Python读取实时数据流示例

1、#coding:utf-8

chose = [
('foo',1,2),
('bar','hello'),
('foo',3,4)
]

def do_foo(x,y):
print('foo',x,y)

def do_bar(s):
print('bar',s)

for tag,*args in chose:
if tag == 'foo':
do_foo(*args)

elif tag == 'bar':
do_bar(*args)

line = 'nobody:*:-2:-2:Unprivileged User:/var/empty:/usr/bin/false'

uname,*fields,homedir,sh = line.split(':')
print(sh)
from collections import deque
def search(lines, pattern, history=5):
previous_lines = deque(maxlen=history)
for li in lines:
if pattern in li:
yield li, previous_lines
previous_lines.append(li)

# Example use on a file
if __name__ == '__main__':
with open(r'./somefiles.py') as f:
for line, prevlines in search(f, 'python', 5):
for pline in prevlines:
print(pline, end='')
print(line, end='')
print('-' * 20)

2、import heapq

portfolio = [
{'name': 'IBM', 'shares': 100, 'price': 91.1},
{'name': 'AAPL', 'shares': 50, 'price': 543.22},
{'name': 'FB', 'shares': 200, 'price': 21.09},
{'name': 'HPQ', 'shares': 35, 'price': 31.75},
{'name': 'YHOO', 'shares': 45, 'price': 16.35},
{'name': 'ACME', 'shares': 75, 'price': 115.65}
]
cheap = heapq.nsmallest(3, portfolio, key=lambda s: s['price'])
expensive = heapq.nlargest(3, portfolio, key=lambda s: s['price'])
print(cheap)
print(expensive)

3、读取流数据源

如果数据是来自一个连续的数据源，我们需要读取连续数据，接下来

我们介绍一个适用于许多真是场景的简单解决方案，然而它并不是通用的。

操作步骤：

在本节中我们将想你演示如何读取一个实时变化的文件，并把输入打印出来。

import time
import os
import sys

if len(sys.argv) != 2:
print('>>sys.stderr,"请输入需要读取的文件名！"')

filename = sys.argv[1]

if not os.path.isfile(filename):
print('>>sys.stderr,"请给出需要的文件：\%s\: is not a file" % filename')

with open(filename,'r') as f:
filesize = os.stat(filename)[6]
f.seek(filesize)
while True:
where = f.tell()
line = f.readline()
if not line:
time.sleep(1)
f.seek(where)
else:
print(line)

以上这篇Python读取实时数据流示例就是小编分享给大家的全部内容了，希望能给大家一个参考

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