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| datasette-cluster-map | {
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"description": "# datasette-cluster-map\n\n[](https://pypi.python.org/pypi/datasette-cluster-map)\n[](https://github.com/simonw/datasette-cluster-map/blob/master/LICENSE)\n\n\nA [Datasette plugin](http://datasette.readthedocs.io/en/latest/plugins.html) that detects tables with `latitude` and `longitude` columns and then plots them on a map using [Leaflet.markercluster](https://github.com/Leaflet/Leaflet.markercluster).\n\nMore about this project: [Datasette plugins, and building a clustered map visualization](https://simonwillison.net/2018/Apr/20/datasette-plugins/)\n\n## Demo\n\n[datasette-cluster-map-demo.datasettes.com](https://datasette-cluster-map-demo.datasettes.com/) hosts a demo of this plugin running against several different tables.\n\n\n\n## Installation\n\nRun `pip install datasette-cluster-map` to add this plugin to your Datasette virtual environment. Datasette will automatically load the plugin if it is installed in this way.\n\nIf you are deploying using the `datasette publish` command you can use the `--install` option:\n\n datasette publish now mydb.db --install=datasette-cluster-map\n\nIf any of your tables have a `latitude` and `longitude` column, a map will be automatically displayed.\n\nIf your columns are called something else you can configure the column names using [plugin configuration](https://datasette.readthedocs.io/en/stable/plugins.html#plugin-configuration) in a `metadata.json` file. For example, if all of your columns are called `xlat` and `xlng` you can create a `metadata.json` file like this:\n\n {\n \"title\": \"Regular metadata keys can go here too\",\n \"plugins\": {\n \"datasette-cluster-map\": {\n \"latitude_column\": \"xlat\",\n \"longitude_column\": \"xlng\"\n }\n }\n }\n\nThen run Datasette like this:\n\n datasette mydata.db -m metadata.json\n\nThis will configure the required column names for every database loaded by that Datasette instance.\n\nIf you want to customize the column names for just one table in one database, you can do something like this:\n\n {\n \"databases\": {\n \"polar-bears\": {\n \"tables\": {\n \"USGS_WC_eartag_deployments_2009-2011\": {\n \"plugins\": {\n \"datasette-cluster-map\": {\n \"latitude_column\": \"Capture Latitude\",\n \"longitude_column\": \"Capture Longitude\"\n }\n }\n }\n }\n }\n }\n }\n\nYou can also use a custom SQL query to rename those columns to `latitude` and `longitude`, [for example](https://datasette-cluster-map-demo.datasettes.com/polar-bears-455fe3a?sql=select+*%2C+%22Capture+Latitude%22+as+latitude%2C+%22Capture+Longitude%22+as+longitude+from+[USGS_WC_eartag_deployments_2009-2011]):\n\n select *,\n \"Capture Latitude\" as latitude,\n \"Capture Longitude\" as longitude\n from [USGS_WC_eartag_deployments_2009-2011]\n\n## How I deployed the demo\n\n datasette publish now \\\n --install=datasette-cluster-map \\\n --name=\"datasette-cluster-map-demo\" \\\n --alias=\"datasette-cluster-map-demo.datasettes.com\" \\\n polar-bears.db sf-trees.db\n\n\n",
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| datasette-jellyfish | {
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"description": "# datasette-jellyfish\n\n[](https://pypi.org/project/datasette-jellyfish/)\n[](https://github.com/simonw/datasette-jellyfish/blob/master/LICENSE)\n\nDatasette plugin that adds custom SQL functions for fuzzy string matching, built on top of the [Jellyfish](https://github.com/jamesturk/jellyfish) Python library by James Turk and Michael Stephens.\n\nInteractive demos:\n\n* [soundex, metaphone, nysiis, match_rating_codex comparison](https://datasette-jellyfish.now.sh/fixtures?sql=SELECT%0D%0A++++soundex%28%3As%29%2C+%0D%0A++++metaphone%28%3As%29%2C+%0D%0A++++nysiis%28%3As%29%2C+%0D%0A++++match_rating_codex%28%3As%29&s=demo).\n* [distance functions comparison](https://datasette-jellyfish.now.sh/fixtures?sql=SELECT%0D%0A++++levenshtein_distance%28%3As1%2C+%3As2%29%2C%0D%0A++++damerau_levenshtein_distance%28%3As1%2C+%3As2%29%2C%0D%0A++++hamming_distance%28%3As1%2C+%3As2%29%2C%0D%0A++++jaro_distance%28%3As1%2C+%3As2%29%2C%0D%0A++++jaro_winkler%28%3As1%2C+%3As2%29%2C%0D%0A++++match_rating_comparison%28%3As1%2C+%3As2%29%3B&s1=barrack+obama&s2=barrack+h+obama)\n\nExamples:\n\n SELECT soundex(\"hello\");\n -- Outputs H400\n SELECT metaphone(\"hello\");\n -- Outputs HL\n SELECT nysiis(\"hello\");\n -- Outputs HAL\n SELECT match_rating_codex(\"hello\");\n -- Outputs HLL\n SELECT porter_stem(\"running\");\n -- Outputs run\n SELECT levenshtein_distance(\"hello\", \"hello world\");\n -- Outputs 6\n SELECT damerau_levenshtein_distance(\"hello\", \"hello world\");\n -- Outputs 6\n SELECT hamming_distance(\"hello\", \"hello world\");\n -- Outputs 6\n SELECT jaro_distance(\"hello\", \"hello world\");\n -- Outputs 0.8181818181818182\n SELECT jaro_winkler(\"hello\", \"hello world\");\n -- Outputs 0.890909090909091\n SELECT match_rating_comparison(\"hello\", \"helloo\");\n -- Outputs 1\n\nSee [the Jellyfish documentation](https://jellyfish.readthedocs.io/en/latest/) for an explanation of each of these functions.\n\n",
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| datasette-jq | {
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"description": "# datasette-jq\n\n[](https://pypi.org/project/datasette-jq/)\n[](https://circleci.com/gh/simonw/datasette-jq)\n[](https://github.com/simonw/datasette-jq/blob/master/LICENSE)\n\nDatasette plugin that adds custom SQL functions for executing [jq](https://stedolan.github.io/jq/) expressions against JSON values.\n\nInstall this plugin in the same environment as Datasette to enable the `jq()` SQL function.\n\nUsage:\n\n select jq(\n column_with_json,\n \"{top_3: .classifiers[:3], v: .version}\"\n )\n\nSee [the jq manual](https://stedolan.github.io/jq/manual/#Basicfilters) for full details of supported expression syntax.\n\n\n",
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| datasette-json-html | {
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