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although this can lead to if statements with lots of elifs and nested if elifs that can be dif cult to maintain For more complex grammars, and those that are recursive, PyParsing, PLY, and other generic parser generators are a better choice than using regexes or nite state automata, or doing a handcrafted recursive descent parser Of all the approaches, PyParsing seems to require the least amount of code, although it can be tricky to get recursive grammars right, at least at rst PyParsing works at its best when we take full advantage of its prede ned functionality of which there is quite a lot more than we covered in this chapter and use the programming patterns that suit it This means that in more complex cases we cannot simply translate a BNF directly into PyParsing syntax, but must adapt the implementation of the BNF to t in with the PyParsing philosophy PyParsing is an excellent module, and it is used in many programming projects PLY not only supports the direct translation of BNFs, it requires that we do this, at least for the plyyacc module It also has a powerful and exible lexer which is suf cient in its own right for handling many simple grammars PLY also has excellent error reporting PLY uses a table-driven algorithm that makes its speed independent of the size or complexity of the grammar, so it tends to run faster than parsers that use recursive descent such as PyParsing One aspect of PLY that may take some getting used to is its heavy reliance on introspection, where both docstrings and function names have signi cance Nonetheless, PLY is an excellent module, and has been used to create some complex parsers, including ones for the C and ZXBasic programming languages Although it is generally straightforward to create a parser that accepts valid input, creating one that accepts all valid input and rejects all invalid input can be quite a challenge For example, do the rst-order logic parsers in this chapter s last section accept all valid formulas and reject all invalid ones And even if we do manage to reject invalid input, do we provide error messages that correctly identify what the problem is and where it occurred Parsing is a large and fascinating topic, and this chapter is designed to introduce the very basics, so further reading and practical experience are essential for those wanting to go further One other point that this chapter hints at is that as large and wide-ranging as Python s standard library is, many high-quality, third-party packages and modules that provide very useful additional functionality are also available Most of these are available through the Python Package Index, pypipythonorg/pypi, but some can only be discovered using a search engine In general, when you have some specialized need that is not met by Python s standard library, it is always worth looking for a third-party solution before writing your own.

[ Team LiB ]

Create a suitable BNF and then write a simple program for parsing basic BIBTEX book references, and that produces output in the form of a dictionary of dictionaries For example, given input like this:

@Book{blanchette+summerfield08, author = "Jasmin Blanchette and Mark Summerfield", title = "C++ GUI Programming with Qt 4, Second Edition", year = 2008, publisher = "Prentice Hall" }

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atoms and money, a contract is a binding agreement between two or more parties that speci es the supply of goods or services for a known price In the world of bits and services, a contract has a similar function: It s an agreement between two or more parties that speci es the messages that can be exchanged and the terms and conditions of those messages A contract is a description of the messages that are passed to and from service endpoints Each endpoint is de ned by the ABCs: an addressable location on the network where messages are sent, a binding that describes how messages are sent, and a contract that describes the message formats Remember that a service is really a collection of endpoints, and the endpoints implement the speci c algorithms in code They can implement high-level business functions, such as entering orders into a ful llment system, or they can be more ne-grained, such as looking up a customer s address High-level functions typically require complex data structures, whereas targeted functions often work in more basic data types In either case, an endpoint must specify the operations it implements and the data formats it expects Together, these speci cations make up the contract

the expected output would be a dictionary like this (here, pretty printed):

[ Team LiB ]

{'blanchette+summerfield08': { 'author': 'Jasmin Blanchette and Mark Summerfield', 'publisher': 'Prentice Hall', 'title': 'C++ GUI Programming with Qt 4, Second Edition', 'year': 2008 } }

Each book has an identi er and this should be used as the key for the outer dictionary The value should itself be a dictionary of key value items Each book s identi er can contain any characters except whitespace, and each key=value eld s value can either be an integer or a double-quoted string String values can include arbitrary whitespace including newlines, so replace every internal sequence of whitespace (including newlines) with a single space, and of course strip whitespace from the ends Note that the last key=value for a given book is not followed by a comma Create the parser using either PyParsing or PLY If using PyParsing, the Regex() class will be useful for the identi er and the QuotedString() class will be useful when de ning the value Use the delimitedList() function for handling the list of key=values If using PLY, the lexer is suf cient, providing you use separate tokens for integer and string values A solution using PyParsing should take around 30 lines, while one using PLY might take about 60 lines A solution that includes both PyParsing and PLY functions is provided in BibTeXpy

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