What are the Differences between Yield and Return in Python?
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In Python, a generator is defined as a function that shall return an iterator through which we can iterate upon. It is quite easy to create such a generator where it implements the yield statement instead of the return statement. With the below article, we shall be deep diving into the Python yield vs return and which one should be preferred over the other with code examples and elaborate explanations.
The distinguishing factor between generator functions and normal user-defined functions is, with the generator functions you will find the "yield" statement in their definitions while in the normal function, the return statement is widely used. The "yield" keyword in the generator identifies the function as the generator object.
While implementing the yield statement, it must be noted that it hauls the function, and returns the value to the caller function. The yield statement can restart from where it is left off and can also be called multiple times. Whereas the return statement is implemented whenever we want to end the execution of the function and returns the value to the caller function. Without the return statement, the function shall not output anything and is considered to be nothing.
Python Yield
Introduction
The Python yield statement used in the generator shall be implemented when the scenario wants to use the statement that takes the place of a function's return to deliver a value back to the caller of the generator without ruining the local variables.
In the "generator" it does not return a data value to the caller of the function, instead, it returns another generator object. The functions execution can be temporarily halted, where the state gets saved. Once the scenarios arise to resume the function at a later stage, it is this yield keyword that helps.
Code :
Output :
Explanation:
As seen above, we used the Python yield generator to calculate the number of times a letter appeared in the function. Also, we calculate the function where we calculate the addition, subtraction, multiplication as well as division between two numbers as seen above. The yield can run many times, and it takes the place of a function's return to suspend the execution without losing any local variables.
Python Return
Introduction
The return statement in a function shall be implemented whenever scenarios ask you to end the execution of the function while passing a value back to the function. Here no value is explicitly returned to the caller of the function, instead, the value is returned which is sent back to the calling function. A function can have several return statements, but it must be noted that only one can be invoked at one time depending on every one of the statements' respective invocations.
A return statement is always found at the very end of a function block which justifies its purpose to return the final result of carrying out the statements contained in that function. You might sometimes also find a return statement is defined at an earlier stage in the function block to terminate or halt the execution of the subsequent statements. With that being said, this shall result in the execution of the program at the caller getting restarted instantly. Sometimes you might also find the "None" return object type, which is considered to be equal to the use case when no value is supplied for the return object in Python.
Code :
Output :
Explanation :
As observed above, we have used the return statement in the UDF to print the sample strings by creating the object inside a class. Also, we printed all the possible operators defined in the UDF sampleFunc() using the return statement. The return results in carrying out all of the statements that are contained within that function and hence are placed at the very end of a function block.
Python Yield vs Return
Below is the table representing the differences between the Python yield vs return functions in a much more formatted manner :
| S.No. | Basis of Comparison | YIELD | RETURN |
|---|---|---|---|
| 1 | About | The yield function is used to convert a regular Python function into a generator. | The return is used for signifying the end of the execution where it “returns” the result to the caller statement. |
| 2 | Function | It replaces the return of a function to pause its execution of the function without losing any local variables. | It exits a function and returns a value to its caller. |
| 3 | Uses | When the generator gives an intermediate result to the caller, the caller will then use the yield function. | When a function is prepared to send a value, it mandatorily uses it. |
| 4 | Execution | The code was written after the yield statement gets executed in the next following function call. | The code written after the return statement won't get executed in the next following function call. |
| 5 | Compilation | Ability to run many times. | It ability to only run a single time. |
| 6 | Starts | The yield statement function gets executed from the last state where the previous function got paused. | Each of the function calls runs the function from the beginning. |
When to Prefer Yield Instead of Return in Python and When to Prefer Return Over Yield?
You might be wondering to figure out when you want may want to use the Python yield vs return function and how to understand which scenarios are best suited for either of them. Let us try to understand this via a code example and elaborate explanation to understand this in much more detail :
Yield
We learned that we use the Python yield to pause the execution of a function and revert the value to the caller. Still, when you want to enable the function again, it already has retained enough state to resume from where it left off. Once the function resumes, it immediately continues the execution after the last yield run. This offers the code to produce a series of values over some time, rather than computing them all at once and reverting them as a list. For scenarios where you need to iterate over a sequence, but don’t want to store the entire series in memory, we should be implementing the yield statement.
In python, Yield is used as a generator where the generator function works as a normal function. Here, to generate a value, it does that with the yield keyword rather than the return. We can also say that when the body of a def contains a yield keyword instead of a return, the function automatically is called a generator function.
Code :
Output :
Explanation :
As observed above, we created a UDF where it returns 11111 on the first time, 22222 on the second time, and 33333 on the third time. We used the for loop to loop for each yield statement mentioned in the function. For scenarios where you need to iterate over a sequence, but don’t want to store the entire series in memory, we should be implementing the yield statement.
Return :
With the return statement, it sends a defined value back to the caller while as studied the Yield produces a series of values.
Code :
Output :
Explanation :
As observed above, we created a UDF that shall return the square of a number which are less than 60. We used the for loop to iterate over the function for the rach value starting from 2. We ran an infinite loop using the while loop to generate the squares with the yield statement function that multiplies the same number with itself.
Learn More
Some articles which must be revisited to revise the concepts which are also used to implement the various methods we learned so far are listed below :
- if-else loop Python.
- not Python.
- and Python.
- print Python.
Conclusion
- The distinguishing factor between generator functions and a normal user-defined function is, with the generator functions you will find the "yield" statement in their definitions while in the normal function, the return statement is widely used.
- A function can have several return statements, but it must be noted that only one can be invoked at one time depending on every one of the statements' respective invocations.
- The Python yield statement used in the generator shall be implemented when the scenario wants to use the statement that takes the place of a function's return to deliver a value back to the caller of the generator without ruining the local variables.
- The return statement in a function shall be implemented when scenarios ask you to end the execution of the function while passing a value back to the function. No value is explicitly returned to the caller of the function, instead, the value is the return that is sent back to the calling function.