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# Benchmarks of Starlark execution
# option:set
def bench_range_construction(b):
for _ in range(b.n):
range(200)
def bench_range_iteration(b):
for _ in range(b.n):
for x in range(200):
pass
# Make a 2-level call tree of 100 * 100 calls.
def bench_calling(b):
list = range(100)
def g():
for x in list:
pass
def f():
for x in list:
g()
for _ in range(b.n):
f()
# Measure overhead of calling a trivial built-in method.
emptydict = {}
range1000 = range(1000)
def bench_builtin_method(b):
for _ in range(b.n):
for _ in range1000:
emptydict.get(None)
def bench_int(b):
for _ in range(b.n):
a = 0
for _ in range1000:
a += 1
def bench_bigint(b):
for _ in range(b.n):
a = 1 << 31 # maxint32 + 1
for _ in range1000:
a += 1
def bench_gauss(b):
# Sum of arithmetic series. All results fit in int32.
for _ in range(b.n):
acc = 0
for x in range(92000):
acc += x
def bench_mix(b):
"Benchmark of a simple mix of computation (for, if, arithmetic, comprehension)."
for _ in range(b.n):
x = 0
for i in range(50):
if i:
x += 1
a = [x for x in range(i)]
largedict = {str(v): v for v in range(1000)}
def bench_dict_equal(b):
"Benchmark of dict equality operation."
for _ in range(b.n):
if largedict != largedict:
fail("invalid comparison")
largeset = set([v for v in range(1000)])
def bench_set_equal(b):
"Benchmark of set union operation."
for _ in range(b.n):
if largeset != largeset:
fail("invalid comparison")
flat = { "int": 1, "float": 0.2, "string": "string", "list": [], "bool": True, "nil": None, "tuple": (1, 2, 3) }
deep = {
"type": "int",
"value": 1,
"next": {
"type": "float",
"value": 0.2,
"next": {
"type": "string",
"value": "string",
"next": {
"type": "list",
"value": [ 1, "", True, None, (1, 2) ],
"next": {
"type": "bool",
"value": True,
"next": {
"type": "tuple",
"value": (1, 2.0, "3"),
"next": None
}
}
}
}
}
}
deep_list = [ deep for _ in range(100) ]
def bench_to_json_flat_mixed(b):
"Benchmark json.encode builtin with flat mixed input"
for _ in range(b.n):
json.encode(flat)
def bench_to_json_flat_big(b):
"Benchmark json.encode builtin with big flat integer input"
for _ in range(b.n):
json.encode(largedict)
def bench_to_json_deep(b):
"Benchmark json.encode builtin with deep input"
for _ in range(b.n):
json.encode(deep)
def bench_to_json_deep_list(b):
"Benchmark json.encode builtin with a list of deep input"
for _ in range(b.n):
json.encode(deep)
def bench_issubset_unique_large_small(b):
"Benchmark set.issubset builtin"
s = set(range(10000))
for _ in range(b.n):
s.issubset(range(1000))
def bench_issubset_unique_small_large(b):
"Benchmark set.issubset builtin"
s = set(range(1000))
for _ in range(b.n):
s.issubset(range(10000))
def bench_issubset_unique_same(b):
"Benchmark set.issubset builtin"
s = set(range(1000))
for _ in range(b.n):
s.issubset(range(1000))
def bench_issubset_duplicate_large_small(b):
"Benchmark set.issubset builtin"
s = set(range(10000))
l = list(range(200)) * 5
for _ in range(b.n):
s.issubset(range(1000))
def bench_issubset_duplicate_small_large(b):
"Benchmark set.issubset builtin"
s = set(range(1000))
l = list(range(2000)) * 5
for _ in range(b.n):
s.issubset(l)
def bench_issubset_duplicate_same(b):
"Benchmark set.issubset builtin"
s = set(range(1000))
l = list(range(200)) * 5
for _ in range(b.n):
s.issubset(l)
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