extract.py

import os
from enum import Enum
import pexpect
import json
import re
from tqdm import tqdm 
import json
import git
import pickle
import requests
from collections import defaultdict

from utils import make_lean_repl, send_tactic, send_command_icanon, send_command_zsh, BASE_PATH

class ParseState(Enum):
    defn = 0
    inductive = 1
    block_comment = 2
    prop = 3
    mutual = 4

def loc_tag(fname, line_ind):
    return f'{fname}:{line_ind}'

def parse_file(fname):
    lines = None
    with open(fname, 'r') as f:
        lines = f.readlines()
    imports = []
    defns = []
    props = []
    comments = []

    prev_state = None
    state = None
    data = []

    def change_state(new_state, line_ind, line):
        nonlocal data, state, prev_state
        route_map = {ParseState.defn: defns, ParseState.inductive: defns, 
                     ParseState.prop: props, ParseState.block_comment: comments,
                     ParseState.mutual: defns}
        if state in route_map:
            route_map[state].append(data)
            data = []
        if new_state in route_map:
            data = [(loc_tag(fname, line_ind), line)]
        prev_state = state
        state = new_state

    for line_ind, line in enumerate(lines):
        line_str = line.strip()
        if state == ParseState.block_comment: # end of block comment: reset state
            if line_str.endswith('-/'):
                state = prev_state
                prev_state = None
                continue
        elif line_str.startswith('--'): # inline comment: maintain state
            comments.append((loc_tag(fname, line_ind), line))
            continue
        elif line_str.startswith('/-'): # start block comment
            change_state(ParseState.block_comment, line_ind, line)
            continue
        elif line_str.startswith('mutual'):
            change_state(ParseState.mutual, line_ind, line)
            continue
        elif line_str.startswith('end') and state == ParseState.mutual:
            #manually handle mutual stuff, its pretty annoying
            data.append((loc_tag(fname, line_ind), line))
            change_state(None, line_ind, line)
            continue
        elif state == ParseState.mutual:
            data.append((loc_tag(fname,line_ind), line))
            continue
        elif line.startswith('import'):
            assert state is None
            imports.append(line)
            continue
        elif line_str.startswith('def prop'): # one of the propositions to prove
            change_state(ParseState.prop, line_ind, line)
        elif line_str.startswith('def') or line_str.startswith('lemma') or line_str.startswith('theorem'): # a function definition
            change_state(ParseState.defn, line_ind, line)
        elif line_str.startswith('inductive'):
            change_state(ParseState.inductive, line_ind, line)
        elif len(line_str) == 0:
            change_state(None, line_ind, line)
        else:
            data.append((loc_tag(fname,line_ind), line))
    
    change_state(None, -1, '') # handle EOF


    return imports, defns, props, comments


def process_defns(defns):
    new_defns = []
    for defn in defns:
        inds, lines = zip(*defn)
        prop_text = ''.join(lines)
        ind = min(inds)
        max_ind = max(inds)

        if lines[0].strip().startswith('mutual'):
            # manually process mutual defns
            names = []
            for line in lines:
                if line.strip().startswith('def'):
                    inner_name = [s for s in line.strip().split(' ') if len(s) > 0][1]
                    names.append(inner_name)
                    #names.append(f'_root_.{inner_name}')
        else:

            names = [[s for s in prop_text.split(' ') if len(s) > 0][1].strip()]

        for name in names:
            if name.endswith(':'):
                name = name[:-1]
            new_defns.append(((ind, max_ind), name, prop_text))
    return new_defns

# take in a raw parsed prop (list of lines), output the corresponding lemma for a theorem prover to prove
def process_prop(prop, default_proof=':= by sorry'):
    inds, lines = zip(*prop)
    prop_text = ''.join(lines)
    ind = min(inds)
    max_ind = max(inds)
    name = prop_text.split(' ')[1]
    assert prop_text[:3] == 'def'
    prop2 = 'theorem' + prop_text[3:]
    # TBD what default proof should be; different setups might want different things. i.e. tactic mode just wants
    # a 'by', proof term generation wants nothing, a proof rewriter that expects an initial valid state might want 
    # 'by sorry'.
    prop2 = prop2.strip().replace(':=', ':') + f'{default_proof}' 
    return ((ind, max_ind), name, prop2)

#NOTE: if I eventually choose to handle chained dependencies, I'll want this to return a dictionary representing
# the dependency graph of imports. As of now I have the code for adding in other LeanSrc import definitions, but
# I'm not dealing with the import order in my later sort.
#
# collect all the (location_tag, definition_text) definitions from other files in LeanSrc specified 
# by import_names
def collect_import_defns(import_names):
    import_names = import_names[:] # don't modify original list
    defns = []
    seen = set()
    while len(import_names) > 0:
        imp = import_names.pop()
        if imp in seen:
            continue
        seen.add(imp)
        i, d, p, c = parse_file(f'{BASE_PATH}/{imp}.lean')
        import_names += [imp_str.split('.')[-1].strip() for imp_str in i if 'LeanSrc' in imp_str]
        defns += d
    return defns

#errors I have come across: 
# "function expected at\n  <ident>\nterm has type"
# "unknown identifier '<ident>'"
def match_error(err_str):
    m1 = re.search('expected at\n\s+(.+)\nterm has', err_str)
    if m1 is not None:
        return m1.group(1)
    m2 = re.search("unknown (identifier|constant) '(.+)'", err_str)
    if m2 is not None:
        return m2.group(2)
    if 'invalid dotted identifier notation' in err_str:
        return err_str.strip().split(' ')[-1]
    print(f'ERROR: err string <<{err_str}>> is not a recognized error pattern')
    exit()
    return None

# these are a result of other things not being defined, and don't contain semantic information about what definition to add
# note that I AM NOT IGNORING THESE ERRORS IN THE FINAL PROP WITH DEPS, i.e. I only output the prop w deps once I have
# no errors at all. These are just ignored for the purpose of finding new dependencies
ignore_errs = ['equality or iff proof expected', 'invalid occurrence of universe level',
                'function is not recursive', 'failed to prove termination', 'unsolved goals',
                'invalid field notation', 'result is not type correct',
                'invalid argument, variable is not a proposition', 'tactic failed. Possible reasons']
def collect_relevant_defns(prop, defns, lean_repl, env, import_order):
    """
    Collect the functions and type definitions used in a prop from a list of defns sourced from the 
    current file and potentially from other libraries, although for now I'm not handling mathlib. 
    This will rely on names being unique, so please don't shadow any names in the files you're importing.
    """
    # use _env because we want all definition dependence checks to be based on the original env
    outp, _env = send_command(lean_repl, prop, env=env) # ignore resulting env; we just want to see the error
    errors = [m for m in outp['messages'] if m['severity'] == 'error']
    #print(errors)
    seen = set()
    seen_locs = set()
    all_deps = []

    while True:
        # reset to original environment
        env2 = env
        all_deps = order_deps(all_deps, import_order)
        errors = []
        seen_err = set()
        for defn in all_deps:
            #print()
            #print(defn[1])
            outp, env2 = send_command(lean_repl, defn[1], env=env2)
            tmp = [(m, defn[1]) for m in outp.get('messages', []) if m['severity'] == 'error' and m['data'] not in seen_err]
            errors += tmp
            for m, _ in tmp:
                seen_err.add(m['data'])
        # env2 is the environment after all dependencies have been added.
        #print('new iteration outp:', outp)
        #print('new iteration errs:', errors)
        #errors = [m for m in outp.get('messages', []) if m['severity'] == 'error']

        # if the dependencies are added without error, also add in the prop.
        if len(errors) == 0:
            outp, env2 = send_command(lean_repl, prop, env=env2)
            errors = [(m, prop) for m in outp.get('messages', []) if m['severity'] == 'error']

        if len(errors) == 0: # all dependencies plus prop statement does not error
            break

        while len(errors) > 0:
            err, err_cause = errors.pop()
            if any([uerr in err['data'] for uerr in ignore_errs]):
                continue
            if 'invalid pattern variable, must be atomic' in err['data']:
                found_ind = False
                defn_line = err_cause.split('\n')[0]
                for ident in defn_line.strip().split(' '):
                    if ident in defns and ident not in seen:
                        found_ind = True
                        cp = err.copy()
                        
                        cp['data'] = f"unknown identifier '{ident}'" # spoof a better error message
                        #print('FOUND INDUCTIVE:', cp['data'])
                        errors.append((cp, err_cause))
                if not found_ind:
                    print('ERROR: failed to resolve inductive type pattern var problem')
                    exit()
                continue

            ident_str = match_error(err['data'])
            ident_str = ident_str.replace('_root_.','')
            #print(ident_str, ident_str in defns)
            if ident_str not in defns:
                print(f'ERROR: couldnt find identifier {ident_str}')
                print(err)
                exit()
                continue
            if ident_str in seen:
                continue
                # don't add the same defn twice
                #print(f'ERROR: circular dependency: {ident_str}')
            seen.add(ident_str)

            if defns[ident_str][0] in seen_locs:
                continue
            seen_locs.add(defns[ident_str][0])
            all_deps.append(defns[ident_str])

    return all_deps

def order_deps(defns, import_order):
    if len(defns) == 0:
        return defns
    order_map = {fname: i for i, fname in enumerate(import_order)}
    line_nums = [int(defn[0][0].split(':')[-1]) for defn in defns]
    max_line_num = max(line_nums)
    def import_rank(defn):
        fpath, line_ind = defn[0][0].split(':')
        fname = re.search(BASE_PATH + '/(\S+)\.lean', fpath).group(1)
        return order_map[fname]*max_line_num + int(line_ind)
    return sorted(defns, key=import_rank)

def extract_file_props(fname, full_path, send_command, default_proof=':= by sorry', repl_type='zsh'):
    # imports, definitions (code and types), propositions, and comments.
    # d, p, and c are lists of lists; each sublit contains the original lines of the file that comprise
    # the definition, proposition, or comment.
    i, d, p, c = parse_file(full_path)

    imp_names = [imp_str.split('.')[-1].strip() for imp_str in i if 'LeanSrc' in imp_str]
    imp_d = collect_import_defns(imp_names)

    all_d = imp_d + d 
    import_order = imp_names + [fname] # imports go first
    all_d = process_defns(all_d)
    defns_by_name = {name: (ind, defn) for ind, name, defn in all_d}
    

    props = [process_prop(prop, default_proof=default_proof) for prop in p]
    #TODO
    lemma_props = [(ind, name, defn.split('\n')[0].strip().replace('lemma', 'theorem').replace(':= by', default_proof))
                   for ind, name, defn in all_d if defn.strip().startswith('lemma')]
    props = lemma_props # + props
    #props_by_name = {name: (ind, defn) for ind, name, defn in props}
    lean_repl = make_lean_repl(repl_type=repl_type)

    props_with_deps = {}

    outp, mathlib_env = send_command(lean_repl, 'import Mathlib', env=None, first=True)
    ct = 0
    for prop_loc, prop_name, prop in tqdm(props, desc='analyzing and loading lean code + properties'):
        ct += 1
        env = mathlib_env

        all_deps = collect_relevant_defns(prop, defns_by_name, lean_repl, env, import_order)

        for defn in all_deps:
            print(defn[-1])
            outp, env = send_command(lean_repl, defn[-1], env=env)
        print('final output of deps', outp)

        outp, env = send_command(lean_repl, prop, env=env)
        for message in outp['messages']:
            if message['severity'] == 'error':
                print(f'error at prop {prop_name}')
                print(message)
                print()
                exit()
        props_with_deps[prop_name] = all_deps + [(prop_loc, prop)]

    lean_repl.close()
    #print(lean_repl.exitstatus, lean_repl.signalstatus)
    return props_with_deps, c

def output_prop_with_deps(prop, prop_name, folder='LeanSrc/benchmark'):
    lines = '\n'.join(['import Mathlib'] + [code_lines for _loc, code_lines in prop])
    with open(os.path.join(folder, prop_name + '.lean'), 'w') as f:
        f.write(lines)

def convert_file_props(fname, new_fname):
    i, d, p, c = parse_file(f'{BASE_PATH}/{fname}.lean')
    imp_names = [imp_str.split('.')[-1].strip() for imp_str in i if 'LeanSrc' in imp_str]
    imp_d = collect_import_defns(imp_names)

    all_d = imp_d + d 
    import_order = imp_names + [fname] # imports go first
    all_d = process_defns(all_d)
    defns_by_name = {name: (ind, defn) for ind, name, defn in all_d}

    props = [process_prop(prop) for prop in p]

    with open(new_fname, 'w') as f:
        defn_lines = '\n'.join([defn for _, _, defn in all_d])
        f.write(defn_lines + '\n')

        prop_lines = '\n'.join([prop for _, _, prop in props])
        f.write(prop_lines + '\n')

def format_llema_input(pwd, lean_url, lean_sha):
    dcts = []
    for prop_name in pwd:
        
        lines = '\n'.join(['import Mathlib'] + [code_lines for _loc, code_lines in pwd[prop_name]])
        lines = lines.replace(':= by sorry', '')
        loc, _ = pwd[prop_name][-1] # last line comes from the prop of interest
        fpath = loc.split(':')[0]
        dct = {'full_name': prop_name,
               'statement': lines,
                'url': lean_url,
                'commit': lean_sha,
                'file_path': fpath,
                'split': 'valid'}
        
        dcts.append(json.dumps(dct) + '\n')
    with open('leancb_lemma_inp.jsonl', 'w') as f:
        f.writelines(dcts)

def pwd_to_json(pwd, send_command, loc2comm, repl_type='zsh'):

    lean_repl = make_lean_repl(repl_type=repl_type)

    outp, mathlib_env = send_command(lean_repl, 'import Mathlib', env=None, first=True)
    assert len([m for m in outp.get('messages', []) if m['severity'] == 'error']) == 0, str(outp)
    
    dcts = []
    for prop_name in pwd:
        deps = '\n\n'.join(['import Mathlib'] + [code_lines for _loc, code_lines in pwd[prop_name][:-1]])
        prop_loc, prop_defn = pwd[prop_name][-1] # last line comes from the prop of interest
        fpath = prop_loc[0].split(':')[0]
        cline = int(prop_loc[0].split(':')[1]) - 1
        score = 5
        if cline in loc2comm:
            comm = loc2comm[cline]
            if 'core: ' in comm: # allow for (S/s)core
                score = int(comm.split('core:')[1].strip().split('/')[0].strip())

        env = mathlib_env
        for _loc, code_lines in pwd[prop_name]:
            outp, env = send_command(lean_repl, code_lines, env=env)
        ps = outp['sorries'][0]['goal']

        locs = [loc for loc, _code_lines in pwd[prop_name]]
        fname2line = defaultdict(lambda: 0)
        for loc in locs:
            fpath, line_num = loc[1].split(':')
            fname2line[fpath] = max(fname2line[fpath], int(line_num))

        dct = {'full_name': prop_name,
               'prop_defn': prop_defn,
               'prop_loc': prop_loc[0],
               'score': score,
               'deps': deps,
               'proof_state': ps,
                'file_locs': [(fpath, fname2line[fpath]) for fpath in fname2line]}
        
        dcts.append(json.dumps(dct) + '\n')
    with open('codeprops_bench.jsonl', 'w') as f:
        f.writelines(dcts)


if __name__ == '__main__':
    #main_fname = 'Properties'
    main_fname = 'Sorts'

    #convert_file_props(main_fname, os.path.join(folder,'all_props.lean'))

    main_full_path = f'{BASE_PATH}/{main_fname}.lean'
    """
    pwd = extract_file_props(main_fname, main_full_path) # props with deps
    for prop_name in pwd:
        output_prop_with_deps(pwd[prop_name], prop_name, folder=folder)
    """
    
    use_icanon = True

    if use_icanon:
        send_command = send_command_icanon
        repl_type = 'icanon'
    else:
        send_command = send_command_zsh
        repl_type = 'zsh'


    rerun = True
    if rerun:
        pwd, comments = extract_file_props(main_fname, main_full_path, send_command, repl_type=repl_type) # props with deps
        with open(f'comm_{main_fname}.pkl', 'wb') as f:
            pickle.dump(comments, f)
        with open(f'pwd_{main_fname}.pkl', 'wb') as f:
            pickle.dump(pwd, f)
    else:
        with open(f'pwd_{main_fname}.pkl', 'rb') as f:
            pwd = pickle.load(f)
        with open(f'comm_{main_fname}.pkl', 'rb') as f:
            comments = pickle.load(f)

    loc2comm = {}
    for loc, comm in comments:
        fname, line_str = loc.strip().split(':')
        if fname != main_full_path:
            continue
        loc2comm[int(line_str.strip())] = comm

    # use to test specific props
    #pwd_spec = {}
    #test_pname = 'prop_29'
    #pwd_spec[test_pname] = pwd[test_pname]
    #pwd = pwd_spec

    pwd_to_json(pwd, send_command, loc2comm, repl_type=repl_type)
        
    #data, by_score = parse_benchmark_output('bench_out_pythia.txt', pwd, loc2comm)

    #sorries = outp['sorries']
    #for sorry in sorries:
    #    ps = sorry['proofState']
    #    # also has 'pos', 'endPos'
    #    goal = sorry['goal']
    #    send_tactic