But you can go even more idiomatic with a list comprehension:. If you're okay with reading the entire file's contents into memory, you can also use str. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. Read file into list and strip newlines Ask Question.
Asked 8 years, 3 months ago. Active 3 years ago. Viewed 41k times. SilentGhost SilentGhost k 61 61 gold badges silver badges bronze badges. In the case you are working with Big Data using readlines is not very efficient as it can result in MemoryError. In this case it is better to iterate over the file using for line in f: and working with each line variable.
I checked the memory profile of different ways given in the answers using the procedure mentioned here. The memory usage is far better when each line is read from the file and processed, as suggested by DevShark here. Holding all lines in a collection object is not a good idea if memory is a constraint or the file is large.
The execution time is similar in both the approaches. That way you don't have to allocate an extra list. Show 4 more comments. AMC 2, 7 7 gold badges 11 11 silver badges 33 33 bronze badges. Felix Kling Felix Kling k gold badges silver badges bronze badges. Better, use f. Is the second version, with for line in open filename safe? That is, will the file be automatically closed? Best to read the file one line at a time rather than reading the whole file into memory all at once. Doing so doesn't scale well with large input files.
See below answer by robert. Yes, to the point others are making here, while it's not "best practice" to use open without the context manager or some other guaranteed way to close it , this is not really one of those cases - when the object has no more references to it it will be garbage collected and the file closed, which should happen immediately on error or not, when the list comprehension is done processing.
Show 3 more comments. This is more explicit than necessary, but does what you want. I prefer this answer since it doesn't require to load the whole file into memory in this case it is still appended to array though, but there might be other circumstances. Certainly for big files this approach might mitigate problems.
Appending to an array is slow. I cannot think of a use case where this is the best solution. Note: This solution does not strip newlines.
This solution does load the whole file to memory. I don't know why people think it does not. Show 1 more comment. This will yield an "array" of lines from the file. Mark Amery k 67 67 gold badges silver badges bronze badges. Noctis Skytower Noctis Skytower Vanuan Since there is no remaining reference to the file after the line is run, the destructor should automatically close the file. Creating a tuple takes about 4.
My solution favors space over speed when the need for mutability is unknown. Eneko Alonso Eneko Alonso Add a comment. According to Python's Methods of File Objects , the simplest way to convert a text file into a list is : with open 'file.
Old answer: Using with and readlines : with open 'file. Pedro Lobito Pedro Lobito 82k 28 28 gold badges silver badges bronze badges. You would be correct if the line is after the 'with' clause — mightyandweakcoder. For example: def process line : if 'save the world' in line. DevShark DevShark 7, 7 7 gold badges 29 29 silver badges 54 54 bronze badges.
This was exactly what I needed - and thanks for explaining the downsides. As a beginner in Python, it's awesome to understand why a solution is the solution. Think a bit more Corey. Do you really ever want your computer to read each line, without ever doing anything with these lines? Surely you can realize you always need to process them one way or another.
You always need to do something with the lines. It can be as simple as printing the lines, or counting them. There is no value in having your process read the lines in memory, but not doing anything with it. You always need to do something with them. I think the point you are trying to make is that you might want to apply a function to all of them at once, rather than one by one. That is indeed the case sometimes. But it is very inefficient from a memory standpoint to do so, and prevents you from reading files if its footprint is larger than your Ram.
That's why typically generic parsers operate in the way I described. PierreOcinom that is correct. Given that the file is opened in read only mode, you couldn't modify the original file with the code above.
Show 8 more comments. PythonProgrammi PythonProgrammi EricOLebigot from the examples shown, it looks like read. Are you sure they're equivalent? So, if you use read. Also, there is no point in doing readlines in a list comprehension: simply iterating over the file is better, as it doesn't waste time and memory by creating an intermediate list of the lines. Show 2 more comments. Opening the file I assume that you want to open a specific file and you don't deal directly with a file-handle or a file-like-handle.
For reading a file you can omit the mode or pass it in explicitly: open filename open filename, 'r' Both will open the file in read-only mode. In case you want to read in a binary file on Windows you need to use the mode rb : open filename, 'rb' On other platforms the 'b' binary mode is simply ignored.
The last approach is the recommended approach to open a file in Python! The splitlines function turns the contents of the file into a list containing the elements of the file line by line. List comprehension is a compact way of creating lists. The example [x for x in range 3 ] creates the list [0, 1, 2]. If you want to learn more about list comprehensions, please have a look at our blog tutorial here. Now let us have a look at a one-line solution to our problem using list comprehension.
Thus far we have seen how we can read a text file line by line and store the elements in a list. Now let us discuss how we can do the same for a csv file. The approach used by us, in this case, is the pandas library in Python which allows us to read the data from the csv file and store the values in an array.
We can convert the array to a list using the tolist method. Whenever we open a file object, we can use a for loop to read its contents using the in keyword. With the in keyword, we can loop through the lines of the file. Unfortunately, this solution will not work for our client. File management is a delicate procedure in any programming language. Files must be handled with care to prevent their corruption. When a file is opened, care must be taken to ensure the resource is later closed.
And there is a limit to how many files can be opened at once in Python. In order to avoid these problems, Python provides us with the Context Manager.
A method like readlines will work okay for small files, but what if we have a more complex document? Using Python with statements will ensure that files are handled safely.
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