Summary
A list of all the Adventures published until now.

The Adventures of a Pythonista in Schemeland have grown to become a rather big series. I think a table of contents is needed to index all the episodes. Here it is.

Part I - Introduction

Ep1 A bit of history

Ep2 About scheme implementations

Ep3 Of parenthesis and indentation

Ep4 Scheme bibliography (and a first program)

Ep5 About tail call optimization (and the module system)

Ep6 The danger of benchmarks

Part II - Macros

Ep7 Symbols and lists

Ep8 Quoting and quasi-quoting

Ep9 Introduction to (sweet-)macros

Ep10 Features of (sweet-)macros

Ep11 The multiple evaluation problem (and easy-test)

Ep12 Are macros really useful?

Part III - Functional Aspects

Ep13 Micro-introduction to functional programming

Ep14 Currying, partial application, and fold

Ep15 List destructuring

Ep16 Multiple values (and opt-lambda)

Ep17 List comprehension

Ep18 Streams

Part IV - The Module System

Ep19 Using modules

Ep20 Evaluation strategy of Scheme programs

Ep21 The different meanings of phase separation

Ep22 The Dark Tower of Meta-levels

Ep23 Separate compilation and import semantics

Ep24 Mutating variables across modules

Part V - Macros, again

Ep25 Back to macros (and accumulators)

Ep26 Macros taking macros as arguments (and the beauty of parentheses)

Ep27 Syntax objects and syntax transformers

Ep28 Hygienic macros

Ep29 Breaking hygiene

Ep30 Comparing identifiers

You can find an (experimental) book version of the Adventures (in PDF) here .

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About the Blogger

Michele Simionato started his career as a Theoretical Physicist, working in Italy, France and the U.S. He turned to programming in 2003; since then he has been working professionally as a Python developer and now he lives in Milan, Italy. Michele is well known in the Python community for his posts in the newsgroup(s), his articles and his Open Source libraries and recipes. His interests include object oriented programming, functional programming, and in general programming metodologies that enable us to manage the complexity of modern software developement.