Saravanan666/pypi-org huggingface dataset:
Package: nuclia
Nuclia Python ClientIn order to installpipinstallnucliaAuthenticationNucliaYou can login with your Nuclia userHow to sign-upvianucliaauthloginNuclia KnowledgeboxYou can login to a specific knowledgebox if you have a Service Token (How to get a Service Token) or your NucliaDB isdeployed on-premisenucliaauthkb--urlKB_URL--tokenSERVICE_TOKENKB_URL its the url of the Knowledge Box. On the cloud service you can retrieve it on the dashboard. On the on-premise/community deployment its the url mapped to it.Nuclia Understanding APIYou can login with a Nuclia Understanding API key to process files, predict and train using our systemnucliaauthnua--keyZZZZDocumentationYou can find the documentationhere
Package: nucliadb
nucliadbThis module contains most of the Python components for NucliaDB:ingestreaderwritersearchtrainNucliaDB MigrationsThis module is used to manage NucliaDB Migrations.All migrations will be provided in themigrationsfolder and have a filename
that follows the structure:[sequence]_[migration name].py.
Wheresequenceis the order the migration should be run in with zero padding.
Example:0001_migrate_data.py.Each migration should have the following:fromnucliadb.migrator.contextimportExecutionContextasyncdefmigrate(context:ExecutionContext)->None:"""Non-kb type of migration. Migrate global data."""asyncdefmigrate_kb(context:ExecutionContext,kbid:str)->None:"""Migrate kb.Must have both types of migrations."""How migrations are managedAll migrations utilize a distributed lock to prevent simulateously running jobsGlobal migration state:current versiontarget versionKBs to migrateKB Migration State:current versionMigrations are currently run with a deployment and will be continuously retried on failure.Running migrations in a deployment is to make sure a migration does not prevent code deployment.
Package: nuclia.plone
# nuclia.plone![Nuclia logo](https://nuclia.cloud/assets/logos/logo_text.svg)This Plone add-on allows to index Plone contents in [Nuclia](https://nuclia.com/).## Create a Nuclia knowledge box[Create a Nuclia account](https://docs.nuclia.dev/docs/quick-start/create)## Install the add-onAddnuclia.plonein your buildout in theeggssection and run buildout.Restart Plone.Go to Site Setup / Add-ons and installnuclia.plone.Go to Nuclia settings, and enter the following:Knowledge box ID: you have a default knowledge box created with your Nuclia account, go to [Nuclia dashboard](https://nuclia.cloud/), the knowledge box ID is indicated on the home page in theNuclia APi endpointAPI key: see [how to get an API key](https://docs.nuclia.dev/docs/quick-start/push#get-a-service-access-token)Region: this the geographical region your knowledge box is attached to (at the moment onlyeurope-1is supported)Widget ID: see [how to create a widget](https://docs.nuclia.dev/docs/quick-start/search#add-a-search-widget-to-your-website)## UsageEverytime aFileor aLinkcontent is created, it is indexed in Nuclia.The Nuclia search widget is visible on the/@@nuclia-searchview.ContributorsEric BREHAULT,ebrehault@gmail.comChangelog1.0a3 (2022-10-10)Fix project metadata.
[ebrehault]1.0a2 (2022-10-03)Fix project metadata.
[ebrehault]1.0a1 (2022-10-03)Initial release.
[ebrehault]
Package: nuclipy
nuclipyA simple template based vulnerability scanner (Inspired by ProjectDiscovery'sNuclei)Dependenciesnuclipy depends uponpython3and the following modulesrequests,argparseandPyYaml.InstallationInstallation on Windows:python -m pip install nuclipyInstallation on Linux:sudo pip3 install nuclipyUsageShort fromLong formDescription-h--helpShow the help menu-u--hostnameHostname to scan for vulnerabilities-U--hostnamesFile containing target hostnames-t--templateTemplate id or path of template-T--threadsNumber of threads (default=10)-o--outputOutput fileHow to use templates?You can find some templates intemplates/directory.Use a specific templatepython-mnuclipy-uexample.com-tgit-config.yamlUse all templatespython-mnuclipy-uexample.com-tallSave the output to a filepython-mnuclipy-uexample.com-tall-onuclipy-output.txtCheck all templates, for multiple targetspython-mnuclipy-Utarget_hostnames.txt-tallHow to write your own templates?id:git-configname:Git Config Exposureseverity:mediumrequests:-method:GETpaths:-"HOSTNAME/.git/config"patterns:-\[core\]id: id_of_the_template, usually resembles to the filename of the template without extensionname: Name of the template to show in the resultsseverity: severity of the vulnerability (high,low,mediumorinfo)requests: Some request attributes and List ofpathsandpatternsmethod: HTTP request method (GETorPOST)redirects: Allow redirection or not (tureorfalse)paths: List of paths to send requestspatterns: List of Regular Expressioins to match in the responses (withANDcondition)
Package: nucml
NucMLPedro Vicente-Valdez, PhDNuclear Engineering - UC Berkeleypedro.vicentevz@berkeley.eduNeutronics Lab - Massimiliano Fratoni, PhDNucML is the first and only end-to-end python-based supervised machine learning pipeline for enhanced bias-free nuclear data generation and evaluation to support the advancement of next-generation nuclear systems. It offers capabilities that allows researchers to navigate through each step of the ML-based nuclear data cross section evaluation pipeline. Some of the supported activities include include dataset parsing and compilation of reaction data, exploratory data analysis, data manipulation and feature engineering, model training and evaluation, and validation via criticality benchmarks. Some of the inherit benefits of this approach are the reduced human-bias in the generation and solution and the fast iteration times. Resulting data from these models can aid the current NDE and help decisions in uncertain scenarios.Installation and SetupPlease refer to the Installation guide in the official documentation here:https://pedrojrv.github.io/nucml/getting-started.html.How to CiteIf you usedNucMLfor your work, feel free to cite us using (use previous resource in the meantime):Vicente-Valdez, P., Bernstein, L., & Fratoni, M. (2020). Application of Machine Learning to Nuclear Data Evaluation. ANS Virtual Winter Meeting, 123, 1287–1290. https://doi.org/10.13182/T123-32998
Package: nucosMQ
nucosMQis a python messaging module (in the sense of zeroMQ) written
in pure Python. We are aware of other projects likesnakeMQbut we
were not able to produce reasonable results with that, since we depend
in our related projects on massive threading.The underlying protocoll istcpand as an alternativeudpyet not
very far implemented. The Communication isthread safe, so it may be
used together with whatever GUI-Library. The module is light-weighted,
pure python and ready to use.The project is in alpha stage: every usage is on your own risk and
responsibility.nucosMQimplements two kind of connections: server-client connection
and link-connection. The server accepts many clients, the link is a
one-to-one connection. The connections may be established also with your
individual authentification method, which can be integrated easily (see
examples).A publish/subscribe logic is implemented, where clients can subscribe to
a topic and the server acts as a broker for that topology.Installpip install nucosMQor download the tarball athttps://github.com/DocBO/nucosMQ, unzip and
typepython setup.py installDocumentationhttps://pythonhosted.org/nucosMQRecommended test runnernose2 --plugin nose2.plugins.junitxml --junit-xmlLicenceMIT LicensePlatformsNo specific platform dependency. Python 2.7 should work as well as
Python 3.4/3.5. Up to now only Linux OS is tested.
Package: nuctools
Nuctools is a python package which was initially intended to assist with reduction
of data taken at the RPI linear accelerator, and was significantly influenced by
technical expertise and advice from Yaron Danon and other RPI research staff. It
includes functions to dead-time correct [^1], group counts data, convert to cps,
and convert neutron time-of-flight (TOF) to neutron energy.Moduleagl_tools.pyhas the capability to read list-mode data produced at GELINA.
This capability was developed to make data-reduction of GELINA data easier and relied
on verification with the original Analysis of Geel List-mode (AGL) code.The moduletrans_tools.pywas originally designed to reduce data generated by the
Comtec MCS6A Multi-stop TDC TOF clock, but will be generalized to accept other
formats of raw TOF data.trans_tools.pyis designed to reduce all the data
necessary to calculate transmission and propagate the associated covariance.Modulesam_tools.pyhas been made to assist in reading and writing files that
are used in the i/o for the code SAMMY. The packagenuctoolsalso contains
functions to assist in plotting with different styles commonly used at RPI.Moduleendf_tools.pyprovides functions to read and write ENDF/B-VI format
pointwise cross section data.To Installnuctoolscan now be installed withpip! Simply type:python-mpipinstallnuctoolsIf you'd rather install from the source found in GitHub, open a terminal and type:cd ~/git clone https://github.com/brownjm1968/nuctools.gitcd nuctoolspython -m pip install .To DocumentMake sure you have numpydoc and sphinx installed, withpipinstaller:python-mpipinstallnumpydoc
python-mpipinstallsphinxAt the sphinx websitehttp://www.sphinx-doc.org/en/master/usage/quickstart.html,
there is a brief walkthrough for first time sphinx users. This is a good place
find info on sphinx, however you shouldn't have to create the documentation, it
should be good to go when the nuctools is downloaded. The sphinx-quickstart will
write a "conf.py" for you, but you should have the properly designed conf.py
already. To use the theme I've used for the docs, you need to runpython -m pip install sphinx-rtd-theme.In the terminal navigate to the top nuctools folder and type:sphinx-apidoc--force-odocs/nuctools/where "docs/" is the output directory and "nuctools/" is where the documented
modules live. Then navigate inside the terminal to the "docs/" folder where you
just generated .rst files and type:makehtmlNote:To build the equations properly you must have LaTeX installedSome packages are required for html, and can be installed withpip(e.g.python -m pip install sphinx)To TestMake sure you have pytest, withpip:python-mpipinstallpytestThen inside the top nuctools folder type:pytestPytest should automatically go into the "tests/" folder and find python files that start
with "test".[^1]: Danon, Yaron. "Design and Construction of the RPI Enhanced Thermal Neutron Target and Thermal Cross Section Measurements of Rare Earth Isotopes.", Doctoral Thesis, RPI, (1993).
Package: nucular
Nucular is a system for creating full text indices for fielded data.
It can be accessed via a Python API or via a suite of command line interfaces.Nucular archives fielded documents and retrieves them based on field value,
field prefix, field word prefix, or full text word prefix, word proximity or
combinations of these. Nucular also includes features for determining values
related to a query often called query facets.FeaturesNucular is very light weight. Updates and accesses do not require any
server process or other system support such as shared memory locking.Nucular supports concurrency. Arbitrary concurrent updates and accesses
by multiple processes or threads are supported, with no possible locking issues.Nucular is pure Python.
Nucular indexes and retrieves data quickly.
Nucular has a funny name.More information about nucular including links to documentation,
and releases is available athttp://nucular.sourceforge.net.
Package: nucwf
NUCWFLibrary for online accessing, reading and writing A=3 and A=4 wave functions.When using the data files or software, please cite the original work:InstallationThe source code and examples are available athttps://jugit.fz-juelich.de/a.nogga/nucwavef.gitThe easiest way to install is using pip:pip install nucwfUsageThe package provides an interface to download the data files from our repository and to read the files and test.
More advanced options will be documented elsewhere.
Jupyter notebook downloading an example data base inexamples.
This directory also includes some example scripts to modify the database locally.For downloading specific files to a local directory, e.g.,$HOME/work/wftestuseimport os 
from nucwf import access
testdf=access.database(workdir=os.environ["HOME"]+"/work/wftest")This downloads a pandas dataframe with the available wave function files and stores it intotestdf. The pandas dataframe can be printed usingimport pandas as pd  
pd.set_option('display.max_columns', None)
print(testdf.pddf)Downloading wave function files of, e.g., row 4  of the table is done byimport os 
# get file info from table 
row=testdf.pddf.loc[[4]]
wfid=row.to_dict('records')[0]
# retrieve file
hashname,uniquename=testdf.get_file(**wfid)
# print name and file size 
print("hashname:    ",hashname)
print("filesize:    ",os.path.getsize(hashname))
print("uniquename:  ",uniquename)The files are downloaded and gunzipped. They are partly also compressed using the ZFP compressors (seehttps://github.com/LLNL/zfp).
Using the files might require to install the corresponding HDF plugins (https://github.com/LLNL/H5Z-ZFP).
The local files will be first stored under theirhashname.
However, the python method also returns a suggestion for a unique file nameuniquenamethat includes the parameters of the file.  If wanted, users may rename the file using the provideduniquename.The database contains two kinds to files: A=3 and A=4 wave functions.
You can read in and get some basic properties using the wavefilea4 constructorwfa4=access.wavefilea4(hashname,printlevel=1)A=3 wave functions can be tested similarly using the wavefilea3 constructorwfa3=access.wavefilea3(hashname,printlevel=1)
Package: nucypher-core
Python bindings fornucypher-coreThis repo contains the Python bindings for themain Rust project.BuildYou will need to havesetuptools-rustinstalled. Then, for development you can just dopip install -e .as usual.DevelopmentUpdatenucypher-core-python/stubtest-allowlist.txtwith:cdumbral-pre-python
python-mmypy.stubtestnucypher_core--generate-allowlist>stubtest-allowlist.txt
Package: nucypher-ipfs
NuCypher IPFSThis Python SDK allows python developer experiment NuCypher network to securely upload and download your files to IPFS.Installationinstall with pip:pip install nucypher-ipfsIf runs into connect module issue, it may cause of duplicate dependencies, fix bypip uninstall ipfs-api ipfsapi
pip install ipfsapiUsageTo use this, you must first import it and specify host name and port of a runnning instance of Ursula:>>> import nucypher_ipfs

>>> client = nucypher_ipfs.connect_ursula("https://localhost:9151")This current version connects to public IPFS gateway of Infura through API thus no need to setup additional IPFS host.Now that you have a client instance, you can make requests and process responses from the service. To begin we apparently need to get a public key of our recipient or we can generate a new one from following:>>> recipient_privkeys, recipient_pubkeys = client.generate_recipient_keys()Policy public keys will be required for the data owner to encrypt the data that belongs to the policy:>>> policy_pubkey = client.generate_owner_policy_public_key(max_days=5)Specify the file to be uploaded to IPFS network, the hash of our encrypted file will be returned when it finish.>>> filename = "test.txt"

>>> receipt = client.uploadFile(filename=filename , policy_pubkey=policy_pubkey)
{'data_source_public_key': ..., 'hash_key': 'Qmd9RNRiyT6SUMPpxWJoRmZMVGEEMcBaPRKY6EdUGTvaLk'}We can then take a look to our encrypted data by opening:https://gateway.ipfs.io/ipfs/<your hash here>A recipient can be deligated by provide their public key:>>> policy_info = client.authorize(recipient_pubkeys=recipient_pubkeys, max_days=5)Once eveything is ready, the recipient can now able to decrypt the file and download to the local machine:>>> client.downloadFile(downloadFilename="downloadFile.txt",
        recipient_privkeys=recipient_privkeys, 
        receipt=receipt, 
        policy_info=policy_info)DocumentationMore detailed information on NuCypher:https://github.com/nucypher/nucypherLicenseThis code is distributed under the terms of theMIT license.  Details can be found in the fileLICENSEin this repository.
Package: nudatus
Nudatus is a tool to remove comments from Python scripts.It was created for use inuflashto help squeeze longer programs onto the micro:bit but it should be suitable for various environments with restricted storage.NoteNudatus uses the tokenizer built into Python so only supports the syntax of the version it’s running on, but it’s extremely unlikely this will cause you any issues (print is handled fine).Personally I pronounce nudatus as new-dat-us which I appreciate is probably ‘wrong’.UsageNudatus is designed to be embedded within a greater tool (likeuflashorMubyntoll) but also provides a CLI tool:nudatus [-h] [--version] [input] [output]An input file must be specified but if output is omitted the result will be printed on stdout.Calling from a Python script is quite simple:importnudatussource=''# Input scriptresult=nudatus.mangle(source)# Result as str0.0.5Drop support for everything below Python 3.5Format with blackAdd type annotations (not that there is much to type)0.0.2Respect the contents of lists and dicts0.0.1Initial release.
Package: nudebomb
NudebombThe Nudebomb recursively strips matroska media files of unwanted audio and
subtitle tracks.NewsYou may find user focused nudebomb changes in theNEWS file.RequirementsMKVToolNixPython3Installpip installUsagePosixnudebomb -rl eng,fre /mnt/moviesWindowsnudebomb -b C:\\Program/ Files\MKVToolNix\mkvmerge.exe -rl eng,jap \\nas\moviesConfigYou may configure Nudebomb options via the command, a yaml config file and
environment variables.Environment variable formatPrefix environment variables withNUDEBOMB_NUDEBOMB__and enumerate lists
elements:NUDEBOMB_NUDEBOMB__RECURSE=TrueNUDEBOMB_NUDEBOMB__LANGUAGES__0=undNUDEBOMB_NUDEBOMB__LANGUAGES__1=engLang FilesWhile you may have a primary language, you probably want videos from other
countries to keep their native language as well. Lang files let you do this.Lang files are persistent files on disk that nudebomb parses to keep to all
languages in them in the mkvs in the current directory and all mkvs in sub
directories.Valid lang file names are: 'lang', 'langs', '.lang', or '.langs' They include
comma separated list of languages to keep like the-loption.e.g. You may have an entire collecttion of different TV shows with a root lang
file containing theenglanguage. Under that directory you may have a specific
TV show directory with lang file containingjpn. All mkvs in season
directories under that would then keep both theengandjpnlanguages, while
other TV shows would keep onlyenglanguages.For each mkv file, nudebomb looks up the directory tree for each parent lang
file and uses the union of all languages found to determine what languages to
keep.APIsLangfiles would be obsolete if nudebomb could deterimining native languages for
mkv files by polling and caching results from major online media databases. It's
the right thing to do, but I don't care to implement it. Patches or forks
welcome.InspirationNudebomb is a radical fork ofmkvstrip.
It adds recursion, lang files, timestamps and more configuration to mkvstrip and
fixes some minor bugs.
Package: nudenet
NudeNet: lightweight Nudity detectionhttps://nudenet.notai.tech/in-browser demo (the detector is run client side, i.e: in your browser, images are not sent to a server)pipinstall--upgradenudenetfromnudenetimportNudeDetectornude_detector=NudeDetector()nude_detector.detect('image.jpg')# Returns list of detectionsdetection_example=[{'class':'BELLY_EXPOSED','score':0.799403190612793,'box':[64,182,49,51]},{'class':'FACE_FEMALE','score':0.7881264686584473,'box':[82,66,36,43]},]all_labels=["FEMALE_GENITALIA_COVERED","FACE_FEMALE","BUTTOCKS_EXPOSED","FEMALE_BREAST_EXPOSED","FEMALE_GENITALIA_EXPOSED","MALE_BREAST_EXPOSED","ANUS_EXPOSED","FEET_EXPOSED","BELLY_COVERED","FEET_COVERED","ARMPITS_COVERED","ARMPITS_EXPOSED","FACE_MALE","BELLY_EXPOSED","MALE_GENITALIA_EXPOSED","ANUS_COVERED","FEMALE_BREAST_COVERED","BUTTOCKS_COVERED",]Dockerdockerrun-it-p8080:8080ghcr.io/notai-tech/nudenet:latestcurl-Ff1=@"images.jpeg""http://localhost:8080/infer"{"prediction":[[{"class":"BELLY_EXPOSED","score":0.8511635065078735,"box":[71,182,31,50]},{"class":"FACE_FEMALE","score":0.8033977150917053,"box":[83,69,21,37]},{"class":"FEMALE_BREAST_EXPOSED","score":0.7963727712631226,"box":[85,137,24,38]},{"class":"FEMALE_BREAST_EXPOSED","score":0.7709134817123413,"box":[63,136,20,37]},{"class":"ARMPITS_EXPOSED","score":0.7005534172058105,"box":[60,127,10,20]},{"class":"FEMALE_GENITALIA_EXPOSED","score":0.6804671287536621,"box":[81,241,14,24]}]],"success":true}⏎
Package: nudepy
AboutNudity detection with Python. Port ofnude.jsto Python.Installationfrom pip:$ pip install --upgrade nudepyfrom easy_install:$ easy_install -ZU nudepyRequirementsPython2.7+ and Python3.3+CythonPillowUsagevia command-line$nudepyIMAGE_FILEvia Python ModuleimportnudefromnudeimportNudeprint(nude.is_nude('./nude.rb/spec/images/damita.jpg'))n=Nude('./nude.rb/spec/images/damita.jpg')n.parse()print("damita :",n.result,n.inspect())seeexamples.LinksPyPIGitHub
Package: nudisxs
nudisxsTable of ContentsOverviewREQUIREMENTSInstallationUsageLicenseOverviewThenudisxspackage integrates Python with Fortran computational routines, offering a user-friendly interface for complex neutrino-nucleon interaction simulations. This includes both charged and neutral current exchange calculations.RequirementsLHAPDF. Install it with python support. Followinstallationinstructions. Installations to a custom place like/foo/lhapdfrequires setup of three variablesexport PATH=$PATH:/foo/lhapdf/binexport LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/foo/lhapdf/libexport PYTHONPATH=$PYTHONPATH:/foo/lhapdf/lib/pythonX.Y/site-packagesInstallationInstalling from PyPiYou can easily installnudisxsfrom PyPi using pip:pip install nudisxsInstalling from GitTo install the latest development version directly from the repository:git clone git@git.jinr.ru:dnaumov/nudisxs.gitcd nudisxspython install .UsagePython Interface
Thedisxs.pymodule innudisxsprovides all necessary interfaces to the underlying Fortran code. This includes functions for initialization and calculation of cross-sections.InitializationCommon initialization functions:most used:init_neutrino()init_pdf()init_target()for experts:init_masses()init_bend_factor()init_q2_min()init_abc()init_structure_functions()init_r_function()init_final_hadron_mass()init_fl_function()init_qc()double differential cross-sections\frac{d^2\sigma}{dxdy}are available asdisxs.xs_cc(e,x,y)for charged current exchange anddisxs.xs_nc(e,x,y)for neutral current exchange.some examples can be found innudisxs/tests/test_dis.pynudisxs/tests/test_dis_total.pyLicensenudisxsis distributed under the terms of theMITlicense.
Package: nudity
AboutNudity detection with re-trained Tensorflow MobileNet Model. Accuracy is 92.2% based on my dataset. Give it a try:http://nudity.canaydogan.netInstallation$pipinstallnudityRequirementsPython3.5+Usagevia command-line$nudity--image=IMAGE_FILEvia Python ModulefromnudityimportNuditynudity=Nudity();print(nudity.has('/file/path/example.jpg'))# gives you True or Falseprint(nudity.score('/file/path/example.jpg'))# gives you nudity score 0 - 1
Package: nudityradar
AboutNudity detection with re-trained Tensorflow MobileNet Model. Accuracy is 92.2% based on my dataset.Installation$pipinstallnudityRequirementsPython3.5+Usagevia command-line$nudity--image=IMAGE_FILEvia Python ModulefromnudityimportNuditynudity=Nudity();print(nudity.has('/file/path/example.jpg'))# gives you True or Falseprint(nudity.score('/file/path/example.jpg'))# gives you nudity score 0 - 1