Saravanan666/pypi-org huggingface dataset:
Package: ascvid
ascvidis an ASCII video player with quite exact results. It is mostly advised to be used under Linux, but it might work on Windows too (its behavior under Mac is untested, and it will likely not work well).
Here is a little showcase of what it can do:It requires a Truecolor terminal to work like this. If you are on a stupider terminal, the results will look less realistic.The produced graphics aren’t blinking as in other ASCII video players, however, the videos might lag a bit if your terminal is zoomed out.ascvidalso supports audio output and pausing your video! It’s a true video player.Installationpython3 -m pip install ascvidThen you can just runascvidand you’re good to go.CLI OptionsNOTE :: –no-truecolor option lags like my brain, so if you are on a stupid terminal, you are better off using –no-color in ASCII mode... code-block:: consoleUsage: ascvid [OPTIONS] FILEOptions:-H,--hide-cursorHide the cursor while playing the video-A,--no-audioDon’t play audio stream-f,--fpsTEXTNumber of FPS the video’s supposed to run at. If
None, it’s determined from the video. If “max”,
ascvid will try its best to keep the video from
lagging-c,--charTEXTCharacter to be used while rendering the video
frames-C,--no-colorDon’t color output-a,--asciiUse multiple ASCII characters. Best to be used with
–no-truecolor-T,--no-truecolorReduces color palette. Use this flag on more stupid
terminals (windows).-F,--fastToggles off resizing each frame individually, rather
resizes the entire video. Use this if the video is
lagging too much.-d,--disable-controlsDisables pausing the video-t,--titleTEXTSets the title of the video. If not set, file name
will be used instead-h,--hide-titlehides the title-n,--new-windowOpens in a new terminal window-t,--termTEXTSpecify terminal in format ‘<terminal command> <run
command switch> {}’-o,--outfileTEXTSpecify output file-d,--debugDebug mode: show current/target fps-s,--subsSubtitle file to use--helpShow this message and exit.
Package: asc-viewer
LTspice ASC ViewerLTspiceis one of the best schematic entry tools out there. It lets you draw any schematic imaginable. LTspice's simple appearance belies its true power.You can draw graphs for computer science.You can define buses.You can nest schematics for complex hierarchies.Now if only we could use these schematics in a Python GUI.AscCanvasThe AscCanvas class lets you import a schematic and show it as a wxPython window. It supports zooming, scrolling, searching and subclassing. It usesrtreelibto look up symbols and nets under the mouse pointer.To show a schematic, you will need to import these files:ASY files are symbols, i.e., components, and they are imported in batch by specifying a list of paths. Load them by callingAscCanvas.load_symbols()ASC files are schematics. They define the connectivity between instances of symbols. Load them by callingAscCanvas.load_asc().asc_viewerasc_vieweris a demo executable that lets you open schematics and shows how to useAscCanvas.Installationpip install asc_viewer
Package: asda-tools
ASDA toolsSimple Python3 parser for.parfiles produced by ASDASoft by Delta
Electronics. Main purpose of this tool is to help with comparing servo driver
configuration backups using 'normal' tools such asvimdiff.It can also be used as an diff-tool for git, so you will get human-readable git
diffs while commiting raw binary.parfiles to your repository.WarningThis was tested only on a few files produced by ASDASoft version 5.4.1.0 with
ASDA-A2 servo driver. Implementation may be incomplete for other series.On the other hand, this script tries to work on the safe side - if it produces
json output without giving any error, then you can be sure, that it can
completely recreate original.parfile from this json.This script was created by examination of few.parfiles. The script is most
probably not complete. If you find that it fails on any.parfile produced by
ASDASoft, feel free to create new issue and please include that.parfile.
(You will probably need to zip it before Github will accept it.)Using as git diff-toolAll the parsing is located in a single scriptasda_tools/asdapar2json.pyand
it has no special dependency. So you can copy it to your repository. (Let's
assume, it will be in the same place as in this repository, insideasda_toolsdirectory.)Then you need to asociate.parfiles with new difftool by creating a.gitattributeswith content:*.par diff=asdapar2jsonAnd lastly, you need to enable this script in every clone of your repository.That is security measure-- script will be run automatically by git in the
background. It might be better idea to have script somewhere outside of the
repository and update it manually. Otherwisemallicious version can be run by
git when you switch to branch from untrusted source!But it should be safe in case of your private repository.In that case, just add:[diff "asdapar2json"]
	textconv = `git rev-parse --show-toplevel`/asda_tools/asdapar2json.pyto the file.git/config.If you are brave enough to run my version, you can test it on this repository :)Just clone it, edit the.git/configand run:git log -p test/test_files/test_01_pr.par
Package: asdconfigobj
ConfigObjis a simple but powerful config file reader and writer: anini
file round tripper. Its main feature is that it is very easy to use, with a
straightforward programmer’s interface and a simple syntax for config files.List of FeaturesNested sections (subsections), to any levelList valuesMultiple line valuesFull Unicode supportString interpolation (substitution)Integrated with a powerful validation systemincluding automatic type checking/conversionand allowing default valuesrepeated sectionsAll comments in the file are preservedThe order of keys/sections is preservedPowerfulunreprmode for storing/retrieving Python data-typesChangelogRelease 5.1.0Unified modules into the ‘configobj’ package (#72, #31, #32)Addedvalidatev1.1.0 shim to allow a gradual migration,
rewrite your imports asfrom configobj.validate import …to get rid of itAlternative line comment markers for more INI compatibility (#79)More detailed multi-error reports (#73)Added ‘decoupled’ mode to merge() (#115)fix:mixed_listaccepts type name variants (#110)fix: Don’t quote git-style section titles (#74)docs: Explicit mention offorce_listand its pitfalls (#112)Older ReleasesRelease 5.0.6 improves error messages in certain edge casesRelease 5.0.5 corrects a unicode-bug that still existed in writing filesRelease 5.0.4 corrects a unicode-bug that still existed in reading files after
fixing lists of string in 5.0.3Release 5.0.3 corrects errors related to the incorrectly handling unicode
encoding and writing out filesRelease 5.0.2 adds a specific error message when trying to install on
Python versions older than 2.5Release 5.0.1 fixes a regression with unicode conversion not happening
in certain cases PY2Release 5.0.0 updates the supported Python versions to 2.6, 2.7, 3.2, 3.3
and is otherwise unchangedRelease 4.7.2 fixes several bugs in 4.7.1Release 4.7.1 fixes a bug with the deprecated options keyword in 4.7.0.Release 4.7.0 improves performance adds features for validation and
fixes some bugs.
Package: asdf-astropy
ASDF serialization support for astropyThis package includes plugins that provide ASDF serialization support for astropy
objects.  The plugins are automatically enabled when the package is installed.The plugins in this package supersede those in theastropy.io.misc.asdfmodule;
when this package is installed, the astropy plugins will be ignored.  Theastropy.io.misc.asdfmodule will be removed in a future version of astropy.LicenseThis project is Copyright (c) Association of Universities for Research in Astronomy (AURA)
and licensed under the terms of the BSD 3-Clause license. This package is based upon
theAstropy package templatewhich is licensed under the BSD 3-clause license. See the licenses folder for
more information.InstallationStable releases of the asdf-astropy python package are registeredat
PyPi. The latest stable version
can be installed usingpip:$pipinstallasdf-astropyThe latest development version of asdf-astropy is available from themainbranchon github. To clone the project:$gitclonehttps://github.com/astropy/asdf-astropyTo install:$cdasdf-astropy$pipinstall.To install indevelopment
mode$pipinstall-e.TestingTo install the test dependencies from a source checkout of the repository:$pipinstall-e".[test]"To run the unit tests from a source checkout of the repository:$pytestIt is also possible to run the test suite from an installed version of
the package.$pipinstall"asdf-astropy[test]"$pytest--pyargsasdf-astropyIt is also possible to run the tests usingtox.$pipinstalltoxTo list all available environments:$tox-vaTo run a specific environment:$tox-e<envname>ContributingWe love contributions! asdf-astropy is open source,
built on open source, and we’d love to have you hang out in our community.
Package: asdff
asdffAdetailer Stable Diffusion diFFusers pipeline예시from pip installpip install asdffimporttorchfromasdffimportAdPipelinepipe=AdPipeline.from_pretrained("stablediffusionapi/counterfeit-v30",torch_dtype=torch.float16)pipe.safety_checker=Nonepipe.to("cuda")common={"prompt":"masterpiece, best quality, 1girl","num_inference_steps":28}result=pipe(common=common)images=result[0]from custom pipelineultralytics 설치 필요pip install ultralyticsimporttorchfromdiffusersimportDiffusionPipelinepipe=DiffusionPipeline.from_pretrained("stablediffusionapi/counterfeit-v30",torch_dtype=torch.float16,custom_pipeline="Bingsu/adsd_pipeline")pipe.safety_checker=Nonepipe.to("cuda")common={"prompt":"masterpiece, best quality, 1girl","num_inference_steps":28}result=pipe(common=common)images=result[0]그 외스케줄러를 변경하고, 입력 이미지를 제공하는 예시importtorchfromasdffimportAdPipelinefromdiffusersimportDPMSolverMultistepSchedulerfromdiffusers.utilsimportload_imagepipe=AdPipeline.from_pretrained("stablediffusionapi/counterfeit-v30",torch_dtype=torch.float16)pipe.safety_checker=Nonepipe.scheduler=DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)pipe=pipe.to("cuda")common={"prompt":"masterpiece, best quality, 1girl","num_inference_steps":20}images=load_image("https://i.imgur.com/8TX2AX6.png")result=pipe(common=common,images=[images])argumentscommon: Mapping[str, Any] | Nonetxt2img와 inpaint에서 공통적으로 사용할 인자들txt2img_only: Mapping[str, Any] | Nonetxt2img에서만 사용할 인자. common과 겹치는 인자는 덮어씁니다.StableDiffusionPipeline.callinpaint_only: Mapping[str, Any] | Noneinpaint에서만 사용할 인자. common과 겹치는 인자는 덮어씁니다.strength: 0.4가 기본값으로 적용됩니다.StableDiffusionInpaintPipeline.callimages: Image | Iterable[Image] | Noneinpaint를 수행할 이미지들. 주어지면 txt2img의 결과를 대체하기 때문에txt2img_only는 무시됩니다.detectors: DetectorType | Iterable[DetectorType] | NoneDetectorType: Callable[[Image.Image], Optional[List[Image.Image]]]pil Image를 입력으로 받아 마스크 이미지의 리스트(마스크), 또는 None을 반환하는 Callable.그런 Callable 하나, Callable의 리스트 또는 NoneNone일경우,default_detector가 사용됩니다.fromasdffimportAdPipelinepipe=AdPipeline.from_pretrained(...)pipe.default_detector>>><functionasdff.yolo.yolo_detector(image:'Image.Image',model_path:'str | None'=None,confidence:'float'=0.3)->'list[Image.Image] | None'>사용 예시fromfunctoolsimportpartialimporttorchfromasdffimportAdPipeline,yolo_detectorfromhuggingface_hubimporthf_hub_downloadpipe=AdPipeline.from_pretrained("stablediffusionapi/counterfeit-v30",torch_dtype=torch.float16)pipe.safety_checker=Nonepipe.to("cuda")person_model_path=hf_hub_download("Bingsu/adetailer","person_yolov8s-seg.pt")person_detector=partial(yolo_detector,model_path=person_model_path)common={"prompt":"masterpiece, best quality, 1girl","num_inference_steps":28}result=pipe(common=common,detectors=[person_detector,pipe.default_detector])resultmask_dilation: int, default = 4마스크 감지 후, cv2.dilate 함수를 적용해 마스크 영역을 키우는 데, 이 때 적용할 커널의 크기.mask_blur: int, default = 4dilation 후 적용할 가우시안 블러의 커널 크기.mask_padding: int, default = 32dilation 적용 후 이 값만큼 bbox의 가로세로 영역을 더해서 이미지를 자른 뒤, inpaint를 시도하게 됩니다.
Package: asdfghjkl
ASD(FGHJK)LThe library is called "ASDL", which stands forAutomaticSecond-orderDifferentiation (forFisher,Gradient covariance,Hessian,Jacobian, andKernel)Library.
ASDL is a PyTorch extension for computing 1st/2nd-order metrics and performing 2nd-order optimization of deep neural networks.You can importasdfghjklby sliding your finger on a QWERTY keyboard :innocent:importasdfghjklADL vs ASDLBasic metrics supported by a standard automatic differentiation libarary (ADL)metricdefinitionneural networkloss(averaged) gradientAdvanced 1st/2nd-order metrics (FGHJK) supported by ASDLmetricdefinitionFisher information matrixFisher information matrix (MC estimation)empiricalFisherGradient covarianceHessianJacobian (per example)JacobianKernelMatrix approximationsSupported operationsmatrix-vector productpower methodconjugate gradient methodpreconditioning gradient
Package: asdf-pydantic
asdf-pydanticCreate ASDF tags withpydanticmodels.fromasdf_pydanticimportAsdfPydanticModelclassRectangle(AsdfPydanticModel):_tag="asdf://asdf-pydantic/examples/tags/rectangle-1.0.0"width:floatheight:float# After creating extension and install ...af=asdf.AsdfFile()af["rect"]=Rectangle(width=1,height=1)#ASDF 1.0.0#ASDF_STANDARD 1.5.0%YAML1.1%TAG!tag:stsci.edu:asdf/---!core/asdf-1.1.0asdf_library:!core/software-1.0.0{author:The ASDF Developers,homepage:'http://github.com/asdf-format/asdf',name:asdf,version:2.14.3}history:extensions:-!core/extension_metadata-1.0.0extension_class:asdf.extension.BuiltinExtensionsoftware:!core/software-1.0.0{name:asdf,version:2.14.3}-!core/extension_metadata-1.0.0{extension_class:mypackage.shapes.ShapesExtension,extension_uri:'asdf://asdf-pydantic/shapes/extensions/shapes-1.0.0'}rect:!<asdf://asdf-pydantic/shapes/tags/rectangle-1.0.0>{height:1.0,width:1.0}...FeaturesCreate ASDF tag from yourpydanticmodels with batteries (converters) included.Validates data models as you create them and not only when reading and writing ASDF files.Preserve Python types when deserializing ASDF files.All the cool things that comes withpydantic(e.g., JSON encoder, JSON schema, Pydantic types)Comes with schemas.Installationpip install asdf-pydanticUsageDefine your data model# mypackage/shapes.pyfromasdf_pydanticimportAsdfPydanticModelclassRectangle(AsdfPydanticModel):_tag="asdf://asdf-pydantic/examples/tags/rectangle-1.0.0"width:floatheight:floatThen create an extension with the converter included withasdf-pydantic:# mypackage/extensions.pyfromasdf.extensionimportExtensionfromasdf_pydantic.converterimportAsdfPydanticConverterfrommypackage.shapesimportRectangleAsdfPydanticConverter.add_models(Rectangle)classShapesExtension(Extension):extension_uri="asdf://asdf-pydantic/examples/extensions/shapes-1.0.0"converters=[AsdfPydanticConverter()]tags=[*AsdfPydanticConverter().tags]Install the extension either by entry point specification or add it toasdf.get_config():importasdffrommypackage.extensionsimportShapeExtensionasdf.get_config().add_extension(ShapesExtension())af=asdf.AsdfFile()af["rect"]=Rectangle(width=1,height=1)withopen("shapes.asdf","wb")asfp:af.write_to(fp):maxdepth: 1
autoapi
Package: asdf-sextant
ASDF SextantLanding page for all thingsASDF:https://seismic-data.orgThis isAdaptableSeismicDataFormat - if you are looking
for theAdvancedScientificDataFormat, go here:https://asdf.readthedocs.io/en/latest/This is an experimental graphical user interface intended to enable the
interactive exploration of ASDF files. It is best suited to deal with
earthquake data.Installation$condainstallpyasdfpyside2
$pipinstallasdf-sextantIt is important to installpyside2viacondaif you useconda-
otherwise it is easy to install some version of Qt withcondaand another
viapipwhich just crashes.UsageStart it with:$asdf-sextantAlternatively you can directly open a file with it:$asdf-sextantfilename.h5DevDependenciesThe GUI has the following dependencies:Python 3.7 or 3.8pyasdfpyside2pyqtgraph>=0.11.0rc0qdarkstyleMiscRebuild the UI file in case its necessary with:pyside2-uic -g python --output=asdf_sextant_window.py asdf_sextant_window.ui
Package: asdf-standard
ASDF standard 1.6.0This document describes the Advanced Scientific Data Format (ASDF),
pronouncedAZ-diff.  You can read the full specification atthe online documentation.This is theAdvancedScientificDataFormat - if you are looking for theAdaptableSeismicDataFormat, go here:http://seismic-data.org/ContributingPlease open a newissueor newpull requestfor bugs, feedback, or new features you would like to see. If there is an issue you would like to work on, please leave a comment and we will be happy to assist. New contributions and contributors are very welcome!There are two mailing lists for ASDF:asdf-usersasdf-developersGetting More InformationFAQ pageon the wiki.ASDF: A new data format for astronomy, published inAstronomy and Computing:Greenfield, P., Droettboom, M., & Bray, E. (2015). ASDF: A new data format for astronomy.Astronomy and Computing, 12: 240-251.
doi:10.1016/j.ascom.2015.06.004
Package: asdfy
AsdfyA library to process ASDFDataSet(s) frompyasdf.Prerequisitespyasdf
mpi4pyInstallationpip install asdfyUsageBasic usagefrom asdfy import ASDFProcessor
ASDFProcessor('input.h5', 'output.h5', process_func).run()Defailed explinationTBD. Refer totests/main.pyfor now. To run tests:cd tests
mpi4un -n 4 python main.pyASDFProcessorsrcUnion[str, Iterable[str]]Path to input ASDFDataSet(s)dststrPath to output ASDFDataSetfuncCallable[..., ASDFOutput]Processing function, each argument correspond to an input dataset.input_typeLiteral['stream', 'trace', 'auxiliary', 'auxiliary_group'] = 'trace'Type of input datainput_tagOptional[str] = NoneInput waveform tag or auxiliary group, None for using the first availableoutput_tagOptional[str] = NoneOutput waveform tag or auxiliary group, None for using input_tag or input_typeaccessorbool = FalsePass the origional accessor to the processing function. Set to .True. if you need event or station info.onerrorOptional[Callable[[Exception], None]] = NoneCallback when error occurs
Package: asdf-zarr
ASDF serialization support for ZarrThis packages includes an extension for the Python libraryasdfto add support
for reading and writing chunkedZarrarrays.InstallationThis extension is available on PyPI. We are actively developing
this extension and until a stable release (1.0.0) is made it
is possible that breaking changes will be introduced. If you
are using this extension please let us know so we can look into
adding your project to downstream testing in our CI.$pipinstallasdf-zarrAlternatively this extension can be installed by cloning
and installing the git repository.$gitclonehttps://github.com/asdf-format/asdf-zarr$cdasdf-zarr$pipinstall.UsageFor background on ASDF array storage and examples
of how to use this extension see the notebooks
subdirectory of this repository.Testingpytestis used for testing.
Tests can be run (from the source checkout of this repository):$pytestContributingWe welcome feedback and contributions to this project.
Package: asdicts
Missed utilities for working with Python dictionaries.Python has great builtins for working with lists as well as dictionaries, but
some utilities for working with dictionaries are still missed. This fills the
gap.Project Informationasdictsis released under theApache Licence 2.0,
and the code onGitHub. It’s rigorously
tested on Python 3.6+. If you’d like to contribute toasdictsyou’re most welcome!SupportShould you have any question, any remark, or if you find a bug, or if there is
something you can’t do with theasdicts, pleaseopen an issue.Release Information1.1.0 (2021-01-26)FeaturesEnable Python 3.6 supportFull changelog.Creditsasdictsis written and maintained bySerghei Iakovlev.A full list of contributors can be found inGitHub’s overview.
Package: asdl
A copy of the ASDL parser used in CPython 3.5, cleaned a bit and packaged here.Installation$pipinstallasdlUsagefromasdlimportASDLParser,parsesyntax="""
    module Lambda {
        term =
            Lambda(name x, term body) |
            Apply(term function, term argument) |
            Variable(name x)
    }
"""print(ASDLParser().parse(syntax))print(asdl.parse("./test/Python.asdl"))Output:Module(Lambda, [Type(term, Sum([Constructor(Lambda, [Field(name, x), Field(term, body)]), Constructor(Apply, [Field(term, function), Field(term, argument)]), Constructor(Variable, [Field(name, x)])]))])Module(Python, [Type(mod, Sum([Constructor(Module, [Field(stmt, body, seq=True)]), Constructor(Interactive, [Field(stmt, body, seq=True)]), Constructor(Expression, [Field(expr, body)]), Constructor(Suite, [Field(stmt, body, seq=True)])])), Type(stmt, Sum([Constructor(FunctionDef, [Field(identifier, name), Field(arguments, args), Field(stmt, body, seq=True), Field(expr, decorator_list, seq=True), Field(expr, returns, opt=True)]), …LicenseSame as CPython: Python Software Foundation License (LICENSE file included
here).
Package: asdl-adt
ASDL ADTThis is a modern Python (3.8+) library for generating helpful algebraic data types out of ASDL definitions.Development setupFirst, clone the repo:$gitclonegit@github.com:ChezJrk/asdl.git$cdasdlThen create a virtual environment and install the requirements into it:$python3-mvenv$HOME/.venv/asdl$source$HOME/.venv/asdl/bin/activate$python-mpipinstall-Upipsetuptoolswheel$python-mpipinstall-rrequirements.txtThen install thepre-commithooks:$ pre-commit installFinally, you can run the tests with tox:$ toxThis will test on Python 3.8, 3.9, and 3.10.
Package: asdm
asdmAgile System Dynamics ModellingASDM is a python library that enables its users to create and simulate System Dynamics (SD) models. It can also simulate SD models saved in the XMILE format, including advanced features such as arrays and conveyors. The support is being continuously improved.In the library:asdm/asdm.pyconsists of the main functionalities, including the lexer, parser, and interpreter.asdm/utilities.pyprovies a data visualisation tool.asdm/Inferenceconsists of tools for model calibration.InstallationPython versionThe library is developed and used withPython 3.11. However, it should also work with other versions. If you encounter a problem and believe it is related to python version, please open an issue or contact me.Operating systemThe library is developed and used onmacOS. Some tests have also been done onWindowsandUbuntu Linux, but they are not comprehensive. If you encounter a problem and believe it is related to the OS, please open an issue or contact me.Create an environmentWe recommend that you create a new environment to use the library, although this is not always necessary. For example, if you use anaconda, this can be done by:conda create --name asdmClone this repository to your local computerTo clone this repository to your local environment, please ensure thatgitis installed in your system, then use the following command:git clone https://github.com/wzh1895/ASDM.gitInstall dependenciesASDM relies on a number of other python libraries as dependencies. To install them, use the following commands:cd asdm
conda install --file requirements.txt -c conda-forgeUsagePlease refer toDocumentationfor the commonly used functions.Tutorial Jupyter NotebooksWe also use Jupyter Notebooks to provide demoes of ASDM's functionalities.SD ModellingCreating an SD model from scratchAdding stocks, flows, auxiliariesSupport for nonlinear functions (MIN, MAX, etc.)Support for stochastic functions (random binomial trial, etc.)Running simulationsExporting and examing simulation outcomesDisplaying simulation outcomes as graphWe will add more tutorial notebooks.You are welcomed to share your own tutorial notebooks through apull request. When sharing notebooks, please make sure it does not contain sensitive data.LicenceASDM is made public under the MIT licence.ContributorsWang Zhaomain authorPhD candidate & research assistant at University of Strathclyde, UKWang has given multiple talks on ASDM at different gatherings and conferences of modellers, operational researchers, and healthcare experts. This is the YouTube link toone of the talks.Wang can be reached atwang.zhao@strath.ac.uk.Matt StammerscontributorConsultant Gastroenterologist & open-source software developer at University Hospital Southampton, UKMatt created a webapp using streamlit to allow users to interact with a simulation dashboard in their web browsers or on smartphones, such as in thisdemo. The simulation of the SD model in the backend is powered by ASDM. This is a part of an initiativeReally Useful Models.Matt'sGitHub Homepage