Example of some common pendulum use cases

pendulum_examples.py

#!/usr/bin/env python3
"""
Example of common pendulum use cases

Author: jongbin.jung
"""

import pandas as pd
import pendulum

current_time = pendulum.now()
print(current_time)
# > 2023-06-22T14:55:15.468166-07:00

print(current_time.in_tz("US/Eastern"))
# > 2023-06-22T17:55:15.468166-04:00

current_time.to_date_string()
# > '2023-06-22'

other_time = pendulum.parse("2023-03-06 15:32:00-07:00")
print(other_time)
# > 2023-03-06T15:32:00-07:00

current_time.start_of("month")
# > DateTime(2023, 6, 1, 0, 0, 0, tzinfo=Timezone('America/Los_Angeles'))

current_time.start_of("week")  # Returne most-recent Monday
# > DateTime(2023, 6, 19, 0, 0, 0, tzinfo=Timezone('America/Los_Angeles'))

current_time.subtract(weeks=1).start_of("week")  # Monday of previous week
# > DateTime(2023, 6, 12, 0, 0, 0, tzinfo=Timezone('America/Los_Angeles'))

# Monday prior to a year from current time?
current_time.add(years=1).start_of("week")
# > DateTime(2024, 6, 17, 0, 0, 0, tzinfo=Timezone('America/Los_Angeles'))

# Wednesday after to a month from current time?
current_time.add(months=1).next(pendulum.WEDNESDAY)
# > DateTime(2023, 7, 26, 0, 0, 0, tzinfo=Timezone('America/Los_Angeles'))

# 12 hours later?
current_time.add(hours=12)
current_time + pendulum.duration(hours=12)

# With pandas DataFrames/Series ------------------------------------------------

df = pd.DataFrame({"ts": pd.date_range("2023-06-04", "2023-06-05", periods=3)})
#                    ts
# 0 2023-06-04 00:00:00
# 1 2023-06-04 12:00:00
# 2 2023-06-05 00:00:00

df.assign(
    this_week_of=df.ts.apply(lambda t: pendulum.instance(t).start_of("week")),
)
#                    ts              this_week_of
# 0 2023-06-04 00:00:00 2023-05-29 00:00:00+00:00 2023-05-22
# 1 2023-06-04 12:00:00 2023-05-29 00:00:00+00:00 2023-05-22
# 2 2023-06-05 00:00:00 2023-06-05 00:00:00+00:00 2023-05-29