Saravanan666/pypi-org huggingface dataset:
Package: similarius
SimilariusSimilarius is a Python library to compare web page and evaluate the level of similarity.The tool can be used as a stand-alone tool or to feed other systems.RequirementsPython 3.8+RequestsScikit-learnBeautifulsoup4nltkInstallationSource installSimilariuscan be install with poetry. If you don't have poetry installed, you can do the followingcurl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python.$poetryinstall
$poetryshell
$similarius-hpip installation$pip3installsimilariusUsagedacru@dacru:~/git/Similarius/similarius$similarius--help
usage:similarius.py[-h][-oORIGINAL][-wWEBSITE[WEBSITE...]]optionalarguments:-h,--helpshowthishelpmessageandexit-oORIGINAL,--originalORIGINALWebsitetocompare-wWEBSITE[WEBSITE...],--websiteWEBSITE[WEBSITE...]WebsitetocompareUsage exampledacru@dacru:~/git/Similarius/similarius$similarius-ocircl.lu-weuropa.eucircl.eucircl.luUsed as a libraryimportargparsefromsimilariusimportget_website,extract_text_ressource,sk_similarity,ressource_difference,ratioparser=argparse.ArgumentParser()parser.add_argument("-w","--website",nargs="+",help="Website to compare")parser.add_argument("-o","--original",help="Website to compare")args=parser.parse_args()# Originaloriginal=get_website(args.original)ifnotoriginal:print("[-] The original website is unreachable...")exit(1)original_text,original_ressource=extract_text_ressource(original.text)forwebsiteinargs.website:print(f"\n**********{args.original}<->{website}**********")# Comparecompare=get_website(website)ifnotcompare:print(f"[-]{website}is unreachable...")continuecompare_text,compare_ressource=extract_text_ressource(compare.text)# Calculatesim=str(sk_similarity(compare_text,original_text))print(f"\nSimilarity:{sim}")ressource_diff=ressource_difference(original_ressource,compare_ressource)print(f"Ressource Difference:{ressource_diff}")ratio_compare=ratio(ressource_diff,sim)print(f"Ratio:{ratio_compare}")
Package: similar.py
similarA dependency less python library made for finding similar text inspired fromsimilarUsageimportsimilarmatch=similar.best_match("apply",["pickle","apple","orange"])print(match)>appleExtrasAlso works withfile -importsimilarmatch=similar.best_match("apply",open("words.txt","r"))print(match)>appleor generator objectimportsimilardefgenwords():forwordin["picke","apple","orange"]:yieldwordmatch=similar.best_match("apply",genwords())print(match)>apple
Package: similar-search
isearchAn image search tool to find similar images on your disk.Installpip install similar-searchUsageisearch [-h] [-a ahash/dhash/phash] [-l 1-10] baseimg gallery...Argumentspositional arguments:baseimg: the image to searchgallery: the gallery for searching sourcesoptions:-h, --help: show this help message and exit-a ahash/dhash/phash: image similarity recognition algorithm (default: "phash")-l 1-10: tolerance level of the similarity algorithm (default: 10)-v: show isearch's version
Package: similar-sounding-words
Similar sounding wordsThis is a list of similar sounding words that I have collected from various sources on the web
and added to as I find new pairs.Unlike most homophone, homograph, and homonym resources this list is not targeting
ESL or educational use. Instead it is designed for finding common errors in speech recognition texts.
Specifically I use it withCasterfor voice programming.In addition to my custom file I currently have five different sources:https://7esl.com/homophones/https://web.ku.edu/~edit/wordsall.htmlhttp://www.singularis.ltd.uk/bifroest/misc/homophones-list.htmlhttps://www.teachingtreasures.com.au/teaching-tools/Basic-worksheets/worksheets-english/upper/homophones-list.htmhttps://www.thoughtco.com/homonyms-homophones-and-homographs-a-b-1692660I preprocessed some of these files in a text editor and
random three Jupiter notebook available in the github repository
to generate the index.All source files are copyright their respective authors.TODOadd mapping of words to numbers
Package: similarwebact
SimilarWeb for Team ACT v.0.0.1This module has been built to provide a better environment specifically for Similarweb in Team ACT.This module itself would not contain any confidential information & nor is incapable of retrieving any data unless the correct API credential is given.
The guide of pulling data will be only provided internally, no inquires will be accepted from outsiders.FunctionalitiesConversion DataMore functionalities will be added in sooner time.
Package: similarweb-rest-api
similarweb REST APIIntroductionThe similarweb REST API is a library that simplifies the access to the REST API of Similarweb.InstallationTo install the library, run the following command:Copy codepip install similarweb-rest-apiUsageTo use the library, import the SimilarwebApi class and create an instance of it. Then, use the get method to make a request to the API.fromsimilarweb_rest_apiimportSimilarwebApiapi=SimilarwebApi()response=api.get('website/traffic',domain='example.com',start_date='2020-01-01',end_date='2020-01-31')The get method returns a SimilarwebResponse object, which contains the API response in various formats. To access the response in a specific format, use one of the following methods:to_json:returns the response as a JSON stringto_dataframe:returns the response as a Pandas DataFrameto_sql:returns an SQL statement to insert the response into a tableto_xml:returns the response as an XML documentto_excel:writes the response to an Excel fileto_csv:writes the response to a CSV fileto_html:returns the response as an HTML tableto_jsonl:writes the response to a JSON Lines fileto_yaml:returns the response as a YAML documentFor example, to convert the response to a DataFrame and display the first 5 rows:df=response.to_dataframe()df.head()ParametersThe following parameters can be passed to the get function:name:The name of the API endpoint.domain:The domain to get data for.api_key:Your API key.start_date:The start date for the data range (in the format YYYY-MM).end_date:The end date for the data range (in the format YYYY-MM).LicenseThis library is free to use for non-commercial purposes. For commercial use, please contact the author for permission.ContactIf you have any questions or suggestions, please contact the author Damien Frigewski atdfrigewski@gmail.com.
Package: similarweb-scraper
similarweb_scrapersimilarweb_scraperis is a python library for scraping similarweb with proxycrawl api and it can bypass the distil projection so far. It also provides some functionality for transforming scraped data into pd dataframe.InstallationUse the package managerpipto install foobar.pipinstallsimilarweb-scraper## Usagefromsimilarweb_scraperimportscraper### get the website htmlweb_scrape=scraper()web_scrape.login(#api key from proxycrawl.com)web_scrape.webpage_scrape(#websit e.g: hk.yahoo.com)### get the html codesoup=web_scrape.og_soup### get the html code as json formatweb_json=web_scrape.json_storage### get data into json formatdf=web_scrape.metrics_to_df(#str(metrics_type))##metrics_type name :#'country_share',#'traffic_share',# engagement',#'monthly_traffic_data'# more function will be available soonContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: simim
SimIMSimIM is a tool for simulating the extra-galactic sky in radio, sub-mm and
far-infrared. Full documentation is available viaRead the
Docs. Source code is avialable viaGitHub.This is Version 0.1, which includes only basic utilities for downloading and
formatting simulation data, adding new properties such as spectral line emission
to simulations, and visualizing basic data. Incremental releases will add
functionality building light cones, making data cubes or maps, and creating mock
timestreams.
Package: siminotes
SimiNotes - CLI Tool for Similar Note RetrievalSimiNotes is a command-line interface (CLI) tool written in Python that enables users to discover similar notes within their
notes collection. The tool utilizes sentence embeddings with sbert to compare a given query against a corpus of user notes.FeaturesEmbedding:Utilizes sbert to generate vector embeddings for notes.Similarity Search:Finds notes similar to a given query based on embeddings.Configurable:Allows users to configure directories, file extensions, and exclusion criteria.InstallationBefore using this CLI tool, ensure that you have Python and pip installed. Additionally, install the PyTorch library by
following the steps below:Download and install Python and pip from theofficial site.Install the PyTorch library separately based on your requirements. For the CPU version, use the following command:pip3installtorchtorchvisiontorchaudio--index-urlhttps://download.pytorch.org/whl/cpuNow, install the SimiNotes CLI tool:pipinstallsiminotesConfigurationBefore using the CLI, configure some essential values, such as the notes directory and exclusions. SimiNotes uses a
configuration file (config.txt) to set preferences. Configure the tool by creating the file in the appropriate configuration
directory.Configuration DirectoryLinux:~/.config/siminotesconfig/macOS:~/.siminotesconfig/Windows:For Windows, use AppData\Roaming for per-user configuration:AppData\Roaming\Siminotes\Alternatively, placeconfig.txtin the home directory:~/.siminotesconfig/Configuration File (config.txt)Create aconfig.txtfile in the configuration directory. Below is an example configuration:notes_dir = /path/to/your/notes
exclude_dir = directory1,directory2
exclude_file = file1,file2
note_extension = .mdConfiguration Parameters:notes_dir: Path to the directory containing your notes.exclude_dir: Comma-separated directories to exclude from the search. Paths should be relative to notes_dir.exclude_file: Comma-separated files to exclude from the search. Paths should be relative to notes_dir.note_extension: The extension of your note files (e.g., .md).UsageNow let's use our cli,Command-Line ArgumentsQuery via Text:siminotestext"Your Query Text"Query via File:siminotesfilefilenameBoth will result in,Top files which are similar to given query:
Value range from -1 to 1, where going toward 1 means note is close to query

/... with score 0.43386968970298767

/... with score 0.42138463258743286

...TroubleshootingIf you encounter any errors or problems with this tool, please open an issue in the repository.LicenseThis project is licensed under the MIT License.ContributingFeel free to contribute to SimiNotes by creating issues or submitting pull requests.AcknowledgmentsSentence-BERTfor sentence embeddings.Future:I feel like simple dot product hits are enough to find similar notes but in future if there is need to
improve results then consider this roopRetrieve and RerankVid TutIf it is taking more memory, then we can quantise the vectors into int8Quantisation GuideGithub Repo to check
Package: simio-di
SimioSmall and simple dependency injector. Made for frameworkSimio.SupportsProviders,Variables,DependenciesWorks with async functionsFriendly with mypyDoes not steal constructor and doesn't change injected objectSupports Singletone injections or new instances on every injectionEasy to useExamplesSo for example let's look at this codeimportasynciofromdataclassesimportdataclassfromsimio_diimportDepends,Var,DependencyInjector,DependenciesContainer@dataclassclassMongoClient:mongo_dsn:str@dataclassclassWorker:mongo:Depends[MongoClient]env_type:Var['env']asyncdefstart_worker(worker:Worker,env:Var['env']):# do some work...# To make it work all you need to do is:config={MongoClient:{'mongo_dsn':'localhost:27017'},'env':'dev',}di=DependencyInjector(config,deps_container=DependenciesContainer())asyncio.run(di.inject(start_worker))But what if we wanna use interfaces instead of realization? Use providers!importasynciofromdataclassesimportdataclassfromtypingimportProtocolfromsimio_diimportProvide,Depends,Var,DependencyInjector,DependenciesContainer@dataclassclassUserDaoProtocol(Protocol):asyncdefget_user_info(self):...asyncdefupdate_user_info(self):...asyncdefuser_page_handler(user_dao:Provide[UserDaoProtocol]):# do some work...# Now lets make realization of protocol@dataclassclassMongoClient:mongo_dsn:Var['mongo_dsn']@dataclassclassMongoUserDao:mongo:Depends[MongoClient]asyncdefget_user_info(self):...asyncdefupdate_user_info(self):...# Now lets make it workconfig={# Provider bindingsUserDaoProtocol:MongoUserDao,# Variables'mongo_dsn':'localhost:27017',}di=DependencyInjector(config,deps_container=DependenciesContainer())injected_handler=di.inject(user_page_handler)asyncio.run(injected_handler)If you need your clients as singletone, useSingletoneDependenciesContainerfromsimio_diimportDependencyInjector,SingletoneDependenciesContainerconfig={# some config}di=DependencyInjector(config,deps_container=SingletoneDependenciesContainer())di.inject(something)TestingDI does not change object that's being injected, so you can use deps in test like this:asyncdefuser_page_handler(user_dao:Provide[UserDaoProtocol]):...asyncdeftest_user_page_handler():result=awaituser_page_handler(user_dao=Mock())
Package: simiotics-lambada
lambadaManage AWS Lambda functions using a Simiotics Function RegistryInstallpip install -U simiotics-lambadaUseThis section lets you try outlambadausing ourexamplehellofunction.First, export yourSIMIOTICS_FUNCTION_REGISTRYenvironment variable. This tellslambadawhich
Simiotics Function Registry to work with. If you do not have a private Simiotics account, you can
use our free, public, and totally open registry:export SIMIOTICS_FUNCTION_REGISTRY=registry-alpha.simiotics.com:7011Make sure that your AWS credentials are available either by exportingAWS_ACCESS_KEY_IDandAWS_SECRET_ACCESS_KEYor by ensuring that the profile you want to use isdefaultin your
AWS credentials file, or by exportingAWS_PROFILE. If you are not familiar with AWS
authentication, you can read more here:https://docs.aws.amazon.com/cli/latest/userguide/cli-chap-configure.htmlDecide on a key under which you would like to register thehellofunction into the Simiotics
Function Registry. For example:HELLO_KEY=hello-$(date -u +%s)Register the function against the Simiotics Function Registry usinglambada:lambada register --key $HELLO_KEY \
    --code examples/hello/hello.py \
    --handler hello \
    --requirements examples/hello/requirements.txtCheck that the function was successfully registered (if the output of the following command is
empty, there is a problem):lambada list | grep "$HELLO_KEY"Create an AWS IAM role capable of executing thehellofunction and logging to CloudWatch:lambada create_role --key $HELLO_KEY --name iam-lambada-demoDeploy the function as an AWS Lambda:lambada deploy --key $HELLO_KEY --name lambda-lambada-demoThis should return an AWS Lambda ARN of the form:arn:aws:lambda:<REGION>:<PROJECT ID>:function:lambda-lambada-demoNow you can invoke the deployed Lambda using the AWS command-line interface:OUTFILE=$(mktemp)
aws lambda invoke --function-name lambda-lambada-demo \
    --payload '{"target": "Sophia"}' \
    $OUTFILE
cat $OUTFILE
rm $OUTFILETo take down the AWS Lambda:lambada down --key $HELLO_KEYThis only removes the AWS Lambda. It doesn't delete the IAM role. If you would like to get rid of
that, as well:lambada down --key $HELLO_KEY --teardownKick back,enjoy some smooth tunes, and let the
Lambdas proliferate.SupportIf you experience any problems with this tool, please add an issue on this repository.
Package: simipro
SIMSIMISimsimiAPI in Python.DescriptionWorld first popular Chatbot for daily conversation (Service launched in 2002). A unique daily conversation with diversity, fun and vitality. Service provided with 130 million sets of daily small talks in 81 languages compiled through more than 20 million panels. Service in 81 languages. More than 350 million cumulative users worldwide. (Based on June-2018), Records of more than 200 million times of responses made per day.REQUIREMENTSPYTHON >=3.9.X+REQUESTSInstallationpip3installsimiproOrpipinstall-ihttps://test.pypi.org/simple/simiproSimiTalkImport ModulefromsimiproimportsimiTalkUse SimSimi talk functionfromsimiproimportsimiTalkreq=simiTalk("hi","en")print(req)Response{"status":"true","time":"06:55:47 PM","type":"text","lc":"en","ans":"Hello back","author":"𝙷𝙰𝚇𝙾𝚁 𝚇𝙽𝚇","owner":"https://t.me/haxor_xnx","channel":"https://t.me/Toxinum"}Realtime Example for SimSimi talkfromsimiproimportsimiTalkmsg="hi"lang="en"req=simiTalk(msg,lang)print(req["ans"])ResponseHellothereSimiTeachImport ModulefromsimiproimportsimiTeachUse SimSimi teach functionfromsimiproimportsimiTeachreq=simiTeach("hi","hello, "en", "YOUR_SECRET_KEY")print(req)Response{"status":"true","time":"06:55:47 PM","type":"text","lc":"en","ask":"hello world","ans":"Hello back","author":"𝙷𝙰𝚇𝙾𝚁 𝚇𝙽𝚇","owner":"https://t.me/haxor_xnx","channel":"https://t.me/Toxinum"}Realtime Example for SimSimi teachfromsimiproimportsimiTeachmsgAsk="hi"msgAns="hello"lang="en"secretKey="YOUR_SECRET_KEY"req=simiTeach(msgAsk,msgAns,lang,secretKey)print(req["ask"])print(req["ans"])Responsehi
helloLicenseMIT LicenseCopyright (c) 2023 Mohammad AlaminPermission 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.Build withSimsimiofficial api.Open Source Project.Contact With Developer
Package: simisimi
CID SimilarityLabEl primer paquete de NLP desarrollador por elCentro de Inteligencia Digital. La clase implementada les permitira interactuar con los modelos de lenguaje generados a partir de dos grande corpus.The GuardianyThe New York Timesfueron las grandes fuentes informaciÃ³n para llevar a acabo este proyecto.Pueden encontrar toda la documentaciÃ³naquÃ­.
Package: simlearn
The PyStarPyStar is a user-friendly application for anyone who would like to learn simulations. It shows relevant quantities for each of modeling system.
Explore and enjoy.RequirementsThis application usesESPResSo packageas a backend. Thus, it is essential to get compiled your package. The rest can be installed viapip3 install -r requirements.txtIntroductionPyStar is an application to learn about simulations. The application can provide you variety of use cases: starting from demonstration concents of model/methods to new students and ending by comprehensive university course about modeling.The application is written in user-friendly way. You can pull slicers, toggle checkboxes drag and drop particles to tune your own simulation setup.QuickStartimportespressomdfromsimlearnimportPyStarPyStar.run()Future Content of the SoftwareIntroduce new ensembles: NpT, REIntroduce new systems: chains, gels, combs.....The teamPyStar is currently maintained byAlexander D. Kazakovwith contributions coming from talented individuals in various forms and means. A non-exhaustive but growing list needs to mention: Tabea G. Langen, Pascal Hebbeker, Peter Kosovan, Filip Uhlík, Lucie Nová.
Package: simlin
# SIMLIN - Simple Image Manipulator for LinuxVersion 0.0.6![Simlin Demo](https://www.linuxnorth.org/simlin/output.gif)This project is simply for learning.  Do not use it for anything important as it could have unintended consequences.SIMLIN is a Simple Image Manipulator for Linux.  This utility does only one thing at the moment.  It takes images in the current working folder and resizes them in the ‘resized’ subfolder.The end goal is to have a fully functional command line utility that will do various scriptable batch image manipulations.## UsageResize can be completed in batch or interactive modebatch mode
simlin -r <int> -q <int>Where -r is the new horizontal size and -q is the image quality (0-95)interactive mode. go to directory and typesimlin## Installsudo pip3 install simlin.## RequiresPython3Pillow (latest version)
Package: simmed
TD SDK Core Python基于 Python3 核心框架，集成 flask，nacos，zip更新依赖pipreqs ./ --encoding utf-8  --force安装依赖pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/  --trusted-host  mirrors.aliyun.com制作包# 构建
python setup.py build

# 直接源码安装
python setup.py install

# 打包dist, zip或tar.gz
python setup.py sdist

# 打包whl
python setup.py bdist_wheel上传到 PyPipython3 -m twine upload dist/*

# windows下使用以下命令上传
twine upload dist/*上传包https://packages.simmed.cn/#browse/upload:pypi安装包pip install simmed

# 环境依赖,注意python版本
yum install python3-devel -y

# 加速
pip install xxxx -i https://pypi.tuna.tsinghua.edu.cn/simple引用包import simmed.config as config
from simmed.simmed_core import init_flask_app, set_zipkin_tags, get_config, rpc_rest_service, log
Package: simmer
SImMERRepository for developing theSImMERimage reduction pipeline. If you'd like to help out, take a look at ourways to contribute. If you use this package in your research, please citeour paper.InstallationTo install with conda (the recommended method), runconda config --add channels conda-forge
conda install simmerTo install with pip, runpip install simmerOr, to install from source, runpython3 -m pip install -U pip
python3 -m pip install -U setuptools setuptools_scm pep517
git clone https://github.com/arjunsavel/SImMER.git


cd simmer
python3 -m pip install -e .DocumentationTo get started, read the docs atour readthedocs site.