DiskDict is a replacement for Python dict object with one big difference.
When the number of items in the dict is larger than cache_size, the
disk will be used to store newly added data. This makes it possible for
the dict to contain more data than the available RAM. The drawback is that
the dict becomes much slower, but still usable.
The disk data is stored in a temp file, which is removed by the OS when process exists.
DiskDict could/should be used as a default dict object.
d = DiskDict(cache_size=2)
d[1] = 1
d[2] = 4
d[3] = 9
d[4] = 16
d[5] = 25
# d == {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}
d[10] = 100
d[20] = 400
d[30] = 900
d[40] = 1600
d[50] = 2500
# d = {1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 40: 1600, 10: 100, 50: 2500, 20: 400, 30: 900}
d[1] = -1
d[2] = -4
d[3] = -9
d[4] = -16
d[5] = -25
# d = {1: -1, 2: -4, 3: -9, 4: -16, 5: -25, 40: 1600, 10: 100, 50: 2500, 20: 400, 30: 900}
# d.counters = {'mem_hits': 6, 'misses': 0, 'cache_file_size': 63, 'set_ops': 15,
# 'get_ops': 25, 'mem_items': 1, 'disk_items': 8, 'disk_hits': 19,
# 'len': 9, 'del_ops': 1}
Write : n=1000000, s='a'*1024, ops/s=85607
Read SEQ: n=1000000, s='a'*1024, ops/s=131875
Read RND: n=1000000, s='a'*1024, ops/s=106608
Write : n=1000000, s=range(100), ops/s=28614
Read SEQ: n=1000000, s=range(100), ops/s=27398
Read RND: n=1000000, s=range(100), ops/s=26072
Write : n=1000000, s='a'*1024, ops/s=316754
Read SEQ: n=1000000, s='a'*1024, ops/s=704680
Read RND: n=1000000, s='a'*1024, ops/s=409498
2014-11-04:
Added more dict-methods
2014-01-23:
First release.
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