The ultimate guide to senior engineering interviews. Strategies developed by FAANG engineers on Python concurrency, multithreading, monitors, and event loops. Prep faster for top company questions.

Concurrency in Python is one of the most complex and advanced topics brought up during senior engineering interviews. Knowledge of concurrency and multithreading can put interviewees at a considerable advantage. This course lays the foundations of advanced concurrency and multithreading and explains concepts such as Monitors, Event Loops and Deferred Callbacks in depth. It also builds simple and complete solutions to popular concurrency problems that can be asked about in interviews like the Reader-Writer Problem and the Dining Philosopher Problem. While prior knowledge of concurrency is not required to follow through with this course, familiarity with the very basic Python would be helpful.

Python Concurrency for Senior Engineering Interviews

<div class="card">
# Futures
<div class="ans">
You can think of <code class="clazz">Future</code> as an entity that represents a deferred computation that may or may not have been completed. It is an object that represents the outcome of a computation to be completed in future. We can query about the status of the deferred computation using the methods exposed by the <code class="clazz">Future</code> class. Some of the useful ones are:
<ul>
<li>done: Returns true if the execution of the callable was successfully completed or cancelled.</li>

<li>cancel: Attempts to cancel execution of a callable. Note if the task is already finished or executing the method returns False.</li>

<li>cancelled: Returns True if the task was successfully cancelled.</li>

<li>running: Returns True if the task is currently running and can't be cancelled.</li>
</ul> 

You should treat futures as read-only entities and never create them. They are returned by sub classes of <code class="clazz">Executor</code> class.
In the example below, we'll exercise all the above methods. Note that we attempt to cancel the task but since it is already executing the framework is unable to cancel it.


```python
from concurrent.futures import ThreadPoolExecutor
import time


def square(item):
 # simulate a computation by sleeping
 time.sleep(5)
 return item * item


if __name__ == '__main__':
 executor = ThreadPoolExecutor(max_workers=10)

 future = executor.submit(square, 7)

 print("is running : " + str(future.running()))
 print("is done : " + str(future.done()))
 print("Attempt to cancel : " + str(future.cancel()))
 print("is cancelled : " + str(future.cancelled()))

 executor.shutdown()

```

</div>
</div>

<div>
# Futures
<div>
You can think of <code>Future</code> as an entity that represents a deferred computation that may or may not have been completed. It is an object that represents the outcome of a computation to be completed in future. We can query about the status of the deferred computation using the methods exposed by the <code>Future</code> class. Some of the useful ones are:
<ul>
<li>done: Returns true if the execution of the callable was successfully completed or cancelled.</li>

<li>cancel: Attempts to cancel execution of a callable. Note if the task is already finished or executing the method returns False.</li>

<li>cancelled: Returns True if the task was successfully cancelled.</li>

<li>running: Returns True if the task is currently running and can't be cancelled.</li>
</ul> 

You should treat futures as read-only entities and never create them. They are returned by sub classes of <code>Executor</code> class.
In the example below, we'll exercise all the above methods. Note that we attempt to cancel the task but since it is already executing the framework is unable to cancel it.


```python
from concurrent.futures import ThreadPoolExecutor
import time


def square(item):
 # simulate a computation by sleeping
 time.sleep(5)
 return item * item


if __name__ == '__main__':
 executor = ThreadPoolExecutor(max_workers=10)

 future = executor.submit(square, 7)

 print("is running : " + str(future.running()))
 print("is done : " + str(future.done()))
 print("Attempt to cancel : " + str(future.cancel()))
 print("is cancelled : " + str(future.cancelled()))

 executor.shutdown()

```

</div>
</div>

This lesson gets into the details of working with threading.Future ( not to be confused with asycncio.Future).

The Basics

Threading Module

Multiprocessing

Concurrent Package

Async.io

Global Interpreter Lock

Interview Practise Problems

The End

Futures

Futures