combined csv output

main.py

@@ -3,6 +3,9 @@
 import datetime as dt
 import dateutil.relativedelta
 import os
+import requests
+import timeutils
+import csv
 
 CACHE_DIR = "cache"
 CACHE_FILE_TEMPLATE  = "cache_{}_{}_{}.data"
@@ -10,7 +13,8 @@ NFF_URL_TIMEFORMAT   = "%d.%m.%Y"
 NFF_INPUT_TIMEFORMAT = "%d.%m.%Y %H:%M"
 OUTSIDE_DATA_URL     = "http://umweltdaten.nuernberg.de/csv/wetterdaten/messstation-nuernberg-flugfeld/archiv/csv-export/SUN/nuernberg-flugfeld/{dtype}/individuell/{fromDate}/{toDate}/export.csv"
 
-dtypes = [ "lufttemperatur-aussen", "luftfeuchte", "luftdruck" ]
+headers = [ "Datum/Zeit", "Temperatur [°C]", "rel. Luftfeuchte [%]", "Luftdruck [mbar]", "Windgeschwindigkeit [m/s]", "Windrichtung N=0, O=90, S=180, W=270", "Niederschlag [mm = L/m2]"]
+dtypes  = [ "lufttemperatur-aussen", "luftfeuchte", "luftdruck", "windgeschwindigkeit", "windrichtung", "niederschlagsmenge" ]
 
 def downloadFlugfeldData(fromTime, toTime, dtype):
 
@@ -20,13 +24,11 @@ def downloadFlugfeldData(fromTime, toTime, dtype):
     toTimeStr   = toTime.strftime(NFF_URL_TIMEFORMAT)
     cacheFile   = CACHE_FILE_TEMPLATE.format(dtype, fromTimeStr, toTimeStr)
     fullpath    = os.path.join(cacheDir, cacheFile)
-    print(cacheFile)
 
     # check for cache file
     content = None
     if not os.path.isfile(fullpath):
         url = OUTSIDE_DATA_URL.format(dtype=dtype, fromDate=fromTimeStr, toDate=toTimeStr)
-        print(url)
         r = requests.get(url)
         content = r.content.decode('utf-8', "ignore") # ignore bad bytes
 
@@ -42,7 +44,9 @@ def downloadFlugfeldData(fromTime, toTime, dtype):
     return content
 
 def checkLastMonths(backwardsMonths=6):
-    
+   
+    fullContentDict = dict()
+
     today = dt.datetime.today() 
     monthsToCheck = [ today.month - x for x in range(0, backwardsMonths)  ]
     monthsToCheckFixed = list(map(lambda x: x if x > 0 else x + 12, monthsToCheck))
@@ -63,6 +67,63 @@ def checkLastMonths(backwardsMonths=6):
 
         for dtype in dtypes:
             content = downloadFlugfeldData(start, end, dtype)
+            dataList = parse(content, dtype)
+            for d in dataList:
+                if d.time in fullContentDict:
+                    fullContentDict[d.time] += [d]
+                else:
+                    fullContentDict.update({ d.time : [d] })
+
+    return fullContentDict
+
+def parse(content, dtype):
+    skipBecauseFirstLine = True
+    dataList = []
+    for l in content.split("\n"):
+        if not ";" in l:
+            continue
+        elif not l.strip():
+            continue
+        elif skipBecauseFirstLine:
+            skipBecauseFirstLine = False
+            continue
+        try:
+            timeStr, value = l.split(";")
+            timestamp = dt.datetime.strptime(timeStr, NFF_INPUT_TIMEFORMAT)
+            cleanFloat = value.replace(",",".")
+
+            # - means the value is missing in the data set (happens sometimes) #
+            if cleanFloat.strip() == "-" or cleanFloat.strip() == "+":
+                continue
+
+            dataList += [Data(dtype, float(cleanFloat), timestamp)]
+
+        except ValueError as e:
+            print("Warning: {}".format(e))
+
+    return dataList
+
+class Data:
+    def __init__(self, dtype, value, time):
+        self.dtype = dtype
+        self.value = value
+        self.time  = time
+
+    def __str__(self):
+        return "Data: {} {} {}".format(self.dtype, self.time, self.value)
 
 if __name__ == "__main__":
-    checkLastMonths()
+    dictForCSV = checkLastMonths()
+
+    with open('test.csv', 'w', newline='') as file:
+
+        fieldnames = ["time"] + dtypes
+        writer = csv.DictWriter(file, fieldnames=fieldnames)
+        writer.writeheader()
+
+        for key in dictForCSV.keys():
+            rowdict = { "time" : key }
+            for data in dictForCSV[key]:
+                rowdict.update({ data.dtype : data.value })
+            writer.writerow(rowdict) 
+