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">
   # Working with Managers   
   <div class="ans">
<p>Using managers we can start processes on separate hosts that can share data amongst themselves. Once connected, there is no difference in the way processes use shared resources whether running locally or remotely.</p>

## Secure Communication
<p>A manager can be created by specifying an <b>authkey</b> which must be a byte string. <b>authkey</b> is the authentication key which will be used to check the validity of incoming connections to the server process. If <b>authkey</b> is None then <code class="mthd">current_process().authkey</code> is used. The manager created in the consumer process must also use the same <b>authkey</b> to connect with the manager in the main process.</p>

<p>Objects are passed between client and server via pickling, which can introduce security holes as unpacking a pickle may cause code to be executed. Pickles from an unknown
source should never be trusted. To mitigate this risk, all communication in the processing
package can be secured with <i>digest authentication</i> using the <code class="abtc">hmac</code> module from the standard library. Callers can pass authentication keys to the manager explicitly, but default values are generated if no key
is passed.</p>

<p>We'll rewrite a basic example using the <b>authkey</b>.</p>

</div>
</div>


<div>
   # Working with Managers   
   <div>
<p>Using managers we can start processes on separate hosts that can share data amongst themselves. Once connected, there is no difference in the way processes use shared resources whether running locally or remotely.</p>

## Secure Communication
<p>A manager can be created by specifying an <b>authkey</b> which must be a byte string. <b>authkey</b> is the authentication key which will be used to check the validity of incoming connections to the server process. If <b>authkey</b> is None then <code>current_process().authkey</code> is used. The manager created in the consumer process must also use the same <b>authkey</b> to connect with the manager in the main process.</p>

<p>Objects are passed between client and server via pickling, which can introduce security holes as unpacking a pickle may cause code to be executed. Pickles from an unknown
source should never be trusted. To mitigate this risk, all communication in the processing
package can be secured with <i>digest authentication</i> using the <code>hmac</code> module from the standard library. Callers can pass authentication keys to the manager explicitly, but default values are generated if no key
is passed.</p>

<p>We'll rewrite a basic example using the <b>authkey</b>.</p>

</div>
</div>


This lesson describes how to implement basic security when working with managers, and caveats to be mindful of.

The Basics

Threading Module

Multiprocessing

Concurrent Package

Async.io

Global Interpreter Lock

Interview Practise Problems

The End

Working with Managers

Working with Managers