https://github.com/monoand6/web3cat

Data visualization for EVM-based blockchains
https://github.com/monoand6/web3cat

Last synced: 3 months ago
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Data visualization for EVM-based blockchains

• Host: GitHub
• URL: https://github.com/monoand6/web3cat
• Owner: monoand6
• License: mit
• Created: 2022-09-08T13:22:14.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-03-31T20:32:17.000Z (over 1 year ago)
• Last Synced: 2024-04-26T17:32:44.172Z (7 months ago)
• Language: Python
• Homepage:
• Size: 21.1 MB
• Stars: 9
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE.md

Awesome Lists containing this project

• On-Chain-Investigations-Tools-List - web3cat

README

        
.. image:: https://readthedocs.org/projects/web3cat/badge/?version=latest

    :target: https://web3cat.readthedocs.io/en/latest/?badge=latest

    :alt: Documentation Status

Welcome to Web3cat!

===================

.. image:: /docs/images/web3cat.png

    :width: 180

**Meow, fellow researcher!**

Web3cat is a framework for fetching and analyzing blockchain data.

Currently, it supports only EVM chains: `Ethereum `_,

`Polygon `_, `BNB `_, etc.

Design philosophy

-----------------

#. Visualize the data with minimum code

#. Free for downloading, saving, and analyzing the data however you want

#. Cache the data to avoid re-fetching anything at all

#. Fully decentralized, that is, depending only on the blockchain RPC

Quick demo

----------

.. image:: /docs/images/web3cat_demo.gif

Getting started

---------------

1. Install python package 

.. code::

    pip install web3cat

2. Set up your archive node rpc. The easiest (and also free) way is to use

   `Alchemy `_.

3. Set initial configuration

.. code::

    import os

    os.environ['WEB3_PROVIDER_URI'] = 'https://eth-mainnet.g.alchemy.com/v2/'

    os.environ['WEB3_CACHE_PATH']="cache.sqlite3"

4. (optional for Jupyter) Initialize bokeh for python notebooks

.. code::

    from bokeh.io import output_notebook

    output_notebook()

5. Run sample visualization

.. code::

    from web3cat.view import View

    from datetime import datetime

    v = View(token="DAI", start=datetime(2022, 6, 1), end = datetime(2022, 10, 30)) \

        .total_supply() \

        .balance(["0x5d3a536E4D6DbD6114cc1Ead35777bAB948E3643", "0xbEbc44782C7dB0a1A60Cb6fe97d0b483032FF1C7"])

    v.show()

.. image:: docs/images/view1.png

6. Get underlying data

    .. code::

        v.get_data(0).transfers[["date", "block_number", "from", "to", "value"]]

    .. image:: docs/images/view_getting_started1.png

Roadmap

-------

Use framework base layers to add analytics for protocols like

Uniswap, Liquity, Aave, Compound, Frax, etc.

Contributing

------------

So far no bureaucracy here, open issues, make pull requests, and have fun!