Saravanan666/pypi-org huggingface dataset:
Package: seapie
seapiepip installseapieAdditional licensingShow detailsThis software is licensed under The Unlicense as the author's protest towards
the modern copyright landscape. If you need a different lisence for a legal or
compability reasons, just ask.DocumentationShow details>>>importseapie>>>help(seapie)>>># Or take a look at the well documented source.Development detailsShow detailsLintingseapie$python-misort.
seapie$python-mblack.
seapie$python-mflake8src/test/Testingseapie$pythontest/??????Building & releasing# Remember to increment __version__ in version.pyseapie$python-mbuild--wheel&&rm-rfbuild/&&rm-rfsrc/seapie.egg-info/
seapie$python-mtwinecheckdist/*
seapie$python-mtwineuploaddist/*
seapie$rm-rfdist/
Package: seapipy
SeapiPyA Surface evolver API for pythonDocumentation:https://seapipy.readthedocs.io/InstallationUsageTo create a simple tissue 10x10 tissue, you can create a lattice object and initialize the vertices, edges and cells of
the system. Then, you might create values for the cell volumes directly. You could also create normally distributed
tensions for the edges.importseapipyasseplattice=sep.lattice_class.Lattice(10,10)vertices,edges,cells=lattice.create_example_lattice()volume_values={k:500fork,vincells.items()}initial_edges_tensions=lattice.get_normally_distributed_densities(edges)Then, you could create the Surface Evolver object using this variables and then initialize the Surface Evolver slate
where all the functions will be written into, before saving to diskse_object=sep.surface_evolver.SurfaceEvolver(vertices,edges,cells,initial_edges_tensions,volume_values,polygonal=False)se_file=se_object.generate_fe_file()The polygonal=False allows curved edges to exist in the tissue. Now, various Surface Evolver functions might be added
to the file buffer in these_filevariable. For example we could add an initial relaxing for the tissue withse_object.initial_relaxing()Afterwards, we could add a saving function to create a checkpoint in the Surface Evolver simulation usingse_object.save_one_step("path/to/saving/checkpoint","step_")Which would save the state of the Surface Evolver simulation at"path/to/saving/chekcpoint"with name"step_"followed
by the number of times it has been saved.
Finally you could save the whole Surface Evolver slate into the disk and run it usingse_object.save_fe_file("SurfaceEvolverFile")sep.command.run_evolver("path/to/SurfaceEvolverFile","path/to/SurfaceEvolverExecutable")
Package: seaplane
Seaplane Python SDKSimple Python library to manage your resources at seaplane.What is Seaplane?Seaplane is the global platform for building and scaling your application stack
without the complexity of managing cloud infrastructure.It serves as a reference application for how our APIs can be utilized.Not sure where to go to quickly run a workload on Seaplane? See ourGetting
Startedguide.To build and test this software yourself, see the CONTRIBUTIONS.md document that is a peer to this one.InstallationpipinstallseaplaneConfigure your API KEYYou can provide your Seaplane API key to the library in a few waysSetSEAPLANE_API_KEYenvironment variable.Useconfigobject in order to set the api key.fromseaplane.configimportconfigconfig.set_api_key("your_api_key")LicenseLicensed under the Apache License, Version 2.0,LICENSE. Copyright 2022 Seaplane IO, Inc.
Package: seaport
The modernMacPortsportfile updater.> seaport clip gping
🌊 Starting seaport...
👍 New version is 1.2.0-post
🔻 Downloading from https://github.com/orf/gping/tarball/v1.2.0-post/gping-1.2.0-post.tar.gz
🔎 Checksums:
Old rmd160: 8b274132c8389ec560f213007368c7f521fdf682
New rmd160: 4a614e35d4e1e496871ee2b270ba8836f84650c6
Old sha256: 1879b37f811c09e43d3759ccd97d9c8b432f06c75a27025cfa09404abdeda8f5
New sha256: 1008306e8293e7c59125de02e2baa6a17bc1c10de1daba2247bfc789eaf34ff5
Old size: 853432
New size: 853450
⏪️ Changing revision numbers
No changes necessary
📋 The contents of the portfile have been copied to your clipboard!InstallationMacPorts 🍎sudo port install seaportPyPi 🐍pip3 install seaport
# Optionally, install GitHub CLI to send PRs
sudo port install gh⚡️ Features🖥Command Line Tool⏩Automatically determines new version numbers and checksumsfor MacPorts portfiles.📋Copies the changes to your clipboard, and optionallysends a PR to update them.🔎 Containsadditional checking functionality, such as running tests, linting and installing the updated program.🐍Python API📚 Library for convenient access to portfile information. Easily import as a Python module for your project.⌨️PEP 561 compatible, with built in support for type checking.📦 Works out of the box with allsupported Python versions(3.7-3.11).To find out more, please read theDocumentation.🤔 How to use seaportFor simple ports with straightforward updates, useseaport pr example_port.
This sends a PR with the updated portfile and automatically fills in the PR template for you.For ports that require some manual changes, useseaport clip example_port.
This updates the version number and checksums so you don’t have to. 😎Be sure to check out theflags overviewfor information on additional features.🔥 seaport vs port bumpFeatures🌊 seaport🛼 port bump🔒 Updates checksums✅✅📚 Updates the revision number✅✅📝 Can write changes to the original file✅✅⏮ Can update portfile to a specific version✅✅🔮 Updates the version number via livecheck✅❌🚀 Can send a pull request (both for updated and new ports)✅❌🧪 Can lint/test/install the port to check if the update works✅❌📋 Copies changes to clipboard✅❌🌎 Can both manually and automatically set the url to download from✅❌🔨 ContributingIssue Tracker:https://github.com/harens/seaport/issuesSource Code:https://github.com/harens/seaportAny change, big or small, that you think can help improve this project is more than welcome 🎉.As well as this, feel free to open an issue with any new suggestions or bug reports. Every contribution is appreciated.For more information, please read ourcontributing pageon how to get started.©️ LicenseSimilar to other MacPorts-based projects, seaport is licensed under theBSD 3-Clause “New” or “Revised” License.📒 Notice of Non-Affiliation and DisclaimerThis project is not affiliated, associated, authorized, endorsed by, or in any way officially connected with the MacPorts Project, or any of its subsidiaries or its affiliates. The official MacPorts Project website can be found athttps://www.macports.org.The name MacPorts as well as related names, marks, emblems and images are registered trademarks of their respective owners.
Package: seapy
# IntroductionSeaPy is a Python module to assist in performing a Statistical Energy Analysis, or SEA.
SEA is used within vibroacoustics to model the flow of acoustic power through a vibrating system.
An example is modeling the vibrations in cars due to the engine.
SEA is generally used in the high-frequency region whereas finite-element analysis is used in the low-frequency region.First step in performing an SEA is creating the geometry.
Then, the relevant components are modeled as subsystems, where each subsystem represents one wave type.
The subsystems are then connected through couplings.
Power is added into the system through excitation of one or more subsystems.
Power dissipation in subsystems and couplings are modeled using loss factors.
Finally, a single matrix composed of loss factors, modal densities and input powers, are solved resulting in the modal energies of each subsystem, from which their vibration or noise levels can be calculated.# SeaPyThis module provides several classes and functions to perform an SEA. First, an object of the main class System() has to be created.
Then, components, subsystems, couplings and excitations can be added to the System() instance.
Finally, when all properties have been set, the modal energies can be solved by executing the solveSystem() method of the System() instance.# PrerequisitesRequired are:Python 3.4 or higherNumPymatplotlib# InstallingVia pip:pip install seapyVia conda:conda install -c …Or clone this repository:## DocumentationDocumentation can be viewed at [Python Hosted(https://pythonhosted.org/seapy/) and also [here](http://www.fridh.nl/seapy/).## Reporting bugs
Package: seaqube
SeaQuBeSemantic Quality Benchmark for Word Embeddings, i.e. Natural Language Models in Python. AcronymSeaQuBeorseaqube.This python framework provides several text augmentation implementations and word embedding quality evaluation methods. It is designed to fit in your machine learning pipeline. TheBaseAugmentationclass provides the same api as the python packagenlpaug, so that this packages can used together smoothly. HoweverBaseAugmentationprovides also other methods. Detailed examples see beneath.SeaQuBeprovides also a toolkit to wrap a trained nlp model to a nice interactive tool.FeaturesText Data AugmentationChaining and Reducing of Text Data AugmentationsWord Embedding Quality MethodsInteractive NLM Model WrapperDemoAugmentation in three linesExample of Basic Text AugmentationExample of Text Augmentation ChainingExample of Word Embedding EvaluationExample of Interactive NLPAugmentationLevelAugmenterDescriptionCharacterQwertyAugmentationSimulate keyboard distance errorCorpusUnigramAugmentationReplace ubiquitous words with other ubiquitous wordsWordActive2PassiveAugmentationChange surface of document using an simple active-to-passive transformerWordEDAAugmentationAugment document using theEDAalgorithmWordEmbeddingAugmentationReplace similar word usingWordNetWordTranslationAugmentationChange surface of document using translation and back-translation (withGoogleTranslate)Augmentation ChainerThe streaming feature of augmentation is implemented in theAugmentationStreamerclass. OneReduceingclass exist, more can implemented
extending theBaseReductionclass.ActionClassDescriptionStreamingAugmentationStreamerRun augmentation for each document through all chained augmentations.ReducingUniqueCorpusReductionGetting a list of documents, only unique documents are returned.Word Embedding EvaluationMethodDescriptionWordAnalogyBenchmarkThis method benchmark how go relations of the type:a is to b as c is to dcan be solved correctly.WordSimilarityBenchmarkThis methods compares the similarity of a word pair, calculated by a model with a human estimated similarity score.WordOutliersBenchmarkThis method benchmark how good a outlier of a group of words can be detected.SemanticWordnetBenchmarkBased on the WordNet graph, the goodnes of the semantic / similarity of a nlp model is benchmarked.InstallationSeaQuBecan be installed from PyPip using:pip install seaqubeor run in the main directory:python setup.py install.External DependenciesSome external dependencies are not installed automatically, butseaqubeornltkmight throw errors with an instruction what to do.
For examplesequbemight ask you to run:python-c"from seaqube import download;download('vec4ir')"Quick Demofromseaqube.augmentation.wordimportActive2PassiveAugmentation,EDAAugmentation,TranslationAugmentation,EmbeddingAugmentationtranslate=TranslationAugmentation(max_length=2)translate.doc_augment(['This','is','a','tokenized','corpus'])Setup Dev EnvironmentTODO
Package: search4
An OSINT tool that helps you to find people on the internet. It's small and fast!PrerequisitesInstall python3 as per your distro.Installing search4Now you can install search4 using git:pip3 install -U search4Or, if you already downloaded search4, you can install it directly from the directory:pip3 install .You can use the-eflag to install the project in editable mode (i.e. setuptools "develop mode") from a local project path or a VCS url.Demosearch4 -u usernameCopyright & LicenseCopyright (C)  2022meaniiLicensed under the terms of theGNU General Public License v3.0
Package: search4file
search4filepip install search4file你好，我是Python程序员晚枫。这个库实现的功能：根据文件内容，搜索文件位置。已经集成到python-office里了👉视频教程开发者微信：CoderWanFeng功能通过内容查找文件通过名称查找图片ocr识别图片内容通过字幕、画面查找视频To List有3类并行推进的任务：1、查找逻辑3个按照内容查找的接口，需要实现接口传送门负责开发：@yinzeyuandefsearch_pdf_file(self,file_path,search_content):passdefsearch_ppt_file(self,file_path,search_content):passdefsearch_excel_file(self,file_path,search_content):pass1个按照文件名查找的接口，需要实现接口传送门负责开发：@yinzeyuanclassSearchByName():# 搜索文件名的逻辑defsearch_files(self,search_path,search_content):pass2、优化逻辑优化内容，目前主要有：目前的word查找基于python-docx库，而这个库不支持mac、linux库。考虑改为解压docx的方式，对解压后的文件进行查找。目前对文件的查找，采用单线程同步遍历的方式，速度太慢。考虑改为进程 + 协程的异步方式，提高查询效率。增加OCR自动根据指定的图片内容，进行图片搜索。例如：用户输入：河流，查找出电脑里所有和河流有关的图片识别出视频里的内容。例如：用户输入：大山，查找出某个视频里，所有和大山有关的画面、字幕3、交流群
Package: searchads-api
# About Phiturehttp://phiture.comis a Berlin-based mobile growth consultancy working with the teams behind leading apps. Using the company’s industry-acclaimed Mobile Growth Stack as a strategic framework, Phiture team offers 4 key services: App Store Optimization, Apple Search Ads, User Retention services and Growth Consulting.# Apple Searchads API Library in PythonIn order to facilitate the usage of the Apple Search Ads API Phiture’s Engineers
have built a library in Python which allows users to manage campaigns, ad groups,
keywords and creative sets. This library only requires intermediate Python skills
and therefore makes it possible not only for Engineers but also for Data Analysts
and Apple Search Ads Consultants to work with it.
While the library is extensive it is not complete and users are encouraged to commit suggestions.Read the docs on github.# Example Usage:Setup for v4 of the librarycreate a certs directory inside of your project folder, or create a different certs directory and specify it using the certificates_dir_path argument.api = SearchAdsAPI(2134535, “public.pem”,”private.key”,
client_id=”SEARCHADS.07875add-f6cd-4111-9c38-b84501d557c8”,
team_id=”SEARCHADS.07879add-d6cd-4111-9c38-b84501d527c8”,
key_id=”78a167b1-e423-4ab4-bcd1-8be75a4d7b7e”, verbose=True)### Campaign MethodsCreate a new campaignres = api.create_campaign(1433439534, [‘AU’], “test”, 1, 1, “EUR”)## Changelogversion 0.1.1 Added granularity level reportsversion 0.7.1 fixed some issues with granularityversion 1.1.1 added support for the v4 of the Apple Search Ads APIversion 1.2.1 refresh access_tokn only when neededversion 1.5.1 handles API error with Exceptionversion 1.5.3 fixed token update issueversion 1.6.1 added new product page, reporting, and Ad endpoints. Deprecated creatives endpointsversion 1.6.3 includes new bug fixesversion 1.7.1 added impression share reports and new find methods along product pages to match Searchads API version 4.7version 1.7.6 fixed an issue with token updateversion 1.7.7 fixed an issue update_campaignversion 1.7.8 updated the dependenciesversion 1.7.9 always use the latest requests packageversion 1.7.10 always use the latest requests package
Package: searchagent
searchagent is an Apache2 licensed library for storing prompts for summarization, question and answer tasks with large language models.Why?For production, once you ship your binary, how are you going to maintain the prompts?As a team, is there a centralized place to store prompts for re-use?Because some other libraries are heavy weight.How to Use$pipinstallsearchagentfromsearchagent.promptsimportPromptsdefsomeMethod():prompts=Prompts().get_data()print(prompts["system"])
Package: searchalg
searchalgDevelopment SetupCreate and activate virtual environmentpython -m venv venv
source venv/bin/activate or venv\Scripts\activateInstall dev-dependencies (editable)flit installPublish to PypiUpdate the__version__insearchalg/__init__.pySetSOURCE_DATE_EPOCH=$(date +%s)(seeflit reproducible builds)Update theCHANGELOG.mdincluding the value ofSOURCE_DATE_EPOCHvariablePublish the package to pypi:flit publish
Package: search-algos
search-algossearch-algos is a Python package that includes various searching algorithms for lists and python dictionaries. The package is designed to be easy to use and can be integrated into any Python project that requires optimized searching functionality.Searching Algos:Linear SearchBinary SearchExponential SearchFibonacci SearchInterpolation SearchJump SearchTernary SearchInstallationYou can install search-algos using pip:pip install search-algosUsageTo use the searching algorithms in search-algos, you first need to import the package:from search_algos import linear_search, binary_search

lst = [1, 2, 3, 4, 5]
item = 3

print(linear_search(lst, item))  # Output: 2
print(binary_search(lst, item))  # Output: 2ContributingIf you would like to contribute to search-algos, you can fork the repository and submit a pull request. We welcome contributions of all kinds, including bug reports, feature requests, and code contributions.Licensesearch-algos is licensed under the MIT License. See the LICENSE file for more information.
Package: search-analysis
Search AnalysisThe search analysis library contains multiple tools to help you analyze your search engine approach.Free software: MIT licenseDocumentation: Coming soonFeaturesUse-Case: Analyze Single ApproachGet Metrics: Precision, Recall, F-ScoreFind queries that perform especially bad/goodAnalyze false positives, false negatives and true positivesFor every query get score, field value, highlightingUse-Case Compare Two ApproachesVisualization of metrics side by sideFind queries with biggest differenceAnalyze false positives, false negatives, true positives and calculate disjoint setsGet scores visualized side by side(For now it’s only possible to work with Elasticsearch)HelpFor questions you can contact us via E-Mail or through our website (https://www.pragmalingu.de/).CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-03-16)First release on PyPI.
Package: searchbible
# Search Bible AIIntegrate Unique Bible App resources with AI toolsBuilt upon our projects, the [UniqueBible App](https://github.com/eliranwong/UniqueBible) and [LetMeDoIt AI](https://github.com/eliranwong/letmedoit), SearchBible AI is our latest Bible app that aims to integrate our comprehensive Bible resources with the recent advancements in AI technology and tools.# Installation / Upgrade> pip install –upgrade searchbible# Usage> searchbible> searchbible <query>e.g.> searchbible “John 3:16”> searchbible “Jesus loves”enter a single reference to display a full chapterenter multiple references to display versesenter a bible version abbreviation, e.g. KJV, to switch to a particular bible versionenter a search query to perform a simple searchenter ‘.verses’ or press ‘Ctrl+F’ to perform a detailed search for versesenter ‘.paragraphs’ or press ‘Esc+F’ to perform a detailed search for paragraphspress ‘Ctrl+P’ to toggle bible comparisonpress ‘Esc+P’ to select bible versions for comparisonpress ‘Ctrl+G’ to launch ChatGPT chatbotpress ‘Esc+G’ to luanch GeminiPro chatbotpress ‘Ctrl+K’ to display available shortcut keysenter ‘{config.exit_entry}’ or press ‘Ctrl+Q’ to exit current feature of quit the app## Shortcutsenter “:” to reload previously selected chapter and verseenter “<chatper_number>:” to open a particular chapter in the same book, e.g. “3:”enter “:<verse_number>” to select a particular verse in the same chapter, e.g. “:16”To start with default entry from terminal, e.g.:> searchbible KJV> searchbible “John 3:16; Rm 5:8”> searchbible “Jesus love”## UBA module converterTo convert an UniqueBible App bible files, with a given path, e.g. /temp/KJV.bible> searchbibleconverter -b /temp/KJV.bibleFor batch conversion, place multiple bible files in a folder, e.g. /temp/> searchbibleconverter -b /temp/![batch_conversion](https://github.com/eliranwong/searchbibleai/assets/25262722/18fb9bf6-1e57-45ca-85c5-232c5b78d0b2)# ProgressSupport conversion of UnqiueBible App bibles (done)Build simple cli interface for reading single bible chapter (done)Build simple cli interface for searching verses (done)Build simple cli interface for searching paragraphs (done)Integrate bible comparison feature (done)Integrates ChatGPT and Gemini Pro features (partial)Support more UnqiueBible App bible resources (pending)Build a Qt-based graphical user interface, like we do in [UniqueBible App](https://github.com/eliranwong/UniqueBible) (pending)# New Features that are not available in oiginal Unique Bible Appbible modules vector database formats on top of SQLite formatsupport searching individual paragraphs in addition to searching individual versessupport semantic searches (i.e. search for meaning); both in verses and paragraphssupport cross-language semantic searches, e.g. search a Greek bible with English input or search an English bible with Chinese inputcombination of literal search, semantic search and regular expression search in a single searchmore to be added
Package: searchbibleai
# ATTENTIONThis package is renamed to “searchbible”.Please visithttps://pypi.org/project/searchbiblefor all latest updates.# Search Bible AIIntegrate Unique Bible App resources with AI toolsBuilt upon our projects, the [UniqueBible App](https://github.com/eliranwong/UniqueBible) and [LetMeDoIt AI](https://github.com/eliranwong/letmedoit), SearchBible AI is our latest Bible app that aims to integrate our comprehensive Bible resources with the recent advancements in AI technology and tools.# Installation / Upgrade> pip install –upgrade searchbible# Usage> searchbibleTo convert an UniqueBible App bible file, e.g.:> searchbibleconvertor -b “/temp/NET.bible”# ProgressSupport conversion UnqiueBible App bibles (done)Build simple cli interface for reading single bible chapter (partial)Build simple cli interface for searching verses (partial)Build simple cli interface for searching paragraphs (pending)Integrates ChatGPT and Gemini Pro features (pending)Support more UnqiueBible App bible resources (pending)Build a Qt-based graphical user interface, like we do in [UniqueBible App](https://github.com/eliranwong/UniqueBible) (pending)
Package: search-binary
binarysearch_buildA simple implementation of binary search in Python.Binary SearchBinary Search is a searching algorithm used in a sorted array by repeatedly dividing the search interval in half.InstallationMake sure you have Python installed in your system.Run Following command in the CMD.pip install search_binaryUsageHere's an example of how to use thebinary_searchfunction:from search_binary import binary_search

arr = [1, 2, 3, 4, 5, 6, 7, 8, 9]
target = 5
result = binary_search(arr, target)
print(result) # Output: 4Thebinary_searchfunction takes in two arguments:arrandtarget. Thearrargument is a list of sorted values, and thetargetargument is the value you're searching for in the list. The function returns the index of the target value in the list, or-1if the target value is not found.ContributingContributions are welcome! If you'd like to contribute, simply fork the repository, make your changes, and submit a pull request.LicenseThis package is licensed under the MIT License. See theLICENSEfile for details.
Package: search-cli
Search CLISmall tools to interface with search engine form the command line that has tight integration with the linux X clipboard.For python 3 installs:sudo apt install surfraw surfraw-extra xclip python3-tkFor python 2sudo apt install surfraw surfraw-extra xclip python-tkinstall withpip install .orpip install search-cliPrograms:searchorsr: Search from the command line with a backoff to search for what ever is on your clipboard if you don't type anythingsearch_highlighted: Search for the highlighted span.search_gui: Create a text input box and search for entered text with<Enter>search_gui_highlighted: Same as above but seeded with the currently highlighted text.search_highlighted,search_gui, andsearch_gui_highlightedare ideal for keybinding.When the search bar loses focus (you click away) it will automatically close. If you don't like this behavior you can setSR_CLOSE_LOSS_FOCUStonoto stop it.Windows:On windows only searching with google is supported. To run you will need python installed
and the entry point scripts exectuable. This normally involes adding paths like the
following to your path (control panel->System and Security->System->Advanced system settings->Environment Variables)C:\Users\LENOVO\AppData\Local\Programs\Python\Python37-32\Scripts
C:\Users\LENOVO\AppData\Local\Programs\Python\Python37-32On windows I can't get the selected text the same way I can on Linux so there areautoHotKeyscripts in thewinfolder than can simulate this behavior.