Resample OHLCV-1s with uniform

resample.py

"""
OHLCV-1s data follows standard convention of most vendors and doesn't print on intervals
when there's no trade. This is the typical approach as there's no way to infer the type
of price interpolation or forward fill preferred. If you need prices printed uniformly
with forward filling or price interpolation, you can follow this example to do it on
client side.

See also: https://databento.com/docs/examples/basics-historical/tick-resampling/example
"""

import databento as db


client = db.Historical()

data = client.timeseries.get_range(
    dataset="GLBX.MDP3",
    schema="ohlcv-1s",
    stype_in="continuous",
    symbols=["ES.n.1"],
    start="2025-04-15T15:30",
    end="2025-04-15T15:40",
)

df = data.to_df(tz="US/Eastern")

# Step 1: Resample to 1-second frequency
df_resampled = df.resample('1s').asfreq()

# Step 2: Identify which rows were created by resampling (i.e., rows that were NaN)
new_rows_mask = df_resampled['close'].isna()

# Step 3: Forward fill the resampled data
df_resampled = df_resampled.ffill()

# Step 4: For synthetic rows, set OHLC to the last close
df_resampled.loc[new_rows_mask, ['open', 'high', 'low']] = df_resampled['close'][new_rows_mask]

# Step 5: Set volume to 0 for synthetic rows
df_resampled.loc[new_rows_mask, 'volume'] = 0