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：根据the OPs comment below，这就是他试图在上面作为示例输入描述的内容：
$ 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"]的值的新bash变量？
为了完整起见，我尝试了诸如echo ${SM_TRAINING_ENV} | jq .之类的简单操作，并在尝试中遇到的所有错误不断出现。
编辑：：我们已得知此值不是正确的json，因此请重新输入问题。我认为环境将其设置为python字典的值，因此jq似乎不可用。删除了json标签。也许这是awk的工作？
如果我假设结构不因正则表达式模式s3.*?model而变化，但不确定如何将正则表达式模式设置为新变量，则看起来我可以匹配所需的值。
答案 0 :(得分：0)
首先，您需要引用JSON值，以便双引号将包含在该值中。
SM_TRAINING_ENV='{"additional_framework_parameters":{},"channel_input_dirs":{"training":"/opt/ml/input/data/training"},"current_host":"algo-1","framework_module":"sagemaker_tensorflow_container.training:main","hosts":["algo-1"],"hyperparameters":{"bool_param":true,"float_param":1.25,"int_param":5,"model_dir":"s3://bucket/detection/prefix/testing-2019-04-06-02-24-20-194/model","str_param":"bla"},"input_config_dir":"/opt/ml/input/config","input_data_config":{"training":{"RecordWrapperType":"None","S3DistributionType":"FullyReplicated","TrainingInputMode":"File"}},"input_dir":"/opt/ml/input","is_master":true,"job_name":"testing-2019-04-06-02-24-20-194","log_level":20,"master_hostname":"algo-1","model_dir":"/opt/ml/model","module_dir":"s3://bucket/prefix/testing-2019-04-06-02-24-20-194/source/sourcedir.tar.gz","module_name":"launcher.sh","network_interface_name":"ethwe","num_cpus":8,"num_gpus":1,"output_data_dir":"/opt/ml/output/data","output_dir":"/opt/ml/output","output_intermediate_dir":"/opt/ml/output/intermediate","resource_config":{"current_host":"algo-1","hosts":["algo-1"],"network_interface_name":"ethwe"},"user_entry_point":"launcher.sh"}'
然后，您可以使用jq实用程序提取所需的值。
new_var=$(echo "$SM_TRAINING_ENV" | jq '.hyperparameters.model_dir')
答案 1 :(得分：-1)
这并不是真正的索引，但是如果顺序总是相同的话，它就可以工作：
NEW_VAR=$(echo $SM_TRAINING_ENV | egrep -o s3.*?model | head -1)
还是会更喜欢一些不依赖顺序的东西。