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installation:loading-spatialite | installation | loading-spatialite | Loading SpatiaLite | The datasetteproject/datasette image includes a recent version of the SpatiaLite extension for SQLite. To load and enable that module, use the following command: docker run -p 8001:8001 -v `pwd`:/mnt \ datasetteproject/datasette \ datasette -p 8001 -h 0.0.0.0 /mnt/fixtures.db \ --load-extension=spatialite You can confirm that SpatiaLite is successfully loaded by visiting http://127.0.0.1:8001/-/versions | ["Installation", "Advanced installation options", "Using Docker"] | [{"href": "http://127.0.0.1:8001/-/versions", "label": "http://127.0.0.1:8001/-/versions"}] |
installation:installing-plugins-using-pipx | installation | installing-plugins-using-pipx | Installing plugins using pipx | You can install additional datasette plugins with pipx inject like so: pipx inject datasette datasette-json-html injected package datasette-json-html into venv datasette done! ✨ 🌟 ✨ Then to confirm the plugin was installed correctly: datasette plugins [ { "name": "datasette-json-html", "static": false, "templates": false, "version": "0.6" } ] | ["Installation", "Advanced installation options", "Using pipx"] | [] |
installation:installing-plugins | installation | installing-plugins | Installing plugins | If you want to install plugins into your local Datasette Docker image you can do so using the following recipe. This will install the plugins and then save a brand new local image called datasette-with-plugins : docker run datasetteproject/datasette \ pip install datasette-vega docker commit $(docker ps -lq) datasette-with-plugins You can now run the new custom image like so: docker run -p 8001:8001 -v `pwd`:/mnt \ datasette-with-plugins \ datasette -p 8001 -h 0.0.0.0 /mnt/fixtures.db You can confirm that the plugins are installed by visiting http://127.0.0.1:8001/-/plugins Some plugins such as datasette-ripgrep may need additional system packages. You can install these by running apt-get install inside the container: docker run datasette-057a0 bash -c ' apt-get update && apt-get install ripgrep && pip install datasette-ripgrep' docker commit $(docker ps -lq) datasette-with-ripgrep | ["Installation", "Advanced installation options", "Using Docker"] | [{"href": "http://127.0.0.1:8001/-/plugins", "label": "http://127.0.0.1:8001/-/plugins"}, {"href": "https://datasette.io/plugins/datasette-ripgrep", "label": "datasette-ripgrep"}] |
installation:id1 | installation | id1 | Installation | If you just want to try Datasette out you don't need to install anything: see Try Datasette without installing anything using Glitch There are two main options for installing Datasette. You can install it directly on to your machine, or you can install it using Docker. If you want to start making contributions to the Datasette project by installing a copy that lets you directly modify the code, take a look at our guide to Setting up a development environment . Basic installation Datasette Desktop for Mac Using Homebrew Using pip Advanced installation options Using pipx Installing plugins using pipx Upgrading packages using pipx Using Docker Loading SpatiaLite Installing plugins A note about extensions | [] | [] |
installation:installation-datasette-desktop | installation | installation-datasette-desktop | Datasette Desktop for Mac | Datasette Desktop is a packaged Mac application which bundles Datasette together with Python and allows you to install and run Datasette directly on your laptop. This is the best option for local installation if you are not comfortable using the command line. | ["Installation", "Basic installation"] | [{"href": "https://datasette.io/desktop", "label": "Datasette Desktop"}] |
installation:installation-basic | installation | installation-basic | Basic installation | ["Installation"] | [] | |
installation:installation-advanced | installation | installation-advanced | Advanced installation options | ["Installation"] | [] | |
installation:installation-extensions | installation | installation-extensions | A note about extensions | SQLite supports extensions, such as SpatiaLite for geospatial operations. These can be loaded using the --load-extension argument, like so: datasette --load-extension=/usr/local/lib/mod_spatialite.dylib Some Python installations do not include support for SQLite extensions. If this is the case you will see the following error when you attempt to load an extension: Your Python installation does not have the ability to load SQLite extensions. In some cases you may see the following error message instead: AttributeError: 'sqlite3.Connection' object has no attribute 'enable_load_extension' On macOS the easiest fix for this is to install Datasette using Homebrew: brew install datasette Use which datasette to confirm that datasette will run that version. The output should look something like this: /usr/local/opt/datasette/bin/datasette If you get a different location here such as /Library/Frameworks/Python.framework/Versions/3.10/bin/datasette you can run the following command to cause datasette to execute the Homebrew version instead: alias datasette=$(echo $(brew --prefix datasette)/bin/datasette) You can undo this operation using: unalias datasette If you need to run SQLite with extension support for other Python code, you can do so by install Python itself using Homebrew: brew install python Then executing Python using: /usr/local/opt/python@3/libexec/bin/python A more convenient way to work with this version of Python may be to use it to create a virtual environment: /usr/local/opt/python@3/libexec/bin/python -m venv datasette-venv Then activate it like this: source datasette-venv/bin/activate Now running python and pip will work against a version of … | ["Installation"] | [] |
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