0 /ˆพึ 0ภำ 1ˆฮึ ƒœภำ์1#! /usr/bin/env python # Python interface to the Internet finger daemon. # # Usage: finger [options] [user][@host] ... # # If no host is given, the finger daemon on the local host is contacted. # Options are passed uninterpreted to the finger daemon! import sys, string from socket import * # Hardcode the number of the finger port here. # It's not likely to change soon... # FINGER_PORT = 79 # Function to do one remote finger invocation. # Output goes directly to stdout (although this can be changed). # def finger(host, args): s = socket(AF_INET, SOCK_STREAM) s.connect((host, FINGER_PORT)) s.send(args + '\n') while 1: buf = s.recv(1024) if not buf: break sys.stdout.write(buf) sys.stdout.flush() # Main function: argument parsing. # def main(): options = '' i = 1 while i < len(sys.argv) and sys.argv[i][:1] == '-': options = options + sys.argv[i] + ' ' i = i+1 args = sys.argv[i:] if not args: args = [''] for arg in args: if '@' in arg: at = string.index(arg, '@') host = arg[at+1:] arg = arg[:at] else: host = '' finger(host, options + arg) # Call the main function. # main() 3ˆยึ „ M:ฯภำ8‰3๓ “๏ic @sัdZdZdddddddd gZd d lmZmZmZmZmZm Z d d l m Z d „Z d„Z d„Zd„Zd„Zd„Zd„Zd„Zd„Zd„Zd„Zd„Zd„Zd„Zyd dlTWnek rnXd„ZeZd*d„ZeZd*d„Ze dkrอgZ!d d!d"d#d$d%d&d'd(d)g Z"xe"D]Z#e e!e#ƒqrWgZ$xe!rฎe$j%ee!ƒƒq’We$GHd d*l&Z&e&j'ƒnd*S(+s๏Heap queue algorithm (a.k.a. priority queue). Heaps are arrays for which a[k] <= a[2*k+1] and a[k] <= a[2*k+2] for all k, counting elements from 0. For the sake of comparison, non-existing elements are considered to be infinite. The interesting property of a heap is that a[0] is always its smallest element. Usage: heap = [] # creates an empty heap heappush(heap, item) # pushes a new item on the heap item = heappop(heap) # pops the smallest item from the heap item = heap[0] # smallest item on the heap without popping it heapify(x) # transforms list into a heap, in-place, in linear time item = heapreplace(heap, item) # pops and returns smallest item, and adds # new item; the heap size is unchanged Our API differs from textbook heap algorithms as follows: - We use 0-based indexing. This makes the relationship between the index for a node and the indexes for its children slightly less obvious, but is more suitable since Python uses 0-based indexing. - Our heappop() method returns the smallest item, not the largest. These two make it possible to view the heap as a regular Python list without surprises: heap[0] is the smallest item, and heap.sort() maintains the heap invariant! soHeap queues [explanation by Fran็ois Pinard] Heaps are arrays for which a[k] <= a[2*k+1] and a[k] <= a[2*k+2] for all k, counting elements from 0. For the sake of comparison, non-existing elements are considered to be infinite. The interesting property of a heap is that a[0] is always its smallest element. The strange invariant above is meant to be an efficient memory representation for a tournament. The numbers below are `k', not a[k]: 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 In the tree above, each cell `k' is topping `2*k+1' and `2*k+2'. In an usual binary tournament we see in sports, each cell is the winner over the two cells it tops, and we can trace the winner down the tree to see all opponents s/he had. However