id,page,ref,title,content,breadcrumbs,references
changelog:id82,changelog,id82,0.29.2 (2019-07-13),"Bumped Uvicorn to 0.8.4, fixing a bug where the query string was not included in the server logs. ( #559 )
Fixed bug where the navigation breadcrumbs were not displayed correctly on the page for a custom query. ( #558 )
Fixed bug where custom query names containing unicode characters caused errors.","[""Changelog""]","[{""href"": ""https://www.uvicorn.org/"", ""label"": ""Uvicorn""}, {""href"": ""https://github.com/simonw/datasette/issues/559"", ""label"": ""#559""}, {""href"": ""https://github.com/simonw/datasette/issues/558"", ""label"": ""#558""}]"
configuration:configuration-reference-css-js,configuration,configuration-reference-css-js,Custom CSS and JavaScript,"Datasette can load additional CSS and JavaScript files, configured in datasette.yaml like this:
[[[cog
from metadata_doc import config_example
config_example(cog, """"""
extra_css_urls:
- https://simonwillison.net/static/css/all.bf8cd891642c.css
extra_js_urls:
- https://code.jquery.com/jquery-3.2.1.slim.min.js
"""""")
]]]
[[[end]]]
The extra CSS and JavaScript files will be linked in the of every page:
You can also specify a SRI (subresource integrity hash) for these assets:
[[[cog
config_example(cog, """"""
extra_css_urls:
- url: https://simonwillison.net/static/css/all.bf8cd891642c.css
sri: sha384-9qIZekWUyjCyDIf2YK1FRoKiPJq4PHt6tp/ulnuuyRBvazd0hG7pWbE99zvwSznI
extra_js_urls:
- url: https://code.jquery.com/jquery-3.2.1.slim.min.js
sri: sha256-k2WSCIexGzOj3Euiig+TlR8gA0EmPjuc79OEeY5L45g=
"""""")
]]]
[[[end]]]
This will produce:
Modern browsers will only execute the stylesheet or JavaScript if the SRI hash
matches the content served. You can generate hashes using www.srihash.org
Items in ""extra_js_urls"" can specify ""module"": true if they reference JavaScript that uses JavaScript modules . This configuration:
[[[cog
config_example(cog, """"""
extra_js_urls:
- url: https://example.datasette.io/module.js
module: true
"""""")
]]]
[[[end]]]
Will produce this HTML:
","[""Configuration"", null]","[{""href"": ""https://www.srihash.org/"", ""label"": ""www.srihash.org""}, {""href"": ""https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules"", ""label"": ""JavaScript modules""}]"
plugin_hooks:plugin-hook-extra-css-urls,plugin_hooks,plugin-hook-extra-css-urls,"extra_css_urls(template, database, table, columns, view_name, request, datasette)","This takes the same arguments as extra_template_vars(...)
Return a list of extra CSS URLs that should be included on the page. These can
take advantage of the CSS class hooks described in Custom pages and templates .
This can be a list of URLs:
from datasette import hookimpl
@hookimpl
def extra_css_urls():
return [
""https://stackpath.bootstrapcdn.com/bootstrap/4.1.0/css/bootstrap.min.css""
]
Or a list of dictionaries defining both a URL and an
SRI hash :
@hookimpl
def extra_css_urls():
return [
{
""url"": ""https://stackpath.bootstrapcdn.com/bootstrap/4.1.0/css/bootstrap.min.css"",
""sri"": ""sha384-9gVQ4dYFwwWSjIDZnLEWnxCjeSWFphJiwGPXr1jddIhOegiu1FwO5qRGvFXOdJZ4"",
}
]
This function can also return an awaitable function, useful if it needs to run any async code:
@hookimpl
def extra_css_urls(datasette):
async def inner():
db = datasette.get_database()
results = await db.execute(
""select url from css_files""
)
return [r[0] for r in results]
return inner
Examples: datasette-cluster-map , datasette-vega","[""Plugin hooks"", ""Page extras""]","[{""href"": ""https://www.srihash.org/"", ""label"": ""SRI hash""}, {""href"": ""https://datasette.io/plugins/datasette-cluster-map"", ""label"": ""datasette-cluster-map""}, {""href"": ""https://datasette.io/plugins/datasette-vega"", ""label"": ""datasette-vega""}]"
changelog:new-configuration-settings,changelog,new-configuration-settings,New configuration settings,"Datasette's Settings now also supports boolean settings. A number of new
configuration options have been added:
num_sql_threads - the number of threads used to execute SQLite queries. Defaults to 3.
allow_facet - enable or disable custom Facets using the _facet= parameter. Defaults to on.
suggest_facets - should Datasette suggest facets? Defaults to on.
allow_download - should users be allowed to download the entire SQLite database? Defaults to on.
allow_sql - should users be allowed to execute custom SQL queries? Defaults to on.
default_cache_ttl - Default HTTP caching max-age header in seconds. Defaults to 365 days - caching can be disabled entirely by settings this to 0.
cache_size_kb - Set the amount of memory SQLite uses for its per-connection cache , in KB.
allow_csv_stream - allow users to stream entire result sets as a single CSV file. Defaults to on.
max_csv_mb - maximum size of a returned CSV file in MB. Defaults to 100MB, set to 0 to disable this limit.","[""Changelog"", ""0.23 (2018-06-18)""]","[{""href"": ""https://www.sqlite.org/pragma.html#pragma_cache_size"", ""label"": ""per-connection cache""}]"
settings:setting-cache-size-kb,settings,setting-cache-size-kb,cache_size_kb,"Sets the amount of memory SQLite uses for its per-connection cache , in KB.
datasette mydatabase.db --setting cache_size_kb 5000","[""Settings"", ""Settings""]","[{""href"": ""https://www.sqlite.org/pragma.html#pragma_cache_size"", ""label"": ""per-connection cache""}]"
full_text_search:full-text-search-advanced-queries,full_text_search,full-text-search-advanced-queries,Advanced SQLite search queries,"SQLite full-text search includes support for a variety of advanced queries , including AND , OR , NOT and NEAR .
By default Datasette disables these features to ensure they do not cause errors or confusion for users who are not aware of them. You can disable this escaping and use the advanced queries by adding &_searchmode=raw to the table page query string.
If you want to enable these operators by default for a specific table, you can do so by adding ""searchmode"": ""raw"" to the metadata configuration for that table, see Configuring full-text search for a table or view .
If that option has been specified in the table metadata but you want to over-ride it and return to the default behavior you can append &_searchmode=escaped to the query string.","[""Full-text search""]","[{""href"": ""https://www.sqlite.org/fts5.html#full_text_query_syntax"", ""label"": ""a variety of advanced queries""}]"
full_text_search:full-text-search-enabling,full_text_search,full-text-search-enabling,Enabling full-text search for a SQLite table,"Datasette takes advantage of the external content mechanism in SQLite, which allows a full-text search virtual table to be associated with the contents of another SQLite table.
To set up full-text search for a table, you need to do two things:
Create a new FTS virtual table associated with your table
Populate that FTS table with the data that you would like to be able to run searches against","[""Full-text search""]","[{""href"": ""https://www.sqlite.org/fts3.html#_external_content_fts4_tables_"", ""label"": ""external content""}]"
json_api:json-api-table-arguments,json_api,json-api-table-arguments,Special table arguments,"?_col=COLUMN1&_col=COLUMN2
List specific columns to display. These will be shown along with any primary keys.
?_nocol=COLUMN1&_nocol=COLUMN2
List specific columns to hide - any column not listed will be displayed. Primary keys cannot be hidden.
?_labels=on/off
Expand foreign key references for every possible column. See below.
?_label=COLUMN1&_label=COLUMN2
Expand foreign key references for one or more specified columns.
?_size=1000 or ?_size=max
Sets a custom page size. This cannot exceed the max_returned_rows limit
passed to datasette serve . Use max to get max_returned_rows .
?_sort=COLUMN
Sorts the results by the specified column.
?_sort_desc=COLUMN
Sorts the results by the specified column in descending order.
?_search=keywords
For SQLite tables that have been configured for
full-text search executes a search
with the provided keywords.
?_search_COLUMN=keywords
Like _search= but allows you to specify the column to be searched, as
opposed to searching all columns that have been indexed by FTS.
?_searchmode=raw
With this option, queries passed to ?_search= or ?_search_COLUMN= will
not have special characters escaped. This means you can make use of the full
set of advanced SQLite FTS syntax ,
though this could potentially result in errors if the wrong syntax is used.
?_where=SQL-fragment
If the execute-sql permission is enabled, this parameter
can be used to pass one or more additional SQL fragments to be used in the
WHERE clause of the SQL used to query the table.
This is particularly useful if you are building a JavaScript application
that needs to do something creative but still wants the other conveniences
provided by the table view (such as faceting) and hence would like not to
have to construct a completely custom SQL query.
Some examples:
facetable?_where=_neighborhood like ""%c%""&_where=_city_id=3
facetable?_where=_city_id in (select id from facet_cities where name != ""Detroit"")
?_through={json}
This can be used to filter rows via a join against another table.
The JSON parameter must include three keys: table , column and value .
table must be a table that the current table is related to via a foreign key relationship.
column must be a column in that other table.
value is the value that you want to match against.
For example, to filter roadside_attractions to just show the attractions that have a characteristic of ""museum"", you would construct this JSON:
{
""table"": ""roadside_attraction_characteristics"",
""column"": ""characteristic_id"",
""value"": ""1""
}
As a URL, that looks like this:
?_through={%22table%22:%22roadside_attraction_characteristics%22,%22column%22:%22characteristic_id%22,%22value%22:%221%22}
Here's an example .
?_next=TOKEN
Pagination by continuation token - pass the token that was returned in the
""next"" property by the previous page.
?_facet=column
Facet by column. Can be applied multiple times, see Facets . Only works on the default JSON output, not on any of the custom shapes.
?_facet_size=100
Increase the number of facet results returned for each facet. Use ?_facet_size=max for the maximum available size, determined by max_returned_rows .
?_nofacet=1
Disable all facets and facet suggestions for this page, including any defined by Facets in metadata .
?_nosuggest=1
Disable facet suggestions for this page.
?_nocount=1
Disable the select count(*) query used on this page - a count of None will be returned instead.","[""JSON API"", ""Table arguments""]","[{""href"": ""https://www.sqlite.org/fts3.html"", ""label"": ""full-text search""}, {""href"": ""https://www.sqlite.org/fts5.html#full_text_query_syntax"", ""label"": ""advanced SQLite FTS syntax""}, {""href"": ""https://latest.datasette.io/fixtures/facetable?_where=_neighborhood%20like%20%22%c%%22&_where=_city_id=3"", ""label"": ""facetable?_where=_neighborhood like \""%c%\""&_where=_city_id=3""}, {""href"": ""https://latest.datasette.io/fixtures/facetable?_where=_city_id%20in%20(select%20id%20from%20facet_cities%20where%20name%20!=%20%22Detroit%22)"", ""label"": ""facetable?_where=_city_id in (select id from facet_cities where name != \""Detroit\"")""}, {""href"": ""https://latest.datasette.io/fixtures/roadside_attractions?_through={%22table%22:%22roadside_attraction_characteristics%22,%22column%22:%22characteristic_id%22,%22value%22:%221%22}"", ""label"": ""an example""}]"
full_text_search:id1,full_text_search,id1,Full-text search,"SQLite includes a powerful mechanism for enabling full-text search against SQLite records. Datasette can detect if a table has had full-text search configured for it in the underlying database and display a search interface for filtering that table.
Here's an example search :
Datasette automatically detects which tables have been configured for full-text search.",[],"[{""href"": ""https://www.sqlite.org/fts3.html"", ""label"": ""a powerful mechanism for enabling full-text search""}, {""href"": ""https://register-of-members-interests.datasettes.com/regmem/items?_search=hamper&_sort_desc=date"", ""label"": ""an example search""}]"
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""}]"
testing_plugins:testing-datasette-client,testing_plugins,testing-datasette-client,Using datasette.client in tests,"The datasette.client mechanism is designed for use in tests. It provides access to a pre-configured HTTPX async client instance that can make GET, POST and other HTTP requests against a Datasette instance from inside a test.
A simple test looks like this:
@pytest.mark.asyncio
async def test_homepage():
ds = Datasette(memory=True)
response = await ds.client.get(""/"")
html = response.text
assert ""
"" in html
Or for a JSON API:
@pytest.mark.asyncio
async def test_actor_is_null():
ds = Datasette(memory=True)
response = await ds.client.get(""/-/actor.json"")
assert response.json() == {""actor"": None}
To make requests as an authenticated actor, create a signed ds_cookie using the datasette.client.actor_cookie() helper function and pass it in cookies= like this:
@pytest.mark.asyncio
async def test_signed_cookie_actor():
ds = Datasette(memory=True)
cookies = {""ds_actor"": ds.client.actor_cookie({""id"": ""root""})}
response = await ds.client.get(""/-/actor.json"", cookies=cookies)
assert response.json() == {""actor"": {""id"": ""root""}}","[""Testing plugins""]","[{""href"": ""https://www.python-httpx.org/async/"", ""label"": ""HTTPX async client""}]"
internals:internals-datasette-client,internals,internals-datasette-client,datasette.client,"Plugins can make internal simulated HTTP requests to the Datasette instance within which they are running. This ensures that all of Datasette's external JSON APIs are also available to plugins, while avoiding the overhead of making an external HTTP call to access those APIs.
The datasette.client object is a wrapper around the HTTPX Python library , providing an async-friendly API that is similar to the widely used Requests library .
It offers the following methods:
await datasette.client.get(path, **kwargs) - returns HTTPX Response
Execute an internal GET request against that path.
await datasette.client.post(path, **kwargs) - returns HTTPX Response
Execute an internal POST request. Use data={""name"": ""value""} to pass form parameters.
await datasette.client.options(path, **kwargs) - returns HTTPX Response
Execute an internal OPTIONS request.
await datasette.client.head(path, **kwargs) - returns HTTPX Response
Execute an internal HEAD request.
await datasette.client.put(path, **kwargs) - returns HTTPX Response
Execute an internal PUT request.
await datasette.client.patch(path, **kwargs) - returns HTTPX Response
Execute an internal PATCH request.
await datasette.client.delete(path, **kwargs) - returns HTTPX Response
Execute an internal DELETE request.
await datasette.client.request(method, path, **kwargs) - returns HTTPX Response
Execute an internal request with the given HTTP method against that path.
These methods can be used with datasette.urls - for example:
table_json = (
await datasette.client.get(
datasette.urls.table(
""fixtures"", ""facetable"", format=""json""
)
)
).json()
datasette.client methods automatically take the current base_url setting into account, whether or not you use the datasette.urls family of methods to construct the path.
For documentation on available **kwargs options and the shape of the HTTPX Response object refer to the HTTPX Async documentation .","[""Internals for plugins"", ""Datasette class""]","[{""href"": ""https://www.python-httpx.org/"", ""label"": ""HTTPX Python library""}, {""href"": ""https://requests.readthedocs.io/"", ""label"": ""Requests library""}, {""href"": ""https://www.python-httpx.org/async/"", ""label"": ""HTTPX Async documentation""}]"
deploying:deploying-buildpacks,deploying,deploying-buildpacks,Deploying using buildpacks,"Some hosting providers such as Heroku , DigitalOcean App Platform and Scalingo support the Buildpacks standard for deploying Python web applications.
Deploying Datasette on these platforms requires two files: requirements.txt and Procfile .
The requirements.txt file lets the platform know which Python packages should be installed. It should contain datasette at a minimum, but can also list any Datasette plugins you wish to install - for example:
datasette
datasette-vega
The Procfile lets the hosting platform know how to run the command that serves web traffic. It should look like this:
web: datasette . -h 0.0.0.0 -p $PORT --cors
The $PORT environment variable is provided by the hosting platform. --cors enables CORS requests from JavaScript running on other websites to your domain - omit this if you don't want to allow CORS. You can add additional Datasette Settings options here too.
These two files should be enough to deploy Datasette on any host that supports buildpacks. Datasette will serve any SQLite files that are included in the root directory of the application.
If you want to build SQLite files or download them as part of the deployment process you can do so using a bin/post_compile file. For example, the following bin/post_compile will download an example database that will then be served by Datasette:
wget https://fivethirtyeight.datasettes.com/fivethirtyeight.db
simonw/buildpack-datasette-demo is an example GitHub repository showing a Datasette configuration that can be deployed to a buildpack-supporting host.","[""Deploying Datasette""]","[{""href"": ""https://www.heroku.com/"", ""label"": ""Heroku""}, {""href"": ""https://www.digitalocean.com/docs/app-platform/"", ""label"": ""DigitalOcean App Platform""}, {""href"": ""https://scalingo.com/"", ""label"": ""Scalingo""}, {""href"": ""https://buildpacks.io/"", ""label"": ""Buildpacks standard""}, {""href"": ""https://github.com/simonw/buildpack-datasette-demo"", ""label"": ""simonw/buildpack-datasette-demo""}]"
publish:publish-heroku,publish,publish-heroku,Publishing to Heroku,"To publish your data using Heroku , first create an account there and install and configure the Heroku CLI tool .
You can publish one or more databases to Heroku using the following command:
datasette publish heroku mydatabase.db
This will output some details about the new deployment, including a URL like this one:
https://limitless-reef-88278.herokuapp.com/ deployed to Heroku
You can specify a custom app name by passing -n my-app-name to the publish command. This will also allow you to overwrite an existing app.
Rather than deploying directly you can use the --generate-dir option to output the files that would be deployed to a directory:
datasette publish heroku mydatabase.db --generate-dir=/tmp/deploy-this-to-heroku
See datasette publish heroku for the full list of options for this command.","[""Publishing data"", ""datasette publish""]","[{""href"": ""https://www.heroku.com/"", ""label"": ""Heroku""}, {""href"": ""https://devcenter.heroku.com/articles/heroku-cli"", ""label"": ""Heroku CLI tool""}]"
spatialite:spatialite-warning,spatialite,spatialite-warning,Warning,"The SpatiaLite extension adds a large number of additional SQL functions , some of which are not be safe for untrusted users to execute: they may cause the Datasette server to crash.
You should not expose a SpatiaLite-enabled Datasette instance to the public internet without taking extra measures to secure it against potentially harmful SQL queries.
The following steps are recommended:
Disable arbitrary SQL queries by untrusted users. See Controlling the ability to execute arbitrary SQL for ways to do this. The easiest is to start Datasette with the datasette --setting default_allow_sql off option.
Define Canned queries with the SQL queries that use SpatiaLite functions that you want people to be able to execute.
The Datasette SpatiaLite tutorial includes detailed instructions for running SpatiaLite safely using these techniques","[""SpatiaLite""]","[{""href"": ""https://www.gaia-gis.it/gaia-sins/spatialite-sql-5.0.1.html"", ""label"": ""a large number of additional SQL functions""}, {""href"": ""https://datasette.io/tutorials/spatialite"", ""label"": ""Datasette SpatiaLite tutorial""}]"
changelog:improved-support-for-spatialite,changelog,improved-support-for-spatialite,Improved support for SpatiaLite,"The SpatiaLite module
for SQLite adds robust geospatial features to the database.
Getting SpatiaLite working can be tricky, especially if you want to use the most
recent alpha version (with support for K-nearest neighbor).
Datasette now includes extensive documentation on SpatiaLite , and thanks to Ravi Kotecha our GitHub
repo includes a Dockerfile that can build
the latest SpatiaLite and configure it for use with Datasette.
The datasette publish and datasette package commands now accept a new
--spatialite argument which causes them to install and configure SpatiaLite
as part of the container they deploy.","[""Changelog"", ""0.23 (2018-06-18)""]","[{""href"": ""https://www.gaia-gis.it/fossil/libspatialite/index"", ""label"": ""SpatiaLite module""}, {""href"": ""https://github.com/r4vi"", ""label"": ""Ravi Kotecha""}, {""href"": ""https://github.com/simonw/datasette/blob/master/Dockerfile"", ""label"": ""Dockerfile""}]"
spatialite:id1,spatialite,id1,SpatiaLite,"The SpatiaLite module for SQLite adds features for handling geographic and spatial data. For an example of what you can do with it, see the tutorial Building a location to time zone API with SpatiaLite .
To use it with Datasette, you need to install the mod_spatialite dynamic library. This can then be loaded into Datasette using the --load-extension command-line option.
Datasette can look for SpatiaLite in common installation locations if you run it like this:
datasette --load-extension=spatialite --setting default_allow_sql off
If SpatiaLite is in another location, use the full path to the extension instead:
datasette --setting default_allow_sql off \
--load-extension=/usr/local/lib/mod_spatialite.dylib",[],"[{""href"": ""https://www.gaia-gis.it/fossil/libspatialite/index"", ""label"": ""SpatiaLite module""}, {""href"": ""https://datasette.io/tutorials/spatialite"", ""label"": ""Building a location to time zone API with SpatiaLite""}]"
publish:cli-package,publish,cli-package,datasette package,"If you have docker installed (e.g. using Docker for Mac ) you can use the datasette package command to create a new Docker image in your local repository containing the datasette app bundled together with one or more SQLite databases:
datasette package mydatabase.db
Here's example output for the package command:
datasette package parlgov.db --extra-options=""--setting sql_time_limit_ms 2500""
Sending build context to Docker daemon 4.459MB
Step 1/7 : FROM python:3.11.0-slim-bullseye
---> 79e1dc9af1c1
Step 2/7 : COPY . /app
---> Using cache
---> cd4ec67de656
Step 3/7 : WORKDIR /app
---> Using cache
---> 139699e91621
Step 4/7 : RUN pip install datasette
---> Using cache
---> 340efa82bfd7
Step 5/7 : RUN datasette inspect parlgov.db --inspect-file inspect-data.json
---> Using cache
---> 5fddbe990314
Step 6/7 : EXPOSE 8001
---> Using cache
---> 8e83844b0fed
Step 7/7 : CMD datasette serve parlgov.db --port 8001 --inspect-file inspect-data.json --setting sql_time_limit_ms 2500
---> Using cache
---> 1bd380ea8af3
Successfully built 1bd380ea8af3
You can now run the resulting container like so:
docker run -p 8081:8001 1bd380ea8af3
This exposes port 8001 inside the container as port 8081 on your host machine, so you can access the application at http://localhost:8081/
You can customize the port that is exposed by the container using the --port option:
datasette package mydatabase.db --port 8080
A full list of options can be seen by running datasette package --help :
See datasette package for the full list of options for this command.","[""Publishing data""]","[{""href"": ""https://www.docker.com/docker-mac"", ""label"": ""Docker for Mac""}]"
deploying:deploying-openrc,deploying,deploying-openrc,Running Datasette using OpenRC,"OpenRC is the service manager on non-systemd Linux distributions like Alpine Linux and Gentoo .
Create an init script at /etc/init.d/datasette with the following contents:
#!/sbin/openrc-run
name=""datasette""
command=""datasette""
command_args=""serve -h 0.0.0.0 /path/to/db.db""
command_background=true
pidfile=""/run/${RC_SVCNAME}.pid""
You then need to configure the service to run at boot and start it:
rc-update add datasette
rc-service datasette start","[""Deploying Datasette""]","[{""href"": ""https://www.alpinelinux.org/"", ""label"": ""Alpine Linux""}, {""href"": ""https://www.gentoo.org/"", ""label"": ""Gentoo""}]"
publish:publish-vercel,publish,publish-vercel,Publishing to Vercel,"Vercel - previously known as Zeit Now - provides a layer over AWS Lambda to allow for quick, scale-to-zero deployment. You can deploy Datasette instances to Vercel using the datasette-publish-vercel plugin.
pip install datasette-publish-vercel
datasette publish vercel mydatabase.db --project my-database-project
Not every feature is supported: consult the datasette-publish-vercel README for more details.","[""Publishing data"", ""datasette publish""]","[{""href"": ""https://vercel.com/"", ""label"": ""Vercel""}, {""href"": ""https://github.com/simonw/datasette-publish-vercel"", ""label"": ""datasette-publish-vercel""}, {""href"": ""https://github.com/simonw/datasette-publish-vercel/blob/main/README.md"", ""label"": ""datasette-publish-vercel README""}]"
performance:http-caching,performance,http-caching,HTTP caching,"If your database is immutable and guaranteed not to change, you can gain major performance improvements from Datasette by enabling HTTP caching.
This can work at two different levels. First, it can tell browsers to cache the results of queries and serve future requests from the browser cache.
More significantly, it allows you to run Datasette behind a caching proxy such as Varnish or use a cache provided by a hosted service such as Fastly or Cloudflare . This can provide incredible speed-ups since a query only needs to be executed by Datasette the first time it is accessed - all subsequent hits can then be served by the cache.
Using a caching proxy in this way could enable a Datasette-backed visualization to serve thousands of hits a second while running Datasette itself on extremely inexpensive hosting.
Datasette's integration with HTTP caches can be enabled using a combination of configuration options and query string arguments.
The default_cache_ttl setting sets the default HTTP cache TTL for all Datasette pages. This is 5 seconds unless you change it - you can set it to 0 if you wish to disable HTTP caching entirely.
You can also change the cache timeout on a per-request basis using the ?_ttl=10 query string parameter. This can be useful when you are working with the Datasette JSON API - you may decide that a specific query can be cached for a longer time, or maybe you need to set ?_ttl=0 for some requests for example if you are running a SQL order by random() query.","[""Performance and caching""]","[{""href"": ""https://varnish-cache.org/"", ""label"": ""Varnish""}, {""href"": ""https://www.fastly.com/"", ""label"": ""Fastly""}, {""href"": ""https://www.cloudflare.com/"", ""label"": ""Cloudflare""}]"
changelog:new-visual-design,changelog,new-visual-design,New visual design,"Datasette is no longer white and grey with blue and purple links! Natalie Downe has been working on a visual refresh, the first iteration of which is included in this release. ( #1056 )","[""Changelog"", ""0.51 (2020-10-31)""]","[{""href"": ""https://twitter.com/natbat"", ""label"": ""Natalie Downe""}, {""href"": ""https://github.com/simonw/datasette/pull/1056"", ""label"": ""#1056""}]"
spatialite:making-use-of-a-spatial-index,spatialite,making-use-of-a-spatial-index,Making use of a spatial index,"SpatiaLite spatial indexes are R*Trees. They allow you to run efficient bounding box queries using a sub-select, with a similar pattern to that used for Searches using custom SQL .
In the above example, the resulting index will be called idx_museums_point_geom . This takes the form of a SQLite virtual table. You can inspect its contents using the following query:
select * from idx_museums_point_geom limit 10;
Here's a live example: timezones-api.datasette.io/timezones/idx_timezones_Geometry
pkid
xmin
xmax
ymin
ymax
1
-8.601725578308105
-2.4930307865142822
4.162120819091797
10.74019718170166
2
-3.2607860565185547
1.27329421043396
4.539252281188965
11.174856185913086
3
32.997581481933594
47.98238754272461
3.3974475860595703
14.894054412841797
4
-8.66890811920166
11.997337341308594
18.9681453704834
37.296207427978516
5
36.43336486816406
43.300174713134766
12.354820251464844
18.070993423461914
You can now construct efficient bounding box queries that will make use of the index like this:
select * from museums where museums.rowid in (
SELECT pkid FROM idx_museums_point_geom
-- left-hand-edge of point > left-hand-edge of bbox (minx)
where xmin > :bbox_minx
-- right-hand-edge of point < right-hand-edge of bbox (maxx)
and xmax < :bbox_maxx
-- bottom-edge of point > bottom-edge of bbox (miny)
and ymin > :bbox_miny
-- top-edge of point < top-edge of bbox (maxy)
and ymax < :bbox_maxy
);
Spatial indexes can be created against polygon columns as well as point columns, in which case they will represent the minimum bounding rectangle of that polygon. This is useful for accelerating within queries, as seen in the Timezones API example.","[""SpatiaLite""]","[{""href"": ""https://timezones-api.datasette.io/timezones/idx_timezones_Geometry"", ""label"": ""timezones-api.datasette.io/timezones/idx_timezones_Geometry""}]"
facets:speeding-up-facets-with-indexes,facets,speeding-up-facets-with-indexes,Speeding up facets with indexes,"The performance of facets can be greatly improved by adding indexes on the columns you wish to facet by.
Adding indexes can be performed using the sqlite3 command-line utility. Here's how to add an index on the state column in a table called Food_Trucks :
sqlite3 mydatabase.db
SQLite version 3.19.3 2017-06-27 16:48:08
Enter "".help"" for usage hints.
sqlite> CREATE INDEX Food_Trucks_state ON Food_Trucks(""state"");
Or using the sqlite-utils command-line utility:
sqlite-utils create-index mydatabase.db Food_Trucks state","[""Facets""]","[{""href"": ""https://sqlite-utils.datasette.io/en/stable/cli.html#creating-indexes"", ""label"": ""sqlite-utils""}]"
full_text_search:configuring-fts-by-hand,full_text_search,configuring-fts-by-hand,Configuring FTS by hand,"We recommend using sqlite-utils , but if you want to hand-roll a SQLite full-text search table you can do so using the following SQL.
To enable full-text search for a table called items that works against the name and description columns, you would run this SQL to create a new items_fts FTS virtual table:
CREATE VIRTUAL TABLE ""items_fts"" USING FTS4 (
name,
description,
content=""items""
);
This creates a set of tables to power full-text search against items . The new items_fts table will be detected by Datasette as the fts_table for the items table.
Creating the table is not enough: you also need to populate it with a copy of the data that you wish to make searchable. You can do that using the following SQL:
INSERT INTO ""items_fts"" (rowid, name, description)
SELECT rowid, name, description FROM items;
If your table has columns that are foreign key references to other tables you can include that data in your full-text search index using a join. Imagine the items table has a foreign key column called category_id which refers to a categories table - you could create a full-text search table like this:
CREATE VIRTUAL TABLE ""items_fts"" USING FTS4 (
name,
description,
category_name,
content=""items""
);
And then populate it like this:
INSERT INTO ""items_fts"" (rowid, name, description, category_name)
SELECT items.rowid,
items.name,
items.description,
categories.name
FROM items JOIN categories ON items.category_id=categories.id;
You can use this technique to populate the full-text search index from any combination of tables and joins that makes sense for your project.","[""Full-text search"", ""Enabling full-text search for a SQLite table""]","[{""href"": ""https://sqlite-utils.datasette.io/"", ""label"": ""sqlite-utils""}]"
ecosystem:sqlite-utils,ecosystem,sqlite-utils,sqlite-utils,"sqlite-utils is a key building block for the wider Datasette ecosystem. It provides a collection of utilities for manipulating SQLite databases, both as a Python library and a command-line utility. Features include:
Insert data into a SQLite database from JSON, CSV or TSV, automatically creating tables with the correct schema or altering existing tables to add missing columns.
Configure tables for use with SQLite full-text search, including creating triggers needed to keep the search index up-to-date.
Modify tables in ways that are not supported by SQLite's default ALTER TABLE syntax - for example changing the types of columns or selecting a new primary key for a table.
Adding foreign keys to existing database tables.
Extracting columns of data into a separate lookup table.","[""The Datasette Ecosystem""]","[{""href"": ""https://sqlite-utils.datasette.io/"", ""label"": ""sqlite-utils""}]"
sql_queries:sql-views,sql_queries,sql-views,Views,"If you want to bundle some pre-written SQL queries with your Datasette-hosted database you can do so in two ways. The first is to include SQL views in your database - Datasette will then list those views on your database index page.
The quickest way to create views is with the SQLite command-line interface:
sqlite3 sf-trees.db
SQLite version 3.19.3 2017-06-27 16:48:08
Enter "".help"" for usage hints.
sqlite> CREATE VIEW demo_view AS select qSpecies from Street_Tree_List;
You can also use the sqlite-utils tool to create a view :
sqlite-utils create-view sf-trees.db demo_view ""select qSpecies from Street_Tree_List""","[""Running SQL queries""]","[{""href"": ""https://sqlite-utils.datasette.io/"", ""label"": ""sqlite-utils""}, {""href"": ""https://sqlite-utils.datasette.io/en/stable/cli.html#creating-views"", ""label"": ""create a view""}]"
full_text_search:configuring-fts-using-sqlite-utils,full_text_search,configuring-fts-using-sqlite-utils,Configuring FTS using sqlite-utils,"sqlite-utils is a CLI utility and Python library for manipulating SQLite databases. You can use it from Python code to configure FTS search, or you can achieve the same goal using the accompanying command-line tool .
Here's how to use sqlite-utils to enable full-text search for an items table across the name and description columns:
sqlite-utils enable-fts mydatabase.db items name description","[""Full-text search"", ""Enabling full-text search for a SQLite table""]","[{""href"": ""https://sqlite-utils.datasette.io/"", ""label"": ""sqlite-utils""}, {""href"": ""https://sqlite-utils.datasette.io/en/latest/python-api.html#enabling-full-text-search"", ""label"": ""it from Python code""}, {""href"": ""https://sqlite-utils.datasette.io/en/latest/cli.html#configuring-full-text-search"", ""label"": ""using the accompanying command-line tool""}]"
changelog:v1-0-a8,changelog,v1-0-a8,1.0a8 (2024-02-07),"This alpha release continues the migration of Datasette's configuration from metadata.yaml to the new datasette.yaml configuration file, introduces a new system for JavaScript plugins and adds several new plugin hooks.
See Datasette 1.0a8: JavaScript plugins, new plugin hooks and plugin configuration in datasette.yaml for an annotated version of these release notes.","[""Changelog""]","[{""href"": ""https://simonwillison.net/2024/Feb/7/datasette-1a8/"", ""label"": ""Datasette 1.0a8: JavaScript plugins, new plugin hooks and plugin configuration in datasette.yaml""}]"
changelog:id11,changelog,id11,0.63 (2022-10-27),See Datasette 0.63: The annotated release notes for more background on the changes in this release.,"[""Changelog""]","[{""href"": ""https://simonwillison.net/2022/Oct/27/datasette-0-63/"", ""label"": ""Datasette 0.63: The annotated release notes""}]"
changelog:v1-0-a2,changelog,v1-0-a2,1.0a2 (2022-12-14),"The third Datasette 1.0 alpha release adds upsert support to the JSON API, plus the ability to specify finely grained permissions when creating an API token.
See Datasette 1.0a2: Upserts and finely grained permissions for an extended, annotated version of these release notes.
New /db/table/-/upsert API, documented here . upsert is an update-or-insert: existing rows will have specified keys updated, but if no row matches the incoming primary key a brand new row will be inserted instead. ( #1878 )
New register_permissions(datasette) plugin hook. Plugins can now register named permissions, which will then be listed in various interfaces that show available permissions. ( #1940 )
The /db/-/create API for creating a table now accepts ""ignore"": true and ""replace"": true options when called with the ""rows"" property that creates a new table based on an example set of rows. This means the API can be called multiple times with different rows, setting rules for what should happen if a primary key collides with an existing row. ( #1927 )
Arbitrary permissions can now be configured at the instance, database and resource (table, SQL view or canned query) level in Datasette's Metadata JSON and YAML files. The new ""permissions"" key can be used to specify which actors should have which permissions. See Other permissions in datasette.yaml for details. ( #1636 )
The /-/create-token page can now be used to create API tokens which are restricted to just a subset of actions, including against specific databases or resources. See API Tokens for details. ( #1947 )
Likewise, the datasette create-token CLI command can now create tokens with a subset of permissions . ( #1855 )
New datasette.create_token() API method for programmatically creating signed API tokens. ( #1951 )
/db/-/create API now requires actor to have insert-row permission in order to use the ""row"" or ""rows"" properties. ( #1937 )","[""Changelog""]","[{""href"": ""https://simonwillison.net/2022/Dec/15/datasette-1a2/"", ""label"": ""Datasette 1.0a2: Upserts and finely grained permissions""}, {""href"": ""https://github.com/simonw/datasette/issues/1878"", ""label"": ""#1878""}, {""href"": ""https://github.com/simonw/datasette/issues/1940"", ""label"": ""#1940""}, {""href"": ""https://github.com/simonw/datasette/issues/1927"", ""label"": ""#1927""}, {""href"": ""https://github.com/simonw/datasette/issues/1636"", ""label"": ""#1636""}, {""href"": ""https://github.com/simonw/datasette/issues/1947"", ""label"": ""#1947""}, {""href"": ""https://github.com/simonw/datasette/issues/1855"", ""label"": ""#1855""}, {""href"": ""https://github.com/simonw/datasette/issues/1951"", ""label"": ""#1951""}, {""href"": ""https://github.com/simonw/datasette/issues/1937"", ""label"": ""#1937""}]"
changelog:id35,changelog,id35,0.54 (2021-01-25),"The two big new features in this release are the _internal SQLite in-memory database storing details of all connected databases and tables, and support for JavaScript modules in plugins and additional scripts.
For additional commentary on this release, see Datasette 0.54, the annotated release notes .","[""Changelog""]","[{""href"": ""https://simonwillison.net/2021/Jan/25/datasette/"", ""label"": ""Datasette 0.54, the annotated release notes""}]"
internals:internals-utils-await-me-maybe,internals,internals-utils-await-me-maybe,await_me_maybe(value),"Utility function for calling await on a return value if it is awaitable, otherwise returning the value. This is used by Datasette to support plugin hooks that can optionally return awaitable functions. Read more about this function in The “await me maybe” pattern for Python asyncio .
async datasette.utils. await_me_maybe value : Any Any
If value is callable, call it. If awaitable, await it. Otherwise return it.","[""Internals for plugins"", ""The datasette.utils module""]","[{""href"": ""https://simonwillison.net/2020/Sep/2/await-me-maybe/"", ""label"": ""The “await me maybe” pattern for Python asyncio""}]"
changelog:id51,changelog,id51,0.49 (2020-09-14),"See also Datasette 0.49: The annotated release notes .
Writable canned queries now expose a JSON API, see JSON API for writable canned queries . ( #880 )
New mechanism for defining page templates with custom path parameters - a template file called pages/about/{slug}.html will be used to render any requests to /about/something . See Path parameters for pages . ( #944 )
register_output_renderer() render functions can now return a Response . ( #953 )
New --upgrade option for datasette install . ( #945 )
New datasette --pdb option. ( #962 )
datasette --get exit code now reflects the internal HTTP status code. ( #947 )
New raise_404() template function for returning 404 errors. ( #964 )
datasette publish heroku now deploys using Python 3.8.5
Upgraded CodeMirror to 5.57.0. ( #948 )
Upgraded code style to Black 20.8b1. ( #958 )
Fixed bug where selected facets were not correctly persisted in hidden form fields on the table page. ( #963 )
Renamed the default error template from 500.html to error.html .
Custom error pages are now documented, see Custom error pages . ( #965 )","[""Changelog""]","[{""href"": ""https://simonwillison.net/2020/Sep/15/datasette-0-49/"", ""label"": ""Datasette 0.49: The annotated release notes""}, {""href"": ""https://github.com/simonw/datasette/issues/880"", ""label"": ""#880""}, {""href"": ""https://github.com/simonw/datasette/issues/944"", ""label"": ""#944""}, {""href"": ""https://github.com/simonw/datasette/issues/953"", ""label"": ""#953""}, {""href"": ""https://github.com/simonw/datasette/issues/945"", ""label"": ""#945""}, {""href"": ""https://github.com/simonw/datasette/issues/962"", ""label"": ""#962""}, {""href"": ""https://github.com/simonw/datasette/issues/947"", ""label"": ""#947""}, {""href"": ""https://github.com/simonw/datasette/issues/964"", ""label"": ""#964""}, {""href"": ""https://codemirror.net/"", ""label"": ""CodeMirror""}, {""href"": ""https://github.com/simonw/datasette/issues/948"", ""label"": ""#948""}, {""href"": ""https://github.com/simonw/datasette/issues/958"", ""label"": ""#958""}, {""href"": ""https://github.com/simonw/datasette/issues/963"", ""label"": ""#963""}, {""href"": ""https://github.com/simonw/datasette/issues/965"", ""label"": ""#965""}]"
changelog:id60,changelog,id60,0.44 (2020-06-11),"See also Datasette 0.44: The annotated release notes .
Authentication and permissions, writable canned queries, flash messages, new plugin hooks and more.","[""Changelog""]","[{""href"": ""https://simonwillison.net/2020/Jun/12/annotated-release-notes/"", ""label"": ""Datasette 0.44: The annotated release notes""}]"
changelog:id58,changelog,id58,0.45 (2020-07-01),"See also Datasette 0.45: The annotated release notes .
Magic parameters for canned queries, a log out feature, improved plugin documentation and four new plugin hooks.","[""Changelog""]","[{""href"": ""https://simonwillison.net/2020/Jul/1/datasette-045/"", ""label"": ""Datasette 0.45: The annotated release notes""}]"
changelog:v0-28-databases-that-change,changelog,v0-28-databases-that-change,Supporting databases that change,"From the beginning of the project, Datasette has been designed with read-only databases in mind. If a database is guaranteed not to change it opens up all kinds of interesting opportunities - from taking advantage of SQLite immutable mode and HTTP caching to bundling static copies of the database directly in a Docker container. The interesting ideas in Datasette explores this idea in detail.
As my goals for the project have developed, I realized that read-only databases are no longer the right default. SQLite actually supports concurrent access very well provided only one thread attempts to write to a database at a time, and I keep encountering sensible use-cases for running Datasette on top of a database that is processing inserts and updates.
So, as-of version 0.28 Datasette no longer assumes that a database file will not change. It is now safe to point Datasette at a SQLite database which is being updated by another process.
Making this change was a lot of work - see tracking tickets #418 , #419 and #420 . It required new thinking around how Datasette should calculate table counts (an expensive operation against a large, changing database) and also meant reconsidering the ""content hash"" URLs Datasette has used in the past to optimize the performance of HTTP caches.
Datasette can still run against immutable files and gains numerous performance benefits from doing so, but this is no longer the default behaviour. Take a look at the new Performance and caching documentation section for details on how to make the most of Datasette against data that you know will be staying read-only and immutable.","[""Changelog"", ""0.28 (2019-05-19)""]","[{""href"": ""https://simonwillison.net/2018/Oct/4/datasette-ideas/"", ""label"": ""The interesting ideas in Datasette""}, {""href"": ""https://github.com/simonw/datasette/issues/418"", ""label"": ""#418""}, {""href"": ""https://github.com/simonw/datasette/issues/419"", ""label"": ""#419""}, {""href"": ""https://github.com/simonw/datasette/issues/420"", ""label"": ""#420""}]"
changelog:id118,changelog,id118,0.22 (2018-05-20),"The big new feature in this release is Facets . Datasette can now apply faceted browse to any column in any table. It will also suggest possible facets. See the Datasette Facets announcement post for more details.
In addition to the work on facets:
Added docs for introspection endpoints
New --config option, added --help-config , closes #274
Removed the --page_size= argument to datasette serve in favour of:
datasette serve --config default_page_size:50 mydb.db
Added new help section:
datasette --help-config
Config options:
default_page_size Default page size for the table view
(default=100)
max_returned_rows Maximum rows that can be returned from a table
or custom query (default=1000)
sql_time_limit_ms Time limit for a SQL query in milliseconds
(default=1000)
default_facet_size Number of values to return for requested facets
(default=30)
facet_time_limit_ms Time limit for calculating a requested facet
(default=200)
facet_suggest_time_limit_ms Time limit for calculating a suggested facet
(default=50)
Only apply responsive table styles to .rows-and-column
Otherwise they interfere with tables in the description, e.g. on
https://fivethirtyeight.datasettes.com/fivethirtyeight/nba-elo%2Fnbaallelo
Refactored views into new views/ modules, refs #256
Documentation for SQLite full-text search support, closes #253
/-/versions now includes SQLite fts_versions , closes #252","[""Changelog""]","[{""href"": ""https://simonwillison.net/2018/May/20/datasette-facets/"", ""label"": ""Datasette Facets""}, {""href"": ""https://docs.datasette.io/en/stable/introspection.html"", ""label"": ""docs for introspection endpoints""}, {""href"": ""https://github.com/simonw/datasette/issues/274"", ""label"": ""#274""}, {""href"": ""https://fivethirtyeight.datasettes.com/fivethirtyeight/nba-elo%2Fnbaallelo"", ""label"": ""https://fivethirtyeight.datasettes.com/fivethirtyeight/nba-elo%2Fnbaallelo""}, {""href"": ""https://github.com/simonw/datasette/issues/256"", ""label"": ""#256""}, {""href"": ""https://docs.datasette.io/en/stable/full_text_search.html"", ""label"": ""Documentation for SQLite full-text search""}, {""href"": ""https://github.com/simonw/datasette/issues/253"", ""label"": ""#253""}, {""href"": ""https://github.com/simonw/datasette/issues/252"", ""label"": ""#252""}]"
plugin_hooks:plugin-hook-handle-exception,plugin_hooks,plugin-hook-handle-exception,"handle_exception(datasette, request, exception)","datasette - Datasette class
You can use this to access plugin configuration options via datasette.plugin_config(your_plugin_name) , or to render templates or execute SQL queries.
request - Request object
The current HTTP request.
exception - Exception
The exception that was raised.
This hook is called any time an unexpected exception is raised. You can use it to record the exception.
If your handler returns a Response object it will be returned to the client in place of the default Datasette error page.
The handler can return a response directly, or it can return return an awaitable function that returns a response.
This example logs an error to Sentry and then renders a custom error page:
from datasette import hookimpl, Response
import sentry_sdk
@hookimpl
def handle_exception(datasette, exception):
sentry_sdk.capture_exception(exception)
async def inner():
return Response.html(
await datasette.render_template(
""custom_error.html"", request=request
)
)
return inner
Example: datasette-sentry","[""Plugin hooks""]","[{""href"": ""https://sentry.io/"", ""label"": ""Sentry""}, {""href"": ""https://datasette.io/plugins/datasette-sentry"", ""label"": ""datasette-sentry""}]"
introspection:jsondataview-plugins,introspection,jsondataview-plugins,/-/plugins,"Shows a list of currently installed plugins and their versions. Plugins example :
[
{
""name"": ""datasette_cluster_map"",
""static"": true,
""templates"": false,
""version"": ""0.10"",
""hooks"": [""extra_css_urls"", ""extra_js_urls"", ""extra_body_script""]
}
]
Add ?all=1 to include details of the default plugins baked into Datasette.","[""Introspection""]","[{""href"": ""https://san-francisco.datasettes.com/-/plugins"", ""label"": ""Plugins example""}]"
json_api:json-api-pagination,json_api,json-api-pagination,Pagination,"The default JSON representation includes a ""next_url"" key which can be used to access the next page of results. If that key is null or missing then it means you have reached the final page of results.
Other representations include pagination information in the link HTTP header. That header will look something like this:
link: ; rel=""next""
Here is an example Python function built using requests that returns a list of all of the paginated items from one of these API endpoints:
def paginate(url):
items = []
while url:
response = requests.get(url)
try:
url = response.links.get(""next"").get(""url"")
except AttributeError:
url = None
items.extend(response.json())
return items","[""JSON API""]","[{""href"": ""https://requests.readthedocs.io/"", ""label"": ""requests""}]"
pages:rowview,pages,rowview,Row,"Every row in every Datasette table has its own URL. This means individual records can be linked to directly.
Table cells with extremely long text contents are truncated on the table view according to the truncate_cells_html setting. If a cell has been truncated the full length version of that cell will be available on the row page.
Rows which are the targets of foreign key references from other tables will show a link to a filtered search for all records that reference that row. Here's an example from the Registers of Members Interests database:
../people/uk~2Eorg~2Epublicwhip~2Fperson~2F10001
Note that this URL includes the encoded primary key of the record.
Here's that same page as JSON:
../people/uk~2Eorg~2Epublicwhip~2Fperson~2F10001.json","[""Pages and API endpoints""]","[{""href"": ""https://register-of-members-interests.datasettes.com/regmem/people/uk~2Eorg~2Epublicwhip~2Fperson~2F10001"", ""label"": ""../people/uk~2Eorg~2Epublicwhip~2Fperson~2F10001""}, {""href"": ""https://register-of-members-interests.datasettes.com/regmem/people/uk~2Eorg~2Epublicwhip~2Fperson~2F10001.json"", ""label"": ""../people/uk~2Eorg~2Epublicwhip~2Fperson~2F10001.json""}]"
pages:tableview,pages,tableview,Table,"The table page is the heart of Datasette: it allows users to interactively explore the contents of a database table, including sorting, filtering, Full-text search and applying Facets .
The HTML interface is worth spending some time exploring. As with other pages, you can return the JSON data by appending .json to the URL path, before any ? query string arguments.
The query string arguments are described in more detail here: Table arguments
You can also use the table page to interactively construct a SQL query - by applying different filters and a sort order for example - and then click the ""View and edit SQL"" link to see the SQL query that was used for the page and edit and re-submit it.
Some examples:
../items lists all of the line-items registered by UK MPs as potential conflicts of interest. It demonstrates Datasette's support for Full-text search .
../antiquities-act%2Factions_under_antiquities_act is an interface for exploring the ""actions under the antiquities act"" data table published by FiveThirtyEight.
../global-power-plants?country_long=United+Kingdom&primary_fuel=Gas is a filtered table page showing every Gas power plant in the United Kingdom. It includes some default facets (configured using its metadata.json ) and uses the datasette-cluster-map plugin to show a map of the results.","[""Pages and API endpoints""]","[{""href"": ""https://register-of-members-interests.datasettes.com/regmem/items"", ""label"": ""../items""}, {""href"": ""https://fivethirtyeight.datasettes.com/fivethirtyeight/antiquities-act%2Factions_under_antiquities_act"", ""label"": ""../antiquities-act%2Factions_under_antiquities_act""}, {""href"": ""https://global-power-plants.datasettes.com/global-power-plants/global-power-plants?_facet=primary_fuel&_facet=owner&_facet=country_long&country_long__exact=United+Kingdom&primary_fuel=Gas"", ""label"": ""../global-power-plants?country_long=United+Kingdom&primary_fuel=Gas""}, {""href"": ""https://global-power-plants.datasettes.com/-/metadata"", ""label"": ""its metadata.json""}, {""href"": ""https://github.com/simonw/datasette-cluster-map"", ""label"": ""datasette-cluster-map""}]"
contributing:contributing-documentation,contributing,contributing-documentation,Editing and building the documentation,"Datasette's documentation lives in the docs/ directory and is deployed automatically using Read The Docs .
The documentation is written using reStructuredText. You may find this article on The subset of reStructuredText worth committing to memory useful.
You can build it locally by installing sphinx and sphinx_rtd_theme in your Datasette development environment and then running make html directly in the docs/ directory:
# You may first need to activate your virtual environment:
source venv/bin/activate
# Install the dependencies needed to build the docs
pip install -e .[docs]
# Now build the docs
cd docs/
make html
This will create the HTML version of the documentation in docs/_build/html . You can open it in your browser like so:
open _build/html/index.html
Any time you make changes to a .rst file you can re-run make html to update the built documents, then refresh them in your browser.
For added productivity, you can use use sphinx-autobuild to run Sphinx in auto-build mode. This will run a local webserver serving the docs that automatically rebuilds them and refreshes the page any time you hit save in your editor.
sphinx-autobuild will have been installed when you ran pip install -e .[docs] . In your docs/ directory you can start the server by running the following:
make livehtml
Now browse to http://localhost:8000/ to view the documentation. Any edits you make should be instantly reflected in your browser.","[""Contributing""]","[{""href"": ""https://readthedocs.org/"", ""label"": ""Read The Docs""}, {""href"": ""https://simonwillison.net/2018/Aug/25/restructuredtext/"", ""label"": ""The subset of reStructuredText worth committing to memory""}, {""href"": ""https://pypi.org/project/sphinx-autobuild/"", ""label"": ""sphinx-autobuild""}]"
testing_plugins:testing-plugins-pytest-httpx,testing_plugins,testing-plugins-pytest-httpx,Testing outbound HTTP calls with pytest-httpx,"If your plugin makes outbound HTTP calls - for example datasette-auth-github or datasette-import-table - you may need to mock those HTTP requests in your tests.
The pytest-httpx package is a useful library for mocking calls. It can be tricky to use with Datasette though since it mocks all HTTPX requests, and Datasette's own testing mechanism uses HTTPX internally.
To avoid breaking your tests, you can return [""localhost""] from the non_mocked_hosts() fixture.
As an example, here's a very simple plugin which executes an HTTP response and returns the resulting content:
from datasette import hookimpl
from datasette.utils.asgi import Response
import httpx
@hookimpl
def register_routes():
return [
(r""^/-/fetch-url$"", fetch_url),
]
async def fetch_url(datasette, request):
if request.method == ""GET"":
return Response.html(
""""""
"""""".format(
request.scope[""csrftoken""]()
)
)
vars = await request.post_vars()
url = vars[""url""]
return Response.text(httpx.get(url).text)
Here's a test for that plugin that mocks the HTTPX outbound request:
from datasette.app import Datasette
import pytest
@pytest.fixture
def non_mocked_hosts():
# This ensures httpx-mock will not affect Datasette's own
# httpx calls made in the tests by datasette.client:
return [""localhost""]
async def test_outbound_http_call(httpx_mock):
httpx_mock.add_response(
url=""https://www.example.com/"",
text=""Hello world"",
)
datasette = Datasette([], memory=True)
response = await datasette.client.post(
""/-/fetch-url"",
data={""url"": ""https://www.example.com/""},
)
assert response.text == ""Hello world""
outbound_request = httpx_mock.get_request()
assert (
outbound_request.url == ""https://www.example.com/""
)","[""Testing plugins""]","[{""href"": ""https://pypi.org/project/pytest-httpx/"", ""label"": ""pytest-httpx""}]"
index:datasette,index,datasette,Datasette,"An open source multi-tool for exploring and publishing data
Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size and publish that as an interactive, explorable website and accompanying API.
Datasette is aimed at data journalists, museum curators, archivists, local governments and anyone else who has data that they wish to share with the world. It is part of a wider ecosystem of tools and plugins dedicated to making working with structured data as productive as possible.
Explore a demo , watch a presentation about the project or Try Datasette without installing anything using Glitch .
Interested in learning Datasette? Start with the official tutorials .
Support questions, feedback? Join the Datasette Discord .",[],"[{""href"": ""https://pypi.org/project/datasette/"", ""label"": null}, {""href"": ""https://docs.datasette.io/en/stable/changelog.html"", ""label"": null}, {""href"": ""https://pypi.org/project/datasette/"", ""label"": null}, {""href"": ""https://github.com/simonw/datasette/actions?query=workflow%3ATest"", ""label"": null}, {""href"": ""https://github.com/simonw/datasette/blob/main/LICENSE"", ""label"": null}, {""href"": ""https://hub.docker.com/r/datasetteproject/datasette"", ""label"": null}, {""href"": ""https://datasette.io/discord"", ""label"": null}, {""href"": ""https://pypi.org/project/datasette/"", ""label"": null}, {""href"": ""https://docs.datasette.io/en/stable/changelog.html"", ""label"": null}, {""href"": ""https://pypi.org/project/datasette/"", ""label"": null}, {""href"": ""https://github.com/simonw/datasette/actions?query=workflow%3ATest"", ""label"": null}, {""href"": ""https://github.com/simonw/datasette/blob/main/LICENSE"", ""label"": null}, {""href"": ""https://hub.docker.com/r/datasetteproject/datasette"", ""label"": null}, {""href"": ""https://datasette.io/discord"", ""label"": null}, {""href"": ""https://fivethirtyeight.datasettes.com/fivethirtyeight"", ""label"": ""Explore a demo""}, {""href"": ""https://static.simonwillison.net/static/2018/pybay-datasette/"", ""label"": ""a presentation about the project""}, {""href"": ""https://datasette.io/tutorials"", ""label"": ""the official tutorials""}, {""href"": ""https://datasette.io/discord"", ""label"": ""Datasette Discord""}]"
contributing:contributing-formatting-blacken-docs,contributing,contributing-formatting-blacken-docs,blacken-docs,"The blacken-docs command applies Black formatting rules to code examples in the documentation. Run it like this:
blacken-docs -l 60 docs/*.rst","[""Contributing"", ""Code formatting""]","[{""href"": ""https://pypi.org/project/blacken-docs/"", ""label"": ""blacken-docs""}]"
spatialite:importing-geojson-polygons-using-shapely,spatialite,importing-geojson-polygons-using-shapely,Importing GeoJSON polygons using Shapely,"Another common form of polygon data is the GeoJSON format. This can be imported into SpatiaLite directly, or by using the Shapely Python library.
Who's On First is an excellent source of openly licensed GeoJSON polygons. Let's import the geographical polygon for Wales. First, we can use the Who's On First Spelunker tool to find the record for Wales:
spelunker.whosonfirst.org/id/404227475
That page includes a link to the GeoJSON record, which can be accessed here:
data.whosonfirst.org/404/227/475/404227475.geojson
Here's Python code to create a SQLite database, enable SpatiaLite, create a places table and then add a record for Wales:
import sqlite3
conn = sqlite3.connect(""places.db"")
# Enable SpatialLite extension
conn.enable_load_extension(True)
conn.load_extension(""/usr/local/lib/mod_spatialite.dylib"")
# Create the masic countries table
conn.execute(""select InitSpatialMetadata(1)"")
conn.execute(
""create table places (id integer primary key, name text);""
)
# Add a MULTIPOLYGON Geometry column
conn.execute(
""SELECT AddGeometryColumn('places', 'geom', 4326, 'MULTIPOLYGON', 2);""
)
# Add a spatial index against the new column
conn.execute(""SELECT CreateSpatialIndex('places', 'geom');"")
# Now populate the table
from shapely.geometry.multipolygon import MultiPolygon
from shapely.geometry import shape
import requests
geojson = requests.get(
""https://data.whosonfirst.org/404/227/475/404227475.geojson""
).json()
# Convert to ""Well Known Text"" format
wkt = shape(geojson[""geometry""]).wkt
# Insert and commit the record
conn.execute(
""INSERT INTO places (id, name, geom) VALUES(null, ?, GeomFromText(?, 4326))"",
(""Wales"", wkt),
)
conn.commit()","[""SpatiaLite""]","[{""href"": ""https://pypi.org/project/Shapely/"", ""label"": ""Shapely""}, {""href"": ""https://whosonfirst.org/"", ""label"": ""Who's On First""}, {""href"": ""https://spelunker.whosonfirst.org/id/404227475/"", ""label"": ""spelunker.whosonfirst.org/id/404227475""}, {""href"": ""https://data.whosonfirst.org/404/227/475/404227475.geojson"", ""label"": ""data.whosonfirst.org/404/227/475/404227475.geojson""}]"
writing_plugins:id1,writing_plugins,id1,Writing plugins,"You can write one-off plugins that apply to just one Datasette instance, or you can write plugins which can be installed using pip and can be shipped to the Python Package Index ( PyPI ) for other people to install.
Want to start by looking at an example? The Datasette plugins directory lists more than 90 open source plugins with code you can explore. The plugin hooks page includes links to example plugins for each of the documented hooks.",[],"[{""href"": ""https://pypi.org/"", ""label"": ""PyPI""}, {""href"": ""https://datasette.io/plugins"", ""label"": ""Datasette plugins directory""}]"
settings:setting-num-sql-threads,settings,setting-num-sql-threads,num_sql_threads,"Maximum number of threads in the thread pool Datasette uses to execute SQLite queries. Defaults to 3.
datasette mydatabase.db --setting num_sql_threads 10
Setting this to 0 turns off threaded SQL queries entirely - useful for environments that do not support threading such as Pyodide .","[""Settings"", ""Settings""]","[{""href"": ""https://pyodide.org/"", ""label"": ""Pyodide""}]"
changelog:id14,changelog,id14,Features,"Datasette is now compatible with Pyodide . This is the enabling technology behind Datasette Lite . ( #1733 )
Database file downloads now implement conditional GET using ETags. ( #1739 )
HTML for facet results and suggested results has been extracted out into new templates _facet_results.html and _suggested_facets.html . Thanks, M. Nasimul Haque. ( #1759 )
Datasette now runs some SQL queries in parallel. This has limited impact on performance, see this research issue for details.
New --nolock option for ignoring file locks when opening read-only databases. ( #1744 )
Spaces in the database names in URLs are now encoded as + rather than ~20 . ( #1701 )
is now displayed as and is accompanied by tooltip showing ""2.3MB"". ( #1712 )
The base Docker image used by datasette publish cloudrun , datasette package and the official Datasette image has been upgraded to 3.10.6-slim-bullseye . ( #1768 )
Canned writable queries against immutable databases now show a warning message. ( #1728 )
datasette publish cloudrun has a new --timeout option which can be used to increase the time limit applied by the Google Cloud build environment. Thanks, Tim Sherratt. ( #1717 )
datasette publish cloudrun has new --min-instances and --max-instances options. ( #1779 )","[""Changelog"", ""0.62 (2022-08-14)""]","[{""href"": ""https://pyodide.org/"", ""label"": ""Pyodide""}, {""href"": ""https://lite.datasette.io/"", ""label"": ""Datasette Lite""}, {""href"": ""https://github.com/simonw/datasette/issues/1733"", ""label"": ""#1733""}, {""href"": ""https://github.com/simonw/datasette/issues/1739"", ""label"": ""#1739""}, {""href"": ""https://github.com/simonw/datasette/pull/1759"", ""label"": ""#1759""}, {""href"": ""https://github.com/simonw/datasette/issues/1727"", ""label"": ""this research issue""}, {""href"": ""https://github.com/simonw/datasette/issues/1744"", ""label"": ""#1744""}, {""href"": ""https://github.com/simonw/datasette/issues/1701"", ""label"": ""#1701""}, {""href"": ""https://github.com/simonw/datasette/issues/1712"", ""label"": ""#1712""}, {""href"": ""https://hub.docker.com/datasetteproject/datasette"", ""label"": ""official Datasette image""}, {""href"": ""https://github.com/simonw/datasette/issues/1768"", ""label"": ""#1768""}, {""href"": ""https://github.com/simonw/datasette/issues/1728"", ""label"": ""#1728""}, {""href"": ""https://github.com/simonw/datasette/pull/1717"", ""label"": ""#1717""}, {""href"": ""https://github.com/simonw/datasette/issues/1779"", ""label"": ""#1779""}]"
plugin_hooks:plugin-hook-slots,plugin_hooks,plugin-hook-slots,Template slots,"The following set of plugin hooks can be used to return extra HTML content that will be inserted into the corresponding page, directly below the
heading.
Multiple plugins can contribute content here. The order in which it is displayed can be controlled using Pluggy's call time order options .
Each of these plugin hooks can return either a string or an awaitable function that returns a string.","[""Plugin hooks""]","[{""href"": ""https://pluggy.readthedocs.io/en/stable/#call-time-order"", ""label"": ""call time order options""}]"
plugin_hooks:id1,plugin_hooks,id1,Plugin hooks,"Datasette plugins use plugin hooks to customize Datasette's behavior. These hooks are powered by the pluggy plugin system.
Each plugin can implement one or more hooks using the @hookimpl decorator against a function named that matches one of the hooks documented on this page.
When you implement a plugin hook you can accept any or all of the parameters that are documented as being passed to that hook.
For example, you can implement the render_cell plugin hook like this even though the full documented hook signature is render_cell(row, value, column, table, database, datasette) :
@hookimpl
def render_cell(value, column):
if column == ""stars"":
return ""*"" * int(value)
List of plugin hooks
prepare_connection(conn, database, datasette)
prepare_jinja2_environment(env, datasette)
Page extras
extra_template_vars(template, database, table, columns, view_name, request, datasette)
extra_css_urls(template, database, table, columns, view_name, request, datasette)
extra_js_urls(template, database, table, columns, view_name, request, datasette)
extra_body_script(template, database, table, columns, view_name, request, datasette)
publish_subcommand(publish)
render_cell(row, value, column, table, database, datasette, request)
register_output_renderer(datasette)
register_routes(datasette)
register_commands(cli)
register_facet_classes()
register_permissions(datasette)
asgi_wrapper(datasette)
startup(datasette)
canned_queries(datasette, database, actor)
actor_from_request(datasette, request)
actors_from_ids(datasette, actor_ids)
jinja2_environment_from_request(datasette, request, env)
filters_from_request(request, database, table, datasette)
permission_allowed(datasette, actor, action, resource)
register_magic_parameters(datasette)
forbidden(datasette, request, message)
handle_exception(datasette, request, exception)
skip_csrf(datasette, scope)
get_metadata(datasette, key, database, table)
menu_links(datasette, actor, request)
Action hooks
table_actions(datasette, actor, database, table, request)
view_actions(datasette, actor, database, view, request)
query_actions(datasette, actor, database, query_name, request, sql, params)
row_actions(datasette, actor, request, database, table, row)
database_actions(datasette, actor, database, request)
homepage_actions(datasette, actor, request)
Template slots
top_homepage(datasette, request)
top_database(datasette, request, database)
top_table(datasette, request, database, table)
top_row(datasette, request, database, table, row)
top_query(datasette, request, database, sql)
top_canned_query(datasette, request, database, query_name)
Event tracking
track_event(datasette, event)
register_events(datasette)",[],"[{""href"": ""https://pluggy.readthedocs.io/"", ""label"": ""pluggy""}]"
plugins:id1,plugins,id1,Plugins,"Datasette's plugin system allows additional features to be implemented as Python
code (or front-end JavaScript) which can be wrapped up in a separate Python
package. The underlying mechanism uses pluggy .
See the Datasette plugins directory for a list of existing plugins, or take a look at the
datasette-plugin topic on GitHub.
Things you can do with plugins include:
Add visualizations to Datasette, for example
datasette-cluster-map and
datasette-vega .
Make new custom SQL functions available for use within Datasette, for example
datasette-haversine and
datasette-jellyfish .
Define custom output formats with custom extensions, for example datasette-atom and
datasette-ics .
Add template functions that can be called within your Jinja custom templates,
for example datasette-render-markdown .
Customize how database values are rendered in the Datasette interface, for example
datasette-render-binary and
datasette-pretty-json .
Customize how Datasette's authentication and permissions systems work, for example datasette-auth-passwords and
datasette-permissions-sql .",[],"[{""href"": ""https://pluggy.readthedocs.io/"", ""label"": ""pluggy""}, {""href"": ""https://datasette.io/plugins"", ""label"": ""Datasette plugins directory""}, {""href"": ""https://github.com/topics/datasette-plugin"", ""label"": ""datasette-plugin""}, {""href"": ""https://github.com/simonw/datasette-cluster-map"", ""label"": ""datasette-cluster-map""}, {""href"": ""https://github.com/simonw/datasette-vega"", ""label"": ""datasette-vega""}, {""href"": ""https://github.com/simonw/datasette-haversine"", ""label"": ""datasette-haversine""}, {""href"": ""https://github.com/simonw/datasette-jellyfish"", ""label"": ""datasette-jellyfish""}, {""href"": ""https://github.com/simonw/datasette-atom"", ""label"": ""datasette-atom""}, {""href"": ""https://github.com/simonw/datasette-ics"", ""label"": ""datasette-ics""}, {""href"": ""https://github.com/simonw/datasette-render-markdown#markdown-in-templates"", ""label"": ""datasette-render-markdown""}, {""href"": ""https://github.com/simonw/datasette-render-binary"", ""label"": ""datasette-render-binary""}, {""href"": ""https://github.com/simonw/datasette-pretty-json"", ""label"": ""datasette-pretty-json""}, {""href"": ""https://github.com/simonw/datasette-auth-passwords"", ""label"": ""datasette-auth-passwords""}, {""href"": ""https://github.com/simonw/datasette-permissions-sql"", ""label"": ""datasette-permissions-sql""}]"
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""}]"
metadata:specifying-units-for-a-column,metadata,specifying-units-for-a-column,Specifying units for a column,"Datasette supports attaching units to a column, which will be used when displaying
values from that column. SI prefixes will be used where appropriate.
Column units are configured in the metadata like so:
[[[cog
metadata_example(cog, {
""databases"": {
""database1"": {
""tables"": {
""example_table"": {
""units"": {
""column1"": ""metres"",
""column2"": ""Hz""
}
}
}
}
}
})
]]]
[[[end]]]
Units are interpreted using Pint , and you can see the full list of available units in
Pint's unit registry . You can also add custom units to the metadata, which will be
registered with Pint:
[[[cog
metadata_example(cog, {
""custom_units"": [
""decibel = [] = dB""
]
})
]]]
[[[end]]]","[""Metadata""]","[{""href"": ""https://pint.readthedocs.io/"", ""label"": ""Pint""}, {""href"": ""https://github.com/hgrecco/pint/blob/master/pint/default_en.txt"", ""label"": ""unit registry""}, {""href"": ""http://pint.readthedocs.io/en/latest/defining.html"", ""label"": ""custom units""}]"
changelog:id30,changelog,id30,0.57 (2021-06-05),"This release fixes a reflected cross-site scripting security hole with the ?_trace=1 feature. You should upgrade to this version, or to Datasette 0.56.1, as soon as possible. ( #1360 )
In addition to the security fix, this release includes ?_col= and ?_nocol= options for controlling which columns are displayed for a table, ?_facet_size= for increasing the number of facet results returned, re-display of your SQL query should an error occur and numerous bug fixes.","[""Changelog""]","[{""href"": ""https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks"", ""label"": ""reflected cross-site scripting""}, {""href"": ""https://github.com/simonw/datasette/issues/1360"", ""label"": ""#1360""}]"
changelog:id31,changelog,id31,0.56.1 (2021-06-05),"This release fixes a reflected cross-site scripting security hole with the ?_trace=1 feature. You should upgrade to this version, or to Datasette 0.57, as soon as possible. ( #1360 )","[""Changelog""]","[{""href"": ""https://owasp.org/www-community/attacks/xss/#reflected-xss-attacks"", ""label"": ""reflected cross-site scripting""}, {""href"": ""https://github.com/simonw/datasette/issues/1360"", ""label"": ""#1360""}]"
contributing:contributing-formatting-prettier,contributing,contributing-formatting-prettier,Prettier,"To install Prettier, install Node.js and then run the following in the root of your datasette repository checkout:
npm install
This will install Prettier in a node_modules directory. You can then check that your code matches the coding style like so:
npm run prettier -- --check
> prettier
> prettier 'datasette/static/*[!.min].js' ""--check""
Checking formatting...
[warn] datasette/static/plugins.js
[warn] Code style issues found in the above file(s). Forgot to run Prettier?
You can fix any problems by running:
npm run fix","[""Contributing"", ""Code formatting""]","[{""href"": ""https://nodejs.org/en/download/package-manager/"", ""label"": ""install Node.js""}]"
deploying:nginx-proxy-configuration,deploying,nginx-proxy-configuration,Nginx proxy configuration,"Here is an example of an nginx configuration file that will proxy traffic to Datasette:
daemon off;
events {
worker_connections 1024;
}
http {
server {
listen 80;
location /my-datasette {
proxy_pass http://127.0.0.1:8009/my-datasette;
proxy_set_header Host $host;
}
}
}
You can also use the --uds option to Datasette to listen on a Unix domain socket instead of a port, configuring the nginx upstream proxy like this:
daemon off;
events {
worker_connections 1024;
}
http {
server {
listen 80;
location /my-datasette {
proxy_pass http://datasette/my-datasette;
proxy_set_header Host $host;
}
}
upstream datasette {
server unix:/tmp/datasette.sock;
}
}
Then run Datasette with datasette --uds /tmp/datasette.sock path/to/database.db --setting base_url /my-datasette/ .","[""Deploying Datasette"", ""Running Datasette behind a proxy""]","[{""href"": ""https://nginx.org/"", ""label"": ""nginx""}]"
getting_started:getting-started-datasette-lite,getting_started,getting-started-datasette-lite,Datasette in your browser with Datasette Lite,"Datasette Lite is Datasette packaged using WebAssembly so that it runs entirely in your browser, no Python web application server required.
You can pass a URL to a CSV, SQLite or raw SQL file directly to Datasette Lite to explore that data in your browser.
This example link opens Datasette Lite and loads the SQL Murder Mystery example database from Northwestern University Knight Lab .","[""Getting started""]","[{""href"": ""https://lite.datasette.io/"", ""label"": ""Datasette Lite""}, {""href"": ""https://lite.datasette.io/?url=https%3A%2F%2Fraw.githubusercontent.com%2FNUKnightLab%2Fsql-mysteries%2Fmaster%2Fsql-murder-mystery.db#/sql-murder-mystery"", ""label"": ""example link""}, {""href"": ""https://github.com/NUKnightLab/sql-mysteries"", ""label"": ""Northwestern University Knight Lab""}]"
changelog:id13,changelog,id13,0.62 (2022-08-14),"Datasette can now run entirely in your browser using WebAssembly. Try out Datasette Lite , take a look at the code or read more about it in Datasette Lite: a server-side Python web application running in a browser .
Datasette now has a Discord community for questions and discussions about Datasette and its ecosystem of projects.","[""Changelog""]","[{""href"": ""https://lite.datasette.io/"", ""label"": ""Datasette Lite""}, {""href"": ""https://github.com/simonw/datasette-lite"", ""label"": ""at the code""}, {""href"": ""https://simonwillison.net/2022/May/4/datasette-lite/"", ""label"": ""Datasette Lite: a server-side Python web application running in a browser""}, {""href"": ""https://datasette.io/discord"", ""label"": ""Discord community""}]"
authentication:permissions-execute-sql,authentication,permissions-execute-sql,execute-sql,"Actor is allowed to run arbitrary SQL queries against a specific database, e.g. https://latest.datasette.io/fixtures?sql=select+100
resource - string
The name of the database
Default allow . See also the default_allow_sql setting .","[""Authentication and permissions"", ""Built-in permissions""]","[{""href"": ""https://latest.datasette.io/fixtures?sql=select+100"", ""label"": ""https://latest.datasette.io/fixtures?sql=select+100""}]"
authentication:authentication-permissions-table,authentication,authentication-permissions-table,Access to specific tables and views,"To limit access to the users table in your bakery.db database:
[[[cog
config_example(cog, """"""
databases:
bakery:
tables:
users:
allow:
id: '*'
"""""")
]]]
[[[end]]]
This works for SQL views as well - you can list their names in the ""tables"" block above in the same way as regular tables.
Restricting access to tables and views in this way will NOT prevent users from querying them using arbitrary SQL queries, like this for example.
If you are restricting access to specific tables you should also use the ""allow_sql"" block to prevent users from bypassing the limit with their own SQL queries - see Controlling the ability to execute arbitrary SQL .","[""Authentication and permissions"", ""Access permissions in ""]","[{""href"": ""https://latest.datasette.io/fixtures?sql=select+*+from+facetable"", ""label"": ""like this""}]"
full_text_search:full-text-search-table-or-view,full_text_search,full-text-search-table-or-view,Configuring full-text search for a table or view,"If a table has a corresponding FTS table set up using the content= argument to CREATE VIRTUAL TABLE shown below, Datasette will detect it automatically and add a search interface to the table page for that table.
You can also manually configure which table should be used for full-text search using query string parameters or Metadata . You can set the associated FTS table for a specific table and you can also set one for a view - if you do that, the page for that SQL view will offer a search option.
Use ?_fts_table=x to over-ride the FTS table for a specific page. If the primary key was something other than rowid you can use ?_fts_pk=col to set that as well. This is particularly useful for views, for example:
https://latest.datasette.io/fixtures/searchable_view?_fts_table=searchable_fts&_fts_pk=pk
The fts_table metadata property can be used to specify an associated FTS table. If the primary key column in your table which was used to populate the FTS table is something other than rowid , you can specify the column to use with the fts_pk property.
The ""searchmode"": ""raw"" property can be used to default the table to accepting SQLite advanced search operators, as described in Advanced SQLite search queries .
Here is an example which enables full-text search (with SQLite advanced search operators) for a display_ads view which is defined against the ads table and hence needs to run FTS against the ads_fts table, using the id as the primary key:
[[[cog
from metadata_doc import metadata_example
metadata_example(cog, {
""databases"": {
""russian-ads"": {
""tables"": {
""display_ads"": {
""fts_table"": ""ads_fts"",
""fts_pk"": ""id"",
""searchmode"": ""raw""
}
}
}
}
})
]]]
[[[end]]]","[""Full-text search""]","[{""href"": ""https://latest.datasette.io/fixtures/searchable_view?_fts_table=searchable_fts&_fts_pk=pk"", ""label"": ""https://latest.datasette.io/fixtures/searchable_view?_fts_table=searchable_fts&_fts_pk=pk""}]"
changelog:through-for-joins-through-many-to-many-tables,changelog,through-for-joins-through-many-to-many-tables,?_through= for joins through many-to-many tables,"The new ?_through={json} argument to the Table view allows records to be filtered based on a many-to-many relationship. See Special table arguments for full documentation - here's an example . ( #355 )
This feature was added to help support facet by many-to-many , which isn't quite ready yet but will be coming in the next Datasette release.","[""Changelog"", ""0.29 (2019-07-07)""]","[{""href"": ""https://latest.datasette.io/fixtures/roadside_attractions?_through={%22table%22:%22roadside_attraction_characteristics%22,%22column%22:%22characteristic_id%22,%22value%22:%221%22}"", ""label"": ""an example""}, {""href"": ""https://github.com/simonw/datasette/issues/355"", ""label"": ""#355""}, {""href"": ""https://github.com/simonw/datasette/issues/551"", ""label"": ""facet by many-to-many""}]"
metadata:metadata-column-descriptions,metadata,metadata-column-descriptions,Column descriptions,"You can include descriptions for your columns by adding a ""columns"": {""name-of-column"": ""description-of-column""} block to your table metadata:
[[[cog
metadata_example(cog, {
""databases"": {
""database1"": {
""tables"": {
""example_table"": {
""columns"": {
""column1"": ""Description of column 1"",
""column2"": ""Description of column 2""
}
}
}
}
}
})
]]]
[[[end]]]
These will be displayed at the top of the table page, and will also show in the cog menu for each column.
You can see an example of how these look at latest.datasette.io/fixtures/roadside_attractions .","[""Metadata""]","[{""href"": ""https://latest.datasette.io/fixtures/roadside_attractions"", ""label"": ""latest.datasette.io/fixtures/roadside_attractions""}]"
authentication:permissions-view-query,authentication,permissions-view-query,view-query,"Actor is allowed to view (and execute) a canned query page, e.g. https://latest.datasette.io/fixtures/pragma_cache_size - this includes executing Writable canned queries .
resource - tuple: (string, string)
The name of the database, then the name of the canned query
Default allow .","[""Authentication and permissions"", ""Built-in permissions""]","[{""href"": ""https://latest.datasette.io/fixtures/pragma_cache_size"", ""label"": ""https://latest.datasette.io/fixtures/pragma_cache_size""}]"
sql_queries:canned-queries-named-parameters,sql_queries,canned-queries-named-parameters,Canned query parameters,"Canned queries support named parameters, so if you include those in the SQL you will then be able to enter them using the form fields on the canned query page or by adding them to the URL. This means canned queries can be used to create custom JSON APIs based on a carefully designed SQL statement.
Here's an example of a canned query with a named parameter:
select neighborhood, facet_cities.name, state
from facetable
join facet_cities on facetable.city_id = facet_cities.id
where neighborhood like '%' || :text || '%'
order by neighborhood;
In the canned query configuration looks like this:
[[[cog
config_example(cog, """"""
databases:
fixtures:
queries:
neighborhood_search:
title: Search neighborhoods
sql: |-
select neighborhood, facet_cities.name, state
from facetable
join facet_cities on facetable.city_id = facet_cities.id
where neighborhood like '%' || :text || '%'
order by neighborhood
"""""")
]]]
[[[end]]]
Note that we are using SQLite string concatenation here - the || operator - to add wildcard % characters to the string provided by the user.
You can try this canned query out here:
https://latest.datasette.io/fixtures/neighborhood_search?text=town
In this example the :text named parameter is automatically extracted from the query using a regular expression.
You can alternatively provide an explicit list of named parameters using the ""params"" key, like this:
[[[cog
config_example(cog, """"""
databases:
fixtures:
queries:
neighborhood_search:
title: Search neighborhoods
params:
- text
sql: |-
select neighborhood, facet_cities.name, state
from facetable
join facet_cities on facetable.city_id = facet_cities.id
where neighborhood like '%' || :text || '%'
order by neighborhood
"""""")
]]]
[[[end]]]","[""Running SQL queries"", ""Canned queries""]","[{""href"": ""https://latest.datasette.io/fixtures/neighborhood_search?text=town"", ""label"": ""https://latest.datasette.io/fixtures/neighborhood_search?text=town""}]"
changelog:writable-canned-queries,changelog,writable-canned-queries,Writable canned queries,"Datasette's Canned queries feature lets you define SQL queries in metadata.json which can then be executed by users visiting a specific URL. https://latest.datasette.io/fixtures/neighborhood_search for example.
Canned queries were previously restricted to SELECT , but Datasette 0.44 introduces the ability for canned queries to execute INSERT or UPDATE queries as well, using the new ""write"": true property ( #800 ):
{
""databases"": {
""dogs"": {
""queries"": {
""add_name"": {
""sql"": ""INSERT INTO names (name) VALUES (:name)"",
""write"": true
}
}
}
}
}
See Writable canned queries for more details.","[""Changelog"", ""0.44 (2020-06-11)""]","[{""href"": ""https://latest.datasette.io/fixtures/neighborhood_search"", ""label"": ""https://latest.datasette.io/fixtures/neighborhood_search""}, {""href"": ""https://github.com/simonw/datasette/issues/800"", ""label"": ""#800""}]"
internals:internals-tracer,internals,internals-tracer,datasette.tracer,"Running Datasette with --setting trace_debug 1 enables trace debug output, which can then be viewed by adding ?_trace=1 to the query string for any page.
You can see an example of this at the bottom of latest.datasette.io/fixtures/facetable?_trace=1 . The JSON output shows full details of every SQL query that was executed to generate the page.
The datasette-pretty-traces plugin can be installed to provide a more readable display of this information. You can see a demo of that here .
You can add your own custom traces to the JSON output using the trace() context manager. This takes a string that identifies the type of trace being recorded, and records any keyword arguments as additional JSON keys on the resulting trace object.
The start and end time, duration and a traceback of where the trace was executed will be automatically attached to the JSON object.
This example uses trace to record the start, end and duration of any HTTP GET requests made using the function:
from datasette.tracer import trace
import httpx
async def fetch_url(url):
with trace(""fetch-url"", url=url):
async with httpx.AsyncClient() as client:
return await client.get(url)","[""Internals for plugins""]","[{""href"": ""https://latest.datasette.io/fixtures/facetable?_trace=1"", ""label"": ""latest.datasette.io/fixtures/facetable?_trace=1""}, {""href"": ""https://datasette.io/plugins/datasette-pretty-traces"", ""label"": ""datasette-pretty-traces""}, {""href"": ""https://latest-with-plugins.datasette.io/github/commits?_trace=1"", ""label"": ""a demo of that here""}]"
facets:id3,facets,id3,Facet by date,"If Datasette finds any columns that contain dates in the first 100 values, it will offer a faceting interface against the dates of those values.
This works especially well against timestamp values such as 2019-03-01 12:44:00 .
Example here: latest.datasette.io/fixtures/facetable?_facet_date=created","[""Facets""]","[{""href"": ""https://latest.datasette.io/fixtures/facetable?_facet_date=created"", ""label"": ""latest.datasette.io/fixtures/facetable?_facet_date=created""}]"
facets:id2,facets,id2,Facet by JSON array,"If your SQLite installation provides the json1 extension (you can check using /-/versions ) Datasette will automatically detect columns that contain JSON arrays of values and offer a faceting interface against those columns.
This is useful for modelling things like tags without needing to break them out into a new table.
Example here: latest.datasette.io/fixtures/facetable?_facet_array=tags","[""Facets""]","[{""href"": ""https://latest.datasette.io/fixtures/facetable?_facet_array=tags"", ""label"": ""latest.datasette.io/fixtures/facetable?_facet_array=tags""}]"
csv_export:id1,csv_export,id1,CSV export,"Any Datasette table, view or custom SQL query can be exported as CSV.
To obtain the CSV representation of the table you are looking, click the ""this
data as CSV"" link.
You can also use the advanced export form for more control over the resulting
file, which looks like this and has the following options:
download file - instead of displaying CSV in your browser, this forces
your browser to download the CSV to your downloads directory.
expand labels - if your table has any foreign key references this option
will cause the CSV to gain additional COLUMN_NAME_label columns with a
label for each foreign key derived from the linked table. In this example
the city_id column is accompanied by a city_id_label column.
stream all rows - by default CSV files only contain the first
max_returned_rows records. This option will cause Datasette to
loop through every matching record and return them as a single CSV file.
You can try that out on https://latest.datasette.io/fixtures/facetable?_size=4",[],"[{""href"": ""https://latest.datasette.io/fixtures/facetable.csv?_labels=on&_size=max"", ""label"": ""In this example""}, {""href"": ""https://latest.datasette.io/fixtures/facetable?_size=4"", ""label"": ""https://latest.datasette.io/fixtures/facetable?_size=4""}]"
authentication:permissions-view-table,authentication,permissions-view-table,view-table,"Actor is allowed to view a table (or view) page, e.g. https://latest.datasette.io/fixtures/complex_foreign_keys
resource - tuple: (string, string)
The name of the database, then the name of the table
Default allow .","[""Authentication and permissions"", ""Built-in permissions""]","[{""href"": ""https://latest.datasette.io/fixtures/complex_foreign_keys"", ""label"": ""https://latest.datasette.io/fixtures/complex_foreign_keys""}]"
binary_data:binary-linking,binary_data,binary-linking,Linking to binary downloads,"The .blob output format is used to return binary data. It requires a _blob_column= query string argument specifying which BLOB column should be downloaded, for example:
https://latest.datasette.io/fixtures/binary_data/1.blob?_blob_column=data
This output format can also be used to return binary data from an arbitrary SQL query. Since such queries do not specify an exact row, an additional ?_blob_hash= parameter can be used to specify the SHA-256 hash of the value that is being linked to.
Consider the query select data from binary_data - demonstrated here .
That page links to the binary value downloads. Those links look like this:
https://latest.datasette.io/fixtures.blob?sql=select+data+from+binary_data&_blob_column=data&_blob_hash=f3088978da8f9aea479ffc7f631370b968d2e855eeb172bea7f6c7a04262bb6d
These .blob links are also returned in the .csv exports Datasette provides for binary tables and queries, since the CSV format does not have a mechanism for representing binary data.","[""Binary data""]","[{""href"": ""https://latest.datasette.io/fixtures/binary_data/1.blob?_blob_column=data"", ""label"": ""https://latest.datasette.io/fixtures/binary_data/1.blob?_blob_column=data""}, {""href"": ""https://latest.datasette.io/fixtures?sql=select+data+from+binary_data"", ""label"": ""demonstrated here""}, {""href"": ""https://latest.datasette.io/fixtures.blob?sql=select+data+from+binary_data&_blob_column=data&_blob_hash=f3088978da8f9aea479ffc7f631370b968d2e855eeb172bea7f6c7a04262bb6d"", ""label"": ""https://latest.datasette.io/fixtures.blob?sql=select+data+from+binary_data&_blob_column=data&_blob_hash=f3088978da8f9aea479ffc7f631370b968d2e855eeb172bea7f6c7a04262bb6d""}]"
binary_data:binary,binary_data,binary,Binary data,"SQLite tables can contain binary data in BLOB columns.
Datasette includes special handling for these binary values. The Datasette interface detects binary values and provides a link to download their content, for example on https://latest.datasette.io/fixtures/binary_data
Binary data is represented in .json exports using Base64 encoding.
https://latest.datasette.io/fixtures/binary_data.json?_shape=array
[
{
""rowid"": 1,
""data"": {
""$base64"": true,
""encoded"": ""FRwCx60F/g==""
}
},
{
""rowid"": 2,
""data"": {
""$base64"": true,
""encoded"": ""FRwDx60F/g==""
}
},
{
""rowid"": 3,
""data"": null
}
]",[],"[{""href"": ""https://latest.datasette.io/fixtures/binary_data"", ""label"": ""https://latest.datasette.io/fixtures/binary_data""}, {""href"": ""https://latest.datasette.io/fixtures/binary_data.json?_shape=array"", ""label"": ""https://latest.datasette.io/fixtures/binary_data.json?_shape=array""}]"
changelog:miscellaneous,changelog,miscellaneous,Miscellaneous,"Got JSON data in one of your columns? Use the new ?_json=COLNAME argument
to tell Datasette to return that JSON value directly rather than encoding it
as a string.
If you just want an array of the first value of each row, use the new
?_shape=arrayfirst option - example .","[""Changelog"", ""0.23 (2018-06-18)""]","[{""href"": ""https://latest.datasette.io/fixtures.json?sql=select+neighborhood+from+facetable+order+by+pk+limit+101&_shape=arrayfirst"", ""label"": ""example""}]"
authentication:permissions-view-database-download,authentication,permissions-view-database-download,view-database-download,"Actor is allowed to download a database, e.g. https://latest.datasette.io/fixtures.db
resource - string
The name of the database
Default allow .","[""Authentication and permissions"", ""Built-in permissions""]","[{""href"": ""https://latest.datasette.io/fixtures.db"", ""label"": ""https://latest.datasette.io/fixtures.db""}]"
authentication:authentication-permissions-execute-sql,authentication,authentication-permissions-execute-sql,Controlling the ability to execute arbitrary SQL,"Datasette defaults to allowing any site visitor to execute their own custom SQL queries, for example using the form on the database page or by appending a ?_where= parameter to the table page like this .
Access to this ability is controlled by the execute-sql permission.
The easiest way to disable arbitrary SQL queries is using the default_allow_sql setting when you first start Datasette running.
You can alternatively use an ""allow_sql"" block to control who is allowed to execute arbitrary SQL queries.
To prevent any user from executing arbitrary SQL queries, use this:
[[[cog
config_example(cog, """"""
allow_sql: false
"""""")
]]]
[[[end]]]
To enable just the root user to execute SQL for all databases in your instance, use the following:
[[[cog
config_example(cog, """"""
allow_sql:
id: root
"""""")
]]]
[[[end]]]
To limit this ability for just one specific database, use this:
[[[cog
config_example(cog, """"""
databases:
mydatabase:
allow_sql:
id: root
"""""")
]]]
[[[end]]]","[""Authentication and permissions"", ""Access permissions in ""]","[{""href"": ""https://latest.datasette.io/fixtures"", ""label"": ""the database page""}, {""href"": ""https://latest.datasette.io/fixtures/facetable?_where=_city_id=1"", ""label"": ""like this""}]"
authentication:permissions-view-database,authentication,permissions-view-database,view-database,"Actor is allowed to view a database page, e.g. https://latest.datasette.io/fixtures
resource - string
The name of the database
Default allow .","[""Authentication and permissions"", ""Built-in permissions""]","[{""href"": ""https://latest.datasette.io/fixtures"", ""label"": ""https://latest.datasette.io/fixtures""}]"
sql_queries:id3,sql_queries,id3,Cross-database queries,"SQLite has the ability to run queries that join across multiple databases. Up to ten databases can be attached to a single SQLite connection and queried together.
Datasette can execute joins across multiple databases if it is started with the --crossdb option:
datasette fixtures.db extra_database.db --crossdb
If it is started in this way, the /_memory page can be used to execute queries that join across multiple databases.
References to tables in attached databases should be preceded by the database name and a period.
For example, this query will show a list of tables across both of the above databases:
select
'fixtures' as database, *
from
[fixtures].sqlite_master
union
select
'extra_database' as database, *
from
[extra_database].sqlite_master
Try that out here .","[""Running SQL queries""]","[{""href"": ""https://latest.datasette.io/_memory?sql=select%0D%0A++%27fixtures%27+as+database%2C+*%0D%0Afrom%0D%0A++%5Bfixtures%5D.sqlite_master%0D%0Aunion%0D%0Aselect%0D%0A++%27extra_database%27+as+database%2C+*%0D%0Afrom%0D%0A++%5Bextra_database%5D.sqlite_master"", ""label"": ""Try that out here""}]"
settings:setting-trace-debug,settings,setting-trace-debug,trace_debug,"This setting enables appending ?_trace=1 to any page in order to see the SQL queries and other trace information that was used to generate that page.
Enable it like this:
datasette mydatabase.db --setting trace_debug 1
Some examples:
https://latest.datasette.io/?_trace=1
https://latest.datasette.io/fixtures/roadside_attractions?_trace=1
See datasette.tracer for details on how to hook into this mechanism as a plugin author.","[""Settings"", ""Settings""]","[{""href"": ""https://latest.datasette.io/?_trace=1"", ""label"": ""https://latest.datasette.io/?_trace=1""}, {""href"": ""https://latest.datasette.io/fixtures/roadside_attractions?_trace=1"", ""label"": ""https://latest.datasette.io/fixtures/roadside_attractions?_trace=1""}]"
settings:setting-template-debug,settings,setting-template-debug,template_debug,"This setting enables template context debug mode, which is useful to help understand what variables are available to custom templates when you are writing them.
Enable it like this:
datasette mydatabase.db --setting template_debug 1
Now you can add ?_context=1 or &_context=1 to any Datasette page to see the context that was passed to that template.
Some examples:
https://latest.datasette.io/?_context=1
https://latest.datasette.io/fixtures?_context=1
https://latest.datasette.io/fixtures/roadside_attractions?_context=1","[""Settings"", ""Settings""]","[{""href"": ""https://latest.datasette.io/?_context=1"", ""label"": ""https://latest.datasette.io/?_context=1""}, {""href"": ""https://latest.datasette.io/fixtures?_context=1"", ""label"": ""https://latest.datasette.io/fixtures?_context=1""}, {""href"": ""https://latest.datasette.io/fixtures/roadside_attractions?_context=1"", ""label"": ""https://latest.datasette.io/fixtures/roadside_attractions?_context=1""}]"
introspection:jsondataview-versions,introspection,jsondataview-versions,/-/versions,"Shows the version of Datasette, Python and SQLite. Versions example :
{
""datasette"": {
""version"": ""0.60""
},
""python"": {
""full"": ""3.8.12 (default, Dec 21 2021, 10:45:09) \n[GCC 10.2.1 20210110]"",
""version"": ""3.8.12""
},
""sqlite"": {
""extensions"": {
""json1"": null
},
""fts_versions"": [
""FTS5"",
""FTS4"",
""FTS3""
],
""compile_options"": [
""COMPILER=gcc-6.3.0 20170516"",
""ENABLE_FTS3"",
""ENABLE_FTS4"",
""ENABLE_FTS5"",
""ENABLE_JSON1"",
""ENABLE_RTREE"",
""THREADSAFE=1""
],
""version"": ""3.37.0""
}
}","[""Introspection""]","[{""href"": ""https://latest.datasette.io/-/versions"", ""label"": ""Versions example""}]"
introspection:jsondataview-threads,introspection,jsondataview-threads,/-/threads,"Shows details of threads and asyncio tasks. Threads example :
{
""num_threads"": 2,
""threads"": [
{
""daemon"": false,
""ident"": 4759197120,
""name"": ""MainThread""
},
{
""daemon"": true,
""ident"": 123145319682048,
""name"": ""Thread-1""
},
],
""num_tasks"": 3,
""tasks"": [
"" cb=[set.discard()]>"",
"" wait_for=()]> cb=[run_until_complete..()]>"",
"" wait_for=()]>>""
]
}","[""Introspection""]","[{""href"": ""https://latest.datasette.io/-/threads"", ""label"": ""Threads example""}]"
introspection:jsondataview-databases,introspection,jsondataview-databases,/-/databases,"Shows currently attached databases. Databases example :
[
{
""hash"": null,
""is_memory"": false,
""is_mutable"": true,
""name"": ""fixtures"",
""path"": ""fixtures.db"",
""size"": 225280
}
]","[""Introspection""]","[{""href"": ""https://latest.datasette.io/-/databases"", ""label"": ""Databases example""}]"
introspection:jsondataview-config,introspection,jsondataview-config,/-/config,"Shows the configuration for this instance of Datasette. This is generally the contents of the datasette.yaml or datasette.json file, which can include plugin configuration as well. Config example :
{
""settings"": {
""template_debug"": true,
""trace_debug"": true,
""force_https_urls"": true
}
}
Any keys that include the one of the following substrings in their names will be returned as redacted *** output, to help avoid accidentally leaking private configuration information: secret , key , password , token , hash , dsn .","[""Introspection""]","[{""href"": ""https://latest.datasette.io/-/config"", ""label"": ""Config example""}]"
authentication:authentication-permissions-allow,authentication,authentication-permissions-allow,"Defining permissions with ""allow"" blocks","The standard way to define permissions in Datasette is to use an ""allow"" block in the datasette.yaml file . This is a JSON document describing which actors are allowed to perform a permission.
The most basic form of allow block is this ( allow demo , deny demo ):
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow:
id: root
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
This will match any actors with an ""id"" property of ""root"" - for example, an actor that looks like this:
{
""id"": ""root"",
""name"": ""Root User""
}
An allow block can specify ""deny all"" using false ( demo ):
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow: false
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
An ""allow"" of true allows all access ( demo ):
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow: true
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
Allow keys can provide a list of values. These will match any actor that has any of those values ( allow demo , deny demo ):
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow:
id:
- simon
- cleopaws
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
This will match any actor with an ""id"" of either ""simon"" or ""cleopaws"" .
Actors can have properties that feature a list of values. These will be matched against the list of values in an allow block. Consider the following actor:
{
""id"": ""simon"",
""roles"": [""staff"", ""developer""]
}
This allow block will provide access to any actor that has ""developer"" as one of their roles ( allow demo , deny demo ):
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow:
roles:
- developer
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
Note that ""roles"" is not a concept that is baked into Datasette - it's a convention that plugins can choose to implement and act on.
If you want to provide access to any actor with a value for a specific key, use ""*"" . For example, to match any logged-in user specify the following ( allow demo , deny demo ):
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow:
id: ""*""
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
You can specify that only unauthenticated actors (from anonymous HTTP requests) should be allowed access using the special ""unauthenticated"": true key in an allow block ( allow demo , deny demo ):
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow:
unauthenticated: true
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
Allow keys act as an ""or"" mechanism. An actor will be able to execute the query if any of their JSON properties match any of the values in the corresponding lists in the allow block. The following block will allow users with either a role of ""ops"" OR users who have an id of ""simon"" or ""cleopaws"" :
[[[cog
from metadata_doc import config_example
import textwrap
config_example(cog, textwrap.dedent(
""""""
allow:
id:
- simon
- cleopaws
role: ops
"""""").strip(),
""YAML"", ""JSON""
)
]]]
[[[end]]]
Demo for cleopaws , demo for ops role , demo for an actor matching neither rule .","[""Authentication and permissions"", ""Permissions""]","[{""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%22id%22%3A+%22root%22%7D&allow=%7B%0D%0A++++++++%22id%22%3A+%22root%22%0D%0A++++%7D"", ""label"": ""allow demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%22id%22%3A+%22trevor%22%7D&allow=%7B%0D%0A++++++++%22id%22%3A+%22root%22%0D%0A++++%7D"", ""label"": ""deny demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22root%22%0D%0A%7D&allow=false"", ""label"": ""demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22root%22%0D%0A%7D&allow=true"", ""label"": ""demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22cleopaws%22%0D%0A%7D&allow=%7B%0D%0A++++%22id%22%3A+%5B%0D%0A++++++++%22simon%22%2C%0D%0A++++++++%22cleopaws%22%0D%0A++++%5D%0D%0A%7D"", ""label"": ""allow demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22pancakes%22%0D%0A%7D&allow=%7B%0D%0A++++%22id%22%3A+%5B%0D%0A++++++++%22simon%22%2C%0D%0A++++++++%22cleopaws%22%0D%0A++++%5D%0D%0A%7D"", ""label"": ""deny demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22simon%22%2C%0D%0A++++%22roles%22%3A+%5B%0D%0A++++++++%22staff%22%2C%0D%0A++++++++%22developer%22%0D%0A++++%5D%0D%0A%7D&allow=%7B%0D%0A++++%22roles%22%3A+%5B%0D%0A++++++++%22developer%22%0D%0A++++%5D%0D%0A%7D"", ""label"": ""allow demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22cleopaws%22%2C%0D%0A++++%22roles%22%3A+%5B%22dog%22%5D%0D%0A%7D&allow=%7B%0D%0A++++%22roles%22%3A+%5B%0D%0A++++++++%22developer%22%0D%0A++++%5D%0D%0A%7D"", ""label"": ""deny demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22simon%22%0D%0A%7D&allow=%7B%0D%0A++++%22id%22%3A+%22*%22%0D%0A%7D"", ""label"": ""allow demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22bot%22%3A+%22readme-bot%22%0D%0A%7D&allow=%7B%0D%0A++++%22id%22%3A+%22*%22%0D%0A%7D"", ""label"": ""deny demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=null&allow=%7B%0D%0A++++%22unauthenticated%22%3A+true%0D%0A%7D"", ""label"": ""allow demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22hello%22%0D%0A%7D&allow=%7B%0D%0A++++%22unauthenticated%22%3A+true%0D%0A%7D"", ""label"": ""deny demo""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22cleopaws%22%0D%0A%7D&allow=%7B%0D%0A++++%22id%22%3A+%5B%0D%0A++++++++%22simon%22%2C%0D%0A++++++++%22cleopaws%22%0D%0A++++%5D%2C%0D%0A++++%22role%22%3A+%22ops%22%0D%0A%7D"", ""label"": ""Demo for cleopaws""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22trevor%22%2C%0D%0A++++%22role%22%3A+%5B%0D%0A++++++++%22ops%22%2C%0D%0A++++++++%22staff%22%0D%0A++++%5D%0D%0A%7D&allow=%7B%0D%0A++++%22id%22%3A+%5B%0D%0A++++++++%22simon%22%2C%0D%0A++++++++%22cleopaws%22%0D%0A++++%5D%2C%0D%0A++++%22role%22%3A+%22ops%22%0D%0A%7D"", ""label"": ""demo for ops role""}, {""href"": ""https://latest.datasette.io/-/allow-debug?actor=%7B%0D%0A++++%22id%22%3A+%22percy%22%2C%0D%0A++++%22role%22%3A+%5B%0D%0A++++++++%22staff%22%0D%0A++++%5D%0D%0A%7D&allow=%7B%0D%0A++++%22id%22%3A+%5B%0D%0A++++++++%22simon%22%2C%0D%0A++++++++%22cleopaws%22%0D%0A++++%5D%2C%0D%0A++++%22role%22%3A+%22ops%22%0D%0A%7D"", ""label"": ""demo for an actor matching neither rule""}]"
authentication:allowdebugview,authentication,allowdebugview,The /-/allow-debug tool,"The /-/allow-debug tool lets you try out different ""action"" blocks against different ""actor"" JSON objects. You can try that out here: https://latest.datasette.io/-/allow-debug","[""Authentication and permissions"", ""Permissions""]","[{""href"": ""https://latest.datasette.io/-/allow-debug"", ""label"": ""https://latest.datasette.io/-/allow-debug""}]"
contributing:contributing-continuous-deployment,contributing,contributing-continuous-deployment,Continuously deployed demo instances,"The demo instance at latest.datasette.io is re-deployed automatically to Google Cloud Run for every push to main that passes the test suite. This is implemented by the GitHub Actions workflow at .github/workflows/deploy-latest.yml .
Specific branches can also be set to automatically deploy by adding them to the on: push: branches block at the top of the workflow YAML file. Branches configured in this way will be deployed to a new Cloud Run service whether or not their tests pass.
The Cloud Run URL for a branch demo can be found in the GitHub Actions logs.","[""Contributing""]","[{""href"": ""https://latest.datasette.io/"", ""label"": ""latest.datasette.io""}, {""href"": ""https://github.com/simonw/datasette/blob/main/.github/workflows/deploy-latest.yml"", ""label"": "".github/workflows/deploy-latest.yml""}]"
authentication:permissions-view-instance,authentication,permissions-view-instance,view-instance,"Top level permission - Actor is allowed to view any pages within this instance, starting at https://latest.datasette.io/
Default allow .","[""Authentication and permissions"", ""Built-in permissions""]","[{""href"": ""https://latest.datasette.io/"", ""label"": ""https://latest.datasette.io/""}]"
changelog:latest-datasette-io,changelog,latest-datasette-io,latest.datasette.io,"Every commit to Datasette master is now automatically deployed by Travis CI to
https://latest.datasette.io/ - ensuring there is always a live demo of the
latest version of the software.
The demo uses the fixtures from our
unit tests, ensuring it demonstrates the same range of functionality that is
covered by the tests.
You can see how the deployment mechanism works in our .travis.yml file.","[""Changelog"", ""0.23 (2018-06-18)""]","[{""href"": ""https://latest.datasette.io/"", ""label"": ""https://latest.datasette.io/""}, {""href"": ""https://github.com/simonw/datasette/blob/master/tests/fixtures.py"", ""label"": ""the fixtures""}, {""href"": ""https://github.com/simonw/datasette/blob/master/.travis.yml"", ""label"": "".travis.yml""}]"
plugin_hooks:plugin-hook-jinja2-environment-from-request,plugin_hooks,plugin-hook-jinja2-environment-from-request,"jinja2_environment_from_request(datasette, request, env)","datasette - Datasette class
A Datasette instance.
request - Request object or None
The current HTTP request, if one is available.
env - Environment
The Jinja2 environment that will be used to render the current page.
This hook can be used to return a customized Jinja environment based on the incoming request.
If you want to run a single Datasette instance that serves different content for different domains, you can do so like this:
from datasette import hookimpl
from jinja2 import ChoiceLoader, FileSystemLoader
@hookimpl
def jinja2_environment_from_request(request, env):
if request and request.host == ""www.niche-museums.com"":
return env.overlay(
loader=ChoiceLoader(
[
FileSystemLoader(
""/mnt/niche-museums/templates""
),
env.loader,
]
),
enable_async=True,
)
return env
This uses the Jinja overlay() method to create a new environment identical to the default environment except for having a different template loader, which first looks in the /mnt/niche-museums/templates directory before falling back on the default loader.","[""Plugin hooks""]","[{""href"": ""https://jinja.palletsprojects.com/en/3.0.x/api/#jinja2.Environment"", ""label"": ""Jinja environment""}, {""href"": ""https://jinja.palletsprojects.com/en/3.0.x/api/#jinja2.Environment.overlay"", ""label"": ""overlay() method""}]"
internals:datasette-render-template,internals,datasette-render-template,"await .render_template(template, context=None, request=None)","template - string, list of strings or jinja2.Template
The template file to be rendered, e.g. my_plugin.html . Datasette will search for this file first in the --template-dir= location, if it was specified - then in the plugin's bundled templates and finally in Datasette's set of default templates.
If this is a list of template file names then the first one that exists will be loaded and rendered.
If this is a Jinja Template object it will be used directly.
context - None or a Python dictionary
The context variables to pass to the template.
request - request object or None
If you pass a Datasette request object here it will be made available to the template.
Renders a Jinja template using Datasette's preconfigured instance of Jinja and returns the resulting string. The template will have access to Datasette's default template functions and any functions that have been made available by other plugins.","[""Internals for plugins"", ""Datasette class""]","[{""href"": ""https://jinja.palletsprojects.com/en/2.11.x/api/#jinja2.Template"", ""label"": ""Template object""}, {""href"": ""https://jinja.palletsprojects.com/en/2.11.x/"", ""label"": ""Jinja template""}]"
plugin_hooks:plugin-hook-extra-template-vars,plugin_hooks,plugin-hook-extra-template-vars,"extra_template_vars(template, database, table, columns, view_name, request, datasette)","Extra template variables that should be made available in the rendered template context.
template - string
The template that is being rendered, e.g. database.html
database - string or None
The name of the database, or None if the page does not correspond to a database (e.g. the root page)
table - string or None
The name of the table, or None if the page does not correct to a table
columns - list of strings or None
The names of the database columns that will be displayed on this page. None if the page does not contain a table.
view_name - string
The name of the view being displayed. ( index , database , table , and row are the most important ones.)
request - Request object or None
The current HTTP request. This can be None if the request object is not available.
datasette - Datasette class
You can use this to access plugin configuration options via datasette.plugin_config(your_plugin_name)
This hook can return one of three different types:
Dictionary
If you return a dictionary its keys and values will be merged into the template context.
Function that returns a dictionary
If you return a function it will be executed. If it returns a dictionary those values will will be merged into the template context.
Function that returns an awaitable function that returns a dictionary
You can also return a function which returns an awaitable function which returns a dictionary.
Datasette runs Jinja2 in async mode , which means you can add awaitable functions to the template scope and they will be automatically awaited when they are rendered by the template.
Here's an example plugin that adds a ""user_agent"" variable to the template context containing the current request's User-Agent header:
@hookimpl
def extra_template_vars(request):
return {""user_agent"": request.headers.get(""user-agent"")}
This example returns an awaitable function which adds a list of hidden_table_names to the context:
@hookimpl
def extra_template_vars(datasette, database):
async def hidden_table_names():
if database:
db = datasette.databases[database]
return {
""hidden_table_names"": await db.hidden_table_names()
}
else:
return {}
return hidden_table_names
And here's an example which adds a sql_first(sql_query) function which executes a SQL statement and returns the first column of the first row of results:
@hookimpl
def extra_template_vars(datasette, database):
async def sql_first(sql, dbname=None):
dbname = (
dbname
or database
or next(iter(datasette.databases.keys()))
)
result = await datasette.execute(dbname, sql)
return result.rows[0][0]
return {""sql_first"": sql_first}
You can then use the new function in a template like so:
SQLite version: {{ sql_first(""select sqlite_version()"") }}
Examples: datasette-search-all , datasette-template-sql","[""Plugin hooks"", ""Page extras""]","[{""href"": ""https://jinja.palletsprojects.com/en/2.10.x/api/#async-support"", ""label"": ""async mode""}, {""href"": ""https://datasette.io/plugins/datasette-search-all"", ""label"": ""datasette-search-all""}, {""href"": ""https://datasette.io/plugins/datasette-template-sql"", ""label"": ""datasette-template-sql""}]"
changelog:id74,changelog,id74,0.32 (2019-11-14),"Datasette now renders templates using Jinja async mode . This means plugins can provide custom template functions that perform asynchronous actions, for example the new datasette-template-sql plugin which allows custom templates to directly execute SQL queries and render their results. ( #628 )","[""Changelog""]","[{""href"": ""https://jinja.palletsprojects.com/en/2.10.x/api/#async-support"", ""label"": ""Jinja async mode""}, {""href"": ""https://github.com/simonw/datasette-template-sql"", ""label"": ""datasette-template-sql""}, {""href"": ""https://github.com/simonw/datasette/issues/628"", ""label"": ""#628""}]"
changelog:id71,changelog,id71,0.35 (2020-02-04),"Added five new plugins and one new conversion tool to the The Datasette Ecosystem .
The Datasette class has a new render_template() method which can be used by plugins to render templates using Datasette's pre-configured Jinja templating library.
You can now execute SQL queries that start with a -- comment - thanks, Jay Graves ( #653 )","[""Changelog""]","[{""href"": ""https://jinja.palletsprojects.com/"", ""label"": ""Jinja""}, {""href"": ""https://github.com/simonw/datasette/pull/653"", ""label"": ""#653""}]"
internals:datasette-sign,internals,datasette-sign,".sign(value, namespace=""default"")","value - any serializable type
The value to be signed.
namespace - string, optional
An alternative namespace, see the itsdangerous salt documentation .
Utility method for signing values, such that you can safely pass data to and from an untrusted environment. This is a wrapper around the itsdangerous library.
This method returns a signed string, which can be decoded and verified using .unsign(value, namespace=""default"") .","[""Internals for plugins"", ""Datasette class""]","[{""href"": ""https://itsdangerous.palletsprojects.com/en/1.1.x/serializer/#the-salt"", ""label"": ""itsdangerous salt documentation""}, {""href"": ""https://itsdangerous.palletsprojects.com/"", ""label"": ""itsdangerous""}]"
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""}]"
changelog:id54,changelog,id54,0.47.2 (2020-08-12),Fixed an issue with the Docker image published to Docker Hub . ( #931 ),"[""Changelog""]","[{""href"": ""https://hub.docker.com/r/datasetteproject/datasette"", ""label"": ""published to Docker Hub""}, {""href"": ""https://github.com/simonw/datasette/issues/931"", ""label"": ""#931""}]"
changelog:id67,changelog,id67,0.38 (2020-03-08),"The Docker build of Datasette now uses SQLite 3.31.1, upgraded from 3.26. ( #695 )
datasette publish cloudrun now accepts an optional --memory=2Gi flag for setting the Cloud Run allocated memory to a value other than the default (256Mi). ( #694 )
Fixed bug where templates that shipped with plugins were sometimes not being correctly loaded. ( #697 )","[""Changelog""]","[{""href"": ""https://hub.docker.com/r/datasetteproject/datasette"", ""label"": ""Docker build""}, {""href"": ""https://github.com/simonw/datasette/issues/695"", ""label"": ""#695""}, {""href"": ""https://github.com/simonw/datasette/issues/694"", ""label"": ""#694""}, {""href"": ""https://github.com/simonw/datasette/issues/697"", ""label"": ""#697""}]"
deploying:apache-proxy-configuration,deploying,apache-proxy-configuration,Apache proxy configuration,"For Apache , you can use the ProxyPass directive. First make sure the following lines are uncommented:
LoadModule proxy_module lib/httpd/modules/mod_proxy.so
LoadModule proxy_http_module lib/httpd/modules/mod_proxy_http.so
Then add these directives to proxy traffic:
ProxyPass /my-datasette/ http://127.0.0.1:8009/my-datasette/
ProxyPreserveHost On
A live demo of Datasette running behind Apache using this proxy setup can be seen at datasette-apache-proxy-demo.datasette.io/prefix/ . The code for that demo can be found in the demos/apache-proxy directory.
Using --uds you can use Unix domain sockets similar to the nginx example:
ProxyPass /my-datasette/ unix:/tmp/datasette.sock|http://localhost/my-datasette/
The ProxyPreserveHost On directive ensures that the original Host: header from the incoming request is passed through to Datasette. Datasette needs this to correctly assemble links to other pages using the .absolute_url(request, path) method.","[""Deploying Datasette"", ""Running Datasette behind a proxy""]","[{""href"": ""https://httpd.apache.org/"", ""label"": ""Apache""}, {""href"": ""https://datasette-apache-proxy-demo.datasette.io/prefix/"", ""label"": ""datasette-apache-proxy-demo.datasette.io/prefix/""}, {""href"": ""https://github.com/simonw/datasette/tree/main/demos/apache-proxy"", ""label"": ""demos/apache-proxy""}, {""href"": ""https://httpd.apache.org/docs/2.4/mod/mod_proxy.html#proxypreservehost"", ""label"": ""ProxyPreserveHost On""}]"
getting_started:getting-started-demo,getting_started,getting-started-demo,Play with a live demo,"The best way to experience Datasette for the first time is with a demo:
global-power-plants.datasettes.com provides a searchable database of power plants around the world, using data from the World Resources Institude rendered using the datasette-cluster-map plugin.
fivethirtyeight.datasettes.com shows Datasette running against over 400 datasets imported from the FiveThirtyEight GitHub repository .","[""Getting started""]","[{""href"": ""https://global-power-plants.datasettes.com/global-power-plants/global-power-plants"", ""label"": ""global-power-plants.datasettes.com""}, {""href"": ""https://www.wri.org/publication/global-power-plant-database"", ""label"": ""World Resources Institude""}, {""href"": ""https://github.com/simonw/datasette-cluster-map"", ""label"": ""datasette-cluster-map""}, {""href"": ""https://fivethirtyeight.datasettes.com/fivethirtyeight"", ""label"": ""fivethirtyeight.datasettes.com""}, {""href"": ""https://github.com/fivethirtyeight/data"", ""label"": ""FiveThirtyEight GitHub repository""}]"
getting_started:getting-started-glitch,getting_started,getting-started-glitch,Try Datasette without installing anything using Glitch,"Glitch is a free online tool for building web apps directly from your web browser. You can use Glitch to try out Datasette without needing to install any software on your own computer.
Here's a demo project on Glitch which you can use as the basis for your own experiments:
glitch.com/~datasette-csvs
Glitch allows you to ""remix"" any project to create your own copy and start editing it in your browser. You can remix the datasette-csvs project by clicking this button:
Find a CSV file and drag it onto the Glitch file explorer panel - datasette-csvs will automatically convert it to a SQLite database (using sqlite-utils ) and allow you to start exploring it using Datasette.
If your CSV file has a latitude and longitude column you can visualize it on a map by uncommenting the datasette-cluster-map line in the requirements.txt file using the Glitch file editor.
Need some data? Try this Public Art Data for the city of Seattle - hit ""Export"" and select ""CSV"" to download it as a CSV file.
For more on how this works, see Running Datasette on Glitch .","[""Getting started""]","[{""href"": ""https://glitch.com/"", ""label"": ""Glitch""}, {""href"": ""https://glitch.com/~datasette-csvs"", ""label"": ""glitch.com/~datasette-csvs""}, {""href"": ""https://glitch.com/edit/#!/remix/datasette-csvs"", ""label"": null}, {""href"": ""https://github.com/simonw/sqlite-utils"", ""label"": ""sqlite-utils""}, {""href"": ""https://data.seattle.gov/Community/Public-Art-Data/j7sn-tdzk"", ""label"": ""Public Art Data""}, {""href"": ""https://simonwillison.net/2019/Apr/23/datasette-glitch/"", ""label"": ""Running Datasette on Glitch""}]"
changelog:id115,changelog,id115,0.22.1 (2018-05-23),"Bugfix release, plus we now use versioneer for our version numbers.
Faceting no longer breaks pagination, fixes #282
Add __version_info__ derived from __version__ [Robert Gieseke]
This might be tuple of more than two values (major and minor
version) if commits have been made after a release.
Add version number support with Versioneer. [Robert Gieseke]
Versioneer Licence:
Public Domain (CC0-1.0)
Closes #273
Refactor inspect logic [Russ Garrett]","[""Changelog""]","[{""href"": ""https://github.com/warner/python-versioneer"", ""label"": ""versioneer""}, {""href"": ""https://github.com/simonw/datasette/issues/282"", ""label"": ""#282""}, {""href"": ""https://github.com/simonw/datasette/issues/273"", ""label"": ""#273""}]"
plugin_hooks:plugin-hook-publish-subcommand,plugin_hooks,plugin-hook-publish-subcommand,publish_subcommand(publish),"publish - Click publish command group
The Click command group for the datasette publish subcommand
This hook allows you to create new providers for the datasette publish
command. Datasette uses this hook internally to implement the default cloudrun
and heroku subcommands, so you can read
their source
to see examples of this hook in action.
Let's say you want to build a plugin that adds a datasette publish my_hosting_provider --api_key=xxx mydatabase.db publish command. Your implementation would start like this:
from datasette import hookimpl
from datasette.publish.common import (
add_common_publish_arguments_and_options,
)
import click
@hookimpl
def publish_subcommand(publish):
@publish.command()
@add_common_publish_arguments_and_options
@click.option(
""-k"",
""--api_key"",
help=""API key for talking to my hosting provider"",
)
def my_hosting_provider(
files,
metadata,
extra_options,
branch,
template_dir,
plugins_dir,
static,
install,
plugin_secret,
version_note,
secret,
title,
license,
license_url,
source,
source_url,
about,
about_url,
api_key,
): ...
Examples: datasette-publish-fly , datasette-publish-vercel","[""Plugin hooks""]","[{""href"": ""https://github.com/simonw/datasette/tree/main/datasette/publish"", ""label"": ""their source""}, {""href"": ""https://datasette.io/plugins/datasette-publish-fly"", ""label"": ""datasette-publish-fly""}, {""href"": ""https://datasette.io/plugins/datasette-publish-vercel"", ""label"": ""datasette-publish-vercel""}]"
contributing:contributing-bug-fix-branch,contributing,contributing-bug-fix-branch,Releasing bug fixes from a branch,"If it's necessary to publish a bug fix release without shipping new features that have landed on main a release branch can be used.
Create it from the relevant last tagged release like so:
git branch 0.52.x 0.52.4
git checkout 0.52.x
Next cherry-pick the commits containing the bug fixes:
git cherry-pick COMMIT
Write the release notes in the branch, and update the version number in version.py . Then push the branch:
git push -u origin 0.52.x
Once the tests have completed, publish the release from that branch target using the GitHub Draft a new release form.
Finally, cherry-pick the commit with the release notes and version number bump across to main :
git checkout main
git cherry-pick COMMIT
git push","[""Contributing""]","[{""href"": ""https://github.com/simonw/datasette/releases/new"", ""label"": ""Draft a new release""}]"
changelog:id76,changelog,id76,0.31.1 (2019-11-12),Deployments created using datasette publish now use python:3.8 base Docker image ( #629 ),"[""Changelog""]","[{""href"": ""https://github.com/simonw/datasette/pull/629"", ""label"": ""#629""}]"
changelog:id77,changelog,id77,0.31 (2019-11-11),"This version adds compatibility with Python 3.8 and breaks compatibility with Python 3.5.
If you are still running Python 3.5 you should stick with 0.30.2 , which you can install like this:
pip install datasette==0.30.2
Format SQL button now works with read-only SQL queries - thanks, Tobias Kunze ( #602 )
New ?column__notin=x,y,z filter for table views ( #614 )
Table view now uses select col1, col2, col3 instead of select *
Database filenames can now contain spaces - thanks, Tobias Kunze ( #590 )
Removed obsolete ?_group_count=col feature ( #504 )
Improved user interface and documentation for datasette publish cloudrun ( #608 )
Tables with indexes now show the CREATE INDEX statements on the table page ( #618 )
Current version of uvicorn is now shown on /-/versions
Python 3.8 is now supported! ( #622 )
Python 3.5 is no longer supported.","[""Changelog""]","[{""href"": ""https://github.com/simonw/datasette/pull/602"", ""label"": ""#602""}, {""href"": ""https://github.com/simonw/datasette/issues/614"", ""label"": ""#614""}, {""href"": ""https://github.com/simonw/datasette/pull/590"", ""label"": ""#590""}, {""href"": ""https://github.com/simonw/datasette/issues/504"", ""label"": ""#504""}, {""href"": ""https://github.com/simonw/datasette/issues/608"", ""label"": ""#608""}, {""href"": ""https://github.com/simonw/datasette/issues/618"", ""label"": ""#618""}, {""href"": ""https://www.uvicorn.org/"", ""label"": ""uvicorn""}, {""href"": ""https://github.com/simonw/datasette/issues/622"", ""label"": ""#622""}]"
changelog:v0-28-register-output-renderer,changelog,v0-28-register-output-renderer,register_output_renderer plugins,"Russ Garrett implemented a new Datasette plugin hook called register_output_renderer ( #441 ) which allows plugins to create additional output renderers in addition to Datasette's default .json and .csv .
Russ's in-development datasette-geo plugin includes an example of this hook being used to output .geojson automatically converted from SpatiaLite.","[""Changelog"", ""0.28 (2019-05-19)""]","[{""href"": ""https://github.com/simonw/datasette/pull/441"", ""label"": ""#441""}, {""href"": ""https://github.com/russss/datasette-geo"", ""label"": ""datasette-geo""}, {""href"": ""https://github.com/russss/datasette-geo/blob/d4cecc020848bbde91e9e17bf352f7c70bc3dccf/datasette_plugin_geo/geojson.py"", ""label"": ""an example""}]"
changelog:the-road-to-datasette-1-0,changelog,the-road-to-datasette-1-0,The road to Datasette 1.0,"I've assembled a milestone for Datasette 1.0 . The focus of the 1.0 release will be the following:
Signify confidence in the quality/stability of Datasette
Give plugin authors confidence that their plugins will work for the whole 1.x release cycle
Provide the same confidence to developers building against Datasette JSON APIs
If you have thoughts about what you would like to see for Datasette 1.0 you can join the conversation on issue #519 .","[""Changelog"", ""0.44 (2020-06-11)""]","[{""href"": ""https://github.com/simonw/datasette/milestone/7"", ""label"": ""milestone for Datasette 1.0""}, {""href"": ""https://github.com/simonw/datasette/issues/519"", ""label"": ""the conversation on issue #519""}]"
internals:internals-utils,internals,internals-utils,The datasette.utils module,"The datasette.utils module contains various utility functions used by Datasette. As a general rule you should consider anything in this module to be unstable - functions and classes here could change without warning or be removed entirely between Datasette releases, without being mentioned in the release notes.
The exception to this rule is anything that is documented here. If you find a need for an undocumented utility function in your own work, consider opening an issue requesting that the function you are using be upgraded to documented and supported status.","[""Internals for plugins""]","[{""href"": ""https://github.com/simonw/datasette/issues/new"", ""label"": ""opening an issue""}]"
changelog:id46,changelog,id46,Smaller changes,"Wide tables shown within Datasette now scroll horizontally ( #998 ). This is achieved using a new
element which may impact the implementation of some plugins (for example this change to datasette-cluster-map ).
New debug-menu permission. ( #1068 )
Removed --debug option, which didn't do anything. ( #814 )
Link: HTTP header pagination. ( #1014 )
x button for clearing filters. ( #1016 )
Edit SQL button on canned queries, ( #1019 )
--load-extension=spatialite shortcut. ( #1028 )
scale-in animation for column action menu. ( #1039 )
Option to pass a list of templates to .render_template() is now documented. ( #1045 )
New datasette.urls.static_plugins() method. ( #1033 )
datasette -o option now opens the most relevant page. ( #976 )
datasette --cors option now enables access to /database.db downloads. ( #1057 )
Database file downloads now implement cascading permissions, so you can download a database if you have view-database-download permission even if you do not have permission to access the Datasette instance. ( #1058 )
New documentation on Designing URLs for your plugin . ( #1053 )","[""Changelog"", ""0.51 (2020-10-31)""]","[{""href"": ""https://github.com/simonw/datasette/issues/998"", ""label"": ""#998""}, {""href"": ""https://github.com/simonw/datasette-cluster-map/commit/fcb4abbe7df9071c5ab57defd39147de7145b34e"", ""label"": ""this change to datasette-cluster-map""}, {""href"": ""https://github.com/simonw/datasette/issues/1068"", ""label"": ""#1068""}, {""href"": ""https://github.com/simonw/datasette/issues/814"", ""label"": ""#814""}, {""href"": ""https://github.com/simonw/datasette/issues/1014"", ""label"": ""#1014""}, {""href"": ""https://github.com/simonw/datasette/issues/1016"", ""label"": ""#1016""}, {""href"": ""https://github.com/simonw/datasette/issues/1019"", ""label"": ""#1019""}, {""href"": ""https://github.com/simonw/datasette/issues/1028"", ""label"": ""#1028""}, {""href"": ""https://github.com/simonw/datasette/issues/1039"", ""label"": ""#1039""}, {""href"": ""https://github.com/simonw/datasette/issues/1045"", ""label"": ""#1045""}, {""href"": ""https://github.com/simonw/datasette/issues/1033"", ""label"": ""#1033""}, {""href"": ""https://github.com/simonw/datasette/issues/976"", ""label"": ""#976""}, {""href"": ""https://github.com/simonw/datasette/issues/1057"", ""label"": ""#1057""}, {""href"": ""https://github.com/simonw/datasette/issues/1058"", ""label"": ""#1058""}, {""href"": ""https://github.com/simonw/datasette/issues/1053"", ""label"": ""#1053""}]"
changelog:id43,changelog,id43,0.52 (2020-11-28),"This release includes a number of changes relating to an internal rebranding effort: Datasette's configuration mechanism (things like datasette --config default_page_size:10 ) has been renamed to settings .
New --setting default_page_size 10 option as a replacement for --config default_page_size:10 (note the lack of a colon). The --config option is deprecated but will continue working until Datasette 1.0. ( #992 )
The /-/config introspection page is now /-/settings , and the previous page redirects to the new one. ( #1103 )
The config.json file in Configuration directory mode is now called settings.json . ( #1104 )
The undocumented datasette.config() internal method has been replaced by a documented .setting(key) method. ( #1107 )
Also in this release:
New plugin hook: database_actions(datasette, actor, database, request) , which adds menu items to a new cog menu shown at the top of the database page. ( #1077 )
datasette publish cloudrun has a new --apt-get-install option that can be used to install additional Ubuntu packages as part of the deployment. This is useful for deploying the new datasette-ripgrep plugin . ( #1110 )
Swept the documentation to remove words that minimize involved difficulty. ( #1089 )
And some bug fixes:
Foreign keys linking to rows with blank label columns now display as a hyphen, allowing those links to be clicked. ( #1086 )
Fixed bug where row pages could sometimes 500 if the underlying queries exceeded a time limit. ( #1088 )
Fixed a bug where the table action menu could appear partially obscured by the edge of the page. ( #1084 )","[""Changelog""]","[{""href"": ""https://github.com/simonw/datasette/issues/992"", ""label"": ""#992""}, {""href"": ""https://github.com/simonw/datasette/issues/1103"", ""label"": ""#1103""}, {""href"": ""https://github.com/simonw/datasette/issues/1104"", ""label"": ""#1104""}, {""href"": ""https://github.com/simonw/datasette/issues/1107"", ""label"": ""#1107""}, {""href"": ""https://github.com/simonw/datasette/issues/1077"", ""label"": ""#1077""}, {""href"": ""https://github.com/simonw/datasette-ripgrep"", ""label"": ""datasette-ripgrep plugin""}, {""href"": ""https://github.com/simonw/datasette/issues/1110"", ""label"": ""#1110""}, {""href"": ""https://github.com/simonw/datasette/issues/1089"", ""label"": ""#1089""}, {""href"": ""https://github.com/simonw/datasette/issues/1086"", ""label"": ""#1086""}, {""href"": ""https://github.com/simonw/datasette/issues/1088"", ""label"": ""#1088""}, {""href"": ""https://github.com/simonw/datasette/issues/1084"", ""label"": ""#1084""}]"
changelog:id50,changelog,id50,0.49.1 (2020-09-15),Fixed a bug with writable canned queries that use magic parameters but accept no non-magic arguments. ( #967 ),"[""Changelog""]","[{""href"": ""https://github.com/simonw/datasette/issues/967"", ""label"": ""#967""}]"
changelog:id26,changelog,id26,0.59 (2021-10-14),"Columns can now have associated metadata descriptions in metadata.json , see Column descriptions . ( #942 )
New register_commands() plugin hook allows plugins to register additional Datasette CLI commands, e.g. datasette mycommand file.db . ( #1449 )
Adding ?_facet_size=max to a table page now shows the number of unique values in each facet. ( #1423 )
Upgraded dependency httpx 0.20 - the undocumented allow_redirects= parameter to datasette.client is now follow_redirects= , and defaults to False where it previously defaulted to True . ( #1488 )
The --cors option now causes Datasette to return the Access-Control-Allow-Headers: Authorization header, in addition to Access-Control-Allow-Origin: * . ( #1467 )
Code that figures out which named parameters a SQL query takes in order to display form fields for them is no longer confused by strings that contain colon characters. ( #1421 )
Renamed --help-config option to --help-settings . ( #1431 )
datasette.databases property is now a documented API. ( #1443 )
The base.html template now wraps everything other than the