view mercurial/narrowspec.py @ 46057:e0313b0a6f7e

copies-rust: parse the changed-file sidedata directly in rust It does not make much sense to parse the data into python object using slow python code to later turn them into rust object. We directly pass the binary blob and use it directly in Rust. Ideally we could directly read the sidedata in Rust, using a revlog in Rust. However we do not have this ready to use yet. This more direct approach provides a nice speedup over the board. Especially five cases that we previously too slow to return in the previous changeset are not able to finish. Notably, we are now significantly faster than the Python version of this code in all the meaningful cases. I looked at the various cases that remains significantly slower then the filelog version and they are currently 3 main source of slowness: * The isancestor computation: even if we cache them, if the revs spawn over a large amount of history the ancestry checking is still quite expensive. Using a different approach more centered on the graph we are currently considering might yield significant speed. * Merging of the map from the two parents: in some case, this climb up to ⅔ of the time spent in copy tracing. See inline comment for idea to handle this better. * Extracting data from the filelog. I would like to think this mostly comes from the fact my test repositories pre-date Valentin Gatien-Baron improvement of the `files` field (99ebde4fec99) and that more recent revisions will be faster to fetch. Further testing on this aspect is needed. This revision compared to the previous one: =========================================== Repo Case Source-Rev Dest-Rev # of revisions old time new time Difference Factor time per rev -------------------------------------------------------------------------------------------------------------------------------------------------------------- mercurial x_revs_x_added_0_copies ad6b123de1c7 39cfcef4f463 : 1 revs, 0.000047 s, 0.000049 s, +0.000002 s, × 1.0426, 49 µs/rev mercurial x_revs_x_added_x_copies 2b1c78674230 0c1d10351869 : 6 revs, 0.000181 s, 0.000114 s, -0.000067 s, × 0.6298, 19 µs/rev mercurial x000_revs_x000_added_x_copies 81f8ff2a9bf2 dd3267698d84 : 1032 revs, 0.005852 s, 0.004223 s, -0.001629 s, × 0.7216, 4 µs/rev pypy x_revs_x_added_0_copies aed021ee8ae8 099ed31b181b : 9 revs, 0.000229 s, 0.000305 s, +0.000076 s, × 1.3319, 33 µs/rev pypy x_revs_x000_added_0_copies 4aa4e1f8e19a 359343b9ac0e : 1 revs, 0.000058 s, 0.000060 s, +0.000002 s, × 1.0345, 60 µs/rev pypy x_revs_x_added_x_copies ac52eb7bbbb0 72e022663155 : 7 revs, 0.000146 s, 0.000173 s, +0.000027 s, × 1.1849, 24 µs/rev pypy x_revs_x00_added_x_copies c3b14617fbd7 ace7255d9a26 : 1 revs, 0.001206 s, 0.000446 s, -0.000760 s, × 0.3698, 446 µs/rev pypy x_revs_x000_added_x000_copies df6f7a526b60 a83dc6a2d56f : 6 revs, 0.025275 s, 0.010360 s, -0.014915 s, × 0.4099, 1726 µs/rev pypy x000_revs_xx00_added_0_copies 89a76aede314 2f22446ff07e : 4785 revs, 0.080303 s, 0.048002 s, -0.032301 s, × 0.5978, 10 µs/rev pypy x000_revs_x000_added_x_copies 8a3b5bfd266e 2c68e87c3efe : 6780 revs, 0.152641 s, 0.075705 s, -0.076936 s, × 0.4960, 11 µs/rev pypy x000_revs_x000_added_x000_copies 89a76aede314 7b3dda341c84 : 5441 revs, 0.099107 s, 0.056705 s, -0.042402 s, × 0.5722, 10 µs/rev pypy x0000_revs_x_added_0_copies d1defd0dc478 c9cb1334cc78 : 43646 revs, 2.137894 s, 0.794685 s, -1.343209 s, × 0.3717, 18 µs/rev pypy x0000_revs_xx000_added_0_copies bf2c629d0071 4ffed77c095c : 26389 revs, 0.022202 s, 0.020209 s, -0.001993 s, × 0.9102, 0 µs/rev pypy x0000_revs_xx000_added_x000_copies 08ea3258278e d9fa043f30c0 : 11316 revs, 0.228946 s, 0.122475 s, -0.106471 s, × 0.5350, 10 µs/rev netbeans x_revs_x_added_0_copies fb0955ffcbcd a01e9239f9e7 : 2 revs, 0.000186 s, 0.000142 s, -0.000044 s, × 0.7634, 71 µs/rev netbeans x_revs_x000_added_0_copies 6f360122949f 20eb231cc7d0 : 2 revs, 0.000133 s, 0.000113 s, -0.000020 s, × 0.8496, 56 µs/rev netbeans x_revs_x_added_x_copies 1ada3faf6fb6 5a39d12eecf4 : 3 revs, 0.000320 s, 0.000241 s, -0.000079 s, × 0.7531, 80 µs/rev netbeans x_revs_x00_added_x_copies 35be93ba1e2c 9eec5e90c05f : 9 revs, 0.001339 s, 0.000729 s, -0.000610 s, × 0.5444, 81 µs/rev netbeans x000_revs_xx00_added_0_copies eac3045b4fdd 51d4ae7f1290 : 1421 revs, 0.015694 s, 0.010198 s, -0.005496 s, × 0.6498, 7 µs/rev netbeans x000_revs_x000_added_x_copies e2063d266acd 6081d72689dc : 1533 revs, 0.018457 s, 0.015312 s, -0.003145 s, × 0.8296, 9 µs/rev netbeans x000_revs_x000_added_x000_copies ff453e9fee32 411350406ec2 : 5750 revs, 0.111691 s, 0.060517 s, -0.051174 s, × 0.5418, 10 µs/rev netbeans x0000_revs_xx000_added_x000_copies 588c2d1ced70 1aad62e59ddd : 67005 revs, 1.166017 s, 0.611102 s, -0.554915 s, × 0.5241, 9 µs/rev mozilla-central x_revs_x_added_0_copies 3697f962bb7b 7015fcdd43a2 : 2 revs, 0.000197 s, 0.000164 s, -0.000033 s, × 0.8325, 82 µs/rev mozilla-central x_revs_x000_added_0_copies dd390860c6c9 40d0c5bed75d : 8 revs, 0.000626 s, 0.000334 s, -0.000292 s, × 0.5335, 41 µs/rev mozilla-central x_revs_x_added_x_copies 8d198483ae3b 14207ffc2b2f : 9 revs, 0.000303 s, 0.000463 s, +0.000160 s, × 1.5281, 51 µs/rev mozilla-central x_revs_x00_added_x_copies 98cbc58cc6bc 446a150332c3 : 7 revs, 0.001679 s, 0.000730 s, -0.000949 s, × 0.4348, 104 µs/rev mozilla-central x_revs_x000_added_x000_copies 3c684b4b8f68 0a5e72d1b479 : 3 revs, 0.006947 s, 0.003522 s, -0.003425 s, × 0.5070, 1174 µs/rev mozilla-central x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 0.133070 s, 0.072518 s, -0.060552 s, × 0.5450, 12086 µs/rev mozilla-central x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.008705 s, 0.005760 s, -0.002945 s, × 0.6617, 3 µs/rev mozilla-central x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 8315 revs, 0.005913 s, 0.005720 s, -0.000193 s, × 0.9674, 0 µs/rev mozilla-central x000_revs_x000_added_x000_copies 7c97034feb78 4407bd0c6330 : 7839 revs, 0.101373 s, 0.063310 s, -0.038063 s, × 0.6245, 8 µs/rev mozilla-central x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 45299 revs, 0.046526 s, 0.043608 s, -0.002918 s, × 0.9373, 0 µs/rev mozilla-central x0000_revs_xx000_added_x000_copies f78c615a656c 96a38b690156 : 30263 revs, 0.313954 s, 0.204831 s, -0.109123 s, × 0.6524, 6 µs/rev mozilla-central x00000_revs_x0000_added_x0000_copies 6832ae71433c 4c222a1d9a00 : 153721 revs, 3.367395 s, 2.161906 s, -1.205489 s, × 0.6420, 14 µs/rev mozilla-central x00000_revs_x00000_added_x000_copies 76caed42cf7c 1daa622bbe42 : 210546 revs, 4.691820 s, 3.291831 s, -1.399989 s, × 0.7016, 15 µs/rev mozilla-try x_revs_x_added_0_copies aaf6dde0deb8 9790f499805a : 2 revs, 0.001199 s, 0.001213 s, +0.000014 s, × 1.0117, 606 µs/rev mozilla-try x_revs_x000_added_0_copies d8d0222927b4 5bb8ce8c7450 : 2 revs, 0.001216 s, 0.001225 s, +0.000009 s, × 1.0074, 612 µs/rev mozilla-try x_revs_x_added_x_copies 092fcca11bdb 936255a0384a : 4 revs, 0.000613 s, 0.000564 s, -0.000049 s, × 0.9201, 141 µs/rev mozilla-try x_revs_x00_added_x_copies b53d2fadbdb5 017afae788ec : 2 revs, 0.001906 s, 0.001549 s, -0.000357 s, × 0.8127, 774 µs/rev mozilla-try x_revs_x000_added_x000_copies 20408ad61ce5 6f0ee96e21ad : 1 revs, 0.092766 s, 0.035918 s, -0.056848 s, × 0.3872, 35918 µs/rev mozilla-try x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 0.136074 s, 0.073788 s, -0.062286 s, × 0.5423, 12298 µs/rev mozilla-try x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.009067 s, 0.006151 s, -0.002916 s, × 0.6784, 3 µs/rev mozilla-try x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 8315 revs, 0.006243 s, 0.006165 s, -0.000078 s, × 0.9875, 0 µs/rev mozilla-try x000_revs_x000_added_x000_copies 1346fd0130e4 4c65cbdabc1f : 6657 revs, 0.114463 s, 0.065421 s, -0.049042 s, × 0.5715, 9 µs/rev mozilla-try x0000_revs_x_added_0_copies 63519bfd42ee a36a2a865d92 : 40314 revs, 0.433683 s, 0.313749 s, -0.119934 s, × 0.7235, 7 µs/rev mozilla-try x0000_revs_x_added_x_copies 9fe69ff0762d bcabf2a78927 : 38690 revs, 0.411278 s, 0.297867 s, -0.113411 s, × 0.7242, 7 µs/rev mozilla-try x0000_revs_xx000_added_x_copies 156f6e2674f2 4d0f2c178e66 : 54487 revs, 0.155133 s, 0.111300 s, -0.043833 s, × 0.7174, 2 µs/rev mozilla-try x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 45299 revs, 0.048933 s, 0.046202 s, -0.002731 s, × 0.9442, 1 µs/rev mozilla-try x0000_revs_xx000_added_x000_copies 89294cd501d9 7ccb2fc7ccb5 : 97052 revs, 8.100385 s, 1.999640 s, -6.100745 s, × 0.2469, 20 µs/rev mozilla-try x0000_revs_x0000_added_x0000_copies e928c65095ed e951f4ad123a : 52031 revs, 1.446720 s, 0.809134 s, -0.637586 s, × 0.5593, 15 µs/rev mozilla-try x00000_revs_x_added_0_copies 6a320851d377 1ebb79acd503 : 363753 revs, killed , 47.406785 s, , , 130 µs/rev mozilla-try x00000_revs_x00000_added_0_copies dc8a3ca7010e d16fde900c9c : 444327 revs, 1.369537 s, 0.996219 s, -0.373318 s, × 0.7274, 2 µs/rev mozilla-try x00000_revs_x_added_x_copies 5173c4b6f97c 95d83ee7242d : 362229 revs, killed , 47.273399 s, , , 130 µs/rev mozilla-try x00000_revs_x000_added_x_copies 9126823d0e9c ca82787bb23c : 359344 revs, killed , 47.419099 s, , , 131 µs/rev mozilla-try x00000_revs_x0000_added_x0000_copies 8d3fafa80d4b eb884023b810 : 192665 revs, 5.186079 s, 3.512653 s, -1.673426 s, × 0.6773, 18 µs/rev mozilla-try x00000_revs_x00000_added_x0000_copies 1b661134e2ca 1ae03d022d6d : 237259 revs, killed , 44.459049 s, , , 187 µs/rev mozilla-try x00000_revs_x00000_added_x000_copies 9b2a99adc05e 8e29777b48e6 : 391148 revs, killed , 52.837926 s, , , 135 µs/rev This revision compared to the python code: ========================================== Repo Case Source-Rev Dest-Rev # of revisions Python-Time Rust-Time Difference Factor time per rev -------------------------------------------------------------------------------------------------------------------------------------------------------------- mercurial x_revs_x_added_0_copies ad6b123de1c7 39cfcef4f463 : 1 revs, 0.000044 s, 0.000049 s, +0.000005 s, × 1.1136, 49 µs/rev mercurial x_revs_x_added_x_copies 2b1c78674230 0c1d10351869 : 6 revs, 0.000138 s, 0.000114 s, -0.000024 s, × 0.8261, 19 µs/rev mercurial x000_revs_x000_added_x_copies 81f8ff2a9bf2 dd3267698d84 : 1032 revs, 0.005052 s, 0.004223 s, -0.000829 s, × 0.8359, 4 µs/rev pypy x_revs_x_added_0_copies aed021ee8ae8 099ed31b181b : 9 revs, 0.000219 s, 0.000305 s, +0.000086 s, × 1.3927, 33 µs/rev pypy x_revs_x000_added_0_copies 4aa4e1f8e19a 359343b9ac0e : 1 revs, 0.000055 s, 0.000060 s, +0.000005 s, × 1.0909, 60 µs/rev pypy x_revs_x_added_x_copies ac52eb7bbbb0 72e022663155 : 7 revs, 0.000128 s, 0.000173 s, +0.000045 s, × 1.3516, 24 µs/rev pypy x_revs_x00_added_x_copies c3b14617fbd7 ace7255d9a26 : 1 revs, 0.001089 s, 0.000446 s, -0.000643 s, × 0.4096, 446 µs/rev pypy x_revs_x000_added_x000_copies df6f7a526b60 a83dc6a2d56f : 6 revs, 0.017407 s, 0.010360 s, -0.007047 s, × 0.5952, 1726 µs/rev pypy x000_revs_xx00_added_0_copies 89a76aede314 2f22446ff07e : 4785 revs, 0.094175 s, 0.048002 s, -0.046173 s, × 0.5097, 10 µs/rev pypy x000_revs_x000_added_x_copies 8a3b5bfd266e 2c68e87c3efe : 6780 revs, 0.238009 s, 0.075705 s, -0.162304 s, × 0.3181, 11 µs/rev pypy x000_revs_x000_added_x000_copies 89a76aede314 7b3dda341c84 : 5441 revs, 0.125876 s, 0.056705 s, -0.069171 s, × 0.4505, 10 µs/rev pypy x0000_revs_x_added_0_copies d1defd0dc478 c9cb1334cc78 : 43646 revs, 3.581556 s, 0.794685 s, -2.786871 s, × 0.2219, 18 µs/rev pypy x0000_revs_xx000_added_0_copies bf2c629d0071 4ffed77c095c : 26389 revs, 0.016721 s, 0.020209 s, +0.003488 s, × 1.2086, 0 µs/rev pypy x0000_revs_xx000_added_x000_copies 08ea3258278e d9fa043f30c0 : 11316 revs, 0.242367 s, 0.122475 s, -0.119892 s, × 0.5053, 10 µs/rev netbeans x_revs_x_added_0_copies fb0955ffcbcd a01e9239f9e7 : 2 revs, 0.000165 s, 0.000142 s, -0.000023 s, × 0.8606, 71 µs/rev netbeans x_revs_x000_added_0_copies 6f360122949f 20eb231cc7d0 : 2 revs, 0.000114 s, 0.000113 s, -0.000001 s, × 0.9912, 56 µs/rev netbeans x_revs_x_added_x_copies 1ada3faf6fb6 5a39d12eecf4 : 3 revs, 0.000296 s, 0.000241 s, -0.000055 s, × 0.8142, 80 µs/rev netbeans x_revs_x00_added_x_copies 35be93ba1e2c 9eec5e90c05f : 9 revs, 0.001124 s, 0.000729 s, -0.000395 s, × 0.6486, 81 µs/rev netbeans x000_revs_xx00_added_0_copies eac3045b4fdd 51d4ae7f1290 : 1421 revs, 0.013060 s, 0.010198 s, -0.002862 s, × 0.7809, 7 µs/rev netbeans x000_revs_x000_added_x_copies e2063d266acd 6081d72689dc : 1533 revs, 0.017112 s, 0.015312 s, -0.001800 s, × 0.8948, 9 µs/rev netbeans x000_revs_x000_added_x000_copies ff453e9fee32 411350406ec2 : 5750 revs, 0.660350 s, 0.060517 s, -0.599833 s, × 0.0916, 10 µs/rev netbeans x0000_revs_xx000_added_x000_copies 588c2d1ced70 1aad62e59ddd : 67005 revs, 10.032499 s, 0.611102 s, -9.421397 s, × 0.0609, 9 µs/rev mozilla-central x_revs_x_added_0_copies 3697f962bb7b 7015fcdd43a2 : 2 revs, 0.000189 s, 0.000164 s, -0.000025 s, × 0.8677, 82 µs/rev mozilla-central x_revs_x000_added_0_copies dd390860c6c9 40d0c5bed75d : 8 revs, 0.000462 s, 0.000334 s, -0.000128 s, × 0.7229, 41 µs/rev mozilla-central x_revs_x_added_x_copies 8d198483ae3b 14207ffc2b2f : 9 revs, 0.000270 s, 0.000463 s, +0.000193 s, × 1.7148, 51 µs/rev mozilla-central x_revs_x00_added_x_copies 98cbc58cc6bc 446a150332c3 : 7 revs, 0.001474 s, 0.000730 s, -0.000744 s, × 0.4953, 104 µs/rev mozilla-central x_revs_x000_added_x000_copies 3c684b4b8f68 0a5e72d1b479 : 3 revs, 0.004806 s, 0.003522 s, -0.001284 s, × 0.7328, 1174 µs/rev mozilla-central x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 0.085150 s, 0.072518 s, -0.012632 s, × 0.8517, 12086 µs/rev mozilla-central x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.007064 s, 0.005760 s, -0.001304 s, × 0.8154, 3 µs/rev mozilla-central x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 8315 revs, 0.004741 s, 0.005720 s, +0.000979 s, × 1.2065, 0 µs/rev mozilla-central x000_revs_x000_added_x000_copies 7c97034feb78 4407bd0c6330 : 7839 revs, 0.190133 s, 0.063310 s, -0.126823 s, × 0.3330, 8 µs/rev mozilla-central x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 45299 revs, 0.035651 s, 0.043608 s, +0.007957 s, × 1.2232, 0 µs/rev mozilla-central x0000_revs_xx000_added_x000_copies f78c615a656c 96a38b690156 : 30263 revs, 0.440694 s, 0.204831 s, -0.235863 s, × 0.4648, 6 µs/rev mozilla-central x00000_revs_x0000_added_x0000_copies 6832ae71433c 4c222a1d9a00 : 153721 revs, 18.454163 s, 2.161906 s, -16.292257 s, × 0.1172, 14 µs/rev mozilla-central x00000_revs_x00000_added_x000_copies 76caed42cf7c 1daa622bbe42 : 210546 revs, 31.562719 s, 3.291831 s, -28.270888 s, × 0.1043, 15 µs/rev mozilla-try x_revs_x_added_0_copies aaf6dde0deb8 9790f499805a : 2 revs, 0.001189 s, 0.001213 s, +0.000024 s, × 1.0202, 606 µs/rev mozilla-try x_revs_x000_added_0_copies d8d0222927b4 5bb8ce8c7450 : 2 revs, 0.001204 s, 0.001225 s, +0.000021 s, × 1.0174, 612 µs/rev mozilla-try x_revs_x_added_x_copies 092fcca11bdb 936255a0384a : 4 revs, 0.000586 s, 0.000564 s, -0.000022 s, × 0.9625, 141 µs/rev mozilla-try x_revs_x00_added_x_copies b53d2fadbdb5 017afae788ec : 2 revs, 0.001845 s, 0.001549 s, -0.000296 s, × 0.8396, 774 µs/rev mozilla-try x_revs_x000_added_x000_copies 20408ad61ce5 6f0ee96e21ad : 1 revs, 0.063822 s, 0.035918 s, -0.027904 s, × 0.5628, 35918 µs/rev mozilla-try x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 0.088038 s, 0.073788 s, -0.014250 s, × 0.8381, 12298 µs/rev mozilla-try x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.007389 s, 0.006151 s, -0.001238 s, × 0.8325, 3 µs/rev mozilla-try x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 8315 revs, 0.004868 s, 0.006165 s, +0.001297 s, × 1.2664, 0 µs/rev mozilla-try x000_revs_x000_added_x000_copies 1346fd0130e4 4c65cbdabc1f : 6657 revs, 0.222450 s, 0.065421 s, -0.157029 s, × 0.2941, 9 µs/rev mozilla-try x0000_revs_x_added_0_copies 63519bfd42ee a36a2a865d92 : 40314 revs, 0.370675 s, 0.313749 s, -0.056926 s, × 0.8464, 7 µs/rev mozilla-try x0000_revs_x_added_x_copies 9fe69ff0762d bcabf2a78927 : 38690 revs, 0.358020 s, 0.297867 s, -0.060153 s, × 0.8320, 7 µs/rev mozilla-try x0000_revs_xx000_added_x_copies 156f6e2674f2 4d0f2c178e66 : 54487 revs, 0.145235 s, 0.111300 s, -0.033935 s, × 0.7663, 2 µs/rev mozilla-try x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 45299 revs, 0.037606 s, 0.046202 s, +0.008596 s, × 1.2286, 1 µs/rev mozilla-try x0000_revs_xx000_added_x000_copies 89294cd501d9 7ccb2fc7ccb5 : 97052 revs, 7.382439 s, 1.999640 s, -5.382799 s, × 0.2709, 20 µs/rev mozilla-try x0000_revs_x0000_added_x0000_copies e928c65095ed e951f4ad123a : 52031 revs, 7.273506 s, 0.809134 s, -6.464372 s, × 0.1112, 15 µs/rev mozilla-try x00000_revs_x_added_0_copies 6a320851d377 1ebb79acd503 : 363753 revs, killed , 47.406785 s, , , 130 µs/rev mozilla-try x00000_revs_x00000_added_0_copies dc8a3ca7010e d16fde900c9c : 444327 revs, 1.074593 s, 0.996219 s, -0.078374 s, × 0.9271, 2 µs/rev mozilla-try x00000_revs_x_added_x_copies 5173c4b6f97c 95d83ee7242d : 362229 revs, killed , 47.273399 s, , , 130 µs/rev mozilla-try x00000_revs_x000_added_x_copies 9126823d0e9c ca82787bb23c : 359344 revs, killed , 47.419099 s, , , 131 µs/rev mozilla-try x00000_revs_x0000_added_x0000_copies 8d3fafa80d4b eb884023b810 : 192665 revs, 27.746195 s, 3.512653 s, -24.233542 s, × 0.1266, 18 µs/rev mozilla-try x00000_revs_x00000_added_x0000_copies 1b661134e2ca 1ae03d022d6d : 237259 revs, killed , 44.459049 s, , , 187 µs/rev mozilla-try x00000_revs_x00000_added_x000_copies 9b2a99adc05e 8e29777b48e6 : 391148 revs, killed , 52.837926 s, , , 135 µs/rev This revision compared to the filelog algorithm: ================================================ Repo Case Source-Rev Dest-Rev # of revisions filelog sidedata Difference Factor time per rev -------------------------------------------------------------------------------------------------------------------------------------------------------------- mercurial x_revs_x_added_0_copies ad6b123de1c7 39cfcef4f463 : 1 revs, 0.000906 s, 0.000049 s, -0.000857 s, × 0.0540, 48 µs/rev mercurial x_revs_x_added_x_copies 2b1c78674230 0c1d10351869 : 6 revs, 0.001844 s, 0.000114 s, -0.001730 s, × 0.0618, 18 µs/rev mercurial x000_revs_x000_added_x_copies 81f8ff2a9bf2 dd3267698d84 : 1032 revs, 0.018577 s, 0.004223 s, -0.014354 s, × 0.2273, 4 µs/rev pypy x_revs_x_added_0_copies aed021ee8ae8 099ed31b181b : 9 revs, 0.005009 s, 0.000305 s, -0.004704 s, × 0.0608, 33 µs/rev pypy x_revs_x000_added_0_copies 4aa4e1f8e19a 359343b9ac0e : 1 revs, 0.209606 s, 0.000060 s, -0.209546 s, × 0.0002, 59 µs/rev pypy x_revs_x_added_x_copies ac52eb7bbbb0 72e022663155 : 7 revs, 0.017008 s, 0.000173 s, -0.016835 s, × 0.0101, 24 µs/rev pypy x_revs_x00_added_x_copies c3b14617fbd7 ace7255d9a26 : 1 revs, 0.019227 s, 0.000446 s, -0.018781 s, × 0.0231, 445 µs/rev pypy x_revs_x000_added_x000_copies df6f7a526b60 a83dc6a2d56f : 6 revs, 0.765782 s, 0.010360 s, -0.755422 s, × 0.0135, 1726 µs/rev pypy x000_revs_xx00_added_0_copies 89a76aede314 2f22446ff07e : 4785 revs, 1.186068 s, 0.048002 s, -1.138066 s, × 0.0404, 10 µs/rev pypy x000_revs_x000_added_x_copies 8a3b5bfd266e 2c68e87c3efe : 6780 revs, 1.266745 s, 0.075705 s, -1.191040 s, × 0.0597, 11 µs/rev pypy x000_revs_x000_added_x000_copies 89a76aede314 7b3dda341c84 : 5441 revs, 1.666389 s, 0.056705 s, -1.609684 s, × 0.0340, 10 µs/rev pypy x0000_revs_x_added_0_copies d1defd0dc478 c9cb1334cc78 : 43646 revs, 0.001070 s, 0.794685 s, +0.793615 s, × 742.69, 18 µs/rev pypy x0000_revs_xx000_added_0_copies bf2c629d0071 4ffed77c095c : 26389 revs, 1.076269 s, 0.020209 s, -1.056060 s, × 0.0187, 0 µs/rev pypy x0000_revs_xx000_added_x000_copies 08ea3258278e d9fa043f30c0 : 11316 revs, 1.355085 s, 0.122475 s, -1.232610 s, × 0.0903, 10 µs/rev netbeans x_revs_x_added_0_copies fb0955ffcbcd a01e9239f9e7 : 2 revs, 0.028551 s, 0.000142 s, -0.028409 s, × 0.0049, 70 µs/rev netbeans x_revs_x000_added_0_copies 6f360122949f 20eb231cc7d0 : 2 revs, 0.157319 s, 0.000113 s, -0.157206 s, × 0.0007, 56 µs/rev netbeans x_revs_x_added_x_copies 1ada3faf6fb6 5a39d12eecf4 : 3 revs, 0.025722 s, 0.000241 s, -0.025481 s, × 0.0093, 80 µs/rev netbeans x_revs_x00_added_x_copies 35be93ba1e2c 9eec5e90c05f : 9 revs, 0.053374 s, 0.000729 s, -0.052645 s, × 0.0136, 80 µs/rev netbeans x000_revs_xx00_added_0_copies eac3045b4fdd 51d4ae7f1290 : 1421 revs, 0.038146 s, 0.010198 s, -0.027948 s, × 0.2673, 7 µs/rev netbeans x000_revs_x000_added_x_copies e2063d266acd 6081d72689dc : 1533 revs, 0.229215 s, 0.015312 s, -0.213903 s, × 0.0668, 9 µs/rev netbeans x000_revs_x000_added_x000_copies ff453e9fee32 411350406ec2 : 5750 revs, 0.974484 s, 0.060517 s, -0.913967 s, × 0.0621, 10 µs/rev netbeans x0000_revs_xx000_added_x000_copies 588c2d1ced70 1aad62e59ddd : 67005 revs, 3.924308 s, 0.611102 s, -3.313206 s, × 0.1557, 9 µs/rev mozilla-central x_revs_x_added_0_copies 3697f962bb7b 7015fcdd43a2 : 2 revs, 0.035563 s, 0.000164 s, -0.035399 s, × 0.0046, 81 µs/rev mozilla-central x_revs_x000_added_0_copies dd390860c6c9 40d0c5bed75d : 8 revs, 0.145766 s, 0.000334 s, -0.145432 s, × 0.0022, 41 µs/rev mozilla-central x_revs_x_added_x_copies 8d198483ae3b 14207ffc2b2f : 9 revs, 0.026283 s, 0.000463 s, -0.025820 s, × 0.0176, 51 µs/rev mozilla-central x_revs_x00_added_x_copies 98cbc58cc6bc 446a150332c3 : 7 revs, 0.087403 s, 0.000730 s, -0.086673 s, × 0.0083, 104 µs/rev mozilla-central x_revs_x000_added_x000_copies 3c684b4b8f68 0a5e72d1b479 : 3 revs, 0.209484 s, 0.003522 s, -0.205962 s, × 0.0168, 1173 µs/rev mozilla-central x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 2.197867 s, 0.072518 s, -2.125349 s, × 0.0329, 12084 µs/rev mozilla-central x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.090142 s, 0.005760 s, -0.084382 s, × 0.0638, 3 µs/rev mozilla-central x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 8315 revs, 0.742658 s, 0.005720 s, -0.736938 s, × 0.0077, 0 µs/rev mozilla-central x000_revs_x000_added_x000_copies 7c97034feb78 4407bd0c6330 : 7839 revs, 1.166159 s, 0.063310 s, -1.102849 s, × 0.0542, 8 µs/rev mozilla-central x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 45299 revs, 6.721719 s, 0.043608 s, -6.678111 s, × 0.0064, 0 µs/rev mozilla-central x0000_revs_xx000_added_x000_copies f78c615a656c 96a38b690156 : 30263 revs, 3.356523 s, 0.204831 s, -3.151692 s, × 0.0610, 6 µs/rev mozilla-central x00000_revs_x0000_added_x0000_copies 6832ae71433c 4c222a1d9a00 : 153721 revs, 15.880822 s, 2.161906 s, -13.718916 s, × 0.1361, 14 µs/rev mozilla-central x00000_revs_x00000_added_x000_copies 76caed42cf7c 1daa622bbe42 : 210546 revs, 20.781275 s, 3.291831 s, -17.489444 s, × 0.1584, 15 µs/rev mozilla-try x_revs_x_added_0_copies aaf6dde0deb8 9790f499805a : 2 revs, 0.084165 s, 0.001213 s, -0.082952 s, × 0.0144, 606 µs/rev mozilla-try x_revs_x000_added_0_copies d8d0222927b4 5bb8ce8c7450 : 2 revs, 0.503744 s, 0.001225 s, -0.502519 s, × 0.0024, 612 µs/rev mozilla-try x_revs_x_added_x_copies 092fcca11bdb 936255a0384a : 4 revs, 0.021545 s, 0.000564 s, -0.020981 s, × 0.0261, 140 µs/rev mozilla-try x_revs_x00_added_x_copies b53d2fadbdb5 017afae788ec : 2 revs, 0.240699 s, 0.001549 s, -0.239150 s, × 0.0064, 774 µs/rev mozilla-try x_revs_x000_added_x000_copies 20408ad61ce5 6f0ee96e21ad : 1 revs, 1.100682 s, 0.035918 s, -1.064764 s, × 0.0326, 35882 µs/rev mozilla-try x_revs_x0000_added_x0000_copies effb563bb7e5 c07a39dc4e80 : 6 revs, 2.234809 s, 0.073788 s, -2.161021 s, × 0.0330, 12295 µs/rev mozilla-try x000_revs_xx00_added_0_copies 6100d773079a 04a55431795e : 1593 revs, 0.091222 s, 0.006151 s, -0.085071 s, × 0.0674, 3 µs/rev mozilla-try x000_revs_x000_added_x_copies 9f17a6fc04f9 2d37b966abed : 8315 revs, 0.764722 s, 0.006165 s, -0.758557 s, × 0.0080, 0 µs/rev mozilla-try x000_revs_x000_added_x000_copies 1346fd0130e4 4c65cbdabc1f : 6657 revs, 1.185655 s, 0.065421 s, -1.120234 s, × 0.0551, 9 µs/rev mozilla-try x0000_revs_x_added_0_copies 63519bfd42ee a36a2a865d92 : 40314 revs, 0.089736 s, 0.313749 s, +0.224013 s, × 3.4963, 7 µs/rev mozilla-try x0000_revs_x_added_x_copies 9fe69ff0762d bcabf2a78927 : 38690 revs, 0.084132 s, 0.297867 s, +0.213735 s, × 3.5404, 7 µs/rev mozilla-try x0000_revs_xx000_added_x_copies 156f6e2674f2 4d0f2c178e66 : 54487 revs, 7.581932 s, 0.111300 s, -7.470632 s, × 0.0146, 2 µs/rev mozilla-try x0000_revs_xx000_added_0_copies 9eec5917337d 67118cc6dcad : 45299 revs, 6.671144 s, 0.046202 s, -6.624942 s, × 0.0069, 1 µs/rev mozilla-try x0000_revs_xx000_added_x000_copies 89294cd501d9 7ccb2fc7ccb5 : 97052 revs, 7.674771 s, 1.999640 s, -5.675131 s, × 0.2605, 20 µs/rev mozilla-try x0000_revs_x0000_added_x0000_copies e928c65095ed e951f4ad123a : 52031 revs, 9.870343 s, 0.809134 s, -9.061209 s, × 0.0819, 15 µs/rev mozilla-try x00000_revs_x_added_0_copies 6a320851d377 1ebb79acd503 : 363753 revs, 0.094781 s, 47.406785 s, +47.312004 s, × 500.17, 130 µs/rev mozilla-try x00000_revs_x00000_added_0_copies dc8a3ca7010e d16fde900c9c : 444327 revs, 26.690029 s, 0.996219 s, -25.693810 s, × 0.0373, 2 µs/rev mozilla-try x00000_revs_x_added_x_copies 5173c4b6f97c 95d83ee7242d : 362229 revs, 0.094941 s, 47.273399 s, +47.178458 s, × 497.92, 130 µs/rev mozilla-try x00000_revs_x000_added_x_copies 9126823d0e9c ca82787bb23c : 359344 revs, 0.233811 s, 47.419099 s, +47.185288 s, × 202.80, 131 µs/rev mozilla-try x00000_revs_x0000_added_x0000_copies 8d3fafa80d4b eb884023b810 : 192665 revs, 19.321750 s, 3.512653 s, -15.809097 s, × 0.1817, 18 µs/rev mozilla-try x00000_revs_x00000_added_x0000_copies 1b661134e2ca 1ae03d022d6d : 237259 revs, 21.358350 s, 44.459049 s, +23.100699 s, × 2.0815, 187 µs/rev mozilla-try x00000_revs_x00000_added_x000_copies 9b2a99adc05e 8e29777b48e6 : 391148 revs, 25.328737 s, 52.837926 s, +27.509189 s, × 2.0860, 135 µs/rev Differential Revision: https://phab.mercurial-scm.org/D9307
author Pierre-Yves David <pierre-yves.david@octobus.net>
date Thu, 12 Nov 2020 15:54:10 +0100
parents 89a2afe31e82
children ced66295ea90
line wrap: on
line source

# narrowspec.py - methods for working with a narrow view of a repository
#
# Copyright 2017 Google, Inc.
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.

from __future__ import absolute_import

from .i18n import _
from .pycompat import getattr
from . import (
    error,
    match as matchmod,
    merge,
    mergestate as mergestatemod,
    requirements,
    scmutil,
    sparse,
    util,
)

# The file in .hg/store/ that indicates which paths exit in the store
FILENAME = b'narrowspec'
# The file in .hg/ that indicates which paths exit in the dirstate
DIRSTATE_FILENAME = b'narrowspec.dirstate'

# Pattern prefixes that are allowed in narrow patterns. This list MUST
# only contain patterns that are fast and safe to evaluate. Keep in mind
# that patterns are supplied by clients and executed on remote servers
# as part of wire protocol commands. That means that changes to this
# data structure influence the wire protocol and should not be taken
# lightly - especially removals.
VALID_PREFIXES = (
    b'path:',
    b'rootfilesin:',
)


def normalizesplitpattern(kind, pat):
    """Returns the normalized version of a pattern and kind.

    Returns a tuple with the normalized kind and normalized pattern.
    """
    pat = pat.rstrip(b'/')
    _validatepattern(pat)
    return kind, pat


def _numlines(s):
    """Returns the number of lines in s, including ending empty lines."""
    # We use splitlines because it is Unicode-friendly and thus Python 3
    # compatible. However, it does not count empty lines at the end, so trick
    # it by adding a character at the end.
    return len((s + b'x').splitlines())


def _validatepattern(pat):
    """Validates the pattern and aborts if it is invalid.

    Patterns are stored in the narrowspec as newline-separated
    POSIX-style bytestring paths. There's no escaping.
    """

    # We use newlines as separators in the narrowspec file, so don't allow them
    # in patterns.
    if _numlines(pat) > 1:
        raise error.Abort(_(b'newlines are not allowed in narrowspec paths'))

    components = pat.split(b'/')
    if b'.' in components or b'..' in components:
        raise error.Abort(
            _(b'"." and ".." are not allowed in narrowspec paths')
        )


def normalizepattern(pattern, defaultkind=b'path'):
    """Returns the normalized version of a text-format pattern.

    If the pattern has no kind, the default will be added.
    """
    kind, pat = matchmod._patsplit(pattern, defaultkind)
    return b'%s:%s' % normalizesplitpattern(kind, pat)


def parsepatterns(pats):
    """Parses an iterable of patterns into a typed pattern set.

    Patterns are assumed to be ``path:`` if no prefix is present.
    For safety and performance reasons, only some prefixes are allowed.
    See ``validatepatterns()``.

    This function should be used on patterns that come from the user to
    normalize and validate them to the internal data structure used for
    representing patterns.
    """
    res = {normalizepattern(orig) for orig in pats}
    validatepatterns(res)
    return res


def validatepatterns(pats):
    """Validate that patterns are in the expected data structure and format.

    And that is a set of normalized patterns beginning with ``path:`` or
    ``rootfilesin:``.

    This function should be used to validate internal data structures
    and patterns that are loaded from sources that use the internal,
    prefixed pattern representation (but can't necessarily be fully trusted).
    """
    if not isinstance(pats, set):
        raise error.ProgrammingError(
            b'narrow patterns should be a set; got %r' % pats
        )

    for pat in pats:
        if not pat.startswith(VALID_PREFIXES):
            # Use a Mercurial exception because this can happen due to user
            # bugs (e.g. manually updating spec file).
            raise error.Abort(
                _(b'invalid prefix on narrow pattern: %s') % pat,
                hint=_(
                    b'narrow patterns must begin with one of '
                    b'the following: %s'
                )
                % b', '.join(VALID_PREFIXES),
            )


def format(includes, excludes):
    output = b'[include]\n'
    for i in sorted(includes - excludes):
        output += i + b'\n'
    output += b'[exclude]\n'
    for e in sorted(excludes):
        output += e + b'\n'
    return output


def match(root, include=None, exclude=None):
    if not include:
        # Passing empty include and empty exclude to matchmod.match()
        # gives a matcher that matches everything, so explicitly use
        # the nevermatcher.
        return matchmod.never()
    return matchmod.match(
        root, b'', [], include=include or [], exclude=exclude or []
    )


def parseconfig(ui, spec):
    # maybe we should care about the profiles returned too
    includepats, excludepats, profiles = sparse.parseconfig(ui, spec, b'narrow')
    if profiles:
        raise error.Abort(
            _(
                b"including other spec files using '%include' is not"
                b" supported in narrowspec"
            )
        )

    validatepatterns(includepats)
    validatepatterns(excludepats)

    return includepats, excludepats


def load(repo):
    # Treat "narrowspec does not exist" the same as "narrowspec file exists
    # and is empty".
    spec = repo.svfs.tryread(FILENAME)
    return parseconfig(repo.ui, spec)


def save(repo, includepats, excludepats):
    validatepatterns(includepats)
    validatepatterns(excludepats)
    spec = format(includepats, excludepats)
    repo.svfs.write(FILENAME, spec)


def copytoworkingcopy(repo):
    spec = repo.svfs.read(FILENAME)
    repo.vfs.write(DIRSTATE_FILENAME, spec)


def savebackup(repo, backupname):
    if requirements.NARROW_REQUIREMENT not in repo.requirements:
        return
    svfs = repo.svfs
    svfs.tryunlink(backupname)
    util.copyfile(svfs.join(FILENAME), svfs.join(backupname), hardlink=True)


def restorebackup(repo, backupname):
    if requirements.NARROW_REQUIREMENT not in repo.requirements:
        return
    util.rename(repo.svfs.join(backupname), repo.svfs.join(FILENAME))


def savewcbackup(repo, backupname):
    if requirements.NARROW_REQUIREMENT not in repo.requirements:
        return
    vfs = repo.vfs
    vfs.tryunlink(backupname)
    # It may not exist in old repos
    if vfs.exists(DIRSTATE_FILENAME):
        util.copyfile(
            vfs.join(DIRSTATE_FILENAME), vfs.join(backupname), hardlink=True
        )


def restorewcbackup(repo, backupname):
    if requirements.NARROW_REQUIREMENT not in repo.requirements:
        return
    # It may not exist in old repos
    if repo.vfs.exists(backupname):
        util.rename(repo.vfs.join(backupname), repo.vfs.join(DIRSTATE_FILENAME))


def clearwcbackup(repo, backupname):
    if requirements.NARROW_REQUIREMENT not in repo.requirements:
        return
    repo.vfs.tryunlink(backupname)


def restrictpatterns(req_includes, req_excludes, repo_includes, repo_excludes):
    r"""Restricts the patterns according to repo settings,
    results in a logical AND operation

    :param req_includes: requested includes
    :param req_excludes: requested excludes
    :param repo_includes: repo includes
    :param repo_excludes: repo excludes
    :return: include patterns, exclude patterns, and invalid include patterns.
    """
    res_excludes = set(req_excludes)
    res_excludes.update(repo_excludes)
    invalid_includes = []
    if not req_includes:
        res_includes = set(repo_includes)
    elif b'path:.' not in repo_includes:
        res_includes = []
        for req_include in req_includes:
            req_include = util.expandpath(util.normpath(req_include))
            if req_include in repo_includes:
                res_includes.append(req_include)
                continue
            valid = False
            for repo_include in repo_includes:
                if req_include.startswith(repo_include + b'/'):
                    valid = True
                    res_includes.append(req_include)
                    break
            if not valid:
                invalid_includes.append(req_include)
        if len(res_includes) == 0:
            res_excludes = {b'path:.'}
        else:
            res_includes = set(res_includes)
    else:
        res_includes = set(req_includes)
    return res_includes, res_excludes, invalid_includes


# These two are extracted for extensions (specifically for Google's CitC file
# system)
def _deletecleanfiles(repo, files):
    for f in files:
        repo.wvfs.unlinkpath(f)


def _writeaddedfiles(repo, pctx, files):
    mresult = merge.mergeresult()
    mf = repo[b'.'].manifest()
    for f in files:
        if not repo.wvfs.exists(f):
            mresult.addfile(
                f,
                mergestatemod.ACTION_GET,
                (mf.flags(f), False),
                b"narrowspec updated",
            )
    merge.applyupdates(
        repo,
        mresult,
        wctx=repo[None],
        mctx=repo[b'.'],
        overwrite=False,
        wantfiledata=False,
    )


def checkworkingcopynarrowspec(repo):
    # Avoid infinite recursion when updating the working copy
    if getattr(repo, '_updatingnarrowspec', False):
        return
    storespec = repo.svfs.tryread(FILENAME)
    wcspec = repo.vfs.tryread(DIRSTATE_FILENAME)
    if wcspec != storespec:
        raise error.Abort(
            _(b"working copy's narrowspec is stale"),
            hint=_(b"run 'hg tracked --update-working-copy'"),
        )


def updateworkingcopy(repo, assumeclean=False):
    """updates the working copy and dirstate from the store narrowspec

    When assumeclean=True, files that are not known to be clean will also
    be deleted. It is then up to the caller to make sure they are clean.
    """
    oldspec = repo.vfs.tryread(DIRSTATE_FILENAME)
    newspec = repo.svfs.tryread(FILENAME)
    repo._updatingnarrowspec = True

    oldincludes, oldexcludes = parseconfig(repo.ui, oldspec)
    newincludes, newexcludes = parseconfig(repo.ui, newspec)
    oldmatch = match(repo.root, include=oldincludes, exclude=oldexcludes)
    newmatch = match(repo.root, include=newincludes, exclude=newexcludes)
    addedmatch = matchmod.differencematcher(newmatch, oldmatch)
    removedmatch = matchmod.differencematcher(oldmatch, newmatch)

    ds = repo.dirstate
    lookup, status = ds.status(
        removedmatch, subrepos=[], ignored=True, clean=True, unknown=True
    )
    trackeddirty = status.modified + status.added
    clean = status.clean
    if assumeclean:
        assert not trackeddirty
        clean.extend(lookup)
    else:
        trackeddirty.extend(lookup)
    _deletecleanfiles(repo, clean)
    uipathfn = scmutil.getuipathfn(repo)
    for f in sorted(trackeddirty):
        repo.ui.status(
            _(b'not deleting possibly dirty file %s\n') % uipathfn(f)
        )
    for f in sorted(status.unknown):
        repo.ui.status(_(b'not deleting unknown file %s\n') % uipathfn(f))
    for f in sorted(status.ignored):
        repo.ui.status(_(b'not deleting ignored file %s\n') % uipathfn(f))
    for f in clean + trackeddirty:
        ds.drop(f)

    pctx = repo[b'.']
    newfiles = [f for f in pctx.manifest().walk(addedmatch) if f not in ds]
    for f in newfiles:
        ds.normallookup(f)
    _writeaddedfiles(repo, pctx, newfiles)
    repo._updatingnarrowspec = False