Other common usages of hashes are for cryptographic and security reasons.Ī concrete example of this is when you try to download open-source software from the internet. There are a lot of things that rely on hashes, and hash tables are just one of them. If you want to try one of these algorithms by yourself, just point your browser to, insert a text of any length in the textbox, click the crypt button and get your 128bit MD5 hash back. Some popular hash algorithms are MD5, SHA-1, SHA-2, NTLM. This is not a mandatory feature for every hash functions but becomes important when they have to be cryptographically secure. They produce fixed-length values: it doesn’t matter if your input is one, ten, or ten thousand bytes, the resulting hash will be always of a fixed, predetermined length.Īnother characteristic that is quite common in hash functions is that they often are one-way functions: thanks to a voluntary data loss implemented in the function, you can get a hash from a string but you can’t get the original string from a hash.They are deterministic: the same string will always produce the same hash.They are fast to compute: calculate the hash of a piece of data have to be a fast operation.Hash functions have three major characteristics: Hash Functionsīefore introducing hash tables and their Python implementation you have to know what is a hash function and how it works.Ī hash function is a function that can map a piece of data of any length to a fixed-length value, called hash. Knowing how Python hash tables work will give you a deeper understanding of how dictionaries work and this could be a great advantage for your Python understanding because dictionaries are almost everywhere in Python. Hi guys, have you ever wondered how can Python dictionaries be so fast and reliable? The answer is that they are built on top of another technology: hash tables.
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