Saravanan666/pypi-org huggingface dataset:
Package: dv-mock-api
DV360 Mock apiThe DV360 mock api is a static api that can be configured to return many reponses like the DV360 and DBM api's. The difference is the calls are not real.LocalIf you want to run locally please use avirtual environment. This can be done withpipenv. Next you can run the./main.pyfile. This will start a simple flask server with all endpoints.To be able to test make sure to add thegoogle-credentials.jsonOAuth credentials to thesecretsfolder.If you want to test the application you can use themake run_all_testscommand. To add new tests, create a new test in thetestsfolder and add it to the makefile. This will ensure the tests are ran in the pipeline.UsageTo use the mock api in your testing suite make sure to target thedv360-mock-apihost. If you are using thegoogleapipackage, you will need to change the discovery url.This will look like the following:service=discovery.build(api_service,api_version,http=self.http,discoveryServiceUrl=f"http://localhost:5050/discover/{api_service}/{api_version}")When running the tests you will need to use therunnerthis will start the fake api in a seperate thread on port:5050. This will look like so:fromdjango.testimportTestCasefromdv_mock_apiimportrunnerclassATestCase(TestCase):defsetUp(self):runner.create_app()deftest_some_method(self):pass# do testing here
Package: dvoryan
рџ’Ў Instead of the code in this repository, it is recommended to use thenon-negativity-constraineddiffusion kurtosis imaging available in, for example,DIPY.dkmri.pydkmri.pystands for diffusion kurtosis magnetic resonance imaging in Python. It is a Python package for estimating diffusion and kurtosis tensors from diffusion-weighted magnetic resonance data. The estimation is performed using regularized non-linear optimization informed by a fully-connected feed-forward neural network that is trained to learn the mapping from data to kurtosis metrics. Details can be found in thearXiv preprintandsource code.This software can be used from the command line or in a Python interpreter.The command-line interface does not require any knowledge about Python.Python interface is for people comfortable with basic Python programming.InstallationFirst, make sure you have installedPython.If you just want to use the command-line interface, the recommended way of installingdkmri.pyis to usepipx:pipx install dkmripipx automatically creates an isolated environment in which the dependencies are installed.If you want to use the Python interface, you can usepip(you should installdkmri.pyin an isolated environment usingvenvorcondato avoid dependency issues):pip install dkmriUsage exampleCommand-line interfaceThe command for usingdkmri.pyisdkmri.py data bvals bvecs optional-argumentswheredata,bvals, andbvecsare the paths of the files containing the
diffusion-weighted data, b-values, and b-vectors, andoptional-argumentsis
where to define things such as which parameter maps to save.For example, a command for computing a mean kurtosis map fromdata.nii.gzand
saving it inmk.nii.gzcould bedkmri.py data.nii.gz bvals.txt bvecs.txt -mask mask.nii.gz -mk mk.nii.gzTo see a full description of the arguments, execute the following:dkmri.py -hPython interfaceSee theexample notebook.SupportIf you have questions, found bugs, or need help, please open anissue on Github.CitationIf you find this repository useful in work that leads to a scientific publication, please cite thearXiv preprint.
Package: dvp
The Delphix Virtualization SDK helps developers build plugins to ingest and provision data on top of the Delphix platform. For more information please refer to thedocumentation.Getting StartedPlease refer to theGetting Startedsection of the documentation.DisclaimerThe software is provided “as-is” without any warranties of any kind. To the maximum extent permitted by applicable law, Delphix Corp. and its affiliates disclaim any liability, implied warranties, including, without limitation, any implied warranties of merchantability, fitness for a particular purpose and non-infringement of intellectual property rights.
Package: dvp-api
Delphix Virtualization Platform APIThis API helps developers build plugins to ingest and provision data on top of the Delphix Virtualization Platform.
The API is fully generated based on protobuf definitions. Currently, plugin developers are not expected to work directly
against this API but instead use the Virtualization SDK that makes creation of platform plugins easy. For details on the
Virtualization SDK, please refer to itsdocumentation.DisclaimerThe software is provided “as-is” without any warranties of any kind. To the maximum extent permitted by applicable law,
Delphix Corp. and its affiliates disclaim any liability, implied warranties, including, without limitation, any implied
warranties of merchantability, fitness for a particular purpose and non-infringement of intellectual property rights.
Package: dvp-common
Standalone installation of this package is not supported.Please install thedvppackage which will install this package.DisclaimerThe software is provided “as-is” without any warranties of any kind. To the maximum extent permitted by applicable law, Delphix Corp. and its affiliates disclaim any liability, implied warranties, including, without limitation, any implied warranties of merchantability, fitness for a particular purpose and non-infringement of intellectual property rights.
Package: dvpipe
dvpipeA small Python utility for piping data from function to function in sequential order.dvpipe allows you to pass data from function to function sequentially as you would in
tradional method chaining. You can use dvpipe to transform any type of data not
just DataFrames as withDataFrame.pipe()Installation$ pip install dvpipeUsageprocessed_data=pipe(data,func_a,func_b,func_c,...)Examplefromdvpipeimportpipedata=(pipe(data,clean,transform,aggregate))Why?dvpipe attempts to help solve this classic problem seen in many data tranformation applications to allow for cleaner, more understandable code.data=clean(data)data=transform(data)data=aggregate(data)Functions with ArgumentsUse Python tuples for functions with parameters.df=pipe(df,(replace_foo,'bar'))Full Examplefromdvpipeimportpiperaw_data={'foo':1,'bar':2}defsubtract_foo(data):data['foo']=data['foo']-1returndatadefadd_bar(data):data['bar']=data['bar']+1returndatadefadd_entry(data,entry):data.update(entry)returndatadata=(pipe(raw_data,subtract_foo,add_bar,(add_entry,{'foobar':5})))
Package: dvplc
NAMEdvplc- encode/decode/verify Dava game engine's SmartDLC DVPL files.STATUSTested on Linux & Working :-)TODOTest on other platformsInstallationPython 3.10+ is requiredMy recommendation is to usegitas yourpackage manager.# Clone repo
git clone --recurse-submodules https://github.com/Jylpah/dvplc.git

# Install required Python modules with Python pip
cd dvplc
pip install -r requirements.txtIfyou forgot to add the--recurse-submodulesoption togit cloneyou can rungit submodule update --initafter cloning the repository.Updategit pull --recurse-submodulesSYNOPSISdvplc [OPTIONS] MODE FILE | DIR [FILE | DIR] ...DESCRIPTIONMODEencode- Encode source files to DVPL formatdecode- Decode DVPL files to source filesverify- Verify DVPL filesGENERAL OPTIONS--verboseVerbose logging messages--debugShow debug logging messages--silentSilence logging messages--forceOverwrite files, default isFalse--threadsINTNumber of worker threads. By default the number of threads are defined automatically.--keepPlace converted files to the same directory as source files (default)--replaceDelete source files after conversion--mirrorDIRMirror source tree structure to DIR and place converted files there. All source files have to be under working dir.encodeOPTIONS--compressionlz4|lz4_hc|rfc1951|noneDVPL File formatCreditsMaddoxkkmUINT32LE compression Type0: no compression (format used in all uncompressed .dvpl files from SmartDLC)1: LZ4 (not observed but handled by this decompressor)2: LZ4_HC (format used in all compressed .dvpl files from SmartDLC)3: RFC1951 (not implemented in this decompressor since it's not observed)UINT32LE compression Type:0: no compression (format used in all uncompressed .dvpl files from SmartDLC)1: LZ4 (not observed but handled by this decompressor)2: LZ4_HC (format used in all compressed .dvpl files from SmartDLC)3: RFC1951 (not implemented in this decompressor since it's not observed)
Package: dvp-libs
Standalone installation of this package is not supported.Please install thedvppackage which will install this package.DisclaimerThe software is provided “as-is” without any warranties of any kind. To the maximum extent permitted by applicable law, Delphix Corp. and its affiliates disclaim any liability, implied warranties, including, without limitation, any implied warranties of merchantability, fitness for a particular purpose and non-infringement of intellectual property rights.
Package: dvpn
DieVPNTool that allows to switch between VPNs with ease and speedSupportedVPNsAnyConnectVPN- CiscoTunnelblickViscosityOSMacOSLinux (Debian, Ubuntu, ...)WindowsPython3.7+InstallingInstall and update usingpip:pipinstalldvpn

or

pip3installdvpnHow to set up with GUIUsedvpn guiin terminal to add your VPNs, passwords and usernames are stored in plaintext so be sure to have disk
encrypted.If it seems applications is freezing, it is just side effect of compatibility solution on OSX and not using threaded
connection/disconnection currently#TODOjust wait it will finishPlease be patient and don't click multiple times on buttons in same timeHow to set up with CLICopytemplate_secret.jsontopackage/config/secret.jsonEdit secret accordingly to json format and your credentialsNow you can use cli commandsFuture Release will contain auto vpn resolvedvpn autoresolveFor Tunnelblick you must install tunnelblickctlon macOS use:brew tap benwebber/tunnelblickctl
brew install tunnelblickctlHow to set up ManuallyClone repository withgit clone https://github.com/jiri-otoupal/dievpn.gitInstall requirements withpip install -r requirements.txt(ignore / delete windows requirements pywin32 & wexpect if
your pip is trying to install them)Copytemplate_secret.jsontopackage/config/secret.jsonEdit secret accordingly to json format and your credentialsUsageAll commands need to be launched in os terminal not in Pycharm terminalAccess all functions through guidvpn guior CLIConnect to VPN specified inconfig/secret.jsondvpn connect {name_in_credentials}Disconnect from any currently connected VPNdvpn disconnect
Package: dvp-platform
Standalone installation of this package is not supported.Please install thedvppackage which will install this package.DisclaimerThe software is provided “as-is” without any warranties of any kind. To the maximum extent permitted by applicable law, Delphix Corp. and its affiliates disclaim any liability, implied warranties, including, without limitation, any implied warranties of merchantability, fitness for a particular purpose and non-infringement of intellectual property rights.
Package: dvp-tools
Standalone installation of this package is not supported.Please install thedvppackage which will install this package.DisclaimerThe software is provided “as-is” without any warranties of any kind. To the maximum extent permitted by applicable law, Delphix Corp. and its affiliates disclaim any liability, implied warranties, including, without limitation, any implied warranties of merchantability, fitness for a particular purpose and non-infringement of intellectual property rights.
Package: dvq
DVQ - DNA Validations and Quick comparisonsA package with some useful functions to compare DNA sequences both visually and statistically.Methods:Persistant Homological RepresentationsColorSquareC-Curve- Removed from development plan due it being redundant vs a 2D LineSpider Representation- Removed from development plan due to it being found to be difficult to use for large sequencesKL DivergencePerpelxityEntropy2D LineK-Mer overlapWen's MethodOverview:How to use dvqfromdvqimportvisualvisual.plot_2d_comparison([seqs_1,seqs_2],['seq_1','seq_2'])
Package: dvrip
Home-page:https://github.com/alexshpilkin/dvripAuthor: Alexander Shpilkin
Author-email:ashpilkin@gmail.comLicense: UNKNOWN
Description: UNKNOWN
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: System Administrators
Classifier: License :: CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Communications
Classifier: Topic :: Internet
Classifier: Topic :: Multimedia :: Sound/Audio :: Capture/Recording
Classifier: Topic :: Multimedia :: Video :: Capture
Classifier: Topic :: Office/Business
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Requires-Python: >=3.7, <4
Description-Content-Type: text/x-rst
Provides-Extra: dvr-find
Provides-Extra: dvr-time
Package: dvr-scan
Video Motion Event Detection and Extraction ToolWebsite:http://www.dvr-scan.com/Documentation:http://dvr-scan.readthedocs.org/Github:https://github.com/Breakthrough/DVR-Scan/DVR-Scan is a command-line application thatautomatically detects motion events in video files(e.g. security camera footage).  DVR-Scan looks for areas in footage containing motion, and saves each event to a separate video clip.  DVR-Scan is free and open-source software, and works on Windows, Linux, and Mac.QuickstartInstall usingpip:pip install –upgrade dvr-scan[opencv]Scanvideo.mp4(separate clips for each event):dvr-scan -i video.mp4Only scan a region of interest (see user guideor hitHfor controls):dvr-scan -i video.mp4 -rDraw boxes around motion:dvr-scan -i video.mp4 -bbUseffmpegto extract events:dvr-scan -i video.mp4 -m ffmpegFor help or other issues, feel free to submit any bugs or feature requests to Github:https://github.com/Breakthrough/DVR-Scan/issuesLicensed under BSD 2-Clause (see theLICENSEfile for details).Copyright (C) 2016-2023 Brandon Castellano.
All rights reserved.
Package: dvsgc
DVS Gesture ChainOfficial implementation of the dataset defined inSpiking Neural Networks for event-based action recognition: A new task to understand their advantageInstallationFrom PyPI:pip install dvsgcFromGitHub source code:git clone https://github.com/VicenteAlex/DVS-Gesture-Chain.git
pip install requirementsDocumentationJust instantiate DVSGestureChain and run it as a torchvision.datasets.DatasetFolder:Inherits fromtorchvision.datasets.DatasetFolderCLASS dvsgc.DVSGestureChain(
            root, frames_number, split, validation=0.2, split_by='number', alpha_min=0.5, alpha_max=0.7, seq_len=4,
            class_num=3, repeat=True, dvsg_path=None, transform=None, target_transform=None)Arguments:root(str): root path of the datasetframes_number(int): the integrated frame numbersplit(str): split from: ['train', 'validation', 'test']validation(float): fraction of the training set to use for validationsplit_by(str):timeornumberalpha_min(float): lower bound for the gesture duration as a factor of its total durationalpha_max(float): upper bound for the gesture duration as a factor of its total durationseq_len(int): number of gestures in the chainclass_num(int): number of classes to use (up to 11)repeat(bool): whether to allow repetition of the same gesture twice in a rowdvsg_path(str): If DVS-Gesture events are saved in another folder they can be retrieved by indicating the path
here, else they will be created again in roottransform(Optional[Callable]): a function/transform that takes in a sample and returns a transformed version.target_transform(Optional[Callable]): a function/transform that takes in the target and transforms it.Usage:Example:train_set = dvsgc.DVSGestureChain(root=dataset_dir, split='train', frames_number=T)
train_loader = torch.utils.data.DataLoader(train_set, batch_size=N, shuffle=True, num_workers=4, pin_memory=True, drop_last=True)

validation_set = dvsgc.DVSGestureChain(root=dataset_dir, split='validation', frames_number=T)
validation_loader = torch.utils.data.DataLoader(validation_set, batch_size=N, shuffle=True, num_workers=4, pin_memory=True, drop_last=True)Downloading the data:DVS-GC requires to download the data from the originalDVS-Gesture dataset,
as this is not downloaded automatically, the first time the dataset is used the following message will appear:
"This dataset can not be downloaded automatically, please download files manually and put files atroot/download".
Follow the instructions and download the DVS-Gesture files into that folder. Then re-run.Saving memory:The first time the dataset is used, the code will extract DVS-Gestures to the folder "extract", then build events from
it in the folder "events_np" and then, from those events, create the frames for the DVS-GC dataset in a "DVSGC..." folder.Once events_np is created, the extract folder and download folder are no longer necessary.The "events_np" folder will be used every time a new DVS-GC dataset is created with different parameters. Alternatively,
if an already existing DVS-GC dataset is used, "events_np" is not necessary.
Package: dvsportal
DVSPortalAsynchronous Python client for the DVSPortal API. This library provides an easy-to-use async interface to interact with the DVSPortal API, allowing for operations such as fetching balances, creating reservations, and managing license plates.InstallationTo install DVSPortal, run the following command in your terminal:pipinstalldvsportalEnsure you are using Python 3.9 or newer, as this library utilizes modern Python features and type hinting.RequirementsPython 3.9+aiohttpasync_timeoutyarlThese dependencies will be automatically installed when you install the DVSPortal package.Quick StartHere's a quick example to get you started:importasynciofromdvsportalimportDVSPortalasyncdefmain():asyncwithDVSPortal(api_host='api.example.com',identifier='your_identifier',password='your_password')asportal:awaitportal.update()print(f"Balance:{portal.balance}")print(f"Unit Price:{portal.unit_price}")print(f"Active Reservations:{portal.active_reservations}")if__name__=='__main__':asyncio.run(main())Replace'api.example.com','your_identifier', and'your_password'with your actual DVSPortal API host and credentials.ExamplesCreating a ReservationTo create a reservation for a license plate:importasynciofromdvsportalimportDVSPortalfromdatetimeimportdatetime,timedeltaasyncdefcreate_reservation():asyncwithDVSPortal(api_host='api.example.com',identifier='your_identifier',password='your_password')asportal:awaitportal.create_reservation(license_plate_value='ABC123',date_from=datetime.now(),date_until=datetime.now()+timedelta(days=1))print("Reservation created successfully.")if__name__=='__main__':asyncio.run(create_reservation())Managing License PlatesTo add a new license plate:importasynciofromdvsportalimportDVSPortalasyncdefadd_license_plate():asyncwithDVSPortal(api_host='api.example.com',identifier='your_identifier',password='your_password')asportal:awaitportal.store_license_plate(license_plate='ABC123',name='My Car')print("License plate added successfully.")if__name__=='__main__':asyncio.run(add_license_plate())FeaturesAsynchronous API communicationFetching account balance and unit pricesManaging reservationsHandling license platesHow to ContributeFork the repository on GitHub.Clone your forked repository to your local machine.Create a new branch for your feature or bug fix.Implement your changes.Run tests to ensure your changes don't break existing functionality.Commit your changes with a clear commit message.Push your changes to your fork on GitHub.Submit a pull request from your fork to the main DVSPortal repository.Before contributing, please read the contribution guidelines in the CONTRIBUTING.md file.LicenseDVSPortal is released under the MIT License. See the LICENSE file for more details.AcknowledgementsThis project is developed and maintained by [Your Name or Organization]. Contributions from the open-source community are welcome.
Package: dvs-printf
simple pritning animetion styles for python Projectdvs_printf - GitHubInstallationjust copy and past this oneliner command on TerminalLinux / macOSpip3installdvs_printfpython3-mpipinstalldvs_printfWindowspipinstalldvs_printf

python-mpipinstalldvs_printfDocumentationdvs_printfThis function makes your python project looks good,
by using printf's styl animetion function you can print you stream in uniq stylesprintf function keywordsfromdvs_printfimportprintfprintf(*values,styl='typing',speed=3,intervel=2,stay=True)valuesvalues stream can be anythin like(string, int, float, list, set, tuple, dict)and you can give multiple input as any-data-typeprintf(str,list,[tuple,set],dict,int,...)stylstyl is different types of print animetion
each style type works differently according to description below["typing","headline","mid","f2b","b2f","gunshort","sniper","metrix","metrix2","firing","help"]optiondescriptiontypingprint like typingheadlineprint like head lines in newsmidprint line from midf2bremove word from (back to front)b2fremove word from (front to back)gunshortfiring the words from short gunsnipersniping the words from end of the terminalmetrixprint random words to real linemetrix2print 1st word and 2nd random wordfiringjust look like firing (Just For Fun)speedSpeed is printf's animetion speed,defult speed is 3you can setspeed from ( 1 to 6 )1 = Very Slow
2 = Slow
3 = Mediam
4 = Mediam Fast
5 = Fast
6 = Very Fastprintf("hello world",speed=2)intervelintervel is waiting time between printing
of two lines (intervel in second)defult intervel is 2,
you can set intervel from0 to 10 or greaterprintf("hello world","hii I am coder",intervel=2)>>>helloworld(Thenwatingtimeofinterveltimeinsecond)>>>hiiIamcoderstaystay decides after styl animetion whether you want thestream OR Not.stay can be True or False,(defult stay = True).if you want to remove printed line. you can setstay=False.So, After styl amimetion and intervel time printed Line can be removes.but some stylestake No action on stay,
whether it isTrue OR False. it works as it should be.Ex.(typing, f2b, b2f, metrix, metrix2)printf("hello world",styl="headline",stay=True)listfunctionlistfunction(*values:any,getMet:bool|None=False)->listAn additionl function which is used by printf functionlistfunction( ) takesAny DataTypein input and return a new list.
created by input values & it break deta sets by index and add them into
new list then return that list.getMetdetult getMet = Falseif metrix is given, setgetMet=True,
it breaks metix inrows by indexand convet that in to string.
Package: dvtag
DVTAGA tool for tagging your doujin voice library.InstallationRequire Python>=3.9pipinstalldvtagUsage$ dvtag -h
usage: dvtag [-h] [-w2f] [-w2m] dirpath

Doujin Voice Tagging Tool (tagging in place)

positional arguments:
  dirpath     a required directory path

options:
  -h, --help  show this help message and exit
  -w2f        transcode all wav files to flac [LOSELESS] (default: False)
  -w2m        transcode all wav files to mp3 (default: False)You must ensure that every doujin voice folder name contains a specific id format(in dlsite) - likeRJ123123,rj123123 xxx,xxxx RJ123123├── EXcute
│   ├── RJ321580
│   └── RJ328009
│
├── Kaleidoscope
│   └── RJ329141
│
├── PINK PUNK PRO
│   └── RJ321217
│
├── plug in.XX
│   ├── [RJ310972][XXXxx][plug in.XX]
│   └── RJ341111
│
├── ReApple
│   ├── [RJ263247]
│   └── RJ301616Then tagging with commanddvtag:dvtag/path/to/your/libraryIf you havewavaudio files and you want to convert these all toflac/mp3, run with option-w2f/-w2m. For exampledvtag-w2f/path/to/your/library