Saravanan666/pypi-org huggingface dataset:
Package: sdflexutils
sdflexutilsis a library for interfacing and managing HPE Superdome Flex
Servers. This library is used by OpenStack Ironic hardware typesdflex-redfishfor managing Superdome Flex Servers in OpenStack Ironic
environment. This hardware type is provided bysdflex-ironic-driver.InstallationInstall the module fromPyPI:pip install sdflexutilsor:git clone https://github.com/HewlettPackard/sdflexutils
cd sdflexutils
pip install .UsageFor interfacing with the Superdome Flex Server, useSDFlexClientobject:>>> from sdflexutils import client
>>> sdflex_client = client.SDFlexClient('https://10.10.1.57', 'administrator', 'password', 'redfish/v1/Systems/Partition0')
>>> sdflex_client.get_host_power_status()
'OFF'
>>>DocumentationFor more documentation onsdflexutilslibrary, seesdflexutils
wiki page.Reporting BugsTo report bugs, usegithub issues.
Package: sdflit
SDF-LitUsagepipinstallsdflitTry it in Python:>>>importsdflitassdf>>>sphere=sdf.Sphere((0,0,0),1)>>>sphere.distance((0,0,0))-1.0>>>sphere.distance((1,0,0))0.0>>>sphere.distance((1,1,1))0.7320507764816284DevelopmentSetup Python venv:python-mvenv.envsource.env/bin/activate
pipinstallmaturinBuild Python package after each modification:maturindevelopLicenseThis work is licensed under aApache-2.0.Copyright (c) 2023-present, Zexin Yuan
Package: sdf-timing
python-sdf-timingPython library for working Standard Delay Format (SDF) Timing Annotation files.Standard Delay FormatFrom Wikipedia;Standard Delay Format (SDF) is an IEEE standard for the representation and
interpretation of timing data for use at any stage of an electronic design
process. It finds wide applicability in design flows, and forms an efficient
bridge betweenDynamic timing verificationandStatic timing analysis....It is an ASCII format that is represented in a tool and language independent
way and includes path delays, timing constraint values, interconnect delays
and high level technology parameters.It has usually two sections: one for interconnect delays and the other for
cell delays.SDF format can be used for back-annotation as well as forward-annotation.Linkspython-sdf-timing GitHub RepositorySDF Parser written in C++-Verilog To Routing-
Verilog to Routing can generate an SDF file for doing post implementation timing simulation.
Package: sd-geninfo
sd-geninfoPython CLI for reading metadata embedded in images generated by Stable Diffusion.DependenciesPython 3.xpython-pillow/PillowInstallation$pipinstallsd-geninfoUsageusage: sd-geninfo [-h] [-i INPUT] [-c COLOR] [-m] [-f {json,yaml}]

Python CLI for reading metadata embedded in images generated by Stable Diffusion.

options:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Path to input image from which to read metadata,
                        alternatively you can pass the input path on stdin
  -c COLOR, --color COLOR
                        Whether or not the JSON output should be printed in
                        color, to pretty print the json result in color, defaults
                        to "--color=auto" which will pretty print when stdout is
                        detected as a terminal, pass "--color=never" to force
                        printing in plain text, pass "--color=always" to force
                        pretty printing
  -m, --minify          Whether or not to minify the json result, defaults to
                        False
  -f {json,yaml}, --format {json,yaml}
                        The format to output the metadata in, json or yaml,
                        defaults to json
Package: sdg-flasher
Универсальный загрузчик ПО в микроконтроллеры:
avr8, 1887ve4u, avr16, 1986ve1t, 1986ve91t, stm32f4Можно использовать из командной строки:
python -m sdg_flasher -p COM1 -c 500000_O_2 -d ve1t -a 85 -o w -f "ololo.hex"Пример использования:fromsdg_ioimportSdgIOfromsdg_flasherimportFlasherio=SdgIO('COM1','115200_O_2')Flasher(io,file='ololo.hex',device='ve1t, opt='wv', addr=b'', rebootcmd='b'').do()
Package: sdg-io
СКБ-шный стек протоколов обмена через "последовательный порт"Передача:-> CRC16 -> SLIP -> UART.Прием:<- CRC16 <- SLIP <- UART.CRC16-> канальный уровень, контроль целостности пакетов (на библиотеке crcmod).SLIP-> канальный уровень, для деление потока на пакеты (https://tools.ietf.org/html/rfc1055).UART-> физический уровень (на библиотеке pyserial).Для контроля целостности пакета используется контрольная суммаCRC-16, рассчитываемая
по алгоритмуCRC-16 CCITT REVERSED(полином –0x1021, начальное значение –0хFFFF).CRCрассчитывается по данным до их преобразования в пакет, передается после данных младшим байтом вперед.
БайтыCRCвходят в состав пакета, т.е. подлежат перекодировке поSLIP.Информационные сообщения между устройствами пересылаются в виде пакетов кодированныхSLIP-ом:
признаком конца пакета является байт со значением0хC0.
байт данных со значением0хC0заменяется последовательностью байт0хDB 0хDC;
байт данных со значением0хDBзаменяется последовательностью байт0хDB 0хDD.
Для повышения помехоустоичивости обмена применяется0хС0перед пакетом.Структура пакета -0хС0, data bytes..., crc16L, crc16H, 0хС0.Пример использования:fromsdg_ioimportSdgIO,rand_bytesp=SdgIO('COM1','115200_O_2')p.write(rand_bytes(mtu=256))# — send msg —print(p.read(timeout=.3))# — recive msg —
Package: sdgne
AboutSDGnE (Synthetic Data Generation and Evaluation) is a Python package designed to generate synthetic data and evaluate its quality using neural network models.This tool is intended for developers and researchers who require synthetic datasets for testing and development.The current dittto versionv1.0.0usesAutoencodersandSMOTEto generate synthetic data.Getting Startedpip install sdgneNotebooksTo get started, we have created notebook for the Autoencoder and SMOTE algorithm.Auto EncoderAutoencoders are a class of neural networks designed for unsupervised learning and representing features in a smaller space. They consist of an encoder and a decoder, intending to learn the input data's compressed representation (encoding).  We leverage this architecture to generate synthetic data.SMOTESMOTE, abbreviated as Synthetic Minority Oversampling Technique, is used to generate synthetic data from the original dataset. Over the years, several variants of SMOTE have been developed, each tailored to specific scenarios and requirements. These variants employ distinct methodologies and innovations to enhance the generation of synthetic data, thereby improving model performance by ensuring a more balanced distribution of classes. We provide a few SMOTE variants for synthetic data generation.ComparisonIn this notebook, we will compare theSingle Encoder Autoencoderand theSMOTE Algorithmfor synthetic data generation. We will generate synthetic data using both the algorithms and perform statistical evaluation.FeaturesData Generation: Create synthetic datasets that mimic the statistical properties of real-world data.Neural Autoencoders: Utilize various autoencoder architectures to learn data representations.Evaluation Metrics: Assess the quality of synthetic data using built-in evaluation metrics.Extensibility: Easily extend the package with custom data generators and evaluators.LinksDocumentation:https://seattle-university.gitbook.io/sdgne/
Package: sdhash
# SDHash [![Build Status](https://travis-ci.org/horia141/sdhash.svg?branch=master)](https://travis-ci.org/horia141/sdhash)A Python library for computing hashes of images which ignore perceptual differences.## Usage```pythonimport sdhashfrom PIL import Imagei1 = Image.open('test1.png')i2 = Image.open('test1_noise.png')i3 = Image.open('test2.png')sdhash.test_duplicate(i1, i2) # Truesdhash.test_duplicate(i1, i3) # Falsesdhash.hash_image(i1) # [ an md5 output ]```## BackgroundSuppose you want to test that two images are identical. The naive approach of simply comparing the byte-array representation of the two is not good.## Algorithm## Installation ##The Python image library and NumPy/SciPy etc.Installation is simple, via `pip`:```bashpip install sdhash```## TODOResistance to rotation, mirroring etc.Tunable knobs (for similarity detection etc.)
Package: sdinterp
Spacial data interpolationThis package provides single interface for different interpolation methods.ExampleRegular usage of ordinary kriging methodimportnumpyasnpfromsdinterp.variogramimportcalc_empirical,get_cov_model,fit_cov_modelfromsdinterp.interpolation.krigingimportOrdinary# prepare datan=100points=np.random.random((n,2))target=np.random.random((n,))# get empirical variogram and fit model to itbin_center,gamma=calc_empirical(points,target)cov_model=get_cov_model("exponential")fit_cov_model(cov_model,bin_center,gamma)# init interpolation modelmodel=Ordinary(cov_model,points,target)# evaluate modelprediction=model(np.random.random((1000,2)))Supported methodsSimple KrigingOrdinary KrigingUniversal KrigingInverse Distance WeightingNearest NeighboursLinearRadial basis functionSupported covariance modelsGaussianExponentialMaternIntegralStableRationalCubicLinearCircularSphericalRequirementsgstools >= 1.4.1numpy >= 1.23.5scipy >= 1.10.0Develop and testDownload projectCreate new virtualenv and install requirements.txtFor testing runpytestfrom rootBuild and releaseBuild withpython -m buildDeploy totest.pypi.orgwithtwine upload --repository testpypi dist/*Deploy topypi.orgwithtwine upload dist/*ContactYou can contact me viapopov.aleksandr.v01@gmail.com
Package: sdio
import setuptoolswith open("README.md", "r") as fh:
long_description = fh.read()setuptools.setup(
name='sdio',version='0.1',
scripts=['sdio'] ,
author="ShanmugK",
author_email="shanmugk@gmail.com",
description="A SD io-ctl",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/javatechy/dokr",
packages=setuptools.find_packages(),
classifiers=[
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
"Operating System :: OS Independent",
],
)
Package: sd-ironmq
A plugin for theServer Densityagent that monitorsIronMQ queuesusing API version 3.PyPI page|GitHub projectFor details how to write one, read theofficial docs on plugins. Or find moreofficial plugins.FeaturesMonitors all queues of the given projects.Recorded metrics:size (key: <projectid/-name>:<queuename>:size)total_messages (key: <projectid/-name>:<queuename>:size)Example for metric keys:billingproject:invoicequeue:size
billingproject:invoicequeue:total_messagesHow to useInstall via PyPI or …Get it from pypi, installing it somewhere:pip install sd-ironmqSymlink it to your plugin directory, on Debian/Ubuntu by default:/usr/bin/sd-agent/pluginsInstall via curlcurlthe latest version from GitHub directly into your Plugin directory:curl https://raw.githubusercontent.com/engagespark/sd-ironmq/master/IronMQ.py > /usr/bin/sd-agent/plugins/IronMQ.pyConfigureAdd this section to your/etc/sd-agent/config.cfg:[IronMQ]
host=mq-aws-eu-west-1-1.iron.io
# comma separated list of project IDs
project_ids=<your-project-ids>
token=<your-token>Restart the agentOn Debian/Ubuntu:service sd-agent restartOther configuration optionsMetric Keys: Use Project Names instead of IDsLet’s say you configured the queues of your billing project to be monitored:project_ids=2342934839ai239ai89iFor a queueinvoices, the metric keys would look like so:2342934839ai239ai89i:invoices:size
2342934839ai239ai89i:invoices:total_messagesThat’s not beautiful, nor understandable. Also it exposes IronMQ internals unnecessarily. Configure a name for the project ID like so:2342934839ai239ai89i.name=billingThe name is then used in the keys:billing:invoices:size
billing:invoices:total_messagesTest locallyCreate an example.cfg in the working directory:[IronMQ]
host=mq-aws-eu-west-1-1.iron.io
project_ids=<your-project-ids>
token=<your-token>Run the plugin:python IronMQ.pyReleasingPrepareInstalltwineandwheel:$ pip install -r requirements_dev.txtSetup your.pypirc.Release a new versionUpdate CHANGELOG.Update version in setup.py, commit, push.Tag as that version, seegit tag,push –tagsBuild distributables:$ python setup.py sdist bdist_wheelUpload distributable to PyPI:$ twine upload --sign dist/*LicenseMIT, seeLICENSEfile, CopyrightengageSPARK
Package: sdist_check
sdist_check|sources|issuessetuptoolsplugin providing a new commandsdist_check. It is
run like any other regularsetuptoolscommand:$ python setup.py sdist_check
running sdist_checkand does some additional checks compared to thesetuptoolsbuilt-in
commandcheck. For instance it scans distributions built withsdistfor files you most probably do not want to be part of the
distribution.A list of all supported options of thesdist_checkcommand can be
retrieved like this:$ python setup.py sdist_check --help
Common commands: (see '--help-commands' for more)

  setup.py build      will build the package underneath 'build/'
  setup.py install    will install the package

  ...

Options for 'sdist_check' command:
  --metadata (-m)          Verify meta-data
  --restructuredtext (-r)  Checks if long string meta-data syntax are
                           reStructuredText-compliant
  --strict (-s)            Will exit with an error if a check fails
  --badfiles (-b)          Check files included in dist for unusual names

...Thebadfilesoption is a list of filename patterns which are
considered as non-wanted in distributions. By default, we look for
files named like"*~".Changes0.1 (2015-10-06)Initial release.
Package: sdj-remotetools
SDJ-REMOTETOOLSDescriptionsdj-remotetoolsis a python collection of tools working through SSH.ToolsAll tools handle SSH connection using Paramiko.rcatWorks like 'cat' command but for remote files through SSH and with few enhancementsusage: rcat [-h] [-p] [-e ENCODING] [-b] [-s] remote_files [remote_files ...]

Works like 'cat' but through SSH.

positional arguments:
  remote_files          SSH path to the remote files, space separate, ie: joe@remote.host:/path/to/file

options:
  -h, --help            show this help message and exit
  -p, --password        Ask user for password
  -e ENCODING, --encoding ENCODING
                        Character encoding, ie: utf-8 (default)
  -b, --border          Draw border around the content
  -s, --syntax_highlight
                        Enable console syntax highlightingrlistWorks like 'ls' command but for remote path through SSH (with fewer options).usage: rlist [-h] [-a] [-l] [-p] ssh_url

Works almost liks 'ls' but through SSH

positional arguments:
  ssh_url         SSH path to a remote file or directory, space separate, ie: joe@remote.host:/remote/path

options:
  -h, --help      show this help message and exit
  -a, --all       Show hidden and 'dot' files. Default: False
  -l, --long      Display extended file metadata as a table
  -p, --password  Ask user for password. Default: FalserexecExecutes command on a list of remote hosts and output results on screen or to a file.usage: rexec [-h] [-u USERNAME] [-p PASSWORD] [-o OUTPUT] [-s] remote_hosts command

Executes command on a list of remote hosts and output result.

positional arguments:
  remote_hosts          A coma separated list of hosts. Ex: root@127.0.0.1,joe@example.org
  command               The command to execute on remote hosts

options:
  -h, --help            show this help message and exit
  -u USERNAME, --username USERNAME
                        Username for ssh authentication. Must be the same for all hosts
  -p PASSWORD, --password PASSWORD
                        Password for ssh authentication. Must be the same for all hosts
  -o OUTPUT, --output OUTPUT
                        Write output to this file. It not set output will print on stdout
  -s, --syntax_highlight
                        Enable console syntax highlighting
Package: sdjson
Custom JSON Encoder for Python utilising functools.singledispatch to support custom encoders for both Python’s built-in classes and user-created classes, without as much legwork.DocsTestsPyPIAnacondaActivityQAOtherUsageCreating and registering a custom encoder is as easy as:>>> import sdjson
>>>
>>> @sdjson.dump.register(MyClass)
>>> def encode_myclass(obj):
...     return dict(obj)
>>>In this case,MyClasscan be made JSON-serializable simply by callingdict()on it. If your class requires more complicated logic
to make it JSON-serializable, do that here.Then, to dump the object to a string:>>> class_instance = MyClass()
>>> print(sdjson.dumps(class_instance))
'{"menu": ["egg and bacon", "egg sausage and bacon", "egg and spam", "egg bacon and spam"],
"today\'s special": "Lobster Thermidor au Crevette with a Mornay sauce served in a Provencale
manner with shallots and aubergines garnished with truffle pate, brandy and with a fried egg
on top and spam."}'
>>>Or to dump to a file:>>> with open("spam.json", "w") as fp:
...     sdjson.dumps(class_instance, fp)
...
>>>sdjsonalso provides access toload,loads,JSONDecoder,JSONDecodeError, andJSONEncoderfrom thejsonmodule,
allowing you to usesdjsonas a drop-in replacement
forjson.If you wish to dump an object without using the custom encoders, you
can pass a differentJSONEncodersubclass, or indeedJSONEncoderitself to get the stock functionality.>>> sdjson.dumps(class_instance, cls=sdjson.JSONEncoder)
>>>When you’ve finished, if you want to unregister the encoder you can call:>>> sdjson.encoders.unregister(MyClass)
>>>to remove the encoder forMyClass. If you want to replace the encoder with a
different one it is not necessary to call this function: the@sdjson.encoders.registerdecorator will replace any existing decorator for
the given class.Note that this module cannot be used to create custom encoders for any objectjsonalready knows about; that is:dict,list,tuple,str,int,float,bool, andNone.TODOAdd support for custom decoders.
Package: sdkBraspag
#SDK Braspag###Gerar Token de autenticaÃ§Ã£ofrom Auth import Auth


client_id = {{client Id fornecido pela Braspag}}
client_secret = {{client Secret fornecido pela Braspag}}

auth = Auth(client_id, client_secret)

# Gera o token de autenticaÃ§Ã£o
auth.generate_token()

# Retorna o token gerado
print(bp.token)

# Verifica se o token ainda Ã© vÃ¡lido
print(bp.expired_token())
Package: sdk-dominator
# SDK DominatorBased on `Dominator` gun from `Psycho-Pass`, it reads and analyzes user data to determine the risk of user on financial systems.### Helper methodsIf you want, you can send `User` model to `Dominator` and it will call few methods that you can use.Sample:```pythonfrom dominator import Dominatorfrom core.models import UserDominator().validate_tax_id("...", user=User)```If `Tax ID` is invalid, `Dominator` will try call `dominator_lock_account()` method inside the given model. So you just need create a method to execute anything you may need do if account need be locked.If `Tax ID` is valid, `Dominator` will call for `dominator_is_valid_tax_id` sending the `SERPRO` answer as parameter.Sample `CPF` answer parameter:```{"tax_id": "077.703.749-10","name": "RAPHAEL FILIPE SCHUBERT","birthday": pendulum.date(year=1992, month=2, day=10),"raw": {"ni": "07770374910","nome": "RAPHAEL FILIPE SCHUBERT","nascimento": "10021992","situacao": {"codigo": "0", "descricao": "Regular"}}}```It will be sended as `serpro` parameter, so you will need an method like:`def dominator_is_valid_tax_id(self, *args, **kwargs)` than you will be able to access it as `serpro['tax_id']` or any data inside it.You can provide an `cpf_django_model` on `validate_tax_id` method that will try find and store SERPRO CPF on database.
Package: sdk_entrepot_gpf
SDK Python pour la GéoplateformeInstallationInstallez le module via pip :pipinstallsdk_entrepot_gpfVous pouvez ensuite l'utiliser comme exécutableou l'importer dans vos scripts Python.DéveloppementSi vous souhaitez participer au développement du projet, consultez ledocument détaillant comment procéder.
Package: sdk-ifood
SDK PYTHONSDK de integração IFood em pythonQuer contribuir ? Envie seu PR😎IntroduçãoCriação de sdk com intuito de aprendizado próprio na geração de pacotes opensourcePara que você possa realizar os testes crie sua conta de desenvolvedor no novo portal do desenvolvedor do IFoodClique aqui para acessar o portal do Dev do IFoodDocumentaçãoAs funções são bem intuitivas, basta dar uma breve olhada na documentação da API do IFood e solicitar o desejado no SDKClique aqui para acessar a documentação da APIInstalaçãoInstale a dependência via gerenciador pippip install sdk-ifoodExemplo práticofromifood.exceptionimportIfoodExceptionfromifood.modelimportOrderfromifood.serviceimportIfoodServicetry:ifood_service=IfoodService(client_id='seu client_id',client_secret='seu client_secret',grant_type='client_credentials')# print(ifood_service.credentials.token)# Cada módulo deles são separados no serviço:"""- financial- merchant- order- catalog"""# Buscando os eventos de pedido da sua lojaevent_list=ifood_service.order.get_events_polling()foreventinevent_list:# Se o evento for igual a PLACED realize sua regra de negócioifevent.full_code=='PLACED':# Realize o request dos detalhes, pois se não o IFood não aceitará seu request de confirmaçãoorder:Order=ifood_service.order.get_order_details(event.order_id)# print(order)ifood_service.order.post_order_confirm(event.order_id)# Realizando o ack do eventoifood_service.order.post_events_ack(event)exceptIfoodExceptionasifoodException:print(ifoodException.__str__())Caso deseje utilizar os serviços dos módulos avulsos:fromifood.serviceimportAuthenticationService,OrderServicefromifood.modelimportToken,Order# Create a token instancecredentials=AuthenticationService(client_id='seu client_id',client_secret='seu client_secret')credentials.execute()print(credentials.token)# Módulo pedidoorder_service=OrderService(credentials.token)order:Order=order_service.get_order_details('id do pedido')Em breve mais módulos e correções...
Package: sdkite
SDKiteA simple framework for building SDKs and API clients📖 Documentation|📃 ChangelogThis project is under heavy development. Breaking changes in future versions are to be
expected.Main points before alpha version:Minimal documentationComplete documentationImprove HTTP adapterSupport for more request body types (basic types)Support for even more request body types (files, iterables)Handle retryingHandlebadstatus codesBuiltin auth handlers like basic authUsual shortcuts like.get(...)for.request('get', ...)Allow to disable interceptors on a specific requestWraptrequests' exceptionsSupport more HTTP adaptersReal end-to-end integration test for HTTP endpointsRemoverequestsfrom dependenciesAnd more!
Package: sdklib
Sdklib helps you to write you own client library which will consume a specific service.HighlightsPython 2.7+ or 3.3+.Only http/https protocol is currently supported.BDD integration.InstallInstall thesdklibpackage using pip:pip install sdklibSampleFind my first SDK on github:https://github.com/ivanprjcts/my-first-sdkfromsdklib.httpimportHttpSdkclassFirstSdk(HttpSdk):"""
    My First Sdk.
    """DEFAULT_HOST="http://mockapi.sdklib.org"API_ITEMS_URL_PATH="/items/"defcreate_item(self,name,description=None):"""
        Create an item.

        :type name: str
        :type description: str
        :return: SdkResponse
        """params=parse_args(name=name,description=description)returnself.post(self.API_ITEMS_URL_PATH,body_params=params)Run testsRunning testing with coverage:py.test --cov=sdklib tests/ContributingCheck for open issues or open a fresh issue to start a discussion around a feature idea or a bug.Fork the repository on GitHub to start making your changes to the master branch (or branch off of it).Write a test which shows that the bug was fixed or that the feature works as expected.Send a pull request and bug the maintainer until it gets merged and published. Make sure to add yourself to Authors.AuthorsIvan Martin Vedriel -@ivanprjctsRubén González Alonso -@rgonalo
Package: sdkmanager
A drop-in replacement forsdkmanagerfrom the Android SDK written in Python.
It implements the exact API of thesdkmanagercommand line.  It only deviates from that API if it can be done while being 100%
compatible.The project also attempts to maintain the same terminal output so it can be
compatible with things that scrapesdkmanageroutput.Code FormatThis project uses Black to automatically format all the Python code.  It uses
the version of Black that is in Debian/stable.  To format the code, run:black--skip-string-normalization*.py