#!/usr/bin/env python3
# SPDX-License-Identifier: LGPL-2.1+

from __future__ import print_function

import gdb

class sd_dump_hashmaps(gdb.Command):
        "dump elogind's hashmaps"

        def __init__(self):
                super(sd_dump_hashmaps, self).__init__("sd_dump_hashmaps", gdb.COMMAND_DATA, gdb.COMPLETE_NONE)

        def invoke(self, arg, from_tty):
                d = gdb.parse_and_eval("hashmap_debug_list")
                all_entry_sizes = gdb.parse_and_eval("all_entry_sizes")
                all_direct_buckets = gdb.parse_and_eval("all_direct_buckets")
                uchar_t = gdb.lookup_type("unsigned char")
                ulong_t = gdb.lookup_type("unsigned long")
                debug_offset = gdb.parse_and_eval("(unsigned long)&((HashmapBase*)0)->debug")

                print("type, hash, indirect, entries, max_entries, buckets, creator")
                while d:
                        h = gdb.parse_and_eval("(HashmapBase*)((char*)%d - %d)" % (int(d.cast(ulong_t)), debug_offset))

                        if h["has_indirect"]:
                                storage_ptr = h["indirect"]["storage"].cast(uchar_t.pointer())
                                n_entries = h["indirect"]["n_entries"]
                                n_buckets = h["indirect"]["n_buckets"]
                        else:
                                storage_ptr = h["direct"]["storage"].cast(uchar_t.pointer())
                                n_entries = h["n_direct_entries"]
                                n_buckets = all_direct_buckets[int(h["type"])];

                        t = ["plain", "ordered", "set"][int(h["type"])]

                        print("{}, {}, {}, {}, {}, {}, {} ({}:{})".format(t, h["hash_ops"], bool(h["has_indirect"]), n_entries, d["max_entries"], n_buckets, d["func"], d["file"], d["line"]))

                        if arg != "" and n_entries > 0:
                                dib_raw_addr = storage_ptr + (all_entry_sizes[h["type"]] * n_buckets)

                                histogram = {}
                                for i in xrange(0, n_buckets):
                                        dib = int(dib_raw_addr[i])
                                        histogram[dib] = histogram.get(dib, 0) + 1

                                for dib in sorted(iter(histogram)):
                                        if dib != 255:
                                                print("{:>3} {:>8} {} of entries".format(dib, histogram[dib], 100.0*histogram[dib]/n_entries))
                                        else:
                                                print("{:>3} {:>8} {} of slots".format(dib, histogram[dib], 100.0*histogram[dib]/n_buckets))
                                print("mean DIB of entries: {}".format(sum([dib*histogram[dib] for dib in iter(histogram) if dib != 255])*1.0/n_entries))

                                blocks = []
                                current_len = 1
                                prev = int(dib_raw_addr[0])
                                for i in xrange(1, n_buckets):
                                        dib = int(dib_raw_addr[i])
                                        if (dib == 255) != (prev == 255):
                                                if prev != 255:
                                                        blocks += [[i, current_len]]
                                                current_len = 1
                                        else:
                                                current_len += 1

                                        prev = dib
                                if prev != 255:
                                        blocks += [[i, current_len]]
                                # a block may be wrapped around
                                if len(blocks) > 1 and blocks[0][0] == blocks[0][1] and blocks[-1][0] == n_buckets - 1:
                                        blocks[0][1] += blocks[-1][1]
                                        blocks = blocks[0:-1]
                                print("max block: {}".format(max(blocks, key=lambda a: a[1])))
                                print("sum block lens: {}".format(sum(b[1] for b in blocks)))
                                print("mean block len: {}".format((1.0 * sum(b[1] for b in blocks) / len(blocks))))

                        d = d["debug_list_next"]

sd_dump_hashmaps()
