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What are the data types in Python?
Python’s built-in types are the categories of values that programs work with. A practical introductory inventory is int, float, complex, bool, list, tuple, range, str, bytes, bytearray, memoryview, set, frozenset, and dict. Python also has other built-in types, so this list is not a complete catalogue of its type system.
The Python Software Foundation groups several of these by their purpose in its Python 3.14.8 built-in types documentation. The sections below focus on four useful questions: can the value be changed in place, does it have sequence order and indexing, can it be hashed for use as a key or set member, and what kind of information does it represent?
Which Python numeric types should you use?
The Python documentation identifies three distinct numeric types: integers, floating-point numbers, and complex numbers. Use the one that matches the kind of number your calculation requires.
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| Type | Represents | Mutability and practical note |
|---|---|---|
int |
Whole numbers | Immutable; Python’s documented integer semantics allow unlimited precision. |
float |
Floating-point numbers | Immutable; representation is normally based on the C double type. |
complex |
Numbers with real and imaginary floating-point components | Immutable. |
Decimal and Fraction are useful numeric types from Python’s standard library, but they are not built-in numeric types.
What is bool in Python?
bool represents a truth value and has exactly two values: True and False. It is a subclass of int, so booleans can behave numerically like 1 and 0. The Python documentation discourages relying on that behavior without an explicit conversion; use int(value) when you intentionally need a number.
When should you use a list, tuple, or range?
These are sequence types: their elements have positions and can be accessed by index. Their main difference is whether they can change and how they represent their contents.
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| Type | Mutable? | Ordered and indexable? | Hashable? | Typical use |
|---|---|---|---|---|
list |
Yes | Yes | No | A sequence you expect to update. |
tuple |
No | Yes | Only if all its contents are hashable | A sequence whose structure should not change. |
range |
No | Yes | Yes | A patterned sequence of integers, often for iteration. |
A range represents its integer pattern using a small, fixed amount of memory relative to the number of values it describes; it does not need to store each value as a separate element.
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List versus tuple
Use a list when items may be added, removed, or replaced. Use a tuple when you want an immutable sequence. A tuple’s immutability alone does not make it hashable: every contained value must also be hashable before the tuple can serve as a dictionary key or set member.
A comma creates a tuple; parentheses are often used for clarity but are not what makes it one. (x) is just x, while (x,) is a one-item tuple.
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When should you use a dictionary or a set?
Both dictionaries and sets use hashable objects, but they solve different problems. A dictionary associates keys with values; a set holds distinct members for membership checks and set operations.
| Type | Mutable? | Stores | Indexing? | Hashable? |
|---|---|---|---|---|
dict |
Yes | Hashable keys mapped to arbitrary values | No sequence-style indexing; access values by key | No |
set |
Yes | Distinct hashable objects | No | No |
frozenset |
No | Distinct hashable objects | No | Yes |
Choose a dictionary when you need to retrieve a value using a meaningful key, such as a name or identifier. Choose a set when you need uniqueness or want to test whether an item belongs to a collection, without assigning each item a separate value. Sets do not record position and cannot be indexed.
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Dictionary keys that compare equal can refer to the same entry. For example, 1, 1.0, and True can address the same dictionary key.
What is the difference between str and bytes?
str represents text; the Python documentation describes text data as being handled with str objects, or strings. Use it for human-readable words and characters. Binary data belongs in the bytes family, where the types differ in mutability and access.
| Type | Represents | Mutable? | Use |
|---|---|---|---|
str |
Text | No | Textual content in Python. |
bytes |
Binary sequence | No | Binary data that should not be changed in place. |
bytearray |
Binary sequence | Yes | Binary data that needs in-place changes. |
memoryview |
A view onto buffer data | The view does not copy the underlying data | Accessing buffer data without making a copy. |
Turning bytes into text requires decoding with an encoding. For UTF-8 data, use bytes_value.decode('utf-8') or str(bytes_value, 'utf-8'). Calling str(bytes_value) by itself does not decode the bytes into their text content.
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How do you choose a Python data type?
Start with the job the value must do, then check whether the value needs to change, preserve positions, or act as a key.
- Need an ordered sequence with updates: use a
list. - Need an ordered sequence that should not change: use a
tuple; it is hashable only when all its elements are hashable. - Need a patterned sequence of integers: use a
range. - Need to look up values by key: use a
dict. - Need distinct values or membership checks: use a
set, or afrozensetif the collection itself should be immutable and hashable. - Need human-readable text: use
str. - Need raw binary data: use
bytesfor immutable data,bytearrayfor mutable data, ormemoryviewto access buffer data without copying it. - Need a number: choose
int,float, orcomplexaccording to the numeric form; useboolfor a truth value.
The Python 3.14.8 data structures tutorial provides further examples of working with lists, tuples, dictionaries, and sets.
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