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Writing recursive descent parsers by hand can be quite tricky to get right, and if we need to create many parsers it can soon become tedious both to write them and especially to maintain them One obvious solution is to use a generic parsing module, and those experienced with BNFs or with the Unix lex and yacc tools will naturally gravitate to similar tools In the section following this one we cover PLY (Python Lex Yacc), a tool that exempli es this classic approach But in this section we will look at a very different kind of parsing tool: PyParsing PyParsing is described by its author, Paul McGuire, as an alternative approach to creating and executing simple grammars, vs the traditional lex/yacc approach, or the use of regular expressions (Although in fact, regexes can be used with PyParsing) For those used to the traditional approach, PyParsing requires some reorientation in thinking The payback is the ability to develop parsers that do not require a lot of code thanks to PyParsing providing many high-level elements that can match common constructs and which are easy to understand and maintain PyParsing is available under an open source license and can be used in both noncommercial and commercial contexts However, PyParsing is not

#pragma omp flush (flag)

included in Python s standard library, so it must be downloaded and installed separately although for Linux users it is almost certainly available through the package management system It can be obtained from pyparsingwikispacescom click the page s Download link It comes in the form of an executable installation program for Windows and in source form for Unix-like systems such as Linux and Mac OS X The download page explains how to install it PyParsing is contained in a single module le, pyparsing_py3py, so it can easily be distributed with any program that uses it

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Figure 62 Program showing one way to implement pairwise synchronization in OpenMP The flush construct is vital It forces the memory to be consistent, thereby making the updates to the flag array visible For more details about the syntax of OpenMP see the OpenMP appendix, Appendix A ,

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PyParsing makes no real distinction between lexing and parsing Instead, it provides functions and classes to create parser elements one element for each thing to be matched Some parser elements are provided prede ned by PyParsing, others can be created by calling PyParsing functions or by instantiating PyParsing classes Parser elements can also be created by combining other parser elements together for example, concatenating them with + to form a sequence of parser elements, or OR-ing them with | to form a set of parser element alternatives Ultimately, a PyParsing parser is simply a collection of parser elements (which themselves may be made up of parser elements, etc), composed together If we want to process what we parse, we can process the results that PyParsing returns, or we can add parse actions (code snippets) to particular parser elements, or some combination of both PyParsing provides a wide range of parser elements, of which we will brie y describe some of the most commonly used The Literal() parser element matches the literal text it is given, and CaselessLiteral() does the same thing but ignores case If we are not interested in some part of the grammar we can use Suppress(); this matches the literal text (or parser element) it is given, but does not add it to the results The Keyword() element is almost the same as Literal() except that it must be followed by a nonkeyword character this prevents a match where a keyword is a pre x of something else For example, given the data text, lename , Literal("file") will match filename, with the name part left for the next parser element to match, but Keyword("file") won t match at all Another important parser element is Word() This element is given a string that it treats as a set of characters, and will match any sequence of any of the given characters For example, given the data text, abacus , Word("abc") will match abacus If the Word() element is given two strings, the rst is taken to contain those characters that are valid for the rst character of the match and the second to contain those characters that are valid for the remaining characters This is typically used to match identi ers for example, Word(alphas,.

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