Saravanan666/pypi-org huggingface dataset:
Package: namesilo
A simple wrapper for the NameSiloAPI.InstallTo install via pip:pip install namesiloUsageInstantiating the client:import namesilo# By default the client initializes in sandbox mode
ns = namesilo.NameSilo(‘API KEY HERE’)# Instantiate in live mode
ns = namesilo.NameSilo(‘API KEY HERE’, live=True)From here you can call operations like so:ns.register_domain(domain=’yourdomain.com’, years=’1’)OperationsThis client renames the operations to follow a more consistent convention of
(verb)_(subject). Seenamesilo.NAMESILO_OPERATIONSto seehow these method
names map to their NameSilo counterparts. The goal of this mapping its to make
the API more intuitive.
Package: names-matcher
names-matcherFuzzily biject people's names between two lists.Let's define an identity as a series of names belonging to the same person. The algorithm is:Parse, normalize, and split names in each identity. The result is a set of strings per each.Define the similarity between identities asmax(ratio, token_set_ratio), whereratioandtoken_set_ratioare inspired by string comparison functions fromrapidfuzz.Construct the distance matrix between identities in two specified lists.Solve the Linear Assignment Problem (LAP) on that matrix.Our LAP's solution scales up to ~1000-s of identities.Example:>>> from names_matcher import NamesMatcher
>>> NamesMatcher()([["Vadim Markovtsev", "vmarkovtsev"], ["Long, Waren", "warenlg"]], \
                    [["Warren"], ["VMarkovtsev"], ["Eiso Kant"]])
(array([1, 0], dtype=int32), array([0.75      , 0.57142857]))The first resulting tuple element is the mapping indexes: of same length as the first sequence,
with indexes in the second sequence. The second element is the corresponding confidence values
from 0 to 1.Installationpip3 install names-matcherCommand line interfaceGiven one identity per line in two files, print the matches to standard output:python3 -m names_matcher path/to/file/1 path/to/file/2Each identity is several names merged with|, for example:Vadim Markovtsev|vmarkovtsev|vadimContributingContributions are very welcome and desired! Please follow thecode of conductand read thecontribution guidelines.LicenseApache-2.0, seeLICENSE.
Package: namespacedict
This package provides aNamespaceDictmapping which fully evaluates keys
using Python syntax.  For example, it can perform nested lookups, attribute
lookups, and tuple splicing:>>> from namespacedict import NamespaceDict
>>>
>>> # create a new namespace
>>> ns = NamespaceDict()
>>>
>>> # nested lookup from a list
>>> ns['x'] = [1, 2, 3]
>>> ns['x[1]']
2
>>> # set a docstring attribute
>>> ns['y'] = lambda x: x
>>> ns['y.__doc__'] = 'my function'
>>> ns['y.__doc__']
'my function'
>>>
>>> # set three items from a tuple
>>> ns['a, b, c'] = 'A', 'B', 'C'
>>> ns['b']
'B'Keys are parsed in a safe way using Python’s AST library.  It is thus possible
to create complex dictionary queries that work as expected:>>> ns['one'] = 1
>>> ns['two'] = 2
>>> ns['x[0:two]'] = 5, 4
>>> ns['x[::-one]']
[3, 4, 5]TheNamespaceDicttype can also be used as an adapter for other mappings,
by passing the underlying data structure on initialisation:>>> # create a numpy array with named columns
>>> import numpy as np
>>> a = np.empty(5, dtype=[('col1', int), ('col2', int), ('col3', int)])
>>>
>>> # use NamespaceDict to access array
>>> ns = NamespaceDict(a)
>>>
>>> # access named columns through namespace
>>> ns['col1, col2, col3'] = 1, 2, 3
>>> ns['col2']
array([2, 2, 2, 2, 2])The mapping can be retrieved using the.dataattribute.
Package: namespaces.py
namespaces.pyNo more stupid dotsTired of using the boring oldfoo.barnotation?Feel like cheating on your type checker?Want to pretend like you're writing C++, even though you aren't?Fear not, fornamespaces.pyis here!Exampleimportnamespacesnamespaces.inject()classTest:@staticmethoddefhello():print("hello world!")Test[::"hello"]()# hello world!FeaturesCool::C++ like symbol to make you feel specialShow your linter whose bossPretend this is a feature, I wanted to have 3 listed here to make it seem more evenInstallation$ pip install namespaces.pyDocs?I'm gonna pretend you didn't ask that.CompatibilityAw come on, discovering broken versions is half the fun.
Package: namespacetrie
This is the Namesapce Trie.Namespace Trie is a implementation of a Trie data structure.  Unlike typical
implementations, which are splitting its value into single characters,
Namespace Trie treats its values as namespaces.  Namespaces are strings that
are delimited by a period. Such namespaces often occur in programming
languages, e.g. Java or Python and may also appear while using some libraries
for programming languages that itself do not offer namespacing (e.g. the
Google Closure library offers a namespace feature for JavaScript).  The
Namespace Trie may help you find flaws in the namespace structure.Namespace Trie is developed for use with Closure Depresolver and may at the
moment not be very useful as there is not standalone interface.This file was modified by PyCharm 2.5 for binding GitHub repository
Package: names_translator
names-translatorThat’s a small tool to generate as many possible transliteration options for ukrainian names
First it translates the name into russian using dictionary, then transliterates ukrainian and russian names
using translit-ua package and 19 different transliteration tables. Finally, some heuristic is applied to cover
usual usual trasnliterations for well known names, which aren’t covered by the transliteration tablesInstallationInstall from PyPI.$pipinstallnames_translatorUsage>>>fromnames_translatorimportTransliterator>>>tr=Transliterator()>>>tr.transliterate("Чаплинський","Дмитро","Олександрович"){"Chaplins'kij Dmitro Oleksandrovich",'Chaplinski Dmitri Aleksandrovich','Chaplinskii Dimitry Aleksandrovich','Chaplinskii Dmitrii Aleksandrovich','Chaplinskii Dmitrii Alexandrovich','Chaplinskii Dmitry Aleksandrovich','Chaplinskij Dmitrij Aleksandrovich','Chaplinskiy Dmitriy Aleksandrovich','Chaplinsky Dmitry Aleksandrovich',"Chaplyns'cyi Dmytro Olecsandrovych","Chaplyns'kyi Dmytro Oleksandrovych","Chaplyns'kyj Dmytro Oleksandrovych","Chaplyns'kyy Dmytro Oleksandrovych",'Chaplynski Dmytro Oleksandrovych','Chaplynsky Dmytro Oleksandrovych','Chaplynskyi Dimitry Oleksandrovych','Chaplynskyi Dmitry Oleksandrovych','Chaplynskyi Dmytro Oleksandrovych','Chaplynskyi Dmytro Olexandrovych','Chaplȳnskȳĭ Dmȳtro Oleksandrovȳch','Tchaplynskyy Dmytro Oleksandrovytch','Tschaplynskyj Dmytro Oleksandrowytsch',"Čaplins'kij Dmitro Oleksandrovič",'Čaplins′kij Dmitro Oleksandrovič','Čaplynsʹkyj Dmytro Oleksandrovyč','Чаплинский Дмитрий Александрович','Чаплинський Дмитро Олександрович'}
Package: namesync
Sync DNS records stored in a flat file format to your DNS provider. Cloudflare support currently provided.Installation$ pip install namesyncQuick GuideCreate a file with the name of your domain:$ touch example.comOr, if you have existing records, you can export them:$ namesync --get example.comEnter one record per line with the following format:<record-type> <name> <value> <ttl:optional>For example:A       *       10.10.10.10         # You can even use comments
A       .       10.10.10.10         # . references the domain itself, example.com
A       test    10.10.10.11
A       example 10.10.10.12 86400
CNAME   mail    ghs.googlehosted.com
MX      .       aspmx.l.google.comMX records allow you to specify a priority:MX <name> <value> <priority:optional> <ttl:optional>Like this:MX      .       alt1.aspmx.l.google.com 20
MX      .       aspmx3.googlemail.com 30 86400If the value contains spaces, quote it:TXT     .       "v=spf1 a include:amazonses.com include:_spf.google.com ~all"Then sync your records:$ namesync example.comYou will be given a chance to review your changes before they are synced:The following changes will be made:
ADD    A     *       10.10.10.10
ADD    A     example 10.10.10.12 86400
ADD    A     test    10.10.10.11
ADD    CNAME mail    ghs.googlehosted.com
ADD    MX    .       aspmx.l.google.com
UPDATE A     .       10.10.10.10
REMOVE A     old     10.10.10.13
Do you want to continue? [y/N]Usageusage: namesync [-h] [-g] [-z ZONE] [-y] [-d DATA_DIR] [-t] RECORDS

positional arguments:
  RECORDS               file containing DNS records, one per line. The zone is
                        derived from the basename of this file. For example,
                        if "dns/example.com" is used then the zone is assumed
                        to be "example.com" unless the --zone option is used

optional arguments:
  -h, --help            show this help message and exit
  -g, --get             save existing DNS records to RECORDS
  -z ZONE, --zone ZONE  specify the zone instead of using the RECORDS filename
  -y, --yes             sync records without prompting before making changes
  -d DATA_DIR, --data-dir DATA_DIR
                        the directory where namesync.conf and other cache data
                        is stored. [default: ~/.namesync]
  -t, --dry-run         print actions and exit without making any changes
Package: nametable
nametableserves to bridge the gap betweenNintendo Entertainment System'sPicture Processing Unit'snametablesand Python.Its main goal is to create anObject Orientedapproach to represent a nametable on the NES.It provides the ability to create instances of Pattern and Block directly from memory and inserts them into PatternTable and Nametable, respectively.>>>importnametable>>>pattern=nametable.PatternMeta(bytes.fromhex("41 C2 44 48 10 20 40 80 01 02 04 08 16 21 42 87"))>>>pattern.numpy_arrayarray([[0,1,0,0,0,0,0,3],[1,1,0,0,0,0,3,0],[0,1,0,0,0,3,0,0],[0,1,0,0,3,0,0,0],[0,0,0,3,0,2,2,0],[0,0,3,0,0,0,0,2],[0,3,0,0,0,0,2,0],[3,0,0,0,0,2,2,2],],dtype=ubyte,)>>>pattern_table=nametable.PatternTable((nametable.Pattern(pattern),))>>>block=nametable.Block(pattern_table,(0,0,0,0))>>>block.numpy_arrayarray([[0,1,0,0,0,0,0,3,0,1,0,0,0,0,0,3],[1,1,0,0,0,0,3,0,1,1,0,0,0,0,3,0],[0,1,0,0,0,3,0,0,0,1,0,0,0,3,0,0],[0,1,0,0,3,0,0,0,0,1,0,0,3,0,0,0],[0,0,0,3,0,2,2,0,0,0,0,3,0,2,2,0],[0,0,3,0,0,0,0,2,0,0,3,0,0,0,0,2],[0,3,0,0,0,0,2,0,0,3,0,0,0,0,2,0],[3,0,0,0,0,2,2,2,3,0,0,0,0,2,2,2],[0,1,0,0,0,0,0,3,0,1,0,0,0,0,0,3],[1,1,0,0,0,0,3,0,1,1,0,0,0,0,3,0],[0,1,0,0,0,3,0,0,0,1,0,0,0,3,0,0],[0,1,0,0,3,0,0,0,0,1,0,0,3,0,0,0],[0,0,0,3,0,2,2,0,0,0,0,3,0,2,2,0],[0,0,3,0,0,0,0,2,0,0,3,0,0,0,0,2],[0,3,0,0,0,0,2,0,0,3,0,0,0,0,2,0],[3,0,0,0,0,2,2,2,3,0,0,0,0,2,2,2],],dtype=ubyte,)>>>nametable.Nametable((block,))Nametable(Block(PatternTable((Pattern(PatternMeta(...)),)),(0,0,0,0)),)Getting HelpPlease use thepython-nametabletag onStackOverflowto get help.Aiding others and answers questions is a fantastic way to help!Project Informationnametableis released under theGPL3license.
Its documentation is hosted onGithuband the
repository is hosted onGithub.  The latest release
is hosted onPyPI.
Package: nametag
nametag - set audio file tags based on file namenametag uses regular expressions to parse paths of audio files and
then sets the file tags based on the parsed data.  This allows you to
keep paths and tags in sync by creating the tags from the paths.Everything is configurable with some custom python code: the path
regexes, the character substitution, and the handling of special
cases.  For example, the albumif_then_elseby The Gathering should
not have its underscores changed to spaces.Examples# dry run (do not modify files) + verbose (shows info)$nametag-v--dry-runBetween_the_Buried_and_Me/04-Colors_\(2007\)/05-Ants_of_the_Sky.mp3
/.../Between_the_Buried_and_Me/04-Colors_(2007)/05-Ants_of_the_Sky.mp3:artist='Between the Buried and Me'album='Colors'track='05'title='Ants of the Sky'ext='mp3'album_n='04'year='2007'# extra verbose (shows info before and after processing)$nametag-vvBetween_the_Buried_and_Me/04-Colors_\(2007\)/05-Ants_of_the_Sky.mp3
/.../Between_the_Buried_and_Me/04-Colors_(2007)/05-Ants_of_the_Sky.mp3:-artist='Between_the_Buried_and_Me'album='Colors'track='05'title='Ants_of_the_Sky'ext='mp3'album_n='04'year='2007'+artist='Between the Buried and Me'album='Colors'track='05'title='Ants of the Sky'ext='mp3'album_n='04'year='2007'ConfigurationExample~/.nametagrc.py:# regexes array; each one is tried in turn to match the path; the# default regex (nametag.RX) matches paths as in the examples above.regexes.append(re.compile(r"""..."""))# character substitutions; the default is { "_|": " /" }tr["~"]="_"# custom processing rules; each one is tried in turn until one returns a value@ruledefif_then_else(info,tr):ifinfo.artist=="The_Gathering"andinfo.album=="if_then_else":returninfo._map_values(lambdak,v:vifk=="album"elsetr(v))$nametag--show-config===config===regexes:'/(?P<artist>[^/]*)/(?:(?P<album_n>\\d+)-)?(?P<album>[^/]*?)(?:_\\((?P<year>\\d{4})\\))?/(?P<track>\\d+)(?:-(?P<title>[^/]*))?\\.(?P<ext>mp3|ogg|flac)\\Z''...'tr:{'_|':' /','~':'_'}rules:if_then_elseHelp$nametag--helpTab CompletionFor Bash, add this to~/.bashrc:eval"$(_NAMETAG_COMPLETE=source_bashnametag)"For Zsh, add this to~/.zshrc:eval"$(_NAMETAG_COMPLETE=source_zshnametag)"For Fish, add this to~/.config/fish/completions/nametag.fish:eval(env_NAMETAG_COMPLETE=source_fish nametag)RequirementsPython >= 3.8 + click + pytaglib.Debian/Ubuntu$aptinstallpython3-clickpython3-taglibInstallingUsing pip$pipinstallnametagNB: depending on your system you may need to use e.g.pip3 --userinstead of justpip.From gitNB: this installs the latest development version, not the latest
release.$gitclonehttps://github.com/obfusk/nametag.py.git
$cdnametag
$pipinstall-e.NB: you may need to add e.g.~/.local/binto your$PATHin order
to runnametag.To update to the latest development version:$cdnametag
$gitpull--rebaseLicense
Package: name-tools
This library is no longer maintained.Consider a library likeprobablepeople.A Python library for manipulating and comparing English, Western-style personal names.Released under a BSD-style license.Source:http://github.com/openstates/name_toolsInstallationTo install from PyPI runpip install name_toolsoreasy_install name_toolsTo install from a source package runpython setup.py installUsagename_tools.split(name)breaks a name into 4 (possibly empty) parts,
representing prefixes (‘Mr.’, ‘Dr.’, etc.), a ‘first part’ (given names,
middle names, middle initials), a last name, and suffixes (‘Jr.’,
‘III’, ‘Ph.D’, etc.)>>> import name_tools
>>> name_tools.split("President Barack Hussein Obama II")
('President', 'Barack Hussein', 'Obama', 'II')
>>> name_tools.split("Obama, President Barack H., II")
('President', 'Barack H', 'Obama', 'II')
>>> name_tools.split("Fleet Admiral William Frederick Halsey, Jr., USN")
('Fleet Admiral', 'William Frederick', 'Halsey', 'Jr., USN')
>>> name_tools.split("Dick van Dyke")
('', 'Dick', 'van Dyke', '')name_tools.canonicalize(name)returns a name in a canonical format:
‘Prefixes First Last, Suffixes’, with extra spaces removed and words
capitalized.>>> name_tools.canonicalize('  WASHBURNE,  zoe alleyne')
'Zoe Alleyne Washburne'
>>> name_tools.canonicalize('DR. simon tam')
'Dr. Simon Tam'
>>> name_tools.canonicalize(' thurston b. howell iii')
'Thurston B. Howell, III'name_tools.match(name1, name2)provides a measure of the
similarity between two name, considering factors such as differing word
order (‘Bond, James’ and ‘James Bond’), use of initials
(‘J. R. R. Tolkien’ and ‘John Ronald Reuel Tolkien’) and various
titles and honorifics (‘Fleet Admiral William Frederick Halsey, Jr., USN’,
and ‘William Frederick Halsey’).>>> name_tools.match('Eric Schmidt', 'Eric Schmidt')
1.0
>>> name_tools.match('Bob Dole', 'Dole, Bob')
0.98
>>> name_tools.match("michaeL StepHens", "MichaEl  StePhens")
0.98
>>> name_tools.match("Mr. X", "X")
0.95
>>> name_tools.match('Jeff Tweedy', 'J Tweedy')
0.9
>>> name_tools.match('Ferris Bueller', 'Bueller')
0.8
>>> name_tools.match('John Smith', 'John Johnson')
0.0
Package: nametract
nametractSimple python package to extract everything that looks like a name from the text. Extremely unreliable. Might work for
you if you don't care about possible errors. Currently in development.fromnametractimportextractextract("My name is Peter, and I love Nancy Brown")# ["Peter", "I", "Nancy Brown"]extract("My name is Peter, and I love Nancy Brown",minimal_name_size=2)# ["Peter", "Nancy Brown"]extract("My name is Peter, and I love Nancy Brown",ignore_sentence_start=False)# ["My", "Peter", "I", "Nancy Brown"]extract("С коня сошел Иван Зайцев-Кабачков")# ["Иван Зайцев-Кабачков"]
Package: nameunity
Name UnityPurposeA simple tool to help you unity file names.Automatically generated file names always contains date time information, like
the photos' name created by your phone or camera. But different devices might
provide different format, so it would be me orderless if you store all these
files into one position.This tool would help you automatically rename these files to one single format.FunctionsDirectly get date time information from file name. Example format,IMG_20010101_120000.jpgRequirementsPython >= 3.6Pip >= 10.0InstallpipinstallnameunityAuthorLucasyuanzhendai@gmail.com
Package: namez
namezA package for accessing objects by nameInstallation$pipinstallnamezUsageTODOContributingInterested 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.Licensenamezwas created by Shawn Presser. It is licensed under the terms of the MIT license.Creditsnamezwas created withcookiecutterand thepy-pkgs-cookiecuttertemplate.
Package: naming
namingObject-oriented names for the digital era.namingprovides an interface for dealing with naming conventions; from
defining them, to identifying names and creating new ones.Installationnamingis available for Python 3.7 onwards via PyPI.$pipinstallnamingUsagePlease refer to thedocumentationfor details on contents and usage.>>>importnaming>>>classNameFileConvention(naming.Name,naming.File):...config=dict(first=r'\w+',last=r'\w+',number=r'\d+')...>>>name=NameFileConvention('john doe 07.jpg')>>>name.last'doe'>>>name.number'07'>>>name.get(first='jane',number=99)# returns new name string'jane doe 99.jpg'>>>name.last='connor'# mutates current name>>>nameNameFileConvention("john connor 07.jpg")>>>name.number='not_a_number'...ValueError:Can't set field 'number' with invalid value 'notanumber' on 'NameFileConvention("john doe 07.jpg")'. A valid field value should match pattern: '\d+'
Package: naming-utils
Simple utility for generating unique names with timestamps.Installationpipinstallnaming-utilsUsage>>>fromnaming_utilsimportunique_name_with_ts>>>unique_name_with_ts()'20220508_085805_173693933'>>>unique_name_with_ts(path='log/',extension='log')'log/20220508_085837_602718269.log'>>>fromnaming_utilsimportunique_names_with_ts>>>unique_names_with_ts(count=5,path='log/',extension='log')['log/20220508_085901_689713589.log','log/20220508_085901_689713339.log','log/20220508_085901_68971329.log','log/20220508_085901_689713292.log','log/20220508_085901_688709138.log']
Package: nammv
InstallationResponsitoryGithub page- Install from local responsitory:
1.Clone Responsitory
2.cd folder\
3.pip install -e .\CameraBaslerUsing open Basler camera
Referencepypylon masterfrom connections import Basler
# init camera
camera = Basler()
# open camera by index 0
camera.open(0)
# open camera by serinumber
# camera.open('serinumber_here')
# grab image
mat = camera.grab()
print(mat.shape)
# close camera
camera.close()WebcamUsing open Webcam or RTSP cameraReferenceopencv video capturefrom connections import Webcam
# init camera
camera = Webcam()

# open camera by rtsp
# camera.open('rtsp_link_here')
# open camera by index 0
camera.open(0)

# grab image
mat = camera.grab()
print(mat.shape)

# close camera
camera.close()Socket utilsSome function help send image(numpy array) or text over socket client and serverimport socket
import numpy as np
from connections.socket_utils import send_text, send_image

sk = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sk.connect(("localhost", 5000))

# send text with length with format: {lenth}:text:{your_text}
# ex client send "Hello", server revcieve "5:text:Hello"
msg = time.strftime("Client sent %H:%M:%S\n")
send_text(sk, msg)

# send array with length with format: {lenth}:image:{your_array_encode}
mat = np.random.radnint(0, 256, (640, 480, 3))
send_image(sk, mat)LoggerCustom loggerReferenceLogger console with colorReferenceLogging CookBookfrom connections import Logger
logger = Logger(name="mylog", 
            file_name="logfile.log", 
            file_level=logging.INFO,
            stream_level=logging.INFO)
logger.info("this is info")
logger.warning("this is warning")
logger.error("this is error")
logger.critical("this is critical")
Package: nam-pt
Neural Additive Models (PyTorch)This is a PyTorch re-implementation for neural additive models, check out:Neural Additive Models: Interpretable Machine Learning with Neural Nets.TensorFlow OG ImplementationInstall PackageDependenciestorch==1.7.0fsspec==0.8.4pandas==1.1.4tqdm==4.54.0sklearn==0.0absl-py==0.11.0gcsfs==0.7.1Usageconda env create -f environment.yml
conda activate nam-pt
python run.pyCitingIf you use this code in your research, please cite the following paper:Agarwal, R., Frosst, N., Zhang, X., Caruana, R., & Hinton, G. E. (2020).
Neural additive models: Interpretable machine learning with neural nets.
arXiv preprint arXiv:2004.13912@article{agarwal2020neural,
    title={Neural additive models: Interpretable machine learning with neural nets},
    author={Agarwal, Rishabh and Frosst, Nicholas and Zhang, Xuezhou and
    Caruana, Rich and Hinton, Geoffrey E},
    journal={arXiv preprint arXiv:2004.13912},
    year={2020}
  }Disclaimer about COMPAS dataset: It is important to note that
developing a machine learning model to predict pre-trial detention has a
number of important ethical considerations. You can learn more about these
issues in the Partnership on AIReport on Algorithmic Risk Assessment Tools in the U.S. Criminal Justice System.
The Partnership on AI is a multi-stakeholder organization -- of which Google
is a member -- that creates guidelines around AI.We’re using the COMPAS dataset only as an example of how to identify and
remediate fairness concerns in data. This dataset is canonical in the
algorithmic fairness literature.Disclaimer: This is not an official Google product.
Package: nam-pytorch
nam-pytorchUnofficial PyTorch implementation of Neural Additive Models (NAM) by Agarwal, et al. [abs,pdf]InstallationYou can accessnam-pytorchviapip:$pipinstallnam-pytorchUsageimporttorchfromnam_pytorchimportNAMnam=NAM(num_features=784,link_func="sigmoid")images=torch.rand(32,784)pred=nam(images)# [32, 1]ContributingAs always, if there are any issues with / suggestions for the code, feel free to raise an issue or submit a PR.LicenseMIT