$ git clone -n https://gitee.com/src-anolis-os/anaconda.git /var/lib/mock/dist-an8.8-build-274853-64257/root/chroot_tmpdir/scmroot/anaconda Cloning into '/var/lib/mock/dist-an8.8-build-274853-64257/root/chroot_tmpdir/scmroot/anaconda'... $ git reset --hard origin/a8 HEAD is now at 3b3b048 anaconda: fix multi variants error $ git lfs pull $ wget -O anaconda-33.16.8.9.tar.bz2 http://build.openanolis.cn/kojifiles/upstream-source/anaconda-33.16.8.9.tar.bz2.7d5daf2ca4f438f6d68082c0631c963a --2023-06-15 11:13:30-- http://build.openanolis.cn/kojifiles/upstream-source/anaconda-33.16.8.9.tar.bz2.7d5daf2ca4f438f6d68082c0631c963a Resolving build.openanolis.cn (build.openanolis.cn)... 172.16.0.137 Connecting to build.openanolis.cn (build.openanolis.cn)|172.16.0.137|:80... connected. HTTP request sent, awaiting response... 200 OK Length: 3399040 (3.2M) [application/x-bzip2] Saving to: ‘anaconda-33.16.8.9.tar.bz2’ 0K .......... .......... .......... .......... .......... 1% 17.9M 0s 50K .......... .......... .......... .......... .......... 3% 36.1M 0s 100K .......... .......... .......... .......... .......... 4% 18.4M 0s 150K .......... .......... .......... .......... .......... 6% 34.8M 0s 200K .......... .......... .......... .......... .......... 7% 18.5M 0s 250K .......... .......... .......... .......... .......... 9% 2.20M 0s 300K .......... .......... .......... .......... .......... 10% 35.7M 0s 350K .......... .......... .......... .......... .......... 12% 35.9M 0s 400K .......... .......... .......... .......... .......... 13% 36.6M 0s 450K .......... .......... .......... .......... .......... 15% 36.3M 0s 500K .......... .......... .......... .......... .......... 16% 36.6M 0s 550K .......... .......... .......... .......... .......... 18% 36.3M 0s 600K .......... .......... .......... .......... .......... 19% 35.9M 0s 650K .......... .......... .......... .......... .......... 21% 37.2M 0s 700K .......... .......... .......... .......... .......... 22% 367M 0s 750K .......... .......... .......... .......... .......... 24% 38.2M 0s 800K .......... .......... .......... .......... .......... 25% 35.9M 0s 850K .......... .......... .......... .......... .......... 27% 37.2M 0s 900K .......... .......... .......... .......... .......... 28% 766M 0s 950K .......... .......... .......... .......... .......... 30% 36.8M 0s 1000K .......... .......... .......... .......... .......... 31% 37.2M 0s 1050K .......... .......... .......... .......... .......... 33% 738M 0s 1100K .......... .......... .......... .......... .......... 34% 37.5M 0s 1150K .......... .......... .......... .......... .......... 36% 56.8M 0s 1200K .......... .......... .......... .......... .......... 37% 92.8M 0s 1250K .......... .......... .......... .......... .......... 39% 36.9M 0s 1300K .......... .......... .......... .......... .......... 40% 743M 0s 1350K .......... .......... .......... .......... .......... 42% 35.2M 0s 1400K .......... .......... .......... .......... .......... 43% 741M 0s 1450K .......... .......... .......... .......... .......... 45% 37.4M 0s 1500K .......... .......... .......... .......... .......... 46% 83.2M 0s 1550K .......... .......... .......... .......... .......... 48% 66.5M 0s 1600K .......... .......... .......... .......... .......... 49% 75.4M 0s 1650K .......... .......... .......... .......... .......... 51% 71.0M 0s 1700K .......... .......... .......... .......... .......... 52% 82.5M 0s 1750K .......... .......... .......... .......... .......... 54% 64.8M 0s 1800K .......... .......... .......... .......... .......... 55% 81.4M 0s 1850K .......... .......... .......... .......... .......... 57% 63.3M 0s 1900K .......... .......... .......... .......... .......... 58% 87.9M 0s 1950K .......... .......... .......... .......... .......... 60% 72.4M 0s 2000K .......... .......... .......... .......... .......... 61% 299M 0s 2050K .......... .......... .......... .......... .......... 63% 85.7M 0s 2100K .......... .......... .......... .......... .......... 64% 65.1M 0s 2150K .......... .......... .......... .......... .......... 66% 110M 0s 2200K .......... .......... .......... .......... .......... 67% 288M 0s 2250K .......... .......... .......... .......... .......... 69% 64.9M 0s 2300K .......... .......... .......... .......... .......... 70% 90.9M 0s 2350K .......... .......... .......... .......... .......... 72% 61.7M 0s 2400K .......... .......... .......... .......... .......... 73% 674M 0s 2450K .......... .......... .......... .......... .......... 75% 98.2M 0s 2500K .......... .......... .......... .......... .......... 76% 60.6M 0s 2550K .......... .......... .......... .......... .......... 78% 102M 0s 2600K .......... .......... .......... .......... .......... 79% 509M 0s 2650K .......... .......... .......... .......... .......... 81% 64.4M 0s 2700K .......... .......... .......... .......... .......... 82% 94.6M 0s 2750K .......... .......... .......... .......... .......... 84% 592M 0s 2800K .......... .......... .......... .......... .......... 85% 40.4M 0s 2850K .......... .......... .......... .......... .......... 87% 673M 0s 2900K .......... .......... .......... .......... .......... 88% 556M 0s 2950K .......... .......... .......... .......... .......... 90% 766M 0s 3000K .......... .......... .......... .......... .......... 91% 38.6M 0s 3050K .......... .......... .......... .......... .......... 93% 578M 0s 3100K .......... .......... .......... .......... .......... 94% 778M 0s 3150K .......... .......... .......... .......... .......... 96% 47.6M 0s 3200K .......... .......... .......... .......... .......... 97% 224M 0s 3250K .......... .......... .......... .......... .......... 99% 731M 0s 3300K .......... ......... 100% 591M=0.08s 2023-06-15 11:13:30 (42.8 MB/s) - ‘anaconda-33.16.8.9.tar.bz2’ saved [3399040/3399040]