Saravanan666/pypi-org huggingface dataset:
Package: ascend-great-expectations-gcs
Ascend.io / Great Expectations docker image for Google Cloud storageThis image is a wrapper around official Ascend.io image to use Great Expectations validation tool.Build the docker imageThe image is built with Github action located in this file :  .github/workflows/docker-build.yaml.For now the image is pushed on docker hub at this address: fosk06/ascend-great-expectations-gcs:latestThe image is build on push on main branch and with git tag with the following form "v{X}.{Y}.{Z}"With:X = Major versionY = Minor versionZ = Correction versionUse it on ascend.io platformThis docker image is built for PySpark transforms on Ascend.io platform.
First you need a Google cloud storage bucket named for example "great_expectations_store" and a service account with the role "storage.admin" on this bucket.
Then upload this service account as a credentials on your Ascend.io instance and name it for example "great_expectations_sa".Now you can create your PySpark transform on Ascend.io.
In the advanced settings> Runtime settings > container image URL set the correct docker hub image url : fosk06/ascend-great-expectations-gcs:latestThen in the "Custom Spark Params" click on "require credentials" and chose you credential previously uploaded "great_expectations_sa".Write the PySpark transform# import the custom packagefromascend_great_expectations_gcs.validatorimportValidator# lets admit we are working on a "customer" table, write the expectations in specific functiondefexpectations(validator):validator.expect_column_to_exist("customer_id")validator.expect_column_values_to_not_be_null("customer_id")validator.expect_column_to_exist('created_at')# Ascend.io transform callbackdeftransform(spark_session:SparkSession,inputs:List[DataFrame],credentials=None):df=inputs[0]# instanciate the validatorvalidator=Validator(name=NAME,# name of the validatorgcp_project=PROJECT,# your GCP projectbucket=BUCKET,# the name of your GCP bucket, for example "great_expectations_store"credentials=credentials,# credentials from the transform callback)validator.add_expectations(expectations)validator.run(df)returndftest the classcreate a virtual env
then in ./venv/lib/python3.9/site-package write those two filesascend_great_expectations_gcs_test.pth => set you package folder path
ascend_great_expectations_gcs.pth => set you package folder path herehttps://webdevdesigner.com/q/how-do-you-set-your-pythonpath-in-an-already-created-virtualenv-55773/git tag -d v1.4.1
git push --delete origin v1.4.1
Package: ascend-io-cli
This package contains theAscend CLI. The
CLI is designed to make working with the Ascend.io platform simple and easy. This CLI
wraps theAscend Python SDK.Get help by passing--helpinto any command for a rundown of the syntax for each command.:ascend --helpMake sure you are running the most current version and see what version of theascend-io-sdkand platform you are using:ascend versionThe CLI can save default values for certain parameters. For example, to set a default hostname:ascend config set hostname my-ascendhost.company.ioRemoving a default is as simple as:ascend config unset hostnameAuthenticationYou will want to download your API key from the Ascend UI.Here is some documentationthat shows you how to get your key. Please keep your key secure!Read the DocsAscend.io Python SDK DocumentationAscend Developer HubAscend.io
Package: ascend-io-sdk
This package contains theAscend Python SDK. This SDK is used to script the management of theAscend.ioData Automation Platform. The SDK can be used to create your own customizations of the
platform configuration, integrate with   CI/CD or other tools, as well as fully automate your environment.Automation.Integrate Ascend with any combination of workflow and/or CI/CD tools your organization uses on a daily basis.Transparency.Ascend deploys within your Cloud tenant (GCP, AWS, Azure) so you can see everything the platform is doing.Control.Manage your Ascend Platform, build dataflows, extract metadata, and more in a completely programmatic wayGet StartedYou will need access to an Ascend.io installation. Developers cansign up for a free trial.
If you are already an Ascend customer, have your administrator add you to the platform.Once you have access to the Platform,create your developer API Access Keysandconfigure your local authentication file. Remember to change
the wordtrialin your local authentication file to the name of your Ascend.io instance.Install the python library usingpip:$ pip3 install ascend-io-sdkStart writing your automations with thePython Client.Run the ExamplesIf running some sample code works for you, try out the Ascend Python SDK by listing the dataflows
within your Ascend instance:from ascend.sdk.client import Client
from tabulate import tabulate

hostname = 'my-host-name'
client = Client(hostname)
services = []
for ds in client.list_data_services().data:
    services.append([ds.id, ds.name, ds.created_at, ds.updated_at])

print(tabulate(sorted(services, key=lambda x: x[1]), headers=["id", "name", "created at"]))We release updates to the SDK all the time. If some features are missing, you get stuck, or you find
something that you don’t think is right, please let us know. We’re here to make the developer experience
as easy and enjoyable as possible. We know that fabulous Developer Relations is key!Read the DocsAscend.io Python SDK DocumentationAscend Developer HubAscend.io
Package: ascendpbm-package
This is a growing library intended to make use of other python packages streamlined and scaleable for ascendpbm. It is to include tools for interfacing with FTP, SFTP, FTPS, email, Microsoft Graph API, PostgreSQL, bash scripts, reporting infrastructure/packages, and much more. Please note that it will require several unlisted dependencies and requirements such as our business environments, Anaconda installations, and many python packages.
Package: aschot-pulumi-dbtcloud
dbt Cloud Resource ProviderThe dbt Cloud Resource Provider lets you manage dbt Cloud resources.InstallationThis package is available for several languages/platforms:Node.js (JavaScript/TypeScript)To use from JavaScript or TypeScript in Node.js, install using eithernpm:npminstall@achot/pulumi_dbtcloudoryarn:yarnadd@achot/pulumi_dbtcloudPythonTo use from Python, install usingpip:pipinstallaschot-pulumi-dbtcloudGoTo use from Go, usego getto grab the latest version of the library:gogetgithub.com/a-schot/pulumi-dbtcloud/sdk/go/dbtcloud.NETTo use from .NET, install usingdotnet add package:dotnetaddpackageASchot.Pulumi.DbtcloudConfiguration OptionsUsepulumi config set dbtcloud:<option> (--secret).OptionEnvironment VariableRequired/OptionalDefaultDescriptiontokenDBT_CLOUD_TOKENRequiredThe API token for your dbt Cloud useraccountIdDBT_CLOUD_ACCOUNT_IDRequiredThe ID for your dbt Cloud accounthostUrlDBT_CLOUD_HOST_URLOptionalhttps://cloud.getdbt.com/apiThe host URL for your dbt Cloud account
Package: ascify
SummaryThis is a lightweight library for turning images to grid of ascii tokens.
Visual example:InstallationThe simplest and recommended way to install this package is to install
it with PyPI:pip install ascifyTo install from source, do:git clone https://github.com/theonekeyg/ascify.git && cd ascify
pip install .UsageBasic usageThe simplest usage, with only default parameters would look like this:fromascify.gridimportAsciiGridgrid=AsciiGrid("./sample_image.png")grid.start()print(grid)ConfigurabilityAscify framework is highly configurable, you can change output grid size,
size of the moving window through the original image, output ascii tokens and
logic behind choosing tokens for particular window (which i call renditions).
All renditions take numpy.array of size (step, step, 3) as their first parameter,
which represents the moving window at certain position on the image.
Examples of implemented renditions can be found in./ascify/renditions.pyfile. For instance, default rendition looks the following:defdefault_rendition(img_slice,ascii_tokens):forchar,thresholdinascii_tokens.items():if(img_slice.mean()>=threshold):returncharBesides of configuring rendition itself, you can configure ascii tokens, used
for the output ascii grid. The tokens are passed directly to the rendition and
don't participate in any other part of ascify, so the format of ascii tokens
depends only on the logic of corresponding rendition used with it.However, if you use one of the default renditions, the expected tokens format
is object with implemented__getitem__method, keys to which represens tokens
themselves, and values represent threshold values. The default token dictonary
looks the following:default_tokens={"@":200,"#":155,"&":100,"*":50,".":0}
Package: ascii2graph
ascii2graphConverts ASCII text to a graph (represented as a dictionary of connections and
angles). It can represent directed and undirected graphs.Installation$pipinstallascii2graphExamplefromascii2graphimportgraphtext=r'''a->boo^   |   x|   v  /c<--d-e| |f-g'''result=graph(text)print(result)This produces the following graph (dictionary):result={(1,4,'a'):[(1,7,'boo',90)],(4,4,'c'):[(1,4,'a',0)],(4,8,'d'):[(4,4,'c',270),(4,10,'e',90),(6,8,'f',180)],(4,10,'e'):[(2,12,'x',45),(4,8,'d',270),(6,10,'g',180)],(2,12,'x'):[(4,10,'e',225)],(6,8,'f'):[(6,10,'g',90),(4,8,'d',0)],(6,10,'g'):[(6,8,'f',270),(4,10,'e',0)],(1,7,'boo'):[(4,8,'d',180)]}Nodes can be anything that is not one of these characters:- | / \ v ^ < >There is one exception (sorry!): If "/" is part of[sometext/foo], then it is not interpreted
as an edge. The reason is that I needed this to visualize Git branches and Git history where I needed[origin/somebranch].Use caseI use it inhttps://github.com/bast/gitinkto create SVG graphics for teaching
Git DAGs from plain text files because it is so easy to change a text file and
simply generate a new SVG image. This module helps me to obtain a graph
representation that I can use somewhere else to generate graphics.
Package: ascii-animator
ascii-animatorA simple ASCII text animator.Theascii-art-animatorCLI will take as input a GIF image, extract all the frames from it, convert each frame to ASCII art usingascii-magic, then display each frame to the terminal usinglist2term.Installationpipinstallascii_animatorUsageusage: ascii-art-animator [-h] [-s SPEED] [-f FILE] [-d] [-a] [-m MAX_LOOPS] [-c COLUMNS]

Ascii Art Animator from GIF

optional arguments:
  -h, --help            show this help message and exit
  -s SPEED, --speed SPEED
                        speed of the animation: very_slow, slow, normal, fast (default normal)
  -f FILE, --file FILE  the path to a gif file
  -d, --debug           display debug messages to stdout
  -a, --show_axis       display the grid axis
  -m MAX_LOOPS, --max_loops MAX_LOOPS
                        maximum number of loops, set to 0 to loop through image until keyboard interrupt (default 1)
  -c COLUMNS, --columns COLUMNS
                        the number of characters per row (default 150)ExamplesASCII Art AnimatorUseascii-art-animatorto convert the followingGIF imageto an ascii animation and demonstrate the use of the optional arguments.show x and y axisloop through the image 3 timesset columns to 100 charactersascii-art-animator-fdocs/images/marcovich.gif-a-m3-c100Equalizer Bars AnimationCreate an animation by subclassing theAnimationclass to resemble symmetrical equalizer bars and display it to the terminal using theAnimatorclass.Matrix AnimationCreate an animation by subclassing theAnimationclass to resemble the Matrix and display it to the terminal using theAnimatorclass.Game-Of-LifeA Conway Game-Of-Life implementation that usesascii_animatorto display the game to the terminal.DevelopmentClone the repository and ensure the latest version of Docker is installed on your development server.Build the Docker image:dockerimagebuild\-tascii-animator:latest.Run the Docker container:dockercontainerrun\--rm\-it\-v$PWD:/code\ascii-animator:latest\bashExecute the build:pyb-X
Package: ascii_art
_ _              _
  __ _ ___  ___(_|_)   __ _ _ __| |_
 / _` / __|/ __| | |  / _` | '__| __|
| (_| \__ \ (__| | | | (_| | |  | |_
 \__,_|___/\___|_|_|  \__,_|_|   \__|Draw ascii art(bar, chart, histogram) in your terminal. We love terminal, right? :)Install$ pip install ascii_artUsagesee examples folder.ContributeIt sucks? Why not help me improve it? Let me know the bad things.Want a new feature? Feel free to file an issue for a feature request.Find a bug? Open an issue please, or it’s better if you can send me a pull request.Contributions are always welcome at any time! :sparkles: :cake: :sparkles:KudosIt’s a python port of the originalchart,barsandhistogram, all the glories should belong totj.LicenseMIT ©lord63.
Package: asciiartist
Ascii ArtistAn ascii art generator that's actually good.
Does edge detection and selects the most appropriate characters.InstallingInstalling with pip:pip install asciiartistInstalling from wheel:Download the wheel file from this project's releases and runpip install <path/to/wheel>Quick Startfromasciiartistimportasciiartist,display_edgesfromPILimportImageimg=Image.open("niko.png")art,edges=asciiartist(img,# The image!30,# Number of lines of the output ascii artnoise_reduction=2,# Level of noise reduction (optional)line_weight=1,# Weight of the lines to draw (optional)text_ratio=2.2# Height/width ratio of each character (optional))print(art)# `art` is a string u can just print# v Display the result of edge detection.#   Good for finetuning params.display_edges(edges)Build from SourceRun the script./model/model-gen.pyand build the wheel withpoetry build -f wheel.How it worksRoughly, howAscii Artistgenerates the drawings:Run edge detectionSegment the image for each charPass each segment through aCNNto get the most appropriate character.The CNN is trained with distorted images of characters (in font consolas),
created in a way that emulates the output of the edge detection.Bye^-^__=E.L__      
                                        >#-=@>@F* `<_   
                                      _/`@o<FTFC@[_~_.__
                                   _./`\_`<__      @@7*`
                              _,~``      *v `^L_  )(    
                         _,~^C___ _    ````*@```````    
                   __,;@"*'`C` *@@_       _-V           
               __,@'^`CC)-[_L-----o,,}<@F--             
    __,-Ec>C<4@'C`'`"-[_,/   _,L-L             ,"       
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                        _   _           __~``           
                        ``  "<`  _                      
                              `(V\_                     
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                   _____,,~~<7oEE(@@_Eo@@Fo,            
       ___,-~-^````               .-.__V)  ,_
Package: asciibars
asciibarsasciibarsis a Python module for plotting bar charts in ASCII.How to install itpip install asciibarsHow to use itImport the module:import asciibarsDefine your data with both labels and counts:data_p = [
    ('Gigi',        64  ),
    ('Carletto',    12  ),
    ('Silvio',      0   ),
    ('Priscilla',   30  ),
    ('Rodolfo',     57  ),
    ('Sigismondo',  70  )
]Generate your bar chart in ASCII:asciibars.plot(data_p)The command above will print:Gigi       | 64 ██████████████████
Carletto   | 12 ███
Silvio     |  0 ▏
Priscilla  | 30 █████████
Rodolfo    | 57 ████████████████
Sigismondo | 70 ████████████████████Arguments of asciibars.plotInputTypeDescriptiondata[(str, float)]data array with labels and countsep_lcstrlabel-count separatorunitstrstring unit for barzerostrstring for bar when equal to zeromax_lengthintmaximum bar length in plotneg_unitstrnegated bar unit (e.g., '░')neg_maxintmaximum value when negated bar is usedcount_pfstrcount postfix (e.g., '%')ExamplesPlease find more examples below.asciibars.plot(data_p,sep_lc=' -> ',unit='▓',max_length=40)

Gigi       -> 64 ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓
Carletto   -> 12 ▓▓▓▓▓▓▓
Silvio     ->  0 ▏
Priscilla  -> 30 ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓
Rodolfo    -> 57 ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓
Sigismondo -> 70 ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓asciibars.plot(data_p,unit='▓',neg_unit='░')

Gigi       | 64 ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓░░
Carletto   | 12 ▓▓▓░░░░░░░░░░░░░░░░░
Silvio     |  0 ░░░░░░░░░░░░░░░░░░░░
Priscilla  | 30 ▓▓▓▓▓▓▓▓▓░░░░░░░░░░░
Rodolfo    | 57 ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓░░░░
Sigismondo | 70 ▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓asciibars.plot(data_p,unit='▓',neg_unit='░',neg_max=100,count_pf='%')

Gigi       | 64% ▓▓▓▓▓▓▓▓▓▓▓▓▓░░░░░░░
Carletto   | 12% ▓▓░░░░░░░░░░░░░░░░░░
Silvio     |  0% ░░░░░░░░░░░░░░░░░░░░
Priscilla  | 30% ▓▓▓▓▓▓░░░░░░░░░░░░░░
Rodolfo    | 57% ▓▓▓▓▓▓▓▓▓▓▓░░░░░░░░░
Sigismondo | 70% ▓▓▓▓▓▓▓▓▓▓▓▓▓▓░░░░░░
                                 100%data_pn = [
    ('One',     64  ),
    ('Two',     38  ),
    ('Three',   0   ),
    ('Four',    -18 ),
    ('Five',    -30 )
]

asciibars.plot(data_pn,sep_lc=' ',count_pf='%')

One    64%       ██████████████
Two    38%       ████████
Three   0%       ▏
Four  -18%   ████
Five  -30% ██████Change logPlease find the change loghere.AcknowledgmentsThanks to:Alexfor inspiring this work withthis blog post.Jinhang Jiangfor the tutorial onhow to publish your first Python package.CHANGELOGThe dates are reported as YYYY-MM-DD.Version 0.0.1 2022-12-26Alpha releaseVersion 0.0.2 2022-12-26Improved readmeVersion 0.0.3 2022-12-26README: added pip install command
Package: asciibee
<(||')asciibee<(||')An image-to-ascii-art converterDescriptionThe default settings are tuned to work best with fine art. Play with different
shaders, chunk sizes, and value inversion for different results. Remember to
decrease your font size if you can't see the whole image.Scaling is accomplished by dividing the image into chunks and converting each
chunk to a single character. The chunk size can be adjusted with the -c flag.
The chunk size defaults to the pixel width of the image divided by 100. The
output will tell you what chunk size was used.Installation$ pip install asciibeeUsageThe best way to learn how to use the app is via the help text:$ asciibee --helpThe most simple command is passing in a path to an image file:$ asciibee ~/Downloads/starrynight.pngYou can use it as an importable module as well.fromasciibee.imageimportAsciiImageimage=AsciiImage('/Users/jnakama/Downloads/port.jpeg')image.convert()# Converts the image to a matrix of ASCII charactersimage.ascii_matrix# It's stored hereimage.show()# Prints the charactersDevelopmentThe build system and package manager ispoetry.The easiest way to run the app locally:$ poetry run python -m asciibee.main <path_to_image>You can also install the deps and run it without thepoetry runprefix....         .....             ......
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                                     ...-##@#+-...
                                        ..--...
Package: ascii-canvas
Treat Strings like Items on a 2D CanvasWith this primitive library you can do things like this:fromascii_canvasimportcanvasfromascii_canvasimportitemcanvas_=canvas.Canvas()rect_a=item.Item('+-----+\n|Hello|\n+-----+',position=[0,0])rect_b=item.Item('+-----+\n|World|\n+-----+',position=[16,5])rect_c=item.Item('+-+\n|!|\n+-+',position=[32,0])line_a=item.Line(start=[7,1],end=[15,6])line_b=item.Line(start=[23,6],end=[31,1])canvas_.add_item(rect_a)canvas_.add_item(rect_b)canvas_.add_item(rect_c)canvas_.add_item(line_a)canvas_.add_item(line_b)print(canvas_.render())Which results in this output:+-----+                         +-+
|Hello|----+               +----|!|
+-----+    |               |    +-+
           |               |
           |               |
           |    +-----+    |
           +----|World|----+
                +-----+
Package: asciicast2movie
generate movie (video clip) from asciicastCan be used as command line tool for convert asciicast file to video files:asciicast2movie.py input_asciicast_file.cast output_video_file.mp4Can be also imported as a module and contains functions:* asciicast2video - convert asciicast data to moviepy video clipRequires:* pyte (https://pypi.org/project/pyte/) VTXXX terminal emulator* tty2img (https://pypi.org/project/tty2img/) lib for rendering pyte screen as image* moviepy (https://pypi.org/project/moviepy/) video editing library* numpy (https://pypi.org/project/numpy/) array computing (for moviepy)Copyright © 2020, Robert Ryszard Paciorek <rrp@opcode.eu.org>, MIT licence
Package: asciicells
Home Page:https://github.com/mitnk/asciicellsInstall$ pip install asciicellsHigh level usagesAfter installed, an executableasciicellswould available for use.
If not, please replace following examples withpython-masciicells.$ asciicells -f demo.csv

+-----+---------+-----------+
| No. | sample  | name      |
|     |         |           |
| 1   | a,b,c   | lettes    |
|     |         |           |
| 2   | + - x / | operators |
+-----+---------+-----------+With header:$ asciicells -f demo.csv -H

+-----+---------+-----------+
| No. | sample  | name      |
+-----+---------+-----------+
| 1   | a,b,c   | lettes    |
|     |         |           |
| 2   | + - x / | operators |
+-----+---------+-----------+Also support TSV:asciicells -f demo.tsv -t -HLow level usages>>> import asciicells
>>> ac = asciicells.AsciiCells()
>>> L = [['a', 'b'], ['1', '2']]
>>> print(ac.render(L))
+---+---+
| a | b |
|   |   |
| 1 | 2 |
+---+---+More information:https://github.com/mitnk/asciicells