Saravanan666/pypi-org huggingface dataset:
Package: booru-note-copy
note_copyCopy translation notes between booru-style imageboardsIntroductionnote_copyis a program that copies translation notes from one booru post to another, either on the same site or across sites.InstallationThe recommended way to install thebooru-note-copymodule is to simply usepipenv:$ pipenv install booru-note-copyOr, if you prefer plain, oldpip:$ pip install --user booru-note-copyOnce installed, the program is accessible asnote_copy.ExampleTo copy notes between posts, simply supply two post IDs:$ note_copy --source d1671559 --destination g2244172This will copy the notes from the source and change the tags on the destination post as necessary. On first usage, you will be prompted for your login information for each site used so that the notes can be created with your account. If you choose to store this data, the files are created in the.note_copydirectory inside your home directory. For sites that require passwords, only the hash of the password is stored.The script can also read from a file to copy notes between multiple pairs at once. The file should have a pair of post IDs per line, with the IDs separated by whitespace.$ cat ids
d1671559 g2244172
d1701853 g2283415
$ note_copy --file idsThe lower-case prefixes are called short codes and can be used to identify the site on which the post is located. Alternatively, the full domain of the site can be used instead of the short code, e.g.gelbooru.com2244172.note_copyis also able to be run as a module:$ python -m note_copy -s d1102540 -d g1433185RequirementsPython 3.5+Usageusage: note_copy [-h] [-s SOURCE] [-d DESTINATION] [-f FILE]

optional arguments:
  -h, --help            show this help message and exit
  -s SOURCE, --source SOURCE
                        The post from which notes will be copied
  -d DESTINATION, --destination DESTINATION
                        The post to which notes will be copied
  -f FILE, --file FILE  File containing post pairs, separated by whitespace,
                        one per lineYou need to provide either a source/destination combo or a file; you cannot use both sets of arguments simultaneously.Supported sitesSite NameShort CodeDomainLogin InformationDanbooruddanbooru.donmai.usUsername, API keyGelbooruggelbooru.comUsername, password, API key
Package: boos
A python library and cli for theBose SoundTouch (R) API.To be able to use my Bose Soundtouch 10 from the command line.And to be able to use it as library for Home-Assistanthttps://home-assistant.io/And to be ‘my first pip’ package :-)InstallationTo install boos python library, simply:pipinstallboosboosrequires Python >= 3.4.Quick StartConnect to your Bose SoundTouch (R) device and activate preset 3To work in python:fromboosimportBoosbooz=Boos("http://boos.fritz.box:8090")booz.preset(3)booz.vol()booz.vol(30)Or if you can run python 3 code for example on Linux:# create a symbolic link to the cli.py
# and (for now) be sure in cli.py you have the right url definedsudoln-s./boos/cli.py/usr/local/bin/boos# runboosboosset3boosvolboosvol30Or create a virtualenv and create some bash file::virtualenv -p python3 boos
cd boos
pip install boos# and a bash file like:#!/bin/bashsource /home/richard/venv/boos/bin/activate
/home/richard/dev/boos/boos/cli.py “$@”LinksAs an alternative have a look athttps://github.com/chassing/badtouchBose SoundTouch (R) APIhttp://products.bose.com/api-developer/index.htmlHome Assistanthttps://home-assistant.io/PackagingAll fromhttps://python-packaging-user-guide.readthedocs.org/en/latest/distributing/#source-distributions# source distpython3setup.pysdist# creating a universal wheel?python3setup.pybdist_wheel# now setup a local webserver to testcddistpython-mSimpleHTTPServer9000# and in another terminal
# create a python 3 virtual environment venv (all as usual)virtualenv-ppython3venvcdvenvsourcebin/activate# now in pythonpython3>>>fromboosimportBoos>>>booz=Boos("http://boos.fritz.box:8090")>>>booz.preset(3)# setting to preset 3>>>print(booz.now_playing())# should show current playing song/source# https://packaging.python.org/en/latest/distributing/#uploading-your-project-to-pypi
#
# create a .pypirc file in home dir[distutils]index-servers=pypitestpypi[testpypi]repository=https://testpypi.python.org/pypiusername=<yourusernamegoeshere>password=<yourpasswordgoeshere>[pypi]repository=https://pypi.python.org/pypiusername=<yourusernamegoeshere>password=<yourpasswordgoeshere>#
# to upload it to testpypi (https://wiki.python.org/moin/TestPyPI)
# first register the projectpythonsetup.pyregister-rhttps://testpypi.python.org/pypi# preferred (given you have username and testpypi as key in .pypirc:twineupload-rtestpypidist/*# orpythonsetup.pysdistupload-rhttps://testpypi.python.org/pypi# after upload install via
# searchpipsearch--indexhttps://testpypi.python.org/pypiboos# installpipinstall-ihttps://testpypi.python.org/pypiboos# or to pypi
# preferred:
# first register projectpythonsetup.pyregister# preferred (given you have username and testpypi as key in .pypirc:twineupload-rpypidist/*# orpythonsetup.pysdistupload-rhttps://pypi.python.org/pypi# and installpipinstallboos
Package: boosint
MaigretAboutBoOSINTcollects databy username onlyby checking nearly every data publicly available about a username and it's aliases.Main featuresProfile pages parsing, extraction of personal info, links to other profiles, etc.Recursive search by new usernames and other ids foundSearch by tags (site categories, countries)Censorship and captcha detectionRequests retriesFinding of websitesFinding device information, telephone number, email addressesFinding locations, gender, birthdays and real namesInstallationPackage installingComing soon...Cloning# or clone and install manuallygitclonehttps://github.com/protdos/boosint&&cdboosint

pip3install-rrequirements.txt# usagecdboosint

python3boosint.pyusername# usage with pypi (see above)boosintusername# currently not availableUsage (coming soon...)# make txt or json reportsboosintusername--typetxt

boosintusername--typejson# filename output (default is report.json)boosintusername--outputreport.txt

boosintusername--outputreport.jsonUseboosint -hto get full options description.Sources / CreditsHere is a list of sources I used:MaigretBlackBirdGitReconThe code is partly combined but the most of it is written by myself.
Package: boostbuild
BoostBoost is a simple build system that aims to create an interface for shell command substitution across different operative systems. Boost tries to centralize build steps on different development environments.Boost adds a simple way to add custom commands with different behaviours for different platforms.CommandsA command is a group of functions which determines the behaviour of an action on different environments. A command needs to implement these functions:generic_exec(args: List[str]) -> dict: function if the code is the same across multiple platforms orwin_exec(args: List[str]) -> dict: for Windows commands.posix_exec(args: List[str]) -> dict: for Posix commands.Currently, commands files under cmd package which implement above deffined functions can be automatically used by its file name. For example,boost.cmd.deletecan be used inside anyboost.yamlboosttargets by using the keyworddelete.Using BoostTo use Boost, first, create aboost.yamlfile in your project directory. This is an example of a simple boost file.vars:file:example.txtcurrent_dir:exec pwdboost:dev:|delete {file}asd {current_dir}vars: Define key-value pairs representing variables that needs to be used inside boost targets. If a variable needs to store the output from a command, useexecfollowed by the commands that needs to be captured.boost: Define key-value pairs named boost targets. Target key will be used to call that specific target. Value contains a list of commands separated by\nthat will be triggered when calling a specific target.
If a value needs to use a variable, use$followed by the variable name that was previously declared onvarssection.To call a boost target, runboost <TARGET>. If no boost target was specified, boost will use the first defined target.Developing boostRequirements:poetryRunpoetry install. Whit the previous command, you can runpoetry run boostto test boost, boost command does automatically triggerboostbuild.main:mainfunction.
Package: boostedblob
boostedblobboostedblob is a command line tool and async library to perform basic file operations on local
paths, Google Cloud Storage paths and Azure Blob Storage paths.boostedblob is derived from the excellentblobfile.The fun part of implementing boostedblob isboostedblob/boost.py, which provides aconcurrent.futures-like interface for running and composing async tasks in a concurrency limited
environment.InstallationJust runpip install boostedblob. boostedblob requires Python 3.8 or better.UsageFor an overview and list of commands:bbb--helpFor help with a specific command:bbbls--helpTo enable tab completion, add the following to your shell config (replacingzshwithbash,
if appropriate):eval"$(bbbcompleteinitzsh)"Note that the quotes are necessary. You can also inline the result ofbbb complete init zshinto
your shell config to make your shell startup a little faster.ContributingFor developer documentation (getting started, running tests, debugging tricks, codebase tips),
seeCONTRIBUTING.md
Package: boosterpacks
To use (with caution), simply do::>>> from boosterpacks import *
>>> cards = [(u'neut_u_modulehealer', u'1'), (u'terr_t_PrecisionStrike', u'2'), (u'terr_t_PulseBarrage', u'3'),(u'terr_t_NuclearStrike', u'4'),\
        (u'shan_u_NaninteSwarm', u'3'), (u'shan_t_CorruptTransform', u'3'), (u'shan_u_ParasiticThrall', u'5'), (u'shan_t_Infestation', u'2')]
>>> boosterpack = BoosterGenerator(cards)
>>> print (boosterpack.generate())
Package: booster-pytorch
BoosterA lightweight library to ease the training and the debugging of deep neural networks with PyTorch. Data structures and paradigms.Data StructuresDiagnosticA two level dictionary structure to store the model diagnostics. Compatible with Tensorboard datastructure.Example:fromboosterimportDiagnosticdata={'loss':{'nll':[45.,58.],'kl':[22.,18.]},'info':{'batch_size':16,'runtime':0.01}}diagnostic=Diagnostic(data)AggregatorA module to compute the running average of the diagnostics.fromboosterimportAggregator,Diagnosticaggregator=Aggregator()...aggregator.initialize()forxindata_loader:data=optimization_step(model,data)aggregator.update(data)summmary=aggregator.data# summary is an instance of Diagnosticsummmary=summary.to('cpu')The output is a Diagnostic object and can easily be logged to Tensorboard.# log to tensorboardwriter=SummaryWriter(log_dir="...")summary.log(writer,global_step)EvaluatorThe Evaluator computes a forward pass through the model, the loss and additional Diagnostics.frombooster.evaluationimportClassificationmodel=Classifier()evaluator=Classification(categories=10)# evaluate modeldata=next(iter(loader))loss,diagnostics,output=evaluator(model,data)Pipeline: model + evaluatorThe pipeline fuses the model forward pass with the evaluator and can be wrapped into a custom Dataparallel class that handles the diagnostics.fromboosterimportPipeline,DataParallelPipeline# fuse model + evaluatorpipeline=Pipeline(model,evaluator)# wrap as DataParallelparallel_pipeline=DataParallelPipeline(pipeline,device_ids=device_ids)# evaluate model on multiple devices and gather loss and diagnosticsdata=next(iter(loader))loss,diagnostics,output=parallel_pipeline(data)
Package: boost-loss
Boost LossUtilities for easy use of custom losses in CatBoost, LightGBM, XGBoost. This sounds very simple, but in reality it took a lot of work.InstallationInstall this via pip (or your favourite package manager):pipinstallboost-lossUsageBasic Usageimportnumpyasnpfromboost_lossimportLossBasefromnumpy.typingimportNDArrayclassL2Loss(LossBase):defloss(self,y_true:NDArray,y_pred:NDArray)->NDArray:return(y_true-y_pred)**2/2defgrad(self,y_true:NDArray,y_pred:NDArray)->NDArray:# dL/dy_predreturn-(y_true-y_pred)defhess(self,y_true:NDArray,y_pred:NDArray)->NDArray:# d^2L/dy_pred^2returnnp.ones_like(y_true)importlightgbmaslgbfromboost_lossimportapply_custom_lossfromsklearn.datasetsimportload_bostonX,y=load_boston(return_X_y=True)apply_custom_loss(lgb.LGBMRegressor(),L2Loss()).fit(X,y)Built-in losses are available. [^bokbokbok]fromboost_loss.regressionimportLogCoshLosstorch.autogradLoss [^autograd]importtorchfromboost_loss.torchimportTorchLossBaseclassL2LossTorch(TorchLossBase):defloss_torch(self,y_true:torch.Tensor,y_pred:torch.Tensor)->torch.Tensor:return(y_true-y_pred)**2/2Contributors ✨Thanks goes to these wonderful people (emoji key):34j💻🤔📖This project follows theall-contributorsspecification. Contributions of any kind welcome![^bokbokbok]: Inspired byorchardbirds/bokbokbok[^autograd]: Inspired byTomerRonen34/treeboost_autograd
Package: boostmpi
NoteI’ve mostly discontinued maintenance of this package. It turns out mpi4py is a far better and more capable MPI wrapper. In the medium to short term, I would suggest switching any code depending on boostmpi to mpi4py.boostmpi is a high-quality Python wrapper around theMessage Passing Interface(MPI).
MPI is a standardized interface to libraries such asOpenMPIandMPICHthat provide high-performance inter-process communication
for distributed-memory computing.boostmpi uses theBoost.MPI library, which
gives MPI a very usable C++ interface.
This C++ interface is then made accessible to Python
via theBoost.Python library.boostmpi was originally distributed as part of theBoost C++ library. This separate
distribution aims to make the software more accessible.boostmpi (born as Boost.MPI.Python) was written byDoug Gregorand is currently maintained byAndreas Kloeckner
Package: boostng
boostng: :rocket: Scripts for speeding up development with angularYou can use boostng to generate a template Angular compnent entirely compatible to JHipster.In order to install the script runpipinstallboostngJust start the script in the parent/target directory:boostngYou will be asked to enter the components name. The name should be like this: parent-name (e.g. stock-list)Afterwards the script will generate the following content:├── name
│   ├── parent-name.component.html
│   ├── parent-name.component.css
│   ├── parent-name.component.ts
│   ├── parent-name.module.ts
│   ├── parent-name.route.ts
Package: boostnote-to-wordpress
Automatically upload images from boostnote and post markdown aricle to Wordpress.Usageupload2wp <your boostnote scon file> [<wordpress article status>]Installationpip install git+https://github.com/lepture/mistune-contrib
pip install boostnote_to_wordpressRequirementsWP REST API - OAuth 1.0a Serverwordpress_oauthCompatibilityLicenceAuthorsboostnote_to_wordpress was written byfx-kirin.
Package: boost_queue
Introduction============boost_queue.cpp contains a queue class which follows the API from Queue.Queue ofthe Python stdlib. The main difference is how the underlying locking is done. InPython-2.X Queue.Queue uses a busy loop in case of a blocking operation.This queue implementation uses condition variables from Boost to avoid the busyloop.boost_queue provides two methods not supported by the Queue from the stdlib.put_many(items, block=True, timeout=None)Instead of pushing a single item a list of items is pushed to the Queue atomicly.'items' needs to support __len__ and __iter__ for this call.If block equals 'True' the call blocks until enough free space is available toput all items at once.get_many(items, block=True, timeout=None)Instead of returning a single item a tuple of items is returned atomicly.Whereas 'items' is the  number of items this tuple should contain.If block equals 'True' the call blocks until enough items are in the Queue.The main usage of this calls are applications where the Queue is heavily used.concurrent_queue.hpp contains a Python independent C++ Queue.Changelog=========0.4.2 - December 29, 2012------------------------* Fix memory leak in get_many (Appears only if the timeout is reached)0.4.1 - October 09, 2012------------------------* Fix memory leak in get_many* Fix segfault if block and timeout are used0.4 - March 14, 2012--------------------* add a get_many method* add a put_many method0.3 - March 03, 2012--------------------* Fix a memory leak* Release the GIL less often. Now the GIL is only released if the queue needs to wait.In the versions before the GIL was released on *every* get/put operation which ledto a lot of unneeded context switches. This change leads to a significantperformance improvement if you work heavily on the queue.0.2 - February 27, 2012-----------------------Let boost_queue.Empty and boost_queue.Full exceptions inhert from Queue.Empty andQueue.Full. This allows other code to pass around the boost_queue.Queue object withouttoo many changes in old code.0.1 - February 02, 2012----------------------- Initial release
Package: boostsrl
boostsrlis a set of Python wrappers aroundBoostSRLwith a scikit-learn interface.Documentation:https://boostsrl.readthedocs.io/en/latest/Questions?ContactAlexander L. Hayes(hayesall)Getting StartedPrerequisites:Java 1.8Python (3.6, 3.7)InstallationpipinstallboostsrlBasic UsageThe general setup should be similar to scikit-learn. But there are a few extra requirements in terms of setting
background knowledge and formatting the data.A minimal working example (using the Toy-Cancer data set imported with ‘example_data’) is:>>>fromboostsrl.rdnimportRDN>>>fromboostsrlimportBackground>>>fromboostsrlimportexample_data>>>bk=Background(...modes=example_data.train.modes,...use_std_logic_variables=True,...)>>>clf=RDN(...background=bk,...target='cancer',...)>>>clf.fit(example_data.train)>>>clf.predict_proba(example_data.test)array([0.88079619,0.88079619,0.88079619,0.3075821,0.3075821])>>>clf.classes_array([1.,1.,1.,0.,0.])example_data.trainandexample_data.testare eachboostsrl.Databaseobjects, so this hides some of
the complexity behind the scenes.This example abstracts away some complexity in exchange for compactness.
For more thorough examples, see the‘docs/examples/’directory.ContributingWe have adopted theContributor Covenant Code of Conductversion 1.4. Please read,
follow, and report any incidents which violate this.Questions, Issues, and Pull Requests are welcome. Please refer toCONTRIBUTING.mdfor
information on submitting issues and pull requests.Versioning and ReleasesWe useSemVerfor versioning.
SeeReleasesfor stable versions that are available, or theProject Page on PyPi.
Package: boosty
Boosty WrapperTable of ContentsInstallationLicenseUsageInstallationpip install boostyLicenseboostyis distributed under the terms of theMITlicense.[!IMPORTANT]!WARNING! this version of library is very unstableIf you use it, contact maintainer to help make it stableUsageOptional:specifyIGNORE_MISSING_AND_EXTRA_FIELDSenvironment variable to disable strict schema validationOptional:fillauth.jsonfile with authentication data:{"access_token":"ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff","device_id":"ffffffff-ffff-ffff-ffff-ffffffffffff","expires_at":12345678900,"refresh_token":"ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff"}Example:fromboosty.apiimportAPIapi=API()response=awaitapi.get_post("boosty",post_id="c9fb8a19-c45e-4602-9942-087c3af28c1b")print(response.title)# 'Добро пожаловать на борт!'More examples inexamples/folderTODO for stable releaseapi schemaadd access levels logic for requestsminimal docsuseful properties for modelsmerge reply comment with comment modeladd examplesrender textget video urlget comment urladd testsboosty profilecommentsrepliesvideoentities parsing
Package: bootd
BootD(jango)=====================Wizard startproject from django base templateSetup---------```pip install bootd```Usage---------### Creating project```bootd-admin.py startproject <project_name>```> **NOTE:** shortcut from django-admin.py startproject --template=/PATH_TO_BOOTD/bootd/project_template PROJECT_NAMEUpcoming features---------- Initialize secrets.json from command-line.- Help setup database when using MySQL (create user, password and db for this project).
Package: bootdev
# BootDevCommand line tool to deploy auto-scaling architecture with chef DevOps management.## InstallThere are a few different ways you can install pyechonest:* Use setuptools: `easy_install -U pyechonest`* Download the zipfile from the [releases](https://github.com/echonest/pyechonest/releases) page and install it.* Checkout the source: `git clone git://github.com/echonest/pyechonest.git` and install it yourself.## Getting Started* Install Pyechonest* **Get an API key** - to use the Echo Nest API you need an Echo Nest API key.  You can get one for free at [developer.echonest.com](http://developer.echonest.com).* **Set the API** key - you can do this one of two ways:* set an environment variable named `ECHO_NEST_API_KEY` to your API key* Include this snippet of code at the beginning of your python scripts:```pythonfrom pyechonest import configconfig.ECHO_NEST_API_KEY="YOUR API KEY"```* Check out the [docs](http://echonest.github.com/pyechonest/) and examples below.## Examples*All examples assume you have already setup your api key!*Find artists that are similar to 'Bikini Kill':```pythonfrom pyechonest import artistbk = artist.Artist('bikini kill')print "Artists similar to: %s:" % (bk.name,)for similar_artist in bk.similar: print "\t%s" % (similar_artist.name,)```Search for artist:```pythonfrom pyechonest import artistweezer_results = artist.search(name='weezer')weezer = weezer_results[0]weezer_blogs = weezer.blogsprint 'Blogs about weezer:', [blog.get('url') for blog in weezer_blogs]```Get an artist by name:```pythonfrom pyechonest import artista = artist.Artist('lady gaga')print a.id```Get an artist by Musicbrainz ID:```pythonfrom pyechonest import artista = artist.Artist('musicbrainz:artist:a74b1b7f-71a5-4011-9441-d0b5e4122711')print a.name```Get the top hottt artists:```pythonfrom pyechonest import artistfor hottt_artist in artist.top_hottt():print hottt_artist.name, hottt_artist.hotttnesss```Search for songs:```pythonfrom pyechonest import songrkp_results = song.search(artist='radiohead', title='karma police')karma_police = rkp_results[0]print karma_police.artist_locationprint 'tempo:',karma_police.audio_summary['tempo'],'duration:',karma_police.audio_summary['duration']```Get a song's audio_url and analysis_url:```pythonfrom pyechonest import songss_results = song.search(artist='the national', title='slow show', buckets=['id:7digital-US', 'tracks'], limit=True)slow_show = ss_results[0]ss_tracks = slow_show.get_tracks('7digital-US')print ss_tracks[0].get('preview_url')```-![alt text](http://i.imgur.com/WWLYo.gif "Frustrated cat can't believe this is the 12th time he's clicked on an auto-linked README.md URL")
Package: bootils
It is comprised of abootilsPython package with building blocks
for process and resource management, and a CLI tool namednannythat
watches your child process after starting, until it grows up
into a stable running state.Copyright ©  2015 1&1 Group <jh@web.de>Licensed 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.