% CSci 658-01: Software Language Engineering \
  Python 3 Reflexive Metaprogramming \
  Chapter 1
% **H. Conrad Cunningham** 
% **29 April 2018**

| Copyright (C) 2018, 
  [H. Conrad Cunningham ](<http://www.cs.olemiss.edu/~hcc>)
| Professor of 
  [Computer and Information Science ](<https://www.cs.olemiss.edu>)
| [University of Mississippi ](<http://www.olemiss.edu>)
| 211 Weir Hall
| P.O. Box 1848
| University, MS 38677
| (662) 915-5358

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# Introduction

## Metaprogramming

Basically, *metaprogramming* is writing code that writes code.

**Metaprogramming**: 
:   the writing of computer programs that can treat computer programs
    as their data. A program can read, generate, analyze, and/or
    transform other programs, or even modify itself while running
    (Adapted from \[Wikipedia 2018b, 2018c\] and other sources) 

We often do metaprogramming in our routine programming tasks but do
not call it that.

-   Our web applications may generate HTML, JavaScript, and CSS code
    to enable development of a browser-based user interface.
	
-   Our Java programs may use `instanceof` to check the type of
    objects or otherwise manipulate itself with the Java reflection
    package. 
	
-   Our C programs may use macros to define new features in terms of
    existing features.

Under the above definition, much of our study of domain-specific
languages uses metaprogramming.

-   The `pic` little language processor takes a program expressed in
    an external textual language that describes a picture and
    generates output expressed in another language that gives
    instructions to a display program \[Kernighan 1984\].

-   Several of the 
    [State Machine DSL ](<../658lectureNotes.html#StateMachineDSL>) 
	processors read and parse a program written in a special-purpose
    textual language, represent the program internally in a semantic
    model, and then "execute" the model on inputs.
	
-   Other of the 
    [State Machine DSL ](<../658lectureNotes.html#StateMachineDSL>) 
    processors use the semantic model to generate a "program" in
    another language such as C or the Graphviz dot language for
    graphs.
	
-   The [Computer Configuration 
	](<../658lectureNotes.html#CompConfigDSL>)
	and [Email Message 
	](<../658lectureNotes.html#EmailMessageDSL>)
	internal DSLs use the host language itself to
    encode special-purpose languages. The processors can then read and
    parse descriptions written in these special-purpose languages and
    manipulate the resulting data structures similarly to the external
    DSLs.

-   The Lua- and Python-hosted 
	[Lair Configuration ](<../658lectureNotes.html#LairDSL>)
	and the Ruby-hosted 
	[Survey](<../658lectureNotes.html#SurveyDSL>) 
	internal DSLs manipulate the structure of the
    processing programs themselves to implement the special-purpose
    language.


## Reflexive Metaprogramming

The internal Survey DSL and Lair Configuration DSL are examples of
*reflexive (or reflective) metaprogramming*.

**Reflexive metaprogramming**:
:   the writing of computer programs that manipulate themselves as 
    data.
    (Adapted from \[Wikipedia 2018b, 2018c\] and other sources) 

This manipulation may be at compile time, involving a phase of
transformations in the code before the final program is generated. Or
it may be at runtime, involving manipulation of the program's
metamodel or generation of new code that is dynamically executed
within the program.

The [Survey DSL](<../658lectureNotes.html#SurveyDSL>) is a Ruby
internal DSL. It takes advantage of Ruby's metaprogramming facilities
such as the abilities to trap calls to undefined methods, add methods
or variables dynamically to existing objects at runtime, and execute
dynamically generated strings as Ruby code. It also uses Ruby's
first-class functions (closures) and flexible syntax -- although these
are not technically metaprogramming features of Ruby.

The [Lair Configuration DSL ](<../658lectureNotes.html#LairDSL>)
programs use the metaprogramming features of Lua and Python in similar
ways.

Consider relatively common languages and their metaprogramming
features.

-   Java is a statically typed, compiled language. What are
    metaprogramming features available in Java?
	 
    It has dynamic class loaders, a reflection API, annotation
    processing, dynamic method invocation (a JVM feature), JVM
    bytecode manipulation (mostly with external tools), etc. Java 8+
    also has first-class functions and other features useful in
    metaprogramming.
		 
-   Lua is a dynamically typed, interpreted language. What are the
    metaprogramming features available in Lua?
	
	It has metatables, metamethods, manipulation of environments,
	a debug library (introspection/reflection features), `loadfile`
	and `loadstring` functions to dynamically execute code,
	extensions in C, etc.
	
What about Python 3? 

The reflexive metaprogramming features of Python 3.6 and beyond is the
primary topic of this set of lecture notes.


## Why Study Reflexive Metaprogramming?

In everyday application programming, we often use the products
developed by metaprogrammers, but we seldom use the techniques
directly.

In everyday programming, use of reflexive metaprogramming techniques
should not be one of our first approaches to a problem. We first
should explore techniques supported by core language, its standard
libraries, and stable extension packages. 

If no acceptable solution can be found, then we can consider solutions
that use reflexive metaprogramming techniques. We should approach
metaprogramming with great care because these techniques can make
programs difficult to understand and can introduce vulnerabilities
into our programs. We should design, implement, test, and document the
programs rigorously.

However, reflexive metaprogramming can be an important tool in a
master programmer's toolbox. If our jobs are to develop software
frameworks, libraries, APIs, or domain-specific languages, we can use
these techniques and features to develop powerful products that hide
the complexity from the application programmer.

Even when our jobs are primarily application programming,
understanding reflexive metaprogramming techniques can improve our
abilities to use software frameworks, libraries, and APIs effectively.


## Reflexive Metaprogramming in Python 3

TODO: Update this to better reflect what the final notes cover and
include forward references as appropriate.

The reflexive metaprogramming features of Python 3 include:

1.  Decorators
#.  Metaclasses 
#.  Descriptors
#.  Import hooks
#.  Context managers
#.  Annotations (e.g. type hints)
#.  Abstract Syntax Tree (AST) manipulation
#.  Frame hacks 
#.  Execution of strings as Python 3 code (`exec`, `eval`) 
#.  *Monkeypatching* (i.e. direct dynamic manipulation of attributes
    and methods at runtime)

We have already used the final two in our implementation of
domain-specific languages.  We will look at some of the others in
these notes. In particular, Chapter 3 looks at use of decorators and
metaclasses.

But, in the next chapter, let's first examine the basic features of
Python 3 upon which the reflexive metaprogramming features build.


## Exercises

TODO: Decide if any are appropriate.


## Acknowledgements

I developed these notes in Spring 2018 for use in CSci 658 Software
Language Engineering. The Spring 2018 version used Python 3.6.

Teaching a special topics course on "Ruby and Software Development" in
Fall 2006 kindled my interests in domain-specific languages and
metaprogramming. Building on these interests, I taught another special
topics course on "Software Language Engineering" in which I focused on
Martin Fowler's work on domain-specific languages \[Fowler 2011\]; I
subsequently formalized this as CSci 658. (I have collected some
overall ideas on [Domain-Specific Languages 
](<../DomainSpecificLanguages.html>)
in a separate set of notes \[Cunningham 2018c\].)

The overall set of notes on Python 3 Reflexive Metaprogramming is
inspired by David Beazley's [Python 3 Metaprogramming tutorial
](<http://www.dabeaz.com/py3meta>) from PyCon'2013 \[Beazley 2013a\]. 
In particular, some chapters adapt Beazley's examples.
Beazley's tutorial draws on material from his and Brian K. Jones' book
*Python Cookbook* \[Beazley 2013b\].

Chapter 1 of the notes subsumes my previous notes on Metaprogramming
\[Cunningham 2018b\].

I maintain these notes as text in Pandoc's dialect of Markdown
using embedded LaTeX markup for the mathematical formulas and then
translate the notes to HTML, PDF, and other forms as needed.


## References

\[Beazley 2013a\]:
:   David Beazley. 
    [Python 3 Metaprogramming (Tutorial)
    ](<http://www.dabeaz.com/py3meta/>), 
	*PyCon'2013*, 14 March 2013.

\[Beazley 2013b\]:
:   David Beazley and Brian K. Jones.
    *Python Cookbook, 3rd Edition*,
    O'Reilly Media, May 2013.

\[Cunningham 2018b\]:
:   H. Conrad Cunningham.
	[Metaprogramming ](<../Metaprogramming.html>) notes,
    revised 22 February 2018.
	
\[Cunningham 2018c\]:
:   H. Conrad Cunningham.
	[Domain-Specific Languages 
	](<../DomainSpecificLanguages.html>) notes,
    revised 2 April 2018.
	
\[Fowler 2011\]:
:   Martin Fowler. *Domain-Specific Languages*, Addison Wesley, 2011.

\[Kernighan 1984\]:
:   Brian W. Kernighan.
    [PIC \-- A Graphics Language for Typesetting, Revised User Manual 
	](<http://doc.cat-v.org/unix/v8/picmemo.pdf>), 
	Computing Science Technical Report No. 116, 
	Bell Laboratories, December 1984. 
	\[[local](<../localcopy/picmemo.pdf>)\]

\[Wikipedia 2018b\]:
:   Wikipedia, [Metaprogramming 
    ](<https://en.wikipedia.org/wiki/Metaprogramming>),
	accessed 25 April 2018.

\[Wikipedia 2018c\]:
:   Wikipedia, [Reflection 
    ](<https://en.wikipedia.org/wiki/Reflection_(computer_programming)>),
	accessed 25 April 2018.


## Terms and Concepts

TODO: Update

Metaprogramming, reflexive metaprogramming.
