A visualization that allows users to understand and analyze their spatio-temporal information, with focus on personal semantics.
Python development of the back-end for traceMySteps. Connects with AngularJS front-end also provided in another repository.
1) Test data insertion on the DB.
2) Test querying.
3) Parsing and batch load of multiple GPX files into DB.
4) Complete app.py with the front-end required resources/routes and queries, having in mind the JSON formats needed on the frontend.
- Install Postgresql and Postgis:
brew install postgres
brew install postgis
-
If that’s a fresh installation, initialize database cluster:
initdb /usr/local/var/postgres -
Configure PATH environment variable (if needed):
export PATH=$PATH:'/usr/local/var/postgres'
export PGDATA='/usr/local/var/postgres'
-
Start Postgresql server:
pg_ctl start -
Check status:
pg_ctl status -
Enter postgres default database at start, to run schema to create our database:
psql postgres
\i PATH_TO/schema.sql
-
To quit the created tracemysteps DB:
\q -
To re-access the tracemysteps DB:
psql tracemysteps
While on the project folder:
-
Make sure to have a
MyTracks.lifefile, containing the semantic information about your trips and stays. -
Also make sure to have a
MyTracksfolder, containing all your.gpxfiles. -
Run the Ramer–Douglas–Peucker algorithm in order to simplify dataset:
python process_gpx.py -
Run the
parse_load.pyfile in order to populate the database:python parse_load.py -
Run the app (click "Allow" when prompted):
python app.py -
Stop server:
pg_ctl stop
I strongly advise the use of the pgAdmin3 tool as a visual aid and complement to the shell commands. This Readme will be updated, whenever possible, with the progress on the development and with new instructions.
Available on setup.py