A lightweight PostGIS based dynamic vector tile server.

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Documentation: https://developmentseed.org/timvt/

Source Code: https://github.com/developmentseed/timvt

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⚠️ This project is on pause while we focus on developmentseed/tipg ⚠️

ref: #96

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TiMVT, pronounced tee-MVT, is a python package which helps creating lightweight Vector Tiles service from PostGIS Database.

Built on top of the modern and fast FastAPI framework, timvt is written in Python using async/await asynchronous code to improve the performances and handle heavy loads.

TiMVT is mostly inspired from the awesome urbica/martin and CrunchyData/pg_tileserv projects.

Features

• Multiple TileMatrixSets via morecantile. Default is set to WebMercatorQuad which is the usual Web Mercator projection used in most of Wep Map libraries.)
• Built with FastAPI
• Table and Function layers
• Async API using asyncpg

Install

Install TiMVT from pypi

# update pip (optional)
python -m pip install pip -U

# install timvt
python -m pip install timvt

or install from source:

$ git clone https://github.com/developmentseed/timvt.git
$ cd timvt
$ python -m pip install -e .

PostGIS/Postgres

TiMVT rely mostly on ST_AsMVT function and will need PostGIS >= 2.5.

If you want more info about ST_AsMVT function or on the subject of creating Vector Tile from PostGIS, please read this great article from Paul Ramsey: https://info.crunchydata.com/blog/dynamic-vector-tiles-from-postgis

Configuration

To be able to create Vector Tile, the application will need access to the PostGIS database. TiMVT uses pydantic's configuration pattern which make use of environment variable and/or .env file to pass variable to the application.

Example of .env file can be found in .env.example

POSTGRES_USER=username
POSTGRES_PASS=password
POSTGRES_DBNAME=postgis
POSTGRES_HOST=0.0.0.0
POSTGRES_PORT=5432

# Or you can also define the DATABASE_URL directly
DATABASE_URL=postgresql://username:password@0.0.0.0:5432/postgis

Minimal Application

from timvt.db import close_db_connection, connect_to_db
from timvt.factory import VectorTilerFactory
from timvt.layer import FunctionRegistry
from fastapi import FastAPI, Request

# Create Application.
app = FastAPI()

# Add Function registry to the application state
app.state.timvt_function_catalog = FunctionRegistry()

# Register Start/Stop application event handler to setup/stop the database connection
# and populate `app.state.table_catalog`
@app.on_event("startup")
async def startup_event():
    """Application startup: register the database connection and create table list."""
    await connect_to_db(app)


@app.on_event("shutdown")
async def shutdown_event():
    """Application shutdown: de-register the database connection."""
    await close_db_connection(app)

# Register endpoints.
mvt_tiler = VectorTilerFactory(
    with_tables_metadata=True,
    with_functions_metadata=True,  # add Functions metadata endpoints (/functions.json, /{function_name}.json)
    with_viewer=True,
)
app.include_router(mvt_tiler.router, tags=["Tiles"])

Default Application

While we encourage users to write their own application using TiMVT package, we also provide a default production ready application:

# Install timvt dependencies and Uvicorn (a lightning-fast ASGI server)
$ pip install timvt 'uvicorn[standard]>=0.12.0,<0.14.0'

# Set Database URL environment variable so TiMVT can access it
$ export DATABASE_URL=postgresql://username:password@0.0.0.0:5432/postgis

# Launch Demo Application
$ uvicorn timvt.main:app --reload

You can also use the official docker image

$ docker run \
    -p 8081:8081 \
    -e PORT=8081 \
    -e DATABASE_URL=postgresql://username:password@0.0.0.0:5432/postgis \
    ghcr.io/developmentseed/timvt:latest

:endpoint:/docs

Contribution & Development

See CONTRIBUTING.md

License

See LICENSE

Authors

Created by Development Seed

Changes

See CHANGES.md.