# Debugging Python CLI Applications: A Pro Tip
#protip #dbt #python #cli
Navigating any Python CLI app during runtime can help while debugging.
Here's a quick guide on how to attach a debugger to a Python CLI application, using `dbt` (Data Build Tool) as an example.
## Running Dbt with Python
Instead of using the dbt command directly, you can invoke it through Python:
First figure out the module path by typing:
```bash
cat $(which dbt)
# you will see following
..
import re
import sys
from dbt.cli.main import cli
...
```
`dbt.cli.main` is the module path.
Then you can run:
```bash
python -m dbt.cli.main seed
```
Once you're able to run dbt via Python, attaching a debugger becomes straightforward. For example, to use the Python debugger (pdb), you can start your command like this:
```bash
python -m pdb -m dbt.cli.main seed
```
This approach allows you to get detailed tracebacks in case of errors. For instance:
With the debugger attached, you can step through the code execution.
```python
File "/usr/local/lib/python3.8/site-packages/dbt/cli/main.py", line 761, in seed
results = task.run()
File "/usr/local/lib/python3.8/site-packages/dbt/task/runnable.py", line 454, in run
self._runtime_initialize()
File "/usr/local/lib/python3.8/site-packages/dbt/task/compile.py", line 147, in _runtime_initialize
super()._runtime_initialize()
File "/usr/local/lib/python3.8/site-packages/dbt/task/runnable.py", line 143, in _runtime_initialize
File "/usr/local/lib/python3.8/site-packages/dbt/task/base.py", line 173, in compile_manifest
self.graph = compiler.compile(self.manifest)
File "/usr/local/lib/python3.8/site-packages/dbt/compilation.py", line 453, in compile
self.initialize()
File "/usr/local/lib/python3.8/site-packages/dbt/compilation.py", line 284, in initialize
make_directory(self.config.packages_install_path)
File "/usr/local/lib/python3.8/functools.py", line 875, in wrapper
return dispatch(args[0].__class__)(*args, **kw)
File "/usr/local/lib/python3.8/site-packages/dbt/clients/system.py", line
```
Use breakpoints to pause execution at key points and s to step into functions. This method offers a granular view of the program's flow, making it easier to identify and fix issues.
## Conclusion
By running your Python CLI app through the Python interpreter and attaching a debugger, you gain a powerful tool for navigating and debugging your code in real-time.
This technique is invaluable for developers looking to streamline their debugging process and enhance code quality.