semvec/pypi-packages huggingface dataset:
kraken_connector 0.0.2
WS and HTTP clients for Kraken exchange API
Requires Python: >=3.8,<4.0

# kraken-connector

[![Release](https://img.shields.io/github/v/release/tlg7c5/kraken-connector)](https://img.shields.io/github/v/release/tlg7c5/kraken-connector)
[![Build status](https://img.shields.io/github/actions/workflow/status/tlg7c5/kraken-connector/main.yml?branch=main)](https://github.com/tlg7c5/kraken-connector/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/tlg7c5/kraken-connector/branch/main/graph/badge.svg)](https://codecov.io/gh/tlg7c5/kraken-connector)
[![Commit activity](https://img.shields.io/github/commit-activity/m/tlg7c5/kraken-connector)](https://img.shields.io/github/commit-activity/m/tlg7c5/kraken-connector)
[![License](https://img.shields.io/github/license/tlg7c5/kraken-connector)](https://img.shields.io/github/license/tlg7c5/kraken-connector)

WS and HTTP clients for Kraken exchange API

- **Github repository**: <https://github.com/tlg7c5/kraken-connector/>
- **Documentation** <https://tlg7c5.github.io/kraken-connector/>

## Getting started with your project

First, create a repository on GitHub with the same name as this project, and then run the following commands:

```bash
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:tlg7c5/kraken-connector.git
git push -u origin main
```

Finally, install the environment and the pre-commit hooks with

```bash
make install
```

You are now ready to start development on your project!
The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.

To finalize the set-up for publishing to PyPi or Artifactory, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/publishing/#set-up-for-pypi).
For activating the automatic documentation with MkDocs, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/mkdocs/#enabling-the-documentation-on-github).
To enable the code coverage reports, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/codecov/).

## Releasing a new version

- Create an API Token on [Pypi](https://pypi.org/).
- Add the API Token to your projects secrets with the name `PYPI_TOKEN` by visiting [this page](https://github.com/tlg7c5/kraken-connector/settings/secrets/actions/new).
- Create a [new release](https://github.com/tlg7c5/kraken-connector/releases/new) on Github.
- Create a new tag in the form `*.*.*`.

For more details, see [here](https://fpgmaas.github.io/cookiecutter-poetry/features/cicd/#how-to-trigger-a-release).

---

Repository initiated with [fpgmaas/cookiecutter-poetry](https://github.com/fpgmaas/cookiecutter-poetry).
osifinanceAPI 0.1.1
Python toolkit for interacting with the OSI Finance API
Requires Python: >=3.6

# osifinanceAPI: Python API for OSI Finance REST API
osifinanceAPI is a Python package for accessing OSI Finance's financial calculators. The library enables developers to programmatically calculate taxes, social security, and other tax-related values.

## Installation
You can install osifinanceAPI with pip:

```
pip install osifinanceAPI
```

## Documentation
Full documentation is available [here](https://osifinance.com/docs/osifinanceAPI).

## Quickstart
Getting started with osifinanceAPI is easy.

Like most API clients, osifinanceAPI exposes a single class that provides access to the rest of the API: Osifinance.

The first thing to do is instantiate a new Osifinance object by providing your Osifinance instance’s root API URL and a valid API key. Additionally, you can include constant financial data such as your filing status or salary.

```ruby
# Import the Osifinance class
from osifinanceAPI import Osifinance

# OSI Finance API key
API_KEY = "p@$$w0rd"

# Initialize a new Osifinance object
osi = Osifinance(API_KEY)

# You can now use osi to begin making API calls.

# Working with Osifinance Objects
# osifinanceAPI converts the JSON responses from the host website into Pandas dataframes

# Get income taxes
df_income_taxes = osi.income_taxes(filing_status='single', agi=100000)

# Access the total taxes
df_income_taxes.taxes.total

# State tax information can be found using the StateTaxes Class
from osifinanceAPI import StateTaxes

# Initialize a new StateTaxes object
state_taxes = StateTaxes(API_KEY)

alabama_taxes = state_taxes.alabama(agi=100000)

# Alternatively, you can access a sources dict by passing in sources=True
alabama_taxes = state_taxes.alabama(agi=100000, sources=True)
alabama_taxes['sources']

# To access the dataframe in this case, you must access the data key first
alabama_taxes['data'] 
```

## Contact Us
Need help? Have an idea? Feel free to check out our [Discussions board](https://osifinance.canny.io). Just want to say hi or get extended spport? Come join the [OSI Finance Discord Channel](https://discord.gg/HfmxDqBVjP)!

## Disclaimer
I undestand that OSI Finance reads my financial information when performing calculations and does not store any of my information. For more information, please visit our [Legal Disclaimer](https://osifinance.com/legal-disclaimer).