Saravanan666/pypi-org huggingface dataset:
Package: humanhash3
humanhash provides human-readable representations of digests.Example>>>importhumanhash>>>digest='7528880a986c40e78c38115e640da2a1'>>>humanhash.humanize(digest)'three-georgia-xray-jig'>>>humanhash.humanize(digest,words=6)'high-mango-white-oregon-purple-charlie'>>>humanhash.uuid()('potato-oranges-william-friend','9d2278759ae24698b1345525bd53358b')CaveatsDon’t store the humanhash output, as its statistical uniqueness is only
around 1 in 4.3 billion. Its intended use is as a human-readable (and,
most importantly,memorable) representation of a longer digest,
unique enough for display in a user interface, where a user may need to
remember or verbally communicate the identity of a hash, without having
to remember a 40-character hexadecimal sequence. Nevertheless, you
should keep original digests around, then pass them throughhumanize()only as you’re displaying them.How It WorksThe procedure for generating a humanhash involves compressing the input
to a fixed length (default: 4 bytes), then mapping each of these bytes
to a word in a pre-defined wordlist (a default wordlist is supplied with
the library). This algorithm is consistent, so the same input, given the
same wordlist, will always give the same output. You can also use your
own wordlist, and specify a different number of words for output.InspirationChroma-Hash- A human-viewable representation of a hash (albeit not
one that can be output on a terminal, or shouted down a hallway).The NATO Phonetic Alphabet- A great example of the trade-off
between clarity of human communication and byte-wise efficiency of
representation.
Package: humanhelp
human helphuman interact data clustering toolHow to usePerformance evaluationMake a preprocessed dataset withpandasDataFrame typeMake a clustering algorithm object fromsklearnCall the 'clustering_evaluation(clustering_algorithm_object, dataset)'Expected processing time for the chosen algorithm with dataset will return.Human interact clusteringMake a preprocessed dataset withpandasDataFrame type
0-1. if the dataset has attributes more than 2, it will be compressed on two principles components as PCA method.Make a object 'HumanClusteringInterface(dataset)'Draw lines by clicking. ('c' key can delete the last clicked point)Press the 'z' key. It makes a cluster as draw a line between the first point and the last point.Make clusters as much as you want and after that Press the 'f' key.object.result_df contain the clustering result and object.clustering_result() method can show it as a plot.
Package: human-id
Human IDA simple library for generating human IDs likelook-dead-game-storyorget-nice-office-side.Install withpip install human-idUsage:fromhuman_idimportgenerate_id# Simple: "appear-hard-idea-case"generate_id()# Custom separator: "do,past,job,number"generate_id(separator=",")# More words: "say-may-ask-traditional-power-week"generate_id(word_count=10)# Custom seed - the same UUID will produce the same ID.importuuidgenerate_id(seed=uuid.uuid4())CLIThis module also comes with a small command line tool:humanid-gen❯ humanid-gen --help
Usage: humanid-gen [OPTIONS]

  Generate human readable IDs

Options:
  --words INTEGER  Number of words
  --sep TEXT       Separator
  --seed TEXT      Seed to use
  --count INTEGER  Number of IDs to generate
  --help           Show this message and exit.ImplementationThis library contains 100 of the most common English nouns, adjectives and verbs, and will
generate a phrase containing several of each type, in the orderverb, adjective, noun.The most common words where chosen because they are typically shorter and simpler to read or type,
which is a key property of human readable IDs.By default the ID will contain 4 words, which means there are300^4possible IDs (8,100,000,000). If your
use case requires more IDs then you can up the number of words at the expense of the readability factor. To
have the same number of possible IDs as UUIDs you require 15 words:may-hold-come-foreign-low-white-cold-team-point-study-others-home-service-body-child
Package: humanity-etl
humanity_etlReplicate data from humanity in databricksUsageCLIpython-mhumanity_etl--table<table-name>where table-name is one of the following:timeclocksorALL.APIfromhumanity_etl.tables.timeclocksimporttimeclockstimeclocks()Further configs are set via environment variables:Further configs are set via environment variables:*_ACCESS_TOKEN: API accessAPP_ENV: <development/production> - debug modeSAMPLE_OUTPUT: <True/False> - Save dataframes to csvDEVCreate venvpython-mvenvenvActivate venvunixsourceenv/bin/activatewindowsenv\Scripts\activate.batInstall Packagespipinstall-rrequirements.txtTestmaketestFormatmakeformatmakelintVersion & Releasebump2version<major/minor/patch>makereleasenoteDon't forget togit pushwith--tagspre-commitSetuppre-commitinstallRun allmakepre-commit
Package: humanize-gcode
humanize-gcodeA tool for explaining the commands in machine readable GCode files.Based on the specified GCode flavour, the tool parses a list of GCode commands and their description from the flavour's documentation. With this library it parses the input file and explains the effect of each command.InstallationThe utility is available on PyPi, so it can be installed withpip:pip3 install humanize-gcodeUsageThe package comes with the executable scripthucodethat accepts two arguments. The GCode flavour (currently onlymarlin/smoothieare supported) and the name of the file to annotate (or-for stdin).Example usage~ hucode smoothie testfile.gcodeTODOMore output formats (and possibly customization?)More supported GCode flavoursUse command arguments to influence annotation
Package: humanize-k
humanize--------.. image:: https://secure.travis-ci.org/jmoiron/humanize.png?branch=master:target: http://travis-ci.org/jmoiron/humanizeThis modest package contains various common humanization utilities, like turninga number into a fuzzy human readable duration ('3 minutes ago') or into a humanreadable size or throughput.  It works with python 2.7 and 3.3 and is localizedto Russian, French, Korean and Slovak.usage-----Integer humanization::>>> import humanize>>> humanize.intcomma(12345)'12,345'>>> humanize.intword(123455913)'123.5 million'>>> humanize.intword(12345591313)'12.3 billion'>>> humanize.apnumber(4)'four'>>> humanize.apnumber(41)'41'Date & time humanization::>>> import datetime>>> humanize.naturalday(datetime.datetime.now())'today'>>> humanize.naturaldelta(datetime.timedelta(seconds=1001))'16 minutes'>>> humanize.naturalday(datetime.datetime.now() - datetime.timedelta(days=1))'yesterday'>>> humanize.naturalday(datetime.date(2007, 6, 5))'Jun 05'>>> humanize.naturaldate(datetime.date(2007, 6, 5))'Jun 05 2007'>>> humanize.naturaltime(datetime.datetime.now() - datetime.timedelta(seconds=1))'a second ago'>>> humanize.naturaltime(datetime.datetime.now() - datetime.timedelta(seconds=3600))'an hour ago'Filesize humanization::>>> humanize.naturalsize(1000000)'1.0 MB'>>> humanize.naturalsize(1000000, binary=True)'976.6 KiB'>>> humanize.naturalsize(1000000, gnu=True)'976.6K'Human readable floating point numbers::>>> humanize.fractional(1/3)'1/3'>>> humanize.fractional(1.5)'1 1/2'>>> humanize.fractional(0.3)'3/10'>>> humanize.fractional(0.333)'1/3'>>> humanize.fractional(1)'1'Localization------------How to change locale in runtime ::>>> print humanize.naturaltime(datetime.timedelta(seconds=3))3 seconds ago>>> _t = humanize.i18n.activate('ru_RU')>>> print humanize.naturaltime(datetime.timedelta(seconds=3))3 секунды назад>>> humanize.i18n.deactivate()>>> print humanize.naturaltime(datetime.timedelta(seconds=3))3 seconds agoYou can pass additional parameter *path* to :func:`activate` to specify a path tosearch locales in. ::>>> humanize.i18n.activate('pt_BR')IOError: [Errno 2] No translation file found for domain: 'humanize'>>> humanize.i18n.activate('pt_BR', path='path/to/my/portuguese/translation/')<gettext.GNUTranslations instance ...>How to add new phrases to existing locale files ::$ xgettext -o humanize.pot -k'_' -k'N_' -k'P_:1c,2' -l python humanize/*.py  # extract new phrases$ msgmerge -U humanize/locale/ru_RU/LC_MESSAGES/humanize.po humanize.pot # add them to locale files$ msgfmt --check -o humanize/locale/ru_RU/LC_MESSAGES/humanize{.mo,.po} # compile to binary .moHow to add new locale ::$ msginit -i humanize.pot -o humanize/locale/<locale name>/LC_MESSAGES/humanize.po --locale <locale name>Where <locale name> is locale abbreviation, eg 'en_GB', 'pt_BR' or just 'ru', 'fr' etc.
Package: humanizer
humanizerA developer friendly data/value humanizer for debugging/logging - for Python.IntroductionTODOInstallInstall usingpip:$pipinstallhumanizerUseVery basicexample:fromhumanizerimportbytesize,duration# TODO: add exampleTestClone down source code:$makeinstallRuncolorful tests, with only native environment (dependency sandboxing up to you):$maketestRunless colorful tests, withmulti-environment(usingtox):$maketest-toxAboutThis project was mainly initiated - in lack of solid existing alternatives - to be used at our work atMarkable.aito have common code conventions between various programming environments wherePython(research, CV, AI) is heavily used.LicenseReleased under the MIT license.
Package: humanizer-portugues
SUPERSEEDED BY: https://github.com/staticdev/human-readable.FeaturesThis lib contains various humanization methods such as transforming a time difference in a human-readable duration “três minutos atrás” (three minutes ago) or in a phrase.RequirementsIt works in Python 3.7 and 3.8.InstallationYou can installHumanizer PortuguesviapipfromPyPI:$pipinstallhumanizer-portuguesUsageImport the lib with:importhumanizer_portuguesHumanization filesizes:humanizer_portugues.natural_size(1000000)"1.0 MB"humanizer_portugues.natural_size(1000000,binary=True)"976.6 KiB"humanizer_portugues.natural_size(1000000,gnu=True)"976.6K"Humanization of lists:humanizer_portugues.natural_list(["Cláudio","Maria"],",")"Cláudio, Maria"humanizer_portugues.natural_list(["Cláudio","Maria"],",","e")"Cláudio e Maria"humanizer_portugues.natural_list(["Cláudio","Maria","José"],";","ou")"Cláudio; Maria ou José"Humanization of integers:humanizer_portugues.ap_number(4)"quatro"humanizer_portugues.ap_number(41)"41"humanizer_portugues.int_comma(12345)"12,345"humanizer_portugues.int_word(123455913)"123.5 milhão"humanizer_portugues.int_word(12345591313)"12.3 bilhão"Humanization of floating point numbers:humanizer_portugues.fractional(1/3)"1/3"humanizer_portugues.fractional(1.5)"1 1/2"humanizer_portugues.fractional(0.3)"3/10"humanizer_portugues.fractional(0.333)"333/1000"humanizer_portugues.fractional(1)"1"Humanization of dates and time:importdatetimehumanizer_portugues.natural_clock(datetime.time(0,30,0))"zero hora e trinta minutos"humanizer_portugues.natural_clock(datetime.time(0,30,0),formal=False)"meia noite e meia"humanizer_portugues.natural_date(datetime.date(2007,6,5))"5 de junho de 2007"humanizer_portugues.natural_day(datetime.datetime.now())"hoje"humanizer_portugues.natural_day(datetime.datetime.now()-datetime.timedelta(days=1))"ontem"humanizer_portugues.natural_day(datetime.date(2007,6,5))"5 de junho"humanizer_portugues.natural_delta(datetime.timedelta(seconds=1001))"16 minutos"humanizer_portugues.natural_period(datetime.time(5,30,0).hour)"manhã"humanizer_portugues.natural_time(datetime.datetime.now()-datetime.timedelta(seconds=1))"há um segundo"humanizer_portugues.natural_time(datetime.datetime.now()-datetime.timedelta(seconds=3600))"há uma hora"ContributingContributions are very welcome.
To learn more, see theContributor Guide.LicenseDistributed under the terms of theMITlicense,Humanizer Portuguesis free and open source software.CreditsThis lib is based on originalhumanize, with updates for python3, translation fixes for portuguese, changes in return format and the addition of list humanizing. Localization (i18n) was also removed.
Package: human-json
Human JSONhuman_jsonis a simple python library, that can take a JSON Object, and create a pretty string for that object.JSON is easy to transport, and quite easy to read, but requires some form of prior training to properly understand it.
This library allows one to transform JSON Objects into an easier to read formatExampleThe following Python dictionary (which can represent a JSON Object):{'className':'ComputerScience','classId':2020,'assignments':{'assignment1':{'average_grade':5.5,'description':'Complete Assignment 1','grades':[5,5,5,7]},'assignment2':{'average_grade':None,'description':'Complete Assignment 2','grades':()}},'students':('student1','student2','studentabc',2019,None,10.5),}turns into the following pretty string:className: ComputerScience
classId: 2020
assignments:
	assignment1:
		average_grade: 5.5
		description: Complete Assignment 1
		grades:
			5
			5
			5
			7
	assignment2:
		average_grade: None
		description: Complete Assignment 2
		grades:
			-
students:
	student1
	student2
	studentabc
	2019
	None
	10.5Custom PrefixesYou can also specify an optional prefix, that will be prefixed to each line. A possible prefix is "* ".
Using this prefix, will return a markdown list. This can be directly copy-pasted into a markdown file, for example:*className: ComputerScience*classId: 2020*assignments:*assignment1:*average_grade: 5.5*description: Complete Assignment 1*grades:*5*5*5*7*assignment2:*average_grade: None*description: Complete Assignment 2*grades:*-*students:*student1*student2*studentabc*2019*None*10.5Custom IndentationsYou can also specify a custom indentation. The default is"\t", but you can specify" "or even a number of spaces.
Below is an example using2:className: ComputerScience
classId: 2020
assignments:
  assignment1:
    average_grade: 5.5
    description: Complete Assignment 1
    grades:
      5
      5
      5
      7
  assignment2:
    average_grade: None
    description: Complete Assignment 2
    grades:
      -
students:
  student1
  student2
  studentabc
  2019
  None
  10.5
Package: human_math
human_mathA mathematical expression parserExample usage>>>importhuman_mathashm# import module>>>tree=hm.parse("2 - (-sin(3pi/2)) - 3.0")# parse string (user input, etc.)>>>tree((2-(-1*sin(3*(pi/2))))-3)# console representation uses parentheses everywhere to be strictly non-ambigious>>>tree.evaluate()# evaluate the expression tree-2# nb: sin(3pi/2) = -1 so 2 - (-1) - 3 = -2
Package: humann
HUMAnN v3 is a pipeline for efficiently and accurately determining the coverage and abundance of microbial pathways in a community from metagenomic data. Sequencing a metagenome typically produces millions of short DNA/RNA reads. This process, referred to as functional profiling, aims to describe the metabolic potential of a microbial community and its members. More generally, functional profiling answers the question: What are the microbes in my community-of-interest doing (or capable of doing)?
Package: humann2
HUMAnN2 is a pipeline for efficiently and accurately determining the coverage and abundance of microbial pathways in a community from metagenomic data. Sequencing a metagenome typically produces millions of short DNA/RNA reads. This process, referred to as functional profiling, aims to describe the metabolic potential of a microbial community and its members. More generally, functional profiling answers the question: What are the microbes in my community-of-interest doing (or capable of doing)?
Package: human-name-compare
Human Name Comparethe Problem:Check ifDr. Peter MüllerandPeter K. MüllerandDr. med. Peter Karsten MüllerandP. Müllerindicate if its the same personThere are gazillion tiny bits and pieces which makes this trivial task hard e.g.:"R. Schönthal" "Robert Schönthal" - the only have initials on one side"Erik Schönthal" "Robert Schönthal" - the firstname name doesnt match"Robert Erik Schönthal" "Robert Peter Schönthal" - the middle name doesnt match"Robert-Erik Schönthal" "Robert Erik Schönthal" - we have an "-" in our firstnames"Robeert Schönthal" "Robert Schönthal" - the firstname has a typo"Robert Müller" "Robert Schönthal" - the lastname doesnt match"Herr Robert Müller" "Dr. med. Robert Schönthal" - we have some prefixesand so on...UsageCLI$hn-comparecompare"Robert Schönthal""Robert Schönthal"Pythonfromhuman_name_compareimportmatch_namematch_name("Robert Schönthal","Robert Schönthal")Tests$python-mpytest.
Package: human-parsing
Human Parsing SDK APIInstallation:pip install human_parsingInstall latest version before it's published on PyPipip install -U git+https://github.com/HumanParsingSDK/human_parsing_sdkSupported tasks:Person whole stature segmentationSample 1Sample 2Sample 3Weights storageWeights and models are hostedthereIt'll be download automatically to your<path to user home dir>/.human_parsingdirectory
Package: human-randgen
Human Random Number GeneratorThis is a simple package which makes it easy to generate random numbers with a distribution following human response times. It is possible to fine-tune the generator with existing data (e.g., time between mouse clicks).Installationpip install human_randgenUsageInitialize the generator with your choice of mode and standard deviation. These parameters depend on your use case. For example, if you are simulating a person clicking a mouse every 2 +- 1 seconds, you could try:from human_randgen.model import HumanRng

rng = HumanRng(mode=2, sigma=1)Generate random numbers using therand(num_samples=1)function:rng.rand()Finally, update the generator with existing data with thefitfunction:rng.fit([2.2, 1.8, 5.4, 2.1])This is useful if you are not sure what the mode and standard deviation should be during initialization.Calling thefitfunction will update the mode and standard deviation based on the data, and all following calls torandwill use the updated parameters. In addition, the updated values will be printed out to console. You can save them to reinitialize the generator with the fitted parameters from the onset.Thefitfunction can be called as many times as you want. The more data you pass to this function, the less influence your choice of initialization parameters will have.InternalsThe underlying distribution is lognormal, which is said to represent many human behaviors. During initialization, Newton's method is used to calculate the mean and variance of the lognormal distribution from the given parameters.For fitting, we add a normal-inverse-gamma distribution as the conjugate prior on the parameters and perform MAP estimation.
Package: humanreadable
humanreadableSummarySupported UnitesUsageConvert a human-readable value to another unitConvert a value to a human readable stringSet default unitUnitsInstallationInstallation: pipInstallation: apt (for Ubuntu)DependenciesSummaryhumanreadable is a Python library to convert human-readable values to other units.Supported Unitestime (days, hours, minutes, seconds, etc.)bits per secondUsageConvert a human-readable value to another unitSample Code:importhumanreadableashrprint("\n[Examples: humanreadable.Time]")value="120 sec"print(f"'{value}' to msecs ->{hr.Time(value).milliseconds}")print(f"'{value}' to minutes ->{hr.Time(value).minutes}")value="12 min 40 sec"print(f"'{value}' to seconds ->{hr.Time(value).seconds}")print("\n[Examples: humanreadable.BitsPerSecond]")value="1 Gbps"print(f"'{value}' to Mbps ->{hr.BitsPerSecond(value).mega_bps}")print(f"'{value}' to Kbps ->{hr.BitsPerSecond(value).kilo_bps}")print(f"'{value}' to Kibps ->{hr.BitsPerSecond(value).kibi_bps}")Output:[Examples: humanreadable.Time]
'120 sec' to msecs -> 120000.0
'120 sec' to minutes -> 2.0
'12 minutes 40 seconds' to seconds -> 760.0

[Examples: humanreadable.BitsPerSecond]
'1 Gbps' to Mbps -> 1000.0
'1 Gbps' to Kbps -> 1000000.0
'1 Gbps' to Kibps -> 976562.5Convert a value to a human readable stringSample Code:importhumanreadableashrt=hr.Time("400",default_unit=hr.Time.Unit.SECOND)print(t.to_humanreadable())print(t.to_humanreadable(style="short"))Output:6 minutes 40 seconds
6m 40sSet default unitUnit for an instance is determined by input value.
If a valid unit is not found,default_unitwill be used for the instance (defaults toNone).Sample Code:importhumanreadableashrprint(hr.Time("1",default_unit=hr.Time.Unit.SECOND))Output:1.0 secondsUnitsAvailable units forhumanreadable.TimeUnitAvailable unit specifiers (str)daysd/day/dayshoursh/hour/hoursminutesm/min/mins/minute/minutessecondss/sec/secs/second/secondsmillisecondsms/msec/msecs/millisecond/millisecondsmicrosecondsus/usec/usecs/microsecond/microsecondsAvailable units forhumanreadable.BitsPerSecondUnitAvailable unit specifiers (str)Kbps[kK]bps/[kK]bits?(/|\s?per\s?)(s|sec|second)Kibps[kK]ibps/[kK]ibits?(/|\s?per\s?)(s|sec|second)Mbps[mM]bps/[mM]bits?(/|\s?per\s?)(s|sec|second)Mibps[mM]ibps/[mM]ibits?(/|\s?per\s?)(s|sec|second)Gbps[gG]bps/[gG]bits?(/|\s?per\s?)(s|sec|second)Gibps[gG]ibps/[gG]ibits?(/|\s?per\s?)(s|sec|second)Tbps[tT]bps/[tT]bits?(/|\s?per\s?)(s|sec|second)Tibps[tT]ibps/[tT]ibits?(/|\s?per\s?)(s|sec|second)bpsbps/bits?(/|\s?per\s?)(s|sec|second)InstallationInstallation: pippip install humanreadableInstallation: apt (for Ubuntu)sudo add-apt-repository ppa:thombashi/ppa
sudo apt update
sudo apt install python3-humanreadableDependenciesPython 3.7+Python package dependencies (automatically installed)
Package: human-readable-ids
Human Readable IDPython library to generate a random human readable ID in the format of<adjective> <noun> <number 1-100>.Common UsageThis can be used any time you need a unique value that should be legible by humans (unlike a UUID).Currently this library only contains a single method:get_new_id()In[1]:importhuman_readable_idsIn[2]:human_readable_ids.get_new_id()Out[2]:'Short-term Painting 30'
Package: human-readable-time
# زمان خوانااین یک تابع پایتون است که عددی غیر منفی (ثانیه) را به عنوان ورودی می‌گیرد و زمان را بافرمت خوانا (ساعت:دقیقه:ثانیه) برمی‌گرداند.## چگونه استفاده کنیم1. مخزن را در دستگاه محلی خود کلون کنید.2. تابع `make_readable1` یا`make_readable2` را از ماژول `human_readable_time` وارد کنید.3. تابع `make_readable1` یا`make_readable2` را فراخوانی کنید و تعداد ثانیه‌ها را به عنوان آرگومان ارسال کنید.مثال:```pythonfrom human_readable_time import make_readable1 #OR make_readable2seconds = 3661result = make_readable1(seconds)print(result)  # خروجی: 01:01:01```## جزئیات تابعتابع `make_readable1` یا `make_readable2` ساعت، دقیقه و ثانیه را از تعداد داده شده ثانیه‌ها محاسبه کردهو آن‌ها را با رشته‌ی خوانا فرمت می‌کند. این تابع از تابع `divmod()` برای محاسبه کارآمد و f-string برایفرمت‌بندی خروجی با صفر اولیه استفاده می‌کند.# Human Readable TimeThis is a Python function that takes a non-negative integer representing the number of seconds andreturns the time in a human-readable format (HH:MM:SS).## How to Use1. Clone the repository to your local machine.2. Import the `make_readable1` OR `make_readable2` function from the `human_readable_time` module.3. Call the `make_readable1` OR `make_readable2` function and pass the number of seconds as an argument.Example:```pythonfrom human_readable_time import make_readable1 #OR make_readable2seconds = 3661result = make_readable1(seconds)print(result)  # Output: 01:01:01```## Function DetailsThe `make_readable1` OR `make_readable2` functions calculates the hours, minutes, and seconds fromthe given number of seconds and formats them in a human-readable string. It uses the `divmod()`function for efficient calculation and f-string for formatting the output with leading zeros.