#### Category : hash

To begin I want a list of all unique IPs in this file. here is part of the file im reading in python: [node1] – 190.223.252.106 – User Successful Login [node2] – 239.84.157.20 – User Successful Profile Picture Upload [node2] – 87.130.185.37 – User Successful Login [node6] – 210.155.211.219 – User Successful Payment [node5] – ..

I borrowed this code from another post recently, and it works great for my needs… But I’m trying to reproduce the same results from Python code so the two language functions agree, and I’ve been struggling… These two so far do NOT produce the same results like I need… I suspect it’s an issue with ..

I am studying the SHA256 hash algorithm, which uses big-endian byte order. Would I actually ever have to consider endianness when using hashing algorithms? Maybe when a different endian computer runs my script? Source: Python..

Today, I found a really strange behavior in the Python dict object. Here is the code: nodes = {} for a, b in edges: nodes[a] = np.array([1]) nodes[b] = np.array([1]) for a, b in edges: print(nodes[a]) print(nodes[b]) Here is the error: print(nodes[b]) KeyError: ‘https://support.google.com/chrome/answer/185277’. So I guess one of the edges is not found in ..

Jaccard similarity is used to estimate the similarity between two sets. However, if we want to find pairs of most similar documents, it would take us O(n^2). If using minhashing, it can be done a lot faster (http://infolab.stanford.edu/~ullman/mmds/ch3n.pdf, https://www.fatalerrors.org/a/text-similarity-calculation-minhash-and-lsh-algorithm.html). I am wondering how to implement minhashing to estimate the similarity between two sets, say s1={1, ..

I want to know how to compare two hash values not Hamming distance. Is there a way? The final goal is to determine key of python dictionary that similar images can have in common. for example. import imagehash # img1, img2, img3 are same images img1_hash = imagehash.average_hash(Image.open(‘data/image1.jpg’)) img2_hash = imagehash.average_hash(Image.open(‘data/image2.jpg’)) img3_hash = imagehash.average_hash(Image.open(‘data/image3.jpg’)) img4_hash ..

I change images to hash values and try to classify images with similar hash values into the same group. so for example. import imagehash # img1, img2, img3 are same images img1_hash = imagehash.average_hash(Image.open(‘data/image1.jpg’)) img2_hash = imagehash.average_hash(Image.open(‘data/image2.jpg’)) img3_hash = imagehash.average_hash(Image.open(‘data/image3.jpg’)) img4_hash = imagehash.average_hash(Image.open(‘data/image4.jpg’)) print(img1_has, img2_hash, img3_hash, img4_hash) >>> 81c38181bf8781ff, 81838181bf8781ff, 81838181bf8781ff, ff0000ff3f00e7ff hash_lst = [[‘img1’, ..