Saravanan666/pypi-org huggingface dataset:
Package: panda3d-gltf
panda3d-gltfThis project adds glTF loading capabilities to Panda3D.
One long-term goal for this project is to be used as a reference for adding a builtin, C++ glTF loader to Panda3D.
If and when Panda3D gets builtin support for glTF, this module will go into maintenance mode and be used to backport glTF support to older versions of Panda3D.FeaturesAdds support for native loading of glTF filesSupports glTF 2.0Supports binary glTFIncludes support for the following extensions:KHR_lights (deprecated in favor of KHR_lights_punctual)KHR_lights_punctualBLENDER_physicsShips with agltf2bamcli-tool for converting glTF files to BAMShips withgltf-viewerfor viewing files (including glTF) with a simple PBR rendererInstallationUse pip to install thepanda3d-gltfpackage:pipinstallpanda3d-gltfTo grab the latest development build, use:pipinstallgit+https://github.com/Moguri/panda3d-gltf.gitUsageConfigurationpanda3d-gltfhas the following configuration options.
See below for information on setting these options for the native loader and the CLI.collision_shapes- the type of collision shapes to build.
EitherbuiltinforColisionSolidsorbulletforBulletRigidBodyNodes.
Defaults tobuiltin.flatten_nodes- attempt to flatten resulting scene graph, defaults toFalselegacy_materials- convert imported PBR materials to legacy materials, defaults toFalseno_srgb- do not load textures as sRGB textures, defaults toFalseskip_animations- do not convert animation data found in the glTF file, defaults toFalseskip_axis_conversion- do not perform axis-conversion (useful if glTF data is already non-standard and already Z-Up), defaults toFalseNative loadingpanda3d-gltfships with a Python file loader (requires Panda3D 1.10.4+), which seamlessly adds glTF support to Panda3D'sLoaderclasses.
Thisdoes notadd support topview, which is a C++ application that does not support loading Python file loaders.
Instead ofpview, use thegltf-viewerthat ships withpanda3d-gltf.The loader can be configured via PRC variables.
These PRC variables are prefixed withgltf-but otherwise match the names above.
For example, usegltf-collision-shapes bulletto have the loader load Bullet shapes instead of CollisionSolids.Command LineTo convert glTF files to BAM via the command line, use the suppliedgltf2bamtool:gltf2bamsource.gltfoutput.bamSeegltf2bam -hfor more information on usage and available CLI flags.Viewerpanda3d-gltfships withgltf-viewer.
This is a simple viewer (likepview) to view glTF (or any other file format support by Panda3D) with a simple, PBR renderer.Running TestsFirst installpanda3d-gltfin editable mode along withtestextras:pipinstall-e.[test]Then run the test suite withpytest:pytestBuilding WheelsInstallbuild:pipinstall--upgradebuildand run:python-mbuildLicenseB3D 3-Clause
Package: panda3d-kivy
Panda3D-KivyA Panda3D add-on for Kivy integration.The aim is to make the integration of Kivy apps into a Panda3D application
almost transparent.
Potential uses include creating on-screen GUI, or even RTT 3D UI's.Usage:First, importpanda3d_kivy.app.App- make sure you do this before importing
any Kivy-related stuff:frompanda3d_kivy.appimportAppThen, as usual in Kivy, create a subclass of this App, and use build() or the
KV autoloading system to populate your widget tree:fromkivy.uix.buttonimportButtonclassExample(App):defbuild(self):returnButton(text='Hello, world!')You can then instantiate and run this app inside the__init__of your PandaShowBase, after runningShowBase.__init__(self). You may want to create a
display region for your kivy app, sized according to your needs, otherwisepanda3d_kivywill automatically create one for you that will occupy the
entire window. You must then pass your ShowBase as argument to the Kivy app
instantiation, as well as your display region if applicable, and finally callapp.run()as you normally would:fromdirect.showbase.ShowBaseimportShowBaseclassPandaApp(ShowBase):def__init__(self):ShowBase.__init__(self)self.kivy_app=kivy_app=Example(self)kivy_app.run()# The rest of your ShowBase code hereapp=PandaApp()app.run()Voilà! You should have a working Kivy UI in your Panda application. Have fun!
Package: panda3d-logos
panda3d-logosThe Panda3D logo in various formats, a 3d animated splash screen and code to show it off.Wait, code?Yup. You're already using Panda3D, after all, right? Here's the
pertinent bits ofexamples/panda3d_logo.pyfrompanda3d_logos.splashesimportRainbowSplashsplash=RainbowSplash()interval=splash.setup()# This'll change the scene graph, in# particular reparent the cam!# interval is a Panda3D interval you can .start() it nowsplash.teardown()# To de-litter your state.
Package: panda3d-openvr
panda3d-openvrThis module provides basic integration ofOpenVRwithPanda3DusingpyopenvrRequirementsThis module requires Panda3D > 1.10, pyopenvr and a implementation of OpenVR (SteamVR or OpenComposite (not tested though...)). It supports Windows, Linux and macOS platforms.InstallationFrom wheelpip install panda3d-openvrFrom sourcegit clone https://github.com/el-dee/panda3d-openvr
cd panda3d-openvr
python3 setup.py installUsageTo use panda3d-openvr, first import the p3dopenvr module in your application :from p3dopenvr.p3dopenvr import *Then, once an instance of ShowBase is created, instanciate the VR interface and initialize it :myvr = P3DOpenVR()
myvr.init()Once done, the module will enable the VR application layer of OpenVR, create the left and right cameras and configure the rendering system to send the images of each eye to the VR compositor.Note that, on Linux, SteamVRmustbe already running before you launch your application.The module will create the following hierachy in the scenegraph :Traking space origin (tracking_space)HMD anchor (hmd_anchor)Left eye (left_eye_anchor)Right eye (right_eye_anchor)Tracked device 1Tracked device 2...The controllers will be one the the tracked devices, see the samples to know how to map the tracked device with the actual controller and find its role (left or right hand).By default the left eye image is also rendered on the main application window.DocumentationThere is no manual available, but the code is heavily documented and each functionality is demonstrated in one of the following examples.ExamplesAll the examples are found under samples/ directory, to launch them simply go to their directory and run:python3 main.pyMinimalIn minimal you can find a minimal setup that will draw a Panda avatar in front of you, render cameras for each tracking station and a (ugly) cube where your controllers ought to be.This example shows how to use the simple event and pose interfaces to retrieve the position of the various elements in the tracking space and the events triggered by the user.ActionsIn samples/actions, you can find a demo using action manifest to bind actions from the user to event in the application.
This is more complex to set up than the event interface, but allows the end user to remap the actionsSkeletonIn samples/skeleton, you can find a demo using action manifest to animate the fingers of your virtual hands using the dynamic hand skeleton provided by OpenVR.
See the sample README for where to find the hand models to use.RalphIn samples/ralph you can find a heavily modified version of the Roaming Ralph demo.
In the version, you are Ralph and you can explore the space around you. Using the trackpad on the left controller, you can move forward and backward in the direction you're facing, or rotate the camera.LicenseB3D 3-ClauseSome parts of the code are directly coming from pyopenvr examples, which are (c) pyopenvr author "cmbruns"Ralph demo base is copied over from Panda3D source code.
Package: panda3d-render-pass
Render PassThis library is intended to make multi-pass rendering a little easier in Panda3D.
Each RenderPass objects represents a render target and a scene to render.
If no scene is given, a fullscreen quad is rendered.
This library is meant to replace the FilterManager found in Panda3D's Direct library.ExampleThe code below was added to the "Roaming Ralph" demo to do HDR rendering.
The full sample can be found insamples/roaming-ralph.self.render.set_attrib(LightRampAttrib.make_identity())fb_props=FrameBufferProperties()fb_props.set_float_color(True)fb_props.set_rgba_bits(16,16,16,0)fb_props.set_depth_bits(32)scene_pass=RenderPass('scene',camera=base.camera,scene=base.render,frame_buffer_properties=fb_props,clear_color=LColor(0.53,0.80,0.92,1),)filter_pass=RenderPass('filter',shader=Shader.load(Shader.SL_GLSL,'shaders/fsq.vert','shaders/fsq.frag'))filter_pass._root.set_shader_input('render',scene_pass.output)card=filter_pass.buffer.getTextureCard()card.setTexture(filter_pass.output)card.reparentTo(render2d)
Package: panda3d-stageflow
panda3d-stageflowJust about every game beyond gameplay prototypes goes through distinct
stages: Opening credits, main menu, main game loop, ingame credits, and
so on. These can be arranged as a finite state machine, with data being
passed between stages.In addition, each stage, especially the main menu and main game loop,
can have certain modes that modify their base functionality, mostly
menus that pause the base game; These are called substages.stageflowimplements this basic framework, letting you...focus on eachStageandSubstageseparately,re-useSubstagesover severalStages,use premade typicalStages/Substages.For example:  # FIXME: Abstract Panda3DSplash out of the example...fromdirect.showbase.ShowBaseimportShowBasefromstageflowimportFlowfromstageflow.panda3dimportPanda3DSplashfromstageflow.prefabimportQuitShowBase()base.flow=Flow(stages=dict(splash=Panda3DSplash(exit_stage='quit'),quit=Quit(),),initial_stage='splash',)base.run()This example...creates aFlowwith two stages (namedsplashesandquit),immediately enters thesplashesstage, which creates aTask,starts Panda3D's main loop,lets theTaskplay the splash until it ends, orescapeis pressed,transitions toquit, which in turn ends the program.Installation, etc.Installation:pip install panda3d-stageflowDocumentation:readthedocs.ioSource and issue tracker:GitHub
Package: panda3d-subtitler
Panda3D SubtitlerA subtitle reader/renderer for the Panda3D game engineFeaturesThis library extends the game engine by a simple subtitle reader/renderer. You just open an existing subtitle file, sync it to the audio or video and you'll have subtitles in your panda3d application.Currently this library only supports SubRip subtitle (.srt) files.InstallInstall the subtitler via pippipinstallpanda3d-subtitlerHow to useTo add a browser instance to your running Panda3D application, just instantiate it like shown here:fromsubtitler.subtitlerimportSubtitlermySound=loader.loadSfx("someAudioFile.ogg")subtitles=Subtitler("subtitles")subtitles.loadSubtitleFile("./mySubtitles.srt")subtitles.synchronizeToAudio(mySound)
Package: panda3d-tmx2bam
CLI tool for converting Tiled TMX files to Panda3D BAM files.Usage:$ pip install panda3d-tmx2bam
$ tmx2bam path/to/tmx/file.tmx path/to/bam/file.bamorfrom tmx2bam import Tmx2Bam
from direct.showbase.ShowBase import ShowBase

base = ShowBase()
tmx_map = Tmx2Bam("path/to/tmx/file.tmx")
tmx_map.node.reparent_to(render)
base.run()find() important tiles by their properties/tags and make them move about and all that. Orthographic camera recommended!Currently supports:TMX file with CSV data (default)Custom properties as PandaNode tagsMultiple tilesheetsMultiple layers and GroupsAnimated tilesObject layer/Objects (point, poly, rectangle, text, image)Background imagesMerge animated spritesAllow more shapes than just cardsLeft to do:Infinite maps (chunks)Hexagonal and Isometric tilesTile render orderTilesheet image collectionEmbedded tilesheet in tmxEmbedding texture in bamTiled features I'm not aware ofError handlingA better readmeMind:The Y axis is inverted in panda3d.Animated sprites can only have one steady frame-rate that you can set on the first frame in Tiled.Currently the image resolutions have to be power of two.Rendering individual tiles is slow. Add a custom property named "flatten" to layers to merge them.The ellipse and point objects are not drawn, they're empty nodepaths.I'm not a programmer but I play one on TV. Your mileage may vary.Licensed WTFPL.
Package: pandablob
PandaBlobFunctions to easily transform Azure blobs into pandas DataFrames and vice versa.InstallationInstalling PandaBlob viapipis the preferred method, as it will always install the most recent stable release. If you do not havepipinstalled, thisPython installation guidecan guide you through the process.To install PandaBlob, run this command in your terminal:# Use pip to install PandaBlobpipinstallpandablobDownloading and installing PandaBlob from source is also possible, follow the code below.# Download the packagegitclonehttps://github.com/uijl/pandablob# Go to the correct foldercdpandablob# Install packagepipinstall-e.UsageThe code snip below shows how you can use PandaBlob, all you need is aBlobClientand possibly a pandas DataFrame or some keyword arguments for pandas.# Import the Azure SDK and pandablobimportpandablobfromazure.storage.blobimportContainerClient# Your Azure Credentialsaccount_url="https://my_account_url.blob.core.windows.net/"token="your_key_string"container="your_container"blobname="your_blob_name.csv"container_client=ContainerClient(account_url,container,credential=token)blob_client=container_client.get_blob_client(blob=blobname)# Specifiy your pandas keyword argumentspandas_kwargs={"index_col":0}# Read the blob as a pandas DataFramedf=pandablob.blob_to_df(blob_client,pandas_kwargs)Potential errorsThere are three common errors that can be returned. Two are related to the blob storage and one because of the current limitations of pandablob.ResourceExistsError- If the specified blob is already on the blob, this error is returned. There are two options, you can add theoverwrite=Trueargument to yourdf_to_blobfunction or you can catch the exception. If you wish to enter it in an except statement, you can import it usingfrom azure.core.exceptions import ResourceExistsError;ResourceNotFoundError- If the specified blob is not found, this error is returned. If you wish to enter it in an except statement, you can import it usingfrom azure.core.exceptions import ResourceNotFoundError;TypeError- This error is returned by pandablob if you want to upload or download an extensiontype that is not yet supported. Currently only the following extensions are supported:.csv.json.txt,.xlsand.xlsx.To do list:Some other stuff that needs to be done:Include other files;Easier downloading a .csv file;Added MIT license.
Package: pandablocks
A Python client which connects to the control and data ports of the PandABlocks TCP server.PyPIpip install pandablocksSource codehttps://github.com/PandABlocks/PandABlocks-clientDocumentationhttps://pandablocks.github.io/PandABlocks-clientCommand line tool features an interactive console, load/save control, and HDF5
writing:$ pip install pandablocks

$ pandablocks control <panda-hostname>
< PCAP.     # Hit TAB key...
PCAP.ACTIVE     PCAP.BITS1      PCAP.BITS3      PCAP.GATE       PCAP.SAMPLES    PCAP.TRIG       PCAP.TS_END     PCAP.TS_TRIG
PCAP.BITS0      PCAP.BITS2      PCAP.ENABLE     PCAP.HEALTH     PCAP.SHIFT_SUM  PCAP.TRIG_EDGE  PCAP.TS_START
< PCAP.ACTIVE?
OK =1

$ pandablocks hdf <panda-hostname> /tmp/panda-%d.h5
INFO:Opened '/tmp/panda-1.h5' with 60 byte samples stored in 11 datasets
INFO:Closed '/tmp/panda-1.h5' after writing 50000000 samples. End reason is 'Disarmed'Library features a Sans-IO core with both asyncio and blocking wrappers:frompandablocks.blockingimportBlockingClientfrompandablocks.commandsimportGetwithBlockingClient("hostname-or-ip")asclient:# Commands sent to Control portidn=client.send(Get("*IDN"))print(f"Hello{idn}")fordatainclient.data():# Data captured from Data portprint(f"I got some PCAP data{data}")Seehttps://pandablocks.github.io/PandABlocks-clientfor more detailed documentation.
Package: pandablocks-ioc
A softioc to control aPandABlocks-FPGA.PyPIpip installPandABlocks-iocSource codehttps://github.com/PandABlocks/PandABlocks-iocDocumentationhttps://PandABlocks.github.io/PandABlocks-iocReleaseshttps://github.com/PandABlocks/PandABlocks-ioc/releasesTo run the ioc:$ python -m pandablocks-ioc softioc <pandabox host> <pv prefix> --screens-dir=<directory to output bobfiles> --clear-bobfilesPVs will be available for all the values shown on theweb client:$ caget PANDA:CALC1:INPA
PANDA:CALC1:INPA               ZEROOn start-up the ioc will usePVIto generate bobfiles for viewing the PVs in phoebus:Seehttps://PandABlocks.github.io/PandABlocks-iocfor more detailed documentation.
Package: pandabus
PandaBusThis library provided a simple event bus.Using Example#1：Basic Usingfrompandabusimportbus# Create to event listener(printb should called after printa)@bus.listen("print")defprinta(ent):print(f"hello from printa")@bus.listen("print",after="printa")defprintb(ent):print(f'hello from printb')# send eventbus.send("print")#2：Pro Usingfrompandabusimportbus,EventclassStaticEvent(Event,static=True):msg:strclassDynaEvent(Event,cancelable=True):msg:str# Create to event listener(printb should called after printa,printc)@bus.listen(StaticEvent)defprinta(ent):print(f"{ent.msg}from printa")@bus.listen(StaticEvent)defprintb(ent):print(f"{ent.msg}from printb")@bus.listen(StaticEvent,after=["printa","printb"])defprintc(ent):print(f'{ent.msg}from printc')@bus.listen(DynaEvent)defprintd(ent):print(f"{ent.msg}from printd")ent.cancel()@bus.listen(DynaEvent,after="printd")defprinte(ent):print(f"{ent.msg}from printe")# send eventbus.send(StaticEvent,"hello")bus.send(DynaEvent,"hello again")#3：Own Bus?frompandabusimportbuses,Busbus1=buses.bus1# Simplely get a own bus.bus2=Bus("bus2")# Work too.
Package: pandacell
pandacellAuthor: Eirik B. StavestrandIntroduces a%df(or%%df) magic which can be used in Jupyter notebooks and the IPython console.The magic executes the contents of a cell on a Pandas DataFrame.DescriptionPandas is great and all, but writing Pandas code can be tedious. For example when simply making summing two columns:In[1]:df["a"]+df["b"]It might not look like such a big deal, but all those brackets and quotation marks add up.
Usingpandacell, the above syntax can be written as:In[2]:%dfa+bUnder the hoods, this is accomplished simply by passing the cell contents as a string to Pandas'df.evalfunction.
This isn't very complex, but it does provide a fair deal of functionality and adds a whole lot of readability.If you wish to store the results to a new column, use regular assignment along with the-i(or--inplace) flag:In[3]:%df-ic=a+bIt also works with multiple assignments:In[4]:%%df-i...:c=a+b...:f=c-aYou can use Pandas' various accessors and series method calls:In[5]:%%df-i...:name_upper=name.str.upper()...:yr=timestamp.dt.year...:lower_cased=species.where(cond=species.str[0].str.islower(),other=None)Since variable names are assumed to be columns in the dataframe, regular variables in the local/global namespace can be accessed by prefixing with@In[6]:a=1...:%dfa=@a+1In[7]:defmyfunc(row):...:returnrow+43...:%dfb=a.apply(@myfunc)By default, pandacell operates on any dataframe nameddf. This can be overridden with the-n(or--name) flag:In[8]:%df-n=df_inc=a+bYou can also print subset a dataframe with the-q(or--query) flag:In[9]:%df-qspecies=="setosa"Out[9]:sepal_lengthsepal_widthpetal_lengthpetal_widthspeciesa05.13.51.40.2setosa014.93.01.40.2setosa0In[10]:%df-qspecies.isna()#check for missing valuesOut[10]:EmptyDataFrameColumns:[sepal_length,sepal_width,petal_length,petal_width,species]Index:[]This can be combined with the-iflag to subset the dataframe in-place:In[10]:%df-q-ispecies=="setosa"Pandacell even supports commentsIn[11]:%%df-i...:# Line comment...:c=a+b# Comment at end of lineInspired byhttps://github.com/catherinedevlin/ipython-sqlDevelopmenthttps://github.com/eirki/pandacell
Package: panda-client
How to installDownload the codegit clone https://github.com/PanDAWMS/panda-client.git
cd panda-clientand install itpython setup.py install --prefix=/path/to/install/diror create the tar ballpython setup.py sdist
pip install dist/panda-client-*.tar.gzHow to usesource /path/to/install/dir/etc/panda/panda_setup.[c]sh
prun -h
pathena -hRelease NotesSee ChangeLog.txtCVMFS deploymentLeave the tar ball under: /afs/cern.ch/user/a/atlpan/www/panda-client. The webhttps://atlpan.web.cern.ch/atlpan/panda-client/publishes the afs directory.Update the release notes:https://twiki.cern.ch/twiki/bin/view/PanDA/PandaToolsRequest atlas-adc-tier3sw-install to copy on CVMFSUploading to pippython setup.py sdist uploadUploading source so that wheel generates setup files locally.AcknowledgeIcons fromhttp://iconka.com
Package: panda-client-light
How to installDownload the codegit clone https://github.com/PanDAWMS/panda-client.git
cd panda-clientand install itpython setup.py install --prefix=/path/to/install/diror create the tar ballpython setup.py sdist
pip install dist/panda-client-*.tar.gzHow to usesource /path/to/install/dir/etc/panda/panda_setup.[c]sh
prun -h
pathena -hRelease NotesSee ChangeLog.txtCVMFS deploymentLeave the tar ball under: /afs/cern.ch/user/a/atlpan/www/panda-client. The webhttps://atlpan.web.cern.ch/atlpan/panda-client/publishes the afs directory.Update the release notes:https://twiki.cern.ch/twiki/bin/view/PanDA/PandaToolsRequest atlas-adc-tier3sw-install to copy on CVMFSUploading to pippython setup.py sdist uploadUploading source so that wheel generates setup files locally.AcknowledgeIcons fromhttp://iconka.com
Package: panda-core-data
PandaCoreDataSo, if you already played games like Factorio, Rimworld or Dwarf Fortress and tried to mod them,
you will find that it’s absurdly easy to mod those games for simple things like changing the
balancing, adding items, changing descriptions and etc. Because the data files of the games are
simple raws and not binaries. This library pretty much makes the task of using raws as simple as
possible. Raws in our case is plain text files like xml, json, yaml and etc that
is commonly used to hold data, for now the library supportsyamlandjson.The library might have modding in mind, however it pretty much be used for any sort of software or
game engine that uses python.Internally the library usedataclassesto
handle the data andTinyDBto load them from raws.Thanks for your interest in our package! But for now our things are still a bit of a todo. But, you
can check a basic api documentation here:https://pandacoredata.readthedocs.io/InstallThis package only works with python 3.7 and above because it uses dataclasses.The package is now available with pip, so to install all you need is to run this command:pip install panda-core-dataQuick StartOnce installed, you can run this command:panda_core_data_commands.py -o directory-nameIt will automatically generate the basic directory structure, plus a basic main file.How to CollaborateIf you want to help with the development of this library, I would say that I love you but my
fiancee would get jealous, so I will just say thank you :DBy throwing money at the screenTidelif: We are on Tidelift! So you can get some technical support from them, and they help us. It's a win win! If you are interested,click here(we get some help if you use this referal link too~)Patreon: If you want to help us every month, you can help us by checking our patreon pagehereKo-fi: Do you like Coffee, I love coffee, if you want to send a tip for a coffee, you can do thathereBy providing help with codingFirst, make sure you haveat least Python 3.7, git and pip up and running:python -V
pip -V
git --versiondownload this repository with the following command using git:git clone https://github.com/Cerberus1746/PandaCoreData.gitAnd then cd into the directory with:cd PandaCoreDataNow, if you want to just run the tests to test your changes, you can run:pip install tox
toxIf you want to generate docs, you can install all dependencies with:pip install panda-core-data[docs]And then generate the docs with the command:python setup.py build_sphinxThe docs will be located by default inside the directorydocs/build/htmlSecurity contact informationTo report a security vulnerability, please use theTidelift security contact. Tidelift
will coordinate the fix and disclosure.