Saravanan666/pypi-org huggingface dataset:
Package: advsecurenet
AdvSecureNet - Adversarial Secure NetworksAdvSecureNet is a Python library to for Machine Learning Security. It has been developed byMelih CatalatUniversity of Zurichas a part of his Master's Thesis under the supervision ofProf. Dr. Manuel Günther. Currently, the main focus of the library is on adversarial attacks and defenses on vision tasks. However, it's planned to extend the library to support other tasks such as natural language processing.The library provides a set of tools to generate adversarial examples and to evaluate the robustness of machine learning models against adversarial attacks. It also provides a set of tools to train robust machine learning models. The library is built on top ofPyTorch. It is designed to be modular and extensible. So, anyone can easily run experiments with different configurations.The library currently supports the following attacks:FGSMFGSM TargetedPGDDeepFoolCWLOTSDecision BoundaryThe library currently supports the following defenses:Adversarial TrainingEnsemble Adversarial TrainingThe library supports any model that is implemented in PyTorch. It also provides a set of pre-trained models that can be used for experiments. It's also possible to create and use custom models.The library supports multi-GPU training and adversarial training with DDP (Distributed Data Parallel) from PyTorch. This allows the library to be used for large-scale experiments.InstallationYou can install the library usingpip:pipinstalladvsecurenetYou can also install the library from source:gitclonecdadvsecurenet
pipinstall-e.UsageThe library can be used as a command line tool or as an importable Python package.Command Line Tooladvsecurenetcommand can be used to interact with the library. You can useadvsecurenet --helpto see the available commands and options. Available commands are:attackCommand to execute attacks.config-defaultGenerate a default configuration file based on the name...configsReturn the list of available configuration files.defenseCommand to execute defenses.model-layersCommand to list the layers of a model.modelsCommand to list available models.testCommand to evaluate a model.trainCommand to train a model.weightsCommand to model weights.You can useadvsecurenet <command> --helpto see the available options for a command. For example, you can useadvsecurenet attack --helpto see the available options for theattackcommand. The CLI supports both config yml files and arguments.Python PackageYou can import the library as a Python package. You can use theadvsecurenetmodule to access the library. You can find the available modules and classes in thedocumentation.ExamplesYou can find various examples in theexamplesdirectory. The examples show different use cases of the library and how to use the library as a Python package/CLI tool.ArchitectureThe high-level architecture of the library is shown in the figure below.LicenseThis project is licensed under the terms of the MIT license. SeeLICENSEfor more details.Further InformationFurther information about the library can be found in thedocumentation.
Package: advstats
Library for mathematical analysis of various sampling methodsAboutAdvStats is a python library for mathematical analysis of various sampling methods. So far the package supports analysis on cluster samples and stratifed samples. And the functions support various data formats. If using data from a table, the data can stored in two ways.1DataCluster/ StratumData Point 1Cluster/ Stratum 1Data Point 2Cluster/ Stratum 22Cluster/ Stratum 1Cluster/ Stratum 2Data Point 1Data Point 3Data Point 2Data Point 4The required supporting can also just be manually entered. For more information look at the documentation or the tests.InstallionpipinstalladvstatsDocumentationDocumetation for the package can be found at pavanadapa.github.io(pavanadapa.github.io).FutureImplementation of a two-stage cluster sampling and more sampling methods are coming soon.
Package: advtrain
ADV-TRAIN : ADV-TRAIN is Deep Vision TRaining And INference frameworkThis is a framework built on top of pytorch to make machine learning training and inference tasks easier. Along with that it also enables easy dataset and network instantiations, visualize boundaries and more.Read the latest documentation athttps://adv-train.readthedocs.io/en/latest/Why use this framework?It is very easy to use and well documented and testedThe framework supports resume (Yes you can restart training from where ever you left off when your server crashed!).The framework also implements support for train/validation splits of your choice with early stopping baked in.Single argument change for using different datasets and models i.e. convenience at you fingertipsDataloader parameters optimized for highest possbile performance when traning.Supports multi-gpu training (single parameter update required)InstallingTo install the pip package use the commandpip install advtrainContributingTo clone the repo, it is recommended to use a shallow clone, this is recommended as previous versions have hosted large pretrained modelsgit clone --depth <specify depth> https://github.com/DeepakTatachar/ADV-TRAINRequirements are listed in requirements.txt. Use the commandpip install -r requirements.txtto install all required dependenciesDocumentationRead the latest documentation athttps://adv-train.readthedocs.io/en/latest/To locally make the documentation, navigate to /docs and typemake htmlThis will generate a build directory and will house a html folder within which you shall find index.html (i.e. path is /docs/build/html/index.html)Open this in any web browser. This project uses Sphnix to autogenerate this documentation.Running ExamplesThis repo also has examples on how to train and visualize boundaries in /examples folder. A readme file is provided in the ./examples folder to help out with using and running the examples.Pretrained ModelsWe provide pretrained models in a previous version of the repo. It is "hosted"here. These models have various weight quantized VGG and ResNet models, named according to the naming conventiondatasetname_inputQuant_architecture_activationQuant_weightQuant.ckptWhen running you program using advtrain, place the models in the (current working directory) cwd/pretrained/dataset_name and when load is set to true in instantiate_model it will automatically load the correct model.
Package: advurl-shortner
advurl_shortner - Advanced URL Shortener for PythonEasy-to-use, powerful python library to help you to shorten urls with advanced options. Supports multiple domains, URL TTL, split tests, visit statistics etc.
An extended native Python wrapper forAdvUrlShortner APIwith minimal requirements. Supports all methods and types of responses.FeaturesEasy to useMultiple domainsURL TTL (Time-To-Live) in seconds. Auto expiry URL after some time.Redirect to second URL after primary URL expires (TTL)Randomized and weighted randomnized redirect to different URLs (split tests etc.)Password-protected statistics of visits to a shortened URLPassword protected shortened URL parameters (TTL, second URL, etc.)InstallationIn order install this package, simply run:pipinstalladvurl_shortnerUsageTo use shorten_url, you first need to import the package:importadvurl_shortnerShorten URL:advurl_shortner.short("https://google.com/")# Returns the shortened URLs in JSON# Example: {"urls": ["https://liii.pw/N", "https://illi.ink/N", "https://illi.cfd/N"]}advurl_shortner.short("https://google.com/",description="Google search engine",password="1234x")# Returns shortened URLs, sets a password to access visiting statistics and shortened URL parameters.advurl_shortner.short("https://google.com/",ttl=86400)# Returns the shortened URLs., after 24 hours (86400 seconds) will return "The Link You Followed Has Expired"advurl_shortner.short("https://google.com/",ttl=86400,second_url="https://bing.com/")# Returns the shortened URLs., after 24 hours (86400 seconds)  shortened link will redirect to second_urladvurl_shortner.short("https://google.com/",second_url="https://bing.com/")# Returns shortened URLs. The shortened link is randomly redirected to one of the provided URLs.advurl_shortner.short("https://google.com/",second_url="https://bing.com/",weights=[0.3,0.7])# Returns shortened URLs.# The shortened link is randomly (weighted by weight parameter) redirected to one of the provided URLs.# approximately 30% to "https://google.com/ and 70% to "https://bing.com/"Getting short URL parameters and visit statistics:advurl_shortner.stat("https://illi.cfd/H","aaa")# Returns the parameters and visit statistics of the shortened URL stored with password "1234x".# Example:#{#	"url": "http://google.com/?z=1",#	"second_url": "http://yahoo.com/",#	"ttl": null,#	"date_created": "1703411470",#	"weights": null,#	"description":"Yahoo search engine",#	"visits": 4,#	"primary_url_expired": false#}TODO:More than 2 URLsAdvanced visit statistics
Package: advutils
OverviewThis module encapsulates advanced algorithms for the manipulation data,
counters, events, queues, multiprocessing and more…Stable:Documentation:http://pythonhosted.org/advutilsDownload Page:https://pypi.python.org/pypi/advutilsLatest:Documentation:http://advutils.readthedocs.io/Project Homepage:https://github.com/davtoh/advutilsBSD license, (C) 2015-2017 David Toro <davsamirtor@gmail.com>DocumentationFor API documentation, usage and examples see files in the “documentation”
directory.  The “.rst” files can be read in any text editor or being converted to
HTML or PDF usingSphinx. Read the HTML version is online athttp://advutils.readthedocs.io/en/latest/.Examples are found in the directoryexamplesand unit tests intests.Installationpip install advutilsshould work for most users.Once advutils is successfully installed you can import the it in python as:>>>> import advutilsReleasesAll releases follow semantic rules proposed inhttps://www.python.org/dev/peps/pep-0440/andhttp://semver.org/Contributions and bug reports are appreciated.author: David Toroe-mail:davsamirtor@gmail.comproject:https://github.com/davtoh/advutils
Package: adwordspy
Adwords API wrapperFree software: BSD licenseInstallationpip install adwordspyDocumentationhttps://adwordspy.readthedocs.io/DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.1.0 (2016-05-16)First release on PyPI.
Package: adx2wav
ADX2WAVAn adx2wav c-extension for Python based onadx2wavmod3found onhcs64.com/vgm_ripping.InstallationPIPpip install adx2wavManualpython setup.py installExamplefromadx2wavimportadx2wavwithopen("test.adx","rb")asf:data=f.read()wav=adx2wav(data)withopen("test.wav","wb")asf:f.write(wav)
Package: adxl345
ADXL345=======Python module to use ADXL345. Compatible with Python 2 and Python 3.Based on [pimoroni/adxl345-python](https://github.com/pimoroni/adxl345-python).## InstallInstall it as a dependency using pip:``` bashpip install adxl345```## Usage- Import module and instantiate an ADXL345``` pythonfrom adxl345 import ADXL345adxl345 = ADXL345()```- Get 3-axis accelerations in m.s-²``` pythonaxes = adxl345.get_axes()# Returns something like:# axes['x'] => -0.1614# axes['y'] =>  0.0691# axes['z'] =>  9.8064```- Get 3-axis accelerations in g (Earth gravity)``` pythonaxes = adxl345.get_axes(True)# Returns something like:# axes['x'] => -0.0014# axes['y'] =>  0.0001# axes['z'] =>  1.0012```- Use another IC2 addressBy default, this library uses the `0x53` I2C address.To use another address, set it when creating an instance of ADXL345:``` pythonadxl345 = ADXL345(0x1D)```## Full example``` pythonfrom adxl345 import ADXL345adxl345 = ADXL345()axes = adxl345.get_axes(True)# Returns something like:# axes['x'] => -0.0014# axes['y'] =>  0.0001# axes['z'] =>  1.0012```## LicenseThis project is under [MIT](LICENSE) license.
Package: adz
ADZCommand line interface for HTTP requests defined in yaml configuration file.Installpip install adzQuick startHaving a yaml configuration fileendpoints:
  endpoint:
    request: GET https://httpbin.org/get
    headers:
      Content-Type: application/jsonand running on command lineadz endpointwill executeendpointrequest defined in configuration file and printGET https://httpbin.org/get
HTTP/1.1 200 OK
 • access-control-allow-credentials: true
 • access-control-allow-origin: *
 • content-encoding: gzip
 • content-type: application/json
 • date: Thu, 06 Jun 2019 06:06:06 GMT
 • referrer-policy: no-referrer-when-downgrade
 • server: nginx
 • x-content-type-options: nosniff
 • x-frame-options: DENY
 • x-xss-protection: 1; mode=block
 • content-length: 204
 • connection: keep-alive

{
    "args": {},
    "headers": {
        "Accept": "*/*",
        "Accept-Encoding": "gzip, deflate",
        "Content-Type": "application/json",
        "Host": "httpbin.org",
        "User-Agent": "python-httpx/0.7.1"
    },
    "url": "https://httpbin.org/get"
}ConfigurationFor an example configuration look atdocs/example.yml.settingscolors:bool, default:truecontrol output print in colorsresponse:bool, default:truecontrol response body outputtheme:str, defaultnativeany theme name fromhereshould workvariablesused to interpolate values in headers and urlsvariable: abcapplied onurl: http://example.org/$variableresults inhttp://example.org/abcvariable value starting withfile://is opened as file and loaded as string into variableendpointsdescriptionmethodhttp methodsurlrequestmethod urle.g.get http://example.orgparamsquery string parametersheadersjsonjson stringstring starting withfile://is loaded as json filedatajson stringstring starting withfile://is loaded as json filecookiesfilespath to a file:path/to/file.txtfile name and path:filename: path/to/file.txtConfiguration fileExpected configuration file namesadz.yamloradz.ymlapi.yamlorapi.ymlrest.yamlorrest.ymlExpected locationscurrent location:.user's home:~/.adzdirectory in user's home e.g.~/.adz/Configuration file path can also be set using environmental variableADZ.CLIRunadz -hcommandsadz --config,adz -cpath to yaml configuration fileadz --details <endpoint>,adz -d <endpoint>output details about endpoint from configuration fileadz --list,adz -llist available endpoints in configuration fileadz --output,adz -ooutput processed configuration file as jsonadz --settings,adz -soutput settings in configuration fileadz --var name=value,adz -v name=valueset or override variables in configurationadz --colors,adz --no-colorscontrol output print in colorsadz --response,adz --no-responsecontrol response body outputLicenseADZ is licensed under a three clause BSD License. Full license text can be foundhere.
Package: aea
AEA FrameworkCreate Autonomous Economic Agents (AEAs)The AEA framework allows you to createAutonomous Economic Agents:An AEA is anAgent, representing an individual, family, organisation or object (a.k.a. its "owner") in the digital world. It looks after its owner's interests and has their preferences in mind when acting on their behalf.AEAs areAutonomous; acting with no, or minimal, interference from their owners.AEAs have a narrow and specific focus: creatingEconomicvalue for their owners.To installEnsure you have Python (version3.8,3.9or3.10).(optional) Use a virtual environment (e.g.pipenvorpoetry).Install:pip install aea[all]Please see theinstallation pagefor more details.DocumentationThe full documentation, including how to get started, can be foundhere.ContributingAll contributions are very welcome! Remember, contribution is not only PRs and code, but any help with docs or helping other developers solve their issues are very appreciated!Read below to learn how you can take part in the AEA project.Code of ConductPlease be sure to read and follow ourCode of Conduct. By participating, you are expected to uphold this code.Contribution GuidelinesRead ourcontribution guidelinesto learn about our issue and PR submission processes, coding rules, and more.Development GuidelinesRead ourdevelopment guidelinesto learn about the development processes and workflows when contributing to different parts of the AEA project.Issues, Questions and DiscussionsWe useGitHub Issuesfor tracking requests and bugs, andGitHub Discussionsfor general questions and discussion.LicenseThe AEA project is licensed underApache License 2.0.
Package: ae-ae
aenamespace-root projectae namespace-root: bundling and maintaining templates and documentation of the portions of this namespace.ae namespace root package use-casesthis package is the root project of the ae namespace and their portions (the modules
and sub-packages of the namespace ae). it provides helpers and templates in order to
bundle and ease the maintenance, for example to:update and deploy common outsourced files, optionally generated from templates.merge docstrings of all portions into a single combined and cross-linked documentation.compile and publish documentation via Sphinx ontoReadTheDocs.bulk refactor multiple portions of this namespace simultaneously using thegit repository manager tool (grm).to enable the update and deployment of outsourced files generated from the templates provided by
this root package, add this root package to the development requirements file (dev_requirements.txt)
of each portion project of this namespace. in this entry you can optionally specify the version of
this project.and because this namespace-root package is only needed for development tasks, it will never need to
be added to the installation requirements file (requirements.txt) of a project.please check thegit repository manager manualfor more detailed information on the provided actions of thegrmtool.installationno installation is needed to use this project for your portion projects, because thegrmtool is
automatically fetching this and the other template projects fromhttps://gitlab.com/ae-group(and
in the specified version).an installation is only needed if you want to adapt this namespace-root project for your needs or if you want
to contribute to this root package. in this case please follow the instructions given in the
:ref:contributingdocument.namespace portionsthe following 40 portions are currently included in this namespace:ae_baseae_deepae_django_utilsae_droidae_notifyae_validae_filesae_pathsae_coreae_locknameae_dynamicodae_i18nae_parse_dateae_literalae_progressae_updaterae_consoleae_sys_coreae_sys_dataae_sys_core_shae_sys_data_shae_db_coreae_db_oraae_db_pgae_transfer_serviceae_sideloading_serverae_gui_appae_gui_helpae_kivy_glslae_kivy_dyn_chiae_kivy_relief_canvasae_kivyae_kivy_auto_widthae_kivy_file_chooserae_kivy_iterable_displayerae_kivy_qr_displayerae_kivy_sideloadingae_kivy_user_prefsae_lisz_app_dataae_enaml_app
Package: aeat-web-services
MasterSpanish Tax Agency Electronic Office (AEAT) Integration.Make requestsAEAT Web Servicesand sign your connection and xml using your certificate.Integración con la Agencia Estatal de Administración Tributaria EspañolaRealiza peticiones a losServicios Web de AEATy firma tu conexión y mensajes XML utilizando tu certificado.Usage (English)Example for requesting a list of ENS’s.Initialize a Config object with the desired preconfigured service and if you want to request AEAT test or production endpoints (test_mode).
Finally initialize controller with the config and the desired certificate and make the request with your payload.If you need more control just build the controller by hand, see build_from_config method for inspiration.Preconfigured aduanet services.Official AEAT Web Servicesimportaeatconfig=aeat.Config('ens_presentation',test_mode=True)ctrl=aeat.Controller.build_from_config(config,'cert.pem','key.pem')result=ctrl.request(payload)# See factories for examplesassertresult.valid,f'Error requesting aeat:{result.error}'assertresult.dataisnotNoneUsage (Spanish)Ejemplo de consulta de ENSs.Inicializa el objecto Config con el servicio preconfigurado y si quieres usar los endpoints de AEAT de test o de producción (test_mode).Por último inicializa el controlador con la config y el certificado que gustes y realiza la petición pasándole los datos que necesites.Si necesitas un mayor control simplemente construye el controlador a mano, puedes inspirarte en el método build_from_config.Lista de Servicios Preconfigurados.Servicios Web oficial de AEATimportaeatconfig=aeat.Config('ens_presentation',test_mode=True)ctrl=aeat.Controller.build_from_config(config,'cert.pem','key.pem')result=ctrl.request(payload)# Ver factories para ejemplosassertresult.valid,f'Error requesting aeat:{result.error}'assertresult.dataisnotNoneDjango Rest FrameworkSeveral AEAT Validators and Serializers are provided.Validators: Validate input data to send to AEATSerializers: Serialize AEAT requestfromaeat.rest_frameworkimportvalidatorsvalidator=validators.ENSPresentationValidator(data=payload)assertvalidator.is_valid(raise_exception=True)# Send the request to AEATimportaeatconfig=aeat.Config(service_name,test_mode=settings.AEAT_TEST_MODE)ctrl=aeat.Controller.build_from_config(config,cert_path,key_path)result=ctrl.request(validator.data)assertresult.valid# Parse the responsefromaeat.rest_frameworkimportserializersserializer=serializers.get_class_for_aeat_response(data=result.data)assertserializer.is_valid(raise_exception=False)assert{'mrn':'XXXX'}==serializer.dataassertnotserializer.is_errorPrerequisitesInstall xmlsec prerequisites.
Checkhttps://github.com/mehcode/python-xmlsecInstall$pipinstallaeat-web-servicesDevelop$pythonsetup.pydevelop$pipinstall-rrequirements_test.txtTest$pipinstalltox$toxReleaseshttps://github.com/initios/aeat-web-services/releasesUsefull LinksAEAT Web ServicesAvailable preconfigured servicesStructure, rules and conditions
Package: aeb43
aeb43 is a parser for AEB43 files.NutshellImport:>>> import os
>>> from aeb43 import AEB43Instantiate:>>> aeb43 = AEB43('aeb43/AEB43.txt')The accounts:>>> len(aeb43.accounts)
1
>>> account = aeb43.accounts[0]
>>> account.number
'0001414452'
>>> account.start_date
datetime.date(2018, 3, 18)
>>> account.end_date
datetime.date(2018, 3, 20)
>>> account.initial_balance
Decimal('3005')
>>> account.final_balance
Decimal('2994.02')
>>> account.currency
'978'The transactions:>>> len(account.transactions)
1
>>> transaction = account.transactions[0]
>>> transaction.transaction_date
datetime.date(2018, 3, 19)
>>> transaction.value_date
datetime.date(2018, 3, 19)
>>> transaction.amount
Decimal('-10.98')
>>> transaction.shared_item
'12'
>>> transaction.own_item
'408'
>>> transaction.document
'0000000000'
>>> transaction.reference1
'000000000000'
>>> transaction.reference2
'5540014387733014'
>>> transaction.items
['COMPRA TARG 5540XXXXXXXX3014 DNH*MICHA', 'EL SCOTT']To report issues please visit theaeb43 bugtracker.
Package: ae-base
base 0.3.35ae namespace module portion base: basic constants, helper functions and context manager.installationexecute the following command to install the
ae.base module
in the currently active virtual environment:pipinstallae-baseif you want to contribute to this portion then first forkthe ae_base repository at GitLab.
after that pull it to your machine and finally execute the
following command in the root folder of this repository
(ae_base):pipinstall-e.[dev]the last command will install this module portion, along with the tools you need
to develop and run tests or to extend the portion documentation. to contribute only to the unit tests or to the
documentation of this portion, replace the setup extras keydevin the above command withtestsordocsrespectively.more detailed explanations on how to contribute to this projectare available herenamespace portion documentationinformation on the features and usage of this portion are available atReadTheDocs.