_init = tf.tile(tf.reshape(init_state, [1, target_state_size]), [batch_size, 1]) with tf.variable_scope('rnn'): #Custom RNN cell for producing attention vectors that condition the language model via par-inject class CellAttention(tf.nn.rnn_cell.RNNCell): def __init__(self): super(CellAttention, self).__init__() self.W1 = None self.b1 = None self.W2 = None self.b2 = None self.inner_cell = tf.contrib.rnn.GRUCell(target_state_size) #The inner RNN cell that actually tranforms the input and previous state into the next state @property def state_size(self): return source_state_size @property def output_size(self): return (source_seq_width, source_state_size) #Return the attention vector apart from the next state (to be able to inspect it later) def build(self, inputs_shape): self.W1 = self.add_variable('W1', [source_state_size + target_state_size, preattention_size], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) self.b1 = tf.get_variable('b1', [preattention_size], tf.float32, tf.zeros_initializer()) self.W2 = self.add_variable('W2', [preattention_size, 1], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) self.b2 = tf.get_variable('b2', [1], tf.float32, tf.zeros_initializer()) self.built = True def call(self, next_inputs, curr_states): with tf.variable_scope('attention'): #Replicate the current state for each source sentence word in order to concatenate it with each source sentence word vector expanded_curr_state = tf.tile(tf.reshape(curr_states, [batch_size, 1, target_state_size]), [1, source_seq_width, 1]) pre_attention_input = tf.concat([ source_outputs, expanded_curr_state ], axis=2) pre_attention_input_2d = tf.reshape(pre_attention_input, [batch_size*source_seq_width, source_state_size + target_state_size]) pre_attention_2d = tf.tanh(tf.matmul(pre_attention_input_2d, self.W1) + self.b1) attention_logits = tf.reshape(tf.matmul(pre_attention_2d, self.W2) + self.b2, [batch_size, source_seq_width]) mask = tf.sequence_mask(source_lens, source_seq_width, tf.float32) attention = tf.nn.softmax(attention_logits*mask + -1e10*(1 - mask)) expanded_attention = tf.tile(tf.reshape(attention, [batch_size, source_seq_width, 1]), [1, 1, source_state_size]) attended_sources = tf.reduce_sum(source_outputs*expanded_attention, axis=1) #Pass the input and state to the inner cell to produce the next state (input consists of word embedding and attended source) (new_output, new_state) = self.inner_cell(tf.concat([ attended_sources, next_inputs ], axis=1), curr_states) return ((attention, new_state), new_state) cell = CellAttention() ((attentions, outputs), _) = tf.nn.dynamic_rnn(cell, embedded, sequence_length=target_lens, initial_state=batch_init) with tf.variable_scope('output'): W = tf.get_variable('W', [target_state_size, len(target_vocab)], tf.float32, tf.random_normal_initializer(stddev=init_stddev)) b = tf.get_variable('b', [len(target_vocab)], tf.float32, tf.zeros_initializer()) outputs_2d = tf.reshape(outputs, [batch_size*target_seq_width, target_state_size]) logits_2d = tf.matmul(outputs_2d, W) + b logits = tf.reshape(logits_2d, [batch_size, target_seq_width, len(target_vocab)]) probs = tf.nn.softmax(logits) next_word_probs = probs[:, -1, :] mask = tf.sequence_mask(target_lens, target_seq_width, tf.float32) error = tf.reduce_sum(tf.nn.sparse_softmax_cross_entropy_with_logits(labels=target_targets, logits=logits)*mask)/tf.cast(tf.reduce_sum(target_lens), tf.float32) step = tf.train.AdamOptimizer().minimize(error) init = tf.global_variables_initializer() g.finalize() with tf.Session() as s: s.run([ init ], { }) (fig, ax) = plt.subplots(1, 1) plt.ion() train_errors = list() print('epoch', 'train error', sep='\t') for epoch in range(1, max_epochs+1): s.run([ step ], { source_indexes: index_source_indexes, source_lens: index_source_lens, target_prefixes: index_target_prefixes, target_lens: index_target_lens, target_targets: index_target_targets }) [ train_error ] = s.run([ error ], { source_indexes: index_source_indexes, source_lens: index_source_lens, target_prefixes: index_target_prefixes, target_lens: index_target_lens, target_targets: index_target_targets }) train_errors.append(train_error) if epoch%100 == 0: print(epoch, train_error, sep='\t') ax.cla() ax.plot(np.arange(len(train_errors)), train_errors, color='red', linestyle='-', label='train') ax.set_xlim(0, max_epochs) ax.set_xlabel('epoch') ax.set_ylim(0.0, 2.0) ax.set_ylabel('XE') #Cross entropy ax.grid(True) ax.set_title('Error progress') ax.legend() fig.tight_layout() plt.draw() plt.pause(0.0001) print() for sent in source_tokens: source = [ source_token2index[token] for token in sent ] prefix_prob = 1.0 index_prefix = [ target_token2index['EDGE'] ] for _ in range(max_seq_len): [ curr_probs ] = s.run([ next_word_probs ], { source_indexes: [ source ], source_lens: [ len(source) ], target_prefixes: [ index_prefix ], target_lens: [ len(index_prefix) ] }) selected_index = np.argmax(curr_probs[0, :]) prefix_prob = prefix_prob*curr_probs[0, selected_index] index_prefix.append(selected_index) if selected_index == target_token2index['EDGE']: break index_generated = index_prefix[1:] generated = [ target_index2token[i] for i in index_generated ] [ curr_attentions ] = s.run([ attentions ], { source_indexes: [ source ], source_lens: [ len(source) ], target_prefixes: [ index_generated ], target_lens: [ len(index_generated) ] }) print('Input sentence: ', ' '.join(sent)) print('Generated sentence:', ' '.join(generated)) print('Sentence probability:', prefix_prob) print('Attention:') print('', '\t', *sent) for i in range(len(generated)): print('', generated[i]+'\t', np.round(curr_attentions[0, i, :], 2)) print() fig.show()

52.83682

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3,153

0.249683

0

293

0.023202

0

1,183

0.093681

54835562ea5262f2ee7bb00d7ceac361aa51a6f1

226

py

Python

lnd/utils.py

gsmadi/lightningpy

14f4cc2dd5eb8726a06db8798944302974b890aa

[ "MIT" ]

null

lnd/utils.py

gsmadi/lightningpy

14f4cc2dd5eb8726a06db8798944302974b890aa

[ "MIT" ]

3

2019-08-21T11:51:52.000Z

2019-10-07T11:51:45.000Z

lnd/utils.py

smadici-labs/pylnd

14f4cc2dd5eb8726a06db8798944302974b890aa

[ "MIT" ]

null

import codecs def encode_macaroon(macaroon): encoded_macaroon = codecs.encode(macaroon, 'hex') return encoded_macaroon def read_file(file_path): opened_file = open(file_path, 'rb').read() return opened_file

20.545455

53

0.738938

0

9

0.039823

5483a8653b465908b4e7a3a5f68321bd151006ac

1,649

py

Python

ctapipe/image/muon/ring_fitter.py

chaimain/ctapipe

ff80cff2daaf56e1d05ea6501c68fd83a9cf79d5

[ "BSD-3-Clause" ]

53

2015-06-23T15:24:20.000Z

2021-09-23T22:30:58.000Z

ctapipe/image/muon/ring_fitter.py

chaimain/ctapipe

ff80cff2daaf56e1d05ea6501c68fd83a9cf79d5

[ "BSD-3-Clause" ]

1,537

2015-06-24T11:27:16.000Z

2022-03-31T16:17:08.000Z

ctapipe/image/muon/ring_fitter.py

chaimain/ctapipe

ff80cff2daaf56e1d05ea6501c68fd83a9cf79d5

[ "BSD-3-Clause" ]

275

2015-07-09T14:09:28.000Z

2022-03-17T22:25:51.000Z

import numpy as np from ctapipe.core import Component from ctapipe.containers import MuonRingContainer from .fitting import kundu_chaudhuri_circle_fit, taubin_circle_fit import traitlets as traits # the fit methods do not expose the same interface, so we # force the same interface onto them, here. # we also modify their names slightly, since the names are # exposed to the user via the string traitlet `fit_method` def kundu_chaudhuri(x, y, weights, mask): """kundu_chaudhuri_circle_fit with x, y, weights, mask interface""" return kundu_chaudhuri_circle_fit(x[mask], y[mask], weights[mask]) def taubin(x, y, weights, mask): """taubin_circle_fit with x, y, weights, mask interface""" return taubin_circle_fit(x, y, mask) FIT_METHOD_BY_NAME = {m.__name__: m for m in [kundu_chaudhuri, taubin]} __all__ = ["MuonRingFitter"] class MuonRingFitter(Component): """Different ring fit algorithms for muon rings""" fit_method = traits.CaselessStrEnum( list(FIT_METHOD_BY_NAME.keys()), default_value=list(FIT_METHOD_BY_NAME.keys())[0], ).tag(config=True) def __call__(self, x, y, img, mask): """allows any fit to be called in form of MuonRingFitter(fit_method = "name of the fit") """ fit_function = FIT_METHOD_BY_NAME[self.fit_method] radius, center_x, center_y = fit_function(x, y, img, mask) return MuonRingContainer( center_x=center_x, center_y=center_y, radius=radius, center_phi=np.arctan2(center_y, center_x), center_distance=np.sqrt(center_x ** 2 + center_y ** 2), )

32.333333

71

0.691935

797

0.483323

0

519

0.314736

5484be9bfb8cd5688ba3f0f969954eaa83e32875

1,873

py

Python

Main.py

dalwindercheema/FWPython

4c5d4d6d0b29a199dbf37d16bd4ed9bb2ac22d19

[ "BSD-2-Clause" ]

2

2021-12-18T17:08:02.000Z

2021-12-22T04:19:15.000Z

Main.py

dalwindercheema/FWPython

4c5d4d6d0b29a199dbf37d16bd4ed9bb2ac22d19

[ "BSD-2-Clause" ]

null

Main.py

dalwindercheema/FWPython

4c5d4d6d0b29a199dbf37d16bd4ed9bb2ac22d19

[ "BSD-2-Clause" ]

null

import pandas as pd from os import listdir import numpy from sklearn.model_selection import StratifiedKFold from FS_ALO import WFS from FW_ALO import WFW from WFSWFW_ALO import WFSWFW import matplotlib.pyplot as plt def main_CV(): path='./datasets' direc=sorted(listdir(path)) print(direc) population=20 Total_iter=200 total_reruns=20 Cost=numpy.zeros([len(direc),total_reruns,3],dtype=numpy.float64) CC=numpy.zeros([len(direc),total_reruns,Total_iter,3],dtype=numpy.float64) Best_WFS=[] Best_WFW=[] Best_WFSWFW=[] for dir_idx in range(0,len(direc)): data_path=path+'/'+direc[dir_idx] print(data_path) tl=pd.read_csv(data_path,header=None,dtype='str') tl.drop([0],axis=0,inplace=True) data_array=numpy.array(tl) data=data_array.astype(numpy.float) dim=data.shape train=data[:,0:dim[1]-1] label=data[:,dim[1]-1] for i in range(0,total_reruns): cv=StratifiedKFold(n_splits=10,shuffle=True,random_state=i) Cost[dir_idx,i,0],Elite_pos1,CC[dir_idx,i,:,0]=WFS(train,label,cv,population,Total_iter) Cost[dir_idx,i,1],Elite_pos2,CC[dir_idx,i,:,1]=WFW(train,label,cv,population,Total_iter) Cost[dir_idx,i,2],FS_pos,FW_pos,CC[dir_idx,i,:,2]=WFSWFW(train,label,cv,population,Total_iter) Best_WFS.append(Elite_pos1) Best_WFW.append(Elite_pos2) Best_WFSWFW.append(FS_pos) Best_WFSWFW.append(FW_pos) mean_CC=numpy.mean(CC,axis=1) for i in range(0,1): plt.plot(mean_CC[i,:,0],color='r') plt.plot(mean_CC[i,:,1],color='b') plt.plot(mean_CC[i,:,2],color='g') return Cost,Best_WFS,Best_WFW,Best_WFSWFW,CC # Main program Cost,Best_WFS,Best_WFW,Best_WFSWFW,CC=main_CV()

36.019231

107

0.645489

0

44

0.023492

548634bd7f60817d2246c17acdb44bb98affa644

1,189

py

Python

demo/demo/models.py

dracarysX/django-rest-query

62fe8ee8f72251a1a8982265fff57870f2d43ca9

[ "MIT" ]

2

2017-06-28T02:51:52.000Z

2017-06-28T09:28:33.000Z

demo/demo/models.py

dracarysX/django-rest-query

62fe8ee8f72251a1a8982265fff57870f2d43ca9

[ "MIT" ]

null

demo/demo/models.py

dracarysX/django-rest-query

62fe8ee8f72251a1a8982265fff57870f2d43ca9

[ "MIT" ]

null

#! /usr/bin/env python # -*-coding: utf-8 -*- __author__ = 'dracarysX' from django.db import models class Publisher(models.Model): id = models.AutoField(primary_key=True) name = models.CharField(max_length=100) class Meta: db_table = 'Publisher' def __str__(self): return 'Publisher: {}'.format(self.name) class School(models.Model): id = models.AutoField(primary_key=True) name = models.CharField(max_length=100) class Meta: db_table = 'School' def __str__(self): return 'School: {}'.format(self.name) class Author(models.Model): id = models.AutoField(primary_key=True) name = models.CharField(max_length=50) age = models.IntegerField() school = models.ForeignKey(School) class Meta: db_table = 'Author' def __str__(self): return 'Author: {}'.format(self.name) class Book(models.Model): id = models.AutoField(primary_key=True) name = models.CharField(max_length=50) author = models.ForeignKey(Author) publisher = models.ForeignKey(Publisher) class Meta: db_table = 'Book' def __str__(self): return 'Book: {}'.format(self.name)

22.018519

48

0.652649

1,076

0.904962

0

137

0.115223

54870fd0b78e5e716753c262ab01d38621a1dd9c

4,796

py

Python

feedback-api/src/api/services/feedback/feedback_camunda_service.py

josekudiyirippil/queue-management

e56a987e14cfd2b50b820f679c7669060450da8e

[ "Apache-2.0" ]

30

2018-09-19T03:30:51.000Z

2022-03-07T02:57:05.000Z

feedback-api/src/api/services/feedback/feedback_camunda_service.py

ann-aot/queue-management

8ac8353a1e5f3f27fea74e70831ab5f0590d1805

[ "Apache-2.0" ]

159

2018-09-17T23:45:58.000Z

2022-03-30T17:35:05.000Z

feedback-api/src/api/services/feedback/feedback_camunda_service.py

ann-aot/queue-management

8ac8353a1e5f3f27fea74e70831ab5f0590d1805

[ "Apache-2.0" ]

52

2018-05-18T18:30:06.000Z

2021-08-25T12:00:29.000Z

# Copyright © 2019 Province of British Columbia # # 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. """Submit Citizen feedback. This module consists of API that calls Camunda BPM to save citizen feedback comments. """ import os, requests, json from typing import Dict from jinja2 import Environment, FileSystemLoader from .feedback_base_service import FeedbackBaseService from flask import jsonify class FeedbackCamundaService(FeedbackBaseService): """Implementation from FeedbackService.""" def submit(self, payload): """Submit feedback to Camunda API""" camunda_service_endpoint = os.getenv('FEEDBACK_CAMUNDA_URL') keycloak_endpoint = os.getenv('FEEDBACK_AUTH_URL') keycloak_client_id = os.getenv('FEEDBACK_AUTH_CLIENT_ID') keycloak_client_secret = os.getenv('FEEDBACK_AUTH_CLIENT_SECRET') auth_payload = {"grant_type":"client_credentials", "client_id":keycloak_client_id, "client_secret":keycloak_client_secret} try: auth_response = requests.post(keycloak_endpoint,data=auth_payload) access_token = auth_response.json()['access_token'] headers = {'Content-Type': 'application/json', 'Authorization': f'Bearer {access_token}'} feedback_response = requests.post(camunda_service_endpoint, headers=headers, data=json.dumps(payload), timeout=10.0) response_code = feedback_response.status_code if (response_code != 200 and response_code != 201 and response_code != 202) : raise Exception('Camunda API Failure') return feedback_response.status_code except Exception as e: feedback_type = payload['variables']['engagement']['value'] feedback_message = payload['variables']['citizen_comments']['value'] response_required = payload['variables']['response']['value'] citizen_name = payload['variables']['citizen_name']['value'] citizen_contact = payload['variables']['citizen_contact']['value'] citizen_email = payload['variables']['citizen_email']['value'] service_date = payload['variables']['service_date']['value'] submit_date_time = payload['variables']['submit_date_time']['value'] ENV = Environment(loader=FileSystemLoader('.'), autoescape=True) template = ENV.get_template('camunda_email_template.template') body = template.render(feedback_type =feedback_type, feedback_message =feedback_message, response_required =response_required, citizen_name =citizen_name, citizen_contact =citizen_contact, citizen_email =citizen_email, service_date =service_date, submit_date_time =submit_date_time) application_auth_url = os.getenv('APP_AUTH_URL') application_client_id = os.getenv('APP_AUTH_CLIENT_ID') application_client_secret = os.getenv('APP_AUTH_CLIENT_SECRET') notification_email_url = os.getenv('NOTIFICATION_EMAIL_URL') email_to = (os.getenv('NOTIFICATION_EMAIL_TO')).split(",") app_auth_payload = {"grant_type":"client_credentials", "client_id":application_client_id, "client_secret":application_client_secret} email_payload = { 'bodyType': 'text', 'body': body, 'subject': 'Citizen Feedback - Camunda API failure', 'to': email_to } app_auth_response = requests.post(application_auth_url,data=app_auth_payload) app_access_token = app_auth_response.json()['access_token'] email_headers = {'Content-Type': 'application/json', 'Authorization': f'Bearer {app_access_token}'} email_response = requests.post(notification_email_url, headers=email_headers, data=json.dumps(email_payload)) print(email_response) print(e) return email_response.status_code

51.021277

111

0.641785

3,891

0.811132

0

1,665

0.347092

5489ae18fd1a18ba304d5257203fc13d1b20346d

2,334

py

Python

dezede/urls.py

dezede/dezede

985ed1b42a2a6bab996e26c1b92444ae04afcc2c

[ "BSD-3-Clause" ]

15

2015-02-10T21:16:31.000Z

2021-03-25T16:46:20.000Z

dezede/urls.py

dezede/dezede

985ed1b42a2a6bab996e26c1b92444ae04afcc2c

[ "BSD-3-Clause" ]

4

2021-02-10T15:42:08.000Z

2022-03-11T23:20:38.000Z

dezede/urls.py

dezede/dezede

985ed1b42a2a6bab996e26c1b92444ae04afcc2c

[ "BSD-3-Clause" ]

6

2016-07-10T14:20:48.000Z

2022-01-19T18:34:02.000Z

from django.conf import settings from django.conf.urls import * from django.conf.urls.static import static from django.contrib import admin from django.contrib.sitemaps.views import sitemap from django.views.decorators.cache import cache_page from django.views.generic import TemplateView from ajax_select import urls as ajax_select_urls from .views import ( HomeView, CustomSearchView, autocomplete, ErrorView, BibliographieView, RssFeed, GlobalSitemap, ) admin.autodiscover() urlpatterns = [ url(r'^$', HomeView.as_view(), name='home'), url(r'^', include('libretto.urls')), url(r'^examens/', include('examens.urls')), url(r'^presentation$', TemplateView.as_view(template_name='pages/presentation.html'), name='presentation'), url(r'^contribuer$', TemplateView.as_view(template_name='pages/contribute.html'), name='contribuer'), url(r'^bibliographie$', BibliographieView.as_view(), name='bibliographie'), url(r'^', include('accounts.urls')), url(r'^dossiers/', include('dossiers.urls')), url(r'^admin/lookups/', include(ajax_select_urls)), url(r'^admin/', admin.site.urls), url(r'^i18n/', include('django.conf.urls.i18n')), url(r'^tinymce/', include('tinymce.urls')), url(r'^grappelli/', include('grappelli.urls')), url(r'^recherche/', CustomSearchView(), name='haystack_search'), url(r'^api-auth/', include('rest_framework.urls', namespace='rest_framework')), url(r'^autocomplete$', autocomplete, name='autocomplete'), url(r'^rss\.xml$', RssFeed(), name='rss_feed'), url(r'^sitemap.xml$', cache_page(24*60*60)(sitemap), {'sitemaps': {'global': GlobalSitemap}}, name='django.contrib.sitemaps.views.sitemap'), url(r'^404$', ErrorView.as_view(status=404)), ] if settings.DEBUG: urlpatterns += static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) urlpatterns += static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT) import debug_toolbar urlpatterns += [ url(r'^__debug__/', include(debug_toolbar.urls)), url(r'^403$', ErrorView.as_view(status=403)), url(r'^500$', ErrorView.as_view(status=500)), url(r'^503$', ErrorView.as_view(status=503)), ]

38.9

79

0.662811

0

612

0.262211

548afc21b16ee46ad8044ba3566ba260b8c8d71a

899

py

Python

database/chemtrack/contacts.py

mshobair/invitro_cheminformatics

17201496c73453accd440646a1ee81726119a59c

[ "MIT" ]

null

database/chemtrack/contacts.py

mshobair/invitro_cheminformatics

17201496c73453accd440646a1ee81726119a59c

[ "MIT" ]

null

database/chemtrack/contacts.py

mshobair/invitro_cheminformatics

17201496c73453accd440646a1ee81726119a59c

[ "MIT" ]

null

import datetime from database.database_schemas import Schemas from sqlalchemy import Column, Integer, String, DateTime from database.base import Base class Contacts(Base): """Maps to contacts table in chemprop databases.""" __tablename__ = 'contacts' __table_args__ = {'schema': Schemas.qsar_schema} id = Column(Integer, primary_key=True, nullable=False) first_name = Column(String) last_name = Column(String) vendor_id = Column(Integer) email = Column(String) title = Column(String) phone1 = Column(String) phone2 = Column(String) fax = Column(String) cell = Column(String) other_details = Column(String) department = Column(String) contact_type_id = Column(Integer) created_at = Column(DateTime, default=datetime.datetime.now, nullable=False) updated_at = Column(DateTime, default=datetime.datetime.now, nullable=False)

31

80

0.72525

745

0.828699

0

69

0.076752

548ba908b52f98060805c6474bd241356237c223

7,487

py

Python

otter/generate/autograder.py

drjbarker/otter-grader

9e89e1675b09cf7889995b5f1bc8e1648bf6c309

[ "BSD-3-Clause" ]

null

otter/generate/autograder.py

drjbarker/otter-grader

9e89e1675b09cf7889995b5f1bc8e1648bf6c309

[ "BSD-3-Clause" ]

null

otter/generate/autograder.py

drjbarker/otter-grader

9e89e1675b09cf7889995b5f1bc8e1648bf6c309

[ "BSD-3-Clause" ]

null

""" Gradescope autograder configuration generator for Otter Generate """ import os import json import shutil # import subprocess import zipfile import tempfile import pathlib import pkg_resources import yaml from glob import glob from subprocess import PIPE from jinja2 import Template from .token import APIClient from .utils import zip_folder from ..plugins import PluginCollection from ..run.run_autograder.constants import DEFAULT_OPTIONS TEMPLATE_DIR = pkg_resources.resource_filename(__name__, "templates") MINICONDA_INSTALL_URL = "https://repo.anaconda.com/miniconda/Miniconda3-py38_4.9.2-Linux-x86_64.sh" OTTER_ENV_NAME = "otter-env" def main(tests_path, output_path, config, lang, requirements, overwrite_requirements, environment, username, password, files, assignment=None, plugin_collection=None, **kwargs): """ Runs Otter Generate Args: tests_path (``str``): path to directory of test files for this assignment output_path (``str``): directory in which to write output zip file config (``str``): path to an Otter configuration JSON file lang (``str``): the language of the assignment; one of ``["python", "r"]`` requirements (``str``): path to a Python or R requirements file for this assignment overwrite_requirements (``bool``): whether to overwrite the default requirements instead of adding to them environment (``str``): path to a conda environment file for this assignment username (``str``): a username for Gradescope for generating a token password (``str``): a password for Gradescope for generating a token files (``list[str]``): list of file paths to add to the zip file assignment (``otter.assign.assignment.Assignment``, optional): the assignment configurations if used with Otter Assign **kwargs: ignored kwargs (a remnant of how the argument parser is built) Raises: ``FileNotFoundError``: if the specified Otter configuration JSON file could not be found ``ValueError``: if the configurations specify a Gradescope course ID or assignment ID but not both """ # read in otter_config.json if config is None and os.path.isfile("otter_config.json"): config = "otter_config.json" if config is not None and not os.path.isfile(config): raise FileNotFoundError(f"Could not find otter configuration file {config}") if config: with open(config) as f: otter_config = json.load(f) else: otter_config = {} if "course_id" in otter_config and "assignment_id" in otter_config: client = APIClient() if username is not None and password is not None: client.log_in(username, password) token = client.token else: token = client.get_token() otter_config["token"] = token elif "course_id" in otter_config or "assignment_id" in otter_config: raise ValueError(f"Otter config contains 'course_id' or 'assignment_id' but not both") options = DEFAULT_OPTIONS.copy() options.update(otter_config) # update language options["lang"] = lang.lower() template_dir = os.path.join(TEMPLATE_DIR, options["lang"]) templates = {} for fn in os.listdir(template_dir): fp = os.path.join(template_dir, fn) if os.path.isfile(fp): # prevents issue w/ finding __pycache__ in template dirs with open(fp) as f: templates[fn] = Template(f.read()) template_context = { "autograder_dir": options['autograder_dir'], "otter_env_name": OTTER_ENV_NAME, "miniconda_install_url": MINICONDA_INSTALL_URL, "ottr_branch": "stable", } if plugin_collection is None: plugin_collection = PluginCollection(otter_config.get("plugins", []), None, {}) else: plugin_collection.add_new_plugins(otter_config.get("plugins", [])) plugin_collection.run("during_generate", otter_config, assignment) # create tmp directory to zip inside with tempfile.TemporaryDirectory() as td: # try: # copy tests into tmp test_dir = os.path.join(td, "tests") os.mkdir(test_dir) pattern = ("*.py", "*.[Rr]")[options["lang"] == "r"] for file in glob(os.path.join(tests_path, pattern)): shutil.copy(file, test_dir) # open requirements if it exists requirements = requirements reqs_filename = f"requirements.{'R' if options['lang'] == 'r' else 'txt'}" if requirements is None and os.path.isfile(reqs_filename): requirements = reqs_filename if requirements: assert os.path.isfile(requirements), f"Requirements file {requirements} not found" f = open(requirements) else: f = open(os.devnull) template_context["other_requirements"] = f.read() template_context["overwrite_requirements"] = overwrite_requirements # close the {% if not other_requirements %}stream f.close() # open environment if it exists # unlike requirements.txt, we will always overwrite, not append by default environment = environment env_filename = "environment.yml" if environment is None and os.path.isfile(env_filename): environment = env_filename if environment: assert os.path.isfile(environment), f"Environment file {environment} not found" with open(environment) as f: data = yaml.safe_load(f) data['name'] = template_context["otter_env_name"] template_context["other_environment"] = yaml.safe_dump(data, default_flow_style=False) f.close() else: template_context["other_environment"] = None rendered = {} for fn, tmpl in templates.items(): rendered[fn] = tmpl.render(**template_context) if os.path.isabs(output_path): zip_path = os.path.join(output_path, "autograder.zip") else: zip_path = os.path.join(os.getcwd(), output_path, "autograder.zip") if os.path.exists(zip_path): os.remove(zip_path) with zipfile.ZipFile(zip_path, mode="w") as zf: for fn, contents in rendered.items(): zf.writestr(fn, contents) test_dir = "tests" pattern = ("*.py", "*.[Rr]")[options["lang"] == "r"] for file in glob(os.path.join(tests_path, pattern)): zf.write(file, arcname=os.path.join(test_dir, os.path.basename(file))) zf.writestr("otter_config.json", json.dumps(otter_config, indent=2)) # copy files into tmp if len(files) > 0: for file in files: full_fp = os.path.abspath(file) assert os.getcwd() in full_fp, f"{file} is not in a subdirectory of the working directory" if os.path.isfile(full_fp): zf.write(file, arcname=os.path.join("files", file)) elif os.path.isdir(full_fp): zip_folder(zf, full_fp, prefix="files") else: raise ValueError(f"Could not find file or directory '{full_fp}'") if assignment is not None: assignment._otter_config = otter_config

38.792746

110

0.631762

0

2,746

0.366769