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python-doc/Docs/Basic/07-error-handeling.md
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# 06 Error Handling, Linting, Formatting, and Testing in Python
This document explains how Python handles runtime errors, how to write safer code using `try / except`, and how to improve code quality using **linting**, **formatting**, and **unit testing** tools.
---
## 1. Error Handling with `try / except`
Python uses `try / except` blocks to handle runtime errors gracefully without crashing the program.
### Example
```python
def abbas(a, b):
try:
res = a / b
print(res)
except ZeroDivisionError:
print("Zero Number Detected")
except Exception as e:
print(f"Error Detected {e}")
abbas(1, 0)
```
### Explanation
* The code inside `try` is executed first.
* If no error occurs, the result is printed.
* If `b` is `0`, a `ZeroDivisionError` is raised.
* The specific `ZeroDivisionError` block runs first.
* Any other error is caught by the generic `Exception` block.
### Key Rule
* Always catch **specific exceptions first**.
* Use `Exception` only as a fallback.
---
## 2. Full `try / except` Structure
Python supports additional blocks for more control.
### Syntax
```python
try:
# code that may raise an error
except:
# runs if an error occurs
else:
# runs if no error occurs
finally:
# always runs
```
### Explanation
* `try`: code that may fail
* `except`: handles errors
* `else`: runs only if no exception occurred
* `finally`: runs no matter what (used for cleanup)
---
## 3. Linting with `pylint`
Linting analyzes code for:
* Syntax errors
* Style problems
* Bad practices
### Basic Command
```bash
pylint main.py
```
### Detailed Report
```bash
pylint --report y main.py
```
### Explanation
* `pylint` gives a score and suggestions.
* Helps maintain readable and maintainable code.
* Commonly used in professional Python projects.
---
## 4. Code Formatting with `black`
`black` is an automatic code formatter that enforces a consistent style.
### Command
```bash
black main.py
```
### Explanation
* Reformats code automatically.
* Removes style debates.
* Safe and widely used.
---
## 5. Unit Testing with `unittest`
Unit tests verify that individual parts of code behave as expected.
---
### Application Code
#### `abbas.py`
```python
def bemola(a, b):
try:
res = a / b
print(res)
except ZeroDivisionError:
print("Zero Number Detected")
except Exception as e:
print(f"Error Detected {e}")
```
---
### Test Code
#### `abbas_test.py`
```python
import unittest
from abbas import bemola
class TestAbbas(unittest.TestCase):
def test_bemola(self):
a = 10
b = 2
self.assertEqual(bemola(a, b), 5)
if __name__ == "__main__":
unittest.main()
```
---
### Explanation
#### `unittest.TestCase`
* Base class for writing test cases.
#### Test Method
```python
def test_bemola(self):
```
* Test methods must start with `test_`.
#### Assertion
```python
self.assertEqual(bemola(a, b), 5)
```
* Checks if the function returns the expected result.
---
### Important Note (Design Issue)
The function `bemola` **prints** the result but does not return it.
```python
print(res)
```
This causes the test to fail because the function returns `None`.
#### Correct Implementation
```python
def bemola(a, b):
try:
return a / b
except ZeroDivisionError:
return "Zero Number Detected"
except Exception as e:
return f"Error Detected {e}"
```
This version:
* Returns values instead of printing
* Is testable
* Follows best practices
---
## Summary
* `try / except` prevents program crashes
* `else` runs only when no error occurs
* `finally` always runs
* `pylint` improves code quality
* `black` enforces formatting
* `unittest` verifies correctness
* Functions should **return values**, not print them, when tested