#292 Pythonic identity (auth in Python ecosystem)
Play • 1 hr 5 min
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

Talk Python Training
Linode
Google Cloud Platform Podcast
Google Cloud Platform Podcast
Google Cloud Platform
2020 Year End Wrap Up
This week, four of the podcast’s greatest hosts come together to celebrate all of the fun and informative episodes we’ve been privileged to do this year! Join Mark Mirchandani, Jon Foust, Priyanka Vergadia, and Brian Dorsey as we talk about our favorite guests and shows, some cool things that happened this year, and what we’re looking forward to in 2021! Cool things of the week * A Giant List of Google Cloud Resources blog * Google Cloud 4 Words site Our favorite episodes * Jon’s Favorites * GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast * GCP Podcast Episode 237: NVIDIA with Bryan Catanzaro podcast * Priyanka’s Favorite * GCP Podcast Episode 240: reCAPTCHA Enterprise with Kelly Anderson + Spring ML Potholes with Eric Clark podcast * Mark’s Favorites * GCP Podcast Episode 242: NASA and FDL with James Parr and Madhulika Guhathakurta podcast * GCP Podcast Episode 217: Cost Optimization with Justin Lerma and Pathik Sharma podcast * GCP Podcast Episode 228: Fastly with Tyler McMullen podcast * Brian’s Favorites * GCP Podcast Episode 223: Voice Coding with Emily Shea and Ryan Hileman podcast * GCP Podcast Episode 233: Bare Metal Solution with James Harding and Gurmeet Goindi podcast * GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast Sound Effects Attribution * “Bad Beep” by RicherLandTV of Freesound.org * “Small Group Laugh 6” by Tim.Kahn of Freesound.org * “It’s Always Night in Space” by JamesSilvera of HDInteractive.com * “Easy Cheesy” by LoboLoco of FreeMusicArchive.org
36 min
Python Bytes
Python Bytes
Michael Kennedy and Brian Okken
#217 Use your cloud SSD for fast, cross-process caching
Sponsored by Linode! pythonbytes.fm/linode Special guest: Ogi Moore Watch the live stream on YouTube. Michael #1: diskcache * via Ian Maurer * Python disk-backed cache (Django-compatible). Faster than Redis and Memcached. Pure-Python. * The cloud-based computing of 2020 puts a premium on memory. Gigabytes of empty space is left on disks as processes vie for memory. * Among these processes is Memcached (and sometimes Redis) which is used as a cache. * Wouldn't it be nice to leverage empty disk space for caching? * Features: * Pure-Python * Fully Documented * Benchmark comparisons (alternatives, Django cache backends) * 100% test coverage * Hours of stress testing * Performance matters * Django compatible API * Thread-safe and process-safe * Supports multiple eviction policies (LRU and LFU included) * Keys support "tag" metadata and eviction * Developed on Python 3.8 * Tested on CPython 3.5, 3.6, 3.7, 3.8 * Tested on Linux, Mac OS X, and Windows * Tested using Travis CI and AppVeyor CI Brian #2: TOML is 1.0.0 now. * What does that mean for Python? * Hopefully, some kind of toml parser will make it into Python core. * Any Python access to 1.0.0? Mixed * Implementations and TOML version support page lists: * pytomlpp supports 1.0.0-rc.3, which is a wrapper around C++ tomlplusplus, which does support 1.0.0. Confusing * tomlkit supports 1.0.0-rc.1, so that’s promising * toml supports 0.5.0, great name. It’d be cool if it would support 1.0.0 * What’s different between 0.5.0 and 1.0.0? * Unless I’m mistaken, not much: CHANGELOG * 1.0.0-rc1 * Leading zeroes in exponent parts of floats are permitted. * Allow raw tab characters in basic strings and multi-line basic strings. * Allow heterogenous values in arrays. * Other than that, lots of “Clarify …”, which I’m not sure how those all affect implementation. * I’d love to hear more from people who know more about this Ogi #3: pyqtgraph * pyqtgraph - plotting library, for when you need fast/interactive plots * Uses qt5 (and soon qt6) bindings to generate plots within Qt applications * Fills a niche role, want easy mouse interactivity, running locally on a machine * Often used in engineering/scientific applications when looking at a lot of data, and wanting interactivity Michael #4: Parler + Python = Insurrection in public * via Jim Kring and Mark Little * According to Wikipedia: Parler (/ˈpɑːrlər/) is an American alt-tech microblogging and social networking service. Parler has a significant user base of Donald Trump supporters, conservatives, conspiracy theorists, and right-wing extremists. * ArsTechnica article send in by Mark Little * Ars: Parler’s amateur coding could come back to haunt Capitol Hill rioters * Coding mess * A key reason for her success: Parler’s site was a mess. Its public API used no authentication. * When users deleted their posts, the site failed to remove the content and instead only added a delete flag to it. * Oh, and each post carried a numerical ID that was incremented from the ID of the most recently published one. * Another amateur mistake was Parler’s failure to scrub geolocations from images and videos posted online. * Some 80 terabytes of posts, 1M videos, many already deleted, preserved for posterity. * Catalog and Python pointed out by Shaun King. * See the catalog (maybe, it’s the ugly side of people). * The gist: https://gist.github.com/kylemcdonald/d8884da1a82ef50754ee49e0b6561071 * Partially back online with Russian hosting service? Brian #5: Best-of Web Development with Python * Suggested by Douglas Nichols * Cool list with nice icons * Covers * Frameworks, HTTP Clients, Servers * Auth tools, HTML Processing, URL utilities * OpenAPI, GraphQL, Websocket * RPC, Serverless, Content Management * Web Testing, Web Forms, Markdown * Third-party APIs * Email, Web Scraping & Crawling, Monitoring * Admin UI * API Proxies * Flask/FastAPI/Pyramid/Django Utilities * Nice to see lots of FastAPI projects: * fastapi-sqlalchemy - Adds simple SQLAlchemy support to FastAPI. * fastapi-plugins - FastAPI framework plugins. * fastapi_contrib - Opinionated set of utilities on top of FastAPI. * starlette_exporter - Prometheus exporter for Starlette and FastAPI. * fastapi-utils - Reusable utilities for FastAPI. * fastapi-code-generator - This code generator creates FastAPI app from an.. * slowapi - A rate limiter for Starlette and FastAPI. * fastapi-versioning - api versioning for fastapi web applications. * fastapi-react - Cookiecutter Template for FastAPI + React Projects. Using.. * fastapi_cache - FastAPI simple cache. Ogi #6: Assorted * Pyjion - https://github.com/tonybaloney/Pyjion a JIT extension for CPython that compiles python code using .NET 5 CLR * CuPy - NumPy compatible multi-dimensional array on CUDA, uses _``*array_function_* (enabled with numpy 1.17) code using numpy to operate directly on CuPy arrays * see NEP-18 and CuPy docs * compatible with other libraries as well Extras: Michael: * Trying Firefox + Brave + VPN * Python Web Conf 2021 call for talks, due Jan 29, I’ll be speaking! * PyCon US 2021 launched call for proposals: * December 22, 2020 — Call for proposals opened * February 12, 2021 — Proposals are due * March 16, 2021 — Notifications will be sent to presenters * March 23, 2021 — Deadline for speakers to confirm participation * March 30, 2021 — Schedule is publicly released * April 28, 2021 — Deadline to submit pre-recorded presentation (tutorials will be live) * May 12-13, 2021 — Tutorial days * May 15-16, 2021 — Conference days * Apple launching Racial Equity and Justice Initiatives with partners across a broad range of industries and backgrounds — from students to teachers, developers to entrepreneurs, and community organizers to justice advocates Brian: * PyCascades 2021 schedule https://2021.pycascades.com/program/schedule/ Ogi: * Anthony Explains Video Series * Learn X in Y minutes * Reading Working in Public by Nadia Eghbal - provides some sanity checks for existing maintainers, might be a fantastic perspective for new contributors to open source Joke Tech Support, 2x Working at the help desk? Get the theme song: Here to help song And help by chat: * "Running a successful open source project is just Good Will Hunting in reverse, where you start out as a respected genius and end up being a janitor who gets into fights." - Byrne Hobart
39 min
The Cloudcast
The Cloudcast
Cloudcast Media
A Cloud-First Look Ahead for 2021
Jeremy Burton (@jburton, CEO @Observe_Inc; board member @SnowflakeDB ) talks about the differences between traditional IT companies and Cloud-First companies, from product planning and roadmaps, to customer engagements and marketing messaging.  *SHOW: *484 *SHOW SPONSOR LINKS:* * Okta - You should not be building your own Auth * Learn how Okta helped Cengage improve student success rates during COVID. * BMC Wants to Know if your business is on its A-Game * BMC Autonomous Digital Enterprise * Datadog Security Monitoring Homepage - Modern Monitoring and Analytics * Try Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirt. *CLOUD NEWS OF THE WEEK *- http://bit.ly/cloudcast-cnotw *CHECK OUT OUR NEW PODCAST - **"CLOUDCAST BASICS"* *SHOW NOTES:* * Observe Homepage * Snowflake Homepage - The Data Cloud *Topic 1 *- Welcome to the show. We’ve known each other for a while. You’ve had tremendous success in Leadership, Product and Marketing roles in the past. Tell our audience a little bit of your background and what ultimately brought you to your role at CEO of Observe.  *Topic 1a* - For people that aren’t familiar, what does Observe bring to the market?  *Topic 2 *- We wanted to do a little “before-and-after”, and focus on what it means to be a “Cloud-First” company. What are the most obvious differences between a company like Observe and a company like Dell or EMC? *   * *Topic 3 *- From a product perspective, how do you think about roadmaps and the ways in which you enable new features for customers? Since Observe runs only in the public cloud, how much do you need to think about integrating with the native cloud services?  *Topic 4 *- You have deep expertise in creating marketing messaging, but so much of how customers learn about your products is no longer the company website. How do you think about reaching potential customers, or generally getting your message into the market? *Topic 5 *- Traditional IT was often aligned to centralized buying and architecture groups. How much does Cloud-First change the consumption models for companies - experimentation, on-demand usage, dealing with scaling issues, etc. *Topic 6 *- Overall, what are some of the biggest lessons you’ve learned about the Cloud-First approach as you’ve transitioned over the last 3+ years.  *FEEDBACK?* * Email: show at thecloudcast dot net * Twitter: @thecloudcastnet
37 min
MLOps.community
MLOps.community
Demetrios Brinkmann
When Machine Learning meets privacy - Episode 9
**Private data, Data Science friendly** Data Scientists are always eager to get their hands on more data, in particular, if that data has any value that can be extracted. Nevertheless, in real-world situations, data does not exist in the abundance that we thought existed, in other situations, the data might exist, but not possible to share it with different entities due to privacy concerns, which makes the work of data scientists not only hard, but sometimes even impossible. // Abstract: In the last episode of this series, we've decided to bring not one, but two guests to tells us how Synthetic data can unlock the use of data for Data Science teams whenever privacy concerns are a reality.  Jean-François Rajotte, Researcher and Resident data Scientist at the University of Columbia and Sumit Mukherjee, Senior Applied Scientist at Microsoft's AI for Good, bring us into more detail their expertise not only, in Synthetic data generation, but in it's mind blowing combination with Federated Learning to take the healthcare sector into the next level of AI adoption. //Other links to check on Jean-François Rajotte: https://venturebeat.com/2021/01/20/microsofts-felicia-taps-ai-to-enable-health-providers-to-share-data-anonymously/ https://dsi.ubc.ca/ https://leap-project.github.io/ //Other links to check on Sumit Mukherjee: www.sumitmukherjee.com (Sumit research) https://arxiv.org/abs/2101.07235 https://arxiv.org/pdf/2009.05683.pdf https://github.com/microsoft/privGAN (PrivGan) //Final thoughts Feel free to drop some questions into our slack channel (https://go.mlops.community/slack)  Watch some of the other podcast episodes and old meetups on the channel: https://www.youtube.com/channel/UCG6qpjVnBTTT8wLGBygANOQ ----------- Connect With Us ✌️------------- Join our Slack community:  https://go.mlops.community/slack Follow us on Twitter:  @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Connect with Fabiana on LinkedIn: https://www.linkedin.com/in/fabiana-clemente/ Connect with Jean-François on LinkedIn: https://www.linkedin.com/in/jfraj/ Connect with Sumit on LinkedIn: https://www.linkedin.com/in/sumitmukherjee2/
42 min
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