There are libraries that more efficient than with open function to deal with files in file system
Path.open
from pathlib2 import Path
example_path = Path('./info.csv')
with example_path.open() as f:
print(f.readline())
print(f.read())
Path.read_text(): read file in text format Path.read_bytes(): read file in binary format Path.write_text(): write file in text format Path.write_bytes(): write file in binay format
p = Path('my_binary_file')
p.write_bytes(b'Binary file contents')
fileinput
fileinput.input
as default fileinput take stdin as input source
import fileinput
for line in fileinput.input():
print(line)
to read from file
import fileinput
with fileinput.input(files=('info1.csv', 'info2.csv')) as file:
for line in file:
print(f'{fileinput.filename()} 第{fileinput.lineno()}行: {line}', end='')
it works well with glob
import fileinput
import glob
for line in fileinput.input(glob.glob("*.csv")):
if fileinput.isfirstline():
print(f'Reading {fileinput.filename()}...'.center(50,'-'))
print(str(fileinput.filelineno()) + ': ' + line.upper(), end=""
codecs
it makes encoding/decoding automatically, if the source format is unknown
import codecs
src="......\\xxxx.csv"
dst="......\\xxx_utf8.csv"
def ReadFile(filePath):
with codecs.open(filePath, "r") as f:
return f.read()
def WriteFile(filePath, u, encoding="utf-8"):
# with codecs.open(filePath,"w",encoding) as f:
with codecs.open(filePath, "wb") as f:
f.write(u.encode(encoding, errors="ignore"))
def CSV_2_UTF8(src, dst):
content = ReadFile(src)
WriteFile(dst, content, encoding="utf-8")
CSV_2_UTF8(src, dst)
lazylines
used for lazy reading large files without need of load all data into memory
import lazylines
with lazylines.open('large_file.txt') as lines:
for line in lines:
print(line.strip())
