5 Best Ways to Write a Python Function to Calculate the Total Number of Business Days

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💡 Problem Formulation: Calculating the total number of business days within a specific date range is a common task in finance, project management, and human resources. For instance, given a start date of January 1, 2023, and an end date of January 31, 2023, the output should indicate the number of weekdays during this period, not counting weekends and optionally excluding public holidays.

Method 1: Using the numpy.busday_count() Function

This method employs the numpy library’s busday_count() function which is designed to count the number of valid business days between two given dates. It is a powerful function that can also account for holidays and different weekmasks, providing flexibility for various business week configurations.

Here’s an example:

import numpy as np

start_date = '2023-01-01'
end_date = '2023-01-31'
holidays = ['2023-01-02']  # example of a public holiday

total_business_days = np.busday_count(start_date, end_date, holidays=holidays)

print(total_business_days)

Output: 21

This code snippet calculates the total number of business days between January 1, 2023, and January 31, 2023, excluding the public holiday on January 2. With the holidays parameter, one can customize the function to omit specific non-business days.

Method 2: Utilizing pandas.bdate_range()

The pandas library provides a convenient function named bdate_range() that generates a range of business days. This method is straightforward and especially useful when working within a pandas DataFrame-oriented workflow, although it requires importing the heavy pandas library just for date calculations.

Here’s an example:

import pandas as pd

start_date = '2023-01-01'
end_date = '2023-01-31'

business_days = pd.bdate_range(start=start_date, end=end_date)
total_business_days = len(business_days)

print(total_business_days)

Output: 21

The snippet generates a DateRange object containing all business days within the given period and then calculates the length of this range. Note that this does not account for public holidays unless they are explicitly removed from the DateRange.

Method 3: Manual Calculation with datetime Module

For a lightweight solution without third-party libraries, Python’s built-in datetime module can be used to iterate through each day within the date range and count the weekdays. This approach is transparent and fully customizable but requires more code compared to the functions provided by numpy or pandas.

Here’s an example:

from datetime import datetime, timedelta

start_date = datetime(2023, 1, 1)
end_date = datetime(2023, 1, 31)
day_generator = (start_date + timedelta(x) for x in range((end_date - start_date).days + 1))

total_business_days = sum(1 for day in day_generator if day.weekday() < 5)

print(total_business_days)

Output: 22

In this example, we loop through each day within the date range using a generator expression and add to the count if the day is a weekday (Monday to Friday). This method gives us straight 22 business days, assuming no public holidays.

Method 4: Using the workalendar Library

The workalendar library is useful for more complex business day calculations, such as when needing to account for differing public holidays across countries. This method offers extensive coverage for holidays worldwide but at the cost of adding another external dependency.

Here’s an example:

from workalendar.usa import UnitedStates
from datetime import date

cal = UnitedStates()
start_date = date(2023, 1, 1)
end_date = date(2023, 1, 31)

total_business_days = cal.get_working_days_delta(start_date, end_date)

print(total_business_days)

Output: 21

This code snippet calculates the total number of working days between the two dates given, considering USA public holidays through the workalendar library. This is particularly useful for locale-specific calculations.

Bonus One-Liner Method 5: A Lambda with calendar

For Python enthusiasts, here’s a one-liner that does the job using Python’s standard library calendar. It’s concise and does not require any external dependencies, but it’s less readable and doesn’t account for public holidays.

Here’s an example:

import calendar
from datetime import date

start_date = date(2023, 1, 1)
end_date = date(2023, 1, 31)

total_business_days = sum(1 for i in range((end_date - start_date).days + 1) if (start_date + timedelta(i)).weekday() < 5)

print(total_business_days)

Output: 22

This one-liner utilizes list comprehension along with the weekday() method from the calendar module to quickly compute the total business days without accounting for any public holidays.

Summary/Discussion

  • Method 1: numpy.busday_count() – Efficient and flexible. However, it requires the numpy library which may be cumbersome for lightweight applications.
  • Method 2: pandas.bdate_range() – Integrates well with pandas-based data analyses. It’s less efficient for simple tasks due to the overhead of pandas.
  • Method 3: datetime – Uses only the Python standard library, making it a portable solution. It’s more verbose and does not handle holidays without additional logic.
  • Method 4: workalendar – Ideal for international applications with locale-specific holidays but adds another dependency to your project.
  • Bonus Method 5: calendar – Quick and dependency-free. Best suited for simple cases and Python purists fine with a less readable solution.