What’s the data behind the story? HURUmap gives infomediaries like journalists and civic activists an easy ‘plug & play’ toolkit for finding and embedding interactive data visualisations into their storytelling.
HURUmap’s underlying data is quality-checked, from reputable official sources including the government Census, PEPFAR and Uwezo.
The project is built on Wazimap, an open source platform by OpenUp and Media Monitoring Africa for making census data more understandable.
We use Docker Compose to simplify development.
To get started, set the HURUmap App you want to work on and spin up the container like so:
export HURUMAP_APP=hurumap_ke
make web
You can create a db and load initial data by running the the following commands;
make createdb
make loaddata
# (Optional) If sqlalchemy.exc.NoSuchTableError error thrown:
export HURUMAP_APP=hurumap_land
# 1. Local Docker DB
docker-compose up -d db
cat $HURUMAP_APP/sql/*.sql | docker-compose exec -T db psql $HURUMAP_APP
# 2. Remote DB option
cat $HURUMAP_APP/sql/*.sql | docker-compose exec -T -e PGPASSWORD=<pass> db psql -h <db.host.com> -U <user> $HURUMAP_APP
olevel_student_performance.sql
has been split into 2 files by year because as a single
file, it surpasses the maximum file size allowed by Github
TODO: Needs to use docker-compose, test, and QA
-
Ensure
${HURUMAP_APP}/tables.py
has aFieldTable
that has exactly the columns that you're importing. If there are multiple tables with exactly the same columns, perhaps because their Universes are different, then be sure to take note of the table id. -
Do a dry-run of the import, using the table name if necessary.
python manage.py importsimplecsv yourfile.csv --dry-run [--table TABLENAME]
-
If it all looks good, run it without
--dry-run
. -
Update (or create) the raw SQL data:
python manage.py dumppsql --table TABLENAME > sql/TABLENAME.sql
-
Commit to git.
-
All done!
We make the data available in our repository for added availability in two primary ways:
- Django fixtures (primarily
wazimap_geography
) - FieldTables as SQL files.
To do this, run the following command:
export HURUMAP_APP=<hurumap_app>
make dumpdata
We use dokku to deploy on our own servers. It's awesome like sliced bread or chapati. Check out their docs on getting started: https://dokku.viewdocs.com/dokku
Once set up, you'll have to do a couple of things:
# Create app
dokku apps:create hurumap-ke
# Set environment variables
dokku config:set hurumap-ke \
HURUMAP_APP=hurumap_ke \
DJANGO_SETTINGS_MODULE=hurumap_ke.settings \
DATABASE_URL=postgresql://hurumap_ke:hurumap_ke@localhost/hurumap_ke
After ensuring your ssh key is added, from your local machine you should now run:
git remote add dokku dokku@hurumap.org:hurumap-ke
git push dokku
NOTE: You'll have to set up the database before deployment. Either self-hosted or managed.
Dokku allows for checks that make sure you have zero-downtime deployments. We currently only check for DB errors but should allow for better checks in the future.
If you'd like to contribute to HURUmap, check out the CONTRIBUTING.md file on how to get started.
-
Ensure
hurumap_ke/tables.py
has aFieldTable
that has exactly the columns that you're importing. If there are multiple tables with exactly the same columns, perhaps because their Universes are different, then be sure to take note of the table id. -
Do a dry-run of the import, using the table name if necessary.
python manage.py importcsv yourfile.csv --dry-run [--table TABLENAME]
-
If it all looks good, run it without
--dry-run
. -
Update (or create) the raw SQL data:
python manage.py dumppsql --table TABLENAME > sql/TABLENAME.sql
-
Commit to git.
-
All done!
To dump all data tables at once, run
for t in `ls hurumap_ke/sql/[a-z]*.sql`
do
echo $t
pg_dump "postgres://hurumap_ke:hurumap_ke@localhost/hurumap_ke" \
-O -c --if-exists -t $(basename $t .sql) \
| egrep -v "(idle_in_transaction_session_timeout|row_security)" \
> hurumap_ke/sql/$(basename $t .sql).sql
done
HURUmap supports the use of both single and multiple tracking ids on a single page.
For the case of a single tracking id (or when one tracking id needs to be identified as the "default" tracking id), the variable ga_tracking_id
should be set to the string value of the tracking id.
For example:
[hurumap_ke/settings.py]
...
HURUMAP['ga_tracking_id'] = 'UA-44795600-8'
...
And in those cases were multiple tracking ids need to be set, ga_tracking_ids
(with an s) should be set as a list of tracking ids.
For example:
[hurumap_ke/settings.py]
...
HURUMAP['ga_tracking_ids'] = ['UA-44795600-1', 'UA-44795600-2', 'UA-44795600-3']
...
NOTE: By default, HURUMAP['ga_tracking_id'] = 'UA-44795600-8'
. If you're not using ga_tracking_id
at all (such as in those situation where you're only using multiple tracking ids or you're not using Google Analytics altogether), remember to set this variable to blank i.e. HURUMAP['ga_tracking_id'] = ''
?
MIT