In terms of bytecode, in saves a LOAD_ATTR and replaces a CALL_FUNCTION with a COMPARE_OP.
>>> dis.dis(indict)
2 0 LOAD_GLOBAL 0 (name)
3 LOAD_GLOBAL 1 (d)
6 COMPARE_OP 6 (in)
9 POP_TOP
>>> dis.dis(haskey)
2 0 LOAD_GLOBAL 0 (d)
3 LOAD_ATTR 1 (haskey)
6 LOAD_GLOBAL 2 (name)
9 CALL_FUNCTION 1
12 POP_TOP
My feelings are that in is much more readable and is to be preferred in every case that I can think of.
In terms of performance, the timing reflects the opcode
$ python -mtimeit -s'd = dict((i, i) for i in range(10000))' "'foo' in d"
10000000 loops, best of 3: 0.11 usec per loop
$ python -mtimeit -s'd = dict((i, i) for i in range(10000))' "d.has_key('foo')"
1000000 loops, best of 3: 0.205 usec per loop
in is almost twice as fast.