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@ -1,5 +1,7 @@
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import io
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from unittest.mock import Mock, patch
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import pandas as pd
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import pytest
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from docx.oxml.text.paragraph import CT_P
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@ -187,145 +189,134 @@ def test_node_type(document_extractor_node):
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_single_sheet(mock_excel_file):
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"""Test extracting text from Excel file with single sheet."""
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# Mock DataFrame
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mock_df = Mock()
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mock_df.dropna = Mock()
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mock_df.to_markdown.return_value = "| Name | Age |\n|------|-----|\n| John | 25 |"
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"""Test extracting text from Excel file with single sheet and multiline content."""
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# Test multi-line cell
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data = {"Name\nwith\nnewline": ["John\nDoe", "Jane\nSmith"], "Age": [25, 30]}
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df = pd.DataFrame(data)
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# Mock ExcelFile
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mock_excel_instance = Mock()
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mock_excel_instance.sheet_names = ["Sheet1"]
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mock_excel_instance.parse.return_value = mock_df
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mock_excel_instance.parse.return_value = df
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mock_excel_file.return_value = mock_excel_instance
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file_content = b"fake_excel_content"
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result = _extract_text_from_excel(file_content)
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expected_manual = "| Name with newline | Age |\n| ----------------- | --- |\n\
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| John Doe | 25 |\n| Jane Smith | 30 |\n\n"
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expected = "| Name | Age |\n|------|-----|\n| John | 25 |\n\n"
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assert result == expected
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mock_excel_file.assert_called_once()
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mock_df.dropna.assert_called_once_with(how="all", inplace=True)
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mock_df.to_markdown.assert_called_once_with(index=False, floatfmt="")
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assert expected_manual == result
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mock_excel_instance.parse.assert_called_once_with(sheet_name="Sheet1")
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_multiple_sheets(mock_excel_file):
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"""Test extracting text from Excel file with multiple sheets."""
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# Mock DataFrames for different sheets
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mock_df1 = Mock()
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mock_df1.dropna = Mock()
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mock_df1.to_markdown.return_value = "| Product | Price |\n|---------|-------|\n| Apple | 1.50 |"
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"""Test extracting text from Excel file with multiple sheets and multiline content."""
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mock_df2 = Mock()
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mock_df2.dropna = Mock()
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mock_df2.to_markdown.return_value = "| City | Population |\n|------|------------|\n| NYC | 8000000 |"
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# Test multi-line cell
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data1 = {"Product\nName": ["Apple\nRed", "Banana\nYellow"], "Price": [1.50, 0.99]}
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df1 = pd.DataFrame(data1)
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data2 = {"City\nName": ["New\nYork", "Los\nAngeles"], "Population": [8000000, 3900000]}
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df2 = pd.DataFrame(data2)
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# Mock ExcelFile
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mock_excel_instance = Mock()
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mock_excel_instance.sheet_names = ["Products", "Cities"]
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mock_excel_instance.parse.side_effect = [mock_df1, mock_df2]
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mock_excel_instance.parse.side_effect = [df1, df2]
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mock_excel_file.return_value = mock_excel_instance
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file_content = b"fake_excel_content_multiple_sheets"
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result = _extract_text_from_excel(file_content)
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expected = (
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"| Product | Price |\n|---------|-------|\n| Apple | 1.50 |\n\n"
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"| City | Population |\n|------|------------|\n| NYC | 8000000 |\n\n"
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)
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assert result == expected
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expected_manual1 = "| Product Name | Price |\n| ------------ | ----- |\n\
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| Apple Red | 1.5 |\n| Banana Yellow | 0.99 |\n\n"
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expected_manual2 = "| City Name | Population |\n| --------- | ---------- |\n\
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| New York | 8000000 |\n| Los Angeles | 3900000 |\n\n"
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assert expected_manual1 in result
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assert expected_manual2 in result
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assert mock_excel_instance.parse.call_count == 2
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_empty_sheets(mock_excel_file):
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"""Test extracting text from Excel file with empty sheets."""
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# Mock empty DataFrame
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mock_df = Mock()
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mock_df.dropna = Mock()
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mock_df.to_markdown.return_value = ""
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# Empty excel
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df = pd.DataFrame()
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# Mock ExcelFile
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mock_excel_instance = Mock()
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mock_excel_instance.sheet_names = ["EmptySheet"]
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mock_excel_instance.parse.return_value = mock_df
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mock_excel_instance.parse.return_value = df
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mock_excel_file.return_value = mock_excel_instance
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file_content = b"fake_excel_empty_content"
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result = _extract_text_from_excel(file_content)
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expected = "\n\n"
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expected = "| |\n| |\n\n"
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assert result == expected
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mock_excel_instance.parse.assert_called_once_with(sheet_name="EmptySheet")
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_sheet_parse_error(mock_excel_file):
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"""Test handling of sheet parsing errors - should continue with other sheets."""
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# Mock DataFrames - one successful, one that raises exception
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mock_df_success = Mock()
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mock_df_success.dropna = Mock()
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mock_df_success.to_markdown.return_value = "| Data | Value |\n|------|-------|\n| Test | 123 |"
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# Test error
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data = {"Data": ["Test"], "Value": [123]}
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df = pd.DataFrame(data)
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# Mock ExcelFile
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mock_excel_instance = Mock()
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mock_excel_instance.sheet_names = ["GoodSheet", "BadSheet"]
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mock_excel_instance.parse.side_effect = [mock_df_success, Exception("Parse error")]
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mock_excel_instance.parse.side_effect = [df, Exception("Parse error")]
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mock_excel_file.return_value = mock_excel_instance
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file_content = b"fake_excel_mixed_content"
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result = _extract_text_from_excel(file_content)
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expected = "| Data | Value |\n|------|-------|\n| Test | 123 |\n\n"
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assert result == expected
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_file_error(mock_excel_file):
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"""Test handling of Excel file reading errors."""
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mock_excel_file.side_effect = Exception("Invalid Excel file")
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file_content = b"invalid_excel_content"
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expected_manual = "| Data | Value |\n| ---- | ----- |\n| Test | 123 |\n\n"
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with pytest.raises(Exception) as exc_info:
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_extract_text_from_excel(file_content)
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assert expected_manual == result
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# Note: The function should raise TextExtractionError, but since it's not imported in the test,
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# we check for the general Exception pattern
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assert "Failed to extract text from Excel file" in str(exc_info.value)
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assert mock_excel_instance.parse.call_count == 2
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_io_bytesio_usage(mock_excel_file):
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"""Test that BytesIO is properly used with the file content."""
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import io
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# Mock DataFrame
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mock_df = Mock()
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mock_df.dropna = Mock()
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mock_df.to_markdown.return_value = "| Test | Data |\n|------|------|\n| 1 | A |"
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# Test bytesio
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data = {"Test": [1], "Data": ["A"]}
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df = pd.DataFrame(data)
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# Mock ExcelFile
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mock_excel_instance = Mock()
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mock_excel_instance.sheet_names = ["TestSheet"]
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mock_excel_instance.parse.return_value = mock_df
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mock_excel_instance.parse.return_value = df
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mock_excel_file.return_value = mock_excel_instance
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file_content = b"test_excel_bytes"
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result = _extract_text_from_excel(file_content)
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# Verify that ExcelFile was called with a BytesIO object
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mock_excel_file.assert_called_once()
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call_args = mock_excel_file.call_args[0][0]
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assert isinstance(call_args, io.BytesIO)
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call_arg = mock_excel_file.call_args[0][0]
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assert isinstance(call_arg, io.BytesIO)
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expected = "| Test | Data |\n|------|------|\n| 1 | A |\n\n"
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assert result == expected
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expected_manual = "| Test | Data |\n| ---- | ---- |\n| 1 | A |\n\n"
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assert expected_manual == result
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_all_sheets_fail(mock_excel_file):
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"""Test when all sheets fail to parse - should return empty string."""
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# Mock ExcelFile
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mock_excel_instance = Mock()
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mock_excel_instance.sheet_names = ["BadSheet1", "BadSheet2"]
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@ -335,29 +326,6 @@ def test_extract_text_from_excel_all_sheets_fail(mock_excel_file):
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file_content = b"fake_excel_all_bad_sheets"
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result = _extract_text_from_excel(file_content)
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# Should return empty string when all sheets fail
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assert result == ""
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@patch("pandas.ExcelFile")
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def test_extract_text_from_excel_markdown_formatting(mock_excel_file):
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"""Test that markdown formatting parameters are correctly applied."""
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# Mock DataFrame
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mock_df = Mock()
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mock_df.dropna = Mock()
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mock_df.to_markdown.return_value = "| Float | Int |\n|-------|-----|\n| 123456.78 | 42 |"
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# Mock ExcelFile
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mock_excel_instance = Mock()
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mock_excel_instance.sheet_names = ["NumberSheet"]
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mock_excel_instance.parse.return_value = mock_df
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mock_excel_file.return_value = mock_excel_instance
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file_content = b"fake_excel_numbers"
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result = _extract_text_from_excel(file_content)
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# Verify to_markdown was called with correct parameters
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mock_df.to_markdown.assert_called_once_with(index=False, floatfmt="")
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expected = "| Float | Int |\n|-------|-----|\n| 123456.78 | 42 |\n\n"
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assert result == expected
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assert mock_excel_instance.parse.call_count == 2
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