eBike-SQLite/insertLoading.py

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Python
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2024-05-11 08:03:49 +02:00
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
from fitparse import FitFile
from datetime import datetime, timedelta
import os, sys, shutil
from os import walk
import csv
import pandas as pd
path = "/home/manuel/Dropbox/Apps/HealthFitExporter/"
#path = "/Users/manuel/Projekte/eBike-Influx-Calculation/"
ext = ('.fit')
csv_file = "/www/wwwroot/www.manuelw.de/ebike/ebike_data.csv"
output = {}
fitData = {}
fitData["total_distance"] = 0
fitData["total_ascent"] = 0
fitData["avg_speed"] = 0
fitData["avg_speed_count"] = 0
fitFilesCount = 0
loading = sys.argv[1]
watt = sys.argv[2]
row = []
##
### auf neue Files überwachen
def main():
f = []
for base, dirs, files in os.walk(path):
files = [ fi for fi in files if fi.endswith(".fit") ]
if files:
processFIT(files)
##
### parse FIT file und bestimme Handling
def processFIT(files):
global fitFilesCount
print("Files:", len(files))
fitFilesCount = len(files)
for filename in files:
#print(filename)
file = FitFile(path+filename)
for record in file.get_messages("session"):
## nur wenn Radfahren
if record.get_value("sport") == "cycling":
## Verarbeitung starten
doAll(file)
showEnd()
readCSV()
deleteFiles()
##
### todo on all fit files
def doAll(file):
for record in file.get_messages("session"):
fitData["avg_cadence"] = record.get_value("avg_cadence")
#fitData["avg_speed"] += round(float(record.get_value("avg_speed")) / 0.27777777777778, 1)
fitData["avg_speed"] += record.get_value("avg_speed")
fitData["avg_speed_count"] +=1
#fitData["total_ascent"] = float(record.get_value("total_ascent")) if record.get_value("total_ascent") != None else 0
fitData["total_distance"] += float(round(record.get_value("total_distance") / 1000, 1))
fitData["avg_speed"] = round(float(fitData["avg_speed"] / fitData["avg_speed_count"]), 1)
doHealthFit(file, record.get_value("min_altitude"))
def doHealthFit(file, min_alt=0.0):
### Kadenz
i=0
cadence=0
last_elev=min_alt
ges_elev=0.0
for record in file.get_messages("record"):
## korrekte Kadenz ermitteln
if record.get_value("cadence") != None and record.get_value("cadence") > 0:
i+=1
cadence += record.get_value("cadence")
## korrekte Höhenmeter ermitteln
if record.get_value("altitude") != None:
if record.get_value("altitude") > last_elev:
ges_elev += record.get_value("altitude") - last_elev
last_elev = record.get_value("altitude")
#fitData["avg_cadence"] = int(cadence/i)
fitData["total_ascent"] += round(float(ges_elev), 1)
fitData["total_ascent"] = round(float(fitData["total_ascent"]), 1)
def showEnd():
print("Akku geladen",loading)
print("Ladung Wh",watt)
print("Total Range", fitData["total_distance"])
print("Total Ascent", fitData["total_ascent"])
print("AVG Speed", fitData["avg_speed"])
def readCSV():
global fitData, fitFilesCount
with open(csv_file, "r", encoding="utf-8", errors="ignore") as scraped:
row = []
try:
row.extend(scraped.readlines()[-1].replace("\n", "").split(","))
row = row[0:-5]
dropCSV()
row.extend([fitData["total_distance"], fitData["total_ascent"], fitData["avg_speed"], watt, fitFilesCount])
writeCSV(row)
except:
print("EXCEPTION")
row.extend(["Date", "Loading", "Total Range", "Total Ascent", "AVG Speed", "Loaded Wh", "Fahrten"])
writeCSV(row)
def writeCSV(row):
with open(csv_file, 'a', newline='') as csvfile:
spamwriter = csv.writer(csvfile, delimiter=',', quotechar='|', quoting=csv.QUOTE_MINIMAL)
spamwriter.writerow(row)
spamwriter.writerow([datetime.today().strftime('%d-%m-%Y'), loading, 0, 0, 0, 0, 0])
def dropCSV():
df = pd.read_csv(csv_file, index_col='Date', on_bad_lines='skip')
df = df.iloc[:-1]
df.to_csv(csv_file, index=True)
def deleteFiles():
for filename in os.listdir(path):
file_path = os.path.join(path, filename)
try:
if os.path.isfile(file_path) or os.path.islink(file_path):
os.unlink(file_path)
#print("lösche... test")
elif os.path.isdir(file_path):
shutil.rmtree(file_path)
except Exception as e:
print('Failed to delete %s. Reason: %s' % (file_path, e))
if __name__ == '__main__':
main()