# Data Sharing Across Compute Environments
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Amazon SageMaker Unified Studio provides magic commands to facilitate data sharing across different compute environments. This section outlines three key commands: `%push`, `%pop`, and `%send_to_remote`.

## %push
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The `%push` command allows you to upload specified variables to your project's shared S3 storage within Amazon SageMaker Unified Studio.

```
%push <var_name>
%push <var_name1>,<var_name2>
%push -v <var_name>
%push -v <var_name> --namespace <namespace_name>
```

**Key Features:**
+ Supports multiple variable uploads when comma-separated
+ -v specifies the variable name (alternative syntax)
+ Optional --namespace argument (defaults to kernel ID)
+ Uploaded variables are accessible to all project members

**Supported Connections:**
+ Local Python connections
+ AWS Glue connections
+ AWS EMR connections

**Supported Language:** Python

## %pop
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The %pop command enables you to download specified variables from shared project Amazon S3 storage to your current compute environment.

```
%pop <var_name>
%pop <var_name1>,<var_name2>
%pop -v <var_name>
%pop -v <var_name> --namespace <namespace_name>
```

**Key Features:**
+ Supports multiple variable downloads when comma-separated
+ -v specifies the variable name (alternative syntax)
+ Optional --namespace argument (defaults to kernel ID)

**Supported Connections:**
+ Local Python connections
+ AWS Glue connections
+ AWS EMR connections

**Supported Language:** Python

## %send\_to\_remote
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The %send\_to\_remote command allows you to send a variable from the local kernel to a remote compute environment.

```
%send_to_remote --name <connection_name> --language <language> --local <local_variable_name> --remote <remote_variable_name>
```

** Key Features:**
+ Supports both Python and Scala in remote environments
+ Python remote supports dict, df, and str data types
+ Scala remote supports df and str data types

** Arguments:**
+  -l or --language: Specifies the connection language
+ -n or --name: Specifies the connection to be used
+ --local: Defines the local variable name
+ --remote or -r: Defines the remote variable name

**Supported Connections:** local Python connections

**Supported Language:**
+ Python
+ Scala

## Security considerations
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 Remember that variables uploaded using `%push` are accessible to all project members within your Amazon SageMaker Unified Studio project. Ensure that sensitive data is handled appropriately and in compliance with your organization's data governance policies.