Remove bstr and reimplement bits that are used in decode

[lopopolo]

The only remaining use of bstr in boba was a single call to
ByteSlice::find_not_byteset in boba::decode::inner. After looking at
the bstr source, for an alphabet the size of bubblebabble's encoding,
it computed a [u8; 256] lookup table and checks for membership with
O(1) array access.

Because we know the alphabet ahead of time, we can pre-compute the table
and implement this with Iterator::find.

This results in a modest 3% speedup in decode performance, mostly because
the alphabet lookup table is a pre-computed const.

boba now has no dependencies outside of alloc and std.

Benches

boba::encode/empty      time:   [46.845 ns 47.052 ns 47.277 ns]
                        change: [-0.0306% +1.5149% +3.1697%] (p = 0.04 < 0.05)
                        Change within noise threshold.
Found 2 outliers among 100 measurements (2.00%)
  2 (2.00%) high severe
boba::encode/1234567890 time:   [90.846 ns 91.399 ns 91.988 ns]
                        change: [+0.2467% +2.0851% +4.0831%] (p = 0.02 < 0.05)
                        Change within noise threshold.
Found 6 outliers among 100 measurements (6.00%)
  1 (1.00%) low mild
  3 (3.00%) high mild
  2 (2.00%) high severe
boba::encode/Pineapple  time:   [87.152 ns 87.562 ns 87.976 ns]
                        change: [+0.2536% +2.1208% +4.0694%] (p = 0.02 < 0.05)
                        Change within noise threshold.
Found 7 outliers among 100 measurements (7.00%)
  3 (3.00%) high mild
  4 (4.00%) high severe
boba::encode/emoji      time:   [141.63 ns 142.15 ns 142.74 ns]
                        change: [-1.3811% +0.4342% +2.2508%] (p = 0.65 > 0.05)
                        No change in performance detected.
Found 11 outliers among 100 measurements (11.00%)
  6 (6.00%) high mild
  5 (5.00%) high severe

boba::decode/empty      time:   [2.6051 ns 2.6243 ns 2.6540 ns]
                        change: [-2.0287% -0.3042% +1.3373%] (p = 0.75 > 0.05)
                        No change in performance detected.
Found 14 outliers among 100 measurements (14.00%)
  7 (7.00%) high mild
  7 (7.00%) high severe
boba::decode/1234567890 time:   [104.86 ns 105.34 ns 105.86 ns]
                        change: [-3.7604% -2.5821% -1.2118%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
  1 (1.00%) high mild
  9 (9.00%) high severe
boba::decode/Pineapple  time:   [100.09 ns 100.78 ns 101.54 ns]
                        change: [-4.5410% -2.9169% -1.1301%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
  4 (4.00%) high mild
  8 (8.00%) high severe
boba::decode/emoji      time:   [161.38 ns 161.98 ns 162.68 ns]
                        change: [-4.5053% -3.2074% -1.6301%] (p = 0.00 < 0.05)
                        Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
  5 (5.00%) high mild
  6 (6.00%) high severe