Saravanan666/pypi-org huggingface dataset:
Package: pypesa
PyPesaPython Pesa SDKInstallationThis package is available inPython Package Indexand can be installed usingpippip install pypesaThe package comprise both original open API codes and refactored codes.To use original open API code importopen_apimodulefrom pypesa.open_api import APIContext, APIMethodType, APIRequestTo use refactored code importMPESAfromvodacommodule.from pypesa.vodacom import MPESAFeaturesCustomer to Business (C2B)Business to Customer (B2C)Business to Business (B2B)Payment ReversalTransaction StatusDirect debit creation and PaymentPre-requisitesThe following are required and are obtained fromVodacom Open Api portalApi KeyPublic KeySee more indocumentation.ExamplesCustomer to Business payment via vodacom m-pesa# vodacom M-PESAfrommobile_payments.vodacomimportMPESAapi_key='<your-api-key>'public_key='<open-api-public-key>'m_pesa=MPESA(api_key=api_key,public_key=public_key)# Customer to Business paymentparameters={'input_Amount':'1000',# amount to be charged'input_Country':'TZN','input_Currency':'TZS','input_CustomerMSISDN':'000000000001','input_ServiceProviderCode':'000000','input_ThirdPartyConversationID':'c9e794e10c63479992a8b08703abeea36','input_TransactionReference':'T23434ZE3','input_PurchasedItemsDesc':'Shoes',}response=m_pesa.customer2business(parameters)Check more examples of methods and responses indocsCreditsOpenpesaInnocent ZendaAll ContributorsLicenseCode released underMIT LICENSE
Package: pype-schema
A class hierarchy designed to represent configurations of process engineering systems, such as wastewater treatment or desalination plants.Useful Commandspip install-e.This will install your package in editable mode.pytest pype_schema/tests--cov=pype_schema--cov-report=htmlProduces an HTML test coverage report for the entire project which can
be found athtmlcov/index.html.docs/make htmlThis will generate an HTML version of the documentation which can be found
at_build/html/index.html.flake8 pype_schema--count--verbose--show-source--statisticsThis will lint the code and share all the style errors it finds.black pype_schemaThis will reformat the code according to strict style guidelines.Legal DocumentsLICENSECONTRIBUTING
Package: pypest
PyPESTThis is a Python package for the PEST(http://www.pesthomepage.org/)tool.It extends the capacity of current PEST that it can be applied to almost any computational numerical model.AbstarctModel calibration can be tedious and computationally expensive, especially when the models are spatially distributed. We developed a Python software package based on the Parameter ESTimation (PEST) code to automate and speed up the calibration process. This package is model independent and can be customized for any computational models. To speed up the calibration, it uses a parent-child structure to conduct model calibration in a parallel computing environment. The software package can be used to (1) automate input data preparation for model simulation; (2) automate input data preparation for PEST calibration; and (3) analyze/visualize the model outputs.IllustrationModel conceptCode template structureCitationChang Liao, Teklu Tesfa, Zeli Tan, Chao Chen, & L. Ruby Leung. (2020).AcknowledgementThe research described in this paper was primarily funded by a Laboratory Directed Research and Development (LDRD) Program project at Pacific Northwest National Laboratory. CL and LRL were also partly supported by U.S. Department of Energy Office of Science Biological and Environmental Research through the Earth and Environmental System Modeling program as part of the Energy Exascale Earth System Model (E3SM) project.UsageIn order to run the program, you need:git clonegit@github.com:changliao1025/pypest.gitcompile PEST/BeoPEST and place it under the system pathuse exisitng supported models, oradd new models based on the template filesContactPlease contact Chang Liao (chang.liao@pnnl.gov) if you have any questions.
Package: pypesto
pyPESTO - Parameter EStimation TOolbox for pythonpyPESTOis a widely applicable and highly customizable toolbox for
parameter estimation.Feature overviewpyPESTO features include:Multi-start local optimizationProfile computationResult visualizationInterface toAMICIfor efficient
simulation and sensitivity analysis of ordinary differential equation (ODE)
models
(example)Parameter estimation pipeline for systems biology problems specified inSBMLandPEtab(example)Parameter estimation with ordinal data as described inSchmiester et al. (2020)andSchmiester et al. (2021).
(example)Parameter estimation with censored data. (example)Parameter estimation with nonlinear-monotone data. (example)Quick installThe simplest way to installpyPESTOis via pip:pip3installpypestoMore information is available here:https://pypesto.readthedocs.io/en/latest/install.htmlDocumentationThe documentation is hosted on readthedocs.io:https://pypesto.readthedocs.ioExamplesMultiple use cases are discussed in the documentation. In particular, there are
jupyter notebooks in thedoc/exampledirectory.ContributingWe are happy about any contributions. For more information on how to contribute
to pyPESTO check outhttps://pypesto.readthedocs.io/en/latest/contribute.htmlHow to CiteCiteable DOI for the latest pyPESTO release:When using pyPESTO in your project, please citeSchälte, Y., Fröhlich, F., Jost, P. J., Vanhoefer, J., Pathirana, D., Stapor, P.,
Lakrisenko, P., Wang, D., Raimúndez, E., Merkt, S., Schmiester, L., Städter, P.,
Grein, S., Dudkin, E., Doresic, D., Weindl, D., & Hasenauer, J. (2023). pyPESTO: A
modular and scalable tool for parameter estimation for dynamic models,
Bioinformatics, 2023, btad711,doi:10.1093/bioinformatics/btad711When presenting work that employs pyPESTO, feel free to use one of the icons indoc/logo/:There is a list ofpublications using pyPESTO.
If you used pyPESTO in your work, we are happy to include
your project, please let us know via a GitHub issue.ReferencespyPESTO supersedesPESTOa parameter estimation
toolbox for MATLAB, whose development is discontinued.
Package: pypestutils
PyPestUtilsSuite of Python tools based on PEST utilities to support parameterization with pilot points, drawing stochastic realizations, and MODFLOW post-processing for structured and unstructured grids. This package consists of a (pre-)compiled shared fortran library, and a corresponding low-level python wrapper around the library functions.  There are also higher-level "helper" functions to further abstract the granular low-level function calls for common workflow elements.The low-level functions are relatively strict in their argument types - this is required to effectively pass the array-type data container references to the fortran library.  As such, the low-level python functions perform considerable type checking.  The higher-level helpers attempt to support a variety of argument types and will attempt coerce to the required type.This package is currently in pre-alpha development, and is not suitable for use, but early adopters are welcome to have a go.ExamplesThere are several jupyter notebook examples of using pypestutils for a structured and quadtree Freyberg model.  These notebooks rely on bothflopyandpyEMUto help with visualization and processing.The use the low-level python interface to the shared fortran library, you create aPESTUTILSLIBinstance and then can directly call the shared library routines:from pypestutils.pestutilslib import PestUtilsLib
lib = PestUtilsLib() #the constructor searches for the shared lib
grid_info = lib.install_mf6_grid_from_file("grid","freyberg6.disv.grb")
easting,northing,elev = lib.get_cell_centres_mf6("grid",grid_info["ncells"])The higher-level helper functions obsecure the calls the fortran library and string together multiple low-level function calls:import pypestutils.helpers as helpers
grid_info = helpers.get_grid_info_from_file("freyberg6.disv.grb")DocumentationThe documentation for pypestutils can be foundhereThe documentation for the shared FORTRAN library can be foundhereInstallationDependenciespypestutils requiresnumpyandpandasEasy wayUsepipto install a built distribution for Windows, Linux or macOS:pip install pypestutilsto also include optional requirements use:pip install pypestutils[optional]From sourceInstallation from source requires a Fortran compiler and build tools. SeeBUILD.mdfor details.DisclaimerThis software is preliminary or provisional and is subject to revision. It is
being provided to meet the need for timely best science. This software is
provided "as is" and "as-available", and makes no representations or warranties
of any kind concerning the software, whether express, implied, statutory, or
other. This includes, without limitation, warranties of title,
merchantability, fitness for a particular purpose, non-infringement, absence
of latent or other defects, accuracy, or the presence or absence of errors,
whether or not known or discoverable.
Package: pypeta
Pypetapypeta is the python code interface for BGI-PETA database. It provides APIs for login, querying and fetching data.InstallationFrom source code.$ git clone https://github.com/JaylanLiu/pypeta
$ cd pypeta
$ python setup.py installExample usageImport libraies:import pypetaLogin to BGI-PETA database via PETA account:peta=pypeta.Peta(username='bgi-peta@genomics.cn',password='******')Or login via token:peta=pypeta.Peta(token = '******')Get all visable studies info:peta.list_visible_studys()Set target study id and other filters:peta.select_studys(["chol_nus_2012"])
peta.data_restriction["attributesEqualFilters"]=[]Also studies and filters can be load from a json file, which can be get from the PETA website:peta.set_data_restriction_from_json_file('json.txt')Fetch SNV and InDel data as MAF format:peta.fetch_mutation_data()Fetch clinical info as tsv format:peta.fetch_clinical_data()
Package: pypetb
THE PROCESS ENGINEER TOOLBOXProcess Engineer Tool Box is a package where a set of tools are developed to help in our daily tasks. It is based in the use of pandas. In daily chemical industry task, focused on data analysis
and improvement projects developing, no long dataset are
usually used and pandas cover all the requirements.2- INSTALLATIONUse the package managerpipto install pyPETB.pipinstallpypetb3- USAGEPlease refer to theDocumentationGage R&Ruse case4- LICENSEDistributed under theMIT License.5- ROADMAPV0.1 RnRnumeric class to analyze numerical measurement system --> AvailableV0.2 Capability class to make process capability analysis --> AvailableV0.3 RnRcat class to analyze categorical measurement system (Atributes) --> On goingV0.4 DOE class to analyze DOE resultsV1.1 Periodic Table class (Very useful for V1.2 release)V1.2 MEB class for develop material and energy balances6- ACKNOLEDGMENTSThanks to Noël Santiago for his coaching during our six sigma green belt trainingThanks to Ted Hessing for his detailed article calculating RnR:https://sixsigmastudyguide.com/repeatability-and-reproducibility-rr/
Package: pypetl-canary
PyPETLPyPETL (Python Pipeline Extract Transform Load) is an unofficial fork ofPETL by Juarez Rudsatz and teams. This for extending the capabilities of the PETL package by optimizing IO process of the pipeline and an engine that capable on dynamically retrieve connection credential and manage several cloud services (only AWS Secret Manager for now).RequirementsIn order to use this package, the installer will install the following required package and its dependencies in your system:pandas>= 1.4.3petl>= 1.7.11redshift-connector>= 2.0.908psycopg2-binary>= 2.9.3paramiko>= 2.11.0sshtunnel>= 0.4.0InstallationYou cannot install this python package normally because this package can only be installed by build it from the source, not from PyPi Package Repositories. You can use the following command to install this package to your system:gitclonehttps://github.com/Renos-id/pypetl.gitcdpypetl
pipinstallsetuptoolswheel
pipuninstallpypetl
pythonsetup.pyinstall--prefix~/.local/Please remember that you need to logged in to renos github beforehand.
Package: pypetrophysics
# PyPetrophysics
This is a python package containing a number of common petrophysical calculations that can be quickly called upon.# Status
![Tests](https://github.com/andymcdgeo/PyPetrophysics/workflows/Tests/badge.svg?branch=master) ![Test Coverage](https://img.shields.io/codecov/c/github/andymcdgeo/PyPetrophysics/master?color=%2334a1eb&label=Test%20Coverage) [![PyPI](https://img.shields.io/pypi/v/PyPetrophysics.svg)](https://pypi.org/project/PyPetrophysics/) ![Hex.pm](https://img.shields.io/hexpm/l/plug)# Install
To install, use the following command:pip install pypetrophysics# Documentation
Documentation is available at:https://pypetrophysics.readthedocs.io/en/latest/index.html# Reporting Issues
I would love to hear from you if you have come across any bugs, errors or suggestions. To create a new issue, click on the issues tab at the top of the repo and create a new case.
Package: pypetting
PypettingPypetting provides a simple set of wrappers to write complex worklists for the
Tecan EVOware pipetting software. Unfortunately it does not entirely avoid
interacting with the original software, but it reduces the necessary
interactions with it to a minimum.InstallationInstall using pip withpip install pypetting.Pypetting has only been tested with Python 3.10.0.ExamplesDefine a position on the gridfrompypettingimportGridSitesite=GridSite(grid=36,site=1,carrier="MP 3Pos")Define labwaresfrompypettingimportLabwaregreiner96=Labware(name="96 Well Griner",rows=8,columns=12,spacing=1)trough100=Labware("Trough 100+25ml",8,12)Pipetting from one column to the nextfrompypettingimportGridSite,Labware,aspirate,dispense,write_gwlpipetting_site=GridSite(36,1,"MP 3Pos")labware=Labware("96 Well Greiner",8,12,spacing=1)ALL=8*[True]worklist=[aspirate(pipetting_site,1,ALL,50,"LB CD ZMAX",labware=labware),dispense(pipetting_site,2,ALL,50,"LB CD ZMAX",labware=labware),]write_gwl("worklist.gwl",worklist)Place plate in the incubatorfrompypettingimportGridSite,Labware,transfer_labware,return_plate,write_gwlsrc=GridSite(36,0,"MP 3Pos")dest=GridSite(68,0,"StoreX 22Pos")labware=Labware("96 Well Greiner",8,12,spacing=1)worklist=[transfer_labware(src,dest,labware),return_plate(1,1),]write_gwl("worklist.gwl",worklist)How to avoid EVOwareThe authors of Pypetting have strong opinions about the design of EVOware. To
implement more complex workflows, modern techniques for modularization and
abstraction of logic are required. ANY general purpose programming language
provides these tools. Thus outsourcing as much logic as possible is desirable.We suggest the following workflow for any form of iterative task:Call an application to generate the workflow, store the return value of the
application in a variable e.g. calledreturn_valueExecute workflowsJump to the application whenreturn_valueis non-zeroLicenseMIT LicenseCopyright (c) 2021 Nicolas OchsnerPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: pypetwalk
pypetwalkpypetwalkis a Python 3 (>= 3.11) library to communicate with the petWALK.control module.It is intended to be used in custom_componenthapetwalkforHome Assistant.Implementation is based on thepetWALK.control local API (beta) (1.0.0)and some reverse engineering of the internal Websocket and AWS communication.Available functions and their implementation status:Activate/deactivate Brightness sensor (API)Activate/deactivate Motion In (API)Activate/deactivate Motion Out (API)Activate/deactivate Rfid (API)Activate/deactivate Time (API)Open/close door (API)Turn on/off the door (API)Get Device Info (Websocket)Factory reset (Websocket)Init drive start(Websocket)Delete RFID tag (Websocket)Delete all RFID tags (Websocket)Delete Pet RFID tag (Websocket)Start RFID tag Learning (Websocket)Stop RFID tag Learning (Websocket)Check if RFID Tag exists (Websocket)Get RFID tag list (Websocket)Set system time (Websocket)Get Wlan network list (Websocket)Set Wlan network (Websocket)Scan for Wlan networks (Websocket)ZigBee join allowed (Websocket)ZigBee confirm join (Websocket)ZigBee list devices (Websocket)ZigBee name device (Websocket)ZigBee remove device (Websocket)ZigBee update (Websocket)Update Infos (AWS)Get Notification Settings (AWS)Get Timeline (AWS)
Package: pypework
A library to add a neat, readable, functional pipeline syntax to Python.It allows you to rewrite messy nested function calls such as this:title_sanitized=replace(replace(replace(lowercase("Lorem Ipsum Dolor 2018/02/18")," ","_"),"/","-"),"@","at")title_sanitized# -> "lorem_ipsum_dolor_2018-02-18"In a far more readable format like this:title_sanitized=("Lorem Ipsum Dolor 2018/02/18">>f.lowercase>>f.replace("/","-")>>f.replace(" ","_")>>f.replace("@","at"))title_sanitized# -> "lorem_ipsum_dolor_2018-02-18"
Package: pypey
PypeyLibrary for composing lazily-evaluated data-processing pipelines:>>>fromurllib.requestimporturlopen>>>importre>>>frompypeyimportpype,px>>># prints plain text message from example.com>>>(pype(urlopen('http://example.com'))....map(bytes.decode,str.split)....flat()....slice(90,114)....map(px(re.sub,r'\<\/?p\>',''))....to(' '.join))'This domain is for use in illustrative examples in documents. You may use this domain in literature without prior coordination or asking for permission.'Supports argument unpacking:>>>importos>>>frompypeyimportpype>>># reads environment variables with "PYTHON" in them and prints their name>>>pype.dict(os.environ).select(lambdakey,val:'PYTHON'inkey).pick(0).print()PYTHONPATHIPYTHONENABLEPYTHONIOENCODINGPYTHONUNBUFFERED<pypey.pype.Pypeobjectat0x7ffa54006a30>Supports parallelism:>>>fromtimeitimporttimeit>>>timeit("from math import log10; from pypey import pype; pype(range(1, 10_000_000)).map(log10).to(sum, print)",number=5)65657052.0800596665657052.0800596665657052.0800596665657052.0800596665657052.0800596610.055954356997972>>>timeit("from math import log10; from pypey import pype; pype(range(1, 10_000_000)).map(log10, workers=8).to(sum, print)",number=5)65657052.0800596665657052.0800596665657052.0800596665657052.0800596665657052.080059665.446932412014576InstallingInstall with pip:pipinstallpypeyTestingUnit tests are written withpytest. Run with:pipinstallpytest

pytestPypey has been tested with python 3.7, 3.8 and 3.9. Afew testscontainingpositional-only argumentswill fail if they are run with 3.7 as
it's a feature only available from 3.8 onwards.DocumentationExtensive documentation athttps://pypey.readthedocs.io/en/stable/index.html.Unit testsdocument through behaviour specification.ChangelogCheck theChangelogfor fixes and enhancements of each version.LicenseCopyright Jose Llarena 2021.Distributed under the terms of theMITlicense, Pypey is free
and open source software.
Package: pypez
OverviewA simple module for specifying and executing a sequence of commands, with up to 1 level of branching (where several tasks are executed in parallel) before
continuing with a single line of execution.Featuresexecutes a sequences of command lines, allowing some steps to run in parallel, before proceeding sequentially again.save command standard output to a log file.use temp output files for each command until it completes successfully. Then move them to their final location.by default don’t rerurn steps if the output file(s) exist and are newer than the input file(s).run locally by default or on SGE (with –use_SGE) or LSF (with –use_LSF).
Package: pypf3
This is the PrintFlow 3 Service application.
This application provides tools to integrate Noosh Online with Canto Cumulus, along with maintaining a JSON based data store of integration objects.In general, integration calls are made using using REST-like web service calls. The ‘requests’ python package is used to do all HTTP requests.The application needs to run with “sudo” to ensure permissions required for file system manipulation apply.In order to make use of this code for production use, you need various authenticated access tokens and serial numbers to use the various applications.
Use of the software on with commercial versions of Noosh Online and/or Canto Cumulus and/or Canto Cumulus basis is considered commercial use.
However, the source code can be explored and used on a free basis, and if useful, can be re-factored as required for any development purpose.To deploy run: python3 setup.py bdist_egg upload - if any issues, first run python3 setup.py register
To update runtime on server: sudo /usr/local/bin/easy_install-3.3 -U pypf3
Package: pypfilt
DescriptionA bootstrap particle filter that can be used for recursive Bayesian estimation and forecasting.
See theonline documentationfor tutorials, how-to guides, and API documentation.LicenseThe code is distributed under the terms of theBSD 3-Clause license(seeLICENSE), and the documentation is distributed under the terms of theCreative Commons BY-SA 4.0 license.InstallationTo install the latest release:pip install pypfiltTo install the latest release with plotting support (requiresmatplotlib):pip install pypfilt[plot]To install the latest development version, clone this repository and run:pip install .
Package: pypfm
Python pfm files reader. Fast and python3 compatible, with compression
includedInstallpip install pypfmIf you know the size upfront, specify it:frompypfmimportPFMLoaderloader=PFMLoader((width,height),color=False,compress=False)Otherwise it will find it by itself (slower):frompypfmimportPFMLoaderloader=PFMLoader(color=False,compress=False)Read a pfm filepfm=loader.load_pfm('test.pfm')Save a pfm file:loader.save_pfm('test.pfm',pfm)Using zfp compression:frompypfmimportPFMLoaderloader=PFMLoader(color=False,compress=True)pfm=loader.load_pfm('test.pfm')loader.save_pfm('test.pfm',pfm)
Package: pypgadmin
A web client for PostgreSQL written in Python. In spirit and
intention, it is a PhpPgAdmin clone.This is still unusable.Quickstartgit clone https://github.com/darylyu/pypgadmin
cd pypgadmin
pip install -r requirements/dev.txt
python manage.py db init
python manage.py db migrate
python manage.py db upgrade
python manage.py serverDeploymentIn your production environment, make sure thePYPGADMIN_ENVenvironment variable is set to"prod".ShellTo open the interactive shell, runpython manage.py shellBy default, you will have access toapp,db, and theUsermodel.Running TestsTo run all tests, runpython manage.py testMigrationsWhenever a database migration needs to be made. Run the following commmands:python manage.py db migrateThis will generate a new migration script. Then run:python manage.py db upgradeTo apply the migration.For a full migration command reference, runpython manage.py db--help.
Package: pypgdb
pypgdbpgdb is a simple wrapper around psycopg2 python library to simplify its usage.Connection is established before the first query or manually by callingopenfunction.You can close connection usingclosefunction or by deleting PGDB object.Use logger object for more output informationpgdb.logger.setLevel(logging.INFO)Typical usage examplefrompypgdbimportpgdbimportloggingdb=pgdb.PGDB("host=127.0.0.1 dbname=my_db port=5432 user=myUser password=myPassword")pgdb.logger.setLevel(logging.INFO)res=db.query("SELECT 'hello world'::TEXT, NOW()")Installationpypgdb requires psycopg2>=2.8.3 to run.pip installation:pipinstallpypgdbInstall from source:pythonsetup.pybdist_wheel
pipinstalldist\pypgdb-VERSION-py3-none-any.whl