$ git clone -n https://gitee.com/gcdota930915/anaconda.git /var/lib/mock/dist-an8.6-build-159059-58513/root/chroot_tmpdir/scmroot/anaconda Cloning into '/var/lib/mock/dist-an8.6-build-159059-58513/root/chroot_tmpdir/scmroot/anaconda'... $ git reset --hard origin/a8 HEAD is now at d0f104d Fix some text describe $ wget -O anaconda-33.16.6.7.tar.bz2 http://build.openanolis.cn/kojifiles/upstream-source/anaconda-33.16.6.7.tar.bz2.8ab20f29d153b7e2a16423795b5d5755 --2022-11-09 16:20:23-- http://build.openanolis.cn/kojifiles/upstream-source/anaconda-33.16.6.7.tar.bz2.8ab20f29d153b7e2a16423795b5d5755 Resolving build.openanolis.cn (build.openanolis.cn)... 8.141.190.229, 8.141.190.228, 8.141.190.224, ... Connecting to build.openanolis.cn (build.openanolis.cn)|8.141.190.229|:80... connected. HTTP request sent, awaiting response... 200 OK Length: 3427324 (3.3M) [application/x-bzip2] Saving to: ‘anaconda-33.16.6.7.tar.bz2’ 0K .......... .......... .......... .......... .......... 1% 1.10M 3s 50K .......... .......... .......... .......... .......... 2% 760K 4s 100K .......... .......... .......... .......... .......... 4% 1.09M 3s 150K .......... .......... .......... .......... .......... 5% 1.12M 3s 200K .......... .......... .......... .......... .......... 7% 1.11M 3s 250K .......... .......... .......... .......... .......... 8% 2.20M 3s 300K .......... .......... .......... .......... .......... 10% 1.12M 3s 350K .......... .......... .......... .......... .......... 11% 2.11M 2s 400K .......... .......... .......... .......... .......... 13% 1.13M 2s 450K .......... .......... .......... .......... .......... 14% 2.02M 2s 500K .......... .......... .......... .......... .......... 16% 2.32M 2s 550K .......... .......... .......... .......... .......... 17% 2.20M 2s 600K .......... .......... .......... .......... .......... 19% 2.03M 2s 650K .......... .......... .......... .......... .......... 20% 2.26M 2s 700K .......... .......... .......... .......... .......... 22% 1.86M 2s 750K .......... .......... .......... .......... .......... 23% 2.86M 2s 800K .......... .......... .......... .......... .......... 25% 2.24M 2s 850K .......... .......... .......... .......... .......... 26% 2.28M 2s 900K .......... .......... .......... .......... .......... 28% 2.32M 2s 950K .......... .......... .......... .......... .......... 29% 13.9M 1s 1000K .......... .......... .......... .......... .......... 31% 2.27M 1s 1050K .......... .......... .......... .......... .......... 32% 2.37M 1s 1100K .......... .......... .......... .......... .......... 34% 2.39M 1s 1150K .......... .......... .......... .......... .......... 35% 14.9M 1s 1200K .......... .......... .......... .......... .......... 37% 2.47M 1s 1250K .......... .......... .......... .......... .......... 38% 2.30M 1s 1300K .......... .......... .......... .......... .......... 40% 16.3M 1s 1350K .......... .......... .......... .......... .......... 41% 2.44M 1s 1400K .......... .......... .......... .......... .......... 43% 14.3M 1s 1450K .......... .......... .......... .......... .......... 44% 2.66M 1s 1500K .......... .......... .......... .......... .......... 46% 8.59M 1s 1550K .......... .......... .......... .......... .......... 47% 2.94M 1s 1600K .......... .......... .......... .......... .......... 49% 11.7M 1s 1650K .......... .......... .......... .......... .......... 50% 2.36M 1s 1700K .......... .......... .......... .......... .......... 52% 67.6M 1s 1750K .......... .......... .......... .......... .......... 53% 2.44M 1s 1800K .......... .......... .......... .......... .......... 55% 21.7M 1s 1850K .......... .......... .......... .......... .......... 56% 2.51M 1s 1900K .......... .......... .......... .......... .......... 58% 8.28M 1s 1950K .......... .......... .......... .......... .......... 59% 2.99M 1s 2000K .......... .......... .......... .......... .......... 61% 6.12M 1s 2050K .......... .......... .......... .......... .......... 62% 2.57M 1s 2100K .......... .......... .......... .......... .......... 64% 250M 0s 2150K .......... .......... .......... .......... .......... 65% 7.01M 0s 2200K .......... .......... .......... .......... .......... 67% 4.99M 0s 2250K .......... .......... .......... .......... .......... 68% 10.4M 0s 2300K .......... .......... .......... .......... .......... 70% 2.60M 0s 2350K .......... .......... .......... .......... .......... 71% 6.51M 0s 2400K .......... .......... .......... .......... .......... 73% 121M 0s 2450K .......... .......... .......... .......... .......... 74% 3.92M 0s 2500K .......... .......... .......... .......... .......... 76% 8.69M 0s 2550K .......... .......... .......... .......... .......... 77% 5.92M 0s 2600K .......... .......... .......... .......... .......... 79% 5.32M 0s 2650K .......... .......... .......... .......... .......... 80% 9.60M 0s 2700K .......... .......... .......... .......... .......... 82% 23.2M 0s 2750K .......... .......... .......... .......... .......... 83% 3.26M 0s 2800K .......... .......... .......... .......... .......... 85% 10.3M 0s 2850K .......... .......... .......... .......... .......... 86% 19.9M 0s 2900K .......... .......... .......... .......... .......... 88% 3.17M 0s 2950K .......... .......... .......... .......... .......... 89% 11.7M 0s 3000K .......... .......... .......... .......... .......... 91% 47.1M 0s 3050K .......... .......... .......... .......... .......... 92% 3.00M 0s 3100K .......... .......... .......... .......... .......... 94% 11.4M 0s 3150K .......... .......... .......... .......... .......... 95% 34.9M 0s 3200K .......... .......... .......... .......... .......... 97% 3.64M 0s 3250K .......... .......... .......... .......... .......... 98% 7.32M 0s 3300K .......... .......... .......... .......... ...... 100% 11.7M=1.1s 2022-11-09 16:20:24 (3.06 MB/s) - ‘anaconda-33.16.6.7.tar.bz2’ saved [3427324/3427324]