Basic Data Types in Python

Basic Data Types in Python

by John Sturtz basics python

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Basic Data Types in Python

Now you know how to interact with the Python interpreter and execute Python code. It’s time to dig into the Python language. First up is a discussion of the basic data types that are built into Python.

Here’s what you’ll learn in this tutorial:

  • You’ll learn about several basic numeric, string, and Boolean types that are built into Python. By the end of this tutorial, you’ll be familiar with what objects of these types look like, and how to represent them.
  • You’ll also get an overview of Python’s built-in functions. These are pre-written chunks of code you can call to do useful things. You have already seen the built-in print() function, but there are many others.


In Python 3, there is effectively no limit to how long an integer value can be. Of course, it is constrained by the amount of memory your system has, as are all things, but beyond that an integer can be as long as you need it to be:

>>> print(123123123123123123123123123123123123123123123123 + 1)

Python interprets a sequence of decimal digits without any prefix to be a decimal number:

>>> print(10)

The following strings can be prepended to an integer value to indicate a base other than 10:

Prefix Interpretation Base
0b (zero + lowercase letter 'b')
0B (zero + uppercase letter 'B')
Binary 2
0o (zero + lowercase letter 'o')
0O (zero + uppercase letter 'O')
Octal 8
0x (zero + lowercase letter 'x')
0X (zero + uppercase letter 'X')
Hexadecimal 16

For example:

>>> print(0o10)

>>> print(0x10)

>>> print(0b10)

For more information on integer values with non-decimal bases, see the following Wikipedia sites: Binary, Octal, and Hexadecimal.

The underlying type of a Python integer, irrespective of the base used to specify it, is called int:

>>> type(10)
<class 'int'>
>>> type(0o10)
<class 'int'>
>>> type(0x10)
<class 'int'>

Floating-Point Numbers

The float type in Python designates a floating-point number. float values are specified with a decimal point. Optionally, the character e or E followed by a positive or negative integer may be appended to specify scientific notation:

>>> 4.2
>>> type(4.2)
<class 'float'>
>>> 4.
>>> .2

>>> .4e7
>>> type(.4e7)
<class 'float'>
>>> 4.2e-4

Deep Dive: Floating-Point Representation

The following is a bit more in-depth information on how Python represents floating-point numbers internally. You can readily use floating-point numbers in Python without understanding them to this level, so don’t worry if this seems overly complicated. The information is presented here in case you are curious.

Almost all platforms represent Python float values as 64-bit “double-precision” values, according to the IEEE 754 standard. In that case, the maximum value a floating-point number can have is approximately 1.8 ⨉ 10308. Python will indicate a number greater than that by the string inf:

>>> 1.79e308
>>> 1.8e308

The closest a nonzero number can be to zero is approximately 5.0 ⨉ 10-324. Anything closer to zero than that is effectively zero:

>>> 5e-324
>>> 1e-325

Floating point numbers are represented internally as binary (base-2) fractions. Most decimal fractions cannot be represented exactly as binary fractions, so in most cases the internal representation of a floating-point number is an approximation of the actual value. In practice, the difference between the actual value and the represented value is very small and should not usually cause significant problems.

Complex Numbers

Complex numbers are specified as <real part>+<imaginary part>j. For example:

>>> 2+3j
>>> type(2+3j)
<class 'complex'>


Strings are sequences of character data. The string type in Python is called str.

String literals may be delimited using either single or double quotes. All the characters between the opening delimiter and matching closing delimiter are part of the string:

>>> print("I am a string.")
I am a string.
>>> type("I am a string.")
<class 'str'>

>>> print('I am too.')
I am too.
>>> type('I am too.')
<class 'str'>

A string in Python can contain as many characters as you wish. The only limit is your machine’s memory resources. A string can also be empty:

>>> ''

What if you want to include a quote character as part of the string itself? Your first impulse might be to try something like this:

>>> print('This string contains a single quote (') character.')
SyntaxError: invalid syntax

As you can see, that doesn’t work so well. The string in this example opens with a single quote, so Python assumes the next single quote, the one in parentheses which was intended to be part of the string, is the closing delimiter. The final single quote is then a stray and causes the syntax error shown.

If you want to include either type of quote character within the string, the simplest way is to delimit the string with the other type. If a string is to contain a single quote, delimit it with double quotes and vice versa:

>>> print("This string contains a single quote (') character.")
This string contains a single quote (') character.

>>> print('This string contains a double quote (") character.')
This string contains a double quote (") character.

Escape Sequences in Strings

Sometimes, you want Python to interpret a character or sequence of characters within a string differently. This may occur in one of two ways:

  • You may want to suppress the special interpretation that certain characters are usually given within a string.
  • You may want to apply special interpretation to characters in a string which would normally be taken literally.

You can accomplish this using a backslash (\) character. A backslash character in a string indicates that one or more characters that follow it should be treated specially. (This is referred to as an escape sequence, because the backslash causes the subsequent character sequence to “escape” its usual meaning.)

Let’s see how this works.

Suppressing Special Character Meaning

You have already seen the problems you can come up against when you try to include quote characters in a string. If a string is delimited by single quotes, you can’t directly specify a single quote character as part of the string because, for that string, the single quote has special meaning—it terminates the string:

>>> print('This string contains a single quote (') character.')
SyntaxError: invalid syntax

Specifying a backslash in front of the quote character in a string “escapes” it and causes Python to suppress its usual special meaning. It is then interpreted simply as a literal single quote character:

>>> print('This string contains a single quote (\') character.')
This string contains a single quote (') character.

The same works in a string delimited by double quotes as well:

>>> print("This string contains a double quote (\") character.")
This string contains a double quote (") character.

The following is a table of escape sequences which cause Python to suppress the usual special interpretation of a character in a string:

Usual Interpretation of
Character(s) After Backslash
“Escaped” Interpretation
\' Terminates string with single quote opening delimiter Literal single quote (') character
\" Terminates string with double quote opening delimiter Literal double quote (") character
\<newline> Terminates input line Newline is ignored
\\ Introduces escape sequence Literal backslash (\) character

Ordinarily, a newline character terminates line input. So pressing Enter in the middle of a string will cause Python to think it is incomplete:

>>> print('a

SyntaxError: EOL while scanning string literal

To break up a string over more than one line, include a backslash before each newline, and the newlines will be ignored:

>>> print('a\
... b\
... c')

To include a literal backslash in a string, escape it with a backslash:

>>> print('foo\\bar')

Applying Special Meaning to Characters

Next, suppose you need to create a string that contains a tab character in it. Some text editors may allow you to insert a tab character directly into your code. But many programmers consider that poor practice, for several reasons:

  • The computer can distinguish between a tab character and a sequence of space characters, but you can’t. To a human reading the code, tab and space characters are visually indistinguishable.
  • Some text editors are configured to automatically eliminate tab characters by expanding them to the appropriate number of spaces.
  • Some Python REPL environments will not insert tabs into code.

In Python (and almost all other common computer languages), a tab character can be specified by the escape sequence \t:

>>> print('foo\tbar')
foo     bar

The escape sequence \t causes the t character to lose its usual meaning, that of a literal t. Instead, the combination is interpreted as a tab character.

Here is a list of escape sequences that cause Python to apply special meaning instead of interpreting literally:

Escape Sequence “Escaped” Interpretation
\a ASCII Bell (BEL) character
\b ASCII Backspace (BS) character
\f ASCII Formfeed (FF) character
\n ASCII Linefeed (LF) character
\N{<name>} Character from Unicode database with given <name>
\r ASCII Carriage Return (CR) character
\t ASCII Horizontal Tab (TAB) character
\uxxxx Unicode character with 16-bit hex value xxxx
\Uxxxxxxxx Unicode character with 32-bit hex value xxxxxxxx
\v ASCII Vertical Tab (VT) character
\ooo Character with octal value ooo
\xhh Character with hex value hh


>>> print("a\tb")
a    b
>>> print("a\141\x61")
>>> print("a\nb")
>>> print('\u2192 \N{rightwards arrow}')
→ →

This type of escape sequence is typically used to insert characters that are not readily generated from the keyboard or are not easily readable or printable.

Raw Strings

A raw string literal is preceded by r or R, which specifies that escape sequences in the associated string are not translated. The backslash character is left in the string:

>>> print('foo\nbar')
>>> print(r'foo\nbar')

>>> print('foo\\bar')
>>> print(R'foo\\bar')

Triple-Quoted Strings

There is yet another way of delimiting strings in Python. Triple-quoted strings are delimited by matching groups of three single quotes or three double quotes. Escape sequences still work in triple-quoted strings, but single quotes, double quotes, and newlines can be included without escaping them. This provides a convenient way to create a string with both single and double quotes in it:

>>> print('''This string has a single (') and a double (") quote.''')
This string has a single (') and a double (") quote.

Because newlines can be included without escaping them, this also allows for multiline strings:

>>> print("""This is a
string that spans
across several lines""")
This is a
string that spans
across several lines

You will see in the upcoming tutorial on Python Program Structure how triple-quoted strings can be used to add an explanatory comment to Python code.

Boolean Type, Boolean Context, and “Truthiness”

Python 3 provides a Boolean data type. Objects of Boolean type may have one of two values, True or False:

>>> type(True)
<class 'bool'>
>>> type(False)
<class 'bool'>

As you will see in upcoming tutorials, expressions in Python are often evaluated in Boolean context, meaning they are interpreted to represent truth or falsehood. A value that is true in Boolean context is sometimes said to be “truthy,” and one that is false in Boolean context is said to be “falsy.” (You may also see “falsy” spelled “falsey.”)

The “truthiness” of an object of Boolean type is self-evident: Boolean objects that are equal to True are truthy (true), and those equal to False are falsy (false). But non-Boolean objects can be evaluated in Boolean context as well and determined to be true or false.

You will learn more about evaluation of objects in Boolean context when you encounter logical operators in the upcoming tutorial on operators and expressions in Python.

Built-In Functions

The Python interpreter supports many functions that are built-in: sixty-eight, as of Python 3.6. You will cover many of these in the following discussions, as they come up in context.

For now, a brief overview follows, just to give a feel for what is available. See the Python documentation on built-in functions for more detail. Many of the following descriptions refer to topics and concepts that will be discussed in future tutorials.


Function Description
abs() Returns absolute value of a number
divmod() Returns quotient and remainder of integer division
max() Returns the largest of the given arguments or items in an iterable
min() Returns the smallest of the given arguments or items in an iterable
pow() Raises a number to a power
round() Rounds a floating-point value
sum() Sums the items of an iterable

Type Conversion

Function Description
ascii() Returns a string containing a printable representation of an object
bin() Converts an integer to a binary string
bool() Converts an argument to a Boolean value
chr() Returns string representation of character given by integer argument
complex() Returns a complex number constructed from arguments
float() Returns a floating-point object constructed from a number or string
hex() Converts an integer to a hexadecimal string
int() Returns an integer object constructed from a number or string
oct() Converts an integer to an octal string
ord() Returns integer representation of a character
repr() Returns a string containing a printable representation of an object
str() Returns a string version of an object
type() Returns the type of an object or creates a new type object

Iterables and Iterators

Function Description
all() Returns True if all elements of an iterable are true
any() Returns True if any elements of an iterable are true
enumerate() Returns a list of tuples containing indices and values from an iterable
filter() Filters elements from an iterable
iter() Returns an iterator object
len() Returns the length of an object
map() Applies a function to every item of an iterable
next() Retrieves the next item from an iterator
range() Generates a range of integer values
reversed() Returns a reverse iterator
slice() Returns a slice object
sorted() Returns a sorted list from an iterable
zip() Creates an iterator that aggregates elements from iterables

Composite Data Type

Function Description
bytearray() Creates and returns an object of the bytearray class
bytes() Creates and returns a bytes object (similar to bytearray, but immutable)
dict() Creates a dict object
frozenset() Creates a frozenset object
list() Creates a list object
object() Creates a new featureless object
set() Creates a set object
tuple() Creates a tuple object

Classes, Attributes, and Inheritance

Function Description
classmethod() Returns a class method for a function
delattr() Deletes an attribute from an object
getattr() Returns the value of a named attribute of an object
hasattr() Returns True if an object has a given attribute
isinstance() Determines whether an object is an instance of a given class
issubclass() Determines whether a class is a subclass of a given class
property() Returns a property value of a class
setattr() Sets the value of a named attribute of an object
super() Returns a proxy object that delegates method calls to a parent or sibling class


Function Description
format() Converts a value to a formatted representation
input() Reads input from the console
open() Opens a file and returns a file object
print() Prints to a text stream or the console

Variables, References, and Scope

Function Description
dir() Returns a list of names in current local scope or a list of object attributes
globals() Returns a dictionary representing the current global symbol table
id() Returns the identity of an object
locals() Updates and returns a dictionary representing current local symbol table
vars() Returns __dict__ attribute for a module, class, or object


Function Description
callable() Returns True if object appears callable
compile() Compiles source into a code or AST object
eval() Evaluates a Python expression
exec() Implements dynamic execution of Python code
hash() Returns the hash value of an object
help() Invokes the built-in help system
memoryview() Returns a memory view object
staticmethod() Returns a static method for a function
__import__() Invoked by the import statement


In this tutorial, you learned about the built-in data types and functions Python provides.

The examples given so far have all manipulated and displayed only constant values. In most programs, you are usually going to want to create objects that change in value as the program executes.

Head to the next tutorial to learn about Python variables.

Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Basic Data Types in Python

🐍 Python Tricks 💌

Get a short & sweet Python Trick delivered to your inbox every couple of days. No spam ever. Unsubscribe any time. Curated by the Real Python team.

Python Tricks Dictionary Merge

About John Sturtz

John Sturtz John Sturtz

John is an avid Pythonista and a member of the Real Python tutorial team.

» More about John

Each tutorial at Real Python is created by a team of developers so that it meets our high quality standards. The team members who worked on this tutorial are:

Master Real-World Python Skills With Unlimited Access to Real Python

Join us and get access to thousands of tutorials, hands-on video courses, and a community of expert Pythonistas:

Level Up Your Python Skills »

Master Real-World Python Skills
With Unlimited Access to Real Python

Join us and get access to thousands of tutorials, hands-on video courses, and a community of expert Pythonistas:

Level Up Your Python Skills »

What Do You Think?

Rate this article:

What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment below and let us know.

Commenting Tips: The most useful comments are those written with the goal of learning from or helping out other students. Get tips for asking good questions and get answers to common questions in our support portal.

Looking for a real-time conversation? Visit the Real Python Community Chat or join the next “Office Hours” Live Q&A Session. Happy Pythoning!

Keep Learning

Related Tutorial Categories: basics python

Recommended Video Course: Basic Data Types in Python