115 lines
5.0 KiB
Markdown
115 lines
5.0 KiB
Markdown
# Welcome!
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When I first learned Python nearly 25 years ago, I was immediately
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struck by how I could productively apply it to all sorts of messy work
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projects. Fast-forward a decade and I found myself teaching others the
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same fun. The result of that teaching is this course--A no-nonsense
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treatment of Python that has been actively taught to more than 400
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in-person groups since 2007. Traders, systems admins, astronomers,
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NASA rocket scientists, and even a few software engineers--they've all
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taken this course. Now, I'm happy to make it freely available.
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Enjoy!
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--David Beazley ([https://dabeaz.com](https://dabeaz.com)), [@dabeaz](https://twitter.com/dabeaz)
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## Prerequisites and Target Audience
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The material you see here is the core of an instructor-led Python
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training course. It is typically taught in-person over the span of
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three or four days--requiring approximately 25-35 hours of work. This
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includes the completion of approximately 130 hands-on coding exercises.
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The target audience is scientists, engineers, and programmers who
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already have experience in at least one other programming language. No
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prior knowledge of Python is required, but knowledge of common
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programming topics is assumed. Most participants find the course
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challenging--even if they've already been doing a bit of Python
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programming.
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The goal of this course is to cover foundational aspects of Python
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programming with an emphasis on script writing, data manipulation, and
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program organization. The course does NOT focus on Python tooling,
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IDEs, or third-party packages (i.e., it's not focused on using data
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science libraries in Jupyter Notebooks or on how to deploy web apps).
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It IS a course that aims to cover fundamental ideas about how Python
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programs work and how they are organized. Students WILL have to write
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functions and classes, work with code spread across multiple source
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files, deal with modules, and solve various problems related to
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refactoring.
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To complete this course, you simply need a basic installation of
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Python 3.6 or newer and time to work on it--especially the latter.
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## What This Course is Not
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This is not a course for absolute beginners on how to program a
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computer. It is assumed that you already have programming experience
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in some other programming language or Python itself. You're not
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going to find cute stories about looping--or why you would want to do it.
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This is not a course that aims to cover everything there is to know
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about Python. There is only so much material you can cover in 3-4 days
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before heads start to explode. If you're working through the material
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and wondering "why isn't X being covered?" there's probably a good
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reason--it was once included and it made everyone's head explode.
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This is not a course that simply covers reference material, tricks, or
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recipes that you could just look up on [python.org](https://python.org),
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Google, or Stack Overflow. Yes, there is enough reference
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material to be functional, but the course is more focused on how to
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work with and think about Python coding.
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This is not a course for software engineers on how to write or
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maintain a one-million line Python program. I don't write programs
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like that and neither should you. Delete something already!
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Python is a great language for personal productivity, prototyping ideas,
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and hacking cool things together. The course is about doing THAT in
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a way that's both practical and not so "hacky" that you co-workers
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give you stink-eye when they look at your code.
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## Take me to the Course Already!
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Ok, ok. Point your browser [HERE](Notes/Contents)!
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## Community Discussion
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Want to discuss the course? You can join the conversation on
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[Gitter](https://gitter.im/dabeaz-course/practical-python).
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## Acknowledgements
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Llorenç Muntaner was instrumental in converting the course content from
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Apple Keynote to the online structure that you see here.
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Various instructors have presented this course at one time or another
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over the last 12 years. This includes (in alphabetical order): Ned
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Batchelder, Juan Pablo Claude, Mark Fenner, Michael Foord, Matt
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Harrison, Raymond Hettinger, Daniel Klein, Travis Oliphant, James
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Powell, Michael Selik, Hugo Shi, Ian Stokes-Rees, Yarko Tymciurak,
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Bryan Van de ven, Peter Wang, and Mark Wiebe.
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I'd also like to thank the thousands of students who have taken this
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course and contributed to its success with their feedback and
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discussion.
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## Questions and Answers
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### Q: How is this course licensed?
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Practical Python Programming is licensed under a Creative Commons Attribution ShareAlike 4.0 International License.
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### Q: May I use this material to teach my own Python course?
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Yes, as long as appropriate attribution is given.
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### Q: May I make derivative works?
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Yes, as long as such works carry the same license terms and provide attribution.
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### Q: Do you accept contributions?
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Bug reports are appreciated and may be filed through the [issue
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tracker](https://github.com/dabeaz-course/practical-python/issues).
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Pull requests are not accepted except by invitation. Please file an
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issue first.
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