Saravanan666/pypi-org huggingface dataset:
Package: promid
PromID: A deep learning-based tool to identify promotersInstallationPromID can be installed from thegithub repository:gitclonehttps://github.com/PromStudy/PromID.gitcdPromID
pipinstall.PromID requirestensorflow>=1.7.0, the GPU version is highly recommended.UsagePromID can be run from the command line:promid-Ihg19.fa-Ohg19_promoters.bedRequired parameters:-I: Input fasta file.-O: Output bed file.Optional parameters:-D: Minimum soft distance between the predicted TSS, defaults to 1000.-C: Comma separated list of chromosomes to use for promoter prediction, defaults to all.-T1: Decision threshold for the scan model, defaults to 0.2.-T2: Decision threshold for the prediction model, defaults to 0.5.
Package: prominence-cli
PROMINENCE Command Line InterfaceThe PROMINENCE CLI presents a simple batch-system style interface to PROMINENCE written in Python. It can be installed easily on any system using pip:pip install prominence-cliTo upgrade the CLI the--upgradeoption needs to be added:pip install --upgrade prominence-cliVisithttps://prominence.readthedocs.iofor more information.This work is co-funded by theEOSC-hub project(Horizon 2020) under Grant number 777536.
Package: promisedio-promise
Despite the fact that this code is distributed under the MIT License,
IT IS PROHIBITED to use, copy, modify, merge, publish, distribute, sublicense,
and/or sell copies of the Software for any commercial or non-commercial purposes
by Jet Brains and any of its subsidiaries, parent organization or affiliates.PromisedIOPromisedIO is free and open source software released under the permissive MIT license.You can read about promiseshere.promise moduleclearfreelistsclearfreelists()->NoneClear all freelists.deferreddeferred()->DeferredCreate newDeferredobject.exec_asyncexec_async(coro:Coroutine,context:Any=None)->NoneStart new coroutine and set thecontextfor the new coroutine.get_contextget_context()->AnyGet context of current corroutine.process_promise_chainprocess_promise_chain()->intProcess all scheduled (resolved or rejected) promises.Returns active promise count.run_foreverrun_forever()->NoneStart simple event loop.setfreelistlimitssetfreelistlimits(promise_limit:int=-1,promiseiter_limit:int=-1,deferred_limit:int=-1,coroutine_limit:int=-1)->NoneUpdate freelist limits. Default limit for each type is 1024.DeferredDeferred.promiseDeferred.promise()->PromiseGet relatedPromiseobject.Deferred.rejectDeferred.reject(value:Exception)->NoneReject relatedPromiseobject with the given exceptionvalue.Deferred.resolveDeferred.resolve(value:Any)->NoneResolve relatedPromiseobject with the givenvalue.LockLock.newLock.__new__()->AnyCreate newLockobject.Lock.acquireLock.acquire()->PromiseAcquire the lock.Lock.releaseLock.release()->PromiseRelease the lock.PromisePromise.catchPromise.catch(rejected:Callable)->PromiseThe same as.then(None, rejected)Promise.thenPromise.then(fulfilled:Callable=None,rejected:Callable=None)->PromiseCreate newPromise.It takes up to two arguments: callback functions for the success and failure cases of the promise.
Package: promisio
promisioJavaScript-style async programming for Python.ExamplesCreate a promise-based async function using thepromisifydecorator. It works
on both sync and async functions!frompromisioimportpromisify@promisifyasyncdeff():awaitasyncio.sleep(1)return42@promisifydefg(x):returnx*2asyncdefmain():print(awaitf())# prints 42print(awaitg(42))# prints 84promise=f()# runs function in the background without waiting# ... do other stuff here in parallel with f runningawaitpromise# finally wait for f to completeThe return value of the decorated function is a JavaScript-style promise object
that can be awaited. Thethen(),catch()andfinally_()methods to chain
promises work as in JavaScript. ThePromise.all(),Promise.all_settled(),Promise.any(),Promise.race(),Promise.resolve()andPromise.reject()are also available. Promises in this package are extended to also support
cancellation via thecancel()andcancelled()methods.ResourcesDocumentationPyPIChange Log
Package: promisipy
IntroductionThis Python project provides a concurrency framework using promises, enabling asynchronous execution of tasks with support for both threading and multiprocessing. It allows for easy task execution management, result handling, and synchronization of concurrent operations without delving into the complexities of threading or multiprocessing modules directly.FeaturesSimple API: Intuitive and easy-to-use API for managing asynchronous task executions.Concurrency Modes: Supports both threading and multiprocessing to cater to different use cases.Promise-Based: Utilize promises for handling asynchronous execution results and errors.Event Loop: Central event loop for managing and synchronizing promise lifecycles.Decorators: Simplify asynchronous function execution with decorators.InstallationThis project does not require installation of external packages. Ensure you have Python 3.8 or newer installed on your system, as this project utilizes features introduced in Python 3.8.To install it, run the following command:pip install promisipyUsageBasic ConceptsPromise: Represents the eventual completion (or failure) of an asynchronous operation and its resulting value.Event Loop: Manages the lifecycle of promises, including registration, execution, and unregistration.promisipyDecorator: Converts a regular function into one that returns a promise when called, executing the function in a separate thread or process.Creating a PromiseTo create a promise, instantiate aPromiseobject with a target function. Specify the concurrency mode ("threading"or"multiprocessing") according to your needs.Waiting for a Promise to ResolveUse thewaitmethod on a promise object to block until the promise has resolved. This method returns aPromise.Resolutionobject containing the result or error.Executing Functions AsynchronouslyDecorate functions with@promisipy(mode="threading")or@promisipy(mode="multiprocessing")to run them asynchronously as promises.ExamplesBasic Promise ExecutionfrompromisipyimportPromise,promisipy# Function to execute asynchronouslydeftask():return"Result of async task"# Create and start a promisepromise=Promise(execution=task,mode="threading").start()# Wait for the promise to resolveresolution=promise.wait()print("Result:",resolution.result)UsingpromisipyDecoratorfrompromisipyimportpromisipy@promisipy(mode="threading")defasync_task():return"Result from decorated async task"# The function now returns a promisepromise=async_task()# Wait for the promise to resolve and print the resultprint("Result:",promise.wait().result)Waiting for Multiple PromisesfrompromisipyimportPromise,promisipy# Define multiple tasksdeftask1():return"Result of task 1"deftask2():return"Result of task 2"# Create promises for each taskpromise1=Promise(execution=task1,mode="threading").start()promise2=Promise(execution=task2,mode="threading").start()# Wait for all promises to resolveresults=Promise.all([promise1,promise2])print("Results:",[res.resultforresinresults])This framework is versatile and can be adapted for various asynchronous execution needs, simplifying the handling of concurrent operations in your Python applications.
Package: prommis
prommisProcess Optimization and Modeling for Minerals SustainabilityGetting started (for PrOMMiS contributors)Unless otherwise noted, these commands assume that the working directory is the root of the local clone of this repository (i.e. the directory containing this README file).Installationcondacreate--nameprommis-dev--yespython=3.11
condaactivateprommis-dev
gitclonehttps://github.com/prommis/prommis&&cdprommis
pipinstall-rrequirements-dev.txtBefore committingBefore running any of these commands, ensure theprommis-devConda environment has been activated:condaactivateprommis-devSort import statementsisortsrc/prommisFormatting codeblack.Running linter (Pylint)pylintprommisRunning testspytest# run the complete test suitepytest-ktest_my_flowsheet.py# run only test defined in the file named test_my_flowsheet.pyBuilding documentationFrom thedocs/subdirectory:jupyter-bookbuild.Testing (executing) notebooksFrom thedocs/subdirectory:pytest--nbmake-m"solution".
Package: promobot-appeal-processing
Promobot Appeal ProcessingDocumentation:https://digital-fracture.github.io/promobot-appeal-processingGoogle Colab notebook with training codeInstallationpip install promobot-appeal-processingNeeded resource filesPutthisto the root directory
of your project to let the package function properlyUsescatboostspaCy- NERLicensepromobot-appeal-processingis distributed under the terms of theMITlicense.
Package: promoe
promoeProtonize selected atoms with the use of MOE and Pymol.Free software: GNU General Public License v3Documentation:https://promoe.readthedocs.io.OverviewFeaturesProtonize the binding site of a pdb id automaticallyRemove water atoms that are unable to interact with the ligand after protonizationExtract charges for residuesExtract all ligand IDsExtract all alternative locationsHistory0.1.0 (2019-09-30)First release on PyPI.
Package: promoterExtract
OverviewThe promoterExtract is python package for nucleotide manipulation
in bioinformatics. The package contains two subcommands including
create and extract. The create subcommand is used for creating
database and extract subcomand is used for extracting promoter sequence.
Both two subcomand is executed through get_promoter command in command line.
Argument -l means the length of promoter, int type.
Argument -u utr5 after TSS, int type.
Argument -f reference genome fasta of a specific organism.
Argument -g annotation file including GTF and GFF.
Argument -o means output file path.Brief introduction of format packageInstallpipinstallpromoterExtract# othergitclonehttps://github.com/SitaoZ/promoterExtract.gitcdpromoterExtract;pythonsetup.pyinstallUsagewhichget_promoter
get_promoter-hget_promotercreate-hget_promoterextract-h# step 1get_promotercreate-gath.gff3# step 2get_promoterextract-l200-u100-fath.fa-ggff.db-opromoter.csv
Package: promotion
Edit a file, create a new file, and clone from Bitbucket in under 2 minutesWhen you're done, you can delete the content in this README and update the file with details for others getting started with your repository.We recommend that you open this README in another tab as you perform the tasks below. You canwatch our videofor a full demo of all the steps in this tutorial. Open the video in a new tab to avoid leaving Bitbucket.Edit a fileYou’ll start by editing this README file to learn how to edit a file in Bitbucket.ClickSourceon the left side.Click the README.md link from the list of files.Click theEditbutton.Delete the following text:Delete this line to make a change to the README from Bitbucket.After making your change, clickCommitand thenCommitagain in the dialog. The commit page will open and you’ll see the change you just made.Go back to theSourcepage.Create a fileNext, you’ll add a new file to this repository.Click theNew filebutton at the top of theSourcepage.Give the file a filename ofcontributors.txt.Enter your name in the empty file space.ClickCommitand thenCommitagain in the dialog.Go back to theSourcepage.Before you move on, go ahead and explore the repository. You've already seen theSourcepage, but check out theCommits,Branches, andSettingspages.Clone a repositoryUse these steps to clone from SourceTree, our client for using the repository command-line free. Cloning allows you to work on your files locally. If you don't yet have SourceTree,download and install first. If you prefer to clone from the command line, seeClone a repository.You’ll see the clone button under theSourceheading. Click that button.Now clickCheck out in SourceTree. You may need to create a SourceTree account or log in.When you see theClone Newdialog in SourceTree, update the destination path and name if you’d like to and then clickClone.Open the directory you just created to see your repository’s files.Now that you're more familiar with your Bitbucket repository, go ahead and add a new file locally. You canpush your change back to Bitbucket with SourceTree, or you canadd, commit,andpush from the command line.
Package: promplate
Promplate</Promplate/> = <template> // promptPromplateis a prompting framework focusing on developing experience. However, it can also be a super-convenient SDK for simple LLM calls. Promplate progressively enhance your prompting workflow. And it values flexibility as well as perfect conventions.Learn moreInstallationpipinstallpromplatePromplatesupports both CPython and PyPy, from3.8to3.12. It even supports running in browsers through wasm implementations of python.DocumentationYou can visit our official docs site atdocs.py.promplate.dev.IDE Support 🌹Promplateis fully typed, which means static type checker will find bugs correctly (if you usepyrightfor type checking).We recommend using VS Code as your IDE when coding with promplate, because it natively uses pyright.The language design of promplate is similar toJinja2. So you can use the.j2file extension for template files for syntax highlight.Developmentusepoetryto manage dependencies.useisortto sort import statements.useblackto format code.usepyrightto check type annotations.Development should be done ondevbranch, using>=3.10language features. Themasterbranch is used forpy3.8compatible releases.Promplateis well tested withpytest. GitHub Actions are used to run tests and linting. And there are test results continually generated onVercel(py3.9)andNetlify(py3.8). There isa coverage reporttoo.Future Features (or TODOs?)more documentationjavascript implementationimprove error handlingpossible ways would be similar toJinja2
Package: promplate-pyodide
promplate-pyodideRun yourpromplateproject in the browser withpyodide!UsageIf you just want to use its templating staff:frommicropipimportinstall# in pyodide runtimeawaitinstall("promplate-pyodide")frompromplate_pyodideimport*patch_promplate()If you also want to use its OpenAI LLM, you should register theopenaimodule because it is not compatible with pyodide.
Note that you can register it as the JavaScript OpenAI SDK because its API is similar to the Python SDK.patch_promplate(True)This will patchensuremethod to return a JavaScript array instead of a Python list.
And it will remove sync APIs ofpromplate.llm.openaibecause the JavaScript OpenAI SDK is async-only.
Package: prompt
Python Prompt PackagePrompt and verify user input on the command line.Python 3.3+ and Wheels are supported.The project was initiated by Stefan Fischer.Documentationis
available on PythonHosted.Questionscan be asked via e-mail.Changesbetween releases are documented.Source codeis
tracked on GitHub.Bugscan be
reported on the issue tracker.InstallThe package is available onPyPI:$ pip install promptUseAn extensivedocumentationis available.Some simple use cases:import prompt

email = prompt.email()

# modify default prompt
integer = prompt.integer(prompt="Please enter a number: ")

# allow empty response
real = prompt.real(empty=True)

# require a two digit number using a regular expression
regex = prompt.regex("^\d\d$")ContributeWrite a bug report or send a pull request.Othercontributorshave done so before.Roadmapof planned improvementsIssuesthat
have been reportedLicenseCopyright (c) 2015-2017 Stefan FischerThe source code is available under theMIT License.SeeLICENSEfor further details.HistoryAll notable changes to this project will be documented in this file.This project adheres toSemantic Versioning.You shouldKeep a CHANGELOG, too!Next ReleaseAddedChangedDeprecatedFixedRemovedSecurity0.4.1- 2017-06-05Changedimproved infrastructure0.4.0- 2016-03-22Removedsupport for Python 3.20.3.2- 2016-03-22Addedunit testscoverage testing0.3.1- 2015-10-10Fixeddisplay of README on PyPI0.3.0- 2015-10-10Addedmodule documentationdocumentation on PythonHosted0.2.0- 2015-09-27Addedprompt.email()prompt.secret()0.1.0 - 2015-09-16Addedminimum viable product
Package: prompt2model
Prompt2Model - Generate Deployable Models from InstructionsPrompt2Modelis a system that takes a natural
language task description (like the prompts used for
LLMs such as ChatGPT) to train a small
special-purpose model that is conducive for deployment.Quick StartNotebookYou can run our demo ofPrompt2Modelthrough a notebook:Open LocallyOpen in ColabCommand LineYou can also run through the command line.pipinstallprompt2modelPrompt2Modelsupports various platforms such as OpenAI, Anthropic, Huggingface, etc. usingLiteLLM.If you are using OpenAI models (such as the defaultgpt-3.5-turbo), please obtain an
OpenAI API key on theirwebsitethen set
the environment variableOPENAI_API_KEYto your API key by running
the following command in your terminal:exportOPENAI_API_KEY=<yourkey>List of all supported providersYou can then runpythonprompt2model_demo.pyto create a small model from a prompt, as shown in
the demo video below. This script must be run on a
device with an internet connection to access the OpenAI
API. For best results, run
this script on a device with a GPU for training
your model.Demohttps://github.com/neulab/prompt2model/assets/2577384/8d73394b-3028-4a0b-bdc3-c127082868f2Tips and Examples to Write a Good PromptYou can see the tips and examples to write
a good prompt inprompt_examples.ComponentsTheprompt2modelpackage is composed
of several components, each designed
to fulfill a specific purpose. To gain
a comprehensive understanding of how to
utilize each component effectively,
please consult thereadme.mdfile
situated in the directory of the respective
component. These files can be found at./prompt2model/<component>/readme.md.
They provide detailed information and
instructions on customizing and maximizing
the functionality of each
component within the package.ContributionIf you're interested in contributing to theprompt2modelproject, pleaserefer toCONTRIBUTING.mdopen anissueor submit a PRjoin us ondiscordor reach out to@vijaytarianand@Chenan3_Zhaoon TwitterCiteWe havewritten a paper describing Prompt2Model in detail.If you use Prompt2Model in your research, please cite our paper:@misc{prompt2model,title={Prompt2Model: Generating Deployable Models from Natural Language Instructions},author={Vijay Viswanathan and Chenyang Zhao and Amanda Bertsch and Tongshuang Wu and Graham Neubig},year={2023},eprint={2308.12261},archivePrefix={arXiv},primaryClass={cs.CL}}
Package: prompt4all
Prompt is all you need !!這個專案是我基於openai api將我的一些想法落實的實驗場
一切都會環繞在如何協助人們更有效率的運用prompt來實現複雜的任務目前這個專案中已經實現了:暗黑模式 (new)將與ChatGPT交互模式抽象化(api/base_api/GptBaseApi)streaming 對話自動繼續(當因為字數因素中斷，會自動背景重發繼續，然後將回傳結果接在前面中斷的位置，使用者將完全沒有中斷的感覺，這是我開始這專案時最想完成的功能)歷史對話紀錄長文自動摘要(以縮減tokens數)超參數調整ChatGPT inside的傳統自然語言處理任務ChatGPT 與Dall.E2協作語氣改寫長文本滾動式摘要以及平行分塊摘要~~coming soon 會議錄音自動整理!!!!目前這個專案正在實現:更彈性的上下文管理機制，目前預計會有[@PROMPT] 一般指令[@GLOBAL] 全局指令(以append形式累加)[@SKIP] 跳脫上文(只要全局指令，無須上文)[@SANDBOX] 沙箱隔絕(連全局指令都不需要)[@EXPLAIN] 解釋上文[@OVERRIDE] 覆寫全局更多進階的商業應用場景目前這個專案未來希望實現:儲存思維鏈以及私有知識結合更多外部api如何開始使用:透過git將本專案下載至本機，並安裝相關requirementsgit clone https://github.com/AllanYiin/Prompt_Is_All_You_Need
cd Prompt_Is_All_You_Need
pip install -r requirements.txt
pip install -e .或者是直接利用以下語法安裝:pip install prompt4all --upgrade請依照指示將金鑰值賦值至環境變數OPENAI_API_KEY
執行以下語法即可啟動python -m prompt4all.app金鑰值賦值方法:如果您是在windows平台:
請在系統->進階系統設定->環境變數->使用者變數
中點選「新增」，在變數名稱中輸入:“OPENAI_API_KEY”
在值的部分輸入您的OpenAI API密鑰
需要重開機才能有效抓取到金鑰值如果您是在linux平台:
輸入以下命令：export OPENAI_API_KEY=your_api_key_here 將“your_api_key_here”替換為您的OpenAI API密鑰
Package: prompt4all-liteon
Prompt is all you need !!這個專案是我基於openai api將我的一些想法落實的實驗場
一切都會環繞在如何協助人們更有效率的運用prompt來實現複雜的任務目前這個專案中已經實現了:暗黑模式 (new)將與ChatGPT交互模式抽象化(api/base_api/GptBaseApi)streaming 對話自動繼續(當因為字數因素中斷，會自動背景重發繼續，然後將回傳結果接在前面中斷的位置，使用者將完全沒有中斷的感覺，這是我開始這專案時最想完成的功能)歷史對話紀錄長文自動摘要(以縮減tokens數)超參數調整ChatGPT inside的傳統自然語言處理任務ChatGPT 與Dall.E2協作語氣改寫長文本滾動式摘要以及平行分塊摘要~~coming soon 會議錄音自動整理!!!!目前這個專案正在實現:更彈性的上下文管理機制，目前預計會有[@PROMPT] 一般指令[@GLOBAL] 全局指令(以append形式累加)[@SKIP] 跳脫上文(只要全局指令，無須上文)[@SANDBOX] 沙箱隔絕(連全局指令都不需要)[@EXPLAIN] 解釋上文[@OVERRIDE] 覆寫全局更多進階的商業應用場景目前這個專案未來希望實現:儲存思維鏈以及私有知識結合更多外部api如何開始使用:透過git將本專案下載至本機，並安裝相關requirementsgit clone https://github.com/AllanYiin/Prompt_Is_All_You_Need
cd Prompt_Is_All_You_Need
pip install -r requirements.txt
pip install -e .或者是直接利用以下語法安裝:pip install prompt4all --upgrade請依照指示將金鑰值賦值至環境變數OPENAI_API_KEY
執行以下語法即可啟動python -m prompt4all.app金鑰值賦值方法:如果您是在windows平台:
請在系統->進階系統設定->環境變數->使用者變數
中點選「新增」，在變數名稱中輸入:“OPENAI_API_KEY”
在值的部分輸入您的OpenAI API密鑰
需要重開機才能有效抓取到金鑰值如果您是在linux平台:
輸入以下命令：export OPENAI_API_KEY=your_api_key_here 將“your_api_key_here”替換為您的OpenAI API密鑰
Package: promptapp
This is Prompt’s CLI.It has been developed using Python 2.There are two main folders: classes and tests.You can run unit and functional testing very easily using the bash script runTests.sh found at the project’s root.
That script also generates a coverage report in html, which will fall in the htmlcov folder, also at the project’s root.** WARNING **
You should use the bash script when being placed at the project’s root folder in your bash terminal, since there are
strong dependencies with paths. Correct test running is not guaranteed if this precondition isn’t met.Packaging has been configured followinghttps://python-packaging-user-guide.readthedocs.org/en/latest/
Package: prompt-args
Decorator to prompt input for missing arguments.Installpipinstallprompt_argsUsagefromprompt_argsimportPromptprint("Test automatic prompting")@Prompt.decoratedefmy_func(first_name:str,last_name:str="",status:str="well"):print(f"Hello,{first_name}{last_name}, I am{status}")my_func()print("\nTest controlled prompting")@Prompt.decorate(first_name=Prompt("First Name: "),last_name=Prompt("Last Name: ",default=""),status=Prompt("How are you? ",default="well"))defmy_func(first_name:str,last_name:str,**kwargs):print(f"Hello,{first_name}{last_name}, I am{kwargs.get('status')}")my_func()my_func("Jane","Doe",status="great")# Test error when a prompt is given, but the function argument does not existprint("\nTest controlled prompt error")try:@Prompt.decorate(first_name=Prompt("First Name: "),last_name=Prompt("Last Name: ",default=""),status=Prompt("How are you? ",default="well"))defmy_func(first_name:str,last_name:str):print(f"Hello,{first_name}{last_name}")exceptValueErrorase:assert"no corresponding function argument"instr(e)OutputTest automatic prompting
Enter First Name: John
Enter Last Name ['']:
Enter Status ['well']:
Hello, John , I am well

Test controlled prompting
First Name: John
Last Name ['']: Doe
How are you ['well']? just fine
Hello, John Doe, I am just fine
Hello, Jane Doe, I am great

Test controlled prompt errorRegister prompt helpers (“Enter … [{prompt_help}]: “).fromprompt_argsimportPrompt# Test built in bool converter with Y/n prompt help infoprint("Testing builtin type converter")@Prompt.decoratedefmy_func(x:int,confirm:bool=False):print(f"Change x to{x}?{confirm}")# Test nomy_func()# Test ymy_func()# Test custom type converterprint("\nTesting custom type converter")deflong_confirm(value:str)->bool:returnvalue=="Yes I am sure"Prompt.register_type_converter(bool,long_confirm,prompt_help="Yes I am sure/no")@Prompt.decoratedefmy_super_serious_func(x:int,confirm:bool=False):print(f"Change x to{x}?{confirm}")# Test invalid ymy_super_serious_func()# Test full Yes I am suremy_super_serious_func()Output:Testing builtin type converter
Enter X: 10
Enter Confirm [Y/n]: n
Change x to 10? False
Enter X: 12
Enter Confirm [Y/n]: y
Change x to 12? True

Testing custom type converter
Enter X: 20
Enter Confirm [Yes I am sure/no]: y
Change x to 20? False
Enter X: 25
Enter Confirm [Yes I am sure/no]: Yes I am sure
Change x to 25? TrueDo not prompt for some argumentsfromprompt_argsimportPromptprint("Test no prompting for some arguments")@Prompt.decorate(status=Prompt.no_prompt)defmy_func(first_name:str,last_name:str="",status:str="well"):print(f"Hello,{first_name}{last_name}, I am{status}")# Status should not be promptedmy_func()OutputTest no prompting for some arguments
Enter First Name: John
Enter Last Name ['']: Doe
Hello, John Doe, I am well