Saravanan666/pypi-org huggingface dataset:
Package: bundle-app
This python package builds a macOS Application bundle for
a python/tkinter app.  It embeds the frameworks built by
the 3-manifolds frameworks project within the app.To get started, by building a simple example app, run
this command:python3 -m bundle_app.init SillyThis will create a directory named silly which serves
as a development directory for the app.  In particular,
the script main.py is what runs your app.  To create your
silly app, do:cd silly
python3 -m bundle_app.buildWhen you build your real app you will want to replace
the icon file with one designed for your app and edit
main.py so that it runs your app.  You may create a
Requirements.txt file in the development directory to
specify pypi packages which should be installed within
the embedded python framework.  You may also edit
info.toml and the sdef file to suit your needs.To add pypi packages to your app, add a standard
requirements.txt file to the development directory
and run:python3 -m bundle_app.add_packagesTo remove unnecessary components and reduce the size
of your app bundle, first edit the file superfluous.txt
and then run:python3 -m bundle_app.streamline
Package: bundle-celery
Version:2.5ContentsThis bundle installs the following packages:['celery>=2.5,<3.0', 'django-celery>=2.5,<3.0',
 'Flask-Celery>=2.5,<3.0', 'django',
 'setproctitle', 'celerymon', 'cyme',
 'kombu-sqlalchemy', 'django-kombu']What is this?This is a bundle of several packages that you can use as a shortcut in the
requirements lists of your applications.  Bundles are used to follow a
common group of packages, or a package with an optional extension feature.You can install all of the packages in this bundle by,using pip:$ pip install -U bundle-celeryorusing easy_install:$ easy_install -U bundle-celeryOr if you want to add this bundle as a dependency in your application, you
can add the following identifier in yoursetup.py’s requires list or
in your pip requirements files:bundle-celeryYou can also specify a specific version:bundle-celery>=2.5
Package: bundleman
BundleMan try to manage releasing of application built on versioned products
under subversion.An application is seen as a products suite defined using subversion
svn:externals property. An application is a bundle of products. Products are
versioned piece of software.Releasing an application is about taking care of tagging the source
repository, managing version of each products, managing CHANGELOGs, creating
a source package archive, giving ways to maitain a release without blocking
the trunk development.Main features:BundleMan is free software distributed under the GNU GPL.It uses a recommended trunk/branches/tags repository layouts for
products and bundles.It uses standard versioning MAJOR.MINOR.BUGFIX-RELEASE for products.Versioning of products is done automaticly by analysing a CHANGES file.Enforce CHANGELOG quality by requiring a product CHANGES file.It generates an application CHANGELOG.There is no locking of the trunk or version’s conflict when patching a
released application.Can manage public, private or remote products.BundleMan is written in python and can be easily customized.
Package: bundler.py
bundler.pyA simple tool for packing shippable virtualenvsbundler.py bundle [-h] [--output OUTPUT] [--compression {gz,bz2,xz} | --gz | --bz2 | --xz] [venv]Bundle a virtualenv folder into a tarball, ready for caching or shipping between environmentsOutput files are just compressed tar files, with an additional metadata file (currently unused, but
intended for future validation post-unpacking)bundler.py unpack [-h] [--shebang SHEBANG] [--python PYTHON] [--no-repair] bundle_path [output]Unpack and optionally repair a bundle into a usable virtualenvbundler.py repair [-h] [--shebang SHEBANG] [--python PYTHON] pathRepair a virtualenv, rewritingvenv/binscript shebangs, and updatingbin/pythonsymlinks to point
to the correct path.Future versions will inspect shebangs before rewriting, so as not to break potential shell scripts
and other files that get stuck invenv/binDevelopmentThis project uses poetry for development dependency management, although it's not strictly necessary.py.testis used for testing,flakeheavenfor linting, andblackfor formatting.
Package: bundlewrap
By allowing for easy and low-overhead config management, BundleWrap fills the gap between complex deployments using Chef or Puppet and old school system administration over SSH.
While most other config management systems rely on a client-server architecture, BundleWrap works off a repository cloned to your local machine. It then automates the process of SSHing into your servers and making sure everything is configured the way it’s supposed to be. You won’t have to install anything on managed servers.
Package: bundlewrap-keepass
Use secrets fromkeepassin yourBundleWraprepo.Installationpip install bundlewrap-keepassSetupCreate.bw_keepass.cfgin your home. It should contain two lines: First
line should contain a path to your keepass file, second line may contain
your password.If you're not comfortable putting your password into a plain-text file,
you may also useBW_KEEPASS_PASSWORDin your environment variables.You may also setBW_KEEPASS_FILEin your environment to overwrite the
location of your keepass file. Please note that if you set the file path
in your environment, youmustalso set the password.UsageAll function calls accept lists or strings as their arguments. If you
need to traverse into subdirectories in your keepass file, you have to
use|as separator when not using lists.For example, if you want to access the Password for 'mysite', which is
located inside the directory 'bundlewrap', you can use either one of
these:bwkeepass.password('bundlewrap|mysite')
bwkeepass.password(['bundlewrap', 'mysite'])Examplenodes.py:importbwkeepassaskeepassnodes={'somenode':{'metadata':{'my_secret':keepass.password('my_identifier'),},},}Available Fields/Methods are:bwkeepass.password()for passwordsbwkeepass.username()for usernamesbwkeepass.url()for urlsbwkeepass.notes()for notesNote: This will insert a proxy object into your metadata, the actual secret is not retrieved until you convert it to a string (e.g. by inserting it in a template or calling str() explicitly).© 2021Franziska Kunsmann
Package: bundlewrap-pass
Use secrets frompassin yourBundleWraprepo.Installationpip install bundlewrap-passSetupThere's no setup needed. Please note bundlewrap-pass will override yourPASSWORD_STORE_DIRto the content ofBW_PASS_DIR, which in turn will
default to~/.password-store. Keep this in mind if you want to use
a custom path to your passwordstore repo.usagebundlewrap-pass will use the first line ofpassoutput to get itspasswordattribute. You can also retrieve any other saved attributes,
as long as your pass entries conform to the format which browserpass uses:my_super_secure_password
custom_attribute: foo
another_attr: barYou can then retrieve those attributes using theattrmethod of
bundlewrap-pass.Examplenodes.py:importbwpassnodes={'somenode':{'metadata':{'my_secret':bwpass.password('my_identifier'),'my_custom_attr':bwpass.attr('my_identifier','custom_attribute'),},},}Note: This will insert a proxy object into your metadata, the actual secret is not retrieved until you convert it to a string (e.g. by inserting it in a template or calling str() explicitly).© 2021Franziska Kunsmann
Package: bundling-score
This work is licensed under aCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.Bundling scoreSmall utility to extract the bundling score from actomyosin network images.InstallationWith pipDownload the packagegit clonehttps://gitlab.college-de-france.fr/gdelabbey/bundling_score.gitInstall with pippython3 -m pip install bundling_score/With condaOpen Anaconda PromptInstall git and pipconda install -c anaconda gitconda install pipDownload and install the packagegit clonehttps://gitlab.college-de-france.fr/gdelabbey/bundling_score.gitpip install bundling_score/ExamplesTwo examples are available in theexamplesdirectory.
Package: bunga
BungaControl and monitor your system.Project homepage:https://github.com/eerimoq/bungaInstallation$pipinstallbungaThe shell subcommandConnect to your system (in this case theMonolinux example project)
and execute thedfcommand.The log subcommandStream logs from your system to your PC.The plot subcommandPlot any command output over time. The plot below shows the CPU load.$ bunga plot cpuPresshor?to show the help.Define plots in~/.bunga-plot.json.{"cpu":{"title":"CPU [%]","command":"cat proc/stat","pattern":"cpu\\s+\\d+\\s+\\d+\\s+\\d+\\s+(\\d+)","algorithm":"delta","interval":2,"timespan":60"scale":-1,"offset":100,"y-min":0,"y-max":100},"uptime":{"title":"Uptime [s]","command":"cat proc/uptime","max-age":600}}The execute subcommandExecute given command,lsin the example below, and print its
output.$ bunga execute ls
mnt etc proc init root devThe get_file subcommandGet a file from your system.$ bunga get_file README.rst
100%|█████████████████████████████████████| 1.19k/1.19k [00:00<00:00, 74.1kB/s]The put_file subcommandPut a file on your system.$ bunga put_file README.rst
100%|█████████████████████████████████████| 1.19k/1.19k [00:00<00:00, 24.1kB/s]
Package: bungio
BungIOBungIO is a modern and pythonic wrapper for Bungies Destiny 2 API.Python 3.10+Asynchronous100% typed and raw api coverageRatelimit compliantManifest supportOAuth2 supportEasily used in combination with other libraries like FastApiClickhereto get started or visit
theguidesorapi reference.Basic ExampleimportasyncioimportosfrombungioimportClientfrombungio.modelsimportBungieMembershipType,DestinyActivityModeType,DestinyUser# create the client obj with our bungie authenticationclient=Client(bungie_client_id=os.getenv("bungie_client_id"),bungie_client_secret=os.getenv("bungie_client_secret"),bungie_token=os.getenv("bungie_token"),)asyncdefmain():# create a user obj using a known bungie iduser=DestinyUser(membership_id=4611686018467765462,membership_type=BungieMembershipType.TIGER_STEAM)# iterate thought the raids that user has playedasyncforactivityinuser.yield_activity_history(mode=DestinyActivityModeType.RAID):# print the date of the activityprint(activity.period)# bungio is by nature asynchronous, it can only be run in an asynchronous contextasyncio.run(main())
Package: bunit
A dead simple binary unit conversion tool.UsageHereinafter are few examples of how to use this tool.Converting between two unitsecho "1024" | bunit --in=kiB --out=MiB
1.0echo "128" | bunit --in=b --out=B
16Converting between units of the same systemecho "32" | bunit --in=GiB
+------+-------------+
| Unit |    Value    |
+------+-------------+
| kiB  | 33554432.00 |
| MiB  |   32768.00  |
| GiB  |    32.00    |
| TiB  |     0.03    |
| PiB  |     0.00    |
| EiB  |     0.00    |
| ZiB  |     0.00    |
| YiB  |     0.00    |
+------+-------------+Converting between units of different systemsecho "1" | bunit --in=GiB --system=bytes
+------+---------------+
| Unit |     Value     |
+------+---------------+
|  B   | 1073741824.00 |
|  kB  |   1073741.82  |
|  MB  |    1073.74    |
|  GB  |      1.07     |
|  TB  |      0.00     |
|  PB  |      0.00     |
|  EB  |      0.00     |
|  ZB  |      0.00     |
|  YB  |      0.00     |
+------+---------------+
Package: bunkai
BunkaiBunkai is a sentence boundary (SB) disambiguation tool for Japanese texts.Bunkaiは日本語文境界判定器です．Quick StartInstall$pipinstall-UbunkaiDisambiguation without Models$echo-e'宿を予約しました♪!まだ2ヶ月も先だけど。早すぎかな(笑)楽しみです★\n2文書目の先頭行です。▁改行はU+2581で表現します。'\|bunkai宿を予約しました♪!│まだ2ヶ月も先だけど。│早すぎかな(笑)│楽しみです★2文書目の先頭行です。▁│改行はU+2581で表現します。Feed a document as one line by using▁(U+2581) for line breaks.1行は1つの文書を表します．文書中の改行は▁(U+2581) で与えてください．The output shows sentence boundaries with│(U+2502).出力では文境界は│(U+2502) で表示されます．Disambiguation for Line Breaks with a ModelIf you want to disambiguate sentence boundaries for line breaks, please add a--modeloption with the path to the model.改行記号に対しても文境界判定を行いたい場合は，--modelオプションを与える必要があります．First, please install extras to use--modeloption.--modelオプションを利用するために、まずextraパッケージをインストールしてください．$pipinstall-U'bunkai[lb]'Second, please setup a model. It will take some time.次にモデルをセットアップする必要があります．セットアップには少々時間がかかります．$bunkai--modelbunkai-model-directory--setupThen, please designate the directory.そしてモデルを指定して動かしてください．$echo-e"文の途中で改行を▁入れる文章ってありますよね▁それも対象です。"|bunkai--modelbunkai-model-directory文の途中で改行を▁入れる文章ってありますよね▁│それも対象です。Morphological Analysis ResultYou can get morphological analysis results with--maoption.--maオプションを付与すると形態素解析結果が得られます．$echo-e'形態素解析し▁ます。結果を 表示します！'|bunkai--ma形態素	名詞,一般,*,*,*,*,形態素,ケイタイソ,ケイタイソ解析	名詞,サ変接続,*,*,*,*,解析,カイセキ,カイセキし	動詞,自立,*,*,サ変・スル,連用形,する,シ,シ▁EOSます	助動詞,*,*,*,特殊・マス,基本形,ます,マス,マス。	記号,句点,*,*,*,*,。,。,。EOS結果	名詞,副詞可能,*,*,*,*,結果,ケッカ,ケッカを	助詞,格助詞,一般,*,*,*,を,ヲ,ヲ記号,空白,*,*,*,*, ,*,*表示	名詞,サ変接続,*,*,*,*,表示,ヒョウジ,ヒョージし	動詞,自立,*,*,サ変・スル,連用形,する,シ,シます	助動詞,*,*,*,特殊・マス,基本形,ます,マス,マス！	記号,一般,*,*,*,*,！,！,！EOSPython LibraryYou can also use Bunkai as Python library.BunkaiはPythonライブラリとしても使えます．frombunkaiimportBunkaibunkai=Bunkai()forsentenceinbunkai("はい。このようにpythonライブラリとしても使えます！"):print(sentence)For more information, seeexamples.ほかの例はexamplesをご覧ください．DocumentsDocumentsReferencesYuta Hayashibe and Kensuke Mitsuzawa.
Sentence Boundary Detection on Line Breaks in Japanese.
Proceedings of The 6th Workshop on Noisy User-generated Text (W-NUT 2020), pp.71-75.
November 2020.[PDF][bib]LicenseApache License 2.0
Package: bunker
openapi-clientAn OpenAPI specification for Bunker ServiceThis Python package is automatically generated by theOpenAPI Generatorproject:API version: 0.1.1Package version: 1.0.0Build package: org.openapitools.codegen.languages.PythonClientCodegenRequirements.Python 2.7 and 3.4+Installation & Usagepip installIf the python package is hosted on Github, you can install directly from Githubpipinstallgit+https://github.com/GIT_USER_ID/GIT_REPO_ID.git(you may need to runpipwith root permission:sudo pip install git+https://github.com/GIT_USER_ID/GIT_REPO_ID.git)Then import the package:importopenapi_clientSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importopenapi_clientGetting StartedPlease follow theinstallation procedureand then run the following:from__future__importprint_functionimporttimeimportopenapi_clientfromopenapi_client.restimportApiExceptionfrompprintimportpprint# create an instance of the API classapi_instance=openapi_client.BunkerApi(openapi_client.ApiClient(configuration))person=openapi_client.Person()# Person | The user to create (optional)try:api_response=api_instance.create_person(person=person)pprint(api_response)exceptApiExceptionase:print("Exception when calling BunkerApi->create_person:%s\n"%e)Documentation for API EndpointsAll URIs are relative tohttp://localhost:8080/v1ClassMethodHTTP requestDescriptionBunkerApicreate_personPOST/personsBunkerApidelete_documentDELETE/persons/{person_id}/documents/{document_id}BunkerApidelete_faceDELETE/persons/{person_id}/faces/{face_id}BunkerApidelete_personDELETE/persons/{person_id}BunkerApidelete_scanDELETE/persons/{person_id}/scans/{scan_id}BunkerApiget_documentGET/persons/{person_id}/documents/{document_id}BunkerApiget_faceGET/persons/{person_id}/faces/{face_id}BunkerApiget_personGET/persons/{person_id}BunkerApiget_scanGET/persons/{person_id}/scans/{scan_id}BunkerApirequest_scanPOST/persons/{person_id}/scans/BunkerApiupload_documentPOST/persons/{person_id}/documents/BunkerApiupload_facePOST/persons/{person_id}/faces/Documentation For ModelsDocumentErrorMessageFacePersonScanDocumentation For AuthorizationApiKeyAuthType: API keyAPI key parameter name: apikeyLocation: HTTP headerAuthor
Package: bunnet
The logo is generated byWOMBO DreamOverviewBunnet- is a Python object-document mapper (ODM) for MongoDB. It is a synchronous fork ofBeanie ODM.When using Bunnet each database collection has a correspondingDocumentthat
is used to interact with that collection. In addition to retrieving data,
Bunnet allows you to add, update, or delete documents from the collection as
well.Bunnet saves you time by removing boilerplate code, and it helps you focus on
the parts of your app that actually matter.InstallationPIPpipinstallbunnetPoetrypoetryaddbunnetExamplefromtypingimportOptionalfrompymongoimportMongoClientfrompydanticimportBaseModelfrombunnetimportDocument,Indexed,init_bunnetclassCategory(BaseModel):name:strdescription:strclassProduct(Document):name:str# You can use normal types just like in pydanticdescription:Optional[str]=Noneprice:Indexed(float)# You can also specify that a field should correspond to an indexcategory:Category# You can include pydantic models as well# Bunnet uses Pymongo client under the hoodclient=MongoClient("mongodb://user:pass@host:27017")# Initialize bunnet with the Product document classinit_bunnet(database=client.db_name,document_models=[Product])chocolate=Category(name="Chocolate",description="A preparation of roasted and ground cacao seeds.")# Bunnet documents work just like pydantic modelstonybar=Product(name="Tony's",price=5.95,category=chocolate)# And can be inserted into the databasetonybar.insert()# You can find documents with pythonic syntaxproduct=Product.find_one(Product.price<10).run()# And update themproduct.set({Product.name:"Gold bar"})LinksDocumentationDoc- Tutorial, API documentation, and development guidelines.ResourcesGitHub- GitHub page of the
projectChangelog- list of all
the valuable changesDiscord- ask your questions, share
ideas or just sayHello!!Supported byJetBrains
Package: bunnymq
BunnyMQSimple messaging with RabbitMQ and Python.Head over to thetutorialto get started.This is a small library inspired by the Python standard libraryqueuemodule and thehotqueuelibrary. Primarily geared towards programmer happiness :slightly_smiling_face:Basic Usage:>>>queue=Queue('test')>>>queue.put(1)>>>queue.put('hello',priority=8)>>>queue.put({'a':1})>>>queue.get()'hello'>>>queue.task_done()>>>queue.get()1>>>queue.requeue()Iterating over a queue indefinitely, waiting if nothing is available:>>>foriteminqueue:...print(item)...queue.task_done()FeaturesSimple usageAutomatic serialization and deserialization of Python objectsAdding custom serializers or turning serialization off is trivialAutomatic retry while publishingAutomatic handling of connection failures while consumingEasy parallelization by starting multiple workers to share the load.Installpip install bunnymqRequirementsPython 3.6+RabbitMQ serverPika
Package: bunnyplot
bunnyplotA utility for producting GraphML graphs and other visualizations of RabbitMQUsage% bunnyplot --help
Usage: bunnyplot [OPTIONS] URL OUTPUT_PATH

Options:
  -u, --username TEXT
  -p, --password TEXT
  --help               Show this message and exit.Usage with yEdBy default, yEd will not recognize node labels or properties. These must be mapped using the Properties Mapper(Edit > Properties Mapper...).bunnyplot provides a preset for mapping properties.bunnyplot.cnfx. Import this to your properties mapper and apply the changes. You should see the nodes change size, shape and colour.You may also need to rearrange them into a better layout. Use theLayoutmenu to select a type e.g.Organicand apply.DevelopmentThis project uses pipenv to manage it'sdevelopmentenvironment.Development dependencies should be specified insetup.py. Package dependencies should not change in the Pipfile.Code should be formatted withblack. Use the pipenv scriptformat-checkandformatto check and format code, respectively.
Package: bunq
Python wrapper for thebunq API.InstallationThis package has been tested with Python 3.6.0, but probably works fine with 3.3 and later.
Python 2.6 and later should also work, but no guarantees.To install, usesetuptools, run:python ./setup.py installor for installing locally for the user:python ./setup.py install--userThere is no PyPI package as of yet.UsageThe module is a thin wrapper around the bunq API and takes care of the following:setting the required HTTP headerssigning of the outgoing messageverification of the response (still very limited)The code is blissfully unaware of the API endpoints and the data they need and return.
You will need the bunq API documentation to figure out all the endpoints and required parameters and possible responses.After installation this module is called simply bunq. You will probably want to import it like:from bunq import APIand instantiate and API object like so:my_api_instance = API(private_key, token)There are several examples in theexamplesdirectory to give you an idea how this module can be used.DocumentationThe code itself is documented with docstrings.External documentation will be coming ASAP.TODOtestsbetter verification of responseautomated session creationuse a more lightweight crypto library, likehttps://github.com/sybrenstuvel/python-rsaactive session awarenesstesting validity of tokendeal with rsa key encryptionautomagically retrieve server public key when not givenAttributionAll code is licensed under the MIT License. SeeLICENSE.python3-krakenexwas a big inspiration.
Package: bunqclient
# bunqclientPython client for the bunq public API![Code Climate](https://codeclimate.com/github/bartbroere/bunqclient.svg)![BCH compliance](https://bettercodehub.com/edge/badge/bartbroere/bunqclient?branch=master)![Release](https://img.shields.io/pypi/v/bunqclient.svg)![Licence](https://img.shields.io/pypi/l/bunqclient.svg)![Versions](https://img.shields.io/pypi/pyversions/bunqclient.svg)## InstallationInstalling the latest release can be done from PyPi:```pip install bunqclient```The latest unreleased version can be installed from GitHub:```git clone https://github.com/bartbroere/bunqclient/cd ./bunqclientpython setup.py install```## UsageBefore using it, make sure that you understand the cost scheme of this API.Replace the value of the parameter ``secret`` with the API key generated inthe bunq app.```pythonfrom bunqclient import BunqClientbunq = BunqClient(secret="")```To use the sandbox version change the ``base`` parameter. Note that you shoulduse a separate API key for this. A sandbox key can be acquired by asking bunqsupport.```pythonfrom bunqclient import BunqClientbunq_sandbox = BunqClient(base="https://sandbox.public.api.bunq.com/v1",secret="")`````LIST`` requests are basically ``GET`` requests without a specified key. Thefirst two API calls have the same effect. The third requests a specific``monetary-account``. Due to the way Python interprets variable names, dashes(``-``) in API methods and keys should be replaced with underscores (``_``).```pythonbunq.request(method="LIST", monetary_account="", user=1)bunq.request(method="GET", monetary_account="", user=1)bunq.request(method="GET", monetary_account=11, user=1)```These API calls return a python dictionary with the query's result.## ContributingTo report bugs and submit feature requests, please open an issue on GitHub.Pull requests that resolve issues or TODO's are also greatly appreciated.
Package: bunting
Bunting Python SDKBunting Lab's Python SDK allows you to use theBunting Labs geospatial APIsin your own libraries.Installation$pipinstallbuntingExampleimportBuntingClientfrombunting# Get your API key from https://buntinglabs.com/account/registerbc=BuntingClient('gK6vkrFQXiU9')# Download from openstreetmaphighways=bc.osm.extract('leisure=park',bbox=(5.976563,52.449314,6.245728,52.562995))# Get as GeoDataFramehighways.as_gdf()