Saravanan666/pypi-org huggingface dataset:
Package: faraday-grpc-client
faraday-grpc-clientA python grpc client for LL Faraday (Node Stats)This is a wrapper around the default grpc interface that handles setting up credentials (including macaroons.DependenciesPython 3.6+Working LND lightning node, take note of its ip address.Copy your pool.macaroon and tls.cert files from~/.faraday/mainnetto a directoy on your machine.Installationpipinstallfaraday-grpc-clientGenerating LND Proto Filesvirtualenvlndsourcelnd/bin/activate
pipinstallgrpciogrpcio-toolsgoogleapis-common-protossh
gitclonehttps://github.com/lightningnetwork/lnd.git
mkdirgenprotos
gitclonehttps://github.com/googleapis/googleapis.git

python3-mgrpc_tools.protoc--python_out=.--grpc_python_out=.frdgrpc/compiled/*.protofrompathlibimportPathimportshutilimportshforprotoinlist(Path("../lnd/lnrpc").rglob("*.proto")):shutil.copy(proto,Path.cwd())protos=list(Path(".").glob("*.proto"))forprotofileinprotos:try:sh.python("-m","grpc_tools.protoc","--proto_path=.","--python_out=.","--grpc_python_out=.",str(protofile))protos.remove(protofile)exceptExceptionase:print(f"Error in proto:{protofile}")Last Step:
In File: verrpc_pb2_grpc.py
Change:
import verrpc_pb2 as verrpc__pb2
To:
from lndgrpc import verrpc_pb2 as verrpc__pb2Deploy to Test-PyPipoetrybuild
twinecheckdist/*
twineupload--repository-urlhttps://test.pypi.org/legacy/dist/*
Package: farapy
FaraPy | The Best Python CMSFaraPy is an smart open source python CMS built on Django. FaraPy is a SEO friendly content management system with lots of possibilities and really really easy to develop.How to installlocal install on windows:if you have installed the python on your system jost go to foldre press the Shift + Right click and choose powershell or cmd
then run this tow lines of commands:pipinstallfarapy
farapystartsampleprojectcdsampleproject
pythonmanage.pyrunserver80then open your browser and type localhost to see the CMS :)if you want to run it on other port, insted of 80 type your own port. for example:python manage.py runserver 8000for Entering to admin panel just add/panelat the end of your site url.the default user name is:adminandThe default password is:adminFeaturesGreat AITheme EditorTheme Manager / UploadEasy to developComptible with Shared hosts which support pythonAutomatic cache system with AIFast process cause of great algorithmsSEOlized
Package: faraway
Functions and Datasets to support statistics book(s) by Julian FarawayI am the author ofLinear Models with RandExtending the Linear Model with RA new book entitledLinear Models with Pythonwill be published soon. This package
contains data (and documentation) along with a few functions to support this book.DataAll the datasets fromLinear Models with Rare included. These are all small datasets
useful for teaching or other example purposes.You can load a dataset (for example) withimport faraway.datasets.composite
composite = faraway.datasets.composite.load()
compositeand you can see the description withprint(faraway.datasets.composite.DESCR)The datasets included areclot        fat         infmort     peanut      resceram    swiss
aatemp      coagulation fortune     jsp         penicillin  salmonella  teengamb
abrasion    composite   fpe         kanga       pima        sat         truck
air         cornnit     fruitfly    leafburn    pipeline    savings     tvdoctor
alfalfa     corrosion   galamiss    manilius    pressure    seatpos     uswages
anaesthetic crawl       galapagos   mba         prostate    sexab       wafer
butterfat   denim       gammaray    meatspec    pulp        snail       warpbreaks
cars        divusa      generic     newhamp     punting     sono        whiteside
cheddar     eco         globwarm    oatvar      pvc         speedo
chmiss      eggprod     hips        odor        rabbit      star
chredlin    families    hsb         ozone       rats        statedataThis is a subset of those available in myR package on CRANwhere you can also see documentation on these datasets.FunctionsCurrently, there is only one useful function which is an alternative to the regression summary function
used instatsmodels. It is much more compact. Supposelmodis an OLSresults object, then (note the spelling issumary())lmod.sumary()would produce something likecoefs stderr tvalues pvalues
Intercept  7.068 19.154    0.37  0.7154
Area      -0.024  0.022   -1.07  0.2963
Elevation  0.319  0.054    5.95  0.0000
Nearest    0.009  1.054    0.01  0.9932
Scruz     -0.241  0.215   -1.12  0.2752
Adjacent  -0.075  0.018   -4.23  0.0003

n=30 p=6 Residual SD=60.975 R-squared=0.77
Package: farbe
farbeInstallation$pipinstallfarbeTestJust type in these commands and check if your terminal can print colors properly:>>>importfarbe
>>>farbe.test()It prints the supported combinations of colors and effects:Basic UsageSpecify the color you want to use and feed a string to theFarbeobject'sprintmethod.>>>fromfarbeimportColor,Farbe
>>>bb=Farbe(Color.Fg.BrightBlue)>>>bb.print('Hello, Bright Blue')Hello,BrightBlue
>>>white_fg_red_bg=Farbe(Color.Fg.White,Color.Bg.Red)>>>white_fg_red_bg.print('White characters on red background')Whitecharactersonredbackground
>>>italic=Farbe(Color.Fg.Normal,effects=[Color.Effect.Italic])>>>italic.print('Characters in italic')CharactersinitalicUsing Colored objectsColoredobjects can be used in combination with normal strings.>>>red=Farbe(Color.Fg.Red)>>>yellow=Farbe(Color.Fg.Yellow)>>>error=red.colored('Error')>>>warning=yellow.colored('Warning')>>>print('['+error+'] Something went wrong!')[Error]Somethingwentwrong!
>>>print('🐍 '+warning+'! 🐍')🐍Warning!🐍Supported Colors and EffectsForeground ColorsColor NameCodeNormalColor.Fg.NormalBlackColor.Fg.BlackRedColor.Fg.RedGreenColor.Fg.GreenYellowColor.Fg.YellowBlueColor.Fg.BlueMagentaColor.Fg.MagentaCyanColor.Fg.CyanWhiteColor.Fg.WhiteBrightBlackColor.Fg.BrightBlackBrightRedColor.Fg.BrightRedBrightGreenColor.Fg.BrightGreenBrightYellowColor.Fg.BrightYellowBrightBlueColor.Fg.BrightBlueBrightMagentaColor.Fg.BrightMagentaBrightCyanColor.Fg.BrightCyanBrightWhiteColor.Fg.BrightWhiteBackground ColorsColor NameCodeNormalColor.Bg.NormalBlackColor.Bg.BlackRedColor.Bg.RedGreenColor.Bg.GreenYellowColor.Bg.YellowBlueColor.Bg.BlueMagentaColor.Bg.MagentaCyanColor.Bg.CyanWhiteColor.Bg.WhiteBrightBlackColor.Bg.BrightBlackBrightRedColor.Bg.BrightRedBrightGreenColor.Bg.BrightGreenBrightYellowColor.Bg.BrightYellowBrightBlueColor.Bg.BrightBlueBrightMagentaColor.Bg.BrightMagentaBrightCyanColor.Bg.BrightCyanBrightWhiteColor.Bg.BrightWhiteEffectsEffectCodeBoldColor.Effect.BoldFaintColor.Effect.FaintItalicColor.Effect.ItalicUnderlineColor.Effect.UnderlineSlowBlinkColor.Effect.SlowBlinkRapidBlinkColor.Effect.RapidBlinkReverseColor.Effect.ReverseConcealColor.Effect.ConcealCrossOutColor.Effect.CrossOut
Package: farbencounter
Counts the unique colors in an image and returns a DataFrame with color counts and optional color coordinates.Tested against Windows 10 / Python 3.11 / Anacondapip install farbencounter# Example usagefromfarbencounterimportcount_colorspic=r"https://www.python.org/static/img/python-logo.png"img=open_image_in_cv(pic,channels_in_output=3)df,colorcoords=count_colors(img=img,sort=True,get_color_coords=True)# df: DataFrame containing color information and counts# colorcoords: Dictionary containing color coordinates# df# Out[3]:#             a    r    g    b      c# 0           0    0    0    0    456# 1          26    0    0   26      2# 2        3612    0   14   28      2# 3        3619    0   14   35      1# 4        3870    0   15   30      9# ..        ...  ...  ...  ...    ...# 849  16776316  255  252  124      2# 850  16776431  255  252  239      1# 851  16776432  255  252  240      1# 852  16776830  255  254  126      1# 853  16777215  255  255  255  18608# [854 rows x 5 columns]# colorcoords# ....# (44, 99, 147): array([[48, 32]]),#  (45,#   45,#   45): array([[230,  28],#         [170,  32],#         [189,  52]], dtype=int64),#  (45, 86, 119): array([[12, 25]]),#  (45, 94, 133): array([[ 8, 30]]),#  (45, 96, 139): array([[20, 43]]),#  (45, 101, 150): array([[45, 36]]),#  (46, 35, 12): array([[36, 53]]),#  (46,#   46,#   46): array([[239,  14],#         [143,  23],#         [143,  28],#         [170,  34],#         [185,  34],#         [ 84,  45],#         [ 90,  48],#         [118,  48],#         [119,  48],#         [201,  48],#         [194,  52]], dtype=int64)# ....
Package: farbfeld
farbfeld.pyThis is a small Python module for reading and writing pixel data
from farbfeld images (https://tools.suckless.org/farbfeld/).InstallationThe module is available on PyPI:https://pypi.org/project/farbfeld/You can install it withpip:pip install farbfeldUsageTo read an image, open the desired file and read the pixels
from it usingfarbfeld.read:importfarbfeldwithopen('image.ff','rb')asf:data=farbfeld.read(f)Note that since farbfeld stores pixel components as 16-bit
unsigned integers, you may have to normalize them or scale
them to a different range (e.g. 8-bit). For example, using
NumPy and Matplotlib:importfarbfeldimportnumpyasnpimportmatplotlib.pyplotaspltwithopen('image.ff','rb')asf:data=farbfeld.read(f)data_8bit=np.array(data).astype(np.uint8)plt.imshow(data_8bit,interpolation='nearest')plt.show()To write a farbfeld image, open the desired file and write the pixels
into it usingfarbfeld.write:importfarbfeld# An example 2x2 imagedata=[[[1,2,3,4],[5,6,7,8]],[[9,10,11,12],[13,14,15,16]],]withopen('image.ff','wb')asf:farbfeld.write(f,data)Source codeThe source code is available on GitHub:https://github.com/jmp/farbfeld
Package: farbox-gevent-websocket
Licensed under the Apache License, Version 2.0 (the “License”);
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.Download-URL:https://bitbucket.org/Jeffrey/gevent-websocketDescription: UNKNOWN
Platform: UNKNOWN
Classifier: Environment :: Web Environment
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python
Classifier: Topic :: Internet
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Package: farbox-misaka
A CFFI binding forHoedown(version 3), a markdown parsing library.Documentation can be found at:http://misaka.61924.nl/InstallationMisaka has been tested on CPython 2.6, 2.7, 3.2, 3.3, 3.4, 3.5 and PyPy 2.6. It needs
CFFI 1.0 or newer, because of this it will not work on PyPy 2.5 and older.With pip:pip install farbox-misakaOr manually:python setup.py installExampleVery simple example:importmisakaasmprintm.html('some other text')Or:frommisakaimportMarkdown,HtmlRendererrndr=HtmlRenderer()md=Markdown(rndr)print(md('some text'))
Package: farc
farcFramework for Asyncio/Actor/AHSM Run-to-completion Concurrency
written in Python3.  In other words, a cheap knock-off ofQPthat uses Python3 coroutines.This bookdescribes QP and how to programstatecharts(a.k.a. hierarchical state machines).This framework has fewer than 1000 LOC.  It allows the programmer to create
highly-concurrent programs by using a message-passing system and
run-to-completion message handlers within a state-machine architecture.
With these tools, complex, asynchronous operations are decomposed
into managable chunks of code.Known Issue: On windows, Ctrl+C is supressed by asyncio event loop's
run_forever() (bug report).
The workaround is to inject an event to awake the event loop.Note:  This project used to be called "pq" but that name was taken in PyPI,
so I renamed to farc (ugh).Code Repositoryhttps://github.com/dwhall/farcRelease History2020/11/07  0.2.0BREAKS API: Removed initEvent argument from Ahsm.start()BREAKS API: Renamed camel-case procedures with underscoresBREAKS API: Eliminated @staticmethod and use of "me"BREAKS API: Removed VcdSpy (debug helper) class from default namespaceSerialize Event values using pickle.  This might lead to a runtime error for some.call Framework.run() as soon as possible when an event is posted to AHSM (Max Peng).Reimplement HSM algorithm and include hsm_test (Sze Tan)Consolidated all files into__init__.py2019/05/15  0.1.1Removed 'initialState' argument from farc.Hsm() constructor;
framework now expects Hsm/Ahsm classes to have 'initial()' method.Made state methods private in examples to demonstrate a best-practice.Created farc.Framework.run_forever() helper function.Misc comment and doctring improvements2018/10/09  0.1.0   Initial release
Package: farcaster
farcaster-pyfarcaster-py is a modern Python SDK for the Farcaster protocolFull documentation can be foundhereInstallationpipinstall-Ufarcasteror install withPoetry:poetryaddfarcasterUsageThis SDK leverages the Warpcast API.Warpcastis one of many Farcasterclients. As more APIs are created and hosted by different clients, these will be added to the SDK.To use the Warpcast API you need to have a Farcaster account. We will use the mnemonic or private key of the Farcaster custody account (not your main wallet) to connect to the API.First, save your Farcaster mnemonic or private key to a.envfile. Now you can initialize the client, and automatically connect to the Farcaster API!importosfromfarcasterimportWarpcastfromdotenvimportload_dotenv# can be installed with `pip install python-dotenv`load_dotenv()client=Warpcast(mnemonic=os.environ.get("<MNEMONIC_ENV_VAR>"))print(client.get_healthcheck())ExamplesGet a castresponse=client.get_cast("0x321712dc8eccc5d2be38e38c1ef0c8916c49949a80ffe20ec5752bb23ea4d86f")print(response.cast.author.username)# "dwr"Publish a castresponse=client.post_cast(text="Hello world!")print(response.cast.hash)# "0x...."Get a user by usernameuser=client.get_user_by_username("mason")print(user.username)# "mason"Get a user's followers using a fid (farcaster ID)response=client.get_followers(fid=50)print(response.users)# [user1, user2, user3]Stream recent castsforcastinclient.stream_casts():ifcast:print(cast.text)# "Hello world!"Get users who recently joined Farcasterresponse=client.get_recent_users()print(response.users)# [user1, user2, user3]Get your own user objectuser=client.get_me()print(user.username)# "you"Recast a castresponse=client.recast("0x....")print(response.cast.hash)# "0x...."and many, many more things. The full specification can be found on theReference page.Please note that support for Python 3.7 is no longer actively maintained. Python 3.8, 3.9, or 3.10 are recommended.🛡 LicenseThis project is licensed under the terms of theMITlicense. SeeLICENSEfor more details.DisclaimerThis code is being provided as is. No guarantee, representation or warranty is being made, express or implied, as to the safety or correctness of the code. It has not been audited and as such there can be no assurance it will work as intended, and users may experience delays, failures, errors, omissions or loss of transmitted information. Nothing in this repo should be construed as investment advice or legal advice for any particular facts or circumstances and is not meant to replace competent counsel. It is strongly advised for you to contact a reputable attorney in your jurisdiction for any questions or concerns with respect thereto. a16z is not liable for any use of the foregoing, and users should proceed with caution and use at their own risk. Seeour disclosures pagefor more info.
Package: farcaster-cli
farcaster-clifarcaster-cli is a CLI client for the Farcaster protocolInstallationpipinstallfarcaster-clior install withPoetry:poetryaddfarcaster-cliUsageThis client leverages the Warpcast API.Warpcastis one of many Farcasterclients. As more APIs are created and hosted by different clients, these will be added to the CLI.To use the Warpcast API you need to have a Farcaster account. We will use the mnemonic or private key of the Farcaster custody account (not your main wallet) to connect to the API.First, save your Farcaster mnemonic or private key to a $MNEMONIC environment variable. Now you can initialize the client, and automatically connect.exportMNEMONIC=<yourcustodyseedphrasehere>farcaster-cli$MNEMONIC--watch-allThis subscribes to all recent casts. If you want only the casts of people you follow, remove--watch-all.
You can also include--skip-existingto only get new casts after the client starts.
Package: farcy
Definition:a form of glanders chiefly affecting the skin and superficial lymphatic
vessels of horses and mules.While horses and mules function with farcy, such animals wouldlikelyprefer
not to have them, and they are an eyesore to those viewing such
animals. Unreviewed source code is analogous to farcy for equines, where the
resulting execution of the source code will likely work as intended, but may be
an eyesore to those working with the source. Farcy attempts to instruct authors
of pull requests to remove eyesores they’ve added by commenting on changes
introduced in pull requests.Installation and executionFarcy is easiest to install usingpip:$pipinstallfarcyFarcy is run by specifying a github repository owner (or organization), the
repository name, and an optional log level:$farcy--levelINFOappfoliofarcyConfigurationFarcy allows to be configured using configuration files. Existence of a configuration
file is optional and values can be overwritten by commandline arguments. On boot,
Farcy will look for a configuration file at~/.config/farcy/farcy.conf.The configuration file can contain aDEFAULTsection and a section per repository
with specific settings. TheDEFAULTsection can take an optionalrepositorykey.[DEFAULT]
log_level: INFO
repository:appfolio/farcy

[appfolio/farcy]
debug: true
exclude_paths: npm_modules, vendor, db
limit_users: balloob, bboe
pr_issue_report_limit: 32

[appfolio/gemsurance]
exclude_users: bboe
log_level: WARNING
pr_issue_report_limit: 10Configuration files for the various linters can be placed in~/.config/farcy/handler_NAME.conf. ReplaceNAMEwith the name of the handler.Optional external packages needed for various file typesPython:farcywill take advantage of two tools for python files:flake8andpep257. These can be installed alongsidefarcyvia:$pipinstallfarcy[python]Ruby: In order to provide code review of ruby files,rubocopis
required. Install via:$geminstallrubocopJavaScript: jsxhint is used to provide code review for JavaScript and JSX files. Install via:$npminstall-gjsxhintDockerFarcy is available as a Docker image with all the handlers installed and ready to be used.To get started, create a config folder with a configuration filefarcy.confthat points at your repository.[DEFAULT]
repository: appfolio/farcyAfter that, run the Docker container in interactive mode to setup your GitHub credentials. This will create the filegithub_authin your configuration folder. This file can be reused if you plan on creating multiple containers.$dockerrun-t-i-v/path/to/local/farcy/config:/configappfolio/farcyAfter the initial setup, Farcy is ready to go and you can run the Docker container in daemon mode.$dockerrun-d--name="farcy"-v/path/to/local/farcy/config:/configappfolio/farcyCopyright and licenseSource released under the Simplified BSD License.Copyright (c), 2014, AppFolio, IncCopyright (c), 2014, Bryce BoeCopyright (c), 2015, Paulus Schoutsen
Package: fare
This repository contains code and example analysis for evaluating the fairness of rankings with respect to protected groups, using the pairwise error metrics and auditing methodology presented in the paper:“FARE: Diagnostics for Fair Ranking using Pairwise Error Metrics” in the proceedings of the Web Conference (WWW 2019)
by Caitlin Kuhlman, MaryAnn VanValkenburg, Elke RundensteinerThis work is released under the 3-Clause BSD License.The three pairwise error metrics presented in the paper,Rank Equality, Rank Parity, and Rank Calibrationare included in the fare package distibution, along with methods to perform fairness auditing of rankings.Example analysis, including the experiments in the paper, is available in the jupyter notebooks in the examples folder.
Package: farepa
farepaPython Boilerplate contains all the boilerplate you need to create a Python package.Free software: GNU General Public License v3Documentation:https://farepa.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-03-18)First release on PyPI.
Package: farglot
FarGlotA Transformer-based SocialNLP toolkit forFarcaster.Installationpip install farglotExamplesfromfarglotimportCastAnalyzersentiment_analyzer=CastAnalyzer.sequence_analzyer_from_model_name(hub_address="nemes.farcaster.xyz:2283",model_name="pysentimiento/robertuito-sentiment-analysis")sentiment_analyzer.predict_cast(fid=2,hash_hex="0bcdcbf006ec22b79f37f2cf2a09c33413883937")# {'NEG': 0.051998768001794815, 'NEU': 0.22470703721046448, 'POS': 0.7232941389083862}sentiment_analyzer.predict_casts_by_fid(fid=2)# {'NEG': 0.03734538331627846, 'NEU': 0.505352795124054, 'POS': 0.4573018550872803}Generate a Training Corpus from aHubInstall the FarGlot CLIpip install "farglot[cli]"Define Training Set Classifier(s){"name":"labels","default_value":1// optional}For multi-label classfication:[{"name":"class_one","default_value":1// optional},{"name":"class_two","default_value":2// optional},{"name":"class_three","default_value":3// optional}]Usagefarglotinit
farglotset-classifers-path/path/to/class_configs.json
farglotset-hub-db-path/path/to/.rocks/rocks.hub._default
farglotnew-training-set--out./data/training-set.csvTuningTODO: Example of fine-tuning and uploading dataset and model toHugging FaceTuning ResourcesNot sure how to where to start? Check out the following blog posts on tuning an LLM:Datasets and PreprocessingHyperparameters and MetricsThis largely is largely adapted off ofpysentimiento.
Package: fargv
fargv: The laziest command-line argument parserInstallationpip3pipinstall--user--upgradegit+https://github.com/anguelos/fargvUsage in 3 Simple Steps!Fast argument parserImport"""The script's docstring Becomes the general description in the help if defined"""fromfargvimportfargvDefine a dictionary with default parametersparams={"anInt":1,"aFloat":0.1,"aBoolean":False,"anotherBoolean":True,"aString":"Hello","aStringReference":"{aString}World","anIntWithHelp":[2,"This would be the help"],"aChoice":[("choice1","choice2","choice3","choice4"),"And this must be the help"],"aPositionalSwitch":[set([]),"This is a convenient way to pass colections of things"]}Parse user provided argv to override defaultsnew_params,help_str=fargv(params)In shell:my_program-anInt34-aFloat=2.3-aBoolean-anotherBoolean=FalseFeatures:Type checkingAutomatic help generationParams usable as dictionary or structCan read environmental variables as wellmacro-parametersfast autocomplete generationSwitches with positional valuesAutocompleteStatic autocomplete for any program using fargv can be enabled with a single command.The following command enables autocomplete for fargv_demo.py in the current shell where it is run.source<(./examples/fargv_demo.py-bash_autocomplete)fargv_demo.py should be an executable file employing the shebang (#!/usr/bin/env python3) or something equivalent.
For a temporary solution, the autocomplete bash code can go in a script in /etc/bash_completion.d or in .bashrc.Switch MacrosA switch might be a macro for other switches.
This allows for example to break many files into a single root switch and all other switches beeing file names relative to that path.