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">
   # Daemon Thread   
   <div class="ans">
<p>In Greek mythology, a <b>daemon</b> was a supernatural being of a nature between gods and humans whereas in the computer science realm <span class="hi-yl">a daemon is a computer program that runs as a background process rather than being under the direct control of an interactive user.</span> A daemon thread in Python runs in the background. <span class="hi-yl">The difference between a regular thread and a daemon thread is that <b>a Python program will not exit until all regular/user threads terminate.</b> However, a program may exit if the daemon thread is still not finished.</sopan></p>

<p>For folks coming from Java background, this is similar to how JVM treats daemon threads. Daemon threads don't hold up a Java program from terminating.</p>

## Marking a thread Daemon
<p>We can mark a thread daemon by passing in true for the <code class="mthd">daemon</code> field in the <code class="clazz">Thread</code> class's constructor.</p>
### Creating a daemon thread
<b>

```python
daemonThread = Thread(target=daemon_thread_task, daemon=True)
```
</b>
<p>In the below snippet the main thread creates a <b>non-daemonic</b> thread and exits. However, the program continues to run. The code widget throws an error because the execution times out.</p>
</div>
</div>


<div>
   # Daemon Thread   
   <div>
<p>In Greek mythology, a <b>daemon</b> was a supernatural being of a nature between gods and humans whereas in the computer science realm <span>a daemon is a computer program that runs as a background process rather than being under the direct control of an interactive user.</span> A daemon thread in Python runs in the background. <span>The difference between a regular thread and a daemon thread is that <b>a Python program will not exit until all regular/user threads terminate.</b> However, a program may exit if the daemon thread is still not finished.</sopan></p>

<p>For folks coming from Java background, this is similar to how JVM treats daemon threads. Daemon threads don't hold up a Java program from terminating.</p>

## Marking a thread Daemon
<p>We can mark a thread daemon by passing in true for the <code>daemon</code> field in the <code>Thread</code> class's constructor.</p>
### Creating a daemon thread
<b>

```python
daemonThread = Thread(target=daemon_thread_task, daemon=True)
```
</b>
<p>In the below snippet the main thread creates a <b>non-daemonic</b> thread and exits. However, the program continues to run. The code widget throws an error because the execution times out.</p>
</div>
</div>


This lesson describes how daemon threads exit as soon as the main program thread exits.

The Basics

Threading Module

Multiprocessing

Concurrent Package

Async.io

Global Interpreter Lock

Interview Practise Problems

The End

Daemon Thread

Daemon Thread