Update Dockerfile

Author: FJiayang

Dockerfile

@@ -1,5 +1,5 @@
 # ==============================================================================
-# Dockerfile for a feature-rich, optimized code-server development environment
+# Dockerfile for a streamlined, optimized code-server development environment
 #
 # Features:
 # - Base: code-server (latest)
@@ -8,7 +8,6 @@
 # - Optimization (China):
 #   - Timezone: Asia/Shanghai
 #   - PyPI Mirror: Alibaba Cloud (for uv/pip)
-#   - Conda Mirror: TUNA (Tsinghua University)
 # - Convenience: Auto-activates conda environment in the terminal
 # ==============================================================================
 
@@ -26,13 +25,13 @@ ENV UV_DIR=/home/coder/.local
 ENV PATH=${CONDA_DIR}/bin:${UV_DIR}/bin:${PATH}
 # Set the timezone.
 ENV TZ=Asia/Shanghai
-# Configure UV/pip to use the Alibaba Cloud mirror.
+# Configure UV/pip to use the Alibaba Cloud mirror. This is the core of the optimization.
 ENV UV_INDEX_URL=https://mirrors.aliyun.com/pypi/simple
 
 # Step 4: Switch to the ROOT user for system-level installations.
 USER root
 
-# Step 5: Install system dependencies, set timezone, install and configure Conda.
+# Step 5: Install system dependencies, set timezone, and install Miniforge.
 RUN \
     # Update package lists and install necessary tools.
     apt-get update && apt-get install -y --no-install-recommends \
@@ -49,7 +48,7 @@ RUN \
     && rm miniforge.sh \
     # Give the 'coder' user ownership of the conda directory.
     && chown -R coder:coder ${CONDA_DIR} \
-    # Create symbolic links for 'conda' and 'python3' to be accessible by root for debugging.
+    # Create symbolic links for 'conda' and 'python3' for easier root access (debugging).
     && ln -s ${CONDA_DIR}/bin/conda /usr/local/bin/conda \
     && ln -s ${CONDA_DIR}/bin/python /usr/local/bin/python3 \
     # Clean up apt cache to reduce image size.
@@ -59,28 +58,16 @@ RUN \
 # Step 6: Switch back to the standard, non-root 'coder' user.
 USER coder
 
-# Step 7: As the 'coder' user, configure tools and create the development environment.
+# Step 7: As the 'coder' user, install 'uv' and create the development environment.
 RUN \
     # Install 'uv' (the fast Python package manager).
     curl -LsSf https://astral.sh/uv/install.sh | sh && \
     \
-    # Configure Conda to use Tsinghua University mirrors for faster package downloads.
-    # We add our desired channels first.
-    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/conda-forge/ && \
-    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/ && \
-    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r/ && \
-    conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2/ && \
-    # --- [ THE FIX IS HERE ] ---
-    # Then, we tell conda to NOT use the built-in 'defaults' channels.
-    conda config --set nodefaults true && \
-    # (Optional) We can verify the channel configuration.
-    conda config --set show_channel_urls true && \
-    \
-    # Create the default conda environment. This will be fast due to the mirror.
+    # Create the default conda environment using Conda's default channels.
     conda create -n py${PYTHON_VERSION} python=${PYTHON_VERSION} -y && \
     \
     # Pre-install common Python packages into the new environment using 'uv'.
-    # This will use the Alibaba Cloud PyPI mirror configured via ENV var.
+    # This will automatically and quickly use the Alibaba Cloud PyPI mirror.
     uv pip install --python=${CONDA_DIR}/envs/py${PYTHON_VERSION}/bin/python \
         numpy \
         pandas \
@@ -92,5 +79,4 @@ RUN \
     # Configure the shell to automatically activate this environment on login.
     echo "conda activate py${PYTHON_VERSION}" >> ~/.bashrc
 
-# Step 8: The base image's entrypoint will automatically start code-server.
-# All our PATH and environment variable configurations will be inherited by the application.
+# Step 8: The base image's entrypoint will start code-server.