Saravanan666/pypi-org huggingface dataset:
Package: clustroai-sdk
ClustroAI SDKClustroAI SDK is a powerful toolkit designed to harness idle computing resources for AI applications. It provides a comprehensive platform for AI enthusiasts and developers to utilize and monetize computing power efficiently.Key FeaturesResource Utilization: ClustroAI SDK helps in tapping into underutilized computing resources, turning them into valuable assets for AI computation.AI Platform Integration: Seamlessly integrates with AI platforms, enabling easy access to computational resources.Common APIscreate_model: Create a new AI model.list_models: List all available AI models.get_model: Retrieve details of a specific model.create_inference_job: Set up a job for model inference.create_worker: Initialize a worker for computation tasks.run: Execute a predefined task or process.username_run: Run a task under a specific user context.WarningIn the clustroai-sdk, the 'create' API requires the 'admin' role for creation. Additionally, the call frequency for other APIs is limited to 10 times per minute.Getting StartedTo get started with ClustroAI SDK, install the package from PyPI:pipinstallclustroai-sdk

fromclustroai_sdkimportClustroAIapi_key="Your Clustro API_Key"clustroai=ClustroAI(api_key,timeout=180)all_models=clustroai.list_models()print(all_models)single_model=clustroai.get_model("097d04a6-1b30-424d-bf55-675fbc405a40")print(single_model)#clustroai.create_inference_job(model_id="9d1a93eb-0c6e-46ff-9014-f265ab04c7bd", name="test_job", set_as_model_default=True)result=clustroai.run(input="A majestic lion jumping from a big stone at night",job_id='4ece46f4-f06d-4962-96c8-91e5c1d08ad6',sync=True)print(result)More InformationFor more information, detailed documentation, and API reference, visitClustroAI.
Package: clustutils4r
Clustering UtilitiesThis packages provides a simple convenience wrapper around some basic sklearn utilities for clustering. The only function available iseval_clustering().Installationpip install clustutils4rAvailable Parametersmodel: Clustering model object (untrained)X: Numpy array containing preprocessed, normalized, complete dataset featuresgt_labels: Numpy array containing encoded ground-truth labels forX(often not available)num_clusters: Range of no. of clusters to grid search over.num_runs: No. of runs per no. of cluster (defaults = 10).make_metrics_plots: Plot various clustering evaluation metrics. Depending on whethergt_labelsare provided, you will get one or two sets of plots - one for non-ground truth-based metrics and another for ground truth-based metrics. (default =True).annotate_topN_best_scores: Whether to annotate top N score in metrics plots (defined byannotN) (defaults =True).annotN: No. of top scores to annotated in metrics plots (defaults = 3).make_silhoutte_plots: Whether to make silhouette plots for eachnum_clustersvalue (default =False).embed_data_in_2d: Whether to compute TSNE embeddings of theXto plotted alongside silhouette plot or plot the first 2 features (default =False).RESULTS_DIR: location to store results; directory will be created if it does not existsave: set True if you want to save all results in RESULTS_DIR; defaults to Falseshow: display all results; useful in notebooks; defaults to FalseExample Usageimportmatplotlib.pyplotasplt%matplotlibinlineimportos,collectionsfromsklearnimportdatasetsfromsklearn.clusterimportKMeansfromsklearn.mixtureimportGaussianMixturefromclustutils4r.eval_clusteringimporteval_clustering## Load the datasetX,y=datasets.make_blobs(n_samples=5*100,centers=5,n_features=2,random_state=0)## Setup modelmodel=KMeans()model_params={'init':'k-means++','n_init':1}n_clusters_param_name='n_clusters'# model = GaussianMixture()# model_params = {'covariance_type':'full', 'n_init':1}# n_clusters_param_name='n_components'## Run the evaluationrange_clusters=list(range(3,10+1))labelled_datapoints,\nongt_metrics,\gt_metrics=eval_clustering(X=X,gt_labels=y,model=model,model_params=model_params,n_clusters_param_name=n_clusters_param_name,num_clusters=range_clusters,num_runs=10,annotate_topN_best_scores=True,annotN=3,make_metrics_plots=True,make_silhoutte_plots=False,show=True,save=True,RESULTS_DIR=os.getcwd()+'/results',)
Package: clutchclient
Clutch ClientThis is the command-line client interface for native/HTML hybrid products of
Clutch.io.Note: You do not need to use this if you’re only using Clutch A/B testing.Commandsstartapp - Starts a new applicationstartscreen - Starts a new screen for your applicationupload - Uploads a new version of your application to your Clutch.io servicedev - Enters into development mode for your Clutch application
Package: clutchless
Other linksDeveloper documentationSupportbtc: bc1q9spjh7nuqatz4pa7dscd0357p3ql588tla6af7Quick startInstall the package:$pipinstallclutchlessThe-hflag can be used to bring up documentation, e.g.clutchless-h:A tool for working with torrents and their data in the Transmission BitTorrent client.

Usage:
    clutchless [options] [-v ...] <command> [<args> ...]

Options:
    -a <address>, --address <address>   Address for Transmission (default is http://localhost:9091/transmission/rpc).
    -h, --help  Show this screen.
    -v, --verbose   Verbose terminal output (multiple -v increase verbosity).

The available clutchless commands are:
    add         Add metainfo files to Transmission (with or without data).
    find        Locate data that belongs to metainfo files.
    link        For torrents with missing data in Transmission, find the data and set the location.
    archive     Copy metainfo files from Transmission for backup.
    organize    Migrate torrents to a new location, sorting them into separate folders for each tracker.
    prune       Clean up things in different contexts (files, torrents, etc.).
    dedupe      Delete duplicate metainfo files from paths.
    rename      Changes the name of metainfo files based on metainfo (torrent name and info hash).

See 'clutchless help <command>' for more information on a specific command.ExamplesTo copy all the metainfo files (.torrent) in Transmission to~/torrent_archive:clutchless archive ~/torrent_archiveTo add some torrents to Transmission, searching~/torrent_archivefor metainfo files and finding data in~/torrent_data:clutchless add ~/torrent_archive -d ~/torrent_dataTo look for matching data given a search folder (~/torrent_data) and a directory (~/torrent_files)
that contains metainfo files:clutchless find ~/torrent_files -d ~/torrent_dataTo organize torrents into folders under~/new_placeand named by tracker, withdefault_folderfor ones missing
a folder name for one reason or another:clutchless organize ~/new_place -d default_folderRemove torrents that are completely missing data:clutchless prune clientRemove metainfo files from some folders (folder1,folder2) that are found in Transmission:clutchless prune folder ~/folder1 ~/folder2To associate torrent to their matching data found in any number of folders (in this case just two):clutchless link ~/data_folder_1 ~/data_folder_2To delete duplicate metainfo files in~/folder1:clutchless dedupe ~/folder1To rename all the metainfo files in~/folder1according to metainfo (format:torrent_name.hash.torrent):clutchless rename ~/folder1
Package: clutchserver
Clutch.ioClutch.io is two projects:Native A/B testing for iOS and AndroidA toolkit for developing hybrid native/HTML applications for iOSYou may be interested in one or the other, but this project is the server
component for both projects.PrerequisitesPython 2.6 or GreaterPostgreSQL (including the required headers to compile psycopg2)libevent 2.0.20S3 Account (for hybrid native/html application framework ONLY)Installing and Running Clutch.ioBefore you get started, make sure all of the prerequisites are installed and
that PostgreSQL is running.  Now we need to create a Clutch user and database:createuser -s clutchcreatedb -E utf8 –owner=clutch clutchNext we need to install Clutch:easy_install clutchserverNow we will generate a configuration file used to setup ports and such:clutch-config > conf.pyYou can check the configuration defaults provided by clutch-config and decide
whether they are right for your setup.  For most people, the defaults should be
just fine.  When you’re ready, let’s start up the server:clutch-all conf.pyThat’s it, you’re now running Clutch.io!  Visithttp://127.0.0.1:8000/to see
it in action.More DocumentationSeehttp://clutchio.github.com/Local DocumentationTo generate a local copy of the above documentation, first check out this repo:git clonehttps://github.com/clutchio/clutch.gitMake sure you have Sphinx installed so that you can generate the docs:easy_install Sphinx==1.1.3Now change to the docs directory and make the docscd clutch/docs
make htmlFinally, open the docs:open _build/html/index.htmlTestsTo run the tests, generate a test configuration file using clutch-config like
above, but instead of using clutch-all to run it, use clutch-test:clutch-test conf.pyThis is one area where this project could use a lot of help.  If you’re
interested in contributing, helping out by improving our test coverage is a
great place to start!
Package: cluttermanager
Clutter ManagerIf you are a clumsy guy like me who clutters up their filesystem with all sorts of files, then this tool is for you.Clutter Manager sorts all the files inside the folders according to their respective types and makes an Index for all the files for easy searching.UsageInstall using PyPIpipinstallcluttermanagerRun cluttermanagercluttermanager--root<pathtoanyclumsydirectory>[--abstract<True/False>][--undo]Usage [Developer]Clone Directorygitclonehttps://github.com/puneet29/cluttermanager.gitChange directorycdcluttermanagerCreate and activate Virtual Environmentpython3-mvenvvenv
.venv/bin/activateInstall cluttermanagerpython3setup.pyinstallRun cluttermanagercluttermanager--root<pathtoanyclumsydirectory>[--abstract<True/False>][--undo]TODOInitial releaseAbstraction parameterUndo clutterMake a PyPI packageDeploy on PyPIIndexingDepth parameterDocumentation
Package: cluwards
Cluwards - CLUCoin CLI Reward TrackerEasily track a wallet's CLUCoin rewards.If you'd like to donate, send some CLU here: 0x44f6498D1403321890F3f2917E00F22dBDE3577aInstallationRequires Python 3.6+ Installedpip install cluwardsorgit clone github.com/M4cs/cluwards
cd cluwards
python setup.py installUsagecluwards ADDROutput in terminal:â•­â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€ CLUCoin Reward Summary: â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â•®
â”‚ Current Balance: 190,356,559.872826358                                       â”‚
â”‚ Total Rewards over last 3 minutes: 5,860.180806946                           â”‚
â”‚ Average Reward per Block over last 1 minute: 147.43492824695                 â”‚
â”‚ Average Reward per Block over last 3 minutes: 97.66968011576666666666666667  â”‚
â”‚ Total Rewards over last 3 minutes: 5,860.180806946                           â”‚
â”‚ Total Rewards Since Tracking Began: 5860.180806946                           â”‚
â•°â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â”€â•¯This will update every 15 seconds.
Package: clvm-rs
Theclvm_rswheel has python bindings for the rust implementation of clvm.BuildUsematurinto build the python interface. First, install into current virtualenv with$ pip install maturinWhile in thewheeldirectory, buildclvm_rsinto the current virtualenv with$ maturin develop --releaseOn UNIX-based platforms, you may get a speed boost onsha256operations by building
with OpenSSL.$ maturin develop --release --features=opensslTo build the wheel, do$ maturin build --releaseor$ maturin build --release --features=openssl
Package: clx-sdk-xms
This is the Python SDK for the CLX Communications REST API (also
called XMS) for sending and receiving single or batch SMS messages. It
also supports scheduled sends, organizing your frequent recipients
into groups, and customizing your message for each recipient using
parametrization.This library is compatible with Python 2.7 and 3.3 and later.Getting StartedThe SDK is packaged usingsetuptoolsand is available in thePyPIrepository under the nameclx-sdk-xms. You can therefore, for
example, usepipto install the library using the commandpip installclx-sdk-xms.After installing the SDK it is recommended to read thetutorialandClient documentation.LicenseThis project is licensed under the Apache License Version 2.0. See the
LICENSE.txt file for the license text.
Package: clygon
clygonClygon is a library built to calculate everything from circles to polygons. You can calculate the interior angles of a polygon, or the area of any n-gon, and even the arc length, radius, or central angle of a circle.To install the package, runpip install clygon==0.0.5in your terminal or cmd prompt.How can I use it?Import the library:from clygon.shapes import Polygon, CircleInstantiate the class:eleven = Polygon(sides=11)Perform your calculations/attributes:print("The shape is called:", eleven.name())
print("The sum of the interior angles is:", eleven.sum_of_interior_angles())
print(eleven.sum_of_interior_angles(exp=True))
print("

 The interior angles are", eleven.interior_angles())
print(eleven.interior_angles(exp=True))Run the code!Example usage for polygons:from clygon.shapes import Polygon

eleven = Polygon(sides=11)
print("The shape is called:", eleven.name())
print("The sum of the interior angles is:", eleven.sum_of_interior_angles())
print(eleven.sum_of_interior_angles(exp=True))
print("

 The interior angles are", eleven.interior_angles())
print(eleven.interior_angles(exp=True))

fourtytwo = Polygon(sides=42)
print(fourtytwo.name())
print("if apothem=5, area =",fourtytwo.area(apothem=5))
print("if base=5, area =",fourtytwo.area(base=5))
print("if base=5, perimeter =",fourtytwo.perimeter(base=5))
print("ext. angles=",fourtytwo.exterior_angles())Output:The shape is called: Hendecagon
The sum of the interior angles is: 1620
The formula for the sum of interior angles is: 180(n-2) where n is the number of sides
180(11 - 2)
180(9)
1620


 The interior angles are 180.0
The formula for each individual interior angle is: 180(n-2)/n where n is the number of sides
180(11 - 2)/11
180(9)/11
1620/11 
147.27272727272728
42-gon
if apothem=5, area = 78.68662202004133
if base=5, area = 3502.819067894399
if base=5, perimeter = 210
ext. angles= 8.571428571428571Example usage for circles:from clygon.shapes import Circle, finder_form

circle = Circle(radius=8)
print("Area:", circle.area())
print("The area of some of the circle is:", circle.part_area(radius=8, central_angle=40))
print("The perimeter is:", circle.perimeter())
print("If the arc length is 50, the central angle is: ", circle.finder(arc_length=50, radius=8))
print("The formula to solve for the central angle is: ", finder_form())Output:Area: 201.06192982974676
The area of some of the circle is: 22.340214425527417
The perimeter is: 50.26548245743669
If the arc length is 50, the central angle is:  358.09862195676453
The formula to solve for the central angle is:  The formula is: Arc Length = (Central angle * π * Radius)/180
Package: clyngor-with-clingo
Clyngor with clingoThis is a python package installing a clingo binary along theclyngor package,
so the end-user will not have to care about the clingo installation.The clingo binary is taken for Linux, OSX and Windows onthe official release pageInstallationWhen someone (who doesn't understand "install clingo binary in your path") have to install clyngor, give them that line instead:pip install clyngor-with-clingoA clingo executable will appear in theirbin. May need root access if the said someone is working at system level.MaintenanceThe package must be updated to use new clingo binaries.Scriptretrieve-clingo.sh <clingo version>will automatically retrieve the given clingo version.Scriptput-clingo-version.sh <clingo version>will automatically push the given clingo version into the package.Usezest.releaserto upload new versions ; be careful tomatch clingo version with package version.How to perform this magicThe current solution: faking clingo as a python scriptLink to the way of doing that. Thanks !I end upreproducing the same entry point implementation, using pkg_resource, and it works:
binaries are embedded in the package using theMANIFEST.in, and the package only real operation
is to delegate command line arguments to the proper clingo binary.This seems to work, but:user has not control over the installed binary (however that package is all about having the user to not have to cope with that, but still… Experienced users should never use it)the 3 binaries are sent to the user, and the choice is made at execution time.The on-the-fly solution: hack upon setuptools to download binary at installationMethod used bypyasp.Has a lot of drawbacks, such as binary downloading from the client side, and necessity to use--no-cache-dirpip flag to force pip to execute the hack.The proper but non-working solution: embed a platform-specific binary into a python packageThe python part of the package is simplistic (well, there could benopython in this package),
bewe still need a basic architecture.platform-specific magicSetuptools provides sincePEP 508the environment markers,
theoreticallyusable in setup.cfgwithsetuptools:[options.data_files]
bin/clingo =
    bin/linux/clingo; platform_system=="Linux"
    bin/macos/clingo; platform_system=="Darwin"
    bin/win/clingo.exe; platform_system=="Windows"But it does not works.A question has been asked about it, alsoon SO.Probably it's because data_files does not support environment markers. Hence this solution has been abandonned.
Package: clype
Playing around with the new type annotations in Python 3.5 and 3.6, I
noticed they can be used to define command line interfaces from a
regular python function. It’s kind of like whatclickdoes, but better.UsageSimpleCli Example:# test.pyfromtypingimportList,OptionalfrompathlibimportPathfromclypeimportSimpleCli@SimpleClidefmycli(v:Optional[bool],paths:List[Path]):print('v:',v)print('paths ({}):'.format(type(paths[0])),*paths)if__name__=='__main__':mycli.run()Result:$ python test.py -v dir/file.ext
v: True
paths (<class 'pathlib.PosixPath'>): dir/file.extSubcommandCli Example:# test.pyfromtypingimportList,OptionalfrompathlibimportPathfromclypeimportSubcommandClimycli=SubcommandCli('mycli')@mycli.commanddefbar(r:Optional[bool],path:Path):"""
    The first command
    """pass@mycli.commanddeffoo(v:Optional[bool],paths:List[Path]):"""
    The second command
    """passif__name__=='__main__':mycli.run()Result:$ python test.py -h
usage: mycli [-h] command ...
optional arguments:
  -h, --help  show this help message and exit
commands:
  bar       The first command
  foo       The second command
$ python test.py bar -h
usage: mycli bar [-h] [-r] path
positional arguments:
  path
optional arguments:
  -h, --help  show this help message and exit
  -r
Package: clypper
clypperRapidly create supercuts from various video sources.InstallationpipinstallclypperUsageA text file specifying the video source url as well as start and end timestamps can be converted to a supercut using a single command:$catinput.txt
https://www.youtube.com/watch?v=dQw4w9WgXcQ0:430:44
https://www.youtube.com/watch?v=o0u4M6vppCI1:551:59
$clypper-iinput.txt-osupercut.mp4[..]$filesupercut.mp4
supercut.mp4:ISOMedia,MP4BaseMediav1[IS014496-12:2003]Developer notesMaking a new release$bump2versionpatch# minor major$poetrypublish--build
Package: cly-why
Why?I wanted a simple library to write small to moderate cli programs.
It only uses the standard library.Why not X?X = argparseIts way more then what I need 99% of the time.X = clickI don't particularly like decorators.X = richI like pprint, but it always seems like to muchX = typerI've used typer a bit, but it never clicked with me.Core FunctionsText-Decorate and ColorizeTake a string and color/text-decoration name and returns the string wrapped in its ansi codeClyEntrypoint function
By default ignores functions that start with '_'/underscoreFeature ListColorize and Text DecorateTestsAutomatic Fish Shell CompletionsPromptsText PromptMultiline PromptFzf SelectorDate Selector2 line functionalityimportcly_whyif__name__=="__main__":cly_why.cly()
Package: cm
This module will present simplest mechanism for working with command line options and arguments.Example of the usage bellow:importcmfromcm.options.pathimportbasefromcm.options.dbimportport,nameport.type=intport.default=10port.help="Lolwat"base.help="Base path"if__name__=='__main__':cm.parse_command_line()and try to run it$ python test.py--helpList of available program options:
Group "db"
    --db-port       Lolwat [default: "10"]
    --db-name


Group "path"
    --path-base     Base path
Package: cm2diffop
SourcesCalc_3d.pyCalc_diff_ops.pyTaylor.pyGet_Diff_Op_mat_vec.pyRequired pacakgesnumpy:conda intall numpyscipy:conda install scipyicecream:conda install icecream(conda-forge channel)progress:conda install progresscm2utils:[your anaconda env]/bin/pip install cm2utils, developed by CM2Lab.Last updateApril 26, 2021
Package: cm2mem
cm2memTo use, initialize a Memory instance. Use massive=False if you're using aMassMemoryand not aMassiveMemory.
Use the Memory class as if it were an array, for example:print(mem[123])ormem[123] = 255.
You can also use binary strings as indexes and values, for example:print(mem['00000011'])ormem['0b00000011'] = '00000001'To initialize a Memory object from pre-existing data (data you copied from a Memory ingame), useUtil.load(data). (This will automatically determine the type of memory aswell)You can use the various functions under thePremadeclass to (quickly) write values to aMassiveMemorythat allow you to use theMassiveMemoryas a multiplier, adder, etc..Premadeusage example:from cm2mem import *
mem = Memory()
Premade.multiplier(mem)
print(mem.pack())The functions under thePremadeclass ONLY work withMassiveMemoryYou can find a couple utility functions under theUtilclass.If you need help with anything, feel free to DM me on Discord @animepfpMay break if memory in Circuit Maker 2 is modified. (DM me if that happens, or if you find a bug)
Package: cm2mem-gsq
cm2memTo use, initialize a Memory instance. Use massive=False if you're using aMassMemoryand not aMassiveMemory.
Use the Memory class as if it were an array, for example:print(mem[123])ormem[123] = 255.You can use the various functions under thepremadeclass to (quickly) write values to aMassiveMemorythat allow you to use theMassiveMemoryas a multiplier, adder, etc..The functions under thepremadeclass ONLY work withMassiveMemoryIf you need help with anything, feel free to DM me on Discord @animepfpMay break if memory in Circuit Maker 2 is modified. (DM me if that happens, or if you find a bug)