How fast will a list comprehension deal with the same task? Filter a list with list comprehension # filter_list.py It takes 65 milliseconds to filter a list of one million elements. I'm using Python 3.8 for benchmarks (you can read about the whole setup in the Introduction article): $ python -m timeit -s "from filter_list import for_loop" "for_loop()" Let's measure the execution time of this function. I will write a separate article about comparing boolean values soon.
If not element % 2 is equivalent to if element % 2 = 0, but it's slightly faster. Instead, we have to create a new one containing only the even numbers: # filter_list.py One important thing to keep in mind is that we can't remove items from a list as we iterate over it. Let's use a simple scenario for a loop operation - we have a list of numbers, and we want to remove the odd ones. In this article, I will compare their performance and discuss when a list comprehension is a good idea, and when it's not. You can often hear that list comprehension is "more Pythonic" (almost as if there was a scale for comparing how Pythonic something is 😉). Let's run the script and provide our Iliad.txt to it: $ python app.py Iliad.Many simple "for loops" in Python can be replaced with list comprehensions. Typically, for this, you'd create a Bag of Words Model, using libraries like NLTK, though, this implementation will suffice. Once all the lines are recorded into the dictionary, we order it via order_bag_of_words() which returns a list of tuples in the (word, word_count) format, sorted by the word count.įinally, we print the top ten most common words. It delimits the spaces between words and adds the word to the dictionary - bag_of_words. If so, its read line-by-line and each line is passed on into the record_word_cnt() function. The script uses the os module to make sure that the file we're attempting to read actually exists. Return sorted(words, key= lambda x: x, reverse=desc)ĭef record_word_cnt( words, bag_of_words): for word in words:īag_of_words = 1 if _name_ = '_main_': format(sorted_words))ĭef order_bag_of_words( bag_of_words, desc= False): Let's start off with the readline() method, which reads a single line, which will require us to use a counter and increment it: filepath = 'Iliad.txt' with open(filepath) as fp: Reading a File Line-by-Line in Python with readline()
#ONE LINE FOR LOOP PYTHON CODE#
Note: For the remainder of this article we will be working with the text of the book The "Iliad of Homer", which can be found at, as well as in the GitHub repo where the code is for this article. Here's how you can use it to open a file: fp = open( 'path/to/file.txt', 'r') The built-in open() function is what you use to open a file object for either reading or writing purposes.
Python is a great general-purpose programming language, and it has a number of very useful file IO functionality in its standard library of built-in functions and modules.
Read a File Line-by-Line in Python with readline().In case you want to try out some of these examples by yourself, the code used in this article can be found at the following GitHub repo.
#ONE LINE FOR LOOP PYTHON HOW TO#
Throughout this article, we'll be covering a number of code examples that demonstrate how to read files line by line. While it's up to you to determine a suitable size for the chunks of data you're processing, for many applications, it's suitable to process a file one line at a time.
#ONE LINE FOR LOOP PYTHON FREE#
What do you do when the file you are trying to process is quite large, like several GB of data or larger? The answer to this problem is to read in chunks of a file at a time, process it, then free it from memory so you can process another chunk until the whole massive file has been processed. A common task in programming is opening a file and parsing its contents.
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