Saravanan666/pypi-org huggingface dataset:
Package: webqresp
Hence name: WEB Quick RESPonse.Install:sudo apt-get install --yes gcc libevent-dev python-dev python-pip
sudo pip install webqrespUsage:webqresp http://example.com/
webqresp --repeat=3 --start=5 --response-seconds=0.5 --header='X-Name: Value' --content='{"name": "value"}' --method=POST http://example.com/some/page--repeat- Number of times to repeat the test, showing aggregated stats in the end. Default:1.--start- Number of concurrent requests to start with. Default:1.--response-seconds- Maximal response time in seconds for each request to pass the test. Default:1.--header- Additional headers, e.g.--header='Content-Type:application/json'--header='X-Name:Value'.--content- Content forPOST, etc. E.g.'name1=value1&name2=value2'or'{"name1":"value1", "name2":"value2"}'.--method- HTTP Method. Default:GET.url- URL to test, e.g.http://example.com/some/page.Criterion:Maximal number of concurrent requests to the slowest URL
while each request gets successful response within a second.Why:Popular criterion Requests Per Second (RPS, req/s) has a great flaw of being confusing when comparing measurement before and after optimization. Please seeexplanation.Another criterion - Milliseconds Per Request (ms/req) calculated as 1000/(req/s) as proposed in the article above also has flaws:It shows real response duration experienced by a user only when requests are sent sequentially, not concurrently:Let’s take 100,000 requests and send them to a server in a sequence, waiting for each response before sending the next request. If server processes all this in 10 seconds, it is giving 10,000 req/s, and each request gets response in 0.1 ms - great!Now let’s send 100,000 requests at the same time, not waiting for responses. If server processes all this in 10 seconds, it is giving the same 10,000 req/s, however while this criterion still shows false 0.1 ms, each request may get response in up to 10 seconds - that is not acceptable.It still keeps proportion ambiguity:Let’s take 10,000 req/s == 0.1 ms/req == 10,000 concurrent requests with 1 second for each response - this is acceptable.The same 10,000 req/s == 0.1 ms/req == 100,000 requests with 10 seconds for each response - this is not acceptable.Our criterion is constructed so that:It cares about real response duration for each user in the worst concurrent case.It is not a proportion. It is not ambiguous. Once 1 second is reached or failure occurs, it stops incrementing concurrent requests and returns the result.Single slowest URL is chosen to save time configuring the tool, because anyway “A chain is only as strong as its weakest link”.
Package: webracecondition
webraceconditionTiny package to test webraceconditionsWeb race conditions, also known as web application race conditions or simply race conditions, refer to a class of software vulnerabilities that can occur in web applications when multiple users or processes attempt to access and modify shared resources or data concurrently. These vulnerabilities arise due to the unpredictable interleaving of execution threads or processes, and they can lead to unintended and potentially harmful consequences.In a web race condition scenario, two or more actions that depend on each other's state may interfere with each other when executed concurrently. This interference can result in unexpected behavior, data corruption, or security breaches. Common examples of web race conditions include issues related to session management, data updates, file access, and database transactions.Developers need to be aware of the potential for race conditions in web applications and implement proper synchronization mechanisms, such as locks, semaphores, or transactions, to ensure safe and consistent access to shared resources. Failing to address race conditions can leave web applications vulnerable to data inconsistency, security vulnerabilities, and unreliable behavior. Therefore, thorough testing and code review are essential to identify and mitigate web race conditions in web applications to maintain their reliability and security.:warning: This is for educational purpose. Do not try on live servers without permission!InstallpipinstallwebraceconditionLast-Frame-Sync AttackThe Last-Frame-Sync Attack leverages the capabilities of HTTP/2 to induce web race conditions by synchronizing the final frames of multiple requests within a single TCP packet. This technique enables the simultaneous arrival of approximately 20-30 requests at the server, with the exact number depending on the Maximum Segment Size (MSS), all while eliminating the impact of network jitter.fromwebraceconditionimportEngine,Requestengine=Engine("https://your-target.com")foriinrange(20):engine.add_request(Request("GET","/race"))forroundtripinengine.last_frame_sync_attack():print(roundtrip)Dependent-Streams AttackThe Dependent-Streams Attack leverages HTTP/2's dependent streams feature to induce web race conditions by coordinating the concurrent execution of scheduled requests. It entails dispatching an extensive chain of requests, followed by numerous requests that depend on the final request in the chain.fromwebraceconditionimportEngine,Request,LongRunningChainengine=Engine("https://your-target.com")foriinrange(20):engine.add_request(Request("GET","/race")chain=LongRunningChain(Request("GET","/long"))foriinrange(10):chain.add_request(chain.root)forroundtripinengine.dependent_streams_attack(chain):print(roundtrip)LicenseMIT
Package: webracer
WebRacer started as a high level web application testing library, similar
to twill but with a more comprehensive API. With time the client portion
became sufficiently useful standalone.Agent moduleThe agent module provides a browser level HTTP client. Besides the standard
request/response functionality the agent module notably offers an easy
to use form API.Test case moduleWebRacer provides a test case class that offers more convenient integration
of the rest of WebRacer into unittest-based test suites.Both intuitive to use and exhaustiveThe goal of WebRacer is to expose HTTP and web-related functions in
a manner that makes code for common tasks intuitive and concise, but
does not compromise completeness. Phrased differently, WebRacer is meant
to be suitable for all use cases involving driving or testing web applications
rather than a certain predetermined subset of them.WebRacer does not require the use of a framework. In fact, assertions that
it provides are defined on the session class and may be used in web crawlers
that do not employ unittest at all.Documented and testedWebRacer aims to eventually have 100% documentation and test coverage.ScopeCurrently WebRacer tests HTTP applications via actual HTTP.Support for testing WSGI applications without running an HTTP server
is planned.The application being tested may be launched in another thread in
the test process or may be external to the test/driver process.FeaturesMultiple concurrent test sessionsResponse assertionsComprehensive form handlingNote: API is not yet stable.ExamplesThe largest application using WebRacer at this time isWolis.TestsExecute the test suite by runningnosetests.The test suite uses some nose features and will not work with unittest alone.LicenseReleased under the 2 clause BSD license.
Package: webraft
WebRaftcreating and reading JSON Web Tokens, extracting user agent
information, retrieving IP data, and creating and reading API keysHow to install webraftpipinstallwebraftDocumentationopen Github repository for the WebRaft Python library. The link is included in the package's documentation to provide
users with access to the source code and additional information about the library.https://github.com/MominIqbal-1234/webraftCheck Our Site :https://image.mefiz.com/Developed by : Momin Iqbal
Package: webrcon
WebRcon PackageInstallpip install webrconorpip install https://github.com/lewdneko/webrcon/archive/master.zipDocswebrcon.RconConnector(host, port, password, message_callback=None, console_callback=None)Initialises the classhost: str- the IP/hostname of the server accepting WebRconport: Union[str, int]- the port the server is accepting WebRcon onpassword: str- the password used to connect over WebRconmessage_callback: func- a sync or async function that is called whenever a chat message is sentconsole_callback: func- a sync or async function that is called whenever a console message is sentawaitRconConnector.start(loop, **kwargs)Opens a connection to the serverloop- an asyncio event loop, can be obtained through asyncio.get_event_loop()kwargs- passed to websockets.client.connect -read the docsawaitRconConnector.close()Closes the connection to the serverawaitRconConnector.command(command, callback)Sends a command over RCON to the servercommand: str- The command you want to be sent to the servercallback: func- A sync/async function that should take a single argument. The passed value will be a dict consisting of the output from the RCON server.The response to your command will be under theMessagekey.webrcon.InvalidServerYour host/port/password combination is incorrect or the server isn't running.webrcon.ConnectionClosedYou closed the connection and still tried to send a command. Good one.
Package: webrecon
Web ReconSource CodeThis package is designed to help users search the interwebz for pretty much anything (legal).  You can use this package, which wraps other cloud packages and SDKs for ease of use and integration.Goals of this projectCreate a single source code repository that can handle searchingAllow other projects to use the search with minimal integration and code changesServerless frameworks like AWS Lambda, Google Cloud Functions, and Azure Automations.  If the platform allows python with dependencies,webreconshouldbe able to run there.Container clusters like ECS, EKS, Kubernetes in general, etc.  All the Dockers, basically.UseSearching with Google CSETo use Google Custom Search Engine you will want to use thegcse.search()function.  You can include the library in your source code byimportingwebrecon.gcse.  See thedocstringfor up to date notes on params etc.
You can send in any of the parameters that the GCSE API from python offers up and a couple more too.
The updated list of params from the Alphabet-Googlez folks can be foundhereand the current supported list of params for the search fromwebrecon.gsce.search()q: This parameter is the actual search term.  It can be helpful to useGoogle search operators.filters<[String]>: Send a list of keys that might be found in the results from the search so that you can filter the results you deal with in your actual final result set.key: The developer key for Google.  You can find this in your GCSE console (manually log into the browser, amigoritos).cx: The GCSE ID.  Same story as thekeyparameter.kwargs: You can pass any number of arguments in as key value pairs, at the end of your parameters list.  These arguments will be dutifully passed along to the actual Google custom search method.Examplefrom webrecon import gcse
...
res = gcse.search('intext:HUGO BOSS Genesis 2 Virgin Wool Dress Pants',
				  'title',
				  'link',
				  num=3,
				  exactTerm='Genesis 2')

print(res)
[
	{
		'title': 'Hugo Boss Pants',
		'link': 'https://www.macys.com/shop/b/hugo-boss-pants?id=78110'
	},
	{
		'title': 'HUGO BOSS 100% Wool Pants for Men for sale | eBay',
		'link': 'https://www.ebay.com/b/HUGO-BOSS-100-Wool-Pants-for-Men/57989/bn_4243898'
	},
	{
		'title': "HUGO BOSS | Trousers for Men | Elegant and Casual Men's Trousers",
		'link': 'https://www.hugoboss.com/us/men-pants/'
	}
]
Package: webreg
UCI WebReg Python APIEverything you need to create a UCI WebReg Bot within 5 minutes!IntroductionDesigned for UC Irvine WebReg,
WebReg API is a Python API you need to create your own enrollment bot script within less than 10 lines of code!Unlike other bots, it is deeply integrated with WebReg and takes advantage of Selenium technology
which makes it robust, fast, and secure.HighlightsSecure.The top priority is that you'll never get banned because of using this.
The bot simulates that a real person and a real browser would do so any kind of behavioral detection will not be able to distinguish you from other people.Robust.The API keeps track of the WebReg login status. So it won't crash due to exceptions like maintenance or unopened enrollment window.Versatile.The API helps you not only enroll in classes, but also check study lists, waitlists, and so on.PrerequisiteChrome browser and Python 3.6+Working FunctionsAdd/Change/Drop coursesAdd/Drop wait list coursesSee open sections of a courseFetch study list and wait listAuto-logoutDeploymentInstall Seleniumpip3installseleniumDownload WebDriver and make it executablehttps://sites.google.com/a/chromium.org/chromedriver/downloadschmod+x./webdriverMake it yoursgitclonehttps://github.com/maao666/UCI_WebReg_API.gitExampleformWebRegimportWebRegfrompprintimportpprint# Not required# Replace username and password with yourswr=WebReg().login('username','password')# Add a coursewr.add_course('16570')# Change to Pass/No Passwr.change_course('16570',letter_grade=False)# Drop a coursewr.drop_course('16570')# See available sectionspprint(wr.list_open_sections('16570'))# Get study listpprint(wr.get_study_list())#It automatically logs out so no logout operation requiredWe humbly ask you for a star if this helps you.To UCI Registrar: The technology you use for WebReg is so lame! I can't believe you use a Shell script for load-balancing and redirecting. Such a shame on you and OIT for creating such a terrible user experience! I'm confident that you are not smart enough to catch my bot till I graduate. We'll see.
Package: webrepl
webreplPython module to handle micropython websocket (WS) repl protocol (client side only). It is modified original implementation to automatize working with web repl.ExamplesSimple example to get output of command:import webrepl
repl=webrepl.Webrepl(**{'host':'192.168.4.1','port':8266,'password':'ulx3s'})
resp=repl.sendcmd("import os; os.listdir()")
print(resp.decode("ascii"))Example to get version of webrepl on device:import webrepl
repl=webrepl.Webrepl(**{'host':'192.168.4.1','port':8266,'password':'ulx3s','debug':True})
ver=repl.get_ver()
print(ver)RequirementsIt should work with both python2 and python3 with simple pip commands:pip install webreplwebreplcmd examplesFew webreplcmd examples:webreplcmd --host 192.168.4.1 --password ulx3s ls
webreplcmd --host 192.168.4.1 --password ulx3s get src-remote-file.txt dest-local-file.txt
webreplcmd --host 192.168.4.1 --password ulx3s -v get src-remote-file.txt dest-local-file.txt
webreplcmd --host 192.168.4.1 --password ulx3s put src-local-file.txt dest-remote-file.txt
webreplcmd --host 192.168.4.1 --password ulx3s -v put src-local-file.txt dest-remote-file.txt
webreplcmd --host 192.168.4.1 --password ulx3s cat main.py
webreplcmd --host 192.168.4.1 --password ulx3s cmd 'import os; os.listdir()'
webreplcmd --host 192.168.4.1 --password ulx3s rm uftpd.pyNote that you can also specify basic parameters using environment variables:export WEBREPL_HOST=127.0.0.1
export WEBREPL_PASSWORD=ulx3s
export WEBREPL_PORT=8266and then you can just specify command:webreplcmd lsAll options are listed using --help:webreplcmd --helpRequirementsIt should work with both python2 and python3 with simple pip commands:sudo apt-get update
sudo apt-get install -y python3 python3-pip
sudo pip3 install webreplManualusage: webreplcmd [-h] [--host HOST] [--port PORT] [--verbose] [--debug]
                    [--password PASSWORD] [--before BEFORE] [--cmd CMD]
                    [--after AFTER]
                    CMD [CMD ...]

webrepl - connect to websocket webrepl

positional arguments:
  CMD                   commands for repl

optional arguments:
  -h, --help            show this help message and exit
  --host HOST, -i HOST  Host to connect to
  --port PORT, -P PORT  Port to connect to
  --verbose, -v         Verbose information
  --debug, -d           Enable debugging messages
  --password PASSWORD, -p PASSWORD
                        Password used to connect to
  --before BEFORE, -B BEFORE
                        command to execute before
  --cmd CMD, -c CMD     command to execute
  --after AFTER, -A AFTER
                        command to execute after

webreplcmd --host 192.168.4.1 --password ulx3s ls
webreplcmd --host 192.168.4.1 --password ulx3s get src-remote-file.txt dest-local-file.txt
webreplcmd --host 192.168.4.1 --password ulx3s put src-local-file.txt dest-remote-file.txt
webreplcmd --host 192.168.4.1 --password ulx3s cat main.py
webreplcmd --host 192.168.4.1 --password ulx3s cmd 'import os; os.listdir()'
Package: webrequests
A simple wrapper of requests, simple but useful!InstallationpipinstallwebrequestsFeaturesRandom User-AgentTry again when request failedDownload file from an url, with progress barGet a BeautifulSoup from an urlUsagefromwebrequestsimportWebRequest# request an urlurl='http://output.nsfc.gov.cn/captcha/defaultCaptcha'resp=WebRequest.get_response(url)resp=WebRequest.get_response(url,method='POST',max_try=5,timeout=5)print(resp.headers)# download file from an urlurl='https://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz'WebRequest.download(url)WebRequest.download(url,'out.jpg',max_try=5,timeout=10)# request with sessionsession=requests.session()resp=WebRequest.get_response('http://www.cip.cc/',session=session)print(resp.cookies)print(session.cookies)# get a soupsoup=WebRequest.get_soup('http://www.cip.cc/')print(soup.select_one('.kq-well pre').text.strip())
Package: web-rich-object
This module aims to describe a URL as a Web Rich Object.It firstly uses OpenGraph protocol and try to guess without.>>> from web_rich_object import WebRichObject
>>> wro = WebRichObject('https://www.youtube.com/watch?v=4nzaATIOAAE')
>>> wro.title
'Sir Samuel - Urban Classik [CLIP OFFICIEL]'
>>> wro.site_name
'YouTube'
>>> wro.image
'https://i.ytimg.com/vi/4nzaATIOAAE/maxresdefault.jpg'
>>> wro.url
'https://www.youtube.com/watch?v=4nzaATIOAAE'
Package: webrtc-audio-processing
WebRTC Audio Processing for PythonPython binding of WebRTC Audio Processing.Requirementsswigcompile toolchainpythonBuildThere are two way to build the package.using setup.pygitclonehttps://github.com/xiongyihui/python-webrtc-audio-processing.gitcdpython-webrtc-audio-processing
gitsubmoduleinit&&gitsubmoduleupdate
pythonsetup.pybuild
sudopythonsetup.pyinstallusing Makefilegitclonehttps://github.com/xiongyihui/python-webrtc-audio-processing.gitcdpython-webrtc-audio-processing
gitsubmoduleinit&&gitsubmoduleupdatecdwebrtc-audio-processing
./autogen.sh
./configure--with-pic
makecd../src
makeUsagefromwebrtc_audio_processingimportAudioProcessingModuleasAPap=AP(enable_vad=True,enable_ns=True)ap.set_stream_format(16000,1)# set sample rate and channelsap.set_ns_level(1)# NS level from 0 to 3ap.set_vad_level(1)# VAD level from 0 to 3audio_10ms='\0'*160*2# 10ms, 16000 sample rate, 16 bits, 1 channel# only support processing 10ms audio data each timeaudio_out=ap.process_stream(audio_10ms)print('voice:{}'.format(ap.has_voice()))
Package: webrtc-streaming
WebRTC StreamingReady to use WebRTC StreamingFree software: BSD licenseDocumentation:https://webrtc-streaming.readthedocs.io.FeaturesReceive OpenCV images and send it using WebRTCInstall PyPI$pipinstallwebrtc_streamingUsage exampleCheck examples folderCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.HistoryTODO
Package: webrtcvad
py-webrtcvadThis is a python interface to the WebRTC Voice Activity Detector
(VAD).  It is compatible with Python 2 and Python 3.AVADclassifies a piece of audio data as being voiced or unvoiced. It can
be useful for telephony and speech recognition.The VAD that Google developed for theWebRTCproject is reportedly one of the best available, being fast, modern
and free.How to use itInstall the webrtcvad module:pip install webrtcvadCreate aVadobject:import webrtcvad
vad = webrtcvad.Vad()Optionally, set its aggressiveness mode, which is an integer
between 0 and 3. 0 is the least aggressive about filtering out
non-speech, 3 is the most aggressive. (You can also set the mode
when you create the VAD, e.g.vad = webrtcvad.Vad(3)):vad.set_mode(1)Give it a short segment (“frame”) of audio. The WebRTC VAD only
accepts 16-bit mono PCM audio, sampled at 8000, 16000, or 32000 Hz.
A frame must be either 10, 20, or 30 ms in duration:# Run the VAD on 10 ms of silence. The result should be False.
sample_rate = 16000
frame_duration = 10  # ms
frame = b'\x00\x00' * (sample_rate * frame_duration / 1000)
print 'Contains speech: %s' % (vad.is_speech(frame, sample_rate)Seeexample.pyfor
a more detailed example that will process a .wav file, find the voiced
segments, and write each one as a separate .wav.How to run unit testsTo run unit tests:pip install -e ".[dev]"
python setup.py test
Package: webrtcvad123
py-webrtcvadThis is a python interface to the WebRTC Voice Activity Detector
(VAD).  It is compatible with Python 2 and Python 3.AVADclassifies a piece of audio data as being voiced or unvoiced. It can
be useful for telephony and speech recognition.The VAD that Google developed for theWebRTCproject is reportedly one of the best available, being fast, modern
and free.How to use itInstall the webrtcvad module:pip install webrtcvadCreate aVadobject:import webrtcvad
vad = webrtcvad.Vad()Optionally, set its aggressiveness mode, which is an integer
between 0 and 3. 0 is the least aggressive about filtering out
non-speech, 3 is the most aggressive. (You can also set the mode
when you create the VAD, e.g.vad = webrtcvad.Vad(3)):vad.set_mode(1)Give it a short segment (“frame”) of audio. The WebRTC VAD only
accepts 16-bit mono PCM audio, sampled at 8000, 16000, 32000 or 48000 Hz.
A frame must be either 10, 20, or 30 ms in duration:# Run the VAD on 10 ms of silence. The result should be False.
sample_rate = 16000
frame_duration = 10  # ms
frame = b'\x00\x00' * int(sample_rate * frame_duration / 1000)
print 'Contains speech: %s' % (vad.is_speech(frame, sample_rate)Seeexample.pyfor
a more detailed example that will process a .wav file, find the voiced
segments, and write each one as a separate .wav.How to run unit testsTo run unit tests:pip install -e ".[dev]"
python setup.py testHistory2.0.10Fixed memory leak. Thank you,bond005!2.0.9Improved example code. Added WebRTC license.2.0.8Fixed Windows compilation errors. Thank you,xiongyihui!
Package: webrtcvad-wheels
py-webrtcvad-wheelsThis is a python interface to the WebRTC Voice Activity Detector (VAD).
It is compatible with Python 2 and Python 3.  It is forked fromwiseman/py-webrtcvadto
provide releases with binary wheels.AVADclassifies a piece of audio data as being voiced or unvoiced. It can
be useful for telephony and speech recognition.The VAD that Google developed for theWebRTCproject is reportedly one of the best available, being fast, modern
and free.How to use itInstall the webrtcvad module:pip install webrtcvadCreate aVadobject:import webrtcvad
vad = webrtcvad.Vad()Optionally, set its aggressiveness mode, which is an integer
between 0 and 3. 0 is the least aggressive about filtering out
non-speech, 3 is the most aggressive. (You can also set the mode
when you create the VAD, e.g.vad = webrtcvad.Vad(3)):vad.set_mode(1)Give it a short segment (“frame”) of audio. The WebRTC VAD only
accepts 16-bit mono PCM audio, sampled at 8000, 16000, 32000 or 48000 Hz.
A frame must be either 10, 20, or 30 ms in duration:# Run the VAD on 10 ms of silence. The result should be False.
sample_rate = 16000
frame_duration = 10  # ms
frame = b'\x00\x00' * int(sample_rate * frame_duration / 1000)
print 'Contains speech: %s' % (vad.is_speech(frame, sample_rate)Seeexample.pyfor
a more detailed example that will process a .wav file, find the voiced
segments, and write each one as a separate .wav.How to run unit testsTo run unit tests:pip install -e ".[dev]"
python setup.py testHistory2.0.10Fixed memory leak. Thank you,bond005!2.0.9Improved example code. Added WebRTC license.2.0.8Fixed Windows compilation errors. Thank you,xiongyihui!