python - CSV 文件行递增

Question

目前我正在开发一个 CSV 文件程序，我必须将 CSV 文件分区为不重叠的部分(按行)，但不应在磁盘中创建任何额外的文件。

目前我正在使用此程序按行读取 CSV 文件的特定部分:

def dataFromFile(fname):
    record = []
    count=0
    with open(fname, 'rb') as f:
         reader = csv.reader(f)
         for row in reader:
             while '' in row:
                   row.remove('')
             count+=1
             record.append(row)
    print count
    return record[0:4]

这里我能够读取 0-4 范围内的行。但是是否有可能自动执行此操作，即我们是否可以在每次读取接下来的 4 行等等直到 CSV 文件末尾时手动给出该范围？

CSV 文件包含:

apple   beer    rice    chicken
apple   beer    rice    
apple   beer        
apple   mango       
milk    beer    rice    chicken
milk    beer    rice    
milk    beer        
milk    mango       

Answer 1

您可以使用yield :

def dataFromFile(fname):
    record = []
    print'Opening the file is executed once'
    count = 0
    with open(fname) as f:
        for row in csv.reader(f, delimiter=' '):
            count += 1
            fields = [field for field in row if field]
            if fields:
                record.append(fields)
            if len(record) == 4:
                print 'Last yielded row:', count
                yield(record)
                record = []
    if record:
        yield record

以及调用:

for row in dataFromFile('your.csv'):
   print row

来自口译员

>>> import csv
>>> 
>>> def dataFromFile(fname):
    record = []
    print 'Opening the file is executed once'
    count = 0
    with open(fname) as f:
        for row in csv.reader(f, delimiter=' '):
            count += 1

            fields = [field for field in row if field]
            if fields:
                record.append(fields)
            if len(record) == 4:
                print 'Last yielded row:', count
                yield(record)
                record = []
    if record:
        yield record 
... 
>>> for row in dataFromFile('your.csv'):
...     print row
... 
Opening the file is executed once
Last yielded row: 4
[['apple', 'beer', 'rice', 'chicken'], ['apple', 'beer', 'rice'], ['apple', 'beer'], ['apple', 'mango']]
Last yielded row: 8
[['milk', 'beer', 'rice', 'chicken'], ['milk', 'beer', 'rice'], ['milk', 'beer'], ['milk', 'mango']]
>>>