QWC Data Service¶
Edit spatial and unlocated features of datasets via GeoJSON.
This service is integrated into qwc-docker
, consult qwc-services.github.io for the general qwc-services
documentation.
Setup¶
Uses PostgreSQL connection service or connection to a PostGIS database. This connection's user requires read and write access to the configured tables.
qwc_demo example¶
Uses PostgreSQL connection service qwc_geodb
(GeoDB).
The user qwc_service_write
requires read and write access to the configured tables
of the data layers from the QGIS project qwc_demo.qgs
.
Setup PostgreSQL connection service file ~/.pg_service.conf
:
[qwc_geodb]
host=localhost
port=5439
dbname=qwc_demo
user=qwc_service_write
password=qwc_service_write
sslmode=disable
Configuration¶
The static config and permission files are stored as JSON files in $CONFIG_PATH
with subdirectories for each tenant,
e.g. $CONFIG_PATH/default/*.json
. The default tenant name is default
.
Data Service config¶
Permissions¶
- JSON schema
- File location:
$CONFIG_PATH/<tenant>/permissions.json
Example:
{
"$schema": "https://raw.githubusercontent.com/qwc-services/qwc-services-core/master/schemas/qwc-services-permissions.json",
"users": [
{
"name": "demo",
"groups": ["demo"],
"roles": []
}
],
"groups": [
{
"name": "demo",
"roles": ["demo"]
}
],
"roles": [
{
"role": "public",
"permissions": {
"data_datasets": [
{
"name": "qwc_demo.edit_points",
"attributes": [
"id",
"name",
"description",
"num",
"value",
"type",
"amount",
"validated",
"datetime"
],
"writable": true,
"creatable": true,
"readable": true,
"updatable": true,
"deletable": true
}
]
}
}
]
}
Usage¶
Set the CONFIG_PATH
environment variable to the path containing the service config and permission files when starting this service (default: config
).
Base URL:
http://localhost:5012/
Service API:
http://localhost:5012/api/
Sample requests:
curl 'http://localhost:5012/qwc_demo.edit_points/'
General Information for all operations¶
Datatypes-Encoding¶
JSON only defines recommendations or has no information concerning the encoding of some quite common used database data types. Following a description on how these are encoded in the data service API.
- Date: ISO date strings
YYYY-MM-DD
- Datetime: ISO date/time strings
YYYY-MM-DDThh:mm:ss
- UUID: Hex-encoded string format. Example:
'6fa459ea-ee8a-3ca4-894e-db77e160355e'
Feature-ID¶
For operations like updating or deleting features, records are identified by
a feature id
. This id
refers to the primary key of the database
table and is usually kept constant over time.
Filter expressions¶
Query operations support passing filter expressions to narrow down the results. This expression is a serialized JSON array of the format:
[["<name>", "<op>", <value>],"and|or",["<name>","<op>",<value>],...]
name
is the attribute column name. Ifname
begins with?
, the filter is only applied if the column name exists.-
op
can be one of"=", "!=", "<>", "<", ">", "<=", ">=", "LIKE", "ILIKE", "IS", "IS NOT"
The operators are applied on the original database types.
If value is null
, the operator should be IS
or IS NOT
.
value
can be of typestring
,int
,float
ornull
.
For string operations, the SQL wildcard character %
can be used.
Filter examples¶
- Find all features in the dataset with a number field smaller 10 and a matching name field:
[["name","LIKE","example%"],"and",["number","<",10]]
- Find all features in the dataset with a last change before 1st of January 2020 or having
NULL
as lastchange value:[["lastchange","<","2020-01-01T12:00:00"],"or",["lastchange","IS",null]]
Docker usage¶
To run this docker image you will need a PostGIS database. For testing purposes you can use the demo DB.
The following steps explain how to download the demo DB docker image and how to run the qwc-data-service
with docker-compose
.
Step 1: Clone qwc-docker
git clone https://github.com/qwc-services/qwc-docker
cd qwc-docker
Step 2: Create docker-compose.yml file
cp docker-compose-example.yml docker-compose.yml
Step 3: Start docker containers
docker-compose up qwc-data-service
For more information please visit: https://github.com/qwc-services/qwc-docker
Development¶
Create a virtual environment:
virtualenv --python=/usr/bin/python3 --system-site-packages .venv
Without system packages:
python3 -m venv .venv
Activate virtual environment:
source .venv/bin/activate
Install requirements:
pip install -r requirements.txt
Start local service:
CONFIG_PATH=/PATH/TO/CONFIGS/ python src/server.py
Testing¶
Run all tests:
python test.py
Run single test module:
python -m unittest tests.feature_validation_tests
Run single test case:
python -m unittest tests.feature_validation_tests.FeatureValidationTestCase
Run single test method:
python -m unittest tests.feature_validation_tests.FeatureValidationTestCase.test_field_constraints