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import sys

from pathlib import Path

import numpy as np

import pandas as pd



def get_scid_df(filename, limitsize=sys.maxsize):

f = Path('/Users/Me/SierraPython/NQM4.CME.scid' )

assert f.exists(), f"{f} file not found"

stat = f.stat()

offset = 56 if stat.st_size < limitsize else stat.st_size - ((limitsize // 40) * 40)

sciddtype = np.dtype(

[

("Time", "<u8"),

("Open", "<f4"),

("High", "<f4"),

("Low", "<f4"),

("Close", "<f4"),

("Trades", "<i4"),

("Volume", "<i4"),

("BidVolume", "<i4"),

("AskVolume", "<i4"),

]

)

df = pd.DataFrame(

data=np.memmap(f, dtype=sciddtype, offset=offset, mode="r"), copy=False

)

df.dropna(inplace=True)

df["Time"] = df["Time"] - 2209161600000000

df.drop(df[(df.Time < 1)].index, inplace=True)

df.set_index("Time", inplace=True)

df.index = pd.to_datetime(df.index, unit="us")

df.index = df.index.tz_localize(tz="utc")

return df





def resample_scdf(scdf_or_filename, period="1Min", tz="UTC", limitsize=sys.maxsize):

df = (

get_scid_df(scdf_or_filename, limitsize)

if isinstance(scdf_or_filename, str)

else scdf_or_filename

)

assert isinstance(

df, pd.DataFrame

), f"{scdf_or_filename} has to be SC df or valid scid file"

df = df.resample(period).agg(

{

"Open": "first",

"High": "max",

"Low": "min",

"Close": "last",

"Trades": "sum",

"Volume": "sum",

"BidVolume": "sum",

"AskVolume": "sum",

}

)

if tz != "UTC":

tz = "America/New_York" if tz == "EST" else tz

tz = "America/Los_Angeles" if tz == "PST" else tz

df.index = df.index.tz_convert(tz)

return df

print(resample_scdf("NQM4.CME.scid", tz="EST"))