PySpritmonitor

Python package for reading Spritmonitor.de's CSV data.

Usage

Either pass paths to CSV files stored locally or obtain data directly from Spritmonitor.de by providing login credentials and vehicle's ID.

CSVs stored locally

Export the fueling and cost entries from https://www.spritmonitor.de/ as CSV files.

Import classes Costs and Fuelings from pyspritmonitor module.

from pyspritmonitor import Costs, Fuelings

Pass path to CSV file as argument to Costs and Fuelings.

costs = Costs('data/853999_costs.csv')
fuelings = Fuelings('data/853999_fuelings.csv')

Then you can access data as DataFrame type:

print(costs.df)
print(fuelings.df)

Obtain data from Spritmonitor.de

Import class Login from pyspritmonitor module.

from pyspritmonitor import Login, Costs, Fuelings

Provide class instance with your username, password and vehicle's ID.

login = Login(username='MyUsername', password='MyPassword', vehicle_id='999999')

Then pass class Login variables costs_csv and fuelings_csv to classes Costs and Fuelings.

costs = Costs(login.costs_csv)
fuelings = Fuelings(login.fuelings_csv)

The rest remains same as when accessing CSVs stored locally described above.

JSON in Note

You can pack JSON objects into Spritmonitor's 'Note' field and then unpack it by using argument json_in_note=True:

fuelings = Fuelings(fuelings_path, json_in_note=True)

Each variable is then converted into separate column.

Time variables

If some of the columns contain time, you can convert them to Timedelta types by passing their names to parameter time_columns:

fuelings = Fuelings(fuelings_path, json_in_note=True, time_columns='BC-Time')