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Source code for galaxy_test.base.rules_test_data



[docs]def check_example_1(hdca, dataset_populator): assert hdca["collection_type"] == "list" assert hdca["element_count"] == 2 first_dce = hdca["elements"][0] first_hda = first_dce["object"] assert first_hda["hid"] > 3
[docs]def check_example_2(hdca, dataset_populator): assert hdca["collection_type"] == "list:list" assert hdca["element_count"] == 2 first_collection_level = hdca["elements"][0] assert first_collection_level["element_type"] == "dataset_collection" second_collection_level = first_collection_level["object"] assert second_collection_level["collection_type"] == "list" assert second_collection_level["elements"][0]["element_type"] == "hda"
[docs]def check_example_3(hdca, dataset_populator): assert hdca["collection_type"] == "list" assert hdca["element_count"] == 2 first_element = hdca["elements"][0] assert first_element["element_identifier"] == "test0forward"
[docs]def check_example_4(hdca, dataset_populator): assert hdca["collection_type"] == "list:list" assert hdca["element_count"] == 2 first_collection_level = hdca["elements"][0] assert first_collection_level["element_identifier"] == "single", hdca assert first_collection_level["element_type"] == "dataset_collection" second_collection_level = first_collection_level["object"] assert "elements" in second_collection_level, hdca assert len(second_collection_level["elements"]) == 1, hdca i1_element = second_collection_level["elements"][0] assert "object" in i1_element, hdca assert "element_identifier" in i1_element assert i1_element["element_identifier"] == "i1", hdca
EXAMPLE_1 = { "rules": { "rules": [ { "type": "add_column_metadata", "value": "identifier0", } ], "mapping": [ { "type": "list_identifiers", "columns": [0], } ], }, "test_data": { "type": "list", "elements": [ { "identifier": "i1", "contents": "0", "class": "File", }, { "identifier": "i2", "contents": "1", "class": "File", }, ] }, "check": check_example_1, "output_hid": 6, } EXAMPLE_2 = { "rules": { "rules": [ { "type": "add_column_metadata", "value": "identifier0", }, { "type": "add_column_metadata", "value": "identifier0", } ], "mapping": [ { "type": "list_identifiers", "columns": [0, 1], } ], }, "test_data": { "type": "list", "elements": [ { "identifier": "i1", "contents": "0", "class": "File", }, { "identifier": "i2", "contents": "1", "class": "File", }, ] }, "check": check_example_2, "output_hid": 6, } # Flatten EXAMPLE_3 = { "rules": { "rules": [ { "type": "add_column_metadata", "value": "identifier0", }, { "type": "add_column_metadata", "value": "identifier1", }, { "type": "add_column_concatenate", "target_column_0": 0, "target_column_1": 1, } ], "mapping": [ { "type": "list_identifiers", "columns": [2], } ], }, "test_data": { "type": "list:paired", "elements": [ { "identifier": "test0", "elements": [ { "identifier": "forward", "class": "File", "contents": "TestData123" }, { "identifier": "reverse", "class": "File", "contents": "TestData123" }, ] } ] }, "check": check_example_3, "output_hid": 6, } # Nesting with group tags. EXAMPLE_4 = { "rules": { "rules": [ { "type": "add_column_metadata", "value": "identifier0", }, { "type": "add_column_group_tag_value", "value": "type", "default_value": "unused" } ], "mapping": [ { "type": "list_identifiers", "columns": [1, 0], } ], }, "test_data": { "type": "list", "elements": [ { "identifier": "i1", "contents": "0", "class": "File", "tags": ["random", "group:type:single"] }, { "identifier": "i2", "contents": "1", "class": "File", "tags": ["random", "group:type:paired"] }, { "identifier": "i3", "contents": "2", "class": "File", "tags": ["random", "group:type:paired"] }, ] }, "check": check_example_4, "output_hid": 8, }