Saravanan666/pypi-org huggingface dataset:
Package: isyntax2raw
iSyntax ConverterPython tool that uses Philips' SDK to write slides in an intermediary raw format.RequirementsPython 3.6+Philips iSyntax SDK (https://www.openpathology.philips.com)The iSyntax SDKmustbe downloaded separately from Philips and the
relevant license agreement agreed to before any conversion can take place.As of version 0.4.0, which has a Python 3.6+ requirement, the supported
iSyntax SDK versions and environments are as follows:iSyntax SDK 1.2.1 (CentOS 7, Ubuntu 18.04, Windows 10 64-bit)iSyntax SDK 2.0 (CentOS 8, Ubuntu 18.04, Windows 10 64-bit)UsageBasic usage is:isyntax2raw write_tiles /path/to/input.isyntax /path/to/directory.zarrPlease seeisyntax2raw write_tiles --helpfor detailed information.Output tile width and height can optionally be specified; default values are
detailed in--help.A directory structure containing the pyramid tiles at all resolutions and
macro/label images will be created.  The default format is Zarr compliant withhttps://ngff.openmicroscopy.org/0.4.
Additional metadata is written to a JSON file.  Be mindful of available disk space, as
larger .isyntax files can result in >20 GB of tiles.Use of the Zarr file type will result in losslessly compressed output.  This
is the only format currently supported by the downstreamraw2ometiff(as of
version 0.3.0).Background colorAny missing tiles are filled with 0 by default, which displays as black.
The fill value can be changed using the--fill_coloroption, which accepts
a single integer between 0 and 255 inclusive.  Setting--fill_color=255will cause any missing tiles to display as white.PerformanceThis package ishighlysensitive to underlying hardware as well as
the following configuration options:--max_workers--tile_width--tile_height--batch_sizeOn systems with significant I/O bandwidth, particularly SATA or
NVMe based storage, we have found sharply diminishing returns with worker
counts > 4.  There are significant performance gains to be had utilizing
larger tile sizes but be mindful of the consequences on the downstream
workflow.  You may find increasing the batch size on systems with very
high single core performance to give modest performance gains.In general, expect to need to tune the above settings and measure
relative performance.LicenseThe iSyntax converter is distributed under the terms of the BSD license.
Please seeLICENSE.txtfor further details.Areas to improveCurrently assumes brightfield (RGB, 8 bits per channel) without really
checking the metadata.  Probably should check bit depths etc.
Package: isypy
IsypySimple Monte Carlo Solver for the Ising model in 1, 2 or three dimensions.RequirementsTested on python3.6.2 (will not work on python2)Installation$ cd isypy # (go to directory with the setup.py file)$ pip install -e .Running tests and examples$ cd isypy && python -m unittest discover$ cd isypy/isypy/tests && python -m isypy params_ising.json
Package: it
InspectorTigerIT, Inspector Tiger, is a modern python code review tool / framework. It comes
with bunch of pre-defined handlers which warns you about improvements and possible
bugs. Beside these handlers, you can write your own or use community ones.ALPHABET="ABCDEFGHIJKLMNOPQRSTUVWXYZ"classFoo(SomeObjects):defbar(self,x=[],y:Union[int,None]=None):x.append(1)for_inrange(3):try:super(bla,bla).foo_baz()exceptException:print("An exception")exceptAttributeError:print("An attribute error")finally:continuemy_iterable=list(token[0]fortokenintokens)forainmy_iterable:yieldamy_other_iterable=list(map(itemgetter(0),tokens))forainrange(len(my_other_iterable)):print(a,"=>",my_other_iterable[a])Think about this piece of code, you see some bugs or improvements, don't you?
But what if there were hundreds of lines code in this form inside your big codebase.
How would you find these patterns? By writing regex queries? LOL, of course not.$itexample.py[Inspector Tiger] INFO - InspectorTiger inspected 🔎 and found these problems;[Inspector Tiger] INFO -[upgrade]- example.py:1:0     => ALPHABET_CONSTANT- example.py:5:27    => OPTIONAL- example.py:9:16    => SUPER_ARGS- example.py:17:22   => USE_COMPREHENSION- example.py:18:8    => YIELD_FROM- example.py:21:28   => MAP_USE_COMPREHENSION- example.py:22:8    => BUILTIN_ENUMERATE[general]- example.py:5:4     => DEFAULT_MUTABLE_ARG- example.py:8:12    => CONTROL_FLOW_INSIDE_FINALLY- example.py:8:12    => UNREACHABLE_EXCEPTTutorialsInspecting python with Inspector TigerAPIAlso Inspector Tiger comes with a builtin server (it.server) which offers a
basic REST API. If you want to try it without downloading, you can use our heroku instance.(.venv)[  6:02PM  ]  [  isidentical@x200  ]$curl-shttps://inspector.herokuapp.com-d'{"source": "Union[MyType, None]"}'|jq{"status": "success","result": {"upgradeable": [{"code": "OPTIONAL","column": 0,"lineno": 1,"filename": "<unknown>"}]}}
Package: ita
material for any purpose, even commercially.
The matterial is provided by Akimasa Morihata “AS IS” and any express
or implied warranties are disclaimed. In no event shall Akimasa
Morihata be liable for any damages and on any theory of liability
arising in any way out of the use of this software, even if advised of
the possibility of such damage.Akimasa Morihata, 2018-2023Description: This project provides a resource for a lecture, “introduction toalgorithms”, in Junior Division of the College of Arts and Sciences,
the University of Tokyo.これは東京大学教養学部で開講されている総合科目「アルゴリズム入門」で使
用するサポートパッケージです。不明な点がある場合やバグを発見した場合は
森畑（morihata@graco.c.u-tokyo.ac.jp）までご連絡ください。Akimasa Morihata, the Univerisy of Tokyo, 2018-2023.Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Package: itacate
Itacatl: Provisión de comida que se lleva para un viaje o un paseo, o que ha sobrado de una fiesta y se da a algunos invitados.El módulo de configuración de flask para el resto del mundo, por que me gusta cómo funciona. Escribe tus configuraciones en archivos python e impórtalas según el entorno, sobreescribiéndolas en cascada.Theconfigmodule fromflaskfor the rest of the world, just because I like how it works. Write your config files in normal python files and import them depending on environment variables. Overwrite them in cascade.Cómo usar / Usage# settings.pyDEBUG=FalseBE_MAGIC=TrueSECREY_KEY=''FIZ_BOZ=15STORAGE_DIR='media'DB_NAME='mysql'# settings_develop.pyDEBUG=True#settings.json{"FIZ_BOZ":10}# module.pyfromitacateimportConfigimportosclassMyObject:STORAGE_DIR='/var/www/media'DB_NAME='postgres'config=Config(os.path.dirname(os.path.realpath(__file__)))config.from_pyfile('settings.py')config.from_envvar('MY_APP_SETTINGS',silent=False)# export MY_APP_SETTINGS=/path/to/settings_develop.pyconfig.from_mapping({'SECREY_KEY':'lalala',})config.from_json('settings.json')config.from_object(MyObject)config.from_object(__name__)# from this same module!assertconfig.BE_MAGIC==Trueassertconfig.DEBUG==Trueassertconfig.FIZ_BOZ==10assertconfig.SECREY_KEY=='lalala'assertconfig.STORAGE_DIR=='/var/www/media'assertconfig.DB_NAME=='postgres'
Package: itachip2ir
itachip2irA small module for interacting with the Global Caché iTach WF2IR or IP2IRHow To Usefromitachip2irimportVirtualDevice,iTachcommands={"toggle_power":"sendir,1:3,1,40192,1,1,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,49,23,49,529,96,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,49,23,49,528,96,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,49,23,49,553,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,49,23,49,554,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,49,23,49,554,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,49,23,49,554,97,23,49,23,25,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,25,23,49,23,49,23,25,23,49,23,25,23,25,23,25,23,49,23,49,23,49,4000"}itach=iTach(ipaddress="192.168.1.111",port=4998)blueray=itach.add(VirtualDevice(name="blueray",commands=commands))if__name__=="__main__":print(blueray.toggle_power())Check theexamples/folder for moreThe source for this project is available here.
Package: ita-converter
ita-converterita-converter is a lightweight and fast Python library that converts an image to ASCII art. It allows users to resize images, convert them to grayscale, and customize the symbols used to create the ASCII art.InstallationYou can install ita-converter using pip:pip install ita-converterUsageTo use ita-converter, simply import theget_ascii_art()function and pass in the path to the image file you want to convert. By default, the function will use a set of ASCII characters to create the art, but you can also pass in your own symbol set.fromita_converterimportget_ascii_artascii_art=get_ascii_art("path/to/image.png",symbol_set=["@","#","*"," "])print(ascii_art)By default, the function will use color in the output. If you want a black and white output, setcolortoFalse.ascii_art=get_ascii_art("path/to/image.png",color=False)print(ascii_art)You can also resize the image and specify the width and height of the output. If you only specify the width, the height will be adjusted automatically to maintain the aspect ratio.ascii_art=get_ascii_art("path/to/image.png",width=50,height=50)print(ascii_art)You can specify thecolour_type. By default it is ANSI, but you can also set it to HTML.ascii_art=get_ascii_art("path/to/image.png",colour_type="html")print(ascii_art)orascii_art=get_ascii_art("path/to/image.png",colour_type="ansi")ContributingContributions are welcome! If you have an idea for a new feature or want to report a bug, please open an issue. If you want to contribute code, please fork therepository, make your changes, and submit a pull request.Licenseita-converter is licensed under theMIT License.
Package: itacovidlib
# Italian COVID Library (itacovidlib)
![Italian COVID Library logo](https://github.com/FedericoCorchia/Italian_COVID_Library/blob/main/logo.png)A Python library for COVID-19 infections and vaccinations in Italy data retrieval and analysis.## Installing Italian COVID Library
You can install this library directly from PyPi:pip install itacovidlibYou can also just clone this repository and use it as a normal Python package:git clone https://github.com/FedericoCorchia/itacovidlib## Requirements
Functioning of Italian COVID Library requires the following:
- Python (3.8.1 or higher)
- numpy
- pandas (1.2.0 or higher)
- geopandas (0.7.0 or higher)
- requests
- epyestim
- setuptools## Usage
Instructions on using Italian COVID Library, also including practical examples:[Italian COVID Library Tutorial](https://github.com/FedericoCorchia/Italian_COVID_Library/blob/main/Tutorial.ipynb)## Data Sources
For data on COVID-19 cases in Italy: [pcm-dpc/COVID-19](https://github.com/pcm-dpc/COVID-19) - “COVID-19 Italia - Monitoraggio situazione” by Dipartimento della Protezione CivileFor data on vaccinations in Italy: [italia/covid19-opendata-vaccini](https://github.com/italia/covid19-opendata-vaccini) - “Open Data su consegna e somministrazione dei vaccini anti COVID-19 in Italia - Commissario straordinario per l’emergenza Covid-19”, by Commissario straordinario per l’emergenza Covid-19 - Presidenza del Consiglio dei MinistriBoth are released underCreative Commons - Attribution 4.0 International (CC BY 4.0)[Full license](https://creativecommons.org/licenses/by/4.0/legalcode) - [Summary](https://creativecommons.org/licenses/by/4.0/deed.en)For .geojson files with Italian regions and provinces: [datajournalism-it/regioni-con-trento-bolzano.geojson](https://gist.github.com/datajournalism-it/f1abb68e718b54f6a0fe) and [datajournalism-it/province.geojson](https://gist.github.com/datajournalism-it/212e7134625fbee6f9f7) by Datajournalism.itDownloader functions provide the original data as they are without any modification apart from translating them into English and optimising their presentation.## Further project details
This is a programming project for the Software and Computing for Nuclear and Subnuclear Physics course, Master Course in Nuclear and Subnuclear Physics, University of Bologna.
Package: itaewon
ItaewonMy personal python library to speed-up my workflow.Also, i found myself switching to R and Python quite frequently. This is my attempt to minimize that.The implementation is quite simple, since i'm simply runningRscripts in the background.Sample usage is shown below.Installation# !pip install itaewon==0.1.4importpandasaspdimportnumpyasnpimportwarningswarnings.filterwarnings('ignore')data=pd.DataFrame()error=np.random.normal(0,5,300)data['X']=np.random.normal(5,2.6,300)data['Z']=np.random.binomial(1,0.3,300)data['Y']=10*data['X']+2*data['Z']+errorTesting RModelsfromitaewon.rmodelsimportRModelsformula='Y ~ X + Z'rmodel=RModels(data,formula)model=rmodel.linear_regression()rmodel.infer_linear(model)Residuals       
 Min.   :-14.6393  
 1st Qu.: -3.4848  
 Median : -0.1583  
 Mean   :  0.0000  
 3rd Qu.:  3.3146  
 Max.   : 16.2795  

$coefficients
             Estimate Std. Error   t value      Pr(>|t|)
(Intercept) -1.109010  0.6718716 -1.650627  9.987172e-02
X           10.163182  0.1150433 88.342270 2.862585e-215
Z            1.426163  0.6222261  2.292033  2.260318e-02


$sigma
[1] 4.922223


$r.squared
[1] 0.9634044


$adj.r.squared
[1] 0.963158


fstatistic 3909.3683074439355
p_value [1] 4.668023e-214new_data=pd.DataFrame()new_data['X']=[0,1,2,3]new_data['Z']=[1,0,0,1]rmodel.predict(model,new_data,True,'confidence')PredictedLowerUpper00.317153-1.2339121.86821819.0541737.92166810.186677219.21735518.25852620.176184330.80670029.67183131.941568rmodel.predict(model,new_data,True,'prediction')PredictedLowerUpper00.317153-9.49309310.12739919.054173-0.69865718.807003219.2173559.48316428.951546330.80670021.05359540.559804rmodel.predict(model,new_data)Predicted00.31715319.054173219.217355330.806700Testing the custom modulefromitaewon.customimportCustomfromsklearn.linear_modelimportLinearRegression,LogisticRegressionlr=LinearRegression()custom=Custom(data[['X','Z']],data['Y'],True,lr)custom.custom()RMSE for LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None, normalize=False) : 4.752017508515921lr=LogisticRegression()custom=Custom(data[['X','Y']],data['Z'],False,lr)print(custom.custom()[0])print(custom.custom()[1])[[70  0]
 [29  0]]
              precision    recall  f1-score   support

           0       0.71      1.00      0.83        70
           1       0.00      0.00      0.00        29

    accuracy                           0.71        99
   macro avg       0.35      0.50      0.41        99
weighted avg       0.50      0.71      0.59        99
Package: italian-csv-type-prediction
This package is an attempt at predicting common types in CSVs about Italian people
and places using ensemble heuristics with Decision Random Forests and Spacy NLP tool.How do I install this package?As usual, just download it using pip:apt-getupdate-yapt-getinstall-qyyapt-utilsbuild-essentialsoftware-properties-commonlocaleslocales-allcurlautoconfautomakelibtoolpython-devpkg-configcurlhttps://raw.githubusercontent.com/LucaCappelletti94/italian_csv_type_prediction/master/setup.sh|shpipinstallitalian_csv_type_predictionTests CoverageSince some software handling coverages sometimes
get slightly different results, here’s three of them:Usage examplesTo get the typization of a list of data you can use:fromitalian_csv_type_predictionimportpredict_typespredictions=predict_types([#list of words to predict goes here])
Package: italian-dictionary
ItalianDictionaryThis package searches for word meanings ondizionario-italiano.Installpipinstallitalian-dictionaryUsageimportitalian_dictionary# Use this to get only the meaningdefinition=italian_dictionary.get_definition('cane',limit=3,all_data=False)#Use this to get all datas of a word (all_data default is True)datas=italian_dictionary.get_definition('albero')Complete data responseThis function will return a dictionary like this:{'sillabe':['al','be','ro'],'lemma':'Ã lbero','pronuncia':' /Ëˆalbero/','grammatica':['sostantivo maschile'],'definizione':['pianta con fusto alto, legnoso, provvisto di rami nella parte superiore',"MARINERIA --  palo che regge i pennoni con le vele e tutta l'attrezzatura",'MECCANICA --  parte rotante, generalmente cilindrica, che, in una macchina, ha la funzione di trasmettere potenza meccanica da un organo a un altro'],'locuzioni':["linea d'asse o d'alberi di una nave",'ad albero che cade dÃ gli dÃ gli','svasare un albero','albero portaelica','albero a calcese','albero castalio','albero matricino','alberi a mezzovento','albero optronico','albero pizzuto','andare agli alberi pizzuti','alberi rinterzati','albero del sego']}TestsTo run tests you needpytestWhen in project folder:python -m pytest
Package: italian-holidays
ItalianHolidaysA simple Python helper class to determine Italian holidays with the possibility to set custom holidays. Easter holidays' calculation will work for dates between 1900-2199.InstallUsing Pippipinstallitalian-holidaysUsagefromitalian_holidaysimportitalian_holidaysfromdatetimeimportdatetimecustom_holidays=["01-03","01-05"]# date format: month-day | in this example: 3 January, 5 January# But accepts also array of datetime objectcustom_holidays=[datetime(2021,1,3),datetime(2021,1,5)]holidays=italian_holidays(custom_holidays)# or simply italian_holidays() if you have no custom holidays to set# Passing stringis_holiday=holidays.is_holiday("2024-01-03")print(is_holiday)# True# Passing datetime objectday=datetime(2031,4,14)is_holiday=holidays.is_holiday(day)print(is_holiday)# True# Getting holiday's name (return None if date is not an italian holiday, return 'Custom holiday' if is one of the given dates)holiday_name=holidays.holiday_name("2020-11-01")print(holiday_name)# All Saints' DayLicenceSource code can be found ongithub, licenced underMIT.Developed byGiuseppe Bruno
Package: italianskin.templates
ItalianSkin (IS) is a product for Plone that aims making Plone compliant to latest Xhtml 1.0 Strict standards, a positive answer to the italian tight law called Legge Stanca, among its main features a useful tool for costumizing your visualization.Besides assuring whole compliance with the capital principles of italian law on web for public administration (Legge Stanca, 4/2004), ItalianSkin enables a comprehensive safeguard for final user improving the code for an appropriate readability by means such as screen readers (a necessary instrument for blind users) and produces an alternative high-visibility layout thought expressly for partially-sighted people.Compared to a traditional Plone site, ItalianSkin introduces:Support for a bare Xhtml 1.0 Strict code, valid for the whole portal, as well as for other popular products used by the community (separately to install). tableless layout
. traditional layoutFitting Plone site pages and popular third part products to W3C’s accessibility principles, following requirements established by italian civil law (legge Stanca), avoiding those code instruments that weigh down or make impossible a proper visualization.Dynamic evaluation and correction of non-compliant elements of the code to the Xhtml Stric grammar, eventually mistaken by an inexpert user.Answering the free software issue about an open source code, ItalianSkin is released under the same licence as Plone.Further Informations:
- Frequently Asked Question about Italianskin onhttp://redomino.com/it/labs/progetti/ItalianSkin/documentazione/domande-frequenti- Credits: information on authors, co-workers and Licence onhttp://redomino.com/it/labs/progetti/ItalianSkin/credits
Package: italianskin.tool
italianskin.tool provides a tool for italianskin; you can also use the tool without italianskin.templates.
You’re now free to choose between three given styles or even use your own customised style just adding a css file from the ZMI interface and setting its name and class id on the italianskin.tool graphic interface. No javascript needed.A few info on the styles you’ll find as default:Plone Default (contrast improved) - some light changes for a better contrast on plone default styleHigh Contrast (background black)  - changes on background, font, link for dark colors, a better contrast in a plone default style.High Contrast (background black - Padding/fonts modified) - following High Contrast changes on colors, it emphasizes dimensions (fonts, paddings, margins; no borders or images), a high-visibility layout thought expressly for partially-sighted people.Answering the free software issue about an open source code, ItalianSkin is released under the same licence as Plone.Further Informations:
- Frequently Asked Question about Italianskin onhttp://redomino.com/it/labs/progetti/ItalianSkin/documentazione/domande-frequenti- Credits: information on authors, co-workers and Licence onhttp://redomino.com/it/labs/progetti/ItalianSkin/credits
Package: italianswirls
Italian Swirls 🍝Minimal Python language server, based onJediandpygls.Still in development but works on my machine. ✨Supported features:LSP methodDescriptiontextDocument/completionCompletetextDocument/definitionGo to definitiontextDocument/typeDefinitionGo to type definitiontextDocument/hoverShow documentationtextDocument/referencesShow referencestextDocument/renameRenaming symbols and filesInstallTODOAboutWhy?General-purpose servers (e.g. pyls, py-lsp) try to do too much and break stuff
too often for me. Locking Neovim when I press tab, crashes of all kind,
LspRestart failing. Also I like my linting and formatting done by dedicated
tools such asnvim-lintandformatter.Other Jedi-based servers (e.g. jedi-language-server) seem to focus on coc-nvim
and frequently fail on Neovim's native LSP client for me. I tried to fix
jedi-language-server several times when it failed me but I thought it could be
fun to try pygls to redo it as small and simple as I can. And running a Node
server to get Python completions? No way. That said, jedi-language-server is a
good project and if you're fine with coc-nvim you should definitely check it
out. Lots of the code here isstoleninspired from this project.Why the name?Take the string “Is this a Star Wars reference?” Language Server, compress it toITASWRLSand expand it back to Italian Swirls. Italian dishes are made of few
elements that work well together. Enough questions!LicenseGPLv3.
Package: italian_vip_says
# Italian Vip Says[![codecov](https://codecov.io/gh/lotrekagency/italian-vip-says/branch/master/graph/badge.svg)](https://codecov.io/gh/lotrekagency/italian-vip-says)[![Build Status](https://travis-ci.org/lotrekagency/italian-vip-says.svg?branch=master)](https://travis-ci.org/lotrekagency/italian-vip-says)[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/Owanesh/italian-vip-says/blob/master/LICENSE)**Cottanzo**: Ciao Jovy, come ttai?**Jovanotty** : Fto bene, graffie. Fono folo un poco ftanco, vengo da Faffari* * *### Use it ✌🏻```pyfrom italian_vip_says import cottanzo, jovanottyjovanotty('Sono solo stasera a Sassuolo')>>> Fono folo ftafera a Faffuolocottanzo('Sono solo stasera a Sassuolo')>>> Tono tolo ttatera a Tattuolo```### Test it 💪🏻```shpip install -r requirements-dev.txtpytest -s --cov italian_vip_says```🙏🏻 Based on [Jovanotti](https://github.com/dottorblaster/jovanotti "dottorblaster rulez")![Maurittio](https://media.tenor.com/images/94585f8a56f4adaee5c1fc8434b86acc/tenor.gif)