#Python credit card validator plus#

'''Checks a credit card number and returns a matching brand name, or INVALID if no brand matched.''' Then, match each of the expressions one by one until you find a match or a brand was not found: import re I would improve the way you distinguish between cards by introducing a mapping between brands and regular expressions (like it was done in pycard module). You can check the length to be in range in one go: if not(13 <= len(str(number)) <= 16): add docstrings to each of the defined functions.I'd pass around the credit card number as a string instead of converting it to string in every single validation step.use if _name_ = '_main_': to avoid the main() function to be executed when the module is imported.Sum_even = sum(split_to_digits(''.join(int_to_str(even_indices)))) Sum_odd = sum(split_to_digits(''.join(int_to_str(mul(odd_indices, 2))))) # cc_number = int(input('Enter a valid credit card number: ')) If you find anything that could be done in a better, faster, or more Pythonic way, please let me know. I tried to add some Pythonic ways of doing things, but there are probably many more things I could have done. For those of you unfamiliar with the problem, here is the description.īecause I took the program and converted from C to Python, it is probably not going to be written in the most Pythonic way. I wrote it in C, and then I thought that I could go about the same thing in Python, and wrote the same program in Python. People entering the numbers may have different ideas yet.I have began taking the CS50 course on EDX the past couple of days, and one of the tasks to accomplish was to write a credit card validator in C. Visa and MasterCard put digits in sets of 4, while Amex and Discover use groups of 4, 5 and 6 digits. This regex allows any amount of spaces and dashes anywhere in the number. All these regexes were taken from RegexBuddy’s library. You can use the specific regular expressions below to alert customers when they try to use a kind of card you don’t accept, or to route orders using different cards to different processors. They’re just a sequence of 13 to 16 digits, with a few specific digits at the start that identify the card issuer. Validating credit card numbers is the ideal job for regular expressions. Validating Credit Card Numbers on Your Order Form Though the savings are minimal here, so is the effort of typing the extra plus.

But it’s a good habit to keep regex efficiency in the back of your mind. In this case, the savings are only a few microseconds. Without the plus, three replacements would be required. If the input has consecutive non-digits, such as 1=2, then + matches the three equals signs at once and deletes them in one replacement.

#Python credit card validator plus#

If you’re wondering what the plus is for: that’s for performance. If this regex looks odd, remember that in a character class, the hyphen is a literal when it occurs right before the closing bracket (or right after the opening bracket or negating caret). This is a simple way of detecting common mis-typings of card numbers. If you only want to replace spaces and dashes, you could use +. Credit card numbers have what is called a check digit.

To remove all non-digits from the card number, simply use the “replace all” function in your scripting language to search for the regex + and replace it with nothing. So your order form should accept card numbers with spaces or dashes in them. Physical credit cards have spaces within the card number to group the digits, making it easier for humans to read or type in. The first step is to remove all non-digits from the card number entered by the customer. This can be very useful to prove in a security audit that you’re not improperly exposing your clients’ financial details. You can use a slightly different regular expression to find credit card numbers, or number sequences that might be credit card numbers, within larger documents. Each card issuer has its own range of card numbers, identified by the first 4 digits. You can even determine the type of credit card being used. With a few simple regular expressions, you can easily verify whether your customer entered a valid credit card number on your order form.