如何合并两个JSON文件并仅保留指定非空对象？

需求说明 #

有两个结构相似的JSON文件，核心结构如下：

{"biosample": {"id": "xxxx"}, "wgs_qc_metrics": {"aln_metrics": {}, "variant_metrics": {}}}

需要实现：

• 仅合并指定对象：保留data1的aln_metrics和data2的variant_metrics
• 排除冗余空对象：已知data1的variant_metrics和data2的aln_metrics始终为空，输出中要排除这些空对象
• 保留data1的biosample信息，不能让data2的空aln_metrics覆盖data1的有效数据

输入文件示例 #

File1.json #

{
    "biosample": {
        "id": "NA12878"
    },
    "wgs_qc_metrics": {
        "aln_metrics": {
            "insert_size_std_deviation": "98.2",
            "mad_autosome_coverage": "0",
            "mean_autosome_coverage": "0.00",
            "mean_insert_size": "447.3",
            "pct_autosomes_15x": "0.00",
            "pct_reads_mapped": "99.63",
            "pct_reads_properly_paired": "97.9",
            "yield_bp_q30": "1996315"
        },
        "variant_metrics": {}
    }
}

File2.json #

{
    "biosample": {
        "id": "NA12878-chr14-AKT1"
    },
    "wgs_qc_metrics": {
        "aln_metrics": {},
        "variant_metrics": {
            "count_deletions": 848,
            "count_insertions": 850,
            "count_snvs": 8489,
            "ratio_heterozygous_homzygous_indel": 1.49,
            "ratio_heterozygous_homzygous_snv": 1.05,
            "ratio_insertion_deletion": 1.0,
            "ratio_transitions_transversions_snv": 2.13
        }
    }
}

之前的错误尝试 #

最初用字典解包合并wgs_qc_metrics，会导致data2的空aln_metrics覆盖data1的有效数据：

json.dump({"biosample": data1["biosample"], "wgs_qc_metrics": {**data1["wgs_qc_metrics"], **data2["wgs_qc_metrics"]}}, f, sort_keys=True, indent=4)

生成的输出中aln_metrics变成空对象，不符合预期。

后续尝试的代码存在拼写错误（varinat_metrics应为variant_metrics），且路径错误（直接取data1["aln_metrics"]而非data1["wgs_qc_metrics"]["aln_metrics"]），无法正确运行。

修正后的解决方案 #

直接基于data1的结构，将data2的有效variant_metrics替换或更新到data1的对应位置，这样既保留data1的所有有效数据，又注入data2的有效内容：

import json
import argparse

def load_json(file_path):
    with open(file_path, 'r') as f:
        return json.load(f)

def save_merged_json(data1, data2, outfile):
    # 用data2的variant_metrics替换data1的空对象
    data1['wgs_qc_metrics']['variant_metrics'] = data2['wgs_qc_metrics']['variant_metrics']
    # 也可以用update，效果一样（因为data1的variant_metrics是空的）
    # data1['wgs_qc_metrics']['variant_metrics'].update(data2['wgs_qc_metrics']['variant_metrics'])
    
    with open(outfile, "w") as f:
        json.dump(data1, f, sort_keys=True, indent=4)
        f.write("\n")

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("--input-aln-metrics", required=True, help="Path to File1.json")
    parser.add_argument("--input-variants-metrics", required=True, help="Path to File2.json")
    parser.add_argument("--output-json", required=True, help="Path to merged output JSON")
    args = parser.parse_args()
    
    aln_data = load_json(args.input_aln_metrics)
    variant_data = load_json(args.input_variants_metrics)
    save_merged_json(aln_data, variant_data, args.output_json)

代码说明 #

1. load_json函数统一处理JSON文件加载，简化代码结构
2. 在save_merged_json中，直接将data2的variant_metrics赋值给data1的对应字段，因为data1的该字段原本是空对象，赋值后直接替换为有效数据
3. 最终保存修改后的data1，自然保留了data1的biosample和aln_metrics，同时加入了data2的variant_metrics，且没有空对象残留

预期输出 #

{
    "biosample": {
        "id": "NA12878"
    },
    "wgs_qc_metrics": {
        "aln_metrics": {
            "insert_size_std_deviation": "98.2",
            "mad_autosome_coverage": "0",
            "mean_autosome_coverage": "0.00",
            "mean_insert_size": "447.3",
            "pct_autosomes_15x": "0.00",
            "pct_reads_mapped": "99.63",
            "pct_reads_properly_paired": "97.9",
            "yield_bp_q30": "1996315"
        },
        "variant_metrics": {
            "count_deletions": 848,
            "count_insertions": 850,
            "count_snvs": 8489,
            "ratio_heterozygous_homzygous_indel": 1.49,
            "ratio_heterozygous_homzygous_snv": 1.05,
            "ratio_insertion_deletion": 1.0,
            "ratio_transitions_transversions_snv": 2.13
        }
    }
}

内容的提问来源于stack exchange，提问作者user3214212