update assignment python

Python: Replacing/Updating Elements in a List (with Examples)

This concise, example-based article gives you some solutions to replace or update elements in a list in Python.

Using indexing or slicing

If you want to update or replace a single element or a slice of a list by its index, you can use direct assignment with the [] operator. This is usually the simplest and fastest way to modify a list element or slice.

This approach doesn’t create a new list but changes the original list.

Using list comprehension

If you want to update or replace multiple elements in a list based on a condition or a function, you can use list comprehension to create a new list with the updated or replaced elements. This is usually more concise and readable than other approaches. However, it may also create a new list object in memory, which may be less efficient than modifying the original list in place.

Code example:

With this approach, the original list is intact.

Using the enumerate() function

If you want to update or replace multiple elements in a list in place (without creating a new list) based on a condition or a function, you can use the enumerate() function to loop over the list and get both the index and the value of each element. Then, you can use direct assignment to modify the element in the original list. This may be more efficient than creating a new list object in memory. However, it may also be less concise and readable than using a list comprehension.

Use a for loop or a while loop

You can also use a for loop or a while loop instead of the enumerate() function. However, the code will be a little bit longer.

Example ( for loop):

Another example ( white loop):

pprint is a standard module of Python. I used it in the example above just to make the output easier to read. You can use the print() function if you don’t care how your output looks.

Next Article: Ways to Combine Lists in Python

Previous Article: Python: Using type hints with map() function – Examples

Series: Python List Tutorials (Basic and Advanced)

Related Articles

• Python Warning: Secure coding is not enabled for restorable state
• Python TypeError: write() argument must be str, not bytes
• 4 ways to install Python modules on Windows without admin rights
• Python TypeError: object of type ‘NoneType’ has no len()
• Python: How to access command-line arguments (3 approaches)
• Understanding ‘Never’ type in Python 3.11+ (5 examples)
• Python: 3 Ways to Retrieve City/Country from IP Address
• Using Type Aliases in Python: A Practical Guide (with Examples)
• Python: Defining distinct types using NewType class
• Using Optional Type in Python (explained with examples)
• Python: How to Override Methods in Classes
• Python: Define Generic Types for Lists of Nested Dictionaries

Search tutorials, examples, and resources

• PHP programming
• Symfony & Doctrine
• Laravel & Eloquent
• Tailwind CSS
• Sequelize.js
• Mongoose.js

5 Best Ways to Update Elements in a Given Range in Python

💡 Problem Formulation: Python developers often encounter the need to update elements within a certain range in a list or array. This task involves taking an existing sequence of elements and applying an operation that alters one or more items in a specified index range. For instance, given a list [1, 2, 3, 4, 5] and a requirement to increment elements from index 1 to 3 by 2, the output should be [1, 4, 5, 4, 5].

Method 1: Using Loop to Update Elements

Iterative updating of list elements using a loop is the most straightforward method. This approach involves iterating over the specified range of indices and updating each element individually according to the desired operation.

Here’s an example:

This code snippet iterates from the start_index to the end_index and increments each element by the increment_value . The modified list reflects the updated elements in the specified range.

Method 2: Using List Comprehension

List comprehension offers a more Pythonic way to update elements in a range. It’s a concise and readable method to generate a new list by applying an operation to each element within the specified indices.

In this code snippet, list comprehension is used to iterate over each element and its index. If the index is within the given range, the element is incremented by increment_value , and if not, the element remains unchanged.

Method 3: Using Slicing and Mapping

Using slicing in combination with the map() function enables bulk operations on a sublist and reassigns the updated range back to the original list. This method is suitable for performing complex transforms.

This code snippet uses a lambda function to add the increment_value to each element in the slice of the list. Afterwards, the updated slice replaces the original range in the list, resulting in the desired updated list.

Method 4: Using NumPy Library

For numerical computations and array operations, using the NumPy library is the most efficient approach. NumPy provides vectorized operations that are fast and convenient for updating elements in bulk.

NumPy allows using direct array slicing and arithmetic operations to update the elements. The code applies an in-place addition to the specified range, thus modifying the array with great performance.

Bonus One-Liner Method 5: Using slice assignment

Python’s slice assignment allows you to update elements in a range directly. This one-liner approach is quick but may be less readable for complex operations.

This one-liner updates the slice directly with a list comprehension that operates on the sliced segment. It’s essentially a compact version of method 2, utilizing direct slice assignment for the update.

Summary/Discussion

• Method 1: Loop to Update Elements. Simple and easy to understand. May be inefficient for large lists.
• Method 2: List Comprehension. Compact and Pythonic. Can lack clarity with complex operations.
• Method 3: Slicing and Mapping. Effective for complex updates. Readability can suffer in comparison to list comprehension.
• Method 4: Using NumPy Library. Highly efficient for numerical updates. Requires external library and is specific to numerical data.
• Method 5: Slice Assignment One-Liner. Fast and concise for simple updates. Can become unwieldy for more elaborate tasks.

Assignment Operators

Add and assign, subtract and assign, multiply and assign, divide and assign, floor divide and assign, exponent and assign, modulo and assign.

For demonstration purposes, let’s use a single variable, num . Initially, we set num to 6. We can apply all of these operators to num and update it accordingly.

Assigning the value of 6 to num results in num being 6.

Expression: num = 6

Adding 3 to num and assigning the result back to num would result in 9.

Expression: num += 3

Subtracting 3 from num and assigning the result back to num would result in 6.

Expression: num -= 3

Multiplying num by 3 and assigning the result back to num would result in 18.

Expression: num *= 3

Dividing num by 3 and assigning the result back to num would result in 6.0 (always a float).

Expression: num /= 3

Performing floor division on num by 3 and assigning the result back to num would result in 2.

Expression: num //= 3

Raising num to the power of 3 and assigning the result back to num would result in 216.

Expression: num **= 3

Calculating the remainder when num is divided by 3 and assigning the result back to num would result in 2.

Expression: num %= 3

We can effectively put this into Python code, and you can experiment with the code yourself! Click the “Run” button to see the output.

The above code is useful when we want to update the same number. We can also use two different numbers and use the assignment operators to apply them on two different values.

Python Tutorial

File handling, python modules, python numpy, python pandas, python matplotlib, python scipy, machine learning, python mysql, python mongodb, python reference, module reference, python how to, python examples, python assignment operators.

Assignment operators are used to assign values to variables:

Related Pages

COLOR PICKER

Contact Sales

If you want to use W3Schools services as an educational institution, team or enterprise, send us an e-mail: [email protected]

Report Error

If you want to report an error, or if you want to make a suggestion, send us an e-mail: [email protected]

Top Tutorials

Top references, top examples, get certified.

• Table of Contents
• Course Home
• Assignments
• Peer Instruction (Instructor)
• Peer Instruction (Student)
• Change Course
• Instructor's Page
• Progress Page
• Edit Profile
• Change Password
• Scratch ActiveCode
• Scratch Activecode
• Instructors Guide
• About Runestone
• Report A Problem
• Mixed-up code Questions
• Write Code Questions
• Peer Instruction: Iterations Multiple Choice Questions
• 6.1 Updating variables
• 6.2 The while statement
• 6.3 Infinite loops
• 6.4 Finishing iterations with continue
• 6.5 Definite loops using for
• 6.6 Loop patterns
• 6.7 Debugging
• 6.8 Glossary
• 6.9 Multiple Choice Questions
• 6.10 Mixed-up code Questions
• 6.11 Write Code Questions
• 6.12 Group Work - Loops (For, Range, While)
• 6. Loops and Iterations" data-toggle="tooltip">
• 6.2. The while statement' data-toggle="tooltip" >

Before you keep reading...

Runestone Academy can only continue if we get support from individuals like you. As a student you are well aware of the high cost of textbooks. Our mission is to provide great books to you for free, but we ask that you consider a $10 donation, more if you can or less if $10 is a burden.

Making great stuff takes time and $$. If you appreciate the book you are reading now and want to keep quality materials free for other students please consider a donation to Runestone Academy. We ask that you consider a $10 donation, but if you can give more thats great, if $10 is too much for your budget we would be happy with whatever you can afford as a show of support.

6.1. Updating variables ¶

Commonly, assignment statements are used to update a variable, where the new value of the variable depends on the old.

This means “get the current value of x , add 1, and then update x with the new value.”

If you try to update a variable that doesn’t exist, you get an error, because Python evaluates the right side before it assigns a value to x :

Before you can update a variable, you have to initialize it, usually with a simple assignment:

When you update a variable by adding 1 it’s called an increment ; subtracting 1 is called a decrement .

Q-5: Consider the code block below. What happens when you run this program?

• The integer "2" prints.
• Incorrect! Take another look at the second line. Try again!
• We get a TypeError.
• Incorrect! This will not cause a TypeError because x, y, and 1 are all integers. Try again!
• We get a NameError.
• Correct! This will cause a NameError because x has not been initialized yet.
• The program compiles with no errors but nothing prints.
• Incorrect! This program will not compile. Try again!

• Python Course
• Python Basics
• Interview Questions
• Python Quiz
• Popular Packages
• Python Projects
• Practice Python
• AI With Python
• Learn Python3
• Python Automation
• Python Web Dev
• DSA with Python
• Python OOPs
• Dictionaries

Assignment Operators in Python

The Python Operators are used to perform operations on values and variables. These are the special symbols that carry out arithmetic, logical, and bitwise computations. The value the operator operates on is known as the Operand. Here, we will cover Different Assignment operators in Python .

Here are the Assignment Operators in Python with examples.

Assignment Operator

Assignment Operators are used to assign values to variables. This operator is used to assign the value of the right side of the expression to the left side operand.

Addition Assignment Operator

The Addition Assignment Operator is used to add the right-hand side operand with the left-hand side operand and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the addition assignment operator which will first perform the addition operation and then assign the result to the variable on the left-hand side.

S ubtraction Assignment Operator

The Subtraction Assignment Operator is used to subtract the right-hand side operand from the left-hand side operand and then assigning the result to the left-hand side operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the subtraction assignment operator which will first perform the subtraction operation and then assign the result to the variable on the left-hand side.

M ultiplication Assignment Operator

The Multiplication Assignment Operator is used to multiply the right-hand side operand with the left-hand side operand and then assigning the result to the left-hand side operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the multiplication assignment operator which will first perform the multiplication operation and then assign the result to the variable on the left-hand side.

D ivision Assignment Operator

The Division Assignment Operator is used to divide the left-hand side operand with the right-hand side operand and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the division assignment operator which will first perform the division operation and then assign the result to the variable on the left-hand side.

M odulus Assignment Operator

The Modulus Assignment Operator is used to take the modulus, that is, it first divides the operands and then takes the remainder and assigns it to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the modulus assignment operator which will first perform the modulus operation and then assign the result to the variable on the left-hand side.

F loor Division Assignment Operator

The Floor Division Assignment Operator is used to divide the left operand with the right operand and then assigs the result(floor value) to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the floor division assignment operator which will first perform the floor division operation and then assign the result to the variable on the left-hand side.

Exponentiation Assignment Operator

The Exponentiation Assignment Operator is used to calculate the exponent(raise power) value using operands and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the exponentiation assignment operator which will first perform exponent operation and then assign the result to the variable on the left-hand side.

Bitwise AND Assignment Operator

The Bitwise AND Assignment Operator is used to perform Bitwise AND operation on both operands and then assigning the result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise AND assignment operator which will first perform Bitwise AND operation and then assign the result to the variable on the left-hand side.

Bitwise OR Assignment Operator

The Bitwise OR Assignment Operator is used to perform Bitwise OR operation on the operands and then assigning result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise OR assignment operator which will first perform bitwise OR operation and then assign the result to the variable on the left-hand side.

Bitwise XOR Assignment Operator 

The Bitwise XOR Assignment Operator is used to perform Bitwise XOR operation on the operands and then assigning result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise XOR assignment operator which will first perform bitwise XOR operation and then assign the result to the variable on the left-hand side.

Bitwise Right Shift Assignment Operator

The Bitwise Right Shift Assignment Operator is used to perform Bitwise Right Shift Operation on the operands and then assign result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise right shift assignment operator which will first perform bitwise right shift operation and then assign the result to the variable on the left-hand side.

Bitwise Left Shift Assignment Operator

The Bitwise Left Shift Assignment Operator is used to perform Bitwise Left Shift Opertator on the operands and then assign result to the left operand.

Example: In this code we have two variables ‘a’ and ‘b’ and assigned them with some integer value. Then we have used the bitwise left shift assignment operator which will first perform bitwise left shift operation and then assign the result to the variable on the left-hand side.

Walrus Operator

The Walrus Operator in Python is a new assignment operator which is introduced in Python version 3.8 and higher. This operator is used to assign a value to a variable within an expression.

Example: In this code, we have a Python list of integers. We have used Python Walrus assignment operator within the Python while loop . The operator will solve the expression on the right-hand side and assign the value to the left-hand side operand ‘x’ and then execute the remaining code.

Assignment Operators in Python – FAQs

What are assignment operators in python.

Assignment operators in Python are used to assign values to variables. These operators can also perform additional operations during the assignment. The basic assignment operator is = , which simply assigns the value of the right-hand operand to the left-hand operand. Other common assignment operators include += , -= , *= , /= , %= , and more, which perform an operation on the variable and then assign the result back to the variable.

What is the := Operator in Python?

The := operator, introduced in Python 3.8, is known as the “walrus operator”. It is an assignment expression, which means that it assigns values to variables as part of a larger expression. Its main benefit is that it allows you to assign values to variables within expressions, including within conditions of loops and if statements, thereby reducing the need for additional lines of code. Here’s an example: # Example of using the walrus operator in a while loop while (n := int(input("Enter a number (0 to stop): "))) != 0: print(f"You entered: {n}") This loop continues to prompt the user for input and immediately uses that input in both the condition check and the loop body.

What is the Assignment Operator in Structure?

In programming languages that use structures (like C or C++), the assignment operator = is used to copy values from one structure variable to another. Each member of the structure is copied from the source structure to the destination structure. Python, however, does not have a built-in concept of ‘structures’ as in C or C++; instead, similar functionality is achieved through classes or dictionaries.

What is the Assignment Operator in Python Dictionary?

In Python dictionaries, the assignment operator = is used to assign a new key-value pair to the dictionary or update the value of an existing key. Here’s how you might use it: my_dict = {} # Create an empty dictionary my_dict['key1'] = 'value1' # Assign a new key-value pair my_dict['key1'] = 'updated value' # Update the value of an existing key print(my_dict) # Output: {'key1': 'updated value'}

What is += and -= in Python?

The += and -= operators in Python are compound assignment operators. += adds the right-hand operand to the left-hand operand and assigns the result to the left-hand operand. Conversely, -= subtracts the right-hand operand from the left-hand operand and assigns the result to the left-hand operand. Here are examples of both: # Example of using += a = 5 a += 3 # Equivalent to a = a + 3 print(a) # Output: 8 # Example of using -= b = 10 b -= 4 # Equivalent to b = b - 4 print(b) # Output: 6 These operators make code more concise and are commonly used in loops and iterative data processing.

Please Login to comment...

Similar reads.

• Python-Operators
• Best External Hard Drives for Mac in 2024: Top Picks for MacBook Pro, MacBook Air & More
• How to Watch NFL Games Live Streams Free
• OpenAI o1 AI Model Launched: Explore o1-Preview, o1-Mini, Pricing & Comparison
• How to Merge Cells in Google Sheets: Step by Step Guide
• #geekstreak2024 – 21 Days POTD Challenge Powered By Deutsche Bank

Improve your Coding Skills with Practice

What kind of Experience do you want to share?

Add and update an item in a dictionary in Python

This article explains how to add an item (key-value pair) to a dictionary ( dict ) or update the value of an existing item in Python.

Add or update a single item in a dictionary

Specify keyword arguments, specify an iterable of key-value pairs, specify other dictionaries.

See the following articles to learn how to add a dictionary to a dictionary (i.e., merge dictionaries), remove an item from a dictionary, and change a key name.

• Merge dictionaries in Python
• Remove an item from a dictionary in Python (clear, pop, popitem, del)
• Change a key name in a dictionary in Python

You can add an item to a dictionary or update the value of an existing item as follows.

If a non-existent key is specified, a new item is added; if an existing key is specified, the value of that item is updated (overwritten).

To avoid updating the value for an existing key, use the setdefault() method. See the following article for details.

• Add an item if the key does not exist in dict with setdefault in Python

Add or update multiple items in a dictionary: update()

You can add or update multiple items at once using the update() method.

• Built-in Types - dict.update() — Python 3.11.3 documentation

If the keyword argument ( key=value ) is specified for update() , the item with that key and value is added. If the key already exists, it is overwritten with the value specified in the argument.

An error is raised if the same key is specified multiple times.

In this case, keys must be valid identifiers in Python. They cannot start with a number or contain symbols other than _ .

• Valid variable names and naming rules in Python

In other approaches, values that are invalid as identifiers can be used as keys.

You can pass a list of (key, value) pairs to update() . If a key in the list duplicates an existing key, it is overwritten with the value specified in the argument.

In the above example, a list of tuples was specified. However, any iterable containing key-value pairs (two-element iterables) is acceptable. This could include a tuple of lists, such as ([key1, value1], [key2, value2], ...) , or other iterable structures.

You can use zip() to add items by pairing elements from a list of keys and a list of values.

• zip() in Python: Get elements from multiple lists

When using an iterable of key-value pairs, duplicate keys are acceptable. The value corresponding to the later occurrence of a key will overwrite the earlier one.

You can specify another dictionary as an argument to update() to add all its items.

Passing multiple dictionaries directly to update() will result in an error. You can prefix dictionaries with ** and pass each element as a keyword argument.

• Expand and pass a list and dictionary as arguments in Python

When using ** , as shown in the above example, duplicate keys between the caller's dictionary and the dictionary specified in the argument are not a problem. However, if the same keys are found across multiple dictionaries specified in the argument, this will result in an error.

For more details on merging dictionaries, refer to the following article.

Related Categories

Related articles.

• Extract specific key values from a list of dictionaries in Python
• Pretty-print with pprint in Python
• Sort a list of dictionaries by the value of the specific key in Python
• Create a dictionary in Python ({}, dict(), dict comprehensions)
• Get keys from a dictionary by value in Python
• Set operations on multiple dictionary keys in Python
• Swap keys and values in a dictionary in Python
• Iterate through dictionary keys and values in Python
• Check if a key/value exists in a dictionary in Python
• Get maximum/minimum values and keys in Python dictionaries

• Python »
• 3.12.6 Documentation »
• The Python Tutorial »
• 5. Data Structures
• Theme Auto Light Dark |

5. Data Structures ¶

This chapter describes some things you’ve learned about already in more detail, and adds some new things as well.

5.1. More on Lists ¶

The list data type has some more methods. Here are all of the methods of list objects:

Add an item to the end of the list. Equivalent to a[len(a):] = [x] .

Extend the list by appending all the items from the iterable. Equivalent to a[len(a):] = iterable .

Insert an item at a given position. The first argument is the index of the element before which to insert, so a.insert(0, x) inserts at the front of the list, and a.insert(len(a), x) is equivalent to a.append(x) .

Remove the first item from the list whose value is equal to x . It raises a ValueError if there is no such item.

Remove the item at the given position in the list, and return it. If no index is specified, a.pop() removes and returns the last item in the list. It raises an IndexError if the list is empty or the index is outside the list range.

Remove all items from the list. Equivalent to del a[:] .

Return zero-based index in the list of the first item whose value is equal to x . Raises a ValueError if there is no such item.

The optional arguments start and end are interpreted as in the slice notation and are used to limit the search to a particular subsequence of the list. The returned index is computed relative to the beginning of the full sequence rather than the start argument.

Return the number of times x appears in the list.

Sort the items of the list in place (the arguments can be used for sort customization, see sorted() for their explanation).

Reverse the elements of the list in place.

Return a shallow copy of the list. Equivalent to a[:] .

An example that uses most of the list methods:

You might have noticed that methods like insert , remove or sort that only modify the list have no return value printed – they return the default None . [ 1 ] This is a design principle for all mutable data structures in Python.

Another thing you might notice is that not all data can be sorted or compared. For instance, [None, 'hello', 10] doesn’t sort because integers can’t be compared to strings and None can’t be compared to other types. Also, there are some types that don’t have a defined ordering relation. For example, 3+4j < 5+7j isn’t a valid comparison.

5.1.1. Using Lists as Stacks ¶

The list methods make it very easy to use a list as a stack, where the last element added is the first element retrieved (“last-in, first-out”). To add an item to the top of the stack, use append() . To retrieve an item from the top of the stack, use pop() without an explicit index. For example:

5.1.2. Using Lists as Queues ¶

It is also possible to use a list as a queue, where the first element added is the first element retrieved (“first-in, first-out”); however, lists are not efficient for this purpose. While appends and pops from the end of list are fast, doing inserts or pops from the beginning of a list is slow (because all of the other elements have to be shifted by one).

To implement a queue, use collections.deque which was designed to have fast appends and pops from both ends. For example:

5.1.3. List Comprehensions ¶

List comprehensions provide a concise way to create lists. Common applications are to make new lists where each element is the result of some operations applied to each member of another sequence or iterable, or to create a subsequence of those elements that satisfy a certain condition.

For example, assume we want to create a list of squares, like:

Note that this creates (or overwrites) a variable named x that still exists after the loop completes. We can calculate the list of squares without any side effects using:

or, equivalently:

which is more concise and readable.

A list comprehension consists of brackets containing an expression followed by a for clause, then zero or more for or if clauses. The result will be a new list resulting from evaluating the expression in the context of the for and if clauses which follow it. For example, this listcomp combines the elements of two lists if they are not equal:

and it’s equivalent to:

Note how the order of the for and if statements is the same in both these snippets.

If the expression is a tuple (e.g. the (x, y) in the previous example), it must be parenthesized.

List comprehensions can contain complex expressions and nested functions:

5.1.4. Nested List Comprehensions ¶

The initial expression in a list comprehension can be any arbitrary expression, including another list comprehension.

Consider the following example of a 3x4 matrix implemented as a list of 3 lists of length 4:

The following list comprehension will transpose rows and columns:

As we saw in the previous section, the inner list comprehension is evaluated in the context of the for that follows it, so this example is equivalent to:

which, in turn, is the same as:

In the real world, you should prefer built-in functions to complex flow statements. The zip() function would do a great job for this use case:

See Unpacking Argument Lists for details on the asterisk in this line.

5.2. The del statement ¶

There is a way to remove an item from a list given its index instead of its value: the del statement. This differs from the pop() method which returns a value. The del statement can also be used to remove slices from a list or clear the entire list (which we did earlier by assignment of an empty list to the slice). For example:

del can also be used to delete entire variables:

Referencing the name a hereafter is an error (at least until another value is assigned to it). We’ll find other uses for del later.

5.3. Tuples and Sequences ¶

We saw that lists and strings have many common properties, such as indexing and slicing operations. They are two examples of sequence data types (see Sequence Types — list, tuple, range ). Since Python is an evolving language, other sequence data types may be added. There is also another standard sequence data type: the tuple .

A tuple consists of a number of values separated by commas, for instance:

As you see, on output tuples are always enclosed in parentheses, so that nested tuples are interpreted correctly; they may be input with or without surrounding parentheses, although often parentheses are necessary anyway (if the tuple is part of a larger expression). It is not possible to assign to the individual items of a tuple, however it is possible to create tuples which contain mutable objects, such as lists.

Though tuples may seem similar to lists, they are often used in different situations and for different purposes. Tuples are immutable , and usually contain a heterogeneous sequence of elements that are accessed via unpacking (see later in this section) or indexing (or even by attribute in the case of namedtuples ). Lists are mutable , and their elements are usually homogeneous and are accessed by iterating over the list.

A special problem is the construction of tuples containing 0 or 1 items: the syntax has some extra quirks to accommodate these. Empty tuples are constructed by an empty pair of parentheses; a tuple with one item is constructed by following a value with a comma (it is not sufficient to enclose a single value in parentheses). Ugly, but effective. For example:

The statement t = 12345, 54321, 'hello!' is an example of tuple packing : the values 12345 , 54321 and 'hello!' are packed together in a tuple. The reverse operation is also possible:

This is called, appropriately enough, sequence unpacking and works for any sequence on the right-hand side. Sequence unpacking requires that there are as many variables on the left side of the equals sign as there are elements in the sequence. Note that multiple assignment is really just a combination of tuple packing and sequence unpacking.

5.4. Sets ¶

Python also includes a data type for sets . A set is an unordered collection with no duplicate elements. Basic uses include membership testing and eliminating duplicate entries. Set objects also support mathematical operations like union, intersection, difference, and symmetric difference.

Curly braces or the set() function can be used to create sets. Note: to create an empty set you have to use set() , not {} ; the latter creates an empty dictionary, a data structure that we discuss in the next section.

Here is a brief demonstration:

Similarly to list comprehensions , set comprehensions are also supported:

5.5. Dictionaries ¶

Another useful data type built into Python is the dictionary (see Mapping Types — dict ). Dictionaries are sometimes found in other languages as “associative memories” or “associative arrays”. Unlike sequences, which are indexed by a range of numbers, dictionaries are indexed by keys , which can be any immutable type; strings and numbers can always be keys. Tuples can be used as keys if they contain only strings, numbers, or tuples; if a tuple contains any mutable object either directly or indirectly, it cannot be used as a key. You can’t use lists as keys, since lists can be modified in place using index assignments, slice assignments, or methods like append() and extend() .

It is best to think of a dictionary as a set of key: value pairs, with the requirement that the keys are unique (within one dictionary). A pair of braces creates an empty dictionary: {} . Placing a comma-separated list of key:value pairs within the braces adds initial key:value pairs to the dictionary; this is also the way dictionaries are written on output.

The main operations on a dictionary are storing a value with some key and extracting the value given the key. It is also possible to delete a key:value pair with del . If you store using a key that is already in use, the old value associated with that key is forgotten. It is an error to extract a value using a non-existent key.

Performing list(d) on a dictionary returns a list of all the keys used in the dictionary, in insertion order (if you want it sorted, just use sorted(d) instead). To check whether a single key is in the dictionary, use the in keyword.

Here is a small example using a dictionary:

The dict() constructor builds dictionaries directly from sequences of key-value pairs:

In addition, dict comprehensions can be used to create dictionaries from arbitrary key and value expressions:

When the keys are simple strings, it is sometimes easier to specify pairs using keyword arguments:

5.6. Looping Techniques ¶

When looping through dictionaries, the key and corresponding value can be retrieved at the same time using the items() method.

When looping through a sequence, the position index and corresponding value can be retrieved at the same time using the enumerate() function.

To loop over two or more sequences at the same time, the entries can be paired with the zip() function.

To loop over a sequence in reverse, first specify the sequence in a forward direction and then call the reversed() function.

To loop over a sequence in sorted order, use the sorted() function which returns a new sorted list while leaving the source unaltered.

Using set() on a sequence eliminates duplicate elements. The use of sorted() in combination with set() over a sequence is an idiomatic way to loop over unique elements of the sequence in sorted order.

It is sometimes tempting to change a list while you are looping over it; however, it is often simpler and safer to create a new list instead.

5.7. More on Conditions ¶

The conditions used in while and if statements can contain any operators, not just comparisons.

The comparison operators in and not in are membership tests that determine whether a value is in (or not in) a container. The operators is and is not compare whether two objects are really the same object. All comparison operators have the same priority, which is lower than that of all numerical operators.

Comparisons can be chained. For example, a < b == c tests whether a is less than b and moreover b equals c .

Comparisons may be combined using the Boolean operators and and or , and the outcome of a comparison (or of any other Boolean expression) may be negated with not . These have lower priorities than comparison operators; between them, not has the highest priority and or the lowest, so that A and not B or C is equivalent to (A and (not B)) or C . As always, parentheses can be used to express the desired composition.

The Boolean operators and and or are so-called short-circuit operators: their arguments are evaluated from left to right, and evaluation stops as soon as the outcome is determined. For example, if A and C are true but B is false, A and B and C does not evaluate the expression C . When used as a general value and not as a Boolean, the return value of a short-circuit operator is the last evaluated argument.

It is possible to assign the result of a comparison or other Boolean expression to a variable. For example,

Note that in Python, unlike C, assignment inside expressions must be done explicitly with the walrus operator := . This avoids a common class of problems encountered in C programs: typing = in an expression when == was intended.

5.8. Comparing Sequences and Other Types ¶

Sequence objects typically may be compared to other objects with the same sequence type. The comparison uses lexicographical ordering: first the first two items are compared, and if they differ this determines the outcome of the comparison; if they are equal, the next two items are compared, and so on, until either sequence is exhausted. If two items to be compared are themselves sequences of the same type, the lexicographical comparison is carried out recursively. If all items of two sequences compare equal, the sequences are considered equal. If one sequence is an initial sub-sequence of the other, the shorter sequence is the smaller (lesser) one. Lexicographical ordering for strings uses the Unicode code point number to order individual characters. Some examples of comparisons between sequences of the same type:

Note that comparing objects of different types with < or > is legal provided that the objects have appropriate comparison methods. For example, mixed numeric types are compared according to their numeric value, so 0 equals 0.0, etc. Otherwise, rather than providing an arbitrary ordering, the interpreter will raise a TypeError exception.

Table of Contents

• 5.1.1. Using Lists as Stacks
• 5.1.2. Using Lists as Queues
• 5.1.3. List Comprehensions
• 5.1.4. Nested List Comprehensions
• 5.2. The del statement
• 5.3. Tuples and Sequences
• 5.5. Dictionaries
• 5.6. Looping Techniques
• 5.7. More on Conditions
• 5.8. Comparing Sequences and Other Types

Previous topic

4. More Control Flow Tools

• Report a Bug
• Show Source

How to Update Python

Python receives a major update once every 12 months, with bug-fix updates and security patches being released every few months. The most recent version of Python – Python 3.9 – introduces features like Union Operators in dict, the Flexible function, and Type Hinting Generics.  Updating Python can be confusing regardless of which OS you’re running. Do you remove the old version first? Or can you update the package directly? Here’s an easy tutorial on how to update Python.

If you are struggling with your Python coursework then you can consider taking  help with python homework  and excel in Python programming.

How to Update Python in Linux, Mac, or Windows

It is possible to install two major versions of Python – say, Python 2.x and Python 3.x – on one computer and use both. If you want to move from Python 2.x to 3.x, you don’t have to uninstall the previous version unless you don’t want to use it anymore. Furthermore, Python 3 now comes with the “py.exe” launcher integrated by default. The launcher helps users in two ways: 

• Users can run Python from any shell using the command “py.” Typing “python” is no longer required.
• Allows you to use two different versions of Python 3 at the same time. You can specify which version of Python you want to use to run code with simple switches in commands (like “py -3.6”).

In other words, you won’t need to change the PATH variable every time you want to use another version of Python. But the launcher only comes installed on the Windows version of Python 3. Updating Python in computers with Linux or macOS can be more complicated.

Note: If you’ve not installed Python on your computer yet, you cannot update to a newer version. If you’re having trouble installing Python on your computer, reading our Python installation guide will help.

Updating Python in Linux

Updating Python Using Apt-Get

Updating Python in Mac

Updating Python on a machine with macOS is a lot easier than updating it on a Linux machine. A Mac can have more than one version of Python installed. Therefore, you can update Python by visiting https://www.python.org/downloads/mac-osx/ , downloading the installer, and running it. If you have Homebrew installed on your Mac, you can run the following command on the Terminal:             brew install python After the process completes, your computer will have the latest version of Python 3. You can verify this by running the command:             python3 --version If you want to upgrade pip and add a new library to it, you can enter the following command:             pip3 install <PROJECT NAME>

Updating Python in Windows

Every version of Python, including the newest release , has some limitations. However, updating to the latest version of Python allows you to use all the new features. Furthermore, updated versions also come with bug fixes and improved security measures . With this guide handy, you should be able to get your hands on the newest Python version in a matter of minutes. Going through our Python usage guide next will help you quickly pick up all that you can do with Python.

• Python Tips and Tricks
• Python Library Tutorials
• Python How To's
• Python Tutorials

Signup for new content

Thank you for joining our mailing list!

Latest Articles

• Five Key Applications of Artificial Intelligence and Machine Learning in Finance and Python's Impact on Them
• Essential System Administrator Tools: Script Automation - Bash, Python and PowerShell
• The Benefits of Engaging in Python Projects for Beginners
• Understanding Web App Development: A Beginner's Guide
• Discover How to Get FL Studio for Free and Start Creating Music Today
• Data Structure
• csv in python
• logging in python
• Python Counter
• python subprocess
• numpy module
• Python code generators
• python tutorial
• csv file python
• python logging
• Counter class
• Python assert
• numbers_list
• binary search
• Insert Node
• Python tips
• python dictionary
• Python's Built-in CSV Library
• logging APIs
• Constructing Counters
• Matplotlib Plotting
• any() Function
• linear search
• Python tools
• python update
• logging module
• Concatenate Data Frames
• python comments
• Recursion Limit
• Data structures
• installation
• python function
• pandas installation
• Zen of Python
• concatenation
• Echo Client
• NumPy Pad()
• install python
• how to install pandas
• Philosophy of Programming
• concat() function
• Socket State
• Python YAML
• remove a node
• function scope
• Tuple in Python
• pandas groupby
• socket programming
• Python Modulo
• Dictionary Update()
• datastructure
• bubble sort
• find a node
• calling function
• GroupBy method
• Np.Arange()
• Modulo Operator
• Python Or Operator
• Python salaries
• pyenv global
• NumPy arrays
• insertion sort
• in place reversal
• learn python
• python packages
• zeros() function
• Scikit Learn
• HTML Parser
• circular queue
• effiiciency
• python maps
• Num Py Zeros
• Python Lists
• HTML Extraction
• selection sort
• Programming
• install python on windows
• reverse string
• python Code Editors
• pandas.reset_index
• Infinite Numbers in Python
• Python Readlines()
• Programming language
• remove python
• concatenate string
• Code Editors
• reset_index()
• Train Test Split
• Local Testing Server
• Python Input
• priority queue
• web development
• uninstall python
• python string
• code interface
• round numbers
• train_test_split()
• Flask module
• Linked List
• machine learning
• compare string
• pandas dataframes
• arange() method
• Singly Linked List
• python scripts
• learning python
• python bugs
• ZipFunction
• plus equals
• np.linspace
• SQLAlchemy advance

• All Communities Products ArcGIS Pro ArcGIS Survey123 ArcGIS Online ArcGIS Enterprise Data Management Geoprocessing ArcGIS Web AppBuilder ArcGIS Experience Builder ArcGIS Dashboards ArcGIS Spatial Analyst ArcGIS CityEngine All Products Communities Industries Education Water Resources State & Local Government Transportation Gas and Pipeline Water Utilities Roads and Highways Telecommunications Natural Resources Electric Public Safety All Industries Communities Developers Python JavaScript Maps SDK Native Maps SDKs ArcGIS API for Python ArcObjects SDK ArcGIS Pro SDK Developers - General ArcGIS REST APIs and Services ArcGIS Online Developers File Geodatabase API Game Engine Maps SDKs All Developers Communities Global Comunidad Esri Colombia - Ecuador - Panamá ArcGIS 開発者コミュニティ Czech GIS ArcNesia Esri India GeoDev Germany ArcGIS Content - Esri Nederland Esri Italia Community Comunidad GEOTEC Esri Ireland Používatelia ArcGIS All Global Communities All Communities Developers User Groups Industries Services Community Resources Global Events Learning Networks ArcGIS Topics GIS Life View All Communities
• ArcGIS Ideas
• Community Resources Community Help Documents Community Blog Community Feedback Member Introductions Community Ideas All Community Resources
• All Communities
• Change "Assign_Status" by python script for Workfo...
• GeoNet, The Esri Community - STAGE
• ArcGIS AppStudio
• ArcGIS AppStudio Questions
• Subscribe to RSS Feed
• Mark Topic as New
• Mark Topic as Read
• Float this Topic for Current User
• Printer Friendly Page

Change "Assign_Status" by python script for Workforce

• Mark as New
• Report Inappropriate Content
• Previous Topic

• Terms of Use
• Community Guidelines
• Community Resources
• Contact Community Team
• Trust Center
• Contact Esri
• ' + lingoLXML.snapshotItem(k).textContent + '

• Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers
• Advertising & Talent Reach devs & technologists worldwide about your product, service or employer brand
• OverflowAI GenAI features for Teams
• OverflowAPI Train & fine-tune LLMs
• Labs The future of collective knowledge sharing
• About the company Visit the blog

Collectives™ on Stack Overflow

Find centralized, trusted content and collaborate around the technologies you use most.

Q&A for work

Connect and share knowledge within a single location that is structured and easy to search.

Get early access and see previews of new features.

Update locals from inside a function

I would like to write a function which receives a local namespace dictionary and update it. Something like this:

When I call this function from the interactive python shell it works all right, like this:

However, when I call UpdateLocals from inside a function, it doesn't do what I expect:

How can I make the second case work like the first?

Aswin's explanation makes sense and is very helpful to me. However I still want a mechanism to update the local variables. Before I figure out a less ugly approach, I'm going to do the following:

Of course the construction of the string statements can be automated, and the details can be hidden from the user.

• Why do you even want to do this? The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter. –  Konstantin Commented May 18, 2015 at 4:39
• I see. Thank you! Then how can I update the local dictionary of variables inside a function? This is what I'm looking for. –  shaoyl85 Commented May 18, 2015 at 4:43
• 1 What are you trying to achieve in the first place? XY problem –  Konstantin Commented May 18, 2015 at 4:45
• Giving a better insight of what you need will help us help you :) –  Aswin Murugesh Commented May 18, 2015 at 4:47
• For example, implementing some nice fault recovery mechanism. When a program failed and restart, it calls this function to read a dictionary from a file and update the local variables. With this, the user when writing the program can simply initialize the variables as usual and then call the update locals function. –  shaoyl85 Commented May 18, 2015 at 4:58

2 Answers 2

You have asked a very good question. In fact, the ability to update local variables is very important and crucial in saving and loading datasets for machine learning or in games. However, most developers of Python language have not come to a realization of its importance. They focus too much on conformity and optimization which is nevertheless important too.

Imagine you are developing a game or running a deep neural network (DNN), if all local variables are serializable, saving the entire game or DNN can be simply put into one line as print(locals()) , and loading the entire game or DNN can be simply put into one line as locals().update(eval(sys.stdin.read())) .

Currently, globals().update(...) takes immediate effect but locals().update(...) does not work because Python documentation says:

The default locals act as described for function locals() below: modifications to the default locals dictionary should not be attempted. Pass an explicit locals dictionary if you need to see effects of the code on locals after function exec() returns.

Why they design Python in such way is because of optimization and conforming the exec statement into a function:

To modify the locals of a function on the fly is not possible without several consequences: normally, function locals are not stored in a dictionary, but an array, whose indices are determined at compile time from the known locales. This collides at least with new locals added by exec. The old exec statement circumvented this, because the compiler knew that if an exec without globals/locals args occurred in a function, that namespace would be "unoptimized", i.e. not using the locals array. Since exec() is now a normal function, the compiler does not know what "exec" may be bound to, and therefore can not treat is specially.

Since global().update(...) works, the following piece of code will work in root namespace (i.e., outside any function) because locals() is the same as globals() in root namespace:

But this will not work inside a function.

However, as hacker-level Python programmers, we can use sys._getframe(1).f_locals instead of locals() . From what I have tested so far, on Python 3, the following piece of code always works:

However, sys._getframe(1).f_locals does not work in root namespace.

• 1 Finally a normal answer –  iliar Commented Jul 13, 2022 at 11:06
• oui . si . yes ... and no sarcasm in the comments !! hurray –  sol Commented Oct 14, 2022 at 13:28
• If the variable is defined locally before the call to update it does not work python def f1(): a = 1 sys._getframe(1).f_locals.update({'a':3, 'b':4}) print(a, b) f1() as it will print "1 4" –  sdementen Commented Jan 25, 2023 at 4:20

The locals are not updated here because, in the first case, the variable declared has a global scope. But when declared inside a function, the variable loses scope outside it.

Thus, the original value of the locals() is not changed in the UpdateLocals function.

PS: This might not be related to your question, but using camel case is not a good practice in Python. Try using the other method.

update_locals() instead of UpdateLocals()

Edit To answer the question in your comment:

There is something called a System Stack. The main job of this system stack during the execution of a code is to manage local variables, make sure the control returns to the correct statement after the completion of execution of the called function etc.,

So, everytime a function call is made, a new entry is created in that stack, which contains the line number (or instruction number) to which the control has to return after the return statement, and a set of fresh local variables.

The local variables when the control is inside the function, will be taken from the stack entry. Thus, the set of locals in both the functions are not the same. The entry in the stack is popped when the control exits from the function. Thus, the changes you made inside the function are erased, unless and until those variables have a global scope.

• Thank you! But I print a inside the function, why it still loses scope? –  shaoyl85 Commented May 18, 2015 at 4:43
• 1 @shaoyl85: That is why they are called local variables. When the control goes outside the function, such a variable does not exist. By passing the locals() dictionary, you are just sending a dictionary with those values. But changing that does not change the original locals in the calling function –  Aswin Murugesh Commented May 18, 2015 at 4:45
• I thought when the UpdateLocals is called, the function TestUpdateLocals hasn't finished executing yet, so the "locals dictionary" is still somewhere in the memory. I could do something hacky, such as constructing some statement strings to manually pull out the values in the dictionary and use them to set the local variables, then exec this constructed statement string. It would be ugly and I don't prefer doing that. –  shaoyl85 Commented May 18, 2015 at 4:55
• @shaoyl85: There is something called System stack. search for it to see how function calls are executed and how the local variables are managed. When the new function is called, a stack entry is created in the system stack, and so the locals of the test_update_locals function is not the current set of locals in update_locals –  Aswin Murugesh Commented May 18, 2015 at 4:58

Your Answer

Reminder: Answers generated by artificial intelligence tools are not allowed on Stack Overflow. Learn more

Sign up or log in

Post as a guest.

Required, but never shown

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy .

Not the answer you're looking for? Browse other questions tagged python or ask your own question .

• The Overflow Blog
• The world’s largest open-source business has plans for enhancing LLMs
• Looking under the hood at the tech stack that powers multimodal AI
• Featured on Meta
• Join Stack Overflow’s CEO and me for the first Stack IRL Community Event in...
• User activation: Learnings and opportunities
• What does a new user need in a homepage experience on Stack Overflow?
• Announcing the new Staging Ground Reviewer Stats Widget

Hot Network Questions

• What is an apologetic to confront Schellenberg's non-resistant divine hiddenness argument?
• How to make a soundless world
• "00000000000000"
• Count squares in my pi approximation
• What makes amplifiers so expensive?
• '05 Scion tC, bought used. 145k miles , unknown if spark plugs were ever changed. Should I change 'em?
• Why is 'это' neuter in this expression?
• Is it ethical to request partial reimbursement to present something from my previous position?
• What can I do to limit damage to a ceiling below bathroom after faucet leak?
• Is SQL .bak file compressed without explicitly stating to compress?
• Would a scientific theory of everything be falsifiable?
• Why is Germany looking to import workers from Kenya, specifically?
• Get the size (height, width and S=height*width in em) of the displayed image and draw it
• I didn't make it into a graduate program last year. How can I make a compelling case with an unchanged profile?
• How to get on to the roof?
• Is the forced detention of adult students by private universities legal?
• Is internal energy depended on the acceleration of the system?
• Copyright on song first performed in public
• Seeking a Text-Based Version of Paul Dirac's 1926 Paper on Quantum Mechanics
• Hungarian Immigration wrote a code on my passport
• Cutting a curve through a thick timber without waste
• How to plausibly delay the creation of the telescope
• CX and CZ commutation
• Was the total glaciation of the world, a.k.a. snowball earth, due to Bok space clouds?