file_path="/Users/nikpi/Desktop/sample.json"withopen(file=file_path,mode='r')asread_file:object=json.load(read_file)pretty_object=json.dumps(object,indent=4)print(pretty_object)# Returns:# {# "activity": "Plan a trip to another country",# "type": "recreational",# "participants": 1,...
json.load 接收file-like object,用来解析再方便不过了。 load(fp, encoding=None, cls=None, object_hook=None, parse_float=None, parse_int=None, parse_constant=None, object_pairs_hook=None, **kw) Deserialize ``fp`` (a ``.read()``-supporting file-like object containing a JSON document) ...
下表是说明将Python数据类型转换为各自的JSON类型的表格。 要记住的要点: dump() –将数据转换为JSON文件 dumps() –将数据转换为JSON字符串 load() –将JSON文件转换为Python对象 loads()–将JSON字符串的对象转换为Python对象 漂亮的印刷: Pretty Printing负责代码对齐并使其以人类可读的格式进行。让我们看下面的...
Example 5: Python pretty print JSON importjson person_string ='{"name": "Bob", "languages": "English", "numbers": [2, 1.6, null]}'# Getting dictionaryperson_dict = json.loads(person_string)# Pretty Printing JSON string backprint(json.dumps(person_dict, indent =4, sort_keys=True)) ...
["streaming API"]' Compact encoding:: >>> import json >>> json.dumps([1,2,3,{'4': 5, '6': 7}], sort_keys=True, separators=(',',':')) '[1,2,3,{"4":5,"6":7}]' Pretty printing:: >>> import json >>> print json.dumps({'4': 5, '6': 7}, sort_keys=True,...
curlhttp://api.joind.in| python -mjson.tool you need python installed, but the json extension is probably included, and that's all you need for this tool. the result is something like: you can also use this approach to present json data that has been captured to another file, for ex...
Pretty printing(一种格式化输出) >>>data_json3=json.dumps(data,sort_keys=True,indent=4,separators=(',',':'))>>>printdata_json3[1,2,3,{"4":5,"6":7}] 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. indent 会让每个键值对显示的时候,以缩进几个字符对齐。以方便查看 ...
usage: pprintjson.py [-h] [-i num] [-o file] [-c cmd] [-v] [file] A pretty-printing function for json. positional arguments: file json <file> to pretty-print optional arguments: -h, --help show this help message and exit -i num, --indent num indent <num> number of spaces...
1importjson23person_string ='{"name": "Bob", "languages": "English", "numbers": [2, 1.6, null]}'45#Getting dictionary6person_dict =json.loads(person_string)78#Pretty Printing JSON string back9print(json.dumps(person_dict, indent = 4, sort_keys=True)) ...
Making JSON human readable (aka "pretty printing") is as easy as passing an integer value for the indent parameter: >>> import json >>> data = {'people':[{'name': 'Scott', 'website': 'stackabuse.com', 'from': 'Nebraska'}]} >>> json.dumps(data, indent=4) { "people": [ ...