Create a numpy array of one datetime64 per day and mark the start of the month

startdate = np.datetime64('2022-01-01T00:00:00.000000')
 # 10000 days. This array contains 0 (Day 0), 1 (Day 1), etc
day_offsets = np.arange(10000, dtype=np.int64)
usec_per_day = int(1e6) * 86400 # 86.4k sec per day, 1e6 microseconds per second
# Compute microseconds offset from first day
usec_offsets = day_offsets * usec_per_day
# Compute timestamps
timestamps = startdate + usec_offsets

# Mark start of month in boolean array
is_start_of_month = np.zeros_like(timestamps, dtype=bool)
for index, timestamp in np.ndenumerate(timestamps):
    is_start_of_month[index[0]] = timestamp.astype(datetime).day == 1

Using this method, timestamps will be the start of each day

array(['2022-01-01T00:00:00.000000', '2022-01-02T00:00:00.000000',
       '2022-01-03T00:00:00.000000', ..., '2101-12-30T00:00:00.000000',
       '2101-12-31T00:00:00.000000', '2102-01-01T00:00:00.000000'],
      dtype='datetime64[us]')