def delete_all_db_data(ath_un, mfp_username, db_host, db_name, superuser_un,
superuser_pw, encr_pass):
db_name = (db_name)
conn = None
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
sql = """
SELECT truncate_schema('public');
"""
try:
# connect to the PostgreSQL server
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
# create a cursor
cur = conn.cursor()
# execute a statement
with StdoutRedirection(ath_un):
print(('Deleting DB data for user: '******'....'))
cur.execute(sql)
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except Exception as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(error)))
finally:
if conn is not None:
conn.close()
with StdoutRedirection(ath_un):
print(('All DB data for user: '******' deleted successfully.'))
with ProgressStdoutRedirection(ath_un):
print(('All DB data for user: '******' deleted successfully.'))
def insert_df_values(ath_un, conn, datafrm, table, unique):
# Creating a list of tupples from the dataframe values
tpls = [tuple(x) for x in datafrm.to_numpy()]
# dataframe columns with Comma-separated
cols = ','.join(list(datafrm.columns))
unique = ','.join(unique)
# SQL query to execute
sql = "INSERT INTO %s(%s) VALUES %%s ON CONFLICT (%s) DO NOTHING;" % (
table, cols, unique)
cur = conn.cursor()
try:
psycopg2.extras.execute_values(cur, sql, tpls)
conn.commit()
with StdoutRedirection(ath_un):
print('Custom data succesfully inserted to: {}'.format(table))
with ProgressStdoutRedirection(ath_un):
print('Custom data succesfully inserted to: {}'.format(table))
except (Exception, psycopg2.DatabaseError) as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(e)))
cur.close()
def delete_all_files(output, ath_un):
folder = os.path.join(output, ath_un)
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
for the_file in os.listdir(folder):
file_path = os.path.join(folder, the_file)
if os.path.isfile(file_path):
os.unlink(file_path)
elif os.path.isdir(file_path):
shutil.rmtree(file_path)
with StdoutRedirection(ath_un):
print(('All XML,JSON and FIT files for user: '******' deleted successfully.'))
with ProgressStdoutRedirection(ath_un):
print(('All XML,JSON and FIT files for user: '******' deleted successfully.'))
def backup_user_db(db_name, ath_un, output, dbx_auth_token, encr_pass):
if os.name == 'nt':
backup_file_path = output + '\\' + ath_un + '\DB_Backup.gz'
else:
backup_file_path = output + '/' + ath_un + '/DB_Backup.gz'
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
open(pidfile).close
# read connection parameters
params = config(filename="encrypted_settings.ini",
section="postgresql",
encr_pass=encr_pass)
superuser_un = params.get("user")
superuser_pw = params.get("password")
db_host = params.get("host")
try:
with gzip.open(backup_file_path, 'wb') as f:
with StdoutRedirection(ath_un):
print('Backing up DB, please wait....')
with ProgressStdoutRedirection(ath_un):
print('Backing up DB, please wait....')
# create .pgpass in user's AppData or home directory
if os.name == 'nt':
appdata_dir = os.getenv('APPDATA')
pgpass_dir = os.path.join(appdata_dir, "postgresql")
pgpassfile = os.path.join(pgpass_dir, "pgpass.conf")
if not os.path.exists(pgpass_dir):
os.makedirs(pgpass_dir)
if not os.path.exists(pgpassfile):
open(pgpassfile,
'w+').write(db_host + ':5432:*:postgres:' +
superuser_pw)
open(pgpassfile).close
else:
pgpassfile = os.path.expanduser('~') + '/.pgpass'
if not os.path.exists(pgpassfile):
open(pgpassfile,
'w+').write(db_host + ':5432:*:postgres:' +
superuser_pw)
open(pgpassfile).close
os.chmod(pgpassfile, 0o600)
# execute pg_dump
popen = subprocess.Popen(
['pg_dump', '-h', db_host, '-U', superuser_un, db_name],
stdout=subprocess.PIPE,
universal_newlines=True)
for stdout_line in iter(popen.stdout.readline, ""):
f.write(stdout_line.encode())
popen.stdout.close()
popen.wait()
try:
os.remove(pgpassfile)
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(
sys.exc_info()[-1].tb_lineno) + ' ' + str(e)))
with StdoutRedirection(ath_un):
print(
'DB backup completed. The backup file will be uploaded to Dropbox now.'
)
with ProgressStdoutRedirection(ath_un):
print(
'DB backup completed. The backup file will be uploaded to Dropbox now.'
)
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(e)))
today = datetime.datetime.today().strftime('%Y%m%d')
download_folder_dbx = 'DB_Backup'
file_name_to = today + '_DB_Backup.gz'
dbx_file_exists = check_if_file_exists_in_dbx(file_name_to, dbx_auth_token,
download_folder_dbx,
encr_pass)
if dbx_file_exists == True:
with StdoutRedirection(ath_un):
print((file_name_to + ' already exists in Dropbox, skipping.'))
with ProgressStdoutRedirection(ath_un):
print((file_name_to + ' already exists in Dropbox, skipping.'))
else:
try:
with StdoutRedirection(ath_un):
print(('Uploading ' + file_name_to + ' Dropbox, please wait.'))
download_files_to_dbx(backup_file_path, file_name_to,
dbx_auth_token, download_folder_dbx,
encr_pass)
with StdoutRedirection(ath_un):
print('DB Backup file uploaded to Dropbox successfuly')
with ProgressStdoutRedirection(ath_un):
print('DB Backup file uploaded to Dropbox successfuly')
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print(
(str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(e)))
def parse_dataset(dataset, conn, start_date_dt, end_date_dt, data_source):
for row in dataset.itertuples():
glucose_nmol = None
glucose_nmol_avrg = None
ketone_nmol = None
utc_time_str = None
if data_source == 'glimp_android':
record_type = row._9 #Current(5) or 15min average(3)
if record_type == 5:
glucose_nmol = round((float(row._6) / 18), 2)
else:
glucose_nmol_avrg = round((float(row._6) / 18), 2)
local_time = row._2
epoch_time = row._3
local_time_dt = datetime.datetime.strptime((local_time),
"%d/%m/%Y %H.%M.%S")
local_time_str = datetime.datetime.strftime(
(local_time_dt), "%Y-%m-%d %H:%M:%S")
utc_time_str = datetime.datetime.utcfromtimestamp(
epoch_time).strftime('%Y-%m-%d %H:%M:%S')
else:
ketone_nmol = row._7
glucose_nmol = row._6
glucose_nmol_avrg = row._5
local_time = row._3
local_time_dt = local_time.to_pydatetime(
) #Convert from pandas to python datetime
local_time_str = datetime.datetime.strftime(
(local_time_dt), "%Y-%m-%d %H:%M:%S")
local_date_str = datetime.datetime.strftime((local_time_dt),
"%Y-%m-%d")
try:
# create a cursor
cur = conn.cursor()
# execute a statement
cur.execute(sql_local2gmt, (local_date_str, ))
result = cur.fetchone()
# close the communication with the PostgreSQL
conn.commit()
cur.close()
if result is not None:
utc_time_dt = local_time_dt - result[0]
utc_time_str = datetime.datetime.strftime(
(utc_time_dt), "%Y-%m-%d %H:%M:%S")
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' ' + str(error)))
# Compare if the Record Date is within the download Date range. This only works if parsed from top of the csv file.
# The most recent record at the top
if local_time_dt > end_date_dt + datetime.timedelta(days=1):
continue
if local_time_dt < start_date_dt:
break
with ProgressStdoutRedirection(ath_un):
print(
('Inserting BG record from Glimp/LibreView. Time: ' +
str(local_time_str) + ' Glucose: ' + str(glucose_nmol)))
with StdoutRedirection(ath_un):
print(
('Inserting BG record from Glimp/LibreView. Time: ' +
str(local_time_str) + ' Glucose: ' + str(glucose_nmol)))
try:
# create a cursor
cur = conn.cursor()
# execute a statement
cur.execute(
sql,
(ath_un, local_time_str, glucose_nmol, glucose_nmol_avrg,
ketone_nmol, data_source, utc_time_str))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' ' + str(error)))
def dwnld_insert_strava_data(ath_un, db_host, db_name, superuser_un,
superuser_pw, strava_refresh_token, start_date_dt,
end_date_dt, save_pwd, encr_pass):
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
strava_params = config(filename="encrypted_settings.ini",
section="strava",
encr_pass=encr_pass)
STRAVA_CLIENT_ID = str(strava_params.get("strava_client_id"))
STRAVA_CLIENT_SECRET = str(strava_params.get("strava_client_secret"))
STRAVA_TOKEN_URL = str(strava_params.get("strava_token_url"))
sql_insert_strava_refresh_token = """
DO
$do$
BEGIN
IF EXISTS (SELECT id FROM athlete WHERE ath_un = %s) THEN
UPDATE athlete SET strava_refresh_token = %s where ath_un= %s;
END IF;
END
$do$
"""
sql_insert_activity_summary = """
INSERT INTO strava_activity_summary(athlete_id,strava_activity_id,strava_athlete_id,name,distance,moving_time,elapsed_time,total_elevation_gain,type,
workout_type,external_id,upload_id,start_date,start_date_local,timezone,utc_offset,start_latitude,start_longitude,end_latitude,end_longitude,location_city,
location_state,location_country,map,summary_polyline,trainer,commute,manual,gear_id,average_speed,max_speed,average_cadence,average_temp,average_watts,
weighted_average_watts,kilojoules,device_watts,average_heartrate,max_heartrate,max_watts,elev_high,elev_low,suffer_score)
VALUES
((select id from athlete where ath_un=%s),%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
ON CONFLICT (start_date) DO NOTHING;
"""
sql_insert_activity_streams = """
INSERT INTO strava_activity_streams(activity_id,altitude,cadence,distance,grade_smooth,heartrate,latitude,longitude,moving,temp,time_gmt,velocity_smooth,watts)
VALUES
((select id from strava_activity_summary where strava_activity_id=%s),%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
ON CONFLICT (time_gmt) DO NOTHING;
"""
sql_insert_utc_offset = """
INSERT INTO gmt_local_time_difference (athlete_id,local_date,local_midnight_timestamp,gmt_midnight_timestamp,gmt_local_difference)
VALUES
((select id from athlete where ath_un=%s),%s,%s,%s,%s)
ON CONFLICT (local_date) DO NOTHING;
"""
sql_timezone = """
INSERT INTO timezones(gc_activity_id,strava_activity_id,timestamp_local,timestamp_gmt,timezone,long_degr,lat_degr,alt_avrg,end_time_gmt)
VALUES
(null,(select id from strava_activity_summary where strava_activity_id=%s),%s,%s,%s,%s,%s,%s,%s)
ON CONFLICT (timestamp_gmt,long_degr,lat_degr) DO NOTHING;
"""
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
def refresh_oauth_tokens():
#Refresh the access token
payload = dict(grant_type='refresh_token',
refresh_token=strava_refresh_token,
client_id=STRAVA_CLIENT_ID,
client_secret=STRAVA_CLIENT_SECRET)
refresh = requests.post(STRAVA_TOKEN_URL, data=payload)
response = refresh.json()
oauth_token = response['access_token']
refresh_token = response['refresh_token']
expires_at = response['expires_at']
if save_pwd == True:
encrypted_refresh_token = base64.b64encode(
encrypt(refresh_token, encr_pass))
encrypted_refresh_token = encrypted_refresh_token.decode('utf-8')
else:
encrypted_refresh_token = None
try:
cur = conn.cursor()
cur.execute(sql_insert_strava_refresh_token,
(ath_un, encrypted_refresh_token, ath_un))
conn.commit()
cur.close()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print(
(str(datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(e)))
return oauth_token, expires_at
oauth_token, expires_at = refresh_oauth_tokens()
header = {'Authorization': 'Bearer {}'.format(oauth_token)}
epoch_start_date = start_date_dt.timestamp()
epoch_end_date = end_date_dt.timestamp()
#Loop through all activities
page = 1
activities_url = "https://www.strava.com/api/v3/activities"
while True:
# Retry 3 times if request fails
tries = 3
for i in range(tries):
try:
#Check if the oauth token is stil valid, and refresh if not.
if int(datetime.now().timestamp()) > expires_at:
oauth_token, expires_at = refresh_oauth_tokens()
header = {'Authorization': 'Bearer {}'.format(oauth_token)}
with ProgressStdoutRedirection(ath_un):
print(
str(datetime.now()) +
'The Strava oauth token expired and has been refreshed'
)
# get page of 200 activities from Strava
r = requests.get(
'{}?before={}&after={}&page={}&per_page=200'.format(
activities_url, epoch_end_date, epoch_start_date,
str(page)),
headers=header)
sleep_sec = api_rate_limits(r)
except Exception as e:
if i < tries - 1:
time.sleep(10)
continue
else:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(
sys.exc_info()[-1].tb_lineno) + ' ' +
str(e)))
raise
break
if sleep_sec == 0:
pass
else:
time.sleep(sleep_sec)
pass
# if no results then exit loop
if (not r.json()):
if conn is not None:
conn.close()
with StdoutRedirection(ath_un):
print('Strava Activities Inserted Successfully')
with ProgressStdoutRedirection(ath_un):
print('Strava Activities Inserted Successfully')
break
#Do something with the response/data
activity_data = json.loads(r.text)
#assign activity values to variables
for activity in activity_data:
if "id" in activity:
strava_activity_id = activity['id']
#PG: Check whether the data for this activity have been inserted into to DB during one of the previous runs
data_exist_for_activity = 'Strava activity {} data'.format(
strava_activity_id)
data_exists = check_data_file_exists(data_exist_for_activity,
ath_un, db_host, db_name,
superuser_un,
superuser_pw, encr_pass)
if data_exists == True:
with StdoutRedirection(ath_un):
print((
'Strava activity {} data already downloaded and inserted to DB. Skipping.'
.format(strava_activity_id)))
with ProgressStdoutRedirection(ath_un):
print((
'Strava activity {} data already downloaded and inserted to DB. Skipping'
.format(strava_activity_id)))
continue
else:
strava_activity_id = None
if "id" in activity['athlete']:
strava_athlete_id = activity['athlete']['id']
else:
strava_athlete_id = None
if "name" in activity:
name = activity['name']
else:
name = None
if "distance" in activity:
distance = activity['distance']
else:
distance = None
if "moving_time" in activity:
moving_time = activity['moving_time']
else:
moving_time = None
if "elapsed_time" in activity:
elapsed_time = activity['elapsed_time']
else:
elapsed_time = None
if "total_elevation_gain" in activity:
total_elevation_gain = activity['total_elevation_gain']
else:
total_elevation_gain = None
if "type" in activity:
type = activity['type']
else:
type = None
if "workout_type" in activity:
workout_type = activity['workout_type']
else:
workout_type = None
if "external_id" in activity:
external_id = activity['external_id']
else:
external_id = None
if "upload_id" in activity:
upload_id = activity['upload_id']
else:
upload_id = None
if "start_date" in activity:
start_date = activity['start_date']
start_date_dt = datetime.strptime(start_date,
'%Y-%m-%dT%H:%M:%SZ')
start_date = datetime.strftime(start_date_dt,
'%Y-%m-%d %H:%M:%S')
else:
start_date = None
if "start_date_local" in activity:
start_date_local = activity['start_date_local']
start_date_local_dt = datetime.strptime(
start_date_local, '%Y-%m-%dT%H:%M:%SZ')
start_date_local = datetime.strftime(start_date_local_dt,
'%Y-%m-%d %H:%M:%S')
else:
start_date_local = None
if "timezone" in activity:
timezone = activity['timezone']
else:
timezone = None
if "utc_offset" in activity:
utc_offset = activity['utc_offset']
else:
utc_offset = None
if "start_latlng" in activity:
start_latlng = activity['start_latlng']
#if start_latlng is not None: #Changed 2021/10/29
if start_latlng:
start_latitude = start_latlng[0]
start_longitude = start_latlng[1]
else:
start_latitude = None
start_longitude = None
else:
start_latitude = None
start_longitude = None
if "end_latlng" in activity:
end_latlng = activity['end_latlng']
#if end_latlng is not None: #Changed 2021/10/29
if end_latlng:
end_latitude = end_latlng[0]
end_longitude = end_latlng[1]
else:
end_latitude = None
end_longitude = None
else:
end_latitude = None
end_longitude = None
if "location_city" in activity:
location_city = activity['location_city']
else:
location_city = None
if "location_state" in activity:
location_state = activity['location_state']
else:
location_state = None
if "location_country" in activity:
location_country = activity['location_country']
else:
location_country = None
if "id" in activity['map']:
map = activity['map']['id']
else:
map = None
if "summary_polyline" in activity['map']:
summary_polyline = activity['map']['summary_polyline']
else:
summary_polyline = None
if "trainer" in activity:
trainer = activity['trainer']
else:
trainer = None
if "commute" in activity:
commute = activity['commute']
else:
commute = None
if "manual" in activity:
manual = activity['manual']
else:
manual = None
if "gear_id" in activity:
gear_id = activity['gear_id']
else:
gear_id = None
if "average_speed" in activity:
average_speed = activity['average_speed']
else:
average_speed = None
if "max_speed" in activity:
max_speed = activity['max_speed']
else:
max_speed = None
if "average_cadence" in activity:
average_cadence = activity['average_cadence']
else:
average_cadence = None
if "average_temp" in activity:
average_temp = activity['average_temp']
else:
average_temp = None
if "average_watts" in activity:
average_watts = activity['average_watts']
else:
average_watts = None
if "weighted_average_watts" in activity:
weighted_average_watts = activity['weighted_average_watts']
else:
weighted_average_watts = None
if "kilojoules" in activity:
kilojoules = activity['kilojoules']
else:
kilojoules = None
if "device_watts" in activity:
device_watts = activity['device_watts']
else:
device_watts = None
if "average_heartrate" in activity:
average_heartrate = activity['average_heartrate']
else:
average_heartrate = None
if "max_heartrate" in activity:
max_heartrate = activity['max_heartrate']
else:
max_heartrate = None
if "max_watts" in activity:
max_watts = activity['max_watts']
else:
max_watts = None
if "elev_high" in activity:
elev_high = activity['elev_high']
else:
elev_high = None
if "elev_low" in activity:
elev_low = activity['elev_low']
else:
elev_low = None
if "suffer_score" in activity:
suffer_score = activity['suffer_score']
else:
suffer_score = None
with StdoutRedirection(ath_un):
print('Downloading Strava activity {} from: {}'.format(
strava_activity_id, start_date_local))
with ProgressStdoutRedirection(ath_un):
print('Downloading Strava activity {} from: {}'.format(
strava_activity_id, start_date_local))
#Insert activity summary data to DB
try:
cur = conn.cursor()
cur.execute(
sql_insert_activity_summary,
(ath_un, strava_activity_id, strava_athlete_id, name,
distance, moving_time, elapsed_time, total_elevation_gain,
type, workout_type, external_id, upload_id, start_date,
start_date_local, timezone, utc_offset, start_latitude,
start_longitude, end_latitude, end_longitude,
location_city, location_state, location_country, map,
summary_polyline, trainer, commute, manual, gear_id,
average_speed, max_speed, average_cadence, average_temp,
average_watts, weighted_average_watts, kilojoules,
device_watts, average_heartrate, max_heartrate, max_watts,
elev_high, elev_low, suffer_score))
conn.commit()
cur.close()
# Update the files table
data_file_path_insert(data_exist_for_activity, ath_un, db_host,
db_name, superuser_un, superuser_pw,
encr_pass)
#Insert utc offset into gmt_local_time_difference table if the record not already present from gc
gmt_local_difference = timedelta(seconds=utc_offset)
local_date = start_date_local_dt.date()
local_midnight = start_date_local_dt.replace(hour=00,
minute=00,
second=00)
gmt_midnight = local_midnight - gmt_local_difference
cur = conn.cursor()
cur.execute(sql_insert_utc_offset,
(ath_un, local_date, local_midnight, gmt_midnight,
gmt_local_difference))
conn.commit()
cur.close()
#Insert timezone info into timezones table if the record not already present from gc
if start_latitude is not None:
#Calculate avereage altitude for a better weather data accuracy
avg_altitude = int((elev_high + elev_low) / 2)
#Drop (GMT+hh:mm) from timezone string
timezone = re.sub("[(].*[) ]", "", timezone)
#Calculate end_time_gmt_str
end_time_gmt_dt = start_date_dt + timedelta(
seconds=elapsed_time)
end_time_gmt_str = datetime.strftime((end_time_gmt_dt),
"%Y-%m-%d %H:%M:%S")
cur = conn.cursor()
with StdoutRedirection(ath_un):
print(('Inserting timezone info: ' + str(timezone) +
' and local tz timestamp:' + str(local_date)))
with ProgressStdoutRedirection(ath_un):
print(('Inserting timezone info: ' + str(timezone) +
' and local tz timestamp:' + str(local_date)))
cur.execute(
sql_timezone,
(strava_activity_id, start_date_local, start_date,
timezone, start_longitude, start_latitude,
avg_altitude, end_time_gmt_str))
conn.commit()
cur.close()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(
sys.exc_info()[-1].tb_lineno) + ' ' + str(e)))
#Get all available streams for the activity
types = 'time,distance,latlng,altitude,velocity_smooth,heartrate,cadence,watts,temp,moving,grade_smooth'
df_columns = {
'activity_id', 'time_gmt', 'distance', 'latitude', 'longitude',
'altitude', 'velocity_smooth', 'heartrate', 'cadence', 'watts',
'temp', 'moving', 'grade_smooth'
}
df_columns = sorted(df_columns)
# Retry 3 times if request fails
tries = 3
for i in range(tries):
try:
#Check if the oauth token is stil valid, and refresh if not.
if int(datetime.now().timestamp()) > expires_at:
oauth_token, expires_at = refresh_oauth_tokens()
header = {
'Authorization': 'Bearer {}'.format(oauth_token)
}
with ProgressStdoutRedirection(ath_un):
print(
str(datetime.now()) +
'The Strava oauth token expired and has been refreshed'
)
streams = requests.get(
"https://www.strava.com/api/v3/activities/{}/streams?keys={}"
.format(strava_activity_id, types),
headers=header)
sleep_sec = api_rate_limits(streams)
except Exception as e:
if i < tries - 1:
time.sleep(10)
continue
else:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(
sys.exc_info()[-1].tb_lineno) + ' ' +
str(e)))
raise
break
if sleep_sec == 0:
pass
else:
time.sleep(sleep_sec)
pass
#TODO: if sleep_sec > 6hrs request a new access_token
#Do something with the response/data
activity_streams = json.loads(streams.text)
#Check if there is data in activity_streams
if 'message' in activity_streams:
if "Resource Not Found" in activity_streams['message']:
with ErrorStdoutRedirection(ath_un):
print(
str(datetime.now()) +
' No streams retrieved for {}. Moving onto next activity.'
.format(strava_activity_id))
continue
if "Rate Limit Exceeded" in activity_streams['message']:
with ErrorStdoutRedirection(ath_un):
print(
str(datetime.now()) +
' Download Rate limit exceeded. This attempt did not get caught by api_rate_limits() function!'
)
#Usualy due to failed request on a very last attempt before limit, and subsequent succesfull retry.Too messy, move onto next activity and see what happens.
continue
else:
pass
activity_streams_df = pd.DataFrame(columns=df_columns)
for stream in activity_streams:
if "time" in stream['type']:
activity_id_list = []
time_stream = stream['data']
for i in range(len(time_stream)):
time_stream[i] = start_date_dt + timedelta(
0, int(time_stream[i]))
time_stream[i] = datetime.strftime(
time_stream[i], '%Y-%m-%d %H:%M:%S')
activity_id_list.append(strava_activity_id)
activity_streams_df['activity_id'] = activity_id_list
activity_streams_df['time_gmt'] = time_stream
if "distance" in stream['type']:
distance_stream = stream['data']
activity_streams_df['distance'] = distance_stream
if "latlng" in stream['type']:
latlng_stream = stream['data']
latitude = []
longitude = []
if latlng_stream is not None:
for i in range(len(latlng_stream)):
latitude.append(latlng_stream[i][0])
longitude.append(latlng_stream[i][1])
activity_streams_df['latitude'] = latitude
activity_streams_df['longitude'] = longitude
if "altitude" in stream['type']:
altitude_stream = stream['data']
activity_streams_df['altitude'] = altitude_stream
if "velocity_smooth" in stream['type']:
velocity_smooth_stream = stream['data']
activity_streams_df[
'velocity_smooth'] = velocity_smooth_stream
if "heartrate" in stream['type']:
heartrate_stream = stream['data']
activity_streams_df['heartrate'] = heartrate_stream
if "cadence" in stream['type']:
cadence_stream = stream['data']
activity_streams_df['cadence'] = cadence_stream
if "watts" in stream['type']:
watts_stream = stream['data']
activity_streams_df['watts'] = watts_stream
if "temp" in stream['type']:
temp_stream = stream['data']
activity_streams_df['temp'] = temp_stream
if "moving" in stream['type']:
moving_stream = stream['data']
activity_streams_df['moving'] = moving_stream
if "grade_smooth" in stream['type']:
grade_smooth_stream = stream['data']
activity_streams_df['grade_smooth'] = grade_smooth_stream
activity_streams_df = activity_streams_df.reindex(
sorted(activity_streams_df.columns),
axis=1) # Sort df alphabeticaly
activity_streams_df = activity_streams_df.where(
pd.notnull(activity_streams_df), None) # Replace NaN with None
df2list = activity_streams_df.values.tolist()
#Insert activity streams data to DB
try:
cur = conn.cursor()
for sublist in df2list:
cur.execute(sql_insert_activity_streams, (sublist))
conn.commit()
cur.close()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(
sys.exc_info()[-1].tb_lineno) + ' ' + str(e)))
# increment page
page += 1
def cstm_data_insert(ath_un, usr_params_str, usr_params_int, db_host,
superuser_un, superuser_pw):
cstm_dbx_link = usr_params_str[0]
download_folder = usr_params_str[1]
download_folder = os.path.join(download_folder, 'CSTM_Temp_CSV')
archive_folder = os.path.join(download_folder, 'Archive')
table_name = usr_params_str[2]
date_format = usr_params_str[3]
timezone = usr_params_str[4]
datetime_clmn = usr_params_str[5]
unique = usr_params_int
dataframes = []
# Download the csv file from dropbox using share link
with StdoutRedirection(ath_un):
print('Downloading custom csv files from: {}'.format(cstm_dbx_link))
with ProgressStdoutRedirection(ath_un):
print('Downloading custom csv files from: {}'.format(cstm_dbx_link))
cstm_dbx_link = cstm_dbx_link[:-1] + '1' # Replace the 0 at the end of the link with 1.Will download as .zip file.
table_name = 'cstm_{}'.format(table_name)
response = urllib.request.urlopen(cstm_dbx_link)
sniffer = csv.Sniffer()
db_name = str(str2md5(ath_un)) + '_Athlete_Data_DB'
archive_params = config(filename="encrypted_settings.ini",
section="archive")
preserve_files = str(archive_params.get("preserve_files"))
#Insert usr_params to athlete table..
cstm_user_insert(ath_un, usr_params_str, usr_params_int, table_name,
db_host, db_name, superuser_un, superuser_pw)
conn = None
# connect to the PostgreSQL server
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
sql_select_athlete_id = """
SELECT id FROM athlete WHERE ath_un = %s;
"""
# Extract the downloaded file in to variable
downloadFile = io.BytesIO()
downloadFile.write(response.read())
downloadFile.seek(0) #Move pointer to the beginning
# Create output directory (if it does not already exist).
if not os.path.exists(download_folder):
os.makedirs(download_folder)
# Create Archive directory (if it does not already exist).
if preserve_files == "true":
if not os.path.exists(archive_folder):
os.makedirs(archive_folder)
#Insert the data from csv to dataframe
if zipfile.is_zipfile(downloadFile):
with zipfile.ZipFile(downloadFile, 'r') as z:
#List the content of the zip file
zipfile_content = z.namelist()
#Iterate through list and only extract files
for item in zipfile_content:
z.extract(item, download_folder)
downloadFile.close()
for filename in os.listdir(download_folder):
if os.path.isfile(os.path.join(download_folder, filename)):
#Detect whether the csv file has a header.
with open(os.path.join(download_folder, filename), 'r') as f:
has_header = sniffer.has_header(f.read())
if has_header:
f.seek(0) #Move pointer to the beginning
data_count = csv_match_columns2data(ath_un, f)
df = pd.read_csv(os.path.join(download_folder,
filename),
usecols=data_count)
else:
df = pd.read_csv(os.path.join(download_folder,
filename),
header=None)
dataframes.append(df)
f.close()
#Archive csv files
if preserve_files == "false":
#Remove the csv file from download folder
os.remove(os.path.join(download_folder, filename))
with StdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB.'
.format(filename)))
with ProgressStdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB.'
.format(filename)))
else:
#Move the csv to archive folder and remove from download
if os.path.exists(os.path.join(archive_folder, filename)):
#Replace the existing file with the updated one
os.remove(os.path.join(archive_folder, filename))
os.rename(os.path.join(download_folder, filename),
os.path.join(archive_folder, filename))
with StdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file archived'
.format(filename)))
with ProgressStdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file archived'
.format(filename)))
else:
#Remove the csv file from download folder
os.remove(os.path.join(download_folder, filename))
else:
filename = re.search(r'([^\/]+)\?.*$', cstm_dbx_link).group(
1) #Exctract the filename from the link
downloadFile.seek(0) #Move pointer to the beginning
#Detect whether the csv file has a header.
wrapper = io.TextIOWrapper(downloadFile, encoding='utf-8')
has_header = sniffer.has_header(wrapper.read())
downloadFile.seek(0) #Move pointer to the beginning
if has_header:
data_count = csv_match_columns2data(ath_un, wrapper)
downloadFile.seek(0) #Move pointer to the beginning
df = pd.read_csv(downloadFile, usecols=data_count)
else:
df = pd.read_csv(downloadFile, header=None)
#Archive downloaded File
if preserve_files == "true":
downloadFile.seek(0) #Move pointer to the beginning
with open(os.path.join(archive_folder, filename), 'wb') as f:
f.write(downloadFile.read())
with StdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file archived'
.format(filename)))
with ProgressStdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file archived'
.format(filename)))
else:
with StdoutRedirection(ath_un):
print(('The content of \"{}\" parsed and inserted into DB.'.
format(filename)))
with ProgressStdoutRedirection(ath_un):
print(('The content of \"{}\" parsed and inserted into DB.'.
format(filename)))
wrapper.close()
dataframes.append(df)
downloadFile.close()
#Remove duplicates
dataframes = pd.concat(dataframes).drop_duplicates().reset_index(drop=True)
#---- Parse and format datetime values ----
cur = conn.cursor()
#Iterate through values in df datetime column
if datetime_clmn is not None:
datetime_clmn = int(datetime_clmn)
#set how to to interpret the the first value in an ambiguous 3-integer date
#eu date format dd/mm/yyyy
if date_format == "eu":
first_val = "day"
#us date format mm/dd/yyyy
else:
first_val = 'month'
#add timestamp_gmt and timestamp_local columns
datetime_clmn_gmt = "timestamp_gmt"
datetime_clmn_local = "timestamp_local"
dataframes[datetime_clmn_gmt] = np.nan
dataframes[datetime_clmn_local] = np.nan
item_row_nr = 0
for item in dataframes[dataframes.columns[datetime_clmn]]:
timestamps = datefinder.find_dates(str(item), first=first_val)
for timestamp in timestamps:
#If the timestamp is timezone aware
if timestamp.tzinfo is not None:
timestamp_utc = timestamp.astimezone(pytz.UTC)
timestamp_utc = datetime.datetime.strftime(
timestamp_utc, "%Y-%m-%d %H:%M:%S.%f")
timestamp_local = datetime.datetime.strftime(
timestamp, "%Y-%m-%d %H:%M:%S.%f %Z")
#If the timestamp is timezone naive
else:
local_timezone = pytz.timezone(timezone)
timestamp_local_tz = local_timezone.localize(timestamp,
is_dst=True)
timestamp_utc = timestamp_local_tz.astimezone(pytz.UTC)
timestamp_utc = datetime.datetime.strftime(
timestamp_utc, "%Y-%m-%d %H:%M:%S.%f")
timestamp_local = datetime.datetime.strftime(
timestamp_local_tz, "%Y-%m-%d %H:%M:%S.%f %Z")
#insert timestamp_utc and timezone_local values to the newly created df columns
row_index = dataframes.index[item_row_nr]
dataframes.loc[row_index, datetime_clmn_gmt] = timestamp_utc
dataframes.loc[row_index, datetime_clmn_local] = timestamp_local
item_row_nr += 1
cur.execute(sql_select_athlete_id, (ath_un, ))
result = cur.fetchone()
conn.commit()
ath_un_id = result[0]
dataframes['athlete_id'] = ath_un_id
cur.close()
#format column names to comply with postgres rules
dataframes.rename(columns={i: format_column_name(i)
for i in df.columns},
inplace=True)
#Get list of unique column names from column numbers (suplied by user) and add athlete_id column to the list
for i in unique:
x = unique.index(i)
unique[x] = dataframes.columns[i]
unique.append("athlete_id")
#Check if the table already exists
cur = conn.cursor()
cur.execute(
"SELECT EXISTS (SELECT FROM pg_tables WHERE tablename = '{}');".
format(table_name))
result = cur.fetchone()
conn.commit()
if result[0] is True:
with StdoutRedirection(ath_un):
print(
'The custom table {} already exists. Will now insert the new data'
.format(table_name))
with ProgressStdoutRedirection(ath_un):
print(
'The custom table {} already exists. Will now insert the new data'
.format(table_name))
pass
else:
with StdoutRedirection(ath_un):
print('Creating custom table: {}'.format(table_name))
with ProgressStdoutRedirection(ath_un):
print('Creating custom table: {}'.format(table_name))
cur.execute(gen_tbl_sql(ath_un, dataframes, table_name, unique))
conn.commit()
cur.close()
insert_df_values(ath_un, conn, dataframes, table_name, unique)
# close the communication with the PostgreSQL
if conn is not None:
conn.close()
def gc_wellness_insert(file_path, ath_un, db_host, db_name, superuser_un,
superuser_pw, encr_pass):
db_name = (db_name)
conn = None
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
#Create empty dataframe using sorted db fields as headers. This will be converted to empty dataframe and merged with xml dataframe
db_fields_list = {
'athlete_id', 'calendar_date', 'wellness_min_heart_rate',
'wellness_total_steps_goal', 'sleep_sleep_duration',
'wellness_floors_descended', 'wellness_floors_ascended',
'wellness_bodybattery_drained', 'wellness_max_heart_rate',
'wellness_total_distance', 'wellness_vigorous_intensity_minutes',
'food_calories_consumed', 'wellness_user_intensity_minutes_goal',
'wellness_common_active_calories', 'food_calories_remaining',
'wellness_moderate_intensity_minutes', 'wellness_bmr_calories',
'common_total_distance', 'wellness_active_calories',
'wellness_total_calories', 'wellness_resting_heart_rate',
'wellness_max_stress', 'wellness_average_steps',
'wellness_max_avg_heart_rate', 'wellness_abnormalhr_alerts_count',
'wellness_total_steps', 'wellness_average_stress',
'common_total_calories', 'wellness_user_floors_ascended_goal',
'wellness_min_avg_heart_rate', 'wellness_bodybattery_charged'
}
#Sort alphabeticaly
db_fields_list = sorted(db_fields_list)
db_df = pd.DataFrame(columns=db_fields_list)
#List to store XML tags for xml_df column names
column_list = []
#List to store XML values in xml_df dataframe and used as params for SQL insert/update query
xml_list = []
xml_list.append(ath_un)
column_list.append('athlete_id')
#Parse the XML document, and append the data to column_list and xml_list lists.
root = parse(file_path).getroot()
for startDate in root.iter('statisticsStartDate'):
date = startDate.text
xml_list.append(date)
column_list.append('calendar_date')
for category in root.findall('.//metricsMap/*'):
if category.tag != 'SLEEP_SLEEP_DURATION':
column_list.append(category.tag.lower())
for tag in root.iter(category.tag):
for item in tag.iterfind('item'):
xml_list.append(item.findtext('value'))
else:
column_list.append(category.tag.lower())
for tag in root.iter(category.tag):
for item in tag.iterfind('item'):
if item.findtext('calendarDate') == date:
xml_list.append(item.findtext('value'))
#Combine xml_list and column_list in a xml_df dataframe
xml_df = pd.DataFrame(xml_list).T # Write in DF and transpose it
xml_df.columns = column_list # Update column names
xml_df = xml_df.reindex(sorted(xml_df.columns),
axis=1) # Sort alphabeticaly
#Combine the dataframes
combined_df = db_df.append(xml_df)
#Drop all columns that do not exist as DB fields
combined_df = combined_df[db_fields_list]
#Export all values to list
df2list = combined_df.values.tolist()
#Flatten the list
df2list = [item for sublist in df2list for item in sublist]
#Build a list of parameters to pass to sql query
query_params = df2list + df2list
query_params.append(date)
# PG Amend path for postgres "pg_read_file()" function.
text = file_path
head, sep, tail = text.partition('temp/')
pg_read_file = (tail, )
list_sql = """
INSERT INTO garmin_connect_wellness (athlete_id, calendar_date, common_total_calories, common_total_distance, food_calories_consumed,
food_calories_remaining, sleep_duration, wellness_abnormalhr_alerts_count, wellness_active_calories, wellness_average_steps, wellness_average_stress,
wellness_bmr_calories, wellness_body_battery_drained, wellness_bodybattery_charged, wellness_common_active_calories, wellness_floors_ascended,
wellness_floors_descended, wellness_max_avg_heart_rate, wellness_max_heart_rate, wellness_max_stress, wellness_min_avg_heart_rate,
wellness_min_heart_rate, wellness_moderate_intensity_minutes, wellness_resting_heart_rate, wellness_total_calories, wellness_total_distance,
wellness_total_steps, wellness_total_steps_goal, wellness_user_floors_ascended_goal, wellness_user_intensity_goal, wellness_vigorous_intensity_minutes)
VALUES ((select id from athlete where ath_un=%s),%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
ON CONFLICT (calendar_date) DO UPDATE
SET (athlete_id, calendar_date, common_total_calories, common_total_distance, food_calories_consumed, food_calories_remaining, sleep_duration,
wellness_abnormalhr_alerts_count, wellness_active_calories, wellness_average_steps, wellness_average_stress, wellness_bmr_calories,
wellness_body_battery_drained, wellness_bodybattery_charged, wellness_common_active_calories, wellness_floors_ascended, wellness_floors_descended,
wellness_max_avg_heart_rate, wellness_max_heart_rate, wellness_max_stress, wellness_min_avg_heart_rate, wellness_min_heart_rate,
wellness_moderate_intensity_minutes, wellness_resting_heart_rate, wellness_total_calories, wellness_total_distance, wellness_total_steps,
wellness_total_steps_goal, wellness_user_floors_ascended_goal, wellness_user_intensity_goal, wellness_vigorous_intensity_minutes)
= ((select id from athlete where ath_un=%s),%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
WHERE garmin_connect_wellness.calendar_date
= %s;
"""
try:
# connect to the PostgreSQL server
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
# create a cursor
cur = conn.cursor()
# execute a statement
with StdoutRedirection(ath_un):
print('Inserting Wellness Data into postgreSQL:')
with ProgressStdoutRedirection(ath_un):
print('Inserting Wellness Data into postgreSQL:')
#cur.execute(xpath_sql,(athlete_id,pg_read_file,athlete_id,file2import,file2import,file2import))
cur.execute(list_sql, (query_params))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(error)))
finally:
if conn is not None:
conn.close()
with StdoutRedirection(ath_un):
print('Wellness Data Inserted Successfully')
with ProgressStdoutRedirection(ath_un):
print('Wellness Data Inserted Successfully')
def gc_original_record_insert(file_path,activity_id,ath_un,db_host,db_name,superuser_un,superuser_pw, encr_pass):
start=time.time()
file2import = (file_path)
gc_activity_id = (activity_id)
ath_un = (ath_un)
db_name = (db_name)
activity_type,altitude,cadence,distance,enhanced_altitude,enhanced_speed,fractional_cadence,heart_rate,position_lat,position_long,speed,stance_time,stance_time_balance,step_length,timestamp,vertical_oscillation,vertical_ratio,accumulated_power,left_pedal_smoothness,left_torque_effectiveness,power,right_pedal_smoothness,right_torque_effectiveness,temperature,avg_speed,avg_swimming_cadence,event,event_group,event_type,length_type,message_index,start_time,swim_stroke,total_calories,total_elapsed_time,total_strokes,total_timer_time,est_core_temp = [None]*38
hrv_record_list = (None, None, None, None)
hrv_record_list_combined = []
hrv_rmssd = None
hrv_sdrr = None
hrv_pnn50 = None
hrv_pnn20 = None
fitfile = FitFile(file2import)
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
conn = None
# connect to the PostgreSQL server
conn = psycopg2.connect(dbname=db_name, host=db_host, user=superuser_un,password=superuser_pw)
# two-phase insert prepapre
conn.tpc_begin(conn.xid(42, 'transaction ID', ath_un))
# Get all data messages that are of type record
for record in fitfile.get_messages('record'):
# Go through all the data entries in this record
for record_data in record:
if record_data.name == 'activity_type':
activity_type = record_data.value
if record_data.name == 'altitude':
altitude = record_data.value
if record_data.name == 'cadence':
cadence = record_data.value
if record_data.name == 'distance':
distance = record_data.value
if record_data.name == 'enhanced_altitude':
enhanced_altitude = record_data.value
if record_data.name == 'enhanced_speed':
enhanced_speed = record_data.value
if record_data.name == 'fractional_cadence':
fractional_cadence = record_data.value
if record_data.name == 'heart_rate':
heart_rate = record_data.value
if record_data.name == 'position_lat':
position_lat = record_data.value
if record_data.name == 'position_long':
position_long = record_data.value
if record_data.name == 'speed':
speed = record_data.value
if record_data.name == 'stance_time':
stance_time = record_data.value
if record_data.name == 'stance_time_balance':
stance_time_balance = record_data.value
if record_data.name == 'step_length':
step_length = record_data.value
if record_data.name == 'timestamp':
timestamp = record_data.value
if record_data.name == 'vertical_oscillation':
vertical_oscillation = record_data.value
if record_data.name == 'vertical_ratio':
vertical_ratio = record_data.value
if record_data.name == 'accumulated_power':
accumulated_power = record_data.value
if record_data.name == 'left_pedal_smoothness':
left_pedal_smoothness = record_data.value
if record_data.name == 'left_torque_effectiveness':
left_torque_effectiveness = record_data.value
if record_data.name == 'power':
power = record_data.value
if record_data.name == 'right_pedal_smoothness':
right_pedal_smoothness = record_data.value
if record_data.name == 'right_torque_effectiveness':
right_torque_effectiveness = record_data.value
if record_data.name == 'temperature':
temperature = record_data.value
if record_data.name == 'Est Core Temp':
est_core_temp = record_data.value
sql = """
INSERT INTO garmin_connect_original_record (activity_type,altitude,cadence,distance,enhanced_altitude,enhanced_speed,fractional_cadence,heart_rate,position_lat
,position_long,speed,stance_time,stance_time_balance,step_length,timestamp,vertical_oscillation,vertical_ratio,accumulated_power
,left_pedal_smoothness,left_torque_effectiveness,power,right_pedal_smoothness,right_torque_effectiveness,temperature,est_core_temp,lap_id)
VALUES
(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,(select id from garmin_connect_original_lap where timestamp >= %s and start_time < %s LIMIT 1))
ON CONFLICT (timestamp,lap_id) DO NOTHING;
"""
try:
# create a cursor
cur = conn.cursor()
# execute a statement
with StdoutRedirection(ath_un):
print(('Inserting track record from session: ' + str(gc_activity_id) + ' with timestamp:' + str(timestamp)))
cur.execute(sql,(activity_type,altitude,cadence,distance,enhanced_altitude,enhanced_speed,fractional_cadence,heart_rate,position_lat,position_long,speed,stance_time,
stance_time_balance,step_length,timestamp,vertical_oscillation,vertical_ratio,accumulated_power,left_pedal_smoothness,left_torque_effectiveness,
power,right_pedal_smoothness,right_torque_effectiveness,temperature,est_core_temp,str(timestamp),str(timestamp)))
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' + sys._getframe().f_code.co_name + ']' + ' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) + ' ' + str(error)))
# Get all data messages that are of type hrv
for record in fitfile.get_messages('hrv'):
# Go through all the data entries in this record
for record_data in record:
if record_data.name == 'time':
hrv_record_list = record_data.value
for i in hrv_record_list:
if i != None:
hrv_record = i
hrv_record_list_combined.append(hrv_record*1000)
sql_hrv = """
INSERT INTO garmin_connect_hrv_tracking(gc_activity_id,hrv)
VALUES
(%s,%s);
"""
try:
# create a cursor
cur = conn.cursor()
# execute a statement
with StdoutRedirection(ath_un):
print(('Inserting hrv record from session: ' + str(gc_activity_id)))
cur.execute(sql_hrv,(gc_activity_id,hrv_record))
# close the communication with the PostgreSQL
cur.close()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' + sys._getframe().f_code.co_name + ']' + ' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) + ' ' + str(e)))
else:
continue
# two-phase insert commit or rollback
try:
conn.tpc_prepare()
except (Exception, psycopg2.DatabaseError) as error:
conn.tpc_rollback()
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' + sys._getframe().f_code.co_name + ']' + ' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) + ' ' + str(error)))
else:
try:
conn.tpc_commit()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' + sys._getframe().f_code.co_name + ']' + ' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) + ' ' + str(e)))
#PG: Add Pool Swim specific data
for record in fitfile.get_messages('sport'):
for record_data in record:
sport = record_data.value
if sport == 'Pool Swim':
with StdoutRedirection(ath_un):
print(('Activity ' + str(gc_activity_id) + ' is a Pool Swim. Inserting additional data'))
for record in fitfile.get_messages('length'):
for record_data in record:
if record_data.name == 'avg_speed':
avg_speed = record_data.value
if record_data.name == 'avg_swimming_cadence':
avg_swimming_cadence = record_data.value
if record_data.name == 'event_group':
event_group = record_data.value
if record_data.name == 'event_type':
event_type = record_data.value
if record_data.name == 'length_type':
length_type = record_data.value
if record_data.name == 'message_index':
message_index = record_data.value
if record_data.name == 'start_time':
start_time = record_data.value
if record_data.name == 'swim_stroke':
swim_stroke = record_data.value
if record_data.name == 'timestamp':
timestamp = record_data.value
if record_data.name == 'total_calories':
total_calories = record_data.value
if record_data.name == 'total_elapsed_time':
total_elapsed_time = record_data.value
if record_data.name == 'total_strokes':
total_strokes = record_data.value
if record_data.name == 'total_timer_time':
total_timer_time = record_data.value
sql_swim = """
CREATE TEMPORARY TABLE temp_garmin_connect_original_record(avg_speed real,avg_swimming_cadence int,event varchar,event_group varchar,event_type varchar,length_type varchar,message_index int
,start_time varchar,swim_stroke varchar,total_calories int,total_elapsed_time real,total_strokes int,total_timer_time real, timestamp varchar) ON COMMIT DROP;
INSERT INTO temp_garmin_connect_original_record (avg_speed,avg_swimming_cadence,event,event_group,event_type,length_type,message_index
,start_time,swim_stroke,total_calories,total_elapsed_time,total_strokes,total_timer_time,timestamp)
VALUES
(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s);
UPDATE garmin_connect_original_record
SET avg_speed = temp_garmin_connect_original_record.avg_speed,
avg_swimming_cadence = temp_garmin_connect_original_record.avg_swimming_cadence,
event = temp_garmin_connect_original_record.event,
event_group = temp_garmin_connect_original_record.event_group,
event_type = temp_garmin_connect_original_record.event_type,
length_type = temp_garmin_connect_original_record.length_type,
message_index = temp_garmin_connect_original_record.message_index,
start_time = temp_garmin_connect_original_record.start_time,
swim_stroke = temp_garmin_connect_original_record.swim_stroke,
total_calories = temp_garmin_connect_original_record.total_calories,
total_elapsed_time = temp_garmin_connect_original_record.total_elapsed_time,
total_strokes = temp_garmin_connect_original_record.total_strokes,
total_timer_time = temp_garmin_connect_original_record.total_timer_time
FROM temp_garmin_connect_original_record
WHERE temp_garmin_connect_original_record.timestamp = garmin_connect_original_record.timestamp and garmin_connect_original_record.gc_activity_id = %s;
"""
try:
# create a cursor
cur = conn.cursor()
# execute a statement
with StdoutRedirection(ath_un):
print(('Inserting Pool swim data record from session: ' + str(gc_activity_id) + ' with timestamp:' + str(timestamp)))
cur.execute(sql_swim,(avg_speed,avg_swimming_cadence,event,event_group,event_type,length_type,message_index,start_time,swim_stroke,total_calories,total_elapsed_time,total_strokes,total_timer_time,timestamp,gc_activity_id))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' + sys._getframe().f_code.co_name + ']' + ' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) + ' ' + str(e)))
with StdoutRedirection(ath_un):
print(('--- All record data for session: ' + str(gc_activity_id) + ' inserted successfully. ---'))
with ProgressStdoutRedirection(ath_un):
print(('--- All record data for session: ' + str(gc_activity_id) + ' inserted successfully. ---'))
#Correct Errors. Change all values with SD > 2 to mean
hrv_record_list_combined = np.array(hrv_record_list_combined)
hrv_record_list_combined[np.abs(zscore(hrv_record_list_combined)) > 2] = np.median(hrv_record_list_combined)
#Calculate the square root of the mean square of the differences of RR-intervals
hrv_rmssd = np.sqrt(np.mean(np.square(np.diff(hrv_record_list_combined))))
#Calculate the standard deviation of the RR-intervals
hrv_sdrr = np.std(hrv_record_list_combined)
#Calculate the number of pairs of successive RR-intervals that differ by more than 50/20 ms
nn50 = np.sum(np.abs(np.diff(hrv_record_list_combined)) > 50)*1
nn20 = np.sum(np.abs(np.diff(hrv_record_list_combined)) > 20)*1
#Calculate he proportion of NN50/NN20 divided by the total number of RR-intervals.
hrv_pnn50 = 100 * nn50 / len(hrv_record_list_combined)
hrv_pnn20 = 100 * nn20 / len(hrv_record_list_combined)
sql_hrv_stats = '''
UPDATE garmin_connect_original_session
SET hrv_rmssd = %s,
hrv_sdrr = %s,
hrv_pnn50 = %s,
hrv_pnn20 = %s
WHERE gc_activity_id = %s;
'''
try:
# create a cursor
cur = conn.cursor()
# execute a statement
with StdoutRedirection(ath_un):
print(('Inserting hrv stats for session: ' + str(gc_activity_id)))
cur.execute(sql_hrv_stats,(hrv_rmssd,hrv_sdrr,hrv_pnn50,hrv_pnn20,gc_activity_id))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' + sys._getframe().f_code.co_name + ']' + ' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) + ' ' + str(e)))
# close the communication with the PostgreSQL
if conn is not None:
conn.close()
end = time.time()
with ProgressStdoutRedirection(ath_un):
print('\nExecution_time:')
with ProgressStdoutRedirection(ath_un):
print((end-start))
def gc_bodycomposition_insert(file_path, ath_un, db_host, db_name,
superuser_un, superuser_pw, encr_pass):
""" Connect to the PostgreSQL database server """
athlete_id = (ath_un, )
db_name = (db_name)
body_water = []
muscle_mass_gm = []
visceral_fat = []
weight_gm = []
bmi = []
body_fat = []
physique_rating = []
timestamp = []
calendar_date = []
metabolic_age = []
bone_mass_gm = []
caloric_intake = []
source_type = []
conn = None
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
# PG Amend path for postgres "pg_read_file()" function.
text = file_path
head, sep, tail = text.partition('temp/')
pg_read_file = (tail, )
sql = """
INSERT INTO garmin_connect_body_composition(athlete_id,body_water,muscle_mass_gm,visceral_fat,weight_gm,bmi,
body_fat,physique_rating,timestamp,calendar_date,metabolic_age,
bone_mass_gm,caloric_intake,source_type)
SELECT
(select id from athlete where ath_un=%s),
unnest (xpath('//*[local-name()="item"]/*[local-name()="bodyWater"]/text()', x))::text::numeric AS body_water,
unnest (xpath('//*[local-name()="item"]/*[local-name()="muscleMass"]/text()', x))::text::int AS muscle_mass_gm,
unnest (xpath('//*[local-name()="item"]/*[local-name()="visceralFat"]/text()', x))::text::int AS visceral_fat,
unnest (xpath('//*[local-name()="item"]/*[local-name()="weight"]/text()', x))::text::numeric AS weight_gm,
unnest (xpath('//*[local-name()="item"]/*[local-name()="bmi"]/text()', x))::text::numeric AS bmi,
unnest (xpath('//*[local-name()="item"]/*[local-name()="bodyFat"]/text()', x))::text::numeric AS body_fat,
unnest (xpath('//*[local-name()="item"]/*[local-name()="physiqueRating"]/text()', x))::text::text AS physique_rating,
to_char(to_timestamp(unnest (xpath('//*[local-name()="item"]/*[local-name()="samplePk"]/text()', x))::text::numeric/1000) AT TIME ZONE 'UTC','YYYY-MM-DD HH24:MI:SS') AS timestamp,
unnest (xpath('//*[local-name()="item"]/*[local-name()="calendarDate"]/text()', x))::text::text AS calendar_date,
unnest (xpath('//*[local-name()="item"]/*[local-name()="metabolicAge"]/text()', x))::text::text AS metabolic_age,
unnest (xpath('//*[local-name()="item"]/*[local-name()="boneMass"]/text()', x))::text::int AS bone_mass_gm,
unnest (xpath('//*[local-name()="item"]/*[local-name()="caloricIntake"]/text()', x))::text::text AS caloric_intake,
unnest (xpath('//*[local-name()="item"]/*[local-name()="sourceType"]/text()', x))::text::text AS source_type
FROM UNNEST (xpath('//*[local-name()="root"]', pg_read_file(%s)::xml)) x
ON CONFLICT (athlete_id,timestamp) DO NOTHING;
"""
pd_df_sql = """
INSERT INTO garmin_connect_body_composition(athlete_id,body_water,muscle_mass_gm,visceral_fat,weight_gm,bmi,
body_fat,physique_rating,timestamp,calendar_date,metabolic_age,
bone_mass_gm,caloric_intake,source_type)
VALUES ((select id from athlete where ath_un=%s),%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
ON CONFLICT (athlete_id,timestamp) DO NOTHING;
"""
#Parse the XML document, and append the data to lists
xml_document = parse(file_path)
for item in xml_document.iterfind('item'):
body_water.append(item.findtext('bodyWater'))
muscle_mass_gm.append(item.findtext('muscleMass'))
visceral_fat.append(item.findtext('visceralFat'))
weight_gm.append(item.findtext('weight'))
bmi.append(item.findtext('bmi'))
body_fat.append(item.findtext('bodyFat'))
physique_rating.append(item.findtext('physiqueRating'))
timestamp.append(
datetime.datetime.utcfromtimestamp(
float(item.findtext('samplePk')) /
1000).strftime('%Y-%m-%d %H:%M:%S'))
calendar_date.append(item.findtext('calendarDate'))
metabolic_age.append(item.findtext('metabolicAge'))
bone_mass_gm.append(item.findtext('boneMass'))
caloric_intake.append(item.findtext('caloricIntake'))
source_type.append(item.findtext('sourceType'))
#Get the data from lists to dataframe
df = pd.DataFrame({
'body_water': body_water,
'muscle_mass_gm': muscle_mass_gm,
'visceral_fat': visceral_fat,
'weight_gm': weight_gm,
'bmi': bmi,
'body_fat': body_fat,
'physique_rating': physique_rating,
'timestamp': timestamp,
'calendar_date': calendar_date,
'metabolic_age': metabolic_age,
'bone_mass_gm': bone_mass_gm,
'caloric_intake': caloric_intake,
'source_type': source_type
})
#Replace empty string with None.Required for SQL insert
df.replace(r'', np.nan, inplace=True)
df = df.where(pd.notnull(df), None)
try:
# connect to the PostgreSQL server
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
# create a cursor
cur = conn.cursor()
with StdoutRedirection(ath_un):
print('Inserting Body composition Data into postgreSQL:')
with ProgressStdoutRedirection(ath_un):
print('Inserting Body composition Data into postgreSQL:')
#Iterate through rows in pandas dataframe
for row in df.itertuples():
df_body_water = row.body_water
df_muscle_mass_gm = row.muscle_mass_gm
df_visceral_fat = row.visceral_fat
df_weight_gm = row.weight_gm
df_bmi = row.bmi
df_body_fat = row.body_fat
df_physique_rating = row.physique_rating
df_timestamp = row.timestamp
df_calendar_date = row.calendar_date
df_metabolic_age = row.metabolic_age
df_bone_mass_gm = row.bone_mass_gm
df_caloric_intake = row.caloric_intake
df_source_type = row.source_type
cur.execute(
pd_df_sql,
(athlete_id, df_body_water, df_muscle_mass_gm, df_visceral_fat,
df_weight_gm, df_bmi, df_body_fat, df_physique_rating,
df_timestamp, df_calendar_date, df_metabolic_age,
df_bone_mass_gm, df_caloric_intake, df_source_type))
### Insert using Xpath method ###
#cur.execute(xpath_sql,(athlete_id,pg_read_file))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(error)))
finally:
if conn is not None:
conn.close()
with StdoutRedirection(ath_un):
print('Body composition Data Inserted Successfully')
def gc_activity_insert(file_path, ath_un, activity, db_host, db_name,
superuser_un, superuser_pw, encr_pass):
""" Connect to the PostgreSQL database server """
file2import = (file_path, )
athlete_id = (ath_un, )
activity_id = (activity, )
db_name = db_name
conn = None
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
sql = """DO
$do$
BEGIN
IF
(SELECT
count(xpath('//*[local-name()="Lap"]/@StartTime', x))::text::int
FROM unnest(xpath('//*[local-name()="Lap"]', pg_read_file(%s)::xml)) x) = 1
THEN
INSERT INTO garmin_connect_activity (activity_timestamp,sport,athlete_id,gc_activity_id)
SELECT
(xpath('//*[local-name()="Activity"]/*[local-name()="Id"]/text()', x))[1]::text::text AS activity_timestamp,
(xpath('//*[local-name()="Activity"]/@Sport', x))[1]::text::text AS sport,
(select id from athlete where ath_un=%s),
%s
FROM UNNEST
(xpath('//*[local-name()="Activity"]',pg_read_file(%s)::xml)) x;
INSERT INTO garmin_connect_lap (gc_activity_id,lap_id,activity_timestamp,total_time_seconds,distance_meters,maximum_speed,calories,average_hr_bpm,maximum_hr_bpm,intensity,cadence,trigger_method,
extensions_ns3_lx_avgspeed,extensions_ns3_lx_maxbikecadence,extensions_ns3_lx_steps,extensions_ns3_lx_avgwatts,extensions_ns3_lx_maxwatts,extensions_ns3_lx_avgruncadence,
extensions_ns3_lx_maxruncadence)
SELECT
%s,
unnest (xpath('//*[local-name()="Lap"]/@StartTime', x))::text::text AS lap_id,
(xpath('//*[local-name()="Activity"]/*[local-name()="Id"]/text()', x))[1]::text::text AS activity_timestamp,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="TotalTimeSeconds"]/text()', x))::text::numeric AS total_time_seconds,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="DistanceMeters"]/text()', x))::text::numeric AS distance_meters,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="MaximumSpeed"]/text()', x))::text::numeric AS maximum_speed,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Calories"]/text()', x))::text::numeric AS calories,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="AverageHeartRateBpm"]/*[local-name()="Value"]/text()', x))::text::integer AS average_hr_bpm,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="MaximumHeartRateBpm"]/*[local-name()="Value"]/text()', x))::text::integer AS maximum_hr_bpm,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Intensity"]/text()', x))::text::text AS intensity,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Cadence"]/text()', x))::text::integer AS cadence,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="TriggerMethod"]/text()', x))::text::text AS trigger_method,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="AvgSpeed"]/text()', x))::text::numeric AS extensions_ns3_lx_avgspeed,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="MaxBikeCadence"]/text()', x))::text::integer AS extensions_ns3_lx_maxbikecadence,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="Steps"]/text()', x))::text::integer AS extensions_ns3_lx_steps,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="AvgWatts"]/text()', x))::text::integer AS extensions_ns3_lx_avgwatts,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="MaxWatts"]/text()', x))::text::integer AS extensions_ns3_lx_maxwatts,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="AvgRunCadence"]/text()', x))::text::integer AS extensions_ns3_lx_avgruncadence,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="MaxRunCadence"]/text()', x))::text::integer AS extensions_ns3_lx_maxruncadence
FROM UNNEST (xpath('//*[local-name()="Activity"]', pg_read_file(%s)::xml)) x;
INSERT INTO garmin_connect_trackpoint (trackpoint_time, lap_id, position_latitude_degrees, position_longitude_degrees,altitude_meters,distance_meters,hr_bpm,extensions_ns3_tpx_speed,extensions_ns3_tpx_watts,extensions_ns3_tpx_runcadence)
SELECT
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="Time"]/text()', x))::text::text AS trackpoint_time,
(select unnest (xpath('//*[local-name()="Lap"]/@StartTime', x))::text::text AS lap_id
from unnest(xpath('//*[local-name()="Lap"]', pg_read_file(%s)::xml)) x),
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="Position"]/*[local-name()="LatitudeDegrees"]/text()', x))::text::numeric AS position_latitude_degrees,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="Position"]/*[local-name()="LongitudeDegrees"]/text()', x))::text::numeric AS position_longitude_degrees,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="AltitudeMeters"]/text()', x))::text::numeric AS altitude_meters,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="DistanceMeters"]/text()', x))::text::numeric AS distance_meters,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="HeartRateBpm"]/*[local-name()="Value"]/text()', x))::text::integer AS hr_bpm,
unnest(xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/*[local-name()="Extensions"]
/*[local-name()="TPX"]/*[local-name()="Speed"]/text()', x))::text::numeric AS extensions_ns3_tpx_speed,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/*[local-name()="Extensions"]
/*[local-name()="TPX"]/*[local-name()="Watts"]/text()', x))::text::integer AS extensions_ns3_tpx_watts,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/*[local-name()="Extensions"]
/*[local-name()="TPX"]/*[local-name()="RunCadence"]/text()', x))::text::integer AS extensions_ns3_tpx_runcadence
FROM unnest(xpath('//*[local-name()="Lap"]', pg_read_file(%s)::xml)) x;
ELSE
INSERT INTO garmin_connect_activity (activity_timestamp,sport,athlete_id,gc_activity_id)
SELECT
(xpath('//*[local-name()="Activity"]/*[local-name()="Id"]/text()', x))[1]::text::text AS activity_timestamp,
(xpath('//*[local-name()="Activity"]/@Sport', x))[1]::text::text AS sport,(select id from athlete where ath_un=%s),
%s
FROM UNNEST (xpath('//*[local-name()="Activity"]',pg_read_file(%s)::xml)) x;
INSERT INTO garmin_connect_lap (gc_activity_id,lap_id,activity_timestamp,total_time_seconds,distance_meters,maximum_speed,calories,average_hr_bpm,maximum_hr_bpm,intensity,cadence,trigger_method,
extensions_ns3_lx_avgspeed,extensions_ns3_lx_maxbikecadence,extensions_ns3_lx_steps,extensions_ns3_lx_avgwatts,extensions_ns3_lx_maxwatts,extensions_ns3_lx_avgruncadence,
extensions_ns3_lx_maxruncadence)
SELECT
%s,
unnest (xpath('//*[local-name()="Lap"]/@StartTime', x))::text::text AS lap_id,
(xpath('//*[local-name()="Activity"]/*[local-name()="Id"]/text()', x))[1]::text::text AS activity_timestamp,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="TotalTimeSeconds"]/text()', x))::text::numeric AS total_time_seconds,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="DistanceMeters"]/text()', x))::text::numeric AS distance_meters,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="MaximumSpeed"]/text()', x))::text::numeric AS maximum_speed,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Calories"]/text()', x))::text::numeric AS calories,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="AverageHeartRateBpm"]/*[local-name()="Value"]/text()', x))::text::integer AS average_hr_bpm,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="MaximumHeartRateBpm"]/*[local-name()="Value"]/text()', x))::text::integer AS maximum_hr_bpm,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Intensity"]/text()', x))::text::text AS intensity,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Cadence"]/text()', x))::text::integer AS cadence,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="TriggerMethod"]/text()', x))::text::text AS trigger_method,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="AvgSpeed"]/text()', x))::text::numeric AS extensions_ns3_lx_avgspeed,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="MaxBikeCadence"]/text()', x))::text::integer AS extensions_ns3_lx_maxbikecadence,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="Steps"]/text()', x))::text::integer AS extensions_ns3_lx_steps,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="AvgWatts"]/text()', x))::text::integer AS extensions_ns3_lx_avgwatts,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="MaxWatts"]/text()', x))::text::integer AS extensions_ns3_lx_maxwatts,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="AvgRunCadence"]/text()', x))::text::integer AS extensions_ns3_lx_avgruncadence,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Extensions"]/*[local-name()="LX"]/*[local-name()="MaxRunCadence"]/text()', x))::text::integer AS extensions_ns3_lx_maxruncadence
FROM UNNEST (xpath('//*[local-name()="Activity"]', pg_read_file(%s)::xml)) x;
INSERT INTO garmin_connect_trackpoint (trackpoint_time, lap_id, position_latitude_degrees, position_longitude_degrees,altitude_meters,distance_meters,hr_bpm,extensions_ns3_tpx_speed,extensions_ns3_tpx_watts,extensions_ns3_tpx_runcadence)
SELECT
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="Time"]/text()', x))::text::text AS trackpoint_time,
(xpath('//*[local-name()="Lap"]/@StartTime', x))[1]::text::text AS lap_id,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="Position"]/*[local-name()="LatitudeDegrees"]/text()', x))::text::numeric AS position_latitude_degrees,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="Position"]/*[local-name()="LongitudeDegrees"]/text()', x))::text::numeric AS position_longitude_degrees,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="AltitudeMeters"]/text()', x))::text::numeric AS altitude_meters,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="DistanceMeters"]/text()', x))::text::numeric AS distance_meters,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/
*[local-name()="HeartRateBpm"]/*[local-name()="Value"]/text()', x))::text::integer AS hr_bpm,
unnest(xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/*[local-name()="Extensions"]
/*[local-name()="TPX"]/*[local-name()="Speed"]/text()', x))::text::numeric AS extensions_ns3_tpx_speed,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/*[local-name()="Extensions"]
/*[local-name()="TPX"]/*[local-name()="Watts"]/text()', x))::text::integer AS extensions_ns3_tpx_watts,
unnest (xpath('//*[local-name()="Lap"]/*[local-name()="Track"]/*[local-name()="Trackpoint"]/*[local-name()="Extensions"]
/*[local-name()="TPX"]/*[local-name()="RunCadence"]/text()', x))::text::integer AS extensions_ns3_tpx_runcadence
FROM unnest(xpath('//*[local-name()="Lap"]', pg_read_file(%s)::xml)) x;
END IF;
END
$do$
"""
try:
# connect to the PostgreSQL server
with ProgressStdoutRedirection(ath_un):
print(
'Connecting to the PostgreSQL server to insert TCX activity data...'
)
try:
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
except Exception as e:
with ProgressStdoutRedirection(ath_un):
print(
(str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(e)))
# create a cursor
try:
cur = conn.cursor()
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print(
(str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(e)))
# execute a statement
with StdoutRedirection(ath_un):
print('Inserting Activity Data into postgreSQL:')
with ProgressStdoutRedirection(ath_un):
print('Inserting Activity Data into postgreSQL:')
cur.execute(
sql,
(file2import, athlete_id, activity_id, file2import, activity_id,
file2import, file2import, file2import, athlete_id, activity_id,
file2import, activity_id, file2import, file2import))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.IntegrityError) as ex:
if ex.pgcode == '23505':
with StdoutRedirection(ath_un):
print(
'The record for this activity already exists in the database.Skipping...'
)
with ErrorStdoutRedirection(ath_un):
print(
'The record for this activity already exists in the database.Skipping...'
)
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
' ' + str(error)))
finally:
if conn is not None:
conn.close()
def mm_data_insert(output, start_date, end_date, ath_un, encr_pass,
mm_dbx_link, save_pwd, db_host, db_name, superuser_un,
superuser_pw):
# Before executing the script go to your droppox Apps/Mind Monitor folder.
# Right click on the folder, select 'Share' option and copy the generated link.
# Assign the link string to the 'mm_dbx_link' parameter.
user_output = os.path.join(output, ath_un)
download_folder = os.path.join(user_output, 'MM_Historical_EEG')
archive_folder = os.path.join(download_folder, 'Archive')
#Get PID of the current process and write it in the file
pid = str(os.getpid())
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
path_params = config(filename="encrypted_settings.ini", section="archive")
preserve_files = str(path_params.get("preserve_files"))
if save_pwd == True:
encrypted_link = base64.b64encode(encrypt(mm_dbx_link, encr_pass))
encrypted_link = encrypted_link.decode('utf-8')
else:
encrypted_link = None
#PG: insert MM export link into database
mm_user_insert(encrypted_link, ath_un, db_host, db_name, superuser_un,
superuser_pw, encr_pass)
# Download the MM export csv file from dropbox using share link
mm_dbx_link = mm_dbx_link[:-1] + '1' # Replace the 0 at the end of the link with 1.Will download as .zip file.
response = urllib.request.urlopen(mm_dbx_link)
# Extract the downloaded folder in to variable
compressedFile = io.BytesIO()
compressedFile.write(response.read())
compressedFile.seek(0)
#Check if the date variable are of string or datetime type
if type(start_date) == str: #Script run as standalone
start_date_dt = datetime.datetime.strptime(start_date, "%Y-%m-%d")
else: #Script run from flask server (variable passes as datetime type)
start_date_dt = start_date
if type(end_date) == str: #Script run as standalone
end_date_dt = datetime.datetime.strptime(end_date, "%Y-%m-%d")
else: #Script run from flask server (variable passes as datetime type)
end_date_dt = end_date
# Create output directory (if it does not already exist).
if not os.path.exists(download_folder):
os.makedirs(download_folder)
# Create Archive directory (if it does not already exist).
if preserve_files == "true":
if not os.path.exists(archive_folder):
os.makedirs(archive_folder)
with zipfile.ZipFile(compressedFile, 'r') as z:
#List the content of the zip file
zipfile_content = z.namelist()
#Iterate through list and only extract files within date range
for item in zipfile_content:
#Extract date from filename
item_date = item[12:22]
if item_date != '':
item_date_dt = datetime.datetime.strptime(
item_date, "%Y-%m-%d")
else:
continue
# Check if the file date is within the download Date range.
if item_date_dt > end_date_dt + datetime.timedelta(
days=1) or item_date_dt < start_date_dt:
continue
else:
#PG: Check whether the data from this file "file_path" have been inserted into to DB during one of the previous runs
data_file_exists = check_data_file_exists(
os.path.join(download_folder, item), ath_un, db_host,
db_name, superuser_un, superuser_pw, encr_pass)
if data_file_exists == True:
with StdoutRedirection(ath_un):
print(('{} already exists in {}. Skipping.'.format(
item, download_folder)))
with ProgressStdoutRedirection(ath_un):
print(('{} already exists in {}. Skipping.'.format(
item, download_folder)))
continue
z.extract(item, download_folder)
#Insert filepath into the db
try:
data_file_path_insert(os.path.join(download_folder,
item), ath_un, db_host,
db_name, superuser_un, superuser_pw,
encr_pass)
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(
sys.exc_info()[-1].tb_lineno) + ' ' +
str(e)))
for filename in os.listdir(download_folder):
if filename.endswith(".zip"):
with zipfile.ZipFile(os.path.join(download_folder, filename),
'r') as z:
z.extractall(download_folder)
os.remove(os.path.join(download_folder, filename))
with StdoutRedirection(ath_un):
print((
'The content of \"{}\" extracted into csv and the original removed'
.format(filename)))
with ProgressStdoutRedirection(ath_un):
print((
'The content of \"{}\" extracted into csv and the original removed'
.format(filename)))
db_name = str(str2md5(ath_un)) + '_Athlete_Data_DB'
conn = None
# connect to the PostgreSQL server
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
sql = """
INSERT INTO mind_monitor_eeg(timestamp,delta_tp9,
delta_af7,delta_af8,delta_tp10,athlete_id,theta_tp9,theta_af7,theta_af8,theta_tp10,alpha_tp9,alpha_af7,alpha_af8,alpha_tp10,beta_tp9,beta_af7,beta_af8,
beta_tp10,gamma_tp9,gamma_af7,gamma_af8,gamma_tp10,raw_tp9,raw_af7,raw_af8,raw_tp10,aux_right,accelerometer_x,accelerometer_y,accelerometer_z,
gyro_x,gyro_y,gyro_z,head_band_on,hsi_tp9,hsi_af7,hsi_af8,hsi_tp10,battery,elements,timestamp_gmt)
VALUES
(%s,%s,%s,%s,%s,(select id from athlete where ath_un=%s),%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s
,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)
ON CONFLICT (athlete_id,timestamp) DO NOTHING;
"""
sql_local2gmt = """
SELECT gmt_local_difference FROM gmt_local_time_difference WHERE local_date = %s;
"""
for filename in os.listdir(download_folder):
if filename.endswith(".csv"):
# Read/Parse the .csv file and load the data into pandas dataset
with StdoutRedirection(ath_un):
print(
('Parsing and inserting the content of \"{}\" into the DB'.
format(filename)))
with ProgressStdoutRedirection(ath_un):
print(
('Parsing and inserting the content of \"{}\" into the DB'.
format(filename)))
dataset = pd.read_csv(os.path.join(download_folder, filename),
sep=",",
header=None)
dataset.drop(dataset.index[:1], inplace=True) #Drop the first row
for row in dataset.itertuples():
local_time = row._1
local_time_dt = datetime.datetime.strptime(
(local_time), "%Y-%m-%d %H:%M:%S.%f")
local_time_str = datetime.datetime.strftime(
local_time_dt, "%Y-%m-%d %H:%M:%S.%f")
local_date_str = datetime.datetime.strftime((local_time_dt),
"%Y-%m-%d")
utc_time_str = None
delta_tp9 = row._2
delta_af7 = row._3
delta_af8 = row._4
delta_tp10 = row._5
theta_tp9 = row._6
theta_af7 = row._7
theta_af8 = row._8
theta_tp10 = row._9
alpha_tp9 = row._10
alpha_af7 = row._11
alpha_af8 = row._12
alpha_tp10 = row._13
beta_tp9 = row._14
beta_af7 = row._15
beta_af8 = row._16
beta_tp10 = row._17
gamma_tp9 = row._18
gamma_af7 = row._19
gamma_af8 = row._20
gamma_tp10 = row._21
raw_tp9 = row._22
raw_af7 = row._23
raw_af8 = row._24
raw_tp10 = row._25
aux_right = row._26
accelerometer_x = row._27
accelerometer_y = row._28
accelerometer_z = row._29
gyro_x = row._30
gyro_y = row._31
gyro_z = row._32
head_band_on = row._33
hsi_tp9 = row._34
hsi_af7 = row._35
hsi_af8 = row._36
hsi_tp10 = row._37
battery = row._38
elements = row._39
# Check if the Record Date is within the download Date range.
if local_time_dt > end_date_dt + datetime.timedelta(
days=1) or local_time_dt < start_date_dt:
break
else:
try:
# create a cursor
cur = conn.cursor()
# execute a statement
cur.execute(sql_local2gmt, (local_date_str, ))
result = cur.fetchone()
# close the communication with the PostgreSQL
conn.commit()
cur.close()
if result is not None:
utc_time_dt = local_time_dt - result[0]
utc_time_str = datetime.datetime.strftime(
(utc_time_dt), "%Y-%m-%d %H:%M:%S.%f")
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' ' + str(error)))
try:
# create a cursor
cur = conn.cursor()
# execute a statement
cur.execute(
sql,
(local_time_str, delta_tp9, delta_af7, delta_af8,
delta_tp10, ath_un, theta_tp9, theta_af7,
theta_af8, theta_tp10, alpha_tp9, alpha_af7,
alpha_af8, alpha_tp10, beta_tp9, beta_af7,
beta_af8, beta_tp10, gamma_tp9, gamma_af7,
gamma_af8, gamma_tp10, raw_tp9, raw_af7, raw_af8,
raw_tp10, aux_right, accelerometer_x,
accelerometer_y, accelerometer_z, gyro_x, gyro_y,
gyro_z, head_band_on, hsi_tp9, hsi_af7, hsi_af8,
hsi_tp10, battery, elements, utc_time_str))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.now()) + ' ' + str(error)))
if preserve_files == "false":
#Remove the csv file from download folder
os.remove(os.path.join(download_folder, filename))
with StdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file removed'
.format(filename)))
with ProgressStdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file removed'
.format(filename)))
else:
#Move the csv to archive folder
if not os.path.exists(os.path.join(archive_folder, filename)):
os.rename(os.path.join(download_folder, filename),
os.path.join(archive_folder, filename))
with StdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file archived'
.format(filename)))
with ProgressStdoutRedirection(ath_un):
print((
'The content of \"{}\" parsed and inserted into DB and the original csv file archived'
.format(filename)))
else:
#Remove the csv file from download folder
os.remove(os.path.join(download_folder, filename))
# close the communication with the PostgreSQL
if conn is not None:
conn.close()
def dwnld_insert_nutrition(mfp_username, mfp_password, ath_un, start_date,
end_date, encr_pass, save_pwd, auto_synch, db_host,
superuser_un, superuser_pw):
Crypto.Random.atfork()
db_name = str(str2md5(ath_un)) + '_Athlete_Data_DB'
if save_pwd == True:
encrypted_pwd = base64.b64encode(encrypt(mfp_password, encr_pass))
encrypted_pwd = encrypted_pwd.decode('utf-8')
else:
encrypted_pwd = None
#Get PID of the current process and write it in the file
pid = (str(os.getpid()))
pidfile = PID_FILE_DIR + ath_un + '_PID.txt'
open(pidfile, 'w').write(pid)
with StdoutRedirection(ath_un):
print("Attempting to login to MFP...")
with ProgressStdoutRedirection(ath_un):
print("Attempting to login to MFP...")
try:
client = myfitnesspal.Client(mfp_username, mfp_password)
except ValueError as e:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
'-E1- ' + str(e)))
with StdoutRedirection(ath_un):
print(('Wrong MFP credentials for user {}. Skipping.'.format(
mfp_username)))
return
with StdoutRedirection(ath_un):
print('MFP Login successful! Proceeding...')
with ProgressStdoutRedirection(ath_un):
print('MFP Login successful! Proceeding...')
mfp_user_insert(mfp_username, encrypted_pwd, ath_un, db_host, db_name,
superuser_un, superuser_pw,
encr_pass) #PG: insert MFP user details into database
# read DB connection parameters from ini file
conn = None
# connect to the PostgreSQL server
with ProgressStdoutRedirection(ath_un):
print('Connecting to the PostgreSQL server...')
conn = psycopg2.connect(dbname=db_name,
host=db_host,
user=superuser_un,
password=superuser_pw)
for single_date in daterange(start_date, end_date):
date_in_range = single_date.strftime("%Y-%m-%d")
data_exist_for_date = 'Nutrition_Data_For_' + date_in_range
#PG: Check whether the data for this date have been inserted into to DB during one of the previous runs
data_exists = check_data_file_exists(data_exist_for_date, ath_un,
db_host, db_name, superuser_un,
superuser_pw, encr_pass)
if data_exists == True:
with StdoutRedirection(ath_un):
print((
'Nutrition data for {} already downloaded and inserted to DB. Skipping.'
.format(date_in_range)))
with ProgressStdoutRedirection(ath_un):
print((
'Nutrition data for {} already downloaded and inserted to DB. Skipping.'
.format(date_in_range)))
continue
with StdoutRedirection(ath_un):
print(('Downloading nutrition data: ' + date_in_range))
with ProgressStdoutRedirection(ath_un):
print(('Downloading nutrition data: ' + date_in_range))
try:
day = client.get_date(single_date)
meals = day.meals
for meal in meals:
meal_name = meal.name
entry = meal.entries
with StdoutRedirection(ath_un):
print(('****' + meal_name + '****'))
for item in entry:
food_item = item.short_name
if food_item is None:
food_item = 'Generic'
with StdoutRedirection(ath_un):
print((food_item.encode("utf-8")))
units = item.unit
if units is None:
units = 'piece'
quantity = item.quantity
if quantity is None:
quantity = 1.0
nutrients = item.nutrition_information
for nutrient, value in nutrients.items():
if nutrient == 'fiber':
fiber_value = value
if nutrient == 'sodium':
sodium_value = value
if nutrient == 'carbohydrates':
carbohydrates_value = value
if nutrient == 'calories':
calories_value = value
if nutrient == 'fat':
fat_value = value
if nutrient == 'protein':
protein_value = value
sql = """
INSERT INTO mfp_nutrition(athlete_id,date,meal,food_item,units,quantity,fiber,sodium,carbohydrates,calories,fat,protein)
VALUES
((select id from athlete where mfp_username=%s),%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s);
"""
try:
# create a cursor
cur = conn.cursor()
# execute a statement
with StdoutRedirection(ath_un):
print('Inserting record....')
with ProgressStdoutRedirection(ath_un):
print('Inserting record....')
cur.execute(sql,
(mfp_username, date_in_range, meal_name,
food_item, units, quantity, fiber_value,
sodium_value, carbohydrates_value,
calories_value, fat_value, protein_value))
conn.commit()
# close the communication with the PostgreSQL
cur.close()
except (Exception, psycopg2.DatabaseError) as error:
with ErrorStdoutRedirection(ath_un):
print((str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(
sys.exc_info()[-1].tb_lineno) +
'-E2- ' + str(error)))
# Update the files table
data_file_path_insert(data_exist_for_date, ath_un, db_host,
db_name, superuser_un, superuser_pw,
encr_pass)
except Exception as e:
with ErrorStdoutRedirection(ath_un):
print(
(str(datetime.datetime.now()) + ' [' +
sys._getframe().f_code.co_name + ']' +
' Error on line {}'.format(sys.exc_info()[-1].tb_lineno) +
'-E3- ' + str(e)))
continue
# close the communication with the PostgreSQL
if conn is not None:
conn.close()
with StdoutRedirection(ath_un):
print('--- All nutrition data inserted successfully. ---')
with ProgressStdoutRedirection(ath_un):
print('--- All nutrition data inserted successfully. ---')