How to get rid of \n and in my json file

2024/11/15 17:29:33

thanks for reading I am creating a json file as a result of an API that I am using. My issue is that the outcome gets has \h and '' in it and a .json file does not process the \n but keeps them, so the file becomes faulty.

This is my code, it is python:

json_arr = []
for text in gtm_Q6_df['ANSWER']:response = natural_language_understanding.analyze(text=text,language = 'en',features=Features(categories=CategoriesOptions(limit=3),)).get_result()#print("Input text: ",text)#print(json.dumps(response, indent=2))json_data = (json.dumps(response, indent=2))json_arr.append (json_data)with open('data.json','w') as outline: #with open('data.json','w') as outline:json.dump(json_arr,outline)print("break")
print(json_arr)


['{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 113,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.734718,\n      "label": "/business and industrial/advertising and marketing/marketing"\n    },\n    {\n      "score": 0.675452,\n      "label": "/business and industrial/business operations/management/business process"\n    },\n    {\n      "score": 0.620496,\n    "label": "/business and industrial/advertising and marketing/brand management"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 215,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.913644,\n      "label": "/technology and computing/operating systems"\n    },\n    {\n      "score": 0.855434,\n      "label": "/technology and computing/hardware/computer"\n    },\n    {\n      "score": 0.842841,\n      "label": "/technology and computing/hardware/computer components/chips and processors"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 14,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.885687,\n      "label": "/automotive and vehicles/cars/hybrid"\n    },\n    {\n      "score": 0.821966,\n     "label": "/automotive and vehicles/electric vehicles"\n    },\n    {\n      "score": 0.77387,\n      "label": "/shopping/retail"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 86,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.967686,\n      "label": "/education/homework and study tips"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n  "text_characters": 80,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.822388,\n      "label": "/automotive and vehicles/cars/sedan"\n    },\n    {\n      "score": 0.754857,\n      "label": "/automotive and vehicles/cars/hybrid"\n    },\n    {\n      "score": 0.68194,\n      "label": "/automotive and vehicles/cars/car culture"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 13,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.921873,\n      "label": "/real estate/architects"\n    },\n    {\n      "score": 0.790383,\n      "label": "/business and industrial/construction"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 52,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    
{\n      "score": 0.939684,\n      "label": "/technology and computing/computer reviews"\n    },\n    {\n      "score": 0.931032,\n      "label": "/technology and computing/tech news"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 14,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.979729,\n      "label": "/education/homework and study tips"\n    
},\n    {\n      "score": 0.850809,\n      "label": "/real estate/architects"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 28,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.999484,\n      "label": "/education/teaching and classroom resources"\n    }\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 113,\n    "features": 
1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.734718,\n      "label": "/business and industrial/advertising and marketing/marketing"\n    },\n    {\n      "score": 0.675452,\n      "label": "/business and industrial/business operations/management/business process"\n    },\n    {\n      "score": 0.620496,\n      "label": "/business and industrial/advertising and marketing/brand management"\n    
}\n  ]\n}', '{\n  "usage": {\n    "text_units": 1,\n    "text_characters": 215,\n    "features": 1\n  },\n  "language": "en",\n  "categories": [\n    {\n      "score": 0.913644,\n      "label": "/technology and computing/operating systems"\n    },\n    {\n      "score": 0.855434,\n      "label": "/technology and computing/hardware/computer"\n    },\n    {\n      "score": 0.842841,\n      "label": "/technology and computing/hardware/computer components/chips and processors"\n    }\n  ]\n}']

Answer

The fundamental issue is that you're creating multiple JSON strings (json_data = (json.dumps(response, indent=2))) and then adding them to an array (json_arr.append(json_data)), and then converting that array to JSON (json.dump(json_arr,outline)). So the result is a JSON array of strings (containing JSON).

You don't want to create a string before adding to the array, just include response in json_arr. Then it all gets converted together later by your existing json.dump(json_arr,outline) call:

json_arr = []
for text in gtm_Q6_df['ANSWER']:response = natural_language_understanding.analyze(text=text,language = 'en',features=Features(categories=CategoriesOptions(limit=3),)).get_result()json_arr.append (response) # <==== change is herewith open('data.json','w') as outline: #with open('data.json','w') as outline:json.dump(json_arr,outline)print("break")
print(json_arr)

You may need to tweak that slightly, I don't do much Python, but the fundamental issue is that you're converting the data in each reponse to JSON twice. Do it just once, all together, at the end.

https://en.xdnf.cn/q/120430.html

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