`Makefile`の依存関係の可視化

LANG=C make -pによって出力されたMakefileのデータベースをパースして，依存関係をDOT形式で出力します．
再帰的なmakeの呼び出しにも対応しています．
GNU Makeを仮定しています．

LANG=C make -p | python3 make_p_to_json.py | python3 json_to_dot.py | dot -Tpdf >| workflow.pdf

のように利用します．
たとえば，sjackman/uniqtag-paperに適用すると，以下のようなPDFが得られます．

make_p_to_json.py

Makefileに記述された依存関係を

[{"target1": ["dep1", "dep2", ...], ...}, ...]

という構造のJSON形式で出力します．
一番外側の配列の各要素は，makeを再帰的に呼び出している場合に対応します．

LANG=C make -p | python3 make_p_to_json.py > graph.json

の様に利用します．

#!/usr/bin/python

import sys
import json
import re


def main(args):
    _parse_args(args)
    json.dump(parse_make_p(sys.stdin), sys.stdout)


def parse_make_p(fp, graphs=None):
    if graphs is None:
        graphs = []
    for l in fp:
        if l.startswith('# Make data base, printed on '):
            graphs.append(_parse_db(fp))
    if not graphs:
        raise ValueError("{} seems not connected to `LANG=C make -p`".format(fp))
    return graphs


def _parse_db(fp):
    for l in fp:
        if l.startswith('# Files'):
            fp.readline() # skip the first empty line
            return _parse_entries(fp)
    return {}


def _parse_entries(fp):
    deps_graph = {}
    for l in fp:
        if l.startswith('# files hash-table stats:'):
            return deps_graph
        elif l.startswith('# Not a target:'):
            _skip_until_next_entry(fp)
        elif l.startswith("# makefile (from '"):
            fp.readline() # skip information on target specific variable value
        else:
            _parse_entry(l, deps_graph)
            _skip_until_next_entry(fp)
    return deps_graph



TARGET_SPLIT_REGEX = re.compile(r':{1,2} *')
def _parse_entry(l, deps_graph):
    target, deps = TARGET_SPLIT_REGEX.split(l, 1)
    deps_graph[target] = [dep for dep in deps.split() if dep != '|']


def _skip_until_next_entry(fp):
    for l in fp:
        if _is_new_entry(l):
            return


def _is_new_entry(s):
    return s.startswith('\n')


def _parse_args(args):
    if len(args) != 1:
        print("# parse Makefile's database and print dependency graph in JSON format")
        print("LANG=C gmake -p | {} | json_to_dot.py | dot -Tpdf >| workflow.pdf".format(args[0]))
        sys.exit(1)


if __name__ == '__main__':
    main(sys.argv)

json_to_dot.py

make_p_to_json.pyが出力したJSONをDOT形式に変換します．

python3 json_to_dot.py < graph.json | dot -Tpdf > workflow.pdf

の様に利用します．

#!/usr/bin/python

import sys
import json


class Id(object):

    def __init__(self):
        super().__init__()
        self._i = 0

    @property
    def i(self):
        self._i += 1
        return self._i


def main(args):
    _parse_args(args)
    print("""
digraph G {
   graph [rankdir=LR]
   node [shape=plaintext]
    edge [color="#00000088"]
    """)
    i = Id()
    for graph in json.load(sys.stdin):
        print_single_graph(graph, i)
    print("}")


def print_single_graph(graph, i):
    name_to_node = {}
    print("subgraph cluster{}{{".format(i.i))
    for target, deps in graph.items():
        target_str = _escape(target)
        _register_node(target_str, i, name_to_node)
        target_node = name_to_node[target_str]
        for dep_str in (_escape(dep) for dep in deps):
            _register_node(dep_str, i, name_to_node)
            print('{} -> {}'.format(target_node, name_to_node[dep_str]))
    print("}")


def _register_node(name, i, name_to_node):
    if not (name in name_to_node):
        node = 'n{}'.format(i.i)
        name_to_node[name] = node
        print('{}[label={}]'.format(node, name))


def _escape(s):
    return '"{}"'.format(s.replace('"', r'\"'))


def _parse_args(args):
    if len(args) != 1:
        print('# convert a dependency graph stored in JSON format to DOT format')
        print('{} < deps.json | dot -Tpdf >| workflow.pdf'.format(args[0]))
        sys.exit(1)


if __name__ == '__main__':
    main(sys.argv)

必要なもの

• GNU Make
• Python 3
• Graphviz

License

GPL version 3.