How can I convert a list of dictionaries from a CSV into a JSON object in Python?

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[{'10': 'i ve been with what is now comcast since 2001 the company has really grown and improved and delivers a great service along with great customer service ', 'aspects':['service']},
{'20': 'good service but lack of options to allow it be more affordable allowing individual channel choices would be great ', 'aspects':['lack', 'service']},
{'30': 'it a good service but very expensive', 'aspects':['service']}, {'40': 'good service', 'aspects':['service']},
{'50': 'good service but over priced ', 'aspects':['service']}]

Since my data is being read from a CSV file it's being read as a string. I'm unable to read it in its original type i.e. list of dict and then convert it to a json file
Apr 17, 2018 in Python by ariaholic
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You could try using the AST module. Abstract Syntax Trees or AST will help you in converting to a JSON file.

example

[code]
import ast
s = """[{'10': 'i ve been with what is now comcast since 2001 the company has really grown and improved and delivers a great service along with great customer service ', 'aspects':['service']},
{'20': 'good service but lack of options to allow it be more affordable allowing individual channel choices would be great ', 'aspects':['lack', 'service']},
{'30': 'it a good service but very expensive', 'aspects':['service']}, {'40': 'good service', 'aspects':['service']},
{'50': 'good service but over priced ', 'aspects':['service']}]"""

print(ast.literal_eval(s))
[/code]

output for the above code is

[{'10': 'i ve been with what is now comcast since 2001 the company has really grown and improved and delivers a great service along with great customer service ', 'aspects': ['service']}, {'aspects': ['lack', 'service'], '20': 'good service but lack of options to allow it be more affordable allowing individual channel choices would be great '}, {'30': 'it a good service but very expensive', 'aspects': ['service']}, {'aspects': ['service'], '40': 'good service'}, {'aspects': ['service'], '50': 'good service but over priced '}]
answered Apr 17, 2018 by anonymous

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