difflib

问题 I have a column in a dataframe that is like this: OWNER -------------- OTTO J MAYER OTTO MAYER DANIEL J ROSEN DANIEL ROSSY LISA CULLI LISA CULLY LISA CULLY CITY OF BELMONT CITY OF BELMONT CITY Some of the names in my data frame are misspelled or having extra/missing characters. I need a column where the names are replaced by any close match in the same column. However, all the similar names need to be group by under one same name. For example this is I what I expect from the data frame above:

问题 I'm using difflib 's SequenceMatcher to get_opcodes() and than highlight the changes with css to create some kind of web diff . First, I set a min_delta so that I consider two strings different if only 3 or more characters in the whole string differ, one after another ( delta means a real, encountered delta, which sums up all one-character changes): matcher = SequenceMatcher(source_str, diff_str) min_delta = 3 delta = 0 for tag, i1, i2, j1, j2 in matcher.get_opcodes(): if tag == "equal":

问题 I'm currently using method get_close_matches method from difflib to iterate through a list of 15,000 strings to get the closest match against another list of approx 15,000 strings: a=['blah','pie','apple'...] b=['jimbo','zomg','pie'...] for value in a: difflib.get_close_matches(value,b,n=1,cutoff=.85) It takes .58 seconds per value which means it will take 8,714 seconds or 145 minutes to finish the loop. Is there another library/method that might be faster or a way to improve the speed for

问题 I am using difflib.HtmlDiff to compare two files. I want the differences to be highlighted in the outputted html. This already works when there are a maximum of two different chars in one line: a = "2.000" b = "2.120" But when there are more different characters on one line then in the output the whole line is marked red (on the left side) or green (on the right side of the table): a = "2.000" b = "2.123" Is this behaviour configurable? So can I set the number of different characters at which

问题 I am trying to use the SequenceMatcher method in Python's difflib package to identify string similarity. I have experienced strange behavior with the method, though, and I believe my problem may be related to the package's "junk" filter, a problem described in detail here. Suffice it to say that I thought I could fix my problem by passing an autojunk flag to my SequenceMatcher in the way described by the difflib documentation: import difflib def matches(s1, s2): s = difflib.SequenceMatcher

问题 I am trying to figure this out... Can the difflib.* library in Python be used to make some kind of plagiarism detection program? If so how? Maybe anyone could help me to figure out this question. 回答1: It could be used, but you're going to face all the same general issues you find in automated plagiarism detection. It might give you a little bit of a head start on implementing some of the algorithms you need, but I don't think it is likely to take you very far. 回答2: The short answer is yes.

问题 Downloading this page and making a very minor edit to it, changing the first 65 in this paragraph to 68 : I then run it through the following code to pull out the diffs. import bs4 from bs4 import BeautifulSoup import urllib2 import lxml.html as lh url = 'https://secure.ssa.gov/apps10/reference.nsf/links/02092016062645AM' response = urllib2.urlopen(url) content = response.read() # get response as list of lines root = lh.fromstring(content) section1 = root.xpath("//div[@class = 'column-12']")

问题 I'd like to compare differences between two lists of strings. For my purposes, whitespace is noise and these differences do not need to be shown. Reading into difflib's documentation, "the default [for charjunk ] is module-level function IS_CHARACTER_JUNK() , which filters out whitespace characters". Perfect, except I don't see it working, or making much difference (<- pun!). import difflib A = ['3 4\n'] B = ['3 4\n'] print ''.join(difflib.ndiff(A, B)) # default: charjunk=difflib.IS_CHARACTER

问题 I'm using difflib SequenceMatcher (ratio() method) to define similarity between text files. While difflib is relatively fast to compare a small set of text files e.g. 10 files of 70 kb on average comparing to each other (46 comparisons) takes about 80 seconds. The issue here is that i have a collection of 3000 txt files (75 kb on average), a raw estimation on how much time SequenceMatcher needs to complete the comparison job is 80 days! I tried "real_quick_ratio()" and "quick_ratio()" methods

问题 I want to use something like difflib.get_close_matches but instead of the most similar strings, I would like to obtain the indexes (i.e. position in the list). The indexes of the list are more flexible because one can relate the index to other data structures (related to the matched string). For example, instead of: >>> words = ['hello', 'Hallo', 'hi', 'house', 'key', 'screen', 'hallo', 'question', 'format'] >>> difflib.get_close_matches('Hello', words) ['hello', 'hallo', 'Hallo'] I would