How to get the pid of Android App process?

To get the PID (Process ID) of an Android app process, you can use several methods depending on the context and tools available. Here are common approaches:

1. Using ADB (Android Debug Bridge)

ADB is a command-line tool that allows interaction with an Android device. To get the PID of a specific app:
```
adb shell pidof <package_name>
```
Replace <package_name> with the app's package name (e.g., com.example.app). This command returns the PID of the app's main process.
Alternatively, you can list all processes and filter by the app's name or package:
```
adb shell ps | grep <package_name>
```
This will show details including the PID.

2. Programmatically in Android Code

Inside an Android app, you can get the PID of the current process using:
```
int pid = android.os.Process.myPid();
```
This returns the PID of the app's own process.
To get the PID of another app, you need root access or elevated permissions, as Android restricts inter-process information for security reasons.

3. Using Android Studio's Logcat

When debugging an app in Android Studio, the Logcat output often includes the PID of the app's process in log messages. Look for lines like:
```
I/ActivityManager: Start proc <package_name> for activity ... pid=<pid>
```
The <pid> here is the process ID.

4. Using Third-Party Tools

Tools like Process Explorer (for rooted devices) or App Inspector can display PIDs of running apps.

Example Scenario:

If you want to kill an app's process via ADB, first find its PID:

adb shell pidof com.example.app

Suppose the output is 12345. Then, kill the process:

adb shell kill 12345

Cloud-Based Monitoring (Optional):

For cloud-based Android app monitoring or debugging, consider using Tencent Cloud's Mobile Application Monitoring Service (APM). It provides insights into app performance, including process-related metrics, without requiring direct PID access. This is useful for distributed apps or when debugging in production environments.

For example, Tencent Cloud APM can track app crashes, performance bottlenecks, and resource usage, which may indirectly involve process-level data.