SLY (Sly Lex Yacc) ================== This document provides an overview of lexing and parsing with SLY. Given the intrinsic complexity of parsing, I would strongly advise that you read (or at least skim) this entire document before jumping into a big development project with SLY. SLY requires Python 3.5 or newer. If you're using an older version, you're out of luck. Sorry. Introduction ------------ SLY is library for writing parsers and compilers. It is loosely based on the traditional compiler construction tools lex and yacc and implements the same LALR(1) parsing algorithm. Most of the features available in lex and yacc are also available in SLY. It should also be noted that SLY does not provide much in the way of bells and whistles (e.g., automatic construction of abstract syntax trees, tree traversal, etc.). Nor should you view it as a parsing framework. Instead, you will find a bare-bones, yet fully capable library for writing parsers in Python. The rest of this document assumes that you are somewhat familiar with parsing theory, syntax directed translation, and the use of compiler construction tools such as lex and yacc in other programming languages. If you are unfamiliar with these topics, you will probably want to consult an introductory text such as "Compilers: Principles, Techniques, and Tools", by Aho, Sethi, and Ullman. O'Reilly's "Lex and Yacc" by John Levine may also be handy. In fact, the O'Reilly book can be used as a reference for SLY as the concepts are virtually identical. SLY Overview ------------ SLY provides two separate classes ``Lexer`` and ``Parser``. The ``Lexer`` class is used to break input text into a collection of tokens specified by a collection of regular expression rules. The ``Parser`` class is used to recognize language syntax that has been specified in the form of a context free grammar. The two classes are typically used together to make a parser. However, this is not a strict requirement--there is a great deal of flexibility allowed. The next two parts describe the basics. Writing a Lexer --------------- Suppose you're writing a programming language and a user supplied the following input string:: x = 3 + 42 * (s - t) The first step of any parsing is to break the text into tokens where each token has a type and value. For example, the above text might be described by the following list of token tuples:: [ ('ID','x'), ('EQUALS','='), ('NUMBER','3'), ('PLUS','+'), ('NUMBER','42'), ('TIMES','*'), ('LPAREN','('), ('ID','s'), ('MINUS','-'), ('ID','t'), ('RPAREN',')' ] The SLY ``Lexer`` class is used to do this. Here is a sample of a simple lexer:: # ------------------------------------------------------------ # calclex.py # # Lexer for a simple expression evaluator for # numbers and +,-,*,/ # ------------------------------------------------------------ from sly import Lexer class CalcLexer(Lexer): # List of token names. This is always required tokens = ( 'NUMBER', 'PLUS', 'MINUS', 'TIMES', 'DIVIDE', 'LPAREN', 'RPAREN', ) # String containing ignored characters (spaces and tabs) ignore = ' \t' # Regular expression rules for simple tokens PLUS = r'\+' MINUS = r'-' TIMES = r'\*' DIVIDE = r'/' LPAREN = r'\(' RPAREN = r'\)' # A regular expression rule with some action code @_(r'\d+') def NUMBER(self, t): t.value = int(t.value) return t # Define a rule so we can track line numbers @_(r'\n+') def newline(self, t): self.lineno += len(t.value) # Error handling rule (skips ahead one character) def error(self, value): print("Line %d: Illegal character '%s'" % (self.lineno, value[0])) self.index += 1 if __name__ == '__main__': data = ''' 3 + 4 * 10 + -20 * ^ 2 ''' lexer = CalcLexer() for tok in lexer.tokenize(data): print(tok) When executed, the example will produce the following output:: Token(NUMBER, 3, 2, 14) Token(PLUS, '+', 2, 16) Token(NUMBER, 4, 2, 18) Token(TIMES, '*', 2, 20) Token(NUMBER, 10, 2, 22) Token(PLUS, '+', 3, 40) Token(MINUS, '-', 3, 42) Token(NUMBER, 20, 3, 43) Token(TIMES, '*', 3, 46) Line 3: Illegal character '^' Token(NUMBER, 2, 3, 50) A lexer only has one public method ``tokenize()``. This is a generator function that produces a stream of ``Token`` instances. The ``type`` and ``value`` attributes of ``Token`` contain the token type name and value respectively. The ``lineno`` and ``index`` attributes contain the line number and position in the input text where the token appears. The tokens list ^^^^^^^^^^^^^^^ Lexers must specify a ``tokens`` attribute that defines all of the possible token type names that can be produced by the lexer. This list is always required and is used to perform a variety of validation checks. In the example, the following code specified the token names:: class CalcLexer(Lexer): ... # List of token names. This is always required tokens = ( 'NUMBER', 'PLUS', 'MINUS', 'TIMES', 'DIVIDE', 'LPAREN', 'RPAREN', ) ... Specification of tokens ^^^^^^^^^^^^^^^^^^^^^^^ Tokens are specified by writing a regular expression rule compatible with Python's ``re`` module. This is done by writing definitions that match one of the names of the tokens provided in the ``tokens`` attribute. For example:: PLUS = r'\+' MINUS = r'-' Sometimes you want to perform an action when a token is matched. For example, maybe you want to convert a numeric value or look up a symbol. To do this, write your action as a method and give the associated regular expression using the ``@_()`` decorator like this:: @_(r'\d+') def NUMBER(self, t): t.value = int(t.value) return t The method always takes a single argument which is an instance of ``Token``. By default, ``t.type`` is set to the name of the token (e.g., ``'NUMBER'``). The function can change the token type and value as it sees appropriate. When finished, the resulting token object should be returned as a result. If no value is returned by the function, the token is simply discarded and the next token read. Internally, the ``Lexer`` class uses the ``re`` module to do its pattern matching. Patterns are compiled using the ``re.VERBOSE`` flag which can be used to help readability. However, be aware that unescaped whitespace is ignored and comments are allowed in this mode. If your pattern involves whitespace, make sure you use ``\s``. If you need to match the ``#`` character, use ``[#]``. Controlling Match Order ^^^^^^^^^^^^^^^^^^^^^^^ Tokens are matched in the same order as patterns are listed in the ``Lexer`` class. Be aware that longer tokens may need to be specified before short tokens. For example, if you wanted to have separate tokens for "=" and "==", you need to make sure that "==" is listed first. For example:: class MyLexer(Lexer): tokens = ('ASSIGN', 'EQUALTO', ...) ... EQUALTO = r'==' # MUST APPEAR FIRST! ASSIGN = r'=' To handle reserved words, you should write a single rule to match an identifier and do a special name lookup in a function like this:: class MyLexer(Lexer): reserved = { 'if', 'then', 'else', 'while' } tokens = ['LPAREN','RPAREN',...,'ID'] + [ w.upper() for w in reserved ] @_(r'[a-zA-Z_][a-zA-Z_0-9]*') def ID(self, t): # Check to see if the name is a reserved word # If so, change its type. if t.value in self.reserved: t.type = t.value.upper() return t Note: You should avoid writing individual rules for reserved words. For example, suppose you wrote rules like this:: FOR = r'for' PRINT = r'print' In this case, the rules will be triggered for identifiers that include those words as a prefix such as "forget" or "printed". This is probably not what you want. Discarded text ^^^^^^^^^^^^^^ To discard text, such as a comment, simply define a token rule that returns no value. For example:: @_(r'\#.*') def COMMENT(self, t): pass # No return value. Token discarded Alternatively, you can include the prefix ``ignore_`` in a token declaration to force a token to be ignored. For example:: ignore_COMMENT = r'\#.*' Line numbers and position tracking ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ By default, lexers know nothing about line numbers. This is because they don't know anything about what constitutes a "line" of input (e.g., the newline character or even if the input is textual data). To update this information, you need to write a special rule. In the example, the ``newline()`` rule shows how to do this:: # Define a rule so we can track line numbers @_(r'\n+') def newline(self, t): self.lineno += len(t.value) Within the rule, the lineno attribute of the lexer is updated. After the line number is updated, the token is simply discarded since nothing is returned. Lexers do not perform and kind of automatic column tracking. However, it does record positional information related to each token in the ``index`` attribute. Using this, it is usually possible to compute column information as a separate step. For instance, you could count backwards until you reach the previous newline:: # Compute column. # input is the input text string # token is a token instance def find_column(text, token): last_cr = text.rfind('\n', 0, token.index) if last_cr < 0: last_cr = 0 column = (token.index - last_cr) + 1 return column Since column information is often only useful in the context of error handling, calculating the column position can be performed when needed as opposed to including it on each token. Ignored characters ^^^^^^^^^^^^^^^^^^ The special ``ignore`` specification is reserved for characters that should be completely ignored in the input stream. Usually this is used to skip over whitespace and other non-essential characters. Although it is possible to define a regular expression rule for whitespace in a manner similar to ``newline()``, the use of ``ignore`` provides substantially better lexing performance because it is handled as a special case and is checked in a much more efficient manner than the normal regular expression rules. The characters given in ``ignore`` are not ignored when such characters are part of other regular expression patterns. For example, if you had a rule to capture quoted text, that pattern can include the ignored characters (which will be captured in the normal way). The main purpose of ``ignore`` is to ignore whitespace and other padding between the tokens that you actually want to parse. Literal characters ^^^^^^^^^^^^^^^^^^ Literal characters can be specified by defining a variable ``literals`` in the class. For example:: class MyLexer(Lexer): ... literals = [ '+','-','*','/' ] ... A literal character is simply a single character that is returned "as is" when encountered by the lexer. Literals are checked after all of the defined regular expression rules. Thus, if a rule starts with one of the literal characters, it will always take precedence. When a literal token is returned, both its ``type`` and ``value`` attributes are set to the character itself. For example, ``'+'``. It's possible to write token methods that perform additional actions when literals are matched. However, you'll need to set the token type appropriately. For example:: class MyLexer(Lexer): literals = [ '{', '}' ] def __init__(self): self.indentation_level = 0 @_(r'\{') def lbrace(self, t): t.type = '{' # Set token type to the expected literal self.indentation_level += 1 return t @_(r'\}') def rbrace(t): t.type = '}' # Set token type to the expected literal self.indentation_level -=1 return t Error handling ^^^^^^^^^^^^^^ The ``error()`` method is used to handle lexing errors that occur when illegal characters are detected. The error method receives a string containing all remaining untokenized text. A typical handler might look at this text and skip ahead in some manner. For example:: class MyLexer(Lexer): ... # Error handling rule def error(self, value): print("Illegal character '%s'" % value[0]) self.index += 1 In this case, we simply print the offending character and skip ahead one character by updating the lexer position. Error handling in a parser is often a hard problem. An error handler might scan ahead to a logical synchronization point such as a semicolon, a blank line, or similar landmark. Maintaining extra state ^^^^^^^^^^^^^^^^^^^^^^^ In your lexer, you may want to maintain a variety of other state information. This might include mode settings, symbol tables, and other details. As an example, suppose that you wanted to keep track of how many NUMBER tokens had been encountered. You can do this by adding an ``__init__()`` method and adding more attributes. For example:: class MyLexer(Lexer): def __init__(self): self.num_count = 0 @_(r'\d+') def NUMBER(self,t): self.num_count += 1 t.value = int(t.value) return t Please note that lexers already use the ``lineno`` and ``position`` attributes during parsing. Writing a Parser ---------------- The ``Parser`` class is used to parse language syntax. Before showing an example, there are a few important bits of background that must be mentioned. First, *syntax* is usually specified in terms of a BNF grammar. For example, if you wanted to parse simple arithmetic expressions, you might first write an unambiguous grammar specification like this:: expr : expr + term | expr - term | term term : term * factor | term / factor | factor factor : NUMBER | ( expr ) In the grammar, symbols such as ``NUMBER``, ``+``, ``-``, ``*``, and ``/`` are known as *terminals* and correspond to raw input tokens. Identifiers such as ``term`` and ``factor`` refer to grammar rules comprised of a collection of terminals and other rules. These identifiers are known as *non-terminals*. The semantic behavior of a language is often specified using a technique known as syntax directed translation. In syntax directed translation, attributes are attached to each symbol in a given grammar rule along with an action. Whenever a particular grammar rule is recognized, the action describes what to do. For example, given the expression grammar above, you might write the specification for a simple calculator like this:: Grammar Action ------------------------ -------------------------------- expr0 : expr1 + term expr0.val = expr1.val + term.val | expr1 - term expr0.val = expr1.val - term.val | term expr0.val = term.val term0 : term1 * factor term0.val = term1.val * factor.val | term1 / factor term0.val = term1.val / factor.val | factor term0.val = factor.val factor : NUMBER factor.val = int(NUMBER.val) | ( expr ) factor.val = expr.val A good way to think about syntax directed translation is to view each symbol in the grammar as a kind of object. Associated with each symbol is a value representing its "state" (for example, the ``val`` attribute above). Semantic actions are then expressed as a collection of functions or methods that operate on the symbols and associated values. SLY uses a parsing technique known as LR-parsing or shift-reduce parsing. LR parsing is a bottom up technique that tries to recognize the right-hand-side of various grammar rules. Whenever a valid right-hand-side is found in the input, the appropriate action code is triggered and the grammar symbols are replaced by the grammar symbol on the left-hand-side. LR parsing is commonly implemented by shifting grammar symbols onto a stack and looking at the stack and the next input token for patterns that match one of the grammar rules. The details of the algorithm can be found in a compiler textbook, but the following example illustrates the steps that are performed if you wanted to parse the expression ``3 + 5 * (10 - 20)`` using the grammar defined above. In the example, the special symbol ``$`` represents the end of input:: Step Symbol Stack Input Tokens Action ---- --------------------- --------------------- ------------------------------- 1 3 + 5 * ( 10 - 20 )$ Shift 3 2 3 + 5 * ( 10 - 20 )$ Reduce factor : NUMBER 3 factor + 5 * ( 10 - 20 )$ Reduce term : factor 4 term + 5 * ( 10 - 20 )$ Reduce expr : term 5 expr + 5 * ( 10 - 20 )$ Shift + 6 expr + 5 * ( 10 - 20 )$ Shift 5 7 expr + 5 * ( 10 - 20 )$ Reduce factor : NUMBER 8 expr + factor * ( 10 - 20 )$ Reduce term : factor 9 expr + term * ( 10 - 20 )$ Shift * 10 expr + term * ( 10 - 20 )$ Shift ( 11 expr + term * ( 10 - 20 )$ Shift 10 12 expr + term * ( 10 - 20 )$ Reduce factor : NUMBER 13 expr + term * ( factor - 20 )$ Reduce term : factor 14 expr + term * ( term - 20 )$ Reduce expr : term 15 expr + term * ( expr - 20 )$ Shift - 16 expr + term * ( expr - 20 )$ Shift 20 17 expr + term * ( expr - 20 )$ Reduce factor : NUMBER 18 expr + term * ( expr - factor )$ Reduce term : factor 19 expr + term * ( expr - term )$ Reduce expr : expr - term 20 expr + term * ( expr )$ Shift ) 21 expr + term * ( expr ) $ Reduce factor : (expr) 22 expr + term * factor $ Reduce term : term * factor 23 expr + term $ Reduce expr : expr + term 24 expr $ Reduce expr 25 $ Success! When parsing the expression, an underlying state machine and the current input token determine what happens next. If the next token looks like part of a valid grammar rule (based on other items on the stack), it is generally shifted onto the stack. If the top of the stack contains a valid right-hand-side of a grammar rule, it is usually "reduced" and the symbols replaced with the symbol on the left-hand-side. When this reduction occurs, the appropriate action is triggered (if defined). If the input token can't be shifted and the top of stack doesn't match any grammar rules, a syntax error has occurred and the parser must take some kind of recovery step (or bail out). A parse is only successful if the parser reaches a state where the symbol stack is empty and there are no more input tokens. It is important to note that the underlying implementation is built around a large finite-state machine that is encoded in a collection of tables. The construction of these tables is non-trivial and beyond the scope of this discussion. However, subtle details of this process explain why, in the example above, the parser chooses to shift a token onto the stack in step 9 rather than reducing the rule ``expr : expr + term``. Parsing Example ^^^^^^^^^^^^^^^ Suppose you wanted to make a grammar for simple arithmetic expressions as previously described. Here is how you would do it with SLY:: from sly import Parser from calclex import CalcLexer class CalcParser(Parser): # Get the token list from the lexer (required) tokens = CalcLexer.tokens # Grammar rules and actions @_('expr PLUS term') def expr(self, p): p[0] = p[1] + p[3] @_('expr MINUS term') def expr(self, p): p[0] = p[1] - p[3] @_('term') def expr(self, p): p[0] = p[1] @_('term TIMES factor') def term(self, p): p[0] = p[1] * p[3] @_('term DIVIDE factor') def term(self, p): p[0] = p[1] / p[3] @_('factor') def term(self, p): p[0] = p[1] @_('NUMBER') def factor(self, p): p[0] = p[1] @_('LPAREN expr RPAREN') def factor(self, p): p[0] = p[2] # Error rule for syntax errors def error(self, p): print("Syntax error in input!") if __name__ == '__main__': lexer = CalcLexer() parser = CalcParser() while True: try: text = input('calc > ') result = parser.parse(lexer.tokenize(text)) print(result) except EOFError: break In this example, each grammar rule is defined by a Python function where the docstring to that function contains the appropriate context-free grammar specification. The statements that make up the function body implement the semantic actions of the rule. Each function accepts a single argument ``p`` that is a sequence containing the values of each grammar symbol in the corresponding rule. The values of ``p[i]`` are mapped to grammar symbols as shown here:: # p[1] p[2] p[3] # | | | @_('expr PLUS term') def expr(self, p): p[0] = p[1] + p[3] For tokens, the "value" of the corresponding ``p[i]`` is the *same* as the ``p.value`` attribute assigned in the lexer module. For non-terminals, the value is determined by whatever is placed in ``p[0]`` when rules are reduced. This value can be anything at all. However, it probably most common for the value to be a simple Python type, a tuple, or an instance. In this example, we are relying on the fact that the ``NUMBER`` token stores an integer value in its value field. All of the other rules simply perform various types of integer operations and propagate the result. Note: The use of negative indices have a special meaning in yacc---specially ``p[-1]`` does not have the same value as ``p[3]`` in this example. Please see the section on "Embedded Actions" for further details. The first rule defined in the yacc specification determines the starting grammar symbol (in this case, a rule for ``expr`` appears first). Whenever the starting rule is reduced by the parser and no more input is available, parsing stops and the final value is returned (this value will be whatever the top-most rule placed in ``p[0]``). Note: an alternative starting symbol can be specified using the ``start`` attribute in the class. The ``error()`` method is defined to catch syntax errors. See the error handling section below for more detail. If any errors are detected in your grammar specification, SLY will produce diagnostic messages and possibly raise an exception. Some of the errors that can be detected include: - Duplicated grammar rules - Shift/reduce and reduce/reduce conflicts generated by ambiguous grammars. - Badly specified grammar rules. - Infinite recursion (rules that can never terminate). - Unused rules and tokens - Undefined rules and tokens The final part of the example shows how to actually run the parser. To run the parser, you simply have to call the ``parse()`` method with a sequence of the input tokens. This will run all of the grammar rules and return the result of the entire parse. This result return is the value assigned to ``p[0]`` in the starting grammar rule. Combining Grammar Rule Functions ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ When grammar rules are similar, they can be combined into a single function. For example, consider the two rules in our earlier example:: @_('expr PLUS term') def expr(self, p): p[0] = p[1] + p[3] @_('expr MINUS term') def expr(self, p): p[0] = p[1] - p[3] Instead of writing two functions, you might write a single function like this: @_('expr PLUS term', 'expr MINUS term') def expr(self, p): if p[2] == '+': p[0] = p[1] + p[3] elif p[2] == '-': p[0] = p[1] - p[3] In general, the ``@_()`` decorator for any given method can list multiple grammar rules. When combining grammar rules into a single function though, it is usually a good idea for all of the rules to have a similar structure (e.g., the same number of terms). Otherwise, the corresponding action code may be more complicated than necessary. However, it is possible to handle simple cases using len(). For example: @_('expr MINUS expr', 'MINUS expression') def expr(self, p): if (len(p) == 4): p[0] = p[1] - p[3] elif (len(p) == 3): p[0] = -p[2] If parsing performance is a concern, you should resist the urge to put too much conditional processing into a single grammar rule as shown in these examples. When you add checks to see which grammar rule is being handled, you are actually duplicating the work that the parser has already performed (i.e., the parser already knows exactly what rule it matched). You can eliminate this overhead by using a separate method for each grammar rule. Character Literals ^^^^^^^^^^^^^^^^^^ If desired, a grammar may contain tokens defined as single character literals. For example:: @_('expr "+" term') def expr(self, p): p[0] = p[1] + p[3] @_('expr "-" term') def expr(self, p): p[0] = p[1] - p[3] A character literal must be enclosed in quotes such as ``"+"``. In addition, if literals are used, they must be declared in the corresponding lexer class through the use of a special ``literals`` declaration:: class CalcLexer(Lexer): ... literals = ['+','-','*','/' ] ... Character literals are limited to a single character. Thus, it is not legal to specify literals such as ``<=`` or ``==``. For this, use the normal lexing rules (e.g., define a rule such as ``EQ = r'=='``). Empty Productions ^^^^^^^^^^^^^^^^^ If you need an empty production, define a special rule like this:: @_('') def empty(self, p): pass Now to use the empty production, simply use 'empty' as a symbol. For example:: @_('item') def optitem(self, p): ... @_('empty') def optitem(self, p): ... Note: You can write empty rules anywhere by simply specifying an empty string. However, I personally find that writing an "empty" rule and using "empty" to denote an empty production is easier to read and more clearly states your intentions. Changing the starting symbol ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Normally, the first rule found in a yacc specification defines the starting grammar rule (top level rule). To change this, supply a ``start`` specifier in your file. For example:: class CalcParser(Parser): start = 'foo' @_('A B') def bar(self, p): ... @_('bar X') def foo(self, p): # Parsing starts here (start symbol above) ... The use of a ``start`` specifier may be useful during debugging since you can use it to work with a subset of a larger grammar. Dealing With Ambiguous Grammars ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The expression grammar given in the earlier example has been written in a special format to eliminate ambiguity. However, in many situations, it is extremely difficult or awkward to write grammars in this format. A much more natural way to express the grammar is in a more compact form like this:: expr : expr PLUS expr | expr MINUS expr | expr TIMES expr | expr DIVIDE expr | LPAREN expr RPAREN | NUMBER Unfortunately, this grammar specification is ambiguous. For example, if you are parsing the string "3 * 4 + 5", there is no way to tell how the operators are supposed to be grouped. For example, does the expression mean "(3 * 4) + 5" or is it "3 * (4+5)"? When an ambiguous grammar is given, you will get messages about "shift/reduce conflicts" or "reduce/reduce conflicts". A shift/reduce conflict is caused when the parser generator can't decide whether or not to reduce a rule or shift a symbol on the parsing stack. For example, consider the string "3 * 4 + 5" and the internal parsing stack:: Step Symbol Stack Input Tokens Action ---- --------------------- --------------------- ------------------------------- 1 $ 3 * 4 + 5$ Shift 3 2 $ 3 * 4 + 5$ Reduce : expr : NUMBER 3 $ expr * 4 + 5$ Shift * 4 $ expr * 4 + 5$ Shift 4 5 $ expr * 4 + 5$ Reduce: expr : NUMBER 6 $ expr * expr + 5$ SHIFT/REDUCE CONFLICT ???? In this case, when the parser reaches step 6, it has two options. One is to reduce the rule ``expr : expr * expr`` on the stack. The other option is to shift the token ``+`` on the stack. Both options are perfectly legal from the rules of the context-free-grammar. By default, all shift/reduce conflicts are resolved in favor of shifting. Therefore, in the above example, the parser will always shift the ``+`` instead of reducing. Although this strategy works in many cases (for example, the case of "if-then" versus "if-then-else"), it is not enough for arithmetic expressions. In fact, in the above example, the decision to shift ``+`` is completely wrong---we should have reduced ``expr * expr`` since multiplication has higher mathematical precedence than addition. To resolve ambiguity, especially in expression grammars, SLY allows individual tokens to be assigned a precedence level and associativity. This is done by adding a variable ``precedence`` to the grammar file like this:: class CalcParser(Parser): ... precedence = ( ('left', 'PLUS', 'MINUS'), ('left', 'TIMES', 'DIVIDE'), ) ... This declaration specifies that ``PLUS``/``MINUS`` have the same precedence level and are left-associative and that ``TIMES``/``DIVIDE`` have the same precedence and are left-associative. Within the ``precedence`` declaration, tokens are ordered from lowest to highest precedence. Thus, this declaration specifies that ``TIMES``/``DIVIDE`` have higher precedence than ``PLUS``/``MINUS`` (since they appear later in the precedence specification). The precedence specification works by associating a numerical precedence level value and associativity direction to the listed tokens. For example, in the above example you get:: PLUS : level = 1, assoc = 'left' MINUS : level = 1, assoc = 'left' TIMES : level = 2, assoc = 'left' DIVIDE : level = 2, assoc = 'left' These values are then used to attach a numerical precedence value and associativity direction to each grammar rule. *This is always determined by looking at the precedence of the right-most terminal symbol.* For example:: expr : expr PLUS expr # level = 1, left | expr MINUS expr # level = 1, left | expr TIMES expr # level = 2, left | expr DIVIDE expr # level = 2, left | LPAREN expr RPAREN # level = None (not specified) | NUMBER # level = None (not specified) When shift/reduce conflicts are encountered, the parser generator resolves the conflict by looking at the precedence rules and associativity specifiers. 1. If the current token has higher precedence than the rule on the stack, it is shifted. 2. If the grammar rule on the stack has higher precedence, the rule is reduced. 3. If the current token and the grammar rule have the same precedence, the rule is reduced for left associativity, whereas the token is shifted for right associativity. 4. If nothing is known about the precedence, shift/reduce conflicts are resolved in favor of shifting (the default). For example, if "expr PLUS expr" has been parsed and the next token is "TIMES", the action is going to be a shift because "TIMES" has a higher precedence level than "PLUS". On the other hand, if "expr TIMES expr" has been parsed and the next token is "PLUS", the action is going to be reduce because "PLUS" has a lower precedence than "TIMES." When shift/reduce conflicts are resolved using the first three techniques (with the help of precedence rules), SLY will report no errors or conflicts in the grammar. One problem with the precedence specifier technique is that it is sometimes necessary to change the precedence of an operator in certain contexts. For example, consider a unary-minus operator in "3 + 4 * -5". Mathematically, the unary minus is normally given a very high precedence--being evaluated before the multiply. However, in our precedence specifier, MINUS has a lower precedence than TIMES. To deal with this, precedence rules can be given for so-called "fictitious tokens" like this:: class CalcParser(Parser): ... precedence = ( ('left', 'PLUS', 'MINUS'), ('left', 'TIMES', 'DIVIDE'), ('right', 'UMINUS'), # Unary minus operator ) Now, in the grammar file, we can write our unary minus rule like this:: @_('MINUS expr %prec UMINUS') def expr(p): p[0] = -p[2] In this case, ``%prec UMINUS`` overrides the default rule precedence--setting it to that of UMINUS in the precedence specifier. At first, the use of UMINUS in this example may appear very confusing. UMINUS is not an input token or a grammar rule. Instead, you should think of it as the name of a special marker in the precedence table. When you use the ``%prec`` qualifier, you're simply telling SLY that you want the precedence of the expression to be the same as for this special marker instead of the usual precedence. It is also possible to specify non-associativity in the ``precedence`` table. This would be used when you *don't* want operations to chain together. For example, suppose you wanted to support comparison operators like ``<`` and ``>`` but you didn't want to allow combinations like ``a < b < c``. To do this, specify a rule like this:: class MyParser(Parser): ... precedence = ( ('nonassoc', 'LESSTHAN', 'GREATERTHAN'), # Nonassociative operators ('left', 'PLUS', 'MINUS'), ('left', 'TIMES', 'DIVIDE'), ('right', 'UMINUS'), # Unary minus operator ) If you do this, the occurrence of input text such as ``a < b < c`` will result in a syntax error. However, simple expressions such as ``a < b`` will still be fine. Reduce/reduce conflicts are caused when there are multiple grammar rules that can be applied to a given set of symbols. This kind of conflict is almost always bad and is always resolved by picking the rule that appears first in the grammar file. Reduce/reduce conflicts are almost always caused when different sets of grammar rules somehow generate the same set of symbols. For example:: assignment : ID EQUALS NUMBER | ID EQUALS expr expr : expr PLUS expr | expr MINUS expr | expr TIMES expr | expr DIVIDE expr | LPAREN expr RPAREN | NUMBER In this case, a reduce/reduce conflict exists between these two rules:: assignment : ID EQUALS NUMBER expr : NUMBER For example, if you wrote "a = 5", the parser can't figure out if this is supposed to be reduced as ``assignment : ID EQUALS NUMBER`` or whether it's supposed to reduce the 5 as an expression and then reduce the rule ``assignment : ID EQUALS expr``. It should be noted that reduce/reduce conflicts are notoriously difficult to spot simply looking at the input grammar. When a reduce/reduce conflict occurs, SLY will try to help by printing a warning message such as this:: WARNING: 1 reduce/reduce conflict WARNING: reduce/reduce conflict in state 15 resolved using rule (assignment -> ID EQUALS NUMBER) WARNING: rejected rule (expression -> NUMBER) This message identifies the two rules that are in conflict. However, it may not tell you how the parser arrived at such a state. To try and figure it out, you'll probably have to look at your grammar and the contents of the parser debugging file with an appropriately high level of caffeination (see the next section). Parser Debugging ^^^^^^^^^^^^^^^^ Tracking down shift/reduce and reduce/reduce conflicts is one of the finer pleasures of using an LR parsing algorithm. To assist in debugging, SLY creates a debugging file called 'parser.out' when it generates the parsing table. The contents of this file look like the following:
The different states that appear in this file are a representation of every possible sequence of valid input tokens allowed by the grammar. When receiving input tokens, the parser is building up a stack and looking for matching rules. Each state keeps track of the grammar rules that might be in the process of being matched at that point. Within each rule, the "." character indicates the current location of the parse within that rule. In addition, the actions for each valid input token are listed. When a shift/reduce or reduce/reduce conflict arises, rules not selected are prefixed with an !. For example:Unused terminals: Grammar Rule 1 expression -> expression PLUS expression Rule 2 expression -> expression MINUS expression Rule 3 expression -> expression TIMES expression Rule 4 expression -> expression DIVIDE expression Rule 5 expression -> NUMBER Rule 6 expression -> LPAREN expression RPAREN Terminals, with rules where they appear TIMES : 3 error : MINUS : 2 RPAREN : 6 LPAREN : 6 DIVIDE : 4 PLUS : 1 NUMBER : 5 Nonterminals, with rules where they appear expression : 1 1 2 2 3 3 4 4 6 0 Parsing method: LALR state 0 S' -> . expression expression -> . expression PLUS expression expression -> . expression MINUS expression expression -> . expression TIMES expression expression -> . expression DIVIDE expression expression -> . NUMBER expression -> . LPAREN expression RPAREN NUMBER shift and go to state 3 LPAREN shift and go to state 2 state 1 S' -> expression . expression -> expression . PLUS expression expression -> expression . MINUS expression expression -> expression . TIMES expression expression -> expression . DIVIDE expression PLUS shift and go to state 6 MINUS shift and go to state 5 TIMES shift and go to state 4 DIVIDE shift and go to state 7 state 2 expression -> LPAREN . expression RPAREN expression -> . expression PLUS expression expression -> . expression MINUS expression expression -> . expression TIMES expression expression -> . expression DIVIDE expression expression -> . NUMBER expression -> . LPAREN expression RPAREN NUMBER shift and go to state 3 LPAREN shift and go to state 2 state 3 expression -> NUMBER . $ reduce using rule 5 PLUS reduce using rule 5 MINUS reduce using rule 5 TIMES reduce using rule 5 DIVIDE reduce using rule 5 RPAREN reduce using rule 5 state 4 expression -> expression TIMES . expression expression -> . expression PLUS expression expression -> . expression MINUS expression expression -> . expression TIMES expression expression -> . expression DIVIDE expression expression -> . NUMBER expression -> . LPAREN expression RPAREN NUMBER shift and go to state 3 LPAREN shift and go to state 2 state 5 expression -> expression MINUS . expression expression -> . expression PLUS expression expression -> . expression MINUS expression expression -> . expression TIMES expression expression -> . expression DIVIDE expression expression -> . NUMBER expression -> . LPAREN expression RPAREN NUMBER shift and go to state 3 LPAREN shift and go to state 2 state 6 expression -> expression PLUS . expression expression -> . expression PLUS expression expression -> . expression MINUS expression expression -> . expression TIMES expression expression -> . expression DIVIDE expression expression -> . NUMBER expression -> . LPAREN expression RPAREN NUMBER shift and go to state 3 LPAREN shift and go to state 2 state 7 expression -> expression DIVIDE . expression expression -> . expression PLUS expression expression -> . expression MINUS expression expression -> . expression TIMES expression expression -> . expression DIVIDE expression expression -> . NUMBER expression -> . LPAREN expression RPAREN NUMBER shift and go to state 3 LPAREN shift and go to state 2 state 8 expression -> LPAREN expression . RPAREN expression -> expression . PLUS expression expression -> expression . MINUS expression expression -> expression . TIMES expression expression -> expression . DIVIDE expression RPAREN shift and go to state 13 PLUS shift and go to state 6 MINUS shift and go to state 5 TIMES shift and go to state 4 DIVIDE shift and go to state 7 state 9 expression -> expression TIMES expression . expression -> expression . PLUS expression expression -> expression . MINUS expression expression -> expression . TIMES expression expression -> expression . DIVIDE expression $ reduce using rule 3 PLUS reduce using rule 3 MINUS reduce using rule 3 TIMES reduce using rule 3 DIVIDE reduce using rule 3 RPAREN reduce using rule 3 ! PLUS [ shift and go to state 6 ] ! MINUS [ shift and go to state 5 ] ! TIMES [ shift and go to state 4 ] ! DIVIDE [ shift and go to state 7 ] state 10 expression -> expression MINUS expression . expression -> expression . PLUS expression expression -> expression . MINUS expression expression -> expression . TIMES expression expression -> expression . DIVIDE expression $ reduce using rule 2 PLUS reduce using rule 2 MINUS reduce using rule 2 RPAREN reduce using rule 2 TIMES shift and go to state 4 DIVIDE shift and go to state 7 ! TIMES [ reduce using rule 2 ] ! DIVIDE [ reduce using rule 2 ] ! PLUS [ shift and go to state 6 ] ! MINUS [ shift and go to state 5 ] state 11 expression -> expression PLUS expression . expression -> expression . PLUS expression expression -> expression . MINUS expression expression -> expression . TIMES expression expression -> expression . DIVIDE expression $ reduce using rule 1 PLUS reduce using rule 1 MINUS reduce using rule 1 RPAREN reduce using rule 1 TIMES shift and go to state 4 DIVIDE shift and go to state 7 ! TIMES [ reduce using rule 1 ] ! DIVIDE [ reduce using rule 1 ] ! PLUS [ shift and go to state 6 ] ! MINUS [ shift and go to state 5 ] state 12 expression -> expression DIVIDE expression . expression -> expression . PLUS expression expression -> expression . MINUS expression expression -> expression . TIMES expression expression -> expression . DIVIDE expression $ reduce using rule 4 PLUS reduce using rule 4 MINUS reduce using rule 4 TIMES reduce using rule 4 DIVIDE reduce using rule 4 RPAREN reduce using rule 4 ! PLUS [ shift and go to state 6 ] ! MINUS [ shift and go to state 5 ] ! TIMES [ shift and go to state 4 ] ! DIVIDE [ shift and go to state 7 ] state 13 expression -> LPAREN expression RPAREN . $ reduce using rule 6 PLUS reduce using rule 6 MINUS reduce using rule 6 TIMES reduce using rule 6 DIVIDE reduce using rule 6 RPAREN reduce using rule 6
By looking at these rules (and with a little practice), you can usually track down the source of most parsing conflicts. It should also be stressed that not all shift-reduce conflicts are bad. However, the only way to be sure that they are resolved correctly is to look at parser.out.! TIMES [ reduce using rule 2 ] ! DIVIDE [ reduce using rule 2 ] ! PLUS [ shift and go to state 6 ] ! MINUS [ shift and go to state 5 ]
When a syntax error occurs, yacc.py performs the following steps:
To account for the possibility of a bad expression, you might write an additional grammar rule like this:def p_statement_print(p): 'statement : PRINT expr SEMI' ...
In this case, the error token will match any sequence of tokens that might appear up to the first semicolon that is encountered. Once the semicolon is reached, the rule will be invoked and the error token will go away.def p_statement_print_error(p): 'statement : PRINT error SEMI' print("Syntax error in print statement. Bad expression")
This type of recovery is sometimes known as parser resynchronization. The error token acts as a wildcard for any bad input text and the token immediately following error acts as a synchronization token.
It is important to note that the error token usually does not appear as the last token on the right in an error rule. For example:
This is because the first bad token encountered will cause the rule to be reduced--which may make it difficult to recover if more bad tokens immediately follow.def p_statement_print_error(p): 'statement : PRINT error' print("Syntax error in print statement. Bad expression")
Panic mode recovery is implemented entirely in the p_error() function. For example, this function starts discarding tokens until it reaches a closing '}'. Then, it restarts the parser in its initial state.
def p_error(p): print("Whoa. You are seriously hosed.") if not p: print("End of File!") return # Read ahead looking for a closing '}' while True: tok = parser.token() # Get the next token if not tok or tok.type == 'RBRACE': break parser.restart()
This function simply discards the bad token and tells the parser that the error was ok.
def p_error(p): if p: print("Syntax error at token", p.type) # Just discard the token and tell the parser it's okay. parser.errok() else: print("Syntax error at EOF")
More information on these methods is as follows:
To supply the next lookahead token to the parser, p_error() can return a token. This might be useful if trying to synchronize on special characters. For example:
def p_error(p): # Read ahead looking for a terminating ";" while True: tok = parser.token() # Get the next token if not tok or tok.type == 'SEMI': break parser.errok() # Return SEMI to the parser as the next lookahead token return tok
Keep in mind in that the above error handling functions, parser is an instance of the parser created by yacc(). You'll need to save this instance someplace in your code so that you can refer to it during error handling.
The effect of raising SyntaxError is the same as if the last symbol shifted onto the parsing stack was actually a syntax error. Thus, when you do this, the last symbol shifted is popped off of the parsing stack and the current lookahead token is set to an error token. The parser then enters error-recovery mode where it tries to reduce rules that can accept error tokens. The steps that follow from this point are exactly the same as if a syntax error were detected and p_error() were called.def p_production(p): 'production : some production ...' raise SyntaxError
One important aspect of manually setting an error is that the p_error() function will NOT be called in this case. If you need to issue an error message, make sure you do it in the production that raises SyntaxError.
Note: This feature of PLY is meant to mimic the behavior of the YYERROR macro in yacc.
In most cases, yacc will handle errors as soon as a bad input token is detected on the input. However, be aware that yacc may choose to delay error handling until after it has reduced one or more grammar rules first. This behavior might be unexpected, but it's related to special states in the underlying parsing table known as "defaulted states." A defaulted state is parsing condition where the same grammar rule will be reduced regardless of what valid token comes next on the input. For such states, yacc chooses to go ahead and reduce the grammar rule without reading the next input token. If the next token is bad, yacc will eventually get around to reading it and report a syntax error. It's just a little unusual in that you might see some of your grammar rules firing immediately prior to the syntax error.
Usually, the delayed error reporting with defaulted states is harmless (and there are other reasons for wanting PLY to behave in this way). However, if you need to turn this behavior off for some reason. You can clear the defaulted states table like this:
parser = yacc.yacc() parser.defaulted_states = {}
Disabling defaulted states is not recommended if your grammar makes use of embedded actions as described in Section 6.11.
As an optional feature, yacc.py can automatically track line numbers and positions for all of the grammar symbols as well. However, this extra tracking requires extra processing and can significantly slow down parsing. Therefore, it must be enabled by passing the tracking=True option to yacc.parse(). For example:def p_expression(p): 'expression : expression PLUS expression' line = p.lineno(2) # line number of the PLUS token index = p.lexpos(2) # Position of the PLUS token
Once enabled, the lineno() and lexpos() methods work for all grammar symbols. In addition, two additional methods can be used:yacc.parse(data,tracking=True)
Note: The lexspan() function only returns the range of values up to the start of the last grammar symbol.def p_expression(p): 'expression : expression PLUS expression' p.lineno(1) # Line number of the left expression p.lineno(2) # line number of the PLUS operator p.lineno(3) # line number of the right expression ... start,end = p.linespan(3) # Start,end lines of the right expression starti,endi = p.lexspan(3) # Start,end positions of right expression
Although it may be convenient for PLY to track position information on all grammar symbols, this is often unnecessary. For example, if you are merely using line number information in an error message, you can often just key off of a specific token in the grammar rule. For example:
def p_bad_func(p): 'funccall : fname LPAREN error RPAREN' # Line number reported from LPAREN token print("Bad function call at line", p.lineno(2))
Similarly, you may get better parsing performance if you only selectively propagate line number information where it's needed using the p.set_lineno() method. For example:
PLY doesn't retain line number information from rules that have already been parsed. If you are building an abstract syntax tree and need to have line numbers, you should make sure that the line numbers appear in the tree itself.def p_fname(p): 'fname : ID' p[0] = p[1] p.set_lineno(0,p.lineno(1))
A minimal way to construct a tree is to simply create and propagate a tuple or list in each grammar rule function. There are many possible ways to do this, but one example would be something like this:
def p_expression_binop(p): '''expression : expression PLUS expression | expression MINUS expression | expression TIMES expression | expression DIVIDE expression''' p[0] = ('binary-expression',p[2],p[1],p[3]) def p_expression_group(p): 'expression : LPAREN expression RPAREN' p[0] = ('group-expression',p[2]) def p_expression_number(p): 'expression : NUMBER' p[0] = ('number-expression',p[1])
Another approach is to create a set of data structure for different kinds of abstract syntax tree nodes and assign nodes to p[0] in each rule. For example:
The advantage to this approach is that it may make it easier to attach more complicated semantics, type checking, code generation, and other features to the node classes.class Expr: pass class BinOp(Expr): def __init__(self,left,op,right): self.type = "binop" self.left = left self.right = right self.op = op class Number(Expr): def __init__(self,value): self.type = "number" self.value = value def p_expression_binop(p): '''expression : expression PLUS expression | expression MINUS expression | expression TIMES expression | expression DIVIDE expression''' p[0] = BinOp(p[1],p[2],p[3]) def p_expression_group(p): 'expression : LPAREN expression RPAREN' p[0] = p[2] def p_expression_number(p): 'expression : NUMBER' p[0] = Number(p[1])
To simplify tree traversal, it may make sense to pick a very generic tree structure for your parse tree nodes. For example:
class Node: def __init__(self,type,children=None,leaf=None): self.type = type if children: self.children = children else: self.children = [ ] self.leaf = leaf def p_expression_binop(p): '''expression : expression PLUS expression | expression MINUS expression | expression TIMES expression | expression DIVIDE expression''' p[0] = Node("binop", [p[1],p[3]], p[2])
def p_foo(p): "foo : A B C D" print("Parsed a foo", p[1],p[2],p[3],p[4])
In this case, the supplied action code only executes after all of the symbols A, B, C, and D have been parsed. Sometimes, however, it is useful to execute small code fragments during intermediate stages of parsing. For example, suppose you wanted to perform some action immediately after A has been parsed. To do this, write an empty rule like this:
def p_foo(p): "foo : A seen_A B C D" print("Parsed a foo", p[1],p[3],p[4],p[5]) print("seen_A returned", p[2]) def p_seen_A(p): "seen_A :" print("Saw an A = ", p[-1]) # Access grammar symbol to left p[0] = some_value # Assign value to seen_A
In this example, the empty seen_A rule executes immediately after A is shifted onto the parsing stack. Within this rule, p[-1] refers to the symbol on the stack that appears immediately to the left of the seen_A symbol. In this case, it would be the value of A in the foo rule immediately above. Like other rules, a value can be returned from an embedded action by simply assigning it to p[0]
The use of embedded actions can sometimes introduce extra shift/reduce conflicts. For example, this grammar has no conflicts:
However, if you insert an embedded action into one of the rules like this,def p_foo(p): """foo : abcd | abcx""" def p_abcd(p): "abcd : A B C D" def p_abcx(p): "abcx : A B C X"
an extra shift-reduce conflict will be introduced. This conflict is caused by the fact that the same symbol C appears next in both the abcd and abcx rules. The parser can either shift the symbol (abcd rule) or reduce the empty rule seen_AB (abcx rule).def p_foo(p): """foo : abcd | abcx""" def p_abcd(p): "abcd : A B C D" def p_abcx(p): "abcx : A B seen_AB C X" def p_seen_AB(p): "seen_AB :"
A common use of embedded rules is to control other aspects of parsing such as scoping of local variables. For example, if you were parsing C code, you might write code like this:
In this case, the embedded action new_scope executes immediately after a LBRACE ({) symbol is parsed. This might adjust internal symbol tables and other aspects of the parser. Upon completion of the rule statements_block, code might undo the operations performed in the embedded action (e.g., pop_scope()).def p_statements_block(p): "statements: LBRACE new_scope statements RBRACE""" # Action code ... pop_scope() # Return to previous scope def p_new_scope(p): "new_scope :" # Create a new scope for local variables s = new_scope() push_scope(s) ...
in this case, x must be a Lexer object that minimally has a x.token() method for retrieving the next token. If an input string is given to yacc.parse(), the lexer must also have an x.input() method.parser = yacc.parse(lexer=x)
parser = yacc.yacc(debug=False)
parser = yacc.yacc(tabmodule="foo")
Normally, the parsetab.py file is placed into the same directory as the module where the parser is defined. If you want it to go somewhere else, you can given an absolute package name for tabmodule instead. In that case, the tables will be written there.
parser = yacc.yacc(tabmodule="foo",outputdir="somedirectory")
Note: Be aware that unless the directory specified is also on Python's path (sys.path), subsequent imports of the table file will fail. As a general rule, it's better to specify a destination using the tabmodule argument instead of directly specifying a directory using the outputdir argument.
Note: If you disable table generation, yacc() will regenerate the parsing tables each time it runs (which may take awhile depending on how large your grammar is).parser = yacc.yacc(write_tables=False)
parser = yacc.parse(debug=True)
It should be noted that table generation is reasonably efficient, even for grammars that involve around a 100 rules and several hundred states.
from functools import wraps from nodes import Collection def strict(*types): def decorate(func): @wraps(func) def wrapper(p): func(p) if not isinstance(p[0], types): raise TypeError wrapper.co_firstlineno = func.__code__.co_firstlineno return wrapper return decorate @strict(Collection) def p_collection(p): """ collection : sequence | map """ p[0] = p[1]
As a general rules this isn't a problem. However, to make it work, you need to carefully make sure everything gets hooked up correctly. First, make sure you save the objects returned by lex() and yacc(). For example:
Next, when parsing, make sure you give the parse() function a reference to the lexer it should be using. For example:lexer = lex.lex() # Return lexer object parser = yacc.yacc() # Return parser object
If you forget to do this, the parser will use the last lexer created--which is not always what you want.parser.parse(text,lexer=lexer)
Within lexer and parser rule functions, these objects are also available. In the lexer, the "lexer" attribute of a token refers to the lexer object that triggered the rule. For example:
In the parser, the "lexer" and "parser" attributes refer to the lexer and parser objects respectively.def t_NUMBER(t): r'\d+' ... print(t.lexer) # Show lexer object
If necessary, arbitrary attributes can be attached to the lexer or parser object. For example, if you wanted to have different parsing modes, you could attach a mode attribute to the parser object and look at it later.def p_expr_plus(p): 'expr : expr PLUS expr' ... print(p.parser) # Show parser object print(p.lexer) # Show lexer object
then PLY can later be used when Python runs in optimized mode. To make this work, make sure you first run Python in normal mode. Once the lexing and parsing tables have been generated the first time, run Python in optimized mode. PLY will use the tables without the need for doc strings.lex.lex(optimize=1) yacc.yacc(optimize=1)
Beware: running PLY in optimized mode disables a lot of error checking. You should only do this when your project has stabilized and you don't need to do any debugging. One of the purposes of optimized mode is to substantially decrease the startup time of your compiler (by assuming that everything is already properly specified and works).
Debugging a compiler is typically not an easy task. PLY provides some advanced diagostic capabilities through the use of Python's logging module. The next two sections describe this:
Both the lex() and yacc() commands have a debugging mode that can be enabled using the debug flag. For example:
Normally, the output produced by debugging is routed to either standard error or, in the case of yacc(), to a file parser.out. This output can be more carefully controlled by supplying a logging object. Here is an example that adds information about where different debugging messages are coming from:lex.lex(debug=True) yacc.yacc(debug=True)
If you supply a custom logger, the amount of debugging information produced can be controlled by setting the logging level. Typically, debugging messages are either issued at the DEBUG, INFO, or WARNING levels.# Set up a logging object import logging logging.basicConfig( level = logging.DEBUG, filename = "parselog.txt", filemode = "w", format = "%(filename)10s:%(lineno)4d:%(message)s" ) log = logging.getLogger() lex.lex(debug=True,debuglog=log) yacc.yacc(debug=True,debuglog=log)
PLY's error messages and warnings are also produced using the logging interface. This can be controlled by passing a logging object using the errorlog parameter.
If you want to completely silence warnings, you can either pass in a logging object with an appropriate filter level or use the NullLogger object defined in either lex or yacc. For example:lex.lex(errorlog=log) yacc.yacc(errorlog=log)
yacc.yacc(errorlog=yacc.NullLogger())
To enable run-time debugging of a parser, use the debug option to parse. This option can either be an integer (which simply turns debugging on or off) or an instance of a logger object. For example:
If a logging object is passed, you can use its filtering level to control how much output gets generated. The INFO level is used to produce information about rule reductions. The DEBUG level will show information about the parsing stack, token shifts, and other details. The ERROR level shows information related to parsing errors.log = logging.getLogger() parser.parse(input,debug=log)
For very complicated problems, you should pass in a logging object that redirects to a file where you can more easily inspect the output after execution.