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Talk Python To Me - Python conversations for passionate developers

Updated 4 days ago

Technology
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Talk Python to Me is a weekly podcast hosted by Michael Kennedy. The show covers a wide array of Python topics as well as many related topics. Our goal is to bring you the human story behind the Python packages and frameworks you know and love.

Read more

Talk Python to Me is a weekly podcast hosted by Michael Kennedy. The show covers a wide array of Python topics as well as many related topics. Our goal is to bring you the human story behind the Python packages and frameworks you know and love.

iTunes Ratings

320 Ratings
Average Ratings
299
11
9
0
1

Great

By Takethelguy - Aug 07 2019
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5/5 podcast that is great to listen to.

Exceptional

By Sunshine131313 - Jun 20 2017
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One of the best developer related podcasts, assuming you work in python.

iTunes Ratings

320 Ratings
Average Ratings
299
11
9
0
1

Great

By Takethelguy - Aug 07 2019
Read more
5/5 podcast that is great to listen to.

Exceptional

By Sunshine131313 - Jun 20 2017
Read more
One of the best developer related podcasts, assuming you work in python.
Cover image of Talk Python To Me - Python conversations for passionate developers

Talk Python To Me - Python conversations for passionate developers

Updated 4 days ago

Read more

Talk Python to Me is a weekly podcast hosted by Michael Kennedy. The show covers a wide array of Python topics as well as many related topics. Our goal is to bring you the human story behind the Python packages and frameworks you know and love.

Rank #1: #39 Getting your first dev job as a Python developer (part 1)

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How often do you meet people who are looking to get into the software development space? Do they ask you for advice? Maybe they want to know your story of how you got started and landed that first big job. Maybe they want to know what they should be doing right now.

This episode of Talk Python To Me is the first in a two part series that attempts to bring a wide spectrum of thoughts on this discussion. It's "Getting your first dev job as a Python developer, part 1", episode number 39, recorded December 10th 2015.

Links from the show:

Soft Skills: The software developer's life manual:
Manning.com (print and ebook) manning.com/books/soft-skills
Amazon.com (print only) amzn.to/1IZrXfL
The End of Jobs: Money, Meaning and Freedom Without the 9-to-5:
amzn.to/1Q6RoDP
Hired's Listener Special: hired.com/talkpythontome
SOLID Principles book: amzn.to/1Op81UY

Sponsors

Talk Python Training
Codeship
Dec 22 2015
50 mins
Play

Rank #2: #19 Automate the Boring Stuff with Python

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Some of the things we do in life are tedious and boring. It's the kind of thing that machines or robots could do. So let's build those machines!

This week we talk Al Sweigart, the author of Automating the Boring Stuff. You'll learn how he hopes to engage and teach Python to a unique and broad segment of the population. We'll discuss why, at first, it might make more sense to keep things simple rather than insisting on the "right" patterns and best practices.

Links from the show:

Book: Automate the boring stuff: automatetheboringstuff.com
Invent with Python: inventwithpython.com
Al at Github: github.com/asweigart
@alsweigart: twitter.com/alsweigart
Al's books at Amazon.com:
* Making Games with Python and PyGame
* Hacking Secret Ciphers with Python
* Invent Your Own Computer Games with Python
* Automate the Boring Stuff with Python

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Talk Python Training
Codeship
Aug 04 2015
41 mins
Play

Rank #3: #56 Data Science from Scratch

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You likely know that Python is one of the fastest growing languages for data science.

This is a discipline that combines the scientific inquiry of hypotheses and tests, the mathematical intuition of probability and statistics, the AI foundations of machine learning, a fluency in big data processing, and the Python language itself. That is a very broad set of skills we need to be good data scientists and yet each one is deep and often hard to understand.

That's why I'm excited to speak with Joel Grus, a data scientist from Seattle. He wrote a book to help us all understand what's actually happening when we employ libraries such as scikit-learn or numpy. It's called Data Science from Scratch and that's the topic of this week's episode.

Links from the show:

Book: Data Science from Scratch: amzn.to/1rhcbdT
Joel on Twitter: @joelgrus
Joel on the web: joelgrus.com
Partially Derivative Episode: partiallyderivative.com
Allen Institute for Artificial Intelligence: allenai.org

Data Science Libraries

numpy: numpy.org
Numpy episode: #34:
Continuum: Scientific Python and The Business of Open Source
:
talkpython.fm/episodes/show/34

pandas: pandas.pydata.org
scikit-learn: scikit-learn.org
scikit-learn episode: #31: Machine Learning with Python and scikit-learn:
talkpython.fm/episodes/show/31

matplotlib: matplotlib.org
Google's TensorFlow: tensorflow.org

Sponsors

GoCD
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Apr 27 2016
51 mins
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Rank #4: #90 Data Wrangling with Python

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Do you have a dirty, messy data problem? Whether you work as a software developer or as a data scientist, you've surely run across data that was malformed, incomplete, or maybe even wrong. Don't let messy data wreck your apps or generate wrong results.

What should you do? Listen to this episode of Talk Python To Me with Katharine Jarmul about the book she co-authored called Data Wrangling with Python and her PyCon UK presentation entitled How to Automate your Data Cleanup with Python.

Links from the show:

Katharine on the web: kjamistan.com
Katharine on twitter: @kjam
Book: Data Wrangling with Python: Tips and Tools to Make Your Life Easier: amzn.to/2fGc0Cx
Pycon 2016: How to Automate your Data Cleanup with Python: youtube.com/watch?v=gp-ngPV_ZX8

Packages from Data Cleanup talk
Dedupe Python Library: github.com/datamade/dedupe
probablepeople: github.com/datamade/probablepeople
usaddress: github.com/datamade/usaddress
jellyfish: github.com/jamesturk/jellyfish
Fuzzywuzzy: github.com/seatgeek/fuzzywuzzy
scrubadub: github.com/datascopeanalytics/scrubadub
pint: pint.readthedocs.io
arrow: github.com/crsmithdev/arrow
pdftables.six: github.com/vnaydionov/pdftables
Datacleaner: github.com/rhiever/datacleaner
Parserator: github.com/datamade/parserator
Gensim: radimrehurek.com/gensim
Faker: github.com/joke2k/faker
Dask: dask.pydata.org
SpaCy: spacy.io
Airflow: airflow.incubator.apache.org
Luigi: luigi.readthedocs.io
Hypothesis (testing): hypothesis.works

Katharine's courses

Data Pipelines with Python
shop.oreilly.com/product/0636920055334.do
Data Wrangling & Analysis with Python. Learn Pandas
shop.oreilly.com/product/0636920051831.do

Sponsors
Rollbar: rollbar.com/talkpythontome
GoCD: go.cd

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GoCD
Talk Python Training
Dec 21 2016
1 hour 1 min
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Rank #5: #130 10 books Python developers should be reading

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One of the hallmarks of successful developers is continuous learning. The best developers I know don't just keep learning, it's one of the things that drives them. That's why I'm excited to bring you this episode on 10 books Python developers should read.

You'll meet Timo Koola who is an avid reader and self-learner in the Python space. He's found 10 books from his experience that have had huge affects on him and we'll discuss them next.

Links from the show

Timo on Twitter: @tkoola
Newspaper package: github.com/codelucas/newspaper

The 10 Books
Automate the Boring Stuff with Python: amzn.to/2vyr1yD
Python Pocket Reference: amzn.to/2tmH5XU
Python Cookbook: amzn.to/2vfbAfz
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython: amzn.to/2u5lP60
Working Effectively with Legacy Code: amzn.to/2uwtigT
Python Testing with pytest: amzn.to/2veXP0g
Hands-On Machine Learning with Scikit-Learn and TensorFlow: amzn.to/2tco1rc
About Face: The Essentials of Interaction Design: amzn.to/2uwtugk
Thinking in Systems: A Primer: amzn.to/2u6FbJF
Thinking, Fast and Slow: amzn.to/2tnnlTN
Learn You a Haskell for Great Good!: amzn.to/2veOjdv

Sponsors

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Sep 19 2017
51 mins
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Rank #6: #48 Building Flask-based Web Apps

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When you think of Python web microframeworks, Flask is definitely near the top of the list. With almost 19,000 stars on GitHub it's a powerful and extensible web framework and it even powers the bandwidth intensive audio delivery of the Talk Python To Me podcast.

In this episode, number 48, we'll talk with Miguel Grinberg who has written some amazing Flask tutorials, books, and open source projects!

Links from the show:

Miguel on Twitter: @miguelgrinberg
Miguel's blog: blog.miguelgrinberg.com
"Flask At Scale" tutorial at PyCon 2016 in Portland:
blog.miguelgrinberg.com/post/flask-at-scale-tutorial-at-pycon-2016-in-portland
Flask Web Development (Amazon): amzn.to/1oVnibk
Flask Web Development (O'Reilly):
http://shop.oreilly.com/product/0636920031116.do?cmp=af-webplatform-books-videos-product_cj_9781449372620_%25zp

Open source projects
Flask-SocketIO: github.com/miguelgrinberg/Flask-SocketIO
Flask-Migrate: github.com/miguelgrinberg/Flask-Migrate
Flask-HTTPAuth: github.com/miguelgrinberg/Flask-HTTPAuth
python-socketio: github.com/miguelgrinberg/python-socketio
Flask-Moment: github.com/miguelgrinberg/Flask-Moment
Flask-PageDown: github.com/miguelgrinberg/Flask-PageDown
Climax: github.com/miguelgrinberg/climax

Introduction to the PuDB Python Debugging Tool:
heather.cs.ucdavis.edu/~matloff/pudb.html
Course Kickstarter: talkpython.fm/course
Michael's Online courses project:
blog.michaelckennedy.net/2016/02/16/im-building-20-online-python-courses-and-i-need-your-help-video-course-library-announced
Talk Python Training: https://training.talkpython.fm/

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GoCD
Mar 01 2016
49 mins
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Rank #7: #131 Top 10 machine learning libraries

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Data science has been one of the major driving forces behind the explosion of Python in recent years. It's now used for AI research, controls some of the most powerful telescopes in the world, tracks crop growth and prediction and so much more.

But with all this growth, there is an explosion of data science and machine learning libraries. That's why I invited Pete Garcin onto the show. He's going to share his top 10 machine learning libraries. After this episode, you should be able to pick the right one for the job.

Links from the show

Pete on Twitter: @rawktron
Pete on GitHub: github.com/rawktron
ActivePython: activestate.com/activepython
NeuroBlast AI Game: github.com/ActiveState/neuroblast

The 10 Machine Learning Libraries
Numpy/Scipy: numpy.org
Scikit-Learn: scikit-learn.org
Keras: keras.io
TensorFlow: tensorflow.org
Theano: deeplearning.net/software/theano
Pandas: pandas.pydata.org
Caffe/Caffe 2: caffe.berkeleyvision.org
Jupyter: jupyter.org
CNTK: microsoft.com/en-us/cognitive-toolkit
NLTK: nltk.org

Sponsors

DataCamp
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Sep 26 2017
53 mins
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Rank #8: #71 Soft Skills: The software developer's life manual

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Writing good, clean code and having a deep working knowledge of Python is critical to your success as a Python developer. But if you look at those who have truly excelled in their career, it's often because they bring something in addition to coding skills.

We all want to be the most successful and satisfied version of ourselves. But that's much easier said than done.

That's why I'm excited to introduce you to John Sonmez. He's had a brilliantly successful career as a developer and he wrote a book to help all of us do the same. It's called Soft Skills: The software developer's life manual and it's packed full of concrete, practical steps you can take to stand out in the tech industry.

Links from the show:

Simple Programmer: simpleprogrammer.com
John on Twitter: @jsonmez
Soft Skills Book: manning.com/books/soft-skills
John's Pluralsight courses: pluralsight.com/search?q=sonmez

Sponsors

Talk Python Training
GoCD
Aug 11 2016
1 hour 5 mins
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Rank #9: #82 Grokking Algorithms in Python

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Algorithms underpin almost everything we do in programming and in problem solving in general. Yet, many of us have partial or incomplete knowledge of the most important and common ones. In this episode, you'll meet Adit Bhargava, the author of the light and playful Grokking Algorithms: An illustrated guide book.

If you struggled to understand and learn the key algorithms, this episode is for you.

Links from the show:

Adit on the web: adit.io
Book: Grokking Algorithms: An illustrated guide (Manning, with ebook):
manning.com/books/grokking-algorithms
Book: Grokking Algorithms: An illustrated guide (Amazon):
amzn.to/2dQngeA
Grokking Algorithms GitHub: github.com/egonSchiele/grokking_algorithms
Adit on Twitter: @_egonschiele
High perf search of Talk Python: talkpython.fm/search

Sponsors

Capital One
Intel
Talk Python Training
Oct 27 2016
58 mins
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Rank #10: #73 Machine learning at the new Microsoft

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In this episode we catch up with David Crook, a developer evangelist at Microsoft. He is a co-organizer for the Fort Lauderdale Machine Learning User Group and is involved in many more user groups and meetups. You hear about some really cool projects where they are using Python and TensorFlow to work on simple things like growing more food to help feed the world.

Links from the show:

David on Twitter: @data4bots
David on the web: dacrook.com/
Fort Lauderdale machine learning UG:
meetup.com/Fort-Lauderdale-Machine-Learning-Meetup
Azure machine learning: azure.microsoft.com/en-us/services/machine-learning
TensoFlow: tensorflow.org

Sponsors

Talk Python Training
Capital One
Aug 26 2016
1 hour 4 mins
Play

Rank #11: #58 Create better Python programs with concurrency, libraries, and patterns

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What do you focus on once you've learned the core concepts of the Python programming language and ecosystem?

Obviously, knowing a few fundamental packages in your space is critical. If you're a web developer, you should probably know flask or pyramid, and sqlalchemy really well. If you're a data scientist, import pandas, numpy, matplotlib need to be something you type often and intuitively.

But then what? Well I have a few topics for you! This week you'll meet Mark Summerfield, prolific author of many Python books. We spend time digging into the ideas behind his book Python in Practice: Create Better Programs Using Concurrency, Libraries, and Patterns.

What I really like about these topics is that they have a "long shelf life". You find them relevant over time even as frameworks come and go.

Links from the show:

Mark on the web: qtrac.eu

Books:
Python in Practice: Create Better Programs Using Concurrency, Libraries, and Patterns:
amzn.to/1SMkk4n
Programming in Python 3: A Complete Introduction to the Python Language:
amzn.to/24quCP1
Rapid GUI Programming with Python and Qt: The Definitive Guide to PyQt:
amzn.to/1TlYHUk
Advanced Qt Programming: Creating Great Software with C++ and Qt 4:
amzn.to/1SMkpVr
Programming in Go: Creating Applications for the 21st Century:
amzn.to/1TlYO28
Advanced Python 3 Programming Techniques:
amzn.to/1SMkvwp
Programming in Python 3: A Complete Introduction to the Python Language:
amzn.to/24quYF2

Packages:
APSW package: rogerbinns.github.io/apsw
cx_freeze: cx-freeze.sourceforge.net
pywin32: sourceforge.net/projects/pywin32
roman package: pypi.python.org/pypi/roman
wmi package: timgolden.me.uk/python/wmi
Records: SQL for Humans:
kennethreitz.org/essays/introducing-records-just-write-sql

Extras:
Michael's episode on Away From The Keyboard pocdast:
awayfromthekeyboard.com
Updated course / player:
talkpython.fm/course

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GoCD
May 10 2016
54 mins
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Rank #12: #25 Effective Python

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What if you could bottle up all the wisdom and hard-fought experience of many expert Python developers and power up your own skills? That's what Brett Slatkin did and he put it in his book Effective Python.

Brett has had a unique opportunity to learn the correct and efficient ways to write Python. He has worked at Google on Google App Engine (GAE) alongside greats such as Guido van Rossum and Alex Martelli. Join the conversation where we discuss some of that wisdom when we talk about Brett's book "Effective Python".

Links from the show:

Book website: effectivepython.com
Book discount code: informit.com/EFFPY
Checkout for a 35% discount off the book.
Effective Python on Amazon: amzn.to/1ETVjdk
Twitter: @haxor
Brett's website: onebigfluke.com

Sponsors

Talk Python Training
Codeship
Sep 15 2015
54 mins
Play

Rank #13: #42 Python in Startups and Investing

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Have you ever dreamt of creating a startup that will change the world? You and your two best friends leave the dull world of writing internal business apps and go heads-down for three months to launch something amazing?

It turns out that Python plays a key role in many early stage startups. And this week's guest, Leah Culver has some amazing experience and stories about both!

Links from the show:

Leah on Twitter: @leahculver
Leah's website: leahculver.com
Grove: grove.io
Convore [historical]: wikipedia.org/wiki/Convore
Pownce [historical]: wikipedia.org/wiki/Pownce
boto package: github.com/boto
Startup music #1: Takin' VC Money by Smixx
Startup music #2: Seed round by Smixx

Sponsors

Talk Python Training
GoCD
Jan 19 2016
54 mins
Play

Rank #14: #173 Coming into Python from another Industry (part 1)

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Not everyone comes to software development and Python through 4-year computer science programs at universities. This episode highlights one alternative journey into Python.

Over the course of two episodes, you will meet people who started in other industries and now make Python part of their daily experience. Some of them have used programming to power-up their specialization. Others decided they'd rather be doing programming fulltime and made that switch.

This is part 1 of this two-part series. Our guests this time are Derrick Chambers, Jim Taysom, Arash Soheili, and Rob Ward.

Links from the show

Guests

Rob Ward
Twitter: @JBalloonist
Github: github.com/JBalloonist
Linkedin: linkedin.com/in/jballoonist

Arash Soheili
Twitter: @tonyarash
Linkedin: inkedin.com/in/arashsoheili
Medium: medium.com/@asoheili

Derrick Chambers
Twitter: @derchambers
Github: github.com/d-chambers

Jim Taysom
Twitter: @JamesTaysom
Github: github.com/jmtaysom
Radiant Solutions: adiantsolutions.com

Packages references
Obspy - python package for seismology: github.com/obspy/obspy
Sortedcontainers: grantjenks.com/docs/sortedcontainers
hupper: github.com/Pylons/hupper

Sponsors

Linode
Brilliant
Talk Python Training
Aug 07 2018
56 mins
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Rank #15: #88 Lightweight Django

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Django is a very popular Python web framework. One reason is you have many building blocks to drop in for large sections of your application. Need a full-on admin table editor backend? That's a few lines of code and boom you have a basic table editor.

This applies to many people. But those of us, myself included, who appreciate lightweight frameworks where we choose just what is included and piece together our web apps from best-of-breed components find this a turn off.

This week you'll meet Julia Elman and Mark Lavin, authors of Lightweight Django who are here to dispel the myth that Django apps have to be built out of large building blocks.

Links from the show:

Lightweight Django by Julia Elman and Mark Lavin:
shop.oreilly.com/product/0636920032502.do
Twitter: @juliaelman
Julia Elman web: juliaelman.com
Mark Lavin web: mlavin.org
Mark's Twitter: @DrOhYes
Lightweight Django code examples : github.com/lightweightdjango
Intermediate Django: Building Modern, Scalable, and Maintainable Web Applications by Mark Lavin:
shop.oreilly.com/product/0636920040903.do

Sponsors
GoCD: go.cd
pyup.io: pyup.io

Sponsors

GoCD
pyup
Talk Python Training
Dec 06 2016
59 mins
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Rank #16: #12 Deep Dive into Modules and Packages

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Quick: What's the difference between a module, a package, and packing in Python? Find out in this episode of Talk Python To Me.

All Python programmers use the import statement, but do you really know how it works and what it allows? Join David and Michael to take a deep dive into diabolical issues related to modules, packages, and imports. When we're done, you'll finally be ready to unleash your million line micro framework on the world!

Links from the show:

David's PyCon tutorial:
youtube.com/watch?v=MCs5OvhV9S4

David's website:
dabeaz.com

Book: Python Essential Reference:
dabeaz.com/per.html
@ Amazon

Book: Python Cookbook:
dabeaz.com/cookbook.html
@ Amazon

Pycon video collection:
bit.ly/pycon2015mk

Sponsor: CodeShip:
codeship.com

Sponsor: Hired ($4,000 bonus link):
hired.com/talkpythontome

Sponsors

Codeship
Talk Python Training
Jun 16 2015
52 mins
Play

Rank #17: #120 Python in Finance

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This week we'll enter the world of stock markets, trades, hedge funds and more. You'll meet Yves Hilpisch who runs The Python Quants where Python, open-source, education, and finance intersect.

Links from the show

Yves on Twitter: @dyjh
Personal site: hilpisch.com

The Python Quants Group: tpq.io
Yves on YouTube: youtube.com/results
Quant platform: pqp.io
DX Analytics: dx-analytics.com
For Python Quants Bootcamp: fpq.io
Python for Quant Finance Meetup: pqf.tpq.io
Books: books.tpq.io

Sponsors

Linode
Rollbar
Talk Python Training
Jul 12 2017
1 hour 7 mins
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Rank #18: #24 Fluent Python

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Are you fluent in Python or do you speak the language with an accent? Maybe you have a hint of C++ in your for-in loop or even a little C# coming through in your function names. Python's ease of learning can also lead to non-pythonic patterns for even experienced developers. It's so easy to jump in and (superficially) learn the language that you might miss the deeper understanding and Pythonic thinking.

Luciano Ramalho is here to help us clear up that accent that has been giving us away to our peers and he is giving everyone a deeper understanding of this language we love with his just released book "Fluent Python".

Links from the show:

Fluent Python at O'Reilly: shop.oreilly.com/product/0636920032519.do
Luciano on Twitter: @ramalhoorg
Book on Twitter: @FluentPython
Fluent Python on Amazon: amzn.to/1EhZeG4
Luciano's encapsulation with descriptors: youtube.com/watch?v=L-q0cQ7Gyws

Sponsors

Talk Python Training
Codeship
Sep 08 2015
1 hour 8 mins
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Rank #19: #96 Exploring Awesome Python

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Python is said to be a language that comes with "batteries included". That has many meanings depending on the level you're focusing on. At the lowest, it's a very rich and expressive language. Most commonly it means Python has a powerful and comprehensive standard library (itertools and elementtree anyone?).

But more holistically, most of the batteries are external, interchangeable ones, from PyPI. Right now, http://pypi.io has 97,326 packages listed on it. That's fantastic. However, it does lead to a discoverability problem. What options do I have for admin backends on web apps, cryptography, raw socket programming, and so on?

This week, Matt Makai is back with me (remember him from episode 26 last year?). We're talking about Awesome Python. A website and open source project attempting to categorize and somewhat rank these options.

Links from the show:

Awesome Python: awesome-python.com
Full Stack Python: fullstackpython.com
Matt Makai: @mattmakai

The 10 Choices
six: pypi.org/project/six/
bokeh: github.com/bokeh/bokeh
mkdocs: mkdocs.org
python-Markdown: github.com/waylan/Python-Markdown
wagtail: wagtail.io
python-patterns: github.com/faif/python-patterns
authomatic: peterhudec.github.io/authomatic
beaker: github.com/bbangert/beaker
passlib: pythonhosted.org/passlib
pip-tools: github.com/nvie/pip-tools

Sponsors

Anaconda, Inc
Talk Python Training
Jan 25 2017
52 mins
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Rank #20: #211 Classic CS problems in Python

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Many of you studied computer science at a University to get into programming and your careers. But I bet most of you came through some self-study or some sort of back door into the industry. I count myself among that crowd.

This is one of the true bright spots of our industry. That we can earn our way in without necessarily getting college degrees. But sometimes that academic formalism would come in handy. That's where David Kopec's book comes in super handy. It's an approachable and quick into to CS and that's our topic on this episode.

Just for you listeners, 40% discount code on David's book: podtalkpython19

Links from the show

David on Twitter: @davekopec
Classic Computer Science Problems in Python book: manning.com

Sponsors

Microsoft Visual Studio Code
Microsoft Azure
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May 11 2019
1 hour 8 mins
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