Saravanan666/pypi-org huggingface dataset:
Package: seerbit-python-v2
seerbit-python-v2A SeerBit API Library for Python (Version 2)FeaturesThe Library supports all APIs under the following services:Payments via API (mobile money, cards, account, etc.)Recurring PaymentsTransaction StatusGetting StartedA full getting started guide for integrating SeerBit can be found atgetting started docs.DocumentationThe documentation, installation guide, detailed description of the SeerBit API and all of its features isavailable on the documentation websiteRequirementsPython 3.9PipInstallationPipRun this command on the terminal:pip install seerbit-python-v2ContributingYou can contribute to this repository so that anyone can benefit from it:Improved featuresResolved bug fixes and issuesExamplesYou can also check thedemosUsing the LibraryInitiate Account OptionInstantiate a client and set the parameters.fromseerbit.clientimportClientfromseerbit.enumsimportEnvironmentEnumfromseerbit.seerbitlibimportSeerBitclient=Client()client.api_base=SeerBit.LIVE_API_BASEclient.environment=EnvironmentEnum.LIVE.valueclient.private_key="private_key"client.public_key="public_key"client.timeout=20To initiate a transaction request you need to perform authentication operation and acquire a token.fromseerbit.service.authenticationimportAuthenticationauth_service=Authentication(client)auth_service.auth()token=auth_service.get_token()After you have retrieved your token, pass it to the AccountService constructor along with your client object. You can then construct your payload and call theauthorize()method of the AccountService class.fromrandomimportrandintfromseerbit.service.account_serviceimportAccountServicerandom_number=randint(10000000,99999999)payment_ref="SBT_"+str(random_number)account_payload={"publicKey":client.public_key,"amount":"100.00","fee":"10","fullName":"John Doe","mobileNumber":"08037456590","currency":"NGN","country":"NG","paymentReference":payment_ref,"email":"johndoe@gmail.com","productId":"Foods","productDescription":"Uba Account Transaction ","clientAppCode":"kpp64","channelType":"BANK_ACCOUNT","redirectUrl":"https://checkout.seerbit.com","deviceType":"Apple Laptop","sourceIP":"127.0.0.1:3456","accountName":"John S Doe","accountNumber":"1234567890","bankCode":"033","bvn":"12345678901","dateOfBirth":"04011984","retry":"false","invoiceNumber":"1234567891abc123ac"}account_service=AccountService(client,token)json_response=account_service.authorize(account_payload)Find more exampleshere.LicenceGNU General Public License. For more information, see the LICENSE file.Websitehttps://seerbit.com
Package: seerep-grpc
SEEREP gRPC APIThis packages provides theProtocol BuffersandFlatbuffersclasses for gRPC API ofSEEREP.UsageImport the classes from theseerep.pborseerep.fbmodules like this:fromseerep.pbimportimage_pb2asimagefromseerep.pbimportimage_service_pb2_grpcasimageServicefromseerep.fbimportImagefromseerep.fbimportimage_service_grpc_fbasimageServiceExamplesFor more advanved examples take a look in the SEEREP repositoryhere.NoteIf you are not using the wheel, you manually need to install theflatccompiler
since it's not available on pypi. Instructions can be foundhere
Package: sees
seesA modern OpenSees rendererseesis a finite element rendering library that leverages modern
web technologies to produce sharable, efficient, and beautiful renderings.Documentation is currently under development.FeaturesExtruded deformed shapeDetailed section renderingA wide selection of rendering backends and output file types, including
optimized 3D web formats like.glb.Correctly render models that treat bothyorzas the
vertical coordinate.Command Line InterfaceTo create a rendering, execute the following command from the anaconda prompt (after activating the appropriate environment):python-mseesmodel.json-omodel.htmlwheremodel.jsonis a JSON file generate from executing the following OpenSees command:print-JSONmodel.jsonIf you omit the-o <file.html>portion, it will plot immediately in a new
window. You can also use a.pngextension to save a static image file, as
opposed to the interactive html.NotePrinting depends on the JSON output of a model. Several materials and
elements in the OpenSeesPy and upstream OpenSees implementations do not
correctly print to JSON. For the most reliable results, use theopenseespackage.By default, the rendering treats the $y$ coordinate as vertical.
In order to manually control this behavior, just pass the  option--vert 3to render model $z$ vertically, or--vert 2to render model $y$ vertically.If theopenseespackage is installed,
you can directly render a Tcl script without first printing to JSON,
by just passing a Tcl script instead of the JSON file:python-mseesmodel.tcl-omodel.htmlTo plot an elevation (elev) plan (plan) or section (sect) view, run:python-mseesmodel.json--viewelevand add-o <file.extension>as appropriate.To see the help page runpython-msees--helpSee alsoopenseesosmgmdofsdofSupport
Package: seesaw
Seesaw toolkit==============An asynchronous toolkit for distributed web processing. Written in Python and named after its behavior, it supports concurrent downloads, uploads, etc.This toolkit is well-known for [Archive Team projects](http://archiveteam.org). It also powers the [Archive Team warrior](http://archiveteam.org/index.php?title=Warrior).[![Build Status](https://secure.travis-ci.org/ArchiveTeam/seesaw-kit.png)](http://travis-ci.org/ArchiveTeam/seesaw-kit)[![Coverage Status](https://coveralls.io/repos/ArchiveTeam/seesaw-kit/badge.svg)](https://coveralls.io/r/ArchiveTeam/seesaw-kit)Installation------------Requires Python 2 or 3.Needs the Tornado library for event-driven I/O. The complete list of Python modules needed are listed in requirements.txt.How to try it out-----------------To run the example pipeline:sudo pip install -r requirements.txt./run-pipeline --help./run-pipeline examples/example-pipeline.py someonePoint your browser to `http://127.0.0.1:8001/`.You can also use `run-pipeline2` or `run-pipeline3` to be explicit for the Python version.Overview--------General idea: a set of `Task`s that can be combined into a `Pipeline` that processes `Item`s:* An `Item` is a thing that needs to be downloaded (a user, for example). It has properties that are filled by the `Task`s.* A `Task` is a step in the download process: it takes an item, does something with it and passes it on. Example Tasks: getting an item name from the tracker, running a download script, rsyncing the result, notifying the tracker that it's done.* A `Pipeline` represents a sequence of `Task`s. To make a seesaw script for a new project you'd specify a new `Pipeline`.A `Task` can work on multiple `Item`s at a time (e.g., multiple Wget downloads). The concurrency can be limited by wrapping the task in a `LimitConcurrency` `Task`: this will queue the items and run them one-by-one (e.g., a single Rsync upload).The `Pipeline` needs to be fed empty `Item` objects; by controlling the number of active `Item`s you can limit the number of items. (For example, add a new item each time an item leaves the pipeline.)With the `ItemValue`, `ItemInterpolation` and `ConfigValue` classes it is possible to pass item-specific arguments to the `Task` objects. The value of these objects will be re-evaluated for each item. Examples: a path name that depends on the item name, a configurable bandwidth limit, the number of concurrent downloads.Consult [the wiki](https://github.com/ArchiveTeam/seesaw-kit/wiki) for more information.
Package: seesaw2
Seesaw toolkitAn asynchronous toolkit for distributed web processing. Written in Python and named after its behavior, it supports concurrent downloads, uploads, etc.This toolkit is well-known forArchive Team projects. It also powers theArchive Team warrior.InstallationRequires Python 2 or 3.Needs the Tornado library for event-driven I/O. The complete list of Python modules needed are listed in requirements.txt.How to try it outTo run the example pipeline:sudo pip install -r requirements.txt
./run-pipeline --help
./run-pipeline examples/example-pipeline.py someonePoint your browser tohttp://127.0.0.1:8001/.You can also userun-pipeline2orrun-pipeline3to be explicit for the Python version.OverviewGeneral idea: a set ofTasks that can be combined into aPipelinethat processesItems:AnItemis a thing that needs to be downloaded (a user, for example). It has properties that are filled by theTasks.ATaskis a step in the download process: it takes an item, does something with it and passes it on. Example Tasks: getting an item name from the tracker, running a download script, rsyncing the result, notifying the tracker that it's done.APipelinerepresents a sequence ofTasks. To make a seesaw script for a new project you'd specify a newPipeline.ATaskcan work on multipleItems at a time (e.g., multiple Wget downloads). The concurrency can be limited by wrapping the task in aLimitConcurrencyTask: this will queue the items and run them one-by-one (e.g., a single Rsync upload).ThePipelineneeds to be fed emptyItemobjects; by controlling the number of activeItems you can limit the number of items. (For example, add a new item each time an item leaves the pipeline.)With theItemValue,ItemInterpolationandConfigValueclasses it is possible to pass item-specific arguments to theTaskobjects. The value of these objects will be re-evaluated for each item. Examples: a path name that depends on the item name, a configurable bandwidth limit, the number of concurrent downloads.Consultthe wikifor more information.
Package: seesus
seesus: a social, environmental, and economic sustainability classifierseesusis aPythonpackage that evaluates whether a textual expression aligns with the concept of sustainability as defined by the United Nations Sustainable Development Goals (SDGs). It labels a statement with the 17 SDGs as well as 169 specific targets and categorizes the statement into social, environmental, or economic sustainability. For analysis inR, please checkSDGdector.seesuscurrently has four main functions:Evaluate whether a statement aligns with the concept of sustainabilityIdentify SDGs and associated targets in a statementClassify a statement into social, environmental, and economic sustainabilityExamine and customize match syntaxInstallationpip install seesusExamplefromseesusimportSeeSustext="We aim to contribute to the mitigation of climate change by reducing carbon emissions in the city."result=SeeSus(text)# print result on whether a statement aligns with sustainability, True or Falseprint(result.sus)# print the names of identified SDGsprint(result.sdg)# print the descriptions of identified SDGsprint(result.sdg_desc)# print the names of identified SDG targetsprint(result.target)# print the descriptions of identified SDG targetsprint(result.target_desc)# determine which dimension of sustainability (social, environmental, or economic) a statement belongs toprint(result.see)# print match syntaxSeeSus.show_syntax("SDG1_general")# customize match dyntaxSeeSus.edit_syntax("SDG1_general","my match terms")Please runexample.ipynbto see more example usage.
Package: seeta-det
SeetaDetSeetaDet is a platform implementing popular object detection algorithms.This platform works withSeetaDragon, and uses thePyTorchstyle.InstallationInstall from PyPI:pipinstallseeta-detOr, clone this repository to local disk and install:cdseetadet&&pipinstall.You can also install from the remote repository:pipinstallgit+ssh://git@github.com/seetaresearch/seetadet.gitIf you prefer to develop locally, build but not install tosite-packages:cdseetadet&&pythonsetup.pybuildQuick StartTrain a detection modelcdtools
pythontrain.py--cfg<MODEL_YAML>We have provided the default YAML examples intoconfigs.Test a detection modelcdtools
pythontest.py--cfg<MODEL_YAML>--exp_dir<EXP_DIR>--iter<ITERATION>Export a detection model to ONNXcdtools
pythonexport.py--cfg<MODEL_YAML>--exp_dir<EXP_DIR>--iter<ITERATION>Serve a detection modelcdtools
pythonserve.py--cfg<MODEL_YAML>--exp_dir<EXP_DIR>--iter<ITERATION>Benchmark and Model ZooResults and models are available in theModel Zoo.LicenseBSD 2-Clause license
Package: seetm
SEETM (Sinhala-English Equivalent Token Mapper) allows creating equivalent token maps and replace them with a base token to avoid OOV tokens and generate a single feature for all equivalent tokens in a Sinhala-English code-switching dataset in rasa-based conversational AIs.FeaturesAllows mapping multiple equivalent tokens into a base tokenFully supports rasa 2.8.x projectsProvides an easy-to-use CLIProvides an efficient server-based GUIProvides a fully-functional custom whitespace tokenizerFully-supports Sinhala in the GUIWhat's Cooking?Mapping suggestions in the SEETM server GUIAutomatically generated mappingsLimitations and Known IssuesShould manually add the SEETM tokenizer to the rasa pipeline or else the token maps are not taking any effectIPA-based suggestions could contain slight changes based on th IPA mapping origin. (SEETM uses CMU)Resources and ReferencesCMUPronunciation Dictionaryeng-to-ipapip package (GitHub)📒 Docs:https://seetm.github.io📦 PyPi:https://pypi.org/project/seetm/1.1.1/🪵 Full Changelog:https://github.com/SEETM-NLP/seetm/blob/main/CHANGELOG.md
Package: seEvo1D
InstallationseEvo1D is python based lib available at pypipython -m pip install seEvo1Ddependecies will be installed with programUsageTo run program simply type in command linepython -m seEvo1Dbasicly seEvo is standalone program which provides possibility to simulate slighlty effect evolution in one dimension - slightly advantegous, slightly deleteriousInstructionsProgram contains 4 main views and main status UIOutput buttons provides possibility to draw images from saved files. Each file should have extension '.npz' as default from program. User can create multiple figures from multiple files. Each picture will be save to same directory from which file is loaded, in folder 'Figures'.population growth plot demands selection of multiple files to track population size.
combined mutation wave plot provides possibility to draw both analytic and simulated mutation wave on one plot. multiple files can be selected to draw on one figure.LicenseGNU GENERAL PUBLIC LICENSE  Version 3, 29 June 2007Copyright (C) 2007 Free Software Foundation, Inc.https://fsf.org/Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.DisclaimerseEvo - slighltly effect evolution simulator basing on Gillespie algorithm.
Copyright (C) 2022 by Jarosław GilThis program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.You should have received a copy of the GNU General Public License
along with this program.  If not, seehttps://www.gnu.org/licenses/.AuthorJarosław Gil, Silesian Univeristy of Technology, Department of Computer Graphics, Vision and Digital Systems.
Package: seewav
SeeWav: animation generator for audio waveformsInstallationYou will need a decently recent version of python, most likely 3.6 or 3.7.
You will needffmpeginstalled somewhere with sufficient codec support. If you are using conda,
install it withconda install -c conda-forge ffmpeg. Alternatively, on OSX with Homebrew,
you can runbrew install ffmpeg.# Optional, if you use conda, otherwise find a way to install it.# conda install -c conda-forge ffmpegpip3installseewaveUsageseewaveAUDIO_FILE[OUTPUT_FILE]By default, outputs toout.mp4. Available options:usage:seewav[-h][-rRATE][-cCOLOR][--white][-BBARS][-OOVERSAMPLE][-TTIME][-SSPEED][-WWIDTH][-HHEIGHT][-sSEEK][-dDURATION]audio[out]Generateanicemp4animationfromanaudiofile.

positionalarguments:audioPathtoaudiofileoutPathtooutputfile.Defaultis./out.mp4

optionalarguments:-h,--helpshowthishelpmessageandexit-rRATE,--rateRATEVideoframerate.-cCOLOR,--colorCOLORColorofthebarsas`r,g,b`in[0,1].--whiteUsewhitebackground.Defaultisblack.-BBARS,--barsBARSNumberofbarsonthevideoatonce-OOVERSAMPLE,--oversampleOVERSAMPLELowervalueswillfeellessreactive.-TTIME,--timeTIMEAmountofaudioshownatonceonaframe.-SSPEED,--speedSPEEDHighervaluesmeansfastertransitionsbetweenframes.-WWIDTH,--widthWIDTHwidthinpixelsoftheanimation-HHEIGHT,--heightHEIGHTheightinpixelsoftheanimation-sSEEK,--seekSEEKSeektotimeinsecondsinvideo.-dDURATION,--durationDURATIONDurationinsecondsfromseektime.
Package: sefara
Sefara is a Python library for managing your datasets. It provides a way to specify once what your datasets are (usually fileystem paths) and any metadata (e.g. which experiment they came from), then refer to them conveniently in analysis scripts and notebooks.Sefara doesn’t assume anything about what your datasets are, what format they’re in, or are how they are accessed.Quick exampleDefine a “resource collection” by making a file like this, which we’ll calldatasets.sefara.py:from sefara import export

export(
    "my_first_dataset.hdf5",
    path="/path/to/file1.hdf5",
    tags=["first", "important"],
)
export(
    "my_second_dataset.csv",
    path="/path/to/file2.csv",
    tags=["second", "unimportant"],
)Then, use Sefara to open it in Python:>>> import sefara
>>> datasets = sefara.load("datasets.sefara.py")
>>> print(datasets.filter("tags.important")[0].path)
/path/to/file1.hdf5DocumentationAvailable at:http://timodonnell.github.io/sefara/docs/htmlInstallationpip install sefaraTo run the tests:nosetestsTo build the documentation:pip install -e .
pip install Sphinx
cd docs
make clean setup rst htmlThe docs will be written to the_build/htmldirectory.
Package: sefazetllib
sefazetllibDocumentation:https://main.d32to2oidohzrl.amplifyapp.com/Source code:AWS CodeCommitsefazetllibis a library that provides a simplified and abstracted way to construct ETL/ELT pipelines.FeaturesEasy to use and understand library for constructing ETL/ELT pipelines.Compatibility with popular data processing frameworks, such aspandasandPySpark.Support for file formats such as CSV and Parquet.Provides the ability to extract, transform and load data with customizable configurations.Requirementssefazetllibrequires the following to run:Python3.7.1+pandas1.3+PyArrow6.0+PySpark3.0+PyDeequ1.0+Boto31.24+InstallationUsepipto installsefazetllib:pipinstallsefazetllibUsageHere is an example of how to use thesefazetllib:fromtypingimportTuplefrompandasimportDataFramefromsefazetllibimportBuilderfromsefazetllib.etlimportETLfromsefazetllib.extractimportExtractLocalfromsefazetllib.factory.platformimportPlatformFactoryfromsefazetllib.loadimportLoadLocalfromsefazetllib.transformimportTransformfromsefazetllib.utils.keyimportSurrogateKey@BuilderclassTestingDataFrame(Transform):defexecute(self)->Tuple[str,DataFrame]:return("dataframe",DataFrame([["tom",10],["nick",15],["juli",14]],columns=["Name","Age"]),)(ETL().setPlatform(PlatformFactory("Pandas").create(name="test_pandas")).transform(TestingDataFrame).load(LoadLocal().setFileFormat("parquet").setEntity("load_test").setMode("overwrite").setReference("dataframe").setDuplicates(True).setKey(SurrogateKey().setColumns(["Name","Age"]).setDistribute(False))).extract(ExtractLocal().setFileFormat("parquet").setUrl("load_test.parquet").setReference("extract_test")))TestingTo run the unit tests, run the following command:py-munittesttests/main.py-vLicensesefazetllibis released under theApache-2.0.
Package: seff
This package provides a high-performance solution to reading and writing Python dictionaries to and from binary files. The main advantage over JSON or other text-based serialization formats is its compactness and speed, which can be a crucial factor when working with large data sets.The package provides two main methods,writeandread, to write a Python dictionary or list of dictionaries to a file and read it back. It intelligently manages the type mapping during serialization and deserialization to ensure type consistency.Thewritemethod writes a dictionary (or a list of dictionaries) to a binary file. It automatically handles different data types including int, float, and str. Thereadmethod reads a binary file and reconstructs the dictionary. The package also provides support functions to deal with file operations.This package is designed to be easy-to-use, lightweight and efficient, and is particularly suitable for applications that require handling large amounts of data or high-speed I/O operations.
Package: seffaflik
Seffaflik:KurulumGereksinimlerseffaflik kütüphanesinin kullanımı için gerekli paketler:pandasrequestspython-dateutilsNot: İlgili paketler aşağıda belirtilen yükleme yöntemini izlediğiniz taktirde otomatik olarak yüklenecektir.pip aracılığıyla en son sürümü yükleyin$ pip install seffaflikKimlik (Client Id) OluşturulmasıKütüphane yükleme işlemini tamamladıktan sonra kütüphane aracılığıyla veri çekiş işlemini gerçekleştirebilmeniz için
temin etmiş olduğunuzistemci taniticisi (client id)ile aşağıda belirtilen kimlik oluşturma sürecini de tamamlamış
olmanız gerekmektedir.İstemci tanitici (client id) nasıl temin edilir?importseffaflikseffaflik.Kimlik(istemci_taniticisi="abcdefg")Yukarıdaki işlemi gerçekleştirmenizden sonra ana dizininize özel bir
.seffaflik/.kimlik dosyası yerleştirilir. ~/.seffaflik/.kimlik dosyanız aşağıdaki
gibi görünmelidir:{
  "istemci_taniticisi": "abcdefg"
}Not: İstemci Tanıtıcı geçerliliğini koruduğu sürece kimlik oluşturma işleminin tekrar gerçekleştirilmesine
gerek duyulmamaktadır.KullanımKütüphane yükleme ve kimlik oluşturma işlemleri tamamladıktan sonra kütüphane aracılığıyla şeffaflık platformundan
kolaylıkla veri çekiş işlemine başlanabilmektedir. Kütüphanenin paketleri, alt-paketleri ve modülleri şu şekilde
tasarlanmıştır:seffaflik/
├── dogalgaz/
│   └── stp.py
└── elektrik/
    ├── piyasalar/
    │   ├── dengesizlik.py
    │   ├── dgp.py
    │   ├── genel.py
    │   ├── gip.py    
    │   ├── gop.py
    │   ├── ia.py  
    │   └── yanhizmetler.py
    ├── iletim.py
    ├── santraller.py
    ├── tuketim.py
    ├── yekdem.py
    └── uretim.pyBu çerçevede tüm modüller şu şekilde import edilebilir:fromseffaflik.elektrikimportsantraller,tuketim,uretim,yekdemfromseffaflik.elektrik.piyasalarimportdengesizlik,dgp,genel,gip,gop,ia,yanhizmetlerfromseffaflik.dogalgazimportstpÖrnek İsteklerYukarıda belirtilen modüller import edildikten sonra aşağıda belirtilen örnek istekler yapılabilecektir.1. Piyasa Takas Fiyatı (PTF)df=gop.ptf(baslangic_tarihi='2019-01-01',bitis_tarihi='2019-01-01')2. KGÜP Girebilecek Organizasyonlardf=uretim.organizasyonlar()3. Uzlaştırmaya Esas Veriş Miktarı (UEVM)df=uretim.uevm(baslangic_tarihi='2019-01-01',bitis_tarihi='2019-01-01')4. Dönemsel Serbest Tüketici Sayılarıdf=tuketim.serbest_tuketici_sayisi("2019-01-01","2019-10-01")5. Doğalgaz Sürekli Ticaret Platformu Günlük Fiyatdf=stp.gunluk_fiyat("2019-01-01","2019-10-01")