Saravanan666/pypi-org huggingface dataset:
Package: bad-apple-turtle
bad-apple-turtleA program that plays Bad Apple!! on a Python TurtleThis had just been nearly completely re-written to be better in almost every way. Pypotrace is no longer used in this version.Python-vlc is used when playing back a video along side the turtle, but it technically optional. Make sure VLC Media Player is installed before python-vlc if you want to use it.You can install this withpip install bad-apple-turtle. If you want VLC support, runpip install bad-apple-turtle[vlc], and if you also want to be able to download videos for the script, you can dopip install bad-apple-turtle[vlc,yt-dlp]. From there, you can run the command withbad-apple-turtle. If you want a quick demo and have yt-dlp installed, you can just dobad-apple-turtle --demo.You have several options when running the command. You can directly play a video in a turtle by specifying it in the command with-v/--video. If you don't want the original to play next to it, you can use the--no-vlcargument. If you want to export the resulting vectorized video to a file, you can also specify an output file with-o/--output. You can then play the vectorized video again later using-i/--input. If you specify a vectorized video and a normal video at the same time, the turtle will play the vectorized one while VLC will play the normal video. If you just want to output a file without playing the video at the same time, you can use the--no-playargument. Once the vectorized video is exported, the original is no longer required for turtle playback, though there is no audio included.If the turtle is not synchronized with the video, you can try increasing the--vlc_delayoption, though it's already fairly high. If you are getting lots of dropped frames, you can use the simplification options, which are--max-pointsand--min-area.--max-pointsis the maximum number of points in a frame times the square root of the number of curves before the vectors are simplified.--min-areais the minimum area a curve needs for it to be rendered. Alternatively, you can try increasing--tolerance, which is how much time offset is allowed before frames are dropped, or get a faster computer.Increasing the--thresholdwill increase how much of the greys are converted to black, and decreasing it will increase the amount of white. You can also use-ssand-toto specify starting and ending frames to playback (or export to a file)There are other options and I recommend you use--helpfor more information.I used this video for testing:https://www.youtube.com/watch?v=UkgK8eUdpAoTheoretically, you could probably put any video through this, but I do not know how well it would work and it would be converted to binary black and white.
Package: badboy
How to run for first time?pkg install python git



git clone https://github.com/AitzazImtiaz/Bad-Boy



cd Bad-Boy



ls



make install



badboyBadboy is coming on pip now! Install using:pip install badboyTodoIf enter is clicked, a error message generates in option. Exception Handling needed.Tested on Termux. Download termux fromhereHappy Hacking 😊😁
Package: badbyte
badbyteDeal with bad characters easily during exploit writing with badchars.Table of ContentsInstallationUsageCyclic pattern generateSearch for offset in cyclic patternGenerate payload to check all charactersAnalyze memory dumped after triggerProgramatically use↑Instalationusing pip:pip3installbadbyteor from repo:gitclonegit@github.com:C3l1n/badbyte.gitcdbadbyte
pip3install.↑UsageYou can always use:badbyte--help↑Cyclic pattern generateIt is useful to search for offset at which you should put your
sniper shot constants. For example return address: you generate
pattern with this function, trigger vulnerability  with
generated payload. EIP value (remember about little ending in x86)
has uniq part of pattern and offset of that part could be calculated
with badbyte parse (see next chapter).badbytec-u4-l100--bad"61 62"↑Search for offset in cyclic patternSearch for offset of provided part in --pattern argument.badbyte o -u 4 -l 100 --bad "61 62" -p cocc↑Generate payload to check all charactersbadbyteg--bad"3d 26 25 0d"--preSTART--postSTOPuse:--bad to supply hexascii values of bad characters--pre to set string for marking start point (or leave default)--post to set string for marking stop point (or leave default)Then use payload in your exploit and fire it.↑Analyze memory dumped after triggerCopy hexascii from memory dump of your favourite debugger i.e. windbg:remember to skip addresses and ascii representation. I use vim and column select or visual studio code and alt+shift select.Fire badbyte to analyze output:badbytep-c--preSTART--postSTOP↑Programatically useDocumentation not made (feel free to read code) but you can find in example/programatically_generate_payload.py example of payload generation in exploit.
Package: badcode
IntroductionDocsCommandsPre-requisitesInstallation and DownloadsFAQOther ResourcesBug Tracker and SupportUnit-TestsLicense and CopyrightAuthor and ThanksIntroductionDocsCommandsPre-requisitesInstallation and DownloadsFAQQuestion:?Answer:.Other ResourcesBug Tracker and SupportUnit TestsLicense and CopyrightAuthor and Thankswas developed by
Package: badd
BadD(etector)Description (How it can help)BadD(etector) was created for detecting bad things in user-generated content in Russian.
Now this library supports obscene words detection, advertising detection and toxicity detection.
All the magic done by neural networks.RequirementsPython 3.7+PyTorch 1.8.1Gensim 3.8.1NLTK 3.2.5pymorphy2 0.9.1emoji 1.2.0How to installlocally (dev mode)python3-mpipinstall-e<path-to-lib>from githubpipinstallgit+https://github.com/wksmirnowa/badd.git@masterfrom pippipinstallbaddUsageDownload files and models for:ObsceneDetectorAdDetectorToxicDetectorObscene words detectionImport the ObsceneDetector classimporttorchfrombaddimportObsceneDetectorSet pathes to files and device# path to vocabvocab_path="obscene_vocab.json"# path to embeddingsfasttext_path="obscene_embeddings.pickle"# path to modelmodel_path="obscene_model_cpu.pth"# set devicedevice=torch.device('cpu')Use ObsceneDetectorobscene_detector=ObsceneDetector(vocab_path,fasttext_path,model_path,device)Predict every word in textobscene_detector.predict_text(text)Predict probability for every word in textobscene_detector.predict_probability(text)Check whether any obscene word is in textobscene_detector.obscene_in_text(text)Attributesobscene_detector.obscene_wordslist of found obscene words. Available after one of the methods
(predict_probability,predict_text,obscene_in_text) was runned.Ad detectionImport the AdDetector classimporttorchfrombaddimportAdDetectorSet pathes to files and device# path to vocabvocab_path="ad_vocab.json"# path to embeddingsfasttext_path="ad_embeddings.pickle"# path to modelmodel_path="ad_model_cpu.pth"# set devicedevice=torch.device('cpu')Use AdDetectorad_detector=AdDetector(vocab_path,fasttext_path,model_path,device)Predict textad_detector.predict_text(text)Predict probability for textad_detector.predict_probability(text)Check whether a text is adad_detector.is_ad(text)Toxic texts detectionImport the ToxicDetector classimporttorchfrombaddimportToxicDetectorSet pathes to files and device# path to vocabvocab_path="toxic_vocab.json"# path to embeddingsfasttext_path="toxic_embeddings.pickle"# path to modelmodel_path="toxic_model_cpu.pth"# set devicedevice=torch.device('cpu')Use AdDetectortoxic_detector=ToxicDetector(vocab_path,fasttext_path,model_path,device)Predict texttoxic_detector.predict_text(text)Predict probability for texttoxic_detector.predict_probability(text)Check whether a text is toxictoxic_detector.is_toxic(text)
Package: baddns
BadDNSCheck subdomains for subdomain takeovers and other DNS tomfooleryBadDNS is a standalone tool andBBOTmodule for detecting domain/subdomain takeovers of all kinds, including other DNS issues like NSEC walks and Subdomain Takeovers.InstallationWe have apypipackage, so you can just dopip install baddnsto make use of the library.UsageAfter installing with pip, you can just runbaddnsfrom the command line.baddns [-h] [-n CUSTOM_NAMESERVERS] [-c CUSTOM_SIGNATURES] [-l] [-m MODULES] [-d] [target]

positional arguments:
  target                subdomain to analyze

options:
  -h, --help            show this help message and exit
  -n CUSTOM_NAMESERVERS, --custom-nameservers CUSTOM_NAMESERVERS
                        Provide a list of custom nameservers separated by comma.
  -c CUSTOM_SIGNATURES, --custom-signatures CUSTOM_SIGNATURES
                        Use an alternate directory for loading signatures
  -l, --list-modules    List available modules and their descriptions.
  -m MODULES, --modules MODULES
                        Comma separated list of module names to use. Ex: module1,module2,module3
  -d, --debug           Enable debug loggingModulesNameDescriptioncnameCheck for dangling CNAME records and interrogate them for subdomain takeover opportunitiesnsCheck for dangling NS records, and interrogate them for takeover opportunitiesmxCheck for dangling MX records and assess their base domains for availabilitynsecEnumerate subdomains by NSEC-walkingreferencesCheck HTML content for links or other references that contain a hijackable domaintxtCheck TXT record contents for hijackable domainszonetransferAttempt a DNS zone transferExamplesSimple checkbaddns subdomaintocheck.example.comSpecify Module(s)baddns -m CNAME subdomaintocheck.example.com
baddns -m CNAME,NS subdomaintocheck.example.comList available Modulesbaddns -lCustom Nameserversbaddns -n 1.1.1.1 subdomaintocheck.example.comDocumentationPlease visit our fulldocumentationfor many more details, including information about specific BadDNS modules.AcknowledgementsBadDNS Signatures are sourced primarily fromNuclei Templatesand fromdnsReaperbyPunk Security, although many have been modified or updated in BadDNS. Much of the research contained in the signatures was originally discussed on the issues page ofcan-i-take-over-xyz.
Package: bade
Micro-blogging with rSTBade is a small command line utility to allow the user to maintain a simple
HTML website and weblog using only plaintext rST for their content. It also
bundles some rST directives and roles (seethe docs) for:rendering DOT graphs to SVGrendering LaTeX to SVGIt’s very similar in spirit to some other things. It’s likePelicanbut it’s a
lot simpler and usesMakoinstead ofJinja2. It’s also likeTinkererbut
without the dependency onSphinx. It also lets you use DOT and LaTeX.Bade is opinionated and simplistic, I wrote it mostly my own usage, so you
probably shouldn’t use it.Plans to extendIn writing Bade, I came up with a few things more I’d like to do:Test suite: Everything should be tested, right?Git integration: For dirty checking on build, maybe stamping a
rendered file with its latest commit hash. There area fewGitHubissuesfor it.Hooks: Let people hook in at interesting points, ie. callgruntpre-build, commit after build, etc.DocumentationIt’shere, there’s atutorial.
Package: badev
badev - The Ballistica Developing HelperThis package is not affiliated with the BombSquad official team.This package aims to facilitate the development of the BombSquad mods
and benefiting from the features of the programs like vscode to autocomplete and give suggestions to you.Getting StartedYou can install this package via pippip install badevBut because this package was created to be used in IDEs like vscode, It is better to use virtual environments.The recommended way to install and usebadevis to install this package with pipenv and then create a virtualenv and import it to your desired IDE.pipenv install -d badev
Package: badfiles
badfilesA malicious file detection engine written with Python and Yara.Free software: Apache-2.0Documentation:https://jeffallan.github.io/badfiles/IntroductionAt some point most applications need to accept files from a third party. Since we do not have absolute control over these files they can present a serious threat vector.The aim of this project is to provide a flexible and expandable solution to triage these files so they can be handled accordingly.FeaturesCurrently, this project focuses on detecting the following:Generally Suspicious Files::heavy_check_mark: Mime type confusion.:black_square_button: Files with a root UID or GID (*NIX only).:black_square_button: Sticky, setuid, or setgit bit (*NIX only).CSV Files:heavy_check_mark: CSV Injection.:black_square_button: Files with a root UID or GID (*NIX only).:black_square_button: Sticky, setuid, or setgit bit (*NIX only).Office Documents:heavy_check_mark: DDE injection.:heavy_check_mark: Files with a root UID or GID (*NIX only).:heavy_check_mark: Sticky, setuid, or setgit bit (*NIX only).Zip Files:heavy_check_mark: Symlink attacks.:heavy_check_mark: Zip slips.:heavy_check_mark: Nested zip bombs.:heavy_check_mark: Flat zip bombs.:heavy_check_mark: Sticky, setuid, or setgit bit (*NIX only).:heavy_check_mark: Files with a root UID or GID (*NIX only).Tar Files:heavy_check_mark: Files with a root UID or GID (*NIX only).:heavy_check_mark: Sticky, setuid, or setgit bit (*NIX only).:black_square_button: Files with absolute paths (*Nix only).Additional FeaturesPlease file an issue or a pull request especially if you have found or created malicious files that bypass these detection mechanisms. Please see thecontributing guidelinesfor more details.Getting StartedUsageCreditsThis package was created withThis Cookiecutter template.This project useszip-bombto create the nested and flat zip bombs for unit testing and detection rules.This project uses a custom Yara rule fromReversing Labsto detect obfuscated CSV injection payloads.Contributors
Package: badfish
Badfish introduces MissFrame, a wrapper overpandasDataFrame,
to wrangle through and investigate missing data. It opens an easy to use
API to summarize and explore patterns in missingness.Badfish provides methods which make it easy to investigate any
systematic issues in data wrangling, surveys, ETL processes which can
lead to missing data.The API has been inspired by typical questions which arise when
exploring missing data.Badfish uses thewhereandhowapi in most of its methods to
prepare a subset of the data to work on.where: Work on a subset of
datawherespecified columns are missing.how: Eitherall|anyof the columns should be missing.Eg.mf.counts(columns = ['Age','Gender'])would give counts of
missing values in the entire dataset.While,mf.counts(where=['Income'],columns = ['Age','Gender'])would give counts of missing values in subset of data whereIncomeis already missing.Installationpip install badfishUsage>>> import badfish as bf
>>> mf = bf.MissFrame(df)ExampleWill add an exmaple IPython notebook soon.CountsBasic counts of missing data per column.>>> mf.counts(where=['gender', 'age'], how='all', columns=['Income', 'Marital Status'])PatternGet counts on different combinations of columns with missing data.Truemeans missing andFalsemeans present.>>> mf.pattern()The same can be visualized in the form of a plot (inspired by VIM
package in R)>>> mf.plot(kind='pattern')

Example plot:Note: Bothwhereandhowcan be used in this method.Itemset MiningUse frequency item set mining to find subgroups where data goes missing
together. Note: This uses the PyMining package.>>> itemsets, rules = mf.frequency_item_set()CohortTries to find signigicant group differences between values of columns
other than the ones specified in the group clause. Group made on the
basis of missing or non-missing of columns in the group clause.
Internally usesscipy.stats.ttest_ind.This method works on the values in each column instead of column names.Note: Experimental method.>>> mf.cohort(group=['gender'], columns=['Income'])LicensePlease see therepository
license.Generally, we have licensed badfish to make it as widely usable as
possible.Call for contributionIf you have any ideas, issues or feature requests, feel free to open an
issue, send a PR or contact us.AuthorsHarsh Nisar&Deshana
DesaiInteresting linkshttps://github.com/tierneyn/ggmissinghttps://github.com/tierneyn/visdathttp://www.njtierney.com/blag/rbloggers/2016/03/06/wombat-2016-wrap-up/
Package: badfmt
badfmtA very bad formatter for any programming language with braces and semicolons (e.g., c/c++/java/javascript/rust)Descriptionbadfmtis a command-line tool that attempts to format code files written in programming languages with braces and semicolons. It makes the code seem like it doesn't have any semicolons or braces but puts them at the very end of the line away from sight. It is designed to be a joke formatter and should not be used in production codebases.InstallationTo installbadfmt, you need to have Python 3.8 or higher installed. You can then usepipto install the package:pipinstallbadfmtUsageTo use badfmt, simply run the following command:python-mbadfmt[filepath]Replace [filepath] with the path to the file you want to format. The tool will attempt to format the file in place.You can also specify the maximum line length using the -l or --line-len option. For example:badfmt -l 80 [filepath]
Package: badFormatter
Bad FormattingThis is gets rid (or at least moves) all those pesky '{', '}' and ';' that we all hate (dont we?)Web versionNo need to install anything - if you prefer you can just head overherein order to shitify your code online!InstallationUse the package managerpipto install bad formatting.pipinstallbadFormatteror clone this repo and run in the same wayUsage (for Pip)importbadFormatterbadFormatter.shitify_print(filename)# prints the code given a filenamebadFormatter.shitify_return(filename)# returns the code given a filenamebadFormatter.shitify_print_text(text)# prints the code reformatted from the inputbadFormatter.shitify_return_text(text)# returns the code reformatted from the inputLicenseMIT
Package: bad-formatting-johnmontgomery2003
Bad FormattingThis is gets rid (or at least moves) all those pesky '{', '}' and ';' that we all hate (dont we?)Web versionNo need to install anything - if you prefer you can just head overherein order to shitify your code online!InstallationUse the package managerpipto install bad formatting.pipinstallfoobaror clone this repo and run in the same wayUsage (for Pip)importbad-formattingbad-formatting.shitify_print(filename)# prints the code given a filenamebad-formatting.shitify_return(filename)# returns the code given a filenamebad-formatting.shitify_print_text(text)# prints the code reformatted from the inputbad-formatting.shitify_return_text(text)# returns the code reformatted from the inputLicenseMIT
Package: bad-framework
BAD - Benchmarking Anomaly DetectionTheBADframework is a distributed framework for benchmarking unsupervised anomaly detection algorithms.For details, please refer to theofficial documentation.InstallationBADcan be easily installed viapipwith the command:pip install bad-frameworkthis installs thebadcommand-line interface.Example usageBefore running experiments, you need to start theBADserver processes:bad server-startThen, you can run a simple experiment with:bad run -c lof -d shuttlethis executes the famousLocal Outlier Factor (LOF)algorithm on theshuttledataset.By default, results are stored in the file./bad_out.csv.The output file contains execution times, hyperparameter settings and evaluation metrics for all executed experiments.The output file can be easily plotted with any graphing library.Please refer to theofficial documentationfor a complete command line reference.Copyright © 2020 Sivam Pasupathipillai -sivam.pasupathipillai@gmail.com.All rights reserved.
Package: badge
Installation$[sudo]pipinstallbadgeFeaturesmd(default),rst,htmlautoformat stringsminimalistic designExamples>>>classTravis(badge.Badge):title="Travis"image="https://api.travis-ci.org/{fullname}.svg?branch={branch}"link="https://travis-ci.org/{fullname}/">>>Travis(fullname="owner/repo")# .md, Markdown by default'[![Travis](https://api.travis-ci.org/owner/repo.svg?branch=master)](https://travis-ci.org/owner/repo/)'>>>Travis(fullname="owner/repo").rst# .rst, reStructuredText'.. image: : https://api.travis-ci.org/owner/repo.svg?branch=master:target:https://travis-ci.org/owner/repo/'readme42.com
Package: badgebtle
DEF CON badge bluetooth libaryA library based on bluepy that performs bluetooth scan for DEF CON badges.UsageBasicfrom badgebtle import BadgeBTLE
b = BadgeBTLE()
neighbors = b.scan()
print(neighbors)DevelopmentSetup$ git clone https://github.com/dczia/python-badgebtle.git
$ virtualenv-3 v
$ source ./v/bin/activate
$ pip install -r requirements.txtBuild and upload to PyPi repository$ python setup.py sdist bdist_wheel
$ pip install twine
$ twine upload dist/badgebtle-x.x.x* #<-- Requires credentials.
Package: badgekit-api-client
[![travis build](https://travis-ci.org/tgs/python-badgekit-api-client.svg)](https://travis-ci.org/tgs/python-badgekit-api-client/)
[![coverage](https://coveralls.io/repos/tgs/python-badgekit-api-client/badge.png)](https://coveralls.io/r/tgs/python-badgekit-api-client)[Documentation on Read the Docs](http://badgekit-api-client.readthedocs.org/)This is a partially-complete Python client for the BadgeKit API -https://github.com/mozilla/badgekit-apiUsing the functionality available so far, you can:Connect to the BadgeKit API server, and check its health (ping),Examine (get) badges, issuers, badge instances, and other objects,List (list) the badges in an issuer, system, etc.Create (create) objects:Create issuer, system, and program objects.Create badges.Create badge instances, i.e. issue badges.You cannot yet update or delete objects.  This will change soon.
Package: badger
Copyright (c) 2017 Joakim UddholmPermission is hereby granted, free of charge, to any person obtaining a copyof this software and associated documentation files (the "Software"), to dealin the Software without restriction, including without limitation the rightsto use, copy, modify, merge, publish, distribute, sublicense, and/or sellcopies of the Software, and to permit persons to whom the Software isfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THEAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHERLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THESOFTWARE.Description: badger======|version| |coverage|Commandline Interface to create svg badges.Install-------.. code:: bashpip install badgerUsage (Commandline)-------------------Simplest use case of static label and value:.. code:: bashbadger version v0.1.2Percentage mode, with color picked relative to where in the 0-100 rangethe value is... code:: bashbadger -p coverage 71.29%Usage (Package)---------------.. code:: pythonfrom badger import Badge, PercentageBadgebadge = Badge("version", "v0.1.2")badge.save("examples/version.svg")percentage_badge = PercentageBadge("coverage", 71.29)badge.save("examples/coverage.svg")Disclaimer==========Code originally heavily copied from https://github.com/dbrgn/coverage-badge . Badgedesign originally from https://github.com/badges/shields.. |version| image:: examples/version.svg.. |coverage| image:: examples/coverage.svgPlatform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Environment :: ConsoleClassifier: Intended Audience :: DevelopersClassifier: License :: OSI Approved :: MITClassifier: Programming Language :: Python :: 3Classifier: Programming Language :: Python :: 3.3Classifier: Programming Language :: Python :: 3.4Classifier: Programming Language :: Python :: 3.5Classifier: Programming Language :: Python
Package: badger2040-pystub
badger2040-pystubPython stub file for the badger2040 module. Contains some documentation and ports from the CPP/C headersDocumentation fromhereTo install:pip install badger2040-pystuborpip install git+https://github.com/V3ntus/badger2040-pystubNote: this is only a stub file, it has no functionality. It is only used for documentation and proper typehinting