[[!meta title="Python"]]

## Learning Python

### Which version to start? 2.x or 3.x?

Short answer: start learning 3.x and, if needed, check the differences with 2.x.

From [Should I use Python 2 or Python 3 for my development activity?](Should I use Python 2 or Python 3 for my development activity?):

    Besides, several aspects of the core language (such as print and exec being
    statements, integers using floor division) have been adjusted to be easier for
    newcomers to learn and to be more consistent with the rest of the language, and
    old cruft has been removed (for example, all classes are now new-style,
    "range()" returns a memory efficient iterable, not a list as in 2.x).

    [...]

    In particular, instructors introducing Python to new programmers should
    consider teaching Python 3 first and then introducing the differences in Python
    2 afterwards (if necessary), since Python 3 eliminates many quirks that can
    unnecessarily trip up beginning programmers trying to learn Python 2.

Also:

* [Python Future: Easy, clean, reliable Python 2/3 compatibility](http://python-future.org/).
* [Should I learn Python 2 or 3?](https://www.dataquest.io/blog/python-2-or-3/).

### General

* Everything is an object. Really? What about symbols like + - and =?
* The `dir()` and `help()` functions are really useful.
* Great idea: iteration protocol.
* There are sequences and sum operations common for all types and specific type operations.

### Iteration and optimization

    In general, leading and trailing double underscores is the naming pattern
    Python uses for implementation details. The names without the underscores in
    this list are the callable methods on string objects.

### Polymorphism

Python encourages polymorphism:

    This is related to the idea of polymorphism mentioned earlier, and it stems
    from Python’s lack of type declarations. As you’ll learn, in Python, we code to
    object interfaces (operations supported), not to types. That is, we care what
    an object does, not what it is. Not caring about specific types means that code
    is automatically applicable to many of them—any object with a compatible
    interface will work, regardless of its specific type. Although type checking is
    supported—and even required in some rare cases—you’ll see that it’s not usually
    the “Pythonic” way of thinking. In fact, you’ll find that polymorphism is
    probably the key idea behind using Python well.

### Numeric Display Formats

* [14. Floating Point Arithmetic: Issues and Limitations — Python 2.7.13 documentation](https://docs.python.org/2/tutorial/floatingpoint.html)
* [What Every Computer Scientist Should Know About Floating-Point Arithmetic](https://docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.html)
* [Floating-point arithmetic - Wikipedia](https://en.wikipedia.org/wiki/Floating-point_arithmetic).

    This floating-point limitation is especially apparent for values that cannot be
    represented accurately given their limited number of bits in memory.

    [...]

    fractions and decimals both allow more intuitive and accurate results than
    floating points sometimes can, in different ways—by using rational
    representation and by limiting precision

### Types

    More formally, there are three major type (and operation) categories in Python
    that have this generic nature:

    Numbers (integer, floating-point, decimal, fraction, others)
    Support addition, multiplication, etc.
    Sequences (strings, lists, tuples)
    Support indexing, slicing, concatenation, etc.
    Mappings (dictionaries)
    Support indexing by key, etc.

    [...]

    The major core types in Python break down as follows:

    Immutables (numbers, strings, tuples, frozensets)
    None of the object types in the immutable category support in-place changes,
    though we can always run expressions to make new objects and assign their
    results to variables as needed.

    Mutables (lists, dictionaries, sets, bytearray)
    Conversely, the mutable types can always be changed in place with operations
    that do not create new objects. Although such objects can be copied, in-place
    changes support direct modification.

So remember that when [copying](https://stackoverflow.com/questions/2612802/how-to-clone-or-copy-a-list#2612815)
or referencing a list.

### Nice stuff

* [Verbose Regular Expressions](http://www.diveintopython3.net/regular-expressions.html#verbosere).

## Implementations

* [MicroPython - Python for microcontrollers](http://micropython.org/) ([compiling](https://github.com/micropython/micropython/wiki/Getting-Started).

## Libraries and applications

* QGIS.
* [SciPy.org — SciPy.org](https://www.scipy.org/) ([package](https://packages.debian.org/stable/python-scipy)).

## Frameworks

* [Welcome | Flask (A Python Microframework)](http://flask.pocoo.org/) ([package](https://packages.debian.org/stretch/python-flask)).
* Async: [asyncio](https://docs.python.org/3/library/asyncio.html), Twisted and Tornado.
* [Anaconda Data Science Platform](https://www.anaconda.com/).

## IDEs

* [PyCharm](https://www.jetbrains.com/pycharm/).

## Test projects

* [Arduino Blog » How close are we to doomsday? A clock is calculating it in real time](https://blog.arduino.cc/2013/03/27/how-close-are-we-to-doomsday-clock/) ([python code](https://github.com/tomschofield/Neurotic-Armageddon-Indicator/blob/master/NAI_SERVER/nai_scraper.py) to parse [Timeline from the Bulletin of the Atomic Scientists](http://thebulletin.org/timeline)).