title: Best Python Podcasts
category: page
slug: best-python-podcasts
sortorder: 0110
toc: False
sidebartitle: Best Python Podcasts
meta: Find out the best Python podcasts as well as general software development podcasts on Full Stack Python.


The [Python community](/python-community.html) has an embarrassment of riches
when it comes to [free and low cost resources](/best-python-resources.html) 
for both new and experienced software developers. These great resources 
include several Python podcasts that are released on regular schedules.

This page contains a list of active Python-specific and software engineering
high-quality podcasts.


## Python-specific podcasts
These podcasts are run and recorded by Python developers who focus on
topics that are important to our field. Each podcast series has a long
list of previously-recorded episodes that are still relevant even if they
are several years old so you will always have some great material to
listen and learn.

* [Talk Python to Me](https://talkpython.fm) focuses on the
  people and organizations coding on Python. Each episode features a
  different guest interviewee to talk about his or her work.

* [Podcast.\_\_init\_\_](http://podcastinit.com/) is another regular podcast 
  that presents stories about Python and interviews "with the people who 
  make it great".

* [Python Bytes](https://pythonbytes.fm/) is a new podcast from the creators
  of the above mentioned "Talk Python to Me" and "Test and Code Podcast".

* [Test and Code Podcast](http://pythontesting.net/test-podcast/) focuses
  on [testing](/testing.html) and related topics such as mocking and 
  [code metrics](/code-metrics.html).

* [Django Riffs](https://djangoriffs.com/) is a podcast for learning 
  [web application development](/web-development.html) in Python using the 
  [Django web framework](/django.html).

* [The Real Python Podcast](https://realpython.com/podcasts/rpp/) is a weekly
  podcast with interviews, coding tips, and conversation with guests from the
  Python community.

* [Teaching Python](https://www.teachingpython.fm/) is a podcast by two
  teachers about their adventures teaching middle school computer science, 
  problem solving, handling failure, frustration, and success with
  teaching Python programming.



## Favorite podcast episodes
Here are a list of my favorite episodes from various Python podcasts before 
we dive into entire podcast recommendations in the next section. Dig into
these episodes to get a feel for various personalities and styles in
podcast presentation.

* [SQLAlchemy and data access in Python](https://talkpython.fm/episodes/show/5/sqlalchemy-and-data-access-in-python)
  brought me some much-needed context and understanding for how the 
  [object-relational mapping](/object-relational-mappers-orms.html) library
  [SQLAlchemy](/sqlalchemy.html) evolved. This episode interviews 
  SQLAlchemy's creator. The show host, Michael Kennedy, asks great questions 
  based on his in-depth research and prior usage of SQLAlchemy.

* [Python past, present, and future with Guido van Rossum](https://talkpython.fm/episodes/show/100/python-past-present-and-future-with-guido-van-rossum)
  covers the history of Python, Guido's motivations in creating the
  language and shepherding it through almost thirty years of releases.
  Fun fact: the question about whether Python being open source contributed
  to its success was my question when the podcast host Michael Kennedy asked 
  me what topics they should talk about.

* [Deploying Python Web Applications](https://talkpython.fm/episodes/show/26/deploying-python-web-applications-updated).
  *Spoiler alert*: this is the episode I was on Talk Python to Me explaining
  how [Python web application deployments](/deployment.html) work.

* Python Bytes talked extensively about
  [object-relational mappers (ORMs)](/object-relational-mappers-orms.html)
  on 
  [episode #39](https://pythonbytes.fm/episodes/show/39/the-new-pypi) where
  a lot of the discussion was based on the 
  [Full Stack Python ORMs](/object-relational-mappers-orms.html) page.
  Thanks guys, it was great to hear the feedback about what worked and what
  didn't work for you about the explanations!

* The 
  [Python at Netflix](https://talkpython.fm/episodes/show/16/python-at-netflix)
  episode of Talk Python to Me provided an awesome view inside the largest
  internet site by bandwidth and how Python fits into their polyglot 
  organization.

* Another great Talk Python to Me episode, 
  [Python in Finance](https://talkpython.fm/episodes/show/120/python-in-finance),
  explains how Python is used in the broad finance industry for stock trading,
  quantitative analysis and data analytics. Check this one out if you have 
  wondered how opaque private companies like hedge funds use Python to make
  (a lot of) money.

<div class="well see-also">If you prefer to learn Python by reading check out the <a href="/best-python-resources.html">best Python resources page</a> or <a href="/table-of-contents.html">view all topics</a>.</div>


## General software development podcasts
These podcasts are not specific to Python but cover relevant software
engineering topics and often have episodes on Python topics. At the
very least you will become a better general software developer by
listening and learning from them.

* [Software Engineering Daily](https://softwareengineeringdaily.com/)
  incredibly has a podcast every day with a different developer on a
  huge range of relevant development subjects.

* [All things Git](https://www.allthingsgit.com/) talks to developers
  using, building and working with Git with new episodes every two weeks.

* [CodeNewbie](https://www.codenewbie.org/podcast) interviews developers
  who are early in their software development journey to find out their
  stories of why they are programming and what they are working on. There
  are also interviews with experienced developers building well-known
  projects.

* [Developer on Fire](http://developeronfire.com/) interviews programmers, 
  architects and testers with their stories of success, failure and 
  excellence.

* [Command_line Heroes](https://www.redhat.com/en/command-line-heroes)
  covers [operating system](/operating-systems.html)-level topics as
  well as [DevOps](/devops.html).

* [Embedded.fm](http://embedded.fm/) goes into embedded systems and
  hardware hacking.

* [The Changelog](https://changelog.com/) is a weekly podcast on
  general software development matters.

* [Full Stack Radio](http://www.fullstackradio.com/). No relation to 
  Full Stack Python but another one to check out!

* [Exponent](http://exponent.fm/) is not a software development podcast
  but it covers the intersection of corporate strategy and technology in an
  in-depth way that allows me to better understand the decisions businesses
  make when building and releasing software. I listen to every episode 
  (at 1.5x speed) and it's well worth the 45 to 60 minutes spent 
  listening to Ben Thompson and James Allworth go deep on a weekly topic.

* [Test Talks](https://joecolantonio.com/testtalks/) examines a software 
  testing topic each week, usually with a special guest focused on the
  area being examined.

* [The Cloudcast](http://www.thecloudcast.net/) focuses on cloud computing
  and DevOps-related topics.


## Data science and analysis podcasts
The [data](/data.html) science community does not only use Python as its 
core programming language but it plays a big role in almost every
organization performing data analysis. The following podcasts cover
data science broadly and often get specific into Python ecosystem tools.

* [DataFramed](https://www.datacamp.com/community/podcast) is a data
  science podcast that often covers Python libraries and other areas of
  interest to people using Python to analyze [data](/data.html).

* [Data Skeptic](https://www.dataskeptic.com/) covers data science, 
  statistics, machine learning, artificial intelligence and "scientific 
  skepticism".

* [Data stories](http://datastori.es/) is a podcast on data visualization.

* [Partially Derivative](http://partiallyderivative.com/) was a podcast for
  machine learning, artificial intelligence and the data community. They
  finished their last episode in late 2017 but the 
  [episodes list](http://partiallyderivative.com/podcast/) contains
  a slew of existing content.
