Saravanan666/pypi-org huggingface dataset:
Package: goldfinchsong
Easily automate image tweets.Main FeaturesReliable integration with twitter APISimpleEasy to extendRequirementsPython 3. Python 2 isnotsupported and there is no plan to support it.InstallUsepip:pip install goldfinchsongsongDocumentationYou can read the documentation on goldfinchsong’sRead The Docs page.ContributingThe Github repository is the issue tracker. Please submit issues here. Pull requests are appreciated.Please follow the Django Community Code of Conduct (https://www.djangoproject.com/conduct/) while
contributing togoldfinchsong.TestsUsepy.test. Make sure you have it installed. Clone thegoldfinchsongrepository.
From the top project directory, run:py.test testReleases0.1.42/4/16New: Image posting history is kept, avoiding repeats.0.1.31/10/16New: file logging.New: configure filename for file log ininifile.0.1.21/9/16setup.py patch0.1.11/9/16Documentation patch0.1.01/8/16Initial release
Package: goldhand
GoldhandThe ultimate python package to work with stock and crypto datapipinstallgoldhandTradingViewfromgoldhandimport*# tradingView datatw=Tw()# data frame of the stockstw.stock# data frame of the top 300 crypto currencytw.crypto# data frame of the top 3000 etftw.etf# Get a plot of the stock to see the location in the sectortw.get_sec_plot('AMD').show()# Get a plot of the stock to see the location in the industrytw.get_sec_plot('AMD').show()Goldhand classTheGoldHandclass is a part of thegoldhandPython package, which provides functionality for working with stock and crypto data. This class allows users to retrieve detailed information and charts for a specific stock.# Get a detailed chart of a stock AMDticker="AMD"t=GoldHand(ticker)t.df.tail().T# Get a detailed chart of a stock AMDticker="TSLA"t=GoldHand(ticker)t.plotly_last_year(tw.get_plotly_title(ticker)).show()## Stock Chart# Get a detailed chart of a cryptoticker="BTC-USD"t=GoldHand(ticker)t.plotly_last_year(tw.get_plotly_title(ticker)).show()GoldHand Line indicatorticker="TSLA"t=GoldHand(ticker)t.plot_goldhand_line(tw.get_plotly_title(ticker)).show()BacktestThe Backtest class is a powerful tool for evaluating the performance of trading strategies using historical data. It allows you to simulate trades and calculate various performance metrics to assess the profitability and risk of your strategy.It takes a data and a function and display the trades.ticker='TSLA'data=GoldHand(ticker).dfbacktest=Backtest(data,rsi_strategy,plot_title=tw.get_plotly_title(ticker),buy_threshold=30,sell_threshold=70)backtest.summarize_strategy()summarize_strategywill  show the trades summary, a plot with trades and the trades in DataFrame.StrategysRSI Strategy"""RSI strategy for backtesting with Backtest classParameters:- data: pandas DataFrame with columns: date, open, high, low, close, volume and rsi- buy_threshold: int, default 30,  buy when RSI is below this value- sell_threshold: int, default 70, sell when RSI is above this value"""backtest=Backtest(data,rsi_strategy,plot_title=tw.get_plotly_title(ticker),buy_threshold=30,sell_threshold=70)ticker='TSLA'p=show_indicator_rsi_strategy(ticker=ticker,buy_threshold=30,sell_threshold=70,plot_title=tw.get_plotly_title(ticker),add_strategy_summary=True)GoldHand Line indicator"""This function implements the GoldHandLine strategy.Parameters:- data (pandas DataFrame) : The DataFrame containing the data.- buy_at (str): The color of the line to buy at. Default is 'gold'.- sell_at (str): The color of the line to sell at. Default is 'grey'."""backtest=Backtest(data,goldhand_line_strategy,)ticker='BTC-USD'show_indicator_goldhand_line_strategy(ticker=ticker,plot_title=tw.get_plotly_title(ticker),buy_at='gold',sell_at='blue',add_strategy_summary=True)
Package: goldieseeker
goldieseekerA command-line tool for generating and analyzing strategies for Goldie Seeking in Salmon Run.Map IDs:ap - Ark Polarislo - Lost Outpostmb - Marooner's Baysg - Spawning Groundsss - Salmonid SmokeyardHow to UseYou can install goldieseeker with pip using the commandpip install goldieseeker, then rungseek -m [map_id]using one of the above map IDs. Rungseek --helpto see all the other options and features. For more customization, you can edit the files in thegoldieseeker/mapsfolder. (This should be located wherever you installed the package.)Requires Python 3.6 or higher.More extensive documentation coming soon... hopefully?FormattingStrategies are notated in the form "a(b, c)": open A, go to B if A is high, go to C if A is lowIf a gusher is starred (e.g. a*), the Goldie will never be found in that gusherAcknowledgementsThanks to Deelatch and RR for help with search algorithmThanks to the Salmon Run server for feedback on features and UIMap images fromSalmon Learn
Package: gold-miner
About gold-minerThegold-minertool suite applies a simple statistical analysis of
labeled traffic samples to produce a profile which can then be used to
fingerprint an unknown traffic sample with a goal of rapidly
identifying its contents without requiring deep packet inspection.
Specifically,gold-mineris designed to prioritize calculation speed
over higher levels of accuracy that more complex analysis techniques
may produce.DocumentationSee thedocumentationfor full details about how toinstallandusethe gold-miner package(s).See alsoThegold-miner-uipackage contains add-on modules which require a
more extensive list of python pre-requisites but contain more powerful
tools, such asgold-miner-tande.
Package: goldpirate
Gold PirateWhy join the Navy if you can be a Pirate?Python script to download torrent from the Internet.InstallationThe package can be downloaded directly fromPyPi.pipinstallgoldpirateSetup QBitTorrentIn order to download torrent, you need QBitTorrent.Download and installQBitTorrentGo toSettings>WEB UICheckWeb UI interfaceSet port to8080CheckBypass authentication for clients on localhostExampleYou can see the help,-h, man to know all the possibile commands.goldpirate-q"The Matrix"goldpirate-q"Harry Potter"-sageSupported Sites1337xLimeTorrentsTorLockTorrentDownloadsIlCorsaroNero
Package: gold-python
GOLD-PythonGOLD-Python is a port of the GOLD programming language's Finite Automata features to Python 3.10 for a better developer experience.How to installpipinstallgold-pythonUsing the library:defmain():automaton=createAutomaton()print(automaton.acceptsInput(input("Enter: ")))automaton.show()defcreateAutomaton():Q=product(between(0,7),between(0,1))E="01"Q0=(0,0)F=[(0,0)]returnDeterministicAutomata(Q,E,Q0,F,delta)@deltafuncdefdelta(x,y,next):d=int(next)if(x,y)==(0,1):return(0,1)elifx==7:return(0,0)if(d-y==0)else(0,1)else:return(x+1,(y+d)%2)if__name__=="__main__":main()Features:Better Syntax AutocompletionSupport for typesDocstrings for most functionsDocumentation in HTML (work in progress)Progress:Deterministic Finite State AutomataDeterministic Transducer (Mealey)Basic Set Operations (Between, Product)Non-Deterministic Finite State AutomataPushdown AutomataAdvanced Set Operations (String ranges, Parts of sets, etc)GUI Interface to show AutomataFull documentation in Sphinx (Progress: 0%)Release
Package: goldretriever
🐕 Gold RetrieverPowered byJinaandDocArrayEasily empower ChatGPT to store and analyze your data usinggoldretriever, a powerful command-line tool for creating and hosting retrieval plugins in just a few simple steps.🎬 Showcase: Real-world Plugin CreationsPersonal Study Assistant -Blog|Video⚡ Quick Start📦 InstallationEnsure you have Python 3.8 or later.Install the tool via pip:pipinstallgoldretriever🚀 DeploymentRun the following command to deploy the plugin:goldretrieverdeploy--key<youropenaikey>Store the "Gateway (Http)" URL and the Bearer token provided in the output.╭────────────────────────🎉Flowisavailable!────────────────────────╮
││
│IDretrieval-plugin-<pluginid>│
│Gateway(Http)https://retrieval-plugin-<pluginid>.wolf.jina.ai│
│Dashboardhttps://dashboard.wolf.jina.ai/flow/<pluginid>│
││
╰───────────────────────────────────────────────────────────────────────╯
Bearertoken:<yourbearertoken>📚 Data IndexingGather relevant text data files (PDF, TXT, DOCX, PPTX, or MD) in a directory.Index the data:goldretrieverindex--datamy_filesOr, usedocarray (v0.21.0)for text data:fromdocarrayimportDocument,DocumentArraytexts=['Text 1','Text 2','Text 3']docs=DocumentArray([Document(text=text)fortextintexts])docs.save_binary('docs.bin')And then:goldretrieverindex--datadocs.bin🔗 IntegrationGo to OpenAI Plugins.Select "Develop your own plugin".Enter the "Gateway (Http)" URL and Bearer token from the deployment step.🎛️ Advanced Usage🛠️ ConfigurationTo tailor the plugin to your needs, change the name and description during deployment:goldretrieverdeploy--key<youropenaikey>--name"Custom Name"--description"Custom description"If not specified, default values will be used.ArgumentDescriptionDefault ValuenameHuman-readable name, such as the full company nameGold RetrieverdescriptionDescription better tailored to the model, such as token context length considerations or keyword usage for improved plugin promptingPlugin for searching through the user's documents (such as files, emails, and more) to find answers to questions and retrieve relevant information. Use it whenever a user asks something that might be found in their personal information📋 Listing PluginsList your plugins and their status:goldretrieverlistOutput:PluginID:ece735568f|Status:Serving🗑️ Deleting PluginsDelete a plugin:goldretrieverdelete<pluginid>🔍 Indexing Specific PluginsIndex data for a specific plugin:goldretrieverindex--datamy_files--id<plugin_id>If the plugin ID is not specified, the last created plugin will be indexed.🎓 AcknowledgementsThis project is built upon the open-sourcechatgpt-retrieval-pluginrepository developed by OpenAI.
Package: goldsrcmap
goldsrcmapPython library to manipulate goldsrc engine .map fileswork in progress...Usagehttps://github.com/G2Pavon/goldsrcmap/wikiLoad map:#../Mapping/Scripting/example1.pyimportgoldsrcmapasgsm# Load .map filem=gsm.load_map('Mapping/maps/file.map')forentityinm.entities:ifentity.classname=='func_door':# classname @propertyforbrushinentity.brushes:brush.rotate_z(45)ifentity.properties['classname']=='func_wall':# using properties attributeforbrushinentity:# alternative syntax without using brushes @propertybrush.move_by(256,256,64)ifentity['classname']=='func_plat':# without using properties attributeforbrushinentity:brush.move_to(32,32,256,centroid=True)# more logic here# Save the edited map in /Scripting/ foldergsm.save_map(m,'edited.map')Create from scratch:#../Mapping/Scripting/example2.pyimportgoldsrcmapasgsmm=gsm.new_map()# Edit worldspawn propertiesm.worldspawn.properties['wad']='path/to/zhlt.wad; path/to/other.wad'# get worldspawn entity directly with @propertym.worldspawn['skyname']='nebula'# alternative way to add entity property without using properties attribute# Create brushesskybox_room=gsm.BrushGenerator.room(2048,2048,2048,16,[0,0,0],center=True)floor=gsm.BrushGenerator.cuboid(512,512,32,[0,0,-128],texture="grass")# Create entitiesplayer=gsm.EntityGenerator.info_player_start([0,0,0])light=gsm.EntityGenerator.light_environment([0,0,1024],angle=180,pitch=-70)# append brush and entities in mapm.add_brush(skybox_room,floor)# adding individually or as a list also works add_brush([skybox_room, floor])m.add_entity(player,light)# same herebutton=Entity()button.add_brush(gsm.BrushGenerator.cuboid(16,16,48,[82,82,0],texture="black"))button.properties={"classname":"func_button","spawnflags":"1","speed":"5","lip":"0","wait":"2","delay":"0","target":"counter_off","master":"stopsource","targetname":"counter_stop_button"}m.add_entity(button)# Save the new map in cstrikegsm.save_map(m,'cstrike/maps/generated.map')
Package: goless
golessUsing thegolesslibrary, you can writeGolanguage
style concurrent programs in Python.golessprovides functionality for channels, select, and goroutines.golessallows you to use Go’s beautiful and elegant
concurrency programming model,
but in the familiar and comfortable language of Python.goless works on top ofgevent,PyPy, orStackless Python.
It works with PyPy, CPython, and Stackless Python interpreters,
and Python 2.6 to 3.4.golesshas extensivetesting,documentationandexamples.
Seehttps://goless.readthedocs.org/for more information.
Package: golf-federated
Generic and Open Learning FederatorA scalable, portable, and lightweight Federated Learning framework.Free software: MIT licenseDocumentation:https://generic-and-open-learning-federator.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2022-11-28)First release on PyPI.
Package: golfir
golfir: Great Observatories Legacy Fields IR Analysis ToolsThis repository provides tools for modeling Spitzer IRAC and MIPS images based on high resolution templates from existing Hubble imaging in the context of the CHArGE / GOLF project (Brammer, Stefanon et al.).Requirements:grizli (https://github.com/gbrammer/grizli)
skimage
astropy
drizzlepac
photutils
...Installation:$pipinstallgolfir$gitclonegit@github.com:gbrammer/golfir.git$cdgolfir$pipinstall.-rrequirements.txtUsage:See the examples in thenotebookssubdirectory:IRAC-mosaic.ipynb- Generate drizzled IRAC mosaics and PSFs from individual SpitzerBCDexposure files.IRAC-photometry.ipynb- Extract Spitzer photometry using HST template images similar to Mophongo (Labb'e et al.), T-PHOT (Merlin et al.), etc.
Package: golfprofile
PyPi:https://pypi.org/project/golfprofile/สวัสดีจ้า package นี้อธิบายโปรไฟล์ของนาย golf
และสามารถนำไปใช้กับผู้อื่นได้วิธีติดตั้งเปิด CMD / Terminalpipinstallgolfprofileวิธีใช้งานแพ็คเพจนี้เปิด IDLE ขึ้นมาแล้วพิมพ์…my=Profile('loong')my.company='uncle-engineer'my.hobby=['youtuber','sleeping']print(my.name)my.show_email()my.show_myart()my.show_hobby()พัฒนาโดย: RashawatCoding
Package: golftracker
Table of ContentsIntroductionPurpose of the package.InstallationIf you wish to use the package.DevelopmentIf you wish to change the source code and enhance the package.IntroductionThe package provides various scripts to process a golf swing video and export the information to another package "GolfCoach" for analysis. The output feedback can then be used to improve the swing.The package uses Google media pipe for detecting the golfer. It then detects the club head in the video and the golf poses to detect the start and finish of the golf swing. This information in written out to a json file that can be analyzed by a separate packge "GolfCoach" for analysis.This is shown belowSome sample vides for down the line, right hand golfer is available onGoogleDriveEach video example has 3 files.Video filePickle database that is the result of running the scripts below.Json file for exporting to GolfCoach packgeThe general sequence of steps for a video say "0001.mov"Create Swing DatabaseThis step runs google media pipe and stores all the landmarks. It will also try to detect the golf poses and club head position. Current version usually fails on this and requires hand labellling.create_swing_db 00001.movHand Label GolfPosesRun the script below to label the golf poses. The golf pose consist ofStart Pose:Top Pose: Indicates that the backswing is now complete.Finish Pose: Indicates that the swing is complete.label_golf_poses 00001.pklHand Label Club Head PositionLabel the club head in some of the frames. The script will then use a linear approx to fill the position in the remaining frames.label_club_head 00001.pklExport To JsonExport the information to a json file for analysis by the GolfCoach package.dump_swing_db 00001.pklStatusWIP: Detailed src documentation of this package is onReadTheDocsStatusThe current steps are listed hereGolfSwingCaptureInitial thoughts on swing analysis are hereGolfSwingAnalysis
Package: golftrainer
IntrodctionThis package provides a utility for analyzing a golf swing. The input data is represented as a json file
generated byGolfTracker.The json file structure is represented by a data class "GolfData". A factory method is used to create it from the json filename.The structure of theGolfDataclass is shown below.InstallationInstall the package in your virtual env.pip install golftrainerDemoFor this purpose we will usedata/demo.jsonas an example. This file is same as "00001.json" from the below google drive.Setup Jupyter NotebookTo make the notebook run under my virtual env (say 'venv'), follow the following steps.pip install jupyterOr for existing install create a new kernel.ipython kernel install --user --name=venvcd notebooks/demo

jupyter notebook demo1.ipynbOnce we have the notebook the following commands we can use the GolfData object to access the parameters.Generated DataVarious sample golf swing videos shot down the line on a right handed golf player with the corresponding json file are stored in thisGoogleDrive. Each video file (either a mp4 or mov) has 2 output files. The ".pkl" is the pickle database and ".json" is the file that we will use for this package to measure the various metrics associated with the swing.
Package: goli
goliA sophisticated boilerplate generator based on best practices and modern useful templatesNOTE:The project is heavily inspired by cookiecutter and aim to make a good collection of modern boilerplate templates that proven useful in the last years.Why another boilerplate generator?I like the cookiecutter package and I have been using it for years now. However, the field is changing too fast and many cookiecutter templates that I have been using are now outdated. So I find myself always searching for new templates and wasting time by searching on google, github etc.. for modern templates based on best practices (like which package to use for testing, format etc..)Hence, I wanted to create this simple tool, where I integrated all useful templates that have proven useful in the last years and which follow best practices in the field.Please note that goli is not only for python. It can be used with other languages too and I'm planning to add other features in the future.Installationpipinstall-Ugolior install withPoetrypoetryaddgoliThen you can rungoli --helpto show the help message on how to use the packageUsage:goli[OPTIONS]COMMAND[ARGS]...

Options:--helpShowthismessageandexit.

Commands:languagesShowallsupportedprogramminglanguagesnewGeneratenewboilerplatecodeforyourprojecttopicsShowallsupportedtopics.As you can see, goli provides three commands. The languages and topics commands are additional to get more information about how to use the package. The new command is the most important and it is used to start a new project. More on that in the next section.Usagegoli provides the new command, which is used to create a new boilerplate depending on two optional parameters that you need to provide.Thelanguageparameter, which indicates the programming language you want to use or you will use for your project. You can check supported languages if you rungoli languagesThetopicparameter, which should indicate the topic of your project. You can check the topics supported by goli if you rungoli topicsFor example, here is what my command will look like if I'm starting a data science project using pythongolinew--languagepython--topicdata-scienceor the short versiongolinew-lpython-tdata-scienceThis will pull the modern cookiecutter-data-science template (https://github.com/drivendata/cookiecutter-data-science) and execute it in your current working directory. So you don't have to search for templates since best practices are already built-in and being updated regularly.FAQI want to add a useful template that I didn't find in goliIf you want to contribute and add templates, just go togoli/cookiecutters.py, add your template as a class member variable and finally add it in the repos dictionary under the corresponding language and topic.
Package: goliath
GoliathAuthorsLogan Pulley, Zachary Oldham, Ilie Vartic, Deepan Venkatesh, Manikandan SwaminathanAbstractThis package enables Python to offload sets of function calls to pools of remote worker processes.DetailsWhen handling large sets of data, the thread-pool model can often do wonders for parallelizing and thus speeding up a program. However, Python's native support for concurrency is more likepollingthanthreading; it doesn't properly take advantage of multiple CPU cores. This can be frustrating when working in Python with a task that would be easily threadable in other languages.Goliath enables Python to distribute a set of function calls over a set of servers. This essentially simulates the thread-pool model as a pool of servers, each maintaining a pool of Python worker processes. Additionally, these servers can be reached over the Internet, enabling a many-to-many relationship between clients requesting work and servers providing workers; each client can have work distributed across multiple servers, and each server can handle work from multiple clients.Goliath abstracts this entire model and aggregates the results from the servers, finally returning the list of results to the coder.RequirementsPython 3.7+InstallationInstall withpip:pip install goliathUsageSending work (Commander)# foo.pyfromgoliath.commanderimportCommander# The function to executedeffoo(bar,baz):returnstr(bar)+str(baz)# Function to generate list of arguments to trydeffoo_args(bar_range,baz_range):forbarinbar_range:forbazinbaz_range:yield{'bar':bar,'baz':baz}if__name__=='__main__':# Create a commander (doesn't connect yet)cmdr=Commander([# Lieutenants can be hostnames, domains, IPs('lieutenant-hostname',8080),('lieutenant.com',3333),('127.0.0.1',2222)])# Connect to lieutenants, run all the functions, and get resultsresults=cmdr.run(foo,list(foo_args(range(10),range(10))),['foo.py'])Performing work (Lieutenant & Worker)To run a lieutenant on this machine on port 3333 with 8 worker processes:python3 -m goliath.lieutenant localhost 3333 8LicensingGoliath is open-source software, licensed under GNU's Lesser GPL.
Package: golib
golibWhat is this?by: axinergolibThis is a golib.InstallationThis package can be installed using pip (Python3):pip install golibCopyrightCopyright (c) 2022 axinerPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.