Saravanan666/pypi-org huggingface dataset:
Package: parent
Parent is a simple wrapper that allows you to run a program with limited resources and access.Available optionsResource limitsThe resources available for the program can be limited using these options. The limits are enforced using the Linux
kernel's rlimit.OptionDescription-m / --memory NThe program's maximum memory address space in kilobytes.-t / --cpu-time NThe program's maximum CPU time in milliseconds.-r / --real-time NThe program's maximum real-time execution time in milliseconds.--stack NThe program's stack size limit in kilobytes. (-1 for unlimited)-f / --file-size NThe program's maximum file size in kilobytes that it can create or modify.-p / --processes NThe number of threads, or processes, the program can use.I/OProgram's stdin, stdout, and stderr will by default be redirected to parent's. You can change this behaviour using these
options.OptionDescription--stdin FILERedirect a file to the program's stdin.--stdout FILERedirect the program's stdout to a file.--stderr FILERedirect the program's stdout to a file.--stderr-to-stdoutRedirect the program's stderr to stdout.File accessThe program can access any file on the system by default. You can use these settings to restrict its access. Make sure
you at least allow access to the program itself, since if you enable any of these options, the default behavior will be
to prevent access to any files. File access is limited using Linux kernel's landlock. These options can be used multiple
times to allow access to multiple paths.OptionDescription--fs-readonly PATHAllow the program read from files located under the provided path.--fs-readwrite PATHAllow the program write to files located under the provided path.EnvironmentThe program inherits environment variables by default. It is possible to disable default inheritance and pass additional
environment variables.OptionDescription--env NAME VALUESet an environment variable.--empty-envDo not inherit environment.Miscelaneous optionsOptionDescription--drop-capsDrop the program's capabilities.-s / --stats FILESave execution statistics to a file.
Package: parent-aware
Parent AwareA decorator to make objects aware of their parent objects. Particularly useful with dataclasses!Exampleimport dataclasses
from parent_aware import parent_aware

@parent_aware
@dataclasses.dataclass
class Child:
    num: int

@parent_aware
@dataclasses.dataclass
class Parent:
    child: Child

c = Child(2)
p = Parent(child=c)

# Automatically a .parents was added on the child!
assert c.parents == [p]

# If you didn't want .parents, use @parent_aware(parents_name='give_a_name_here')Installationpip install parent_aware
Package: parentheses
Light parentheses parser in Python.Types (Aliases)ParenthesesSymbol=strParseFlag=intConstantsPARENTHESES_ALL:ParseFlag=1PARENTHESES_OPEN:ParseFlag=2PARENTHESES_CLOSE:ParseFlag=3PARENTHESES_ROUND_OPEN:ParenthesesSymbol='('PARENTHESES_ROUND_CLOSE:ParenthesesSymbol=')'PARENTHESES_SQUARE_OPEN:ParenthesesSymbol='['PARENTHESES_SQUARE_CLOSE:ParenthesesSymbol=']'PARENTHESES_CURLY_OPEN:ParenthesesSymbol='{'PARENTHESES_CURLY_CLOSE:ParenthesesSymbol='}'PARENTHESES_DOUBLE_QUOTE:ParenthesesSymbol='"'PARENTHESES_SINGLE_QUOTE:ParenthesesSymbol='\''PARENTHESES_OPEN_SYMBOLS:list[ParenthesesSymbol]=[PARENTHESES_ROUND_OPEN,PARENTHESES_SQUARE_OPEN,PARENTHESES_CURLY_OPEN]PARENTHESES_CLOSE_SYMBOLS:list[ParenthesesSymbol]=[PARENTHESES_ROUND_CLOSE,PARENTHESES_SQUARE_CLOSE,PARENTHESES_CURLY_CLOSE]PARENTHESES_SYMBOLS=PARENTHESES_OPEN_SYMBOLS+PARENTHESES_CLOSE_SYMBOLSPARENTHESES_REGEX=r'\(.*?\)|\[.*?\]|\{.*?\}'PPStringclassPPStringis a class that represents a parsed parentheses string.valid_proc()->boolGet is parentheses in string valid. (Slower but gives more accurate result).Examples:parse('(x)').valid_proc()=>Trueparse('(x').valid_proc()=>Falsevalid()->boolGet is parentheses in string valid. (Faster but gives less accurate result).Examples:parse('(x)').valid()=>Trueparse('(x').valid()=>Falsevalid_quotes(_escaping: bool=False)->boolGet is quoted parentheses valid.Examples:parse('"x"').valid_quotes()=>Trueparse('"x\""').valid_quotes(True)=>Trueparse('"x').valid_quotes()=>Falseparse('"x\""').valid_quotes()=>Falsecount(flag: ParseFlag=PARENTHESES_ALL)->intCount braces in string.Examples:parse('(x)').count()=>2parse('(x)').count(PARENTHESES_OPEN)=>1parse('(x)').count(PARENTHESES_CLOSE)=>1autoclose()->strAutoclose brackets.Examples:parse('{[(x').autoclose()=>{[(x)]}find(remove_braces: bool=False)->listGet content in braces.Examples:parse('(x)[y]{z}').find()=>['(x)','[y]','{z}']parse('(x)[y]{z}').find(True)=>['x', 'y', 'z']remove_braces()->strRemove braces in string.Examples:parse('(x)[y]{z}').remove_braces()=>'x y z'remove(keep_braces: bool=False)->strRemove everything in parentheses.Examples:parse('(x)[y]{z}').remove()=>'   'parse('(x)[y]{z}').remove(True)=>'() [] {}'as_str()->strGet string.Examples:parse('x').as_str()=>'x'Global functionsparse(string: str)->PPStringParse string.Examples:parse('(x)')=>PPString('x')new_parentheses_symbols(open_symbol: ParenthesesSymbol, close_symbol: ParenthesesSymbol)->NoneAdd new parentheses symbols.Examples:new_parentheses_symbols('<','>')=>Noneremove_parentheses_symbols(open_symbol: ParenthesesSymbol, close_symbol: ParenthesesSymbol)->NoneRemove parentheses symbols.Examples:remove_parentheses_symbols('<','>')=>None
Package: parent-import
Parent ImportUnfortunately, importing from parent directory is problematic in Python.This package makes it easier to import from parent directory.Installpip install parent_importExample Usage:file structure:project_name/
    dir1/
        importer.py
    dir2/
        dir3/
            module_to_import.pymodule_to_import.py:print("Module Imported")defmethod1():print("Hello World")importer.py:fromparent_importimportparentdirmodule=parentdir.dir2.dir3.module_to_import# Output: "Module Imported"module.method1()# Output: "Hello World"Note: Accesing parent of parent is also possible as follows:fromparent_importimportparentdirmodule=parentdir.parentdir.another_dir.module_to_importAnother Usage - Import From Parent Directory:fromparent_importimportadd_ancestor_dir_to_pathadd_ancestor_dir_to_path(level=1)importdir2.dir3.module_to_importAnother Usage - Import From Parent of Parent Directory:fromparent_importimportadd_ancestor_dir_to_pathadd_ancestor_dir_to_path(level=2)importanother_dir.module_to_importTODOGet rid ofsys.path.insert(0, self.dir_path)statements in order to speed up module search. (possible?)Override or extendimportstatement to use the Pythonic syntax for importing from parent directory. (possible?)
Package: parenting
parenting - the Python wayNever lend your car to anyone to whom you have given birth.Erma BombeckI have just recently become a first time dad and this is the greatest joy of my life. There is so much to learn and yet my software development experience has prepared so little for this. After my first weeks of daddying, I put some of my learnings into a - what else could I do - Python library. Obviously, this is not going to solve your problems, but maybe it can humor you a bit and this is what dad humor is for.Usageparentingis published onPyPiand you can get it with the standardpipinterface.parentingneeds Python 3.6 and useswasabias a pretty printer.Once you downloaded the library, you find a standard python interface. I implemented classes depending on your relationship to the baby. They yield mostly the same results, however, parenting is not just the parents job sometimes and it is important to recognize that. I currently implemented ten classes so far:mommy(),daddy(),partner,auntie(),uncle(),sister(),brother(),grandma(),grandpa(),friend().# import the class you need, for me its daddy
from parenting import daddy

# init the class
dad = daddy()Ones the class is initiated, you get access to theget_advice()method. This will guide you through a dialog, in which we try to find your baby's problem together. I must admit, this is obviously simplified, yet inspired bySo beruhige ich mein Babyan amazing book byChristine Rankl.Theget_advice()method implements a bunch of criteria to check when your baby starts complaining. In the first three months, complaining is typically screaming rather than actively communicating what the exact problem is.Anyway, I hope this helps you. Probably it won't solve any of your problems, but maybe it humors you, at least to some extend. In my defense, I am a dad now, so I get to make jokes such as that one.
Package: parent-map
Parent-mapAnalyze parental contributions to evolved or engineered protein or DNA sequencesRun parent-map without arguments to start in GUI mode.
Run parent-map with arguments to start in console mode.
Run parent-map.py -h for help and list of arguments.Install from PyPI:pip install parent-mapInstall from Bioconda:conda install -c bioconda parent-mapRun:python -m parent-mapWindows installer:https://sourceforge.net/projects/parent-map/Full documentation:https://parent-map.readthedocs.io/Discussion list:https://groups.google.com/g/parent-maphttps://orcid.org/0000-0003-0847-8095
Package: parenx
parenxSimplify (or "pare") a GeoJSON network ("nx") using raster image skeletonization an Voronoi polygonsProvides functions that use image skeletonization or Voronoi polygons to simplify geographic networks composed of linestrings. The outputs are geographic layers representing simplified or 'primal' representations of the network. Primal networks only contains straight line segmentsSample datasets include:Princes Street in Edinburgh, indata/rnet_princes_street.geojsonRail lines in Doncaster, indata/rnet_doncaster_rail.geojsonInstallationInstall the package into an activatedpythonvirtual environment with the following command:pipinstallparenxInstall the latest development version from GitHub with the following command:pipinstallgit+https://github.com/anisotropi4/parenx.gitThis places theskeletonization.pyandvoronoi.pyscripts into the executable search path.Test to see if the package is installed with the following command:python-c"import parenx; print(parenx.__version__)"ExamplesAbashhelper scriptrun.shand example data is available under thesitepackageproject directory undervenv. The exact path varies with module andpythonversionSkeletonizationThe following creates a simplified network by applying skeletonization to a buffered raster array inoutput.gpkg# Download the data if not already presentif[!-f./data/rnet_princes_street.geojson];thenwgethttps://raw.githubusercontent.com/anisotropi4/parenx/main/data/rnet_princes_street.geojson# Create data folder if not already presentif[!-d./data];thenmkdir./datafimvrnet_princes_street.geojson./datafiskeletonize.py./data/rnet_princes_street.geojsonrnet_princes_street_skeletonized.gpkgVoronoiThe following creates a simplified network by creating set of Voronoi polygons from points on the buffer inoutput.gpkgvoronoi.py./data/rnet_princes_street.geojsonrnet_princes_street_voronoi.gpkgSimple operationTherun.shscript sets a python virtual environment and executes the script against a data file in thedatadirectory$ ./run.shTherun.shscript optionally takes a filename and file-extension. To simplify a file, saysomewhere.geojsonand output toGeoPKGfilessk-simple.gpkgandvr-simple.gpkg$ ./run.sh somewhere.geojon simpleLocating therun.shscriptTo copy therun.shscript into your local directory the following could help$ find . -name run.sh -exec cp {} . \;NotesBoth are the skeletonization and Voronoi approach are generic approaches, with the following known issues:This does not maintain a link between attributes and the simplified networkThis does not identify a subset of edges that need simplificationThe lines are a bit wobblyIt is quite slow
Package: parepy-toolbox
Projeto PAREpy ToolboxEste Ã© o repositÃ³rio para desenvolvedores da plataforma PARE^py (Probabilistic Approach Reliability Engineering) para anÃ¡lise probabilÃ­stica em Engenharia.Como utilizar localmenteOs requisitos para uso local sÃ£o:VS CodePython > 3Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum.
Package: paress
PARESS - Web Scraping el Portal de Archivos EspañolesEste es un módulo que puede ser utilizado para realizar tareas deWeb Scrapingen el Portal de Archivos Españoles.InstalaciónDesde PyPIpip install paressDesde GitHubpip install git+https://github.com/jairomelo/PARESS.gitUsoparess.metadatalist(url,elem,host="http://pares.mcu.es")Regresa un lista de un elemento: título, fecha, signatura, archivo.
El parámetroelemse debe indicar como sigue:
* Título de los elementos: "titulo"
* Nombre de los archivos: "archivo"
* Fechas: "fecha"
* Signaturas: "signatura"Ej.: Cartas y expedientes de personas eclesiásticas, sig. FILIPINAS,301importparessparess.metadatalist("http://pares.mcu.es/ParesBusquedas20/catalogo/contiene/425393","fecha")paress.imagenes(url, ident="descarga", host="http://pares.mcu.es")Descarga las imágenes de un expediente. La ruta debe ser "http://pares.mcu.es/ParesBusquedas20/catalogo/show/xxx".
Puede personalizarse el nombre del archivo de la descarga con el parámetroident.En caso de no incluir este parámetro el programa descarga las imágenes en el directorio '/descarga/' y reemplaza cualquier archivo con el nombre 'descarga.csv'.Nombres muy largos pueden generar errores.Ej: Registro: Virreyes de Santa Fe, sig. Archivo General de Indias, SANTA_FE,541,L.3importparessparess.imagenes("http://pares.mcu.es/ParesBusquedas20/catalogo/show/384442","nombre_directorio")paress.metadata(url,ident="descarga",host="http://pares.mcu.es")Descarga el conjunto de metadatos en un archivo csv.
Puede personalizarse el nombre del archivo de la descarga con el parámetroident.En caso de no incluir este parámetro el programa descarga las imágenes en el directorio '/descarga/' pero no reemplaza ninguna imagen.Nombres muy largos pueden generar errores.Ej.: Cartas y expedientes de personas eclesiásticas, sig. FILIPINAS,301importparessparess.metadata("http://pares.mcu.es/ParesBusquedas20/catalogo/contiene/425393","nombre_directorio")El parámetro URL enparess.metadata()ypares.metadatalist()acepta cualquier ruta que contenga un listado, ya sea una búsqueda simple, avanzada, listado de autoridad o unidad documental.
Package: parestlib
Parameter estimation library (parestlib)This repository contains code and tests for exploring different optimization methods. It is in extremely early development and is not yet ready for public use. For more information, please contact us viacovasim@idmod.org.DisclaimerThe code in this repository was developed by IDM to support our research in disease transmission and managing epidemics. We’ve made it publicly available under the Creative Commons Attribution-Noncommercial-ShareAlike 4.0 License to provide others with a better understanding of our research and an opportunity to build upon it for their own work. We make no representations that the code works as intended or that we will provide support, address issues that are found, or accept pull requests. You are welcome to create your own fork and modify the code to suit your own modeling needs as contemplated under the Creative Commons Attribution-Noncommercial-ShareAlike 4.0 License.
Package: paretl
Parameterized ETLFree software: Apache Software License 2.0Installationpip install paretlYou can also install the in-development version with:pip install https://github.com/TRI-AMDD/paretl/archive/master.zipDocumentationhttps://paretl.readthedocs.io/DevelopmentTo run all the tests run:toxNote, to combine the coverage data from all the tox environments run:Windowsset PYTEST_ADDOPTS=--cov-append
toxOtherPYTEST_ADDOPTS=--cov-append toxChangelog0.0.0 (2020-12-03)First release on PyPI.
Package: paretochart
Pareto chartfor python (similar toMatlab, but much more flexible).FeaturesData labelsfor the chart x-axis.Fully customizablewith uniqueargandkwarginputs:Bar chart: follows the inputs of thematplotlib.pyplot.barfunction (usebar_args=(...)andbar_kw={...}).Cumulative line: follows the inputs of thematplotlib.pyplot.plotfunction (useline_args=(...)andline_kw={...}).Limit line: follows the inputs of thematplotlib.axes.Axes.axhlinefunction (uselimit_kw={...}).Put the chart onarbitrary axes.ExamplesFirst, a simple import:from paretochart import paretoNow, let’s create the numeric data (no pre-sorting necessary):data = [21, 2, 10, 4, 16]We can even assign x-axis labels (in the same order as the data):labels = ['tom', 'betty', 'alyson', 'john', 'bob']For this example, we’ll create 4 plots that show the customization
capabilities:import matplotlib.pyplot as plt

# create a grid of subplots
fig, axes = plt.subplots(2, 2)The first plot will be the simplest usage, with just the data:pareto(data, axes=axes[0, 0])
plt.title('Basic chart without labels', fontsize=10)In the second plot, we’ll add labels, put a cumulative limit at 0.75 (or 75%)
and turn the cumulative line green:pareto(data, labels, axes=axes[0, 1], limit=0.75, line_args=('g',))
plt.title('Data with labels, green cum. line, limit=0.75', fontsize=10)In the third plot, we’ll remove the cumulative line and limit line, make the
bars green and resize them to a width of 0.5:pareto(data, labels, cumplot=False, axes=axes[1, 0], data_kw={'width': 0.5,
    'color': 'g'})
plt.title('Data without cum. line, green bar width=0.5', fontsize=10)In the fourth plot, let’s put the cumulative limit at 95% and make that line
yellow:pareto(data, labels, limit=0.95, axes=axes[1, 1], limit_kw={'color': 'y'})
plt.title('Data trimmed at 95%, yellow limit line', fontsize=10)And last, but not least, let’s show the image:fig.canvas.set_window_title('Pareto Plot Test Figure')
plt.show()This should result in the following image (click hereif the image doesn’t
show up):InstallationSince this is really a single python file, you can simply go to theGitHubpage, simply downloadparetochart.pyand put it in
a directory that python can find it.Alternatively, the file can be installed using:$ pip install --upgrade paretochartor:$ easy_install --upgrade paretochartIf you are using Python3, download the compressed file from here, unzip and run:$ 2to3 -w *.pywhile in the unzipped directory,thenrun:$ python3 setup.py installNOTE:Administrative privileges may be required to perform any of
the above install methods.ContactPlease sendfeature requests, bug reports, or feedbacktoAbraham Lee.
Package: paretos
Paretos packageThis is the paretos package for easy integration of socrates optimization
within customer environments. The package also enables to get the results
of socrates api in an easy and understandable way.InstallationThe installation of the package is simply done via. pippipinstallparetosUsageIn general the complete documentation for usage and classes can be foundhere. In this
readme only brief overview of the most important points to get started is given.DevelopmentThis section is aimed towards developers of the paretos library.Getting StartedYou will find some executable examples in the/examplesfolder.Seeexamples/getting-started.mdfor the necessary steps to run those scripts.Lintingisort .black .Unit Testingpython -m unittest discover test/unittestcoverage run --source paretos -m unittest discover test/unittestcoverage htmlSetting up Testbench for FrontendTo setup some test projects in certain states for frontend tests you can use the script in test/frontend_testbench
To call it you have to set the following environment variables:SOCRATES_URLPARETOS_USERNAMEPARETOS_PASSWORDThen call the script:python test/frontend_testbench/init_testbench.pyThe script will use the socrates-api to create projects and run optimizations to create some edge-cases for frontend tests.Dependenciesrequires connection to Socrates API 1.2.0 or newer
Package: parfis
ParfisParfis is an acronym for Particles and Field Simulator. Parfis is written in
C++ with Python bindings. The algorithm is based on the particle-in-cell
(PIC) method used for interacting many-particle systems. In the PIC method
individual particles (or fluid elements) in a Lagrangian frame are tracked
in a continuous phase space, whereas moments of the distribution such as
densities and currents are computed simultaneously on Eulerian (stationary)
mesh points.Quick startYou can quickly install and try parfis by doing the following in your terminal:pipinstallparfisAfter installing you can try if the library loads and check the info of
the istalled build with the following three commands from your python terminal:fromparfisimportParfisParfis.load_lib()print(Parfis.info())Explore more possibilitiesExplore the possibilities by checking some of the examples given in thedemosection of thedoc web-site.
Package: parfive
A parallel file downloader using asyncio. parfive can handle downloading
multiple files in parallel as well as downloading each file in a number of
chunks.Usageparfive works by creating a downloader object, appending files to it and then
running the download. parfive has a synchronous API, but uses asyncio to
paralellise downloading the files.A simple example is:from parfive import Downloader
dl = Downloader()
dl.enqueue_file("http://data.sunpy.org/sample-data/predicted-sunspot-radio-flux.txt", path="./")
files = dl.download()Parfive also bundles a CLI. The following example will download the two files concurrently.:$ parfive 'http://212.183.159.230/5MB.zip' 'http://212.183.159.230/10MB.zip'
$ parfive --help
usage: parfive [-h] [--max-conn MAX_CONN] [--overwrite] [--no-file-progress]
              [--directory DIRECTORY] [--print-filenames]
              URLS [URLS ...]

Parfive, the python asyncio based downloader

positional arguments:
  URLS                  URLs of files to be downloaded.

optional arguments:
  -h, --help            show this help message and exit
  --max-conn MAX_CONN   Number of maximum connections.
  --overwrite           Overwrite if the file exists.
  --no-file-progress    Show progress bar for each file.
  --directory DIRECTORY
                        Directory to which downloaded files are saved.
  --print-filenames     Print successfully downloaded files's names to stdout.Resultsparfive.Downloader.downloadreturns aparfive.Resultsobject, which is a
list of the filenames that have been downloaded. It also tracks any files which
failed to download.Handling ErrorsIf files fail to download, the urls and the response from the server are stored
in theResultsobject returned byparfive.Downloader. These can be used to
inform users about the errors. (Note, the progress bar will finish in an
incomplete state if a download fails, i.e. it will show4/5 Files Downloaded).TheResultsobject is a list with an extra attributeerrors, this property
returns a list of named tuples, where these named tuples contains the.urland the.response, which is aaiohttp.ClientResponseor aaiohttp.ClientErrorobject.Installationparfive is available on PyPI, you can install it with pip:pip install parfiveor if you want to use FTP downloads:pip install parfive[ftp]RequirementsPython 3.7 or aboveaiohttptqdmaioftp (for downloads over FTP)LicenceMIT LicensedAuthorsparfivewas written byStuart Mumford.