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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,
}