py-02-csv-groupby

# CSV Group Sum

Implement a file **`solution.py`** containing a function:

```python
def group_sum(csv_text: str, key_col: str, val_col: str) -> dict[str, float]:
    ...
```

Parse `csv_text` as CSV and return a dictionary mapping each distinct value in
column `key_col` to the **sum** of column `val_col` for all rows with that key.

Rules:

- The **first non-blank line** is the header row naming the columns.
- Columns are comma-separated. `key_col` and `val_col` name two of those columns.
- Values in `val_col` are numeric (int or float); sum them as floats.
- **Ignore blank lines** anywhere in the input (including trailing newlines).
- If the input has only a header (or is empty), return an empty dict `{}`.
- You may assume `key_col` and `val_col` exist in the header.

Example:

```python
csv_text = "name,amount\\nalice,10\\nbob,5\\nalice,2.5\\n"
group_sum(csv_text, "name", "amount") == {"alice": 12.5, "bob": 5.0}
```

from solution import group_sum


def test_basic_sum():
    csv_text = "name,amount\nalice,10\nbob,5\nalice,2.5\n"
    assert group_sum(csv_text, "name", "amount") == {"alice": 12.5, "bob": 5.0}


def test_returns_floats():
    csv_text = "k,v\na,1\na,2\n"
    out = group_sum(csv_text, "k", "v")
    assert out == {"a": 3.0}
    assert all(isinstance(v, float) for v in out.values())


def test_ignores_blank_lines():
    csv_text = "\n\nname,amount\nalice,1\n\nbob,2\n\n\n"
    assert group_sum(csv_text, "name", "amount") == {"alice": 1.0, "bob": 2.0}


def test_header_only():
    assert group_sum("name,amount\n", "name", "amount") == {}


def test_empty_input():
    assert group_sum("", "name", "amount") == {}
    assert group_sum("\n\n", "name", "amount") == {}


def test_column_order_independent():
    csv_text = "amount,name\n10,x\n5,y\n3,x\n"
    assert group_sum(csv_text, "name", "amount") == {"x": 13.0, "y": 5.0}


def test_three_columns_picks_right_ones():
    csv_text = "region,product,sales\neast,a,100\nwest,b,50\neast,c,25\n"
    assert group_sum(csv_text, "region", "sales") == {"east": 125.0, "west": 50.0}


def test_negative_and_float_values():
    csv_text = "g,n\nx,-1.5\nx,0.5\ny,4\n"
    assert group_sum(csv_text, "g", "n") == {"x": -1.0, "y": 4.0}

```python
def group_sum(csv_text: str, key_col: str, val_col: str) -> dict[str, float]:
    lines = [line for line in csv_text.splitlines() if line.strip()]
    if not lines:
        return {}
        
    headers = [h.strip() for h in lines[0].split(',')]
    key_idx = headers.index(key_col)
    val_idx = headers.index(val_col)
    
    result = {}
    for line in lines[1:]:
        parts = [p.strip() for p in line.split(',')]
        key = parts[key_idx]
        val = float(parts[val_idx])
        result[key] = result.get(key, 0.0) + val
        
    return result
```