Saravanan666/pypi-org huggingface dataset:
Package: vendor
===============Python Vendor===============This package provides an AWS service API for building compiled Python packages,ready for use in your own AWS Lambda functions.Requirements============In addition to Python package requirements that will automatically be dealtwith during package installation, the vendor package assumes that the AWS CLIis installed and configured on your system. By default, vendor makes use ofyour AWS configuration as the ``aws`` command would.To install awscli, please refer to the official documentation:https://docs.aws.amazon.com/cli/latest/userguide/Installation============Programmatic Deployment-----------------------The service package module provides a class for dealing with the Vendor stackdeployment. To create the stack using the default settings, simply do thefollowing:::>>> from vendor.service import VendorService>>> vs = VendorService()>>> vs.service(){'ServiceURL': 'https://abcde01234.execute-api.region.amazonaws.com/api/','Version': '0.1'}If all goes well, you will get back a dictionary containing the service``Version`` and the ``ServiceURL``, which can be used to call your newly createdAPI. If the stacks already exist and are up-to-date, then the function willsimply return the information, rather than recreate it all over again.Manual Deployment-----------------First, deploy the Vendor-deployment stack to prepare a bucket for Serverlessartifacts.::aws cloudformation deploy --stack-name Vendor-deployment --template-file vendor/aws/vendor-deployment.ymlThe deployment bucket name can be found from the stack outputs.::aws cloudformation describe-stacks --stack-name Vendor-deploymentNext we can package and deploy the Vendor service.::aws cloudformation package --template-file vendor/aws/vendor.yml --s3-bucket {Vendor-deployment.BucketName} --output-template-file /tmp/vendorpk.ymlaws cloudformation deploy --stack-name Vendor --template-file /tmp/vendorpk.yml --capabilities CAPABILITY_IAMAgain, the service URL can be found from the stack outputs.::aws cloudformation describe-stacks --stack-name VendorDevelopment===========Build toolchains----------------Because Lambda runs on a readonly filesystem, building is hard as the buildtools are not available on the system. Therefore, we have cheated a little andinstead spawn our own 'Lambda' on a self-destructing EC2 instance. This is doneby passing a script into the EC2 user-data and setting the instance toterminate on shutdown, which the script does on exit.
Package: vendor-grab
Vendor GrabDownload gzipped tar files from URLs and extract only selected files to
destination paths in current working directory.Configuration file is in TOML format. Takes a list of vendors that can have
multiple files.[[vendors]]archive="https://github.com/csstools/normalize.css/archive/refs/tags/12.0.0.tar.gz"# Verify the downloaded tar file with this sha256 hash hexdigest.checksum="0820f46861766b7aef99ffd1601e61279d399700e1683e7863f9400af068e3ed"# The dst_checksum is optional. Delete it to always replace dst files from the downloaded tar file.#dst_checksum = ""# The strip_components will default to 1. It is the same as --strip-components flag in tar command.#strip_components = 1[[vendors.files]]# The source (src) of the file in the tar (with the first component stripped off# since it is usually a directory with the version.src="normalize.css"# The destination (dst) is where it extracts the file to.dst="vendor/normalize.css/normalize.css"# It is common to grab any license files and include them along with source# files.[[vendors.files]]src="LICENSE.md"dst="vendor/normalize.css/LICENSE.md"The created dst files can be committed to source control (git, fossil, etc.) and
if the dst_checksum fields are set; it won't needlessly fetch the tar file each
time. This also prevents the vendor dst files from being modified without also
updating the dst_checksum value.Installpipinstallvendor_grabUsageCreate a configuration file in TOML format that has 'vendors' list. See example
above or theexample-vendors.tomlfile in this
project.Pass the configuration file as the only arg:vendor_grabexample-vendors.tomlView the downloaded files in the 'vendors' directory (if using the
example-vendors.toml configuration file).Why?The Simplest Thing That Could Possibly Work.Why use a tool likenpmto download some CSS files? That was the main reason
I created this script. I did not need all the capability (and potential security
holes) that thenpmtool provided. I simply wanted to automate getting some
vendor files into my git repository and keep them up to date.Initially this script started off as amessy shell scriptthat usedjq,wget,md5sumcommands. It also used JSON for the
configuration, which isn't great for adding inline comments. It was rewritten in
Python to be more compatible and easier to follow.
Package: vendoring
vendoringA command line tool, to simplify vendoring pure Python dependencies.Why does this exist?pip had a "home-grown" setup for vendoring dependencies. Theinvoketask grew in complexity to over 500 lines and, at some point, became extremely difficult to improve and maintain.This tool is based off the overgrowninvoketask, breaking it out into a dedicated codebase with the goal of making it more maintainable and reusable. This also enabled independent evolution of this codebase and better access to infrastructure (like dedicated CI) to ensure it keeps working properly.Should I use it?This tool has no stability promises -- it has only one intended user: pip. There may be unannounced changes to this codebase at any time, as long as the intended user (i.e. the pip project) is prepared for those changes.As a general rule of thumb, if the project is going to be a PyPI package, it should not use this tool.Many downstream redistributors have policies against this kind of bundling of dependencies, which means that they'll patch your software to debundle it. This can cause various kinds of issues, due to violations of assumptions being made about where the dependencies are available/which versions are being used. These issues result in difficult-to-debug errors, which are fairly difficult to communicate with end users.pip is averyspecial case with athorough rationalefor
vendoring/bundling dependencies with itself.ContributingCheck theContributingguide.
Package: vendorize
python-vendorizeallows pure-Python dependencies to be vendorized:
that is, the Python source of the dependency is copied into your own package.
Best used for small, pure-Python dependencies to avoid version conflicts
when other packages require a different version of the same dependency.Dependencies you want vendorizing should be specified invendorize.toml.targetshould be a string containing the path where vendorized dependencies should be placed,
relative to the directory thatvendorize.tomlis in.packagesshould be a list of strings containing the dependencies.
Each of these strings can be anything thatpipwould understand,
such as a package name, a package name with version constraints or an URL.
Dependencies can then be vendorized usingpython-vendorize.For instance, suppose I want to vendorizesixso it can be used from the packagehello.
The directory structure would be something like:- hello
  - __init__.py
- setup.py
- vendorize.tomlvendorize.tomlmight look something like:target = "hello/_vendor"
packages = [
    "six",
]I can then runpython-vendorizein the same directory asvendorize.toml.
The directory structure would then be something like:- hello
  - _vendor
    - six.dist-info
      - ...
    - __init__.py
    - six.py
  - __init__.py
- setup.py
- vendorize.tomlInhello/__init__.py,sixcan be imported from_vendor:from._vendorimportsixInstallationpip install vendorize
Package: vendy
Vendy is a tool for vendoring third-party packages into your project.Disclaimer:This is not an officially supported Google product.Example:In apyproject.tomlfile in the root of your package, define the target
directory (should be in the same directory as thepyproject.tomlfile), and
the packages to vendor:[tool.vendy]target='my_project'packages=["sampleproject==1.2.0",]On the command line:$ python -m vendy
[vendy] Using vendor dir: /private/tmp/my_project/my_project/_vendor
[vendy] Cleaning /private/tmp/my_project/my_project/_vendor
[vendy] Installing vendored libraries
Collecting sampleproject==1.3.0
  Using cached https://files.pythonhosted.org/packages/a1/fd/3564a5176430eac106c27eff4de50b58fc916f5083782062cea3141acfaa/sampleproject-1.3.0-py2.py3-none-any.whl
Installing collected packages: sampleproject
Successfully installed sampleproject-1.3.0
[vendy] Detected vendored libraries: bin, my_data, sample
[vendy] Rewriting all imports related to vendored libs
[vendy] Downloading licenses
Collecting sampleproject==1.3.0
  Using cached https://files.pythonhosted.org/packages/a6/aa/0090d487d204f5de30035c00f6c71b53ec7f613138d8653eebac50f47f45/sampleproject-1.3.0.tar.gz
  Saved ./my_project/_vendor/__tmp__/sampleproject-1.3.0.tar.gz
Successfully downloaded sampleproject
[vendy] Extracting sampleproject-1.3.0/LICENSE.txt into my_project/_vendor/sampleproject.LICENSE.txt
[vendy] Revendoring completeResult:$ tree
.
├── my_project
│   ├── __init__.py
│   └── _vendor
│       ├── bin
│       │   └── sample
│       ├── my_data
│       │   └── data_file
│       ├── sample
│       │   ├── __init__.py
│       │   └── package_data.dat
│       └── sampleproject.LICENSE.txt
└── pyproject.tomlAnd you can import from the vendored library like:-from sampleproject.foo import bar+from myproject._vendor.sampleproject.foo import bar
Package: venezuela-dollar-price
Venezuela Dollar Pricevenezuela_dollar_priceis a Python library created to retrieve the current dollar price in Venezuela. It is simple to use and requires minimal setup.FeaturesGet the latest dollar price in Venezuelan Bolivars.Retrieve historical dollar prices.User-friendly and intuitive to use.InstallationUse the package managerpipto installvenezuela-dollar-price.pipinstallvenezuela-dollar-priceUsageimportvenezuela_dollar_priceasvdp# get the latest dollar price (BCV)latest_price=vdp.get_latest_price("bcv")print(latest_price.rate)# get the latest dollar price ("binance")latest_price=vdp.get_latest_price("binance")print(latest_price.rate)# get the latest dollar price ("parallel")latest_price=vdp.get_latest_price("prom_epv")print(latest_price.rate)# get historical prices of the dollar (BCV)# Note: only works for the BCV and EPV# minimum date: 2020-12-14historical_prices=vdp.get_historical_prices(start_date="2020-01-01",end_date="2023-01-31")forpriceinhistorical_prices:print(price.date,price.rate)ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.LicenseMIT
Package: venim
Venus Imaging AnalysisPython tools for Venus Image AnalysisFree software: MIT licenseDocumentation:https://venim.readthedocs.io.FeaturesIf the feature has been implemented in an importable way, it’s indicated by a filled checkmark [x][x] Read FITS arrays (done via astropy.io.fits)[x] FITS image stats scanner (creates CSV overview file)[ ] For un-calibrated ground-based observations:[ ] Standard image reduction pipeline: bias subtraction, flat field normalization, etc.[ ] Other image clean-up: bad pixels, cosmic rays, detector artifacts[ ] Generate estimated errors for each pixel[ ] Transform detector x,y coordinates into local Lat, Lon[ ] Access PDS data automatically via mission dependent interfaces[x] Automatic downloads per volume orbit[x] Local easy data access per data ID[x] Akatsuki version implemented[ ] VEX[x] Annotate images and implement a point-based circle-fit[ ] Take various gradients of images[ ] Filter images in the spatial frequency domain[ ] Sub-pixel disk registration[ ] Robust stacking of co-registered images[ ] Cloud trackingCreditsThe content of this package is based on summer science work by Nicolas Ardavin and Kenyon Prater, under the lead of Eliot Young and Mark Bullock.
Later improvements have been implemented by the package maintainer Michael Aye.This package was created withCookiecutterand the forkedmichaelaye/cookiecutter-pypackage-condaproject template.History0.4.3 (2020-05-26)fix wavelength finallychange notebooks
* renamed opening_calibrated to open_files.ipynb
* adding finding_files.ipynb0.4.1 (2020-05-26)Convert wavelength to integer for the filelist.0.4.0 (2020-05-26)Add wavelength and exposure to filelistAdd utility functionir2.get_orbit_file_list()0.1.0 (2019-02-07)First release on PyPI.
Package: venmo
VenmoPay or charge people on the command line!$ venmo pay @zackhsi 23.19 "Thanks for the beer <3"
$ venmo charge 19495551234 23.19 "That beer wasn't free!"Installationvenmocan be installed viapip.$ pip install venmoSetupSet up venmo by running:$ venmo configure

> Venmo email [None]: zackhsi@gmail.com
> Venmo password [None]:
> Verification code: 908126  # for 2 factor authenticationThat’s it!ContributingPull requests welcome! To get started, first clone the repository:$ git clone git@github.com:zackhsi/venmo.gitCreate a virtualenv containing an editable installation of venmo, plus
development dependencies:$ make initActivate the virtualenv:$ pipenv shellRun tests:$ make test
Package: venmo-api
Venmo APIDisclaimer: This is an individual effort and is not PayPal/Venmo sponsored or maintained.IntroductionThis is a wrapper for the Venmo API. This library provides a Python interface for the Venmo API. It's compatible with Python versions 3.6+.InstallingYou can install or upgrade venmo-api with:$pip3installvenmo-api--upgradeOr you can install it from the source:$gitclonehttps://github.com/mmohades/Venmo.git--recursive
$cdVenmo
$python3setup.pyinstallGetting StartedUsageIn short, you can send money, request for money, get a user's public transactions, get a user's public profile info, etc. The following is an example of initializing and working with it.fromvenmo_apiimportClient# Get your access token. You will need to complete the 2FA processaccess_token=Client.get_access_token(username='myemail@random.com',password='your password')venmo=Client(access_token=access_token)# Search for users. You get 50 results per page.users=venmo.user.search_for_users(query="Peter",page=2)foruserinusers:print(user.username)# Or, you can pass a callback to make it multi-threadeddefcallback(users):foruserinusers:print(user.username)venmo.user.search_for_users(query="peter",callback=callback,page=2,count=10)Keep this in mind that your access token never expires! You will need to revoke it by yoursef.venmo.log_out("Bearer a40fsdfhsfhdsfjhdkgljsdglkdsfj3j3i4349t34j7d")# Request moneyvenmo.payment.request_money(32.5,"house expenses","1122334455667")# Send moneyvenmo.payment.send_money(13.68,"thanks for the 🍔","1122334455667")Getting a user's transactions (public, friends and privates that happen between your account and user_id account)defcallback(transactions_list):fortransactionintransactions_list:print(transaction)# callback is optional. Max number of transactions per request is 50.venmo_api.user.get_user_transactions(user_id='0000000000000',callback=callback)Documentationvenmo-api's documentation lives atreadthedocs.io.ContributingContributions of all sizes are welcome. You can help with the wrapper documentation located in /docs. You can also help byreporting bugs. You can add more routes to bothVenmo Unofficial API Documentationand thevenmo-apiwrapper.Venmo Unofficial API DocumentationYou can find and contribute to theVenmo Unofficial API Documentation.
Package: venmo-cli
venmo-clivenmo-cli is a simple CLI for Venmo, built on theVenmo APIby mmohades. As with his API, use this toolat your own riskas it isnotsponsored/maintained by PayPal or Venmo.Sample usage$ venmo --help
Usage: venmo [OPTIONS] COMMAND [ARGS]...

  venmo-cli: Venmo for the command-line

Options:
  --help  Show this message and exit.

Commands:
  logout   Logs out of your current session
  pay      Sends money to another user
  request  Requests money from another user$ venmo pay --help
Usage: venmo pay [OPTIONS] USERNAME

  Sends money to another user

Options:
  -a, --amount FLOAT             [required]
  -m, --msg TEXT                 [default: 🤖]
  -p, --privacy PAYMENT_PRIVACY  [default: friends]
  --help                         Show this message and exit.$ venmo pay cameronbernhardt -a 5 -m "thanks for the pizza" --privacy=private
Paid $5 to @cameronbernhardt with message 'thanks for the pizza'$ venmo request cameronbernhardt -a 10 -m "lunch"
Requested $10 from @cameronbernhardt with message 'lunch'
Package: venn
pyvenn: Venn diagrams for 2, 3, 4, 5, 6 setsPlease refer to the Jupyter notebook for demos and a brief explanation of the
interface; a more complete documentation is in the works as the project keeps
evolving:https://github.com/LankyCyril/pyvenn/blob/master/pyvenn-demo.ipynbThis library is an evolution of tctianchi's pyvenn package (see fork URL).Their liberal license (Unlicense) allowed me to fork the repository,
change the license to GPLv3, modify the package's interface and, hopefully,
significantly contribute to and improve the library, and make it installable
from PyPI.The main methods in this version are different from the ones in tctianchi's
implementation, but the original methods are still provided for backwards
compatibility, and I would like to emphasize the importance of tctianchi's work
that allowed for this library to exist (among other things, figuring out the
coordinates best fit for plotting the diagrams' shapes and petals' labels).This iteration of the library implements two main functions:venn(dataset_dict, **kwargs)which plots true Venn diagrams for any number
of sets between 2 and 5 using ellipses, and for 6 sets using trianglespseudovenn(dataset_dict, **kwargs)which plots a Venn-like intersection of
six circles (not all intersections are present in such a plot, but many are).
Package: venn-abers
Venn-ABERS calibrationThis library contains the Python implementation of Venn-ABERS calibration for binary and multiclass classification problems.Installationpip install venn-abersThe method can be applied on top of an underlying scikit-learn algorithm.Example Usagefrom sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB

from venn_abers import VennAbersCalibrator

X, y = make_classification(n_samples=1000, n_classes=3, n_informative=10)
X_train, X_test, y_train, y_test = train_test_split(X, y)

clf = GaussianNB()

# Define Venn-ABERS calibrator
va = VennAbersCalibrator(estimator=clf, inductive=True, cal_size=0.2, random_state=101)

# Fit on the training set
va.fit(X_train, y_train)

# Generate probabilities and class predictions on the test set
p_prime = va.predict_proba(X_test)
y_pred = va.predict(X_test)ExamplesFurther examples can be found in the github repositoryhttps://github.com/ip200/venn-abersin theexamplesfolder:simple_classification.ipynb for a simple example in the binary classification setting.multiclass_classification.ipynb for the multiclass setting.comparison_with_existing.py for the comparison with a previous github implementationCitationIf you find this library useful please consider citing:Vovk, Vladimir, Ivan Petej and Valentina Fedorova. "Large-scale probabilistic predictors with and without guarantees of validity." Advances in Neural Information Processing Systems 28 (2015) (arxiv versionhttps://arxiv.org/pdf/1511.00213.pdf)Vovk, Vladimir, Ivan Petej. "Venn-Abers predictors". Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (2014) (arxiv versionhttps://arxiv.org/abs/1211.0025)Manokhin, Valery. "Multi-class probabilistic classification using inductive and cross Venn–Abers predictors." Conformal and Probabilistic Prediction and Applications, PMLR, 2017.
Package: vennam
VennamVennam is a Python library for converting Python DataFrame to List of Python Dictionary items .InstallationUse the package managerpipto install Vennam.pipinstallvennamversionvennam.__version__# return current version of PackageUsage of PackagefromvennamimportDataFrameToDictasddlist_dict=dd.dftodict(DataFrame)# returns the list of dictionary itemsWord Analysis on DataFrame DatafromvennamimportAnalysisfreqency=Analysis.WordAnalysis(<DataFrame>,<DataFrameColumn>)ExamplefromvennamimportAnalysisfreqency=Analysis.WordAnalysis(data,'description')Word Cloud on DataFrame DatafromvennamimportAnalysisWordClound=Analysis.WordCloud(<DataFrame>,<DataFrameColumn>)ExamplefromvennamimportAnalysisWordClound=Analysis.WordCloud(data,'description')DataBase Connectionfromvennam.DataBaseimportcreate_engineconnection=create_engine(user,password,host,port,database)Examplefromvennam.DataBaseimportcreate_engineconnection=create_engine(user="VVVVV",password="VVVVV",host="VVVVV",port="VVVVV",database="VVVVV")Dumping DataFrame into existing database tablefromvennam.DataBaseimportinsert_dictData_dump=insert_dict(connection,schemaname,tablename,dataframe)Examplefromvennam.DataBaseimportinsert_dictData_dump=insert_dict(schemaname="VVVVV",tablename="VVVVV",connection=connection,dataframe=dataframe)LicenseMIT
Package: vennfig
vennfigvennfigis a Python package and is a wrapper formatplotlib_vennYou can draw simple Venn diagrams with 2 lines of code.Installation:pip install vennfigOn Jupyter:!pip install vennfigExamplesSee all the examples here.A, B Venn diagramimport vennfig as v
# default
v.a_b()

# using params
v.a_b(subs=2, size=6, fill_color='#f5b705', bg_color='#f7edd0', 
    font_size=25, title_a='P', set_a='P', set_b='Q')A AND B, A NAND B Venn diagramimport vennfig as v
# default
v.and_nand()

# using params
v.and_nand(subs=2, size=5, fill_color='#f55faa', bg_color='#f2e4eb', 
         font_size=25, title_a='P and Q', title_b='a nand b', set_a='P', set_b='Q')TRUE, FALSE Venn diagramimport vennfig as v
# default
v.true_false()

# using params
v.true_false(subs=2, size=5, fill_color='#d0f7f3', bg_color='#13edd7', title_a='P, Q, TRUE',
           font_size=25, set_a='P', set_b='Q')OR, NOR Venn diagramimport vennfig as v
# default
v.or_nor()

# using params
v.or_nor(subs=3, size=5, fill_color='#88f77c', bg_color='#daf5d7', font_size=25,
      title_b='P NOR Q', set_a='P', set_b='Q')XOR, XNOR Venn diagramimport vennfig as v
# default
v.xor_xnor()

<!-- using params -->
v.xor_xnor(subs=2, size=5, fill_color='#fa8069', bg_color='#fae5e1', 
         font_size=25, title_a='P XOR Q', set_a='P', set_b='Q')NOT A, NOT B Venn diagramimport vennfig as v
# default
v.not_not()

# using params
v.not_not(subs=3, size=5, fill_color='#e8e815', bg_color='#f2f2aa', font_size=25, 
        title_b='NOT Q', set_a='P', set_b='Q')A NOT B, B NOT A Venn diagramimport vennfig as v
# default
v.x_not_y()

# using params
v.x_not_y(subs=3, size=5, fill_color='#d4812f', bg_color='#e3dad1', font_size=25, 
        title_b='P NOT Q', set_a='P', set_b='Q')Implication Venn diagramimport vennfig as v
# default
v.implication()

# using params
v.implication(subs=3, size=5, fill_color='#5ba870', bg_color='#d7f5df', font_size=25, 
        title_b='Q ⇒ P', set_a='P', set_b='Q')Mutually exclusive Venn diagramimport vennfig as v
# default
v.mut_exclusive()

# using params
v.mut_exclusive(size=10, fill_color='#2d5c91', bg_color='#e1e8f0', font_size=25, 
        title='Mutually exclusive: P∩Q=∅', set_a='P', set_b='Q')Complement Venn diagramimport vennfig as v
# default
v.complement()

# using params 
v.complement(subs=2, size=5, fill_color='#3eacb5', bg_color='#c1d9db', font_color='#d40f19', 
           font_size=25, title_a='Complement P', set_a='P', set_b="P'")Subsets Venn diagramimport vennfig as v
# default
v.subsets()

# using params
v.subsets(size=5, fill_color='#f5b705', bg_color='#f7edd0', font_size=20,
        title='Subsets of P', set_a='P', set_b='Q')