Tests

This section outlines best practices for writing unit tests in the search_query package. Tests are primarily written using pytest and are organized by module (parser, linter, translator, etc.).

To run all tests:

pytest test

Test Types

1. Tokenization Tests

   • Purpose: Verify that a query string is tokenized correctly into expected tokens.

   • Tools: pytest.mark.parametrize for multiple cases.

   • Example:

   @pytest.mark.parametrize(
      "query_str, expected_tokens",
      [
         (
               "AB=(Health)",
               [
                  Token(value="AB=", type=TokenTypes.FIELD, position=(0, 3)),
                  Token(value="(", type=TokenTypes.PARENTHESIS_OPEN, position=(3, 4)),
                  Token(value="Health", type=TokenTypes.SEARCH_TERM, position=(4, 10)),
                  Token(value=")", type=TokenTypes.PARENTHESIS_CLOSED, position=(10, 11)),
               ],
         )
      ],
   )
   def test_tokenization(query_str: str, expected_tokens: list) -> None:
      print(
         f"Run query parser for: \n  {Colors.GREEN}{query_str}{Colors.END}\n--------------------\n"
      )
   
      parser = XYParser(query_str)
      parser.tokenize()
   
      assert parser.tokens == expected_tokens, (
         f"\nExpected: {expected_tokens}\nGot     : {parser.tokens}"
      )
   

2. Linter Message Tests

   • Purpose: Verify that the linter raises expected warnings or errors for malformed input.

   • Approach: - Catch exceptions where necessary. - Use structured comparison with linter messages.

   • Example:

   @pytest.mark.parametrize(
      "query_str, search_field_general, messages",
      [
         (
               '("health tracking" OR "remote monitoring") AND (("mobile application" OR "wearable device")',
               "Title",
               [
                  {
                     "code": "F1001",
                     "label": "unbalanced-parentheses",
                     "message": "Parentheses are unbalanced in the query",
                     "is_fatal": True,
                     "position": (47, 48),
                     "details": "Unbalanced opening parenthesis",
                  },
                  {
                     "code": "E0001",
                     "label": "search-field-missing",
                     "message": "Expected search field is missing",
                     "is_fatal": False,
                     "position": (-1, -1),
                     "details": "Search fields should be specified in the query instead of the search_field_general",
                  },
               ],
         ),
         # add more cases here as needed...
      ],
   )
   def test_linter(query_str: str, search_field_general: str, messages: list[dict]) -> None:
   
      parser = XYParser(query_str, search_field_general=search_field_general)
      try:
         parser.parse()
      except SearchQueryException:
         pass  # Errors are expected in some cases
   
      actual_messages = parser.linter.messages
      if actual_messages != messages:
         print("Expected:")
         for m in messages:
               print(f"  - {m}")
         print("Got:")
         for m in actual_messages:
               print(f"  - {m}")
   
      assert actual_messages == messages
   

3. Translation Tests

   • Purpose: Confirm that parsing + serialization results in the expected generic or structured query string.

Example:

@pytest.mark.parametrize(
   "query_string, expected_translation",
   [
         ("TS=(eHealth) AND TS=(Review)",
         "AND[eHealth[TS=], Review[TS=]]"),
   ],
)
def test_parser_translation(query_string, expected_translation):
   parser = XYParser(query_string)
   query_tree = parser.parse()
   assert query_tree.to_generic_string() == expected_translation

Note

• Use helper functions like parser.print_tokens() to ease debugging.

• Use assert … == … with fallbacks for print(…) for inspection.