Saravanan666/pypi-org huggingface dataset:
Package: bolt-sdk-py2
Bolt SDKThis SDK provides an authentication solution for programatically interacting with Bolt. It wraps the boto3 interface so project wide integration is as easy as refactoringimport boto3toimport bolt as boto3.The package affects the signing and routing protocol of the boto3 S3 client, therefore any non S3 clients created through this SDK will be un-affected by the wrapper.PrerequisitesThe minimum supported version of Python is version 2.Installationpython-mpipinstallbolt-sdk-py2UsageIn order to use this package, toy first need to set some environment variablesexportBOLT_CUSTOM_DOMAIN=<YOUR_CUSTOM_DOMAIN>exportBOLT_REGION=<YOUR_BOLT_CLUSTER_REGION># Optional if not running on an ec2 instance to force read from a read-replica in this azexportBOLT_AZ_ID='<az-id>'If the region and AZ environment variables aren't specified when running on an EC2 instance, the SDK will use the ec2 metadata api to fetch the instance's region and availability zone id.Example usageimportbolt# Create an S3 clients3_client=bolt.client("s3")# Define a function that performs the put_object operations3_client.put_object(Body="data",Bucket="BUCKET_NAME",Key="key")obj=s3_client.get_object(Bucket="BUCKET_NAME",Key="key")body=obj["Body"].read()DebuggingImport the logging and set default level toDEBUG.importlogginglogging.basicConfig(level=logging.DEBUG)
Package: bolt-ta
Bolt is a task runner inspired bygruntand written inpythonthat helps you automate any task in your project
whether it is executed in your development environment or in your CI/CD pipeline.
Bolt gives you the power to specify how tasks should be executed, and it takes
care of the rest. And it is as simple as describing and configuring your tasks
in theboltfile.py.# boltfile.pyimportboltconfig={'pip':{'command':'install','options':{'r':'./requirements.txt'}},'delete-pyc':{'sourcedir':'./src','recursive':True},'nose':{'directory':'./tests','options':{'with-xunit':True,'xunit-file':'./logs/unit_test_log.xml'}}}bolt.register_task('run-tests',['pip','delete-pyc','nose'])# in your favorite shellboltpip# to install requirementsboltnose# executes unit testsboltrun-tests# installs requirements, deletes .pyc files, and runs unit testsWhy Use Bolt?Let’s face it, you want to automate everything, but doing so becomes a burden;
especially, if you are working on a cross-platform application. You may find
your-self switching CI/CD systems and going through the pain of
rewriting your pipelines to the specific domain languages they use. Python
is cross-platform and any pipline will allow you to execute a command. This
makes Bolt ideal to create reusable tasks that can execute in any environment
indpendently of tools. And, It’s fun!How Can I Get Started?You can start by installing bolt and following the examples in theGetting Startedguide. Once you become familiar with Bolt, you can look at other topics inUsing Bolt,
to learn about the different features it provides.This is Great! I want to Help!Help is highly appreciated! If you want to contribute to the project, make sure
to read ourguidelines.
If you are a tool developer, and you want to provide Bolt support in your
library or application don’t hesitate asking for help. We want to build a great
community around Bolt, and we will help you in any way we can.Make sure you read thebolt documentation.
Package: boltun
Boltun (aka rus. [Болтун](https://en.wiktionary.org/wiki/%D0%B1%D0%BE%D0%BB%D1%82%D1%83%D0%BD))===Generates massive datasets from just a single template.```textCommand:> python -m boltun "{{ Hi || Hello }}, [[ 'welcome' | upper? ]][[? ' back' ]] to Boltun [% repeat('!', [1, 3]) %]"Hi, WELCOME back to Boltun !Hello, WELCOME back to Boltun !Hi, welcome back to Boltun !Hello, welcome back to Boltun !Hi, WELCOME to Boltun !Hello, WELCOME to Boltun !Hi, welcome to Boltun !Hello, welcome to Boltun !Hi, WELCOME back to Boltun !!!Hello, WELCOME back to Boltun !!!Hi, welcome back to Boltun !!!Hello, welcome back to Boltun !!!Hi, WELCOME to Boltun !!!Hello, WELCOME to Boltun !!!Hi, welcome to Boltun !!!Hello, welcome to Boltun !!!```Branch   | CI status---------|-------------------master   | [![Build Status](https://travis-ci.org/meiblorn/boltun.svg?branch=master)](https://travis-ci.org/meiblorn/boltun)[![codecov](https://codecov.io/gh/meiblorn/boltun/branch/master/graph/badge.svg)](https://codecov.io/gh/meiblorn/boltun)develop  | [![Build Status](https://travis-ci.org/meiblorn/boltun.svg?branch=develop)](https://travis-ci.org/meiblorn/boltun)[![codecov](https://codecov.io/gh/meiblorn/boltun/branch/develop/graph/badge.svg)](https://codecov.io/gh/meiblorn/boltun)## About[![boltun_simpsons_bart](https://raw.githubusercontent.com/meiblorn/boltun/master/static/simpsons_bart.png)](https://github.com/meiblorn/boltun)**Boltun** is designed to be best alternative for the natural language machine-learning developers and enthusiasts.It was developed as an alternative for such projects as[Chatito](https://github.com/rodrigopivi/Chatito) and [Tracery](http://tracery.io/).Yes, they are almost perfect, especially Tracery, but both of them are written for NodeJS platform.NodeJS is a single threaded language, so that tools are perfect only for small amounts of data.Boltun breaks that bounds of data generation limits.## Getting Started### InstallingUsing pip ([PyPI repository](https://pypi.org/project/boltun/)):```bashpip install boltun```Boltun is also available on[Docker Hub](https://hub.docker.com/r/meiblorn/boltun):```bashdocker pull meiblorn/boltun```For macOS users, Boltun is available via[Homebrew](https://brew.sh)```bashbrew install boltun```### Usage```bashpip -m boltun "<your template>"```## ContributingYou are welcome to contribute ! Just submit your PR and become a part of Boltun community!Please read [contributing.md](contributing.md) for details on our code of conduct, and the process for submitting pull requests to us.## VersioningWe use [SemVer](http://semver.org) for versioning. For the versions available, see the [tags on this repository](https://github.com/meiblorn/boltun/tags).## Authors* **Vadim Fedorenko** - [Meiblorn](https://github.com/meiblorn) -*Initial work*See also the list of [authors](authors.md) who participated in this project.## LicenseThis project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details## Acknowledgments* Your questions will appear here. Feel free to ask me.**Vadim Fedorenko** - [Meiblorn](https://github.com/meiblorn) - *Initial work*
Package: boltz_client
Boltz Python ClientBoltz Reference Client in Python, used by e.g.https://github.com/lnbits/boltzinstallingpoetry installrunning clipoetry run boltzstarting regtestcd dockerchmod +x regtest./regtestrunning testspoetry run pytestOr install the latest release fromPyPIviapip install boltz-client.
Package: boltzmannclean
Fill missing values in a pandas DataFrame using a Restricted Boltzmann Machine.Provides a class implementing the scikit-learn transformer interface for creating and training a Restricted Boltzmann Machine. This can then be sampled from to fill in missing values in training data or new data of the same format. Utility functions for applying the transformations to a pandas DataFrame are provided, with the option to treat columns as either continuous numerical or categorical features.InstallationpipinstallboltzmanncleanUsageTo fill in missing values from a DataFrame with the minimum of fuss, a cleaning function is provided.importboltzmanncleanmy_clean_dataframe=boltzmannclean.clean(dataframe=my_dataframe,numerical_columns=['Height','Weight'],categorical_columns=['Colour','Shape'],tune_rbm=True# tune RBM hyperparameters for my data)To create and use the underlying scikit-learn transformer.my_rbm=boltzmannclean.RestrictedBoltzmannMachine(n_hidden=100,learn_rate=0.01,batchsize=10,dropout_fraction=0.5,max_epochs=1,adagrad=True)my_rbm.fit_transform(a_numpy_array)Here the default RBM hyperparameters are those listed above, and the numpy array operated on is expected to be composed entirely of numbers in the range [0,1] or np.nan/None. The hyperparameters are:n_hidden: the size of the hidden layerlearn_rate: learning rate for stochastic gradient descentbatchsize: batchsize for stochastic gradient descentdropout_fraction: fraction of hidden nodes to be dropped out on each backward pass during trainingmax_epochs: maximum number of passes over the training dataadagrad: whether to use the Adagrad update rules for stochastic gradient descentExampleimportboltzmanncleanimportnumpyasnpimportpandasaspdfromsklearnimportdatasetsiris=datasets.load_iris()df_iris=pd.DataFrame(iris.data,columns=iris.feature_names)df_iris['target']=pd.Series(iris.target,dtype=str)df_iris.head()_sepal length (cm)sepal width (cm)petal length (cm)petal width (cm)target05.13.51.40.2014.93.01.40.2024.73.21.30.2034.63.11.50.2045.03.61.40.20Add some noise:noise=[(0,1),(2,0),(0,4)]fornoisyinnoise:df_iris.iloc[noisy]=Nonedf_iris.head()_sepal length (cm)sepal width (cm)petal length (cm)petal width (cm)target05.1NaN1.40.2None14.93.01.40.202NaN3.21.30.2034.63.11.50.2045.03.61.40.20Clean the DataFrame:df_iris_cleaned=boltzmannclean.clean(dataframe=df_iris,numerical_columns=['sepal length (cm)','sepal width (cm)','petal length (cm)','petal width (cm)'],categorical_columns=['target'],tune_rbm=True)df_iris_cleaned.round(1).head()_sepal length (cm)sepal width (cm)petal length (cm)petal width (cm)target05.13.31.40.2014.93.01.40.2026.33.21.30.2034.63.11.50.2045.03.61.40.20The larger and more correlated the dataset is, the better the imputed values will be.
Package: boludiiin
Boludiiin: Python Web Framework for the giladaBoludiiin is a Python web framework built for learning purposes.It's a WSGI framework and can be used with any WSGI application server such as Gunicorn.InstallationpipinstallboludiiinHow to use itBasic usage:fromboludiiin.apiimportAPIapp=API()@app.route("/home")defhome(request,response):response.text="Hello from the HOME page"@app.route("/hello/{name}")defgreeting(request,response,name):response.text=f"Hello,{name}"@app.route("/book")classBooksResource:defget(self,req,resp):resp.text="Books Page"defpost(self,req,resp):resp.text="Endpoint to create a book"@app.route("/template")deftemplate_handler(req,resp):resp.body=app.template("index.html",context={"name":"boludiiin","title":"Best Framework"}).encode()Unit TestsThe recommended way of writing unit tests is withpytest. There are two built in fixtures
that you may want to use when writing unit tests with boludiiin. The first one isappwhich is an instance of the mainAPIclass:deftest_route_overlap_throws_exception(app):@app.route("/")defhome(req,resp):resp.text="Welcome Home."withpytest.raises(AssertionError):@app.route("/")defhome2(req,resp):resp.text="Welcome Home2."The other one isclientthat you can use to send HTTP requests to your handlers. It is based on the famousrequestsand it should feel very familiar:deftest_parameterized_route(app,client):@app.route("/{name}")defhello(req,resp,name):resp.text=f"hey{name}"assertclient.get("http://testserver/matthew").text=="hey matthew"TemplatesThe default folder for templates istemplates. You can change it when initializing the mainAPI()class:app=API(templates_dir="templates_dir_name")Then you can use HTML files in that folder like so in a handler:@app.route("/show/template")defhandler_with_template(req,resp):resp.html=app.template("example.html",context={"title":"Awesome Framework","body":"welcome to the future!"})Static FilesJust like templates, the default folder for static files isstaticand you can override it:app=API(static_dir="static_dir_name")Then you can use the files inside this folder in HTML files:<!DOCTYPE html><htmllang="en"><head><metacharset="UTF-8"/><title>{{title}}</title><linkhref="/static/main.css"rel="stylesheet"type="text/css"/></head><body><h1>{{body}}</h1><p>This is a paragraph</p></body></html>MiddlewareYou can create custom middleware classes by inheriting from theboludiiin.middleware.Middlewareclass and overriding its two methods
that are called before and after each request:fromboludiiin.apiimportAPIfromboludiiin.middlewareimportMiddlewareapp=API()classSimpleCustomMiddleware(Middleware):defprocess_request(self,req):print("Before dispatch",req.url)defprocess_response(self,req,res):print("After dispatch",req.url)app.add_middleware(SimpleCustomMiddleware)
Package: bomail
bomail is an experimental system for organizing and interacting with email.It can be installed with pip3 (the python package manager) viapip3 install bomail.This software is free.Homepage and information:https://www.bowaggoner.com/bomail/Source:https://www.bitbucket.org/bowaggonerpublic/bomailVersion:0.9.4.1TODOs:- Tree view for threads (see reply structure rather than list by date)- Digital signatures and encryptionCompleted:- (0.9.3.0) Use XDG spec for where to put data and config- (0.9.2.0) Respect the reply-to header on emails
Package: bom-analysis
Bill of Materials AnalysisThis repository allows for an engineering assembly to be represented in a Bill of Materials
(BOM) structure for analysis. The aim was to reduce the cognative complexity of the various data
sets that are required for input or output of an analysis workflow. The repository also
includes a number of features to help with this analysis.The motivation for this package comes from a desire to order complex
system data used by analysis in a logical. The chosen method
for ordering this data is the bill of materials as it provides a common
framework used across engineering.The bill of materials provides a hieracy of materials, components, and assemblies
all of which can contain data that is important for the analysis. For example,
a user may want to assess the mass of an assembly by summing the mass of all
the components in that make it up.The Bill of Materials can be plotted to help understand the system (taken fromexample):tokamak
├── coil_set
│   ├── east
│   ├── north
│   ├── south
│   └── west
└── divertorThe data for each of the components can also be displayed easily:================================================================================
| var           │ value   │ unit          │ description                        │
================================================================================
│ mass          │ 1000    │ metric_ton    │                                    │
================================================================================
│ configuration │ ST      │ dimensionless │                                    │
================================================================================
│ major_radius  │ 2       │ meter         │ the geometric centre of the plasma │
================================================================================InstallationThe easiest way to install bom_analysis is using pippip:pip install bom_analysisHelp and SupportDocumentationExample on Defining a Bill of MaterialExample on Loading a Bill of MaterialExample on Creating a SkeletonExample on Useful FeaturesExample on Handling MaterialsTestingBOM Analysis contains a test suite that can be ran using pytest (must be installed). Three markers have been used to distiguish the different testing levels:unittest: runs unit tests that generally only test an individual method by using mockingintegrationtest: runs the integration testsregressiontest: tests bugs that have been indentified in other versionsThe full test suite can be ran by navigating to the source directory and runningpytest:pytestIt is possible to filter the tests by the markers:pytest -m "unittest"Or filter out markers:pytest -m "not integrationtest and not regressiontest"LicenseBSD 3
Package: boman-cli
IntroductionBoman CLI is a Orchestration script written in python to run security scans on the customer's local or CI/CD environment and upload the results to Boman.ai SaaS server.Installationpip install boman-cliGetting StartedFor helpboman-cli -hTo test the boman cli serverboman-cli -a test-saasTo test the boman configuration written in boman.yaml fileboman-cli -a test-yamlTo run the scanboman-cli -a runTo run the scan on specific Boman SaaS URL (On prem)boman-cli -a run -u {URL}releases:v1.02 with following changes:Version with synk integration, codeql csharp build, exit code sorted
added option to fail/pass build, dast error sorted
Snyk feature added and upload logs to saas function addedv1.3:SCA scan bug fixedV1.4Added scanning on jenkins env with limited permission for SAST/DAST scans.
check-user argument added in --action, to check the permssion of the running user.V1.5Failing Build Filter implemented, you can now pass values sucha as 'only-high,only-medium,only-low' to the -fb argument.
Package: bomapi
Python interface for Australian BOM Weather APIIncludes support for AsyncIO and returns populated objects with objects parsed
ready for use.DisclaimerThis package is not associated with or endorsed by the Australian
Bureau of Meteorology (BOM). Usage may be subject to their term and conditions.
See the copyright notice published on their website for more information:http://reg.bom.gov.au/other/copyright.shtmlInstallation# Pippipinstallbomapi# Pipenvpipenvinstallbomapi# PoetrypoetryaddbomapiUsageFind a locationimportbomapiresults=bomapi.location_search("Wollongong")forresultinresults:print(result.name)Get data from a locationimportbomapigeohash="r3gk6rr"# Wollongong (or use the result object from location_search)location=bomapi.Location(geohash)observations=location.observations()print(observations.rain_since_9am)Async supportimportbomapi.aiogeohash="r3gk6rr"# Wollongonglocation=bomapi.aio.Location(geohash)observations=awaitlocation.observations()print(observations.rain_since_9am)
Package: bombaat
BOMBAAT CLIAzure Active Directory single sign-on (SSO) integration with Amazon Web Services CLI (AWS CLI / BOTO)Bombaat CLI enables you to access AWS Cloud accounts via awscli/boto using Azure AD single sign on serviceSystem RequirementsMac OSX or LinuxPython3.6+PrerequisiteNOTE: If you just want to test the tool, no need to follow the below steps. It installs default drivers and sample cloud profiles.If you have plan to use it in your own environment, this installation requires to host set of configuration files somewhere on the network. (example: you can upload both the zip files to a S3 bucket and update s3 permissions to make it accessible via network)Download the following files.https://bombaat.s3.ap-south-1.amazonaws.com/drivers.ziphttps://bombaat.s3.ap-south-1.amazonaws.com/profiles.zipUnzip profiles.zip, update your cloud environment URLs and name, zip it back.InstallationThese steps are one time setup, which installs bombaat cli and required configuration files.Step 1:$pip3installbombaatstep 2:Ignore this step, if you are not setting this tool in your own environment. Otherwise, run the following command to set the host where you have uploaded zip files as per thePrerequisitestep.Please make sure you are providing hostname without forward slash. For example if you have hosted your zip files underhttps://example.com/drivers.ziporhttps://example.com/profiles.zip, just enterhttps://example.com$bombaatinitStep 3:Download and install configuration files either from default host or from the host configured in step 2.$bombaatupdateallUsageStep 1: Configure cloud profile:Before log in any AWS cloud account, you need to configure the same as it collects login info.Azure AD SSO Username - It should be your email IDDefault - It can be set True or False. [If you set True, the profile becomes your default cloud account while usingawscliorboto. If you dont, it always be False.]$bombaatconfigureYou can always come back and run thebombaat configurecommand to change the settings.Step 2: To log in to a profile:Profiles which you have configured in the previous step will be shown inlogincommand.$bombaatloginHelpTo see help text:$bombaat--help
$bombaat<command>--helpCompatibilityCompatible with Mac OSX or Linux with python3.6 or higher version.RequirementsAzure AD SSO integration with Amazon Web Services. Followthislink to setup Azure SSO with AWS Console.Authorsbombaatwas written byRavi Boodher<boodher@gmail.com>.
Package: bombard
Bombard is a tool for stress test and benchmarking your HTTP server.
Especially it’s good to simulate a heavy load and initial burst of
simultaneous HTTP requests with complex logic.It is designed to be extremely simple yet powerful tool to
load test functional behavior.Thanks to optional Python inlines you can fast and easy describe
complex logic for the tests.Test report shows you how many requests per second your server
is capable of serving and with what latency.Installationpipinstallbombard--upgradeAfter that usebombard(bombard.exein Windows) executable:bombard--helpRequests descriptionRequests can be just URL or contain JSON described like thissupply:# you can redefine variables from command line (--supply host=http://localhost/)host:https://jsonplaceholder.typicode.com/getToken:url:"{host}auth"# use custom {host} variable to stay DRYmethod:POSTbody:# below is JSON object for request bodyemail:name@example.compassword:adminextract:# get token for next requeststoken:In first request you can get security token as in example above.And use it in next requests:postsList:url:"{host}posts"headers:Authorization:"Bearer{token}"# we get {token} in 1st requestscript:|for post in resp[:3]:  # for 1st three posts from response# schedule getPost request (from ammo section)# and provide it with id we got from the responsereload(ammo.getPost, id=post['id'])Included examples. To list examplesbombard--examplesCommand lineFrom command line you can change number of threads, loop count,
supply vars, customize report and so on.Also you can bootstrap your ownbombard.yamlfile from any example you
like:bombard --init --example simpleReportExample of report for the command:bombard --example simple --repeat 2 --threshold 100DocumentationBombard documentationTranslation managed withTransifex
Package: bombardier_cli
Bombardier is a command-line system that allows a system admins to manage alarge number of computers in his or her datacenter over ssh. You can compareBombardier to Chef (www.opscode.com) or ControlTier (www.controltier.org).Bombardier has a more secure than either of those systems and provides abetter user interface (command-line) that (we think) most systemadministrators will prefer for daily work to web-based interfaces (whichyou are limited to with the other products)..For common tasks such as deploying software or making changes to systemconfiguration, this tool can make these tasks a lot faster and a lot morereliable. The basic approach is to drive automated SSH sessions over expect..There are three major pieces of code to this thing:# A "client," which installs on the computers you want to manage. The clientdoes not run as a service, it is more accurately described as client-sidelibraries. The client software can be automatically installed by the server.# (THIS PACKAGE)A server, which runs under Apache and provides a ReSTinterface, and a daemon. The daemon is responsible for managing sshconnections to the computers in the network.# A command-line interfce (CLI), which provides an efficient Cisco-stylecommand-line for driving the whole system.