Uniswap V3 Data Notebook#
In this notebook:
We use the TradingStrategy API to get data for 3 pairs on Uniswap V3
This is done for 3 pairs: eth_usdc, eth_usdt, and usdt_usdc
The following code block shows an example of some the data from the api
[1]:
import requests
import pandas as pd
pairs = {
'eth_usdc': 'https://tradingstrategy.ai/api/candles?pair_id=2697765&exchange_type=uniswap_v3&time_bucket=4h',
'usdt_usdc': 'https://tradingstrategy.ai/api/candles?pair_id=2711887&exchange_type=uniswap_v3&time_bucket=4h',
'eth_usdt': 'https://tradingstrategy.ai/api/candles?pair_id=2697770&exchange_type=uniswap_v3&time_bucket=4h'
}
def get_candles(url: str) -> pd.DataFrame:
x = requests.get(url)
json = x.json()
candles = pd.DataFrame.from_dict(json)
candles.rename(columns = {'ts':'date','o':'open', 'h':'high','l':'low','c':'close','v':'volume'}, inplace = True)
candles['timestamp'] = pd.to_datetime(candles['date'])
candles = candles.set_index('date')
return candles
pair_data = dict([ (k,get_candles(r)) for k,r in pairs.items()])
pair_data['usdt_usdc'].head()
[1]:
| open | high | low | close | volume | xr | b | s | tc | bv | sv | timestamp | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| date | ||||||||||||
| 2023-04-25T20:00:00 | 1.0002 | 1.0002 | 1.0001 | 1.0001 | 3.693619e+07 | 1.0 | None | None | None | None | None | 2023-04-25 20:00:00 |
| 2023-04-26T00:00:00 | 1.0001 | 1.0001 | 1.0001 | 1.0001 | 1.241267e+06 | 1.0 | None | None | None | None | None | 2023-04-26 00:00:00 |
| 2023-04-26T04:00:00 | 1.0001 | 1.0002 | 1.0001 | 1.0002 | 1.618425e+07 | 1.0 | None | None | None | None | None | 2023-04-26 04:00:00 |
| 2023-04-26T08:00:00 | 1.0002 | 1.0002 | 1.0001 | 1.0002 | 3.281721e+07 | 1.0 | None | None | None | None | None | 2023-04-26 08:00:00 |
| 2023-04-26T12:00:00 | 1.0002 | 1.0002 | 1.0002 | 1.0002 | 1.431288e+07 | 1.0 | None | None | None | None | None | 2023-04-26 12:00:00 |
Visual#
Here we visualize the prices and volumes of each of the 3 pairs.
[2]:
from tradingstrategy.charting.candle_chart import visualise_ohlcv
def get_figure(candles: pd.DataFrame, chart_name: str):
return visualise_ohlcv(
candles,
height=600,
theme="plotly_white",
chart_name=chart_name,
y_axis_name="Price",
volume_axis_name="volume",
)
figures = dict([ (k,get_figure(r, k)) for k,r in pair_data.items()])
figures['eth_usdc'].show()
figures['eth_usdt'].show()
figures['usdt_usdc'].show()