Saravanan666/pypi-org huggingface dataset:
Package: titiler.image
TiTiler Image.Source Code:https://github.com/developmentseed/titiler-imageTiTiler.imageis atitilerextension to work with non-geo images.InstallationTo install from PyPI and run:# Make sure to have pip up to datepython-mpipinstall-Upip

python-mpipinstalltitiler.imageTo install from sources and run for development:python-mpipinstall-e.Launchpython-mpipinstalluvicorn
python-muvicorntitiler.image.main:app--reloadUsing Dockergitclonehttps://github.com/developmentseed/titiler-image.gitcdtitiler-pgstac
docker-composeup--buildtilerIt runstitiler.imageusing Gunicorn web server. To run Uvicorn based version:docker-composeup--buildtiler-uvicornFactoriestitiler-imageprovide multiple endpoint Factories (seehttps://developmentseed.org/titiler/advanced/tiler_factories/)MetadataFactoryEndpoints/info?url={...}/metadata?url={...}fromfastapiimportFastAPIfromtitiler.image.factoryimportMetadataFactoryapp=FastAPI()meta=MetadataFactory()app.include_router(meta.router)IIIFFactorySpecification:https://iiif.io/api/image/3.0/Endpoints/{identifier}/info.json: IIIF Image Information Request/{identifier}/{region}/{size}/{rotation}/{quality}.{format}: IIIF Image Request/{identifier}: Redirect do the Image Information Request endpoint or return a simple IIIF viewer (based on headersAcceptvalue)fromfastapiimportFastAPIfromtitiler.image.factoryimportIIIFFactoryapp=FastAPI()iiif=IIIFFactory()app.include_router(iiif.router)LocalTilerFactoryEndpoints/tilejson.json?url={...}: TileJSON document/tiles/{z}/{x}/{y}[@{scale}x.{format}]?url={...}: Tiles endpoint/viewer?url={...}: Simple local tiles viewerfromfastapiimportFastAPIfromtitiler.image.factoryimportLocalTilerFactoryapp=FastAPI()local_tiles=LocalTilerFactory()app.include_router(local_tiles.router)GeoTilerFactoryThis is a lightweight version oftitiler.core.factory.TilerFactory.Endpoints[/TileMatrixSetId]/tilejson.json?url={...}: TileJSON document/tiles[/TileMatrixSetId]/{z}/{x}/{y}[@{scale}x.{format}]?url={...}: Tiles endpoint[/{TileMatrixSetId}]/map?url={...}: Simple dataset viewerfromfastapiimportFastAPIfromtitiler.image.factoryimportGeoTilerFactoryapp=FastAPI()geo=GeoTilerFactory()app.include_router(geo.router)All togetherapp=FastAPI()meta=MetadataFactory()app.include_router(meta.router,tags=["Metadata"])iiif=IIIFFactory(router_prefix="/iiif")app.include_router(iiif.router,tags=["IIIF"],prefix="/iiif")image_tiles=LocalTilerFactory(router_prefix="/image")app.include_router(image_tiles.router,tags=["Local Tiles"],prefix="/image")geo_tiles=GeoTilerFactory(reader=GCPSReader,reader_dependency=GCPSParams,router_prefix="/geo")app.include_router(geo_tiles.router,tags=["Geo Tiles"],prefix="/geo")Contribution & DevelopmentSeeCONTRIBUTING.mdLicenseSeeLICENSEAuthorsSeecontributorsfor a listing of individual contributors.ChangesSeeCHANGES.md.
Package: titiler.mosaic
titiler.mosaicAdds support for MosaicJSON in Titiler.Installation$python-mpipinstall-Upip# From Pypi$python-mpipinstalltitiler.mosaic# Or from sources$gitclonehttps://github.com/developmentseed/titiler.git
$cdtitiler&&python-mpipinstall-esrc/titiler/core-esrc/titiler/mosaicHow TofromfastapiimportFastAPIfromtitiler.mosaic.factoryimportMosaicTilerFactory# Create a FastAPI applicationapp=FastAPI(description="A lightweight Cloud Optimized GeoTIFF tile server",)# Create a set of MosaicJSON endpointsmosaic=MosaicTilerFactory()# Register the Mosaic endpoints to the applicationapp.include_router(mosaic.router,tags=["MosaicJSON"])Seetitiler.applicationfor a full example.Package structuretitiler/
 └── mosaic/
    ├── tests/                   - Tests suite
    └── titiler/mosaic/            - `mosaic` namespace package
        ├── models/
        |   └── responses.py     - mosaic response models
        ├── errors.py            - cogeo-mosaic known errors
        └── factory.py           - Mosaic endpoints factory
Package: titiler.pgstac
Connect PgSTAC and TiTiler.Documentation:https://stac-utils.github.io/titiler-pgstac/Source Code:https://github.com/stac-utils/titiler-pgstacTiTiler-PgSTACis aTiTilerextension that connects to aPgSTACdatabase to create dynamicmosaicsbased onsearch queries.InstallationTo install from PyPI and run:# Make sure to have pip up to date$python-mpipinstall-Upip# Install `psycopg` or `psycopg["binary"]` or `psycopg["c"]`$python-mpipinstallpsycopg["binary"]$python-mpipinstalltitiler.pgstacTo install from sources and run for development:$ git clone https://github.com/stac-utils/titiler-pgstac.git
$ cd titiler-pgstac
$ python -m pip install -e .PgSTACversiontitiler.pgstacdepends onpgstac >=0.3.4(https://github.com/stac-utils/pgstac/blob/main/CHANGELOG.md#v034).psycopgrequirementtitiler.pgstacdepends on thepsycopglibrary. Because there are three ways of installing this package (psycopgor ,psycopg["c"],psycopg["binary"]), the user must install this separately fromtitiler.pgstac.psycopg: no wheel, pure python implementation. It requires thelibpqinstalled in the system.psycopg["binary"]: binary wheel distribution (shipped with libpq) of thepsycopgpackage and is simpler for development. It requires development packages installed on the client machine.psycopg["c"]: a C (faster) implementation of the libpq wrapper. It requires thelibpqinstalled in the system.psycopg[c]orpsycopgare generally recommended for production use.Intitiler.pgstacsetup.py, we have added three options to let users choose which psycopg install to use:pip install titiler.pgstac["psycopg"]: pure pythonpip install titiler.pgstac["psycopg-c"]: use the C wrapper (requires development packages installed on the client machine)pip install titiler.pgstac["psycopg-binary"]: binary wheelsLaunchYou'll need to havePOSTGRES_USER,POSTGRES_PASS,POSTGRES_DBNAME,POSTGRES_HOST,POSTGRES_PORTvariables set in your environment pointing to your Postgres database where pgstac has been installed.export POSTGRES_USER=username
export POSTGRES_PASS=password
export POSTGRES_DBNAME=postgis
export POSTGRES_HOST=database
export POSTGRES_PORT=5432$ pip install uvicorn
$ uvicorn titiler.pgstac.main:app --reloadUsing Docker$ git clone https://github.com/stac-utils/titiler-pgstac.git
$ cd titiler-pgstac
$ docker-compose up --build tilerIt runstitiler.pgstacusing Gunicorn web server. To run Uvicorn based version:$ docker-compose up --build tiler-uvicornContribution & DevelopmentSeeCONTRIBUTING.mdLicenseSeeLICENSEAuthorsSeecontributorsfor a listing of individual contributors.ChangesSeeCHANGES.md.
Package: titivillus
Titivillustitivillusis a Python library and related command-line tools for simulating
stemmatological networks and related data (characters, states, edge length etc.). It
is intended for benchmarking quantitative methods of textual evolution, also providing
dummy tree and networks for their development and debugging.The library is named afterTitivillus, a
demon commonly referenced to in Medieval times and said to work on behalf of Belphegor,
Lucifer, or Satan to introduce errors
into the work of scribes. It can be compared to the twentieth-century folkloric
mischievous creature that causes mechanical failures, the gremlin.How doestitivilluswork?The library offers a number of abstractions suited for the study of textual evolution,
in particular without forcing a purely arboreal evolution. Eachcodexcarries a
number of independentcharacterst, each with its own history.Where applicable, the random generation follows that of another package released by
the author for the simulation of phylogenetic data,ngesh.InstallationIn any standard Python environment,titivilluscan be installed with$pipinstalltitivillusThepipinstallation will automatically fetch dependencies such asnumpyandnetworkx, if necessary. It is highly recommendend that the library is installed in
its own virtual environment.How to useFor most usages, the creation of a random stemma can be easily performed from Python with:importtitivillusstemma=titivillus.random_stemma()Among the various parameters, it is possible to pass a pseudo-random number generator
seed that guarantees reproducibility across different calls.stemma2=titivillus.random_stemma(seed="uppsala")The contents of the stemma can be inspected following the available tests. A graphical
version, usingnetworkx, can be obtained with:importmatplotlib.pyplotaspltimportnetworkxasnxgraph=stemma2.as_graph()nx.draw(graph)plt.show()No stand-alone command-line tool has been released yet.ChangelogVersion 0.0.1:First public release, aligned with experiments for the Apophthegmata PatrumCommunity guidelinesWhile the author can be contacted directly for support, it is recommended that third
parties use GitHub standard features, such as issues and pull requests, to contribute,
report problems, or seek support.Contributing guidelines, including a code of conduct, can be found in theCONTRIBUTING.mdfile.Author and citationThe library is developed by Tiago Tresoldi (tiago.tresoldi@lingfil.uu.se).If you usetitivillus, please cite it as:Tresoldi, Tiago (2021). Titivillus, a tool for simulating random stemmatological
networks. Version 0.0.1. Uppsala. Available at:https://github.com/tresoldi/titivillusIn BibTeX:@misc{Tresoldi2021titivillus,
  author = {Tresoldi, Tiago},
  title = {Titivillus, a tool for simulating random stemmatological networks},
  howpublished = {\url{https://github.com/tresoldi/titivillus}},
  address = {Uppsala},
  year = {2021},
}
Package: title2bib
Descriptiontitle2bib is a module ofbibcureandscihub2pdfInstall$ sudo pip install title2bibor if you want the full version$ sudo pip install bibcureFeatures and how to useGiven a title…$ title2bib An useful paperGiven a file of titles or ids$ title2bib -i  titles.txt -o refs.bibsearch papers related and return the bibsbibcure$ bibcure -i input.bib -o output.bibGiven a bib file…check sure the Arxiv items have been published, then update themcomplete all fields(url, journal, etc) of all bib items using DOI
numberfind and create DOI number associated with each bib item which has
not DOI fieldabbreviate jorunals names$ doitobib 10.1038/s41524-017-0032-0Given a DOI number…get bib item given a doi$ arxivcheck 1601.02785Given a arxiv id…given an arixiv id, check if has been published, and then returns the
updated bib
Package: titlebarctk
pip install titlebarctkCreate a custom title bar for a windows app developed with custom tkinter.--------------------------------------------------import titlebarctk as tbimport customtkinter as ctkdef save_like_this():print("Saving file")def change_text():window_frame.titlebar_text_variable.set("Goodbye, World!")root = ctk.CTk()window_frame = tb.TitleBar(root,height = 20,non_maximised_width=1600,non_maximised_height=900,save_function=save_like_this,title="Eat my dolphin shorts",font=("helvetica", 20),fg_color=["#ffffff", "#000000"],start_fullscreen=False,icon_path="path_to_icon.ico",text_variable="Hello, World!")window_frame.pack(side="top", fill="x")root.after(2000, change_text)root.mainloop()--------------------------------------------------Windows 10Python 3Install requires:- pywin32 306, url: https://pypi.org/project/pywin32/- screeninfo 0.8.1, url: https://pypi.org/project/screeninfo/- PIL 10.2.0, url: https://pypi.org/project/pillow/- customtkinter 0.3, url: https://pypi.org/project/customtkinter/0.3/, url: https://customtkinter.tomschimansky.com/--------------------------------------------------GitHub url: https://github.com/DevDolphin7/TitleBarPyPI url: https://pypi.org/project/titlebarctk/Get in contact: DevDolphin7@outlook.com
Package: titlecase
This filter changes a given text to Title Caps, and attempts to be clever
about SMALL words like a/an/the in the input.
The list of “SMALL words” which are not capped comes from the New York
Times Manual of Style, plus some others like ‘vs’ and ‘v’.The filter employs some heuristics to guess abbreviations that don’t need conversion.OriginalConversionthis is a testThis Is a TestTHIS IS A TESTThis Is a Testthis is a TESTThis Is a TESTMore examples and expected behavior for corner cases are available in thepackage test suite.This library is a resurrection ofStuart Colville’s
titlecase.py,
which was in turn a port ofJohn Gruber’s
titlecase.pl.Issues, updates, pull requests, etc should be directedto github.InstallationThe easiest method is to simply use pip:(sudo) pip install titlecaseUsageTitlecase provides only one function, simply:>>>fromtitlecaseimporttitlecase>>>titlecase('a thing')'A Thing'A callback function may also be supplied, which will be called for every word:>>>defabbreviations(word,**kwargs):...ifword.upper()in('TCP','UDP'):...returnword.upper()...>>>titlecase.titlecase('a simple tcp and udp wrapper',callback=abbreviations)'A Simple TCP and UDP Wrapper'The callback function is supplied with anall_capskeyword argument, indicating
whether the entire line of text was entirely capitalized. ReturningNonefrom
the callback function will allow titlecase to process the word as normal.Command Line UsageTitlecase also provides a command line utilitytitlecase:$ titlecase make me a title
Make Me a Title
$ echo "Can pipe and/or whatever else" | titlecase
Can Pipe and/or Whatever Else
# Or read/write files:
$ titlecase -f infile -o outfileIn addition, commonly used acronyms can be kept in a local file
at~/.titlecase.txt. This file contains one acronym per line.
The acronym will be maintained in the title as it is provided.
Once there is e.g. one line sayingTCP, then it will be automatically
used when used from the command line.$ titlecase I LOVE TCP
I Love TCPLimitationsThis is a best-effort library that uses regexes to try to do intelligent
things, but will have limitations. For example, it does not have the contextual
awareness to distinguish acronyms from words: us (we) versus US (United States).The regexes and titlecasing rules were written for American English. While
there is basic support for Unicode characters, such that something like
“El Niño” will work, it is likely that accents or non-English phrases will
not be handled correctly.If anyone has concrete solutions to improve these or other shortcomings of the
library, pull requests are very welcome!
Package: title-checker
Youtube Links Title Checker 🔎A Python script for checking the titles of each links in a text file and logging it in another file :)it may not be useful for you but for me it was a good help💡🔹FeaturesUsingSeleniumfor scraping the titles of the linksUsingtyperandquestionaryfor CLIYou can choose betweenheadlessandnormalmode for browser behaviourCreates a new file with the date for name to log the resultsYou can easily give it any file that contains several links that are unknown to you🔹Installationpipinstall--upgradetitle_checker🔹UsageCLI:title_checkerstartIn your python script:fromtitle_checker.title_checkerimportcheckerchecker('PATH_TO_YOUR_URL_LIST')Any contribution is welcomed! 🤞
Package: title-grabber-cristianrasch
title_grabberUsage instructionsJust feed it 1 or more files containing URLs (1 per line)python -m title_grabber /abs/path/2/urls1.csv rel/path/2/urls2.csvOptionally, change the output file:python -m title_grabber -o output.csv /abs/path/2/urls1.csv rel/path/2/urls2.csvSee all available config options:python -m title_grabber -husage: title_grabber [-h] [-o OUT_FILE] [--connect-timeout TIMEOUT]
                     [--read-timeout TIMEOUT] [-r RETRIES] [-t THREADS] [-d]
                     [FILES [FILES ...]]

positional arguments:
  FILES                 1 or more CSV files containing URLs (1 per line)

optional arguments:
  -h, --help            show this help message and exit
  -o OUT_FILE, --output OUT_FILE
                        Output file (defaults to out.csv)
  --connect-timeout TIMEOUT
                        HTTP connect timeout. Defaults to the value of the
                        CONNECT_TIMEOUT env var or 10
  --read-timeout TIMEOUT
                        HTTP read timeout. Defaults to the value of the
                        READ_TIMEOUT env var or 15
  --max-redirects REDIRECTS
                        Max. # of HTTP redirects to follow. Defaults to the
                        value of the MAX_REDIRECTS env var or 5
  -r RETRIES, --max-retries RETRIES
                        Max. # of times to retry failed HTTP reqs. Defaults to
                        the value of the MAX_RETRIES env var or 3
  -t THREADS, --max-threads THREADS
                        Max. # of threads to use. Defaults to the value of the
                        MAX_THREADS env var or the # of logical processors in
                        the system (8)
  -d, --debug           Log to STDOUT instead of to a file in the CWD.
                        Defaults to the value of the DEBUG env var or False
  -V, --version         Print program version and exitdev setup instructionsClone the projectgit clone git@github.com:cristianrasch/title_grabber.gitCreate a new virtual environment for itcd title_grabber && python3 -m venv venvInstall its dependenciespip install -r requirements.txtRun the test suite to make sure everything is set up OKpython -m unittest discover -v -s title_grabber/tests/
Package: title-graph
### TitleGraph#### Install`pip install title-graph`#### Build```python setup.py sdist``````twine upload dist/*```#### Usage```pythonfrom title_graph import TitleGraphtg = TitleGraph()# Find likely future job titles>>> tg.query_forward('graduate student', topn=3)('software engineering intern', 0.8774160146713257), ('software engineer intern', 0.8586706519126892), ('software development engineering intern', 0.8407694101333618)]# Find likely previous job titlestg.query_backwards('principal engineer', topn=3)[('engineer', 0.8578487634658813), ('dev engineer', 0.7771068811416626), ('sr engineer', 0.7421303987503052)]# Semantic search job titlestg.query_similar_semantic('front-end ninja', topn=3)[('frontend developer', 0.7447044849395752), ('frontend engineer', 0.6994348764419556), ('front end engineer', 0.6821744441986084)]```
Package: titleize
TitleizeTitleize is a Python module to convert text to Title Case. Title Case is the text format that is commonly used in titles. Example:There Is a Bird Over There. He Is a RobinIt may not look like much but there are specific rules to follow to make This format appealing to the human eye, and I've compressed it down into a Python module.Usage:Titleize is extremely simple to use. Just pass your string to the function and its done! Example:importtitleizeprint(titleize.titleize("i like to look at birds. Birds are really cool animals."))That would outputI Like to Look At Birds. Birds Are Really Cool Animals.Pretty cool, right? What are you waiting for? Install it now withpip install titleize
Package: titleweektrend
titleWeekTrendThis was originally part of a YouTube video views prediction model. You can use it to get the sum of Google Trends for each word in a news or video title over the past week.The input string (the title) will be fixed contractions first, then removed punctuation, converted into lowercase, and finally will be processed by a lemmatiazation.Next, the input title will be split into individual words, and Google Trends for each word in the past week will be crawled and finally a sum will be obtained.
Package: titrate
#asymp*T*oticl*I*kelihood-basedT*ests*forda*R*km*A*t*T*ers*E*arch[<img src=”https://anaconda.org/conda-forge/titrate/badges/version.svg”>](https://anaconda.org/conda-forge/titrate) <img src=”https://anaconda.org/conda-forge/titrate/badges/platforms.svg”> [<img src=”https://badge.fury.io/py/titrate.svg”>](https://pypi.org/project/titrate/)This package is based on the paper [Asymptotic formulae for likelihood-based tests of new physics](https://arxiv.org/abs/1007.1727).(your daily dose of [meme](https://i.imgflip.com/7v739g.jpg))## Why does this package exist?Well, I’m currently doing my PhD on dark matter search with Imaging Air Cherenkov Telescopes (IACTs) and during my research, I looked into a good share of DM papers…
Turns out none of the ones I’ve read really explained how they are calculating their upper limits and most of them lack a good explanation for upper limit vs dark matter mass plots.So to understand what’s going on I went back in time…on arxiv. I thought, for sure the CERN people will know this stuff since calculating upper limits is daily business for them.
I quickly found the paper mentioned above and it only took me three months to understand it.(╯°□°)╯︵ ┻━┻What have I learned?
1. Statistical tests are difficult to understand
2. The decentralized $chi^2$-distribution is the final boss
3.A lot of researchers use a test statistic that is physically not meaningfull (signal strength can be smaller than zero)4.A lot of researchers calculate the median upper limits and bands for the expected signal by using a bunch of toy MCs, which is not necessarily needed if asymptotics are valid## What does this package offer?Adding Asimov datasets to gammapy :heavy_check_mark:Adding test statistics to gammapy :heavy_check_mark:Validation of test statistics :heavy_check_mark:Calculation of ULs :heavy_check_mark:Calculation of median ULs and bands with asymptotic formulae and asimov datasets (faster than toy MCs) :heavy_check_mark:## Disclaimer
This is not a finished version yet and can contain drastic changes
Package: tituemg
tituemg: Librería de Procesamiento de Señales de EMG.JustificacionEsta librería se crea con el propósito de facilitar y agilizar el análisis de señales EMG, proporcionando herramientas en español para investigadores y Estudiantes en el campo.objetivo.Nuestra librería tiene como principal propósito simplificar el procesamiento de señales EMG, brindando herramientas en español. Queremos facilitar el análisis y la comprensión de estas señales, haciendo que la información sea accesible para una audiencia más amplia.instalación de paquete:# PyPIpipinstalltituemg
Package: titulky
TitulkyTiny Python SubRip editor. Display infos, shift and re-fit timestamps.InstallationUse the package manager pip to install titulky.pip3installtitulkyUsageDisplay informations for some.srtfile.python3titulky.pytest.srtShift subtitles by some amount.python3titulky.pytest.srtshift"12.34"Refit subtitles to some interval.python3titulky.pytest.srtshift"1:23.456""2:34:56"By default titulky writes to stdout. You can write the output to a file withpython3titulky.pytest.srtshift5.0--outfileout.srt
Package: titulosuagrm
Consulta Titulos - UAGRMEl sitio oficial de la Universidad Autonoma Gabriel Rene Moreno permite realizar la consulta de titulos por carnet de identidad y por numero de titulo.Sitio Web:https://www.uagrm.edu.bo/udigital/titulosEste es un proyecto con fines academicos y de investigacion Web Scraping.Requisitospipinstallrequestwebdriver-managerseleniumpandas
pipinstalltitulosuagrmEjemplofromtitulosuagrmimportEndpointClientPROCEDENCIAS={"santa_cruz":"SCZ","la_paz":"LPZ","beni":"BEN","pando":"PAN","cochabamba":"CBA","chuquisaca":"CHS","tarija":"TJA","oruro":"ORU","potosi":"POT","extranjero":"EXT"}cliente=EndpointClient()cedula=""#Ingresar un carnet de identidad de un universitario tituladoprocedencia=PROCEDENCIAS["santa_cruz"]resultado=cliente.consultar_endpoint(cedula,procedencia)ifresultadoisnotNone:# Procesar el resultado de acuerdo a tus necesidades# ...print(resultado)