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import os

import pandas as pd

import tempfile

import json

from app_helpers import (

analyze_sheet_for_compression_insights,

format_key_number_format,

get_format_regions,

)

# Helper function as defined in the streamlit_app.py logic (or a simplified version for testing)

def read_csv_with_multiple_encodings(file_path):

"""

Tries to read a CSV file using multiple encodings (utf-8, latin-1, iso-8859-1).

Raises the last exception if all attempts fail.

Returns a pandas DataFrame if successful.

"""

try:

df = pd.read_csv(file_path, encoding='utf-8')

return df

except UnicodeDecodeError:

# print("UTF-8 failed, trying latin-1") # Optional: for debugging test execution

try:

df = pd.read_csv(file_path, encoding='latin-1')

return df

except UnicodeDecodeError:

# print("latin-1 failed, trying iso-8859-1") # Optional: for debugging test execution

try:

df = pd.read_csv(file_path, encoding='iso-8859-1')

return df

except Exception as e:

raise e # Raise the last exception (iso-8859-1 read error)

except Exception as e:

raise e # Raise the last exception (latin-1 read error)

except Exception as e:

raise e # Raise the last exception (utf-8 read error)

# Sample CSV data encoded in 'latin-1'

sample_latin1_csv_data = "Name,City\nJules,Paris\nRené,Montréal\nBjörn,Göteborg".encode('latin-1')

def test_csv_encoding_handling():

"""

Tests the CSV encoding handling by attempting to read a latin-1 encoded CSV.

"""

# Create a temporary file

with tempfile.NamedTemporaryFile(delete=False, suffix=".csv", mode='wb') as tmp_file:

tmp_file.write(sample_latin1_csv_data)

tmp_file_path = tmp_file.name

try:

df = read_csv_with_multiple_encodings(tmp_file_path)

assert df is not None, "DataFrame should not be None"

assert not df.empty, "DataFrame should not be empty"

# Check for expected data (adjust based on actual data and column names)

# Example: Check if "René" is in the 'Name' column

assert "René" in df["Name"].values, "Expected name 'René' not found in DataFrame"

assert "Björn" in df["Name"].values, "Expected name 'Björn' not found in DataFrame"

assert "Montréal" in df["City"].values, "Expected city 'Montréal' not found in DataFrame"

assert "Göteborg" in df["City"].values, "Expected city 'Göteborg' not found in DataFrame"

# Check shape

assert df.shape == (3, 2), f"DataFrame shape mismatch. Expected (3, 2), got {df.shape}"

finally:

# Clean up the temporary file

if os.path.exists(tmp_file_path):

os.remove(tmp_file_path)

def test_format_helpers_accept_current_and_legacy_keys():

current_key = json.dumps({"type": "integer", "nfs": "#,##0"}, sort_keys=True)

legacy_key = json.dumps(

{"font": {"bold": True}, "number_format": "0.00"},

sort_keys=True,

)

current = {"formats": {current_key: ["A1:A2"]}}

legacy = {"format_regions": {legacy_key: ["B1:B2"]}}

assert get_format_regions(current) == current["formats"]

assert get_format_regions(legacy) == legacy["format_regions"]

assert format_key_number_format(json.loads(current_key)) == "#,##0"

assert format_key_number_format(json.loads(legacy_key)) == "0.00"

insights = analyze_sheet_for_compression_insights(current)

assert insights["format_analysis"]["num_unique_formats_overall"] == 1

# Example of how to run this test with pytest (if desired, not run by the agent directly)

# if __name__ == "__main__":

# pytest.main([__file__])