id,node_id,name,full_name,private,owner,html_url,description,fork,created_at,updated_at,pushed_at,homepage,size,stargazers_count,watchers_count,language,has_issues,has_projects,has_downloads,has_wiki,has_pages,forks_count,archived,disabled,open_issues_count,license,topics,forks,open_issues,watchers,default_branch,permissions,temp_clone_token,organization,network_count,subscribers_count,readme,readme_html,allow_forking,visibility,is_template,template_repository,web_commit_signoff_required,has_discussions
184168864,MDEwOlJlcG9zaXRvcnkxODQxNjg4NjQ=,datasette-render-html,simonw/datasette-render-html,0,9599,https://github.com/simonw/datasette-render-html,Plugin for selectively rendering the HTML is specific columns,0,2019-04-30T01:21:25Z,2020-09-24T04:44:47Z,2021-03-17T03:57:13Z,,8,2,2,Python,1,1,1,1,0,2,0,0,1,,"[""datasette"", ""datasette-plugin"", ""datasette-io""]",2,1,2,master,"{""admin"": false, ""push"": false, ""pull"": false}",,,2,1,"# datasette-render-html
[](https://pypi.org/project/datasette-render-html/)
[](https://circleci.com/gh/simonw/datasette-render-html)
[](https://github.com/simonw/datasette-render-html/blob/master/LICENSE)
This Datasette plugin lets you configure Datasette to render specific columns as HTML in the table and row interfaces.
This means you can store HTML in those columns and have it rendered as such on those pages.
If you have a database called `docs.db` containing a `glossary` table and you want the `definition` column in that table to be rendered as HTML, you would use a `metadata.json` file that looks like this:
{
""databases"": {
""docs"": {
""tables"": {
""glossary"": {
""plugins"": {
""datasette-render-html"": {
""columns"": [""definition""]
}
}
}
}
}
}
}
## Security
This plugin allows HTML to be rendered exactly as it is stored in the database. As such, you should be sure only to use this against columns with content that you trust - otherwise you could open yourself up to an [XSS attack](https://owasp.org/www-community/attacks/xss/).
It's possible to configure this plugin to apply to columns with specific names across whole databases or the full Datasette instance, but doing so is not safe. It could open you up to XSS vulnerabilities where an attacker composes a SQL query that results in a column containing unsafe HTML.
As such, you should only use this plugin against specific columns in specific tables, as shown in the example above.
","
datasette-render-html
This Datasette plugin lets you configure Datasette to render specific columns as HTML in the table and row interfaces.
This means you can store HTML in those columns and have it rendered as such on those pages.
If you have a database called docs.db containing a glossary table and you want the definition column in that table to be rendered as HTML, you would use a metadata.json file that looks like this:
This plugin allows HTML to be rendered exactly as it is stored in the database. As such, you should be sure only to use this against columns with content that you trust - otherwise you could open yourself up to an XSS attack.
It's possible to configure this plugin to apply to columns with specific names across whole databases or the full Datasette instance, but doing so is not safe. It could open you up to XSS vulnerabilities where an attacker composes a SQL query that results in a column containing unsafe HTML.
As such, you should only use this plugin against specific columns in specific tables, as shown in the example above.
",,,,,,
190950781,MDEwOlJlcG9zaXRvcnkxOTA5NTA3ODE=,datasette-bplist,simonw/datasette-bplist,0,9599,https://github.com/simonw/datasette-bplist,Datasette plugin for working with Apple's binary plist format,0,2019-06-09T01:15:01Z,2021-06-07T18:05:00Z,2019-06-09T01:17:19Z,,7,9,9,Python,1,1,1,1,0,0,0,0,1,apache-2.0,"[""bplist"", ""datasette"", ""datasette-plugin"", ""datasette-io""]",0,1,9,master,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,0,"# datasette-bplist
[](https://pypi.org/project/datasette-bplist/)
[](https://circleci.com/gh/simonw/datasette-bplist)
[](https://github.com/simonw/datasette-bplist/blob/master/LICENSE)
Datasette plugin for working with Apple's [binary plist](https://en.wikipedia.org/wiki/Property_list) format.
This plugin adds two features: a display hook and a SQL function.
The display hook will detect any database values that are encoded using the binary plist format. It will decode them, convert them into JSON and display them pretty-printed in the Datasette UI.
The SQL function `bplist_to_json(value)` can be used inside a SQL query to convert a binary plist value into a JSON string. This can then be used with SQLite's `json_extract()` function or with the [datasette-jq](https://github.com/simonw/datasette-jq) plugin to further analyze that data as part of a SQL query.
Install this plugin in the same environment as Datasette to enable this new functionality:
pip install datasette-bplist
## Trying it out
If you use a Mac you already have plenty of SQLite databases that contain binary plist data.
One example is the database that powers the Apple Photos app.
This database tends to be locked, so you will need to create a copy of the database in order to run queries against it:
cp ~/Pictures/Photos\ Library.photoslibrary/database/photos.db /tmp/photos.db
The database also makes use of custom SQLite extensions which prevent it from opening in Datasette.
You can work around this by exporting the data that you want to experiment with into a new SQLite file.
I recommend trying this plugin against the `RKMaster_dataNote` table, which contains plist-encoded EXIF metadata about the photos you have taken.
You can export that table into a fresh database like so:
sqlite3 /tmp/photos.db "".dump RKMaster_dataNote"" | sqlite3 /tmp/exif.db
Now run `datasette /tmp/exif.db` and you can start trying out the plugin.
## Using the bplist_to_json() SQL function
Once you have the `exif.db` demo working, you can try the `bplist_to_json()` SQL function.
Here's a query that shows the camera lenses you have used the most often to take photos:
select
json_extract(
bplist_to_json(value),
""$.{Exif}.LensModel""
) as lens,
count(*) as n
from RKMaster_dataNote
group by lens
order by n desc;
If you have a large number of photos this query can take a long time to execute, so you may need to increase the SQL time limit enforced by Datasette like so:
$ datasette /tmp/exif.db \
--config sql_time_limit_ms:10000
Here's another query, showing the time at which you took every photo in your library which is classified as as screenshot:
select
attachedToId,
json_extract(
bplist_to_json(value),
""$.{Exif}.DateTimeOriginal""
)
from RKMaster_dataNote
where
json_extract(
bplist_to_json(value),
""$.{Exif}.UserComment""
) = ""Screenshot""
And if you install the [datasette-cluster-map](https://github.com/simonw/datasette-cluster-map) plugin, this query will show you a map of your most recent 1000 photos:
select
*,
json_extract(
bplist_to_json(value),
""$.{GPS}.Latitude""
) as latitude,
-json_extract(
bplist_to_json(value),
""$.{GPS}.Longitude""
) as longitude,
json_extract(
bplist_to_json(value),
""$.{Exif}.DateTimeOriginal""
) as datetime
from
RKMaster_dataNote
where
latitude is not null
order by
attachedToId desc
","
datasette-bplist
Datasette plugin for working with Apple's binary plist format.
This plugin adds two features: a display hook and a SQL function.
The display hook will detect any database values that are encoded using the binary plist format. It will decode them, convert them into JSON and display them pretty-printed in the Datasette UI.
The SQL function bplist_to_json(value) can be used inside a SQL query to convert a binary plist value into a JSON string. This can then be used with SQLite's json_extract() function or with the datasette-jq plugin to further analyze that data as part of a SQL query.
Install this plugin in the same environment as Datasette to enable this new functionality:
pip install datasette-bplist
Trying it out
If you use a Mac you already have plenty of SQLite databases that contain binary plist data.
One example is the database that powers the Apple Photos app.
This database tends to be locked, so you will need to create a copy of the database in order to run queries against it:
Now run datasette /tmp/exif.db and you can start trying out the plugin.
Using the bplist_to_json() SQL function
Once you have the exif.db demo working, you can try the bplist_to_json() SQL function.
Here's a query that shows the camera lenses you have used the most often to take photos:
select
json_extract(
bplist_to_json(value),
""$.{Exif}.LensModel""
) as lens,
count(*) as n
from RKMaster_dataNote
group by lens
order by n desc;
If you have a large number of photos this query can take a long time to execute, so you may need to increase the SQL time limit enforced by Datasette like so:
Here's another query, showing the time at which you took every photo in your library which is classified as as screenshot:
select
attachedToId,
json_extract(
bplist_to_json(value),
""$.{Exif}.DateTimeOriginal""
)
from RKMaster_dataNote
where
json_extract(
bplist_to_json(value),
""$.{Exif}.UserComment""
) = ""Screenshot""
And if you install the datasette-cluster-map plugin, this query will show you a map of your most recent 1000 photos:
select
*,
json_extract(
bplist_to_json(value),
""$.{GPS}.Latitude""
) as latitude,
-json_extract(
bplist_to_json(value),
""$.{GPS}.Longitude""
) as longitude,
json_extract(
bplist_to_json(value),
""$.{Exif}.DateTimeOriginal""
) as datetime
from
RKMaster_dataNote
where
latitude is not null
order by
attachedToId desc
",,,,,,
191022928,MDEwOlJlcG9zaXRvcnkxOTEwMjI5Mjg=,datasette-render-binary,simonw/datasette-render-binary,0,9599,https://github.com/simonw/datasette-render-binary,Datasette plugin for rendering binary data,0,2019-06-09T15:25:52Z,2021-06-02T09:29:20Z,2019-06-13T16:14:31Z,,62,7,7,Python,1,1,1,1,0,0,0,0,1,apache-2.0,"[""datasette"", ""datasette-plugin"", ""datasette-io""]",0,1,7,master,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,1,"# datasette-render-binary
[](https://pypi.org/project/datasette-render-binary/)
[](https://circleci.com/gh/simonw/datasette-render-binary)
[](https://github.com/simonw/datasette-render-binary/blob/master/LICENSE)
Datasette plugin for rendering binary data.
Install this plugin in the same environment as Datasette to enable this new functionality:
pip install datasette-render-binary
Binary data in cells will now be rendered as a mixture of characters and octets.
","
datasette-render-binary
Datasette plugin for rendering binary data.
Install this plugin in the same environment as Datasette to enable this new functionality:
pip install datasette-render-binary
Binary data in cells will now be rendered as a mixture of characters and octets.
",,,,,,
195696804,MDEwOlJlcG9zaXRvcnkxOTU2OTY4MDQ=,datasette-cors,simonw/datasette-cors,0,9599,https://github.com/simonw/datasette-cors,Datasette plugin for configuring CORS headers,0,2019-07-07T21:03:11Z,2021-02-27T00:31:13Z,2019-07-11T04:40:57Z,,11,9,9,Python,1,1,1,1,0,0,0,0,1,apache-2.0,"[""datasette"", ""datasette-plugin"", ""datasette-io""]",0,1,9,master,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,3,"# datasette-cors
[](https://pypi.org/project/datasette-cors/)
[](https://circleci.com/gh/simonw/datasette-cors)
[](https://github.com/simonw/datasette-cors/blob/master/LICENSE)
Datasette plugin for configuring CORS headers, based on https://github.com/simonw/asgi-cors
You can use this plugin to allow JavaScript running on a whitelisted set of domains to make `fetch()` calls to the JSON API provided by your Datasette instance.
## Installation
pip install datasette-cors
## Configuration
You need to add some configuration to your Datasette `metadata.json` file for this plugin to take effect.
To whitelist specific domains, use this:
```json
{
""plugins"": {
""datasette-cors"": {
""hosts"": [""https://www.example.com""]
}
}
}
```
You can also whitelist patterns like this:
```json
{
""plugins"": {
""datasette-cors"": {
""host_wildcards"": [""https://*.example.com""]
}
}
}
```
## Testing it
To test this plugin out, run it locally by saving one of the above examples as `metadata.json` and running this:
$ datasette --memory -m metadata.json
Now visit https://www.example.com/ in your browser, open the browser developer console and paste in the following:
```javascript
fetch(""http://127.0.0.1:8001/:memory:.json?sql=select+sqlite_version%28%29"").then(r => r.json()).then(console.log)
```
If the plugin is running correctly, you will see the JSON response output to the console.
","
You can use this plugin to allow JavaScript running on a whitelisted set of domains to make fetch() calls to the JSON API provided by your Datasette instance.
Installation
pip install datasette-cors
Configuration
You need to add some configuration to your Datasette metadata.json file for this plugin to take effect.
If the plugin is running correctly, you will see the JSON response output to the console.
",,,,,,
221802296,MDEwOlJlcG9zaXRvcnkyMjE4MDIyOTY=,datasette-template-sql,simonw/datasette-template-sql,0,9599,https://github.com/simonw/datasette-template-sql,Datasette plugin for executing SQL queries from templates,0,2019-11-14T23:05:34Z,2021-05-18T17:58:47Z,2021-05-18T17:58:44Z,https://datasette.io/plugins/datasette-template-sql,23,6,6,Python,1,1,1,1,0,0,0,0,1,apache-2.0,"[""datasette"", ""datasette-plugin"", ""datasette-io""]",0,1,6,main,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,1,"# datasette-template-sql
[](https://pypi.org/project/datasette-template-sql/)
[](https://github.com/simonw/datasette-template-sql/releases)
[](https://github.com/simonw/datasette-template-sql/actions?query=workflow%3ATest)
[](https://github.com/simonw/datasette-template-sql/blob/main/LICENSE)
Datasette plugin for executing SQL queries from templates.
## Examples
[datasette.io](https://datasette.io/) uses this plugin extensively with [custom page templates](https://docs.datasette.io/en/stable/custom_templates.html#custom-pages), check out [simonw/datasette.io](https://github.com/simonw/datasette.io) to see how it works.
[www.niche-museums.com](https://www.niche-museums.com/) uses this plugin to run a custom themed website on top of Datasette. The full source code for the site [is here](https://github.com/simonw/museums) - see also [niche-museums.com, powered by Datasette](https://simonwillison.net/2019/Nov/25/niche-museums/).
[simonw/til](https://github.com/simonw/til) is another simple example, described in [Using a self-rewriting README powered by GitHub Actions to track TILs](https://simonwillison.net/2020/Apr/20/self-rewriting-readme/).
## Installation
Run this command to install the plugin in the same environment as Datasette:
$ pip install datasette-template-sql
## Usage
This plugin makes a new function, `sql(sql_query)`, available to your Datasette templates.
You can use it like this:
```html+jinja
{% for row in sql(""select 1 + 1 as two, 2 * 4 as eight"") %}
{% for key in row.keys() %}
{{ key }}: {{ row[key] }}
{% endfor %}
{% endfor %}
```
The plugin will execute SQL against the current database for the page in `database.html`, `table.html` and `row.html` templates. If a template does not have a current database (`index.html` for example) the query will execute against the first attached database.
### Queries with arguments
You can construct a SQL query using `?` or `:name` parameter syntax by passing a list or dictionary as a second argument:
```html+jinja
{% for row in sql(""select distinct topic from til order by topic"") %}
{{ row.topic }}
{% for til in sql(""select * from til where topic = ?"", [row.topic]) %}
{% endfor %}
```
Here's the same example using the `:topic` style of parameters:
```html+jinja
{% for row in sql(""select distinct topic from til order by topic"") %}
{{ row.topic }}
{% for til in sql(""select * from til where topic = :topic"", {""topic"": row.topic}) %}
{% endfor %}
```
### Querying a different database
You can pass an optional `database=` argument to specify a named database to use for the query. For example, if you have attached a `news.db` database you could use this:
```html+jinja
{% for article in sql(
""select headline, date, summary from articles order by date desc limit 5"",
database=""news""
) %}
{{ article.headline }}
{{ article.date }}
{{ article.summary }}
{% endfor %}
```
","
datasette-template-sql
Datasette plugin for executing SQL queries from templates.
Run this command to install the plugin in the same environment as Datasette:
$ pip install datasette-template-sql
Usage
This plugin makes a new function, sql(sql_query), available to your Datasette templates.
You can use it like this:
{%forrowinsql(""select 1 + 1 as two, 2 * 4 as eight"") %}{%forkeyinrow.keys() %}
{{ key }}: {{ row[key] }}<br>
{%endfor%}{%endfor%}
The plugin will execute SQL against the current database for the page in database.html, table.html and row.html templates. If a template does not have a current database (index.html for example) the query will execute against the first attached database.
Queries with arguments
You can construct a SQL query using ? or :name parameter syntax by passing a list or dictionary as a second argument:
{%forrowinsql(""select distinct topic from til order by topic"") %}
<h2>{{ row.topic }}</h2>
<ul>
{%fortilinsql(""select * from til where topic = ?"", [row.topic]) %}
<li><ahref=""{{ til.url }}"">{{ til.title }}</a> - {{ til.created[:10] }}</li>
{%endfor%}
</ul>
{%endfor%}
Here's the same example using the :topic style of parameters:
{%forrowinsql(""select distinct topic from til order by topic"") %}
<h2>{{ row.topic }}</h2>
<ul>
{%fortilinsql(""select * from til where topic = :topic"", {""topic"": row.topic}) %}
<li><ahref=""{{ til.url }}"">{{ til.title }}</a> - {{ til.created[:10] }}</li>
{%endfor%}
</ul>
{%endfor%}
Querying a different database
You can pass an optional database= argument to specify a named database to use for the query. For example, if you have attached a news.db database you could use this:
{%forarticleinsql(
""select headline, date, summary from articles order by date desc limit 5"",
database=""news""
) %}
<h3>{{ article.headline }}</h2>
<pclass=""date"">{{ article.date }}</p>
<p>{{ article.summary }}</p>
{%endfor%}
",,,,,,
245670670,MDEwOlJlcG9zaXRvcnkyNDU2NzA2NzA=,fec-to-sqlite,simonw/fec-to-sqlite,0,9599,https://github.com/simonw/fec-to-sqlite,Save FEC campaign finance data to a SQLite database,0,2020-03-07T16:52:49Z,2020-12-19T05:09:05Z,2020-03-07T18:21:48Z,,16,8,8,Python,1,1,1,1,0,0,0,0,1,apache-2.0,"[""sqlite"", ""fec"", ""datasette"", ""datasette-io"", ""datasette-tool""]",0,1,8,master,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,2,"# fec-to-sqlite
[](https://pypi.org/project/fec-to-sqlite/)
[](https://circleci.com/gh/simonw/fec-to-sqlite)
[](https://github.com/simonw/fec-to-sqlite/blob/master/LICENSE)
Create a SQLite database using FEC campaign contributions data.
This tool builds on [fecfile](https://github.com/esonderegger/) by Evan Sonderegger.
## How to install
$ pip install fec-to-sqlite
## Usage
$ fec-to-sqlite filings filings.db 1146148
This fetches the filing with ID `1146148` and stores it in tables in a SQLite database called `filings.db`. It will create any tables it needs.
You can pass more than one filing ID, separated by spaces.
","
fec-to-sqlite
Create a SQLite database using FEC campaign contributions data.
This fetches the filing with ID 1146148 and stores it in tables in a SQLite database called filings.db. It will create any tables it needs.
You can pass more than one filing ID, separated by spaces.
",,,,,,
248999994,MDEwOlJlcG9zaXRvcnkyNDg5OTk5OTQ=,datasette-show-errors,simonw/datasette-show-errors,0,9599,https://github.com/simonw/datasette-show-errors,Datasette plugin for displaying error tracebacks,0,2020-03-21T15:06:04Z,2020-09-24T00:17:29Z,2020-09-01T00:32:23Z,,7,1,1,Python,1,1,1,1,0,0,0,0,1,apache-2.0,"[""asgi"", ""datasette"", ""starlette"", ""datasette-plugin"", ""datasette-io""]",0,1,1,master,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,0,"# datasette-show-errors
[](https://pypi.org/project/datasette-show-errors/)
[](https://circleci.com/gh/simonw/datasette-show-errors)
[](https://github.com/simonw/datasette-show-errors/blob/master/LICENSE)
Datasette plugin for displaying error tracebacks.
**This plugin does not work with current versions of Datasette.** See [issue #2](https://github.com/simonw/datasette-show-errors/issues/2).
## Installation
pip install datasette-show-errors
## Usage
Installing the plugin will cause any internal error to be displayed with a full traceback, rather than just a generic 500 page.
Be careful not to use this in a context that might expose sensitive information.
","
datasette-show-errors
Datasette plugin for displaying error tracebacks.
This plugin does not work with current versions of Datasette. See issue #2.
Installation
pip install datasette-show-errors
Usage
Installing the plugin will cause any internal error to be displayed with a full traceback, rather than just a generic 500 page.
Be careful not to use this in a context that might expose sensitive information.
",,,,,,
273609879,MDEwOlJlcG9zaXRvcnkyNzM2MDk4Nzk=,datasette-saved-queries,simonw/datasette-saved-queries,0,9599,https://github.com/simonw/datasette-saved-queries,Datasette plugin that lets users save and execute queries,0,2020-06-20T00:20:42Z,2020-09-24T05:08:37Z,2020-08-15T23:38:46Z,,12,2,2,Python,1,1,1,1,0,0,0,0,1,,"[""datasette"", ""datasette-plugin"", ""datasette-io""]",0,1,2,main,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,1,"# datasette-saved-queries
[](https://pypi.org/project/datasette-saved-queries/)
[](https://github.com/simonw/datasette-saved-queries/releases)
[](https://github.com/simonw/datasette-saved-queries/blob/master/LICENSE)
Datasette plugin that lets users save and execute queries
## Installation
Install this plugin in the same environment as Datasette.
$ pip install datasette-saved-queries
## Usage
When the plugin is installed Datasette will automatically create a `saved_queries` table in the first connected database when it starts up.
It also creates a `save_query` writable canned query which you can use to save new queries.
Queries that you save will be added to the query list on the database page.
## Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-saved-queries
python -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
","
datasette-saved-queries
Datasette plugin that lets users save and execute queries
Installation
Install this plugin in the same environment as Datasette.
$ pip install datasette-saved-queries
Usage
When the plugin is installed Datasette will automatically create a saved_queries table in the first connected database when it starts up.
It also creates a save_query writable canned query which you can use to save new queries.
Queries that you save will be added to the query list on the database page.
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-saved-queries
python -mvenv venv
source venv/bin/activate
Or if you are using pipenv:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
",,,,,,
291359358,MDEwOlJlcG9zaXRvcnkyOTEzNTkzNTg=,datasette-yaml,simonw/datasette-yaml,0,9599,https://github.com/simonw/datasette-yaml,Export Datasette records as YAML,0,2020-08-29T22:32:15Z,2020-12-28T03:20:36Z,2021-05-13T08:59:53Z,,7,2,2,Python,1,1,1,1,0,1,0,0,1,,"[""yaml"", ""datasette"", ""datasette-plugin"", ""datasette-io""]",1,1,2,main,"{""admin"": false, ""push"": false, ""pull"": false}",,,1,1,"# datasette-yaml
[](https://pypi.org/project/datasette-yaml/)
[](https://github.com/simonw/datasette-yaml/releases)
[](https://github.com/simonw/datasette-yaml/actions?query=workflow%3ATest)
[](https://github.com/simonw/datasette-yaml/blob/main/LICENSE)
Export Datasette records as YAML
## Installation
Install this plugin in the same environment as Datasette.
$ datasette install datasette-yaml
## Usage
Having installed this plugin, every table and query will gain a new `.yaml` export link.
You can also construct these URLs directly: `/dbname/tablename.yaml`
## Demo
The plugin is running on [covid-19.datasettes.com](https://covid-19.datasettes.co/) - for example [/covid/latest_ny_times_counties_with_populations.yaml](https://covid-19.datasettes.com/covid/latest_ny_times_counties_with_populations.yaml)
## Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-yaml
python3 -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
","
datasette-yaml
Export Datasette records as YAML
Installation
Install this plugin in the same environment as Datasette.
$ datasette install datasette-yaml
Usage
Having installed this plugin, every table and query will gain a new .yaml export link.
You can also construct these URLs directly: /dbname/tablename.yaml
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-yaml
python3 -mvenv venv
source venv/bin/activate
Or if you are using pipenv:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
",,,,,,
327087207,MDEwOlJlcG9zaXRvcnkzMjcwODcyMDc=,datasette-css-properties,simonw/datasette-css-properties,0,9599,https://github.com/simonw/datasette-css-properties,Experimental Datasette output plugin using CSS properties,0,2021-01-05T18:38:07Z,2021-01-12T17:43:11Z,2021-01-07T22:07:19Z,,10,12,12,Python,1,1,1,1,0,0,0,0,1,,"[""datasette-plugin"", ""datasette-io""]",0,1,12,main,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,2,"# datasette-css-properties
[](https://pypi.org/project/datasette-css-properties/)
[](https://github.com/simonw/datasette-css-properties/releases)
[](https://github.com/simonw/datasette-css-properties/actions?query=workflow%3ATest)
[](https://github.com/simonw/datasette-css-properties/blob/main/LICENSE)
Extremely experimental Datasette output plugin using CSS properties, inspired by [Custom Properties as State](https://css-tricks.com/custom-properties-as-state/) by Chris Coyier.
More about this project: [APIs from CSS without JavaScript: the datasette-css-properties plugin](https://simonwillison.net/2021/Jan/7/css-apis-no-javascript/)
## Installation
Install this plugin in the same environment as Datasette.
$ datasette install datasette-css-properties
## Usage
Once installed, this plugin adds a `.css` output format to every query result. This will return the first row in the query as a valid CSS file, defining each column as a custom property:
Example: https://latest-with-plugins.datasette.io/fixtures/roadside_attractions.css produces:
```css
:root {
--pk: '1';
--name: 'The Mystery Spot';
--address: '465 Mystery Spot Road, Santa Cruz, CA 95065';
--latitude: '37.0167';
--longitude: '-122.0024';
}
```
If you link this stylesheet to your page you can then do things like this;
```html
Attraction name:
```
Values will be quoted as CSS strings by default. If you want to return a ""raw"" value without the quotes - for example to set a CSS property that is numeric or a color, you can specify that column name using the `?_raw=column-name` parameter. This can be passed multiple times.
Consider [this example query](https://latest-with-plugins.datasette.io/github?sql=select%0D%0A++%27%23%27+||+substr(sha%2C+0%2C+6)+as+[custom-bg]%0D%0Afrom%0D%0A++commits%0D%0Aorder+by%0D%0A++author_date+desc%0D%0Alimit%0D%0A++1%3B):
```sql
select
'#' || substr(sha, 0, 6) as [custom-bg]
from
commits
order by
author_date desc
limit
1;
```
This returns the first 6 characters of the most recently authored commit with a `#` prefix. The `.css` [output rendered version](https://latest-with-plugins.datasette.io/github.css?sql=select%0D%0A++%27%23%27+||+substr(sha%2C+0%2C+6)+as+[custom-bg]%0D%0Afrom%0D%0A++commits%0D%0Aorder+by%0D%0A++author_date+desc%0D%0Alimit%0D%0A++1%3B) looks like this:
```css
:root {
--custom-bg: '#97fb1';
}
```
Adding `?_raw=custom-bg` to the URL produces [this instead](https://latest-with-plugins.datasette.io/github.css?sql=select%0D%0A++%27%23%27+||+substr(sha%2C+0%2C+6)+as+[custom-bg]%0D%0Afrom%0D%0A++commits%0D%0Aorder+by%0D%0A++author_date+desc%0D%0Alimit%0D%0A++1%3B&_raw=custom-bg):
```css
:root {
--custom-bg: #97fb1;
}
```
This can then be used as a color value like so:
```css
h1 {
background-color: var(--custom-bg);
}
```
## Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-css-properties
python3 -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
","
datasette-css-properties
Extremely experimental Datasette output plugin using CSS properties, inspired by Custom Properties as State by Chris Coyier.
Install this plugin in the same environment as Datasette.
$ datasette install datasette-css-properties
Usage
Once installed, this plugin adds a .css output format to every query result. This will return the first row in the query as a valid CSS file, defining each column as a custom property:
Values will be quoted as CSS strings by default. If you want to return a ""raw"" value without the quotes - for example to set a CSS property that is numeric or a color, you can specify that column name using the ?_raw=column-name parameter. This can be passed multiple times.
select'#'|| substr(sha, 0, 6) as [custom-bg]
from
commits
order by
author_date desclimit1;
This returns the first 6 characters of the most recently authored commit with a # prefix. The .cssoutput rendered version looks like this:
:root {
--custom-bg:'#97fb1';
}
Adding ?_raw=custom-bg to the URL produces this instead:
:root {
--custom-bg:#97fb1;
}
This can then be used as a color value like so:
h1 {
background-color:var(--custom-bg);
}
Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-css-properties
python3 -mvenv venv
source venv/bin/activate
Or if you are using pipenv:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
",,,,,,
375546675,MDEwOlJlcG9zaXRvcnkzNzU1NDY2NzU=,datasette-placekey,simonw/datasette-placekey,0,9599,https://github.com/simonw/datasette-placekey,SQL functions for working with placekeys,0,2021-06-10T02:31:27Z,2021-06-10T02:33:22Z,2021-06-10T02:32:42Z,https://datasette.io/plugins/datasette-placekey,3,0,0,Python,1,1,1,1,0,0,0,0,1,,"[""datasette"", ""datasette-plugin"", ""datasette-io"", ""placekey""]",0,1,0,main,"{""admin"": false, ""push"": false, ""pull"": false}",,,0,1,"# datasette-placekey
[](https://pypi.org/project/datasette-placekey/)
[](https://github.com/simonw/datasette-placekey/releases)
[](https://github.com/simonw/datasette-placekey/actions?query=workflow%3ATest)
[](https://github.com/simonw/datasette-placekey/blob/main/LICENSE)
SQL functions for working with [placekeys](https://www.placekey.io/).
## Installation
Install this plugin in the same environment as Datasette.
$ datasette install datasette-placekey
## Usage
The following SQL functions are exposed - [documentation here](https://placekey.github.io/placekey-py/placekey.html#module-placekey.placekey).
```sql
select
geo_to_placekey(33.0896104,129.7900839),
placekey_to_geo('@6nh-nhh-kvf'),
placekey_to_geo_latitude('@6nh-nhh-kvf'),
placekey_to_geo_longitude('@6nh-nhh-kvf'),
placekey_to_h3('@6nh-nhh-kvf'),
h3_to_placekey('8a30d94e4c87fff'),
placekey_to_geojson('@6nh-nhh-kvf'),
placekey_to_wkt('@6nh-nhh-kvf'),
placekey_format_is_valid('@6nh-nhh-kvf');
```
## Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-placekey
python3 -mvenv venv
source venv/bin/activate
Or if you are using `pipenv`:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
","