python3词法分析（四）保留字以及关键字

词法分析时识别出来的标识符并没有区分是关键字还是普通的变量名，都识别为NAME，那是如何区分的呢？

Parser/parser.c

static const int n_keyword_lists = 9;
static KeywordToken *reserved_keywords[] = {
    (KeywordToken[]) {{NULL, -1}},
    (KeywordToken[]) {{NULL, -1}},
    (KeywordToken[]) {
        {"if", 510},
        {"in", 518},
        {"as", 520},
        {"is", 530},
        {"or", 531},
        {NULL, -1},
    },
    (KeywordToken[]) {
        {"del", 503},
        {"try", 511},
        {"for", 517},
        {"def", 526},
        {"not", 529},
        {"and", 532},
        {NULL, -1},
    },
    (KeywordToken[]) {
        {"pass", 502},
        {"from", 514},
        {"elif", 515},
        {"else", 516},
        {"with", 519},
        {"None", 523},
        {"True", 524},
        {NULL, -1},
    },
    (KeywordToken[]) {
        {"raise", 501},
        {"yield", 504},
        {"break", 506},
        {"while", 512},
        {"False", 525},
        {"class", 527},
        {NULL, -1},
    },
    (KeywordToken[]) {
        {"return", 500},
        {"assert", 505},
        {"global", 508},
        {"import", 513},
        {"except", 521},
        {"lambda", 528},
        {NULL, -1},
    },
    (KeywordToken[]) {
        {"finally", 522},
        {NULL, -1},
    },
    (KeywordToken[]) {
        {"continue", 507},
        {"nonlocal", 509},
        {NULL, -1},
    },
};
static char *soft_keywords[] = {
    "_",
    "case",
    "match",
    NULL,
};

通过脚本Tools/peg_generator/pegen/c_generator.py从Grammar/python.gram 中提取并生成关键词列表

Makefile

.PHONY: regen-pegen
regen-pegen:
	@$(MKDIR_P) $(srcdir)/Parser
	PYTHONPATH=$(srcdir)/Tools/peg_generator $(PYTHON_FOR_REGEN) -m pegen -q c 
		$(srcdir)/Grammar/python.gram 
		$(srcdir)/Grammar/Tokens 
		-o $(srcdir)/Parser/parser.new.c
	$(UPDATe_FILE) $(srcdir)/Parser/parser.c $(srcdir)/Parser/parser.new.c

Tools/peg_generator/pegen/__main.py__

argparser = argparse.ArgumentParser(
    prog="pegen", description="Experimental PEG-like parser generator"
)
argparser.add_argument("-q", "--quiet", action="store_true", help="Don't print the parsed grammar")
argparser.add_argument(
    "-v",
    "--verbose",
    action="count",
    default=0,
    help="Print timing stats; repeat for more debug output",
)
subparsers = argparser.add_subparsers(help="target language for the generated code")

c_parser = subparsers.add_parser("c", help="Generate C code for inclusion into CPython")
c_parser.set_defaults(func=generate_c_code)
c_parser.add_argument("grammar_filename", help="Grammar description")
c_parser.add_argument("tokens_filename", help="Tokens description")
c_parser.add_argument(
    "-o", "--output", metavar="OUT", default="parse.c", help="Where to write the generated parser"
)
c_parser.add_argument(
    "--compile-extension",
    action="store_true",
    help="Compile generated C code into an extension module",
)
c_parser.add_argument(
    "--optimized", action="store_true", help="Compile the extension in optimized mode"
)
c_parser.add_argument(
    "--skip-actions", action="store_true", help="Suppress code emission for rule actions",
)

Tools/peg_generator/pegen/__main.py__ : main()

def main() -> None:
    from pegen.testutil import print_memstats

    args = argparser.parse_args()
    if "func" not in args:
        argparser.error("Must specify the target language mode ('c' or 'python')")

    t0 = time.time()
    grammar, parser, tokenizer, gen = args.func(args)
    ...

Tools/peg_generator/pegen/__main.py__ : generate_c_code()

Tools/peg_generator/pegen/build.py : build_c_parser_and_generator()

Tools/peg_generator/pegen/build.py : build_c_generator()

Tools/peg_generator/pegen/c_generator.py : generate()

Parser/parser.c

void *
_PyPegen_parse(Parser *p)
{
    // Initialize keywords
    p->keywords = reserved_keywords;
    p->n_keyword_lists = n_keyword_lists;
    p->soft_keywords = soft_keywords;
...
}

Parser/pegen.c
根据识别出来的标识符，去关键词列表中查询，为了方便以及快速的查询，根据关键词的长度进行分类。

static int
_get_keyword_or_name_type(Parser *p, const char *name, int name_len)
{
    assert(name_len > 0);
    if (name_len >= p->n_keyword_lists ||
        p->keywords[name_len] == NULL ||
        p->keywords[name_len]->type == -1) {
        return NAME;
    }
    for (KeywordToken *k = p->keywords[name_len]; k != NULL && k->type != -1; k++) {
        if (strncmp(k->str, name, name_len) == 0) {
            return k->type;
        }
    }
    return NAME;
}

typedef struct {
    char *str;
    int type;
} KeywordToken;

reserved_keywords是一个指针数组中下标就表示关键词的长度，长度相同的关键词放在同一个下标中的同一个数组中。