Saravanan666/pypi-org huggingface dataset:
Package: nastranpy
A library to interact with nastran models.Requirementspython 3.3 (or later)numpyInstallationRun the following command:pip install nastranpyUsage exampleImport the model:import nastranpy


model = nastranpy.Model()
model.read(['/Users/Alvaro/nastran_model_input/nastran_launcher.dat'])Export the model:model.path = '/Users/Alvaro/nastran_model_modified'
model.write()Get help of a given method:help(model.cards)Get help of a given card:nastranpy.card_help('GRID')Get a single card by its id:coord_card = model.coords[45]
grid_card = model.grids[5462]
elem_card = model.elems[234232]
prop_card = model.props[2342]
mat_card = model.mats[4232]
mpc_card_set = model.mpcs[325234]
spc_card_set = model.spcs[234232]
load_card_set = model.loads[234232]Get cards by different ways:# Get grids by ids:
grids = [grid for grid in model.cards('grid', [34, 543453, 234233])]

# Get elements by an ID pattern:
elems = [elem for elem in model.cards('elem', ['9', '34', '*', '*', '1-8'])]

# Get all CQUAD4 and CTRIA cards:
elems = [elem for elem in model.cards(['CQUAD4', 'CTRIA3']]

# Get all shell element cards in a set includes:
elems = [elem for elem in model.cards('e2D', includes=['Sp1_Hng_outbd_v04.bdf',
                                                       'Wing-Box_V16.2.bdf'])]
# Get all element card with a given property:
elems = [elem for elem in self.props[400021].child_cards('elem')]

# Get all property card with a given material:
props = [prop for prop in self.mats[10].child_cards('prop')]Get model info:model.info()Write a model summary to a csv file:model.print_summary()Write card fields to a csv file:model.print_cards(model.cards('grid', includes=['BulkData/Sp2_Sprdr_v05.bdf']))Get ID info for a given card type:print(model.get_id_info('mpc', detailed=True))
print(model.get_id_slot('grid', 1000))Get shell geometrical info:shells_info = {shell.id: (shell.area, shell.normal, shell.centroid) for
               shell in model.cards('e2D')}Renumber cards by correlation:correlation = {
    235437: 4703436,
    235438: 4703437,
    235463: 4703462,
    235464: 4703463,
    235465: 4703464,
}

model.renumber('grid', correlation=correlation)Renumber cards by start id and step:id_list = [
    235472,
    235473,
    235474,
    235488,
    235489,
    235490,
]

model.renumber('grid', model.cards('grid', id_list),
               start=4703465, step=5)Renumber cards by an id pattern:id_list = [
    235496,
    235497,
    235510,
    235511,
    235512,
    235513,
    235514,
    235515,
]

model.renumber('grid', model.cards('grid', id_list),
               id_pattern=['9', '34', '*', '*', '*', '*', '1-8'])Extend elements by steps:# Extend from an element
model.elems[3612829].extend(steps=2)
# Extend from a grid
model.grids[3815443].extend(steps=2)Extend elements by filter:# Extend from an element
model.elems[8048206].extend('e2D')
# Extend from a grid
model.grids[8020333].extend('e2D')Make include self-contained:include = model.includes['BulkData/3C0748_Sp2_ob_Sprdr_v05.bdf']
include.make_self_contained()ContactÁlvaro Sanz Oriz –alvaro.sanz.oriz@gmail.com
Package: nasty-typeshed
Pythonstub filescreated
duringNASTY’s development.These stub files do not try to be feature complete representations of the original
packages, instead they restrict themselves to just the functionality that I needed at
the time.
In rare cases methods might contain deliberatly false type annotations, to make typing
or usage easier.LicenseCopyright 2019-2020 Lukas Schmelzeisen.
Licensed under theApache License, Version 2.0.
Package: nasunitest
nasunitestDocumentation:https://dterrynasuni.github.io/nasunitestSource Code:https://github.com/dterrynasuni/nasunitestPyPI:https://pypi.org/project/nasunitest/Test cookiecutter projectInstallationpipinstallnasunitestDevelopmentClone this repositoryRequirements:PoetryPython 3.7+Create a virtual environment and install the dependenciespoetryinstallActivate the virtual environmentpoetryshellTestingpytestDocumentationThe documentation is automatically generated from the content of thedocs directoryand from the docstrings
of the public signatures of the source code. The documentation is updated and published as aGithub project pageautomatically as part each release.ReleasingTrigger theDraft release workflow(pressRun workflow). This will update the changelog & version and create a GitHub release which is inDraftstate.Find the draft release from theGitHub releasesand publish it. When
a release is published, it'll triggerreleaseworkflow which creates PyPI
release and deploys updated documentation.Pre-commitPre-commit hooks run all the auto-formatters (e.g.black,isort), linters (e.g.mypy,flake8), and other quality
checks to make sure the changeset is in good shape before a commit/push happens.You can install the hooks with (runs for each commit):pre-commitinstallOr if you want them to run only for each push:pre-commitinstall-tpre-pushOr if you want e.g. want to run all checks manually for all files:pre-commitrun--all-filesThis project was generated using thewolt-python-package-cookiecuttertemplate.
Package: nat
Getting Started|Releases|StatusNeuroAnnotation Toolbox (NAT)Python module to use the annotations created withNeuroCurator, for example in aJupyternotebook.This framework has been described in details in the following open-access
paper:https://doi.org/10.3389/fninf.2017.00027.NAT provides the necessary functions and utilities to:reliably annotate the neuroscientific literature,curate published values for modeling parameters,save them in reusable corpora.Getting StartedRequirements:System side:Git 1.7.0+ImageMagick 6Python side:Beautiful Soup 4GitPythonlxmlNumPypandasparsePyzoteroquantitiesSciPyWandInstallation:pipinstallnatReleasesVersions and their notable changes are listed in thereleases section.Releases are synchronized with the ones of NeuroCurator.StatusCreated during 2016.Ongoing stabilization and reengineering in the branchrefactor-architecture.The branchrefactor-architectureisnotintended to be used by end-users.New features, bug fixes and improvements are done on the reengineered code sections.When a reengineered code section is stable, it's merged into the branchmasterand a release is published.
Package: nata
Natais a python package for post-processing and visualizing simulation
output for particle-in-cell codes. It utilizes the numpy interface to provide
a simple way to read, manipulate, and represent simulation output.Installing nataNata is available on PyPI. You can install it by running the following
command inside your terminalpipinstallnataIt can be used inside an IPython shell orjupyter notebooktogether
withipywidgets. Hence, you
might need to run after the installation# can be skipped for notebook version 5.3 and abovejupyternbextensionenable--py--sys-prefixwidgetsnbextensionand if you want to use it inside JupyterLab (note that this requires nodejs
to be installed)jupyterlabextensioninstall@jupyter-widgets/jupyterlab-managerIn case of issues, please visit theinstallation section of ipywidgetsfor further details.Contributing to nataAny type of contribution to nata is appreciated. If you have any issues,
please report themby adding an issue on GitHub. But if
you wish to directly contribute to nata, we recommend to setup a local
development environment. Follow the instruction below for more details.Getting the source codeThe source code is hosted on GitHub. Simply create a fork and apply your
changes. You can always push any changes to your local fork, but if you would
like to share your contribution, please create a pull request, so that it can
be reviewed.Local Development EnvironmentFor the local development environment, we usepoetry. This allows us to deal better with
dependencies issues and to ensure coding standards without the burden of
manually fixing and checking for styles. To use poetry, simply install it
using the latest version by running the following command in your terminal.curl-sSLhttps://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py|pythonAfterwards, simply runpoetryinstallwhich will install all the dependencies (including development packages) in a
virtual environment. If you wish to run a command inside the virtual
environment, simply run it bypoetry run <your command>, e.g. to run all
the testpoetryrunpytesttestsAlternatively, you can directly use the virtual environment by running the
commandpoetryshellwhich will spawn a shell inside the virtual environment. With this, you can
even run jupyter outside of the source directory.In addition, we usepre-committo help us keep
consistency in our development without any additional burden. Please use it
as well. Inside the root directory of the repository, run the commandpoetryrunpre-commitinstallwhich will create commit hooks for you and modify files keeping a consistent
structure.CreditsNatais created and maintained byAnton HelmandFábio Cruz.The development is kindly supported by theGroup for Lasers and Plasmas (GoLP).
Package: nataili
Nataili: Multimodal AI Python Library!! NOTICE: This package is obsolete !!Please switch to usinghordelibwhich is based on ComfyUI.Nataili is a Python library that provides tools for building multimodal AI applications. With its modular design, Nataili makes it easy to use only the tools you need to build custom AI solutions.Some of the technologies included in Nataili are:AITemplate: Fast diffusionBLIP: Image captioningCLIP: Interrogation (ranking, similarity), Embedding (text, image) with cache supportCLIP+MLP PredictorCodeFormer: Post-processing and super-resolution for facesESRGAN: Image super-resolutionGFPGAN: Post-processing for facesLAION-CoCa: Image captioningStable Diffusion: Image generationSD Upscaler: latent diffusion upscaler for Stable Diffusion's autoencoderTrain: Training tools for Stable Diffusion and CLIP+MLP PredictorProjects using NatailiAI Horde workerInstallationpip install natailiFrom source:git clone https://github.com/db0/nataili
cd nataili
pip install -e .DocumentationIndexOverviewModel ManagerBlipClipLAION-CoCa
Package: natalify
NatalifyNatalify is an automation software designed to assist in various tasks. It provides a range of functionalities to automate repetitive actions, saving time and effort.FeaturesInstagram Automation: Natalify allows you to automate actions on Instagram, such as liking posts, commenting, and more.Easy-to-Use: The library provides a user-friendly interface and simple methods to perform automation tasks effortlessly.Customizable: Natalify offers flexibility with customizable settings, allowing you to adjust automation behavior to your specific needs.Secure and Reliable: The library uses industry-standard encryption and follows best practices to ensure data security and privacy.InstallationYou can install Natalify using pip:pipinstallnatalify--- mac and linux ---pip3installnatalifyUSAGETo utilize the library, you can run it directly from the command shell--- windows ---python-mnatalify--- mac and linux --python3-mnatalifyNatalify requires Python 3.8 or higher.usage 2
To incorporate the "natalify" library into your own script, follow these steps:importnatalifynatalify.start()LicenseNatalify is released under the GNU General Public License v3.0 (GPL-3.0).Contributing
Contributions are welcome! If you find any issues or have suggestions for improvements, please feel free to open an issue or submit a pull request.ContactFor any inquiries or feedback, please contact the author:Name: Jack.
Email:kinginjack@gmail.com
Package: natari
natariNapari gamingSliding puzzleRestore the image by reordering the superpixels using theW,A,S,Dkeys!Cell counting arcadeCommander! Cells are intruding our dish! Control your tiny space ship using1and2keys to move it left/right.
Use the9key to shoot a anti-cell bullet.The image originates fromBBBC022v1(Gustafsdottir et al., PLOS ONE, 2013), available from the Broad Bioimage Benchmark Collection (Ljosa et al., Nature Methods, 2012).SnakeTwo mitochondria navigating in a cell searching for stress granules.
The two players can control their mito using theW,A,S,DandI,J,K,Lkeys, respectively.Ping pongDon't drop the organoid! Use your racket and hit it back to your colleague!
The two players can useW,SandI,Kto control their racket, respectively.Thisnapariplugin was generated withCookiecutterusing with@napari'scookiecutter-napari-plugintemplate.InstallationYou can installnatariviapip:pip install natariKnown issuesTo make the keyboard buttons work, you sometimes have to click within the image after starting the game.ContributingContributions are very welcome.License"natari" is free and open source software. The code is in the public domain.See also: unlicense.orgIssuesIf you encounter any problems, pleasefile an issuealong with a detailed description.
Package: natcap.invest
About  InVESTInVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) is a family
of tools for quantifying the values of natural capital in clear, credible, and
practical ways. In promising a return (of societal benefits) on investments in
nature, the scientific community needs to deliver knowledge and tools to
quantify and forecast this return. InVEST enables decision-makers to quantify
the importance of natural capital, to assess the tradeoffs associated with
alternative choices, and to integrate conservation and human development.InVEST is licensed under a permissive, modified BSD license.For more information, see:InVEST API documentationInVEST onGitHubTheNatural Capital Project website.Installing InVESTPython DependenciesRuntime dependencies fornatcap.investare listed inrequirements.txt.Installing via pipIf you have a compiler installed and configured for your system, and
dependencies installed, the easiest way to install InVEST as a python package
is:$pipinstallnatcap.investInstalling the latest development versionThe latest development version of InVEST can be installed from our git
source tree:$pipinstall"git+https://github.com/natcap/invest@main#egg=natcap.invest"DevelopmentDependencies for InVEST are listed inrequirements.txt(runtime
requirements),requirements-dev.txt(development requirements), andrequirements-docs.txt(for building documentation).SupportParticipate in the NatCap forums here:http://community.naturalcapitalproject.orgBugs may be reported athttp://github.com/natcap/invest
Package: natclip
实现windows、macos或及其之间的剪切板文本共享, 可用于moonlight串流等远程控制剪切板不能用或失效的问题.# 教程安装 python 3 和 pip (自行解决)打开终端运行(两台电脑都需要): pip install natclip启动服务端: natclip启动客户端: natclip -c -i=这里填服务端的ip地址服务端防火墙放行tcp端口(默认端口48011)通过服务端再启动客户端连接另一个服务端可以实现多台电脑的共享剪切板套一个加密代理和内网穿透可以实现公网剪切板共享查看其他可修改参数: natclip -h## windows server 端的一个例子![server](server.png)## macos client 端的一个例子![client](client.png)
Package: natedhaliwal
NateDhaliwal-PackageThis is a package that allows Python functions to be used better, with less lines of code.InstallationTo install this package, enter this command line:pip install natedhaliwalThis package allows you to type in colour by specifying the name of the colour as one of its many functions.The program displays the text in the specified colour, which is red, in this case. At the end of the line, the program removes any effects that may continue onto the next line.Withnatedhaliwal, you can also open, create, read, overwrite and add data to and from the file.You can allow the program to wait a specified number of seconds, clear the console or output, generate a random number in the specified range, pick a random item from the specified list, and even scrape websites as well!In addition, you may convert JSON data, and vice-versa. Perfect for dealing with large JSON files!Examples of codeFunctionsdisplay(text, colour,typewriter): Displays text in the output, with an optional color or effect feature, or a typewriter-style display. If the colour field is left empty, it acts like a normalprint()statement.The list of colours/effects are:BoldItalicUnderlineRedPinkYellowGreenBluePurpleGreyThe typewriter must be specified when using it,  setting it to True. It's off by default.clear(): Clears the output screen.randnum(start, end): Gets a random integer from the range given.randlist(listName): Picks a random value from a provided list.randfloat(start, end): Gets a random float from the range given.wait(seconds): Pauses the program for the specified number of seconds.scrape(website_url): Scrapes the given website and returns the data in JSON format.jsontodict(json_data): Converts JSON data to a dictionary.dicttojson(dict_data): Converts a dictionary to JSON.overwritefile(filename, data): Writes the data to the specified file and removes previous data.writefile(filename, data): Adds the data to the specified file.createfile(filename): Creates a new file with the specified name.readfile(filename): Reads the specified file and returns the data.More coming soon!
Package: natest
Simple package to run unit test for network automation python3 code.Explanation by examples:INPUT can be either a file or a return str() or list() Usually is the output of a show commandinput = open('../fixtures/ssh_input', 'r')HAVE is the return of you code run on top of INPUThave = open('../fixtures/have', 'r')WANT must be a file where you have your expected outputwant = open('../fixtures/want', 'r')Create an instance of NaTestmy_test = NaTest()print the input. Ideally the input is saved in a variable and use to run your code (instead of run real ssh commands)print(my_test.read(input))print diff between what we HAVE and what we WANTprint(my_test.result(want, have))Result (compared WANT against HAVE after running code using INPUT):['+ This is an extra line\n']
['- This is a missing line\n']
Package: nathanglover
My Contact DetailsFree software: MIT licenseInstallationpip install nathangloverDocumentationhttps://python-nathanglover.readthedocs.io/DevelopmentTo run the all tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog1.1.0 (2019-09-04)First release on PyPI.
Package: nationalarchivescensus
censusnationalarchivesiepythonapiAn API for the census.nationalarchives.ie written in and for Python.Made for the 1911 census.installationDownload the latest wheel, unwheel it and move the censusie in censusie-0.x.datato wherever python keeps your packages. (Also add a .py to the end, so censusiebecomes censusie.py.documentationgetcensusresults(firstname,lastname,county,town)Returns number of results.If you do not know any parameters just replace it with ''.E.G getcensusresults('', 'Muller', '', '') returns the integer 15.getcensus(firstname,lastname,county,town)Returns firstname and lastname.If you do not know any parameters just replace it with ''.E.G getcensus('', 'Muller', '', '', 3) returns the 3rd person with the surname Muller, which happens to be ('Muller', 'Houe').
Package: nationalarchives-frontend-django
The National Archives Frontend Django TemplatesDjango templates implementation ofTNA componentsfor inclusion in Python Django applications.# Create a virtual environmentpython3-mvenvvenv
../venv/bin/activate# Install the dependenciespipinstall-rrequirements.txt
npminstall# Run the serverpythonmanage.pyrunserver8080http://localhost:8080/# Run the tests against the running servernodetasks/test.mjsHow to use in your own Django projectTemplatesInstall thenationalarchives-frontend-djangopackage from PyPifromdistutils.sysconfigimportget_python_libTEMPLATES=[{"DIRS":[os.path.join(get_python_lib(),"nationalarchives-frontend-django/templates")],}]StylesInstall the@nationalarchives/frontendpackage from npm withnpm install @nationalarchives/frontendAdd the config to enable you to use the static files:STATICFILES_DIRS=["node_modules/@nationalarchives/frontend"]Import the stylesheet with:{% load static %}<linkrel="stylesheet"href="{% static 'nationalarchives/all.css' %}">The@nationalarchives/frontendpackage also includes the SCSS if you wish to compile the CSS yourself.
Package: national-id
Egyptian national ID validator and data-extractor APIRequirmentspython3.6 or laterpip3bottleHow to runInstall requirmentspip3 install -r requirements.txtRunpython3 server.pyServer will be running on port 8001Endpoint can be reached athttp://localhost:8001/get_infoEndpoint/get_infoAccepts post requests with "Content-Type: application/json" HeaderExample request:curl-H"Content-Type: application/json"-d'{"id_number": "29009121201812"}'-XPOSThttp://localhost:8001/get_infoResponse200 OK, json_info: national id is validated and info extraction ok400 Bad Request: Wrong national id number500 Internal Server Error: Invalid request from user (invalid json, invalid form of data)Example response:{"nationl_id_data":{"year_of_birth":"1994","month_of_birth":"9","day_of_birth":"15","governorate":"Al Daqhlia","type":"Male"}}Validations and checksAccording tothis sourceThe national ID consists of the following:+-+--+--+--+--+----+-+|2|90|01|01|12|3456|7|+--------------------+|A|B|C|D|E|F|G|+-+--+--+--+--+----+-+A -> The century: A=2 From (1900-1999), A=3 From (2000-2099)B~D (Date of birth):
B -> Year of birth
C -> Month of birth
D -> Day of birthE -> Governorate code ex: {12: "Al Daqhlia"}F -> Unique code. (Odd is male, Even is female)G -> Check digit for verificationHow to run testsLib test:pytest -s tests/test_national_id.pyTest the endpointpython3 -m pytest -s tests/test_endpoint.pyDockerfileYou can build and run the dockerfile indocker directorydocker build -t waleedhammam/national_id .Pip installableLibrary national id is pip installablepip install national-idto be used in the whole systemExample usage:fromlib.national_idimportNationalIDinstance=NationalID("28510291201512")instance.get_info()Out:(True,{'year_of_birth':'1985','month_of_birth':'10','day_of_birth':'29','governorate':'Al Daqhlia','type':'Male'})
Package: nationalmhfilter
nationalmhfilterThe package showcases the statistics for each state in the United States, and mental heanlth care records of different social groups, providing evidence and directions to improve healthcare services.Installation$pipinstall-ihttps://test.pypi.org/simple/nationalmhfilter==0.2.0UsageTo retrieve the overall mental health service situation of a stateget_service_counts_by_state(records_clean,state)To get the counts of people who received a specific service across the nationget_service_counts(records_clean,service_indicator)To get the service overview of people with the specified presence of symptoms of anxiety/depressionndisplay_indicators_for_symptom_presence(records_clean,presence_filter)Specify query parameters in terms of age, sex, gender identity, race, and education to get service recordsget_service_indicators_by_parameters(records_clean,age=None,sex=None,race=None,education=None,gender_identity=None)Refer to parameters.md and example.ipynb to fully use the filters. Users are able to get the general understanding of disparities of current mental health services in the US. The multiple filters allow people who interested in mental healthcare issues flexibly contrast between states, age and gender groups, and education levels. It showcases potential challenges faced by various social subgroups, prompting a need to improve healthcare services.ContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensenationalmhfilterwas created by Fanxi Wang. It is licensed under the terms of the MIT license.Creditsnationalmhfilterwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.