mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-03 17:11:24 +00:00
Alex
574f96341e
The backend import package is now docsgpt, the name it will carry on PyPI; application was far too generic to install into anyone's site-packages. git mv plus a mechanical rewrite of every import, dotted string and path reference: 734 Python files, the compose files, Dockerfile, workflows, docs, setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage config, .gitignore. Behaviour is unchanged. Kept for one release: - A top-level application package whose meta-path finder resolves application.x.y to the already-imported docsgpt.x.y object, so old imports and entry points (celery -A application.app.celery, uvicorn application.asgi:asgi_app) keep working with a FutureWarning. - Celery registers every application.* task name as an alias of its docsgpt.* task on start-up, so messages queued by the previous release still run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries the previous release wrote are left unread instead of firing twice. The backend image builds from the repository root (docker build -f docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore allow-lists docsgpt/ and application/ and keeps caches, local data, .env files, the sample index files and the Dockerfile out. Compose and the image workflows point at the new context.
236 lines
8.0 KiB
Python
236 lines
8.0 KiB
Python
import pytest
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from pathlib import Path
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from unittest.mock import patch, MagicMock, mock_open
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from docsgpt.parser.file.tabular_parser import CSVParser, PandasCSVParser, ExcelParser
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@pytest.fixture
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def csv_parser():
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return CSVParser()
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@pytest.fixture
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def pandas_csv_parser():
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return PandasCSVParser()
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@pytest.fixture
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def excel_parser():
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return ExcelParser()
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def test_csv_init_parser():
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parser = CSVParser()
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assert isinstance(parser._init_parser(), dict)
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assert not parser.parser_config_set
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parser.init_parser()
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assert parser.parser_config_set
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def test_pandas_csv_init_parser():
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parser = PandasCSVParser()
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assert isinstance(parser._init_parser(), dict)
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assert not parser.parser_config_set
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parser.init_parser()
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assert parser.parser_config_set
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def test_excel_init_parser():
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parser = ExcelParser()
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assert isinstance(parser._init_parser(), dict)
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assert not parser.parser_config_set
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parser.init_parser()
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assert parser.parser_config_set
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def test_csv_parser_concat_rows(csv_parser):
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mock_data = "col1,col2\nvalue1,value2\nvalue3,value4"
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with patch("builtins.open", mock_open(read_data=mock_data)):
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result = csv_parser.parse_file(Path("test.csv"))
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assert result == "col1, col2\nvalue1, value2\nvalue3, value4"
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def test_csv_parser_separate_rows(csv_parser):
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csv_parser._concat_rows = False
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mock_data = "col1,col2\nvalue1,value2\nvalue3,value4"
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with patch("builtins.open", mock_open(read_data=mock_data)):
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result = csv_parser.parse_file(Path("test.csv"))
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assert result == ["col1, col2", "value1, value2", "value3, value4"]
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def test_pandas_csv_parser_concat_rows(pandas_csv_parser):
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mock_df = MagicMock()
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mock_df.columns.tolist.return_value = ["col1", "col2"]
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mock_df.iterrows.return_value = [
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(0, MagicMock(tolist=lambda: ["value1", "value2"])),
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(1, MagicMock(tolist=lambda: ["value3", "value4"]))
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]
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with patch("pandas.read_csv", return_value=mock_df):
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result = pandas_csv_parser.parse_file(Path("test.csv"))
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expected = "HEADERS: col1, col2\nvalue1, value2\nvalue3, value4"
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assert result == expected
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def test_pandas_csv_parser_separate_rows(pandas_csv_parser):
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pandas_csv_parser._concat_rows = False
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mock_df = MagicMock()
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mock_df.apply.return_value.tolist.return_value = ["value1, value2", "value3, value4"]
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with patch("pandas.read_csv", return_value=mock_df):
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result = pandas_csv_parser.parse_file(Path("test.csv"))
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assert result == ["value1, value2", "value3, value4"]
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def test_pandas_csv_parser_header_period(pandas_csv_parser):
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pandas_csv_parser._header_period = 2
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mock_df = MagicMock()
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mock_df.columns.tolist.return_value = ["col1", "col2"]
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mock_df.iterrows.return_value = [
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(0, MagicMock(tolist=lambda: ["value1", "value2"])),
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(1, MagicMock(tolist=lambda: ["value3", "value4"])),
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(2, MagicMock(tolist=lambda: ["value5", "value6"]))
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]
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mock_df.__len__.return_value = 3
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with patch("pandas.read_csv", return_value=mock_df):
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result = pandas_csv_parser.parse_file(Path("test.csv"))
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expected = "HEADERS: col1, col2\nvalue1, value2\nvalue3, value4\nHEADERS: col1, col2\nvalue5, value6"
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assert result == expected
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def test_excel_parser_concat_rows(excel_parser):
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mock_df = MagicMock()
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mock_df.columns.tolist.return_value = ["col1", "col2"]
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mock_df.iterrows.return_value = [
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(0, MagicMock(tolist=lambda: ["value1", "value2"])),
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(1, MagicMock(tolist=lambda: ["value3", "value4"]))
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]
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with patch("pandas.read_excel", return_value=mock_df):
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result = excel_parser.parse_file(Path("test.xlsx"))
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expected = "HEADERS: col1, col2\nvalue1, value2\nvalue3, value4"
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assert result == expected
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def test_excel_parser_separate_rows(excel_parser):
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excel_parser._concat_rows = False
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mock_df = MagicMock()
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mock_df.apply.return_value.tolist.return_value = ["value1, value2", "value3, value4"]
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with patch("pandas.read_excel", return_value=mock_df):
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result = excel_parser.parse_file(Path("test.xlsx"))
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assert result == ["value1, value2", "value3, value4"]
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def test_excel_parser_header_period(excel_parser):
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excel_parser._header_period = 1
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mock_df = MagicMock()
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mock_df.columns.tolist.return_value = ["col1", "col2"]
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mock_df.iterrows.return_value = [
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(0, MagicMock(tolist=lambda: ["value1", "value2"])),
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(1, MagicMock(tolist=lambda: ["value3", "value4"]))
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]
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mock_df.__len__.return_value = 2
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with patch("pandas.read_excel", return_value=mock_df):
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result = excel_parser.parse_file(Path("test.xlsx"))
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expected = "value1, value2\nHEADERS: col1, col2\nvalue3, value4"
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assert result == expected
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def test_csv_parser_import_error(csv_parser):
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import sys
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with patch.dict(sys.modules, {"csv": None}):
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with pytest.raises(ValueError, match="csv module is required to read CSV files"):
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csv_parser.parse_file(Path("test.csv"))
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def test_pandas_csv_parser_import_error(pandas_csv_parser):
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import sys
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with patch.dict(sys.modules, {"pandas": None}):
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with pytest.raises(ValueError, match="pandas module is required to read CSV files"):
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pandas_csv_parser.parse_file(Path("test.csv"))
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def test_pandas_csv_parser_header_period_zero(pandas_csv_parser):
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pandas_csv_parser._header_period = 0
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mock_df = MagicMock()
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mock_df.columns.tolist.return_value = ["c1", "c2"]
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mock_df.iterrows.return_value = [
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(0, MagicMock(tolist=lambda: ["v1", "v2"])),
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(1, MagicMock(tolist=lambda: ["v3", "v4"])),
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]
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with patch("pandas.read_csv", return_value=mock_df):
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result = pandas_csv_parser.parse_file(Path("f.csv"))
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assert result == "HEADERS: c1, c2\nv1, v2\nv3, v4"
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def test_pandas_csv_parser_header_period_one(pandas_csv_parser):
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pandas_csv_parser._header_period = 1
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mock_df = MagicMock()
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mock_df.columns.tolist.return_value = ["a", "b"]
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mock_df.iterrows.return_value = [
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(0, MagicMock(tolist=lambda: ["x", "y"])),
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(1, MagicMock(tolist=lambda: ["m", "n"])),
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]
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mock_df.__len__.return_value = 2
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with patch("pandas.read_csv", return_value=mock_df):
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result = pandas_csv_parser.parse_file(Path("f.csv"))
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assert result == "x, y\nHEADERS: a, b\nm, n"
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def test_pandas_csv_parser_passes_pandas_config():
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parser = PandasCSVParser(pandas_config={"sep": ";", "header": 0})
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mock_df = MagicMock()
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with patch("pandas.read_csv", return_value=mock_df) as mock_read:
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parser.parse_file(Path("conf.csv"))
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kwargs = mock_read.call_args.kwargs
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assert kwargs.get("sep") == ";"
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assert kwargs.get("header") == 0
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def test_excel_parser_custom_joiners_and_prefix(excel_parser):
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excel_parser._col_joiner = " | "
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excel_parser._row_joiner = " || "
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excel_parser._header_prefix = "COLUMNS: "
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mock_df = MagicMock()
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mock_df.columns.tolist.return_value = ["A", "B"]
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mock_df.iterrows.return_value = [
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(0, MagicMock(tolist=lambda: ["x", "y"])),
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]
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with patch("pandas.read_excel", return_value=mock_df):
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result = excel_parser.parse_file(Path("t.xlsx"))
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assert result == "COLUMNS: A | B || x | y"
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def test_excel_parser_import_error(excel_parser):
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import sys
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with patch.dict(sys.modules, {"pandas": None}):
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with pytest.raises(ValueError, match="pandas module is required to read Excel files"):
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excel_parser.parse_file(Path("test.xlsx"))
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def test_excel_numeric_headers_do_not_crash(tmp_path):
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"""Regression: a headerless/numeric xlsx gives integer column labels, and
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``", ".join(headers)`` used to raise TypeError. The XLSX size-gate delegates
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to this parser, so it must handle numeric headers."""
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from openpyxl import Workbook
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from docsgpt.parser.file.tabular_parser import ExcelParser
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wb = Workbook()
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ws = wb.active
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for i in range(5):
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ws.append([i, i * 2, i * 3])
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path = tmp_path / "numeric.xlsx"
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wb.save(str(path))
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out = ExcelParser().parse_file(path)
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assert isinstance(out, str)
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assert len(out) > 0
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