Add CSV and JSON export utilities for PSLab sensor data - #261

Please address the comments from this code review:
## Overall Comments
- Consider defining and enforcing a consistent behavior for empty input across both `export_to_csv` and `export_to_json` (e.g., both raising `ValueError` or both producing empty files), so callers don’t have to handle each exporter differently.
- It may be useful for `export_to_csv` and `export_to_json` to accept file-like objects in addition to file paths, which would make them easier to integrate with in-memory streams and higher-level APIs.
- Clarify and standardize how the exporters handle records with heterogeneous or missing keys (e.g., column ordering, default values), and ensure the implementation consistently applies that strategy.
## Individual Comments
### Comment 1
<location> `tests/test_data_export.py:4-8` </location>
<code_context>
+import pytest
+from pslab.utils.data_export import export_to_csv, export_to_json
+
+def test_export_csv_creates_file(tmp_path):
+ data = [{"a": 1, "b": 2}]
+ file_path = tmp_path / "data.csv"
+ export_to_csv(data, str(file_path))
+ assert file_path.exists()
+
+def test_export_json_creates_file(tmp_path):
</code_context>
<issue_to_address>
**suggestion (testing):** CSV export test only checks that the file exists but not that its contents are correct.
This test would still pass if the CSV had wrong headers, delimiters, or malformed rows. Please extend it to read and assert the contents—for example, that the header matches the expected columns, the row count is correct, and at least one data row matches the input—so it verifies the export logic, not just file creation.
Suggested implementation:
```python
import csv
import pytest
from pslab.utils.data_export import export_to_csv, export_to_json
def test_export_csv_creates_file(tmp_path):
 data = [{"a": 1, "b": 2}]
 file_path = tmp_path / "data.csv"
 export_to_csv(data, str(file_path))
 # File is created
 assert file_path.exists()
 # Contents are correct
 with file_path.open(newline="") as f:
 reader = csv.DictReader(f)
 # Header matches expected columns
 assert reader.fieldnames == ["a", "b"]
 rows = list(reader)
 # Row count is correct
 assert len(rows) == 1
 row = rows[0]
 # Row data matches input (compare as strings to be robust)
 assert row["a"] == str(data[0]["a"])
 assert row["b"] == str(data[0]["b"])
```
```python
def test_export_json_creates_file(tmp_path):
 data = [{"x": 10}]
 file_path = tmp_path / "data.json"
 export_to_json(data, str(file_path))
 assert file_path.exists()
```
</issue_to_address>
### Comment 2
<location> `tests/test_data_export.py:10-8` </location>
<code_context>
+ export_to_csv(data, str(file_path))
+ assert file_path.exists()
+
+def test_export_json_creates_file(tmp_path):
+ data = [{"x": 10}]
+ file_path = tmp_path / "data.json"
+ export_to_json(data, str(file_path))
+ assert file_path.exists()
+
+def test_export_empty_data_raises_error():
</code_context>
<issue_to_address>
**suggestion (testing):** JSON export test should validate the serialized content, not just file creation.
Consider mirroring the CSV test by loading the JSON (e.g., with `json.load`) and asserting the parsed structure and values match `data`. This will catch issues with encoding, formatting, or changes to the top-level container type.
Suggested implementation:
```python
import json
import pytest
from pslab.utils.data_export import export_to_csv, export_to_json
```
```python
def test_export_json_creates_file(tmp_path):
 data = [{"x": 10}]
 file_path = tmp_path / "data.json"
 export_to_json(data, str(file_path))
 assert file_path.exists()
 with file_path.open("r", encoding="utf-8") as f:
 loaded = json.load(f)
 assert loaded == data
```
</issue_to_address>