mirror of
https://github.com/kuhyx/testsAndMisc.git
synced 2026-07-04 22:03:18 +02:00
Krzysztof kuhy Rudnicki
2545d72710
- Add comprehensive tests for all packages (3572 tests, 100% branch coverage) - Split oversized test files to stay under 500-line limit - Add per-file ruff ignores for test-appropriate suppressions - Fix _cache_decks.py to properly convert JSON lists to tuples - Add session-scoped conftest fixture for logging handler cleanup (Python 3.14) - Update ruff pre-commit hook to v0.15.2 - Add codespell ignore words for test data - Add generated output files to .gitignore
366 lines
12 KiB
Python
366 lines
12 KiB
Python
"""Tests for _generation.generate_flashcards_inverse (lines 323-379)."""
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from __future__ import annotations
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from typing import TYPE_CHECKING
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from unittest.mock import patch
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import pytest
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from python_pkg.word_frequency._generation import generate_flashcards_inverse
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from python_pkg.word_frequency._types import FlashcardOptions
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if TYPE_CHECKING:
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from pathlib import Path
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_GEN = "python_pkg.word_frequency._generation"
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class TestGenerateFlashcardsInverse:
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"""Tests for generate_flashcards_inverse."""
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def test_basic_flow(self, tmp_path: Path) -> None:
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"""Cover the happy path through all branches."""
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fp = tmp_path / "t.txt"
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fp.write_text("hello world", encoding="utf-8")
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inverse_output = (
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"INVERSE_MODE\n"
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"Longest excerpt: 5 words\n"
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'Excerpt: "hello world foo bar baz"\n'
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"Max rank used: 3\n"
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"\nVOCAB_DUMP_START\nhello;1\nworld;2\nfoo;3\nVOCAB_DUMP_END\n"
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)
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value=inverse_output,
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello world foo bar baz",
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5,
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3,
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[("hello", 1), ("world", 2), ("foo", 3)],
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),
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),
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patch(
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f"{_GEN}.detect_language",
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return_value="en",
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),
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck content",
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),
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):
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content, excerpt, length, n_words, max_rank = generate_flashcards_inverse(
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fp,
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3,
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FlashcardOptions(source_lang="en"),
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)
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assert content == "deck content"
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assert excerpt == "hello world foo bar baz"
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assert length == 5
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assert n_words == 3
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assert max_rank == 3
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def test_default_options(self, tmp_path: Path) -> None:
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"""Cover options=None branch (line 323)."""
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fp = tmp_path / "t.txt"
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fp.write_text("hello world", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello world",
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2,
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2,
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[("hello", 1), ("world", 2)],
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),
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),
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patch(
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f"{_GEN}.detect_language",
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return_value="en",
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),
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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),
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):
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result = generate_flashcards_inverse(fp, 2)
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assert result[0] == "deck"
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def test_excerpt_length_zero_raises(self, tmp_path: Path) -> None:
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"""Cover the excerpt_length == 0 ValueError branch."""
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fp = tmp_path / "t.txt"
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fp.write_text("text", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=("", 0, 0, []),
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),
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pytest.raises(ValueError, match="No valid excerpt found"),
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):
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generate_flashcards_inverse(fp, 5, FlashcardOptions(source_lang="en"))
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def test_no_vocab_words_raises(self, tmp_path: Path) -> None:
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"""Cover the 'not all_vocab_words' ValueError branch."""
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fp = tmp_path / "t.txt"
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fp.write_text("text", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=("hello", 1, 1, []),
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),
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pytest.raises(ValueError, match="No vocabulary returned"),
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):
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generate_flashcards_inverse(fp, 5, FlashcardOptions(source_lang="en"))
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def test_include_context(self, tmp_path: Path) -> None:
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"""Cover include_context=True path (context generation)."""
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fp = tmp_path / "t.txt"
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fp.write_text("hello world foo", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello world",
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2,
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2,
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[("hello", 1), ("world", 2)],
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),
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),
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patch(
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f"{_GEN}.detect_language",
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return_value="en",
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),
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patch(
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f"{_GEN}.find_word_contexts",
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return_value={"hello": "...hello..."},
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) as mock_ctx,
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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),
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):
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generate_flashcards_inverse(
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fp,
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2,
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FlashcardOptions(
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source_lang="en",
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include_context=True,
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),
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)
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mock_ctx.assert_called_once()
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def test_include_context_rereads_when_empty(self, tmp_path: Path) -> None:
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"""Cover the 'if not text' re-read branch inside context."""
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fp = tmp_path / "t.txt"
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fp.write_text("", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello",
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1,
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1,
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[("hello", 1)],
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),
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),
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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),
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patch(f"{_GEN}.find_word_contexts", return_value={}),
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patch(f"{_GEN}.read_file", return_value="") as mock_read,
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):
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generate_flashcards_inverse(
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fp,
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1,
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FlashcardOptions(
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source_lang="en",
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include_context=True,
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),
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)
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# read_file called twice: once for initial text, once for context
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assert mock_read.call_count == 2
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def test_auto_detect_language(self, tmp_path: Path) -> None:
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"""Cover source_lang=None auto-detection path."""
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fp = tmp_path / "t.txt"
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fp.write_text("hola mundo", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hola mundo",
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2,
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2,
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[("hola", 1), ("mundo", 2)],
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),
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),
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patch(
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f"{_GEN}.detect_language",
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return_value="es",
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) as mock_detect,
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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),
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):
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generate_flashcards_inverse(fp, 2, FlashcardOptions(source_lang=None))
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mock_detect.assert_called_once()
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def test_custom_deck_name(self, tmp_path: Path) -> None:
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"""Cover deck_name from options."""
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fp = tmp_path / "t.txt"
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fp.write_text("hello", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello",
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1,
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1,
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[("hello", 1)],
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),
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),
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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) as mock_deck,
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):
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generate_flashcards_inverse(
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fp,
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1,
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FlashcardOptions(
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source_lang="en",
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deck_name="MyDeck",
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),
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)
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call_kwargs = mock_deck.call_args
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deck_input = call_kwargs[0][0]
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assert deck_input.deck_name == "MyDeck"
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def test_default_deck_name(self, tmp_path: Path) -> None:
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"""Cover auto-generated deck_name when none provided."""
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fp = tmp_path / "sample.txt"
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fp.write_text("hello", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello",
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1,
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1,
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[("hello", 1)],
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),
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),
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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) as mock_deck,
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):
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generate_flashcards_inverse(
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fp,
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5,
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FlashcardOptions(source_lang="en", deck_name=None),
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)
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deck_input = mock_deck.call_args[0][0]
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assert deck_input.deck_name == "sample_top5"
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def test_excerpt_words_filtering(self, tmp_path: Path) -> None:
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"""Cover the excerpt_words filtering logic."""
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fp = tmp_path / "t.txt"
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fp.write_text("hello world", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello",
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1,
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2,
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[("hello", 1), ("world", 2), ("foo", 3)],
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),
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),
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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) as mock_deck,
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):
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generate_flashcards_inverse(fp, 3, FlashcardOptions(source_lang="en"))
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call_kwargs = mock_deck.call_args
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excerpt_words = call_kwargs[1]["excerpt_words"]
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# Only "hello" is in the excerpt, not "world" or "foo"
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assert len(excerpt_words) == 1
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assert excerpt_words[0][0] == "hello"
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def test_no_translate(self, tmp_path: Path) -> None:
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"""Cover no_translate option."""
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fp = tmp_path / "t.txt"
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fp.write_text("text", encoding="utf-8")
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with (
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patch(
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f"{_GEN}.run_vocabulary_curve_inverse",
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return_value="out",
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),
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patch(
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f"{_GEN}.parse_inverse_mode_output",
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return_value=(
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"hello",
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1,
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1,
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[("hello", 1)],
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),
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),
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patch(
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f"{_GEN}.generate_anki_deck",
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return_value="deck",
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) as mock_deck,
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):
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generate_flashcards_inverse(
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fp,
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1,
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FlashcardOptions(
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source_lang="en",
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no_translate=True,
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),
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)
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assert mock_deck.call_args[1]["no_translate"] is True
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