Dataset download

This is a generic example how to access Trading Strategy datasets by hand.

If you are a Python user, you should use the trading-strategy package to access the data (see Code examples). In thes examples, we give Python pseudocode other programming languages can adapt.

Downloading datasets programmatically

All endpoints need your API key in the Authorisation header.

Because files are large, you need to stream them, as they are unlikely to fit in the RAM.

Example how to download:

import os
import requests

# Read API key from the process environment
# should be in format "secret-token:tradingstrategy-48...
# where the secret-token is the part of the API key itself
api_key = os.environ["TRADING_STRATEGY_API_KEY"]

session = requests.Session()
session.headers.update({'Authorization': api_key})
server = "https://tradingstrategy.ai/api"
url = f"{server}/candles-all"
params= {"bucket": "1d"}
resp = session.get(url, allow_redirects=True, stream=True, params=params)
resp.raise_for_status()
size = 0
with open('candles.parquet', 'wb') as handle:
    for block in resp.iter_content(64*1024):
        handle.write(block)
        size += len(block)

print(f"Downloaded {size:,} bytes")

Here is a curl example for getting 1d liquidity candles and save the file in the current folder:

export TRADING_STRATEGY_API_KEY="secret-token:tradingstrategy-..."
curl -v -H "Authorization: $TRADING_STRATEGY_API_KEY" "https://tradingstrategy.ai/api/liquidity-all?bucket=1d" --output liquidity-1d.parquet

Reading datasets

Datasets are distributed as compressed Parquet files, using Parquet version 2.0.

You can read the files using PyArrow:

import pyarrow as pa
from pyarrow import parquet as pq

table: pa.Table = pq.read_table("candles.parquet")

Then, you can directly import the table into your database or convert the table to a Pandas DataFrame for further manipulation.