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14 rows where breadcrumbs contains "Installation" sorted by references
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references 8 ✖
- [{"href": "https://brew.sh/", "label": "Homebrew"}] 2
- [] 1
- [{"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"}] 1
- [{"href": "http://127.0.0.1:8001/-/versions", "label": "http://127.0.0.1:8001/-/versions"}] 1
- [{"href": "https://datasette.io/desktop", "label": "Datasette Desktop"}] 1
- [{"href": "https://hub.docker.com/r/datasetteproject/datasette/", "label": "https://hub.docker.com/r/datasetteproject/datasette/"}, {"href": "https://www.docker.com/docker-mac", "label": "Docker for Mac"}, {"href": "http://127.0.0.1:8001/", "label": "http://127.0.0.1:8001/"}, {"href": "https://latest.datasette.io/fixtures.db", "label": "https://latest.datasette.io/fixtures.db"}] 1
- [{"href": "https://pipxproject.github.io/pipx/", "label": "pipx"}, {"href": "https://brew.sh/", "label": "Homebrew"}] 1
- [{"href": "https://www.python.org/about/gettingstarted/", "label": "Python.org Python For Beginners"}] 1
id | page | ref | title | content | breadcrumbs | references ▼ |
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spatialite:installing-spatialite-on-linux | spatialite | installing-spatialite-on-linux | Installing SpatiaLite on Linux | SpatiaLite is packaged for most Linux distributions. apt install spatialite-bin libsqlite3-mod-spatialite Depending on your distribution, you should be able to run Datasette something like this: datasette --load-extension=/usr/lib/x86_64-linux-gnu/mod_spatialite.so If you are unsure of the location of the module, try running locate mod_spatialite and see what comes back. | ["SpatiaLite", "Installation"] | [] |
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: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:installation-homebrew | installation | installation-homebrew | Using Homebrew | If you have a Mac and use Homebrew , you can install Datasette by running this command in your terminal: brew install datasette This should install the latest version. You can confirm by running: datasette --version You can upgrade to the latest Homebrew packaged version using: brew upgrade datasette Once you have installed Datasette you can install plugins using the following: datasette install datasette-vega If the latest packaged release of Datasette has not yet been made available through Homebrew, you can upgrade your Homebrew installation in-place using: datasette install -U datasette | ["Installation", "Basic installation"] | [{"href": "https://brew.sh/", "label": "Homebrew"}] |
spatialite:installing-spatialite-on-os-x | spatialite | installing-spatialite-on-os-x | Installing SpatiaLite on OS X | The easiest way to install SpatiaLite on OS X is to use Homebrew . brew update brew install spatialite-tools This will install the spatialite command-line tool and the mod_spatialite dynamic library. You can now run Datasette like so: datasette --load-extension=spatialite | ["SpatiaLite", "Installation"] | [{"href": "https://brew.sh/", "label": "Homebrew"}] |
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-docker | installation | installation-docker | Using Docker | A Docker image containing the latest release of Datasette is published to Docker Hub here: https://hub.docker.com/r/datasetteproject/datasette/ If you have Docker installed (for example with Docker for Mac on OS X) you can download and run this image like so: docker run -p 8001:8001 -v `pwd`:/mnt \ datasetteproject/datasette \ datasette -p 8001 -h 0.0.0.0 /mnt/fixtures.db This will start an instance of Datasette running on your machine's port 8001, serving the fixtures.db file in your current directory. Now visit http://127.0.0.1:8001/ to access Datasette. (You can download a copy of fixtures.db from https://latest.datasette.io/fixtures.db ) To upgrade to the most recent release of Datasette, run the following: docker pull datasetteproject/datasette | ["Installation", "Advanced installation options"] | [{"href": "https://hub.docker.com/r/datasetteproject/datasette/", "label": "https://hub.docker.com/r/datasetteproject/datasette/"}, {"href": "https://www.docker.com/docker-mac", "label": "Docker for Mac"}, {"href": "http://127.0.0.1:8001/", "label": "http://127.0.0.1:8001/"}, {"href": "https://latest.datasette.io/fixtures.db", "label": "https://latest.datasette.io/fixtures.db"}] |
installation:installation-pipx | installation | installation-pipx | Using pipx | pipx is a tool for installing Python software with all of its dependencies in an isolated environment, to ensure that they will not conflict with any other installed Python software. If you use Homebrew on macOS you can install pipx like this: brew install pipx pipx ensurepath Without Homebrew you can install it like so: python3 -m pip install --user pipx python3 -m pipx ensurepath The pipx ensurepath command configures your shell to ensure it can find commands that have been installed by pipx - generally by making sure ~/.local/bin has been added to your PATH . Once pipx is installed you can use it to install Datasette like this: pipx install datasette Then run datasette --version to confirm that it has been successfully installed. | ["Installation", "Advanced installation options"] | [{"href": "https://pipxproject.github.io/pipx/", "label": "pipx"}, {"href": "https://brew.sh/", "label": "Homebrew"}] |
installation:installation-pip | installation | installation-pip | Using pip | Datasette requires Python 3.8 or higher. The Python.org Python For Beginners page has instructions for getting started. You can install Datasette and its dependencies using pip : pip install datasette You can now run Datasette like so: datasette | ["Installation", "Basic installation"] | [{"href": "https://www.python.org/about/gettingstarted/", "label": "Python.org Python For Beginners"}] |
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CREATE TABLE [sections] ( [id] TEXT PRIMARY KEY, [page] TEXT, [ref] TEXT, [title] TEXT, [content] TEXT, [breadcrumbs] TEXT, [references] TEXT );