Saravanan666/pypi-org huggingface dataset:
Package: ncall
ncallDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nsynset--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallsynsetnbdev# activate conda environment$condaactivatesynset# make sure the synset package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the synset package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/synset.gitor fromconda$condainstall-cdsm-72synsetor frompypi$pipinstallsynsetDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.NOOP=ncall('noop',noop,*IDENTITY_SYNONYMS,fullrepr=True)NOOPnoop(x: Any, *args, **kwargs) -> AnyNOOP=='identity'TrueNOOP('Hello')'Hello'
Package: ncap-vaip-api
Use the vAIP API to help build up entities based on the vAIP ontologies.There are a few example files demonstrating use:pattern_example.py: creates an IdentityStoragePattern and deploys it to an S3 bucketprocess_example.py: creates all StorageTemplates and TaskTemplates for a single ProcessTemplate, and deploys the ProcessTemplate to Neptunepremade_patterns.py: a collection of functions that build the Patterns used for most of the ProcessTemplates defined inapi/vaip/process_templates.Cloud9 SQLite Version UpgradeOwlReady2 currently requires at least sqlite3.41, Cloud9 starts with 3.7.x.
Below are the steps to upgrade to a compatiable version.## Download
curl https://www.sqlite.org/2023/sqlite-autoconf-3420000.tar.gz | tar xzf - 

##Move into the folder
cd sqlite-autoconf-3420000/ && ./configure

make

sudo make install

## list your sqlite locations
whereis sqlite3

## Move out of the install folder
cd ..

#sqlite version paths
sudo cp sqlite-autoconf-3420000/sqlite3 /usr/local/bin/sqlite3
sudo cp sqlite-autoconf-3420000/sqlite3 /opt/c9/bin/sqlite3
sudo cp sqlite-autoconf-3420000/sqlite3.h /usr/include/sqlite3.h

## Define the path to new version
export LD_LIBRARY_PATH="/usr/local/lib"

## Cleanup 
rm -r sqlite-autoconf-3420000To validate the version of sqlite3 your Python environment is using, run this Python code:import sqlite3
print(sqlite3.sqlite_version)
print(sqlite3.__file__)or in a single line:python -c "import sqlite3; print(sqlite3.sqlite_version); print(sqlite3.__file__)"To trigger a process e.g. dscovr_magpython trigger_process.pyhttps://ncei.noaa.gov/vaip/template/process/d54a223c-6f6b-4f51-b0f2-8f2ab0ceccab/d54a223c-6f6b-4f51-b0f2-8f2ab0ceccabnccf-dev-ingest-trust-us-east-1-560271376700 SWPC/DSCOVR/MAG/mg0/2023/05/ neufieTo trigger a process e.g. ccor1python trigger_process.pyhttps://ncei.noaa.gov/vaip/template/process/9bbf9afb-cb40-46e3-a9e1-c43b4addac04/9bbf9afb-cb40-46e3-a9e1-c43b4addac04nccf-dev-ingest-trust-us-east-1-560271376700 SWPC/GOES-U/CCOR-1/ccor1-l0b/2023/09/05/ neufie
Package: ncarglow
GLOWThe GLobal airglOW Model, independently and easily accessed fromFortran 2003compiler.
Optionally available from scripting languages including:Python ≥ 3.6MatlabGNU Octave ≥ 4.2IDL / GDLWe describe each language below; pick the one(s) that apply for you.
Python is the easiest and recommennded choice.
A Fortran compiler is required in any case.PythonInstall/compile by:gitclonehttps://github.com/space-physics/ncar-glow

pipinstall-encar-glowConfirm the install with:pytestncar-glowThen use examples such as:Simple.py:  Maxwellian precipiation, specify Q and E0.Monoenergetic.py: Specify unit flux for one energy bin, all other energy bins are zero flux.or use GLOW in your own Python program by:importncarglowasglowiono=glow.simple(time,glat,glon,Q,Echar,Nbins)ionois anxarray.Datasetcontaining outputs from GLOW, including:number densities of neutrals, ions and electronsPedersen and Hall currentsvolume emssion rate vs. wavelength and altitudeprecipitating flux vs. energymany more, request if you want it.FortranYou can call this repo from a Meson wrap or CMake Fetch.
To build Fortran code by itself, do either:mesonbuild

mesontest-Cbuildorcmake-Bbuild

cmake--buildbuildMPI / NetCDFThe parallel version of GLOW requires MPI and NetCDF for TIEGCM I/O.mpirun-np2./mpi_glow.bin<~/data/in.namelist.tgcmNote, for an unknown reason,in.namelist.msisonly works with -O0 or -O1 with gfortran 7. We didn't look into why.
Otherwise, -O3 works fine.Matlab / GNU OctaveThe Matlab interface is in thematlabdirectory, and passes data to / from Glow over stdin / stdout pipes.First, compile the Fortran code by runningsetup.mThen,Use built-in energy and altitude bins:Simple.muser input energy grid:Monoenergetic.mNOTE: if using GNU Octave, version ≥ 4.2 is required for propertextscan() functionalityIDL / GDLWe have a small script for IDL / GDL thanks to Guy Grubbs.
Let us know if you want this, we haven't taken the time to upload it yet.
Package: ncar-isd-s3
isd-s3NCAR ISD S3 Object Storage utility.A command line tool to manage data access to the NCAR S3 Object Storage
system.  Developed by the Information Systems Division (ISD), a division
within the Computational and Information Systems Laboratory (CISL) at the
National Center for Atmospheric Research (NCAR).Source Code:https://github.com/NCAR/isd-s3InstallationInstall withpip install ncar-isd-s3You can then import the moduleisd_s3.  For example:from isd_s3 import isd_s3
session = isd_s3.Session()
session.list_buckets()
Package: ncas-amof-netcdf-template
ncas-amof-netcdf-templateMakes 'just-add-data' AMOF-compliant netCDF4 file for either a given NCAS instrument or one of the defined data products.A full description on how to install and use this module can be foundthrough the documentation.RequirementsPython 3.8 or abovePython modules:netCDF4NumPyRequestspandasInstallationReleases ofncas-amof-netcdf-templatecan be installed using conda,conda install -c conda-forge ncas-amof-netcdf-templateor by using pip,pip install ncas-amof-netcdf-templateor releases can bedownloaded from GitHuband installed usingpip install .UsageA fuller description of how to use this module can be found in thedocumentation.importncas_amof_netcdf_templateasnantnant.create_netcdf.main(instrument,date=None,dimension_lengths={},loc='land',products=None)where:instrument- name of NCAS instrument, e.g. "ncas-ceilometer-3"date- date for data, YYYYmmdd format, default to today's date. Optional.dimension_lengths- dictionary of lengths of dimensions, e.g. {'time':96, 'altitude':45}. If length for required dimensions are not given, then python will ask for user input, default empty. Optional.loc- one of 'land', 'air', 'sea', or 'trajectory', default is 'land'. Optional.products- applicable products of desired NCAS instrument to make netCDF for. Setting products asNone(default) makes netCDF file for all available products. Optional.verbose- additional level of information and warnings to print. Only 1 additional layer of warnings are currently available.All products associated with an instrument can be printed byimportncas_amof_netcdf_templateasnantnant.create_netcdf.list_products(instrument)whereinstrumentis replaced with the name of the NCAS instrument.ContributingContributions are welcome from everyone, provided they enhance and improve the capabilities of this package, and code can be distributed under the conditions of thelicence. When contributing, users should create a new branch under their forked repository.Note thatpre-commit-ciwill run on all pull requests to this repository, however autofix is disabled. It is recommended that users ensure their contributions pass these checks before submitting pull requests, however users can typepre-commit.ci autofixinto a comment after a failed pre-commit-ci run to automatically fix issues. Seepre-commitfor more details.LicenceThis package is available under theMIT licence.
Package: ncat-api
ncat-pythonA python wrapper for the NGS’s Coordinate Conversion and Transformation Tool (NCAT) API. More information about the API is availablehere.FeaturesCan make calls to all 5 NCAT services (LLH, SPC, UTM, XYZ, and USNG)Ensures required parameters for different NCAT services are present before making api call.InstallationUsing pip:pip install ncat-apiUsageTo use the package:importNCATfromncatapiMaking RequestsLLH RequestPerform an LLH Service request.fromncatapiimportNCATncat=NCAT()response=ncat.llh({'lat':40.0,'lon':-80.0,'orthoHt':99.0,'inDatum':'nad83(1986)','outDatum':'nad83(2011)','inVertDatum':'NGVD29','outVertDatum':'NAVD88'})Sample Response:{
    'ID': '1664818932872', 
    'nadconVersion': '5.0',
     'vertconVersion': '3.0', 
     'srcDatum': 'NAD83(1986)', 
     'destDatum': 'NAD83(2011)', 
     'srcVertDatum': 'NGVD29', 
     'destVertDatum': 'NAVD88', 
     'srcLat': '40.0000000000', 
     'srcLatDms': 'N400000.00000', 
     'destLat': '39.9999983008',
     'destLatDms': 'N395959.99388',
     'deltaLat': '-0.189',
     'sigLat': '0.000263',
     'sigLat_m': '0.0081',
     'srcLon': '-80.0000000000',
     'srcLonDms': 'W0800000.00000',
     'destLon': '-79.9999976143',
     'destLonDms': 'W0795959.99141',
     'deltaLon': '0.204',
     'sigLon': '0.000221',
     'sigLon_m': '0.0052',
     'heightUnits': 'm',
     'srcEht': 'N/A',
     'destEht': 'N/A',
     'sigEht': 'N/A',
     'srcOrthoht': '99.000',
     'destOrthoht': '98.848',
     'sigOrthoht': '0.005',
     'spcZone': 'PA S-3702',
     'spcNorthing_m': '76,470.391',
     'spcEasting_m': '407,886.681',
     'spcNorthing_usft': '250,886.607',
     'spcEasting_usft': '1,338,208.220',
     'spcNorthing_ift': '250,887.109',
     'spcEasting_ift': '1,338,210.896',
     'spcConvergence': '-01 27 35.22',
     'spcScaleFactor': '0.99999024',
     'spcCombinedFactor': 'N/A',
     'utmZone': 'UTM Zone 17',
     'utmNorthing': '4,428,235.878',
     'utmEasting': '585,360.668',
     'utmConvergence': '00 38 34.18',
     'utmScaleFactor': '0.99968970',
     'utmCombinedFactor': 'N/A',
     'x': 'N/A',
     'y': 'N/A',
     'z': 'N/A',
     'usng': '17SNE8536128236'
 }SPC RequestPerform an SPC Service request.fromncatapiimportNCATncat=NCAT()response=ncat.spc({'northing':173099.419,'easting':503626.812,'spcZone':2402,'inDatum':'nad83(2011)','outDatum':'nad83(NSRS2007)'})USNG RequestPerform an USNG Service request.fromncatapiimportNCATncat=NCAT()response=ncat.usng({'usng':'15SWB4788338641','inDatum':'nad83(2011)','outDatum':'nad83(NSRS2007)'})UTM RequestPerform an UTM Service request.fromncatapiimportNCATncat=NCAT()response=ncat.utm({'northing':4138641.144,'easting':547883.655,'utmZone':15,'spcZone':2401,'inDatum':'NAD83(2011)','outDatum':'NAD83(NSRS2007)'})XYZ RequestPerform an XYZ Service request.fromncatapiimportNCATncat=NCAT()response=ncat.xyz({'x':-217687.279,'y':-5069012.406,'z':3852223.048,'inDatum':'NAD83(2011)','outDatum':'NAD83(NSRS2007)'})
Package: ncbi
TheNCBI C++ Toolkitprovides a wide variety of functionality for analysis, retrieval, and
manipulation of DNA and protein sequences and related data, along with much
general-purpose functionality.  This includes (de)serialization and manipulation
of instances of NCBI data model types (usually defined by ASN.1 specifications).The C++ Toolkit is the result of the efforts of many people at the National
Center for Biotechnology Information over several years.  This module makes most
of its functionality available from Python.
Package: ncbi-acc-download
NCBI accession download scriptA partner script to the popularncbi-genome-downloadscript,ncbi-acc-downloadallows you to download sequences from GenBank/RefSeq by accession through
the NCBIENTREZ API.Installationpip install ncbi-acc-downloadAlternatively, clone this repository from GitHub, then run (in a python virtual environment)pip install .If this fails on older versions of Python, try updating yourpiptool first:pip install --upgrade pipand then rerun thencbi-acc-downloadinstall.ncbi-acc-downloadis only developed and tested on Python releases still under active
support by the Python project. At the moment, this means versions 3.6, 3.7, 3.8, and 3.9.
Specifically, no attempt at testing under Python versions older than 3.6 is being made.ncbi-acc-download0.2.6 was the last version to support Python 2.7.If your system is stuck on an older version of Python, consider using a tool likeHomebreworLinuxbrewto obtain a more up-to-date
version.UsageTo download a nucleotide record AB_12345 in GenBank format, runncbi-acc-download AB_12345To download a nucleotide record AB_12345 in FASTA format, runncbi-acc-download --format fasta AB_12345To download a protein record WP_12345 in FASTA format, runncbi-acc-download --molecule protein WP_12345To just generate a list of download URLs to run the actual download elsewhere, runncbi-acc-download --url AB_12345If you want to concatenate multiple sequences into a single file, runncbi-acc-download --out two_genomes.gbk AB_12345 AB_23456You can use this with/dev/stdoutas the filename to print the downloaded data to
standard output instead of writing to a file if you want to chainncbi-acc-downloadwith other
command line tools, like so:ncbi-genome-download --out /dev/stdout --format fasta AB_12345 AB_23456 | gzip > two_genomes.fa.gzIf you want to download all records covered by a WGS master record instead of the master record itself,
runncbi-acc-download --recursive NZ_EXMP01000000You can supply a genomic range to the accession download using--rangencbi-acc-download NC_007194 --range 1001:9000As cutting a record up with a range operator like that can leave partial features at both ends of the
record, you can combine the range download with the newcorrectextended validator to remove the
partial features.ncbi-acc-download NC_007194 --range 1001:9000 --extended-validation correctYou can get more detailed information on the download progress by using the--verboseor-vflag.To get an overview of all options, runncbi-acc-download --helpLicenseAll code is available under the Apache License version 2, see theLICENSEfile for details.
Package: ncbidare
NCBI DAtaREtrivalRetrives your NCBI search results and through Entrez in a user friendly way.InstallationRun the following to install:pipinstallncbigetUsage# retrives results from NCBI and writes it to a csv file (Accession ID and Definition)# query: search details         count: number of items      filename: output file namefromncbigetimportget_genbankget_genbank(query="Klebsiella pneumoniae",count=1,filename="results.csv")# default#to get list of unique strains from the csv file#MAKE SURE THE FORMAT OF THE CSV FILE IS SIMILAR TO THE RESULT FILE FROM get_genbank() i.e. Descriptions should be in column 3# filename: input file namefromncbigetimportget_strainsget_strains(filename="results.csv")# default#to get fasta file of each strain#MAKE SURE THE FORMAT OF THE CSV FILE IS SIMILAR TO THE RESULT FILE FROM get_genbank() i.e. Descriptions should be in column 3# filename: input file namefromncbigetimportget_fastaget_fasta(filename="results.csv")# defaultDeveloping ncbidareTo install ncbidare along with the tools you need to develop and run tests, run the following in your virtualenv:pipinstall-e.[dev]
Package: ncbi-db
ncbi_dbCollection of commands to query or process NCBI dataInstallationconda install -c mmariotti -c conda-forge -c etetoolkit ncbi_dbToolsThese command line tools are available:ncbi_assemblysearch and download assemblies/genomes for any species/lineage, or its annotation/proteomencbi_sequencessearch and download nucleotide/protein sequences or their metadatancbi_pubmedsearch and format ncbi pubmed entriesncbi_taxonomysearch ncbi taxonomy for species or lineagesncbi_taxonomy_treeobtain a tree from ncbi taxonomy for a set of input speciesncbi_searchgeneric search tool for any ncbi DBparse_genbankparse a genbank flat file; requires installation of GBParsyRun any tool with option -h to display its usage.Most tools require internet, as they connect online to ncbi.Using ncbi_db as moduleTo use these functionalities from another python module, import them from ncbi_db and
run their "main" function providing the same arguments as you would on the command line,
but in form of dictionary. Use option 'silent' to avoid printing results on screen. For example:from ncbi_db import ncbi_sequences
arguments={'m':'P', 'f':1, 'I':'AAB88790', 'silent':1}
results=ncbi_sequences.main(arguments)
print(results){'AAB88790':
 ['AAB88790.1 gi|2411487|gb|AAB88790.1| selenophosphate synthetase [Drosophila melanogaster]',
 'MSYAADVLNSAHLELHGGGDAELRRPFDPTAHDLDASFRLTRFADLKGRGCKVPQDVLSKLVSALQQDYSAQDQEPQFLNVAIPRIGIGLDCSVIPLRHGGLCLVQTTDFFYPIVDDPYMMGKIACANVLSDLYAMGVTDCDNMLMLLAVSTKMTEKERDVVIPLIMRGFKDSALEAGTTVTGGQSVVNPWCTIGGVASTICQPNEYIVPDNAVVGDVLVLTKPLGTQVAVNAHQWIDQPERWNRIKLVVSEKNVRKAYHRAMNSMARLNRVAARLMHKYNAHGATDITGFGLLGHAQTLAAHQKKDVSFVIHNLPVIAKMAAVAKACGNMFQLLQGHSAETSGGLLICLPREQAAAYCKDIEKQEGYQAWIIGIVEKGNKTARIIDKPRVIEVPAKD']}DevelopersMarco Mariottihttps://github.com/marco-mariottiDidac Santesmasseshttps://github.com/didacs
Package: ncbimetadata
ncbimetadatancbimetadata is a package for fast fetching and parsing metadata from ncbi database, and converting to csv format.requirementsPython3InstallationpipinstallncbimetadataUsagemetadata-t8-id565# -t number of threads# -id taxon IDLicenseMITLicenseCopyright (c) 2023 Ryan AlloriadonisPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: ncbitaxonomy
ncbitaxThis library is a cut down version of ETE3 containing only code that
is required to run the ncbi_taxnomy module for the epi2melabs project.
For full information about ETE3 please seehttp://etetoolkit.orgfor more info.The Environment for Tree Exploration (ETE) is a Python programming
toolkit that assists in the recontruction, manipulation, analysis and
visualization of phylogenetic trees (although clustering trees or any
other tree-like data structure are also supported).ETE is currently developed as a tool for researchers working in
phylogenetics and genomics. If you use ETE for a published work,
please cite:::Jaime Huerta-Cepas, François Serra and Peer Bork. "ETE 3: Reconstruction,
analysis and visualization of phylogenomic data."  Mol Biol Evol (2016) doi:
10.1093/molbev/msw046Visithttp://etetoolkit.orgfor more info.
Package: ncBuilder
ncBuildernetCDF4 tool to help creating new files from scratch, and loading variables from existing ones.examplefrom ncBuilder import (
    ncBuilder,
    ncHelper,
)
import datetime as dt
import numpy as np
import pandas as pd

dtNow = dt.datetime.now()
times = pd.date_range('2021-01-01', periods=10).to_pydatetime()
lat = np.arange(-30., 10. + 0.05, 0.05)
lon = np.arange(-60., -30 + 0.05, 0.05)
temp = np.random.rand(times.size, lat.size, lon.size)

nc_file = ncBuilder.initialize_nc(dtNow, '/path/to/file', '_suffix.nc')
# or
nc_file = nc.Dataset('your_nc_file.nc', 'w')
# nc_file = ncBuilder.initialize_nc('file_name_here', '/path/to/file', '_suffix.nc')

# creating dimensions
ncBuilder.create_nc(nc_file,
                    lat,
                    lon,
                    time=times)
# or create variables while creating dimensions
ncBuilder.create_nc(nc_file,
                    lat,
                    lon,
                    time=times, 
                    vars={'temp': {'dims': ('time', 'latitude', 'longitude'),
                                   'units': 'ºC',
                                   'standard_name': 'temperature in ºC',
                                   },
                          })

# creating a single variable
ncBuilder.create_nc_variable(nc_file,
                             'temp',
                             comp_lvl=6,
                             dims=('time',
                                   'latitude',
                                   'longitude'),
                             dtype=np.float64,
                             units='°C',
                             standard_name='temperature in °C')

# updating a variable
ncBuilder.update_nc(nc_file, 'temp', temp)

# updating partially a variable
ncBuilder.update_nc(nc_file, 'temp', temp[:, 5:, :-5], dims=(slice(None), 
                                                             slice(5, None),
                                                             slice(None, -5)))

# loading time
times = ncHelper.load_time(nc_file.variables['time'])

# getting lats and lons
lats, lons = ncHelper.get_lats_lons(nc_file)

# getting nearest point
idx, jdx = ncHelper.get_idx_pos(lat0, lon0, lats, lons)

# closing the nc_file
nc_file.close()version 0.0.7aPackages are now installed with the lib, they were not configured properly.version 0.0.7Added create_nc_dimension, so new custom dimensions can be easily added.Minor modifications to the inner creation of dimensions to accomodate the new function.version 0.0.6Added zlib, fill_value and variable_kw when creating a new variable, so it's more customizableChanged the way dimension variables are created for more consistency of the processversion 0.0.5Added ncHelper, which contains load_time, get_lats_lons and get_idx_posversion 0.0.3Modified function names to use snake_style patternComments added to the main functionsExample updated to follow the new patterns
Package: ncc-cli
ncc_cliNextCloud / ownCloud Command-Line ClientOverviewJust a basic command-line client for NextCloud and ownCloud based servers. This is my project with Python so if you notice any bugs or would like to provide help, please let me know!Installationpip:ncc_cli has been added to pip, so you can simply execute the following:pip install ncc-climanual:Alternatively, you can install the utility manually, but first you will need to install the following dependancies:humanize
tzdm
yaspin
texttable
pyocclientNow you have all of the dependancies installed, you can simply clone the ncc_cli git repo and execute the following:./setup.pyUsageSyntax: ncc [command]ls (-l) <dir> - lists dir contents
put - [local file] <dest remote dir> - uploads file
putdir - [local dir] <dest remote dir> - uploads dir
get - [remote file] <dest local dir> - downloads file
getdir - [remote dir] <dest local dir> - downloads dir as zip
mkdir - [dir name] - creates new dir
rm - [dir/file name] - deletes files or dirs
mkshare - [dir/file name] - creates new share w/link
lsshare - [dir name] - lists shares in dir
rmshare - [dir/file name] - deletes share
cp - [source] [destination] - copies files on server
mv - [source] [destination] - moves files on serverTo DoFind a way of tracking upload progress and counting with tqdm instead of using indefinite spinner.LibrariesThis utility uses the pyocclient library and a couple of other libraries for visual indications, human readable numbers, progress bars etc. Much thanks to all of the developers of their respective libraries.pyocclient -https://github.com/owncloud/pyocclienthumanize -https://github.com/jmoiron/humanizetqdm -https://github.com/tqdm/tqdmyaspin -https://github.com/pavdmyt/yaspintexttable -https://github.com/foutaise/texttableLicenseThis utility is licensed under the GNU GPLv3https://www.gnu.org/licenses/gpl-3.0.en.html