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sp500.py
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72 lines (55 loc) · 1.99 KB
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import csv
import functools as ft
import itertools as it
from collections import namedtuple
from datetime import datetime
class DataPoint(namedtuple("DataPoint", ["date", "value"])):
__slots__ = ()
def __le__(self, other):
return self.value <= other.value
def __lt__(self, other):
return self.value < other.value
def __gt__(self, other):
return self.value > other.value
def consecutive_positives(sequence, zero=0):
def _consecutives():
for itr in it.repeat(iter(sequence)):
yield tuple(
it.takewhile(
lambda p: p > zero, it.dropwhile(lambda p: p <= zero, itr)
)
)
return it.takewhile(lambda t: len(t), _consecutives())
def read_prices(csvfile, _strptime=datetime.strptime):
with open(csvfile) as infile:
reader = csv.DictReader(infile)
for row in reader:
yield DataPoint(
date=_strptime(row["Date"], "%Y-%m-%d").date(),
value=float(row["Adj Close"]),
)
# Read prices and calculate daily percent change.
prices = tuple(read_prices("SP500.csv"))
gains = tuple(
DataPoint(day.date, 100 * (day.value / prev_day.value - 1.0))
for day, prev_day in zip(prices[1:], prices)
)
# Find maximum daily gain/loss.
zdp = DataPoint(None, 0) # zero DataPoint
max_gain = ft.reduce(max, it.filterfalse(lambda p: p <= zdp, gains))
max_loss = ft.reduce(min, it.filterfalse(lambda p: p > zdp, gains), zdp)
# Find longest growth streak.
growth_streaks = consecutive_positives(gains, zero=DataPoint(None, 0))
longest_streak = ft.reduce(
lambda x, y: x if len(x) > len(y) else y, growth_streaks
)
# Display results.
print("Max gain: {1:.2f}% on {0}".format(*max_gain))
print("Max loss: {1:.2f}% on {0}".format(*max_loss))
print(
"Longest growth streak: {num_days} days ({first} to {last})".format(
num_days=len(longest_streak),
first=longest_streak[0].date,
last=longest_streak[-1].date,
)
)