Saravanan666/pypi-org huggingface dataset:
Package: chirimbolito
A Bitcoin address monitoring tool built with a Raspberry Pi and a LCD displayFeaturesIt pulls the balance of the bitcoin addresses you want to monitorIt displays the BTC and FIAT of your choise for each addressIt supports multiple addressesIt is easy to configure trough a json fileThe background color changes according to the FIAT price fluctuations. It compares the price of the present vs the price from yesterday’s closingYou will needone Raspberry Pione micro SD cardone LCD screen,Adafruit RGB Negative 16x2 LCD+Keypad Kit for Raspberry Pione or more bitcoin address to monitorHow to build itInstall Raspbian Stretch Lite on the micro SD card. This is beyond the scope of this document, you can find a good guidehereEnable sshd on a headless Raspberry PiInstall the LCD screen and the micro SD card in the Raspberry PiBoot the Raspberry Pissh into the Raspberry Pi and install the bitcoin address monitoring toolsshpi@raspbianpassword: (the default password is ‘raspberry’)pi@raspbian~ $ sudo apt-get update && sudo apt-get install build-essential python3 python3-dev python3-smbus python3-pip i2c-toolspi@raspbian~ $ sudo pip3 install –upgrade pippi@raspbian~ $ sudo /usr/sbin/usermod -a -G i2c pipi@raspbian~ $ mkdir chirimbolitopi@raspbian~ $ virtualenv chirimbolitopi@raspbian~ $ cd chirimbolitopi@raspbian~/chirimbolito $ source bin/activate(chirimbolito)pi@raspbian~/chirimbolito $ pip3 install chirimbolito(chirimbolito)pi@raspbian~ $ mkdir ~/.config && test -f ~/.config/chirimbolito.json || curl -sLo ~/.config/chirimbolito.jsonhttps://raw.githubusercontent.com/facastagnini/python-chirimbolito/master/chirimbolito.jsonEdit the file~/.config/chirimbolito.jsonto configure the bitcoin addresses that you want to monitor.Start the service (TODO)CONTRIBUITINGContributions gladly accepted, just open a ticket or send a PR :)PACKAGINGpip install –user check-manifest# check MANIFEST.in to make sure we are including everything we needcheck-manifestexport VERSION=’0.dev7’# bump the $VERSION in setup.pypython3 setup.py sdist bdist_wheelgpg –detach-sign -a dist/chirimbolito-$VERSION.tar.gzgpg –detach-sign -a dist/chirimbolito-$VERSION-py3-none-any.whlpython3 -m twine upload –repository pypi dist/*git tag -s $VERSIONgit push –tags
Package: chiron-bot
ChironChiron is a chatbot that listens for messages containing ticket numbers, looks
up the ticket in an appropriate bugtracker, and responds with the ticket title
and URL. Over time, the definition of "bugtracker" has broadened -- it
includes actual bugtrackers like Debathena's, but also MIT class numbers and
Bible verses.It supports running as both a zephyrbot (MIT's chat system) and aZulipbot.FeaturesSupports "tickets" in more than two dozen different "bugtracker" instances --- seebugtrackers.txtfor a listGeneric support for projects usingTracJiraGithub IssuesBugzillaResponds to both personal and class/stream messagesFor personal messages, will reply-all when there are multiple recipientsRunningFor Zulip support, install using thezulipextra, and then run./main.py --protocol=zulip, which will use your~/.zuliprc. Subscriptions are managed
through the usual Zulip mechanisms.For zephyr support, Chiron requiresEvan Broder'spython-zephyr--requirements.zephyr.txtmay be useful -- and must be run with tickets so that
it can sub to incoming zephyrs. You may findk5starthelpful for keeping
current tickets available.If you just run it with./main.py, it will subscribe to zephyr personals only
with some default bugtrackers.Primary production deploymentAlex Dehnert  runs the primary Chiron instance for zephyr, and is
generally happy to add additional matchers, fetchers, or classes. To request
changes, pleasefile an issue (or pull request) on
Github, zephyr him, or send mail tochiron@mit.edu.He also runs instances on some private Zulip realms.Private deploymentsIf you want to run your own private production Chiron instance, you can also
do that. By default,main.pywill only sub to personals. You can pass the--classoption one or more times to tell it to sub to specific classes.
Additionally, when run with the--default-classesoption it will sub to a
variety of default classes. Feel free to crib frommain.pyin setting up
your own Chiron instance, or run it subbed only to personals. However, please
ensure that if you run a Chiron instance that subs to non-personals, it
listens on different classes and/or uses different matchers than the primary
instance, so that users don't receive multiple replies to their zephyrs.
(Using the--classoption and not--default-classesis an easy way to
accomplish this.)Deploying on scriptsThe setup used for running the production zephyr instance on scripts.mit.edu is
in thedeploydirectory. It may be a decent reference for deploying your own
copy of Chiron or other similar zephyrbots.
Package: chiron-bot-adehnert
ChironChiron is a chatbot that listens for messages containing ticket numbers, looks
up the ticket in an appropriate bugtracker, and responds with the ticket title
and URL. Over time, the definition of "bugtracker" has broadened -- it
includes actual bugtrackers like Debathena's, but also MIT class numbers and
Bible verses.It supports running as both a zephyrbot (MIT's chat system) and aZulipbot.FeaturesSupports "tickets" in more than two dozen different "bugtracker" instances --- seebugtrackers.txtfor a listGeneric support for projects usingTracJiraGithub IssuesBugzillaResponds to both personal and class/stream messagesFor personal messages, will reply-all when there are multiple recipientsRunningFor Zulip support, install using thezulipextra, and then run./main.py --protocol=zulip, which will use your~/.zuliprc. Subscriptions are managed
through the usual Zulip mechanisms.For zephyr support, Chiron requiresEvan Broder'spython-zephyr--requirements.zephyr.txtmay be useful -- and must be run with tickets so that
it can sub to incoming zephyrs. You may findk5starthelpful for keeping
current tickets available.If you just run it with./main.py, it will subscribe to zephyr personals only
with some default bugtrackers.Primary production deploymentAlex Dehnert  runs the primary Chiron instance for zephyr, and is
generally happy to add additional matchers, fetchers, or classes. To request
changes, pleasefile an issue (or pull request) on
Github, zephyr him, or send mail tochiron@mit.edu.He also runs instances on some private Zulip realms.Private deploymentsIf you want to run your own private production Chiron instance, you can also
do that. By default,main.pywill only sub to personals. You can pass the--classoption one or more times to tell it to sub to specific classes.
Additionally, when run with the--default-classesoption it will sub to a
variety of default classes. Feel free to crib frommain.pyin setting up
your own Chiron instance, or run it subbed only to personals. However, please
ensure that if you run a Chiron instance that subs to non-personals, it
listens on different classes and/or uses different matchers than the primary
instance, so that users don't receive multiple replies to their zephyrs.
(Using the--classoption and not--default-classesis an easy way to
accomplish this.)Deploying on scriptsThe setup used for running the production zephyr instance on scripts.mit.edu is
in thedeploydirectory. It may be a decent reference for deploying your own
copy of Chiron or other similar zephyrbots.
Package: chirp
Chirp provides a number of related tools for analyzing and comparing
bioacoustic recordings.  It can operate on recordings stored in
standard wave files, with the option of restricting analyses to
specific spectrotemporal regions of the recording.  Regions are
defined with polygons in the time-frequency domain.  The tools consist
of the following programs:chirp :: inspect spectrograms of recordings and define regionscpitch :: determine the pitch of recordingsccompare :: compare libraries of recordings using pitch or spectrogramsChirp is not supported on Windows. The Windows binaries are provided only as a convenience.
Package: chirpstack-api
chirpstack-apiChirpStack gRPC API message and service wrappers for Python.Installpipinstallchirpstack-apiUsageAll messages, services, constants, etc. are auto-generated from the ChirpStack
protobuf definitions. The result is that this package structure matches that
of the protobuf definitions.The protobuf definitions can be found here:https://github.com/chirpstack/chirpstack/tree/master/api/protoLinkschirpstack-apiPython package pageChirpStack documentationCode examples
Package: chirpstack-api-beta
chirpstack-apiChirpStack gRPC API message and service wrappers for Python. This version is for chirpstack v4 and is not supportet by the chirpstack team.Installpipinstallchirpstack-api-betaUsageAll messages, services, constants, etc. are auto-generated from the ChirpStack protobuf definitions. The result is that
this package structure matches that of the protobuf definitions.The protobuf definitions can be found here:https://github.com/brocaar/chirpstack-api/tree/master/protobufLinkschirpstack-apiPython package pageChirpStack documentationChirpStack Application Server API examples
Package: chiscore
chiscoreEstimate the joint significance of test statistics derived from linear combination
of chi-squared distributions.InstallWe recommend installing it viaconda:condainstall-cconda-forgechiscoreAlternatively, chiscore can also be installed usingpip:pipinstallchiscoreRunning the testsAfter installation, you can test itpython-c"import chiscore; chiscore.test()"as long as you havepytest.UsageDavies>>>fromchiscoreimportdavies_pvalue>>>q=1.5>>>w=[[0.3,5.0],[5.0,1.5]]>>>davies_pvalue(q,w){'p_value':0.6151796819770086,'param':{'liu_pval':0.6151796819770086,'Is_Converged':1.0},'p_value_resampling':None,'pval_zero_msg':None}LiuLet us approximate𝑋 = 0.5⋅χ²(1, 1) + 0.4⋅χ²(2, 0.6) + 0.1⋅χ²(1, 0.8),and evaluate Pr(𝑋 > 2).>>>fromchiscoreimportliu_sf>>>>>>w=[0.5,0.4,0.1]>>>dofs=[1,2,1]>>>deltas=[1,0.6,0.8]>>>(q,dof,delta,_)=liu_sf(2,w,dofs,deltas)>>>q0.4577529852208846>>>dof3.5556138890755395>>>delta0.7491921870025307Therefore, we havePr(𝑋 > 2) ≈ Pr(χ²(3.56, 0.75) > 𝑡⁺𝜎ₓ + 𝜇ₓ) = 0.458.P-value>>>fromchiscoreimportoptimal_davies_pvalue>>>q=[1.5,3.0]>>>mu=-0.5>>>var=1.0>>>kur=3.0>>>w=[10.0,0.2,0.1,0.3]>>>remain_var=0.5>>>df=3.4>>>trho=[5.1,0.2]>>>grid=[0.,0.01]>>>optimal_davies_pvalue(q,mu,var,kur,w,remain_var,df,trho,grid)0.966039962464624AuthorsDanilo HortaReferencesLee, Seunggeun, Michael C. Wu, and Xihong Lin. "Optimal tests for rare variant
effects in sequencing association studies." Biostatistics 13.4 (2012): 762-775.Liu, H., Tang, Y., & Zhang, H. H. (2009). A new chi-square approximation to the
distribution of non-negative definite quadratic forms in non-central normal
variables. Computational Statistics & Data Analysis, 53(4), 853-856.LicenseThis project is licensed under theMIT License.
Package: chisel
Chisel is a light-weight Python WSGI application framework built for creating well-documented,
schema-validated JSON web APIs.LinksAPI DocumentationSource codeJSON APIsChisel provides theactiondecorator for easily implementing schema-validated JSON APIs.>>> @chisel.action(spec='''
... # Sum a list of numbers
... action sum_numbers
...     urls
...        GET
...
...     query
...         # The list of numbers
...         float[len > 0] numbers
...
...     output
...         # The sum of the numbers
...         float sum
... ''')
... def sum_numbers(ctx, req):
...     return {'sum': sum(req['numbers'])}
...
>>> application = chisel.Application()
>>> application.add_request(sum_numbers)
>>> application.request('GET', '/sum_numbers', query_string='numbers.0=1&numbers.1=2&numbers.2=4')
('200 OK', [('Content-Type', 'application/json')], b'{"sum":7.0}')Each action defines anactiondefinition usingSchema Markdown.
The action callback is passed two arguments, a requestContextand the schema-validated request input dictionary. The input request dictionary is created by
combining the request’s URL path parameters, query string parameters, and input JSON content
parameters.If there is a schema validation error the appropriate error code is automatically returned.>>> status, _, content_bytes = application.request('GET', '/sum_numbers')
>>> status
'400 Bad Request'>>> content_bytes
b'{"error":"InvalidInput","message":"Required member \'numbers\' missing (query string)"}'API DocumentationYou can add API documentation to your application by adding the Chisel documentation application
requests fromcreate_doc_requests.>>> application = chisel.Application()
>>> application.add_requests(chisel.create_doc_requests())By default the documentation application is hosted at “/doc/”. An example of of Chisel’s documentation output is
availablehere.DevelopmentThis package is developed usingpython-build.
It was started usingpython-templateas follows:template-specializepython-template/template/chisel/-kpackagechisel-kname'Craig A. Hobbs'-kemail'craigahobbs@gmail.com'-kgithub'craigahobbs'-knomain1
Package: chisel-nbdev
chisel-nbdevThe goal of this repo is to provide a seamless way to develop Chisel code in a Jupyter Notebook environment.Requirements (mac)setup some virtualenv (im using python3.8.2)pip install virtualenvfind your python3 binary:which python3which for me is/usr/local/bin/python3create virtualenv:python3 -m virtualenv --python=/usr/local/bin/python3 chisel_nb_envactivate it:source chisel_nb_env/bin/activateinstall jupyterlab (which includes jupyter notebook):pip install jupyterlab## Requirements (mac)setup some virtualenv (im using python3.8.2)pip install virtualenvfind your python3 binary:which python3which for me is/usr/local/bin/python3create virtualenv:python3 -m virtualenv --python=/usr/local/bin/python3 chisel_nb_envactivate it:source chisel_nb_env/bin/activateinstall jupyterlab (which includes jupyter notebook):pip install jupyterlabSetup the Jupyter Scala kernel Almond (https://almond.sh)Borrowed from the Chisel-Bootcamp install guide:https://github.com/freechipsproject/chisel-bootcamp/blob/master/Install.mdIf you experience errors or issues with this section, try running rm -rf ~/.local/share/jupyter/kernels/scala/ first.Next, download coursier (our dependency manager) and use it to install almond (our kernel wrapped around Ammonite) (see here for the source for these instructions):curl -L -o coursier https://git.io/coursier-cli && chmod +x coursier
SCALA_VERSION=2.12.10 ALMOND_VERSION=0.9.1
./coursier bootstrap -r jitpack \
    -i user -I user:sh.almond:scala-kernel-api_$SCALA_VERSION:$ALMOND_VERSION \
    sh.almond:scala-kernel_$SCALA_VERSION:$ALMOND_VERSION \
    --sources --default=true \
    -o almond
./almond --installYou can delete coursier and almond files if you so desire.Start JupyterLabMaking sure you are in your virtualenv then run:jupyter labProject StructureBy default, notebook source files (.ipynb) will live in thenbsfolder.Upon runningnotebook2script()the notebooks innbswill export code to.scfiles in thenbdevfolder. These are auto-generated files that can be imported back into notebooks via Ammonite: For exampleimport $file.MyMod, MyMod._imports the contents of the fileMyMod.sc.Testing NotebooksCurrently can runnbdev_test_nbs('MyMod.ipynb')to run all of the tests contained in theMyMod.ipynbnotebook.Tests are identified by either omitting any export flags (//export) or by including special flags defined insettings.ini(i.e//slowtestorchiseltest).settings.iniConfigurations belong in this file.
Package: chishop
Version:0.1Authors:Ask Solem (askh@opera.com)InstallationFirst you have to install the dependencies:$ python setup.py build
# python setup.py install # (run as root)Initial configuration$ cd chipshop/$ $EDITOR settings.py$ python manage.py syncdbRun the PyPI server$ python manage.py runserverPlease note thatchishop/media/distshas to be writable by the
user the web-server is running as.Contact Informationaskh@opera.com
Package: chi-square-saranya
chi-square-saranyaIt takes a dataframe with categorical columns for input as well as output , input categorical column, output categorical columnInstallationpip install chi-square-saranyaHow to use it?Use this function in your chi-square dataset chi_squ(dataframe,input_column,output_column)LicenseÂ© 2021 Saranya SekarThis repository is licensed under the MIT license. See LICENSE for details.
Package: chiss
chissProjectMon but : Aider les rats de franceReleases06/05/2022Le module chiss marche !Ajout de fonctionnalité complémentaire08/05/2022Son du chissNotes.ipynbenrichi le chissinit.py18/05/2022Méthode por frauderRéajustement du codeCommencement du module daskillFuturs ajoutsLe son du chissLe module daskill (intégérer dans le module chiss)Méthode pour frauder dans les transports en communcsNouveau fichier python pour faire le rat avec ses potesChrome Driver directement dans le module chissFonction pour avoir des feuilles de papier en illimitéComment l'utiliser ?installationpipinstallchissUtilisationExemple 1 :# Importer le module chiss.fromchissimportrat# Utiliser toutes ses fonctionnalités en profondeur.# N'oubliez pas les parenthèses.rat.all()Exemple 2 :# Importer le module chissimportchiss.rataschiss# Passer des moments merveilleux avec le module chiss.# N'oubliez pas les parenthèses.chiss.all()
Package: chistesESP
ï»¿# chistesESP-py
Script de Python que te permite obtener un chiste al azar de miles con un comando.UtilidadimportchistesESPascchiste=c.get_random_chiste()print(chiste)DocumentaciÃ³nLa Ãºnica funciÃ³n,get_random_chiste(), devuelve como string el texto de un diven esta pÃ¡gina.CrÃ©ditosLa pÃ¡ginachistes.comporque de ahÃ­ saco los chistes.El mÃ³duloBeautifulSoup
Package: chistes-gallegos
chistes-gallegosA package containing a function that returns randome jokes about Gallegos.UsageInstallpipinstallchistes-gallegosProgrammingfromchistes_gallegosimportget_jokejoke_string=get_joke()QuickstartReview/edit the generated filesAdd your code, documentation, etc.Create distribution tarball::python setup.py bdist_wheelUpload to PyPI::twine upload dist/*
Package: chitanda
chitandaAn extensible IRC & Discord bot. Requires Python 3.7.Read the documentation athttps://chitanda.readthedocs.io.QuickstartIt is recommended that chitanda be installed withpipx; however, if that is
not possible,pip install --userwill also work.$pipxinstallchitanda
$chitandamigrate# Upgrade database to latest version.$chitandaconfig# See wiki for configuration instructions.$chitandarunLicenseCopyright (C) 2019 dazuling <azuline@riseup.net>

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Package: chitchatcli
CHIT-CHATChit-Chat is a command line chatting software designed for developers to communicate with each other. In addition to being a regular chatting tool, it offers a range of interesting features, such as a ranking system for developers, a search tool for finding other developers with specific tech stacks, and more. Chit-Chat aims to add a bit of social life to developers who are often labeled "introverts" by providing a means of communication through a terminal.INSTALLATIONTo install Chit-Chat, follow the steps below:pip install chitchatcliRun the program:python3 -m chitchatcliTECHNOLOGIES USEDChit-Chat uses MongoDB to store necessary data, Express.js to set up the necessary APIs, and the client interface was written in Python.SCREENSHOTSAUTHORSChit-Chat was developed by the following authors:Akinwonjowo DennisGithub/LinkedInBenjamin EruvieruGithub/LinkedIn/EmailNnaemeka JosephGithub/LinkedIn
Package: chitchat-dataset
chitchat-datasetOpen-domain conversational dataset from the BYUPerception, Control & Cognitionlab'sChit-Chat Challenge.installpip3installchitchat_datasetorsimply download the raw dataset:curl-LOhttps://raw.githubusercontent.com/BYU-PCCL/chitchat-dataset/master/chitchat_dataset/dataset.jsonusageimportchitchat_datasetascccdataset=ccc.Dataset()# Dataset is a subclass of dict()forconvo_id,convoindataset.items():print(convo_id,convo)Seeexamples/for other languages.stats7,168 conversations258,145 utterances1,315 unique participantsformatThedatasetis a mapping from conversationUUIDto a conversation:{"prompt":"What's the most interesting thing you've learned recently?","ratings":{"witty":"1","int":5,"upbeat":5},"start":"2018-04-20T01:57:41","messages":[[{"text":"Hello","timestamp":"2018-04-19T19:57:51","sender":"22578ac2-6317-44d5-8052-0a59076e0b96"}],[{"text":"I learned that the Queen of England's last corgi died","timestamp":"2018-04-19T19:58:14","sender":"bebad07e-15df-48c3-a04f-67db828503e3"}],[{"text":"Wow that sounds so sad","timestamp":"2018-04-19T19:58:18","sender":"22578ac2-6317-44d5-8052-0a59076e0b96"},{"text":"was it a cardigan welsh corgi","timestamp":"2018-04-19T19:58:22","sender":"22578ac2-6317-44d5-8052-0a59076e0b96"},{"text":"?","timestamp":"2018-04-19T19:58:24","sender":"22578ac2-6317-44d5-8052-0a59076e0b96"}]]}how to citeIf you extend or use this work, please cite the paper where it was introduced:@article{myers2020conversational,
  title={Conversational Scaffolding: An Analogy-Based Approach to Response Prioritization in Open-Domain Dialogs},
  author={Myers, Will and Etchart, Tyler and Fulda, Nancy},
  year={2020}
}
Package: chiter
ChIter - iterable as a chainRequirementsPython 3.7+InstallationpipinstallchiterDocumentationComing soonWhy?Chains do not require saving the intermediate state in temporary variablesLook more readableExamplesIt is necessary to get the sum of all numbers from the following sequence:"23,45,67\n45,56,55\n\n45,a,5\n-45,56,0"first wayfromitertoolsimportchaindata="23,45,67\n45,56,55\n\n45,a,5\n-45,56,0"chunks=(chunk.split(',')forchunkindata.split())flat_data=chain.from_iterable(chunks)items=(int(item)foriteminflat_dataifnotitem.isalpha())result=sum(items)assertresult==352second wayfromitertoolsimportchaindata="23,45,67\n45,56,55\n\n45,a,5\n-45,56,0"result=sum((int(item)foriteminchain.from_iterable(map(lambdac:c.split(','),data.split()))ifnotitem.isalpha()))assertresult==352chiter wayfromchiterimportChIterasIdata="23,45,67\n45,56,55\n\n45,a,5\n-45,56,0"result=(I(data.split()).map(lambdax:x.split(',')).flat().filterfalse(str.isalpha).map(int).sum())assertresult==352Related Librariesflupy