Saravanan666/pypi-org huggingface dataset:
Package: opencce
This is `opencce`, a small application that replicates part of the functionalityprovided by the [CCE (Citizen Card Encrypted)](https://joinup.ec.europa.eu/software/cce/description) software by [A-SIT](https://www.a-sit.at/).## How `opencce`  differs…* `opencce` is written in Python and uses only widely available libraries including `openssl`.* `opencce` is Open Source. Please feel free to look at the code.* `opencce` **cannot** currently use your Citizen Card (_ecard_) to perform cryptographic operations.* `opencce` **can** be used as a library or through its command-line interface.However, as far as I can tell, `opencce` is able to decrypt containers produced by the original software. It also produces files that are fully compatible with the original. **If you encounter a case where this is not true, please file an issue!**### Dependencies* [python](http://python.org) (>= 2.7)* [python-m2crypto](https://github.com/martinpaljak/M2Crypto)* [lxml](http://lxml.de)* [python-magic](https://github.com/ahupp/python-magic) (optional)### About python3The main blocker for getting python3 compatibility is `m2crypto`.### InstallationGet the latest version with `pip install opencce`.### Future Plans* Smart Card support.* Compressed archive variant (SMIME is horrible for space efficiency).* Install scripts, package for distributions.### Usage#### Encryption using `opencce`$ opencce encrypt -c certificate.pem another_certificate.cer -- file1.txt file.pdfAdding certificate: certificate.pem ... [OK]Adding certificate: another_certificate.cer ... [OK]Adding file: file1.txt ... [OK]Adding file: file.pdf ... [OK]Encrypting to Container.cce ... [OK]#### Encryption using the Library>>> from opencce.containers.CCEContainer import CCEContainer>>> c = CCEContainer()>>> c.add("file1.txt")>>> c.add("file.pdf")>>> c.add_recipient_certificate("certificate.pem")>>> c.add_recipient_certificate("another_certificate.cer")>>> with open("Container.cce", "wb") as fh: fh.write(c.encrypt())#### Decryption using `opencce`$ opencce decrypt -k key.pem -d Container Container.cceDecrypting container: Container.cce ... [OK]Making sure that the extraction directory is clean: . ... [OK]Extracting file: Container/file1.txt ... [OK]Extracting file: Container/file.pdf ... [OK]#### Decryption using the Library>>> from opencce.containers.CCEContainer import CCEContainer>>> with open("Container.cce", "rb") as fh: c = CCEContainer.load(fh, "key.pem")>>> for path, filename, handle in c.export(): # do something with those files
Package: openccpy
Openccpy___   _____      __    ___     ___    ___   _____   __  __
 / __`\/\ '__`\  /'__`\/' _ `\  /'___\ /'___\/\ '__`\/\ \/\ \
/\ \L\ \ \ \L\ \/\  __//\ \/\ \/\ \__//\ \__/\ \ \L\ \ \ \_\ \
\ \____/\ \ ,__/\ \____\ \_\ \_\ \____\ \____\\ \ ,__/\/`____ \
 \/___/  \ \ \/  \/____/\/_/\/_/\/____/\/____/ \ \ \/  `/___/> \
          \ \_\                                 \ \_\     /\___/
           \/_/                                  \/_/     \/__/Open Chinese Convert is an opensource project for conversion between Traditional Chinese and Simplified Chinese for python.(python 中文繁简体转换工具)特性支持中文繁简体转换(v0.0.2)Quick Startinstallpip install openccpy使用案例# coding=utf-8fromopenccpy.openccimport*classTestOpencc(object):"""核心转换测试类"""deftest_to_simple(self):"""测试转换为简体"""assert"丝"==Opencc.to_simple("絲")assert"一目了然"==Opencc.to_simple("一目瞭然")deftest_to_traditional(self):"""测试转化为繁体"""assert"絲"==Opencc.to_traditional("丝")assert"一目瞭然"==Opencc.to_traditional("一目了然")方法简介转为简体defto_simple(traditional):"""繁体转化为简体1. 如果字符为空，直接返回2. 字符长度为1，返回对应简体字符3. 对应长度大于1，返回对应简体词组:param traditional: 繁体单词/单个词组:return: 对应的简体信息"""转为繁体defto_traditional(simple):"""简体转化为繁体1. 如果字符为空，直接返回2. 字符长度为1，返回对应繁体字符3. 对应长度大于1，返回对应繁体词组:param simple: 简体单词/单个词组:return: 对应的繁体信息"""相关框架中文繁简体转换-java 版本下期计划添加分词功能
Package: opencc-python
What is OpenCC-python?OpenCC-Python is a Python wrapper forOpen Chinese ConverterInstallationTo install opencc-python:pip install opencc-pythonHow to use it?You need to install opencc command tool first, if you are using Windows, the
command tool is already attached in the package, you can use it right away.
Following is a simple example# -*- coding: utf8 -*-
import opencc
cc = opencc.OpenCC('t2s')
print cc.convert(u'Open Chinese Convert（OpenCC）「開放中文轉換」，是一個致力於中文簡繁轉換的項目，提供高質量詞庫和函數庫(libopencc)。')And the output should beOpen Chinese Convert（OpenCC）「开放中文转换」，是一个致力于中文简繁转换的项目，提供高质量词库和函数库(libopencc)。There are four build-in configurations in opencc.BUILDIN_CONFIGS,t2s - Traditional Chinese to Simplified Chineses2t - Simplified Chinese to Traditional Chinesemix2t - Mixed to Traditional Chinesemix2s - Mixed to Simplified ChineseTo use a customized path to opencc command tool, you can pass opencc_path
parameter like thiscc = opencc.OpenCC('t2s',
                   opencc_path='/path/to/opencc')To use your own configuration, you should change the data_path, toocc = opencc.OpenCC(config='/path/to/my/config',
                   opencc_path='/path/to/opencc',
                   data_path='/path/to/data/folder')
Package: opencc-python-reimplemented
開放中文轉換（Pure Python）Open Chinese convert (OpenCC) in pure Python.Introduction 簡介opencc-python是用純 Python 所寫，使用由 BYVoid(byvoid.kcp@gmail.com) 所開發的OpenCC中的字典檔案。opencc-python 可以支援 Python2.7 及 Python3.x。opencc-pythonis made by pure Python with the dictionary files ofOpenCCwhich is developed by BYVoid(byvoid.kcp@gmail.com).opencc-python can run with Python2.7 and Python3.x.Installation 安裝將opencc這個目錄複製到你正在開發的專案中即可，或是執行（需要管理者權限）：pythonsetup.pyinstall套件也可從PyPI安裝，使用指令：pipinstallopencc-python-reimplementedCopy theopenccfolder to your project, or run (admin required)pythonsetup.pyinstallThe package can also be installed fromPyPIby issuing:pipinstallopencc-python-reimplementedUsage 使用方式CodefromopenccimportOpenCCcc=OpenCC('s2t')# convert from Simplified Chinese to Traditional Chinese# can also set conversion by calling set_conversion# cc.set_conversion('s2tw')to_convert='开放中文转换'converted=cc.convert(to_convert)Command Lineusage:python-mopencc[-h][-i<file>][-o<file>][-c<conversion>][--in-enc<encoding>][--out-enc<encoding>]optionalarguments:-h,--helpshowthishelpmessageandexit-i<file>,--input<file>Readoriginaltextfrom<file>.(default:None=STDIN)-o<file>,--output<file>Writeconvertedtextto<file>.(default:None=STDOUT)-c<conversion>,--config<conversion>Conversion(default:None)--in-enc<encoding>Encodingforinput(default:UTF-8)--out-enc<encoding>Encodingforoutput(default:UTF-8)examplewithUTF-8encodedfile:python-mopencc-cs2t-imy_simplified_input_file.txt-omy_traditional_output_file.txt



Seehttps://docs.python.org/3/library/codecs.html#standard-encodingsforlistofencodings.Conversions 轉換hk2s: Traditional Chinese (Hong Kong standard) to Simplified Chineses2hk: Simplified Chinese to Traditional Chinese (Hong Kong standard)s2t: Simplified Chinese to Traditional Chineses2tw: Simplified Chinese to Traditional Chinese (Taiwan standard)s2twp: Simplified Chinese to Traditional Chinese (Taiwan standard, with phrases)t2hk: Traditional Chinese to Traditional Chinese (Hong Kong standard)t2s: Traditional Chinese to Simplified Chineset2tw: Traditional Chinese to Traditional Chinese (Taiwan standard)tw2s: Traditional Chinese (Taiwan standard) to Simplified Chinesetw2sp: Traditional Chinese (Taiwan standard) to Simplified Chinese (with phrases)Issues 問題當轉換有兩個以上的字詞可能時，程式只會使用第一個。When there is more than one conversion available, only the first one is taken.
Package: opencc-test
# opencc-python 開放中文轉換 Python## OpenCC made with Python## Introduction 簡介
opencc-python is made by Python with the dictionary files of [OpenCC](https://github.com/BYVoid/OpenCC) which is developed by BYVoid(<byvoid.kcp@gmail.com>).opencc-python是用Python所寫, 使用由BYVoid(<byvoid.kcp@gmail.com>)所開發的[OpenCC](https://github.com/BYVoid/OpenCC)中的字典檔案.opencc-python can run with Python2.7 and Python3.xopencc-python可以支援Python2.7及Python3.x## Installation 安裝
Just copy the opencc folder to the project you are developing.把opencc這個目錄複製到你正在開發的專案中即可.Or run (require administration privilege)或是執行(需要管理者權限):python setup.py installThe package can also be instally from pypi by issuing:套件也可從pypi安裝, 使用指令:pip install opencc-python-reimplemented## Usage 使用方式from opencc import OpenCCopenCC = OpenCC(‘s2t’)  # convert from Simplified Chinese to Traditional Chinese
# can also set conversion by calling set_conversion
# openCC.set_conversion(‘s2tw’)
to_convert = ‘开放中文转换’
converted = openCC.convert(to_convert)Conversions include 轉換包含:‘hk2s’: Traditional Chinese (Hong Kong standard) to Simplified Chinese‘s2hk’: Simplified Chinese to Traditional Chinese (Hong Kong standard)‘s2t’: Simplified Chinese to Traditional Chinese‘s2tw’: Simplified Chinese to Traditional Chinese (Taiwan standard)‘s2twp’: Simplified Chinese to Traditional Chinese (Taiwan standard, with phrases)‘t2hk’: Traditional Chinese to Traditional Chinese (Hong Kong standard)‘t2s’: Traditional Chinese to Simplified Chinese‘t2tw’: Traditional Chinese to Traditional Chinese (Taiwan standard)‘tw2s’: Traditional Chinese (Taiwan standard) to Simplified Chinese‘tw2sp’: Traditional Chinese (Taiwan standard) to Simplified Chinese (with phrases)## Issues 問題
When there are more than one conversion avaiable, only the first one is taken.當轉換有兩個以上的字詞可能時, 程式只會使用第一個.
Package: opencdms
OpenCDMSThe OpenCDMS software is being developed in a number of separate code repositories.This repository will contain, in a single place, everything that is needed to install the software and also includes the documentation that is published at docs.opencdms.orgCHANGELOG0.1.2 (23-03-23) - Update setup to use markdown and single location for version0.1.1 (23-03-23) - First release on PyPI
Package: opencensus-context
TheOpenCensus Runtime Contextprovides in-process context propagation.
By default,thread local storageis used for Python 2.7, 3.4 and 3.5;contextvarsis used for Python >= 3.6, which providesasynciosupport.InstallationThis library is installed by default withopencensus, there is no need
to install it explicitly.UsageIn most cases context propagation happens automatically within a process,
following the control flow of threads and asynchronous coroutines. The runtime
context is a dictionary stored in acontext variablewhen available, and inthread local storageotherwise.There are cases where you may want to propagate the context explicitly:Explicit Thread CreationfromthreadingimportThreadfromopencensus.common.runtime_contextimportRuntimeContextdefwork(name):# here you will get the context from the parent threadprint(RuntimeContext)thread=Thread(# propagate context explicitlytarget=RuntimeContext.with_current_context(work),args=('foobar',),)thread.start()thread.join()Thread Poolfrommultiprocessing.dummyimportPoolasThreadPoolfromopencensus.common.runtime_contextimportRuntimeContextdefwork(name):# here you will get the context from the parent threadprint(RuntimeContext)pool=ThreadPool(2)# propagate context explicitlypool.map(RuntimeContext.with_current_context(work),['bear','cat','dog','horse','rabbit',])pool.close()pool.join()ReferencesExamplesOpenCensus Project
Package: opencensus-ext-django
Installationpip install opencensus-ext-djangoUsageFor tracing Django requests, you will need to add the following line to
theMIDDLEWAREsection in the Djangosettings.pyfile.MIDDLEWARE=[...'opencensus.ext.django.middleware.OpencensusMiddleware',]Additional configuration can be provided, please readCustomizationfor a complete reference.OPENCENSUS={'TRACE':{'SAMPLER':'opencensus.trace.samplers.ProbabilitySampler(rate=1)','EXPORTER':'''opencensus.ext.ocagent.trace_exporter.TraceExporter(
            service_name='foobar',
        )''',}}ReferencesOpenCensus Project
Package: opencensus-extension-azure-functions
Installationpip install opencensus-extension-azure-functionsPrerequisitesInstallazure-functions-core-toolsor Azure Functionsvscode-extension.How To Use In Python FunctionsUsefunc init--pythonorVSCode Extensions Blade->Azure->Functions->Create NewProject...to create a Python function app.Usefunc new-aanonymous-tHttpTrigger-nHttpTriggerto create an anonymous Http trigger in your function app. If you’re using VSCode, the project creation wizard will guide you through the same process.Includeopencensus-extension-azure-functionsandrequeststo your requirements.txt.In local.settings.json, add new settings"PYTHON_ENABLE_WORKER_DEPENDENCIES": "1"and"APPLICATIONINSIGHTS_CONNECTION_STRING":"InstrumentationKey=aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee". You can acquire your appinsights instrumentation key from your Azure Application Insights resource.Set up a virtual environment for your local developmentCreate a virtual environment withpy-3.7-mvenv .venvin Windows orpython3.7-mvenv .venvin Unix-like systems.Activate the virtual environment with.venv\Scripts\Activate.ps1in Windows PowerShell orsource .venv/bin/activatein Unix-like systems.Change the HTTP trigger file in<project_root>/HttpTrigger/__init__.pyto enable the OpenCensus tracing integration.importjsonimportloggingfromopencensus.extension.azure.functionsimportOpenCensusExtensionlogger=logging.getLogger('HttpTriggerLogger')OpenCensusExtension.configure()defmain(req,context):logger.info('Executing HttpTrigger with OpenCensus extension')# You must use context.tracer to create spanswithcontext.tracer.span("parent"):logger.info('Message from HttpTrigger')returnjson.dumps({'method':req.method,'ctx_func_name':context.function_name,'ctx_func_dir':context.function_directory,'ctx_invocation_id':context.invocation_id,'ctx_trace_context_Traceparent':context.trace_context.Traceparent,'ctx_trace_context_Tracestate':context.trace_context.Tracestate,})Run it in your local development environment byfunc host start--verbosein Core Tools orhitting F5in VSCode.You should now be able to check the trace information in yourApplication Insight->Investigate->Application Map.To use Opencensus Python Extensions in other scenarios,
please visitour example folderReferencesOpenCensus ProjectOpenCensus Python SDKPython Worker Extension InterfaceAuthor Your First Worker Extension
Package: opencensus-ext-fastapi
Installationpip install opencensus-ext-fastapiUsagefromfastapiimportFastAPIfromopencensus.ext.fastapi.fastapi_middlewareimportFastAPIMiddlewareapp=FastAPI(__name__)app.add_middleware(FastAPIMiddleware)@app.get('/')defhello():return'Hello World!'Additional configuration can be provided, please readCustomizationfor a complete reference.app.add_middleware(FastAPIMiddleware,excludelist_paths=["paths"],excludelist_hostnames=["hostnames"],sampler=sampler,exporter=exporter,propagator=propagator,)ReferencesOpenCensus Project
Package: opencensus-ext-flask
Installationpip install opencensus-ext-flaskUsagefromflaskimportFlaskfromopencensus.ext.flask.flask_middlewareimportFlaskMiddlewareapp=Flask(__name__)middleware=FlaskMiddleware(app,excludelist_paths=['_ah/health'])@app.route('/')defhello():return'Hello World!'if__name__=='__main__':importlogginglogger=logging.getLogger('werkzeug')logger.setLevel(logging.ERROR)app.run(host='localhost',port=8080,threaded=True)Additional configuration can be provided, please readCustomizationfor a complete reference.app.config['OPENCENSUS']={'TRACE':{'SAMPLER':'opencensus.trace.samplers.ProbabilitySampler(rate=1)','EXPORTER':'''opencensus.ext.ocagent.trace_exporter.TraceExporter(
            service_name='foobar',
        )''',}}ReferencesOpenCensus Project
Package: opencensus-ext-gevent
Installationpip install opencensus-ext-geventUsageAs gevent is to dateincompatiblewith
the new context variables theOpenCensus gevent helperconfigures OpenCensus to use
a compatible thread based runtime context implementation.No action apart from installing the package is needed as it listens to eventsemitted by geventonce
patching viapatch_allis complete.WarningOpenCensus itself is completely compatible with gevent. Be aware though that not all
available OpenCensus integrations are compatible.You should  check this on a case by case basis.ReferencesOpenCensus Projectgevent
Package: opencensus-ext-google-cloud-clientlibs
OpenCensus can trace HTTP and gRPC requests made with theCloud client libraries.
The request URL, method, and status will be collected.You can enable Google Cloud client libraries integration by specifying'google_cloud_clientlibs'totrace_integrations.Installationpip install opencensus-ext-google-cloud-clientlibsUsagefromopencensus.traceimportconfig_integrationconfig_integration.trace_integrations(['google_cloud_clientlibs'])ReferencesOpenCensus Project
Package: opencensus-ext-grpc
OpenCensus provides the implementation of interceptors for both the client side
and server side to instrument the gRPC requests and responses. The client
interceptors are used to create a decorated channel that intercepts client
gRPC calls and server interceptors act as decorators over handlers.gRPC interceptor is a new feature in the grpcio1.8.0 release, please upgrade
your grpcio to the latest version to use this feature.For sample usage, please refer to the hello world example in the examples
directory.More information about the gRPC interceptors please see theproposal.Installationpip install opencensus-ext-grpcUsagePlease refer to theexamples.
For more information, readgRPC Python Interceptors.ReferencesExamplesgRPCOpenCensus Project
Package: opencensus-ext-httplib
OpenCensus can trace HTTP requests made with the httplib library.You can enable requests integration by specifying'httplib'totrace_integrations.It’s possible to configure a list of URL you don’t want traced. See requests integration
for more information. The only difference is that you need to specify hostname and port
every time.Installationpip install opencensus-ext-httplibUsageimportrequestsfromopencensus.traceimportconfig_integrationfromopencensus.trace.tracerimportTracerconfig_integration.trace_integrations(['httplib'])tracer=Tracer()withtracer.span(name='parent'):response=requests.get('https://www.wikipedia.org/wiki/Rabbit')ReferencesOpenCensus Project
Package: opencensus-ext-jaeger
Installationpip install opencensus-ext-jaegerUsageTheOpenCensus Jaeger Exporterallows you to exportOpenCensustraces toJaeger.fromopencensus.ext.jaeger.trace_exporterimportJaegerExporterfromopencensus.traceimporttracerastracer_moduletracer=tracer_module.Tracer(exporter=JaegerExporter(service_name='my service',agent_host_name='localhost',agent_port=6831,))withtracer.span(name='hello'):print('Hello, World!')ReferencesJaegerOpenCensus Project
Package: opencensus-ext-logging
The logging integration enriches the log records with trace ID, span ID and sampling flag.
The following attributes will be added toLogRecord:traceIdspanIdtraceSampledNote that this only takes effect for loggers created after the integration.Installationpip install opencensus-ext-loggingUsageimportloggingfromopencensus.traceimportconfig_integrationfromopencensus.trace.samplersimportAlwaysOnSamplerfromopencensus.trace.tracerimportTracerconfig_integration.trace_integrations(['logging'])logging.basicConfig(format='%(asctime)straceId=%(traceId)sspanId=%(spanId)s%(message)s')tracer=Tracer(sampler=AlwaysOnSampler())logger=logging.getLogger(__name__)logger.warning('Before the span')withtracer.span(name='hello'):logger.warning('In the span')logger.warning('After the span')ReferencesOpenCensus Project
Package: opencensus-ext-newrelic
New Relic OpenCensus exporterTheopencensus-ext-newrelicpackage provides Python exporters to plug intoOpenCensus! Both spans and metrics may be exported using these exporters!RequirementsOpenCensus-Python version 0.7.x is required to use the exporters.Using the trace exporterThe example code assumes you’ve set the following environment variables:NEW_RELIC_INSERT_KEYimportosimporttimefromopencensus.trace.tracerimportTracerfromopencensus.traceimportsamplersfromopencensus_ext_newrelicimportNewRelicTraceExporternewrelic=NewRelicTraceExporter(insert_key=os.environ["NEW_RELIC_INSERT_KEY"],service_name="Example Service")tracer=Tracer(exporter=newrelic,sampler=samplers.AlwaysOnSampler())withtracer.span(name="main")asspan:time.sleep(0.5)# Send all data and stop the exporternewrelic.stop()Using the stats exporterMetrics are an excellent way to expose aggregated information about your
application. The stats exporter allows metrics to be exported from opencensus
to New Relic.The example code assumes you’ve set the following environment variables:NEW_RELIC_INSERT_KEYimportosimporttimefromopencensus.statsimportaggregationasaggregation_modulefromopencensus.statsimportmeasureasmeasure_modulefromopencensus.statsimportstatsasstats_modulefromopencensus.statsimportviewasview_modulefromopencensus_ext_newrelicimportNewRelicStatsExporter# The stats recorderstats=stats_module.statsview_manager=stats.view_managerstats_recorder=stats.stats_recordernewrelic=NewRelicStatsExporter(os.environ["NEW_RELIC_INSERT_KEY"],service_name="Example Service")view_manager.register_exporter(newrelic)# Create the measures and views# The latency in millisecondsm_latency_ms=measure_module.MeasureFloat("task_latency","The task latency in milliseconds","ms")latency_view=view_module.View("task_latency_latest","The latest task latency",[],m_latency_ms,aggregation_module.LastValueAggregation(),)view_manager.register_view(latency_view)mmap=stats_recorder.new_measurement_map()# Record a metricmmap.measure_float_put(m_latency_ms,50)mmap.record()# Send all data and stop the exporternewrelic.stop()Find and use dataTips on how to find and query your data in New Relic:Find metric dataFind trace/span dataFor general querying information, see:Query New Relic dataIntro to NRQL
Package: opencensus-ext-ocagent
Installationpip install opencensus-ext-ocagentUsageStatsfromopencensus.ext.ocagentimportstats_exporterasocagent_stats_exporterocagent_stats_exporter.new_stats_exporter(service_name='service_name',endpoint='localhost:55678')ReferencesOpenCensus ProjectOpenCensus Services
Package: opencensus-ext-prometheus
Installationpip install opencensus-ext-prometheusUsageThe OpenCensusPrometheusStats Exporter allows users
to export metrics to Prometheus monitoring solution.
The API of this project is still evolving.
The use of vendoring or a dependency management tool is recommended.Prometheus Exporter UsagePrometheus Importfromopencensus.ext.prometheusimportstats_exporterasprometheusfromopencensus.statsimportstatsasstats_modulePrometheus PrerequisitesOpenCensus Python libraries require Python 2.7 or later.Prometheus up and running.Register the Prometheus exporterstats=stats_module.statsview_manager=stats.view_managerexporter=prometheus.new_stats_exporter(prometheus.Options(namespace="<namespace>"))view_manager.register_exporter(exporter)...Prometheus Code ReferenceIn theexamplesfolder, you can find all the necessary steps to get the exporter, register a view, put tags on the measure, and see the values against the Prometheus monitoring tool.For further details for the Prometheus implementation, see the folderprometheus/stats_exporter.Path & FileShort Descriptioncontrib/opencensus-ext-prometheus/examples/End to end examplecontrib/opencensus-ext-prometheus/opencensus/ext/prometheus/stats_exporter/Stats implementation for PrometheusReferencesOpenCensus Project
Package: opencensus-ext-pyramid
Installationpip install opencensus-ext-pyramidUsageIn your application, add the pyramid tween and your requests will be
traced.defmain(global_config,**settings):config=Configurator(settings=settings)config.add_tween('opencensus.ext.pyramid''.pyramid_middleware.OpenCensusTweenFactory')Additional configuration can be provided, please readCustomizationfor a complete reference.fromopencensus.traceimportprint_exporterfromopencensus.traceimportsamplerssettings={'OPENCENSUS':{'TRACE':{'EXPORTER':print_exporter.PrintExporter(),'SAMPLER':samplers.ProbabilitySampler(rate=0.5),}}}config=Configurator(settings=settings)ReferencesOpenCensus Project