Saravanan666/pypi-org huggingface dataset:
Package: columnize
In showing a long lists, sometimes one would prefer to see the value
arranged aligned in columns. Some examples include listing methods of an
object, listing debugger commands, or showing a numeric array with data
aligned.This is a Python module to format a simple (i.e. not nested) list into
aligned columns. A string with embedded newline characters is returned.Setup$ python
>>> import columnizeWith String dataEach column is only as wide as necessary. By default, columns are
separated by two spaces; one was not legible enough. Setcolsepto
adjust the string separate columns. Setdisplaywidthto set the line
width.>>> g = ('bibrons', 'golden', 'madascar', 'leopard', 'mourning', 'suras', 'tokay')
>>> print(columnize.columnize(g, displaywidth=15))
bibrons   suras
golden    tokay
madascar
leopard
mourning>>> print(columnize.columnize(g, displaywidth=19, colsep=' | '))
bibrons  | mourning
golden   | suras
madascar | tokay
leopard>>> print(columnize.columnize(g, displaywidth=18, colsep=' | ', ljust=False))
bibrons | suras
 golden | tokay
madascar
 leopardNormally, consecutive items go down from the top to bottom from the
left-most column to the right-most. Ifarrange_verticalis set false,
consecutive items will go across, left to right, top to bottom.With numeric data>>> print(columnize.columnize(['1', '2', '3', '4'], displaywidth=6)) # => '1  3\n2  4\n'
1  3
2  4>>> print(columnize.columnize(list(range(1,6)), displaywidth=8))
1  3  5
2  4By default entries are left justified:>>>  print(columnize.columnize(list(range(1,16)), displaywidth=10))1  6   11
2  7   12
3  8   13
4  9   14
5  10  15but you can change that withljustor ifarrange_arrayis set toTrue:>>>  print(columnize.columnize(list(range(1,16)), displaywidth=10, ljust=False))
1   6  11
2   7  12
3   8  13
4   9  14
5  10  15>>> print(columnize.columnize(list(range(1,5)), opts={'arrange_array':True, 'displaywidth':6}))
[1, 2
 3, 4]CreditsThis module (essentially one function) was adapted from a private method
of the same name from Python’scmdmodule. Some
adjustments and generalizations have been made.pycolumnize for enterpriseAvailable as part of the Tidelift Subscription.The maintainers of pycolumnize and thousands of other packages are working with Tidelift to deliver commercial support and maintenance for the open source dependencies you use to build your applications. Save time, reduce risk, and improve code health, while paying the maintainers of the exact dependencies you use.Learn more.Security contact informationTo report a security vulnerability, please use theTidelift security contactand Tidelift will coordinate the fix and disclosure.Other stuffAuthors: Rocky Bernsteinrb@dustyfeet.comLicense: MIT
Package: columnizer
columnizerThis is a simple package for which creates columnized text tables.  This is particularly useful where the text is of N length.  You can use the following example, to show a good set of uses. I find this code particularly useful in command line tools.from columnizer import *
def test_columns(columnizer):
    test_text = "the quick brown fox jumped over the lazy dogs!"
    column_count = len(columnizer.columns)
    test_rows = []
    if columnizer.first_row_headers:
        header_titles=["A","B","C","D","E","F","G","H"]
        test_rows.append(header_titles[:column_count])
    test_rows.append([test_text for _ in range(0,column_count)])
    result = columnizer.apply(test_rows)
    print (result)

c = Columnizer(
    columns=[ColumnClipped(width=25), ColumnLineWrap(width=17), ColumnWordWrap(width=17),
             ColumnWordWrap(alignment=ColumnTextAlignment.RIGHT, width=17),
             ColumnWordWrap(alignment=ColumnTextAlignment.CENTER, width=17)],
    style = ColumnTableStyleHeavy())

print ("Heavy:")
test_columns(c)

c = Columnizer(
    columns=[ColumnClipped(width=25), ColumnLineWrap(width=17), ColumnWordWrap(width=17),
             ColumnWordWrap(alignment=ColumnTextAlignment.RIGHT, width=17),
             ColumnWordWrap(alignment=ColumnTextAlignment.CENTER, width=17)])

print ("Default:")
test_columns(c)

print ("Default + Headers:")
c.first_row_headers = True
test_columns(c)Columns are actual classes, and are used to describe the physical size and style of the columns.
Rows are lists of lists, with each container list being used to store data for each column in the row.
Package: columnjump
ColumnjumpPerforms column jump detection on each ramp integration within a JWST NIRISS exposure to correct for jumps in columns. Note that 'columns' are defined in
original detector coordinates (not DMS coordinates) so appear in 3rd
axis of 4D data array. Uses modified version of algorithm documented in CSA-JWST-TN-0003.It is intended this module be run during the DETECTOR1 pipeline between the dark current subtraction and jump detection step.Version 1.1.0 removes a dependency on the jwst pipeline version
Package: column.py
This is a modern re-implementation of the venerable oldcolumnapplication
available on most Unix / Linux systems today.Why re-implement this ancient tool?BSDcolumnhas been, for many, the tool thatalmostworks for every
situation where we want to pretty-print a delimited table in textual form.
Unfortunately, it lacks two highly desirable features.It has no option to right-justify columns instead of left-justifying them.It has no option to specify the output delimiter, and has two spaces
hardcoded.Why not just modify the original code?The original code is over 20 years old, is written in a cryptic C style which
does not lend itself to easy modification, and uses the  compiler-dependentwchar_ttype is not actually wide enough for Unicode.Example Usage & OutputConsider the following  input file, namedSample.txt:Benchmark,Count,Avg,StdDev,Median,Min,Max
Core 1 to Core 2,3000000,125,431.937128,122,87,294738
Core 1 to Core 3,3000000,128,58.326363,123,87,54313
Core 2 to Core 1,3000000,129,323.379763,123,87,291708
Core 2 to Core 3,3000000,128,45.726372,123,74,37875
Core 3 to Core 1,3000000,128,42.615930,123,87,44093
Core 3 to Core 2,3000000,128,172.090219,122,78,266052Under traditionalcolumn, the output looks like this:$ column -t -s, Sample.txt
Benchmark         Count    Avg  StdDev      Median  Min  Max
Core 1 to Core 2  3000000  125  431.937128  122     87   294738
Core 1 to Core 3  3000000  128  58.326363   123     87   54313
Core 2 to Core 1  3000000  129  323.379763  123     87   291708
Core 2 to Core 3  3000000  128  45.726372   123     74   37875
Core 3 to Core 1  3000000  128  42.615930   123     87   44093
Core 3 to Core 2  3000000  128  172.090219  122     78   266052Withcolumn.py, the output looks like this with default options:$ column.py -s, Sample.txt
Benchmark           Count  Avg      StdDev  Median  Min     Max
Core 1 to Core 2  3000000  125  431.937128     122   87  294738
Core 1 to Core 3  3000000  128   58.326363     123   87   54313
Core 2 to Core 1  3000000  129  323.379763     123   87  291708
Core 2 to Core 3  3000000  128   45.726372     123   74   37875
Core 3 to Core 1  3000000  128   42.615930     123   87   44093
Core 3 to Core 2  3000000  128  172.090219     122   78  266052
Package: columns
PRINT A LIST IN COLUMNSDoes what it says on the tin.Print a list in columns based on the size of the current terminal, favoring
vertical space over horizontal, i.e) use all available vertical space before
creating additional columns.INSTALLATIONpip install columnsCLI USAGEusage: columns [-h] list [list ...]

Print a list in columns.

positional arguments:
  list        A list to print.

optional arguments:
  -h, --help  show this help message and exitEXAMPLEScolumns items{0..256}columns $(shuf -n 100 /usr/share/dict/words)
Package: com2ann
Tool for translation of type comments to type annotations in Python.This tool requires Python 3.8 to run. But the supported target code version
is Python 3.4+ (can be specified with--python-minor-version).Currently, the tool translates function and assignment type comments to
type annotations.The philosophy of of the tool is too minimally invasive, and preserve original
formatting as much as possible. This is why the tool doesn’t use un-parse.
Package: coma
ComaConfigurablecommandmanagement for humans.Key Featurescomamakes it easy to build configurable command-based programs in Python by:Removing the boilerplate ofargparse, while retaining fullargparseinteroperability and customizability for complex use cases.Providing a comprehensive set ofhooksto easily tweak, replace, or extendcoma's default behavior.Integrating withomegaconf's extremely rich and powerful configuration management features.Installationpip install comaGetting StartedThedocumentationon ReadTheDocs includes a shortintroductory tutorialand much more!
Package: comala-workflows
Comala Workflow Python LibraryThis is a simple wrapper around the REST API which the Comala Workflow
plugin for Confluence provides.InstallationTo install from pypi use:pip install comala-workflowsUsagefromcomala.workflows.clientimportComalaWorkflowsClientwithComalaWorkflowsClient("https://server:port/contextpath",("user","pass"))asclient:status=client.status(page_id=1,expand=['state','states','approvals','actions','tasks'])Development and DeploymentSee theContribution guidelines for this projectfor details on how to make changes to this library.
Package: coman
CoMan: Conda ManagerA simple CLI for Conda dependency management. CoMan gives you simple commands to manage dependencies in yourenvironment.ymland properly uses lock files. Moreover, it manages unique Conda environments per project directory. CoMan mimicks the workflow ofPoetry(or any other modern dependency manager), but then for Conda.Warning:CoMan is work in progress and may not work in every scenario.CoMan manages:environment.yml:add/removedependencies with version constraintsconda-{platform}.lock:(multi-platform) lock files for reproducable environmentsrequirements.txt:(optional) pinned pip dependencies fromenvironment.yml{CONDA_ROOT}/envs/{basename}-{hash}:unique environments for your project in your default environments directoryInstallationThere is currently no CoMan conda recipe. CoMan is designed to work independently of Conda, so that it can install and run Conda environments on any system (with Micromamba).pipinstall-Ucoman# pipx (recommended)# make sure that pipx uses the python environment in which conda is installed (the conda base environment) if you have those installedcondaactivatebase
pipxinstall-e--pythonpythoncomanLatest development versionpip install --user --upgrade git+https://github.com/wietsedv/coman.gitDevelopmentgitclonegit@github.com:wietsedv/coman.gitcdcoman&&pipinstall-e.Quick startcdprojects/MyProject# "cm" is short for "coman"; use the command you prefer# show system and environment statuscminfo# create environment.yml and lock filecminit# install the environmentcminstall# add "requests" dependency to environment.yml, the lock file(s) and your installed environmentcmaddrequests# show the installed packagescmshow# run a command (use -- to avoid argument conflicts)cmrun--python--version
cmpython----version# available for bash and pythoncoman-python--version# available for bash and python# activate your environment in your current shell (at least works with bash and zsh)cmshell
Package: comanage_nacha
pipinstallcomanage_nachafromcomanage_nachaimportNachaFilewithNachaFile(company_name='COMANAGE LLC',file_id_modifier='A',file_creation_date=datetime.date.today(),file_creation_time=datetime.datetime.utcnow())asnacha:withnacha.add_batch(service_class_code=200,company_name='COMANAGE LLC',company_id='0123456789',effective_entry_date=datetime.date.today())asbatch:batch.add_entry(transaction_code=22,receiving_dfi_routing_number='09100001',routing_number_check_digit=0,receiving_dfi_account_number='0123456789',amount=10000,individual_id='123',individual_name='FRANK')print(nacha.render_to_string())nacha_string=nacha.render_to_string()Authors:Franklyn Tackitt @kageurufu
Package: comandor
ComandorVery Simple Script for Run your command!A simple tool to simplify some repetitive
tasks such as updating the Linux repository and daily tasks!How Installpip install comandorHow Usemake file .comandorsetup config like this (json file){"name":"Update Apps!","debug":true,// run debug mode ( not necessary )"logfile":"./logs.log",// where save logs ( not necessary )"actions":[{"action_name":"scoop update pkg","path":"C:/","commands":["scoop update -g *"],"timeout":5000}// you can add more action]}OR yaml file:name:"testrundcommand"debug:truelogfile:"./logs.log"actions:-action_name:"test12"path:"."commands:-"cd."timeout:5000you can see .comandor.example for more exampleand run this commandcomandorCommand Line Help❯ comandor -h
usage: comandor [-h] [-l LOGFILE] [-c CONFIG] [-d] [-sk SKIP]

options:
  -h, --help            show this help message and exit
  -l LOGFILE, --logfile LOGFILE
                        where save logfile
  -c CONFIG, --config CONFIG
                        where you have config file
  -d, --debug           run debug mod
  -sk SKIP, --skip SKIP
                        skip with text,check text and if found match skipHow run tests?python -m unittest  test/test_comandor.py
Package: comantivirus
# text to audio file converter by python
I make a Python based light weight Computer Anti-Virus. You can you this project, by installing this Anti - Virus package by running those commands that embedded below.To run this project , first run :-pip install comantivirusNow, for use this package, you need some packages.to use thease package, install this packages first :-pip install timepip install ospip install pyautoguiafter run those commands, run command :-make a file in anyware in desktop. ex; ‘xyz.py’.after making thease file, insert this line to the file :-from comantivirus import startthen, call the main function via :-start()then a GUI has open.now follow the GUI instructions and convert a text massage into a audio file & save in your desktop.You can download & install this project for free but to use this package, you need Access key. To get Access key, visit this link to buy Access Key :-https://ankansaha.web.app/html/buyaccesskey.html
Package: comapsmarthome-postgres-client
Provides basic postgres functions for databases request.select:defget_my_data():def_(cursor):cursor.execute(f"select data from database")returncursor.fetchone()result=select(_)returnresult.get('data')ifresultelseNoneinsert:definsert_my_data():data={'data_1':data_1,'data_2':data_2}insert(TABLE_NAME,data)update:
the primary key can be a string for array who have only one primary key but if it's a tuple,
you can put a table of string : ['first_primay_key', 'second_primay_key']defupdate_my_data():data={'data_1':data_1,'data_2':data_2}update(TABLE_NAME,'my_primary_key',data)upsert:
Upsert is a function who insert if the data doesn't exist. And update if the data can be updated.
the primary key can be a string for array who have only one primary key but if it's a tuple,
you can put a table of string : ['first_primay_key', 'second_primay_key']defupsert_my_data():data={'data_1':data_1,'data_2':data_2}upsert(TABLE_NAME,'my_primary_key',data)delete:defdelete_my_data():delete(TABLE_NAME,primary_key,data_id)
Package: comapsmarthome-public-api
COMAP Smart Home public APIPython module to control and retrieve data for COMAP Smart Home products.InstallTo installcomapsmarthome-prublic-apirun :pip install comapsmarthome-public-apiUsage examplefromcomapsmarthome_public_api.client_authimportClientAuthfromcomapsmarthome_public_api.measurement_serviceimportMeasurementsServiceauth=ClientAuth()measurements=MeasurementsService(auth)dt_from='2020-10-01T09:30+01:00'dt_to='2020-10-01T10:30+01:00'serial_number='aa**********'data=measurements.get_measurements(dt_from,dt_to,serial_number=serial_number,measurements=['inside_temperature'])dates=[d['time']fordindata]temperatures=[d['inside_temperature']fordindata]CredentialsTo access COMAP Smart Home product through the API,usernameandpasswordneed to be saved under the environment variablesCOMAP_SMART_HOME_USERNAMEandCOMAP_SMART_HOME_PASSWORD.COMAP_SMART_HOME_USERNAME: COMAP Smart Home user email addressCOMAP_SMART_HOME_PASSWORD: COMAP Smart Home user passwordRequirementsPython >=3.6requests, boto3 and dateutil modulesCOMAP Smart Home user account
Package: comath
A small pure-python package for math-related utility functions.>>>fromcomath.arrayimportpercentile>>>percentile([4,6,8,9,11],0.4)7.0Contents1Installation2Use2.1array2.2func2.3metric2.4segment3Contributing3.1Installing for development3.2Running the tests3.3Adding documentation4Credits1InstallationInstallcomathwith:pipinstallcomath2Usecomathis divided into four sub-modules.2.1arrayArray operations like percentile and median.2.2funcUtility function like a smooth step function and closest larger power of 2.2.3metricComputing moving metrics (moving average, precision and variance).2.4segmentDefines a one-dimensional line segment.3ContributingPackage author and current maintainer is Shay Palachy (shay.palachy@gmail.com); You are more than welcome to approach him for help. Contributions are very welcomed.3.1Installing for developmentClone:gitclonegit@github.com:shaypal5/comath.gitInstall in development mode with test dependencies:cdcomathpipinstall-e".[test]"3.2Running the testsTo run the tests, use:python-mpytest--cov=comath--doctest-modules3.3Adding documentationThis project is documented using thenumpy docstring conventions, which were chosen as they are perhaps the most widely-spread conventions that are both supported by common tools such as Sphinx and result in human-readable docstrings (in my personal opinion, of course). When documenting code you add to this project, please followthese conventions.4CreditsCreated by Shay Palachy  (shay.palachy@gmail.com).
Package: comaze-gym
CoMaze GymAn OpenAI Gym-compatible implementation of the zero-shot coordination and communication benchmark game CoMaze.DescriptionFor an exhaustive description of the game, please refer tothis page.Usagegymmust be installed. An Kuhn's poker environment can be created via running inside apythoninterpreter:>>>importgym>>>importcomaze_gym>>>env=gym.make('CoMaze-7x7-Sparse-v0')InstallationInstalling via pipThis package is available in PyPi ascomaze-gympipinstallcomaze-gymInstalling via cloning this repositorygitclonehttps://www.github.com/Near32/comaze-gymcdcomaze-gym
pipinstall-e.
Package: comb
comb, A simple and high-performance framework for create parallel programUpgrade notesVersion 0.9.xAdd--no-daemonoption.User interrupt directly when user specific--debugoption.change--sleepdata type to float in python3.update documentimprove setup.py filesupport safety user interrupt.support python3Add--onceoption. execute once and exit instead of wait.As of Comb 0.8.99, we change--sleep_maxoption to--sleep-max.change comb script install path,use python library path instead /usr/local/binQuick linksDocumentationSource (github)InstallationAutomatic installation:pip install combcomb is listed inPyPIand
can be installed withpiporeasy_install.
it includes demo applications.Manual installation: Download the latest source fromGithub.git clonehttps://github.com/nextoa/comb.gitcd comb
python setup.py build
sudo python setup.py installThe comb source code ishosted on GitHub.Prerequisites: comb was only test on Python 2.7.  It may be runs on
all Python versions.How to useTo use comb, you should create a python module file. we namedslot.A legal slot must be named ‘Slot’ in your module file and it must be at least contain four method:initializeinitial resource, e.g: database handle__enter__get next data to do,you can fetch one or more data.slotuser custom code__exit__when slot finished, call this methodSlot DemoDeal List DataDeal Mongo MQRecycle Mongo MQCustom Slot optionsStartExecute a comb is very simple. just execute:comb --root SLOT_ROOT_PATH  slot-package.slot-moduleif you setSLOTPATHenvironment, you can use:comb slot-package.slot-moduleQuick View. call:comb   comb.demo.listthis will execute theDeal List DemoNote for production deploymentYou’d better make comb process number equals your cpu core number.We strongly recommend you use comb withsupervisor
Package: combadge
CombadgeCombadge generates a service client implementation from a user service interface
declared by aprotocolclass or an abstract base class.DocumentationSneak peekfromtypingimportListfromhttpximportClientfrompydanticimportBaseModel,Fieldfromtyping_extensionsimportAnnotated,Protocolfromcombadge.support.http.markersimportQueryParam,http_method,pathfromcombadge.support.httpx.backends.syncimportHttpxBackend# 1️⃣ Declare the response models:classCurrentCondition(BaseModel):humidity:inttemperature:Annotated[float,Field(alias="temp_C")]classWeather(BaseModel):current:Annotated[List[CurrentCondition],Field(alias="current_condition")]# 2️⃣ Declare the protocol:classSupportsWttrIn(Protocol):@http_method("GET")@path("/{in_}")defget_weather(self,*,in_:str,format_:Annotated[str,QueryParam("format")]="j1",)->Weather:raiseNotImplementedError# 3️⃣ Bind the service:withHttpxBackend(Client(base_url="https://wttr.in"))[SupportsWttrIn]asservice:# 🚀 Call the service:response=service.get_weather(in_="amsterdam")assertresponse.current[0].humidity==71assertresponse.current[0].temperature==8.0
Package: combat
pyComBatpyComBat [1] is a Python 3 implementation of ComBat [2], one of the most widely used tool for correcting technical biases, called batch effects, in microarray expression data.More detailed documentation can be found atthis address.TO DOMinimum dependenciesWe list here the versions of the packages that have been used for development/testing of pyComBat, as well as for writing the documentation.pyComBat dependenciespython 3.6numpy 1.18.5mpmath 1.1.0pandas 0.24.2patsy 0.5.1Documentationsphinx 2.1.2Usage exampleInstallationYou can install pyComBat directly with:pipinstallcombatYou can upgrade pyComBat to its latest version with:pipinstallcombat--upgradeRunning pyComBatThe simplest way of using pyComBat is to first import it, and then simply use the pycombat function with default parameters:fromcombat.pycombatimportpycombatdata_corrected=pycombat(data,batch)data: The expression matrix as a dataframe. It contains the information about the gene expression (rows) for each sample (columns).batch: List of batch indexes. The batch list describes the batch for each sample. The list of batches contains as many elements as the number of columns in the expression matrix.How to contributePlease refer toCONTRIBUTING.mdto learn more about the contribution guidelines.References[1] Behdenna A, Haziza J, Azencot CA and Nordor A. (2020) pyComBat, a Python tool for batch effects correction in high-throughput molecular data using empirical Bayes methods. bioRxiv doi: 10.1101/2020.03.17.995431[2] Johnson W E, et al. (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8, 118–127
Package: combidata
CombidataCombidata is a case-oriented library designed for compositional testing of combinatorics in IT product functionalities.Installationpip install combidataTable of ContentsInstallationAll entitiesProcessCasesCombinationDataGeneratorQuick Start GuideOverviewCombidata provides a comprehensive solution for compositional testing, allowing users to efficiently test various combinations of functionalities in IT products. With its unique approach to case-oriented testing, Combidata streamlines the testing process, ensuring robust and reliable results.FeaturesCase-Oriented Testing: Focus on specific test cases to ensure thorough testing of functionalities.Compositional Testing: Test combinations of functionalities to ensure interoperability and compatibility.Efficient Workflow: Streamlined processes for test generation, execution, and reporting.Extensive Documentation: Comprehensive guides and tutorials to help you get started and make the most of Combidata.Getting StartedTo get started with Combidata, visit ourQuick Start Guidewhich provides step-by-step instructions on setting up and using the library.SupportIf you need help with Combidata or have any questions, please open an issue on GitHub or contact the maintainers directlyTelegram вЂ”https://t.me/sasisochkaLinkedin вЂ”https://www.linkedin.com/in/yasasisochka/LicenseCombidata is licensed underMIT License.