Inconsistent results between two successive runs about yfinance HOT 5 OPEN

 % cat sp500_daily_ohlc.py
import yfinance as yf
from datetime import datetime, date

auto_adjust = True
df = yf.download(["SPY"], start=date(2023, 1, 1), end=date(2024, 7, 2), auto_adjust=auto_adjust)

time_stamp = datetime.now().strftime("%Y%m%d_%H%M%S")
file_name = f"daily_auto_adjust_{auto_adjust}_{time_stamp}.csv"
print(f"writing data into {file_name}")
df.to_csv(file_name)

 % cat sp500_daily_ohlc.py
import yfinance as yf
from datetime import datetime, date

auto_adjust = False
df = yf.download(["SPY"], start=date(2023, 1, 1), end=date(2024, 7, 2), auto_adjust=auto_adjust)

time_stamp = datetime.now().strftime("%Y%m%d_%H%M%S")
file_name = f"daily_auto_adjust_{auto_adjust}_{time_stamp}.csv"
print(f"writing data into {file_name}")
df.to_csv(file_name)

 % md5sum daily_auto_adjust_*.csv
f470fbd816e09be9037edef54a0f4e59  daily_auto_adjust_False_20240714_142500.csv
001d65b7fa991f4d3aa2c1b8a99cd12d  daily_auto_adjust_False_20240714_142503.csv
ee0e0a82eb6f7307e3a540f3cf30da26  daily_auto_adjust_True_20240714_142435.csv
3b1ff5053c992fcd5965230c96333dbd  daily_auto_adjust_True_20240714_142442.csv

 % diff daily_auto_adjust_False_20240714_142500.csv daily_auto_adjust_False_20240714_142503.csv | head -n 20
2,8c2,8
< 2023-01-03,384.3699951171875,386.42999267578125,377.8299865722656,380.82000732421875,372.7542724609375,74850700
< 2023-01-04,383.17999267578125,385.8800048828125,380.0,383.760009765625,375.63201904296875,85934100
< 2023-01-05,381.7200012207031,381.8399963378906,378.760009765625,379.3800048828125,371.3446960449219,76970500
< 2023-01-06,382.6099853515625,389.25,379.4100036621094,388.0799865722656,379.8604431152344,104189600
< 2023-01-09,390.3699951171875,393.70001220703125,387.6700134277344,387.8599853515625,379.6451416015625,73978100
< 2023-01-10,387.25,390.6499938964844,386.2699890136719,390.5799865722656,382.3075256347656,65358100
< 2023-01-11,392.2300109863281,395.6000061035156,391.3800048828125,395.5199890136719,387.1428527832031,68881100
---
> 2023-01-03,384.3699951171875,386.42999267578125,377.8299865722656,380.82000732421875,372.7543029785156,74850700
> 2023-01-04,383.17999267578125,385.8800048828125,380.0,383.760009765625,375.6319580078125,85934100
> 2023-01-05,381.7200012207031,381.8399963378906,378.760009765625,379.3800048828125,371.3447570800781,76970500
> 2023-01-06,382.6099853515625,389.25,379.4100036621094,388.0799865722656,379.8605041503906,104189600
> 2023-01-09,390.3699951171875,393.70001220703125,387.6700134277344,387.8599853515625,379.6451110839844,73978100
> 2023-01-10,387.25,390.6499938964844,386.2699890136719,390.5799865722656,382.30755615234375,65358100
> 2023-01-11,392.2300109863281,395.6000061035156,391.3800048828125,395.5199890136719,387.14288330078125,68881100
10c10
< 2023-01-13,393.6199951171875,399.1000061035156,393.3399963378906,398.5,390.0597839355469,63903900
---
> 2023-01-13,393.6199951171875,399.1000061035156,393.3399963378906,398.5,390.059814453125,63903900

 % diff daily_auto_adjust_True_20240714_142435.csv daily_auto_adjust_True_20240714_142442.csv | head
2c2
< 2023-01-03,376.2290102149442,378.2453768730092,369.8275195343226,372.75421142578125,74850700
---
> 2023-01-03,376.2290410170059,378.2454078401519,369.827549812291,372.7542419433594,74850700
4,5c4,5
< 2023-01-05,373.635161717404,373.7526153349045,370.73786295793764,371.3447265625,76970500
< 2023-01-06,374.50629665205355,381.0056756304061,371.3740906518094,379.8604431152344,104189600
---
> 2023-01-05,373.63519242321297,373.7526460503659,370.73789342564294,371.3447570800781,76970500
> 2023-01-06,374.5063267394853,381.00570623999096,371.37412048760314,379.8604736328125,104189600

df = yf.download(["SPY"], start=date(2023, 1, 1), end=date(2024, 7, 2))

df = yf.download(["SPY"], start=date(2023, 1, 1), end=date(2024, 7, 2), auto_adjust=True)

df = yf.download(["SPY"], start=date(2023, 1, 1), end=date(2024, 7, 2), auto_adjust=False)