# MMSciCode env reconstruction on the domestic server This bundle reconstructs the 204 MMSciCode conda envs on a domestic Chinese server using mirror sources (no need to download the 165 GB tarball repo). It then packs each env into a tarball and builds a Docker image per env. ## Inputs (from HF: `MMSciCode/mmsci-envs-tmp`) ``` configs/ / env.yml # conda env create -f explicit.txt # conda list --explicit --md5 (URL-pinned fallback) pip-freeze.txt # raw pip freeze from local env pip-clean.txt # pip-freeze with conda-built file:// stripped editable.txt # tab-separated: \t meta.json # python ver, has_cuda hint, editable_count editable_bundle.tar.gz # only present if any env had editable installs ``` ## Domestic-server prerequisites - conda (or miniconda) installed; conda >= 22.x - `mamba` from the base env: `conda install -n base -c conda-forge mamba conda-pack` - Docker (with `nvidia-docker` runtime if envs need GPU) - ~200 GB free disk for staging tarballs + ~300 GB for Docker images ## Step 1 — configure mirrors ```bash cp configs_repo/remote/condarc.template ~/.condarc mkdir -p ~/.config/pip cp configs_repo/remote/pip.conf.template ~/.config/pip/pip.conf ``` ## Step 2 — fetch the artifacts ```bash # example using huggingface_hub with HF_ENDPOINT=https://hf-mirror.com if needed huggingface-cli download MMSciCode/mmsci-envs-tmp \ --repo-type dataset \ --local-dir /home/mmsci/repo \ --include 'configs/**' 'editable_bundle.tar.gz' cd /home/mmsci/repo [ -f editable_bundle.tar.gz ] && tar -xzf editable_bundle.tar.gz # -> editable_sources/ ``` ## Step 3 — build all envs (parallel) and pack each as a tarball ```bash CONFIGS_DIR=/home/mmsci/repo/configs \ OUT_DIR=/home/mmsci/conda_packs \ EDITABLE_SRC=/home/mmsci/repo/editable_sources \ MAMBA_BIN=/opt/conda/bin/mamba \ CONDA_PACK=/opt/conda/bin/conda-pack \ JOBS=4 \ bash /home/mmsci/configs_repo/remote/build_envs_remote.sh ``` Outputs: - `$OUT_DIR/.tar.gz` — per-env conda-pack tarball - `$OUT_DIR/build.state.tsv` — per-env status (done/skip/fail) - `$OUT_DIR/build.failed.txt` — failed envs (re-run script to retry; idempotent) - `$OUT_DIR/_logs/.log` — per-env mamba + pack log Expect 5–15% of envs to fail on first pass (mirror gaps, conda-pack errors, editable misses). Inspect the failed logs and either: - Adjust env.yml (drop the offending pin, add a missing channel), or - Fall back to the original tarball from `MMSciCode/mmsci-envs-tmp` root: `huggingface-cli download MMSciCode/mmsci-envs-tmp --include '.tar.gz' --local-dir $OUT_DIR` ## Step 4 — build Docker images Get the Dockerfile (from the source repo or the HF `docker_build/` upload): ```bash PACKS_DIR=/home/mmsci/conda_packs \ DOCKERFILE=/home/mmsci/configs_repo/Dockerfile.conda-env \ IMAGE_PREFIX=mmsci-py \ JOBS=2 \ bash /home/mmsci/configs_repo/remote/build_docker_images.sh ``` Each env -> `mmsci-py-:latest`. The Dockerfile is the unmodified `Dockerfile.conda-env` — it only does `COPY tarball; tar -xzf; conda-unpack`, so build time per image is whatever your disk can write the tarball at (~30s–2min per image). ## Troubleshooting **`PackageNotFoundError` during `mamba env create`** The Tsinghua/Aliyun mirrors don't have every conda-forge package. Try: ```bash mamba env create -n -f configs//env.yml \ --override-channels -c conda-forge -c defaults ``` If still missing, the explicit URL list often works: ```bash conda create -n --file configs//explicit.txt ``` (URLs point to anaconda.org which is reachable but slow; consider setting `CONDA_SUBDIR=linux-64`.) **`pip install` connection errors** Confirm `~/.config/pip/pip.conf` is in effect: `pip config list`. Some git+https URLs in `pip-freeze.txt` may need a proxy; consider running the build under `https_proxy=...` if you have a corporate proxy. **`conda-pack` editable-packages error** build_envs_remote.sh passes `--ignore-editable-packages` so this should not happen. If it does, the env has an editable install that wasn't recorded in `editable.txt` — re-export from the source machine.