从dict bash var的值创建新的bash var

Question

我的环境创建了一个如下所示的变量：

SM_TRAINING_ENV={"additional_framework_parameters":{},"channel_input_dirs":{"training":"/opt/ml/input/data/training"},"current_host":"algo-1","framework_module":"sagemaker_tensorflow_container.training:main","hosts":["algo-1"],"hyperparameters":{"bool_param":true,"float_param":1.25,"int_param":5,"model_dir":"s3://bucket/detection/prefix/testing-2019-04-06-02-24-20-194/model","str_param":"bla"},"input_config_dir":"/opt/ml/input/config","input_data_config":{"training":{"RecordWrapperType":"None","S3DistributionType":"FullyReplicated","TrainingInputMode":"File"}},"input_dir":"/opt/ml/input","is_master":true,"job_name":"testing-2019-04-06-02-24-20-194","log_level":20,"master_hostname":"algo-1","model_dir":"/opt/ml/model","module_dir":"s3://bucket/prefix/testing-2019-04-06-02-24-20-194/source/sourcedir.tar.gz","module_name":"launcher.sh","network_interface_name":"ethwe","num_cpus":8,"num_gpus":1,"output_data_dir":"/opt/ml/output/data","output_dir":"/opt/ml/output","output_intermediate_dir":"/opt/ml/output/intermediate","resource_config":{"current_host":"algo-1","hosts":["algo-1"],"network_interface_name":"ethwe"},"user_entry_point":"launcher.sh"}

编辑Ed Morton：根据the OPs comment below，这是他试图在上面描述的样本输入：

$ SM_TRAINING_ENV='{"additional_framework_parameters":{},"channel_input_dirs":{"training":"/opt/ml/input/data/training"},"current_host":"algo-1","framework_module":"sagemaker_tensorflow_container.training:main","hosts":["algo-1"],"hyperparameters":{"bool_param":true,"float_param":1.25,"int_param":5,"model_dir":"s3://bucket/detection/prefix/testing-2019-04-06-02-24-20-194/model","str_param":"bla"},"input_config_dir":"/opt/ml/input/config","input_data_config":{"training":{"RecordWrapperType":"None","S3DistributionType":"FullyReplicated","TrainingInputMode":"File"}},"input_dir":"/opt/ml/input","is_master":true,"job_name":"testing-2019-04-06-02-24-20-194","log_level":20,"master_hostname":"algo-1","model_dir":"/opt/ml/model","module_dir":"s3://bucket/prefix/testing-2019-04-06-02-24-20-194/source/sourcedir.tar.gz","module_name":"launcher.sh","network_interface_name":"ethwe","num_cpus":8,"num_gpus":1,"output_data_dir":"/opt/ml/output/data","output_dir":"/opt/ml/output","output_intermediate_dir":"/opt/ml/output/intermediate","resource_config":{"current_host":"algo-1","hosts":["algo-1"],"network_interface_name":"ethwe"},"user_entry_point":"launcher.sh"}'

$ echo "$SM_TRAINING_ENV"
{"additional_framework_parameters":{},"channel_input_dirs":{"training":"/opt/ml/input/data/training"},"current_host":"algo-1","framework_module":"sagemaker_tensorflow_container.training:main","hosts":["algo-1"],"hyperparameters":{"bool_param":true,"float_param":1.25,"int_param":5,"model_dir":"s3://bucket/detection/prefix/testing-2019-04-06-02-24-20-194/model","str_param":"bla"},"input_config_dir":"/opt/ml/input/config","input_data_config":{"training":{"RecordWrapperType":"None","S3DistributionType":"FullyReplicated","TrainingInputMode":"File"}},"input_dir":"/opt/ml/input","is_master":true,"job_name":"testing-2019-04-06-02-24-20-194","log_level":20,"master_hostname":"algo-1","model_dir":"/opt/ml/model","module_dir":"s3://bucket/prefix/testing-2019-04-06-02-24-20-194/source/sourcedir.tar.gz","module_name":"launcher.sh","network_interface_name":"ethwe","num_cpus":8,"num_gpus":1,"output_data_dir":"/opt/ml/output/data","output_dir":"/opt/ml/output","output_intermediate_dir":"/opt/ml/output/intermediate","resource_config":{"current_host":"algo-1","hosts":["algo-1"],"network_interface_name":"ethwe"},"user_entry_point":"launcher.sh"}

如何创建一个等于SM_TRAINING_ENV["hyperparameters"]["model_dir"]值的新bash变量？

为了完整起见，我正在尝试像echo ${SM_TRAINING_ENV} | jq .这样简单的事情，并且不断尝试我所做的一切。

编辑：我被告知这个值不是一个合适的json，所以重写问题。我认为环境将它设置为python字典的值，所以jq似乎不可用。删除了json标签。也许这是awk的工作？

看起来我可以匹配我想要的值，如果我假设结构不会改变正则表达式模式s3.*?model，但不知道如何将正则表达式模式设置为新变量。

Answer 1

首先，您需要引用JSON值，以便双引号将包含在值中。

SM_TRAINING_ENV='{"additional_framework_parameters":{},"channel_input_dirs":{"training":"/opt/ml/input/data/training"},"current_host":"algo-1","framework_module":"sagemaker_tensorflow_container.training:main","hosts":["algo-1"],"hyperparameters":{"bool_param":true,"float_param":1.25,"int_param":5,"model_dir":"s3://bucket/detection/prefix/testing-2019-04-06-02-24-20-194/model","str_param":"bla"},"input_config_dir":"/opt/ml/input/config","input_data_config":{"training":{"RecordWrapperType":"None","S3DistributionType":"FullyReplicated","TrainingInputMode":"File"}},"input_dir":"/opt/ml/input","is_master":true,"job_name":"testing-2019-04-06-02-24-20-194","log_level":20,"master_hostname":"algo-1","model_dir":"/opt/ml/model","module_dir":"s3://bucket/prefix/testing-2019-04-06-02-24-20-194/source/sourcedir.tar.gz","module_name":"launcher.sh","network_interface_name":"ethwe","num_cpus":8,"num_gpus":1,"output_data_dir":"/opt/ml/output/data","output_dir":"/opt/ml/output","output_intermediate_dir":"/opt/ml/output/intermediate","resource_config":{"current_host":"algo-1","hosts":["algo-1"],"network_interface_name":"ethwe"},"user_entry_point":"launcher.sh"}'

然后，您可以使用jq实用程序来提取所需的值。

new_var=$(echo "$SM_TRAINING_ENV" | jq '.hyperparameters.model_dir')

Answer 2

这不是真正的索引，但如果订单总是相同的话，它会起作用：

NEW_VAR=$(echo $SM_TRAINING_ENV | egrep -o s3.*?model | head -1)

更喜欢不依赖于订单的东西。