A Python Roadmap

An interesting tweet. The  roadmap has three sections. I'm not sure this is actually complete, or even grouped correctly. It is a very good list of topics.

	Pratham ⁦‪@PrasoonPratham‬⁩ Here's a complete roadmap of topics to master Python. 🧵 👇🏻   6/25/21, 10:42 AM

Foundations

I want start by quibbling about variables being first. I'm not sold on this.

I think that operators, expressions, and the built-in immutable types are foundational. int, float, str, and tuple are hugely important as core concepts in computing and Python.

I also think that "loops" is a sketchy notion and I kind of wish we wouldn't describe for and while statements as "loops". I think we should call them iterations. They implement two kinds of logical quantifiers "for all" and "there exists." I think we should talk about the final result of a for statement: all of the values in a range are processed. Similarly a for-if-break construct establishes a "for exists" that defines the first value in a range for which a condition is met. And yes, range objects will be central.

I think that a huge amount of programming can be covered with these topics. I'm not sure "basic" is the right term; foundations might be a better idea. 

The use of variables to manage state is part of this. But. Variables, assignment, and state change are a bit more advanced and maybe shouldn't be first.

I also think function definitions are foundational. Mathematics has been defining functions based on other functions. It's a way of providing a mental short-hand for complex concepts. I don't need to know all the details of how to compute a square root to make use of square root as a concept.

The wide varieties of assignment statements, including assignment to decompose collections aren't mentioned in the original post. This may be an important omission, causing me to quibble on "complete."

I agree that files and elements of File IO are part of this foundation. If we limit ourselves to reading and writing files, then they're essentially immutable structures. I think we can safely avoid update-in-place files because this is an application topic more than a language topic. Python offers the minimal level of support via seek and tell, but little more. And most modern application relies on a database for updatable files.

Data Structures

Moving from basic to intermediate. I prefer the term "data structures" which are built on the language foundations. I think that the mutable built-in data structures come next in the roadmap. My preference is to omit terms like Object-Oriented or Functional, and focus on list, dict, and set, and how the iteration works. This means comprehensions and generators are part of this essential data structure section.

No, comprehensions aren't and shouldn't be called "advanced." They're very much a core concept. Thinking about statements to implement a map/filter/reduce over a collection is the essence of a great deal of programming. We don't always learn it that way, but it needs to be presented in that framework even to beginners. A pile of for and if statements and a bunch of variables is a programmer's first step toward a simpler comprehension. In both cases, they're doing a mapping and it needs to be described as mapping one collection to another collection.

This is where the standard library collections module is introduced.  Yes it's part of the library. I think it's too central to be ignored. I think dataclasses belong here, too.

Talking about the mutable data structures means revisiting the for statement and using it on a variety of iterables. The way Python's concepts apply to a variety of data types is an important feature of the language. (In the olden days, they used to talk about "orthogonality" of data and processing; we don't need to dwell on it, but I think it helps to acknowledge it.)

Functional Programming

It appears to me that the functional programming topics can come next. The idea of functional composition via higher-order functions and decorators builds on the existing foundation. This is where map() and filter() belong. Because of the way sorted(), max(), and min() work on collections with a key= function, these are part of the functional programming roadmap. The inconsistency between map() and functions like max() is an important thing to note.

I also think itertools belongs here. We can make the case that it's in the standard library, but then, so is io. I think itertools and functools are as central to practical Python as the math module and collections.

I think typing.NamedTuple and dataclasses belong here, also. A frozen dataclass is stateless, and can be helpful when creating list comprehensions to perform a mapping from one collection to another collection.

Object-Oriented Programming

I think OO programming and related concepts build on the previous material. Class definitions and state management aren't simple, even though they're essential parts of Python.

To an extent, OO programming can be decomposed into two layers. While I hate to overuse "foundation", there seem to be two parts:

OO Foundations -- inheritance, composition, and different kinds of delegation. This tends to expose a number of common design patterns like Strategy, Decorator, and Facade.

OO Features -- this includes metaprogramming, decorators, ABC's, mixins, and the like. These topics are all designed to avoid copy-and-paste in sophisticated edge cases that cross class boundaries.

Concurrency

I'm not sure why concurrency and parallelism are separate topics in the original list. I've had folks try to split this hair a number of ways. The idea is to find a place where async lives that's "concurrency lite" or something.

The concepts here become blurry because threads and processes are OS features, not language features. The async/await language features, however, are clearly part of Python. It becomes particularly awful when working on something practical where asyncio doesn't provide the feature you need. Specifically, blocking file system I/O isn't part of asyncio and requires an explicit appeal to the underlying thread pool for the blocking operation. 

To an extent, async/await needs to be on the roadmap. It's tricky, though, to cover this without also digressing into threads as a way to deal with blocking operations.

Test, Integration, and Deployment

This is where tools show up. This is where pip, unittest, pytest, tox/nox, coverage, etc. live. Are these part of the language? Or are the part of the broader ecosystem?

I submit they're explicitly not part of the language. The roadmap ends just before this topic. The idea is that we should have a Python roadmap that uses the language and the standard library.

Once we've talked about the language (and some of the library) we can move on to pip and packaging. I don't think pip is and "intermediate" topic. I find that premature introduction of pip is a sign of trying to create useful interesting examples. Examples that don't use pip wind up being kind of boring. Everyone wants to play with pygame and pillow and other kinds of projects, but, those aren't foundational to the language. They're interesting and appealing and -- frankly -- a lot of fun.

tl;dr

I'm not a fan of the roadmap. I like some of it. I don't like some of it.

I am a fan of presenting the idea for discussion.