Saravanan666/pypi-org huggingface dataset:
Package: python-datatable
datatableThis is an automate Fork of datatable.
Because there is no automated build / publish pipeline for the datatable package, and it is not optimal to always install from GitHub.
Fork-URL:https://github.com/semmjon/datatable.gitThis is a Python package for manipulating 2-dimensional tabular data structures
(aka data frames). It is close in spirit topandasorSFrame; however we
put specific emphasis on speed and big data support. As the name suggests, the
package is closely related to R'sdata.tableand attempts to mimic its core
algorithms and API.Requirements: Python 3.6+ (64 bit) and pip 20.3+.Project goalsdatatablestarted in 2017 as a toolkit for performing big data (up to 100GB)
operations on a single-node machine, at the maximum speed possible. Such
requirements are dictated by modern machine-learning applications, which need
to process large volumes of data and generate many features in order to
achieve the best model accuracy. The first user ofdatatablewasDriverless.ai.The set of features that we want to implement withdatatableis at least
the following:Column-oriented data storage.Native-C implementation for all datatypes, including strings. Packages such
as pandas and numpy already do that for numeric columns, but not for
strings.Support for date-time and categorical types. Object type is also supported,
but promotion into object discouraged.All types should support null values, with as little overhead as possible.Data should be stored on disk in the same format as in memory. This will
allow us to memory-map data on disk and work on out-of-memory datasets
transparently.Work with memory-mapped datasets to avoid loading into memory more data than
necessary for each particular operation.Fast data reading from CSV and other formats.Multi-threaded data processing: time-consuming operations should attempt to
utilize all cores for maximum efficiency.Efficient algorithms for sorting/grouping/joining.Expressive query syntax (similar todata.table).Minimal amount of data copying, copy-on-write semantics for shared data.Use "rowindex" views in filtering/sorting/grouping/joining operators to
avoid unnecessary data copying.Interoperability with pandas / numpy / pyarrow / pure python: the users
should have the ability to convert to another data-processing framework
with ease.InstallationOn macOS, Linux and Windows systems installing datatable is as easy aspipinstalldatatableOn all other platforms a source distribution will be needed. For more
information seeBuild instructions.See alsoBuild instructionsDocumentation
Package: python-data-transformer
Приведение и преобразование данных в нужный тип средствами Python, для последующей вставки в бдНаписано на версии python 3.5Установкаpip install python-data-transformerДокументацияНа данный момент отсутствуетЗависимостиОтсутствуютАвторПавел МаксимовСвязаться со мной можно вТелеграми вFacebookУдачи тебе, друг! Поставь звездочку ;)
Package: python-datauri
Data URI manipulation made easy.This isn’t very robust, and will reject a number of valid data URIs. However, it meets the most useful case: a mimetype, a charset, and the base64 flag.Installation$pipinstallpython-datauriParsing>>>fromdatauriimportDataURI>>>uri=DataURI('data:text/plain;charset=utf-8;base64,VGhlIHF1aWNrIGJyb3duIGZveCBqdW1wZWQgb3ZlciB0aGUgbGF6eSBkb2cu')>>>uri.mimetype'text/plain'>>>uri.charset'utf-8'>>>uri.is_base64True>>>uri.datab'The quick brown fox jumped over the lazy dog.'Note thatDataURI.datawill always return bytes.
UseDataURI.textto get a string.Creating from a string>>>fromdatauriimportDataURI>>>made=DataURI.make('text/plain',charset='us-ascii',base64=True,data='This is a message.')>>>madeDataURI('data:text/plain;charset=us-ascii;base64,VGhpcyBpcyBhIG1lc3NhZ2Uu')>>>made.datab'This is a message.'Creating from a fileThis is really just a convenience method.>>>fromdatauriimportDataURI>>>png_uri=DataURI.from_file('somefile.png')>>>png_uri.mimetype'image/png'>>>png_uri.datab'\x89PNG\r\n...'SerializingDataURIis a subclass ofstr, so you can just usestr()to print it out:>>>fromdatauriimportDataURI>>>png_uri=DataURI.from_file('somefile.png')>>>str(png_uri)'data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAASABIA...'Pydantic SupportYou can useDataURIas a type forPydanticv1:fromdatauriimportDataURIfromdatauriimportDataURIfrompydanticimportBaseModelclassProfilePicture(BaseModel):image_data:DataURILicenseThis code is released under theUnlicense.CreditsThis is a repackaging ofthis Gistoriginally written byZachary Voase.
Package: python-datauri-whtsky
Data URI manipulation made easy.This isn’t very robust, and will reject a number of valid data URIs. However, it meets the most useful case: a mimetype, a charset, and the base64 flag.Installation$pipinstallpython-datauriParsing>>>fromdatauriimportDataURI>>>uri=DataURI('data:text/plain;charset=utf-8;base64,VGhlIHF1aWNrIGJyb3duIGZveCBqdW1wZWQgb3ZlciB0aGUgbGF6eSBkb2cu')>>>uri.mimetype'text/plain'>>>uri.charset'utf-8'>>>uri.is_base64True>>>uri.datab'The quick brown fox jumped over the lazy dog.'Note thatDataURI.datawill always return bytes, (which in Python 2 is the same as a string).
UseDataURI.textto get the text type (stron Python 3.x,unicodeon Python 2.x).Creating from a string>>>fromdatauriimportDataURI>>>made=DataURI.make('text/plain',charset='us-ascii',base64=True,data='This is a message.')>>>madeDataURI('data:text/plain;charset=us-ascii;base64,VGhpcyBpcyBhIG1lc3NhZ2Uu')>>>made.datab'This is a message.'Creating from a fileThis is really just a convenience method.>>>fromdatauriimportDataURI>>>png_uri=DataURI.from_file('somefile.png')>>>png_uri.mimetype'image/png'>>>png_uri.datab'\x89PNG\r\n...'LicenseThis code is released under theUnlicense.CreditsThis is a repackaging ofthis Gistoriginally written byZachary Voase.
Package: python-dateconv
python-dateconvDescriptionSimple package for convert time between typesUsage$pipinstallpython-dateconvfromdateconvimport*human_time='2015-01-01 18:21:26'datetime_time=datetime.datetime(2015,1,1,18,21,26)my_unix_time=1420136486print(d2u(datetime_time))# 1420114886print(d2h(datetime_time))# 2015-01-01 18:21:26print(h2u(human_time))# 1420114886print(type(h2d(human_time)))# <type 'datetime.datetime'>print(u2h(my_unix_time))# 2015-01-01 18:21:26print(type(u2d(my_unix_time)))# <type 'datetime.datetime'>
Package: python-datemath
Description: UNKNOWN
Keywords: date math datemath elaticsearch solr
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Provides-Extra: dev
Provides-Extra: test
Package: python-datetime-tz
Home-page:http://github.com/mithro/python-datetime-tzAuthor: Tim Ansell
Author-email:mithro@mithis.comLicense: License :: OSI Approved :: Apache Software License
Description: UNKNOWN
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Internationalization
Package: python-dbip
What isdbip?dbip is a library for IP authentication in Python that focuses on authentication security. It builds algorithms written in pure Python and can be ported to other languages.dbipinfrastructuredbip# library name│__init__.py# function table└─dbip.py# system call tabledbipfunction usage methodFilefunction:IPdatabasethatsupportsIPv6andIPv4dual-stackprotocols.

FileDescription:Add,delete,verifyIPinformation

Fileauthor:mxlbb(cutebabyfox)FileDate:August22,2022Filefunction:dbip.add(ip)dbip.update(ip)dbip.remove(ip)dbip.verify(ip)dbip.printf()Why usedbip?dbipdevelopment principles:Security:dbip(used withwebsockets) is used as authentication, the transmitted data can be in plain text and illegal users can only view it and cannot change it;Defense:dbip(used in conjunction withwebsockets) will form an almost absolute elimination of all illegal user connections and brute force cracking;Performance:dbip(used withwebsockets) will reduce the performance consumption of the server authentication process and greatly improve the resource allocation of productivity.Why not usedbip?If you often use web-provided libraries or have your own set of authentication methods, you can deprecate the library functions provided bydbip.what else?Bug reports, patches and suggestions welcome!To report a security vulnerability, please contact the author:Admin@mengyuns.com.For anything else please open anissueor send apull request.
Package: python-dbusx
OverviewPython-dbusx is a alternative Python interface for D-BUS that supports evented
IO. It builds directly on top of libdbus and has no other dependencies.Building and Installing$ python setup.py build
$ sudo python setup.py installRequirementsPython 2.6, 2.7 or 3.3.To use evented IO, you need an event loop adater that supports theEventLoopinterface from the upcoming PEP 3156. Theloopingpackage
provides adapters for libev and libuv. Seehttps://github.com/geertj/looping.Comments and SuggestionFeel free to add an issue on the Github site. Also feel free to send me an
email ongeertj@gmail.com.
Package: python-ddd
PydddPyddd is a super-GDB debugger which could debug python scripts as the
same way to debug c program line by line in the same inferior.DownloadYou can also download a snapshot from the Git repository:as a.tar.gzfile oras a.zipfileInstallationSince Pyddd is written in the Python language, you need to install
Python (the required version is at least 2.6).LinuxRebuild GDB with Python and reinstall it.$tarxzfgdb-7.8.1.tar.gz$cdgdb-7.8.1$./configure--with-python=python--with-babeltrace=no\--enable-tui=no--enable-host-shared$make&&makeinstallExtract Pyddd package, copy libddd.py to gdb data directory.$cplibddd.py/usr/local/share/gdb/pythonBuild pyddd-ipa.$gcc-g-fPIC-I/usr/include/python2.7-Wl,-lpthread-shared-o\python-ipa.soipa.c$cppython-ipa.so/usr/local/libWindowsInstall Cygwin.Rebuild GDB with Python in Cygwin and reinstall it.$tarxzfgdb-7.8.1.tar.gz$cdgdb-7.8.1$./configure--with-python=python--with-babeltrace=no\--enable-tui=no--enable-host-shared$make&&makeinstallUnzip Pyddd package, copy libddd.py to gdb data directory.$cplibddd.py/usr/local/share/gdb/pythonOpen Cygwin Terminal, build pyddd-ipa.$gcc-g-I/usr/include/python2.7-Wl,-lpthread-shared-o\python-ipa.dllipa.c$cppython-ipa.dll/usr/local/libQuick StartAfter installation, invoke the command prompt, go to the directory
including the debugged script foo.py and run those commands (assume
pyddd is extracted at /usr/local/pyddd):$gdb-x/usr/local/pyddd/init.gdb(gdb)py-exec-filepython(gdb)py-filefoo.py(gdb)py-startFor more, see pyddd.rst and rationale.rst.
Package: python-ddns
Python-DDNSThis is program written in python that acts as a DDNS client for various providers. Supports IPv4 and IPv6.
Tested and supported on the following Python versions:3.63.73.83.93.10-rcProvider ListCloudflareHurricane ElectricStrato - @BraumeisterAfraid.org - @BraumeisterDBSimpleNameCheapPython InstallThe recommended way is to use pip to install it.There is a package available onpypi.pipinstallpython-ddns# Setups the config file to the right namepddns-i# Modify config.conf with the require fields.# To check configurationpddns-t# Recommended to test to make sure everything workspddns# Edit crontab to run scriptcrontab-e# Add0****<path/to/pddns>>/dev/null2>&1#Updates every hour.Source InstallSource install if you would rather install it that way.gitclonehttps://gitlab.com/Cyb3r-Jak3/python-ddnscdpython-ddns/
pythonsetup.pyinstall# Setups the config file to the right namepddns-i# Modify config.conf with the require fields.# To check configurationpddns-t# Recommended to test to make sure everything workspddns# Edit crontab to run scriptcrontab-e# Add0****<path/to/pddns>>/dev/null2>&1# Updates every hour.TODOEasier config editingBetter service functionalityOther DNS systems supported
Package: python-dds238
python-dds238This library is very useful when reading the chinese DDS238 (and its variants: DDS238-2, ...)  power meter.This library supposes that you're using an USB-to-RS485 dongle. It doesn't work yet for modbus-over-TCP
(though if you want to propose an MR, i'd accept it gladly !).InstallationTo install the library, simply type:$ pip3 install python-dds238UsageI'ts very simple:>>>fromdds238importDDS238>>>meter=DDS238(modbus_device='/dev/ttyUSB0',meter_id=20)>>>meter.voltage215.4>>>meter.power1632>>>meter.export_energy1288.2DOC|  current
 |      Returns the current in Amperes
 |
 |  export_energy
 |      Returns the exported energy, in kWh
 |
 |  frequency
 |      Returns the frequency in Herz
 |
 |  import_energy
 |      Returns the imported energy, in kWh
 |
 |  power
 |      Returns the power in Watts. Positive is import. Negative power is exported
 |
 |  power_factor
 |      Returns the power factor (0-1 scalar)
 |
 |  reactive_power
 |      Return the reactive power in VAr
 |
 |  voltage
 |      Returns the voltage in Volts
 |
 |  ----------------------------------------------------------------------
 |
 |  change_address(self, address: int, baudrate=9600)
 |      Change the modbus address and the baudrate of the current device. USE AT YOUR OWN RISK !
Package: python-debauto-br
python-debauto-brCriação de remessas de débito automático no formato CNAB 150 da Febraban.BancosBancoCriadoValidadoSantanderSimSimBanco do BrasilSimSimCaixaSimSimComeçandoPré-requisitosEntre em contato com o banco para obter os dados de sua conta e convênio para poder utilizar o serviço de débito automático.InstalaçãoInstale o pacote via pippip install python-debauto-brUtilizaçãoPara criar uma remessa, devemos primeiro criar uma classe de configuração.fromdebauto.remessaimportConfiguracaocfg=Configuracao(agencia='0001',# Agência bancáriaconta='11-1',# Conta bancáriaconvenio='222222222222',# Número de convênioempresa='Empresa Exemplo',# Nome da empresasequencial='1',# Número sequencialvencimento='01/01/1900'# Data de criação)Agora podemos importar a remessa e passar o arquivo de configuraçãofromdebauto.bancos.caixaimportCaixaremessa=Caixa(cfg)Com a remessa devidamente instanciada, podemos inserir os débitosfromdebauto.remessaimportDebitoremessa.debitos=Debito(9999,# identificacao      25 posições9999,# agência            04 posições9999,# conta              13 posições"01/01/1900",# data vencimento    08 posições10.00,# valor              15 posições"03",# código da moeda    02 posições"Exemplo 1",# identificação co   59 posições0)# 0 - Normal    1 - CancelamentoApós inserir os débitos, temos tudo pronto para criar o arquivo de remessapath='/tmp/'remessa.gerar_txt(path)O código acima criará um arquivo no path /tmp/. O formato do nome do arquivo segue o padrãoNOMEDOBANCO_DATAVENCIMENTO_SEQUENCIAL.txtAutorFlávio MilanVeja a lista completa de contribuidores emcontribuidores.LicençaEste projeto está licenciado sobre MIT License - vejaLICENSE.mdpara mais detalhes.Gostou do projeto?Aceito uma :cerveja:!
Package: python-debian
This package provides Python 3 modules that abstract many formats of Debian
related files. Currently handled are:Debtags information (debian.debtags module)debian/changelog (debian.changelog module)Packages files, pdiffs (debian.debian_support module)Control files of single or multiple RFC822-style paragraphs, e.g.
debian/control, .changes, .dsc, Packages, Sources, Release, etc.
(debian.deb822 module)Raw .deb and .ar files, with (read-only) access to contained
files and meta-information
Package: python-debianbts
python-debianbtsPython-debianbts is a Python library that allows for querying Debian'sBug
Tracking System. Since 2011, python-debianbts is used
by Debian'sreportbugto query the Bug Tracking System and has currently
(2017-11) roughly190.000 installations.Onlinedocumentationis available on readthedocs.Installingpipinstallpython-debianbtsQuickstart>>>importdebianbtsasbts>>>bts.get_bugs(package='python-debianbts')[803900,787723,824111,639458,726878,722226,789047]>>>bts.get_status([803900,787723])[<debianbts.debianbts.Bugreportat0x7f47080d8c10>,<debianbts.debianbts.Bugreportat0x7f47080d80d0>]>>>forbinbts.get_status([803900,787723]):...print(b)...originator:AntonioTerceiro<terceiro@debian.org>date:2015-06-0413:09:02subject:reportbug:crasheswhenqueryingDebianBTSforreportsonwnppmsgid:<20150604130538.GA16742@debian.org>package:python-debianbtstags:['fixed-upstream','patch','jessie']done:Trueforwarded:https://github.com/venthur/python-debianbts/pull/5mergedwith:[722226,726878,789047]severity:importantowner:found_versions:[]fixed_versions:['python-debianbts/1.13']blocks:[]blockedby:[]unarchived:Truesummary:affects:[]log_modified:2019-07-0807:27:36location:archivearchived:Truebug_num:787723source:python-debianbtspending:donedone_by:BastianVenthur<venthur@debian.org>originator:Wookey<wookey@debian.org>date:2015-11-0301:39:01subject:reportbugerrorsoutwithSOAPerrormsgid:<20151103013542.11170.31413.reportbug@cheddar.halon.org.uk>package:python-debianbtstags:[]done:Falseforwarded:mergedwith:[]severity:normalowner:found_versions:[]fixed_versions:['python-debianbts/2.0']blocks:[]blockedby:[]unarchived:Falsesummary:affects:[]log_modified:2015-11-0308:36:04location:db-harchived:Falsebug_num:803900source:python-debianbtspending:pendingdone_by:None
Package: python-debouncer
Asyncio DebouncerDescriptionThis Python package provides adebouncedecorator.
It's designed for rate-limiting function calls in asynchronous Python applications.📋 RequirementsPython 3.9 or later.python-immutable📦 InstallationThe package handle in PyPI ispython-debouncerPippipinstallpython-debouncerPoetrypoetryaddpython-debouncer🛠 UsageImport the decorator and apply it to your async functions:fromdebouncerimportDebounceOptions,debounce@debounce(wait=.5,options=DebounceOptions(trailing=True,leading=False,time_window=3))asyncdefyour_function():# Function bodyLodash documentation⚠️ Important NotemaxWaitin Lodash implementation is renamed totime_windowhere, I think semantically
it makes more sense.🎉 DemoSeedemo.pyfor a usage example.🤝 ContributingContributions are welcome. Please fork the repository and open a pull request.🔒 LicenseThis project is released under the Apache-2.0 License. See theLICENSEfile for more details.
Package: python-deco
pythonDecoractorAn OSS that has something to do with decorators in python:sparkles: FeaturesTime related decoratorsDebugging decoratorsCustom cli input decorators:hammer: InstallTo install, run the following command.$pipinstallpython-deco:package: ModulesInfo: Decorators that provide information about the function.Debug: Decorators that help debug the function.CLI: Decorators that uses variables defined in a [yaml/json] file as function arugments.Fun: Decorators just for FUN!:books: UsageA quick usage example.@timeitfrompyDeco.devimportinactivefrompyDeco.timeimporttimeit@timeitdeffunc():# do somethingreturn12023-02-1700:05:09,721[INFO]Functionfunc()took2.0120s.:construction: TODOUpdate docsRefactor codeFlowchart Modulecreditshttps://bytepawn.com/python-decorators-for-data-scientists.html
Package: python-decouple-aws
Python Decouple AWShelps you to organize and access sensitive information on AWS Secrets Manager.It also makes it easy for you to:Not repeat the boto3 boilerplate code;Define default values;Use os.environ as fall back;Supports Python 3.4+WhySingle place to save all secrets (AWS Secrets Manager)Keep sensitive information away from code and environmentsSimpler API to access AWS Secrets Manager (rather than boto3)Installationpip install python-decouple-awsUsage example 1#  settings.py
from decouple_aws import get_config

# The package provides a wrapper function that will
# fallback to environment variables and fail gracefully
# if AWS Secrets Manager is not accessible for whatever
# reason.
config = get_config('your-project/secret/name', 'ap-southeast-2')

# Use decouple config like normal
MY_EMAIL_USER = config('MY_EMAIL_USER', 'default-user')
MY_EMAIL_PASS = config('MY_EMAIL_PASS')Usage example 2# settings.py
from decouple import Config
from decouple_aws import RepositoryAwsSecretManager

# if you would like it to fail if secrets
# manager is inaccessible, you can build it manually.
# initialise the config with the AWS repository
# Pass the repo your secret name and the region
repo = RepositoryAwsSecretManager('your-project/secret/name', 'ap-southeast-2')
config = Config(repo)

# Use decouple config like normal
MY_SUPER_SECRET_SETTING = config('MY_SUPER_SECRET_SETTING')
Package: python-deepcompare
python-deepcomparepython-deepcompareis a library to deep compare data structures with each other. It can check if two data
structures contain the same data, or if a data structure is a subset of another data structure. The library
supportsSequence(e.g.listortuple) andMapping(e.g.dict) types for the deep comparison.InstallationWith acorrectly configuredpipenvtoolchain:pipenvinstallpython-deepcompareYou may also use classicpipto install the package:pipinstallpython-deepcompareGetting startedHow it worksAs a default, the comparison treats allSequenceand allMappingtypes the same (e.g.(1, 2, 3)is equal to[1, 2, 3]). To enable strict type checks, use thestrictkeyword argument.Thepartial_comparemethod checks if the data structure given as the second parameter is a subset of the data
structure given as the first parameter.ForMappingtypes this means, that all keys of the second data structure are also keys on the first data
structure, and the values of the keys are also equal (e.g.{'a': 1, 'b': 2}is a subset
of{'a': 1, 'b': 2, 'c': 3}, but{'a': 1, 'b': 2, 'd': 4}is not).ForSequencetypes this means, that all values of the second data structure are also values of the first data
structure, and the values are in the same order (e.g.[1, 3, 5]is a subset
of[1, 2, 3, 4, 5], but[1, 5, 3]is not).Usageimportdeepcompare# test if two data structures are equal, but the types to not need to match exactlydeepcompare.compare({'key1':(1,2,3),'key2':{'key3':[4,5,6]}},{'key1':[1,2,3],'key2':{'key3':(4,5,6)}},)# returns: True# test if two data structures are equal, and make sure the types match exactlydeepcompare.compare({'key1':(1,2,3),'key2':{'key3':[4,5,6]}},{'key1':[1,2,3],'key2':{'key3':(4,5,6)}},strict=True,)# returns: False# test if the second data structure is contained within the first, but# the types to not need to match exactlydeepcompare.partial_compare({'key1':(1,2,3),'key2':{'key3':[4,5,6]},'key4':True},{'key1':[1,2],'key2':{'key3':(4,6)}},)# returns: True# test if the second data structure is contained within the first, and# make sure the types match exactlydeepcompare.partial_compare({'key1':(1,2,3),'key2':{'key3':[4,5,6]},'key4':True},{'key1':[1,2],'key2':{'key3':(4,6)}},strict=True,)# returns: FalseList of developersAndreas StockerAStocker@anexia-it.com, Lead Developer
Package: pythondefender
PyDefenderMade with program protection in mind.AcknowledgementsKova / apiPython ProtectorStoryI foundPython Protectora couple months ago and have been using it! But recently, I have been encountering issues, the github hasn't been updated since June 7th (As of September 6th), so I decided, lets use there base, fix the issues, and hopefully update it more in the future!FeaturesConfigurable module system (Enable / Disable Modules)Configurable detection system (What it does when something is detected)Encrypted logging system with remote uploadingDiscord webhook supportClean codeConstantly updatedInstallationPython 3.11 or higher is requiredInstall viaPyPi:py -3 -m pip install -U pythondefenderUsagefrompathlibimportPathfromthreadingimportThreadfrompydefenderimportPyDefenderDefender=PyDefender(debug=True,modules=["AntiProcess","AntiVM","Miscellaneous","AntiDLL","AntiAnalysis","AntiDump"],logs_path=Path.home()/"AppData/Roaming/PyDefender/logs/[Security].log",webhook_url="%INSERT_WEBHOOK_URL&",on_detect=["Report","Exit","Screenshot"],)if__name__=="__main__":DefenderThread=Thread(name="PyDefender Security",target=Defender.start)DefenderThread.start()