Channel Hop
Generates options for a round-trip car journey via channel ferry.
This code provides a framework for evaluating and ranking different combinations of travel options for a simple A-to-B cross-channel car trip. Data collection is on the user, but this makes actually using said data more efficient.
Usage
Given an origin and a destination and two datasets (car routes, ferry crossings), the code will evaluate different combinations and present the results.
Assuming there is at least one route option in the dataset to UK ferry ports of interest from 'MyHouse' (assumed to be in the UK) to 'MyDestination' (assumed to be in FR).
>>> my_trip = Trip('MyOrigin', 'MyDest', ferrydata, cardata)
Where ferrydata and cardata are lists of exdata.FerryData and
exdata.CarData objects providing relevant route data (and
variations).
Why?
Every year, at least once, we/I am faced with the task of comparing routes and timings for the myriad of viable channel ferry crossings for at least one group car trip away to the continent. The comparison is performed in order to satisfy a range of financial constraints and miscellaneous preferences. Every year this process is streamlined a smidgen; this is the next stage in evolution beyond a laborious, incomplete and error-prone spreadsheet-based approach.
It's surprising how many combinations of options there can be for a simple A-to-B return trip. This year there are nearly 300 permutations (and we wondered why it was always such a headache) which was swiftly chopped to 30 distinctly-presented choices based on some simple constraints, then down to three by refining constraints based on discussion with the group. Easy.
Limitations
As to be expected with this type of motivation, the program has now served its purpose (for now!) and is not exactly user friendly, complete or even sensible in some regards. I'm also no graph theorist, and the implementation shows this. It'll likely see extension and iterative improvement in accordance with personal need.