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I would like to get some understanding on how the data types in python - list, tuple, dict and set - are implemented
How are they implemented, importantly the data structure used.
Any place/ url to precisely get this understanding?
The best place to look is the CPython implementation source code:
dict - Hash map targeting fast resolution of keys
list - Looks like an array of PyObjects
tuple - Same as list but with optimisations that a tuple can allow (fixed size, objects)
set - Hash map with optimisations for cache locality
The source code is heavily commented and well written C. This would be the best place to understand the data structures used in detail.
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I know in c++ it already exist
#include <list>
Now I am curious to know if it exist in python also.
You can also take a look at llist python package, which provides some useful features that deque does not. There are not only doubly linked lists, but also single linked lists data structure in that package. IMHO, one of the biggest advantages of this package is the ability to store a reference to the llist elements.
It appears that collections.deque is a doubly-linked-list library in Python. According to the documentation, it should have approximately O(1) cost when appending or popping from the head or the tail, as well as O(n) for regular inserts (which matches what we'd expect from a linked list).
API: http://docs.python.org/2/library/collections.html#collections.deque
Source: https://stackoverflow.com/a/282238/2441252
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I need to make a very simple image that will illustrate a cash flow diagram based on user input. Basically, I just need to make an axis and some arrows facing up and down and proportional to the value of the cash flow. I would like to know how to do this with matplot.
The best tool can be matplotlib. You can simply store the values in a list and then use 'stem' to draw the lines. Then you can use markers with triangle_up and triangle_down to show the arrow.
If you simply need arrows pointing up and down, use Unicode arrows like "↑" and "↓". This would be really simple if rendering in a browser.
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I am an absolute beginner in Python (3.3.2). I know the basic functions like writing text files, variables, loops ,etc but have never written complex code.
My research project requires applying a moving average filter on three columns of a large text file (150 MB in size, having more than 1 million rows). My question is: What should I study in order to develop a methodology to apply the moving average formula within Python?. Excel is not an option because doing so is very tedious in Excel and sometimes it crashes due to longer periods of loading.
Kindly direct me to the 'right' resources/ examples relevant to my problem. I have gone through several python tutorials but didn't find anything relevant.
Check out Pandas. It should have no problem handling 10**6 rows on commonly available modern hardware. And among its many goodies are functions for computing moving averages.
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I've seen the cheatsheet floating around the web, but I'm after something that shows assigning variables; creating literals, tuple, lists, dictionaries, sets; accessing lists, disctionaries; list of operators; list of datatype functions etc..
..so something that I memorize and remember easily.
Thanks!
You can use the Python Quick Reference (PQR), latest versions available from http://rgruet.free.fr/. It is updated for each new version by different people.
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Is there a library similar to Python's difflib on Ruby?
Particularly, I need one that has a method similar to difflib.get_close_matches. Any recommendations?
After some research, I suggest using amatch or SimMetrics (with JRuby) and manually implement the get_close_matches method. Both libs offer implementations of many string similarity algorithms.
You can take a look at diff-lcs.