Saravanan666/pypi-org huggingface dataset:
Package: integrals
integralsintegrals is a Python library for using numerical methods to approximate definit integrals.InstallationUse the package managerpipto install integrals.pipinstallintegralsUsagefromintegralsimportRiemann,Trapezoid,Simpsonfromnumpyimportexpf=lambdax:exp(x**2)riemann=Riemann(x)print(riemann.compute_integral(-1,3,30,'midpoint'))# Computing the integral of f(x) using 'Riemann midpoint sum' from -1 to 3 with 30 sub-intervals.trapezoid=Trapezoid(f)print(trapezoid.compute_integral(-1,3,30))# Computing the integral of f(x) using 'trapezoid rule' from -1 to 3 with 30 sub-intervals.simpson=Simpson(f)print(simpson.compute_integral(-1,3,30))# Computing the integral of f(x) using 'Simpson's rule' from -1 to 3 with 30 sub-intervals.riemann.plot_function()# Plots the function and shows the Rieman's sum rectanglestrapezoid.plot_function()# Plots the function and shows the trapezoidssimpson.plot_function()# Plots the function and shows the sectorsContributingPull 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: integral-timesystem
# INTEGRAL TimeSystem<a rel=”license” href=”http://creativecommons.org/licenses/by/4.0/”><img alt=”Creative Commons License” style=”border-width:0” src=”https://i.creativecommons.org/l/by/4.0/80x15.png” /></a>INTEGRAL in time: time conversion and definition of time-range constructsconvert time between UTC tofind time ranges and observation sets for selection of conditionsExamples:` $ curlhttps://www.astro.unige.ch/cdci/astrooda/dispatch-data/gw/timesystem/api/v1.0/scwlist/nrt/2019-10-11T11:11:11/2020-11-11T11:11:11?ra=161.2647&dec=-59.68443&radius=8&min_good_isgri=1000&return_columns=SWID,RA_SCX,DEC_SCX`` $ curlhttps://www.astro.unige.ch/cdci/astrooda/dispatch-data/gw/timesystem/api/v1.0/scwlist/nrt/2019-10-11T11:11:11/2020-11-11T11:11:11?ra=161.2647&dec=-59.68443&radius=8&min_good_isgri=1000&return_columns=SWID,RA_SCX,DEC_SCX&return_index_version=yes`
Package: integra-sdk
The Integra Python SDK can be used to seemelessly communicate with an Integra reactor.The Integra REST documentation and additional SDKs can be obtained atIntegra REST.The Integra documentation can be found atIntegra Docs.Dependenciespython 2.6+lxmlrequestsintegra_major_minor_buildBuild your own integra_major_minor_buildDownload theIntegra XSD.Installpippip install lxmlpip install requestspip install generateDSgenerateDS.py -o integra_major_minor_build.py integra.xsdUsage1- Init RestTemplate:RestTemplate().init('https://localhost:8443/rest', 'admin', 'integra')2- Invoke RestTemplate REST methods:postget_allget_by_idputdeleteRestTemplate contains a static list of REST resource end points. Example putting it all together; creating a provider:class ProviderServiceTest(unittest.TestCase):

 description = 'test desc'
 hostname = 'localhost'
 name = 'test name'
 password = 'password'
 port = 9999
 timeout = 1000

 def setUp(self):
  RestTemplate().init('https://localhost:8443/rest', 'admin', 'integra')

 def test_create(self):
  prov = self._get_provider()

  prov = RestTemplate().post(RestTemplate.PROVIDERS, prov)
  self.assertIsNotNone(prov, 'Unable to create provider')
  self.assertIsNotNone(prov.get_id())

 def _get_provider(self):
  prov = provider()
  prov.set_description(self.description)
  prov.set_hostname(self.hostname)
  prov.set_name(self.name)
  prov.set_password(self.password)
  prov.set_port(self.port)
  prov.set_secured(True)
  prov.set_timeout(self.timeout)

  return prov

if __name__ == "__main__":
 unittest.main()LicenseThe Integra Python SDK is Open Source software released under theApache 2.0 license.
Package: integrate-ai
integrate.ai Command Line InterfaceA CLI that enables users to interact with integrate.ai's software.This tool allows users to manage client and sdk packages. Use the integate.ai sdk to seamlessly integrate federated learning and analytics workflows directly into your product.Installationintegrate-ai requiresPython >= 3.8pip install integrate-aiQuick StartCreate a new IAI token through the integrate.ai UI.Install integrate-ai-sdkiai sdk install --token <IAI_TOKEN>Pull integrate.ai docker clientiai client pull --token <IAI_TOKEN>Run integrate.ai training sessioniai client train --token <IAI_TOKEN> --session <SESSION_ID> --train_path <PATH_TO_TRAINING_DATA> --test_path <PATH_TO_TEST_DATA> --batch_size 5
Package: integratethis
This program integrates arbitrary commands to various tools.
For example, you can add a program named “filetags” to the “Send to”
folder of the context menu of the Windows File explorer viaintegratethis filetags.The integration method used differs from tool to tool. For the Windows Explorer,
a batch file is placed within the AppDataRoaming folder in case of additional
parameters have to be added to the command and a lnk file to it is created in
the “Send to” folder so that you can use the command from the context menu of
the Windows Exporer. If no additional parameters are required, a lnk file to the
command itself is placed in the “Send to” folder. For details, please look at
the source code or read the help info for the--intoparameter.You can overwrite pre-configured parameters using the command line options.Target group: users who are able to use command line toolsHosted and documented on github:https://github.com/novoid/integratethis
Package: integration-test-plugin
Integration Test PluginA plugin which enable testing of target executables on Python3 unittest framework.Intended userThe person who wants to test executable with automated method. And the executable outputs stream.IntroductionIntegration Test Pluginis a Python package which adds testing functionality for executable to Python unittest.
It supports automation because it is designed to be used with Python unittest together.
And it works on various platforms.User can define their own test case on python3 code using this package.The Integration Test Plugin verifies behavior of process under test through stream such as stdout, stderr, log file.
These verifies have timeout.
When tested process crashes, the crash is detected as timeout.FeaturesVerificationTests can check expected patterns are in stream output.Tests can check exit of process and exit code.Tests can check presence of file, directory.Crash detectionTests can detect and make the result NG if the process under test crashes.Automation supportAll test cases can be discovered and run by command-line operation.MotivationWith stream, we can test behavior of whole executable easily.launch_testingis known as one of testing tool using stream.
It has useful assertions such asassertWaitForverifies that expected string is in stream.
But, it is not available on out of ROS because it depends on ROS environment.Therefore, this project aims to create a generic integration test tool that does not depend on specific platform.PrerequisitesSupported PlatformLinuxWindowsMacOSRequired SoftwarePython 33.6.8 or aboveHow to UseInstallpipinstallintegration_test_pluginExampleThere are 2 examples.Runpython-munittestexample.test_air_conditioner_simulation
python-munittestexample.test_mailerCodetest_air_conditioner_simulationtest_mailerVerifierFollowing verifiers are available on this project.
Details are on implementation comment.VerifierPackageProcessVerifier.assertExit()integration_test_plugin.process_verifierStreamVerifier.assertPattern()integration_test_plugin.stream_verifierassertFileExist()assertFileNotExist()assertDirectoryExist()assertDirectoryNotExist()integration_test_plugin.path_verifierLicenseCopyright 2024Hidekazu TAKAHASHI.
This project is free and open-source software licensed
under theMIT License.
Package: integrator_mandubab
This package implements simple integration function with following signature:def integration(f, a, b, N, method = “endpoint”, implementation = “python”)
where
f –> function to integrate (python function)
a –> lower limit (float)
b –> upper limit (float)
N –> number of intermediate points (integer)
method –> “endpoint” or “midpoint” (string)
implementation –> “python” or “numpy” or “numba” or “cython” (string)
Package: integreat-cms
Integreat Django CMSIntegreat - The mobile guide for newcomers.Multilingual. Offline. Open Source.This content management system helps local integration experts to provide multilingual information for newcomers.TL;DRPrerequisitesFollowing packages are required before installing the project (install them with your package manager):python3.7python3-pipPostgreSQLdatabase serverApache2server withmod_wsgiInstallationpip install integreat-cmsDocumentationFor detailed instructions, tutorials and the source code reference have a look at our great documentation:https://digitalfabrik.github.io/integreat-cms/
Package: integresql-client-python
integresql-client-pythonPython client forIntegreSQL.Current stable version0.9.2Python versionintegresql-client-pythonis tested against Python 3.8+. Older Python versions may work, or may not.How to usefromintegresql_client_pythonimportIntegreSQLintegresql=IntegreSQL('template_directory')# integresql.debug = Truewithintegresqlastpl:withtpl.initialize()asdbinfo:# dbinfo is None if template is already initializedifdbinfo:# connect and import fixturesprint("initialize db with fixtures with db data:",dbinfo)db=tpl.get_database()withdbasdbinfo:# connect and do whatever you wantprint("Do your tests with db data:",dbinfo)# or manually, you can use as many databases as you need or IntegreSQL will allowdbinfo1=db.open()print("Do your tests",dbinfo1)dbinfo2=db.open()print("Do your tests",dbinfo2)dbinfo3=db.open()print("Do your tests",dbinfo3)# connect and do whatever you want# do not forget about closing resources:db.close(dbinfo1)db.close(dbinfo2)db.close(dbinfo3)AuthorsMarcin Sztolcman (marcin@urzenia.net)ContactIf you like or dislike this software, please do not hesitate to tell me about
it via email (marcin@urzenia.net).If you find a bug or have an idea to enhance this tool, please use GitHub'sissues.ChangeLogv0.9.2fixed a bug where test database was returned to pool after every test and got reused.
Renamed methodDatabase.close()toDatabase.mark_unmodified(). UsingDatabaseinwithblock doesn't return selected database to pool anymore.v0.9.1allow using multiple template pathsv0.9.0first public version
Package: integrity
IntegrityDevelopment facilities for the bolt environmentfromintegrityimportComponentfrom./settingsimportsettingsfrom./blocksimportblocksfrom./playerimportplayermain=Component()functionmain.on("main"):ifscoresettings.data.activatedobjmatches1:main.run("active")functionmain.on("active"):as@aat@s:player.run("main")functionblocks.on("placed_by_player"):ifblock~~~stoneexpand:sayPlacedstone!player.run("placed_stone")InstallationThe package can be installed withpip. Note, you must have
bothbeetandmechainstalled to use this package.$pipinstallintegrityGetting StartedTo use this package, we must add the plugin to therequiresection in thebeetproject file alongside withmechaandbolt.require:-bolt-integritypipeline:-mechaNow that we've enabledintegrity, we can import the module
directly inside a bolt scriptfromintegrityimportComponentfoo=Component("foo")FeaturesComponentsContributingContributions are welcome. Make sure to first open an issue
discussing the problem or the new feature before creating a
pull request. The project usespoetry.$poetryinstallYou can run the tests withpoetry run pytest.$poetryrunpytestThe project must type-check withpyright.
If you're using VSCode thepylanceextension should report diagnostics automatically. You can also install
the type-checker locally withnpm installand run it from the command-line.$npmrunwatch
$npmruncheckThe code follows theblackcode style.
Import statements are sorted withisort.$poetryrunisortbolt_expressionsexamplestests
$poetryrunblackbolt_expressionsexamplestests
$poetryrunblack--checkbolt_expressionsexamplestestsLicense -MIT
Package: integrity-check
Integrity CheckThis package is the python version of a cross-language api for runtime internal tests.How to useInstall the package (pip install integrity-check)At the top of one of your python source code files putfrom integrity_check import Integritythen you can do things like:Integrity.check(a == b, "expected {} to be same as {}", a, b)orIntegrity.check(a == b, a, b)or even justIntegrity.check(a == b)The main function ischeck, but the full list of functions is:check(condition, *msg)
    checkNotNone(test, *msg)
    checkIsBool(test, *msg)
    checkIsBoolOrNone(test, *msg)
    checkIsString(test, *msg)
    checkIsStringOrNone(test, *msg)
    checkStringNotNoneOrEmpty(test, *msg)
    checkIsValidNumber(test, *msg)
    checkIsValidNumberOrNone(test, *msg)
    checkIsFunction(test, *msg)
    checkIsFunctionOrNone(test, *msg)

    fail(*msg)In all cases the *msg parameters work like this:check*(test)- the exception will contain a default messagecheck*(test, var1)- the message will be just the string representaiton of var1check*(test, var1, var2, ... varN)- the message will be the string representaitons of the vars in the format "var1, var2, ..., varN"check*(test, "the vars are {} {}", var1, var2)- the message will substitute the string representations of va1, var2 into the {}check*(test, var1, var2, " and {} ", var3)- the message will be "var1, var2 and var3"there can be as many message parameters as you like.
Note that if a variable is a string and happens to contain {} then it will be used in subsequent substitutions.Examplefrom integrity_check import Integrity

def myComplicatedFunction(aNumber, callback, aName):
    Integrity.checkIsValidNumberOrNone(aNumber)
    Integrity.checkIsFunction(callback)
    Integrity.checkStringNotNoneOrEmpty(aName)

    handle = callback(aName)
    Integrity.checkNotNone(handle, "expected valid handle, aName was {}", aName)

    diameter = someOtherFunction(handle)
    Integrity.check(diameter >= 0, "expected non-negative diameter, was {}", diameter)What are the advantages of using Integrity?Consistent api across languagesIf you jump around from one language to another, it is nice to have a consistent way of testing your assumptions regardless of what language you are in. For example:Python:Integrity.check(a == b, "some text {}", a)JavaScript:Integrity.check(a == b, "some text {}", a)C#:Integrity.Check(a == b, "some text {}", a)There are minor consession made to language conventions. For example, in c# the function names are capitalised.Delayed and safe string buildingThe components of the message string are only used if the integrity check fails. This means that the execution time of the check is minimised. The building of the string is guarenteed not to error.Compact formatIf you did not use Integrity (or similar), and wrote the check out by hand, it would look something like:if(a != b):
	raise ValueError("some text " + str(a))note that there is potentional for the creation of the message within ValueError(~) to cause a problem, if, for example, the developer forgot to put str() around an int.
Package: integrityguard
IntegrityGuardMultiplatform agent for file integrity monitoring (FIM).The main motivation for this project is to offer all the minimum features required for a reliable FIM that is independent of any other big monitoring platform.IMPORTANT: This project is currently an ALPHA release. Not suitable for production environment, it is still a work in progress.Features highlightSimple and centralized configuration file (integrityguard.conf)Generate logs of any changes in real-time for future auditingPush notifications to an API endpointSend email alertsSupported hashing methods: “md5”, “sha1”, “sha224”, “sha256”, “sha384”, “sha512”How to use itTo install, runpip install integrityguardEdit/provide the configuration file (integrityguard.conf)To copy the original .conf file, runintegrityguard--taskcopy_config--destination<full_path>To provide the new .conf file path use--config<full_path>Generate the reference hashes, runintegrityguard--taskgenerate_hashesTo provide the target path via command, runintegrityguard--taskgenerate_hashes--target<full_path>Start the monitoring, runintegrityguard--taskmonitorTo provide the target path via command, runintegrityguard--taskmonitor--target<full_path>IMPORTANT: By providing configurations via command line anything defined via .conf file will be overwritten.For more information, runintegrityguard--helpCall for contributorsThis project is just at the begining of its development. We’re currently looking for engaged and energized people to colaborate and make it awesome.History0.4.3 (2022-01-05)Adjusted README file with proper conf and badges #220.4.2 (2022-01-05)Cleaned up variable checks #210.4.1 (2022-01-05)Fixed CLI issues with Click requirement and preload of config #200.4.0 (2022-01-02)Added copy config option to CLI #13Adjusted hash report JSON indentation #14Added CLI feature to define the conf file path #15Added –save-to CLI option #16Updated README and HISTORY files #170.3.2 (2022-01-01)Fixed issue of hash report not being created #120.3.1 (2022-01-01)Fixed copy config to user issue #110.3.0 (2022-01-01)Replaced setuptools data_files feature with copy_config() method #7Added new feature to CLI to show paths for the system #8Adjusted versioning to 0.3.0 #100.2.1 (2021-12-29)Fix version and release history0.2.0 (2021-12-29)Added support for conf file and multiplataform paths #3Adjusted project basic directory structure #4Added CLI support #50.1.1 (2021-12-28)Adjusted README file.0.1.0 (2021-12-28)Alpha release on PyPI.
Package: intelab-python-sdk
intelab-python-sdk安装$pipinstallintelab-python-sdkFFmpeg常用工具(V0.6.0)python运行ffmpeg命令执执行常用的视频处理命令，依赖系统安装的ffmpeg。Linux::sudo apt install ffmpeg功能：视频流分片录制–ffmpeg_record.py拼接多个视频文件–ffmpeg_concat.py获取流地址的当前一帧–ffmpeg_capture.pymp4转mp3–ffmpeg_mp4tomp3.py视频裁剪–ffmpeg_prune.pyCPU资源监控脚本(V0.5.0)协助自己在服务器端监控进程的使用资源情况。每一秒打印一次。Usag::$ intelab_python_sdk ffmpeg
PID    CPU    MEM    MCPU
2243   0.1    0.1    0.1    intelab_python_sdk ffmpeg钉钉群机器人信息发送(V0.4.0)钉钉机器人是钉钉群的一个高级扩展功能， 目前自定义机器人支持文本（text）、链接（link）官方文档参考Usage:>>> from intelab_python_sdk.dingtalk import DingTalkMessage
>>> dingtalk = DingTalkMessage(webhook, secret)
>>> dingtalk.send_text('这是文本信息', mobiles=['15131601294'], at_all=False)  # mobiles是at群中的人(手机号),at_all为True是at全体
>>> dingtalk.send_link('这是标题', '这是内容', 'https://www.baidu.com')
>>> dingtalk.send_markdown('这是标题', '# 这是内容 \n> 这是引用\n [百度](https://baidu.com)')邮箱模块(V0.3.5)对简单的邮件发送进行封装Usage:>>> from intelab_python_sdk.email import EMailMessage
>>> email = EMailMessage('w_angzhiwen@163.com', '发送者', 'xxxxx')  # 'xxxx' 用户密码
>>> msg = email.create(['zw.wang@ilabservice.com'], '你好，我是机器人', '无主题')  # 创建邮件内容
>>> msg = email.send(['zw.wang@ilabservice.com'], msg)  # 发送logging 模块(V0.3.4)日志格式:时间 | 主机名 | 进程号 | 名称 | 级别 | 文件和行号 | 信息Usage:>>> from intelab_python_sdk.logger import log_init
>>> # 初始化配置
>>> log = log_init('test', debug=True, log_path='./logs')
>>> log.info('info')
2019-12-16T17:46:41.930061-+08:00 | wen-work-pc | 25689 | test | INFO    | root:<ipython-input-5-6a92ee17c096>:1 | info
>>> log.debug('debug')
2019-12-16T17:47:31.113047-+08:00 | wen-work-pc | 25689 | test | DEBUG   | root:<ipython-input-6-03b5a4252de9>:1 | debug
>>> log.error('error')
2019-12-16T17:48:02.338739-+08:00 | wen-work-pc | 25689 | test | ERROR   | root:<ipython-input-7-5bfd94e0c8ba>:1 | error

>>> import logging  # 其他文件中
>>> log1 = logging.getLogger()
>>> log1.info('info')
2019-12-16T17:46:41.930061-+08:00 | wen-work-pc | 25689 | test | INFO    | root:<ipython-input-6-d225ecf23612>:1 | info说明：info日志输出到指定路径下的log.info.{日期}error日志输出到指定路径下的error.info.{日期}日志文件每天零点切分修复多进程下零点时切分出多个日志文件的Buglog_init参数说明TimedRotatingFileHandler的使用说明：If backupCount is > 0, when rollover is done, no more than backupCount
files are kept - the oldest ones are deleted.缓存(0.3.0)Usage:>>> from intelab_python_sdk.cache import FileSystemCache
>>> from datetime import datetime
>>> cache = FileSystemCache('.cache')
>>> cache.set('12', datetime.now())
>>> cache.get('12')
datetime.datetime(2019, 12, 19, 12, 16, 1, 511077)
>>> list(cache.keys())
['12']
>>> cache.delete('12')说明：以key为文件名，存储python数据类型更新历史0.6.0更新内容视频流分片录制拼接多个视频文件获取流地址的当前一帧mp4转mp3视频裁剪0.5.0更新内容新增CPU资源监控脚本0.4.0更新内容新增对钉钉群机器人消息推送的接口封装，目前支持文本信息和链接0.3.5更新内容新增utils.get_host_ip()新增email，对简单的发送邮件进行封装0.3.4更新内容日志log_init新增使用参数0.3.1更新内容日志打印在一行，使用|区分。
Package: intelab-python-tool
Common Liabraryilabservice 算法公共库健康检测from intelab_python_tool.tools.Web.flaskAPI import Monitor
Mt = Monitor(scheduler_list)
Mt.run()

scheduler_list: list
such as :  [
            [service_name, monitor_log_path, monitor_type, scheduler_period_type, 
            scheduler_period, dingtalk_function
            restart_flag, args],
            ]

service_name: 如果监控日志，则是重启服务时的服务名；如果是接口测试，则是url
monitor_log_path: 如果监控日志，则是监控的日志文件的绝对路径；如果是接口测试，则是访问接口的方式get or post
monitor_type: 'l'表示监控日志, 'a'表示监控接口
scheduler_period_type: 定时任务的类型，'h'表示按小时，'m'表示按分钟
scheduler_period:  定时任务的时长， 多少小时/多少分钟
dingtalk_function: 发送报警的函数
restart_flag: 是否需要重启服务
args: 接口测试时需要传入的参数
Package: intelecy-pandahouse
PandahouseNote: this is a fork. You probably want to usehttps://github.com/kszucs/pandahousePandas interface for ClickHouse HTTP APIInstallpipinstallpandahouseUsageWriting a dataframe to ClickHouseconnection={"host":"http://clickhouse-host:8123","database":"test"}affected_rows=to_clickhouse(df,table="name",connection=connection)Reading arbitrary ClickHouse query to pandasdf=read_clickhouse("SELECT * FROM{db}.table",index_col="id",connection=connection)
Package: intel-extension-for-deepspeed
Intel® Extension for DeepSpeed*Intel® Extension for DeepSpeed* is an extension that brings Intel GPU (XPU) support to DeepSpeed(https://github.com/Microsoft/DeepSpeed). It comes with the following components:DeepSpeed Accelerator Interface implementationDeepSpeed op builder implmentation for XPUDeepSpeed op builder kernel codeDeepSpeed would automatically use Intel® Extension for DeepSpeed* when it is installed as a python package.   After installation, models ported for DeepSpeed Accelerator Interface that run on DeepSpeed could run on Intel GPU device.InstallationInstall Intel® Extension for PyTorch* followingInstallation GuideInstall Intel® Extension for DeepSpeed*pipinstallintel-extension-for-deepspeedOr, you can build from source:source${DPCPPROOT}/env/vars.shpythonsetup.pyinstallGenerally, DPCPPROOT is /opt/intel/oneapi/compiler/latest for root account, ${HOME}/intel/oneapi/compiler/latest for other accounts.Install DeepSpeedpipinstalldeepspeedGet StartedRefer toexamplesSecurity PolicyPlease report security issues or vulnerabilities to theIntel Security Center.For more information on how Intel works to resolve security issues, seeVulnerability Handling Guidelines.
Package: intel-extension-for-openxla
Intel® Extension for OpenXLA*TheOpenXLAProject brings together a community of developers and leading AI/ML teams to accelerate ML and address infrastructure fragmentation across ML frameworks and hardware.Intel® Extension for OpenXLA* includes PJRT plugin implementation, which seamlessly runs JAX models on Intel GPU. The PJRT API simplified the integration, which allowed the Intel GPU plugin to be developed separately and quickly integrated into JAX.Installationpip install --upgrade intel-extension-for-openxlaSecuritySee Intel'sSecurity Centerfor information on how to report a potential security issue or vulnerability.See also:Security Policy
Package: intel-extension-for-tensorflow
Intel® Extension for TensorFlow*Intel® Extension for TensorFlow* is a heterogeneous, high performance deep learning extension plugin based on TensorFlowPluggableDeviceinterface to bring Intel XPU(GPU, CPU, etc) devices intoTensorFlowopen source community for AI workload acceleration. It allows flexibly plugging an XPU into TensorFlow on-demand, and exposing computing power inside Intel's hardware.Documentation:Intel® Extension for TensorFlow* online document website.InstallationInstall for XPUpip install tensorflow==2.14.0
pip install --upgrade intel-extension-for-tensorflow[xpu]Please refer toXPU installationfor details.Install for CPUpip install tensorflow==2.14.0
pip install --upgrade intel-extension-for-tensorflow[cpu]SecuritySee Intel'sSecurity Centerfor information on how to report a potential security issue or vulnerability.See also:Security Policy