py-prop-logic-kernel 0.0.6

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PROP-LOGIC-KERNEL

This project is a small proposition-logic tactic kernel in Lean, exposed through a line-based REPL.

LEAN MODULE

• PropLogicKernel/Basic.lean: proposition syntax, tactics, goals, and state
• PropLogicKernel/Parser.lean: parser for propositions and tactic commands (written by cursor)
• PropLogicKernel/Resolver.lean: operational semantics for tactics
• PropLogicKernel/Printer.lean: rendering of propositions, tactics, and goals
• PropLogicKernel/REPL.lean: REPL-level state, status lines, and exit-code policy
• REPL/REPL.lean: generic line-based REPL loop
• Main.lean: executable entrypoint

PROPOSITION SPECIFICATION

A proposition P is one of:

• ⊥
• atom
• A ∧ B
• A ∨ B
• A → B

Associativity follows the parser/printer implementation:

• ∧, ∨, and → are parsed right-associatively
• parentheses may be used explicitly

PARSER SPECIFICATION

PropLogicKernel/Parser.lean uppercases proposition input before parsing.

After uppercasing, proposition input is rejected unless every character is one of:

• whitespace
• (, )
• ∧, ∨, →, ⊥
• uppercase letters A-Z
• digits 0-9
• underscore _

Atom names are maximal nonempty strings over:

• uppercase letters A-Z
• digits 0-9
• underscore _

Examples of valid atom names:

• A
• P1
• HELLO_WORLD
• X_2

GOAL/STATE MODEL

A goal consists of:

• a set of hypotheses
• a target proposition

The state tracks:

• a list of goals
• varCount
• newCount
• sorrCount

TACTIC

These are the kernel rules implemented by PropLogicKernel/Resolver.lean.

• intro
  • If goal is A → B, add a fresh hypothesis A and replace the goal with B.
• apply n
  • If hypothesis n is A → B and current goal is B, replace the goal with A.
• exact n
  • If hypothesis n exactly matches the current goal, solve the goal.
• constructor
  • If goal is A ∧ B, split it into two goals.
• left
  • If goal is A ∨ B, replace the goal with A.
• right
  • If goal is A ∨ B, replace the goal with B.
• cases n
  • If hypothesis n is A ∨ B, branch into two goals.
  • If hypothesis n is A ∧ B, add both parts as fresh hypotheses.
  • If hypothesis n is ⊥, solve the goal immediately.

CLASSICAL LOGIC

• lem P
  • Classical only.
  • Adds hypothesis (P → ⊥) ∨ P.
• refine n
  • Classical only.
  • If hypothesis n is A1 → B1 and goal is B, replace the current goal with goals B1 → B and A1.

APPLICATION LEVEL COMMANDS

• sorry
  • Solves the current goal unconditionally and increments sorrCount.
• new P
  • Pushes a fresh goal P and increments newCount.

FAILURE BEHAVIOR

• Parse failures return parse error.
• Resolution failures return an error message and keep the previous state.
• lem and refine fail if classical logic is disabled.
• Any tactic other than new fails on an empty goal stack.

REPL protocol

The executable built by lake build runs REPL.run from REPL/REPL.lean.

For each step:

• write zero or more status/error lines to stderr
• write zero or more output lines to stdout
• write the prompt > to stderr with no trailing newline
• read exactly one newline-terminated line from stdin
• transition to the next state

Status lines are prefixed by -- .

Typical status line:

• -- new_count 1 sorry_count 0 goals_remaining 2

Success marker:

• -- all goals accomplished!

That success marker is emitted iff:

• at least one goal was successfully introduced via new
• no sorry was used
• all goals are solved

EXIT CODE POLICY

At EOF, REPL.run returns the previous step's code.

PropLogicKernel/REPL.lean sets exit code 0 iff (same with all goals accomplished!):

• at least one goal was successfully introduced via new
• no sorry was used
• all goals are solved

Otherwise exit code is 1.

Parse/resolution errors do not automatically force exit code 1; they preserve the previous state. So if the kernel is already in a success state, a later failing command can still leave final exit code 0.

DISCLAIMER: AI GENERATED CODE

The following files were written by Cursor:

• README.md
• All Python code in this repo (for example: py_prop_logic_kernel/)
• PropLogicKernel/Parser.lean