parsing-toys 1.0.1

An educational tool for visualizing Context-Free Grammar (CFG) parsing algorithms.

Parsing Toys

Python bindings for Parsing Toys - an educational tool for visualizing Context-Free Grammar (CFG) parsing algorithms.

Installation

pip install sp-parsing-toys

Usage

Context-Free Grammar

from parsing_toys import ContextFreeGrammar

# Parse a grammar
cfg = ContextFreeGrammar()
cfg.parse("""
    E -> E + T | T
    T -> T * F | F
    F -> ( E ) | id
""")

print(cfg)

# Get terminals and non-terminals
print("Terminals:", cfg.terminals())
print("Non-terminals:", cfg.non_terminals())

Left Factoring & Left Recursion Elimination

from parsing_toys import ContextFreeGrammar

cfg = ContextFreeGrammar()
cfg.parse("""
    S -> a B | a C
    B -> b
    C -> c
""")

cfg.left_factoring()
print("After left factoring:")
print(cfg)

FIRST and FOLLOW Sets

from parsing_toys import ContextFreeGrammar

cfg = ContextFreeGrammar()
cfg.parse("""
    E -> T E'
    E' -> + T E' | ε
    T -> F T'
    T' -> * F T' | ε
    F -> ( E ) | id
""")

ff = cfg.compute_first_and_follow_set()
for i in range(ff.size()):
    symbol = ff.symbol_at(i)
    print(f"{symbol}:")
    print(f"  FIRST: {ff.get_first_set(symbol)}")
    print(f"  FOLLOW: {ff.get_follow_set(symbol)}")

LL(1) Parsing

from parsing_toys import ContextFreeGrammar

cfg = ContextFreeGrammar()
cfg.parse("""
    E -> T E'
    E' -> + T E' | ε
    T -> F T'
    T' -> * F T' | ε
    F -> ( E ) | id
""")

table = cfg.compute_ll1_table()
print("Has conflict:", table.has_conflict())

steps = table.parse("id + id * id")
print(steps)

LR Parsing (LR(0), SLR(1), LR(1), LALR(1))

from parsing_toys import ContextFreeGrammar

cfg = ContextFreeGrammar()
cfg.parse("""
    E -> E + T | T
    T -> T * F | F
    F -> ( E ) | id
""")

# SLR(1) parsing
automaton = cfg.compute_slr1_automaton()
table = cfg.compute_slr1_action_goto_table(automaton)

print("Has conflict:", table.has_conflict())

steps = table.parse("id + id * id")
print(steps)

# Get parse tree
if table.parse_tree:
    svg = table.parse_tree.to_svg()

CYK Parsing

from parsing_toys import ContextFreeGrammar

cfg = ContextFreeGrammar()
cfg.parse("""
    S -> A B
    A -> a
    B -> b
""")

# Convert to Chomsky Normal Form
cfg.to_chomsky_normal_form()
print("Is CNF:", cfg.is_chomsky_normal_form())

# Parse using CYK algorithm
result = cfg.cyk_parse("a b")
print("Accepted:", result.accepted)

Regular Expressions (NFA/DFA)

from parsing_toys import RegularExpression

re = RegularExpression()
re.parse("(a|b)*abb")

# Convert to NFA
nfa = re.to_nfa()
nfa_graph = RegularExpression.to_nfa_graph(nfa)
print("NFA states:", nfa_graph.size())

# Convert to DFA
dfa = RegularExpression.to_dfa(nfa)
dfa_graph = RegularExpression.to_dfa_graph(dfa)
print("DFA states:", dfa_graph.size())

# Minimize DFA
min_dfa = RegularExpression.to_min_dfa(dfa)
min_dfa_graph = RegularExpression.to_dfa_graph(min_dfa)
print("Minimized DFA states:", min_dfa_graph.size())

# Generate SVG visualization
svg = nfa_graph.to_svg()

API Reference

ContextFreeGrammar

• parse(s: str) -> bool: Parse a grammar string
• error_message() -> str: Get error message if parsing failed
• terminals() -> List[str]: Get all terminals
• non_terminals() -> List[str]: Get all non-terminals
• left_factoring(expand: bool = False): Perform left factoring
• left_recursion_elimination() -> bool: Eliminate left recursion
• compute_first_and_follow_set() -> FirstAndFollowSet: Compute FIRST and FOLLOW sets
• compute_ll1_table() -> MTable: Compute LL(1) parsing table
• compute_lr0_automaton() -> FiniteAutomaton: Compute LR(0) automaton
• compute_lr0_action_goto_table(automaton) -> ActionGotoTable: Compute LR(0) ACTION/GOTO table
• compute_slr1_automaton() -> FiniteAutomaton: Compute SLR(1) automaton
• compute_slr1_action_goto_table(automaton) -> ActionGotoTable: Compute SLR(1) ACTION/GOTO table
• compute_lr1_automaton() -> FiniteAutomaton: Compute LR(1) automaton
• compute_lr1_action_goto_table(automaton) -> ActionGotoTable: Compute LR(1) ACTION/GOTO table
• compute_lalr1_automaton() -> FiniteAutomaton: Compute LALR(1) automaton
• compute_lalr1_action_goto_table(automaton) -> ActionGotoTable: Compute LALR(1) ACTION/GOTO table
• to_chomsky_normal_form(): Convert grammar to CNF
• is_chomsky_normal_form() -> bool: Check if grammar is in CNF
• cyk_parse(s: str) -> CYKTable: Parse using CYK algorithm

RegularExpression

• parse(pattern: str) -> bool: Parse a regular expression
• error_message() -> str: Get error message if parsing failed
• to_nfa() -> NFAState: Convert to NFA
• to_dfa(nfa: NFAState) -> DFAState: Convert NFA to DFA (static)
• to_min_dfa(dfa: DFAState) -> DFAState: Minimize DFA (static)
• to_nfa_graph(nfa: NFAState) -> NFAGraph: Convert NFA to graph (static)
• to_dfa_graph(dfa: DFAState) -> DFAGraph: Convert DFA to graph (static)

License

MIT License