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| 293361514 | MDEwOlJlcG9zaXRvcnkyOTMzNjE1MTQ= | geocode-sqlite | eyeseast/geocode-sqlite | 0 | eyeseast 25778 | https://github.com/eyeseast/geocode-sqlite | Geocode rows in a SQLite database table | 0 | 2020-09-06T21:05:39Z | 2022-11-02T19:19:56Z | 2022-11-07T17:31:05Z | 125 | 223 | 223 | Python | 1 | 1 | 1 | 1 | 0 | 6 | 0 | 0 | 8 | Apache License 2.0 apache-2.0 | [] | 6 | 8 | 223 | main | {"admin": false, "maintain": false, "push": false, "triage": false, "pull": false} | 6 | 5 | # geocode-sqlite [](https://pypi.org/project/geocode-sqlite/) [](https://github.com/eyeseast/geocode-sqlite/releases) [](https://github.com/eyeseast/geocode-sqlite/actions?query=workflow%3ATest) [](https://github.com/eyeseast/geocode-sqlite/blob/master/LICENSE) Geocode rows from a SQLite table ## Installation Install this tool using `pip` or `pipx`: ```sh # install inside a virtualenv pip install geocode-sqlite # install globally pipx install geocode-sqlite ``` ## Usage Let's say you have a spreadsheet with addresses in it, and you'd like to map those locations. First, create a SQLite database and insert rows from that spreadsheet using `sqlite-utils`. ```sh sqlite-utils insert data.db data data.csv --csv ``` Now, geocode it using OpenStreetMap's Nominatim geocoder. ```sh geocode-sqlite nominatim data.db data \ --location="{address}, {city}, {state} {zip}" \ --delay=1 \ --user-agent="this-is-me" ``` In the command above, you're using Nominatim, which is free and only asks for a unique user agent (`--user-agent`). This will connect to a database (`data.db`) and read all rows from the table `data` (skipping any that already have both a `latitude` and `longitude` column filled). You're also telling the geocoder how to extract a location query (`--location`) from a row of data, using Python's built-in string formatting, and setting a rate limit (`--delay`) of one request per second. For each row where geocoding succeeds, `latitude` and `longitude` will be populated. If you hit an error, or a rate limit, run the same query and pick up where you left off. The resulting table layout can be visualized with [datasette-cluster-map](https://datasette.io/plugins/datasette-cluster-map). Under th… | <div id="readme" class="md" data-path="README.md"><article class="markdown-body entry-content container-lg" itemprop="text"><h1 dir="auto"><a id="user-content-geocode-sqlite" class="anchor" aria-hidden="true" href="#user-content-geocode-sqlite"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M7.775 3.275a.75.75 0 001.06 1.06l1.25-1.25a2 2 0 112.83 2.83l-2.5 2.5a2 2 0 01-2.83 0 .75.75 0 00-1.06 1.06 3.5 3.5 0 004.95 0l2.5-2.5a3.5 3.5 0 00-4.95-4.95l-1.25 1.25zm-4.69 9.64a2 2 0 010-2.83l2.5-2.5a2 2 0 012.83 0 .75.75 0 001.06-1.06 3.5 3.5 0 00-4.95 0l-2.5 2.5a3.5 3.5 0 004.95 4.95l1.25-1.25a.75.75 0 00-1.06-1.06l-1.25 1.25a2 2 0 01-2.83 0z"></path></svg></a>geocode-sqlite</h1> <p dir="auto"><a href="https://pypi.org/project/geocode-sqlite/" rel="nofollow"><img src="https://camo.githubusercontent.com/48afed6b156b122a781142db699a225016ec438b4f64f9534d5f852433332a50/68747470733a2f2f696d672e736869656c64732e696f2f707970692f762f67656f636f64652d73716c6974652e737667" alt="PyPI" data-canonical-src="https://img.shields.io/pypi/v/geocode-sqlite.svg" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/geocode-sqlite/releases"><img src="https://camo.githubusercontent.com/cca0e9a2e0f5dbbfb761aeb9803bac6602b9831541a309b6c5a73ebec690b35e/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f65796573656173742f67656f636f64652d73716c6974653f696e636c7564655f70726572656c6561736573266c6162656c3d6368616e67656c6f67" alt="Changelog" data-canonical-src="https://img.shields.io/github/v/release/eyeseast/geocode-sqlite?include_prereleases&label=changelog" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/geocode-sqlite/actions?query=workflow%3ATest"><img src="https://github.com/eyeseast/geocode-sqlite/workflows/Test/badge.svg" alt="Tests" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/geocode-sqlite/blob/master/LICENSE"><img src="https://camo.githubusercontent.com/1698104e97… | 1 | public | 0 | 0 | 0 | ||||
| 374846311 | MDEwOlJlcG9zaXRvcnkzNzQ4NDYzMTE= | datasette-geojson | eyeseast/datasette-geojson | 0 | eyeseast 25778 | https://github.com/eyeseast/datasette-geojson | Add GeoJSON output to Datasette queries | 0 | 2021-06-08T01:33:19Z | 2022-02-16T19:59:42Z | 2022-02-16T20:02:49Z | 1102 | 3 | 3 | Python | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 3 | ["datasette-io", "datasette-plugin", "geojson", "gis", "sqlite"] | 1 | 3 | 3 | main | {"admin": false, "maintain": false, "push": false, "triage": false, "pull": false} | 1 | 1 | # datasette-geojson [](https://pypi.org/project/datasette-geojson/) [](https://github.com/eyeseast/datasette-geojson/releases) [](https://github.com/eyeseast/datasette-geojson/actions?query=workflow%3ATest) [](https://github.com/eyeseast/datasette-geojson/blob/main/LICENSE) Add GeoJSON as an output option for datasette queries. ## Installation Install this plugin in the same environment as Datasette. datasette install datasette-geojson ## Usage To render GeoJSON, add a `.geojson` extension to any query URL that includes a `geometry` column. That column should be a valid [GeoJSON geometry](https://datatracker.ietf.org/doc/html/rfc7946#section-3.1). For example, you might use [geojson-to-sqlite](https://pypi.org/project/geojson-to-sqlite/) or [shapefile-to-sqlite](https://pypi.org/project/shapefile-to-sqlite/) to load [neighborhood boundaries](https://bostonopendata-boston.opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0/explore) into a SQLite database. ```sh wget -O neighborhoods.geojson https://opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0.geojson geojson-to-sqlite boston.db neighborhoods neighborhoods.geojson --spatial-index # create a spatial index datasette serve boston.db --load-extension spatialite ``` If you're using Spatialite, the geometry column will be in a binary format. If not, make sure the `geometry` column is a well-formed [GeoJSON geometry](https://datatracker.ietf.org/doc/html/rfc7946#section-3.1). If you used `geojson-to-sqlite` or `shapefile-to-sqlite`, you should be all set. Run this query in Datasette and you'll see a link to download GeoJSON: ```sql select rowid, OBJECTID, Name, Acres, Neighborhood_ID, SqMiles, … | <div id="readme" class="md" data-path="README.md"><article class="markdown-body entry-content container-lg" itemprop="text"><h1 dir="auto"><a id="user-content-datasette-geojson" class="anchor" aria-hidden="true" href="#user-content-datasette-geojson"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M7.775 3.275a.75.75 0 001.06 1.06l1.25-1.25a2 2 0 112.83 2.83l-2.5 2.5a2 2 0 01-2.83 0 .75.75 0 00-1.06 1.06 3.5 3.5 0 004.95 0l2.5-2.5a3.5 3.5 0 00-4.95-4.95l-1.25 1.25zm-4.69 9.64a2 2 0 010-2.83l2.5-2.5a2 2 0 012.83 0 .75.75 0 001.06-1.06 3.5 3.5 0 00-4.95 0l-2.5 2.5a3.5 3.5 0 004.95 4.95l1.25-1.25a.75.75 0 00-1.06-1.06l-1.25 1.25a2 2 0 01-2.83 0z"></path></svg></a>datasette-geojson</h1> <p dir="auto"><a href="https://pypi.org/project/datasette-geojson/" rel="nofollow"><img src="https://camo.githubusercontent.com/526d2a27eb7e19691a8f966dba069780f3fe109d6ac662d72901ff561f31b133/68747470733a2f2f696d672e736869656c64732e696f2f707970692f762f6461746173657474652d67656f6a736f6e2e737667" alt="PyPI" data-canonical-src="https://img.shields.io/pypi/v/datasette-geojson.svg" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/datasette-geojson/releases"><img src="https://camo.githubusercontent.com/367e4f55f2b376367d7fbc8ab6ec5d765b3b04590149b3a8f60794cd39a5b54d/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f65796573656173742f6461746173657474652d67656f6a736f6e3f696e636c7564655f70726572656c6561736573266c6162656c3d6368616e67656c6f67" alt="Changelog" data-canonical-src="https://img.shields.io/github/v/release/eyeseast/datasette-geojson?include_prereleases&label=changelog" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/datasette-geojson/actions?query=workflow%3ATest"><img src="https://github.com/eyeseast/datasette-geojson/workflows/Test/badge.svg" alt="Tests" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/datasette-geojson/blob/main/LICENSE"><img src="https… | 1 | public | 0 | |||||||
| 382986564 | MDEwOlJlcG9zaXRvcnkzODI5ODY1NjQ= | datasette-geojson-map | eyeseast/datasette-geojson-map | 0 | eyeseast 25778 | https://github.com/eyeseast/datasette-geojson-map | Render a map for any query with a geometry column | 0 | 2021-07-05T01:54:13Z | 2022-03-04T00:16:17Z | 2022-04-27T20:39:47Z | 3651 | 9 | 9 | Python | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 10 | ["datasette-io", "datasette-plugin", "geojson", "gis", "leafletjs", "mapping"] | 0 | 10 | 9 | main | {"admin": false, "maintain": false, "push": false, "triage": false, "pull": false} | 0 | 1 | # datasette-geojson-map [](https://pypi.org/project/datasette-geojson-map/) [](https://github.com/eyeseast/datasette-geojson-map/releases) [](https://github.com/eyeseast/datasette-geojson-map/actions?query=workflow%3ATest) [](https://github.com/eyeseast/datasette-geojson-map/blob/main/LICENSE) Render a map for any query with a geometry column ## Installation Install this plugin in the same environment as Datasette. $ datasette install datasette-geojson-map ## Usage Start by loading a GIS file. For example, you might use [geojson-to-sqlite](https://pypi.org/project/geojson-to-sqlite/) or [shapefile-to-sqlite](https://pypi.org/project/shapefile-to-sqlite/) to load [neighborhood boundaries](https://bostonopendata-boston.opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0/explore) into a SQLite database. ```sh wget -O neighborhoods.geojson https://opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0.geojson geojson-to-sqlite boston.db neighborhoods neighborhoods.geojson ``` (The command above uses Spatialite, but that's not required.) Start up `datasette` and navigate to the `neighborhoods` table. ```sh datasette serve boston.db # in another terminal tab open http://localhost:8001/boston/neighborhoods ``` You should see a map centered on Boston with each neighborhood outlined. Clicking a boundary will bring up a popup with details on that feature.  This plugin relies on (and will install) [datasette-geojson](https://github.com/eyeseast/datasette-geojson). Any query that includes a `geometry` column will produce a map of the results. This also includes single row views. Run the incl… | <div id="readme" class="md" data-path="README.md"><article class="markdown-body entry-content container-lg" itemprop="text"><h1 dir="auto"><a id="user-content-datasette-geojson-map" class="anchor" aria-hidden="true" href="#user-content-datasette-geojson-map"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M7.775 3.275a.75.75 0 001.06 1.06l1.25-1.25a2 2 0 112.83 2.83l-2.5 2.5a2 2 0 01-2.83 0 .75.75 0 00-1.06 1.06 3.5 3.5 0 004.95 0l2.5-2.5a3.5 3.5 0 00-4.95-4.95l-1.25 1.25zm-4.69 9.64a2 2 0 010-2.83l2.5-2.5a2 2 0 012.83 0 .75.75 0 001.06-1.06 3.5 3.5 0 00-4.95 0l-2.5 2.5a3.5 3.5 0 004.95 4.95l1.25-1.25a.75.75 0 00-1.06-1.06l-1.25 1.25a2 2 0 01-2.83 0z"></path></svg></a>datasette-geojson-map</h1> <p dir="auto"><a href="https://pypi.org/project/datasette-geojson-map/" rel="nofollow"><img src="https://camo.githubusercontent.com/1534879e09b364c34ab31432e489c7be09c28cdc94c68a85f1ffefc9b2a0f8df/68747470733a2f2f696d672e736869656c64732e696f2f707970692f762f6461746173657474652d67656f6a736f6e2d6d61702e737667" alt="PyPI" data-canonical-src="https://img.shields.io/pypi/v/datasette-geojson-map.svg" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/datasette-geojson-map/releases"><img src="https://camo.githubusercontent.com/d45ff62474954cad3f625bc2d1e121eec6e3b2797d55917af6419fb819b45cef/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f65796573656173742f6461746173657474652d67656f6a736f6e2d6d61703f696e636c7564655f70726572656c6561736573266c6162656c3d6368616e67656c6f67" alt="Changelog" data-canonical-src="https://img.shields.io/github/v/release/eyeseast/datasette-geojson-map?include_prereleases&label=changelog" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/datasette-geojson-map/actions?query=workflow%3ATest"><img src="https://github.com/eyeseast/datasette-geojson-map/workflows/Test/badge.svg" alt="Tests" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/… | 1 | public | 0 | |||||||
| 461322238 | R_kgDOG383_g | sqlite-colorbrewer | eyeseast/sqlite-colorbrewer | 0 | eyeseast 25778 | https://github.com/eyeseast/sqlite-colorbrewer | A custom function to use ColorBrewer scales in SQLite queries | 0 | 2022-02-19T21:53:46Z | 2022-03-03T17:16:40Z | 2022-03-02T03:04:56Z | 19 | 4 | 4 | Python | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | Apache License 2.0 apache-2.0 | [] | 0 | 0 | 4 | main | {"admin": false, "maintain": false, "push": false, "triage": false, "pull": false} | 0 | 1 | # sqlite-colorbrewer [](https://pypi.org/project/sqlite-colorbrewer/) [](https://github.com/eyeseast/sqlite-colorbrewer/releases) [](https://github.com/eyeseast/sqlite-colorbrewer/actions?query=workflow%3ATest) [](https://github.com/eyeseast/sqlite-colorbrewer/blob/main/LICENSE) A custom function to use [ColorBrewer](https://colorbrewer2.org/) scales in SQLite queries. Colors are exported from [here](https://colorbrewer2.org/export/colorbrewer.json). ## Installation To install as a Python library and use with the [standard SQLite3 module](https://docs.python.org/3/library/sqlite3.html): pip install sqlite-colorbrewer To install this plugin in the same environment as Datasette. datasette install sqlite-colorbrewer ## Usage If you're using this library with Datasette, it will be automatically registered as a plugin and available for use in SQL queries, like so: ```sql SELECT colorbrewer('Blues', 9, 0); ``` That will return a single value: `"rgb(247,251,255)"` To use with a SQLite connection outside of Datasette, use the `register` function: ```python >>> import sqlite3 >>> import sqlite_colorbrewer >>> conn = sqlite3.connect(':memory') >>> sqlite_colorbrewer.register(conn) >>> cursor = conn.execute("SELECT colorbrewer('Blues', 9, 0);") >>> result = next(cursor) >>> print(result) rgb(247,251,255) ``` ## Development To set up this plugin locally, first checkout the code. Then create a new virtual environment: cd sqlite-colorbrewer python3 -mvenv venv source venv/bin/activate Or if you are using `pipenv`: pipenv shell Now install the dependencies and test dependencies: pip install -e '.[test]' To run the tests: pytest To build `sqlite_col… | <div id="readme" class="md" data-path="README.md"><article class="markdown-body entry-content container-lg" itemprop="text"><h1 dir="auto"><a id="user-content-sqlite-colorbrewer" class="anchor" aria-hidden="true" href="#user-content-sqlite-colorbrewer"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M7.775 3.275a.75.75 0 001.06 1.06l1.25-1.25a2 2 0 112.83 2.83l-2.5 2.5a2 2 0 01-2.83 0 .75.75 0 00-1.06 1.06 3.5 3.5 0 004.95 0l2.5-2.5a3.5 3.5 0 00-4.95-4.95l-1.25 1.25zm-4.69 9.64a2 2 0 010-2.83l2.5-2.5a2 2 0 012.83 0 .75.75 0 001.06-1.06 3.5 3.5 0 00-4.95 0l-2.5 2.5a3.5 3.5 0 004.95 4.95l1.25-1.25a.75.75 0 00-1.06-1.06l-1.25 1.25a2 2 0 01-2.83 0z"></path></svg></a>sqlite-colorbrewer</h1> <p dir="auto"><a href="https://pypi.org/project/sqlite-colorbrewer/" rel="nofollow"><img src="https://camo.githubusercontent.com/04ce9615649f436d9d448e3c317bf8f12473237aa608429218b746755cbd0ef6/68747470733a2f2f696d672e736869656c64732e696f2f707970692f762f73716c6974652d636f6c6f726272657765722e737667" alt="PyPI" data-canonical-src="https://img.shields.io/pypi/v/sqlite-colorbrewer.svg" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/sqlite-colorbrewer/releases"><img src="https://camo.githubusercontent.com/638c41b57fe97aeaec1e6be4a0f1d0c69e4d9259585553a48a5f21ef40047542/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f65796573656173742f73716c6974652d636f6c6f726272657765723f696e636c7564655f70726572656c6561736573266c6162656c3d6368616e67656c6f67" alt="Changelog" data-canonical-src="https://img.shields.io/github/v/release/eyeseast/sqlite-colorbrewer?include_prereleases&label=changelog" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/sqlite-colorbrewer/actions?query=workflow%3ATest"><img src="https://github.com/eyeseast/sqlite-colorbrewer/workflows/Test/badge.svg" alt="Tests" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/sqlite-colorbrewer/blob/main/LICENSE"><… | 1 | public | 0 | ||||||
| 499911426 | R_kgDOHcwLAg | datasette-query-files | eyeseast/datasette-query-files | 0 | eyeseast 25778 | https://github.com/eyeseast/datasette-query-files | Write Datasette canned queries as plain SQL files | 0 | 2022-06-04T18:52:07Z | 2022-07-02T19:46:52Z | 2022-07-02T20:40:51Z | 24 | 8 | 8 | Python | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 2 | Apache License 2.0 apache-2.0 | ["datasette", "datasette-plugin", "python", "sql", "sqlite"] | 0 | 2 | 8 | main | {"admin": false, "maintain": false, "push": false, "triage": false, "pull": false} | 0 | 1 | # datasette-query-files [](https://pypi.org/project/datasette-query-files/) [](https://github.com/eyeseast/datasette-query-files/releases) [](https://github.com/eyeseast/datasette-query-files/actions?query=workflow%3ATest) [](https://github.com/eyeseast/datasette-query-files/blob/main/LICENSE) Write Datasette canned queries as plain SQL files. ## Installation Install this plugin in the same environment as Datasette. datasette install datasette-query-files Or using `pip` or `pipenv`: pip install datasette-query-files pipenv install datasette-query-files ## Usage This plugin will look for [canned queries](https://docs.datasette.io/en/stable/sql_queries.html#canned-queries) in the filesystem, in addition any defined in metadata. Let's say you're working in a directory called `project-directory`, with a database file called `my-project.db`. Start by creating a `queries` directory with a `my-project` directory inside it. Any SQL file inside that `my-project` folder will become a canned query that can be run on the `my-project` database. If you have a `query-name.sql` file and a `query-name.json` (or `query-name.yml`) file in the same directory, the JSON file will be used as query metadata. ``` project-directory/ my-project.db queries/ my-project/ query-name.sql # a query query-name.yml # query metadata ``` ## Development To set up this plugin locally, first checkout the code. Then create a new virtual environment: cd datasette-query-files python3 -m venv venv source venv/bin/activate Now install the dependencies and test dependencies: pip install -e '.[test]' To run the tests: pytest | <div id="readme" class="md" data-path="README.md"><article class="markdown-body entry-content container-lg" itemprop="text"><h1 dir="auto"><a id="user-content-datasette-query-files" class="anchor" aria-hidden="true" href="#user-content-datasette-query-files"><svg class="octicon octicon-link" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M7.775 3.275a.75.75 0 001.06 1.06l1.25-1.25a2 2 0 112.83 2.83l-2.5 2.5a2 2 0 01-2.83 0 .75.75 0 00-1.06 1.06 3.5 3.5 0 004.95 0l2.5-2.5a3.5 3.5 0 00-4.95-4.95l-1.25 1.25zm-4.69 9.64a2 2 0 010-2.83l2.5-2.5a2 2 0 012.83 0 .75.75 0 001.06-1.06 3.5 3.5 0 00-4.95 0l-2.5 2.5a3.5 3.5 0 004.95 4.95l1.25-1.25a.75.75 0 00-1.06-1.06l-1.25 1.25a2 2 0 01-2.83 0z"></path></svg></a>datasette-query-files</h1> <p dir="auto"><a href="https://pypi.org/project/datasette-query-files/" rel="nofollow"><img src="https://camo.githubusercontent.com/c204f01390d188a0f01eeafcd5f9f369b653b2cfaaef56534a36497a575cc317/68747470733a2f2f696d672e736869656c64732e696f2f707970692f762f6461746173657474652d71756572792d66696c65732e737667" alt="PyPI" data-canonical-src="https://img.shields.io/pypi/v/datasette-query-files.svg" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/datasette-query-files/releases"><img src="https://camo.githubusercontent.com/d614cd96ac7137aced94769f27f45a90dfc8ddd9bbff39b15d6c276704b7e703/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f762f72656c656173652f65796573656173742f6461746173657474652d71756572792d66696c65733f696e636c7564655f70726572656c6561736573266c6162656c3d6368616e67656c6f67" alt="Changelog" data-canonical-src="https://img.shields.io/github/v/release/eyeseast/datasette-query-files?include_prereleases&label=changelog" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/datasette-query-files/actions?query=workflow%3ATest"><img src="https://github.com/eyeseast/datasette-query-files/workflows/Test/badge.svg" alt="Tests" style="max-width: 100%;"></a> <a href="https://github.com/eyeseast/… | 1 | public | 0 | {"id": 400878073, "node_id": "MDEwOlJlcG9zaXRvcnk0MDA4NzgwNzM=", "name": "datasette-plugin-template-repository", "full_name": "simonw/datasette-plugin-template-repository", "private": false, "owner": {"login": "simonw", "id": 9599, "node_id": "MDQ6VXNlcjk1OTk=", "avatar_url": "https://avatars.githubusercontent.com/u/9599?v=4", "gravatar_id": "", "url": "https://api.github.com/users/simonw", "html_url": "https://github.com/simonw", "followers_url": "https://api.github.com/users/simonw/followers", "following_url": "https://api.github.com/users/simonw/following{/other_user}", "gists_url": "https://api.github.com/users/simonw/gists{/gist_id}", "starred_url": "https://api.github.com/users/simonw/starred{/owner}{/repo}", "subscriptions_url": "https://api.github.com/users/simonw/subscriptions", "organizations_url": "https://api.github.com/users/simonw/orgs", "repos_url": "https://api.github.com/users/simonw/repos", "events_url": "https://api.github.com/users/simonw/events{/privacy}", "received_events_url": "https://api.github.com/users/simonw/received_events", "type": "User", "site_admin": false}, "html_url": "https://github.com/simonw/datasette-plugin-template-repository", "description": "GitHub template repository for creating new Datasette plugins, using the simonw/datasette-plugin cookiecutter template", "fork": false, "url": "https://api.github.com/repos/simonw/datasette-plugin-template-repository", "forks_url": "https://api.github.com/repos/simonw/datasette-plugin-template-repository/forks", "keys_url": "https://api.github.com/repos/simonw/datasette-plugin-template-repository/keys{/key_id}", "collaborators_url": "https://api.github.com/repos/simonw/datasette-plugin-template-repository/collaborators{/collaborator}", "teams_url": "https://api.github.com/repos/simonw/datasette-plugin-template-repository/teams", "hooks_url": "https://api.github.com/repos/simonw/datasette-plugin-template-repository/hooks", "issue_events_url": "https://api.github.com/repos/simonw/datasette-plugin-template-repository/issues/events{/numbe… | 0 |
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