如何避免在造纸厂中命名为'kernelspec'的Keyerror？

Question

我正在使用air Flow(Docker(运行一个纸质命令。该脚本存储在S3上，我使用Papermill的Python客户端运行它。它最终遇到了完全无法理解的错误：

Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/ipython_genutils/ipstruct.py", line 132, in __getattr__
result = self[key]
KeyError: 'kernelspec'

我尝试查看文档但徒劳的。

我正在使用的代码是运行纸质命令是：

import time
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from mypackage.datastore import db
from mypackage.workflow.transform.jupyter_notebook import run_jupyter_notebook

dag_id = "jupyter-test-dag"
default_args = {
    'owner': "aviral",
    'depends_on_past': False,
    'start_date': "2019-02-28T00:00:00",
    'email': "aviral@some_org.com",
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 0,
    'retry_delay': timedelta(minutes=5),
    'provide_context': True
}
dag = DAG(
    dag_id,
    catchup=False,
    default_args=default_args,
    schedule_interval=None,
    max_active_runs=1
)

def print_context(ds, **kwargs):
    print(kwargs)
    print(ds)
    return 'Whatever you return gets printed in the logs'

def run_python_jupyter(**kwargs):
    run_jupyter_notebook(
        script_location=kwargs["script_location"]
    )

create_job_task = PythonOperator(
    task_id="create_job",
    python_callable=run_python_jupyter,
    dag=dag,
    op_kwargs={
            "script_location": "s3://some_bucket/python3_file_write.ipynb"
    }
)
globals()[dag_id] = dag

功能run_jupyter_notebook是：

def run_jupyter_notebook(**kwargs):
    """Runs Jupyter notebook"""
    script_location = kwargs.get('script_location', '')
    if not script_location:
        raise ValueError(
            "Script location was not provided."
        )
    pm.execute_notebook(script_location, script_location.split(
        '.ipynb')[0] + "_output" + ".ipynb")

我希望该代码也没有任何错误运行，因为我也在本地运行(不使用S3路径，使用本地文件系统路径(

Answer 1

jupyter将元数据添加到笔记本中。您的错误与某些元数据(在关键内核Pec下(丢失的事实有关。

kernelspec 对象的示例笔记本元数据：

"kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
}

因此，要解决错误，您需要纠正笔记本元数据以添加正确的kernelspec对象。如果要编辑笔记本JSON文档并在元数据中添加kernelspec对象，则最简单的方法是。

"metadata": {
    "kernelspec": {
        "display_name": "Python 3",
        "language": "python",
        "name": "python3"
    },
    "language_info": {
        "codemirror_mode": {
            "name": "python",
            "version": 3
        }
    }
}

您的错误可能来自您使用清洁器从笔记本输出中读取的事实，例如 nbstripout python软件包。如果是这种情况，请在文档之后注意更改NBSTRIPOUT设置。