semvec/pypi-packages huggingface dataset:
lantern3 0.1.0
Light up the Ethereum blockchain
License: MIT
Requires Python: >=3.9,<4.0
Keywords: ethereum

# lantern3.py

Light up the Ethereum blockchain with Lantern3, a Python library that provides high-level interfaces for sending bundled transactions to block builders. Lantern3 aims to increase the success rate of transaction inclusion while mitigating issues such as transaction reverts, front-running, back-running, and sandwich attacks.

## Builders

Lantern3 supports multiple block builders that you can use to send your bundled transactions.

| Name          | RPC Endpoint                | Notes                                               |
| ------------- | --------------------------- | --------------------------------------------------- |
| Flashbots     | https://relay.flashbots.net | [`FlashbotsBuilder`](lantern3/builder/flashbots.py) |
| builder0x69   | https://builder0x69.io      |                                                     |
| beaverbuild   | https://rpc.beaverbuild.org |                                                     |
| rsync-builder | https://rsync-builder.xyz   |                                                     |

Please refer to the documentation of each block builder for any specific requirements or considerations when using them.

## Examples

To get started with Lantern3, you can explore the provided examples. The following example demonstrates a simple transfer of Ether:

```shell
$ python3 examples/simple_transfer.py <YOUR_PRIVATE_KEY>
```

Please note that before running the examples, you may need to install the necessary dependencies by following the installation instructions in the project's documentation.

## Contributing

We welcome contributions to Lantern3! If you encounter any issues, have suggestions, or want to contribute improvements or new features, please open an issue or submit a pull request on the GitHub repository.

## License

Lantern3 is licensed under the [MIT License](https://opensource.org/license/mit/). See the [LICENSE](LICENSE) file for more details.
django-coreplus 0.4
Django functional modules
License: MIT
Requires Python: >=3.8

# 🚀 Django Core Plus

## Description

Django functional modules.

## Installation

Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.

## Usage

Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.

## Support

Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc.

## Roadmap

If you have ideas for releases in the future, it is a good idea to list them in the README.

## Test and Build

Todo

## Contributing

State if you are open to contributions and what your requirements are for accepting them.

For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self.

You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.

## Authors and acknowledgment

Show your appreciation to those who have contributed to the project.

## License

For open source projects, say how it is licensed.

## Project status

If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
alpyvantage 0.2.1
A python API to Alpha Vantage
License: MIT

alpyvantage
=============

**An alternative python backend to the Alpha Vantage API**

.. image:: https://img.shields.io/badge/GitHub-gboehl%2Falpyvantage-blue.svg?style=flat
    :target: https://github.com/gboehl/alpyvantage

.. image:: https://readthedocs.org/projects/alpyvantage/badge/?version=stable
    :target: https://alpyvantage.readthedocs.io

.. image:: https://badge.fury.io/py/alpyvantage.svg
    :target: https://badge.fury.io/py/alpyvantage

.. image:: https://github.com/gboehl/alpyvantage/actions/workflows/continuous-integration.yml/badge.svg
    :target: https://github.com/gboehl/alpyvantage/actions

**alpyvantage** provides a python backend to the Alpha Vantage API. Alpha Vantage provides access to a wide range of financial data and time series. Details can be found in the `official API documentation <https://www.alphavantage.co/documentation/>`_. You can get a free `API key here <https://www.alphavantage.co/support/#api-key>`_.


Installation
------------

Installing the `repository version <https://pypi.org/project/econpizza/>`_ is as simple as typing

.. code-block:: bash

   pip install alpyvantage

in your terminal or Anaconda Prompt.


Documentation
-------------

API calls are straightforward. Either use the build-in functions such as ``time_series_intraday``, ``time_series_weekly``, etc.:

.. code-block:: python

    import alpyvantage as av

    api = av.API(<your_api_key>)

    data, meta_data = api.time_series_intraday('DAX', interval='1min', month='2015-01')

    print(data) # its a pandas.DataFrame

Or use the ``function`` keyword from the `official API documentation <https://www.alphavantage.co/documentation/>`_ and provide the parameters as keyword arguments:

.. code-block:: python

    data, meta_data = api('TIME_SERIES_INTRADAY', symbol='DAX', interval='1min', month='2015-01')

A detailed documentation of the individual functions can be `found here <https://alpyvantage.readthedocs.io>`_.


Issues and contributions
------------------------

Please use the `issues <https://github.com/gboehl/alpyvantage/issues>`_ for questions or if you think anything doesn't do what it is supposed to do. Pull requests are welcome, please include some documentation.