Have you ever wondered how to obtain historical Uni V3 data? 🧵
We created a short tutorial on how to do it using Python and GBQ (LINK HERE)
NB: ☝️ can also be extended to other protocols.
In short, we created a query that:
- Selects the relevant columns from GBQ’s public Ethereum logs database
- Filters info by pool address (e.g. USDC-ETH pool at 0.3%)
- Extracts relevant transaction data (e.g. amounts, sqrtPrice...)
- Cleans & sorts the data.
NB: You will need a Google Big Query credential. See here.
You will also need the following (standard) python packages:
Why do we want this data? It contains a wealth of information! As an example, by investigating the data for the ETH-USDC pool at a 0.3% fee, one can plot the asset price in the pool.
We can also look at the histogram of the time between any two transactions:
Notice that this distribution resembles an exponential distribution with parameter λ = 0.007, meaning that, on average, there is a transaction every ~136 seconds in this pool.
This tutorial is intended to be the "first step" in our series of #ResearchBites investigating Uni V3 pool data (e.g., prices, transactions, etc.), as well as trading strategies in these pools. Stay tuned for more upcoming #ResearchBites from the Panoptic_xyz team!