with open(file_path, 'r') as file:使用with语句打开文件,确保文件在使用完毕后自动关闭。 for line in file:文件对象是可迭代的,逐行读取文件内容,避免一次性将整个文件读入内存,节省内存空间,适用于大型文本文件。 二、分块读取大型文件: def read_large_file_in_chunks(file_path,
chunks = iter(lambda: f.read(record_struct.size), b'') return (record_struct.unpack(chunk) for chunk in chunks) # Example if __name__ == '__main__': with open('data.b','rb') as f: for rec in read_records('<idd', f): # Process rec ... 1. 2. 3. 4. 5. 6. 7....
Reading File in Chunks The read() (without argument) and readlines() methods reads the all data into memory at once. So don't use them to read large files. A better approach is to read the file in chunks using the read() or read the file line by line using the readline(), as ...
读取二进制文件 from struct import Struct def read_records(format, f): record_struct = Struct(format) chunks = iter(lambda: f.read(record_struct.size), b'') return (record_struct.unpack(chunk) for chunk in chunks) Example ifname== 'main': with open('data.b','rb') as f: for rec...
Binary files are buffered in fixed-size chunks; the size of the buffer is chosen using a heuristic trying to determine the underlying device’s “block size” and falling back on io.DEFAULT_BUFFER_SIZE. On many systems, the buffer will typically be 4096 or 8192 bytes long. “Interactive”...
read_csv( 'large.csv', chunksize=chunksize, dtype=dtype_map ) # # 然后每个chunk进行一些压缩内存的操作,比如全都转成sparse类型 # string类型比如,学历,可以转化成sparse的category变量,可以省很多内存 sdf = pd.concat( chunk.to_sparse(fill_value=0.0) for chunk in chunks ) #很稀疏有可能可以装的...
def chunks(l, n):""" Yield successive n-sized chunks from l. """for i in xrange(0, len(l), n):yield l[i:i+n]9. 我如何通过 HTTP 下载文件？import urllib2 urllib2.urlopen('http://www.example.com/').read()10. Python 中的矩阵乘法？(2.x)def matmult(a,b):zip_b = zip(*...
chunks = iter(lambda: f.read(record_struct.size), b'')return (record_struct.unpack(chunk) for chunk in chunks)# Example if __name__ == '__main__':with open('data.b','rb') as f:for rec in read_records('<idd', f):# Process rec ...如果你想将整个⽂件⼀次性读取到⼀...
#coding=utf-8importpandas as pddefread_data(file_name):'''file_name:文件地址'''inputfile= open(file_name,'rb')#可打开含有中文的地址data = pd.read_csv(inputfile, iterator=True,header=None) loop=True chunkSize= 1000#一千行一块chunks =[]whileloop:try: ...
In this part of the tutorial, you’ll read a relatively big WAV file in chunks using lazy evaluation to improve memory use efficiency. Additionally, you’ll write a continuous stream of audio frames sourced from an Internet radio station to a local WAV file. For testing purposes, you can ...