Talk Python To Me

By Michael Kennedy (@mkennedy)

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Rate for this podcast

Subscribers: 2719
Reviews: 4


 Nov 7, 2018
one of my absolute favourite podcasts even though im almost non-skilled im python, always feel inspired listening to this podcast !

Morten
 Oct 3, 2018
:)

Wilber H
 Sep 19, 2018
I wish there was a Python that talks about teaching Python. For reinforcement purposes while driving. Don't get me wrong, conversations are great but some tracks catered to just teaching would be great.

Travis W.
 Aug 31, 2018
Been listening to this podcast for over 6 months now and all I can say is that I'm continually pleased with every episode!

Description

Talk Python to Me is a weekly podcast hosted by developer and entrepreneur Michael Kennedy. We dive deep into the popular packages and software developers, data scientists, and incredible hobbyists doing amazing things with Python. If you're new to Python, you'll quickly learn the ins and outs of the community by hearing from the leaders. And if you've been Pythoning for years, you'll learn about your favorite packages and the hot new ones coming out of open source.

Episode Date
#305 Python community at Python Discord
01:01:41
People often ask me how they can find a Python community to be part of. Maybe discussion forum or slack channel. This week, we look at one of the most active communities in Python Discord. It's Python, on a discord server. But it's more than that too.

You'll meet Leon Sandøy who, along with a team of folks, runs Python Discord.

Links from the show

Leon on Twitter: @lemonsaurus_rex
Leon on the web: lemonsaur.us
Leon on GitHub: github.com

Python Discord: pythondiscord.com
Python Discord's YouTube: youtube.com
Python Discord on Twitter: @pythondiscord
Python Discord on GitHub: github.com

PEP 8 Song: youtube.com

YouTube Live Stream version of this show: youtube.com

Sponsors

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Mar 01, 2021
#304 asyncio all the things with Omnilib
01:00:50
The relatively recent introduction of async and await as keywords in Python have spawned a whole area of high performance, highly scalable frameworks and supporting libraries. One such library that has great async building blocks is Omnilib.

On this episode, you'll meet John Reese. John is the creator of Omnilib, which includes packages such as aioitertools, aiomultiprocess, and aiosqlite. Join us as we async all the things.

Links from the show

Omnilib libraries and project: omnilib.dev
awesome-asyncio: github.com
unsync: asherman.io

Live Youtube Stream: youtube.com

Charities
Power On: poweronlgbt.org
The Trevor Project: thetrevorproject.org

Sponsors

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Feb 21, 2021
#303 Python for Astronomy with Dr. Becky
01:03:56
If you are involved in science or use computational tools in your work, you should be using code to solve your problem. On this episode, we have Dr. Becky Smethurst who's an astrophysicist at Oxford University. She uses Python to explore galaxies and black holes.

Learn how she's using Python to make new discoveries at the cutting edge of research and dive into a couple of her YouTube videos aimed at spreading scientific truth in an entertaining wrapper.

Links from the show

Dr. Becky on Twitter: @drbecky_
Dr. Becky's YouTube channel: youtube.com
5 ways I use code as an astrophysicist video: youtube.com
Astrophysicist reacts to funny space MEMES video: youtube.com
A day in the life of an Oxford University Astrophysicist: youtube.com
Book: Space: 10 things you should know: amazon.com

SpaceMemes
Apple maps: image
Otter space: image
Eclipses: image
Steals a cow: image
Black holes: image

YouTube live stream: youtube.com

Sponsors

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CloudEnv
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Feb 12, 2021
#302 The Data Engineering Landscape in 2021
01:04:33
I'm sure you're familiar with data science. But what about data engineering? Are these the same or how are they related?

Data engineering is dedicated to overcoming data-processing bottlenecks, data cleanup, data flow and data-handling problems for applications that utilize lots of data.

On this episode, we welcome back Tobias Macey to give us the 30,000 ft view of the data engineering landscape in 2021.

Links from the show

Live Stream Recordings:
YouTube: youtube.com

Tobias Macey: boundlessnotions.com

Podcast.__init__: pythonpodcast.com
Data Engineering podcast: dataengineeringpodcast.com

Designing Data-Intensive Applications Book: amazon.com
wally: github.com
lakeFS: lakefs.io
A Beginner’s Guide to Data Engineering: medium.com
Apache Airflow: airflow.apache.org
Dagster: dagster.io
Prefect: prefect.io
#68 Crossing the streams with Podcast.__init__: talkpython.fm/68
dbt: getdbt.com
Great Expectations: github.com
Dask: dask.org
Meltano: meltano.com
Languages trends on StackOverflow: insights.stackoverflow.com
DVC: dvc.org
Pandas: pandas.pydata.org

Sponsors

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Feb 04, 2021
#301 Deploying and running Django web apps in 2021
01:08:34
Have you been learning Django and now want to get your site online? Not sure the best way to host it or the trade offs between the various options? Maybe you want to make sure your Django site is secure. On this episode, I'm joined by two Django experts Will Vincent and Carlton Gibson to talk about deploying and running Django in production along with recent updates in Django 3.2 and beyond.

Links from the show

Guests
Will Vincent: wsvincent.com
Carlton Gibson: @carltongibson

Watch the live stream: youtube.com

Give me back my monolith: craigkerstiens.com
Carlton’s Button hosting platform: btn.dev
Django Software Foundation: djangoproject.com
Django News newsletter: django-news.com
Deployment Checklist: djangoproject.com
Environs 3rd party package for environment variables: github.com
Django Static Files & Templates: learndjango.com
Learn Django: LearnDjango.com

Configuring uWSGI for Production Deployment @ Bloomberg: techatbloomberg.com

Sponsors

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Jan 28, 2021
#300 Building a data science startup (panel)
01:06:22
You've heard that software developers and startups go hand-in-hand. But what about data scientists? Of course they! But how do you turn your data science skill set into a data science business skill set? What are some of the areas ripe for launching such a business into?

On this episode, I welcome back 4 prior guests who have all walked their own version of this path and are currently running successful Python-based Data Science startups:

* Ines Montani from Explosion AI
* Matthew Rocklin from Coiled
* Jonathon Morgan from Yonder AI
* William Stein from Cocalc

Links from the show

Ines Montani
Twitter: @_inesmontani
Explosion AI: explosion.ai

Matthew Rocklin
Twitter: @mrocklin
Coiled: coiled.io
Jobs @ Coiled: jobs.lever.co/coiled

Jonathon Morgan
Twitter: @jonathonmorgan
Yonder AI: yonder-ai.com

William Stein
Twitter: @wstein389
CoCalc: cocalc.com

Talk Python Live Streams: talkpython.fm/youtube

Sentry Promo Code: TALKPYTHON2021

Sponsors

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Jan 22, 2021
#299 Personal search engine with datasette and dogsheep
01:01:42
In this episode, we'll be discussing two powerful tools for data reporting and exploration: Datasette and Dogsheep.

Datasette helps people take data of any shape or size, analyze and explore it, and publish it as an interactive website and accompanying API.

Dogsheep is a collection of tools for personal analytics using SQLite and Datasette. Imagine a unified search engine for everything personal in your life such as twitter, photos, google docs, todoist, goodreads, and more, all in once place and outside of cloud companies.

On this episode we talk with Simon Willison who created both of these projects. He's also one of the co-creators of Django and we'll discuss some early Django history!

Links from the show

Datasette: datasette.io
Dogsheep: dogsheep.github.io
Datasheet newsletter: datasette.substack.com
Video: Build your own data warehouse for personal analytics with SQLite and Datasette: youtube.com

Examples
List: github.com
Personal data warehouses: github.com
Global power plants: datasettes.com
SF data: datasettes.com
FiveThirtyEight: fivethirtyeight.datasettes.com
Lahman’s Baseball Database: baseballdb.lawlesst.net
Live demo of current main: datasette.io

Sponsors

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Jan 17, 2021
#298 Building ML teams and finding ML jobs
56:10
Are you building or running an internal machine learning team? How about looking for a new ML position? On this episode, I talk with Chip Huyen from Snorkel AI about building ML teams, finding ML positions, and teach ML at Stanford.

Links from the show

Chip on Twitter: @chipro
Snorkel AI: snorkel.ai
Chip's Book Preview: twitter.com
handcalcs project: github.com
IBM Buzzword Bingo: youtube.com

Sponsors

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Jan 11, 2021
#297 Python year in review (2020 edition)
01:10:23
2020 will be one for the history books, won't it? I've put together a great group to look back on 2020 - from the Python perspective.

Join me along with Cecil Phillip, Ines Montani, Jay Miller, Paul Everitt, Reuven Lerner, Matt Harrison, and Brian Okken for a light-hearted and fun look back on the major Python events of 2020.

Links from the show

Video version of this episode: youtube.com

Guests
Cecil Phillip: @cecilphillip
Ines Montani: @_inesmontani
Jay Miller: @kjaymiller
Paul Everitt: @paulweveritt
Reuven Lerner: @reuvenmlerner
Matt Harrison: @__mharrison__
Brian Okken: @brianokken

Sponsors

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Dec 28, 2020
#296 Python in F1 racing
01:05:14
Quick: Name the 3 most advanced engineering organizations you can think of? Maybe an aerospace company such as SpaceX or Boeing come to mind. Maybe you thought of CERN and the LHC. But in terms of bespoke engineering capabilities, you should certainly put the F1 racing teams on your list.

These organizations appear as 20-30 people on a race day shown on TV. But in fact, the number of people back at the home base doing the engineering work can be over 500 employees. Almost every tiny part you see on these cars as well as the tools to maintain them are custom-built.

The engineering problems solved are immense. Would it surprise you to know that Python is playing a major role here? On this episode, you'll meet Joe Borg who help pioneer Python's adoption at several F1 teams.

Links from the show

Joe's website: josephb.org
Joe on Twitter: @joedborg

Racing Point F1 team: racingpointf1.com
Scuderia Alpha Tauri F1 team: scuderiaalphatauri.com

MicroK8s: microk8s.io
Charmed Kubernetes: ubuntu.com/kubernetes

Sponsors

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Dec 23, 2020
#295 GIS + Python
57:00
Geography is the study of places and the relationships between people and their environments. Often we think of maps, but maps are static. GIS gets interesting when you realize that we're studying and visualizing data flowing through these locations and communities.

In this episode, you'll meet Silas Toms. He's an author of several Python GIS books and the host of The Mappist Hour podcast. Are you ready to dive into GIS with Python?

Links from the show

Silas on twitter Twitter: @loki_president

Silas' Books:
Mastering Geospatial Analysis with Python: Explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter: amazon.com
ArcPy and ArcGIS – Geospatial Analysis with Python: amazon.com
ArcPy and ArcGIS - Second Edition: Automating ArcGIS for Desktop and ArcGIS Online with Python: amazon.com

The Mappyist Hour podcast: themappyisthour.com

Packages
GeoAlchemy ORM: geoalchemy-2.readthedocs.io
Leaflet.js: leafletjs.com
Mapbox GL: mapbox.com
Deck GL: deck.gl

Sponsors

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Linode
Dec 18, 2020
#294 oso authorizes Python
51:27
When we think about accounts and security, we often think about identity (logging in and proving who you are). But for many applications, especially internal apps at large organizations, that's just step one. The next step is what can you do and what can you not do.

In this episode, you'll learn about a new library called oso. It's a declarative way to create policy code that maps to your mental model for who is allowed to do what in your system. We have two guests, Graham Neray and Sam Scott from the oso project to tell us all about it.

Links from the show

Oso on twitter: @osoHQ
Graham on twitter: @grahamneray
Sam on twitter: @samososos

Oso: osohq.com

Django docs: docs.osohq.com
Flask docs: docs.osohq.com
Python library docs: docs.osohq.com
Source code: github.com/osohq
Debugger docs: docs.osohq.com

Polar Adventure: A text-based adventure game written in Polar: osohq.com

Adding authorization to your Flask app with oso: osohq.com
Building a Django app with data access controls: osohq.com
Django Queryset filters from oso policies: osohq.com

Recent episode on authentication over at Talk Python: talkpython.fm/292
MongoDB most wanted DB: insights.stackoverflow.com
Talk Python [pro edition]: talkpython.fm/pro
FastAPI course: talkpython.fm/fastapi

Sponsors

Talk Python Training
Dec 07, 2020
#293 Learning how to learn as a developer
01:00:07
As software developers, we live in a world of uncertainty and flux. Do you need to build a new web app? Well maybe using Django makes the most sense if you've been doing it for a long time. There is Flask, but it's more mix and match being a microframework. But you've also heard that async and await are game changers and FastAPI might be the right choice.

Whatever it is you're building, there is constant pressure to stay on top of a moving target. Learning is not something you do in school then get a job as a developer. No, it a constant and critical part of your career. That's why we all need to be good, very good, at it.

Matt Harrison is back on Talk Python to talk to us about some tips, tricks, and even science about learning as software developers.

Links from the show

Matt on Twitter: @__mharrison__
Matt's Learning Course (use code TALKPYTHON20 for 20% off): mattharrison.podia.com

Friends of the show: talkpython.fm/friends-of-the-show
Streamlit: streamlit.io
Jupyter LSP: github.com/krassowski/jupyterlab-lsp

Sponsors

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Dec 01, 2020
#292 Pythonic identity (auth in Python ecosystem)
01:05:01
So you're excited about that next app you're about to build. You can visualize the APIs with the smooth scalability taking to the mobile apps. You can see how, finally, this time, you'll get deployment right and it'll be pure continuous delivery out of GitHub with zero downtime.

What you're probably not dreaming about is writing yet another password reset form and integrating mail capabilities just for this purpose. Or how you'll securely store user accounts the right way this time.

Don't worry, we got you covered. Our guests, Christos Matskas and John Patrick Dandison are here to cover a bunch of different libraries and techniques we can use for adding identity to our Python applications.

Links from the show

Christos on Twitter: @christosmatskas
John Patrick Dandison on Twitter: @azureandchill

shhgit live: shhgit.com
Twitch channel for Christos and JP: twitch.tv/425show

Passlib & Folding: passlib.readthedocs.io
Microsoft Authentication Library: github.com/AzureAD
authlib - JavaScript Object Signing and Encryption draft implementation: github.com
django-allauth - Authentication app for Django that "just works": github.com
django-oauth-toolkit - OAuth 2 goodies for Django: github.com
python-oauth2 - A fully tested, abstract interface to creating OAuth clients and servers: github.com
python-social-auth - An easy-to-setup social authentication mechanism: github.com

Sponsors

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Linode
Nov 26, 2020
#291 Operational Resilience with Pyomo
59:36
Do you have a scientific system that needs optimization or solving? Our guest, on this episode, Clark Petri is here to tell us all about pyomo. This is a library that can solve all sorts of cool problems, linear programming, nonlinear equations, and many other things you can throw at it.

We're gonna solve a really fun diet problem: What is the most nutritious meal that you can eat for the least amount of money? The answer might surprise you a little bit! It's going to be a lot of fun. So listen in to hear about how Clark has used pyomo to do his work and how you might use it in yours.

Links from the show

Pyomo: pyomo.org
Clark on Twitter: @clarkpetri
Center for Infrastructure Defense: nps.edu
Thesis: apps.dtic.mil
I’m not alone in my work post: morenuance.com
handcalcs package: github.com
Diet optimization problem: nbviewer.jupyter.org

Talk Python [Pro Edition]: talkpython.fm/pro
Black Friday at Talk Python: talkpython.fm/blackfriday

Sponsors

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Linode
Nov 22, 2020
#290 Side Hustles for Data Scientists
01:08:04
Are you a data scientist looking to branch out on your own and start something new? Maybe you're just looking for a way to work with those exciting libraries that aren't yet in play at the day job. Rather than putting everything on the line, quitting your job, and hoping things work out, maybe you should start with a side-hustle.

On this episode, you'll meet Keith McCormick, a data scientist who has many irons in the fire and he's here to tell us about different types of side hustles and why you may want to try or avoid one.

Links from the show

Keith on Twitter: @kmccormickblog
Keith on LinkedIn: linkedin.com
Keith's courses: linkedin.com
Side Hustle Strategies for Data Science and Analytics Experts course: linkedin.com/learning

Talk Python's Excel to Python course: talkpython.fm/excel

Sponsors

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Nov 13, 2020
#289 Discovering exoplanets with Python
47:26
When I saw the headline "Machine learning algorithm confirms 50 new exoplanets in historic first" I knew the Python angle of this story had to be told! And that's how this episode was born. Join David Armstrong and Jev Gamper as they tell us how they use Python and machine learning to discover not 1, but 50 new exoplanets in pre-existing Keplar satellite data.

Links from the show

Jev Gamper on Twitter: @brutforcimag
Machine learning algorithm confirms 50 new exoplanets in historic first article: techrepublic.com

Sponsors

Brilliant
Talk Python Training
Nov 09, 2020
#288 10 tips to move from Excel to Python
01:03:23
Excel is one of the most used and most empowering piece of software out there. But that doesn't make it a good fit for every data processing need. And when you outgrow Excel, a really good option for a next step is Python and the data science tech stack: Pandas, Jupyter, and friends.

Chris Moffitt is back on Talk Python to give us concrete tips and tricks for moving from Excel to Python!

Links from the show

Chris on Twitter: @chris1610
Practical Business Python: pbpython.com
Escaping Excel Hell with Python and Pandas Episode 200: talkpython.fm
SideTable package: pbpython.com

Learn more and go deeper
Move from Excel to Python with Pandas Course: training.talkpython.fm
Excel to Python webcast: crowdcast.io

Sponsors

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Oct 31, 2020
#287 Testing without dependencies, mocking in Python
01:03:29
We know our unit tests should be relatively independent from other parts of the system. For example, running a test shouldn't generally call a credit card possessing API and talk to a database when your goal is just to test the argument validation.

And yet, your method does all three of those and more. What do you do? Some languages use elaborate dependency passing frameworks that go under the banner of inversion of control (IoC) and dependency injections (DI). In Python, the most common fix is to temporarily redefine what those two functions do using patching and mocking.

On this episode, we welcome back Anna-Lena Pokes to talk us through the whole spectrum of test doubles, dummies, mocks, and more.

Links from the show

Anna-Lena's personal site: alpopkes.com
100 Days of Code episode: talkpython.fm/186
Anna-Lena on Github: github.com
PyCon talk from Lisa Road (2018) - “Demystifying the patch function”: youtube.com
PyCon talk from Edwin Jung (2019) - Mocking and Patching Pitfalls: youtube.com
Keynote talk “Finding Magic in Python” (about magical universe
project): youtube.com
Blog post about mocking in Python: alpopkes.com
Stackoverflow post on difference between stubs and mocks: stackoverflow.com
Freezegun project: github.com
KI Macht Schule (AI goes to school): ki-macht-schule.de
Code Combat: codecombat.com
PDB++: github.com

Sponsors

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Oct 21, 2020
#286 Python and ML at NASA Jet Propulsion Laboratory (JPL)
01:07:32
NASA's Jet Propulsion Laboratory (JPL)'s primary function is the construction and operation of planetary robotic spacecraft, though it also conducts Earth-orbit and astronomy missions. It is also responsible for operating NASA's Deep Space Network.

On this episode, you'll meet Chris Mattman. He's the Division Manager for the Artificial Intelligence, Analytics and Innovation at NASA JPL and he's JPL's first Principal Scientist in the area of Data Science. We cover a wide range of topics, and dive into how Python and open-source are growing in the space exploration field. And he answers the question of whether he thinks we'll have Python running on robots and rovers in space.

Links from the show

Chris on Twitter: @chrismattmann
Chris at JPL: jpl.nasa.gov
Nature: A vision for data science: nature.com
Open source at JPL: github.com
Apache Nutch: nutch.apache.org
7 Minutes of Terror: The Challenges of Getting to Mars: youtube.com
tqdm package: pypi.org
Panama Papers: wikipedia.org

Sponsors

Linode
Monday.com
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Oct 16, 2020
#285 Dask as a Platform Service with Coiled
01:11:04
If you're into data science, you've probably heard about Dask. It's a package that feels like familiar APIs such as Numpy, Pandas, and Scikit-Learn. Yet it can scale that computation across CPU cores on your local machine all the way to distributed grid-based computing in large clusters.

While powerful, this may take some serious setup to execute in its full glory. That's why Matthew Rocklin has teamed up with Hugo Bowne-Anderson and others to launch a business to help Python loving data scientists run Dask workloads in the cloud. And they are here to tell us about they open-source foundation business.

And they must be on to something, between recording and releasing this episode, they raised $5M in VC funding.

Links from the show

Hugo on Twitter: @hugobowne
Matthew on Twitter: @mrocklin
Coiled: coiled.io
Coiled raised $5M in Sept: twitter.com
A brief history of dask article: coiled.io/blog
Coiled: Dask for Everyone, Everywhere: medium.com
The incredible growth of python: stackoverflow.blog
Growth updated (SO Trends current): insights.stackoverflow.com
Coiled Youtube channel: youtube.com
Snorkel package: pypi.org

Sponsors

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Monday.com
Talk Python Training
Oct 09, 2020
#284 Modern and fast APIs with FastAPI
01:06:06
As Python 3 has eclipsed the old constrains of Python 2 and web frameworks that adopted them, we have seen a big jump in new frameworks appearing on the scene taking full advantage of things like type hints, async and await, and more.

No framework has done this more successfully than FastAPI recently. That's why we are here with the creator of FastAPI, Sebastián Ramírez to dive into this exciting new Python web framework.

Links from the show

Sebastian: @tiangolo
FastAPI: fastapi.tiangolo.com
FastAPI: One of the fastest Python frameworks available: fastapi.tiangolo.com
FastAPI for Flask Users: amitness.com
FastAPI Docker image: https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker
ujson: github.com
uvicorn: uvicorn.org
Traffic server: docs.traefik.io
Starlette: starlette.io
Pydantic: pydantic-docs.helpmanual.io

Sponsors

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Oct 04, 2020
#283 Web scraping, the 2020 edition
48:34
Web scraping is pulling the HTML of a website down and parsing useful data out of it. The use-cases for this type of functionality are endless. Have a bunch of data on governmental sites that are only listed online in HTML without a download? There's an API for that! Do you want to keep abreast of what your competitors are featuring on their site? There's an API for that. Need alerts for changes on a website, for example enrollment is now open at your college and you want to be first to get in and avoid the 8am Monday morning course slot? There's an API for that.

That API is screen scraping and Attila Tóth from ScrapingHub is here to tell us all about it.

Links from the show

Attila Tóth on LinkedIn: linkedin.com
Scrapy project: scrapy.org
Scrapinghub on Twitter: @scrapinghub
Scrapinghub: scrapinghub.com
cookiecutter template for Scrapy projects: github.com
Splash: headless browser designed specifically for web scraping: scrapinghub.com/splash
Awesome Web Scraping list: github.com

Talk Python episode 50 on web scraping: talkpython.fm
How Web Scraping is Revealing Lobbying and Corruption in Peru: blog.scrapinghub.com
Web Data Extraction Summit event: extractsummit.io

Sponsors

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Sep 23, 2020
#282 pre-commit framework
59:33
Git hook scripts are useful for identifying simple issues before committing your code. Hooks run on every commit to automatically point out issues in code such as trailing whitespace and debug statements. By pointing these issues out before code review, this allows a code reviewer to focus on the architecture of a change while not wasting time with trivial style nitpicks.

As we created more libraries and projects we recognized that sharing our pre-commit hooks across projects is painful. That's why I'm happy to welcome Anthony Sottile to the show to discuss pre-commit, a framework for managing and maintaining multi-language pre-commit hooks.

Links from the show

Anthony at Twitter: @codewithanthony
pre-commit: pre-commit.com
pre-commit continuous integration: pre-commit.ci
pre-commit hooks: pre-commit.com/hooks.html
pre-commit on GitHub: github.com
shhgit secret discovery project: github.com
babi editor: github.com
Twitch stream: twitch.tv

Anthony on GitHub: github.com

Sponsors

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Sep 17, 2020
#281 Python in Car Racing
01:00:14
I love to bring you stories of Python being used in amazing places outside the traditional tech silos of pure web development and data science.

On this episode, you'll meet Robert "Kane" Replogle, who works on the simulation and test software at Richard Childress Racing. The NASCAR team that just finished #1 and 2 in at the Texas Motor Speedway.

You'll hear how Python is allowing them to model car behavior, air flow, and more much faster than others using outdated tools.

Watch the hot lap around Brands Hatch


Links from the show

Kane on LinkedIn: linkedin.com
Kane on Twitter: @ReplogleRk
Richard Childress Racing: rcrracing.com
Windshear, the 180 mph tunnel: windshearinc.com
NASCAR: nascar.com
blackcellmagic package: pypi.org/project/blackcellmagic
StreamLit: streamlit.io

Sponsors

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Sep 09, 2020
#280 Python and AI in Journalism
55:51
If there has ever been a time in history that journalism is needed to shine a light on what's happening in the world, it's now. Would it surprise you to hear that Python and machine learning are playing an increasingly important role in discovering and bringing us the news? On this episode, you'll meet Carolyn Stansky, a journalist and developer who's been researching this intersection.

Links from the show

Carolyn on Twitter: @carolstran
Carolyn on LinkedIn: linkedin.com
Carolyn's site: workwithcarolyn.com
Carolyn's talk: How AI is enhancing journalism: vimeo.com

Examples of AI / automation in use
Quakebot: bit.ly/quakebot-code
LA Homicide Tracker: homicide.latimes.com
reportermate: github.com
Buzzfeed Finding and tracking secret spy planes: bit.ly/buzzfeed-spy-planes
NY Times comment moderation: bit.ly/nyt-comments
Al Jazzira: Drones in warzones: bit.ly/fmls-keynote

Tools
Qz.ai - Quartz AI Studio, focused on helping smaller papers and journalists: qz.ai
Facets: github.io
Google News Initiative: bit.ly/google-ni

Newspaper3k Package: newspaper.readthedocs.io
FiveThirtyEight: fivethirtyeight.com
Google News and Australia fight: bbc.com
Twitter thread on American news overwhelming other countries: twitter.com

Sponsors

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Sep 05, 2020