Returning a generator in a with statement-CodePudding

I wanted to create a wrapper function over pandas.read_csv to change the default separator and format the file a specific way. This is the code I had :

def custom_read(path, sep="|", **kwargs):
    if not kwargs.get("chunksize", False):
        df_ = pd.read_csv(path, sep=sep, **kwargs)
        return format_df(df_, path)
    else:
        with pd.read_csv(path, sep=sep, **kwargs) as reader:
            return (format_df(chunk, path) for chunk in reader)

It turns out that this segfaults when used like so :

L = [chunk.iloc[:10, :] for chunk in custom_read(my_file)]

From what I understood off the backtrace, the generator is created, then the file is closed and the segfault happens when the generator tries to read from the now closed file.

I could avoid the segfault with a minor refactoring :

def custom_read(path, sep="|", **kwargs):
    if not kwargs.get("chunksize", False):
        df_ = pd.read_csv(path, sep=sep, **kwargs)
        return format_df(df_, path)
    else:
        reader = pd.read_csv(path, sep=sep, **kwargs)
        return (format_df(chunk, path) for chunk in reader)

I couldn't find anything on the particular usecase of generators in with clauses, is it something to avoid ? Is this supposed not to work or is this a bug of some kind ?

Is there a way to avoid this error but still use the encouraged with statement ?

CodePudding user response：

You could use a generator which keeps the file open. See the following example:

import os

def lines_format(lines):
    return "\n".join(f"*{line.strip()}*" for line in lines)

def chunk_gen(file, chunksize):
    with open(file, mode='r') as f:
        while True:
            lines = f.readlines(chunksize)
            if not lines:
                break
            yield lines_format(lines)
    
def get_formatted_pages(file, chunksize=0):
    if chunksize > 0:
        return chunk_gen(file, chunksize)
    else:
        with open(file, mode='r') as f:
            lines = f.readlines()
            return [lines_format(lines)]
                
with open("abc.txt", mode='w') as f:
    f.write(os.linesep.join('abc'))
    
pages = get_formatted_pages("abc.txt")
for i, page in enumerate(pages, start=1):
    print(f"Page {i}")
    print(page)
    
pages = get_formatted_pages("abc.txt", chunksize=2)
for i, page in enumerate(pages, start=1):
    print(f"Page {i}")
    print(page)

Edit: In your pandas.read_csv use case, this would look like

import pandas as pd

df = pd.DataFrame({'char': list('abc'), "num": range(3)})
df.to_csv('abc.csv')

def gen_chunk(file, chunksize):
    with pd.read_csv(file, chunksize=chunksize, index_col=0) as reader:
        for chunk in reader:
            yield format_df(chunk)
            
def format_df(df):
    # do something
    df['char'] = df['char'].str.capitalize()
    return df
    
def get_formatted_pages(file, chunksize=0):
    if chunksize > 0:
        return gen_chunk(file, chunksize)
    else:
        return [format_df(pd.read_csv(file, index_col=0))]
    
list(get_formatted_pages('abc.csv', chunksize=2))