Ask the Ecosystem Lessons from 200+ FOSS Applications - Mahmoud Hashemi
This talk was presented at PyBay2019 - 4th annual Bay Area Regional Python conference. See pybay.com for more details about PyBay and click SHOW MORE for more information about this talk.
Description
If you had to build a software application right now, how would you do it? First step, Python. But then what?
This talk looks at over 200 of the most-successful open-source Python applications to provide advice on building effective software to reach the masses. Architecture, testing, licensing, packaging and distribution, these projects hold lifetimes of work and wisdom, waiting to be learned!
Abstract
If you had to build a software application right now, how would you do it? First step, Python. But then what?
This talk looks at over 200 of the most-successful open-source Python applications to provide empirical advice for building effective software to reach the masses. We'll look at architecture, testing, licensing, and even packaging and distribution. Each of these applications contains answers to every question raised during application development.
Why spend days and weeks piecing together the basics from first principles (blog posts and Stack Overflow), when Python's rich ecosystem readily provides? Go farther by following in the footsteps of such giants as Deluge, Reddit, Pi-Hole, FreeCAD, Unknown Horizons, Calibre, Magic Wormhole, Synapse, Zulip, Anki, Sage Math, Sentry, and more.
In this presentation, we'll explore many questions, just a few of which include:
What userbases do Python-based applications reach?
Where in software is Python leading, and what domains represent its biggest gaps?
What library dependencies appear in the application zeitgeist?
What copyright licenses are used by applications, and how do these practices differ from libraries?
How many projects rely only on donations, as opposed to having foundation or corporation support?
What can Python developers do to support and get involved in Python's rich application space?
A production application is worth a hundred blog posts and a thousand Stack Overflow answers. You've already heard all the talk about best practices, now come hear about the practical practices from real Python applications.
Outline:
3m - Defining the "application"
3m - Distinguishing between open-source application and library development
The top 200 open-source Python applications (methodology and taxonomy)
3m - Exemplars (e.g., Deluge, Anki, Synapse, yum/dnf, etc.)
3m - Methodology and prior art
2m - Taxonomy and organization
Common patterns and antipatterns in Python application design
3m - Architecture
4m - Dependencies
5m - Packaging and distribution
2m - Documentation
3m - Licensing
3m - The role of open-source in future Python usage
3m - Getting involved in open-source
Total: 37 minutes
Original slides: https://t.ly/dwXG8
About the speaker
Mahmoud Hashemi is a backend engineer and architect, open-source library maintainer, and Wikipedian, with ten years of experience building enterprise software. He authored O'Reilly's Enterprise Software with Python, host of the Pyninsula Python meetup group in the San Francisco Bay Area, and presenter of talks on Python and architecture, delivered all around the world.
Sponsor Acknowledgement
This and other PyBay2019 videos are via the help of our media partner AlphaVoice (https://www.alphavoice.io/)!
#pybay #pybay2019 #python #python3 #gdb
Видео Ask the Ecosystem Lessons from 200+ FOSS Applications - Mahmoud Hashemi канала SF Python
Description
If you had to build a software application right now, how would you do it? First step, Python. But then what?
This talk looks at over 200 of the most-successful open-source Python applications to provide advice on building effective software to reach the masses. Architecture, testing, licensing, packaging and distribution, these projects hold lifetimes of work and wisdom, waiting to be learned!
Abstract
If you had to build a software application right now, how would you do it? First step, Python. But then what?
This talk looks at over 200 of the most-successful open-source Python applications to provide empirical advice for building effective software to reach the masses. We'll look at architecture, testing, licensing, and even packaging and distribution. Each of these applications contains answers to every question raised during application development.
Why spend days and weeks piecing together the basics from first principles (blog posts and Stack Overflow), when Python's rich ecosystem readily provides? Go farther by following in the footsteps of such giants as Deluge, Reddit, Pi-Hole, FreeCAD, Unknown Horizons, Calibre, Magic Wormhole, Synapse, Zulip, Anki, Sage Math, Sentry, and more.
In this presentation, we'll explore many questions, just a few of which include:
What userbases do Python-based applications reach?
Where in software is Python leading, and what domains represent its biggest gaps?
What library dependencies appear in the application zeitgeist?
What copyright licenses are used by applications, and how do these practices differ from libraries?
How many projects rely only on donations, as opposed to having foundation or corporation support?
What can Python developers do to support and get involved in Python's rich application space?
A production application is worth a hundred blog posts and a thousand Stack Overflow answers. You've already heard all the talk about best practices, now come hear about the practical practices from real Python applications.
Outline:
3m - Defining the "application"
3m - Distinguishing between open-source application and library development
The top 200 open-source Python applications (methodology and taxonomy)
3m - Exemplars (e.g., Deluge, Anki, Synapse, yum/dnf, etc.)
3m - Methodology and prior art
2m - Taxonomy and organization
Common patterns and antipatterns in Python application design
3m - Architecture
4m - Dependencies
5m - Packaging and distribution
2m - Documentation
3m - Licensing
3m - The role of open-source in future Python usage
3m - Getting involved in open-source
Total: 37 minutes
Original slides: https://t.ly/dwXG8
About the speaker
Mahmoud Hashemi is a backend engineer and architect, open-source library maintainer, and Wikipedian, with ten years of experience building enterprise software. He authored O'Reilly's Enterprise Software with Python, host of the Pyninsula Python meetup group in the San Francisco Bay Area, and presenter of talks on Python and architecture, delivered all around the world.
Sponsor Acknowledgement
This and other PyBay2019 videos are via the help of our media partner AlphaVoice (https://www.alphavoice.io/)!
#pybay #pybay2019 #python #python3 #gdb
Видео Ask the Ecosystem Lessons from 200+ FOSS Applications - Mahmoud Hashemi канала SF Python
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
How to recommend dog breeds using deep learning - Aaron Wiegel - SF Python Meetup - Feb 2018James Abel, "latus - a Personal Cloud Storage App written in Python", PyBay2017"Data Science beasts (failures) and where to find them" - Grishma Jena (PyBay 2023)Nisanthan Nanthakumar - Python, Rust, and Regexes: A Look Back - SF Python (2023-02-08)Roy Williams - Python 3 at Lyft - SF Python Meetup - January 2018Flavio Juvenal, "Your Django app is a User Interface", PyBay2017Clearer Code at Scale - Static Types at Zulip and Dropbox | Greg Price @ PyBay 2018Mahmoud Hashemi, "The Packaging Gradient", PyBay2017Working with dates and times in Pandas - Reuven LernerLuciano Ramalho, Insight About Async/Await, PyBay 2017 Lightning TalkAlex Shepard, Deep Learning for Conservation, PyBay 2017 Lightning TalkAshot Vardanian - Fantastic Data Science Libraries - SF Python @ Sentry (2023-05-10)Automation using Python - Gobind AgarwalSandeep Narayanaswami - Numpy in Graphland, SF Python Meetup Jan 2019Katherine Scott, "Python from Space", PyBay2017Deep Learning By Doing - Bill ChenDidier Lopes - Revolutionizing the financial industry through Python - SF Python @ GGU (2023-06-14)Robotic Motion with Django II - MarkUnderstanding Python’s Debugging Internals - Liran HaimovitchBuilding Conversational AI w Rasa Stack | Alan Nichol @ PyBay2018