Introduction
Are you encountering the frustrating TypeError “zip argument #1 must support iteration” while using Python’s concurrent.futures module? Don’t worry; you’re not alone. This error often occurs when passing arguments to the executor.map()
function that are not iterable. In this blog post, we’ll dive into the details of this error and provide you with a step-by-step solution to fix it. Whether you’re a beginner or an experienced Python developer, this troubleshooting guide will help you overcome this hurdle and continue your concurrent programming with ease. So, let’s get started!
Understanding the Error
The TypeError “zip argument #1 must support iteration” occurs when the executor.map()
function receives arguments that are not iterable. In your specific case, the error arises because you are passing the skip_list
function itself instead of invoking it to return the generator.
Solution: Invoke the skip_list Function
To resolve the error, follow these steps:
- Modify the line where you call
executor.map()
as shown below:pythonCopy codeexecutor.map(documents_processing, skip_list())
By adding parentheses()
afterskip_list
, you are invoking the function to return the generator. - Save your changes and run the program again.
Alternative Solution: Simplify the skip_list Function
If you want to simplify the skip_list
function, you can modify it as follows:
code
def skip_list():
for i in range(0, 100000, 10000):
yield i
This version of skip_list
returns each starting value of the document batch instead of generating a list of values.
Conclusion
By invoking the skip_list
function and ensuring that iterable arguments are passed to the executor.map()
function, you can successfully resolve the TypeError “zip argument #1 must support iteration” in Python’s concurrent.futures module. Remember to double-check that you are passing the correct arguments and invoking functions when necessary.
Now that you have the solution, you can continue working with concurrent programming and efficiently process MongoDB documents using multiprocessing.