Saravanan666/pypi-org huggingface dataset:
Package: n8.butler
Butler 0.0.2It just works. This is basically just a random package.Shorten big numbersStarts shortening at thousand and stops at trillion.frombutlerimportnumbersnumbers.shorten(10000000)Outputs: 10MCountdownsCountdown to day and hourfrombutlerimportcountdowncountdown.day_and_hour('monday',12)Output: [days, hours, minutes, seconds]Countdown to hourfrombutlerimportcountdowncountdown.hour(12)Ouput: [hours, minutes, seconds]
Package: naaf
naafnaafis a library for reading and writing Cryo-ET data based on thecryotypesspecification.Installationpip install naafUsagenaafprovides granular I/O functions such asread_starandread_mrc, which will all return objects following thecryotypesspecification. A higher level function calledreadadds some magic to the IO procedure, guessing file formats and returning a list ofcryotypes.Similarly to theread_*functions,naafprovides a series ofwrite_*functions.From the command lineIf you just need to quickly inspect your data, this command will land in an ipython shell with the loaded data collected in a list calleddata:naafpath/to/files/*/other/path/to/file.starFeaturesCurrentlynaafis capable of reading images in the following formats:.mrc(and the.mrcsor.stvariants)Dynamo.emand particle data in the following formats:Relion.starDynamo.tblCryolo.cboxand.boxWriter functions currently exist for:.mrcDynamo.emRelion.starDynamo.tblImage dataWhen possible (and unless disabled), naaf loads images lazily usingdask. The resulting objects can be treated as normal numpy array, except one needs to callarray.compute()to apply any pending operations and return the result.ContributingContributions are more than welcome! If there is a file format that you wish were supported in reading or writing, simply open an issue about it pointing to the specification. Alternatively, feel free to open a PR with your proposed implementation; you can look at the existing functions for inspiration.
Package: naam
No Argparse Any More.Don’t google argparse just take some NAAMI forget how to use argparse every time I make utilities10+ lines for just parsing arguments? No way!There should be a super pythonic way to parse arguments!!!!I love Kizuna Ai.Installpip install naamHow to use itJust decorate your main function like@naam.bind_argsand execute
it!ExampleHere’s a code (placed in examples/optional.py):fromnaamimportbind_args@bind_argsdefhello(first_name,last_name=None):msg='Hello world! My name is%s.'iflast_nameisNone:print(msg%first_name)else:print(msg%'{}{}'.format(first_name,last_name))hello()With empty arguments, this outputs:Usage: optional.py [-l LAST_NAME | --last_name LAST_NAME] FIRST_NAMEWith arguments, this outputs like:$ python optional.py Miku
Hello world! My name is Miku.

$ python optional.py Miku --last_name Hatsune
Hello world! My name is Miku Hatsune.

$ python optional.py Miku -l Hatsune
Hello world! My name is Miku Hatsune.PrerequisitesNo dependencies. Works on Python 3.x (Built on Python 3.6.2).Features I craveType casting for type-annotated args
Package: naamkaran
naamkaran: generative model for namesNaamkaran is a generative model for names. It is based on a character-level RNN trained on names from the Florida Voter Registration Data.Gradio App.Naamkaran on HFInstallationNaamkaran can be installed from PyPI using pip:pipinstallnaamkaranGeneral APIThe general API for naamkaran is as follows:# naamkaran is the package name
from naamkaran.generate import generate_names

# generate_names is the function that generates names

positional arguments:
  start_letter  The letter to start the name with

optional arguments:
    end_letter  The letter to end the name with (default: None)
    how_many    The number of names to generate (default: 1)
    max_length  The maximum length of the name (default: 5)
    gender      The gender of the name (default: "M")
    temperature The temperature of the model (default: 0.5)

# generate 10 names starting with 'A'
generate_names('A', how_many=10)
['Allis', 'Alber', 'Aderi', 'Albri', 'Alawa',
'Arver', 'Agnee', 'Anous', 'Areyd', 'Adria']


# generate 10 names starting with 'B' and ending with 'n'
generate_names('B', end_letter='n', how_many=10)
['Brian', 'Beran', 'Burin', 'Bahan', 'Balin',
'Bounn', 'Baran', 'Balan', 'Belin', 'Brion']

# generate 5 names starting with 'B' and ending with 'n' with a maximum length of 4
generate_names('B', end_letter='n', how_many=5, max_length=4)
['Bern', 'Bren', 'Bran', 'Bonn', 'Brun']

# generate 10 names starting with 'D' and ending with 'd' with a maximum length of 6
# and a temperature of 0.5
generate_names('D', end_letter='d', how_many=5, max_length=6, temperature=0.5)
['Derayd', 'Davind', 'Deland', 'Denild', 'David']

# generate 10 female names starting with 'A' and ending with 'e' with a maximum length of 5
# and a temperature of 0.5
generate_names('A', end_letter='e', how_many=10, max_length=5, gender="F", temperature=0.5)
['Annhe', 'Annie', 'Altre', 'Anne', 'Ashle',
'Arine', 'Anice', 'Andre', 'Anale', 'Allie']DataThe model is trained on names from the Florida Voter Registration Data from early 2022.
The data are available on theHarvard DataverseAuthorsRajashekar Chintalapati and Gaurav SoodContributingContributions are welcome. Please open an issue if you find a bug or have a feature request.LicenseThe package is released under theMIT License.
Package: naapc
Nested Automated Argument Parsing Configuration (NAAPC)NAAPCcontains two classes: NConfig and NDict.
NDict provides method to easily manipulate nested dictionaries.
NConfig is a subclass of NDict and canautomatically modify configurations according to CLI arguments.InstallationpipinstallnaapcOr from source code:pipinstall.Typical Usage.ndict Usagesfor a sample configuration test.yaml file:task:task:classificationtrain:loss_args:lr:0.1and a sample list configuration test_list.yaml file:l:-d:task:task:classification-d:train:loss_args:lr:0.1fromnaapcimportndictwithopen("test.yaml","r")asf:raw=yaml.safe_load(f)nd=ndict(raw["d"],delimiter=";")nd1=ndict.from_flatten_dict(nd.flatten_dict)# nd1 == ndnd2=ndict.from_list_of_dict(raw["l"])# nd2 == nd1 == nd"task;path"innd# "task" in raw and "path" in raw["task"]delnd["task;path"]# del raw["task]["path]nd["task;path"]="cwd"# raw["task"]["path"] = Path(".").absolute()nd.flatten_dict# {"task;task": "classification", "train;loss_args;lr": 0.1}nd.flatten_dict_split# raw["l"]nd.paths# ["task", "task;task", "train", "train;loss_args", "train;loss_args;lr"]nd.get("task;seed",1)# raw["task"].get("seed", 1)nd.raw_dict# rawnd.size# len(nd.flatten_dict)nd.update({"task;here":"there"})# raw["task]["here] = "therend.items()# raw.items()nd.keys()# raw.keys()nd.values()# raw.values()len(nd)# len(raw)bool(nd)# len(nd) > 0nd1==nd# nd1.flatten_dict == nd.flatten_dictnd1["task;path"]="xcwd"nd1["task;extra"]="ecwd"nd["train;epochs"]=100nd.diff(nd1)# {"task;path": ("cwd", "xcwd"), "task;extra": (None, ecwd), "train;epochs": (100, None)}Check test/test_ndict.py for detailed usage.Known IssuesAssign a list of ndict won't flatten them. Try to avoid using list.TypingAdd a typeNestedOrDict=Union[ndict,dict]
Package: naas
:sparkles: Welcome to Naas!Notebooks as a service (Naas) is an open source platform that allows anyone touching data (business analysts, scientists and engineers) to create powerful data engines combining automation, analytics and AI from the comfort of their Jupyter notebooks.Naas is an attempt to propose an alternative to Google Colab, powered by the community.In addition to Google Colab, Naas platform upgrade notebooks with with 3 low-code layers: features, drivers, templates.Templatesenable the user to create automated data jobs and reports in minutes.Driversact as connectors to push and/or pull data from databases, APIs, and Machine Learning algorithms and more.Featurestransform Jupyter in a production ready environment with scheduling, asset sharing, and notifications.🚀 Quick StartTry all of Naas's features for free using --Naas cloud-- a stable environment, without having to install anything.⚙️ InstallationCheck out our step by step guide on how toset up Naas locally.❤️ ContributingWe value all kinds of contributions - not just code. We are paticularly motivated to support new contributors and people who are looking to learn and develop their skills.Please read ourcontibuting guidelineson how to get started.🤔 Community SupportThe naasdocumentationis a great place to start and to get answers for general questions.Slack(Live Discussions)GitHub Issues(Report Bugs)GitHub Discussions(Questions, Feature Requests)Twitter(Latest News)YouTube(Video Tutorials)Previous Community calls(Video call discussions with the naas team & other contributors.)Naas's community page(To know more):page_with_curl: LicenseThe project is licensed underAGPL-3.0
Package: naas-drivers
Welcome to Naas Drivers 🏎Simple formulas to build highly efficient scripts.You can check the documentation here:https://docs.naas.aiLow code philosophyWe came from excel with the conviction that Python is awesome and much more powerful.
But the number of lines you have to write in Python can be overwelming.So we created simple low code formulas that tech and non-tech people can use to facilitate integrations with third party tools.Simple formulas to interact with powerfull tools.Each driver returns a dataframe to get a strandardized output accross integrations.IssuesIf you found a bug or need a new feature, please raise an issue.Installpython -m pip install naas_driversCheck lintpython3 -m black naasformat betterpython3 -m flake8 naascheck if any left errorPublishThis auto publish on pypip by github action on main branch.Authors:Jeremy RavenelMaxime JublouMartin DonadieuFlorent RavenelLegalLinkedIn driverThis code is in no way affiliated with, authorized, maintained, sponsored or endorsed by Linkedin or any of its affiliates or subsidiaries. It uses an independent and unofficial API. Use at your own risk.
This project violates Linkedin's User Agreement Section 8.2, and because of this, Linkedin may (and will) temporarily or permanently ban your account. We are not responsible for your account being banned.
Package: nabeuserbot-pylibs
Kynanlibs LibraryCore library ofNaya-Pyro, a python based telegram userbot.Installationpip3install-Upy-AyraDocumentationSee more working plugins onthe offical repository!Made with 💕 byKynan.LicenseUltroid is licensed underGNU Affero General Public Licensev3 or later.Credits
Package: nabo
NaboNabo is a flexible Python package that allows projections of cells from one
population to another using single-cell RNA-Seq data. Nabo works by setting one
of the populations as areferenceand then maps cells from other populations
(targets) onto it. Nabo provides data implicit methods of verifying mapping
quality, this allows users to clearly infer similarities between
sub-populations across samples.Please refer to thedocumentationto know more.
Package: nabs
nabsNot a Beamline ScientistThis is the landing site for shared code that interfaces with bluesky and
pcdsdaq for beamline automation and data collection routines for LCLS photon
science.It is named NABS, Not a Beamline Scientist, because it is the go-to when the
question is "Who should be doing this procedure?" and the answer is "Not a
Beamline Scientist!", e.g. it is something that should not be done by hand.
Package: nabto-client
python-nabto-clientPython Wrapper for Nabto ClientRequirementsPython 3.6+python3-devpackage for Debian distributionsInstallationInstall usingpip...pip install -i https://test.pypi.org/simple/ nabto-clientExampleLet's take a look at a quick example of usingnabto_clientto open a session and a tunnel.import nabto_client

NABTO_HOME_DIRECTORY = "/home/nabto/example"

USER = "user"
PASSWORD = "password"

LOCAL_PORT = 7000
NABTO_HOST = "example.appmyproduct.com"
REMOTE_HOST = "localhost"
REMOTE_PORT = 8000

# Initializes the Nabto client API
nabto_client.startup(NABTO_HOME_DIRECTORY)

# Creates a Nabto self signed profile
nabto_client.createSelfSignedProfile(USER, PASSWORD)

with nabto_client.NabtoSession(USER, PASSWORD) as session:
    with nabto_client.NabtoTunnel(session, LOCAL_PORT, NABTO_HOST, REMOTE_HOST, REMOTE_PORT) as port:
        print(f'Opened tunnel on port {port}')
        ...
        
# Releases any resources held by the Nabto client API
nabto_client.shutdown()Tunnel statusThe example above doesn't allow to query the current status of the tunnel because the context manager returns the port not the tunnel object.If you want to query the tunnel status, don't use the context manager, instead create and open a tunnel like this:tunnel = nabto_client.NabtoTunnel(session, LOCAL_PORT, NABTO_HOST, REMOTE_HOST, REMOTE_PORT)
print(f'Tunnel status is {tunnel.status()}') # -1 or TunnelStatus.CLOSED
port = tunnel.openTcp()
print(f'Opened tunnel on port {port}')
print(f'Tunnel status is {tunnel.status()}') # 3 or TunnelStatus.LOCAL
# ... do something with the tunnel
tunnel.close()
if nabto_client.TunnelStatus.CLOSED == tunnel.status():
    print(f'Tunnel is closed')You can also runexample/cli.pyfor an interactive example.python example/cli.py --device example.appmyproduct.com
Package: nabu
NabuESRF tomography processing software.InstallationTo install the development version:pipinstall[--user]git+https://gitlab.esrf.fr/tomotools/nabu.gitTo install the stable version:pipinstall[--user]nabuUsageNabu can be used in several ways:As a Python library, by features likeBackprojector,FlatField, etcAs a standalone application with the command line interfaceFrom Tomwer (https://gitlab.esrf.fr/tomotools/tomwer/)To get quickly started, launch:nabu-configEdit the generated configuration file (nabu.conf). Then:nabunabu.conf--slice500-600will reconstruct the slices 500 to 600, with processing steps depending onnabu.confcontents.DocumentationThe documentation can be found on the silx.org page (https://www.silx.org/pub/nabu/doc).The latest documentation built by continuous integration can be found here:https://tomotools.gitlab-pages.esrf.fr/nabu/Running the testsOnce nabu is installed, runningnabu-testwill execute all the tests. You can also specify specific module(s) to test, for example:nabu-testpreprocmiscYou can also provide morepytestoptions, for example increase verbosity with-v, exit at the first fail with-x, etc. Usenabu-test --helpfor displaying the complete options list.Nabu - what's in a name ?Nabu was the Mesopotamian god of literacy, rational arts, scribes and wisdom.
Package: nac
Simple socket/console game implementation.dependencies & installationWorks under python version: 2.6, 2.7. No additional dependencies. Install package with pip:$ pip install nacoverviewThis repository holds a python package implementing a simple socket game,Noughts and Crosses.First you shall run the server, and then the client:$ ./nac/server.py
$ ./nac/client.pyYou will see the game board represented by few console lines:(0)|(1)|(2)
---+---+---
(3)|(4)|(5)
---+---+---
(6)|(7)|(8)Enter the position you want to put your mark:Your move: 0X |(1)|(2)
---+---+---
(3)|(4)|(5)
---+---+---
(6)|(7)|(8)The server is ‘X’ and the client is ‘O’.
Package: nacal
Módulo "NAcAL" (Notación Asociativa para un Curso de Álgebra Lineal)Este módulo implementa la notación empleada en mi curso deÁlgebra Lineal (Matemáticas II)Aunque no es estrictamente necesario, está pensado para su uso con losNotebooks de Jupyter.
En dicho entorno el módulo muestra como llegar a la mayoría de los resultados empleando el método de
eliminación. Es decir, este módulo o librería, no solo resuelve sistemas de ecuaciones, invierte
matrices, calcula determinantes, diagonaliza matrices tanto por semejanza como por congruencia, etc.
Sino que muestra los pasos empleados para llegar al resultado como si se hiciera con lápiz y papel.
Además, también permite trabajar con subespacios y espacios afines de. También puede trabajar de
manera simbólica, pues emplea los objetos básicos del móduloSympy.https://github.com/mbujosab/CursoDeAlgebraLinealLa documentación explica la programación del código y sirve como
material adicional allibro del curso(este módulo es una implementación literal de lo mostrado en
dicho libro). Puede ver el uso del módulo sin necesidad de
instalar nada, tan solo accediendo a los Notebooks de Jupyter alojados encon su navegador de páginas web (puede tardar unos minutos en
cargar el módulo y el Notebook de demostración).Instalaciónnacalfunciona con Python 3.7. Puede instalar el paquete desde PyPI via pip:pip3installnacalnacalempleaSympy. Para instalar Sympy:pip3installsympyUsoPara emplear este módulo en una consola de Python, una vez instalada:pyhton3
>>>fromnacalimport*Para emplearlo en un Notebook de Jupyter, ejecute en un "Cell" de códigofrom nacal import *DesinstalaciónPara desinstalarnacal:pip3uninstallnacal
Package: nacelle
nacelle is a lightweight Python web framework, built on top of webapp2,
designed for use on Google Appengine.nacelle aims to provide a small but solid set of tools that enable developers
to quickly get a new app up and running, whilst not sacrificing any of the
flexibility and power of webapp2 in the process. Nacelle is suitable for
building everything from tiny prototypes to large complex applications, it
should never get in your way.NoteIf you need portability from appengine then nacelle probably isn’t for you,
use Django, Flask or one of the many other awesome Python web frameworks
that exist, you’ll thank me later.Free software:MIT licenseDocumentation:http://nacelle.rtfd.org.FeaturesAuthentication using Appengine’s built-in users serviceCustom testrunner to help with loading the appengine environment for noseError handling (with optional logging to a sentry server)Session management and automatic secret key generationTemplate rendering (with Jinja2 or Handlebars)Easily run tasks in the background outside of the request loop
Package: nacf
Table of ContentsProloguePackagesUsageDevelopment ProcessHttp FunctionsGetPostBugsFix an error from inspect.Parameter which caused the function parallel down.:err:1:DocsUsageEpoligueHistoryVersion 1.0.2Version 1.0.1Version 1.0.0Version 0.1.2Version 0.1.1Version 0.1.0PrologueNever had such a pure crawler like thisnacf.Although I often write crawlers, I don’t like to use huge frameworks, such as scrapy, but prefer
simplerequests+bs4or more generalrequests_html.  However, these two are inconvenient for a
crawler.  E.g. Places, such as error retrying or parallel crawling, need to be handwritten by
myself.  It is not very difficult to write it while writing too much can be tedious.  Hence I
started writing this nacf (Nasy Crawler Framework), hoping to simplify some error retrying or
parallel writing of crawlers.PackagesTable 1:PackagesPackageVersionDescriptionrequests-html0.10.0HTML Parsing for Humans.nalude0.3.0A standard module.  Inspired by Haskell’s Prelude.Usageseetests.Development ProcessDONE Http FunctionsCLOSED:<Thu Feb 28 20:51:00 2019>DONE GetCLOSED:<Tue Dec 25 17:36:00 2018>DONE PostCLOSED:<Thu Feb 28 20:44:00 2019>DONE BugsCLOSED:<Thu Feb 28 20:51:00 2019>DONE Fix an error from inspect.Parameter which caused the function parallel down.     :err:1:CLOSED:<Wed Dec 26 20:26:00 2018>NEXT DocsNEXT UsageEpoligueHistoryVersion 1.0.2Data:<Sun Mar 10, 2019>Changes:Update nalude.Version 1.0.1Data:<Sun Mar 10, 2019>Changes:Update requests-html.Version 1.0.0Data:<Thu Feb 28, 2019>Changes:Now, old HTTP methods (getandpost) cannot accept multiple URLs. Instead, we can usegetsandposts.Adds:-nacf.htmlnacf.jsonnacf.getsnacf.postsIncludes:-naludeVersion 0.1.2Data:<Wed Dec 26, 2018>Fixed:inspect.Parametererror in last version.Version 0.1.1Data:<Wed Dec 26, 2018>Ignored:An error caused byinspect.ParameterHelp Wanted:Can someone help me about the Parameter?Version 0.1.0Date:<Sun Dec 23, 2018>Commemorate Version:First VersionBasic Functions.
Package: nacha3
nachaNACHAis a fixed sized
record format used to represent financial transactions composed like this:FileHeader
    CompanyBatchHeader
        EntryDetail
            EntryDetailAddendum
            ...
        ...
    CompanyBatchControl
    ...
FileControlwhich we express usingbryl. Writing is
done like this:withopen('sample.nacha','w')asfo:writer=nacha.Writer(fo)withwriter.begin_file(...):withwriter.begin_company_batch(...):writer.entry(...):......Reading is done by iterating records like this:withopen('sample.nacha','r')asfo:reader=Reader(fo,include_terminal=True)forrecord,terminalinreader:...Or structured like this:withopen('sample.nacha','r')asfo:reader=Reader(fo)reader.file_header()forcompany_batch_headerinreader.company_batches():forentry_detail,entry_addendainreader.entries():...reader.company_batch_control()reader.file_control()use$pipinstallnacha3dev$gitclonehttps://github.com/rockxraj68/nacha3.git$cdnacha$mkvirtualenvnacha(nacha)$pipinstall-e.[tests](nacha)$py.testtests.py--cov=nacha--cov-reportterm-missing
Package: nachomines
NachoMinesA python minesweeper game using pygameRequiresPython 3.6 or greaterpygameInstallationpip3installnachominesorgitclonehttps://github.com/nachomonkey/NachoMinescdnachomines
python3setup.pyinstallLaunching the gameThesetup.pyscript installs the "nachomines" python module, a "nachomines" console script, and a .desktop file on linux machines.To launch on Windows or Linux, run:python3-mnachominesor if you cloned the repository, run:python3run_game.pyOn linux, an application by the name "NachoMines" should be found in the "Games" section of your application menuGameplay and ControlsPress <Esc> or <Q> to exitMain MenuThe "Grid Subdivisions" drop-down menu selects the size of the game boardThe "Mine Density" drop-down menu controls the chance in percentage of a square containing a mine.The "Theme" drop-down menu decides if you want a light, dark, ornachotheme during gameplay.GameHover over the blocks using the cursor. Right-click to flag a block.
Left-click to show an empty square and the empty squares near it.Win by flagging all of the mines.CreditsThe success sound was a modified version of asoundby kagateni on freesound.orgLicenseUses the MIT License. See theLICENSE filefor further detail.
Package: nacispreloader
READMEThis package is a preloader for nacis (North American Cartographic Information
Society) shapefiles.  It is intended to supplement python applications making
use of cartopy shapefiles (which are downloaded from nacis servers). By using
this preloader, the nacis download can be replaced with loading shapefiles from
s3 instead (where available).Currently includes:10m roads10m, 50m, 110m countries10m, 50m, 110m states_provinces10m, 50m, 110m coastline10m, 50m, 110m rivers_lake_centerlinesseehttp://www.naturalearthdata.com/downloads/for more information about available shapefiles (those not provided by this preloader).
see alsohttps://gist.github.com/DanielJWood/b71237cc200831acf8e637c05ce2c375#file-natural_earth_s3_links-mdfor alternate download location for the source shapefile zips.How to i use it?from nacis.preloader import Preloader
preloader = Preloader('yours3bucket','yours3prefix')preload roads, countries, coastlines:preloader.preload('roads','cultural','10m')
preloader.preload('countries','cultural','10m')
preloader.preload('coastline','physical','10m')make a chart:import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrsfig = plt.figure(figsize=(7,7))
ax = plt.axes(projection=ccrs.PlateCarree())
ax.coastlines(resolution='10m', color = 'black', linewidth=1.0)
cartopy.feature.NaturalEarthFeature('cultural','countries','10m')
cartopy.feature.NaturalEarthFeature('cultural','roads','10m')
ax.set_extent([-180,180,-90,90])
plt.savefig('out.png')
plt.close()
Package: nacla
# 使用办法:>>> from nacla import nacla
>>> nacla.predict("ming")
(-1.36) Scottish
(-1.66) English
(-1.71) German
>>> nacla.predict("qiang")
(-1.96) English
(-2.01) Dutch
(-2.14) Italian
>>> nacla.predict("xiao ming")
(-0.82) Scottish
(-1.89) English
(-2.20) Greek
>>> nacla.predict("ai guo")
(-0.82) Portuguese
(-1.72) Italian
(-1.93) Spanish