Saravanan666/pypi-org huggingface dataset:
Package: neutron-lbaas-dashboard
Team and repository tagsWarningNeutron-lbaas-dashboard is now deprecated. Please see the FAQ:https://wiki.openstack.org/wiki/Neutron/LBaaS/Deprecationneutron-lbaas-dashboardHorizon panels for Neutron LBaaS v2Free software: Apache licenseDocumentation:https://docs.openstack.org/neutron-lbaas-dashboard/latest/Source:https://git.openstack.org/cgit/openstack/neutron-lbaas-dashboardBugs:https://storyboard.openstack.org/#!/project/907FeaturesPlease see neutron-lbaas repositoryHowtoPackage the neutron_lbaas_dashboard by running:python setup.py sdistThis will create a python egg in the dist folder, which can be used to
install on the horizon machine or within horizon’s python virtual
environment.Copy_1481_project_ng_loadbalancersv2_panel.pyinneutron_lbaas_dashboard/enableddirectory
toopenstack_dashboard/local/enabled.(Optional) Copy the policy file into horizon’s policy files folder, and
add this configPOLICY_FILES:'neutron_lbaas': 'neutron_lbaas_policy.json',Django has a compressor feature that performs many enhancements for the
delivery of static files. If the compressor feature is enabled in your
environment (COMPRESS_OFFLINE = True), run the following commands:$ ./manage.py collectstatic
$ ./manage.py compressFinally restart your web server to enable neutron-lbaas-dashboard
in your Horizon:$ sudo service apache2 restartEnabling neutron-lbaas-dashboard and octavia-dashboardIn general we advise against having both dashboards running at the same
time to avoid confusing users, which is exaggerated since the dashboards
will have the same label.In rare circumstances, e.g. as part of a migration strategy, it might be
necessary to do so. The main issue to watch out for is to avoid neutron-lbaas
and Octavia getting out of sync and neutron-lbaas-dashboard showing phantom
load balancers - this can be avoided if the sync between Octavia and
neutron-lbaas is fully enabled.Here is a table to show some cases:Configuration
neutron-lbaasConfiguration
Octavianeutron-lbaas-
dashboard
enabledoctavia-
dashboard
enabledNotesnot installedv2 API enablednot supportedpreferredoctavia-driverv2 API disabled
v1 API enabledsupportednot
supportedsync
requiredoctavia-driverv2 API enabled
v1 API enabledsupportedpreferredsync
requiredoctavia-proxy
pluginv1 API disabled
v2 API enabledSupported (but
not
recommended)preferredno octavia
driver but
other driversnot installedpreferrednot
supportedno octavia
driver but
other driversv2 API enabled
v1 API disabledpreferredpreferredindependent
services
Package: neutron-lib
Team and repository tagsneutron-libNeutron shared routines and utilitiesFree software: Apache licenseDocumentation:https://docs.openstack.org/neutron-lib/latest/Source:https://opendev.org/openstack/neutron-libBugs:https://bugs.launchpad.net/neutronRelease notes:https://docs.openstack.org/releasenotes/neutron-lib/FeaturesTODO
Package: neutrons
NeutronNeutron scattering physics simulationInstallationDependenciesRustQuickstartDownloading the release tool should be as simple as:cargoinstallneutronsCreate a directory calledinput, and within it add a parameters file calledparameters.json:mkdirinput
touchinput/parameters.jsonThe parameters file should look something likethis.You can then run the program with:neutronsparameters.json
Package: neutron-sync
Neutron SyncA command line utility to sync your personal dotfiles to an encrypted Github. This allows you to share your personal secrets across multiple machines and keep them in sync.Sponsor This ProjectInstallationpipx install neutron-syncSee pipxAdditional DocsHow Neutron Sync WorksPrimary SetupRequirementsPrivate Github repositorygit-crypt installed, seehttps://github.com/AGWA/git-crypt/blob/master/INSTALL.mdUbuntu/Debian:sudo apt install git-cryptRedhat:sudo yum install git-cryptMac:brew install git-cryptSetupgit clone git@github.com:{github-user}/{repo-name}.git
cd {repo-name}
git-crypt init
nsync init `pwd`
git-crypt export-key ~/.dotfiles.key
git-crypt unlock ~/.dotfiles.key
# you may get an error if you have no files initially which is OKAdd filesadds to encrypted repo and creates link at original location# link a directorynsynclink~/.ssh# link a filensynclink~/.tmux.confCommit and Pushwhen files are changednsync savePull Changes from Remotensync pullSetup on Another MachineTransfer Keys to SecondaryWhile files are synced via the git repository, you need to transfer keys to the secondary machine so you can decrypt the repository. By default, it will transfer you encryption key and ssh key.On Primary:nsyncstart-transfer# follow promptsOn Secondary:nsynccomplete-transfer# follow promptsmv{output-dir}/.dotfiles.key~
mkdir.ssh
chmod700.ssh
mv{output-dir}/id_rsa~/.ssh
mv{output-dir}/id_rsa.pub~/.sshSetup - Secondarygit clone git@github.com:{github-user}/{repo-name}.git
cd {repo-name}
nsync init `pwd`
nsync pullTransfer ServerThe transfer server can be used to help assist in setting up a new machine. After initial setup, all transactions are stored in your git repository. All files stored on the transfer server are encrypted on device before being sent and only stored temporarily.File transfers default to usinghttps://www.neutronsync.com/. You can host your own server by running:nsync server
Package: neutron-tempest-plugin
Tempest plugin for Neutron project.It contains the tempest plugin for the functional testing of Neutron Project.Free software: Apache licenseDocumentation:https://docs.openstack.org/neutron/latest/Source:https://opendev.org/openstack/neutron-tempest-pluginBugs:https://bugs.launchpad.net/neutron- tag: tempestRelease notes:https://docs.openstack.org/releasenotes/neutron-tempest-plugin/
Package: neutron-vpnaas
Welcome!This package contains the code for the Neutron VPN as a Service
(VPNaaS) service. This includes third-party drivers. This package
requires Neutron to run.External Resources:The homepage for Neutron is:https://launchpad.net/neutron.  Use this
site for asking for help, and filing bugs. We use a single Launchpad
page for all Neutron projects.Code is available on opendev.org at:https://opendev.org/openstack/neutron-vpnaas.Please refer to Neutron documentation for more information:Neutron README.rstTeam and repository tags
Package: neutron-vpnaas-dashboard
OpenStack Dashboard panels for Neutron VPNaaSDocumentation:https://docs.openstack.org/neutron-vpnaas-dashboard/latest/Source:https://opendev.org/openstack/neutron-vpnaas-dashboardBugs:https://bugs.launchpad.net/neutron-vpnaas-dashboardRelease Notes:https://docs.openstack.org/releasenotes/neutron-vpnaas-dashboard/Team and repository tags
Package: neutron-web
Neutron allows developers to build native Python apps along with CSS and HTML for frontend design. Based onpywebviewfor it's native GUI window and JavaScript-Python communication.You can get started contributing viaCONTRIBUTING.mdoryou can message meon discord (IanTheThird#9732) if you want more insigths on the code and tips on what to contribute.Installationpip install neutron-webBuilding your projectTo build a Neutron project you first need pyinstaller, install pyinstaller throught pip:pip install pyinstaller. Then run the script below in your command prompt/terminal. You can also use other programs to build your project such as py2exe if you prefer.Note:If you are on linux use ":" instead of ";"pyinstaller YOUR_PYTHON_FILE.py --noconsole --onefile --add-data="YOUR_HTML_FILE.html;." --add-data="YOUR_CSS_FILE.css;."You don't need to use--add-dataif your project doesn't have a CSS or HTML fileExamplesFull exampleFor a fully set up example project seeTEMPLATE. The project is build how it's intended, meaning it has a CSS and HTML file for the design and a Python file for the logic. (It is comparable to how websites using JavaScript are built).Other examplesAlthought not recommended for big projects, it's possible to create an app using only a Python file.importNeutronwin=Neutron.Window("Example")HeaderObject=Neutron.elements.Header(win,id="title",content="Hello")defsetName():HeaderObject.setAttribute("style","color: red;")HeaderObject.innerHTML="Hello world!"win.getElementById("submit").innerHTML="clicked!"Neutron.elements.Button(win,id="submit",content="Hi",onclick=Neutron.event(setName))win.show()Another example featuring in-python HTML:importNeutronwin=Neutron.Window("Example")defsetName():name=win.getElementById("inputName").valuewin.getElementById("title").innerHTML="Hello: "+namewin.display(f"""<!DOCTYPE html><html><head lang="en"><meta charset="UTF-8"></head><body><h1 id="title">Hello: </h1><input id="inputName"><button id="submitName" onclick="setName()">Submit</button></body></html>""",pyfunctions=[setName])# Link up any Python functions so that they can be used inside the HTMLwin.show()LoaderTo resolve slow loading times for bigger projects, Neutron features a loader system seen here:importNeutronwin=Neutron.Window("Example",size=(600,100))# The loader covers while all the other elements and css loadswin.loader(content="<h1>Loading App...</h1>",color="#fff",after=lambda:win.toggle_fullscreen())Multiple windowsTo create another window for example when a fuction is called you need to use thechildwindowproperty.def createNewWindow():

    win = Neutrontest.Window("Example", size=(600, 100), childwindow=True)

    win.display(file="secondwindow.html")

    win.show()
Package: neutron-zvm-plugin
About this projectThis project provides the OpenStack Neutron mechanism driver and L2 agent for
the z/VM of IBM z Systems and IBM LinuxOne machines.z/VM provides a highly secure and scalable enterprise cloud infrastructure
and an environment for efficiently running multiple diverse critical
applications on IBM z Systems and IBM LinuxONE with support for more virtual
servers than any other platform in a single footprint.
These z/VM virtual servers can run Linux, z/OS and more.For more information, please refer tohttp://www.vm.ibm.com/LinksDocumentation:http://networking-zvm.readthedocs.io/en/latest/Source:http://git.openstack.org/cgit/openstack/networking-zvmGithub shadow:https://github.com/openstack/networking-zvmBugs:http://bugs.launchpad.net/networking-zvmGerrit:https://review.openstack.org/#/q/project:openstack/networking-zvmLicense: Apache 2.0 license
Package: neutrosophic
بسم الله الرحمن الرحيمOpen Source Neutrosophic PackageThis project aims to provide an open-source Python package to be utilized in Neutrosophic research, academia, and insdustry. This project was initialized in 6th of January 2019.PublicationsPublications of the ProjetThose are publications that describes the project design, structure, and modules.Haitham A. El-Ghareeb: Novel Open Source Python Neutrosophic Package, Neutrosophic  Sets and Systems, vol. 25, 2019, pp. 136-160.Read online:http://fs.unm.edu/NSS/NovelOpenSourcePython.pdfPublications utilizing the ProjectThose are publications that utilized the package in implementing new thoughts and ideas.
Package: neuxus
NeuXusBuild flexible pipeline for real-time processingInstallationBasic useTo Do uploading on PyPipip install neuxusRunRun basic pipeline from NeuXusneuxus basics/generate_send.py -eRun your pipeline from NeuXusneuxus path_to_my_pipeline.pyCustomize your own nodessee template
TODOFor developersClone from source:git clone https://github.com/LaSEEB/NeuXus.gitInstall dev-requirements
ToDoCreate the tar.gz file and install it on your computer:setup.py sdist
pip install nexus-xx.xx.xx.tar.gzTestsLaunch tests with:python -m unittest discover
Package: nevada
nevadaIts English Documentation ishere.nevada는?nevada는네이버의 검색광고 API를 좀 더 쉽게 사용할 수 있도록 해주는 Python 라이브러리입니다.준비하기 (nevada 설치 전)PythonGit client설치하기pip3 install nevadagit clone https://github.com/taegyumin/python_nevada.git네이버에서 API Licnese 발급하기nevada를 이용하기 위해서는 네이버 검색광고시스템에서 API_KEY를 발급 받아야 합니다.네이버 검색광고 시스템 메인 탭에서 회원가입을 합니다.네이버 검색광고 관리 탭으로 이동합니다.사이트 내에서 도구 > API 관리 로 이동합니다.API license를 발급합니다.잘 설치 됐는지 확인하기Python 파일을 만들고, 아래 코드를 실행하십시오.현재 시간이 출력되면 코드가 정상적으로 실행된 겁니다.이때, 코드에서api_key,secret_key,customer_id의 값은 네이버 검색광고 시스템에서 발급 받은 값으로 변경하십시오.from nevada.Common.Connector import *

base_url = 'https://api.naver.com'
api_key = "Naver-search-AD_ACCESS_LICCENSE"
secret_key = "Naver-search-AD_SECRET_KEY"
customer_id = "Naver-search-AD_CUSTOMER_ID"

conn = Connector(base_url, api_key, secret_key, customer_id)
print(conn.get_datetime())자세한 사용 방법은docs의 설명서를 참고해주시기 바랍니다.
Package: neval
neval — Namespaced code evaluatorThis package provides an alternative scoping mechanism
to the standardexecandevalfunctions for running raw Python code.
The goal is to overcome the following behaviour ofexec, as describe
in thedocs:If exec gets two separate objects as globals and locals, the code will
be executed as if it were embedded in a class definition.For instance, when you want to uselocalsas astagingscope andglobalsas an accessible backdrop, the executed code can quickly
result in unexpected behaviour. For example:# ✓ [1]exec("a=[1]; print([i for i in a])",{},{})# ✗ NameError: name 'a' is not definedexec("a=[1]; print([i for i in a if a])",{},{})# ✓ osexec("import os; print(os.__name__)",{},{})# ✗ NameError: name 'os' is not definedexec("import os; (lambda: print(os.__name__))()",{},{})Runcode's alternative evaluationThe main difference is thatnevalhas two arguments callednamespacefor reflecting scope changes (almost likelocals) andnamespace_readonlyto additionally draw from (almost likeglobals). The main deviations are:namespaceis adictor a__dict__attributed object whose keys are
read and written to reflect scope changesnamespace_readonlyis adictor a__dict__attributed object whose
keys are only read, but not writtenif the last statement in the code is an expression, the executed value of
the expression is returnedif an error occurs, a temp file is generated in order for C interpreter to
provide a more informative error message (after Python teardown)for Python >= 3.11 the traceback includes a printout of the code using the newadd_notefeature, similarly toipythonFile"/temp/neval-057d58343544b6d102cac201bdc11527a0224e87",line3,in<module>c=4/0~^~ZeroDivisionError:divisionbyzeroErrorinneval-057d58343544b6d102cac201bdc11527a0224e87:1a=1---->3b=4/04c=5Examplesfromnevalimportnevalneval("a = 1; b = 2; c = 3; d = 4; a + b + c + d")# ✓ 10neval("a = 1; b = 2; c = 3; d = 4; a + b + c + d",ns:={})# ✓ 10ns# ✓ {'a': 1, 'b': 2, 'c': 3, 'd': 4}importnumpyasnpfromtypesimportSimpleNamespaceneval("a = argmax(array([1,2,3,4,3,2,1])**2)",ns:=SimpleNamespace(),np)ns.a# ✓ 3a,b,c=(1,2,3)neval("d = a + b*2 + c*3",ns:=SimpleNamespace(),globals())ns.d# ✓ 14d# ✗ NameError: name 'd' is not definedneval("d = a + b*2 + c*3",globals())d# ✓ 14params=SimpleNamespace(a=1,b=2,c=3)neval("d = a + b*2 + c*3",params)params# ✓ namespace(a=1, b=2, c=3, d=14)neval("""\a = 1 + 2this is incorrectb = a + 3""")# ✗ NameError: name 'this' is not defined#   Error in neval-8efcb70d4b63817f9fd92f3b61eb5a7c0c45cfe9:#         1 a = 1 + 2#   ----> 2 this is incorrect#         3 b = a + 3
Package: nevargs
nevargsIt's a simple package that using shlex formats your cli-like argument strings and format them into a dict>>>importnevargs>>>s="this is -f True fun -c command">>>nevargs.dictify(s){'args':['this','is','fun'],'-f':['True'],'-c':['command']}Arguments with no value are returned underargsand for each flag found, it's arguments are under{flag}
Package: nevax
NeVA: NVIDIA's Visual Question Answering TransformerNeVA is a powerful and versatile Visual Question Answering model by NVIDIA. Neva builds upon the open-source LLaMA model, integrating it with an NVIDIA-trained GPT model to offer state-of-the-art performance.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 NeVA into your Python environment, you can install it via pip:pipinstallnevaxUsageimporttorchfromnevaximportNeva#usageimg=torch.randn(1,3,256,256)caption_tokens=torch.randint(0,4)model=Neva()output=model(img,caption_tokens)DescriptionAt a high level, NeVA utilizes a frozen Hugging Face CLIP model to encode images. These encoded images are projected to text embedding dimensions, concatenated with the embeddings of the given prompt, and subsequently passed through the language model. The training process comprises two main stages:Pretraining: Only the projection layer is trained with the language model kept frozen. This stage uses image-caption pairs for training.Finetuning: Both the language model and the projection layer are trained. This stage utilizes synthetic instruction data generated with GPT4.Model SpecificationsArchitecture Type: TransformerNetwork Architecture: GPT + CLIPModel versions: 8B, 22B, 43BInput & OutputInput Format: RGB Image + TextInput Parameters: temperature, max output tokens, quality, toxicity, humor, creativity, violence, helpfulness, not_appropriateOutput Format: TextIntegration and CompatibilitySupported Hardware Platforms: Hopper, Ampere/TuringSupported Operating Systems: LinuxRuntime: N/ATraining & Fine-tuning DataPretraining Dataset:Link:CC-3MDescription: The dataset comprises CC3M images and captions, refined to 595,000 samples.License:COCO,CC-3M,BLIPFinetuning Dataset:Link: Synthetic data produced by GPT4Description: The dataset, with 158,000 samples, was synthetically generated by GPT4. It encompasses a blend of short question answers, detailed image descriptions, and higher-level reasoning questions.License:CC-BY-NC 4.0 LicenseInferenceEngine: TritonTest Hardware: OtherReferencesVisual Instruction Tuning paperBlogCodebaseDemoLicensingThis project is licensed under theMIT Licenselicense.Citation
Package: neverbounce
Python API wrapper library for theNeverBounceemail
verification service.Installation$ pip install neverbounceThe only dependency is therequestslibrary.UsageSign upto get anAPI username and keyand 1000 free monthly
verifications. Thefree accountsupports onlysingle verifications.Single verification>>> from neverbounce import NeverBounce

>>> neverbounce = NeverBounce('my_api_username', 'my_api_key')
>>> verified = neverbounce.verify('martin@martinkosir.net')

>>> print(str(verified))
martin@martinkosir.net: valid

>>> print(verified.email, verified.result_text, verified.result_code, verified.is_valid)
martin@martinkosir.net valid 0 TrueBulk verificationTo use this features you need toconfigure a payment methodin
NeverBounce account settings.>>> from neverbounce import NeverBounce
>>> neverbounce = NeverBounce('my_api_username', 'my_api_key')Create the job and get it’s id:>>> emails = ['some.email@example.com', 'john.smith@gmail.com']
>>> job_id = neverbounce.create_job(emails).job_idPeriodically check the status of verification job:>>> job_status = neverbounce.check_job(job_id)Use theresultsgenerator to iterate over verified emails if the job has been completed:>>> if job_status.is_completed:
...     for verified in neverbounce.results(job_id):
...         print(verified.email, verified.result_text, verified.result_code, verified.is_valid)
some.email@example.com invalid 1 False
john.smith@gmail.com invalid 1 FalseAccount informationGet the information about your API account:>>> from neverbounce import NeverBounce
>>> neverbounce = NeverBounce('my_api_username', 'my_api_key')
>>> account = neverbounce.account()

>>> print(str(account))
Credits: 999, Jobs Completed: 22, Jobs Processing: 0

>>> print(account.credits, account.jobs_completed, account.jobs_processing)
999 22 0DocumentationOfficial docs for the NeverBounce RESTful APIBuild status
Package: neverd
2D REVerse ENginnering dialogneverdis a 2D reverse engineering tool built on top oftkinter. It provides a set of geometric objects (points, lines and sliders) that can be used in conjunction with an image and a calibration rectangle to extract relevant geometric information.InstallationInstall withpipinstallneverdUsageneverdcan be used both as a normal package or as a CLI tool.For CLI tool usage, do:neverd--help
Package: neverfails
Neverfails involves an ambitious idea: code generation based on specifications.
This idea does not depend on a specific platform or programming language.
In principle, it could be implemented with any framework.
Actually, I have decided to test it using Django as a web framework and
Python as the programming language.Similarly to lettuce, neverfails recognizes the steps using regular expressions
and checks whether they pass or fail. If the step fails, neverfails does not
raise an AssertionError but runs the code to make the step pass, then runs the
step again.
Package: nevergrad
Nevergrad - A gradient-free optimization platformnevergradis a Python 3.8+ library. It can be installed with:pip install nevergradMore installation options, including windows installation, and complete instructions are available in the "Getting started" section of thedocumentation.You can join Nevergrad users Facebook grouphere.Minimizing a function using an optimizer (hereNGOpt) is straightforward:importnevergradasngdefsquare(x):returnsum((x-.5)**2)optimizer=ng.optimizers.NGOpt(parametrization=2,budget=100)recommendation=optimizer.minimize(square)print(recommendation.value)# recommended value>>>[0.499711120.5002944]nevergradcan also support bounded continuous variables as well as discrete variables, and mixture of those.
To do this, one can specify the input space:importnevergradasngdeffake_training(learning_rate:float,batch_size:int,architecture:str)->float:# optimal for learning_rate=0.2, batch_size=4, architecture="conv"return(learning_rate-0.2)**2+(batch_size-4)**2+(0ifarchitecture=="conv"else10)# Instrumentation class is used for functions with multiple inputs# (positional and/or keywords)parametrization=ng.p.Instrumentation(# a log-distributed scalar between 0.001 and 1.0learning_rate=ng.p.Log(lower=0.001,upper=1.0),# an integer from 1 to 12batch_size=ng.p.Scalar(lower=1,upper=12).set_integer_casting(),# either "conv" or "fc"architecture=ng.p.Choice(["conv","fc"]))optimizer=ng.optimizers.NGOpt(parametrization=parametrization,budget=100)recommendation=optimizer.minimize(fake_training)# show the recommended keyword arguments of the functionprint(recommendation.kwargs)>>>{'learning_rate':0.1998,'batch_size':4,'architecture':'conv'}Learn more on parametrization in thedocumentation!Convergence of a population of points to the minima with two-points DE.DocumentationCheck out ourdocumentation! It's still a work in progress, so don't hesitate to submit issues and/or pull requests (PRs) to update it and make it clearer!
The last version of ourdataand the last version of ourPDF report.Citing@misc{nevergrad,author={J. Rapin and O. Teytaud},title={{Nevergrad - A gradient-free optimization platform}},year={2018},publisher={GitHub},journal={GitHub repository},howpublished={\url{https://GitHub.com/FacebookResearch/Nevergrad}},}Licensenevergradis released under the MIT license. SeeLICENSEfor additional details about it.
See also ourTerms of UseandPrivacy Policy.