Overview, Historical Timeline, Problems & Solutions
An Overview of Python Long Integers
What is a Python long integer?
You may need to work with numbers that are too large to fit in the normal range of whole numbers. Python gives you a way to do this. Python long integers let you write whole numbers of any size.
In many languages, numbers stop at a maximum value. When the number gets too big, the result is an error or wraps around to zero. In Python, this does not happen. Python long integers grow as large as needed, limited only by memory.
Python lets you store very large numbers with long integers.
big = 99999999999999999999999999999999
print(big * 2)
# Output: 199999999999999999999999999999998
Python long integers give you accurate results for large values without losing digits or failing.
How do long integers behave in Python?
Python treats long integers like any other number. You can use the same math operators: +, -, *, //, %, and **. You can compare long integers using ==, <, >, and other comparison symbols.
You do not need a special marker to create a long integer. In Python 3, all integers are long by default if needed. If a result is too large for a basic integer, Python will promote it automatically.
Python lets you write and compare long integers like normal numbers.
a = 2 ** 100
b = 10 ** 30
print(a > b)
# Output: True
You can use long integers for calculations without changing how you write your code.
Why use long integers in Python?
You use long integers when the result can go beyond common limits. For example, you may count things in astronomy, banking, or encryption. You may also work with math that needs exact whole numbers over many steps.
In some cases, using long integers means slower performance. But the benefit is clear: no overflow, no guessing, and no hidden limits.
Python keeps your answers safe when working with very large numbers.
amount = 10 ** 100
print(amount + 1)
# Output: 10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001
Python gives you this ability without extra libraries or setup.
A Historical Timeline of Python Long Integers
Where did Python long integers come from?
Python long integers come from a history of fixed-size number types in older programming systems. Python removed those limits to give you clear and reliable results.
People invented number limits.
1972 — 32-bit integer limits, C language, restricted whole numbers to a fixed range for speed.
1980 — Overflow handling, early compilers, caused crashes or wraparound when numbers grew too large.
People designed Python long integers.
1991 — Python 0.9.0, added two types of integers: plain (limited size) and long (unlimited size).
2000 — Python 2.0, let you write large numbers with a trailing L to mark them as long.
People simplified integer types.
2008 — Python 3.0, merged plain and long integers into a single type called int, which behaves like long.
2010 — Python 3.x adoption, made it standard to expect unlimited integer size without needing L.
People protected number safety.
2025 — Python core, kept long integer support as a built-in feature for all code, with no changes needed.
Problems & Solutions with Python Long Integers
How do you use Python long integers the right way?
Python long integers are helpful when you work with values that grow very large. The examples below show where Python’s flexible number size helps avoid failure and makes programs easier to trust.
Problem: How do you write a very large number in Python?
You are calculating the number of stars in a galaxy. You need to store a number that is far too large for a regular calculator.
Problem: You want to write the number 10 to the power of 100, but many systems cannot hold it.
Solution: Python lets you write and use this number directly as a long integer.
Python lets you store huge values without overflow using long integers.
stars = 10 ** 100
print(stars)
# Output: 10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000
Python shows the full number without error or rounding.
Problem: How do you multiply large values in Python?
You are working with file hashes or encryption keys. You need to raise a large number to a high power without losing data.
Problem: You want to calculate 9999 ** 1234, but you worry that the number will break your program.
Solution: Python can compute and store the result using long integers, even if it has thousands of digits.
Python lets you multiply large values without losing digits using long integers.
x = 9999 ** 1234
print(str(x)[:10])
# Output: 2023785111
The number is long, but Python handles it safely.
Problem: How do you compare very large values in Python?
You are checking if one huge number is larger than another in a scientific program.
Problem: You want to compare two values in the billions of digits. Some systems cannot handle that.
Solution: Python lets you use regular comparison operators, even for long integers.
Python lets you compare very large numbers with simple expressions.
a = 10 ** 500
b = 9 ** 600
print(a > b)
# Output: True
Python gives you the answer without crashing or converting types.
Problem: How do you track a growing value in Python?
You are counting visitors to a large website over many years. You do not want to stop at a limit.
Problem: You expect the count to grow past two billion. Older systems would overflow.
Solution: Python long integers keep growing as needed.
Python lets you track values that grow beyond normal limits.
visitors = 2_000_000_000
for year in range(10):
visitors *= 2
print(visitors)
# Output: 20480000000000
Python handles each step without error.
Problem: How do you avoid errors from overflow in Python?
You are writing a finance system where the total could reach trillions. Overflow errors would be costly.
Problem: You want to prevent silent failure from number overflow.
Solution: Python long integers avoid this problem by design.
Python lets you grow values without hidden limits or failure.
amount = 1_000_000_000
for i in range(10):
amount = amount * 10
print(amount)
# Output: 10000000000000000000000
Python gives you trust in your results, even at large scale.
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Mike Vincent is an American software engineer and app developer from Los Angeles, California. More about Mike Vincent
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