Run a single pytest with:

def extract_ints(a_string):
return tuple(map(int, re.findall(r'-?\d+', a_string)))
`pytest -k name_of_test`

http://nbviewer.jupyter.org/url/norvig.com/ipython/Advent%21of%20Code.ipynb

import ipdb; ipdb.set_trace()
run `pytest`

with `pytest -s`

to disable console

```
# this is taken from https://github.com/norvig/pytudes/blob/master/ipynb/Advent%20of%20Code.ipynb
# and just kept here for refernce
# Python 3.x
import re
import numpy as np
import math
import urllib.request
from collections import Counter, defaultdict, namedtuple, deque
from functools import lru_cache
from itertools import permutations, combinations, chain, cycle, product, islice
from heapq import heappop, heappush
def Input(day):
"Open this day's input file."
filename = 'advent2016/input{}.txt'.format(day)
try:
return open(filename)
except FileNotFoundError:
return urllib.request.urlopen("http://norvig.com/ipython/" + filename)
def transpose(matrix): return zip(*matrix)
def first(iterable): return next(iter(iterable))
def nth(iterable, n, default=None):
"Returns the nth item of iterable, or a default value"
return next(islice(iterable, n, None), default)
cat = ''.join
Ø = frozenset() # Empty set
inf = float('inf')
BIG = 10 ** 999
def grep(pattern, lines):
"Print lines that match pattern."
for line in lines:
if re.search(pattern, line):
print(line)
def groupby(iterable, key=lambda it: it):
"Return a dic whose keys are key(it) and whose values are all the elements of iterable with that key."
dic = defaultdict(list)
for it in iterable:
dic[key(it)].append(it)
return dic
def powerset(iterable):
"Yield all subsets of items."
items = list(iterable)
for r in range(len(items)+1):
for c in combinations(items, r):
yield c
# 2-D points implemented using (x, y) tuples
def X(point): return point[0]
def Y(point): return point[1]
def neighbors4(point):
"The four neighbors (without diagonals)."
x, y = point
return ((x+1, y), (x-1, y), (x, y+1), (x, y-1))
def neighbors8(point):
"The eight neighbors (with diagonals)."
x, y = point
return ((x+1, y), (x-1, y), (x, y+1), (x, y-1),
(x+1, y+1), (x-1, y-1), (x+1, y-1), (x-1, y+1))
def cityblock_distance(p, q=(0, 0)):
"City block distance between two points."
return abs(X(p) - X(q)) + abs(Y(p) - Y(q))
def euclidean_distance(p, q=(0, 0)):
"Euclidean (hypotenuse) distance between two points."
return math.hypot(X(p) - X(q), Y(p) - Y(q))
def trace1(f):
"Print a trace of the input and output of a function on one line."
def traced_f(*args):
result = f(*args)
print('{}({}) = {}'.format(f.__name__, ', '.join(map(str, args)), result))
return result
return traced_f
def astar_search(start, h_func, moves_func):
"Find a shortest sequence of states from start to a goal state (a state s with h_func(s) == 0)."
frontier = [(h_func(start), start)] # A priority queue, ordered by path length, f = g + h
previous = {start: None} # start state has no previous state; other states will
path_cost = {start: 0} # The cost of the best path to a state.
while frontier:
(f, s) = heappop(frontier)
if h_func(s) == 0:
return Path(previous, s)
for s2 in moves_func(s):
new_cost = path_cost[s] + 1
if s2 not in path_cost or new_cost < path_cost[s2]:
heappush(frontier, (new_cost + h_func(s2), s2))
path_cost[s2] = new_cost
previous[s2] = s
return dict(fail=True, front=len(frontier), prev=len(previous))
def Path(previous, s):
"Return a list of states that lead to state s, according to the previous dict."
return ([] if (s is None) else Path(previous, previous[s]) + [s])
```

```
# turn a string st into a binary representation
''.join(format(ord(x), 'b') for x in st)
```

stdlib: binascii, collections (especially defaultdict), fractions (gcd), itertools (combinations, combinations_with_replacement, permutations, product, izip, chain), md5, re, os/sys.

Non-std: networkx (graphs and shortest path), sympy (isprime()), numpy (efficient representation of large arrays).

It's useful to have a canned exhaustive tree search prepared (breadth/depth/"best"-first search).

You can use complex numbers to represent 2-dimensional coordinates and direction; turning the unit vector left and right involves multiplying by 1j and -1j, respectively, and movement is addition.

Page created on 9 Apr 2019