Saravanan666/pypi-org huggingface dataset:
Package: blacktip
BlacktipToolkit for financial analysis. Current tools include: Angler.Angler:Easy-to-use large scale analysis tool for United Stated public fundamentals (aggregated from SEC Edgar).
Examine any company that files with the SEC in seconds without having
to download data locally! Registerherebeforehand to be able to use Angler. See below for more details.Full Toolkit DocumentationAnglerOur main SEC analysis tool. After registering your account on theBlacktip Research website, use yourusernameandpasswordto interface with Angler.UsageThe workflow is the following:importfrom blacktip.angler import Anglerinitializeinstance = Angler(username, password)get dataform10K = instance.query10K("AAPL", 2019)manipulate the data# example calculations
debt_sheet = form10K.debt_sheet()
ROE = form10K.calc_ROE()
net_income = form10K.filter(regex="^NetIncomeLoss$")close your instanceinstance.dispose()For explicit documentation, visit theAngler Documentation.
Package: black-tortoise
black_tortoise 项目介绍项目背景待完善项目结构源码查看项目结构 tree 方法tree-I"venv|__pycache__|*.pyc|*.pyo|*.so|*.egg-info|*.egg|*.log|*.txt|*.md|*.json|*.yaml|*.yml|*.ini|*.cfg|*.conf|*.xml|*.html|*.rst|*.rst.txt|*.rst"项目结构说明black_tortoise|dosc
│└──deployment--发布相关文档介绍├──mock_data--mock数据
│├──__init__.py
│└──user
│└──__init__.py
├──setup.py--项目打包配置文件
├──tests--测试用例
│└──__init__.py
└──utils--工具类├──FileUtils.py├──__init__.py└──logger.py
Package: blackvue-acc
![BCH compliance](https://bettercodehub.com/edge/badge/bartbroere/blackvue-acc?branch=master)![Release](https://img.shields.io/pypi/v/blackvue-acc.svg)![Pre-release](https://img.shields.io/github/release/bartbroere/blackvue-acc/all.svg)![Licence](https://img.shields.io/pypi/l/blackvue-acc.svg)![Versions](https://img.shields.io/pypi/pyversions/blackvue-acc.svg)# blackvue_accGet accelerometer records out of BlackVue video. Currently outputs CSV files,with support for more formats added later.Get it:``pip install blackvue_acc`````Usage:blackvue_acc --to-csv <filename>```
Package: blackvue-gps
![BCH compliance](https://bettercodehub.com/edge/badge/bartbroere/blackvue-gps?branch=master)![Release](https://img.shields.io/pypi/v/blackvue-gps.svg)![Pre-release](https://img.shields.io/github/release/bartbroere/blackvue-gps/all.svg)![Licence](https://img.shields.io/pypi/l/blackvue-gps.svg)![Versions](https://img.shields.io/pypi/pyversions/blackvue-gps.svg)# blackvue_gpsGet GPS records out of BlackVue video. Currently outputs CSV files, withsupport for more formats added later.Get it:``pip install blackvue_gps`````Usage:blackvue_gps --to-csv <filename>```
Package: blackvue-wifi
![BCH compliance](https://bettercodehub.com/edge/badge/bartbroere/blackvue-wifi?branch=master)![Release](https://img.shields.io/pypi/v/blackvue-wifi.svg)![Pre-release](https://img.shields.io/github/release/bartbroere/blackvue-wifi/all.svg)![Licence](https://img.shields.io/pypi/l/blackvue-wifi.svg)![Versions](https://img.shields.io/pypi/pyversions/blackvue-wifi.svg)# blackvue-wifiInteract with the HTTP API of a connected BlackVue dashcam over WiFiGet it:``pip install blackvue_wifi`````Usage:blackvue_wifi --download-all-recordings <foldername>blackvue_wifi --download-missing-recordings [--continuously] <foldername>```
Package: blackwidow
Visualizing Python Project Import GraphsInstallation:sudo pip install blackwidowDemo with:python -m blackwidow.web [package_name]Optionally pass in a list of file patterns to excludepython -m blackwidow.web [package_name] --exclude *test*Once the visualization is displayed, you can inspect file names by
hovering over a node.Sample results:Requests:Flask:BlackWidow:
Package: blacs
thelabscript suite» blacsGraphical interface to scientific instruments and experiment supervisionblacssupervises the execution of experiments controlled by thelabscript suite. It manages experiment queuing and hardware-timed execution, and provides manual control over devices between experiment shots.Installationblacs is distributed as a Python package onPyPIandAnaconda Cloud, and should be installed with other components of thelabscript suite. Please see theinstallation guidefor details.
Package: blade
bladeis a powerful set of iterable processing tools extracted fromknifefor standalone use.Vitalsbladeworks with CPython 2.6, 2.7, 3.2,and 3.3 and PyPy 1.8 and 1.9.bladedocumentation is found athttp://packages.python.org/blade/InstallationInstallbladewithpip…:$ pip install blade
[... possibly exciting stuff happening ...]
Successfully installed blade…oreasy_install…:$ easy_install blade
[... possibly exciting stuff happening ...]
Finished processing dependencies for blade…or old school by downloadingbladefromhttp://pypi.python.org/pypi/blade/:$ python setup.py install
[... possibly exciting stuff happening ...]
Finished processing dependencies for bladeDevelopmentPublic repository:https://bitbucket.org/lcrees/blade.Mirror:https://github.com/lcrees/blade/Issue tracker:https://bitbucket.org/lcrees/blade/issuesLicense:BSD
Package: blade2blade
Blade2BladeEvil Sharpens Good.Developed By: The LAION-AI Safety Team|Quick Start|Installation|More about blade2blade|Quick Start :fire:fromblade2bladeimportBlade2Bladeblade=Blade2Blade("shahules786/blade2blade-t5-base")prompt="|prompter| I'm here to test your blade|endoftext|"blade.predict(prompt)InstallationWith Pypipipinstallblade2bladeFrom sourcegit clone https://github.com/LAION-AI/blade2blade.git
cd blade2blade
pip install -e .What is Blade2Blade?Blade2Blade is a system that performs fully automated redteaming and blueteaming on any chat, or classifcation model. By using RL, we tune an adversarial user prompter to attack other models and create user prompts that promote dangerous responses from the attacked model. The attacked model is then optimized against the adversarial user prompter to preform automated blueteaming.Below shows an example of a Blade2Blade type system that attacks GoodT5 (the blueteam model). GoodT5 is a model that is designed to predict Rules of Thumb and safety labels. EvilT5 is a model designed to predict user prompts from the Rules of Thumb and safety labels given to it.What is redteaming and blueteaming?Both red teams and blue teams strive to increase security in a system, but they go about it in different ways. A red team simulates an attacker by looking for weaknesses and trying to get past a system's defences. When an incident occurs, a blue team answers and defends against attacks.What is the final goal of Blade2Blade?We want to make an easy to use package that will add automated redteaming and blueteaming to any existing training loop. By bringing down the requirements for redteaming and blueteaming we hope that companies and individuals will strive to include this in their systems and create safer LLMs.
Package: bladerf-sdr-aio
BladeRF SDR asynchronous wrapperA python wrapper for the bladerf python bindings fromNuand. It provides synchronous as well as asynchronous functionality to send and receive data to and from the BladeRF SDR.InstallationTo install the requirements for this package:python3 -m pip install -r requirements.txtTo install system-wide:sudo python3 setup.py installTo install for your user:python3 setup.py installUsageBelow is an example of how to use the asynchronous wrapper with a python context manager and an asynchronous generator
to continuously receive samples from the SDR for 5 seconds.importasyncioimportbladerffrombladerfsdraioimportAioBladeRFasyncdefmain():withAioBladeRF()assdr:ch_rx=sdr.Channel(bladerf.CHANNEL_RX(0))ch_rx.sample_rate=1e6ch_rx.frequency=1e9asyncdefstream_samples(sdr:AioBladeRF):asyncforsamplesinsdr.stream_samples_async(ch_rx,chunk_size=1024):# .. handle samplesprint(samples.max())asyncdefcancel_after(secs:float,sdr:AioBladeRF):awaitasyncio.sleep(secs)sdr.cancel_receive()awaitasyncio.gather(stream_samples(sdr),cancel_after(5,sdr))if__name__=='__main__':asyncio.run(main())
Package: blades
Installationgitclonehttps://github.com/lishenghui/bladescdbladespipinstall-v-e.# "-v" means verbose, or more output
# "-e" means installing a project in editable mode,
# thus any local modifications made to the code will take effect without reinstallation.cdblades/bladespythontrain.pyfile./tuned_examples/fedsgd_cnn_fashion_mnist.yamlBladesinternally callsray.tune; therefore, the experimental results are output to its default directory:~/ray_results.Experiment ResultsCluster DeploymentTo runbladeson a cluster, you only need to deployRay clusteraccording to theofficial guide.Built-in ImplementationsIn detail, the following strategies are currently implemented:Data Partitioners:Dirichlet PartitionerSharding PartitionerCitationPlease cite ourpaper(and the respective papers of the methods used) if you use this code in your own work:@article{li2023blades,
  title={Blades: A Unified Benchmark Suite for Byzantine Attacks and Defenses in Federated Learning},
  author= {Li, Shenghui and Ju, Li and Zhang, Tianru and Ngai, Edith and Voigt, Thiemo},
  journal={arXiv preprint arXiv:2206.05359},
  year={2023}
}
Package: bladesight
This package contains utilities to help you follow along with the Bladesight tutorials.InstallationpipinstallbladesightUsageDatasetsAll the datasets used in the tutorials are hosted on AWS on a public S3 bucket. This package makes it seamless to download and use these datasets. First import the Datasets object.frombladesightimportDatasetsYou can list the available datasets by printing the using thelist_datasetsmethod.>>>print(Datasets.online_datasets)['bladesight-datasets/intro_to_btt/intro_to_btt_ch02']You can then load a dataset by selecting the dataset like you would have selected a dictionary key, just by using the 'data/' prefix:>>>my_dataset=Datasets['data/intro_to_btt/intro_to_btt_ch02']You can then load the table by selecting the table like you would have selected a dictionary key, just by using the 'table/' prefix:>>>df_proximity_probe=my_dataset['table/aluminium_blisk_1200_rpm']The datasets have been downloaded to your local machine. You can find them in the following directory:~/.bladesight/dataCitationsYou'll see an attribution every time you open a dataset. This attribution is a link to the dataset's citation.Uploading your dataIf you'd like your datasets to be accessible through this package, I'd be more than willing to convert it to the appropriate format and upload it.Please email me atdawie.diamond@bladesight.comto get the ball rolling.Functions and methodsI include all the functions that are used frequently throughout the tutorials in the bladesight package. This is to avoid cluttering the tutorials with code that is not relevant to the tutorial's objective.frombladesight.btt.triggering_criteriaimportthreshold_crossing_hysteresis_posLicenseThis project is licensed under the terms of the MIT license.
Package: blaeu
This is a set ofPythonprograms to start
distributed Internet measurements on the network ofRIPE Atlas
probes, and to analyze their results.For installation, you can use usual Python tools, for instance:pip3 install blaeu(On a Debian machine, the prerequitises are packages python3-pip,
python3-openssl, python3-dnspython, and python3-cymruwhois. This is only
if you install manually, otherwise pip3 will install the dependencies.)Usage requires a RIPE Atlas API key (which itself requires a RIPE
account), and RIPE Atlas credits. If you don’t have a RIPE account,register first. Once you have an account,create a key, grant it the right toschedule a new measurement, and put the key in~/.atlas/auth. If
you don’t have Atlas credits, host a probe,or become aLIRor ask a
friend.You can then use the four programs (-hwill give you a complete list
of their options):blaeu-reachtarget-IP-address(test reachability of the target,
likeping)blaeu-traceroutetarget-IP-address(liketraceroute)blaeu-resolvename(use the DNS to resolve the name)blaeu-certname(display the PKIX certificate)You may also be interested bymy article at RIPE
Labs.Blaeu requires Python 3.Note thatthe old
versionran on Python 2 but is no longer maintained. (It waspartially
documented at RIPE
Labs.)NameIt comes from thefamous Dutch
cartographer. The logo
of the project comes from his “Theatrum Orbis Terrarum” (seethe
source).Reference siteOn FramaGitAuthorStéphane Bortzmeyerstephane+frama@bortzmeyer.org
Package: blag
blagblag is a blog-aware, static site generator, written inPython.an example "deployment" can be foundhereonlinedocumentationis available onhttps://readthedocs.org.blag is named afterthe blag of the webcomic xkcd.FeaturesWrite content inMarkdownGood looking default theme:Theming support usingJinja2templatesGeneration of Atom feeds for blog contentFenced code blocks and syntax highlighting usingPygmentsIntegrated devserverAvailable onPyPIblag runs on Linux, Mac and Windows and requires Python >= 3.8Installblag is available onPyPI, you can install it via:$pipinstallblagOn Debian or Ubuntu, you can also just install the Debian package:$sudoaptitudeinstallblagQuickstart$pipinstallblag# 1. install blag$blagquickstart# 2. create a new site$vimcontent/hello-world.md# 3. create some content$blagbuild# 4. build the website
Package: blagues-api
BlaguesAPI PythonCe paquet Python fournit une interface simple pour intéragir avecBlagues API.Important :Ce paquet ne fournit que des méthodesasynchrones.InstallationVous pouvez simplement ajouter la dépendance à votre projet depuis PyPI :pip install blagues-apiUtilisationPour utiliser l'API, vous devez obtenir une clé gratuite sur le site officiel :https://www.blagues-api.fr/. Vous pourrez ensuite construire un objetBlaguesAPI:fromblagues_apiimportBlaguesAPIblagues=BlaguesAPI("VOTRE_TOKEN_ICI")Toutes les méthodes excepté count renverront un objetBlague, qui permet d'accéder aux différentes propriétés renvoyées par l'API :id,type,joke,answer. En cas d'erreur, vous recevrez une erreur du typeaiohttp.ClientResponseError.Les différents types de blagues peuvent être représentés au choix sous forme d'un string ou d'un objetBlagueType(exemple:BlagueType.GENERAL). La liste des types disponibles est notée dans sur le site officiel.Blague aléatoireawaitblagues.random()# Blague(id=108, type=<BlagueType.GLOBAL: 'global'>, joke="C'est l'histoire d'un poil. Avant, il était bien.", answer='Maintenant, il est pubien.')Il est possible de spécifier des catégories à exclure :awaitblagues.random(disallow=[BlagueType.LIMIT,BlagueType.BEAUF])# Avec des stringsawaitblagues.random(disallow=["limit","beauf"])Blague aléatoire catégoriséeawaitblagues.random_categorized(BlagueType.DEV)# Blague(id=430, type=<BlagueType.DEV: 'dev'>, joke='De quelle couleur sont tes yeux ?', answer='#1292f4 et toi ?')# Avec des stringsawaitblagues.random_categorized("dev")Blague par identifiantawaitblagues.from_id(20)# Blague(id=20, type=<BlagueType.GLOBAL: 'global'>, joke="Qu'est-ce qu'un chou au milieu de l'océan ?", answer='Un chou marin.')Nombre de blaguesawaitblagues.count()# CountJoke(count=1730)La méthode ci-dessus renverra un objetCountJoke, qui permet d'accéder a la propriété renvoyée par l'API :count. En cas d'erreur, vous recevrez une erreur du typeaiohttp.ClientResponseError.
Package: blah
This package is deprecated.Blah has been renamed toMayo. Please use the packagemayoinstead.The main use of Blah is being able to download repositories from a URI
that specifies what version control system (VCS) is being used:import blah

blah.fetch("git+https://github.com/mwilliamson/blah.git", "/tmp/blah")
print open("/tmp/blah/README.md").read()Blah can also be used as a script:blah fetch git+https://github.com/mwilliamson/blah.git /tmp/blahSpecific commits can be selected by appending a hash to the URI,
followed by the name of the commit:blah.fetch("git+https://github.com/mwilliamson/blah.git#74d69b4", "/tmp/blah")At the moment, git and hg URIs are supported.
Package: blake2b-py
blake2b-pyBlake2b hashing in Rust with Python bindings.Building/releasingTo build and publish a release, follow these steps:Bump the versionFirst, bump the package version with the included make target:makebumpversionbump=patchThe above invocation bumps the "patch" version of a semantic version number
("x" in "1.2.x").  Other valid version types are "major" and "minor".  The
version is bumped by modifying source files that contain the version number,
creating a new commit that includes those modifications, then tagging that
commit with the new version.  The new commit and tag are then pushed to the
upstream repository.Building & ReleasingPackages are build and distributed via Github Actions as soon as a tag is
pushed to the remote repository which is taken care of by the bumpversion command.DevelopingYou'll need to haveMaturininstalled on your machine.
Create a virtual environment, and then you can do:$pipinstallmaturin
$maturindevelopto install the dependencies. You may need to specify theMACOSX_DEPLOYMENT_TARGETenvironment variable to your version of MacOS.Run the testsRunningmake test_allwill run all the tests.
Package: blake3
blake3-pyPython bindings for theofficial Rust implementation of
BLAKE3, based onPyO3. These bindings expose all the features of
BLAKE3, including extendable output, keying, and multithreading. The basic API
matches that of Python's standardhashlibmodule.Examplesfromblake3importblake3# Hash some input all at once. The input can be bytes, a bytearray, or a memoryview.hash1=blake3(b"foobarbaz").digest()# Hash the same input incrementally.hasher=blake3()hasher.update(b"foo")hasher.update(b"bar")hasher.update(b"baz")hash2=hasher.digest()asserthash1==hash2# Hash the same input fluently.asserthash1==blake3(b"foo").update(b"bar").update(b"baz").digest()# Hexadecimal output.print("The hash of 'hello world' is",blake3(b"hello world").hexdigest())# Use the keyed hashing mode, which takes a 32-byte key.importsecretsrandom_key=secrets.token_bytes(32)message=b"a message to authenticate"mac=blake3(message,key=random_key).digest()# Use the key derivation mode, which takes a context string. Context strings# should be hardcoded, globally unique, and application-specific.context="blake3-py 2020-03-04 11:13:10 example context"key_material=b"usually at least 32 random bytes, not a password"derived_key=blake3(key_material,derive_key_context=context).digest()# Extendable output. The default digest size is 32 bytes.extended=blake3(b"foo").digest(length=100)assertextended[:32]==blake3(b"foo").digest()assertextended[75:100]==blake3(b"foo").digest(length=25,seek=75)# Hash a large input using multiple threads. Note that this can be slower for# inputs shorter than ~1 MB, and it's a good idea to benchmark it for your use# case on your platform.large_input=bytearray(1_000_000)hash_single=blake3(large_input).digest()hash_two=blake3(large_input,max_threads=2).digest()hash_many=blake3(large_input,max_threads=blake3.AUTO).digest()asserthash_single==hash_two==hash_many# Hash a file with multiple threads using memory mapping. This is what b3sum# does by default.file_hasher=blake3(max_threads=blake3.AUTO)file_hasher.update_mmap("/big/file.txt")file_hash=file_hasher.digest()# Copy a hasher that's already accepted some input.hasher1=blake3(b"foo")hasher2=hasher1.copy()hasher1.update(b"bar")hasher2.update(b"baz")asserthasher1.digest()==blake3(b"foobar").digest()asserthasher2.digest()==blake3(b"foobaz").digest()Installationpip install blake3As usual with Pip, you might need to usesudoor the--userflag
with the command above, depending on how you installed Python on your
system.There are binary wheelsavailable on
PyPIfor most environments. But
if you're building the source distribution, or if a binary wheel isn't
available for your environment, you'll need toinstall the Rust
toolchain.C BindingsExperimental bindings for the official BLAKE3 C implementation are available in
thec_impldirectory. These will probably not be published on PyPI,
and most applications should prefer the Rust-based bindings. But if you can't
depend on the Rust toolchain, and you're on some platform that this project
doesn't provide binary wheels for, the C-based bindings might be an
alternative.
Package: blal
Breath of the Wild LoopAssetList ConverterConverts blal (Loop Asset List) files from machine code to human-readable format. For LoZ:BotW and other Nintendo games.DependenciesA dumped copy of Legend of Zelda: Breath of the Wild (for Wii U or Switch)Python 3.7+ (64-bit, added to system PATH)SetupDownload and install Python 3.7+, 64-bit. You must choose the "Add to System PATH" option during installation.Open a command line and runpip install blalHow to UseFirst, navigate to the folder that contains the LoopAssetList.blal, then run the following function.blal [-b] filefile- path to the file to convert. Will convertBLALfiles toYAML, and vice versa. Ignores other file types.-b- Optional. Convert to big endian mode. Ignored when the filetype is notYAMLContributingIssues:https://github.com/GingerAvalanche/blal/issuesSource:https://github.com/GingerAvalanche/blalLicenseThis software is licensed under the terms of the GNU General Public License, version 3+. The source is publicly available on Github.
Package: blame-reviewers
Blame ReviewersSmall CLI tool for finding appropriate reviewers by searching authors of changed code in git blame.Requirementspython >= 3.7sh>= 1.12.13Installationpip3installblame-reviewersUsageIn the branch of your repo run:➜ ~ git:(awesome-branch) blame-reviewers
Blaming src/filename.py 19,+10...
Blaming src/another_filename.py 1,+132...
Blaming src/and_one_more_file.py 69,+14...

  Birdie Weissnat      Birdie.Weissnat@example.org    35.1093
   Alfreda Klocko       Alfreda.Klocko@example.org    22.141
     Erwin Rempel         Erwin.Rempel@example.org    20.259
    Myah Schmeler        Myah.Schmeler@example.org    19.201
Frederik Schimmel    Frederik.Schimmel@example.org    17.71
   Amalia Gleason       Amalia.Gleason@example.org     3.18
  Raymond Wuckert      Raymond.Wuckert@example.org     3.9
Package: blanc-admin-theme
Descriptionblanc-admin-themebrings fresh air to the default Django Admin
interface which hasn’t changed 10 years from the very first version of
Django framework. This theme just makes UI modern and clean.This app just overrides default admin’s CSS. All changes are about
colors, margins, sizes. Nothing major.No any markup changes.InstallationInstall via pip:pip installblanc-admin-themePutblanc_admin_themeapp in yourINSTALLED_APPSbeforedjango.contrib.admin:INSTALLED_APPS = (
    ...
    'blanc_admin_theme',
    'django.contrib.admin',
    ...
)That’s it.CompatibilityWorks correct in Django 1.6+. Older Django versions use a slightly
different way to show icons, so it requires changing markup or adding
python logic to make this theme compatible.TestingTested in: - IE7+ (IE7 and IE8 are OK in terms of graceful degradation)
- FF30+ (Windows, Ubuntu, OSX) - Chrome 35+ (Windows, Ubuntu, OSX) -
Safari 8 (OSX)
Package: blanc-basic-pages
An alternative to Django Flatpages, with some annoying features removed, but
with some new features such as a page tree powered bydjango-mptt, and
template tags for site navigation.InstallationUsingpip:$pipinstallblanc-basic-pagesDocumentationPackage documentation is hosted onRead the Docs, seehttps://blanc-basic-pages.readthedocs.org/