Create SP500.csv

.gitignore

@@ -99,3 +99,6 @@ ENV/
 
 # mypy
 .mypy_cache/
+
+# VS Code settings
+.vscode

itertools-in-python3/README.md

@@ -0,0 +1,56 @@
+# Itertools in Python 3, By Example
+
+> Supplemental materials for the [Itertools in Python 3, By Example](https://realpython.com/itertools-in-python3) article on [Real Python](https://realpython.com).
+
+This folder contains content for two example from the article: [Analyzing the S&P500](https://realpython.com/python3-itertools/#analyzing-the-sp500) and [Building Relay Teams from Swimmer Data](https://realpython.com/python3-itertools/#building-relay-teams-from-swimmer-data).
+
+## Downloading the Files
+
+### With `git`
+
+If you have `git` installed, the easiest way to access these files is to clone the repository to the directory of your choice:
+
+```console
+git clone https://github.com/realpython/materials.git
+```
+
+Then `cd` into the `itertools-in-python3` directory:
+
+```console
+cd itertools-in-python3
+```
+
+### Without `git`
+
+Alternatively, you can download the entire repository as a `.zip` file from the repository's [homepage](https://github.com/realpython/materials) using the green "Clone or download" button in the top right hand corner.
+
+![Download repo as zip](download-zip.gif)
+
+## Running the Code Examples
+
+To run the code examples, first make sure you have Python 3 installed on your machine. **The code examples WILL NOT work with Python 2.** If you need help installing Python 3, check out Real Python's [Python 3 Installation & Setup Guide](https://realpython.com/installing-python/).
+
+To run the `sp500.py` file, type `python3 sp500.py` into your terminal. Here's how that looks, with output:
+
+```console
+$ python3 sp500.py
+Max gain: 11.58% on 2008-10-13
+Max loss: -20.47% on 1987-10-19
+Longest growth streak: 14 days (1971-03-26 to 1971-04-15)
+```
+
+Similarly, for `swimmers.py`:
+
+```console
+$ python3 swimmers.py
+Backstroke A: Sophia, Grace, Penelope, Addison
+Backstroke B: Elizabeth, Audrey, Emily, Aria
+Breaststroke A: Samantha, Avery, Layla, Zoe
+Breaststroke B: Lillian, Aria, Ava, Alexa
+Butterfly A: Audrey, Leah, Layla, Samantha
+Butterfly B: Alexa, Zoey, Emma, Madison
+Freestyle A: Aubrey, Emma, Olivia, Evelyn
+Freestyle B: Elizabeth, Zoe, Addison, Madison
+```
+
+> **Note:** Depending on your installation, you may need to type `python3.6` or `python36` to run the examples. If you follow the [Python 3 Installation & Setup Guide](https://realpython.com/installing-python/), you should have no problem.

itertools-in-python3/sp500.py

@@ -0,0 +1,61 @@
+from collections import namedtuple
+import csv
+from datetime import datetime
+import itertools as it
+import functools as ft
+
+
+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.))
+              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
+))