def test_fitfile_parses_with_correct_number_of_recs_defs_and_file_size_and_CRC(self):
fit = FitFile(testfile('sample-activity.fit'))
fit.parse()
self.assertEquals(len(fit.records), 3228)
self.assertEquals(len(fit.definitions), 9)
self.assertEquals(fit._file_size, 104761)
self.assertEquals(fit._crc, 0x75C5)
def test_fitfile_parses_with_correct_number_of_recs_defs_and_file_size_and_CRC(self):
fit = FitFile(testfile('sample-activity.fit'))
fit.parse()
self.assertEquals(len(fit.records), 3228)
self.assertEquals(len(fit.definitions), 9)
self.assertEquals(fit._file_size, 104761)
self.assertEquals(fit._crc, 0x75C5)
#!/usr/bin/env python
from fitparse.base import FitFile
fit_file = FitFile('example.fit')
fit_file.parse()
records = fit_file.get_records_as_dicts()
for record in records:
print '\nRecord:'
for key, value in record.iteritems():
print ' - %s: %s' % (key.replace('_', ' ').capitalize(), value)
def FitToDataTable(MyFile, Fields):
File = FitFile(MyFile)
File.parse()
##obtention des enregistrements
Values = File.get_messages()
##iteration sur les header inutiles jusqu'a l'annonce du fichier cycling
Records = ExtractRecords(Values)
# Continue = True
# while Continue :
# Record = Values.next()
# try :
# if Record["sport"] == "cycling" :
# Continue = False
# except KeyError :
# pass
Datas = []
i = 0
#iteration sur les enregistrements
Prec = None
for Record in Records:
# #print(Record)
# if Record.has_key("product")==True :
# #rendu ici il n'y a plus d'enregistrements
# try :
# Record = Values.next()
# if Record.has_key("event_type") == False :
# print("Hey, we have to continue !")
# else :
# break
# except :
# break
# if Record.has_key("event_type") == False :
# #sauter les evenements indiquant le 5km
# #transformer le timestamp moche en un beau chiffre
TIME = time.mktime(Record["timestamp"].timetuple()) + (
Config["FitFile"]["Decalage"] * 60)
#TIME = Record["timestamp"] + (Config["FitFile"]["Decalage"]*60*60)
Record["timestamp"] = int(TIME)
#print(Fields)
#try :
Row = []
NoMissing = True
for Field in Fields:
if Field.RealName not in Record:
Row.append(Field.Default)
#print(" Missing this Field : "+Field.RealName)
NoMissing = False
else:
try:
Row.append(Record[Field.RealName])
except KeyError as e:
print("This Key is missing : " + Field.RealName)
print(Record)
raise e
#Row = list((Record[Field.RealName] for Field in Fields))
# except :
# print("Error : ")
# print(Record)
# print(Row)
# raise KeyError
Row.insert(0, i)
Datas.append(tuple(Row))
i += 1
if NoMissing:
Prec = Record
if Prec is None:
raise ValueError(
"Prec is none, so we have a problem with this file : " + MyFile)
#obtention des types des enregistrements
Types = [VL.GessNumpyType(str(Prec[Field.RealName])) for Field in Fields]
FieldNames = [Field.Name for Field in Fields]
FieldNames.insert(0, "OID")
Types.insert(0, "int32")
#print(Types)
BD = VL.JDataTable(FieldNames, Types, "OID", Datas)
return BD
