Saravanan666/pypi-org huggingface dataset:
Package: giftless
Giftless - a Pluggable Git LFS ServerGiftless a Python implementation of aGit LFSServer. It is designed
with flexibility in mind, to allow pluggable storage backends, transfer
methods and authentication methods.Giftless supports thebasicGit LFS transfer mode with the following
storage backends:Local storageGoogle Cloud StorageAzure Blob Storagewith direct-to-cloud or streamed transfersAmazon S3 StorageIn addition, Giftless implements a custom transfer mode calledmultipart-basic,
which is designed to take advantage of many vendors' multipart upload
capabilities. It requires a specialized Git LFS client to use, and is currently
not supported by standard Git LFS.See thegiftless-clientproject
for a compatible Python Git LFS client.Additional transfer modes and storage backends could easily be added and
configured.DocumentationInstallation GuideGetting StartedFull DocumentationDeveloper GuideLicenseCopyright (C) 2020, Datopian / Viderum, Inc.Giftless is free / open source software and is distributed under the terms of
the MIT license. SeeLICENSEfor details.
Package: giftless-client
Giftless ClientA Git LFS client library implemented in Python, compatible with Git LFS servers in general and specificallyGiftless Git LFS server.giftless-clientis tested on Python 2.7 and 3.6+.InstallationYou can install this library directly from pypi:(venv)$pipinstallgiftless-clientAPIThis module exposes one main class:LfsClient. Typically, you only need to use this class to perform most Git LFS operations. The client provides both a wrapper around the low-level LFS API commands e.g.batchas well as higher level methods to upload and download files.Instantiating a Clientfromgiftless_clientimportLfsClientclient=LfsClient(lfs_server_url='https://git-lfs.example.com',# Git LFS server URLauth_token='somer4nd0mT0ken==',# Bearer token if required by the server (optional)transfer_adapters=['basic']# Enabled transfer adapters (optional))Thetransfer_adaptersparameter is optional, and represents a list of supported transfer adapters by priority
to negotiate with the server; Typically, there is no reason to provide this parameter.Downloading a File from LFS storageDownload a file and save it to file like object.download(file_obj,object_sha256,object_size,organization,repo,**extras)file_objis expected to be an file-like object open for writing in binary modeobject_sha256: sha256 of the object you wish to downloadobject_size: size of the object you wish to downloadorganization,repo: used to generate the prefix for the batch request in formorganization/repoextrasare added to the batch request attributes dict prefixed withx-. This is largely Giftless specific.Note that the download itself is performed by the selectedTransfer Adapter.Uploading a File to LFS storageUpload a file to LFS storageupload(file_obj, organization, repo, **extras)file_obj: a readable, seekable file-like objectOther arguments as per downloadNote that the upload itself is performed by the selectedTransfer Adapter.Sending an LFSbatchAPI requestSend abatchrequestto the LFS server:batch(prefix, operation, objects, ref=None, transfers=None)prefix: add to LFS server url e.g. ifprefix=abcand client was created with server url ofhttps://git-lfs.example.comthen batch request is made by POST tohttps://git-lfs.example.com/abc/objects/batchAll other arguments: seebatch commandfor definitionsExample:client.batch(
  prefix='myorg/myrepo',
  operation='download',
  objects={
      "oid": "12345678",
      "size": 123
    }
)Usage in Command LineWhile the main use forgiftless-clientis as a client library for other projects, this module does include some
command line functionality.Run the following command to get more information:(venv)$giftless-client--helpLicenseGiftless Client is free software distributed under the terms of the MIT license. SeeLICENSEfor details.Giftless Client is (c) 2020 Datopian / Viderum Inc.
Package: giftmaster
giftmasterAdd a short description here!A longer description of your project goes here…Making Changes & ContributingThis project usespre-commit, please make sure to install it before making any
changes:pip install pre-commit
cd giftmaster
pre-commit installIt is a good idea to update the hooks to the latest version:pre-commit autoupdateDon’t forget to tell your contributors to also install and use pre-commit.NoteThis project has been set up using PyScaffold 4.1.4. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.
Package: giftpack
giftpackCommandsaddgiftAggiungi un nuovo regalo al pool.Aliases:newgiftdelgiftElimina dal database il regalo con l'id specificato.getgiftEstrai un regalo qualsiasi.Aliases:drawgiftgetgiftdstEstrai un regalo con un certo destinatario.Aliases:drawgiftdstgetgiftidEstrai un regalo con un certo id.Aliases:drawgiftidgetgiftsrcEstrai un regalo con un certo mittente.Aliases:drawgiftsrclistgiftsElenca tutti i regali registrati.Aliases:listgiftEventsPage StarsException StarsTablesxmasgifts
Package: gifu
O gifu é programa que pode ser usado como auxilio no estudo de outros idiomas, você pode pegar o texto no idioma desejado e começar a ler, as palavras que vçê não consegui ler, você adiciona o caractere@e ele vai da a tradução logo abaixo. ao aperta no botãocriar ankivocê gera um arquivo.txt com as palavras estudadas. e depois é só ir no aplicativo doANKIe importar.InstalaçãoPara instalar, use o pip3 com o pacote “gifu”.$pip3installgifu
Package: gify-plot
gify_plotA simple Python package to turn your plots into gifs (Matplotlib, Seabron, Plotly).This is the output of the example provided in "How to use it".How to install itpip install gify_plotHow to use it# WARNING:

# Using more than 5/7 categories ends with a cluttered result.
# The fewer, the better.

# The following csv can be freely downlaoded at https://www.kaggle.com/datasets/sazidthe1/world-gdp-data?select=gdp_data.csv

df=pd.read_csv("gdp_data.csv")
temp_df=df[(df["country_name"].isin(["Italy","Spain","France","Germany"]))]
gify_plot(temp_df,
           plot_type="line", plot_library="px", name="test_output",
           plot_title="GDP per country", xaxis_title="year", yaxis_title="value", category="country_code",
           save_frames=False
          )OUTPUT: It ouputs a list of png in the dedicated folder, along with the resulting gif.ArgsMandatoryoriginal_df:pd.DataFrame ==> a dataset containing at least three columns:xaxis_title (i.e., an int in YYYY format OR strings in 'YYYY-MM-DD' format ;a range >= 20 years is suggested)yaxis_title (i.e., a list of int or float )category (i.e., categorical variables, n groups <=7 suggested)plot_type:str ==> The plot_type changes according to plot_libraryplot_library:str ==> plt | sns | px  (short forms for matplotlib.pyplot, seaborn and plotly.express)name:str ==> The name of pngs and gif given as output,plot_title:strxaxis_title:str ==> The name of the column with x valuesyaxis_title:str ==> The name of the column with y valuesOptionalcolors= ["blue","red","green","orange","violet","yellow","black","brown","cyan"] ==> it must have at least the same length of groups provided in the dataduration= 100 ==> The delay in skipping to the next frame in msloop= 0save_frames= True ==> If False, delete all png files that have been used to create the gifsort_on_x= Truetick_interval= it scales across x values, default 7.Supported libraries and plots:plt(i.e., matplotlib.pyplot):linebarscatterstackplot (no legend)sns(i.e., seaborn):lineplotscatterplotbarplotpx(i.e., plotly.express):linescatterareabar
Package: gig
gigA CLI to create .gitignore files, to keep your source control so fresh and clean.Install/Upgrade$ pip install -U gigOr, run it withpipx:$ pipx run gig --helpUsageIn the shell. . .$ gig Python Ruby > .gitignoreOr, programmatically, in Python. . .>>>importgig>>>gig.generate_gitignore(["Clojure"])u'\n### Clojure ###\nLeiningen.gitignore'You can also generate global.gitignore_globalfiles. For more info, seehere.$ gig macOS VisualStudioCode --global > ~/.gitignore_globalTo get a list of available templates. . .$ gig list
$ gig list --globalFor more help, rungig --help.RequirementsPython >= 3.8Internet connectionLicenseMIT Licensed.Changelog1.2.0 (2024-01-10)Support Python 3.8-Python 3.12. Older versions no longer supported.1.1.0 (2019-06-30)Add--no-header.1.0.0 (2019-06-27)Write tostdout.Only Python>=3.6 is supported.0.2.0 (2013-09-09)Add support for global gitignore files.0.1.0 (2013-09-07)First release.
Package: gigaanalysis
gigaanalysisversion 0.4.3This library provides a collection of classes and functions for analysing
datasets which are of the from of one independent and one dependent
variable. This is very common in condensed mater physics experiment and
gigaanalysis was produced for use in high magnetic field facilities.Documentation:https://gigaanalysis.readthedocs.io/en/latest/LayoutIt broken into a collection of modules for different usesdata- This contains the Data class which gigaanalysis is built around. It
also contains a few functions for common manipulations.mfunc- This contains mathematical functions that are useful to manipulate
data objects. This is broken into four sections applying numpy ufuncs,
making Data objects, performing FFTs, and transforming Data objects.dset- For saving, loading, and manipulating collections of Data objects which are referred to datasets.fit- For fitting forms to the data contained in Data objects.parse- Contains functions for collecting all the data contained in
datasets together, or distribution of data into Data objects.qo- Functions and classes for analysing quantum osculations
experiments.contour- Class for producing contour maps from a data set, using
Gaussian processes.htsc- Functions which are useful for studying superconductivity.magnetism- Functions for studying magnetism.heatc- Functions for studying heat capacity of materials.diglock- An implementation of a digital lock in.highfield- A class for processing the data from pulsed magnetic field
facilities.const- A few useful scientific constants in different systems of units.RequirementsThis was developed mostly usingpython 3.7.7numpy 1.21.2pandas 1.3.4matplotlib 3.4.3h5py 2.10.0I haven't found any problems with using newer versions of these same
dependencies.
Package: gigachain-community
🦜️🧑‍🤝‍🧑 LangChain CommunityQuick Installpipinstalllangchain-communityWhat is it?LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application.For full documentation see theAPI reference.📕 Releases & Versioninglangchain-communityis currently on version0.0.xAll changes will be accompanied by a patch version increase.💁 ContributingAs an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.For detailed information on how to contribute, see theContributing Guide.
Package: gigachain-experimental
🦜️🧪 GigaChain ExperimentalThis package holds experimental GigaChain code, intended for research and experimental
uses.[!WARNING]
Portions of the code in this package may be dangerous if not properly deployed
in a sandboxed environment. Please be wary of deploying experimental code
to production unless you've taken appropriate precautions and
have already discussed it with your security team.Some of the code here may be marked with security notices. However,
given the exploratory and experimental nature of the code in this package,
the lack of a security notice on a piece of code does not mean that
the code in question does not require additional security considerations
in order to be safe to use.
Package: gigachain-openai
langchain-openaiThis package contains the LangChain integrations for OpenAI through theiropenaiSDK.Installation and SetupInstall the LangChain partner packagepipinstalllangchain-openaiGet an OpenAI api key and set it as an environment variable (OPENAI_API_KEY)LLMSee ausage example.fromlangchain_openaiimportOpenAIIf you are using a model hosted onAzure, you should use different wrapper for that:fromlangchain_openaiimportAzureOpenAIFor a more detailed walkthrough of theAzurewrapper, seehereChat modelSee ausage example.fromlangchain_openaiimportChatOpenAIIf you are using a model hosted onAzure, you should use different wrapper for that:fromlangchain_openaiimportAzureChatOpenAIFor a more detailed walkthrough of theAzurewrapper, seehereText Embedding ModelSee ausage examplefromlangchain_openaiimportOpenAIEmbeddingsIf you are using a model hosted onAzure, you should use different wrapper for that:fromlangchain_openaiimportAzureOpenAIEmbeddingsFor a more detailed walkthrough of theAzurewrapper, seehere
Package: gigafile
gfileA python CLI/module to download and upload fromgigafile.Note: PyPI package name isgigafilesincegfileisn't available. Both CLI and module name are stillgfile.A major update fromthe original. Highlights:Fixed multi-thread uploading (and made sure each threads finish in order so the final file is not broken)Fixed download filename issueSome refactoring and QoL changes.Install$ pip install -U gigafileor$ pip install -U git+https://github.com/fireattack/gfile.gitUsageCLI$gfileuploadpath/to/file

$gfiledownloadhttps://66.gigafile.nu/0320-b36ec21d4a56b143537e12df7388a5367

$gfile-h
usage:Gfile[-h][-p][-oOUTPUT][--aria2[ARIA2]][-nTHREAD_NUM][-sCHUNK_SIZE][-mCHUNK_COPY_SIZE][-tTIMEOUT]{download,upload}uri

positionalarguments:{download,upload}uploadordownloadurifilenametouploadorurltodownload

options:-h,--helpshowthishelpmessageandexit-p,--hide-progresshideprogressbar-oOUTPUT,--outputOUTPUToutputfilenamefordownload(default:useoriginalname)--aria2[ARIA2]downloadwitharia2.Youcanalsospecifyoptionalarguments(default:"-x10 -s10",makesuretoquote).`-o`isalreadyautomaticallyincluded.-nTHREAD_NUM,--thread-numTHREAD_NUMnumberofthreadsusedforupload[default:8]-sCHUNK_SIZE,--chunk-sizeCHUNK_SIZEchunksizeperuploadinbytes;note:chunk_size*threadwillbeloadedintomemory[default:100MB]-mCHUNK_COPY_SIZE,--copy-sizeCHUNK_COPY_SIZEspecifiessizetocopythemainfileintopieces[default:1MB]-tTIMEOUT,--timeoutTIMEOUTspecifiestimeouttime(inseconds)[default:10]ModuleImportfromgfileimportGFileDownloadfilename=GFile('https://XX.gigafile.nu/YYY').download()Uploadurl=GFile('path/to/file',progress=True).upload().get_download_page()
Package: gigalens
Gradient Informed, GPU Accelerated Lens modelling (GIGA-Lens) is a package for fast Bayesian inference on strong
gravitational lenses. For details, please seeour paper. Seeherefor our documentation.UsageInstallationGIGA-Lenscan be installed via pip:pip install gigalensIf pip notes an error after installation about conflicting dependencies, these can usually be safely ignored.
If you wish to test the installation, tests can be run simply by runningtoxin the root directory.If you don’t have access to institutional GPUs, one easy way is to use GPU on Google Colab.  Please remember the
very first cell should have!pip install gigalens. If you do have access to institutional GPUs, you can set up a
notebook to run on GPU.  For example, atNESRC, you can choose the kerneltensorflow-2.6.0, and include in the first cell:!pip install gigalens.RequirementsThe following packages are requirements for GIGA-Lens. However,!pip install gigalensis all you need to do. In fact,
separately installing other packages can cause issues with subpackage dependencies. Some users may find it necessary
to install PyYAML.tensorflow>=2.6.0
tensorflow-probability>=0.15.0
lenstronomy==1.9.3
scikit-image==0.18.2
tqdm==4.62.0The following dependencies are required bylenstronomy:cosmohammer==0.6.1
schwimmbad==0.3.2
dynesty==1.1
corner==2.2.1
mpmath==1.2.1AuthorsGIGALenswas written byAndi Gu.
Package: gigapixel
GigapixelTopaz Gigapixel AI automation toolRequirements•Installation•Usage•Contributing•LicenseRequirementsTopaz Gigapixel AIv6.1.0ornewerrequiredInstallationInstall the current version withPyPIpipinstall-UgigapixelUsageCreateGigapixelinstanceUse.process()method to enhance imagefromgigapixelimportGigapixel,Scale,Mode,OutputFormatfrompathlibimportPath# Path to Gigapixel executable file.exe_path=Path('C:\Program Files\Topaz Labs LLC\Topaz Gigapixel AI\Topaz Gigapixel AI.exe')# Output file suffix. (e.g. pic.jpg -> pic-gigapixel.jpg)# You should set same value inside Gigapixel (File -> Preferences -> Default filename suffix).output_suffix='-gigapixel'# Create Gigapixel instance.app=Gigapixel(exe_path,output_suffix)# Process image.image=Path('path/to/image.jpg')output_path=app.process(image)# Print output path.print(output_path)Additional parameters can be passed toprocess()method(Takes additional time):fromgigapixelimportScale,Mode,OutputFormatoutput_path=app.process(image,scale=Scale.X2,mode=Mode.STANDARD,delete_from_history=True,output_format=OutputFormat.PNG)Warning!Using parameters (scale,mode,output_format,delete_from_history) will takeadditional timeto process single image.
Consider using them only when needed.
To get the best performance, useapp.process(image)ContributingBug reports and/or pull requests are welcomeLicenseThe module is available as open source under the terms of theApache License, Version 2.0
Package: gigasheet
gigasheet-pythonInstallationThe Gigasheet API wrapper is built for Python 3 and may not work with earlier versions of Python.Recommended installationTo run the examples, clone this repository and then run the following steps from the root of the cloned repository:Create a venv (optional, but recommended)python-mvenvvenvsource./venv/bin/activateInstall GigasheetTo install from PyPI, you can simply run:pip install gigasheet.Run an example. See theAuthenticationsection for setting your key. After that, try running some examples in the example folder.pythonexamples/check_setup.pyAlternate installation as standaloneBecause the Gigasheet API wrapper is currently only a single file, you can also downloadgigasheet.pyfrom thegigasheetfolder of this repository and place that file in the same directory as your own script. You can then import gigasheet with the lineimport gigasheet. However, this is not recommended as it is more brittle. It is preferred to use the setup steps described above instead.AuthenticationSet the environment variableGIGASHEET_API_KEYto be your Gigasheet API key to authenticate requests.Contactsupport@gigasheet.comfor more information about how to obtain a Gigasheet API key.ExamplesImport file from S3 and share with a colleagueYou can use the example command-line toolexamples/import_and_share_cli.pyto import a file from S3 and share it to a colleague.First, use the AWS console or an AWS SDK to obtain a pre-signed link for the file you want to import. Then, use the command-line tool like this:python examples/upload_and_share_cli.py --input-url <the s3 presigned link> --share-to <email of colleague> --share-writeRunpython examples/upload_and_share_cli.py --helpto see more options like setting a file name or a share message.Alternatively, if you already have AWS credentials on your machine, you could look at the simplified example script:python examples/upload_from_s3.pyExport from Gigasheet to a local fileYou can use this example script to get an S3 presigned URL of an export and to save it to your local disk:python examples/download_export.pyAPI endpoint documentationhttps://gigasheet.readme.io/LicenseThis project is licensed under the terms of theMIT license.ContactVisit us athttps://gigasheet.comfor more about our product.Contactsupport@gigasheet.comfor more information or for help getting an API key.
Package: gigawave
GigaWave™ Official Python SDKEasy-to-use Python interface forGigaWave™ 6000-SeriesDigital Sampling Oscilloscopes.QuickstartInstall viapip3 install gigawave. Theexample.pyfile is an easy way to get started:fromgigawaveimportGigaWaveimportnumpyasnpimportmatplotlib.pyplotasplt# Connect to scopescope=GigaWave('/dev/ttyUSB0')# Initialize trigger settingsscope.trigger_direction='rising'scope.trigger_level=0# Vscope.trigger_holdoff=100# ns# Read voltage on Channel 1 at T + 50 nsprint(scope.get_voltage(delay=50,channel=1))# Create time-domain plotdelays=np.linspace(48,50,32)voltages=[scope.get_voltage(delay,channel=1,calibrate_timebase=False)fordelayindelays]plt.plot(delays,voltages)plt.xlabel('Time [ns]')plt.ylabel('Voltage [V]')plt.show()# Sample CDF for Channel 1 at T + 50 nsvoltages,cdf=scope.get_cdf(delay=50,channel=1)plt.plot(voltages,cdf)plt.xlabel('Voltage [V]')plt.ylabel('CDF Value')plt.show()Timebase CalibrationBy default, theget_voltageandget_cdfcommands will calibrate the internal timebase on every call.
Acquisition can be significantly sped up by skipping this step (passcalibrate_timebase = False).If this option is used, it is the user's responsibility to calibrate the timebase on a regular basis.
The required calibration frequency will vary depending on the application,
and will decrease as the scope's temperature stabilizes.
Package: giger
CLI for Stable Diffusion tasks.InstallationpipinstallgigerUsagePlease check first of all the help function and theexamples.giger--helpAlso make sure to always obtain the latest version.giger--versionIncrease verbosity to also output thediffuserslogging.giger-vvtemplateUse ajinja2template file and supply data from file. Overwrite variables and print out to console.gigertemplate--confighero=viking--datahero.yml"$(cathero.txt.j2)"Use an inlinejinja2template file and supply data. Write out to file.gigertemplate--confighero=viking"A {{hero}} with long hair and sword"--outputviking.txtYou can also pipe from another command to the template task.echo"A {{hero}} with long hair and sword"|gigertemplate--confighero=viking--outputviking.txtpromptGenerate a prompt with multiple well-known input keywords to choose.gigerprompt"A viking with long hair and sword"--time"Ancient"--type"Comic Book"--art_style"Concept art"--realism"Photorealistic"--rendering_engine"Octane render"--lightning_style"Cinematic"--camera_position"Ultra-Wide-Angle Shot"--resolution"8k"You can also pipe from another command to the prompt task.echo"A viking with long hair and sword"|gigerprompt--time"Ancient"--type"Comic Book"--art_style"Concept art"--realism"Photorealistic"--rendering_engine"Octane render"--lightning_style"Cinematic"--camera_position"Ultra-Wide-Angle Shot"--resolution"8k"imageThe commands pull the chosen model fromhuggingface.co. You choose one with the--modeloption. Also the batch and image sizes can be configured and one can pass the prompt via pipe.Please see the help function for more information.txt2imggigerimage"A viking with long hair and sword, Concept art, Photorealistic, Octane render, Cinematic, Ultra-Wide-Angle Shot, 8k"--output$HOME/Desktop/--namevikingimg2imggigerimage"A viking with long hair and sword, Concept art, Photorealistic, Octane render, Cinematic, Ultra-Wide-Angle Shot, 8k"--output$HOME/Desktop/--nameviking--inputinput.pngcontrolnetgigerimage"A viking with long hair and sword, Concept art, Photorealistic, Octane render, Cinematic, Ultra-Wide-Angle Shot, 8k"--output$HOME/Desktop/--nameviking--inputinput.png--controlnet_model"lllyasviel/sd-controlnet-hed"roopSimply change the face in an input image and render the result to disc.gigerroop--faceface.jpg--inputtarget.png--outputoutput.png