Saravanan666/pypi-org huggingface dataset:
Package: pynanocurrency
pynanocurrencyTHIS PACKAGE HAS BEEN RENAMED TO nanolib. NO FURTHER UPDATES WILL BE MADE TO THIS PYPI PACKAGE.[![image](https://img.shields.io/pypi/v/pynanocurrency.svg)](https://pypi.org/project/pynanocurrency/)
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[![Build Status](https://travis-ci.com/Matoking/pynanocurrency.png?branch=master)](https://travis-ci.com/Matoking/pynanocurrency)
[![image](https://readthedocs.org/projects/pynanocurrency/badge/?version=latest)](https://pynanocurrency.readthedocs.io/en/latest/?badge=latest)A set of tools for handling functions related to the NANO cryptocurrency protocol.FeaturesSolve and verify proof-of-workCreate and deserialize legacy and universal blocksAccount generation from seed using the same algorithm as the original NANO wallet and NanoVaultFunctions for converting between different NANO denominationsHigh performance cryptographic operations using C extensions (signing and verifying blocks, and solving block proof-of-work)
* Proof-of-work solving supports SSE2, SSSE3, SSE4.1 and AVX instruction sets for improved performance. The best supported implementation is selected at runtime with a fallback implementation with universal compatibility.Backed by automated testsCompatible with Python 3.4 and upLicensed under the very permissiveCreative Commons ZerolicenseDocumentationAn online copy of the documentation can be found at [Read the Docs](https://pynanocurrency.readthedocs.io/en/latest/).You can also build the documentation yourself by runningpython setup.py build_sphinx.CommandsThesetup.pyscript comes with a few additional commands besides installation:build_sphinx* Build the documentation inbuild/sphinx/html.test* Run tests using pytestspeed* Run a benchmark testing the performance of various cryptographic operations used in the library.Donationsxrb_33psgb1exxuftgjthbz4tsgzm5qmyzawrfzptpmp3nwzousbypqf6bcmrk69
Package: pynanolab
PyNanoLab is an all-in-one GUI software for data analysis and visualization, expecially for nanopore analysis.You can get tutorials from thePyNanoLab website.InstallitionIn the version 3.X, binary installer (*.exe) is not provided anymore owing to the complex workflow and lost feature and performance.We recommend you use the pip install to obtain all the advanced features.System RequiredFirstly, you should have already installed the python or conda virtual environment in your system.Minicondais recommended. And you should add the conda to your system environment variable.In windows, you also need to install a terminal.git-windowsorwindows-terminalis recommended.1. Create a new python virtual environmentPyNanoLab depend on th PySide6 to create its GUI. And it's not compatible with the other PyQt package. So we highly recommend to install pynanolab to a new python virtual environment.use following command in a terminal:condacreate-npnlpython=3.11.3sourceactivate
condaactivatepnl# activate the pnl environment.condainstallnumpy# optional, install the numpy-MKL to speed up the software.So, you have created a new python virtual environment and activated it.
The name is pnl, and you can change the name to anything you want, and the python  version is specified to 3.11.3.2. Install the pynanolab by pipAfter version 3.x, we provide a pip package, you can directly install as general python packages.If you can't get the package from pip on your system, such as the Apple M1 or other Linux. You can tyr to search and download the wheel file from ourGithub releasefor your special OS.pipinstallpynanolabUse the above command, the pynanolab will be installed automaticly. And a entry fille will be created in theScriptsfolder of the "pnl" virtual environment. In windows is named "pynanolab.exe" and "pynanolab" in Linux and MacOSX.Then, you can directily conduct the following command to open it in a terminal with pnl virtual environment activated.pynanolabIf you want to create a shortcut or a desktop entry. Use the following command:pnl-shortcut3. Upgrade pynanolabIf you use the pip installtion. You can upgrade the packages manually using the following command:pip install --upgrade pynanolabFor binary installation, such as the .exe in windows. If we don't provide a new exe file in thesourceforge. You can manually download the *.whl file for your system from pypi or GitHub. Then, you can unzip the *.whl file use any compressed software (such as 7zip in Windows or unzip in Linux). And you will find the pynanolab folder in the archive. Delete the same "pynanolab" folder in the PATH that you installed the PyNanoLab and replace with the new package in the archive.
Package: pynanopore
Pynanopore: A modular python app for single molecule electrophysiology data.Pynanopore serves as a sophisticated toolkit for analyzing single molecules, designed to interpret complex states within nanopore data automatically. It accomplishes this by constructing a virtual representation of the nanopore mechanism using an electrical circuit analogy. This approach capitalizes on the initial electrical changes that occur when a molecule passes through the nanopore to measure the interactions between the pore and the molecule accurately.Tiny pores on the nanometer scale have shown promising applications in the field of biotechnology, with uses ranging from DNA sequencing to measuring forces at the single-molecule level, and even in identifying molecules by mass on a one-by-one basis. The sophisticated data analysis and modeling techniques provided by Pynanopore are key to significantly enhancing the accuracy of measuring how molecules engage with these nanopores in all these high-tech applications.more info comming soon!!!!this app is still under development!
Package: pynanosvg
pynanosvg|Pynanosvg is a wrapper aroundnanosvga simple svg parsing library. I created pynanosvg because the only other
options in Python were the librsvg bindings, which are very large!InstallSimple:git clone --recursive https://github.com/ethanhs/pynanosvg.git
cd pynanosvg
python3 -m pip install -r requirements.txt
python3 setup.py installor justpython3 -m pip install pynanosvgUsageThe following parses an SVG file, rasterizes it, and saves it as a PNG# import thingsfromsvgimportParser,Rasterizer,SVGfromPILimportImage# for saving rasterized image# Parse from a filesvg=Parser.parse_file('my_cool_img.svg')print('Image is{}by{}.'.format(svg.width,svg.height))rast=Rasterizer()buff=rast.rasterize(svg,svg.width,svg.height)im=Image.frombytes('RGBA',svg.width,svg.height,buff)im.save('my_cool_img.png')# save the converted image!
Package: pynanovnav2-tspspi
Unofficial NanoVNA v2 USB Python library and toolsThis library is work in progressThis is a small library that allows to access the NanoVNA v2 vector network
analyzer using Python. It implements theVectorNetworkAnalyzerbase class ofpylabdevs(since this
is work in progress there is currently an unfinished copy in this repository).Toolsnanovnav2fetchThenanovnav2fetchis a very simple command line utility that
allows one to fetch the S00 and S01 parameters as well as phases
from the NanoVNA v2. Note that this utility always depends onnumpyand requiresmatplotlibto plot or show the traces.$ nanovnav2fetch --help
usage: nanovnav2fetch [-h] [--port PORT] [--debug] [--s00] [--s01] [--phases]
                      [--show] [--plot [PLOT ...]] [--plottitle PLOTTITLE]
                      [--label00 LABEL00] [--label01 LABEL01] [--npz NPZ]
                      [--start START] [--end END] [--step STEP]

NanoVNA v2 USB fetching utility

optional arguments:
  -h, --help            show this help message and exit
  --port PORT           Port to access the NanoVNA v2 (default: /dev/ttyU0)
  --debug               Enable debug mode on the NanoVNA v2
  --s00                 Gather S00 values
  --s01                 Gather S01 values
  --phases              Gather phases for all enabled channels
  --show                Display the rendered graphics (requires matplotlib)
  --plot [PLOT ...]     Supply filename that will be used to plot graphics
                        (required matplotlib)
  --plottitle PLOTTITLE
                        Title for the plot
  --label00 LABEL00     Label for the S00 parameter
  --label01 LABEL01     Label for the S01 parameter
  --npz NPZ             Dump data into supplied NPZ file
  --start START         Start frequency in Hz (default: 50 MHz)
  --end END             End frequency in Hz (default: 4.4 GHz)
  --step STEP           Step size in Hz (default: 1 kHz)
Package: pynapl
pynaplPython Native Automation Package LibraryThe Tastiest Code You May Ever ConsumeOverviewpynaplis the conglomeration of useful tactics that I have made work for my personal and professional automation. The hope is forpynaplto evolve and become something more (someday - Exeggutor!!!).Currently,pynaplwill allow you to send emails. More will come!Detailspynapl.send_mail()This is a script to send out an HTML email.NEVER TESTED ON REAL FRUITNo warranties. No guarantees. But feel free to enjoy as you please.Licensepynaplis registered under the MIT license.That means if you use it, mention me (keep the license in place) and we're cool.
Package: pynaptan
pynaptanA fully typed python library for retrieving UK NaPTAN stops data.Getting startedPynaptan provides a client for querying the NaPTAN data and returning the each
stop as aStopobject.To retrieve stops from NaPTAN,frompynaptanimportNaptanclient=Naptan()istops=client.iget_all_stops()# istops is a generatornext(istops)Stop(atco_code='0100BRP90310',naptan_code='bstgwpa',plate_code='',cleardown_code='',common_name='Temple Meads Stn',common_name_lang='',short_common_name='Temple Meads Stn',short_common_name_lang='',landmark='',landmark_lang='',street='Redcliffe Way',street_lang='',crossing='',crossing_lang='',indicator='T3',indicator_lang='',bearing='SE',nptg_locality_code='N0077020',nptg_locality_name='Temple Meads',parent_locality_name='',grand_parent_locality_name='',town='',town_lang='',suburb='',suburb_lang='',locality_centre=False,grid_type='UKOS',easting=359396,northing=172388,longitude=-2.58569,latitude=51.44901,stop_type='BCT',bus_stop_type='MKD',timing_status='OTH',default_wait_time='',notes='',notes_lang='',administrative_area_code='009',creation_date_time=datetime.datetime(2009,8,25,0,0),modification_date_time=datetime.datetime(2019,9,13,10,41,24),revision_number=92,modification='new',status='active')To retrieve all stops as a list ofStopobjects use the.get_all_stopsmethod,>>frompynaptanimportNaptan>>client=Naptan()>>stops=client.get_all_stops()>>len(stops)436167
Package: pynare
This is a slim Python API to Dynare. It runs the*.modfile, displays the resulting output, and then provides access to the Dynare workspace. It works with both, Matlab and Octave.For fellow linux users (and probably mac users as well), this also provides a script to execute Dynare from comand line.Source:https://github.com/gboehl/pynareDocumentation:https://pynare.readthedocs.io/en/latest/Bug tracker:https://github.com/gboehl/pynare/issuesNOTE:This is at a very early stage and not well-tested (and not tested at all on Windows). Comments via thebug trackerare very welcome.MotivationThe declared goal of this project is to provide access to Dynare without having to learn and use Matlab / Octave. This reflects the acknowledgement that the translation of the Dynare codebase to a more efficient open source alternative is a major effort which may take a while. Meanwhile,pynareencourages young researchers to focus on modern open source languages and, as the whole interface is pure Python, still allows them to use Dynare without Matlab.UsagePackage import and running a modfile:frompynareimportpynaremodfile='/path/to/greatmodel.mod'mod=pynare(modfile)This will give you the usual info about how the Blanchard-Kahn conditions are messed up. Then access the attributes:mod.workspace# will give you the matlab workspaceprint(mod.workspace['beta'])# it contains all the parameters>>>0.995# likely to be the caseI also added theoo_Dynare-object, which contains a lot of usefull stuff. Note that you could have also accessed it viamod.workspace['oo_'].mod.oo_.keys()# it is a dict, so browse it via `keys()`irfs=mod.oo_['irfs']# for instance get your impulse response functions (it's again a dict). Maybe plot them?Just evokingpynarefrom the comand prompt/shell is as simple aspynaremodelpath/crazy.modInstallation viapipInstallation is as simply as running (Windows user from the Anaconda Prompt):pipinstallpynareOf course, installing Dynare remains your responibility.If you care for the bleeding edge developing version (which, at this stage, is recommended), the handy way is to install via thegit-command. If you hav not yet installedgit, Windows users get it here:https://git-scm.com/download/win(Linux users just use the repo of their distro). Then:pipinstallgit+https://github.com/gboehl/pynare
Package: pynarlivs
# pynarlivs![https://badge.fury.io/py/pynarlivs](http://badge.fury.io/py/pynarlivs.png)Ever wanted to interact with ![http://www.narlivs.se](Narlivs) using an API?Yep, there is none. We are here to make your life easier! This library aimsto provide a Pythonic interface for some basic functionalities on Narlivs,i.e. retrieving product information (or, in future, automating the orderprocess).## What do we use pynarlivs for?When receiving a delivery from Narlivs, we get a delivery receipt both on paperand in PDF format. We parse the PDF file programatically in order to automaticallyupdate the in-stock product quantities.## Quickstart guideInstall using pip:```bashpip install pynarlivs```Retrieve product information using its EAN code:```python>>> from narlivs import Narlivs>>> client = Narlivs('username', 'password')>>> product = client.get_product(ean='7310350109265')>>> product<Product sku=100102201 name=BRIO FRUKT  PÅSE >>>> product.data{'ean': '7310350109265','image': '(...)/product/products/images/7310350109265.jpg','name': 'BRIO FRUKT  PÅSE','price': Decimal('3.99'),'sku': '100102201'}```## LicenseMIT License. Please see the LICENSE file.
Package: pynarrator
pynarratorTemplate-based NLG framework for creating text narratives out of dataInstallationYou can install the package from pip:pip3installpynarratorimportosfrompynarratorimportnarrate_descriptive,read_dataBasic Usagepynarrator has a range of functions for creating template-based narratives and also embedded data set that you can use by callingread_data(). Function downloads raw data from github, if you get a SSL error when running it, please run this first:importsslssl._create_default_https_context=ssl._create_unverified_contextsales=read_data()narrative=narrate_descriptive(sales,measure='Sales',dimensions=['Region','Product'],coverage=0.5){'Total Sales': 'Total Sales across all Regions is 38790478.42.',
'Region by Sales': 'Outlying Regions by Sales are NA (18079736.4, 47.0%), EMEA (13555412.7, 35.0%).',
'Product by Sales': 'Outlying Products by Sales are Food & Beverage (15543469.7, 40.0%), Electronics (8608962.8, 22.0%).'}Chat GPTIn order to use ChatGPT in pynarrator, you must specify your OpenAI API token asOPENAI_API_KEYenvironment variable:os.environ['OPENAI_API_KEY']='xx-xxxxxxxxxx'frompynarratorimportgpt_get_completions,enhance_narrative,translate_narrative,summarize_narrativeImprove the narrative text to make it rich with business languageenhance_narrative(narrative)enhance_narrative(narrative,language='Spanish')summarize_narrative(narrative)Complete documentation is available at thenarratorpackage website
Package: pynars
PyNARSDescriptionPython implementation of NARS (Non-Axiomatic-Reasoning-System)Reference:OpenNARS 3.0.4,The Design Report of OpenNARS 3.1.0EnvironmentsPython version: 3.7.10.Only tested under this version, however, Python 3.7 and higher versions maybe acceptable.OS: Windows 10.Only tested under this OS, however, other OSs might be ok.Packages Requirements: seerequirements.txt.It is noted that the version of the python packagetqdmshould be no higher than 3.1.4, otherwise the color display would be abnormal. This is because of a bug oftqdm, which leads to conflicts betweenstyandtqdmand cause unexpected color display ofsty. However, this constraints is not necessary, i.e., higher version oftqdmis ok if you don't mind abnormal display occuring. The abnormal case only occurs if you first run PyNARS when SparseLUT (Sparse Look-Up Table) is built.Installationpip install pynarsInstructionsCopy the filepynars/config.jsonto your workspace-directory.(Optional)In the workspace-directory, run cmdpython -m pynars.Console. To execute an*.nalfile, run cmdpython -m pynars.Console <your-file-name.nal>Input Narsese in the console, input an positive integer to run a number of cycles, or input a comment which is a string with'as the beginning, e.g.' your comment.Pressctrl+Cto exit.ContributionFork the repositoryCreate Feat_xxx branchCommit your codeCreate Pull RequestNote:This document will be imporved in the future.
Package: pyNASA
Meteorite
LandingsNear-Earth Comets - Orbital
ElementsGlobal Landslide Catalog
ExportNASA
FacilitiesFireball And Bolide
ReportsWISE NEA/COMET DISCOVERY
STATISTICSOutgassing
DbOpen Source And General Resource
SoftwareNASA
PatentsExtra-vehicular Activity (EVA) - US and
RussiaCandida albicans response to spaceflight (NASA STS-115) —
GSM1231690_Slide_43SxSW 2016
LeadsA E- GEOD-50881 Gene Chip Assay — Candida albicans response to
spaceflight (NASA
STS-115)BeXRB Monitor
DataS E- GEOD-50881 Study Samples — Candida albicans response to
spaceflight (NASA
STS-115)
Package: pynasafirms
pyNASAFIRMSСлава Україні:ukraine:/Slava Ukraini :ukraine:!Fuck :russia:pyNASAFIRMS is a wrapper for NASA's FIRMS API. Covers all the endpoints that FIRMS supports as of 08/22/2022.RequirementsThis requires Python >= 3.7. In reality it likely works on more but this is what it was developed with.Packages required:requestsQuick StartFirst off, you NEED to get a 'map key' from NASA to query the API:Get it here.At the bottom of the page, theres a 'Map Key' section. Click the 'Get MAP_KEY' button.Once you have a map key, you can set an environment variableFIRMS_MAP_KEYto equal the map key provided by NASA. Otherwise, you can pass a map key to theNasaFirmsobject via theNasaFirms.map_keyattribute.importpynasafirmsclient=pynasafirms.NasaFirms(map_key='xxxxxxxxxx')resp=client.get_country_modis_nrt('UKR')print(resp[0].longitude)....29.24976The above code queries the FIRMS 'country' endpoint with the country code 'UKR' (Ukraine) and theMODIS_NRTsensor. It also has a default parameter for the 'start_date' to be queried. If a date isn't specified, the current local date is used in YYYY-MM-DD and passed to the endpoint. The 'days' defaults 1 unless specified. The FIRMS endpoints only allow for up to 10 days, but this isn't enforced in the wrapper(yet). After the query returns, a list of 'Country' objects are returned.Info on the NASA FIRMS apihere.
Package: pynasapower
pynasapowerDownload meteorological data from NASA POWER restful API (https://power.larc.nasa.gov/) using pynasapower API client.The NASA POWER database is a global database of daily meteorological data designed for agrometeorological applications and more.
Data are retrieced from in-situ observations in combination with satellite data. For more information on the NASA POWER database see the documentation at:https://power.larc.nasa.gov/.Installation from sourcegitclonehttps://github.com/alekfal/pynasapower.gitcdpynasapower/
pipinstall.Installation from PyPIpipinstallpynasapowerNASA POWER API client argumentsgeometry: Single point or polygon geometry asgeopandas.GeoDataFrame. User can use methods pynasapower.geometry.point() or
pynasapower.geometry.bbox() to create an input geometry for this client.start: Start date asdatetime.dateformat. In the examples the value isdatetime.date(2022, 1, 1).end: End date asdatetime.dateformat. In the examples the value
isdatetime.date(2022, 2, 1).path: Local path to store the downloaded data. In the examples"./"is used.to_file: Boolean argument to save data locally. By default isTrue.community: The default POWERcommunityis agroclimatology ("ag"). Other available communities are sustainable buildings ("sb") and renewable energy ("re"). Find more about the POWER communitieshere.parameters: The default parameters for downloading (["TOA_SW_DWN", "ALLSKY_SFC_SW_DWN", "T2M", "T2M_MIN", "T2M_MAX", "T2MDEW", "WS2M", "PRECTOTCORR"]) are selected for downloading if an empty list ([]) is provided by the user. Find more for the POWER parameters inhere.temporal_api: Temporal resolution of the data. The default value is"daily". Other selections are"hourly","monthly","climatology". Read more about the temporal resolution of the datahere.spatial_api: Spatial resolution of the data. By default"point"is selected, but a user can also use"regional". Note that in order to download a region a polygon geometry must be used in thegeometryargument.format: Output format of the data. The default is"csv". Other selections supported by the API client are:"netcdf","json"and"ascii".QuickstartDownload meteorological data for a point in Athens, Greece and save result in*.csvformat.frompynasapower.get_dataimportquery_powerfrompynasapower.geometryimportpoint,bboximportdatetime# Run for point in Athens and save the result in csv formatgpoint=point(23.727539,37.983810,"EPSG:4326")start=datetime.date(2022,1,1)end=datetime.date(2022,2,1)data=query_power(geometry=gpoint,start=start,end=end,path="./data",to_file=True,community="ag",parameters=[],temporal_api="daily",spatial_api="point",format="csv")Download meteorological data for a polygon in Athens, Greece and save result in*.csvformat.# Run for small bbox in Athens and save the result in csv formatgbbox=bbox(23.727539,26.73,37.983810,40.99,"EPSG:4326")start=datetime.date(2022,1,1)end=datetime.date(2022,2,1)data=query_power(geometry=gbbox,start=start,end=end,path="./data",to_file=True,community="ag",parameters=[],temporal_api="daily",spatial_api="point",format="csv")Read more about the software in project'sreadthedocs.
Package: pynast
The official PyNAST source code repository. For documentation on installing and using PyNAST, seehttp://qiime.org/pynast. This documentation will refer to the latest release version of PyNAST. If you’re working with a development version of PyNAST, you should refer to the documentation in PyNAST/doc/.See the [QIIME GitHub organization](https://github.com/qiime) for related software projects and data.Stay up-to-date on PyNAST newsSubscribing to the [QIIME blog](http://qiime.wordpress.com) is the best way to keep up-to-date on news related to PyNAST. You can subscribe via RSS or e-mail on the front page of the blog. This is a very low traffic list, with currently around one e-mail per month or less.The QIIME blog is the primary means by which we will communicate information on bugs, new releases, and news to our users, so we highly recommend subscribing. We won’t share subscriber information with anyone ever.Citing PyNASTIf you make use of [PyNAST](http://qiime.org/pynast) in published work, please cite:PyNAST: a flexible tool for aligning sequences to a template alignment.
J. Gregory Caporaso, Kyle Bittinger, Frederic D. Bushman, Todd Z. DeSantis, Gary L. Andersen, and Rob Knight.
January 15, 2010, DOI 10.1093/bioinformatics/btp636. Bioinformatics 26: 266-267.Need help?Requests for help with PyNAST should be directed to the [QIIME Forum](http://forum.qiime.org).