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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Collect the apple dataset.
This script uses the yfinance package to download the data from Yahoo Finance
and subsequently reformats it to a JSON file that adheres to our dataset
schema. See the README file for more information on the dataset.
Author: G.J.J. van den Burg
License: This file is part of TCPD, see the top-level LICENSE file.
Copyright: 2019, The Alan Turing Institute
"""
import argparse
import clevercsv
import hashlib
import json
import os
import yfinance
import sys
import time
from functools import wraps
from urllib.error import URLError
MD5_CSV = "9021c03bb9fea3f16ecc812d77926168"
MD5_JSON = "22edb48471bd3711f7a6e15de6413643"
SAMPLE = 3
NAME_CSV = "AAPL.csv"
NAME_JSON = "apple.json"
class ValidationError(Exception):
def __init__(self, filename):
self.message = (
"Validating the file '%s' failed. \n"
"Please raise an issue on the GitHub page for this project \n"
"if the error persists." % filename
)
def check_md5sum(filename, checksum):
with open(filename, "rb") as fp:
data = fp.read()
h = hashlib.md5(data).hexdigest()
return h == checksum
def validate(checksum):
"""Decorator that validates the target file."""
def validate_decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
target = kwargs.get("target_path", None)
if os.path.exists(target) and check_md5sum(target, checksum):
return
out = func(*args, **kwargs)
if not os.path.exists(target):
raise FileNotFoundError("Target file expected at: %s" % target)
if not check_md5sum(target, checksum):
raise ValidationError(target)
return out
return wrapper
return validate_decorator
def get_aapl():
""" Get the aapl data frame from yfinance """
date_start = "1996-12-12"
date_end = "2004-05-14"
# We use an offset here to catch potential off-by-one errors in yfinance.
date_start_off = "1996-12-10"
date_end_off = "2004-05-17"
aapl = yfinance.download(
"AAPL",
start=date_start_off,
end=date_end_off,
progress=False,
rounding=False,
threads=False,
)
# Get the actual date range we want
aapl = aapl[date_start:date_end]
aapl = aapl.copy()
# On 2020-08-28 Apple had a 4-for-1 stock split, and this changed
# the historical prices and volumes in the Yahoo API by a factor of
# 4. Since the original dataset was constructed before this time,
# we correct this change here by using a hard-coded closing price.
# This ensures that the resulting dataset has the same values as
# used in the TCPDBench paper.
if (0.2131696 <= aapl["Close"][0] <= 0.2131697) or (
0.21317000 <= aapl["Close"][0] <= 0.21317001
):
aapl["Open"] = aapl["Open"] * 4
aapl["High"] = aapl["High"] * 4
aapl["Low"] = aapl["Low"] * 4
aapl["Close"] = aapl["Close"] * 4
# Adj Close doesn't adhere to factor 4
aapl["Volume"] = aapl["Volume"] // 4
return aapl
def write_csv(target_path=None):
count = 0
while count < 5:
count += 1
try:
aapl = get_aapl()
aapl.round(6).to_csv(target_path, float_format="%.6f")
return
except URLError as err:
print(
"Error occurred (%r) when trying to download csv. Retrying in 5 seconds"
% err,
sys.stderr,
)
time.sleep(5)
@validate(MD5_JSON)
def write_json(csv_path, target_path=None):
with open(csv_path, "r", newline="", encoding="ascii") as fp:
reader = clevercsv.DictReader(
fp, delimiter=",", quotechar="", escapechar=""
)
rows = list(reader)
# offset to ensure drop is visible in sampled series
rows = rows[1:]
if SAMPLE:
rows = [r for i, r in enumerate(rows) if i % SAMPLE == 0]
time = [r["Date"] for r in rows]
close = [float(r["Close"]) for r in rows]
volume = [int(r["Volume"]) for r in rows]
name = "apple"
longname = "Apple Stock"
time_fmt = "%Y-%m-%d"
series = [
{"label": "Close", "type": "float", "raw": close},
{"label": "Volume", "type": "int", "raw": volume},
]
data = {
"name": name,
"longname": longname,
"n_obs": len(time),
"n_dim": len(series),
"time": {
"type": "string",
"format": time_fmt,
"index": list(range(0, len(time))),
"raw": time,
},
"series": series,
}
with open(target_path, "w") as fp:
json.dump(data, fp, indent="\t")
@validate(MD5_JSON)
def write_patch(source_path, target_path=None):
# This patches rounding differences that started to occur around Feb 2021.
from lzma import decompress
from base64 import b85decode
from diff_match_patch import diff_match_patch
dmp = diff_match_patch()
diff = decompress(b85decode(BLOB)).decode("utf-8")
with open(source_path, "r") as fp:
new_json = fp.read()
patches = dmp.patch_fromText(diff)
patched, _ = dmp.patch_apply(patches, new_json)
with open(target_path, "w") as fp:
fp.write(patched)
def collect(output_dir="."):
csv_path = os.path.join(output_dir, NAME_CSV)
json_path = os.path.join(output_dir, NAME_JSON)
write_csv(target_path=csv_path)
try:
write_json(csv_path, target_path=json_path)
except ValidationError:
need_patch = True
if need_patch:
write_patch(json_path, target_path=json_path)
def clean(output_dir="."):
csv_path = os.path.join(output_dir, NAME_CSV)
json_path = os.path.join(output_dir, NAME_JSON)
if os.path.exists(csv_path):
os.unlink(csv_path)
if os.path.exists(json_path):
os.unlink(json_path)
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument(
"-o", "--output-dir", help="output directory to use", default="."
)
parser.add_argument(
"action",
choices=["collect", "clean"],
help="Action to perform",
default="collect",
nargs="?",
)
return parser.parse_args()
def main(output_dir="."):
args = parse_args()
if args.action == "collect":
collect(output_dir=args.output_dir)
elif args.action == "clean":
clean(output_dir=args.output_dir)
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b"Hnuyf)8K}W<<ru=kEIig2os&+%XKeppJm;fyd7cWwcLzEaDxlWU9AYb_U%MKDBV;P@qwoeh1"
b"ytpF|ef6__SGgg-2XGc8h8fn+UXKTFFt}V8%PzAS6=b?Y(bDYFzCCL(HaYZ<Fitly)l9?|M;"
b"KC8zh7D=*H10wci1q7sFt;jbkD<H_<@Naku1HvMd26}E$x7dV7HK;U{&;#@@v~8gvsSSMiNY"
b"g!A!on?7kx!ANx>z-hV}yF#}XfI&&m!wWNh^){$ZVm>jmRtDHbevBw#o_NJ4W4)POR$3g}w4"
b"UTa`iE1#2f}~!kSUDZl^K9b6hrh3G0P1`dmx4oDvC35(bfW-MnWPx-|4T{sh4Rs*<vHN9Oe^"
b"Vc`<<ZuTA}T}td&ssv-*xdR)grr&$v`*$|^uBSaTw?68ywi6dC>{#%J)#;^#x%NY3V6p^HiP"
b"YlIl$iOWHToMB(KleJD%N#k168gwwpI?XiVJlnhm>5aLBK|^OG@z&^LMA=(N(P(IZdZS)ZK2"
b"iI5F>JD=00000TO!Fq)kn{C00G@5=A8lnO;(*3vBYQl0ssI200dcD"
)
if __name__ == "__main__":
main()
|
