Saravanan666/pypi-org huggingface dataset:
Package: blazectl
blaze-ctlController to manage blaze cluster in cloud (aws) environmentConceptsNamespaceBlaze clusters are created in a namespace, where a namespace defines and manges associated resources, such as -EKS ClusterProvisionerBlock DeviceFSX VolumesService AccountBefore we can create a cluster, we need to have a namespace and permission to manage cluster in that namespace.Each namespace has two group of users -blaze-user: they can create / delete cluster and see pod and svc statusblaze-admin: they can additionally manage FSX Volumes, service accounts, gpu supportCommandsLinkInstallpip install blazectlBuildpoetry buildPublishpoetry publish
Package: blazee
Python Library for BlazeeIntroBlazee is the easiest and fastest way to turn your Machine Learning
models and pipelines into a production ready prediction API.It allows you to deploy trained models straight from a Jupyter Notebook
or any other model training environment, and access them live from anywhere
using the Blazee HTTP API.This library can also be usedSupported FrameworksAt the moment, we support the following frameworks:Scikit Learn (Supervised learning models and pipeline)KerasPyTorchXGBoostLightGBMComing soon:H2OXGBoostLightGBMTensorflowInstallationInstall from pippipinstallblazeeSign up and get an API Key fromhttps://blazee.ioUsage# Train your model like you usually do>>>fromsklearn.linear_modelimportLogisticRegressionCV>>>clf=LogisticRegressionCV()>>>...>>>clf.train(X)# Deploy your model on Blazee# Get your API Key on https://blazee.io>>>fromblazeeimportBlazee>>>bz=Blazee(YOUR_API_KEY)>>>model=bz.deploy_model(clf)UploadingmodeltoBlazee...Successfullydeployedmodelbdea76f4-fa0f-4ef1-8bc5-f36978a4488eDeployingmodel...Thiswilltakeafewmoments# Predict a single sample>>>pred=model.predict(X[0])>>>pred.prediction1>>>pred.probas{0:0.08,1:0.91,2:0.01}# Or predict a batch>>>preds=model.batch_predict(X)# Deploy another version of the model>>>clf2=SGDClassifier()>>>...>>>clf2.train(X)>>>model.update(clf2)SupportContact us atsupport@blazee.ioor open a Github Issue for any question or bug report.
Package: blazekit
BlazeKitThe Blazekit project is a user-friendly graphical interface that allows users to interact with a Kubernetes cluster without the need for advanced command-line knowledge. With this GUI, users can easily manage their Kubernetes resources, deploy applications, monitor cluster health, and perform various other operations, all through an intuitive and visually appealing interface.Usagev1.0.2Clear ScreenInstall KubectlInstall AWS CLICluster HealthShow PodsView Pods DetailsDescribe a PodShow NodesView Nodes DetailsDescribe a NodeShow DeploymentsDescribe a DeploymentShow ServicesDescribe a ServiceTerminalDelete Evicted PodsGetting StartedTo get started with BlazeKit, follow these steps:Install the library: Run the following command to install the librarypython3-mpipinstallblazekitRun blazekit: Run BlazeKit with the following commandpython3-mblazekitContributingContributions are welcome! If you'd like to contribute to BlazeKit, please fork the repository and create a pull request.
Package: blazeverify
Blaze Verify Python LibraryBlaze Verify is now Emailable! Please switch to using the Emailable client library:https://emailable.com/docs/api?pythonThis is the official python wrapper for the Blaze Verify API.DocumentationSee thePython API docs.InstallationpipinstallblazeverifyUsageThe library needs to be configured with your account's API key which is available in yourBlaze Verify Dashboard.Setupimportblazeverifyclient=blazeverify.Client('live_...')Verification# verify an email addressresponse=client.verify('evan@blazeverify.com')response.state=>'deliverable'# additional parameters are available. see API docs for additional info.client.verify('evan@blazeverify.com',smtp=False,accept_all=True,timeout=25)Slow Email Server HandlingSome email servers are slow to respond. As a result, the timeout may be reached
before we are able to complete the verification process. If this happens, the
verification will continue in the background on our servers. We recommend
sleeping for at least one second and trying your request again. Re-requesting
the same verification with the same options will not impact your credit
allocation within a 5 minute window.A slow response will return with a 249 status code.response=client.verify('slow@example.com')response.status_code=>249response.message=>'Your request is taking longer than normal. Please send your request again.'Batch VerificationStart a batchemails=['evan@blazeverify.com','support@blazeverify.com',...]response=client.batch(emails)response.id=>'5cff27400000000000000000'# you can optionally pass in a callback url that we'll POST to when the# batch is complete.response=client.batch(emails,callback_url='https://blazeverify.com/')Get the status / results of a batchTo get the status of a batch callbatch_statuswith the batch's id. If your batch is still being processed, you will receive a message along with the current progress of the batch. When a batch is completed, you can access the results in theemailsattribute.response=client.batch_status('5cff27400000000000000000')# if your batch is still runningresponse.processed=>1response.total=>2response.message=>'Your batch is being processed.'# if your batch is completeresponse.emails=>[{'email':'evan@blazeverify.com','state':'deliverable'...},{'email':'support@blazeverify.com','state':'deliverable'...}...]# get the countsresponse.total_counts=>{'deliverable':2,'undeliverable':0...}response.reason_counts=>{'accepted_email':2,'rejected_email':0...}DevelopmentTests can be run with the following command:pythonsetuptestContributingBug reports and pull requests are welcome on GitHub athttps://github.com/blazeverify/blazeverify-python.
Package: blazingdocs
BlazingDocs Python clientHigh-performance document generation API. Generate documents and reports from СSV, JSON, XML with 99,9% uptime and 24/7 monitoring.InstallationRun this line from Terminal:pip install blazingdocsIntegration basicsSetupYou can get your API Key athttps://app.blazingdocs.comclient=BlazingClient('API-KEY')Getting account infoaccount=client.get_account()Getting merge templates listtemplates=client.get_templates()Getting usage infousage=client.get_usage()Executing mergeclient=BlazingClient('API-KEY')parameters=MergeParameters()withopen('templates/PO-Template.json','r',encoding='utf-8')asf:data=f.read()withopen('templates/PO-Template.docx','rb')asf:file=FormFile('PO-Template.docx')file.content=f.read()operation=client.merge_with_form_file(data=data,filename='output.pdf',parameters=parameters,template=file)DocumentationSee more details herehttps://docs.blazingdocs.com
Package: blazogram
BLAZOGRAM - A library for make Telegram Bots.Install$pipinstallblazogramExample UsagefromblazogramimportBot,Dispatcher,BlazeLocalefromblazogram.typesimportMessage,CallbackQuery,ReplyKeyboardMarkup,KeyboardButtonfromblazogram.filtersimportCommand,Datafromblazogram.enumsimportParseModeimportasyncioasyncdefstart_command(message:Message):kb=ReplyKeyboardMarkup()button=KeyboardButton(text='BUTTON')kb.add_button(button)awaitmessage.answer(text='Hello World!',reply_markup=kb)asyncdefsome_func(callback:CallbackQuery):awaitcallback.answer(text='Hello World!',show_alert=True)asyncdefmain():bot=Bot(token='YOUR-BOT-TOKEN',parse_mode=ParseMode.HTML)dp=Dispatcher()dp.message.register(start_command,Command("start"))dp.callback_query.register(some_func,Data("BUTTON_DATA"))awaitbot.skip_updates()try:awaitdp.start_polling(bot)finally:awaitbot.session.close()if__name__=='__main__':asyncio.run(main())Developer - @Blaze_Egor
Package: bl-bfg
Big Friggin Gun (BFG)BFG is a simple modular framework to perform brute-force attacks. It uses
theBruteLoopslibrary for the
brute force and database management logic.FeaturesSQLite DatastoreAuthentication data/requests are maintained in an SQLite database.Query capabilities enable granular timing configurations.Facilitates safe, resumable attacks.Database management tools are embedded in BFG via BruteLoopsRunbfg cli manage-db --help.BruteLoops CapabilitiesResumable attacks thatdo not repeat previous guesses.Simultaneous support for password spraying and credential stuffing.Parallel guessing.Lockout avoidance via two layers of jitter configurations.User/password prioritization.Universal protocol/application capabilities.Granular logging:Lockouts happen. It's part of life.BruteLoops provides a log record for each guess, along with timestamp.Allows operators to reconstruct a timeline of events if things go bad.Modular FrameworkSimple class-based modules provide reusable arguments/components.YAML Attack/Database ProfilesYAML files can be used to supply configuration values to BFG.Avoids complex command line flags.Docker SupportA compose file is available for this project. Seethis documentfor more information.Supported PlatformsOnly Linux is supported at the moment, however a Docker implementation will
soon follow.Quick Installpip3installbl-bfgThen confirm installation:bfg--helpDocumentationSee the docs directory for additional documentation:InstallationExample AttackYAML Attack ProfilesDockerFAQsCurrent Attack ModulesBelow are the attack modules currently in BFG.Most people will be interested inhttp.o365_graphas it can be used to attacklogin.microsoftonline.com.http.accellion_ftp  Accellion FTP HTTP interface login module
http.adfs           Active Directory Federated Services
http.basic_digest   Generic HTTP basic digest auth
http.basic_ntlm     Generic HTTP basic NTLM authentication
http.global_protect Global Protect web interface
http.lync           Brute force Microsoft Lync.
http.mattermost     Mattermost login web interface
http.netwrix        Netwrix web login
http.o365_graph     Office365 Graph API
http.okta           Okta JSON API
http.owa2010        OWA 2010 web interface
http.owa2016        OWA 2016 web interface
http.sap_webdynpro  SAP Netweaver Webdynpro, ver. 7.3007.20120613105137.0000
smb.smb             Target a single SMB server
testing.fake        Fake authentication module for training/testing
Package: blch
BlCha python package that can help you make a blockchain within 50 lines of codeExamplefrom blch import Block, Blockchain

def  main():
	blockchain  =  Blockchain()
	database  = ["Joe gives 2 coins to jack", "Jack gives 3 coins to Joe", "May gave 10 coins to Klaus", "Klaus gave 5 coins to May"]
	
	num  =  0
	for  data  in  database:
	num  +=  1
	
	blockchain.mine(Block(num, data=data))
	for  block  in  blockchain.chain:
		print(block)

	print(blockchain.isValid())
	blockchain.mine(blockchain.chain[0])

if  __name__  ==  '__main__':
	main()This is a simple example of the code which can be tweaked by your needsIf any problems please raise an issue in the github repo of this packageRepoPlease fork my repo and make sure to let me know for any ideas or problems to fix
Package: blcutools
BLCUtoolsBLCUtoolsPythonpipinstallblcutools分句fromblcutools.nlp.preprocessimportSplitSentenceWithPuncstext="北京语言大学（Beijing Language and Culture University），简称“北语”，中华人民共和国教育部直属高等学校，入选国家建设高水平大学公派研究生项目、特色重点学科项目、教育部来华留学示范基地、中国政府奖学金来华留学生接收院校，是在周恩来总理的亲自关怀下建立的，创办于1962年，时名为“外国留学生高等预备学校”；1964年6月由国务院批准定名为“北京语言学院”；1974年毛泽东主席为学校题写校名；1996年6月更名为“北京语言文化大学”；2002年校名简化为“北京语言大学”。"SplitSentenceWithPuncs.split(text)
Package: blcv
Blender for cvThis library helps CV researchers to generate data using blender.Library tutorialThis repo provides a simple packageblcvthat can put models into scene and get images from different viewpoints.InstallYou can usepip install blcvto install the package.Note that we should useblcvin Blender's bundled Python, so you need to install the package in Blender's Python environment.Use the following commands:$ cd /blender-path/2.xx/python/bin//blender-path/2.xx/python/bin$ python.exe get-pip.py/blender-path/2.xx/python/bin$ python.exe -m pip install blcvIf you encounter more problems installing blcv in Blender environment, you can refer to thisanswer.If there is problems usingpip, you can simply clone this repo, and use the files inblcvfolder.Functionsblcvcall_blender(render_code, blender_executable_path, blank_blend_file_path, io_redirect='', background=True): activate Blender and call the scriptrender_code: directory to Blender scriptblender_executable_path: directory to Blender.exeblank_blend_file_path: Blender fileio_redirect: redirect the output into a file, use '' to show the output in command linesbackground: whether run the Blender in background, default as 'True'blcv.toolsBcObject: operate an existed object in the sceneinit(self, id): input the name of the objectdestroy(self): delete the objectset_loc(self, x, y, z): set the object's locationget_loc(self, x, y, z): get the object's locationset_rot(self, x, y, z, w=None, mode='XYZ'): set the object's rotation; the mode includes 'AXIS_ANGLE', 'QUATERNION' and 'XYZ'get_rot(self, mode='XYZ', w=None): set the object's rotation; the mode includes 'AXIS_ANGLE', 'QUATERNION' and 'XYZ'set_scale(self, x, y, z): set the object's scaleget_scale(self, ): get the object's scaleBcCamera(BcObject): operate an camera in the sceneinit(self, id): input the name of the cameraset_camera_to_center(self, dist, azimuth_deg, elevation_deg, theta_deg): given the camera's rotation, set the camera in the position towards the center point [0, 0, 0]BcScene:init(self)set_render_mode(self, mode): set the background modeget_img(self, filepath): save image crop in filaepathimport_obj(shape_file): import a new model into the scene and return its nameDemoYou can modify the configurations and runstart_blender.pyto callblender_scriptin Blender.The demo generates airplane images from circle viewpoints using the models inexamplesfolder, the results will be saved inimagesfolder.ContactIf you have any questions or encounter any problems, feel free to contact me bysarahwei0210@gmail.com.
Package: bld
BldBld (pronouced /bɪld/ as build) is a project build helper. It is mainly aimed at complex project composed by modules with different languages.A typical project example is a client/server project where the server is coded with one language (C++, Go, Python...) and the client in another (Java, Javascript...). Both modules uses their own build system that can rarely be the same. To build the whole project, you end by creating a lot of scripts that cover the main situations.Bld can be used to avoid the creation of all those scripts. Just create a Python module for each project's module where you describe how to build it.InstallationFrom source:gitclonehttps://github.com/osechet/bldcdbld
pythonsetup.pyinstallUsageAt the root of your project, create aprojectfile.pyfile:"""Project definition."""NAME='super-project'VERSION='0.1.0-dev'MODULES=['client','server']BUILD_DIR='build'Set thePROJECT_HOMEenvironment variable to define the root directory of your project:exportPROJECT_HOME="/path/to/super-project"Create a script for each project module in the${PROJECT_HOME}/blddirectory:client.py:"""The client module."""importosdefbuild(project,args):"""Build the module."""# Aliasesrun=project.runmodule_dir=os.path.join(project.root_dir,'client')withproject.chdir(module_dir):withproject.step('client:build',"Build"):run('echo "Building..."')run('sleep 2')server.py:"""The server module."""importosimportplatformdefbuild(project,args):"""Build the module."""# Aliasesrun=project.runmodule_dir=os.path.join(project.root_dir,'server')withproject.chdir(module_dir):withproject.step('server:build',"Build"):run('echo "Building..."')run('sleep 3')Callbldto build the whole project orbld <module>to build a specific module.ReportsBld automatically monitor the time execution of the build. The result is stored at the end of the build in thereports/time.csvfile. The project'sstep()method can be used to monitor a specific block of code. The time report list all the executed steps by name but also the total build execution:client:build,server:build,total
2.015258717990946,3.018017319991486,5.0884078509989195DevelopmentNote: It is advised to work inside a virtual environment. In this section, we'll work with venv.Create the virtual environement:python3-mvenv./venvLater to open the virtual environment:. ./venv/bin/activateInstall requirements (once in virtual environment):python-mpipinstall-rrequirements.txt
python-mpipinstall-rrequirements_dev.txtRun thebldcommand:./bldlib/bld.py-hUnit testsTo run unit tests, callpytest. For code coverage, runpytest --cov=bldlib.TestsTo install the package being developed, runpip install -e .from the project's root directory. You can then uninstall it withpip uninstall bld.Publishingrm-rfdist
pythonsetup.pysdist
twineuploaddist/*
Package: bldg-point-clustering
bldg_point_clusteringPyPi Package:https://pypi.org/project/bldg-point-clustering/Docs:https://bldg-point-clustering.readthedocs.io/en/latest/IntroductionA Python 3.5+ wrapper for clustering building point labels
using KMeans, DBScan, and Agglomerative clustering.InstallationUsing pip for Python 3.5+ run:$pipinstallbldg_point_clusteringQuick StartInstantiate Featurizer object and get featurized Pandas DataFrame.Instantiate Cluster object and pass in featurized
DataFrame to. Then, call a clustering method with the
appropriate parameters.Use the plot3D function in the Plotter to create a
3D plot of metrics returned by any of the clustering trials.Example UsageRunning one iteration of the KMeans algorithm.importpandasaspdimportnumpyasnpfrombldg_point_clustering.clusterimportClusterfrombldg_point_clustering.featurizerimportFeaturizerfilename="GBSF"df=pd.read_csv("./datasets/"+filename+".csv")first_column=df.iloc[:,0]f=Featurizer(filename,corpus=first_column)featurized_df=f.bag_of_words()c=Cluster(df,featurized_df)clustered_df=c.kmeans(n_clusters=300,plot=True,to_csv=True)metrics=c.get_metrics_df()avg_levenshtein_score=np.mean(c.get_levenshtein_scores())Running several iterations of the KMeans algorithm.frombldg_point_clustering.plotterimportplot_3Dc.kmeans_trials()metrics=c.get_metrics_df()plot_3D(metrics,"n_clusters","Avg Levenshtein Score","Silhouette Score")This process is similar for DBScan and Agglomerative.
Package: bldr
BLDRBuild debian packages in a clean docker environmentFeatures:provide a dockerized dpkg-buildpackage wrapper, as Docker can be used to create a clean build environment for Debian packagingeasy-to-use: navigate inside a directory that has a debian subdirectory and run buildcollect the debian dependencies automatically and puts them in Docker build layercache the dependency install step and the re-build will be quickerto test the debian package you can enter to the container which contains the build environmentthe built debian package is stored in a local apt repositorybuild multiple dependent packages, if called multiple times (uses the built packages as build dependencies of the next ones)
Package: bldr-test
This is theREADME.md.  It is being pulled into the markdown files by pdoc.This is a link to the GitHub Pages sitehosting the auto-generated documentation.bolditalicstrikethroughHeaderLink:bldr-test on TestPyPiuse, install:pip3listechopip3install-ihttps://test.pypi.org/simple/bldr-testechopip3listuse, run:python3-mbldr_testuse, uninstall:pip3listechopip3uninstallbldr-testechopip3list(Note:-vs._above intended.  Also note: theechocommands are merely for more legible output)
Package: bleach-allowlist
A curated list of tags, attributes, and styles suitable for filtering
user-provided HTML usingbleach.Currently, it consists of basic set of tags suitable for rendering markdown,
and markup intended for printing, as well as a list of all CSS styles.  Please
send pull requests with improvements or lists of tags and attributes for other
purposes (wikis, comments, etc?).Installationpip install bleach-allowlistUseimport bleach
from bleach_allowlist import print_tags, print_attrs, all_styles

bleach.clean(raw_html, print_tags, print_attrs, all_styles)Properties:markdown_tags: Safe HTML tags needed to render markdown-style markup.markdown_attrs: Safe attributes tags needed to render markdown-style markup.print_tags: Safe HTML tags suitable for printing / PDFs.print_attrs: Safe attributes suitable for printing / PDFs.all_styles: A list of all CSS properties supported by major browsers.standard_styles: A list of standard (non-vendor-specific) CSS properaties.Seebleach_allowlist.pyfor more.Have improvements or lists of tags suitable for other purposes?  Please send a
pull request!  Let’s build a few good task-specific allow-lists rather than
reinventing these lists every time.
Package: bleached
bleachedThis is a small HTML checker. It can validate that HTML code is safe.It does not aim to support the entire HTML spec, rather it focuses on checking HTML that has been run through a sanitizer (such asbleach).How to use?$ pip install bleached
$ python3
>>> import bleached
>>> bleached.is_html_bleached('<p>Hello world</p>')
True
>>> bleached.is_html_bleached('<script>alert("Hello world");</script>')
False
>>> bleached.check_html('<p>Hello world</p>')
>>> bleached.check_html('<script>alert("Hello world");</script>')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
bleached.UnsafeInput: Line 1 character 8 (input index 7): Found forbidden opening tag 'script'Why use this?bleachis a great library for sanitizing untrusted HTML. You should use it instead of this where possible.However, it offers no way to check that a piece of HTML has been sanitized. Running the HTML through bleach again will only work if you have the exact same version, as bleach makes no guarantee of stability of their input. This is where bleached is useful.WarningsNo validation of attributes is performed. If you choose to allow an attribute, it is up to you to validate the values.This accepts a much smaller subset of HTML than web browsers. Be ready for false negatives if you use this to validate HTML documents.
Package: bleachfields
django-bleachfields is a Python module that utilizes existing bleach and HTML parser modules to remove HTML tags and unescape text from a field before saving it to a Django model.
To use, simply call BleachJSONField or BleachTextField in place of a Django text field, such as models.TextField or models.CharField.InstallpipinstallbleachfieldsUsagefromdjango.dbimportmodelsfrombleachfieldsimportBleachJSONField,BleachTextFieldclassPerson(models.Model):name=BleachTextField(max_length=256)response=BleachJSONField()ContactEmail:afrancis@betterworks.comChangesNone to date.