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weight-tracker.py
# CONSTANTS: REPLACE WITH YOUR OWN INFO. IN PARTICULAR, THE TWO DROPBOX FIELDS ARE TO GET YOUR API KEY OUT OF THE PYTHONISTA KEYCHAIN
DATABASE_FILENAME = "weight-tracker-TEST.db"
CSV_FILENAME = 'weights-TEST2.csv'
DROPBOX_KEYCHAIN_NAME = "keychain name goes here, see pythonista keychain docs-- e.g. 'dropbox'"
DROPBOX_KEYCHAIN_FIELD = "keychain field goes here-- e.g. 'myaccount'"
import dropbox, keychain, sqlite3, datetime, csv, dialogs
from matplotlib.pyplot import plot_date, show, subplots, legend
from matplotlib.dates import date2num, DateFormatter
from numpy import mean
token = keychain.get_password(DROPBOX_KEYCHAIN_NAME, DROPBOX_KEYCHAIN_FIELD)
dbx = dropbox.Dropbox(token)
def handle_api_error(e):
errortype = e.error
if errortype.is_path():
if errortype.get_path().is_not_found():
pass
else:
raise Exception("something went wrong on the dropbox end, panicking to save data.")
else:
raise Exception("something went wrong on the dropbox end, panicking to save data.")
def get_db_file():
path = "/" + DATABASE_FILENAME
try:
dbx.files_download_to_file(DATABASE_FILENAME, path)
except dropbox.exceptions.ApiError as e:
handle_api_error(e)
def upload_database():
with open(DATABASE_FILENAME, 'rb') as f:
data = f.read()
path = '/' + DATABASE_FILENAME
dbx.files_upload(data, path, dropbox.files.WriteMode.overwrite)
def connect_to_db(): # being consciously inefficient here, going to attempt to create table every time since perf is meaningless
get_db_file() # make sure that if there's a database on the dropbox we get that.
conn = sqlite3.connect(DATABASE_FILENAME, detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES)
# see https://stackoverflow.com/questions/1829872/how-to-read-datetime-back-from-sqlite-as-a-datetime-instead-of-string-in-python
table = """ CREATE TABLE IF NOT EXISTS weights (
id integer PRIMARY KEY,
date timestamp NOT NULL,
weight integer NOT NULL
); """
# weights will be stored as integers by multiplying original weight by 10 in order to eliminate floating point error. The only time there will be a floating point representation is when printing.
c = conn.cursor()
c.execute(table)
return conn
def add_weight(weight):
conn = connect_to_db()
insert_weight = "INSERT INTO weights(date,weight) VALUES(?,?)"
c = conn.cursor()
data = (datetime.datetime.now(), weight)
c.execute(insert_weight, data)
conn.commit()
conn.close()
upload_database()
print("added!")
def get_csv():
conn = connect_to_db()
c = conn.cursor()
c.execute("SELECT * FROM weights")
data = c.fetchall()
conn.close()
with open(CSV_FILENAME, 'w') as f:
writer = csv.writer(f)
writer.writerow(['id', 'date', 'weight'])
writer.writerows(data)
def validate_input(weight):
bits = weight.partition(".")
characteristic = bits[0].isdigit()
point = bits[1] == "."
mantissa = bits[2].isdigit()
rightsize = len(bits[2]) == 1
return characteristic and point and mantissa and rightsize
def parse_input(weight):
if validate_input(weight):
try:
num = int(weight.replace(".", ""))
except:
raise ValueError("enter a number with exactly one decimal place.")
return(num)
else:
raise ValueError("enter a number with exactly one decimal place.")
def moving_average(size, indata):
outdata = []
for idx, item in enumerate(indata):
endpoint = idx + 1
if idx < size:
field = indata[0:endpoint]
else:
field = indata[endpoint - size: endpoint]
outdata.append(mean(field) / 10)
return outdata
def get_plotting_data():
conn = connect_to_db()
c = conn.cursor()
c.execute("SELECT * FROM weights")
data = c.fetchall()
dates = date2num([x[1] for x in data])
raw_weights = [x[2] / 10.0 for x in data]
smoothed_5 = moving_average(5, [x[2] for x in data])
smoothed_10 = moving_average(10, [x[2] for x in data])
return {"dates": dates, "smoothed_5": smoothed_5, "smoothed_10": smoothed_10, "raw_weights": raw_weights}
def plot_db():
data = get_plotting_data()
myFmt = DateFormatter('%-m-%d')
fig, ax = subplots()
ax.xaxis.set_major_formatter(myFmt)
plot_date(data["dates"], data["smoothed_5"], fmt="b-", label="5-day average")
plot_date(data["dates"], data["smoothed_10"], fmt="g-", label="10-day average")
plot_date(data["dates"], data["raw_weights"], fmt="r-", label="daily weights")
legend(loc='upper left')
show()
if __name__ == "__main__":
user_input = dialogs.form_dialog(fields=[{"type": "text", "key": "weight", "title": "Weight:", "placeholder": "ONE DECIMAL PLACE EXACTLY (example: 100.0)"}])
if user_input["weight"]:
add_weight(parse_input(user_input["weight"]))
print("added weight. now saving updated csv.")
else:
print("no data to add. downloading db and saving csv.")
get_csv()
plot_db()
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