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| def csv_to_dict(path, allowed_keys=None):
"""
Reads csv file and returns dict with keys specified in allowed_keys
parameter; if allowed_keys is Falsy, it will include all columns.
path - string, path to file
allowed_keys - array of strings, columns that you want in the result JSON
return - dict
"""
rows_json = []
try:
with open(path, 'r') as csv_file:
csv_content = csv_file.readlines()
keys = {i: k for i, k in enumerate(csv_content[0].split(','))}
if not allowed_keys:
allowed_keys = set(keys.values())
for row in csv_content[1:]:
row = row.split(',')
rows_json.append({keys[i]: (k if k != 'NaN' else None) for i, k in enumerate(row) if keys[i] in allowed_keys})
except Exception:
import traceback
traceback.print_exc()
return rows_json
def convert_dict_values(array_of_dicts, type_per_key):
"""Convert type of values in dictionary
- array_of_dicts, i.e. [{'pressure': '2.4', 'wheels': '0', 'name': 'Audi'}, ...]
- type_per_key, i.e. {'pressure': float, 'wheels': int}
return: [{'pressure': 2.4, 'wheels': 0, 'name': 'Audi'}, ...]
"""
for _dict in array_of_dicts:
for k, v in _dict:
i_dict[k] = type_per_key[k](v) if k in type_per_key else v
return array_of_dicts
|
