Question

我有一个字典列表（MyList），在某些情况下它们将嵌套数组作为值。我试图遍历列表并在每个字典上应用递归函数（flat）以展平它们，然后将新的平面字典附加到另一个列表中。

我的问题是，生成的字典似乎建立在之前的迭代之上，并保留了之前扁平的dicts中不常见的键值对。我想在输出中为每个字典提供原始键值对。

任何指针都会非常感激。

MyList = [
    {
        "altLabel_attr": [
            "hA20",
            "IMMU-106",
            "Veltuzumab",
            "VELTUZUMAB"
        ],
        "chemblId_attr": "CHEMBL1743088",
        "description_attr": "Veltuzumab (humanized mab)",
        "hasExternalLink": False,
        "internalDocument": True,
        "isBiotherapeutic_attr": True,
        "isImageMap": False,
        "label": "VELTUZUMAB",
        "label_attr": "VELTUZUMAB",
        "prefLabel_attr": "VELTUZUMAB",
        "score": 1,
        "subType": "",
        "subjectUris": [
            "http://rdf.ebi.ac.uk/resource/chembl/molecule/CHEMBL1743088"
        ],
        "substanceType_attr": "Antibody",
        "type": "target"
    },
    {
        "altLabel_attr": [
            "PRONASE",
            "Pronase"
        ],
        "chemblId_attr": "CHEMBL2108476",
        "hasExternalLink": False,
        "internalDocument": True,
        "isImageMap": False,
        "label": "PRONASE",
        "label_attr": "PRONASE",
        "prefLabel_attr": "PRONASE",
        "score": 1,
        "subType": "",
        "subjectUris": [
            "http://rdf.ebi.ac.uk/resource/chembl/molecule/CHEMBL2108476"
        ],
        "substanceType_attr": "Enzyme",
        "type": "target"
    },
    {
        "altLabel_attr": "MDX-1342",
        "chemblId_attr": "CHEMBL2109337",
        "hasExternalLink": False,
        "internalDocument": True,
        "isBiotherapeutic_attr": True,
        "isImageMap": False,
        "label": "MDX-1342",
        "label_attr": "MDX-1342",
        "prefLabel_attr": "MDX-1342",
        "score": 1,
        "subType": "",
        "subjectUris": [
            "http://rdf.ebi.ac.uk/resource/chembl/molecule/CHEMBL2109337"
        ],
        "substanceType_attr": "Antibody",
        "type": "target"
    }
]

这是我的扁平化功能：

def flat(structure, key="", path="", flattened={}):
    if not isinstance(structure,(dict, list)):
        flattened[((path + "_") if path else "") + key] = structure
    elif isinstance(structure, list):
        for i, item in enumerate(structure):           
            flat(item,str(i), "_".join(filter(None,[path,key])), flattened)
    else:
        for new_key, value in structure.iteritems():
            flat(value, new_key, "*".join(filter(None,[path,key])), flattened)
    return flattened

ListFlatDicts = []

for i in MyList:

    i = dict(flat(i))
    ListFlatDicts.append(i)

for i in ListFlatDicts:
    print i

当前输出：

{'altLabel_attr_3': 'VELTUZUMAB', 'altLabel_attr_2': 'Veltuzumab',   'altLabel_attr_1': 'IMMU-106', 'isImageMap': 'false', 'subjectUris_0': 'CHEMBL1743088', 'subType': '', 'internalDocument': 'true', 'label_attr': 'VELTUZUMAB', 'prefLabel_attr': 'VELTUZUMAB', 'substanceType_attr': 'Antibody', 'isBiotherapeutic_attr': 'true', 'altLabel_attr_0': 'hA20', 'hasExternalLink': 'false', 'label': 'VELTUZUMAB', 'score': 1, 'description_attr': 'Veltuzumab (humanized mab)', 'chemblId_attr': 'CHEMBL1743088', 'type': 'target'}

{'altLabel_attr_3': 'VELTUZUMAB', 'altLabel_attr_2': 'Veltuzumab', 'altLabel_attr_1': 'Pronase', 'isImageMap': 'false', 'subjectUris_0': 'CHEMBL2108476', 'subType': '', 'internalDocument': 'true', 'label_attr': 'PRONASE', 'prefLabel_attr': 'PRONASE', 'substanceType_attr': 'Enzyme', 'isBiotherapeutic_attr': 'true', 'altLabel_attr_0': 'PRONASE', 'hasExternalLink': 'false', 'label': 'PRONASE', 'score': 1, 'description_attr': 'Veltuzumab (humanized mab)', 'chemblId_attr': 'CHEMBL2108476', 'type': 'target'}

{'altLabel_attr_3': 'VELTUZUMAB', 'altLabel_attr_2': 'Veltuzumab', 'altLabel_attr_1': 'Pronase', 'isImageMap': 'false', 'subjectUris_0': 'CHEMBL2109337', 'subType': '', 'internalDocument': 'true', 'label_attr': 'MDX-1342', 'prefLabel_attr': 'MDX-1342', 'substanceType_attr': 'Antibody', 'isBiotherapeutic_attr': 'true', 'altLabel_attr_0': 'PRONASE', 'hasExternalLink': 'false', 'label': 'MDX-1342', 'altLabel_attr': 'MDX-1342', 'score': 1, 'description_attr': 'Veltuzumab (humanized mab)', 'chemblId_attr': 'CHEMBL2109337', 'type': 'target'}

期望的输出：

{'altLabel_attr_3': 'VELTUZUMAB', 'altLabel_attr_2': 'Veltuzumab', 'altLabel_attr_1': 'IMMU-106', 'isImageMap': 'false', 'subjectUris_0': 'CHEMBL1743088', 'subType': '', 'internalDocument': 'true', 'label_attr': 'VELTUZUMAB', 'prefLabel_attr': 'VELTUZUMAB', 'substanceType_attr': 'Antibody', 'isBiotherapeutic_attr': 'true', 'altLabel_attr_0': 'hA20', 'hasExternalLink': 'false', 'label': 'VELTUZUMAB', 'score': 1, 'description_attr': 'Veltuzumab (humanized mab)', 'chemblId_attr': 'CHEMBL1743088', 'type': 'target'},

{'prefLabel_attr': 'PRONASE', 'substanceType_attr': 'Enzyme', 'altLabel_attr_1': 'Pronase', 'isImageMap': 'false', 'subjectUris_0': 'CHEMBL2108476', 'altLabel_attr_0': 'PRONASE', 'hasExternalLink': 'false', 'label': 'PRONASE', 'subType': '', 'score': 1, 'internalDocument': 'true', 'chemblId_attr': 'CHEMBL2108476', 'type': 'target', 'label_attr': 'PRONASE'}

{'prefLabel_attr': 'MDX-1342', 'substanceType_attr': 'Antibody', 'isImageMap': 'false', 'isBiotherapeutic_attr': 'true', 'hasExternalLink': 'false', 'label': 'MDX-1342', 'altLabel_attr': 'MDX-1342', 'subType': '', 'score': 1, 'subjectUris_0': 'CHEMBL2109337', 'internalDocument': 'true', 'chemblId_attr': 'CHEMBL2109337', 'type': 'target', 'label_attr': 'MDX-1342'}

展平列表中的每个字典

0 个答案: