Saravanan666/pypi-org huggingface dataset:
Package: antiCPy
TheantiCPypackage provides tools to monitor destabilization because of varying control parameters or the influence of noise. Based on early warning measures it provides an extrapolation tool to estimate the time horizon in which a critical transition will probably occur.antiCPyThe package abbreviationantiCPystands for ''anticipateCriticalPoints (and if you likeChangePoints)
withPython''. The vision of theantiCPypackage is designing a package collection of state-of-the-art
early warning measures, leading indicators and time series analysis tools that focus on system stability and
resilience in general as well as algorithms that might be helpful to estimate time horizons of future transitions or resilience changes.
It provides an easy applicable and efficient toolboxto estimate the drift slope $\hat{\zeta}$ of a polynomial Langevin equation as an early warning signal via Markov Chain Monte Carlo
(MCMC) sampling or maximum posterior (MAP) estimation,to estimate a non-Markovian two-time scale polynomial system via MCMC or MAP with the option of a priori activated time scale separation,to estimate the dominant eigenvalue by empiric dynamic modelling approaches like delay embedding and shadow manifolds combined with
iterated map's linear stability formalism,extrapolate an early warning signal trend to find the probable transition horizon based on the current data information.Computationally expensive algorithms are implemented both, serially and strongly parallelized to minimize computation times. In case of
the change point trend extrapolation it involves furthermore algorithms that allow for computing of complicated fits with high numbers
of change points without memory errors.
The package aims to provide easily applicable methods and guarantee high flexibility and access to the derived interim results
for research purposes.Citing antiCPyIf you useantiCPy'sdrift_slopemeasure, please citeMartin Heßler et al. Bayesian on-line anticipation of critical transitions. New J. Phys. (2022).https://doi.org/10.1088/1367-2630/ac46d4.If you useantiCPy'sdominant_eigenvalueinstead, please citeMartin Heßler et al. Anticipation of Oligocene's climate heartbeat by simplified eigenvalue estimation.
arXiv (2023).https://doi.org/10.48550/arXiv.2309.14179DocumentationYou can find thedocumentation on read the docs.InstallThe package can be installed viapip install antiCPyRelated publicationsUp to now the package is accompanied bythe publicationEfficient Multi-Change Point Analysis to Decode Economic Crisis Information from the S&P500 Mean Market Correlation,the publicationMemory Effects, Multiple Time Scales and Local Stability in Langevin Models of the S&P500 Market Correlation,the publicationIdentifying dominant industrial sectors in market states of the S&P 500 financial data,the publicationQuantifying resilience and the risk of regime shifts under strong correlated noise,the publicationBayesian on-line anticipation of critical transitions,the preprintAnticipation of Oligocene's climate heartbeat by simplified eigenvalue estimation,the preprintQuantifying Tipping Risks in Power Grids and beyond.
Package: antidotes
Antidote - A Skiddies buster toolAntiDOTE v0.2AntiDOTE v0.2ProjectunderdevelopmentDescription:Being a script kid is not bad. But using someone else's tools and script to harm others is absolutely bad. And this thing is actually needed right now.Setup:$python3-mpipinstallantidotesFeatures:This tool contains a scanner module to scan the given urls for infection by most used and popular scripts.It contains a special module for 'Saycheese' or other similar 'camera spoofing' scripts. Inherited fromhttps://github.com/StrinTH/saycheese-antidote.This tool can be run in background and keeps checking for malicious url from clipboard and will scan it automatically.This tool is almost depended on requests package. and some less used others for basic operatons.Some new features will be added soon, to play with skids.Miscellaneous Feature:In case, if you want to run it for always, you can run assistance.pyw by clicking on it, which will keep tracking clipboard urls and scan it.Modules description:Antidote Saycheese:This module is antidote for all those tools and scripts on github and all other platforms which are being used by skids for playing with innocents.Special Feature:You can tease them by sending your message on a image.In case, if you can play with SVG payloads, then may be you can get shell in his/her system through this tool. ;)Antidote Shellphish:This tool is one of the most popular phishing tool among these kids, originally made by @thelinuxchoice (username changed  and Privated now).
tool use send messages as text with this module.Special Feature:You can send message as text but you can be more creative with texts also. ;)Antidote Whatsapp Phisher:There are a lot of tools available on github, similar tohttps://github.com/Ignitetch/whatsapp-phishing(Not targeting to developer, but to the misusers)
so You can send your message as text to them.Antidote z-shadow:z-shadowandshadowavewas the most famous free phising site for skids (Down from a month).This module manipulate complete process of transmission of zshadow server and attacker client.Special Feature:This tool bypasses weak human verification by zshadow and shadowave site.You can use this to spam your message as text to them. After a while, their account will be removed by the site bots itself for overloading.Note:Asz-shadowandshadowavesaredownmorethanforamonth,thistoolisnottestedsomuch.butitwasworkingformorethanhalfayearuninteruptully.TO-DO list:[Done]Add auto scan clipboard copied URLs.9cc7fb7Add anti saythanks module (In case needed)Make GUI for this tool to handle actions for URLs through corner sidebar.Support authors:
Package: antidox
Summaryantidoxis aSphinxextension that can readDoxygenXML “databases” and
insert documentation for entities in Sphinx documents, similar toBreathe.It is intended to befastand simple, thougheasily customizable.Document generation (i.e. conversion between doxy-xml and reStructuredText) is
driven by XML stylesheets (powered bylxml,) while indexing and selection of
documentable entities is done by a SQL database (sqlite3.)Here is anexample projectshowing showing this extension in
action.Example usageGenerate the documentation for an entire header, and include all entities defined
in that header:.. doxy:c:: lua_run.h::*
    :children:The syntax<path>::<identifier>can be used to disambiguate between entities
with the same name in different files.To document a Doxygen group:.. doxy:c:: [CborPretty]
    :children:You can manually specify which children should be documented:.. doxy:c:: be_uint16_t
    :children: u16Cross references are provided by a custom role, e.g.::doxy:r:`be_uint16_t::u16`The complete syntax is decribed in thedocs.Stub generationThegen_stubs.pyscript shows how stub files can be automatically generated.
You can adapt this script to your own project.Generating API docs this way is fast and convenient, but may be suboptimal,
since the spirit of this extension (and of Sphinx) is to generate narrative
documentation and not merely an API reference.Note: BetaThough usable, this extension is still under development. Backwards
compatibility will be kept for all releases with the same major/minor version.Be aware, however, that after updating this extension you may need to do a clean
build of your docs to see the results.ObjectivesReuse API docs made with Doxygen in a Sphinx project.Provide a smooth transition between 100% automatic API docs (what Doxygen
generates) and semi-manual documentation (autodoc-style).Have sensible defaults for automatic documentation generation while allowing
customization.Deal with big projects efficiently: the main tool in use now (Breathe)
has resource usage issues when dealing with large XML files.
Package: anti_forgetful
Never forget your AWS instances!anti_forgetfulis a simple and handy tool for launch a single AWS
instance from the terminal and tying it’s lifetime to the lifetime of
the process on your machine that launched it. This helps to avoid
situations where you forget your instance and leave it running for a
month. That could be thousands of dollars!Please let me know if you have issues!Just tell me how to use it!First, if you haven’t used AWS before:Set up your AWS account.Follow the first two steps (“Install the AWS CLI” and “Configure the
AWS CLI”)here.Next, installanti_forgetful:pip install anti_forgetfulNow, check out theexamplefolder for an example of how to launch a
Jupyter notebook server. To start building your instance, move to that
directory and run:anti_forgetful awscfgThis tells the launcher to useawscfg.pyas your configuration file
and starts to build your instance. It’ll take a few minutes on a freet2.microinstance. After a fewSo how do I write on of these configuration files!The configuration is specified as a Python file:# The name of the public/private key pair and the security group created for# your instance. If this key already exists, it won't be recreated.key_pair_name='tutorial_key_pair'group_name='tutorial_group'# What instance type do you want? https://aws.amazon.com/ec2/instance-types/instance_type='t2.micro'# This option turns off strict host checking in SSH. This can be handy if you# aren't worried about security and want to avoid some manual interaction# launching your instance.no_strict_host_checking=True# The base image to build from. You probably shouldn't change this.base_image_id='ami-428aa838'# The disk size requested from AWS EBS. In GB.root_volume_size=30# Your instance will be given a name so that it can be started and stopped!# Two instances with the same name could get messy... You've been warned.instance_name='tutorial_instance'# This function is run once when your instance is built. Build your docker# images here or install any packages you might want.defsetup_images(s):# Copy a file from the local machine to the instance. Accepts an optional# parameter "dest_filepath" for remote destination.s.copy_to_remote('docker-compose.yml')# Run a shell command on the remote instance.s.run_cmd('docker-compose pull')# This function is run every time your instance boots up.defstart_containers(s):# Forward a port from the remote machine to the local machine through an# ssh tunnel.s.ssh_port_forward(8888,8888)# Star the docker containers!s.run_cmd('docker-compose up')Just in case you still need to terminate some instances.Theawsterminatecommand will list all the instances you currently
have running and give you the option of terminating them.MiscellaneousAt the moment, this is pretty completely integrated with Docker. That
could easily be changed.I’ve only tried this on Ubuntu with Python 3.5 and Python 3.6.
Package: antifungal
Antifungal Peptide Prediction ToolThis repository hosts the Antifungal Peptide Prediction Tool, a Python package for predicting and analyzing antifungal peptides. It integrates various functionalities including peptide sequence processing, descriptor calculation, and machine learning-based prediction models.InstallationTo install the package, run the following command:# optional: create a virtual environmentpipinstallvirtualenv
virtualenvenv--python=python3.8
env\Scripts\activate# activate the virtual environment on Windowssourceenv/bin/activate# activate the virtual environment on Linux# install antifungal package with pippipinstallantifungalUsageThe tool can be used to predict antifungal activities of peptides, as well as rational design, including segment peptide sequences, perform single-point mutation analysis, and globally optimize peptide sequences for enhanced properties.Example Usage for antifungal peptide predictionfromantifungal.predictimportpredict_MICseq=['HIHIRHMWLLR','HIHIRHMWLLRR']pred=predict_MIC(seq)print(pred)# Expected output:# {# 'antifungal': [True, True],# 'prob_antifungal': [95.2, 97.9],# 'MIC_C_albicans': [21.8, 17.34],# 'prob_MIC_C_albicans': [99.8, 99.8],# 'MIC_C_krusei': [7.13, 5.87],# 'prob_MIC_C_krusei': [99.3, 99.4],# 'MIC_C_neoformans': [24.4, 15.57],# 'prob_MIC_C_neoformans': [99.3, 99.6],# 'MIC_C_parapsilosis': [18.3, 17.05],# 'prob_MIC_C_parapsilosis': [84.5, 82.6],# 'AFI': [16.23, 12.82],# 'prob_AFI': [79.16, 79.9],# 'peptide_seq': ['HIHIRHMWLLR', 'HIHIRHMWLLRR']}# }Example Usage for antifungal peptide designfromantifungal.designimportsegment,single_point_mutation,global_optimization# Example for segment classsegment_instance=segment("YOUR_PEPTIDE_SEQUENCE")segment_predictions=segment_instance.get_segmented_sequences().predict()# Example for single_point_mutation classmutation_instance=single_point_mutation("YOUR_PEPTIDE_SEQUENCE")mutation_predictions=mutation_instance.get_mutated_sequences().predict()# Example for global_optimization classoptimization_instance=global_optimization("YOUR_PEPTIDE_SEQUENCE")optimized_seq,results=optimization_instance.optimize()Directory Structuredata/: Contains training data used for model development.training_data/: Stores the datasets utilized in training the predictive models.screening_data: Stores the screening results in the following article.model/: Houses the trained models for antifungal peptide prediction.propy/: Includes a modified version of the propy package, with bug fixes. The original package can be found at PyPI propy.ChemoinfoPy/: Contains Python scripts for variable selection, peptide sequence preprocessing, descriptor calculation, and dataset partitioning for correction and validation purposes.ReferenceFor more detailed information, refer to the paperLarge-Scale Screening of Antifungal Peptides Based on Quantitative Structure–Activity Relationship, ACS Med. Chem. Lett. 2022, 13, 1, 99–104and visit theAntifungal Webserver.LicenseMIT
Package: antigen
AntigenExtendable mutation testing frameworkWhat is mutation testing?Mutation testing provides what coverage tries to, it finds logic that is not covered by your test suite.It finds such places by applying mutations to your code and running the modified code against your test suite.
If the tests succeed with the mutated code, it means the changed expression is likely not covered ny the tests.In comparison to coverage::green_heart: Checks expressions, not lines.:green_heart: Checks whether the expression is covered, not whether it was executed.:x: Can find irrelevant mutants (e.g. mutations in logging or performance optimizations or a mutation that does not break the code):x: Executes the tests many times and thereforetakes much more time.There are mitigations for these downsides::star:	We can mutate only lines that have changed in a given PR:star:	We can show the failing mutants via comments/warnings, as opposed to failing the whole CI pipeline.A much more in-depth explanation about the concept can be found inThis blog post by Goran PetrovicWhy use Antigen?ExtendabilityIn my personal experience, trying to integrate mutation testing into your CI pipeline can be a bit challenging.
There are a lot of features you might want to customize to mitigate some of the downsides of mutation testing, or to be able to integrate it to your project and dev environment effectively.For example, ignoring mutations on logging logic (which depends on your logging framework and conventions), or showing the results on various platforms (e.g. github, bitbucket, gitlab).Antigen puts extendability as a top priority so that adding mutation testing to your project is feasible.How?Mechine friendlyThe core of antigen is a pure python package that can be used by scripts.The actual CLI uses the core package instead of the logic being coupled to it.PluginableAntigen is written as a pipeline, each stage has an interface (e.g. Mutator, MutantFilter, Runner).Extending the logic is as simple as creating an object or function that matches that (simple) interface.The Antigen CLI utilisesentry pointsso that antigen plugins can be added just by installing them with pip.UsageAntigen is currently in development, the API might change between versions.antigen=Antigen(filters=[PatchFilter.from_git_diff("develop")],config=Config(project_root=Path("/home/myuser/myproject/")),)forpathinantigen.find_files("."):formutationinantigen.gen_mutations(path):result=antigen.test_mutation(mutation,run_command="pytest",)print(result)RoadmapAdd CLIUseparsoinstead of the built-inastfor cross-version mutations.Add wrapper class for remote components (i.e.RemoteFilter(hostname),RemoteRunner(hostname)).Add Output component (withJunitXMLOutput,GithubOutput,BitbucketOutputbuiltins)Add Cache component (withFileCache,MongoCachebuiltins)Add Sorter component (for selecting the most likely to succeed mutations)
Package: anti-header
anti-headerinfo: fake chrome, firefox, opera browser header anti headerFeaturesmore header paramsmore request methodInstallationpipinstallanti-headerUsageimportanti_headerfromanti_headerimportHeaderfrompprintimportpprinthd=Header(platform='windows',min_version=90,max_version=100).basehd=Header(platform='windows',min_version=90,max_version=100).randomprint(anti_header.VERSION)# must_header param useagehd=Header(must_header={'aa':'bb'}).randomhd=Header(must_header={'aa':'bb'}).base# rand_header param useagehd=Header(rand_header={'cc':'dd'}).randomhd=Header(rand_header={'cc':'dd'}).base# default_header param useageforiinrange(10):hd=Header(default_header={'ee':'ff'}).basepprint(hd.to_unicode_dict())"""base example{'cjito': 'azhbmf','ee': 'ff','referer': 'https://www.google.com/','user-agent': 'Mozilla/5.0 (X11; Linux i686) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.7.3455.76 Safari/537.36'}random example{'accept-encoding': 'gzip, deflate','accept-type': 'utf-8','ee': 'ff','origin': 'https://www.google.com/','referer': 'https://www.google.com/','sec-ch-ua-mobile': '?0','sec-fetch-mode': 'navigate','te': 'Trailers','upgrade-insecure-requests': '1','user-agent': 'Mozilla/5.0 (SM-G3609 Build/KTU84P; WIFI) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.5.6492.87 Safari/537.36','x-forwarded-for': '1','xorsv': 'pvmcue'}"""If You want to  requests method useage just:# test.pyimportrequestsfromanti_headerimportHeader_url='https://www.google.com/'hd=Header(url=_url,platform='windows')requests.get(_url,header=hd.random.to_unicode_dict())If You want to  scrapy downloadmiddleware method useage just:# random_header.pyfromanti_headerimportHeaderclassRandomHeaderMiddleware(object):def__init__(self):passdefprocess_request(request,spider):request.headers=Headers(url=request.url).randomdefprocess_response(request,response,spider):returnresponseIf You want to  specify param just:fromanti_headerimportHeaderhd=Header(logger=True)# the default install logurutry:fromloguruimportloggerexcept:install("loguru")fromloguruimportlogger# close default singletonhd=Header(dry=True)Make sure that You using latest versionpip install -U anti-headerCheck version via python console:import anti_header

print(anti_header.VERSION)
Package: antiheroes
ANTIHEROESDo you like antiheroes? You can use this python package ANTIHEROES to list and get fascinating antiheroes from movies, TV shows, video games, and comics.Installation# Official Versionpython-mpipinstallantiheroesGetting StartedDirectly after the installation you can use this package. You will need Python Release 3.7.0 or older.You can use 3 Methods:get_hero(): get a random antiherolist_heroes(): list all antiheroespopular_heroes(): list top x antiheroesOpen the python console and use the package>>>fromantiheroesimportget_hero
>>>get_hero()THEHULKentersinyourroom!!!
>>>get_hero()WOLVERINEentersinyourroom!!!
>>>get_hero()ELEKTRANATCHIOSentersinyourroom!!!
>>>get_hero()DUKENUKEMentersinyourroom!!!
>>>get_hero()THEHULKentersinyourroom!!!


>>>fromantiheroesimportlist_heroes
>>>list_heroes()ALLANTIHEROES:[{'name':'WOLVERINE','world':'MARVEL COMICS'},{'name':'DEADPOOL','world':'MARVEL COMICS'},{'name':'ELEKTRA NATCHIOS','world':'MARVEL COMICS'},{'name':'JOHN WICK','world':'JOHN WICK'},{'name':'BLADE','world':'MARVEL COMICS'},


>>>fromantiheroesimportpopular_heroes
>>>popular_heroes(5)MYTOP5ANTIHEROES:[{'name':'WOLVERINE','world':'MARVEL COMICS'},{'name':'DEADPOOL','world':'MARVEL COMICS'},{'name':'ELEKTRA NATCHIOS','world':'MARVEL COMICS'},{'name':'JOHN WICK','world':'JOHN WICK'},{'name':'BLADE','world':'MARVEL COMICS'}]
Package: antikythera
IMSI Catcher detection, analysis and display.Development Environment SetupWindowsWireshark must be installed for thepysharklibrary to have
access to the packet dissectors it needs. See theWireshark Documentationfor details.LinuxSetup a virtual environment to ensure system packages are not used:mkdir -p ~/.virtualenv/antikythera
python3 -m venv ~/.virtualenv/antikythera
source ~/.virtualenv/antikythera/bin/activateNoteThe commandsource~/.virtualenv/antikythera/bin/activatemust
be reran for each new shell instance. When activated the name of the
virtual environment should appear somewhere on the prompt such as:(antikythera) user@hostname:~$Then for Debian or Ubuntu based distributions just run the setup
scriptsudo bash setup.sh. The documentation can be built
locally by runningpython setup.py docsand to run the tests:pip install -r test-requirements.txt
python setup.py testThe program can be installed and ran as follows:python setup.py install
anti
Package: antiless
Antiless.>availabletoanyonewhowantstouseit<Installation! ~ use at the knowledge of knowing it may be buggy ~ !

pip install antilessUsage# default shit if u want to only import for ease - auto switches #fromantilessimportprintfasprint,inputfasinput,initinit(debug=False)print("[DEBUG] Should NOT Show")print("(~) Should NOT Show")print("[INFO] Should Show")print("(*) Should Show")# ==================================## log format: [21:14:38] INF > testfromantilessimportloglog.info("info",sep=">")log.error("error")log.fatal("fatal")log.success("success")log.debug("debug")log.log("Retrieved",code="3131")log.vert("test",test=True,madeby="antilag")importtimefromantilessimportBetaConsolec=BetaConsole(speed=2)whileTrue:try:timestamp=c.getTimestamp()c.alphaPrint("[INF]",f"[{timestamp}] antilag? :Đ",increment=False)time.sleep(0.001)exceptKeyboardInterrupt:exit(0)*antilag@discord|antilagg@github|antilag.dev*
Package: antimait
antimaitantimait is a library made of tools to ease the implementation
of IoT automation systems based on devices such as Arduino and ESP.To install it run:pip3 install antimaitor clone this repository, change directory to the root of the project and run:pip3 install .DocumentationDocumentation for the antimait library can be found in thedocsdirectory or at the following link:https://antimait.github.io/antimait[ita]antimait Ã¨ una libreria composta da strumenti che possono essere utilizzati per semplificare l'implementazione
di progetti basati su Arduino ed Esp nel campo dell'IoT.Per installarla, basterÃ  eseguire:pip3 install antimaito clonare questa repository, spostarsi nella cartella base del progetto ed eseguire:pip3 install .DocumentazioneLa documentazione relativa ad antimait (in lingua inglese) puÃ² essere trivata nella cartelladocso al seguente
link:https://antimait.github.io/antimait
Package: antimeridian
antimeridianFix shapes that cross the antimeridian.
Seethe documentationfor information about the underlying algorithm.
Depends onshapelyandnumpy.Can fix:ShapelyPolygon,MultiPolygon,LineString, andMultiLineStringobjectsGeoJSONPolygons,MultiPolygons,FeaturesandFeatureCollections, as dictionariesAnything that has a__geo_interface__UsagepipinstallantimeridianThen:importantimeridianfixed=antimeridian.fix_geojson(geojson)We also have some utilities to createbounding boxesandcentroidsfrom antimeridian-crossing polygons and multipolygons.
Seethe documentationfor a complete API reference.Command line interfaceUse theclioptional dependency to install theantimeridianCLI:pipinstall'antimeridian[cli]'antimeridianfixinput.json>output.jsonDevelopingClone and install in editable mode with the development optional dependencies:gitclonehttps://github.com/gadomski/antimeridiancdantimeridian
pipinstall-e'.[dev,docs]'We usepytestfor tests:pytestWe useSphinxfor docs:make-CdocshtmlContributingGithubissuesandpull requests, please and thank you!LicenseApache-2.0