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dep: bump pandas from 1.x to 2.x (#4820)
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@ -57,7 +57,7 @@ class CSVExtractor(BaseExtractor):
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docs = []
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try:
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# load csv file into pandas dataframe
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df = pd.read_csv(csvfile, error_bad_lines=False, **self.csv_args)
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df = pd.read_csv(csvfile, on_bad_lines='skip', **self.csv_args)
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# check source column exists
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if self.source_column and self.source_column not in df.columns:
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@ -26,7 +26,6 @@ sympy==1.12
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jieba==0.42.1
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celery~=5.3.6
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redis[hiredis]~=5.0.3
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openpyxl==3.1.2
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chardet~=5.1.0
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python-docx~=1.1.0
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pypdfium2~=4.17.0
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@ -51,7 +50,7 @@ dashscope[tokenizer]~=1.17.0
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huggingface_hub~=0.16.4
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transformers~=4.35.0
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tokenizers~=0.15.0
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pandas==1.5.3
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pandas[performance,excel]~=2.2.2
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xinference-client==0.9.4
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safetensors~=0.4.3
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zhipuai==1.0.7
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@ -78,7 +77,6 @@ qrcode~=7.4.2
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azure-storage-blob==12.13.0
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azure-identity==1.15.0
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lxml==5.1.0
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xlrd~=2.0.1
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pydantic~=1.10.0
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pgvecto-rs==0.1.4
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firecrawl-py==0.0.5
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62
api/tests/unit_tests/libs/test_pandas.py
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62
api/tests/unit_tests/libs/test_pandas.py
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@ -0,0 +1,62 @@
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import pandas as pd
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def test_pandas_csv(tmp_path, monkeypatch):
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monkeypatch.chdir(tmp_path)
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data = {'col1': [1, 2.2, -3.3, 4.0, 5],
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'col2': ['A', 'B', 'C', 'D', 'E']}
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df1 = pd.DataFrame(data)
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# write to csv file
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csv_file_path = tmp_path.joinpath('example.csv')
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df1.to_csv(csv_file_path, index=False)
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# read from csv file
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df2 = pd.read_csv(csv_file_path, on_bad_lines='skip')
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assert df2[df2.columns[0]].to_list() == data['col1']
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assert df2[df2.columns[1]].to_list() == data['col2']
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def test_pandas_xlsx(tmp_path, monkeypatch):
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monkeypatch.chdir(tmp_path)
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data = {'col1': [1, 2.2, -3.3, 4.0, 5],
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'col2': ['A', 'B', 'C', 'D', 'E']}
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df1 = pd.DataFrame(data)
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# write to xlsx file
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xlsx_file_path = tmp_path.joinpath('example.xlsx')
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df1.to_excel(xlsx_file_path, index=False)
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# read from xlsx file
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df2 = pd.read_excel(xlsx_file_path)
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assert df2[df2.columns[0]].to_list() == data['col1']
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assert df2[df2.columns[1]].to_list() == data['col2']
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def test_pandas_xlsx_with_sheets(tmp_path, monkeypatch):
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monkeypatch.chdir(tmp_path)
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data1 = {'col1': [1, 2, 3, 4, 5],
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'col2': ['A', 'B', 'C', 'D', 'E']}
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df1 = pd.DataFrame(data1)
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data2 = {'col1': [6, 7, 8, 9, 10],
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'col2': ['F', 'G', 'H', 'I', 'J']}
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df2 = pd.DataFrame(data2)
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# write to xlsx file with sheets
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xlsx_file_path = tmp_path.joinpath('example_with_sheets.xlsx')
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sheet1 = 'Sheet1'
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sheet2 = 'Sheet2'
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with pd.ExcelWriter(xlsx_file_path) as excel_writer:
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df1.to_excel(excel_writer, sheet_name=sheet1, index=False)
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df2.to_excel(excel_writer, sheet_name=sheet2, index=False)
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# read from xlsx file with sheets
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with pd.ExcelFile(xlsx_file_path) as excel_file:
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df1 = pd.read_excel(excel_file, sheet_name=sheet1)
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assert df1[df1.columns[0]].to_list() == data1['col1']
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assert df1[df1.columns[1]].to_list() == data1['col2']
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df2 = pd.read_excel(excel_file, sheet_name=sheet2)
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assert df2[df2.columns[0]].to_list() == data2['col1']
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assert df2[df2.columns[1]].to_list() == data2['col2']
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