Saravanan666/pypi-org huggingface dataset:
Package: vizmetrics
vizmetricsVizMetrics Library for AI ModelsThis is a library that provides tools to calculate various metrics for AI models, including accuracy, precision, recall, F1 score, ROC curve, and confusion matrix. It also includes functions to plot these metrics as graphs and figures.FeaturesCalculates common metrics for AI models
Plots ROC curves and confusion matrices
Provides easy-to-use functions to display metrics and plotsInstallationTo install the library, use pip:pip install vizmetricsUsageHere is an example of how to use the library to calculate and plot metrics for a binary classification model:pythonimport vizmetrics

# Generate some example data
y_true = [0, 1, 0, 1, 0, 0, 1, 1]
y_pred = [0, 1, 0, 0, 1, 0, 1, 1]

# Example
vizmetrics.plot_confusion_matrix(y_true, y_pred)
vizmetrics.accuracy_confusion_matrix_precision_recall_multiclass(y_true, y_pred)
sens_multicalss = vizmetrics.sensitivity_multiclass(y_true, y_pred)


## License
This library is licensed under the MIT License.
Package: vizmyip
vizmyipVisualizes public IP information of your system.InstallationInstallvizmyipwith pip3$pip3install--uservizmyipRun LocallyAfter the installation,$vizmyipFeedback and ContributingContributions are always welcome! And, if you have any feedback or query, please reach out to me athello@amaharjan.de.RelatedHere are some related links for this project:https://amaharjan.de/what-is-my-ip-a-simple-flask-project/LicenseMIT
Package: viznet
# viznet - a network visualization toolbox![](docs/images/viznetlogo.jpg)viznet is designed for visualizing networks composed of nodes and edges, e.g. tensor networks, neural networks and quantum circuits.It is based on and compatible with matplotlib. The theme brush (for both node and edge) makes the design itself interesting, getting you free from fine tuning the node and wire parameters for hours.## To Install```bash$ pip install viznet```or for the latest version```bash$ git clone https://github.com/GiggleLiu/viznet.git$ cd viznet$ pip install -r requirements.txt$ python setup.py install```## To Run Examples```bash$ cd viznet$ python apps/nn/bm.py      # example on neural network$ python apps/tn/tebd.py    # example on tensor network$ python apps/qc/ghz.py     # example on quantum circuit```you will get something likeBoltzmann Machine       | TEBD----------------------- | -------------------------![](docs/images/bm.png) | ![](docs/images/tebd.png)Quantum Circuit           |  Graph Theory--------------------------| -------------------------------![](docs/images/ghz4.png) | ![](docs/images/contract.gif)The theme for neural network follows from [Neural Network Zoo Page](http://www.asimovinstitute.org/neural-network-zoo/),The theme for quantum circuits follows from [ProjectQ](https://github.com/ProjectQ-Framework/ProjectQ.git).## AuthorThe first release of viznet (v0.1) was developed by [Jin-Guo Liu](https://giggleliu.github.io/)  in the group of Lei Wang at IOP China.## Documentation* Go through notebook `docs/viznet_basic.ipynb` ([online](https://drive.google.com/file/d/1mP9DOoTR4JEhd-ILVXfggpBJOyGatiws/view?usp=sharing)) as a quick introduction* Click [here](http://viznet.readthedocs.io/en/latest/) to read the docs!
Package: vizno
viznoLayout python visualizations in HTML reports.viznolays out and renders your Python visualizations in lightweight web pages. They can either be shared as standalone files, or rendered with fastAPI.QuickstartYou can useviznowith your existing Python code in no time:fromviznoimportReportr=Report()f=...# your existing figure generating coder.widget(f)r.render(output_dir)# output a standalone HTML report to a directoryRefer to thedocumentationfor more information.Content supportedviznosupports rendering objects from the major Python visualization libraries:matplotlibaltairbokehplotlypygalIt also supports displayingpandasdataframes as tables (usingtabulator).Finally,viznosupports advanced typesetting within the reports:Markdown titles, labels and all text withsnarkdowncode display withhighlightjsLaTeX documents withlatex.jsMathJax formulas withmathjaxFeaturesviznois easy to use and involves little boilerplate code. Just create aReportand pass it existing figure objects.viznopages can straightforwardly be served withfastapi, or as HTML files renderable in any browserviznois lightweight, it usesPreactand will only retrieve and load libraries that are used in each page. The size of the complete vizno overhead code is < 10kB.viznois extendable, adding your own components to render arbitrary code is very simple.viznoincludes sensible tooling that allows you to quickly iterate on your reports.ContributingContributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make aregreatly appreciated.LicenseDistributed under the MIT License. SeeLICENSEfor more information.
Package: vizplugins
vizpluginsofficial plugins for VizTracer; currently support tracing cpu and memory usage through psutil.InstallThe prefered way to install vizplugins is via pippip install vizpluginsBasic UsageThe vizplugin should be used with viztracer.You can use VizTracer and the plugin byviztracer --plugin vizplugins.cpu_usage -- my_script.py arg1 arg2which will record the cpu percent of the process and generate aresult.htmlfile in the directory you run this command, which you can open with Chrome.The plugin samples cpu usage per 0.02s by default, but you can explicitly indicate the desired frequency at which to sample data per secondviztracer --plugin "vizplugins.cpu_usage -f 20" -- my_script.py arg1 arg2which will sample data approximately 20 times per second, with a sampling interval of 0.05 second.You can also trace the memory usage and cpu usage byviztracer --plugin vizplugins --cpu_usage --memory_usage -- my_script.py arg1 arg2which will record both the cpu and memory usage.ExampleThe below image is an example of the resulting html, which is called on an recursively defined fibonacci funtion.The "cpu_usage" on the top indicates the corresponding cpu usage at each time period. The "memory_usage" have two colors, representing rss(Resident Set Size, the non-swapped physical memory) and vms(Virtual Memory Size). You can see the details by clicking on one of the periods.
Package: vizpool
📊 VizPool 📊A Python Library Having Low-Code Support for Basic to Advance Static & Interactive Data VisualizationOverviewVizPool enables you to create impressive static and interactive visuals with just one line of code while also providing the higher standards of customization. You will be introduced to a number of class methods to choose from. You can call these methods with specific keyword or positional arguments to generate amazing static and interactive visuals.Following are the major contents to follow, you can jump to any section:InstallationUsageGetting Started with VizPool (Tutorials)Contributing🔗 Project LinkVizPoolis being distributed through PyPI. Check out the PyPI PackagehereInstallationInstall via Pip!pipinstallvizpoolUsageImport the components and use it like any other python packageStatic Visualsfromvizpool.staticimportEDA
fromvizpool.staticimportEvaluationInteractive Visualsfromvizpool.interactiveimportEDAQuickstartEnsure you havePython 3.7+installed.Create a new Python conda environment for the vizpool:$ conda create -n venv  # create venv
$ conda activate venv  # activate venv
$ pip install vizpool # install vizpoolCreate a new Python virtual environment with pip for the vizpool:$ python3 -m venv venv  # create venv
$ . venv/bin/activate   # activate venv
$ pip install vizpool # install vizpool👉 PLease follow the links below to get the complete interactive tutorials ongetting stated with VizPool:1)-VizPool Static API2)-VizPool Interactive API👉 PDF versions of the tutorials are available at the following links:1)-VizPool Static API2)-VizPool Interactive APIContributingYes, Please!  We believe that there is alot of oportunity to make even the most complex visuals available for data comunity, so let's make it more efficient, let's go with low-code!!Please give this repository a star if you find our work useful, Thank you! 🙏Copyright © 2022 VizPoolLet's connect onLinkedIn
Package: viz-python-lib
Python Library forVIZThis library is in alpha state, API unstableBuilt on top ofpython-graphenelibDependenciesLinux dependenciessudoapt-getinstalllibffi-devlibssl-devpython-devWindows dependenciesInstall regular version ofOpenSSL(not Light) suitable for your core processor.MacOS dependenciesApple has deprecated use of OpenSSL in favor of its own TLS and crypto libraries. This means that you will need to install and export some OpenSSL settings yourself, before you can install viz-python-lib:brewinstallopenssland then use the following commandsexportCFLAGS="-I$(brew--prefixopenssl)/include"exportLDFLAGS="-L$(brew--prefixopenssl)/lib"InstallationCurrent published version could be installed viapipinstallviz-python-libManual installation:Installpoetrycdviz-python-lib/
poetryinstallUsageBasic read query example:fromvizimportClientfrompprintimportpprintnode='wss://node.viz.cx/ws'viz=Client(node=node)pprint(viz.info())Direct RPC calls:viz.rpc.some_rpc_method()
Package: vizqes
Plot overview of Multiple Sequence Alignments (MSA)Usage:######################################
# vizqes
######################################
usage:
    vizqes -f multifasta alignment
options:
     -f, --fasta=FILE    multifasta alignment (eg. "align.fas")

   [ -o, --outfile=STR   output file (png, eps, jpg) ]
   [ -c, --colorscheme=STR STR in ("default", "clustal", "lesk",
                                   "cinema", "maeditor", "dna",
                                   "aacid") ]
   [ -x, --boxwidth=INT draw INT pixels per residue (x direction) ]
   [ -y, --boxheight=INT draw INT pixels per residue (y direction) ]

adding identifiers:
   [ -s, --show_names     also draw sequence ids ]
   [ -g, --show_grouping] draw colors for match, mismatch, gap, and gapped matches
                          (ignores colorscheme) ]
   [ -F, --font_file=FONT path to truetype font (monospace fonts recommended) ]
Package: vizro
Documentation|Get Started|Live DemoVisual Intelligence. Beautifully engineeredVizro is a toolkit for creating modular data visualization applicationsWhat is Vizro?Rapidly self-serve the assembly of customized dashboards in minutes - without the need for advanced coding or design experience - to create flexible and scalable, Python enabled data visualization applicationsUse a few lines of simple configuration to create complex dashboards, which are automatically assembled utilizing libraries such asPlotlyandDash, with inbuilt coding and design best practicesDefine high level categories within the configuration, including:components:create charts, tables, input/output interfaces, and morecontrols: create filters, parameter inputs, and custom action controllerspages, layouts and navigation: create multiple pages, with customizable layouts and flexible navigation across themactions and interactions: create interactions between charts, and use pre-defined or customized actions (such as exporting)Configuration can be written in multiple formats includingPydantic models,JSON,YAMLorPython dictionariesfor added flexibility of implementationOptional high-code extensions allow almost infinite customization in a modular way, combining the best of low-code and high-code - for flexible and scalable, Python enabled data visualization applications(Visit the"Why Vizro"section to see a more detailed explanation of Vizro use cases)Key benefitsExamplesLive demoInstallationpip install vizroSee theInstall guidefor more informationPlease note this repository is a monorepo and the corevizropackage can be found in/vizro-coreGetting startedSee theTutorialsfor creating your first dashboardDocumentationSee theDocumentationfor more detailsCommunity and DevelopmentWe encourage you to ask and answer technical questions via theGitHub Issues. This is also the place where you can submit bug reports or request new features.ContributingTo learn more about making a contribution,
please see theContributing Guidefor more informationYou can also view current and formercontributorsReporting a Security VulnerabilityPlease see oursecurity policyLicensevizrois distributed under the terms of theApache License 2.0
Package: vizseq
VizSeq is a Python toolkit for visual analysis on text generation tasks like machine translation, summarization,
image captioning, speech translation and video description. It takes multi-modal sources,
text references as well as text predictions as inputs, and analyzes them visually
inJupyter Notebookor a
built-inWeb App(the former hasFairseq integration).
VizSeq also provides a collection ofmulti-process scorersas
a normal Python package.[Paper][Documentation][Blog]Task CoverageSourceExample TasksTextMachine translation, text summarization, dialog generation, grammatical error correction, open-domain question answeringImageImage captioning, image question answering, optical character recognitionAudioSpeech recognition, speech translationVideoVideo descriptionMultimodalMultimodal machine translationMetric CoverageAccelerated with multi-processing/multi-threading.TypeMetricsN-gram-basedBLEU (Papineni et al., 2002), NIST (Doddington, 2002), METEOR (Banerjee et al., 2005), TER (Snover et al., 2006), RIBES (Isozaki et al., 2010), chrF (Popović et al., 2015), GLEU (Wu et al., 2016), ROUGE (Lin, 2004), CIDEr (Vedantam et al., 2015), WEREmbedding-basedLASER (Artetxe and Schwenk, 2018), BERTScore (Zhang et al., 2019)Getting StartedInstallationVizSeq requiresPython 3.6+and currently runs onUnix/LinuxandmacOS/OS X. It will supportWindowsas well in the future.You can install VizSeq from PyPI repository:$pipinstallvizseqOr install it from source:$gitclonehttps://github.com/facebookresearch/vizseq
$cdvizseq
$pipinstall-e.DocumentationJupyter Notebook ExamplesBasic exampleMultimodal Machine TranslationMultilingual Machine TranslationSpeech TranslationFairseq integrationWeb App ExampleDownload example data:$gitclonehttps://github.com/facebookresearch/vizseq
$cdvizseq
$bashget_example_data.shLaunch the web server:$python-mvizseq.server--port9001--data-root./examples/dataAnd then, navigate to the following URL in your web browser:http://localhost:9001LicenseVizSeq is licensed underMIT. See theLICENSEfile for details.CitationPlease cite as@inproceedings{wang2019vizseq,
  title = {VizSeq: A Visual Analysis Toolkit for Text Generation Tasks},
  author = {Changhan Wang, Anirudh Jain, Danlu Chen, Jiatao Gu},
  booktitle = {In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
  year = {2019},
}ContactChanghan Wang (changhan@fb.com), Jiatao Gu (jgu@fb.com)
Package: viztraverse
VizTreeTraversalLeetCode Describes Deserialize & Draw hereOften, LeetCode problems require a slight learning curve to feel comfortable using their TreeNode data structure. One helpful portion of the LeetCode website
describes a detailed example. Have a look at the linked contenthereUsing the productTo install, use pip3 and the command land as follows:pip3installviztraverseOnce installed you can import the library as follows:importviztraversefromviztraverseThen to use the seriealize library:viztraverse.deserialize([1,1,null,1]);And, finally to draw:viztraverse.draw(viztraverse.deserialize([1,1,null,1]);TroubleshootingThis library requires the correct or proper version for the tkanner library. The problem is specific to MacOS from what the resources sayhereNonetheless, if you must face the problem due to failures, here is a common solution:pip3installtk
Package: viztree
viztreeViztree can generate an html for visualizing the directory tree.The directory tree is visualized withFancytree.Requirementsjinja2InstallingYou can install viztree with pip.$ pip install viztreeOr it is possible to install from GitHub repository.$ pip install git+https://github.com/sky-joker/viztree.gitUsageThe html file that has the directory tree does generate by executing the below command.$ viztreeIf you'd like to specify the directory to generate the tree, please specify the path in the argument of the command.$ viztree some_directoryThe skin can change by specifying the skin option.$ viztree --skin lionYou can look at the visualized directory tree by opening the html file with your browser.
Package: viz.txt
AnupamAS01Creating A ServerfromvidstreamimportStreamingServerserver=StreamingServer('127.0.0.1',9999)server.start_server()# Other Code# When You Are Doneserver.stop_server()Creating A ClientfromvidstreamimportCameraClientfromvidstreamimportVideoClientfromvidstreamimportScreenShareClient# Choose Oneclient1=CameraClient('127.0.0.1',9999)client2=VideoClient('127.0.0.1',9999,'video.mp4')client3=ScreenShareClient('127.0.0.1',9999)client1.start_stream()client2.start_stream()client3.start_stream()
Package: vizu
Vizu - the simple CSV-viewerDoing advanced analysis of data in CSV-format can be done with many tools - Excel and Pandas are two popular choises.
However, to quickly browse through the data for simple analysis and exploration, you will need more button-clicks than you should.vizuis meant to bridge the gap by providing a simple UI to browse a CSV file.It uses the excellent librariesdashandpandasunder the hood for GUI and data manipulation, respectively.Installationpip install vizuBrowse your first .csv fileRun the following command in a terminalvizu path/to/file.csvand go to your browser via the link it outputs.
Package: vizydrop-sdk
Vizydrop SDK for PythonThis project provides a Python package that makes it easy to develop a third-party application integration with
Vizydrop.  The SDK provides everything necessary for developers to integrate their own data sources with our data
visualization platform with minimal effort and only a few lines of code.The SDK supports only Python 3.3 and greater.InstallationDownload PackageThe Vizydrop Python SDK can be installed via PyPI, the Python Package Index:pipinstallvizydrop-sdkDownload Source CodeAlternately, you can get the latest development source code for the SDK by usinggit:gitclonehttps://github.com/vizydrop/vizydrop-python-sdkcdvizydrop-python-sdkpythonsetup.pyinstallUsageApplication samples can be found in theexamples <https://github.com/vizydrop/vizydrop-python-sdk/tree/master/examples>folder within the repository.For detailed documentation on integrating with Vizydrop, regardless of if you’re using the official SDK, please visit
ourdeveloper documentation on GitBook <https://www.gitbook.com/book/vizydrop/developers/details>Contributing and Providing FeedbackIf you encounter any bugs with the SDK, pleasefile an issue on GitHub <https://github.com/vizydrop/vizydrop-python-sdk/issues/new>.  If you are a developer, pull requests
are always welcome.
Package: vizzy
This package serves to provide visualizations from your NLP data.This package was inspired by the work of NeptuneAI and this blog post:https://neptune.ai/blog/exploratory-data-analysis-natural-language-processing-toolsThis repository contains the Vizzy package and some sample notebooks to help you get started using Vizzy.To install this package, you can use pip installpip install vizzyThis is the history file of my package.1/20/23: Updated setup.py to fix missing modules issue1/20/23: Updated vizzy package to fix functions2/1/23: Added new functions and object classes2/6/23: Added new functions to Vizzy Doc module2/7/23: Added new functions to Vizzy Token module2/10/23: Added documentation and simplified functions2/15/23: Added functions2/21/23: Updated package
Package: vjson
vjson0.1.0vjson creates an object to serialize the only of the type specified in JSONSchema. It works like a json module.installNext, execute command.:$ pip install vjsonHow to useYou define an object using JSONSchema.:>>> import vjson
>>> _json = vjson.ValidatedJSON({
... 'type': 'object',
... 'properties': {
...     'price': {'type': 'number'},
...     'name': {'type': 'string'},
...     },
... })This object can dumps/loads()/dump()/load() the serializable object, as in the json module.:>>> _json.loads('{"name" : "Eggs", "price" : 34.99}')
{'name': 'Eggs', 'price': 34.99}
>>> _json.dumps({"name": "Eggs", "price": 34.99})
'{"name": "Eggs", "price": 34.99}'If you try to pass the data that violates the JSONSchema that was specified in the constructor, it raises a vjson.JSONValidationError.:>>> _json.loads('{"name" : "Eggs", "price" : "34.99"}')
Traceback (most recent call last):
  File "/tmp/test/var/src/develop/vjson/src/vjson/__init__.py", line 32, in _wrap
    jsonschema.validate(data, schema)
  File "/tmp/test/env/lib/python3.4/site-packages/jsonschema/validators.py", line 478, in validate
    cls(schema, *args, **kwargs).validate(instance)
  File "/tmp/test/env/lib/python3.4/site-packages/jsonschema/validators.py", line 123, in validate
    raise error
jsonschema.exceptions.ValidationError: '34.99' is not of type 'number'

Failed validating 'type' in schema['properties']['price']:
    {'type': 'number'}

On instance['price']:
    '34.99'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/tmp/test/var/src/develop/vjson/src/vjson/__init__.py", line 34, in _wrap
    raise JSONValidationError(err)
vjson.JSONValidationError: '34.99' is not of type 'number'

Failed validating 'type' in schema['properties']['price']:
    {'type': 'number'}

On instance['price']:
    '34.99'
>>>
Package: vk
vk | python vk.com API wrapperThis is a vk.com (the largest Russian social network) python API wrapper.The goal is to support all API methods (current and future) that can be accessed from server.QuickstartInstallpipinstallvkUsage>>>importvk>>>api=vk.API(access_token='...')>>>api.users.get(user_ids=1)[{'id':1,'first_name':'Pavel','last_name':'Durov',...}]See official VKdocumentationfor detailed API guide.More infoRead full documentation onRead the Docs
Package: vk2gpz-geom
vk_pygeomThis is a collection of geometry related python packagesLicenseThis software is released under the condition described in the LICENSE.installpython3 -m pip install vk2gpz-pygeomorpip install git+ssh://git@github.com/vk2gpz/vk_pygeom.git(notice that ':' in "pip install git+ssh://git@github.com:vk2gpz/vk_pygeom.git" needs to be changed to '/')testpython>>> import vk2gpz.geom.grid.geodesicdome as gd
>>> gd.main()build distribution archivepython3 -m pip install --upgrade build
python3 -m builduploading the distribution archive (change testpypi to pypi for official upload)python3 -m pip install --upgrade twine
python3 -m twine upload --repository testpypi dist/*install pacakge from the project locallypip install vk2gpz-geompip install dynamodb_dataframes --no-index --find-links ./dist
Package: vk2telegraph
VK2TELEGRAPHA simple script that publishes articles from VK in Telegra.phInstallationTo install vk2telegraph with pip, run:pip install vk2telegraphUsageYou can create telegra.ph arcticle:python-mvk2telegraph[url]For examplepython-mvk2telegraphhttps://vk.com/@sample-articleLicenseLicensed under theMITLicense.
Package: vk2tg
vk2tgIntegration vk with TelegramInstallUsing pippip install vk2tgUpgrade if needed:pip install vk2tg --upgradeFrom sourcegit clone https://github.com/uburuntu/vk2tg.git
cd vk2tg
python setup.py installUsageExamples:Duplicate all vk events to TelegramRepost all wall posts to Telegram
Package: vk7
This is a framework for extract data from vk.com (russian social network).
The goal is to give helpful interface for work with api and extracting data.QuickstartInstallpipinstallvk7Usage>>>fromvk7importVk>>>>>>vk=VK('username','password','client_id')>>>vk.users.get(user_ids='1,2'){'response':[{'id':1,'first_name':'Павел','last_name':'Дуров'},{'id':2,'first_name':'Александра','last_name':'Владимирова'}]}>>>>>>items=vk.groups.getMembers(group_id=1,fields='bdate,sex')>>>item=next(items)>>>item{'id':5,'first_name':'Илья','last_name':'Перекопский','sex':2,'bdate':'18.11'}Seehttps://vk.com/dev/methodsfor detailed API guide.