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Build Your Own:

get_timesales() returns tick-by-tick trade records for your symbols over a time range, with optional filtering. Build it step by step:

Step 1 — Import the libraries

import icepython as ice
import pandas as pd

Step 2 — Identify your symbol (Max 10):

symbol = 'HNG 1!-IUS'

Step 3 — Choose your fields:

fields = ['Price', 'Conditions']

Step 4 — Define your date/time range (ISO format):

start_date = '2023-10-10'
end_date   = '2023-10-11'

Step 5 — (Optional) Filter on conditions. For example, only block trades that are also legs, applying AND:

data = ice.get_timesales(symbol, fields, start_date, end_date,
                         conditions=['BlockTrde', 'Leg'],
                         conditionslogic='AND')

Step 6 — Load into a DataFrame and print:

df = pd.DataFrame(list(data))
print(df)

Output:

0                 1                      2
0  Time  HNG 1!-IUS.Price  HNG 1!-IUS.Conditions