在Python中合并多个JSON文件的问题
呼延鹏云
问题内容：
问题答案：
我正在尝试将多个JSON文件组合到Ubuntu平台中。例如，来自两个文件的数据如下：
文件_1
{
"artist":"Gob",
"timestamp":"2011-08-09 01:59:41.352247",
"similars":[
[
"TRTOVWD128F92F4227",
1
],
[
"TRUXNUD128F92F41D0",
0.97294099999999994
],
[
"TRNNOJO128F42992E9",
0.073926900000000004
],
[
"TRGZHTT128F423B2A4",
0.068387699999999996
],
[
"TRGYKYD128F42625F6",
0.065579700000000005
],
[
"TRGIWHY128F42625F5",
0.064063700000000001
],
[
"TRJCJTX128F930CACE",
0.063140100000000005
],
[
"TRMYNWT128F426254B",
0.0613825
],
[
"TRRQOJI128F428C865",
0.061121599999999998
],
[
"TRBNYHM128F428A569",
0.061121599999999998
],
[
"TRDLOYE128F4241E72",
0.060951900000000003
],
[
"TRNRVEW12903CBA24F",
0.060332700000000003
],
[
"TRKKIPG12903CBA083",
0.060155
],
[
"TRZHTGP128F428A63B",
0.059873599999999999
],
[
"TRKQSGZ128F428A851",
0.059873599999999999
],
[
"TRTOPDF128F42AD88A",
0.059687799999999999
],
[
"TRIWOPM128F4241E53",
0.058958900000000002
],
[
"TRCCJUW128F14652DB",
0.057935
],
[
"TRERDDF128F428ECC4",
0.057566600000000002
],
[
"TROKWNN128F421A3D8",
0.057379800000000002
],
[
"TRWGOOK128F42AE765",
0.057125000000000002
],
[
"TRFMNKP128F428ADC0",
0.056875099999999998
],
[
"TRDMLZT128F42A01A8",
0.055808900000000002
],
[
"TRGCJVM128E0780E48",
0.0547389
],
[
"TRRXGAY128F14652D7",
0.0538065
],
[
"TRIPEHH128F1462DFF",
0.052843000000000001
],
[
"TRDUOIP128F147D5A7",
0.051851500000000002
],
[
"TRZCHHD12903CC80A1",
0.051251699999999997
],
[
"TRFDDQS128F426243F",
0.051018300000000003
],
[
"TRZDKAR128F42591B8",
0.050740899999999999
],
[
"TRDVXUG128F1456CBF",
0.050486299999999998
],
[
"TRULRYN128F145FC1C",
0.050219800000000002
],
[
"TRMOWIA128F425CE0F",
0.049977500000000001
],
[
"TRUVPMZ128F42B6DF3",
0.049762000000000001
],
[
"TRSBDWW128F4262666",
0.049643699999999999
],
[
"TRKPHWQ128F4264F8C",
0.0495173
],
[
"TRBBLXU128F42623A1",
0.049416700000000001
],
[
"TRJKLLM128F1456C57",
0.049001599999999999
],
[
"TRSAAEI128F4216C24",
0.048813500000000003
],
[
"TRFXICT128F4264F8A",
0.048776199999999999
],
[
"TRINVLH12903CBE5A1",
0.048334500000000002
],
[
"TRMUUJR128F4262475",
0.048306500000000002
],
[
"TRTORTD128F1456AFA",
0.0468265
],
[
"TRECUJO12903CA7120",
0.046065599999999998
],
[
"TRXIRBQ128F93431BB",
0.0456938
],
[
"TRFDDVK128F42B6DF0",
0.045623799999999999
],
[
"TRSRGPM128F421A30B",
0.043976800000000003
],
[
"TRVUPPR128F429507D",
0.042872500000000001
],
[
"TRMHCZC128F428A4CD",
0.040675200000000002
],
[
"TRUFDRV128F4262352",
0.040675200000000002
],
[
"TRUZZHT128F93229AF",
0.039422199999999998
],
[
"TRLSIHL128F429AF18",
0.039002099999999998
],
[
"TRGETCK128F1460DB1",
0.038499499999999999
],
[
"TRSXXNU128F428AEF2",
0.038303799999999999
],
[
"TRFZXSY128F9330D9F",
0.037855199999999999
],
[
"TRPHFYF128F92F27FA",
0.037772100000000003
],
[
"TRNRHSL128F9337B55",
0.036998000000000003
],
[
"TRPTGNZ128F421A56B",
0.036713099999999999
],
[
"TRPAASI128F9337B6E",
0.036410499999999998
],
[
"TRGCROO128F93431C4",
0.035754300000000003
],
[
"TRCUHZL128F4235446",
0.034968699999999998
],
[
"TRDPOTJ128F429AF0C",
0.034860500000000003
],
[
"TROZUXM128F42790A2",
0.0346483
],
[
"TRJVLOQ128F9345A82",
0.034547799999999997
],
[
"TRQTFRP128F145FC1E",
0.033934600000000002
],
[
"TRQEWHR128F421A3F5",
0.032314599999999999
],
[
"TRNTPJA128F4265039",
0.030702900000000002
],
[
"TRDGXWY12903CF52BD",
0.030292300000000001
],
[
"TRBLEMZ128F93102D0",
0.029224300000000002
],
[
"TRBUUYO128F421A405",
0.028448500000000002
],
[
"TREVBDI12903CED7E6",
0.0279674
],
[
"TRKREBF128F429B317",
0.0258321
],
[
"TRZBYPR128F4233A8D",
0.025655000000000001
],
[
"TRTAZUQ12903CFEA78",
0.024545399999999998
],
[
"TRAIPRO128F429AE69",
0.024304699999999999
],
[
"TRTTVUZ128F92FADD3",
0.023320899999999999
],
[
"TRUYEJI128F4265041",
0.022173700000000001
],
[
"TRAXVGT128F9344507",
0.0213992
],
[
"TRJJBLH128F4260DA1",
0.0175365
],
[
"TRAMCWR128F4233F7F",
0.0161158
],
[
"TRXBLME128F424330F",
0.015760900000000001
],
[
"TRMUQXM128F4260D99",
0.015696000000000002
],
[
"TRHRZBJ128EF345514",
0.0156951
],
[
"TRJXIBT128F42454DB",
0.014519199999999999
],
[
"TRTHPOY128F9345AA5",
0.0137264
],
[
"TRRFGJU128F933B2E6",
0.0012336199999999999
],
[
"TRMYJUA128F428A590",
0.00123149
],
[
"TRNMVTE128F933B2EC",
0.00122703
],
[
"TRYALZM128F1483C7D",
0.0012245299999999999
],
[
"TRZVEJU128F4234F4E",
0.00121805
],
[
"TRQAZDO128F145639F",
0.0012166600000000001
],
[
"TRJXNJM12903CF57ED",
0.0012155
],
[
"TRVAOGO128F427C9D6",
0.00120951
],
[
"TRZMZDS128F422843B",
0.0012065000000000001
],
[
"TRXIEOF12903CE8212",
0.0012058699999999999
],
[
"TRPVVUG128F42A36AA",
0.0012057599999999999
],
[
"TRXGVXS128F428AA5C",
0.0012019400000000001
],
[
"TRUBOGF128E078A5B9",
0.0012017900000000001
],
[
"TRITZSB128F4277CC2",
0.0012014
],
[
"TRGHPHX128F9343544",
0.0011975600000000001
],
[
"TRUKWPE128F428114F",
0.00119666
],
[
"TROBGRB128F93229AB",
0.0011964199999999999
],
[
"TRGKTMW12903CFAE65",
0.00119637
]
],
"tags":[
[
"punk rock",
"100"
],
[
"punk",
"60"
]
],
"track_id":"TRAAAFD128F92F423A",
"title":"Face the Ashes"
}
文件_2
{
"artist":"CLP",
"timestamp":"2011-08-02 06:36:59.879759",
"similars":[
],
"tags":[
],
"track_id":"TRAAAVG12903CFA543",
"title":"Insatiable (Instrumental Version)"
}
我写了一个Python脚本来组合它们。我在每条记录之后添加了新行和逗号。
import glob
read_files = glob.glob("*.json")
with open("merged_file.json", "wb") as outfile:
for f in read_files:
with open(f, "rb") as infile:
outfile.write(infile.read())
outfile.write(',\n')
合并文件的输出为：
{
"artist":"Gob",
"timestamp":"2011-08-09 01:59:41.352247",
"similars":[
[
"TRTOVWD128F92F4227",
1
],
[
"TRUXNUD128F92F41D0",
0.97294099999999994
],
[
"TRNNOJO128F42992E9",
0.073926900000000004
],
[
"TRGZHTT128F423B2A4",
0.068387699999999996
],
[
"TRGYKYD128F42625F6",
0.065579700000000005
],
[
"TRGIWHY128F42625F5",
0.064063700000000001
],
[
"TRJCJTX128F930CACE",
0.063140100000000005
],
[
"TRMYNWT128F426254B",
0.0613825
],
[
"TRRQOJI128F428C865",
0.061121599999999998
],
[
"TRBNYHM128F428A569",
0.061121599999999998
],
[
"TRDLOYE128F4241E72",
0.060951900000000003
],
[
"TRNRVEW12903CBA24F",
0.060332700000000003
],
[
"TRKKIPG12903CBA083",
0.060155
],
[
"TRZHTGP128F428A63B",
0.059873599999999999
],
[
"TRKQSGZ128F428A851",
0.059873599999999999
],
[
"TRTOPDF128F42AD88A",
0.059687799999999999
],
[
"TRIWOPM128F4241E53",
0.058958900000000002
],
[
"TRCCJUW128F14652DB",
0.057935
],
[
"TRERDDF128F428ECC4",
0.057566600000000002
],
[
"TROKWNN128F421A3D8",
0.057379800000000002
],
[
"TRWGOOK128F42AE765",
0.057125000000000002
],
[
"TRFMNKP128F428ADC0",
0.056875099999999998
],
[
"TRDMLZT128F42A01A8",
0.055808900000000002
],
[
"TRGCJVM128E0780E48",
0.0547389
],
[
"TRRXGAY128F14652D7",
0.0538065
],
[
"TRIPEHH128F1462DFF",
0.052843000000000001
],
[
"TRDUOIP128F147D5A7",
0.051851500000000002
],
[
"TRZCHHD12903CC80A1",
0.051251699999999997
],
[
"TRFDDQS128F426243F",
0.051018300000000003
],
[
"TRZDKAR128F42591B8",
0.050740899999999999
],
[
"TRDVXUG128F1456CBF",
0.050486299999999998
],
[
"TRULRYN128F145FC1C",
0.050219800000000002
],
[
"TRMOWIA128F425CE0F",
0.049977500000000001
],
[
"TRUVPMZ128F42B6DF3",
0.049762000000000001
],
[
"TRSBDWW128F4262666",
0.049643699999999999
],
[
"TRKPHWQ128F4264F8C",
0.0495173
],
[
"TRBBLXU128F42623A1",
0.049416700000000001
],
[
"TRJKLLM128F1456C57",
0.049001599999999999
],
[
"TRSAAEI128F4216C24",
0.048813500000000003
],
[
"TRFXICT128F4264F8A",
0.048776199999999999
],
[
"TRINVLH12903CBE5A1",
0.048334500000000002
],
[
"TRMUUJR128F4262475",
0.048306500000000002
],
[
"TRTORTD128F1456AFA",
0.0468265
],
[
"TRECUJO12903CA7120",
0.046065599999999998
],
[
"TRXIRBQ128F93431BB",
0.0456938
],
[
"TRFDDVK128F42B6DF0",
0.045623799999999999
],
[
"TRSRGPM128F421A30B",
0.043976800000000003
],
[
"TRVUPPR128F429507D",
0.042872500000000001
],
[
"TRMHCZC128F428A4CD",
0.040675200000000002
],
[
"TRUFDRV128F4262352",
0.040675200000000002
],
[
"TRUZZHT128F93229AF",
0.039422199999999998
],
[
"TRLSIHL128F429AF18",
0.039002099999999998
],
[
"TRGETCK128F1460DB1",
0.038499499999999999
],
[
"TRSXXNU128F428AEF2",
0.038303799999999999
],
[
"TRFZXSY128F9330D9F",
0.037855199999999999
],
[
"TRPHFYF128F92F27FA",
0.037772100000000003
],
[
"TRNRHSL128F9337B55",
0.036998000000000003
],
[
"TRPTGNZ128F421A56B",
0.036713099999999999
],
[
"TRPAASI128F9337B6E",
0.036410499999999998
],
[
"TRGCROO128F93431C4",
0.035754300000000003
],
[
"TRCUHZL128F4235446",
0.034968699999999998
],
[
"TRDPOTJ128F429AF0C",
0.034860500000000003
],
[
"TROZUXM128F42790A2",
0.0346483
],
[
"TRJVLOQ128F9345A82",
0.034547799999999997
],
[
"TRQTFRP128F145FC1E",
0.033934600000000002
],
[
"TRQEWHR128F421A3F5",
0.032314599999999999
],
[
"TRNTPJA128F4265039",
0.030702900000000002
],
[
"TRDGXWY12903CF52BD",
0.030292300000000001
],
[
"TRBLEMZ128F93102D0",
0.029224300000000002
],
[
"TRBUUYO128F421A405",
0.028448500000000002
],
[
"TREVBDI12903CED7E6",
0.0279674
],
[
"TRKREBF128F429B317",
0.0258321
],
[
"TRZBYPR128F4233A8D",
0.025655000000000001
],
[
"TRTAZUQ12903CFEA78",
0.024545399999999998
],
[
"TRAIPRO128F429AE69",
0.024304699999999999
],
[
"TRTTVUZ128F92FADD3",
0.023320899999999999
],
[
"TRUYEJI128F4265041",
0.022173700000000001
],
[
"TRAXVGT128F9344507",
0.0213992
],
[
"TRJJBLH128F4260DA1",
0.0175365
],
[
"TRAMCWR128F4233F7F",
0.0161158
],
[
"TRXBLME128F424330F",
0.015760900000000001
],
[
"TRMUQXM128F4260D99",
0.015696000000000002
],
[
"TRHRZBJ128EF345514",
0.0156951
],
[
"TRJXIBT128F42454DB",
0.014519199999999999
],
[
"TRTHPOY128F9345AA5",
0.0137264
],
[
"TRRFGJU128F933B2E6",
0.0012336199999999999
],
[
"TRMYJUA128F428A590",
0.00123149
],
[
"TRNMVTE128F933B2EC",
0.00122703
],
[
"TRYALZM128F1483C7D",
0.0012245299999999999
],
[
"TRZVEJU128F4234F4E",
0.00121805
],
[
"TRQAZDO128F145639F",
0.0012166600000000001
],
[
"TRJXNJM12903CF57ED",
0.0012155
],
[
"TRVAOGO128F427C9D6",
0.00120951
],
[
"TRZMZDS128F422843B",
0.0012065000000000001
],
[
"TRXIEOF12903CE8212",
0.0012058699999999999
],
[
"TRPVVUG128F42A36AA",
0.0012057599999999999
],
[
"TRXGVXS128F428AA5C",
0.0012019400000000001
],
[
"TRUBOGF128E078A5B9",
0.0012017900000000001
],
[
"TRITZSB128F4277CC2",
0.0012014
],
[
"TRGHPHX128F9343544",
0.0011975600000000001
],
[
"TRUKWPE128F428114F",
0.00119666
],
[
"TROBGRB128F93229AB",
0.0011964199999999999
],
[
"TRGKTMW12903CFAE65",
0.00119637
]
],
"tags":[
[
"punk rock",
"100"
],
[
"punk",
"60"
]
],
"track_id":"TRAAAFD128F92F423A",
"title":"Face the Ashes"
},
{
"artist":"CLP",
"timestamp":"2011-08-02 06:36:59.879759",
"similars":[
],
"tags":[
],
"track_id":"TRAAAVG12903CFA543",
"title":"Insatiable (Instrumental Version)"
}
当我使用JSON
Lint（http://jsonlint.com/）验证这些记录时，它告诉我该文件已损坏并且不是有效的JSON。即使花了一段时间，我也无法弄清楚合并的出了什么问题。如果有人对此有任何想法，这将是有帮助的。
问题答案：
You can’t just concatenate two JSON strings to make valid
JSON
(or combine them by tacking ',\n' to the end of
each). Instead, you could combine the two (as Python objects) into a Python
list, then use
json.dump to write
it to a file as JSON:
import json
import glob
result = []
for f in glob.glob("*.json"):
with open(f, "rb") as infile:
result.append(json.load(infile))
with open("merged_file.json", "wb") as outfile:
json.dump(result, outfile)
If you wanted to do it without the (unnecesssary) intermediate step of parsing
each JSON file, you could merge them into a list like this:
import glob
read_files = glob.glob("*.json")
with open("merged_file.json", "wb") as outfile:
outfile.write('[{}]'.format(
','.join([open(f, "rb").read() for f in read_files])))
类似资料：
-
问题内容： 我有一个要合并的文件数组。这是我尝试过的，但是没有用。 问题答案： 使用IOUtils可以做到这一点。看我的例子： 如果您不能使用IOUtils lib，请编写自己的实现。例：
-
本文向大家介绍Python将多个excel文件合并为一个文件，包括了Python将多个excel文件合并为一个文件的使用技巧和注意事项，需要的朋友参考一下 利用Python，将多个excel文件合并为一个文件 思路 利用python xlrd包读取excle文件，然后将文件内容存入一个列表中，再利用xlsxwriter将内容写入到一个新的excel文件中。 完整代码 源文件excel1: 源文件e
-
在vertx中将多个文件的内容附加到单个文件中的最佳方式是什么？我尝试过vertx文件系统和asyncFile，但它们都没有附加文件的选项，或者我不知道有任何附加文件。是否有其他方法可以在vertx中异步合并或附加文件。 我能找到的唯一解决方案是制作缓冲区列表并使用循环将内容写入每个先前缓冲区长度的末尾。
-
本文向大家介绍如何用python合并多个excel文件，包括了如何用python合并多个excel文件的使用技巧和注意事项，需要的朋友参考一下 安装模块 1、找到对应的模块 http://www.python-excel.org/ 2、用 pip install 安装 因为使用的是 python3，所以安装的时候采用 pip3。 XlsxWriter 示例 先看看简单的演示： 运行结果如下： 合
-
我有多个json文件，其中包含需要合并的关系数据，每个文件都有一个带有commonkey的记录，这是所有文件中的公共键，在下面的示例中，a0，a1是公共键。值是多个键的嵌套字典，如Key1、key2等，如下所示，我需要合并多个json文件并获得如dboutput.json所示的输出，文件名在合并操作中充当索引。这样的问题是一个相关的问题，它合并了丢失的信息，但在我的情况下，我不希望任何更新替换现有
-
我的python3脚本创建了变量，其值是一个shapefiles列表，每个shapefiles都是一个多边形，表示一个地理区域 但它给出的结果是：AttributeError：“Shape”对象没有属性“union” 我看到了另一种方法，它涉及创建一个shapefilewriter对象，然后依次覆盖列表https://gis.stackexchange.com/questions/103033/u