$ git clone -n https://gitee.com/src-anolis-os/anaconda.git /var/lib/mock/dist-an8.7-build-259449-63788/root/chroot_tmpdir/scmroot/anaconda Cloning into '/var/lib/mock/dist-an8.7-build-259449-63788/root/chroot_tmpdir/scmroot/anaconda'... $ git reset --hard 2dcc24eb7233f000e57204375775437030b00b9b HEAD is now at 2dcc24e Set default timezone to Beijing $ wget -O anaconda-33.16.7.12.tar.bz2 http://build.openanolis.cn/kojifiles/upstream-source/anaconda-33.16.7.12.tar.bz2.d55e50138312232ba83dcf0615bf9140 --2023-05-04 22:32:40-- http://build.openanolis.cn/kojifiles/upstream-source/anaconda-33.16.7.12.tar.bz2.d55e50138312232ba83dcf0615bf9140 Resolving build.openanolis.cn (build.openanolis.cn)... 182.40.60.209, 182.40.60.215, 182.40.60.210, ... Connecting to build.openanolis.cn (build.openanolis.cn)|182.40.60.209|:80... connected. HTTP request sent, awaiting response... 200 OK Length: 3369733 (3.2M) [application/x-bzip2] Saving to: ‘anaconda-33.16.7.12.tar.bz2’ 0K .......... .......... .......... .......... .......... 1% 1.58M 2s 50K .......... .......... .......... .......... .......... 3% 2.19M 2s 100K .......... .......... .......... .......... .......... 4% 8.43M 1s 150K .......... .......... .......... .......... .......... 6% 9.10M 1s 200K .......... .......... .......... .......... .......... 7% 9.69M 1s 250K .......... .......... .......... .......... .......... 9% 3.33M 1s 300K .......... .......... .......... .......... .......... 10% 10.5M 1s 350K .......... .......... .......... .......... .......... 12% 9.81M 1s 400K .......... .......... .......... .......... .......... 13% 9.86M 1s 450K .......... .......... .......... .......... .......... 15% 6.77M 1s 500K .......... .......... .......... .......... .......... 16% 11.4M 1s 550K .......... .......... .......... .......... .......... 18% 12.2M 1s 600K .......... .......... .......... .......... .......... 19% 13.1M 0s 650K .......... .......... .......... .......... .......... 21% 18.6M 0s 700K .......... .......... .......... .......... .......... 22% 13.6M 0s 750K .......... .......... .......... .......... .......... 24% 18.0M 0s 800K .......... .......... .......... .......... .......... 25% 19.1M 0s 850K .......... .......... .......... .......... .......... 27% 17.7M 0s 900K .......... .......... .......... .......... .......... 28% 5.03M 0s 950K .......... .......... .......... .......... .......... 30% 25.2M 0s 1000K .......... .......... .......... .......... .......... 31% 25.7M 0s 1050K .......... .......... .......... .......... .......... 33% 19.6M 0s 1100K .......... .......... .......... .......... .......... 34% 8.57M 0s 1150K .......... .......... .......... .......... .......... 36% 34.3M 0s 1200K .......... .......... .......... .......... .......... 37% 24.1M 0s 1250K .......... .......... .......... .......... .......... 39% 45.4M 0s 1300K .......... .......... .......... .......... .......... 41% 4.03M 0s 1350K .......... .......... .......... .......... .......... 42% 42.6M 0s 1400K .......... .......... .......... .......... .......... 44% 22.8M 0s 1450K .......... .......... .......... .......... .......... 45% 27.9M 0s 1500K .......... .......... .......... .......... .......... 47% 7.17M 0s 1550K .......... .......... .......... .......... .......... 48% 24.4M 0s 1600K .......... .......... .......... .......... .......... 50% 37.7M 0s 1650K .......... .......... .......... .......... .......... 51% 4.06M 0s 1700K .......... .......... .......... .......... .......... 53% 42.4M 0s 1750K .......... .......... .......... .......... .......... 54% 23.3M 0s 1800K .......... .......... .......... .......... .......... 56% 25.2M 0s 1850K .......... .......... .......... .......... .......... 57% 7.09M 0s 1900K .......... .......... .......... .......... .......... 59% 28.1M 0s 1950K .......... .......... .......... .......... .......... 60% 35.9M 0s 2000K .......... .......... .......... .......... .......... 62% 24.2M 0s 2050K .......... .......... .......... .......... .......... 63% 4.31M 0s 2100K .......... .......... .......... .......... .......... 65% 24.1M 0s 2150K .......... .......... .......... .......... .......... 66% 26.8M 0s 2200K .......... .......... .......... .......... .......... 68% 35.0M 0s 2250K .......... .......... .......... .......... .......... 69% 7.03M 0s 2300K .......... .......... .......... .......... .......... 71% 23.5M 0s 2350K .......... .......... .......... .......... .......... 72% 25.1M 0s 2400K .......... .......... .......... .......... .......... 74% 41.8M 0s 2450K .......... .......... .......... .......... .......... 75% 23.0M 0s 2500K .......... .......... .......... .......... .......... 77% 3.73M 0s 2550K .......... .......... .......... .......... .......... 79% 23.4M 0s 2600K .......... .......... .......... .......... .......... 80% 27.7M 0s 2650K .......... .......... .......... .......... .......... 82% 35.5M 0s 2700K .......... .......... .......... .......... .......... 83% 25.1M 0s 2750K .......... .......... .......... .......... .......... 85% 9.69M 0s 2800K .......... .......... .......... .......... .......... 86% 24.7M 0s 2850K .......... .......... .......... .......... .......... 88% 43.3M 0s 2900K .......... .......... .......... .......... .......... 89% 23.5M 0s 2950K .......... .......... .......... .......... .......... 91% 3.74M 0s 3000K .......... .......... .......... .......... .......... 92% 24.3M 0s 3050K .......... .......... .......... .......... .......... 94% 26.2M 0s 3100K .......... .......... .......... .......... .......... 95% 36.1M 0s 3150K .......... .......... .......... .......... .......... 97% 8.41M 0s 3200K .......... .......... .......... .......... .......... 98% 37.1M 0s 3250K .......... .......... .......... .......... 100% 23.3M=0.3s 2023-05-04 22:32:41 (10.6 MB/s) - ‘anaconda-33.16.7.12.tar.bz2’ saved [3369733/3369733]