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Iterating through a range of dates in Python

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Introduction

To iterate through a range of dates in Python, use a while loop with timedelta(days=1) to step from a start date to an end date. For a cleaner approach, write a generator function or use pandas.date_range() for DataFrame-oriented workflows. The dateutil.rrule module provides the most flexibility for complex recurrence patterns like "every weekday" or "first Monday of each month".

Method 1: while Loop with timedelta

python
1from datetime import date, timedelta
2
3start_date = date(2024, 1, 1)
4end_date = date(2024, 1, 10)
5
6current = start_date
7while current <= end_date:
8    print(current)
9    current += timedelta(days=1)
10
11# 2024-01-01
12# 2024-01-02
13# ...
14# 2024-01-10

Method 2: Generator Function

A reusable generator is the most Pythonic approach:

python
1from datetime import date, timedelta
2
3def date_range(start, end, step=timedelta(days=1)):
4    current = start
5    while current <= end:
6        yield current
7        current += step
8
9# Daily iteration
10for d in date_range(date(2024, 1, 1), date(2024, 1, 5)):
11    print(d)
12
13# Weekly iteration
14for d in date_range(date(2024, 1, 1), date(2024, 3, 1), timedelta(weeks=1)):
15    print(d)
16
17# Hourly iteration (with datetime)
18from datetime import datetime
19for dt in date_range(datetime(2024, 1, 1), datetime(2024, 1, 1, 12), timedelta(hours=1)):
20    print(dt)

Method 3: List Comprehension with range

python
1from datetime import date, timedelta
2
3start = date(2024, 1, 1)
4end = date(2024, 1, 10)
5num_days = (end - start).days + 1  # inclusive
6
7dates = [start + timedelta(days=i) for i in range(num_days)]
8print(dates)
9# [datetime.date(2024, 1, 1), ..., datetime.date(2024, 1, 10)]

Method 4: pandas.date_range()

python
1import pandas as pd
2
3# Daily range
4dates = pd.date_range(start='2024-01-01', end='2024-01-10', freq='D')
5for d in dates:
6    print(d.date())
7
8# Business days only (Mon-Fri)
9business_days = pd.date_range(start='2024-01-01', end='2024-01-31', freq='B')
10
11# Monthly on the first day
12monthly = pd.date_range(start='2024-01-01', periods=12, freq='MS')
13
14# Common frequency codes:
15# 'D' = daily, 'B' = business day, 'W' = weekly
16# 'MS' = month start, 'ME' = month end
17# 'QS' = quarter start, 'YS' = year start
18# 'h' = hourly, 'min' = minutely

Method 5: dateutil.rrule

python
1from dateutil.rrule import rrule, DAILY, WEEKLY, MONTHLY, MO, FR
2from datetime import date
3
4# Daily
5for d in rrule(DAILY, dtstart=date(2024, 1, 1), until=date(2024, 1, 5)):
6    print(d.date())
7
8# Every Monday and Friday
9for d in rrule(WEEKLY, byweekday=(MO, FR),
10               dtstart=date(2024, 1, 1), until=date(2024, 2, 1)):
11    print(d.date())
12
13# First day of each month
14for d in rrule(MONTHLY, bymonthday=1,
15               dtstart=date(2024, 1, 1), count=6):
16    print(d.date())

Practical Examples

Filtering Dates by Condition

python
1from datetime import date, timedelta
2
3start = date(2024, 1, 1)
4end = date(2024, 1, 31)
5
6# Only weekdays
7weekdays = [
8    start + timedelta(days=i)
9    for i in range((end - start).days + 1)
10    if (start + timedelta(days=i)).weekday() < 5
11]
12print(f"Weekdays in January 2024: {len(weekdays)}")

Processing Files by Date

python
1from datetime import date, timedelta
2
3start = date(2024, 1, 1)
4end = date(2024, 1, 5)
5
6current = start
7while current <= end:
8    filename = f"logs/app-{current.isoformat()}.log"
9    print(f"Processing {filename}")
10    current += timedelta(days=1)
11
12# Processing logs/app-2024-01-01.log
13# Processing logs/app-2024-01-02.log
14# ...

Date Range in Reverse

python
1from datetime import date, timedelta
2
3start = date(2024, 1, 10)
4end = date(2024, 1, 1)
5
6current = start
7while current >= end:
8    print(current)
9    current -= timedelta(days=1)

Common Pitfalls

  • Off-by-one error on the end date: range((end - start).days) excludes the end date. Add + 1 for an inclusive range. Similarly, the while current <= end_date pattern includes the end date, while while current < end_date excludes it.
  • Mixing date and datetime objects: Adding timedelta to a date returns a date, but adding to a datetime returns a datetime. Comparing a date to a datetime raises TypeError in Python 3. Be consistent with which type you use.
  • Using timedelta(months=1) which does not exist: timedelta only supports days, seconds, and microseconds. There is no months or years parameter because months have variable lengths. Use dateutil.relativedelta(months=1) or pandas.DateOffset(months=1) instead.
  • Not handling timezone-aware datetimes: Iterating over naive dates works fine, but mixing naive and timezone-aware datetimes raises errors. If your data is timezone-aware, ensure the start and end dates use the same timezone.
  • Creating a huge list of dates in memory: For very large ranges (millions of days), a list comprehension stores all dates in memory at once. Use a generator function with yield to iterate lazily without memory overhead.

Summary

  • Use while loop + timedelta(days=1) for simple date iteration
  • Write a generator function with yield for a reusable, memory-efficient date range
  • Use pandas.date_range() for business days, monthly, quarterly, and other complex frequencies
  • Use dateutil.rrule for recurrence patterns like "every Monday and Friday"
  • Use dateutil.relativedelta instead of timedelta when you need month or year increments
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