Saravanan666/pypi-org huggingface dataset:
Package: neoteroi-di
Implementation of dependency injection for Python 3Features:types resolution by signature types annotations (type hints)types resolution by class annotations (type hints)types resolution by names and aliases (convention over configuration)unintrusive: builds objects graphwithoutthe need to change the
source code of classesminimum overhead to obtain services, once the objects graph is builtsupport for singletons, transient, and scoped servicesThis library is freely inspired by .NET StandardMicrosoft.Extensions.DependencyInjectionimplementation (ref.MSDN,
Dependency injection in ASP.NET
Core,Using dependency injection in a .Net Core console
application).
TheContainerProtocolfor v2 is inspired bypunq.Installationpipinstallneoteroi-dineoteroi-diis the new version of the library that was previously namedrodi. It is currentlyalphaand still
subject to change.Efficientneoteroi-diworks by inspecting codeonceat runtime, to generate
functions that return instances of desired types - as long as the object graph
is not altered. Inspections are done either on constructors
(__init__) or class annotations. Validation steps, for
example to detect circular dependencies or missing services, are done when
building these functions, so additional validation is not needed when
activating services.Flexibleneoteroi-dioffers two code APIs:one is kept as generic as possible, using aContainerProtocolfor scenarios
in which it is desirable being able to replaceneoteroi-diwith alternative
implementations of dependency injection for Python. The protocol only expects
a class being able toregisterandresolvetypes, and to tell if a type
is configured in it (__contains__). Even if other implementations of DI
don´t implement these three methods, it should be easy to usecompositionto
wrap other libraries with a compatible class.one is a more concrete implementation, following the previous implementation
inrodi, for scenarios where it's not desirable to consider alternative
implementations of dependency injection.For this reason, the examples report two ways to achieve certain things.ExamplesFor examples, refer to theexamples folder.Recommended practicesAll services should be configured once, when an application starts, and the
object graph shouldnotbe altered during normal program execution.
Example: if you build a web application, configure the object graph when
bootstrapping the application, avoid altering theContainerconfiguration
while handling web requests.Aim at keeping theContainerand service graphs abstracted from the front-end
layer of your application, and avoid mixing runtime values with container
configuration. Example: if you build a web application, avoid if possible
relying on the HTTP Request object being a service registered in your container.Service life style:singleton - instantiated only once per service providertransient - services are instantiated every time they are requiredscoped - instantiated only once per root service resolution call
(e.g. once per web request)Usage in BlackSheepneoteroi-diis used in the second version ofBlackSheepweb framework to implementdependency injectionfor
request handlers.DocumentationUnder construction. 🚧
Package: neoteroi-mkdocs
Plugins for MkDocs and Python Markdownpipinstallneoteroi-mkdocsThis package includes the following plugins and extensions:NameDescriptionmkdocsoadGenerates documentation from OpenAPI specification files.cardsComponent to display cards.timelineComponent to display chronological information with style.ganttComponent to display Gantt diagrams.spantableTables supporting colspan and rowspan.contribsMkDocs plugin to display last commit time and contributors for each file.DocumentationRefer to thedocumentation site. :rocket:PreviewCards extensionGreek Mythology icons made bymax.iconsfromwww.flaticon.comGantt extensionTimeline extensionOpenAPI Documentation extension
Package: neotime
Theneotimemodule defines classes for working with temporal data to nanosecond precision.
These classes comprise a similar set to that provided by the standard librarydatetimemodule.
Inspiration has also been drawn fromISO-8601.OverviewThe classes are listed below:DurationDateTimeDateTimeTODOInstallationTo install the latest stable version of neotime, simply use pip:$ pip install --pre neotimeOr to install the latest bleeding edge code directly from GitHub, use:$ pip install git+https://github.com/technige/neotime.git#egg=neotimeNote that code installed directly from GitHub is likely to be unstable.
Your mileage may vary.More InformationFor more information, read thedocs.
Package: neo-toolbox
Neo ToolboxSmall toolkit for interacting with the Neo N3 blockchain.Available toolsData TransformationCreate Owner BytesCreate Update Invocation FileData TransformationLets you convert between wallet hashes and addresses.Examplefromneo_toolbox.data_transformationimportencode_hash,decode_address# Encode a wallet hashoriginal_hash_hex='a7271ccc82bb311db369719d1868e6ac19ece31f'address=encode_hash(original_hash_hex)print(address)# Outputs: 'NNpbB25aNMY2pD5JkWeAEbsNfp7C3GoZF1'# Decode a wallet addressoriginal_address='NNpbB25aNMY2pD5JkWeAEbsNfp7C3GoZF1'hash_hex=decode_address(original_address)print(hash_hex)# Outputs: 'a7271ccc82bb311db369719d1868e6ac19ece31f'Create Owner BytesThis helper function lets you convert a N3 wallet address to an python variable that can be used
in your smart contract to verify the owner of the contract. This is very useful to add admin
functionality to your smart contract.Examplefromneo_toolbox.create_owner_bytesimportcreate_owner_bytesoriginal_address='NNpbB25aNMY2pD5JkWeAEbsNfp7C3GoZF1'code_snippet=create_owner_bytes(original_address)print(code_snippet)# Outputs: 'OWNER = UInt160(b"\x1f\xe3\xec\x19\xac\xe6h\x18\x9dqi\xb3\x1d1\xbb\x82\xcc\x1c'\xa7")'Create Update Invocation FileThis helper function lets you create aNeo Expressinvocation file that can be used to update a smart contract.Examplefromneo_toolbox.create_update_invocation_fileimportcreate_update_invocation_filenef_file='path/to/sample_contract.nef'manifest_file='path/to/sample_contract.manifest.json'template=create_update_invocation_file('your_contract_name',nef_file,manifest_file,operation='my_custom_update')print(template)# Outputs a JSON string: '[{"contract": ...'Created and maintained by Adapted Consulting AS (Norway).
Package: neovim-gui
### Python Gtk gui for [Neovim](https://github.com/neovim/neovim)[![Build Status](https://travis-ci.org/neovim/python-gui.svg?branch=master)](https://travis-ci.org/neovim/python-gui)
[![Scrutinizer Code Quality](https://scrutinizer-ci.com/g/neovim/python-gui/badges/quality-score.png?b=master)](https://scrutinizer-ci.com/g/neovim/python-gui/?branch=master)
[![Code Coverage](https://scrutinizer-ci.com/g/neovim/python-gui/badges/coverage.png?b=master)](https://scrutinizer-ci.com/g/neovim/python-gui/?branch=master)Simple nvim gui implemented using Gtk#### Installation`sh pip installneovim-gui`#### Usage`sh pynvim `
Package: neovim-sh
Wrapper package to installneovimwith an executable.This allows to installneovimwithpipx:pipxinstall--python=$(whichpython2)neovim-shpipxinstall--python=$(whichpython3)neovim-shTo use inneovim, simply set python host program variables:function!s:SetPythonHostProg(job_id,data,event)if(len(a:data[0])>0)execute(a:data[0])endifendfunction" jobstart is only in neovimifexists("*jobstart")let_=jobstart(['neovim2.sh','--vim'],{'on_stdout':function('s:SetPythonHostProg')})let_=jobstart(['neovim3.sh','--vim'],{'on_stdout':function('s:SetPythonHostProg')})endif
Package: neox
NeoCortex: Multi-Modality Foundation Model for Humanoid RobotsNeoCortex is a cutting-edge, multi-modality foundation model engineered for humanoid robots. With the capability to process an array of modalities including images, text, videos, depth, heatmaps, LIDAR, 3D scenes, point clouds, and more, NeoCortex represents the zenith of robotic perception and cognition.AppreciationAll the creators in Agora,Join Agorathe community of AI engineers changing the world with their creations.LucidRains for inspiring me to devote myself to open source AIInstallationTo integrate NeoCortex into your development environment:pipinstallneoxUsageimporttorchfromneox.modelimportNeoCortex#usageimg=torch.randn(1,3,256,256)caption_tokens=torch.randint(0,4)model=NeoCortex()output=model(img,caption_tokens)Model ArchitectureBuilding on the paradigms established by models like NeVA, NeoCortex expands its horizons to embrace a multi-faceted input system:Images: Processed through a frozen variant of the Hugging Face CLIP model, producing image embeddings.Text: Integrated seamlessly with an NVIDIA-trained GPT variant.LIDAR: Point clouds processed through PointNet or KPConv, extracting essential spatial features. These features, once captured, are projected to text embedding dimensions.Videos: Processed using 3D-CNNs to capture temporal information, then integrated with the main architecture.Heatmaps, 3D Scenes, and Depth: These are funneled through specialized modules tailored for each modality before being integrated.Training comprises three stages:Pretraining: Specific modules (like PointNet for LIDAR) are pretrained, with the main model frozen.Inter-modality Training: The embeddings from different modalities are concatenated, projected, and trained to ensure inter-modality coherence.Finetuning: Utilizing synthetic data generated with advanced GPT versions to ensure the model understands the intricate relationship between various modalities.SpecificationsArchitecture Type: Multi-Modality TransformerSub-Architectures: GPT, CLIP, PointNet, 3D-CNNModel versions: 10B, 30B, 50BInput & OutputInput Formats:Images: RGBText: TokensLIDAR: Point CloudsVideos: FramesAnd more...Output Format: Text or Action TokensIntegration and CompatibilitySupported Hardware Platforms: Hopper, Ampere/Turing, specialized robotic chipsetsSupported Operating Systems: Linux, RoboOSTraining & Fine-tuning DataImage Dataset: [Link to Dataset]LIDAR Dataset: [Link to Dataset]Textual Data: Synthetically produced by GPT versionsLicenses: Various, mainly MIT and CC-BY-NC 4.0InferenceEngine: Triton and specialized robotic inference enginesTest Hardware: Humanoid robotic platformsReferences and MoreVisual Instruction Tuning paperBlogCodebaseDemoLicensingThis project is licensed under the MIT License.For more details, contributions, and support, please refer to theofficial repository.Todo[] -
Package: neoxelox-invoke
Welcome to Invoke!Invoke is a Python (2.7 and 3.4+) library for managing shell-oriented
subprocesses and organizing executable Python code into CLI-invokable tasks. It
draws inspiration from various sources (make/rake, Fabric 1.x, etc) to
arrive at a powerful & clean feature set.To find out what’s new in this version of Invoke, please seethe changelog.The project maintainer keeps aroadmapon his website.Note: this is a fork with custom changes to fullfil my usecase.For a high level introduction, including example code, please seeour main
project website; or for detailed API docs, seethe
versioned API website.
Package: neozot
neozotneozot is a utility to get recommendations from arxiv based on your zotero library.InstallUsing PyPIpip install neozotFrom repositoryClone this repository usinggit clone https://github.com/v-i-s-h/neozot-py.gitInstall usingpipinstall.If you want to install in developer/editable mode,pip install -e .UsageTo run neozot, you canpython -m neozotFirst runOn first run, you are required to provide the path of Zotero data directory aspython -m --zotdir <path-to-zotero-data-dir>Example:python -m neozot --zotdir ~/Zotero/Same can all be used to change the path to Zotero data directory later.Additionally, neozot can also be configured with a couple of options through CLI.
Full command line options areusage: neozot [-h] [--zotdir ZOTDIR] [-d DOMAINS [DOMAINS ...]] [--n-items N_ITEMS] [-f]

Super charge your research

options:
  -h, --help            show this help message and exit
  --zotdir ZOTDIR       Data directory of Zotero
  -d DOMAINS [DOMAINS ...], --domains DOMAINS [DOMAINS ...]
                        arxiv domain(s) to search in (Ex: cs.LG cs.CV cs.AI or high level as cs, math etc)
  --n-items N_ITEMS     Number of items to suggest by default
  -f, --force-refreshExamplesIf you zotero library is in~/Zotero/(directory wherezotero.sqliteis stored) and you
want to get arxiv recommendations fromcsandmathdomains, then usepython-mneozot--zotdir~/Zotero/-dcsmathIf you only want results fromcs.AIandcs.LG, usepython-mneozot--zotdir~/Zotero/-dcs.AIcs.LGThe options in UI sidebar areIconDescriptionSuggestions: Top suggestion from today's arxiv feed based on your Zotero itemsExplore: Show all feed items from arxivBookmarked:Not ImplementedGithub: Visit github repoSettings: Select arxiv domains to follow, number of items to suggest etc
Package: nep
NEP Python libraryNEP+ is a comprehensive software platform that facilitates the integration and design of interactive applications involving a spectrum of agents, whether physical (e.g., robots) or digital (e.g., digital twins).The main functionality of NEP+ is to help and support in the design heterogeneous software architectures (i.e., complex applications composed of several modules developed over different programming languages, running on different operating systems, and performing different tasks).Official website:https://enrique-coronado.gitbook.io/nep-docs/
Package: nep29
NEP 29 CalculatorNEP 29calculator toolsUsage$nep29--helpusage: nep29 [-h] [--n_months N_MONTHS] [--n_minor N_MINOR] packageNEP 29 calculator.positional arguments:package              Package to deprecationoptional arguments:-h, --help           show this help message and exit--n_months N_MONTHS  Number of months to keep supporting (default: 24)--n_minor N_MINOR    Number of minor versions to keep supporting (default: 3)For more information, see https://numpy.org/neps/nep-0029-deprecation_policy.htmlExample:$nep29numpy| version |    date    ||---------|------------||  1.19.0 | 2020-06-20 ||  1.18.0 | 2019-12-22 ||  1.17.0 | 2019-07-26 ||  1.16.0 | 2019-01-14 |CreditsThis package was created withCookiecutterand thehmaarrfk/cookiecutter-pypackageproject template.Development LeadMark Harfouchemark.harfouche@gmail.comContributorsHugo van Kemenade (hugovk)ContributingContributions are welcome, and they are greatly appreciated! Every little bit
helps, and credit will always be given.You can contribute in many ways:Report BugsReport bugs athttps://github.com/hmaarrfk/nep29/issues.If you are reporting a bug, please include:Your operating system name and version.Any details about your local setup that might be helpful in troubleshooting.Detailed steps to reproduce the bug.Fix BugsLook through the GitHub issues for bugs. Anything tagged with "bug" and "help
wanted" is open to whoever wants to implement it.Implement FeaturesLook through the GitHub issues for features. Anything tagged with "enhancement"
and "help wanted" is open to whoever wants to implement it.Write DocumentationNEP29 Calculator could always use more documentation, whether as part of the
official NEP29 Calculator docs, in docstrings, or even on the web in blog posts,
articles, and such.Submit FeedbackThe best way to send feedback is to file an issue athttps://github.com/hmaarrfk/nep29/issues.If you are proposing a feature:Explain in detail how it would work.Keep the scope as narrow as possible, to make it easier to implement.Remember that this is a volunteer-driven project, and that contributions
are welcome :)Get Started!You can follow the scikit-image contribution document and adapt it accordingly.History0.0.17 (2022-11-29)Skip invalid versions instead of erroring.0.0.16 (2022-01-30)Add tests back to distribution.0.0.15 (2022-01-30)Use miniver instead of versioneer.0.0.10 (2021-12-30)Add versioneer.py to the source distribution.0.0.9 (2021-11-17)Retrigger failed build due to travis.org migration.0.0.8 (2021-06-16)Add support for pre-release packages that don't use a dot to separate the pre-release signifier.0.0.7 (2021-11-03)Show default argument values in the help.0.0.6 (2021-11-03)Support a few more time formats0.0.5 (2020-10-13)Use pretty table for better formatting.0.0.4 (2020-10-12)Improve documentation.0.0.1 (2020-03-11)First release on PyPI.
Package: nepal-company-registrar
Nepal Company RegistrarNepal Company Registrar is a Python library for dealing with companies registered in Nepal Company Registrar.InstallationUse the package managerpipto install nepal-company-registrar.pipinstallnepal-company-registrarUsageNepal Company Registrarfromnepali_company_registrarimportNepalCompanyRegistrarnepali_company_registrar=NepalCompanyRegistrar(company_name_input='AGRICULTURAL DEVELOPMENT BANK')# for company inputnepali_company_registrar.is_valid()# returns "True" if it is registered company name# returns "False" if it is not registered in company registrarnepali_company_registrar.get_company_detail()# returns company detail eg. {'name': 'AGRICULTURAL DEVELOPMENT BANK', 'name_in_nepali': 'कृषि विकास बैंक', 'registration_number': '928', 'registration_date': '2062-3-30', 'company_type': 'Public', 'share_holder': None, 'address': 'का.म.न.पा.-११,काठमाण्डौ,बाग्मती'}nepali_company_registrar.list_similar_companies()# returns list of similar companies registered in company registrarContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: nepal-forex
Nepal ForExNepal ForEx is a Python package for making Currency Exchange easier and fast between NPR and Foreign Currencies.It parses current exchange rate from Nepal Rastra Bank.
Exchange rates are genuine and realtime provided by Nepal Rastra Bank.Supported CurrenciesINRUSDEURGBPCHFAUDCADSGDJPYCNYSARQARTHBAEDMYRKRWSEKDKKHKDBHDInstallationUse the package managerpipto install nepal-forex.pipinstallnepal-forexUsageNepal ForExTo get NPR exchange rate of specified currency on specified date.fromnepal_forex.nepal_foreximportnepal_forexnepal_forex.exchange_rate(currency='USD',date='2020-08-27')# Decimal('118.58')To get NPR exchange rate of specified currency of today.fromnepal_forex.nepal_foreximportnepal_forexnepal_forex.exchange_rate(currency='USD')# Decimal('118.58')To convert NPR amount to specified currency of today exchange rate.fromnepal_forex.nepal_foreximportnepal_forexnepal_forex.convert_to(amount=160,currency='USD')# Decimal('1.35')To convert NPR amount to specified currency of specified date exchange rate.fromnepal_forex.nepal_foreximportnepal_forexnepal_forex.convert_to(amount=160,currency='USD',date='2020-08-27')# Decimal('1.35')To convert specified currency amount to NPR of today exchange rate.fromnepal_forex.nepal_foreximportnepal_forexnepal_forex.convert_from(amount=100,currency='USD')# Decimal('11858.00')To convert specified currency amount to NPR of specified date exchange rate.fromnepal_forex.nepal_foreximportnepal_forexnepal_forex.convert_from(amount=100,currency='USD',date='2020-08-27')# Decimal('11858.00')Also Decimal places can be set.fromnepal_forex.nepal_foreximportnepal_forexnepal_forex.convert_to(amount=160,currency='USD',date='2020-08-27',decimal_places=4)# Decimal('1.3582')ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: nepali-date-converter
Nepali Date ConverterThis is a simple project that converts dates between nepali and english dates.InstallationRun the following command to install:'''python
pip install nepali_date_converter
'''Usage'''pythonGenerate "2080-03-18"from nepali_date_converter import english_to_nepali_converter
english_to_nepali_converter(2023,7,3)Generate "2023-07-03"from nepali_date_converter import nepali_to_english_converter
nepali_to_english_converter(2080, 3, 18)
'''Developing nepali_date_converterTo install nepali_date_converter, along with the tools you need to develop and run tests, run the following in your virtualenv:'''bash
$ pip install -e .[dev]
'''
Package: nepali-datetime
Nepali Datetime (Bikram Sambat Date & Nepal Time)The package inspired from Python's coredatetimepackage that
operates on top of Bikram Sambat (B.S) Date & Nepal Time (NPT)+05:45.Supports:Python 3.5+Basic Usage# importing>>>importdatetime>>>importnepali_datetime# today's date>>>datetime.date.today()>>>nepali_datetime.date.today()# now datetime>>>datetime.datetime.now()>>>nepali_datetime.datetime.now()# creating date object>>>datetime.date(2020,9,4)>>>nepali_datetime.date(2077,5,19)# creating datetime object>>>datetime.datetime(2020,9,4,8,26,10,123456)>>>nepali_datetime.datetime(2077,5,19,8,26,10,123456)# date/datetime formatting>>>nepali_datetime.datetime(2077,5,19,8,26,10,123456).strftime("%d%B %Y")# 19 Bhadau 2077# datetime parsed from string (strptime)>>>nepali_datetime.datetime.strptime('2077-09-12','%Y-%m-%d')# nepali_datetime.datetime(2077, 9, 12, 0, 0)# date/datetime formatting with Nepali unicode support>>>nepali_datetime.date(1977,10,25).strftime('%K-%n-%D (%k %N%G)')# १९७७-१०-२५ (७७ माघ आइतबार)# datetime.timedelta addition/subtraction>>>nepali_datetime.date(1990,5,10)+datetime.timedelta(days=350)# nepali_datetime.date(1991, 4, 26)>>>nepali_datetime.datetime(1990,5,10,5,10,20)+datetime.timedelta(hours=3,minutes=15)# nepali_datetime.date(1990, 5, 10, 8, 25, 20)# convert B.S to A.D date and vice-versa>>>nepali_datetime.date(1999,7,25).to_datetime_date()# datetime.date(1942, 11, 10)>>>nepali_datetime.date.from_datetime_date(datetime.date(1942,11,10))# nepali_datetime.date(1999, 7, 25)# Bikram Sambat monthly calendar>>>nepali_datetime.date(2078,1,1).calendar()Baishakh2078SunMonTueWedThuFriSat12345678910111213141516171819202122232425262728293031Installation$pipinstallnepali-datetimeDocumentationComplete usage documentations can be foundhere.ContributionAny contributions are most welcome. Do check this guidelinesCONTRIBUTING.mdfor code contribution.
Package: nepali-date-utils
Nepali Date UtilsOverviewThis lightweight package allows easy conversion between Nepali (BS) and English (AD) dates. Simplify date transformations in your applications with this straightforward utility.InstallationYou can install the package via pip:pipinstallnepali_date_utilsTo convert English date (AD) to Nepali date (BS):fromnepali_date_utilsimportconverterconverter.ad_to_bs("2024/02/03")To convert Nepali date (BS) to English date (AD):fromnepali_date_utilsimportconverterconverter.bs_to_ad("2080/02/03")
Package: nepali-embedding
nepali_embeddingGenerate text embedding for nepali textObjectiveAny NLP downstream tasks such as text classification, Named Entity Recognition performed on nepali textual data requires embedding of the words as the feature embedding matrix.
For english text, there are several ways we can generate embedding such as Word2Vec, Glove, BERT and so on from several open source NLP libraries. However, there seems to be no open source library for such tasks in nepali text. We aim to provide accurate word embedding for nepali text through several NLP based architectures so that it can be used in further NLP downstream tasks in nepali language.Models used overviewWe have developed state of the art models for embedding generation for nepali text.Sabda2VecBakya2VecNepBERTUsageWord_embeddingUse this script to get embedding of a word (sabda).fromnepali_embedding.sabda2vec.inferenceimportSabda2Vecsabda2vec_obj=Sabda2Vec(model_name="sabda2vec_sm")#Get embedding of the tokenembedding=sabda2vec_obj.get_embedding("हार")# Get top similar tokenstop_similar=sabda2vec_obj.get_most_similar("हार",5)# Get similarity between two tokenssimilarity_score=sabda2vec_obj.get_similarity_between_tokens("हार","पराजय")sabda_to_vec_model: https://www.dropbox.com/s/xkd29spkozoavhk/sabda_to_vec_model?dl=0
    sabda_to_vec_model_md: https://www.dropbox.com/s/55m5q4h5ys1l4np/sabda_to_vec_model_md?dl=0Loading embedding from nepBERT modelfromnepali_embedding.nepBERT.embedding_generatorimportNepBERTnepbert=NepBERT()test_sentence='आकाश भाई ज्ञानी मन्छे हो'embedding=nepbert.get_bert_embedding_sentence(test_sentence,)