GIS » Gisaf

h1. Live

While the primary intention is use a database for all layers, Gisaf has the capability to display layers directly from GeoPandas GeodataFrames.

In this case, they can also be updated dynamically, adding animation capabilities to the maps.

This can be used for, eg:

* displaying text (eg. temperatures, well levels)
* moving elements
* results of computations and analysis...



h2. Using live directly from a Python script on the Gisaf server

Eg:

<pre><code class="python">
#!/usr/bin/env python
from asyncio import run

import geopandas as gpd

from shapely.geometry import Point

from gisaf.live import live_server

async def run(gs):
gdf = gpd.GeoDataFrame(
data={
'geometry': [
Point(12.01, 79.81)
]
},
crs='epsg:4326'
)

await live_server.publish_gdf('FooLayer', gdf)

async def main():
await live_server.create_connections()
await run(gs)

if __name__ == '__main__':
run(main())
</code></pre>

Explanations:

1. Initialize the connection with @live_server.create_connections()@.

2. Publish a geo dataframe with @live_server.publish_gdf('name of the layer', gdf)@

h2. From Jupyter notebooks

Quite similarly to the case above, jupyter notebooks (running on a different machine) can be used to publish and control live layers. See the examples in @Templates/gisaf_live_templates@.

h2. Architecture

Gisaf live layers use a redis data store for:

1. Storage of the live layers

2. Publish/subscribe for live updates.

The live updates are sent through a websocket, initiated by the clients (web browsers).

Moreover, Gisaf exposes an HTTP API for external control of the live layers, eg. by Jupyter notebooks running on another server.