Saravanan666/pypi-org huggingface dataset:
Package: go2
go2 is a fast directory findergo2PYPI:https://pypi.org/project/go2/Debian package:https://uclm-arco.github.io/debian/Descriptiongo2 provides an easy method to change among directories by a fast way. go2 is a console
program similar to the old PCTools dm or the ncd from Norton, although this is designed
for bash.Features:cache of recent searches;history list of visited directories;blacklist of directories not to search;configuration file for default options;multithreaded execution.Similar programswcdkcdcdargsapparixautojumpInstallThe recommended way is to install thedebian packageusing
apt-get::# apt-get install go2alternatively you may install from PYPI with:$ sudo pip3 install --prefix /usr go2Once it is installed, each user need to include next line at the end of their~/.bashrc:[ -e /usr/lib/go2/go2.sh ] && source /usr/lib/go2/go2.shIn the next shell session, go2 will be ready to use.Usagego2 is very easy to use. From any directory just execute::$ go2 prefixwhen 'prefix' is the beginning of the directory you want to go. go2 will search in your
'home' and it will list all the directories that match the prefix.Each match has a associated letter. To choose the target, just press the corresponding
key. If you want to abort the search, you may press the ESC key (or C-c). You may choose
the first match pressing ENTER. The selection may occurs in any moment, it is not required
that you wait the searching is finished.go2 remembers all the successful searches, so it is faster each time.Other optionsgo2 has some options to perform searches from the '/' directory, to ask case-insensitive
matching, etc. Try this::$ go2 --help
usage: go2 [-h] [--cd] [-i] [-r] [--setup] [--version] [pattern [pattern ...]]

go2 is a fast directory finder.

This is version 1.20111128, Copyright (C) 2004-2011 David Villa Alises.
go2 comes with ABSOLUTELY NO WARRANTY; This is free software, and you
are welcome to redistribute it under certain conditions; See COPYING
for details.

positional arguments:
  pattern            pattern to find

optional arguments:
  -h, --help         show this help message and exit
  --cd               change to given dir and add it to the cache (useful as
                     'cd' alias)
  -i, --ignore-case  ignore case search
  -r, --from-root    search in whole file system
  --setup            install go2 in your .bashrc
  --version          show program's version number and exit'pattern' may be a word list so it is possible to do things like::$ go2 -r cach arch
a: /var/cache/apt/archives
Searching...
Package: go2scope
Copyright (c) 2019 The Python Packaging Authoritygo2ScopePython Packagego2Scopeis a microscopy automation programming environment, based on the popular Open Source microscopy softwaremicro-manager.go2Scopemainly solves issues with controlling multiple microscopes in a highly automated distributed environment.Python package is intended to provide utilities for interfacing togo2scopewhich is mainly written in C++ and Java.dataiosub-packageReading and writing of "classic" micromanager datasets. Classic dataset is a folder with sub-folders containing metadata and individual image files. Each image can be accessed with four integer coordinates: position, channel, slice and time-point.This package does not work with OME compatible "image stack files".
Package: goa-loader
National Gallery of Art Open Data Programtf.data.DatasetLoadera tf.data Loader for theNational Gallery of Art Open Data Program... and Generative Modeling to Accompany!Table of ContentsOverviewQuickstartExamplesCitationQuickstartGetting started with thegoa_loaderloader is as easy as:pipinstallgoa-loaderThen you can load the dataset with:dataset=goa_loader.load()To make sure your installation works, try out:python examples/basic/visualize_samples.pyOverviewgoa_loader.load()loads a dataset of images from theNational Gallery of Art Open Data Programinto atf.data.Dataset.
This dataset may be used for anything; from generative modeling to style transfer.
Check outQuickstartorexamples/to see how you can get started.ByLuke Wood& othersBackground: National Gallery of Art Open Data ProgramThe National Gallery of Art Open Data Program has an official Github repoTheNational Gallery of Artserves the United States by welcoming all people to explore and experience art, creativity, and our shared humanity. In pursuing our mission, we are making certain data about our collection available to scholars, educators, and the general public in CSV format to support research, teaching, and personal enrichment; to promote interdisciplinary research; to encourage fun and creativity; and to help people understand the inspiration behind great works of art. We hope that access to this dataset will fuel knowledge, scholarship, and innovation, inspiring uses that transform the way we discover and understand the world of art.To the extent permitted by law, the National Gallery of Art waives any copyright or related rights that it might have in this dataset and is releasing this dataset under theCreative Commons Zerodesignation.The dataset provides data records relating to the 130,000+ artworks in our collection and the artists who created them.  You can download the dataset free of charge without seeking authorization from the National Gallery of Art.ExamplesBasic Loading and VisualizationDenoising Diffusion Implicit ModelCitation@misc{goawood2022,title={A tf.data Loader for the National Gallery of Art Open Data Program},author={Wood, Luke and others},year={2022},howpublished={\url{https://github.com/lukewood/goa-loader}},}
Package: goal_oriented
This module provides a simple facility to the goal-oriented programming paradigm.In goal-oriented programming, the programmer subdivides the problem in minor goals,with dependencies between them, and just pass them to a scheduler that willexecute them asyncronously and in the correct order.===In this implementation every goal function receives three arguments:name    -- the unique name of the goalargs    -- the results from its dependenciesresults -- a dictionary where it can write a return value(readable by subcessive goals)The test cointained in the module file illustrates how the module must be used.===An example of usage:"""Usage example"""def goal1(name, args, results):print name, argssleep(1)results[name] = name + " completed!"def goal2(name, args, results):print name, argssleep(2)results[name] = name + " completed!"def goal3(name, args, results):print name, argssleep(2)results[name] = name + " completed!"def goal4(name, args, results):print name, argssleep(1)results[name] = name + " completed!"def goal5(name, args, results):print name, argssleep(3)results[name] = name + " completed!"def goal6(name, args, results):print name, argssleep(1)results[name] = name + " completed!"# goals to run and their dependenciesschedule_goals( goal1 = { 'target': goal1 },goal2 = { 'target': goal2 },goal3 = { 'target': goal3, 'deps': ['goal1', 'goal2'] },goal4 = { 'target': goal4, 'deps': ['goal3'] },goal5 = { 'target': goal5, 'deps': ['goal2'] },goal6 = { 'target': goal6 } )===Output of the example:$ python goal_oriented.pygoal6 {}goal2 {}goal1 {}goal5 {'goal2': 'goal2 completed!'}goal3 {'goal2': 'goal2 completed!', 'goal1': 'goal1 completed!'}goal4 {'goal3': 'goal3 completed!'}real	0m5.018suser	0m0.104ssys	0m0.052s===Have fun... :)
Package: goamazondownloader
Go Amazon Downloader DataA Python Library for download data from campaign Green Ocean AmazonDeveloperAdrianoPereiraFeaturesDownload S-Band Radar (SIPAM)Download Very Low Frequency Sensor (STARNET)For the time being, only the modules to download the files from S-Band Randar (SIPAM) and Very Low
Frequency have been implemented.InstallationVia pip:pip install goamazondownloaderVia source code:git clone https://github.com/AdrianoPereira/goamazondownloader.gitcd goamazondownloaderpython setup.py installDependenciesrequestsbeautifulsoup4UsageThe files are hosted on theARMwebsite.
To download the files it is necessary to have a registration. Registration can be done quickly through the following
link:https://adc.arm.gov/armuserreg/#/new.Download S-Band Radar (SIPAM)fromgoamazondownloaderimportSBandRadardownloader=SBandRadar(year=2014,month=2,day=18,hour=15,minute=0)downloader.login(username="<username>")# <username> maybe your username or e-maildownloader.set_remote_url()downloader.download()Downloader Very Low Frequency Sensor (STARNET)fromgoamazondownloaderimportVLFSensordownloader=VLFSensor(year=2014,month=2,day=18)downloader.login("username")# # <username> maybe your username or e-maildownloader.set_remote_url()downloader.download()ContributingThank you for being interested on making this package better. I encourage everyone to help improving this project with
some new features, bug fixes and performance issues.Need help?If you need help with GoAmazon Downloader, please open an issue with a description of the problem you're facing.LicenseMIT(c) 2020
Package: goastpy
GoAstPy - Python Wrapper for Go AST ParserGoAstPyis a Python wrapper for the built-in Go Abstract Syntax Tree (AST) parser. It allows you to parse and manipulate Go source code from within your Python applications. This package is perfect for developers working with Go code analysis, code generation, or automated refactoring tools in Python.🚀 Installationpipinstallgoastpy📚 Usageimportgoastpyif__name__=='__main__':code='''package mainimport "fmt"func main() {fmt.Println("Hello, World!")}'''parsed_code=goastpy.GoAst(code)print(parsed_code.ast)With GoAstPy, you can quickly and easily parse Go source code, extract information about its structure, and work with it in your Python projects.🛠️ Building the Go Shared Librarycd./goastpy
gobuild-ogoastparser.so-buildmode=c-sharedmain.gogoastparser_export.goThis command generates a shared library file (goastparser.so) that is used by the Python wrapper to interface with the Go AST parser.🔖 GitHub Tagsgolangpythonastgo-ast-parsercode-analysiscode-generationrefactoring📖 LicenseThis project is licensed under the MIT License.🌟 ContributingWe welcome contributions from the community! If you find a bug or have a feature request, pleaseopen an issueor submit apull request. Let's makeGoAstPyeven better together!
Package: goated
Goated Python LibraryA handy library to interacting with, sourcing information from and trading on the Goated Exchange.Creating an authenticated Client to interact with the API using email and passwordfrom goated.client import TradingClient

# Create a Goated Client Object to interact with the API
client = TradingClient.create_with_login(
    url = "https://api.goated.com",
    email = "YOUR_GOATED_EMAIL",
    password = "YOUR_GOATED_PASSWORD"
)Or using API Key and Secret (available from account tab)from goated.client import TradingClient

# Create a Goated Client Object to interact with the API
client = TradingClient.create_with_api_key(
    url = "https://api.goated.com",
    api_key = "YOUR_GOATED_API_KEY",
    api_secret = "YOUR_GOATED_API_SECRET"
)Creating a State container, sourcing and loading some user information into the container# Create a State Container object to hold relational state
state = Container()

# Get balances response from API
balances_response = client.get_balances()
# Add/update it within the state container
state.update_balances(balances_response)

# Get positions response from API
positions_response = client.get_positions() # Without any filters
# Add/update it within the state container
state.update_positions(positions_response)

# Get orders response from API
orders_response = client.get_orders() # Without any filters
# Add/update it within the state container
state.update_orders(orders_response)

print(state.__dict__)Sourcing information from the API# Get all categories
categories = client.get_categories()  # Without any filters

print('Categories:')
print(categories)

# Get subcategory record for first category
category_id = categories[0].get('id')
subcategories = client.get_subcategories(
    category_ids=[category_id]
) if category_id != None else []
print('Subcategories:')
print(subcategories)

# Get events in the first subcategory
subcategory_id = subcategories[0].get('id') if len(subcategories) > 0 else None
events = client.get_events(
    subcategory_ids=[subcategory_id]
) if subcategory_id != None else []
print('Events:')
print(events)

# Get all markets in the first event
event_id = events[0].get('id') if len(events) > 0 else None
markets = client.get_markets(
    event_id=[event_id]
) if event_id != None else []
print('Markets:')
print(markets)
Package: goatherd
Goat HerdPartially-observed visual reinforcement learning domain.Play YourselfYou can play the game yourself with an interactive window and keyboard input.
The mapping from keys to actions, health level, and inventory state are printed
to the terminal.# Install with GUIpip3install'goatherd[gui]'# Start the gamegoatherd# Alternative way to start the gamepython3-mgoatherd.run_guiThe following optional command line flags are available:FlagDefaultDescription--window <width> <height>800 800Window size in pixels, used as width and height.--fps <integer>5How many times to update the environment per second.--record <filename>.mp4NoneRecord a video of the trajectory.--num_cows3The number of cows in the environment.--view <width> <height>7 7The layout size in cells; determines view distance.--length <integer>NoneTime limit for the episode.--seed <integer>NoneDetermines world generation and creatures.Training AgentsInstallation:pip3 install -U goatherdThe environment follows theOpenAI Gyminterface:importgoatherdenv=goatherd.Env(seed=0)obs=env.reset()assertobs.shape==(64,64,3)done=Falsewhilenotdone:action=env.action_space.sample()obs,reward,done,info=env.step(action)Environment DetailsRewardA reward of +1 is given every time the player milks one of the cows.TerminationEpisodes terminate after 1000 steps.Observation SpaceEach observation is an RGB image that shows a local view of the world around
the player, as well as the inventory state of the agent.Action SpaceThe action space is categorical. Each action is an integer index representing
one of the possible actions:IntegerNameDescription0noopDo nothing.1move_leftWalk to the left.2move_rightWalk to the right.3move_upWalk upwards.4move_downWalk downwards.5doPick up a placed fence or milk a cow.6place_fencePlace a fence inventory.QuestionsPleaseopen an issueon Github.
Package: goatpie
GoatPie"GoatCounter" analytics for the CLI, written in Python - get it?InstallationIt's available fromPyPiusingpip:pip install goatpieGetting startedUsing this library is straightforward.CommandlinePretty much self-explanatory - otherwise,--helpis your friend:$ goatpie --help
Usage: goatpie [OPTIONS] URL

  Provides 'Goatcounter' statistics for URL

Options:
  -u, --update            Forces update of local database
  -l, --limit INTEGER     Shows visits & pageviews for the last XY days. Default: 14
  -b, --bar-colors TEXT   Defines two bar colors. Default: 'blue,magenta'
  -t, --text-colors TEXT  Defines three text colors. Default: 'blue,white,cyan'
  --version               Show the version and exit.
  --help                  Show this message and exit.PackageThe underlying module may also be used directly:fromgoatpieimportGoatPie# Initialize itobj=GoatPie(url,token)# Optionally with `data_dir` (SQLite database, config, etc)obj=GoatPie(url,token,data_dir)# Update database# (1) Last update not before one hour (in seconds)obj.update(3600)# (2) Force database updateobj.update(0)# Get pageviews as `pandas.DataFrame` (last seven days)print(obj.get_pageviews(7))#           Day  Pageviews# 0  2022-08-28          1# 1  2022-08-27         13# 2  2022-08-26         20# 3  2022-08-25         35# 4  2022-08-24         84# 5  2022-08-23         64# 6  2022-08-22         23ConfigurationBesides CLI options (seegoatpie --help) you may also configure various options inside~/.config/goatpie/config.inilike so:[DEFAULT]interval=3600step=100bar_colors=blue,magentatext_colors=blue,white,cyan[stats.example.com]interval=0# force updatesstep=1000# more visitorsbar_colors=yellow,red# hotter colorstext_colors=black,blue,black# better suited for light screensWhen first connecting to a 'GoatCounter' domain (such asstats.example.com), you are asked to store your token, in which case your configuration might look like this:[DEFAULT]interval=3600[stats.example.com]interval=0# force updatestoken=my-s3cr3t-t0k3n[stats.another-example.com]interval=1800# half hourtoken=my-0th3r-s3cr3t-t0k3nNote: Section headers are named after the GoatCounter API endpoints you are using, NOT the pages you are tracking!RoadmapAdd testsAdd more testsAdd loggerConfig fileExplain configuration
Package: goat-quantumcontrol
goat_quantumcontrolgoat_quantumcontrol is a python library for the optimization of quantum gates using the GOAT algorithm.The algorithm was developed in 2018 by Machnes et. al. and got published in the following paper:https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.120.150401InstallationUse the package managerpipto install goat_quantumcontrol.pipinstallgoat_quantumcontrolUsageimportgoat_quantumcontrolasQgoat#-----System parameters------# define the drift HamiltonianH0=sigmax# define the control HamiltonianHdrive=sigmaz# define the target gateUtarget=X_gate#-----Pulse parameters------# define the number of time intervalsn_ts=1000# define the evolution timeevo_time=3# define the number of ampsnum_of_amps=2#-----Optimization parameters--# define the number of maximal iterationsmax_iter=200# create an instance of the Pulse class to be usedfourier_pulse=Qgoat.FourierPulseWithEnvelope(n_ts=n_ts,evo_time=evo_time,num_of_amps=num_of_amps,window=None)# create an instance of the Optimizer classoptimizer=Qgoat.Optimizer(H0=H0,Hdrive=Hdrive,target=Utarget,pulse=fourier_pulse,max_iter=max_iter,printProgress=True)# run the optimizationoptimizer.run_optimization()ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.LicenseMIT
Package: gobang
A Gobang(also known as "Five in a Row" and "Gomoku") game equipped with AlphaGo-liked AI.FeaturesFriendly GUIMATCH RULES supportedEasy to installAlphaGo-liked AIGameAI PlayersGreedy AI: the POLICY network without randomnessProbabilistic AI: the POLICY network with randomnessThinking AI(xxx s): MCTS algorithm with POLICY and VALUE networksTo be implementedInstalldependenciesPython 3PyTorchinstall$pipinstallgobangRun$gobang# or$python-mgobangCommentsThis project was originally developed 2 years ago.The AI is developed based on Supervised Learning and Reinforcement learning.ReferencesRocAlphaGoMastering the game of Go with deep neural networks and tree search
Package: gobbet
gobbet - Random news articles in any languageWikinews is a wonderful free source of long-form text in a variety of world languages. gobbet provides you with access to words, sentences and paragraphs taken from Wikinews articles in any of its supported languages. This can be used as filler text for type specimens, web layouts, etc.Example usagefromgobbetimportget_news,unicode_rangeswords,headlines,paragraphs=get_news("el")# ISO language code# words is a Wordlist object; like Counter, but with a few more methodswords=(words.filter_popularity(2)# Only words which occur >=2 times.filter_length(5)# ... of five letters or more ....filter_unicodes(unicode_ranges["Greek"])# .. in Greek script)# Want to find some kerning pair words?bigrams=words.bigrams()# bigrams['οώ'] === {'προώθησε', 'προώθηση', 'προώθησης', 'προώρων'}# headlines and paragraphs are just lists, but...fromgobbetimportfilter_length,filter_unicodesrenderable=filter_unicodes(headlines,[font.getBestCmap().keys()])Licensegobbet was written by Simon Cozens. SeeLICENSEfor the terms of this library.Note that Wikinews text is provided under theCC-BY 2.5license, and your application must comply with the terms of that license in its use of the content.
Package: gobble
Simpler Parsing in Python.Usagefromgobbleimport*Basic parsers:@parserdefnatural():digits=yieldcharacter('0123456789').starreturnint(''.join(digits))Alternatives:@parserdefliteral_null():yieldliteral('NULL')returnNoneliteral=natural/literal_nullOptional elements:@parserdefnatural():sign=yieldcharacter('-+').option('+')factor={'-':-1,'+':1}[sign]value=yieldnaturalreturnvalue*factorSequencing with operators:whitespace=character('\n\r\t').starliteral_expr=literal<<whitespaceActually running a parser:value=literal_expr.execute(input_string)print(value)
Package: gobbler
gobblerA turkey-themed image catalog featuring over 99 hand-picked images to boost the holiday mood.InstallationpipinstallgobblerUsagePythonfromgobbleimportgobblegobble()gobble(99)Command lineusage: gobble [-h] [-n NUM]

A turkey-themed image catalog featuring over 99 hand-picked images to boost
the holiday mood.

optional arguments:
-h, --help         show this help message and exit
-n NUM, --num NUM  Specify image numberLicenseMIT ©Ray Sharma
Package: gobbletgobblers.py
バグ、不具合報告等はGitHubにてissueを開いてくださいUpdate info1.0.~1.0.1・バグ修正1.0.2・バグ修正1.1.~1.1.0・moveモードを使用した際turnがカウントされない問題を修正・勝者がでた場合はカウントを進めないように変更・PEP8に準拠(E501を除く)1.1.1・READMEのミスを修正1.1.2・READMEのミスを修正1.2.~1.2.0・gobb.winnerにwin_lineを追加・READMEを一部編集1.2.1・READMEのミスを修正1.3.~1.3.0・move操作によってかぶされていたゴブレットが姿を現し、それによって列が完成し、移動先でももう一人のプレイヤーの列が完成した場合、後者のプレイヤーの勝利になる可能性があった問題を修正例:before(赤大 無し 赤中青大 青中 赤大無し 無し 無し)after(赤大 赤大 赤中青大 青中 青中無し 無し 無し)この場合、本来は青の勝利だが、赤の勝利という判定になってしまう・READMEのミスを修正1.3.1上記で修正したとか言っといてできてなかったのでちゃんと修正1.3.2move後に列が完成しても判断されなかった不具合を修正installpip install -U gobbletgobblers.pyHow To UseCreate gamefromgobbletgobblersimportGobbletGobblersgobb=GobbletGobblers(FirstPlayer,SecondPlayer,EmptyBoardText)FirstPlayer - 先攻のプレイヤーSecondPlayer - 後攻のプレイヤーEmptyBoardText - 何も置かれていない場所に表示するテキストVariables meangobb.sen, gobb.kou先攻、後攻プレイヤーの情報が格納Attributesplayer - Create Gameの手順で設定されたプレイヤー情報gobbs - プレイヤーの所持している(新たに盤面に設置可能な)ゴブレットcolor - プレイヤーの色(Red / Blue)scolor - プレイヤーの色の略版(r / b) 基本的に内部でのみ使用modes - プレイヤーが選択できるモード(初期: ['p'])gobb.empty_board_textCreate Gameの手順で設定された文字列gobb.turn現在進行しているターン数gobb.now_player現在のプレイヤーAttributesplayer - Create Gameの手順で設定されたプレイヤー情報gobbs - プレイヤーの所持している(新たに盤面に設置可能な)ゴブレットcolor - プレイヤーの色(Red / Blue)scolor - プレイヤーの色の略版(r / b) 基本的に内部でのみ使用modes - プレイヤーが選択できるモード(初期: ['p'])gobb.won勝者が出たかどうかgobb.winner勝者Attributesplayer - Create Gameの手順で設定されたプレイヤー情報gobbs - プレイヤーの所持している(新たに盤面に設置可能な)ゴブレットcolor - プレイヤーの色(Red / Blue)scolor - プレイヤーの色の略版(r / b) 基本的に内部でのみ使用modes - プレイヤーが選択できるモード(初期: ['p'])wine_line - 勝利ラインgobb.board盤面情報gobb.board
├─a1
│  ├─ t
│  ├─ b
│  ├─ m
│  └─ s
├─a2
│  ├─ t
│  ├─ b
│  ├─ m
│  └─ s
├─a3
│  ├─ t
│  ├─ b
│  ├─ m
│  └─ s
.
.
.a1, a2, a3... - 盤面の座標+----+----+----+| a1 | a2 | a3 |+----+----+----+| b1 | b2 | b3 |+----+----+----+| c1 | c2 | c3 |+----+----+----+t - top その座標におけるもっとも大きいゴブレットb - big 一番大きいゴブレットm - meddle 普通サイズのゴブレットs - small 一番小さいゴブレットgobb.choices_putputモード時に設置可能な場所を返すchoices_put=gobb.choices_put()gobb.put指定の座標に指定のサイズのゴブレットを配置gobb.put(place,size)place - 配置する座標size - 配置するゴブレットのサイズgobb.choices_move_frommoveモード時に動かすことのできるゴブレットの座標を返すchoices_move_from=gobb.choices_move_from()gobb.choices_move_tomoveモード時に指定のゴブレットを移動させられる座標を返すchoices_move_to=gobb.choices_move_to(from)from - 移動前のゴブレットの座標gobb.moveゴブレットを移動させるgobb.move(from,to)from - 移動前のゴブレットの座標to - 移動後のゴブレットの座標