openeuler/distroless-pip-ccThe official distroless-pip-cc docker image.
Maintained by: openEuler CloudNative SIG.
Where to get help: openEuler CloudNative SIG, openEuler.
This image provides a minimal python pip runtime with libstdc++ support.
Key Components:
Use Cases:
The tag details are as follows
| Tag | Currently | Architectures |
|---|---|---|
| 23.3.1-cc12.3.1-oe2403lts | PIP 23.3.1 and libstdc++ 12.3.1 on openEuler 24.03-LTS | amd64, arm64 |
Dockerfile Example (Python pip with libstdc++ Dependencies)
# Base image with minimal Python pip runtime and libstdc++ FROM openeuler/distroless-pip-cc:23.3.1-cc12.3.1-oe2403lts # Update CA certificates for SSL verification RUN update-ca-trust # Install Python packages with libstdc++ dependencies, pyarrow requires libstdc++ runtime RUN pip install pyarrow pandas COPY app.py /app/ CMD ["python3", "/app/app.py"]
app.py (PyArrow Data Processing Example)
import pyarrow as pa import pyarrow.parquet as pq import pandas as pd from datetime import datetime def process_data(): """Demonstrates PyArrow's core features with Arrow Tables and Parquet I/O""" data = { "timestamp": [datetime(2023, 1, 1), datetime(2023, 1, 2)], "temperature": [22.5, 23.1], "sensor_id": ["A001", "A002"] } table = pa.Table.from_pydict(data) df = table.to_pandas() print("Pandas DataFrame:") print(df) pq.write_table(table, "/app/data.parquet", compression='SNAPPY') reloaded = pq.read_table("/app/data.parquet") mean_temp = pa.compute.mean(reloaded["temperature"]) print(f"\nMean temperature: {mean_temp.as_py():.2f}°C") if __name__ == "__main__": print(f"PyArrow version: {pa.__version__}") print(f"Running with {pa.cpu_count()} CPU cores") process_data()
For implementation details, refer to the distroless-base-nonroot documentation.
If you have any questions or want to use some special features, please submit an issue or a pull request on openeuler-docker-images.


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TLS 证书验证失败
DNS 解析超时
410 错误:版本过低
402 错误:流量耗尽
身份认证失败错误
429 限流错误
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