每天CookBook之Python-094

• csv文件的读写

 Symbol,Price,Date,Time,Change,Volume
 "AA",39.48,"6/11/2007","9:36am",-0.18,181800
 "AIG",71.38,"6/11/2007","9:36am",-0.15,195500
 "AXP",62.58,"6/11/2007","9:36am",-0.46,935000
 "BA",98.31,"6/11/2007","9:36am",+0.12,104800
 "C",53.08,"6/11/2007","9:36am",-0.25,360900
 "CAT",78.29,"6/11/2007","9:36am",-0.23,225400

import csv

with open('stocks.csv') as f:
    f_csv = csv.reader(f)
    headers = next(f_csv)
    for row in f_csv:
        print(row)

from collections import namedtuple

with open('stocks.csv') as f:
    f_csv = csv.reader(f)
    headings = next(f_csv)
    Row = namedtuple('Row', headings)
    for r in f_csv:
        row = Row(*r)
        print(row.Price)

with open('stocks.csv') as f:
    f_csv = csv.DictReader(f)
    for row in f_csv:
        print(row['Price'])

headers = ['Symbol', 'Price', 'Date', 'Time', 'Change', 'Volume']
rows = [('AA', 39.48, '6/11/2007', '9:36am', -0.18, 181800),
        ('AIG', 71.38, '6/11/2007', '9:36am', -0.15, 195500),
        ('AXP', 62.58, '6/11/2007', '9:36am', -0.46, 935000),
        ]

with open('stocks.csv', 'w') as f:
    f_csv = csv.writer(f)
    f_csv.writerow(headers)
    f_csv.writerows(rows)

headers = ['Symbol', 'Price', 'Date', 'Time', 'Change', 'Volume']
rows = [{'Symbol': 'AA', 'Price': 39.48, 'Date': '6/11/2007',
         'Time': '9:36am', 'Change': -0.18, 'Volume': 181800},
        {'Symbol': 'AIG', 'Price': 71.38, 'Date': '6/11/2007',
         'Time': '9:36am', 'Change': -0.15, 'Volume': 195500},
        {'Symbol': 'AXP', 'Price': 62.58, 'Date': '6/11/2007',
         'Time': '9:36am', 'Change': -0.46, 'Volume': 935000},
        ]

with open('stocks.csv', 'w') as f:
    f_csv = csv.DictWriter(f, headers)
    f_csv.writeheader()
    f_csv.writerows(rows)

import re

with open('stocks.csv') as f:
    f_csv = csv.reader(f)
    headers = [ re.sub('[^a-zA-Z_]', '_', h) for h in next(f_csv) ]
    Row = namedtuple('Row', headers)
    for r in f_csv:
        row = Row(*r)
        print(row)

col_types = [str, float, str, str, float, int]
with open('stocks.csv') as f:
    f_csv = csv.reader(f)
    headers = next(f_csv)
    for row in f_csv:
        row = tuple(convert(value) for convert, value in zip(col_types, row))
        print(row)

field_types = [
    ('Price', float),
    ('Change', float),
    ('Volume', int)
]

with open('stocks.csv') as f:
    for row in csv.DictReader(f):
        row.update((key, conversion(row[key])) for key, conversion in field_types)
        print(row)