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">
   # Timer   
   <div class="ans">
<p><span class="hi-yl">The Timer object allows execution of a callable object after a certain amount of time has elapsed.</span> Consider the snippet below where a <code class="clazz">Timer</code> object executes the method <code class="mthd">say_hi()</code> in a different thread than the main thread. The thread names can be observed from the output.</p>

## Creating a timer
<b>

```python
from threading import Timer
from threading import current_thread
import time


def say_hi():
    print("{0} says Hi!".format(current_thread().getName()))


timer = Timer(1, say_hi)
timer.start()

time.sleep(2)

print("{0} exiting".format(current_thread().getName()))
```
</b>

<p>The timer constructor takes in a floating point number representing the seconds that need to elapse before the task is executed. Though when the task is executed may not be exactly after the passed in number of seconds. It may be slightly more than the interval passed in.</p>
<p>Time is a subclass of the <code class="clazz">Thread</code> class and similarly accepts arguments as a list or a keyword dictionary.</p>
<p>A timer object can also be cancelled using the <code class="mthd">cancel()</code> method before the task has been executed.</p>
</div>
</div>


<div>
   # Timer   
   <div>
<p><span>The Timer object allows execution of a callable object after a certain amount of time has elapsed.</span> Consider the snippet below where a <code>Timer</code> object executes the method <code>say_hi()</code> in a different thread than the main thread. The thread names can be observed from the output.</p>

## Creating a timer
<b>

```python
from threading import Timer
from threading import current_thread
import time


def say_hi():
    print("{0} says Hi!".format(current_thread().getName()))


timer = Timer(1, say_hi)
timer.start()

time.sleep(2)

print("{0} exiting".format(current_thread().getName()))
```
</b>

<p>The timer constructor takes in a floating point number representing the seconds that need to elapse before the task is executed. Though when the task is executed may not be exactly after the passed in number of seconds. It may be slightly more than the interval passed in.</p>
<p>Time is a subclass of the <code>Thread</code> class and similarly accepts arguments as a list or a keyword dictionary.</p>
<p>A timer object can also be cancelled using the <code>cancel()</code> method before the task has been executed.</p>
</div>
</div>


This lesson discusses the Timer class with examples.

The Basics

Threading Module

Multiprocessing

Concurrent Package

Async.io

Global Interpreter Lock

Interview Practise Problems

The End

Timer

Timer