Saravanan666/pypi-org huggingface dataset:
Package: teststar
Celery TestStar=============TestStar is based on Mher's Flower but extends the functionality to scheduled automated test suitesFeatures--------- Scheduled automated python test suites- Across multiple celery workers- Broker is RabbitMQ- Real-time monitoring using Celery Events- Task progress and history- Ability to show task details (arguments, start time, runtime, and more)- Graphs and statistics- Remote Control- View worker status and statistics- Shutdown and restart worker instances- Control worker pool size and autoscale settings- View and modify the queues a worker instance consumes from- View currently running tasks- View scheduled tasks (ETA/countdown)- View reserved and revoked tasks- Apply time and rate limits- Configuration viewer- Revoke or terminate tasks- Broker monitoring- View statistics for all Celery queues- Queue length graphs- HTTP API- Basic Auth and Google OpenID authenticationAPI---Flower API enables to manage the cluster via REST api, call tasks and receive taskevents in real-time via WebSockets.For example you can schedule a deployment of packages: ::$ curl -X POST http://localhost:8888/api/deploy/package/myworkerOr restart worker's pool by: ::$ curl -X POST http://localhost:8888/api/worker/pool/restart/myworkerOr call a task by: ::$ curl -X POST -d '{"args":[1,2]}' http://localhost:8888/api/task/async-apply/tasks.addOr terminate executing task by: ::$ curl -X POST -d 'terminate=True' http://localhost:8888/api/task/revoke/8a4da87b-e12b-4547-b89a-e92e4d1f8efdOr receive task completion events in real-time: ::var ws = new WebSocket('ws://localhost:8888/api/task/events/task-succeeded/');ws.onmessage = function (event) {console.log(event.data);}Installation------------To install, simply: ::$ pip install teststarUsage-----Launch the server and open http://localhost:8888: ::$ teststar --port=8888Or launch from celery: ::$ celery teststar --address=127.0.0.1 --port=8888Broker URL and other configuration options can be passed through the standard Celery options: ::$ celery teststar --broker=amqp://guest:guest@localhost:5672//$ celery teststar --broker_url=amqp://guest:guest@localhost:5672// --broker_api=http://guest:guest@localhost:55672/api/Screenshots-----------.. image:: https://raw.github.com/mdaloia/teststar/master/docs/screenshots/dashboard.png:width: 800px.. image:: https://raw.github.com/mdaloia/teststar/docs/screenshots/pool.png:width: 800px.. image:: https://raw.github.com/mdaloia/teststar/master/docs/screenshots/tasks.png:width: 800px.. image:: https://raw.github.com/mdaloia/teststar/master/docs/screenshots/task.png:width: 800px.. image:: https://raw.github.com/mdaloia/teststar/master/docs/screenshots/monitor.png:width: 800pxMore screenshots_.. _screenshots: https://github.com/mdaloia/teststar/tree/master/docs/screenshotsGetting help------------Please head over to #celery IRC channel on irc.freenode.net or`open an issue`_... _open an issue: https://github.com/mher/flower/issues
Package: test-step-parser
The test step parser is a universal format for describing automated test steps &amp; automatically parse source code and generate a step metadata for AI &amp; humans to create automated tests fast and easy.Installingmake sure you have python 3.7+ installed.we recommend using venv:python -m venv venv
source venv/bin/activate || venv\\Scripts\\activateInstall and update usingpip:pip install -U test_step_parserto exit your virtual environment:(venv) path/to/tests>deactivateSimple Examplespython-mtest_step_parsercreateCommunityPlease checkout our public test repository at:https://github.com/qaviton/test_repositoryThe Qaviton team wants to contribute and share testing experience.
You can use our tests and utilities in your project
and even share your own tests code, functions and experience.Be part of something big.ContributingFor guidance on setting up a development environment and how to make a
contribution to Qaviton, see thecontributing guidelines.DonateThe Qaviton organization develops and supports qaviton and the libraries
it uses. In order to grow the community of contributors and users, and
allow the maintainers to devote more time to the projects,please
donate today.LinksWebsite:https://www.qaviton.comDocumentation:https://github.com/qaviton/qaviton/blob/master/docs/License:Apache License 2.0Releases:https://pypi.org/project/qaviton/Code:https://github.com/qaviton/qavitonIssue tracker:https://github.com/qaviton/qaviton/issuesTest status:Linux, Mac:https://travis-ci.org/qaviton/qavitonWindows:https://ci.appveyor.com/project/qaviton/qavitonTest coverage:https://codecov.io/gh/qaviton/qaviton
Package: testsuite
testsuiteA tool for writing and validating BuildingSync use cases as Schematron files.
See theBuildingSync use-casesrepository for current Schematron and example files for particular use cases.Command line validationSetupInstall from pypipipinstalltestsuiteInstall from sourcePoetryis required to install testsuite.# Copy repogitclonehttps://github.com/BuildingSync/TestSuite.git# install the packagecdTestSuite
poetryinstall# Test that it works, you should see a message describing the usagepoetryruntestsuiteUsagePythonfromtestsuite.validate_schimportvalidate_schematron# run basic validation# returns an array of testsuite.validate_sch.Failuresfailures=validate_schematron('my_schematron.sch','my_xml.xml')# save the svrl result filefailures=validate_schematron('my_schematron.sch','my_xml.xml',result_path='validation_result.svrl')# run a specific phase in schematronfailures=validate_schematron('my_schematron.sch','my_xml.xml',phase='MyPhaseID')# report unfired rules as errorsfailures=validate_schematron('my_schematron.sch','my_xml.xml',strict_context=True)# fetch a file from the use-cases repo and use it for validationimporturllib.requestschematron_url='https://raw.githubusercontent.com/BuildingSync/use-cases/main/SEED/schematron/SEED-1.0.0.sch'schematron_filename='local_schematron.sch'urllib.request.urlretrieve(schematron_url,filename=schematron_filename)failures=validate_schematron(schematron_filename,'my_xml.xml')CLItestsuitevalidatemy_schematron.schmy_xml.xml# see all optionstestsuitevalidate--helpDevelopmentGenerate SchematronFirst create a CSV file that meets the required structure:phase title,phase see,pattern title,pattern see,rule title,rule context,assert test,assert description,assert severity,notesSee the CSV files in this repo for examples.Hierarchy is implied by the lack of text in a column. If no phase data is added to a row, it's considered to be the same phase as the row above. If no pattern data is present, it's assumed to be the same pattern as above. If no rule context is given, it's assumed to be the same as the one above.The generator expects a "exemplary" xml file which should pass the validation. This is used to make sure all rules are applied (schematron will skip rules if the rule context doesn't match or if it only matches nodes that have already been matched within that pattern). If no exemplary file is provided no rule context checks will be made.poetryruntestsuitegeneratepath_to_csv[path_to_exemplary_xml]Testingpoetryruntox-epython
Package: testsuite-prettyprint-outcomes
===============================testsuite-prettyprint-outcomes===============================testsuite-prettyprint-outcomes is a nose2 plugin that prettyprints test outcomes... warning::This project is currently released as a prototype. While as far as I know it works it is untested.Please report bugs you find to the `issue tracker <http://github.com/testsuite/testsuite-prettyprint-outcomes/issues>`_Installation============``pip install testsuite-prettyprint-outcomes``Configuartion=============To add testsuite-prettyprint-outcomes to your plugins go to your nose2 configuration file (unittest2.cfg or nose2.cfg) and add it to the plugins list... code-block::[unittest]plugins = # ...testsuite.prettyprint.outcomesDocumentation=============The documentation for this project can be found at https://testsuite-prettyprint-outcomes.readthedocs.org/en/latest/
Package: testsuite-prettyprint-traceback
===============================testsuite-prettyprint-traceback===============================testsuite-prettyprint-traceback is a nose2 plugin that prettyprints traceback on failures and errors... warning::This project is currently released as a prototype. While as far as I know it works it is untested.Please report bugs you find to the `issue tracker <http://github.com/testsuite/testsuite-prettyprint-traceback/issues>`_Installation============``pip install testsuite-prettyprint-traceback``Configuartion=============To add testsuite-prettyprint-traceback to your plugins go to your nose2 configuration file (unittest2.cfg or nose2.cfg) and add it to the plugins list... code-block::[unittest]plugins = # ...testsuite.prettyprint.tracebackDocumentation=============The documentation for this project can be found at https://testsuite-prettyprint-traceback.readthedocs.org/en/latest/
Package: test-sw-12241
English|简体中文SwanLab is the next-generation machine learning experiment management and visualization tool released by theSwanHub, designed to facilitate effective collaboration in machine learning training.SwanLab provides streamlined APIs that make it easy to track machine learning metrics and record configurations. Additionally, SwanLab provides a visual dashboard for the most intuitive way tomonitor,analyze, andcompareyour training.For specific guidance on SwanLab's features, please refer to theUser Guide.Currently, SwanLab is undergoing rapid iterations and will continue to add new features.InstallationThis repository is tested on Python 3.8+.SwanLab can be installed using pip as follows:pipinstallswanlabQuick tourLet's simulate a simple machine learning training process, usingswanlab.initto initialize the experiment and record configuration information, and usingswanlab.logto track key metrics (in this example, it'slossandacc):importswanlabimporttimeimportrandomlr=0.01epochs=20# Initialize the experiment and record configuration informationswanlab.init(description="This is a sample experiment for machine learning training.",config={"learning_rate":lr,"epochs":epochs,},)# Simulate a machine learning training processforepochinrange(2,epochs):acc=1-2**-epoch-random.random()/epoch-offsetloss=2**-epoch+random.random()/epoch+offset# Track key metricsswanlab.log({"loss":loss,"accuracy":acc})time.sleep(0.1)During the program running, aswanlogfolder will be generated in the directory to record your training data.If you want to visualize your experiment, open the terminal and enter the root directory (no need to enter theswanlogfolder), and run the following command:swanlabwatchIf you see the following output, it means that the experimental board is running successfully:[SwanLab-INFO]:        SwanLab Experiment Dashboard ready in 375ms➜  Local:   http://127.0.0.1:5092Accesshttp://127.0.0.1:5092at this time to enter the experiment dashboard and browse your experimental results：LicenseApache 2.0 License
Package: testteaairdrop
一、安装（python版本建议3.7以上）pipinstalldubborequests二、升级包pipinstall--upgradedubborequests三、示例获取dubbo服务详情# 导入importdubborequests# 获取dubbo服务详情data=dubborequests.search('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')获取服务下的所有方法# 导入importdubborequests# 获取dubbo服务下的所有方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')# 获取dubbo服务指定的方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService','login')通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口importdubborequestsfromdubborequestsimportConfig# 先配置zookeeper中心地址Config.zookeeper_url_list=['192.168.240.15:2181','192.168.240.15:2182','192.168.240.15:2183']invoke_data={"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# 通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口data=dubborequests.zk_invoke(*invoke_data)Telnet命令测试dubbo接口importdubborequestsinvoke_data={"ip":'xxxx',"port":7777,"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# Telnet命令测试dubbo接口data=dubborequests.telnet_invoke(*invoke_data)
Package: testteabugmaker
一、安装（python版本建议3.7以上）pipinstalldubborequests二、升级包pipinstall--upgradedubborequests三、示例获取dubbo服务详情# 导入importdubborequests# 获取dubbo服务详情data=dubborequests.search('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')获取服务下的所有方法# 导入importdubborequests# 获取dubbo服务下的所有方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')# 获取dubbo服务指定的方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService','login')通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口importdubborequestsfromdubborequestsimportConfig# 先配置zookeeper中心地址Config.zookeeper_url_list=['192.168.240.15:2181','192.168.240.15:2182','192.168.240.15:2183']invoke_data={"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# 通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口data=dubborequests.zk_invoke(*invoke_data)Telnet命令测试dubbo接口importdubborequestsinvoke_data={"ip":'xxxx',"port":7777,"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# Telnet命令测试dubbo接口data=dubborequests.telnet_invoke(*invoke_data)
Package: testteaplatfrom
一、安装（python版本建议3.7以上）pipinstalldubborequests二、升级包pipinstall--upgradedubborequests三、示例获取dubbo服务详情# 导入importdubborequests# 获取dubbo服务详情data=dubborequests.search('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')获取服务下的所有方法# 导入importdubborequests# 获取dubbo服务下的所有方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')# 获取dubbo服务指定的方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService','login')通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口importdubborequestsfromdubborequestsimportConfig# 先配置zookeeper中心地址Config.zookeeper_url_list=['192.168.240.15:2181','192.168.240.15:2182','192.168.240.15:2183']invoke_data={"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# 通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口data=dubborequests.zk_invoke(*invoke_data)Telnet命令测试dubbo接口importdubborequestsinvoke_data={"ip":'xxxx',"port":7777,"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# Telnet命令测试dubbo接口data=dubborequests.telnet_invoke(*invoke_data)
Package: test-test782764782642
redis-watcherredis-watcher is theRediswatcher forpycasbin. With this library, Casbin can synchronize the policy with the database in multiple enforcer instances.Installationpip install casbin-redis-watcherSimple Exampleimportosimportcasbinfromcasbin_redis_watcherimportnew_watcher,WatcherOptionsdefcallback_function(event):print("update for remove filtered policy callback, event:{}".format(event))defget_examples(path):examples_path=os.path.split(os.path.realpath(__file__))[0]+"/../examples/"returnos.path.abspath(examples_path+path)if__name__=="main":test_option=WatcherOptions()test_option.host="localhost"test_option.port="6379"test_option.channel="test"test_option.optional_update_callback=callback_functionw=new_watcher(test_option)e=casbin.Enforcer(get_examples("rbac_model.conf"),get_examples("rbac_policy.csv"))e.set_watcher(w)# then the callback function will be called when the policy is updated.e.save_policy()Getting HelppycasbinLicenseThis project is under Apache 2.0 License. See theLICENSEfile for the full license text.
Package: test-timer
Benchmark your code while unit testing themUsecasesProblem solving. To quickly check different implementations and compare versions to find which one performs better.Quick algorithm mockup. Again, to quickly check different approaches and implementations and compare versions to find which one performs better.What it does not provide insights aboutOverall performance score of your application.Algorithmic complexity.importtimeimporttest_timerdeffunction_a():...deffunction_b():time.sleep(1)classTestSrc(test_timer.BenchTestCase):deftest_function_a(self):function_a()deftest_function_b(self):function_b()if__name__=="__main__":test_timer.main()test_function_a(__main__.TestSrc):0:00:00.000052
.
test_function_b(__main__.TestSrc):0:00:01.001192
.
----------------------------------------------------------------------
Ran2testsin1.002s

OKHow to install:pipinstalltest_timer
Package: test-todo
Forex Pythonis a Free Foreign exchange rates and currency conversion.Features:List all currency rates.BitCoin price for all curuncies.Converting amount to BitCoins.Get historical rates for any day since 1999.Conversion rate for one currency(ex; USD to INR).Convert amount from one currency to other.(‘USD 10$’ to INR).Currency symbols.Currency names.Currency Source:Fixer.io is a free API for current and historical foreign exchange rates published by European Central Bank.
The rates are updated daily 3PM CET.BitCoin Price Source:Bitcoin prices calculated every minute. For more infomation visit [CoinDesk API](http://www.coindesk.com/api/).InstallationInstall using python packagepipinstalldjango-blog-it# orgitclonegit://github.com/micropyramid/django-blog-it.gitcddjango-blog-itpythonsetup.pyinstallpipinstallforex-pythonOrdirectlycloningtherepo:pythonsetup.pyinstallUsage Examples:Initialize classpython>>>fromforex_python.converterimportCurrencyRates>>>c=CurrencyRates()list all latest currency rates for “USD”python>>>c.get_rates('USD'){u'IDR':13625.0,u'BGN':1.7433,u'ILS':3.8794,u'GBP':0.68641,u'DKK':6.6289,u'CAD':1.3106,u'JPY':110.36,u'HUF':282.36,u'RON':4.0162,u'MYR':4.081,u'SEK':8.3419,u'SGD':1.3815,u'HKD':7.7673,u'AUD':1.3833,u'CHF':0.99144,u'KRW':1187.3,u'CNY':6.5475,u'TRY':2.9839,u'HRK':6.6731,u'NZD':1.4777,u'THB':35.73,u'EUR':0.89135,u'NOK':8.3212,u'RUB':66.774,u'INR':67.473,u'MXN':18.41,u'CZK':24.089,u'BRL':3.5473,u'PLN':3.94,u'PHP':46.775,u'ZAR':15.747}Get conversion rate from USD to INRpython>>>c.get_rate('USD','INR')67.473Convert amount from USD to INRpython>>>c.convert('USD','INR',10)674.73Get latest Bitcoin price.python>>>fromforex_python.bitcoinimportBtcConverter>>>b=BtcConverter()>>>b.get_latest_price('USD')533.913Convert Amount to Bitcoins based on latest exchange price.python>>>b.convert_to_btc(400,'USD')0.7492699301118473Get currency symbol using currency codepython>>>fromforex_python.converterimportCurrencyCodes>>>c=CurrencyCodes()>>>printc.get_symbol('GBP')£You can view the completeDocumentation HereWe welcome your feedback and support, raisegithub ticketif you want to report a bug. Need new features?Contact us here
Package: test-tools
Test files in project/tests
    __init__.py
    /pkg1
        /fixtures
            foo1.json
            foo2.json
        __init__.py
        test1.py
    /pkg2
        /fixtures
            bar1.json
            bar2.json
        __init__.py
        test2.pyContent of “tests/pkg1/fixtures/foo1.json”:{
    "blah1": [
        ["foo"],
        ["bar"],
        [1],
        [2],
        [true],
        [null]
    ],
    "blah2": [
        [-1234, 0],
        [3456, -2.345],
        [1, 1],
        [99999, false],
        [11, 789],
        [null, null]
    ]
}Content of “tests/pkg1/test1”:from unittest import TestCase

from test_tools import data_provider, FixtureManager

fx_man1 = FixtureManager()
fx_man1.load(fixture_file='foo1')

fx_man2 = FixtureManager()
fx_man2.load(fixture_file='foo2')


class MyTestCase(TestCase):
    @data_provider(fx_man1['blah1'])
    def test_my_cool_feature(self, param1):
        # some code
        pass

    @data_provider(fx_man1['blah2'])
    def test_my_cool_feature(self, param1, param2):
        # some code
        pass

    @data_provider(fx_man2['blah3'])
    def test_my_cool_feature(self, param):
        # some code
        pass
Package: test-topsis
topsis-pythonTopsis analysis of a csv fileUCS633 Project SubmissionName- RAJAT VERMARoll no.- 101703429Group- COE-21About TopsisThe Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multi-criteria decision analysis method, which was originally developed by Ching-Lai Hwang and Yoon in 1981 with further developments by Yoon in 1987, and Hwang, Lai and Liu in 1993. TOPSIS is based on the concept that the chosen alternative should have the shortest geometric distance from the positive ideal solution (PIS) and the longest geometric distance from the negative ideal solution (NIS).Installationpipinstalltopsis_rajatUsageFollowing query on terminal will provide you the topsis analysis for input csv file.tests-topsis -n "dataset-name" -w "w1,w2,w3,w4,..." -i "i1,i2,i3,i4,..."w1,w2,w3,w4 represent weights, and i1,i2,i3,i4 represent impacts where 1 is used for maximize and 0 for minimize.
Size of w and i is equal to number of features.Note that the first row and first column of dataset is droppedRank 1 signifies best decisionContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.LicenseMIT
Package: testtrackpro
TestTrack Pro is the Issue Management software from Seapine SoftwareTestTrack is a registered trademark of Seapine Software.http://www.seapine.com/testtrack.htmlThis library uses the suds library to talk to the TestTrack SDK SOAP API
and includes some helpful extensions for managing your client code and
interactions. There are a number of issues (and crashes) when talking to the
latest TestTrack SOAP API using suds, and this library addresses those.While this module is namedtesttrackproit will work with TestTrack RM
(Requirement Management) and TestTrack TCM (Test Case Management).The TestTrack SOAP API uses a client cookie for managing login sessions.
This cookie must be supplied on (almost) every API call. This library
provides a client wrapper object which will manage the session cookie, and
even releasing the cookie (logging off) as part of a context exit.The TestTrack SOAP API includes entity edit locking where a write lock is
implicit in every edit API call. The client must release the lock with either
a save or cancelSave API call. The lock will remain for 15 minuites, making
other attepts to edit fail on the entity.Python contexts allow for dealing with safely releasing locks on success or
error. All objects returned form API calls which start with the string ‘edit’
will return a context object that can be used with the ‘with’ statement.
At the end of the statement block the appropriate ‘save’ API call will be
made. If an exception occurs in the block, the appropriate ‘cancelSave’ API
call will be made. In either situation the lock will be released.importtesttrackprowithtesttrackpro.TTP('http://hostname/','Project','username','password')asttp:withttp.editDefect(11,bDownloadAttachments=False)asdefect:defect.priority="Immediate"## ttp.saveDefect(defect) is called, or ttp.cancelSave(defect.recordid) on exception.## ttp.DatabaseLogoff() is called, even if an exception occured.Additionally there is a new special edit context API extension when using
python contexts for ignoring the edit lock error, when someone else has the
edit lock on an entity. This is very useful when you do not want your script
or service to error out on a failed edit lock, but instead want to continue
processing.importtesttrackprowithtesttrackpro.TTP('http://hostname/','Project','username','password')asttp:withttp.editDefect(11,bDownloadAttachments=False,ignoreEditLockError=True)asdefect:defect.priority="Immediate"## ttp.saveDefect(defect) is called, or ttp.cancelSave(defect.recordid) on exception.assertnottesttrackpro.have_edit_lock(defect)iftesttrackpro.was_saved(defect):# The priority was changedpasseliftesttrackpro.has_errored(defect):# It was not saved due to an errorpassiftesttrackpro.edit_lock_failed(defect):# because the edit lock failedpasselse:# because of some other error# NOTE: unless there was other code to catch and ignore the#       error, this code is unreachable.pass## ttp.DatabaseLogoff() is called, even if an exception occured.ReferencesProject:DocumentationPyPiGitHubExternal:sudsSeapine SoftwareTestTrackTestTrack ProTestTrack SOAP APITestTrack Python Tutorial