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container-capacity.md

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Prefer Specifying Container Capacity

Specify container capacity where possible in order to allocate memory for the container up front. This minimizes subsequent allocations (by copying and resizing of the container) as elements are added.

Specifying Map Capacity Hints

Where possible, provide capacity hints when initializing maps with make().

make(map[T1]T2, hint)

Providing a capacity hint to make() tries to right-size the map at initialization time, which reduces the need for growing the map and allocations as elements are added to the map.

Note that, unlike slices, map capacity hints do not guarantee complete, preemptive allocation, but are used to approximate the number of hashmap buckets required. Consequently, allocations may still occur when adding elements to the map, even up to the specified capacity.

BadGood
m := make(map[string]os.FileInfo)

files, _ := os.ReadDir("./files")
for _, f := range files {
    m[f.Name()] = f
}
files, _ := os.ReadDir("./files")

m := make(map[string]os.DirEntry, len(files))
for _, f := range files {
    m[f.Name()] = f
}

m is created without a size hint; there may be more allocations at assignment time.

m is created with a size hint; there may be fewer allocations at assignment time.

Specifying Slice Capacity

Where possible, provide capacity hints when initializing slices with make(), particularly when appending.

make([]T, length, capacity)

Unlike maps, slice capacity is not a hint: the compiler will allocate enough memory for the capacity of the slice as provided to make(), which means that subsequent append() operations will incur zero allocations (until the length of the slice matches the capacity, after which any appends will require a resize to hold additional elements).

BadGood
for n := 0; n < b.N; n++ {
  data := make([]int, 0)
  for k := 0; k < size; k++{
    data = append(data, k)
  }
}
for n := 0; n < b.N; n++ {
  data := make([]int, 0, size)
  for k := 0; k < size; k++{
    data = append(data, k)
  }
}
BenchmarkBad-4    100000000    2.48s
BenchmarkGood-4   100000000    0.21s