Support Board

def get_scid_df(symbol, limitsize=sys.maxsize):
f = Path(rf'c:\SierraChart\Data\{symbol}')
assert f.exists(), "file not found"
stat = f.stat()
offset = 56 if stat.st_size < limitsize else stat.st_size - ((limitsize // 40) * 40)

BCOLS = ['datetime', 'open', 'high', 'low', 'close', 'volume', 'trades', 'bidVolume', 'askVolume']
rectype = np.dtype([
(BCOLS[0], '<u8'), (BCOLS[1], '<f4'), (BCOLS[2], '<f4'),
(BCOLS[3], '<f4'), (BCOLS[4], '<f4'), (BCOLS[6], '<i4'),
(BCOLS[5], '<i4'), (BCOLS[7], '<i4'), (BCOLS[8], '<i4')
])

df = pd.DataFrame(data=np.memmap(f, dtype=rectype, offset=offset, mode="r"), copy=False)

df = df.dropna()
years_microseconds = 70 * 365.25 * 24 * 60 * 60 * 10**6 # accounts for leap years supposedly
days_microseconds = 2 * 24 * 60 * 60 * 10**6

total_microseconds = years_microseconds + days_microseconds # 70 years, 2 days
df.datetime = df.datetime - total_microseconds

# Add 6 hours to get to local time
df.datetime = pd.to_datetime(df.datetime, unit='us') + pd.Timedelta(hours=6)
df.set_index('datetime', inplace=True)

# Prices need to be adjusted
if 'ES' in symbol:
div = 100
if any(item in symbol for item in ['6E', '6B']):
div = 10000
for c in ['high', 'low', 'close']:
df[c] = df[c] / div

df.open = df.close

return df