KyberCharts aims to provide historical data for tokens traded on the Kyber Network. This takes the form of a Python library.

The function would take in a start block and an end block, and return a pandas dataframe containing all of Kyber's transactions on the main.net of Ethereum Blockchain in the form OHLCV (Open, High, Low, Closing, Volume).

The use cases range from analytics, to bot trading, to the simple love of data.

The tool queries the smart contracts associated with the Kyber Network and searches through the blocks for the transaction history.

The function can be adjusted to query a range of dates of historical trading data and subsequently visualise it. For example, as a developer, you could use our library to query for the past month of transactions from ETH to ZIL with this API.

We also have implemented a front-end demo with a visualization as a proof of concept.

git clone https://github.com/ryan-foo/ethsg.git

Run this command in your terminal.

python3 kycharts.py

The program will query data from the Ethereum mainnet and automatically cleans it to OHLCV (Open, High, Low, Closing, Volume) data and stores it as a .csv. Beware -- the Ethereum mainnet is a very large set of data to get through!

We had to decide between using the etherscan API and reading directly off the blockchain or through Infura.

We aimed to create an API.

Based on our team's competencies, we decided between Python and Web3js as a means of getting the historical data from either etherscan. We saved this in a Jupyter Notebook. The end-goal was a Python library because the end goal was a data-science library.

Due to the constraints of the hackathon. Our webapp was also limited in its front-end and user experience. However, we believe the main target audience are developers and algorithmic traders, who will find the clean .csv useful for their purposes.

Anthony Cheung, Jeffery Cao, Ryan Foo, Yash Sinha