Saravanan666/pypi-org huggingface dataset:
Package: okab
Okabaltair + okab = static beautyInstallOkabis available withpipbut it is currently in an alpha release as the API is under active development.
Wheels are also available from thereleases.pipinstallokabUsageAs an altair-saver methodTo get started usingokabyou can directly access it'saltair_savercompatible method.Note:Okabas a python library at present still has a runtime dependency onaltair_saverbut this may change in future releases.importaltairasaltfromokab.saverimportOkabSaver...chart.save("chart.png",method=OkabSaver,scale_factor=2)As a standalone CLIYou can provide eithervega-liteorvegaspecs, please specify the--modeto match your spec type, by defaultokabexpectsvega-lite.okab-ibar.vl.json-ochart.pngSeeokab -hfor a list of options.Resultssvgpngpng (scale factor 5)Compiling the WheelsCurrently the wheel generation is highly dependent onmake.
To get started you can bootstrap your environment.
This rule will generate a virtual environment,
install the python and node dependencies,
and the liberation sans font.makebootstrapIn order to build the wheels we will need to compile theokabjs backend into standalone executables for all supported targets.
You can do this ahead of time or as the wheels are built.
Regardless, you'll need to have installedvercel/pkg.npminstall-gpkgIf you'd just like to compile a single wheel for your platform you can specify the target to compile the backend.TARGET=macosx_10_14_x86_64makesingle-wheelTo generate all supported platform wheels:makewheelsHow does it work?We leveragevercel/pkgand distribute self-contained platform-specific executables within the python wheels.
This takes the problems of installing and setting up the needed backends from the user and leaves it to a well crafted CI.First we need access to the libraries that render our visualizationsvega&vega-lite.
We can use thevegaAPI to generate aviewand easily convert this tosvg.Generating appropriate png is a different problem. Thevegaview API can return ansvgorcanvasobject.
In the browser this usesHTML canvas, server-side they rely onnode-canvas.
This works fine in a properly configurednodeenvironment,
butcanvashas a number of system dependencies and caveats that make packaging it withvercel/pkga problem.Instead, we can take advantage of a differentsvgrendering libraryRazrFalcon/resvgandyisibl/resvg-js.AcknowledgementsThis app is made possible by these great open source projects.AltairVega ProjectResvgResvg-js
Package: okadminfinder
OKadminFinder: Easy way to find admin panel of websiteOKadminFinder is an Apache2 Licensed utility, rewritten inPython 3.x, for admins/pentesters who want to find admin panel of a website. There are many other tools but not as effective and secure. Yeah, Okadminfinder has the the ability to use tor and hide your identityRequirementsLinux❯sudoaptinstalltor
❯sudoservicetorstartWindowsdownloadtor windows expert bundlePreviewInstallationPyPi# Install❯pipinstallokadminfinder# Update❯pipinstall--upgradeokadminfinder# Remove❯pipuninstallokadminfinder# Usage❯okadminfinder-hGit Clone# Download and Usage❯gitclonehttps://github.com/mIcHyAmRaNe/okadminfinder3.git
❯cdokadminfinder3
❯chmod+xokadminfinder.py
❯./okadminfinder.py-hFeaturesMultiplatforms(Windows/Linux/MacOS)Easy to install, update and even removeMore than 1000 potential admin panelsConsole works with params, like:❯ okadminfinder -u https://example.com --proxy 127.0.0.1:8080Random-AgentsHTTP/HTTPS ProxiesSocks4/5 & TorYoutube videosokadminfinder : PyPi versionokadminfinder : admin page finderokadminfinder3 : admin page finder (update)admin panel finder Kali Linux 2018.3Most Blogs that shared okadminfinderkitploit.comsecurityonline.infoprodefence.orgkalilinuxtutorials.comonehack.usthe-realworld.orgcrackitdown.comsecuritynewspaper.com
Package: okaeri-sdk
Okaeri SDK for Python (3.7+)Currently supported services:OK! AI.CensorOK! No.ProxyFull documentation available onwiki.okaeri.euin:PolishEnglishInstallationpipinstallokaeri-sdk==1.*Example usageOK! AI.CensorSee full docs in:Polish,Englishfromokaeri_sdkimportAiCensorfromokaeri_sdk.clientimportOkaeriErrorfromokaeri_sdk.aicensorimportAiCensorErrortry:aicensor=AiCensor(f"XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX")prediction=aicensor.get_prediction("o cie k u r//w@!")swear=prediction.general.swearprint(f"swear:{swear}")except(OkaeriError,AiCensorError)ase:print(f"Error:{str(e)}")OK! No.ProxySee full docs in:Polish,Englishfromokaeri_sdkimportNoProxyfromokaeri_sdk.clientimportOkaeriErrorfromokaeri_sdk.noproxyimportNoProxyErrortry:noproxy=NoProxy(f"XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX")info=noproxy.get_info("1.1.1.1")proxy=info.risks.proxyverify=info.suggestions.verifyblock=info.suggestions.blockprint(f"proxy:{proxy}, verify:{verify}, block:{block}")except(OkaeriError,NoProxyError)ase:print(f"Error:{str(e)}")
Package: okami
OkamiOkami is a high-level web scraping framework built entirely for Python 3.6+ using asynchronous model provided by standard libraryasynciomodule withaiohttpas a networking layer andlxmlfor parsing data.Architecture is entirely modular and main components can be swapped out and replaced with custom implementations.Featurescomplete website-wide page processingfull scraping mode or delta mode scraping only unvisited pagesimmediate, on-demand or real-time page processing over HTTP APIsingle page processing via command linelots of pipelines, middlewares and signalsSpiders are very simple implementations. Take a look at an examplehere.Quick startInstall okamipip install okamiRun example web serverOKAMI_SETTINGS=okami.cfg.example okami example serverOpenlocalhost:8000and browse around a little. Quite a remarkable website. We will run our example spider against this website shortly and process few items.Run example spiderOKAMI_SETTINGS=okami.cfg.example okami example spiderOur example spider started and you can see it processing pages. Take a look at an example spider implementationhere.DocumentationRead the rest of documentationhere.LicenseOkami is licensed under a three clause BSD License. Full license text can be foundhere.
Package: ok-anime
Dependenciespython 3.*requestsbs4Installationpip install ok-animeexamplefrom ok_anime import Anime
ok = Anime('Anime Name')
print(ok.title)index:#json of all searchs in OKAnime for anime nameprint(ok.search)#get anime titleprint(ok.title)#get anime genreprint(ok.genre)#get anime urlprint(ok.url)#get anime coverprint(ok.cover)#get anime statusprint(ok.status)#get anime yearprint(ok.year)#get anime episodesprint(ok.episodes)#get anime age_classificationprint(ok.age_classification)print(ok.rate)#get anime rateprint(ok.description)#get animeprint(ok.trailer)#get animeprint(ok.studio)#get animeprint(ok.director)#get your favorite animeprint(ok.favorite_anime('your name in okanime'))this information is fetched from OkAnimeMake sure you don't spam the tests too quickly! One of the tests involves POSTing invalid credentials to OKAnime, so you're likely to be IP-banned if you do this too much in too short a span of time.
Package: okapi
OkapiPython Library to send API info to Storage ServerOkapi setupIn an existing project you should at least modify the following files:requirements/base.txtAdd the following requirement to the project’s settings. It won’t be needed to
addrequestsif the project is already using it.requestsversion should be >= 2.2.11:okapi==X.Y.Zsettings.pyAdd the following configuration to the project’s settings:########## OKAPI CONFIGURATIONOKAPI_PROJECT='your-project-name'OKAPI_URI=Noneifsettings.has_section('okapi'):OKAPI_URI='mongodb://{0},{1},{2}/{3}?replicaSet={4}'.format(settings.get('okapi','host0'),settings.get('okapi','host1'),settings.get('okapi','host2'),settings.get('okapi','name'),settings.get('okapi','replica'),)########## END OKAPI CONFIGURATIONNote that if the project is already usingMongoDB, you shouldn’t store Okapi’s
data into the same database. Okapi creates collections dynamically and could
conflict with your the  project’s.InitializationInitialize Okapi in themodels.pyfile of a basic application of the project.
This way Okapi will be imported at startup time:importrequestsfromdjango.confimportsettingsfromokapi.apiimportApiproject_name=getattr(settings,'OKAPI_PROJECT')mongodb_uri=getattr(settings,'MONGODB_URI')okapi_client=Api(project_name,requests,mongodb_uri)UsageOnce initialized you can use Okapi wherever you userequestslibrary.
Think of Okapi as if you were usingrequestsbecause they both have the same
API.Requests documentation:http://docs.python-requests.org/en/latest/Activating/deactivating okapi in your projectIn the filesettings/base.pyunder theOKAPI CONFIGURATIONsection, you
can add a boolean setting in order to enable/disable okapi for your project. It
could be interesting to have it enabled in QA or staging environment and after
it has been properly tested, activate it also in production.You can have a section intoyour-project-name/settings/dev.py:########## OKAPI CONFIGURATIONOKAPI_ENABLED=True########## END OKAPI CONFIGURATIONAnother one intoyour-project-name/settings/production.py:########## OKAPI CONFIGURATIONOKAPI_ENABLED=False########## END OKAPI CONFIGURATIONAnd so on. Note thatget_custom_settingis a wrapper aroundgetattr.
Then you could initialize it conditionally as shown below:http_lib=requestsif(get_custom_setting('OKAPI_ENABLED')andokapi_uriisnotNone):project_name=get_custom_setting('OKAPI_PROJECT',required=True)okapi_uri=get_custom_setting('OKAPI_URI',required=True)okapi_client=Api(project_name,requests,okapi_uri)http_lib=okapi_client
Package: ok-api
ok_apiok_api- python библиотека для работы с API Одноклассников (API Wrapper ok.ru)Установка$ pip install ok_apiПростой примерfromok_apiimportOkApiok=OkApi(access_token='token',application_key='key',application_secret_key='secret')print(ok.friends.get())ДокументацияПримеры
Package: okapi-em
okapi-emhttps://github.com/rosalindfranklininstitute/okapi-emA napari plugin for processing serial-FIB-SEM data.Powered bychaferandquoll.A full description of this software is presented in biorXiv preprint paper:https://doi.org/10.1101/2022.12.15.520541Thisnapariplugin contains the following tools:slice alignment using constrained SIFTtwo charge artifact suppression filtersdirectional fourier bandapass filterline-by-line filter function optimiser and subtraction (requires charge artifact labels) - useschaferfourier ring correlation (FRC) resolution estimation - usesquollThisnapariplugin was generated withCookiecutterusing@napari'scookiecutter-napari-plugintemplate.InstallationYou can installokapi-emviapip:>pip install okapi-emor using napari's plugin installation enginePlugins->Install/Uninstall Plugins...and filter forOkapi-EM.For installing in development mode , clone this package then navigate to the clonedokapi-emfolder and run:>pip install -e .Okapi-EM is a napari plugin. Launching napari is therefore required.>napariand then navigateMenu->Plugins->Okapi-EMNote that to launch napari in older versions of python (<=3.7) you will need to use the command:>python -m napariComputing requirementsOkapi-EM does not require powerful computers to run. None of the tools use GPU accelaration.The minimum recommended RAM depends on the size of the data being used in napari. For a full image stack of 1Gb, it is recommended that user ensure that 3Gb of RAM is available or can be used. Modern OS's can extend physical RAM usingswapmemory (Linux) or cache (in Windows and also known as virtual memory), but processing can be significantly slower.ContributingContributions are very welcome. Tests can be run withtox, please ensure
the coverage at least stays the same before you submit a pull request.LicenseDistributed under the terms of theApache Software License 2.0license,
"okapi-em" is free and open source softwareCitingPlease cite usage using the following reference.Perdigão, L. M. A. et al. Okapi-EM – a napari plugin for processing and analysing cryogenic serial FIB/SEM images. 2022.12.15.520541 Preprint athttps://doi.org/10.1101/2022.12.15.520541(2022).IssuesThere is currently a known issue with napari running in Linux machines, that it does not find the OpenGL driver correctly.
This will hopefully be resolved in the near future. If you bump into this issue we recommend trying to downgrade the python version. This is not an Okapi-EM problem.If you encounter any problems, please file an issue along with a detailed description.
Package: okapi-python-connector
OkapiPythonConnectorSome routines to connect OKAPI:Orbits software with python.Dependencies:python 3.8+requestspython-dotenvInstallation walk-throughClone connectorgit clonehttps://github.com/OKAPIOrbits/OkapiPythonConnector.gitpython-connector-gitcd python-connector-gitPython environment2.1 Linux/WSLsudo apt install python3-pytestsudo apt-get --assume-yes install python3.8 python3.8-dev python3-pippython3.8 -m pip install python-dotenv2.2 WindowsInstall Python3.8 e.g. from Windows Store. Next, install required packages:python3.8.exe -m pip install -r requirements.txtRunning an exampleSeetryout.pyfor example calls. To get started create a.envfile and add your username and password:OKAPI_TEST_URL=https://api.okapiorbits.com/
OKAPI_TEST_USERNAME=your_username
OKAPI_TEST_PASSWORD=your_passwordMake sure that the username and password itentifiers are identical to those used in the python script.Execute script:python3.8 -m pytestCreating an accountContact us atcontact@okapiorbits.comFor more information, go tohttps://www.okapiorbits.space/documentationCheckout the API athttps://okapiorbits.space/api-redoc/
Package: okareo
Okareo Python SDKPyPI:https://pypi.org/project/okareo/Python library for interacting with Okareo Cloud APIsDocumentationGetting Started, Guides, and API docsInstallationInstall the packagepipinstallokareoGet your API token fromhttps://app.okareo.com/(Note: You will need to register first.)Go directly to the"2. Create your API Token"on the landing page in above app.Set the environment variableOKAREO_API_KEYto your generated API token.Get Started Example NotebooksPlease see and run this notebook:https://github.com/okareo-ai/okareo-python-sdk/blob/main/examples/classification_eval.ipynbSee additional examples under:https://github.com/okareo-ai/okareo-python-sdk/tree/main/examplesUsing Okareo LangChain Callbacks HandlerWe provide a LangChain callback handler that lets you easily integrate your current workflows with the Okareo platform.If don't have LangChain dependencies installed in your environment, you can install the base ones (that will help you run the examples) with:pipinstallokareo[langchain]Integrating callbacks into your chain is as easy as importing the SDK in your module add adding the followingfrom okareo.callbacks import CallbackHandler
...
handler = CallbackHandler(mut_name="my-model", context_token="context-token")
llm = OpenAI(temperature=0.3, callbacks=[handler])During the LangChain LLM runs we will collect input and output information so you can analyze it further with the Okareo toolkit.You can also see an usage example in./examples/langchain_callback_example.pyAll rights reserved for Okareo Inc
Package: okchef
importchefclient=chef.ChefClient('https://api.opscode.com')# not to be confused with chef-client, the agent :)client.authenticate('chef-user','~/chef-user.pem')response=client.get('/users/chef-user')response.json()...{'display_name':'chef-user','email':'chef-user@example.com','first_name':'Chef','last_name':'User','middle_name':'','public_key':'-----BEGIN PUBLIC KEY-----\nMIIBIj...IDAQAB\n-----END PUBLIC KEY-----\n','username':'chef-user'}Authentication & Authorizationokchefuses the auth handler from therequests-cheflibrary athttps://github.com/samstav/requests-chefInstallBefore installingokchef, see the current installation instructions
forrequests-chef:https://github.com/samstav/requests-chef#installIf you don’t feel like reading those, you can use--process-dependency-links(for now)$ pip install -U --process-dependency-links okchefPreferably, you’ve read the install forrequests-chef, so this will
work:# -U ensures you get the latest version
$ pip install -U okchef
Package: okclient
Offenes Köln is a platform that allows for flexible accessto the content of the City of Cologne/Germany's city council information system.Find more information about the platform at http://offeneskoeln.de/.More detailed information on the REST API is available at http://offeneskoeln.de/api/.**Install**pip install okclient**Quick start**import okclientoc = okclient.Client()# Search for documents containing "Haushalt"result = oc.documents(query="haushalt")for doc in result:print doc.date, doc.title# Retrieve the document with identifier "3323/2008"# including attachments and thumbnailsresult = oc.documents("3323/2008", attachments=True,thumbnails=True)print result[0].date, result[0].titleprint result[0].attachments[0].urlprint result[0].attachments[0].content# Find streets surrounding a geo position# (reverse geocoding)streets = oc.streets(lat=50.959, lon=6.946)for street in streets:(name, distance) = streetprint "%s is %d meters away" % (name, distance)# Find position of street "Mittelstraße"# (also called geocoding)mittelstr = oc.locations("Mittelstraße")# return quasi-centroid of that streetprint mittelstr.averages[0]# print out all nodes of that streetsfor node in mittelstr.nodes:print node**Feedback**Feel free to give feedback via the Issue tracking at https://github.com/marians/ok-python-client.**Stay tuned**Stay informed about changes in this client and the API by following ourcommits on Github (see URL above), reading our Blog and/or followingthe twitter account.http://blog.offeneskoeln.de/https://twitter.com/OffenesKoeln
Package: okcompute
OKComputeA framework to make analysis stages clear, self documenting, and fault tolerant.SeeOKCompute Documentationfor details.Key FeaturesGraph of dependencies - Can figure out minimum analysis for set of outputs, or diagnose missing inputsMinimum BoilerplateHuman Readable Reports - Generates HTML documentation implicitly inferred from code and comprehensive reports of what occured during a runSupport for Pandas dataframes with column validationCan specify optional fields or a fallback value if a required field is missingFull stack traces are logged in the run results if an exception occurs during analysisSupports checking for intermediary results to avoid rerunning slow analysis stepsMakes writing unit tests extremely easyTODOMake generated documentation prettierBetter hashing of fields / metrics (avoid collisions based on string names)Add way of specifying a list fields with name determined by data (thread names) with sub keysMake helper functions to reduce boiler plate in saving / resuming from intermediary processingMake reports returned by prune functions more consistentStandardize config/input/output conventionsShould allow metric input/output be dicts?
Package: okdata-resource-auth
okdata-resource-authClient library for authorizing logged-in users against Keycloak resources and scopes.Setupgitclonegit@github.com:oslokommune/okdata-resource-auth.git
python3-mvenv.venvsource.venv/bin/activate
makeinit
maketestPublishmakecleantest# Testmakebump-patchbuild# Bump version and buildmakepublish# Publish module to PyPIgitpush--tags# Push version bump commit and generated tag
Package: okd-camgi
OKD Cluster Autoscaler Must Gather InvestigatorA tool for examiningOKD/OpenShift must-gatherrecords
to investigate cluster autoscaler behavior and configuration.Quickstartinstall fromPyPiwithpip3 install okd-camgi --userHave a must-gather ready to go in$MUST_GATHER_PATHRunokd-camgi --webbrowser $MUST_GATHER_PATHYour web browser should now show a page with a summary of the must-gather and some interactive navigation
buttons. If your browser does not open, you will see the URL printed on the terminal, copy it into a new
browser tab or window.Direct from tar fileokd-camgi can also process must-gather tar files directly, using the--tarflag. for example:$okd-camgipath/to/my/must-gather.tar.gzContainerized ServerAn alternative to running the command line tool is to start a local containerized webserver which
hosts the must-gather investigation page. Follow these steps to start a local server:podman run --rm -it -p 8080:8080 -v /path/to/must-gather:/must-gather:Z quay.io/elmiko/okd-camgiOpen you web browser tohttp://localhost:8080As in the Quickstart, your web browser should now show the must-gather investigation page.
Package: ok-deploy
“OK Deploy” helps you to deliver applications to their intended
target runtime, and manage them during their life-cycle while
remaining in the data center.It is designed to have similarities togit’s interface. “OK”
projects are normalgitrepositories, with some conventions
on the file system structure and branch names applied.Copyright ©  2015 1&1 GroupLicensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: okera-fs-aws
Okera access control for AWS S3 CLI v1DependenciesRequired:Python 2,7, 3.6+AWS CLI v1 for Python 2,7, 3.6+jwt,requests,pytz,urllib3,pathlibpip3installjwtrequestspytzurllib3pathlibInstallationpip3installokera_fs_awsTo verify:>>>importokera_fs_aws>>>okera_fs_aws.version()'2.7.0-b7'ConfigurationIf ~/.aws/config does not exist the user should create it by running aws configure.  The values assigned to access and secret key configurations will not effect the use of the okera_fs_aws plugin.  The ‘plugins’ definition below indicates the AWS CLI should load the ‘okera_fs_aws’ python module found on it’s sys.path.  The [profile okera] section parameterizes the Okera CLI plugin.  There are two additional, optional parameters of the okera profile.  The token_source value can be set to ‘authserver’.  The mode value can be set to ‘proxy’ when the Access Proxy service operates in proxy mode.Example of the okera_fs updates to ~/.aws/config[profile okera]
okera =
    proxy = https://<CDAS Access Proxy service host>:5010
    rest = https://<CDAS REST server host>:8083
    token = <User's JWT token>

[plugins]
okera = okera_fs_awsUsageawss3<command>--profileokera
Package: okerrclient
okerrclientokerrclient is old client forokerrnetwork/host monitoring system (okerr-dev git repo).Most (especially new) users should not need to use this okerrclient package and should useokerrupdateclient instead (it's much newer, redesigned and simpler to use) but okerrclient has features to useokerr APIwhich is missed in small okerrupdate utilities.Example usageassume your project has textid 'mytextid'simple indicator update create (minimalistic)okerrclient -n delme -s OKmore complex exampleokerrclient -i mytextid -n delme -s OK -S bzbzbz -u http://dev.okerr.com/okerr -m "numerical|minlim=0|maxlim=100" -vrun API queriesconfiguretextid=mytextidandapi-key = your_project_okerr_api_keyin/etc/okerrclient.conf.okerrclient --api-indicators
okerrclient --api-indicator --name MyIndicator
okerrclient --api-filter sslcert '!policy:Default'
okerrclient --name MyIndicator --api-set url=http://google.com/ retest=1Or use in script (set policy 'Daily' for all 'whois' indicator with policy 'Default'):foriin`okerrclient--api-filterwhoispolicy:Default`;doechofix$i;okerrclient-iokerr--name$i--api-setpolicy=Daily;doneOther okerr resourcesOkerr main websiteOkerr-server source code repositoryOkerr client (okerrupdate) repositotyandokerrupdate documentationOkerrbench network server benchmarkOkerr custom status pageOkerr JS-powered static status pageOkerr network sensorDemo ISPprototype client for ISP/hoster/webstudio providing paid okerr access to customers