Assets: Remove zombies, introduce approvals

[gavofyork]

Removed the concept of zombies; assets may be self-sufficient (in which case their min-balance actually provides enough value lockup to allow for the storage) or otherwise all non-zero account balances must have a consumer reference (so the account must have some primary balance ED or other provider reference).

Also added the concept of approvals; these work in a similar way to ERC-20 style approvals and allow for an asset owner to distribute assets without needing to pre-fund each account with an existential deposit. A deposit (in the primary token) must be made for each asset distributed, but that may be retracted at any time and the deposit freed.

Also adds transfer_keep_alive, which has a similiar purpose to its namesake in Balances pallet.

TODO:

• Tests
• Benchmarks/weights
• Document new dispatches
• Document changes

Includes #8221

[gavofyork]

@shawntabrizi should be good to go.

[parity-benchapp]

Finished benchmark for branch: gav-assets-approve-api

Benchmark: Benchmark Runtime Pallet

cargo run --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_assets --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/assets/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Pallet: "pallet_assets", Extrinsic: "create", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 48.51
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 48.51
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_create", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 24.46
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 24.46
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "destroy", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ c 24.91
+ s 31.05
+ a 0.968
µs

Reads = 4 + (2 * c) + (2 * s) + (0 * a)
Writes = 2 + (2 * c) + (2 * s) + (1 * a)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
c s a mean µs sigma µs %
0 5000 500 143300 327.4 0.2%
100 5000 500 143200 197 0.1%
200 5000 500 147600 148.6 0.1%
300 5000 500 147800 241.2 0.1%
400 5000 500 152400 477.5 0.3%
500 5000 500 151000 127 0.0%
600 5000 500 157700 348 0.2%
700 5000 500 158900 293 0.1%
800 5000 500 160800 331.6 0.2%
900 5000 500 164200 269.8 0.1%
1000 5000 500 166000 438.9 0.2%
1100 5000 500 169300 246 0.1%
1200 5000 500 169100 152.5 0.0%
1300 5000 500 174100 355.8 0.2%
1400 5000 500 174000 677.6 0.3%
1500 5000 500 177700 465 0.2%
1600 5000 500 181600 406.4 0.2%
1700 5000 500 180500 270.3 0.1%
1800 5000 500 184500 515.7 0.2%
1900 5000 500 188000 263.2 0.1%
2000 5000 500 189400 384 0.2%
2100 5000 500 192900 522.1 0.2%
2200 5000 500 195800 373 0.1%
2300 5000 500 201400 433.2 0.2%
2400 5000 500 203900 346 0.1%
2500 5000 500 202900 338.6 0.1%
2600 5000 500 208100 259 0.1%
2700 5000 500 210700 379.9 0.1%
2800 5000 500 209200 266.4 0.1%
2900 5000 500 214400 436.6 0.2%
3000 5000 500 216600 653.7 0.3%
3100 5000 500 217400 347.1 0.1%
3200 5000 500 223000 447.2 0.2%
3300 5000 500 226000 720 0.3%
3400 5000 500 225100 712.1 0.3%
3500 5000 500 229900 605.7 0.2%
3600 5000 500 232700 702.9 0.3%
3700 5000 500 235300 204.5 0.0%
3800 5000 500 238000 382.9 0.1%
3900 5000 500 238600 459.8 0.1%
4000 5000 500 243000 406.1 0.1%
4100 5000 500 244200 534.7 0.2%
4200 5000 500 244900 446.5 0.1%
4300 5000 500 248900 593.1 0.2%
4400 5000 500 247500 820.6 0.3%
4500 5000 500 250700 827.1 0.3%
4600 5000 500 257300 499.1 0.1%
4700 5000 500 258100 444.2 0.1%
4800 5000 500 259500 354.6 0.1%
4900 5000 500 261600 539.7 0.2%
5000 0 500 110800 228.6 0.2%
5000 100 500 113600 284.2 0.2%
5000 200 500 118800 474.3 0.3%
5000 300 500 120000 294.8 0.2%
5000 400 500 124000 507.3 0.4%
5000 500 500 127300 204.9 0.1%
5000 600 500 129300 288.8 0.2%
5000 700 500 132200 285.7 0.2%
5000 800 500 133600 505.8 0.3%
5000 900 500 138300 210.8 0.1%
5000 1000 500 142400 182.3 0.1%
5000 1100 500 144500 416.6 0.2%
5000 1200 500 148000 205.5 0.1%
5000 1300 500 149100 293.5 0.1%
5000 1400 500 153800 390.3 0.2%
5000 1500 500 157700 324.7 0.2%
5000 1600 500 157100 325.3 0.2%
5000 1700 500 163600 294 0.1%
5000 1800 500 163400 175 0.1%
5000 1900 500 169600 358.7 0.2%
5000 2000 500 172200 595.6 0.3%
5000 2100 500 171500 338.9 0.1%
5000 2200 500 177100 302 0.1%
5000 2300 500 181200 370.3 0.2%
5000 2400 500 186500 273.5 0.1%
5000 2500 500 189000 272.9 0.1%
5000 2600 500 190400 773.1 0.4%
5000 2700 500 195000 684.4 0.3%
5000 2800 500 198200 496.4 0.2%
5000 2900 500 199800 288.3 0.1%
5000 3000 500 205000 295.3 0.1%
5000 3100 500 208000 326.2 0.1%
5000 3200 500 211000 273.2 0.1%
5000 3300 500 214800 359.5 0.1%
5000 3400 500 218100 213.5 0.0%
5000 3500 500 221000 540.7 0.2%
5000 3600 500 222200 425.1 0.1%
5000 3700 500 227500 398.7 0.1%
5000 3800 500 230500 540.2 0.2%
5000 3900 500 232400 692.3 0.2%
5000 4000 500 232100 442.4 0.1%
5000 4100 500 237700 308.9 0.1%
5000 4200 500 242400 519.6 0.2%
5000 4300 500 244000 403.1 0.1%
5000 4400 500 248300 331.5 0.1%
5000 4500 500 251200 440.7 0.1%
5000 4600 500 253100 419.8 0.1%
5000 4700 500 252100 294.7 0.1%
5000 4800 500 259000 370 0.1%
5000 4900 500 255500 415.5 0.1%
5000 5000 0 264300 404.8 0.1%
5000 5000 10 265400 343 0.1%
5000 5000 20 263900 844.5 0.3%
5000 5000 30 261100 457.2 0.1%
5000 5000 40 264200 457.1 0.1%
5000 5000 50 264200 674.6 0.2%
5000 5000 60 264300 753.8 0.2%
5000 5000 70 263000 524.7 0.1%
5000 5000 80 263700 432.9 0.1%
5000 5000 90 264100 544.1 0.2%
5000 5000 100 265900 376.9 0.1%
5000 5000 110 264800 666.7 0.2%
5000 5000 120 260600 498.7 0.1%
5000 5000 130 266300 579.3 0.2%
5000 5000 140 263500 287 0.1%
5000 5000 150 265100 618.6 0.2%
5000 5000 160 261600 262 0.1%
5000 5000 170 265200 569.6 0.2%
5000 5000 180 266200 704.4 0.2%
5000 5000 190 267000 573.7 0.2%
5000 5000 200 263100 498.8 0.1%
5000 5000 210 264800 425.8 0.1%
5000 5000 220 266500 630.6 0.2%
5000 5000 230 264100 548.1 0.2%
5000 5000 240 265200 417.7 0.1%
5000 5000 250 262900 345.5 0.1%
5000 5000 260 259900 909.6 0.3%
5000 5000 270 266200 286.2 0.1%
5000 5000 280 261700 482.5 0.1%
5000 5000 290 262100 465.7 0.1%
5000 5000 300 263000 692.8 0.2%
5000 5000 310 265200 534.9 0.2%
5000 5000 320 261400 807.5 0.3%
5000 5000 330 261100 438.7 0.1%
5000 5000 340 258900 303.4 0.1%
5000 5000 350 261700 584.4 0.2%
5000 5000 360 266000 572.5 0.2%
5000 5000 370 264900 360.7 0.1%
5000 5000 380 259200 773.2 0.2%
5000 5000 390 265600 523.9 0.1%
5000 5000 400 264900 421.1 0.1%
5000 5000 410 261500 721.6 0.2%
5000 5000 420 264700 539.5 0.2%
5000 5000 430 261700 806.4 0.3%
5000 5000 440 267500 568.3 0.2%
5000 5000 450 264300 785 0.2%
5000 5000 460 265500 578.5 0.2%
5000 5000 470 261800 738.2 0.2%
5000 5000 480 265300 355.7 0.1%
5000 5000 490 265000 436.9 0.1%
5000 5000 500 265800 491.7 0.1%

Quality and confidence:
param error
c 0.041
s 0.041
a 0.416

Model:
Time ~= 0
+ c 24.65
+ s 30.83
+ a 3.333
µs

Reads = 4 + (2 * c) + (2 * s) + (0 * a)
Writes = 2 + (2 * c) + (2 * s) + (1 * a)
Pallet: "pallet_assets", Extrinsic: "mint", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 46.91
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 46.91
µs

Reads = 2
Writes = 2
Pallet: "pallet_assets", Extrinsic: "burn", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 47.04
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 47.04
µs

Reads = 2
Writes = 2
Pallet: "pallet_assets", Extrinsic: "transfer", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 71.53
µs

Reads = 4
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 71.53
µs

Reads = 4
Writes = 4
Pallet: "pallet_assets", Extrinsic: "force_transfer", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 71.71
µs

Reads = 4
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 71.71
µs

Reads = 4
Writes = 4
Pallet: "pallet_assets", Extrinsic: "freeze", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 34.81
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 34.81
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "thaw", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 34.89
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 34.89
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "freeze_asset", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 24.65
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 24.65
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "thaw_asset", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 24.86
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 24.86
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "transfer_ownership", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 28.42
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 28.42
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "set_team", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 25.37
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 25.37
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "set_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 53.86
+ n 0.002
+ s 0.005
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n s mean µs sigma µs %
0 50 53.88 0.134 0.2%
1 50 54.19 0.158 0.2%
2 50 54 0.146 0.2%
3 50 54.41 0.085 0.1%
4 50 54.06 0.123 0.2%
5 50 54.29 0.116 0.2%
6 50 54.09 0.083 0.1%
7 50 53.92 0.119 0.2%
8 50 54.66 0.11 0.2%
9 50 54.71 0.34 0.6%
10 50 54.22 0.144 0.2%
11 50 53.98 0.089 0.1%
12 50 54.02 0.151 0.2%
13 50 54.36 0.147 0.2%
14 50 53.84 0.153 0.2%
15 50 54.22 0.089 0.1%
16 50 54.01 0.135 0.2%
17 50 54.08 0.105 0.1%
18 50 54.29 0.131 0.2%
19 50 54.15 0.132 0.2%
20 50 53.98 0.072 0.1%
21 50 54.42 0.131 0.2%
22 50 54.13 0.096 0.1%
23 50 54.01 0.046 0.0%
24 50 54.22 0.086 0.1%
25 50 54.16 0.058 0.1%
26 50 53.94 0.079 0.1%
27 50 54.42 0.166 0.3%
28 50 54.27 0.111 0.2%
29 50 54.23 0.074 0.1%
30 50 54.43 0.134 0.2%
31 50 54.14 0.072 0.1%
32 50 54.3 0.123 0.2%
33 50 54.24 0.076 0.1%
34 50 54.07 0.059 0.1%
35 50 54.43 0.141 0.2%
36 50 54.19 0.129 0.2%
37 50 54.44 0.139 0.2%
38 50 54.45 0.085 0.1%
39 50 54.5 0.064 0.1%
40 50 54.25 0.076 0.1%
41 50 54.43 0.087 0.1%
42 50 54.44 0.159 0.2%
43 50 54.24 0.134 0.2%
44 50 54.39 0.175 0.3%
45 50 54.32 0.13 0.2%
46 50 54.12 0.083 0.1%
47 50 54.3 0.11 0.2%
48 50 54.01 0.098 0.1%
49 50 54.12 0.18 0.3%
50 0 53.43 0.171 0.3%
50 1 53.68 0.087 0.1%
50 2 53.78 0.065 0.1%
50 3 53.97 0.113 0.2%
50 4 53.81 0.106 0.1%
50 5 54.24 0.182 0.3%
50 6 53.86 0.077 0.1%
50 7 53.88 0.097 0.1%
50 8 53.75 0.092 0.1%
50 9 53.68 0.091 0.1%
50 10 53.98 0.1 0.1%
50 11 53.75 0.119 0.2%
50 12 54.2 0.21 0.3%
50 13 53.78 0.092 0.1%
50 14 53.98 0.125 0.2%
50 15 53.82 0.107 0.1%
50 16 54.19 0.16 0.2%
50 17 53.79 0.127 0.2%
50 18 53.97 0.089 0.1%
50 19 53.66 0.099 0.1%
50 20 54.09 0.105 0.1%
50 21 53.8 0.073 0.1%
50 22 54.01 0.104 0.1%
50 23 54.11 0.134 0.2%
50 24 53.99 0.086 0.1%
50 25 54.1 0.114 0.2%
50 26 54.11 0.135 0.2%
50 27 53.93 0.066 0.1%
50 28 54.28 0.111 0.2%
50 29 53.96 0.15 0.2%
50 30 53.84 0.122 0.2%
50 31 53.81 0.063 0.1%
50 32 53.94 0.134 0.2%
50 33 54.04 0.065 0.1%
50 34 53.92 0.141 0.2%
50 35 54.11 0.112 0.2%
50 36 54.01 0.173 0.3%
50 37 54.03 0.096 0.1%
50 38 53.87 0.087 0.1%
50 39 53.93 0.136 0.2%
50 40 53.92 0.123 0.2%
50 41 53.84 0.119 0.2%
50 42 54.22 0.059 0.1%
50 43 53.94 0.096 0.1%
50 44 54.29 0.182 0.3%
50 45 53.9 0.08 0.1%
50 46 54.19 0.154 0.2%
50 47 54.01 0.141 0.2%
50 48 54.14 0.097 0.1%
50 49 54.07 0.068 0.1%
50 50 54.05 0.087 0.1%

Quality and confidence:
param error
n 0
s 0

Model:
Time ~= 53.78
+ n 0
+ s 0.008
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Pallet: "pallet_assets", Extrinsic: "clear_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 52.2
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 52.2
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_set_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 27.23
+ n 0.003
+ s 0.005
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n s mean µs sigma µs %
0 50 27.03 0.112 0.4%
1 50 27.26 0.052 0.1%
2 50 27.39 0.076 0.2%
3 50 27.28 0.108 0.3%
4 50 27.43 0.061 0.2%
5 50 27.53 0.144 0.5%
6 50 27.41 0.068 0.2%
7 50 27.52 0.072 0.2%
8 50 27.77 0.097 0.3%
9 50 27.77 0.069 0.2%
10 50 27.48 0.069 0.2%
11 50 27.53 0.049 0.1%
12 50 27.68 0.066 0.2%
13 50 27.64 0.068 0.2%
14 50 27.55 0.042 0.1%
15 50 27.5 0.087 0.3%
16 50 27.63 0.068 0.2%
17 50 27.57 0.035 0.1%
18 50 27.56 0.077 0.2%
19 50 27.49 0.075 0.2%
20 50 27.49 0.057 0.2%
21 50 27.67 0.066 0.2%
22 50 27.6 0.092 0.3%
23 50 27.6 0.071 0.2%
24 50 27.59 0.06 0.2%
25 50 27.67 0.09 0.3%
26 50 27.63 0.063 0.2%
27 50 27.58 0.052 0.1%
28 50 27.64 0.078 0.2%
29 50 27.62 0.061 0.2%
30 50 27.63 0.103 0.3%
31 50 27.54 0.09 0.3%
32 50 27.56 0.071 0.2%
33 50 27.65 0.076 0.2%
34 50 27.61 0.069 0.2%
35 50 27.69 0.08 0.2%
36 50 27.78 0.052 0.1%
37 50 27.79 0.089 0.3%
38 50 27.62 0.104 0.3%
39 50 27.7 0.086 0.3%
40 50 27.81 0.117 0.4%
41 50 27.67 0.115 0.4%
42 50 27.8 0.098 0.3%
43 50 27.84 0.071 0.2%
44 50 27.76 0.081 0.2%
45 50 27.74 0.063 0.2%
46 50 27.35 0.077 0.2%
47 50 27.45 0.075 0.2%
48 50 27.37 0.061 0.2%
49 50 27.41 0.069 0.2%
50 0 26.87 0.049 0.1%
50 1 27.23 0.069 0.2%
50 2 27.23 0.098 0.3%
50 3 27.32 0.06 0.2%
50 4 27.25 0.116 0.4%
50 5 27.34 0.104 0.3%
50 6 27.32 0.157 0.5%
50 7 27.26 0.055 0.2%
50 8 27.35 0.064 0.2%
50 9 27.32 0.092 0.3%
50 10 27.46 0.096 0.3%
50 11 27.4 0.068 0.2%
50 12 27.32 0.091 0.3%
50 13 27.38 0.023 0.0%
50 14 27.2 0.059 0.2%
50 15 27.38 0.077 0.2%
50 16 27.36 0.057 0.2%
50 17 27.55 0.117 0.4%
50 18 27.33 0.055 0.2%
50 19 27.54 0.087 0.3%
50 20 27.44 0.099 0.3%
50 21 27.39 0.087 0.3%
50 22 27.4 0.135 0.4%
50 23 27.41 0.123 0.4%
50 24 27.29 0.08 0.2%
50 25 27.45 0.055 0.2%
50 26 27.3 0.078 0.2%
50 27 27.44 0.11 0.4%
50 28 27.4 0.062 0.2%
50 29 27.31 0.03 0.1%
50 30 27.47 0.092 0.3%
50 31 27.34 0.049 0.1%
50 32 27.45 0.069 0.2%
50 33 27.43 0.049 0.1%
50 34 27.28 0.098 0.3%
50 35 27.53 0.137 0.4%
50 36 27.38 0.05 0.1%
50 37 27.56 0.046 0.1%
50 38 27.51 0.043 0.1%
50 39 27.45 0.056 0.2%
50 40 27.38 0.053 0.1%
50 41 27.45 0.071 0.2%
50 42 27.37 0.04 0.1%
50 43 27.44 0.106 0.3%
50 44 27.48 0.092 0.3%
50 45 27.52 0.044 0.1%
50 46 27.43 0.075 0.2%
50 47 27.44 0.06 0.2%
50 48 27.61 0.095 0.3%
50 49 27.63 0.075 0.2%
50 50 27.52 0.061 0.2%

Quality and confidence:
param error
n 0
s 0

Model:
Time ~= 27.12
+ n 0.002
+ s 0.008
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Pallet: "pallet_assets", Extrinsic: "force_clear_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 52.37
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 52.37
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_asset_status", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 23.83
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 23.83
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "approve_transfer", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 48.43
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 48.43
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "transfer_approved", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 91.81
µs

Reads = 5
Writes = 5
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 91.81
µs

Reads = 5
Writes = 5
Pallet: "pallet_assets", Extrinsic: "cancel_approval", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 49.21
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 49.21
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_cancel_approval", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 56.05
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 56.05
µs

Reads = 2
Writes = 1

[gavofyork]

This still doesn't look good. Increase of 75% in time to execute...

[gavofyork]

As far as I can tell, it's down to the fact that the new code always bumps reference in the system account, whereas the old code didn't need to if it was a zombie (which is the case with the old benchmarking). odd that reading a storage item and bumping a reference would cost so much.

[gavofyork]

Introduced transfer_keep_alive which should have a lower weight since it will never result in the source account getting killed.

[gavofyork]

suspicious.

[gavofyork]

suspicious

[gavofyork]

/benchmark runtime pallet pallet_assets

[parity-benchapp]

Finished benchmark for branch: gav-assets-approve-api

Benchmark: Benchmark Runtime Pallet

cargo run --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_assets --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/assets/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Compiling node-runtime v2.0.1 (/home/shawntabrizi/bench-bot/git/substrate/bin/node/runtime)
Compiling pallet-assets v3.0.0 (/home/shawntabrizi/bench-bot/git/substrate/frame/assets)
Compiling node-cli v2.0.0 (/home/shawntabrizi/bench-bot/git/substrate/bin/node/cli)
error[E0599]: no function or associated item named force_destroy found for associated type <T as pallet::Config>::WeightInfo in the current scope
--> frame/assets/src/lib.rs:553:35
|
553 | #[pallet::weight(T::WeightInfo::force_destroy(
| ^^^^^^^^^^^^^ function or associated item not found in <T as pallet::Config>::WeightInfo

error[E0308]: mismatched types
--> frame/assets/src/lib.rs:430:12
|
430 | #[pallet::call]
| ^^^^ expected trait ClassifyDispatch, found trait WeighData
|
= note: expected reference &dyn ClassifyDispatch<(&<T as pallet::Config>::AssetId, &DestroyWitness)>
found reference &dyn WeighData<(&<T as pallet::Config>::AssetId, &DestroyWitness)>

error[E0308]: mismatched types
--> frame/assets/src/lib.rs:430:12
|
430 | #[pallet::call]
| ^^^^ expected trait PaysFee, found trait WeighData
|
= note: expected reference &dyn PaysFee<(&<T as pallet::Config>::AssetId, &DestroyWitness)>
found reference &dyn WeighData<(&<T as pallet::Config>::AssetId, &DestroyWitness)>

error: aborting due to 3 previous errors

Some errors have detailed explanations: E0308, E0599.
For more information about an error, try rustc --explain E0308.
error: could not compile pallet-assets

To learn more, run the command again with --verbose.
warning: build failed, waiting for other jobs to finish...
error: build failed

[gavofyork]

/benchmark runtime pallet pallet_assets

[parity-benchapp]

Finished benchmark for branch: gav-assets-approve-api

Benchmark: Benchmark Runtime Pallet

cargo run --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_assets --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/assets/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results

Pallet: "pallet_assets", Extrinsic: "create", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 48.3
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 48.3
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_create", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 23.82
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 23.82
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "destroy", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 0
+ c 24.48
+ s 30.63
+ a 0
µs

Reads = 4 + (2 * c) + (2 * s) + (0 * a)
Writes = 2 + (2 * c) + (2 * s) + (1 * a)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
c s a mean µs sigma µs %
0 5000 500 141000 275.2 0.1%
100 5000 500 144900 425.8 0.2%
200 5000 500 146900 261.2 0.1%
300 5000 500 148800 521.8 0.3%
400 5000 500 151200 398.2 0.2%
500 5000 500 150900 177 0.1%
600 5000 500 153800 358.3 0.2%
700 5000 500 158800 247.7 0.1%
800 5000 500 159700 302 0.1%
900 5000 500 161400 280.2 0.1%
1000 5000 500 165100 255.5 0.1%
1100 5000 500 166100 282.4 0.1%
1200 5000 500 170800 370 0.2%
1300 5000 500 171800 509.2 0.2%
1400 5000 500 173500 333.4 0.1%
1500 5000 500 178000 332.9 0.1%
1600 5000 500 180600 351.3 0.1%
1700 5000 500 179800 271 0.1%
1800 5000 500 184900 400.1 0.2%
1900 5000 500 187000 322.3 0.1%
2000 5000 500 187700 622.1 0.3%
2100 5000 500 191600 299 0.1%
2200 5000 500 195400 405.9 0.2%
2300 5000 500 196800 243.5 0.1%
2400 5000 500 200800 620.6 0.3%
2500 5000 500 202400 753.3 0.3%
2600 5000 500 206600 468.6 0.2%
2700 5000 500 209300 299.9 0.1%
2800 5000 500 210000 91.37 0.0%
2900 5000 500 211500 468.4 0.2%
3000 5000 500 214800 369.8 0.1%
3100 5000 500 218200 693.4 0.3%
3200 5000 500 221100 514.7 0.2%
3300 5000 500 221200 564.1 0.2%
3400 5000 500 225700 820.2 0.3%
3500 5000 500 228200 393.3 0.1%
3600 5000 500 230300 399.2 0.1%
3700 5000 500 227500 249.3 0.1%
3800 5000 500 232500 572.2 0.2%
3900 5000 500 237400 453.9 0.1%
4000 5000 500 240500 357.8 0.1%
4100 5000 500 240600 1023 0.4%
4200 5000 500 243700 513.5 0.2%
4300 5000 500 245900 577.2 0.2%
4400 5000 500 249900 466.9 0.1%
4500 5000 500 251800 587.1 0.2%
4600 5000 500 253400 539.3 0.2%
4700 5000 500 251100 402.1 0.1%
4800 5000 500 257900 643.9 0.2%
4900 5000 500 259300 524.6 0.2%
5000 0 500 108500 342.4 0.3%
5000 100 500 113600 311.9 0.2%
5000 200 500 116700 225.3 0.1%
5000 300 500 119800 336.7 0.2%
5000 400 500 120500 202.8 0.1%
5000 500 500 125200 319.6 0.2%
5000 600 500 127300 241 0.1%
5000 700 500 130800 199.1 0.1%
5000 800 500 134600 155.5 0.1%
5000 900 500 136600 401.5 0.2%
5000 1000 500 139000 553.4 0.3%
5000 1100 500 143600 200.8 0.1%
5000 1200 500 146200 351.5 0.2%
5000 1300 500 148600 328.6 0.2%
5000 1400 500 152000 203.3 0.1%
5000 1500 500 154600 242 0.1%
5000 1600 500 158200 241.4 0.1%
5000 1700 500 160700 332.5 0.2%
5000 1800 500 163900 295.4 0.1%
5000 1900 500 166900 196.2 0.1%
5000 2000 500 171500 334.7 0.1%
5000 2100 500 173000 207.7 0.1%
5000 2200 500 179000 181.8 0.1%
5000 2300 500 182000 220.2 0.1%
5000 2400 500 184400 400.5 0.2%
5000 2500 500 188400 160.6 0.0%
5000 2600 500 190800 462.6 0.2%
5000 2700 500 192700 406.8 0.2%
5000 2800 500 196800 191.3 0.0%
5000 2900 500 197400 398.4 0.2%
5000 3000 500 204800 334.4 0.1%
5000 3100 500 205300 427.9 0.2%
5000 3200 500 208100 281.7 0.1%
5000 3300 500 210700 677.4 0.3%
5000 3400 500 214500 447.2 0.2%
5000 3500 500 219400 293.6 0.1%
5000 3600 500 220800 229.9 0.1%
5000 3700 500 222300 758.5 0.3%
5000 3800 500 229000 320.8 0.1%
5000 3900 500 230300 464.7 0.2%
5000 4000 500 228400 285.1 0.1%
5000 4100 500 236800 514.3 0.2%
5000 4200 500 240100 432.7 0.1%
5000 4300 500 242200 545.6 0.2%
5000 4400 500 241600 511.8 0.2%
5000 4500 500 247100 462.7 0.1%
5000 4600 500 247900 682.3 0.2%
5000 4700 500 251400 843.3 0.3%
5000 4800 500 256100 728.1 0.2%
5000 4900 500 257700 533.6 0.2%
5000 5000 0 260600 653.8 0.2%
5000 5000 10 263800 572.3 0.2%
5000 5000 20 261100 495 0.1%
5000 5000 30 262800 536.3 0.2%
5000 5000 40 262200 596.2 0.2%
5000 5000 50 261000 546.9 0.2%
5000 5000 60 261800 464.2 0.1%
5000 5000 70 259300 883.6 0.3%
5000 5000 80 262300 637.3 0.2%
5000 5000 90 257100 389.4 0.1%
5000 5000 100 263800 730.8 0.2%
5000 5000 110 261500 784.3 0.2%
5000 5000 120 261500 487.3 0.1%
5000 5000 130 263400 618.4 0.2%
5000 5000 140 262900 509.3 0.1%
5000 5000 150 264000 440.8 0.1%
5000 5000 160 259300 672.1 0.2%
5000 5000 170 261900 386.2 0.1%
5000 5000 180 263100 550.4 0.2%
5000 5000 190 259800 463.3 0.1%
5000 5000 200 259500 737.3 0.2%
5000 5000 210 263500 774.5 0.2%
5000 5000 220 263200 586.9 0.2%
5000 5000 230 261500 336.5 0.1%
5000 5000 240 263200 493.3 0.1%
5000 5000 250 262700 594.3 0.2%
5000 5000 260 260400 537.6 0.2%
5000 5000 270 262800 480.9 0.1%
5000 5000 280 260000 521.3 0.2%
5000 5000 290 257800 816.8 0.3%
5000 5000 300 262500 528.3 0.2%
5000 5000 310 260100 890.1 0.3%
5000 5000 320 263800 649.6 0.2%
5000 5000 330 258000 415 0.1%
5000 5000 340 257400 461.8 0.1%
5000 5000 350 261900 586.1 0.2%
5000 5000 360 264500 531.1 0.2%
5000 5000 370 263000 503.9 0.1%
5000 5000 380 257700 728.9 0.2%
5000 5000 390 260100 321.5 0.1%
5000 5000 400 262100 389.7 0.1%
5000 5000 410 259800 446 0.1%
5000 5000 420 263300 420.7 0.1%
5000 5000 430 263400 342.2 0.1%
5000 5000 440 265000 599.2 0.2%
5000 5000 450 258200 523.7 0.2%
5000 5000 460 260900 835.5 0.3%
5000 5000 470 263200 681.3 0.2%
5000 5000 480 258900 536.7 0.2%
5000 5000 490 260000 455.9 0.1%
5000 5000 500 262400 485.6 0.1%

Quality and confidence:
param error
c 0.038
s 0.038
a 0.383

Model:
Time ~= 0
+ c 24.23
+ s 30.46
+ a 2.343
µs

Reads = 4 + (2 * c) + (2 * s) + (0 * a)
Writes = 2 + (2 * c) + (2 * s) + (1 * a)
Pallet: "pallet_assets", Extrinsic: "mint", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 46.43
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 46.43
µs

Reads = 2
Writes = 2
Pallet: "pallet_assets", Extrinsic: "burn", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 46
µs

Reads = 2
Writes = 2
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 46
µs

Reads = 2
Writes = 2
Pallet: "pallet_assets", Extrinsic: "transfer", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 70.79
µs

Reads = 4
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 70.79
µs

Reads = 4
Writes = 4
Pallet: "pallet_assets", Extrinsic: "transfer_keep_alive", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 57.45
µs

Reads = 4
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 57.45
µs

Reads = 4
Writes = 4
Pallet: "pallet_assets", Extrinsic: "force_transfer", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 70.96
µs

Reads = 4
Writes = 4
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 70.96
µs

Reads = 4
Writes = 4
Pallet: "pallet_assets", Extrinsic: "freeze", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 34.29
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 34.29
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "thaw", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 34.41
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 34.41
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "freeze_asset", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 24.37
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 24.37
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "thaw_asset", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 24.09
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 24.09
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "transfer_ownership", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 28.56
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 28.56
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "set_team", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 25.29
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 25.29
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "set_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 53.46
+ n 0
+ s 0.005
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n s mean µs sigma µs %
0 50 53.29 0.178 0.3%
1 50 53.55 0.075 0.1%
2 50 53.72 0.104 0.1%
3 50 53.61 0.11 0.2%
4 50 53.93 0.044 0.0%
5 50 53.65 0.11 0.2%
6 50 53.49 0.124 0.2%
7 50 54 0.109 0.2%
8 50 53.79 0.114 0.2%
9 50 54.08 0.074 0.1%
10 50 53.75 0.118 0.2%
11 50 53.8 0.101 0.1%
12 50 53.55 0.092 0.1%
13 50 53.69 0.076 0.1%
14 50 53.65 0.109 0.2%
15 50 53.92 0.075 0.1%
16 50 53.71 0.154 0.2%
17 50 53.95 0.099 0.1%
18 50 53.69 0.095 0.1%
19 50 53.8 0.066 0.1%
20 50 53.61 0.093 0.1%
21 50 53.94 0.084 0.1%
22 50 53.7 0.134 0.2%
23 50 53.51 0.097 0.1%
24 50 53.85 0.073 0.1%
25 50 53.78 0.138 0.2%
26 50 53.6 0.172 0.3%
27 50 53.67 0.067 0.1%
28 50 53.42 0.068 0.1%
29 50 53.54 0.051 0.0%
30 50 53.84 0.135 0.2%
31 50 53.66 0.088 0.1%
32 50 53.7 0.16 0.2%
33 50 53.54 0.112 0.2%
34 50 53.75 0.118 0.2%
35 50 53.74 0.096 0.1%
36 50 53.77 0.079 0.1%
37 50 53.73 0.055 0.1%
38 50 53.75 0.064 0.1%
39 50 53.65 0.118 0.2%
40 50 53.96 0.088 0.1%
41 50 53.71 0.15 0.2%
42 50 53.81 0.144 0.2%
43 50 53.48 0.067 0.1%
44 50 53.86 0.109 0.2%
45 50 53.73 0.115 0.2%
46 50 53.57 0.084 0.1%
47 50 53.45 0.092 0.1%
48 50 53.69 0.129 0.2%
49 50 53.59 0.141 0.2%
50 0 52.58 0.079 0.1%
50 1 53.17 0.088 0.1%
50 2 53.37 0.078 0.1%
50 3 53.36 0.082 0.1%
50 4 53.3 0.091 0.1%
50 5 53.29 0.078 0.1%
50 6 53.32 0.168 0.3%
50 7 53.39 0.097 0.1%
50 8 53.46 0.112 0.2%
50 9 53.46 0.087 0.1%
50 10 53.5 0.11 0.2%
50 11 53.4 0.077 0.1%
50 12 53.2 0.148 0.2%
50 13 53.46 0.171 0.3%
50 14 53.22 0.124 0.2%
50 15 53.44 0.055 0.1%
50 16 53.29 0.1 0.1%
50 17 53.28 0.181 0.3%
50 18 53.32 0.137 0.2%
50 19 53.29 0.177 0.3%
50 20 53.29 0.07 0.1%
50 21 53.14 0.083 0.1%
50 22 53.31 0.109 0.2%
50 23 53.33 0.1 0.1%
50 24 53.32 0.08 0.1%
50 25 53.31 0.104 0.1%
50 26 53.43 0.215 0.4%
50 27 53.45 0.124 0.2%
50 28 53.46 0.109 0.2%
50 29 53.21 0.104 0.1%
50 30 53.43 0.18 0.3%
50 31 53.51 0.113 0.2%
50 32 53.35 0.142 0.2%
50 33 53.43 0.101 0.1%
50 34 53.27 0.09 0.1%
50 35 53.59 0.108 0.2%
50 36 53.3 0.074 0.1%
50 37 53.31 0.085 0.1%
50 38 53.7 0.113 0.2%
50 39 53.53 0.109 0.2%
50 40 53.43 0.192 0.3%
50 41 53.32 0.087 0.1%
50 42 53.83 0.108 0.2%
50 43 53.36 0.114 0.2%
50 44 53.58 0.051 0.0%
50 45 53.52 0.062 0.1%
50 46 53.48 0.125 0.2%
50 47 53.51 0.164 0.3%
50 48 53.48 0.125 0.2%
50 49 53.45 0.162 0.3%
50 50 53.51 0.116 0.2%

Quality and confidence:
param error
n 0
s 0

Model:
Time ~= 53.36
+ n 0
+ s 0.008
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Pallet: "pallet_assets", Extrinsic: "clear_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 51.72
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 51.72
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_set_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 27.19
+ n 0
+ s 0.002
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Min Squares Analysis

-- Extrinsic Time --

Data points distribution:
n s mean µs sigma µs %
0 50 26.91 0.076 0.2%
1 50 27.34 0.076 0.2%
2 50 27.22 0.052 0.1%
3 50 27.26 0.055 0.2%
4 50 27.32 0.078 0.2%
5 50 27.37 0.154 0.5%
6 50 27.34 0.043 0.1%
7 50 27.34 0.091 0.3%
8 50 27.64 0.099 0.3%
9 50 27.57 0.099 0.3%
10 50 27.28 0.106 0.3%
11 50 27.34 0.114 0.4%
12 50 27.31 0.08 0.2%
13 50 27.37 0.074 0.2%
14 50 27.41 0.096 0.3%
15 50 27.26 0.055 0.2%
16 50 27.26 0.06 0.2%
17 50 27.43 0.057 0.2%
18 50 27.22 0.066 0.2%
19 50 27.29 0.075 0.2%
20 50 27.44 0.064 0.2%
21 50 27.33 0.065 0.2%
22 50 27.35 0.066 0.2%
23 50 27.29 0.072 0.2%
24 50 27.35 0.064 0.2%
25 50 27.39 0.046 0.1%
26 50 27.37 0.084 0.3%
27 50 27.25 0.111 0.4%
28 50 27.38 0.074 0.2%
29 50 27.3 0.07 0.2%
30 50 27.38 0.061 0.2%
31 50 27.49 0.084 0.3%
32 50 27.39 0.038 0.1%
33 50 27.39 0.127 0.4%
34 50 27.36 0.1 0.3%
35 50 27.37 0.045 0.1%
36 50 27.38 0.04 0.1%
37 50 27.44 0.124 0.4%
38 50 27.3 0.05 0.1%
39 50 27.26 0.037 0.1%
40 50 27.33 0.089 0.3%
41 50 27.42 0.071 0.2%
42 50 27.43 0.071 0.2%
43 50 27.51 0.074 0.2%
44 50 27.39 0.088 0.3%
45 50 27.4 0.067 0.2%
46 50 27.15 0.061 0.2%
47 50 27.3 0.096 0.3%
48 50 27.24 0.037 0.1%
49 50 27.27 0.056 0.2%
50 0 27.28 0.092 0.3%
50 1 27.16 0.192 0.7%
50 2 27.08 0.083 0.3%
50 3 27.08 0.102 0.3%
50 4 27.01 0.071 0.2%
50 5 27.11 0.061 0.2%
50 6 27.05 0.051 0.1%
50 7 27.03 0.031 0.1%
50 8 27.19 0.06 0.2%
50 9 27.12 0.054 0.1%
50 10 27.11 0.06 0.2%
50 11 27.06 0.072 0.2%
50 12 27.09 0.109 0.4%
50 13 26.93 0.053 0.1%
50 14 27.03 0.03 0.1%
50 15 26.94 0.045 0.1%
50 16 26.92 0.095 0.3%
50 17 27.07 0.088 0.3%
50 18 27.17 0.111 0.4%
50 19 27.12 0.066 0.2%
50 20 27.17 0.061 0.2%
50 21 27.05 0.064 0.2%
50 22 27.08 0.052 0.1%
50 23 26.92 0.061 0.2%
50 24 27.01 0.081 0.2%
50 25 27.12 0.09 0.3%
50 26 27.07 0.079 0.2%
50 27 27.16 0.071 0.2%
50 28 27.02 0.052 0.1%
50 29 27.02 0.068 0.2%
50 30 27.12 0.061 0.2%
50 31 27.04 0.041 0.1%
50 32 27.09 0.07 0.2%
50 33 27.15 0.065 0.2%
50 34 27.09 0.069 0.2%
50 35 27.12 0.077 0.2%
50 36 27.1 0.075 0.2%
50 37 27.21 0.117 0.4%
50 38 27.18 0.087 0.3%
50 39 27.24 0.055 0.2%
50 40 27.22 0.067 0.2%
50 41 27.1 0.052 0.1%
50 42 27.2 0.067 0.2%
50 43 27.18 0.061 0.2%
50 44 27.24 0.074 0.2%
50 45 27.16 0.082 0.3%
50 46 27.08 0.073 0.2%
50 47 27.15 0.05 0.1%
50 48 27.2 0.097 0.3%
50 49 27.06 0.071 0.2%
50 50 27.33 0.101 0.3%

Quality and confidence:
param error
n 0
s 0

Model:
Time ~= 27.11
+ n 0
+ s 0.005
µs

Reads = 2 + (0 * n) + (0 * s)
Writes = 1 + (0 * n) + (0 * s)
Pallet: "pallet_assets", Extrinsic: "force_clear_metadata", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 51.59
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 51.59
µs

Reads = 2
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_asset_status", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 23.36
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 23.36
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "approve_transfer", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 47.9
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 47.9
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "transfer_approved", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 90.33
µs

Reads = 5
Writes = 5
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 90.33
µs

Reads = 5
Writes = 5
Pallet: "pallet_assets", Extrinsic: "cancel_approval", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 48.59
µs

Reads = 1
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 48.59
µs

Reads = 1
Writes = 1
Pallet: "pallet_assets", Extrinsic: "force_cancel_approval", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis

-- Extrinsic Time --

Model:
Time ~= 54.87
µs

Reads = 2
Writes = 1
Min Squares Analysis

-- Extrinsic Time --

Model:
Time ~= 54.87
µs

Reads = 2
Writes = 1

[gavofyork]

bot merge

[ghost]

Trying merge.

[ghost]

Merge failed: "At least 2 approving reviews are required by reviewers with write access."