所确定的问题是特定于此号码的。还尝试过ParseInt和ParseFloat，结果是相同的。
convertedNumber：number = 0;
this.convertedNumber = Number（'178414025760337 17 '）;
输出：178414025760337 16
答案 0 :(得分：3)
您遇到了问题，因为您的号码比可以由# -*- coding: utf-8 -*-
#!/usr/bin/python2
"""Convert the Yelp Dataset Challenge dataset from json format to csv.
For more information on the Yelp Dataset Challenge please visit http://yelp.com/dataset_challenge
"""
import argparse
import collections
import csv
import simplejson as json
def read_and_write_file(json_file_path, csv_file_path, column_names):
"""Read in the json dataset file and write it out to a csv file, given the column names."""
with open(csv_file_path, 'wb+') as fout:
csv_file = csv.writer(fout)
csv_file.writerow(list(column_names))
with open(json_file_path) as fin:
for line in fin:
line_contents = json.loads(line)
csv_file.writerow(get_row(line_contents, column_names))
def get_superset_of_column_names_from_file(json_file_path):
"""Read in the json dataset file and return the superset of column names."""
column_names = set()
with open(json_file_path) as fin:
for line in fin:
line_contents = json.loads(line)
column_names.update(
set(get_column_names(line_contents).keys())
)
return column_names
def get_column_names(line_contents, parent_key=''):
"""Return a list of flattened key names given a dict.
Example:
line_contents = {
'a': {
'b': 2,
'c': 3,
},
}
will return: ['a.b', 'a.c']
These will be the column names for the eventual csv file.
"""
column_names = []
for k, v in line_contents.iteritems():
column_name = "{0}.{1}".format(parent_key, k) if parent_key else k
if isinstance(v, collections.MutableMapping):
column_names.extend(
get_column_names(v, column_name).items()
)
else:
column_names.append((column_name, v))
return dict(column_names)
def get_nested_value(d, key):
"""Return a dictionary item given a dictionary `d` and a flattened key from `get_column_names`.
Example:
d = {
'a': {
'b': 2,
'c': 3,
},
}
key = 'a.b'
will return: 2
"""
if '.' not in key:
if key not in d:
return None
return d[key]
base_key, sub_key = key.split('.', 1)
if base_key not in d:
return None
sub_dict = d[base_key]
return get_nested_value(sub_dict, sub_key)
def get_row(line_contents, column_names):
"""Return a csv compatible row given column names and a dict."""
row = []
for column_name in column_names:
line_value = get_nested_value(
line_contents,
column_name,
)
if isinstance(line_value, unicode):
row.append('{0}'.format(line_value.encode('utf-8')))
elif line_value is not None:
row.append('{0}'.format(line_value))
else:
row.append('')
return row
if __name__ == '__main__':
"""Convert a yelp dataset file from json to csv."""
parser = argparse.ArgumentParser(
description='Convert Yelp Dataset Challenge data from JSON format to CSV.',
)
parser.add_argument(
'json_file',
type=str,
help='The json file to convert.',
)
args = parser.parse_args()
json_file = args.json_file
csv_file = '{0}.csv'.format(json_file.split('.json')[0])
column_names = get_superset_of_column_names_from_file(json_file)
read_and_write_file(json_file, csv_file, column_names)
（Number（2^53）编码的最大号码大。 / p>
您将不得不使用Number.MAX_VALUE = 9007199254740991之类的库来处理您的电话号码。
BigInt