html_url,issue_url,id,node_id,user,user_label,created_at,updated_at,author_association,body,reactions,issue,issue_label,performed_via_github_app
https://github.com/simonw/datasette/issues/448#issuecomment-969557008,https://api.github.com/repos/simonw/datasette/issues/448,969557008,IC_kwDOBm6k_c45ykQQ,9599,simonw,2021-11-16T00:56:09Z,2021-11-16T00:59:59Z,OWNER,"This looks like it might work:
```sql
with inner as (
select
*
from
ads_with_targets
where
:p0 in (
select
value
from
json_each([ads_with_targets].[target_names])
)
),
deduped_array_items as (
select
distinct j.value,
inner.*
from
json_each([inner].[target_names]) j
join inner
)
select
value,
count(*)
from
deduped_array_items
group by
value
order by
count(*) desc
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",440222719,_facet_array should work against views,
https://github.com/simonw/datasette/issues/448#issuecomment-969557972,https://api.github.com/repos/simonw/datasette/issues/448,969557972,IC_kwDOBm6k_c45ykfU,9599,simonw,2021-11-16T00:56:58Z,2021-11-16T00:56:58Z,OWNER,It uses a CTE which were introduced in SQLite 3.8 - and AWS Lambda Python 3.9 still provides 3.7 - but I've checked and I can use `pysqlite3-binary` to work around that there so I'm OK relying on CTEs for this.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",440222719,_facet_array should work against views,
https://github.com/simonw/datasette/issues/448#issuecomment-969572281,https://api.github.com/repos/simonw/datasette/issues/448,969572281,IC_kwDOBm6k_c45yn-5,9599,simonw,2021-11-16T01:05:11Z,2021-11-16T01:05:11Z,OWNER,"I tried this and it seems to work correctly:
```python
for source_and_config in self.get_configs():
config = source_and_config[""config""]
source = source_and_config[""source""]
column = config.get(""column"") or config[""simple""]
facet_sql = """"""
with inner as ({sql}),
deduped_array_items as (
select
distinct j.value,
inner.*
from
json_each([inner].{col}) j
join inner
)
select
value as value,
count(*) as count
from
deduped_array_items
group by
value
order by
count(*) desc limit {limit}
"""""".format(
col=escape_sqlite(column), sql=self.sql, limit=facet_size + 1
)
```
The queries are _very_ slow though - I had to bump up to 2s time limit even against only a view returning 3,499 rows.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",440222719,_facet_array should work against views,
https://github.com/simonw/datasette/issues/448#issuecomment-969578466,https://api.github.com/repos/simonw/datasette/issues/448,969578466,IC_kwDOBm6k_c45ypfi,9599,simonw,2021-11-16T01:08:29Z,2021-11-16T01:08:29Z,OWNER,Actually with the cache warmed up it looks like the facet query is taking 150ms which is good enough.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",440222719,_facet_array should work against views,
https://github.com/simonw/datasette/issues/448#issuecomment-969582098,https://api.github.com/repos/simonw/datasette/issues/448,969582098,IC_kwDOBm6k_c45yqYS,9599,simonw,2021-11-16T01:10:28Z,2021-11-16T01:10:28Z,OWNER,"Also note that this demo data is using a SQL view to create the JSON arrays - the view is defined as such:
```sql
CREATE VIEW ads_with_targets as
select
ads.*,
json_group_array(targets.name) as target_names
from
ads
join ad_targets on ad_targets.ad_id = ads.id
join targets on ad_targets.target_id = targets.id
group by
ad_targets.ad_id;
```
So running JSON faceting on top of that view is a pretty big ask!","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",440222719,_facet_array should work against views,
https://github.com/simonw/datasette/issues/1511#issuecomment-969600859,https://api.github.com/repos/simonw/datasette/issues/1511,969600859,IC_kwDOBm6k_c45yu9b,9599,simonw,2021-11-16T01:20:13Z,2021-11-16T01:20:13Z,OWNER,"See:
- #830","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1054246919,Review plugin hooks for Datasette 1.0,
https://github.com/simonw/datasette/issues/1012#issuecomment-969602825,https://api.github.com/repos/simonw/datasette/issues/1012,969602825,IC_kwDOBm6k_c45yvcJ,9599,simonw,2021-11-16T01:21:14Z,2021-11-16T01:21:14Z,OWNER,"I'd been wondering how to get new classifiers into Trove - thanks, I'll give this a go.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",718540751,For 1.0 update trove classifier in setup.py,
https://github.com/simonw/datasette/issues/1012#issuecomment-969613166,https://api.github.com/repos/simonw/datasette/issues/1012,969613166,IC_kwDOBm6k_c45yx9u,9599,simonw,2021-11-16T01:27:25Z,2021-11-16T01:27:25Z,OWNER,"Requested here:
- https://github.com/pypa/trove-classifiers/pull/85","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",718540751,For 1.0 update trove classifier in setup.py,
https://github.com/simonw/datasette/issues/1176#issuecomment-969616626,https://api.github.com/repos/simonw/datasette/issues/1176,969616626,IC_kwDOBm6k_c45yyzy,9599,simonw,2021-11-16T01:29:13Z,2021-11-16T01:29:13Z,OWNER,"I'm inclined to create a Sphinx reference documentation page for this, as I did for `sqlite-utils` here: https://sqlite-utils.datasette.io/en/stable/reference.html","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",779691739,"Policy on documenting ""public"" datasette.utils functions",
https://github.com/simonw/datasette/issues/448#issuecomment-969621662,https://api.github.com/repos/simonw/datasette/issues/448,969621662,IC_kwDOBm6k_c45y0Ce,9599,simonw,2021-11-16T01:32:04Z,2021-11-16T01:32:04Z,OWNER,"Tests are failing and I think it's because the facets come back in different orders, need a tie-breaker. https://github.com/simonw/datasette/runs/4219325197?check_suite_focus=true","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",440222719,_facet_array should work against views,
https://github.com/simonw/datasette/issues/1505#issuecomment-970188065,https://api.github.com/repos/simonw/datasette/issues/1505,970188065,IC_kwDOBm6k_c450-Uh,7094907,Segerberg,2021-11-16T11:40:52Z,2021-11-16T11:40:52Z,NONE,A suggestion is to have the option to choose an arbitrary delimiter (and quoting characters ),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1052247023,Datasette should have an option to output CSV with semicolons,
https://github.com/simonw/datasette/issues/1012#issuecomment-970266123,https://api.github.com/repos/simonw/datasette/issues/1012,970266123,IC_kwDOBm6k_c451RYL,45380,bollwyvl,2021-11-16T13:18:36Z,2021-11-16T13:18:36Z,CONTRIBUTOR,"Congratulations, looks like it went through! There was a bit of a hold-up
on the JupyterLab ones, but it's semi automated: a dependabot pr to
warehouse and a CI deploy, with a click in between.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",718540751,For 1.0 update trove classifier in setup.py,
https://github.com/simonw/datasette/issues/1509#issuecomment-970544733,https://api.github.com/repos/simonw/datasette/issues/1509,970544733,IC_kwDOBm6k_c452VZd,9599,simonw,2021-11-16T18:22:32Z,2021-11-16T18:22:32Z,OWNER,"This is mainly happening here:
- https://github.com/simonw/datasette/issues/782","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1054243511,Datasette 1.0 JSON API (and documentation),
https://github.com/simonw/datasette/issues/782#issuecomment-970553780,https://api.github.com/repos/simonw/datasette/issues/782,970553780,IC_kwDOBm6k_c452Xm0,9599,simonw,2021-11-16T18:30:51Z,2021-11-16T18:30:58Z,OWNER,"OK, I'm ready to start working on this today.
I'm going to go with a default representation that looks like this:
```json
{
""rows"": [
{""id"": 1, ""name"": ""One""},
{""id"": 2, ""name"": ""Two""}
],
""next_url"": null
}
```
Note that there's no `count` - all it provides is the current selection of results and an indication as to how the next can be retrieved (`null` if there are no more results).
I'll implement `?_extra=` to provide everything else.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",627794879,Redesign default .json format,
https://github.com/simonw/datasette/issues/782#issuecomment-970554697,https://api.github.com/repos/simonw/datasette/issues/782,970554697,IC_kwDOBm6k_c452X1J,9599,simonw,2021-11-16T18:32:03Z,2021-11-16T18:32:03Z,OWNER,"I'm going to take another look at this:
- https://github.com/simonw/datasette/issues/878","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",627794879,Redesign default .json format,
https://github.com/simonw/datasette/issues/878#issuecomment-970624197,https://api.github.com/repos/simonw/datasette/issues/878,970624197,IC_kwDOBm6k_c452ozF,9599,simonw,2021-11-16T19:49:05Z,2021-11-16T19:49:05Z,OWNER,"Here's the latest version of my weird dependency injection async class:
```python
import inspect
class AsyncMeta(type):
def __new__(cls, name, bases, attrs):
# Decorate any items that are 'async def' methods
_registry = {}
new_attrs = {""_registry"": _registry}
for key, value in attrs.items():
if inspect.iscoroutinefunction(value) and not value.__name__ == ""resolve"":
new_attrs[key] = make_method(value)
_registry[key] = new_attrs[key]
else:
new_attrs[key] = value
# Topological sort of _registry by parameter dependencies
graph = {
key: {
p for p in inspect.signature(method).parameters.keys()
if p != ""self"" and not p.startswith(""_"")
}
for key, method in _registry.items()
}
new_attrs[""_graph""] = graph
return super().__new__(cls, name, bases, new_attrs)
def make_method(method):
@wraps(method)
async def inner(self, **kwargs):
parameters = inspect.signature(method).parameters.keys()
# Any parameters not provided by kwargs are resolved from registry
to_resolve = [p for p in parameters if p not in kwargs and p != ""self""]
missing = [p for p in to_resolve if p not in self._registry]
assert (
not missing
), ""The following DI parameters could not be found in the registry: {}"".format(
missing
)
results = {}
results.update(kwargs)
results.update(await self.resolve(to_resolve))
return await method(self, **results)
return inner
bad = [0]
class AsyncBase(metaclass=AsyncMeta):
async def resolve(self, names):
print("" resolve({})"".format(names))
results = {}
# Resolve them in the correct order
ts = TopologicalSorter()
ts2 = TopologicalSorter()
print("" names = "", names)
print("" self._graph = "", self._graph)
for name in names:
if self._graph[name]:
ts.add(name, *self._graph[name])
ts2.add(name, *self._graph[name])
print("" static_order ="", tuple(ts2.static_order()))
ts.prepare()
while ts.is_active():
print("" is_active, i = "", bad[0])
bad[0] += 1
if bad[0] > 20:
print("" Infinite loop?"")
break
nodes = ts.get_ready()
print("" Do nodes:"", nodes)
awaitables = [self._registry[name](self, **{
k: v for k, v in results.items() if k in self._graph[name]
}) for name in nodes]
print("" awaitables: "", awaitables)
awaitable_results = await asyncio.gather(*awaitables)
results.update({
p[0].__name__: p[1] for p in zip(awaitables, awaitable_results)
})
print(results)
for node in nodes:
ts.done(node)
return results
```
Example usage:
```python
class Foo(AsyncBase):
async def graa(self, boff):
print(""graa"")
return 5
async def boff(self):
print(""boff"")
return 8
async def other(self, boff, graa):
print(""other"")
return 5 + boff + graa
foo = Foo()
await foo.other()
```
Output:
```
resolve(['boff', 'graa'])
names = ['boff', 'graa']
self._graph = {'graa': {'boff'}, 'boff': set(), 'other': {'graa', 'boff'}}
static_order = ('boff', 'graa')
is_active, i = 0
Do nodes: ('boff',)
awaitables: []
resolve([])
names = []
self._graph = {'graa': {'boff'}, 'boff': set(), 'other': {'graa', 'boff'}}
static_order = ()
boff
{'boff': 8}
is_active, i = 1
Do nodes: ('graa',)
awaitables: []
resolve([])
names = []
self._graph = {'graa': {'boff'}, 'boff': set(), 'other': {'graa', 'boff'}}
static_order = ()
graa
{'boff': 8, 'graa': 5}
other
18
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/issues/878#issuecomment-970655304,https://api.github.com/repos/simonw/datasette/issues/878,970655304,IC_kwDOBm6k_c452wZI,9599,simonw,2021-11-16T20:32:16Z,2021-11-16T20:32:16Z,OWNER,"This code is really fiddly. I just got to this version:
```python
import asyncio
from functools import wraps
import inspect
try:
import graphlib
except ImportError:
from . import vendored_graphlib as graphlib
class AsyncMeta(type):
def __new__(cls, name, bases, attrs):
# Decorate any items that are 'async def' methods
_registry = {}
new_attrs = {""_registry"": _registry}
for key, value in attrs.items():
if inspect.iscoroutinefunction(value) and not value.__name__ == ""resolve"":
new_attrs[key] = make_method(value)
_registry[key] = new_attrs[key]
else:
new_attrs[key] = value
# Gather graph for later dependency resolution
graph = {
key: {
p
for p in inspect.signature(method).parameters.keys()
if p != ""self"" and not p.startswith(""_"")
}
for key, method in _registry.items()
}
new_attrs[""_graph""] = graph
return super().__new__(cls, name, bases, new_attrs)
def make_method(method):
@wraps(method)
async def inner(self, _results=None, **kwargs):
print(""inner - _results="", _results)
parameters = inspect.signature(method).parameters.keys()
# Any parameters not provided by kwargs are resolved from registry
to_resolve = [p for p in parameters if p not in kwargs and p != ""self""]
missing = [p for p in to_resolve if p not in self._registry]
assert (
not missing
), ""The following DI parameters could not be found in the registry: {}"".format(
missing
)
results = {}
results.update(kwargs)
if to_resolve:
resolved_parameters = await self.resolve(to_resolve, _results)
results.update(resolved_parameters)
return_value = await method(self, **results)
if _results is not None:
_results[method.__name__] = return_value
return return_value
return inner
class AsyncBase(metaclass=AsyncMeta):
async def resolve(self, names, results=None):
print(""\n resolve: "", names)
if results is None:
results = {}
# Resolve them in the correct order
ts = graphlib.TopologicalSorter()
for name in names:
ts.add(name, *self._graph[name])
ts.prepare()
async def resolve_nodes(nodes):
print("" resolve_nodes"", nodes)
print("" (current results = {})"".format(repr(results)))
awaitables = [
self._registry[name](
self,
_results=results,
**{k: v for k, v in results.items() if k in self._graph[name]},
)
for name in nodes
if name not in results
]
print("" awaitables: "", awaitables)
awaitable_results = await asyncio.gather(*awaitables)
results.update(
{p[0].__name__: p[1] for p in zip(awaitables, awaitable_results)}
)
if not ts.is_active():
# Nothing has dependencies - just resolve directly
print("" no dependencies, resolve directly"")
await resolve_nodes(names)
else:
# Resolve in topological order
while ts.is_active():
nodes = ts.get_ready()
print("" ts.get_ready() returned nodes:"", nodes)
await resolve_nodes(nodes)
for node in nodes:
ts.done(node)
print("" End of resolve(), returning"", results)
return {key: value for key, value in results.items() if key in names}
```
With this test:
```python
class Complex(AsyncBase):
def __init__(self):
self.log = []
async def c(self):
print(""LOG: c"")
self.log.append(""c"")
async def b(self, c):
print(""LOG: b"")
self.log.append(""b"")
async def a(self, b, c):
print(""LOG: a"")
self.log.append(""a"")
async def go(self, a):
print(""LOG: go"")
self.log.append(""go"")
return self.log
@pytest.mark.asyncio
async def test_complex():
result = await Complex().go()
# 'c' should only be called once
assert result == [""c"", ""b"", ""a"", ""go""]
```
This test sometimes passes, and sometimes fails!
Output for a pass:
```
tests/test_asyncdi.py inner - _results= None
resolve: ['a']
ts.get_ready() returned nodes: ('c', 'b')
resolve_nodes ('c', 'b')
(current results = {})
awaitables: [, ]
inner - _results= {}
LOG: c
inner - _results= {'c': None}
resolve: ['c']
ts.get_ready() returned nodes: ('c',)
resolve_nodes ('c',)
(current results = {'c': None})
awaitables: []
End of resolve(), returning {'c': None}
LOG: b
ts.get_ready() returned nodes: ('a',)
resolve_nodes ('a',)
(current results = {'c': None, 'b': None})
awaitables: []
inner - _results= {'c': None, 'b': None}
LOG: a
End of resolve(), returning {'c': None, 'b': None, 'a': None}
LOG: go
```
Output for a fail:
```
tests/test_asyncdi.py inner - _results= None
resolve: ['a']
ts.get_ready() returned nodes: ('b', 'c')
resolve_nodes ('b', 'c')
(current results = {})
awaitables: [, ]
inner - _results= {}
resolve: ['c']
ts.get_ready() returned nodes: ('c',)
resolve_nodes ('c',)
(current results = {})
awaitables: []
inner - _results= {}
LOG: c
inner - _results= {'c': None}
LOG: c
End of resolve(), returning {'c': None}
LOG: b
ts.get_ready() returned nodes: ('a',)
resolve_nodes ('a',)
(current results = {'c': None, 'b': None})
awaitables: []
inner - _results= {'c': None, 'b': None}
LOG: a
End of resolve(), returning {'c': None, 'b': None, 'a': None}
LOG: go
F
=================================================================================================== FAILURES ===================================================================================================
_________________________________________________________________________________________________ test_complex _________________________________________________________________________________________________
@pytest.mark.asyncio
async def test_complex():
result = await Complex().go()
# 'c' should only be called once
> assert result == [""c"", ""b"", ""a"", ""go""]
E AssertionError: assert ['c', 'c', 'b', 'a', 'go'] == ['c', 'b', 'a', 'go']
E At index 1 diff: 'c' != 'b'
E Left contains one more item: 'go'
E Use -v to get the full diff
tests/test_asyncdi.py:48: AssertionError
================== short test summary info ================================
FAILED tests/test_asyncdi.py::test_complex - AssertionError: assert ['c', 'c', 'b', 'a', 'go'] == ['c', 'b', 'a', 'go']
```
I figured out why this is happening.
`a` requires `b` and `c`
`b` also requires `c`
The code decides to run `b` and `c` in parallel.
If `c` completes first, then when `b` runs it gets to use the already-calculated result for `c` - so it doesn't need to call `c` again.
If `b` gets to that point before `c` does it also needs to call `c`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/issues/878#issuecomment-970655927,https://api.github.com/repos/simonw/datasette/issues/878,970655927,IC_kwDOBm6k_c452wi3,9599,simonw,2021-11-16T20:33:11Z,2021-11-16T20:33:11Z,OWNER,"What should be happening here instead is it should resolve the full graph and notice that `c` is depended on by both `b` and `a` - so it should run `c` first, then run the next ones in parallel.
So maybe the algorithm I'm inheriting from https://docs.python.org/3/library/graphlib.html isn't the correct algorithm?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/issues/878#issuecomment-970657874,https://api.github.com/repos/simonw/datasette/issues/878,970657874,IC_kwDOBm6k_c452xBS,9599,simonw,2021-11-16T20:36:01Z,2021-11-16T20:36:01Z,OWNER,"My goal here is to calculate the most efficient way to resolve the different nodes, running them in parallel where possible.
So for this class:
```python
class Complex(AsyncBase):
async def d(self):
pass
async def c(self):
pass
async def b(self, c, d):
pass
async def a(self, b, c):
pass
async def go(self, a):
pass
```
A call to `go()` should do this:
- `c` and `d` in parallel
- `b`
- `a`
- `go`","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/issues/878#issuecomment-970660299,https://api.github.com/repos/simonw/datasette/issues/878,970660299,IC_kwDOBm6k_c452xnL,9599,simonw,2021-11-16T20:39:43Z,2021-11-16T20:42:27Z,OWNER,"But that does seem to be the plan that `TopographicalSorter` provides:
```python
graph = {""go"": {""a""}, ""a"": {""b"", ""c""}, ""b"": {""c"", ""d""}}
ts = TopologicalSorter(graph)
ts.prepare()
while ts.is_active():
nodes = ts.get_ready()
print(nodes)
ts.done(*nodes)
```
Outputs:
```
('c', 'd')
('b',)
('a',)
('go',)
```
Also:
```python
graph = {""go"": {""d"", ""e"", ""f""}, ""d"": {""b"", ""c""}, ""b"": {""c""}}
ts = TopologicalSorter(graph)
ts.prepare()
while ts.is_active():
nodes = ts.get_ready()
print(nodes)
ts.done(*nodes)
```
Gives:
```
('e', 'f', 'c')
('b',)
('d',)
('go',)
```
I'm confident that `TopologicalSorter` is the way to do this. I think I need to rewrite my code to call it once to get that plan, then `await asyncio.gather(*nodes)` in turn to execute it.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/issues/878#issuecomment-970673085,https://api.github.com/repos/simonw/datasette/issues/878,970673085,IC_kwDOBm6k_c4520u9,9599,simonw,2021-11-16T20:58:24Z,2021-11-16T20:58:24Z,OWNER,"New test:
```python
class Complex(AsyncBase):
def __init__(self):
self.log = []
async def d(self):
await asyncio.sleep(random() * 0.1)
print(""LOG: d"")
self.log.append(""d"")
async def c(self):
await asyncio.sleep(random() * 0.1)
print(""LOG: c"")
self.log.append(""c"")
async def b(self, c, d):
print(""LOG: b"")
self.log.append(""b"")
async def a(self, b, c):
print(""LOG: a"")
self.log.append(""a"")
async def go(self, a):
print(""LOG: go"")
self.log.append(""go"")
return self.log
@pytest.mark.asyncio
async def test_complex():
result = await Complex().go()
# 'c' should only be called once
assert tuple(result) in (
# c and d could happen in either order
(""c"", ""d"", ""b"", ""a"", ""go""),
(""d"", ""c"", ""b"", ""a"", ""go""),
)
```
And this code passes it:
```python
import asyncio
from functools import wraps
import inspect
try:
import graphlib
except ImportError:
from . import vendored_graphlib as graphlib
class AsyncMeta(type):
def __new__(cls, name, bases, attrs):
# Decorate any items that are 'async def' methods
_registry = {}
new_attrs = {""_registry"": _registry}
for key, value in attrs.items():
if inspect.iscoroutinefunction(value) and not value.__name__ == ""resolve"":
new_attrs[key] = make_method(value)
_registry[key] = new_attrs[key]
else:
new_attrs[key] = value
# Gather graph for later dependency resolution
graph = {
key: {
p
for p in inspect.signature(method).parameters.keys()
if p != ""self"" and not p.startswith(""_"")
}
for key, method in _registry.items()
}
new_attrs[""_graph""] = graph
return super().__new__(cls, name, bases, new_attrs)
def make_method(method):
parameters = inspect.signature(method).parameters.keys()
@wraps(method)
async def inner(self, _results=None, **kwargs):
print(""\n{}.{}({}) _results={}"".format(self, method.__name__, kwargs, _results))
# Any parameters not provided by kwargs are resolved from registry
to_resolve = [p for p in parameters if p not in kwargs and p != ""self""]
missing = [p for p in to_resolve if p not in self._registry]
assert (
not missing
), ""The following DI parameters could not be found in the registry: {}"".format(
missing
)
results = {}
results.update(kwargs)
if to_resolve:
resolved_parameters = await self.resolve(to_resolve, _results)
results.update(resolved_parameters)
return_value = await method(self, **results)
if _results is not None:
_results[method.__name__] = return_value
return return_value
return inner
class AsyncBase(metaclass=AsyncMeta):
async def resolve(self, names, results=None):
print(""\n resolve: "", names)
if results is None:
results = {}
# Come up with an execution plan, just for these nodes
ts = graphlib.TopologicalSorter()
to_do = set(names)
done = set()
while to_do:
item = to_do.pop()
dependencies = self._graph[item]
ts.add(item, *dependencies)
done.add(item)
# Add any not-done dependencies to the queue
to_do.update({k for k in dependencies if k not in done})
ts.prepare()
plan = []
while ts.is_active():
node_group = ts.get_ready()
plan.append(node_group)
ts.done(*node_group)
print(""plan:"", plan)
results = {}
for node_group in plan:
awaitables = [
self._registry[name](
self,
_results=results,
**{k: v for k, v in results.items() if k in self._graph[name]},
)
for name in node_group
]
print("" results = "", results)
print("" awaitables: "", awaitables)
awaitable_results = await asyncio.gather(*awaitables)
results.update(
{p[0].__name__: p[1] for p in zip(awaitables, awaitable_results)}
)
print("" End of resolve(), returning"", results)
return {key: value for key, value in results.items() if key in names}
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/issues/878#issuecomment-970705738,https://api.github.com/repos/simonw/datasette/issues/878,970705738,IC_kwDOBm6k_c4528tK,9599,simonw,2021-11-16T21:44:31Z,2021-11-16T21:44:31Z,OWNER,Wrote a TIL about what I learned using `TopologicalSorter`: https://til.simonwillison.net/python/graphlib-topologicalsorter,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/issues/878#issuecomment-970712713,https://api.github.com/repos/simonw/datasette/issues/878,970712713,IC_kwDOBm6k_c452-aJ,9599,simonw,2021-11-16T21:54:33Z,2021-11-16T21:54:33Z,OWNER,I'm going to continue working on this in a PR.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",648435885,"New pattern for views that return either JSON or HTML, available for plugins",
https://github.com/simonw/datasette/pull/1512#issuecomment-970718337,https://api.github.com/repos/simonw/datasette/issues/1512,970718337,IC_kwDOBm6k_c452_yB,9599,simonw,2021-11-16T22:02:30Z,2021-11-16T22:02:30Z,OWNER,"I've decided to make the clever `asyncio` dependency injection opt-in - so you can either decorate with `@inject` or you can set `inject_all = True` on the class - for example:
```python
import asyncio
from datasette.utils.asyncdi import AsyncBase, inject
class Simple(AsyncBase):
def __init__(self):
self.log = []
@inject
async def two(self):
self.log.append(""two"")
@inject
async def one(self, two):
self.log.append(""one"")
return self.log
async def not_inject(self, one, two):
return one + two
class Complex(AsyncBase):
inject_all = True
def __init__(self):
self.log = []
async def b(self):
self.log.append(""b"")
async def a(self, b):
self.log.append(""a"")
async def go(self, a):
self.log.append(""go"")
return self.log
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055402144,New pattern for async view classes,
https://github.com/simonw/datasette/pull/1512#issuecomment-970718652,https://api.github.com/repos/simonw/datasette/issues/1512,970718652,IC_kwDOBm6k_c452_28,22429695,codecov[bot],2021-11-16T22:02:59Z,2021-11-16T23:51:48Z,NONE,"# [Codecov](https://codecov.io/gh/simonw/datasette/pull/1512?src=pr&el=h1&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Simon+Willison) Report
> Merging [#1512](https://codecov.io/gh/simonw/datasette/pull/1512?src=pr&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Simon+Willison) (8f757da) into [main](https://codecov.io/gh/simonw/datasette/commit/0156c6b5e52d541e93f0d68e9245f20ae83bc933?el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Simon+Willison) (0156c6b) will **decrease** coverage by `2.10%`.
> The diff coverage is `36.20%`.
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```diff
@@ Coverage Diff @@
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==========================================
Files 34 36 +2
Lines 4430 4604 +174
==========================================
+ Hits 4068 4131 +63
- Misses 362 473 +111
```
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------
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> Powered by [Codecov](https://codecov.io/gh/simonw/datasette/pull/1512?src=pr&el=footer&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Simon+Willison). Last update [0156c6b...8f757da](https://codecov.io/gh/simonw/datasette/pull/1512?src=pr&el=lastupdated&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Simon+Willison). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=Simon+Willison).
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055402144,New pattern for async view classes,
https://github.com/simonw/datasette/issues/1513#issuecomment-970738130,https://api.github.com/repos/simonw/datasette/issues/1513,970738130,IC_kwDOBm6k_c453EnS,9599,simonw,2021-11-16T22:32:19Z,2021-11-16T22:32:19Z,OWNER,"I came up with the following query which seems to work!
```sql
with cte as (
select rowid, country, country_long, name, owner, primary_fuel
from [global-power-plants]
),
truncated as (
select null as _facet, null as facet_name, null as facet_count, rowid, country, country_long, name, owner, primary_fuel
from cte order by rowid limit 4
),
country_long_facet as (
select 'country_long' as _facet, country_long as facet_name, count(*) as facet_count,
null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
owner_facet as (
select 'owner' as _facet, owner as facet_name, count(*) as facet_count,
null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
primary_fuel_facet as (
select 'primary_fuel' as _facet, primary_fuel as facet_name, count(*) as facet_count,
null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
)
select * from truncated
union all select * from country_long_facet
union all select * from owner_facet
union all select * from primary_fuel_facet
```
(Limits should be 101, 31, 31, 31 but I reduced size to get a shorter example table).
Results [look like this](https://global-power-plants.datasettes.com/global-power-plants?sql=with+cte+as+%28%0D%0A++select+rowid%2C+country%2C+country_long%2C+name%2C+owner%2C+primary_fuel%0D%0A++from+%5Bglobal-power-plants%5D%0D%0A%29%2C%0D%0Atruncated+as+%28%0D%0A++select+null+as+_facet%2C+null+as+facet_name%2C+null+as+facet_count%2C+rowid%2C+country%2C+country_long%2C+name%2C+owner%2C+primary_fuel%0D%0A++from+cte+order+by+rowid+limit+4%0D%0A%29%2C%0D%0Acountry_long_facet+as+%28%0D%0A++select+%27country_long%27+as+_facet%2C+country_long+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Aowner_facet+as+%28%0D%0A++select+%27owner%27+as+_facet%2C+owner+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Aprimary_fuel_facet+as+%28%0D%0A++select+%27primary_fuel%27+as+_facet%2C+primary_fuel+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%0D%0Aselect+*+from+truncated%0D%0Aunion+all+select+*+from+country_long_facet%0D%0Aunion+all+select+*+from+owner_facet%0D%0Aunion+all+select+*+from+primary_fuel_facet):
_facet | facet_name | facet_count | rowid | country | country_long | name | owner | primary_fuel
-- | -- | -- | -- | -- | -- | -- | -- | --
| | | 1 | AFG | Afghanistan | Kajaki Hydroelectric Power Plant Afghanistan | | Hydro
| | | 2 | AFG | Afghanistan | Kandahar DOG | | Solar
| | | 3 | AFG | Afghanistan | Kandahar JOL | | Solar
| | | 4 | AFG | Afghanistan | Mahipar Hydroelectric Power Plant Afghanistan | | Hydro
country_long | United States of America | 8688 | | | | | |
country_long | China | 4235 | | | | | |
country_long | United Kingdom | 2603 | | | | | |
owner | | 14112 | | | | | |
owner | Lightsource Renewable Energy | 120 | | | | | |
owner | Cypress Creek Renewables | 109 | | | | | |
primary_fuel | Solar | 9662 | | | | | |
primary_fuel | Hydro | 7155 | | | | | |
primary_fuel | Wind | 5188 | | | | | |
This is a neat proof of concept. ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970742415,https://api.github.com/repos/simonw/datasette/issues/1513,970742415,IC_kwDOBm6k_c453FqP,9599,simonw,2021-11-16T22:37:14Z,2021-11-16T22:37:14Z,OWNER,"The query takes 42.794ms to run.
Here's the equivalent page using separate queries: https://global-power-plants.datasettes.com/global-power-plants/global-power-plants?_facet_size=3&_size=2&_nocount=1
Annoyingly I can't disable facet suggestions but keep facets.
I'm going to turn on tracing so I can see how long the separate queries took.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970758179,https://api.github.com/repos/simonw/datasette/issues/1513,970758179,IC_kwDOBm6k_c453Jgj,9599,simonw,2021-11-16T22:47:38Z,2021-11-16T22:47:38Z,OWNER,"Trace now enabled: https://global-power-plants.datasettes.com/global-power-plants/global-power-plants?_facet_size=3&_size=2&_nocount=1&_trace=1
Here are the relevant traces:
```json
[
{
""type"": ""sql"",
""start"": 31.214430154,
""end"": 31.214817089,
""duration_ms"": 0.3869350000016425,
""traceback"": [
"" File \""/usr/local/lib/python3.8/site-packages/datasette/views/base.py\"", line 262, in get\n return await self.view_get(\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/views/base.py\"", line 477, in view_get\n response_or_template_contexts = await self.data(\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/views/table.py\"", line 705, in data\n results = await db.execute(sql, params, truncate=True, **extra_args)\n""
],
""database"": ""global-power-plants"",
""sql"": ""select rowid, country, country_long, name, gppd_idnr, capacity_mw, latitude, longitude, primary_fuel, other_fuel1, other_fuel2, other_fuel3, commissioning_year, owner, source, url, geolocation_source, wepp_id, year_of_capacity_data, generation_gwh_2013, generation_gwh_2014, generation_gwh_2015, generation_gwh_2016, generation_gwh_2017, generation_data_source, estimated_generation_gwh from [global-power-plants] order by rowid limit 3"",
""params"": {}
},
{
""type"": ""sql"",
""start"": 31.215234586,
""end"": 31.220110342,
""duration_ms"": 4.875756000000564,
""traceback"": [
"" File \""/usr/local/lib/python3.8/site-packages/datasette/views/table.py\"", line 760, in data\n ) = await facet.facet_results()\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/facets.py\"", line 212, in facet_results\n facet_rows_results = await self.ds.execute(\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/app.py\"", line 634, in execute\n return await self.databases[db_name].execute(\n""
],
""database"": ""global-power-plants"",
""sql"": ""select country_long as value, count(*) as count from (\n select rowid, country, country_long, name, gppd_idnr, capacity_mw, latitude, longitude, primary_fuel, other_fuel1, other_fuel2, other_fuel3, commissioning_year, owner, source, url, geolocation_source, wepp_id, year_of_capacity_data, generation_gwh_2013, generation_gwh_2014, generation_gwh_2015, generation_gwh_2016, generation_gwh_2017, generation_data_source, estimated_generation_gwh from [global-power-plants] \n )\n where country_long is not null\n group by country_long order by count desc, value limit 4"",
""params"": []
},
{
""type"": ""sql"",
""start"": 31.221062485,
""end"": 31.228968364,
""duration_ms"": 7.905878999999061,
""traceback"": [
"" File \""/usr/local/lib/python3.8/site-packages/datasette/views/table.py\"", line 760, in data\n ) = await facet.facet_results()\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/facets.py\"", line 212, in facet_results\n facet_rows_results = await self.ds.execute(\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/app.py\"", line 634, in execute\n return await self.databases[db_name].execute(\n""
],
""database"": ""global-power-plants"",
""sql"": ""select owner as value, count(*) as count from (\n select rowid, country, country_long, name, gppd_idnr, capacity_mw, latitude, longitude, primary_fuel, other_fuel1, other_fuel2, other_fuel3, commissioning_year, owner, source, url, geolocation_source, wepp_id, year_of_capacity_data, generation_gwh_2013, generation_gwh_2014, generation_gwh_2015, generation_gwh_2016, generation_gwh_2017, generation_data_source, estimated_generation_gwh from [global-power-plants] \n )\n where owner is not null\n group by owner order by count desc, value limit 4"",
""params"": []
},
{
""type"": ""sql"",
""start"": 31.229809757,
""end"": 31.253902162,
""duration_ms"": 24.09240499999754,
""traceback"": [
"" File \""/usr/local/lib/python3.8/site-packages/datasette/views/table.py\"", line 760, in data\n ) = await facet.facet_results()\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/facets.py\"", line 212, in facet_results\n facet_rows_results = await self.ds.execute(\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/app.py\"", line 634, in execute\n return await self.databases[db_name].execute(\n""
],
""database"": ""global-power-plants"",
""sql"": ""select primary_fuel as value, count(*) as count from (\n select rowid, country, country_long, name, gppd_idnr, capacity_mw, latitude, longitude, primary_fuel, other_fuel1, other_fuel2, other_fuel3, commissioning_year, owner, source, url, geolocation_source, wepp_id, year_of_capacity_data, generation_gwh_2013, generation_gwh_2014, generation_gwh_2015, generation_gwh_2016, generation_gwh_2017, generation_data_source, estimated_generation_gwh from [global-power-plants] \n )\n where primary_fuel is not null\n group by primary_fuel order by count desc, value limit 4"",
""params"": []
},
{
""type"": ""sql"",
""start"": 31.255699745,
""end"": 31.256243889,
""duration_ms"": 0.544143999999136,
""traceback"": [
"" File \""/usr/local/lib/python3.8/site-packages/datasette/facets.py\"", line 145, in suggest\n row_count = await self.get_row_count()\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/facets.py\"", line 132, in get_row_count\n await self.ds.execute(\n"",
"" File \""/usr/local/lib/python3.8/site-packages/datasette/app.py\"", line 634, in execute\n return await self.databases[db_name].execute(\n""
],
""database"": ""global-power-plants"",
""sql"": ""select count(*) from (select rowid, country, country_long, name, gppd_idnr, capacity_mw, latitude, longitude, primary_fuel, other_fuel1, other_fuel2, other_fuel3, commissioning_year, owner, source, url, geolocation_source, wepp_id, year_of_capacity_data, generation_gwh_2013, generation_gwh_2014, generation_gwh_2015, generation_gwh_2016, generation_gwh_2017, generation_data_source, estimated_generation_gwh from [global-power-plants] )"",
""params"": []
}
]
```
```
fetch rows: 0.3869350000016425 ms
facet country_long: 4.875756000000564 ms
facet owner: 7.905878999999061 ms
facet primary_fuel: 24.09240499999754 ms
count: 0.544143999999136 ms
```
Total = 37.8ms
I modified the query to include the total count as well: https://global-power-plants.datasettes.com/global-power-plants?sql=with+cte+as+%28%0D%0A++select+rowid%2C+country%2C+country_long%2C+name%2C+owner%2C+primary_fuel%0D%0A++from+%5Bglobal-power-plants%5D%0D%0A%29%2C%0D%0Atruncated+as+%28%0D%0A++select+null+as+_facet%2C+null+as+facet_name%2C+null+as+facet_count%2C+rowid%2C+country%2C+country_long%2C+name%2C+owner%2C+primary_fuel%0D%0A++from+cte+order+by+rowid+limit+4%0D%0A%29%2C%0D%0Acountry_long_facet+as+%28%0D%0A++select+%27country_long%27+as+_facet%2C+country_long+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Aowner_facet+as+%28%0D%0A++select+%27owner%27+as+_facet%2C+owner+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Aprimary_fuel_facet+as+%28%0D%0A++select+%27primary_fuel%27+as+_facet%2C+primary_fuel+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Atotal_count+as+%28%0D%0A++select+%27COUNT%27+as+_facet%2C+%27%27+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte%0D%0A%29%0D%0Aselect+*+from+truncated%0D%0Aunion+all+select+*+from+country_long_facet%0D%0Aunion+all+select+*+from+owner_facet%0D%0Aunion+all+select+*+from+primary_fuel_facet%0D%0Aunion+all+select+*+from+total_count&_trace=1
```sql
with cte as (
select rowid, country, country_long, name, owner, primary_fuel
from [global-power-plants]
),
truncated as (
select null as _facet, null as facet_name, null as facet_count, rowid, country, country_long, name, owner, primary_fuel
from cte order by rowid limit 4
),
country_long_facet as (
select 'country_long' as _facet, country_long as facet_name, count(*) as facet_count,
null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
owner_facet as (
select 'owner' as _facet, owner as facet_name, count(*) as facet_count,
null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
primary_fuel_facet as (
select 'primary_fuel' as _facet, primary_fuel as facet_name, count(*) as facet_count,
null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
total_count as (
select 'COUNT' as _facet, '' as facet_name, count(*) as facet_count,
null, null, null, null, null, null
from cte
)
select * from truncated
union all select * from country_long_facet
union all select * from owner_facet
union all select * from primary_fuel_facet
union all select * from total_count
```
The trace says that query took 34.801436999998714 ms.
To my huge surprise, this convoluted optimization only shaves the sum query time down from 37.8ms to 34.8ms!
That entire database file is just 11.1 MB though. Maybe it would make a meaningful difference on something larger?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970766486,https://api.github.com/repos/simonw/datasette/issues/1513,970766486,IC_kwDOBm6k_c453LiW,9599,simonw,2021-11-16T22:52:56Z,2021-11-16T22:56:07Z,OWNER,"https://covid-19.datasettes.com/covid is 805.2MB
https://covid-19.datasettes.com/covid/ny_times_us_counties?_trace=1&_facet_size=3&_size=2
Equivalent SQL:
https://covid-19.datasettes.com/covid?sql=with+cte+as+%28%0D%0A++select+rowid%2C+date%2C+county%2C+state%2C+fips%2C+cases%2C+deaths%0D%0A++from+ny_times_us_counties%0D%0A%29%2C%0D%0Atruncated+as+%28%0D%0A++select+null+as+_facet%2C+null+as+facet_name%2C+null+as+facet_count%2C+rowid%2C+date%2C+county%2C+state%2C+fips%2C+cases%2C+deaths%0D%0A++from+cte+order+by+date+desc+limit+4%0D%0A%29%2C%0D%0Astate_facet+as+%28%0D%0A++select+%27state%27+as+_facet%2C+state+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Afips_facet+as+%28%0D%0A++select+%27fips%27+as+_facet%2C+fips+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Acounty_facet+as+%28%0D%0A++select+%27county%27+as+_facet%2C+county+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A%29%2C%0D%0Atotal_count+as+%28%0D%0A++select+%27COUNT%27+as+_facet%2C+%27%27+as+facet_name%2C+count%28*%29+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte%0D%0A%29%0D%0Aselect+*+from+truncated%0D%0Aunion+all+select+*+from+state_facet%0D%0Aunion+all+select+*+from+fips_facet%0D%0Aunion+all+select+*+from+county_facet%0D%0Aunion+all+select+*+from+total_count
```sql
with cte as (
select rowid, date, county, state, fips, cases, deaths
from ny_times_us_counties
),
truncated as (
select null as _facet, null as facet_name, null as facet_count, rowid, date, county, state, fips, cases, deaths
from cte order by date desc limit 4
),
state_facet as (
select 'state' as _facet, state as facet_name, count(*) as facet_count,
null, null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
fips_facet as (
select 'fips' as _facet, fips as facet_name, count(*) as facet_count,
null, null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
county_facet as (
select 'county' as _facet, county as facet_name, count(*) as facet_count,
null, null, null, null, null, null, null
from cte group by facet_name order by facet_count desc limit 3
),
total_count as (
select 'COUNT' as _facet, '' as facet_name, count(*) as facet_count,
null, null, null, null, null, null, null
from cte
)
select * from truncated
union all select * from state_facet
union all select * from fips_facet
union all select * from county_facet
union all select * from total_count
```
_facet | facet_name | facet_count | rowid | date | county | state | fips | cases | deaths
-- | -- | -- | -- | -- | -- | -- | -- | -- | --
| | | 1917344 | 2021-11-15 | Autauga | Alabama | 1001 | 10407 | 154
| | | 1917345 | 2021-11-15 | Baldwin | Alabama | 1003 | 37875 | 581
| | | 1917346 | 2021-11-15 | Barbour | Alabama | 1005 | 3648 | 79
| | | 1917347 | 2021-11-15 | Bibb | Alabama | 1007 | 4317 | 92
state | Texas | 148028 | | | | | | |
state | Georgia | 96249 | | | | | | |
state | Virginia | 79315 | | | | | | |
fips | | 17580 | | | | | | |
fips | 53061 | 665 | | | | | | |
fips | 17031 | 662 | | | | | | |
county | Washington | 18666 | | | | | | |
county | Unknown | 15840 | | | | | | |
county | Jefferson | 15637 | | | | | | |
COUNT | | 1920593 | | | | | | | ","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970767952,https://api.github.com/repos/simonw/datasette/issues/1513,970767952,IC_kwDOBm6k_c453L5Q,9599,simonw,2021-11-16T22:53:52Z,2021-11-16T22:53:52Z,OWNER,It's going to take another 15 minutes for the build to finish and deploy the version with `_trace=1`: https://github.com/simonw/covid-19-datasette/actions/runs/1469150112,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970770304,https://api.github.com/repos/simonw/datasette/issues/1513,970770304,IC_kwDOBm6k_c453MeA,9599,simonw,2021-11-16T22:55:19Z,2021-11-16T22:55:19Z,OWNER,(One thing I really like about this pattern is that it should work exactly the same when used to facet the results of arbitrary SQL queries as it does when faceting results from the table page.),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970780866,https://api.github.com/repos/simonw/datasette/issues/1513,970780866,IC_kwDOBm6k_c453PDC,9599,simonw,2021-11-16T23:01:57Z,2021-11-16T23:01:57Z,OWNER,"One disadvantage to this approach: if you have a SQL time limit of 1s and it takes 0.9s to return the rows but then 0.5s to calculate each of the requested facets the entire query will exceed the time limit.
Could work around this by catching that error and then re-running the query just for the rows, but that would result in the user having to wait longer for the results.
Could try to remember if that has happened using an in-memory Python data structure and skip the faceting optimization if it's caused problems in the past? That seems a bit gross.
Maybe this becomes an opt-in optimization you can request in your `metadata.json` setting for that table, which massively increases the time limit? That's a bit weird too - now there are two separate implementations of the faceting logic, which had better have a REALLY big pay-off to be worth maintaining.
What if we kept the query that returns the rows to be displayed on the page separate from the facets, but then executed all of the facets together using this method such that the `cte` only (presumably) has to be calculated once? That would still lead to multiple facets potentially exceeding the SQL time limit when single facets would not have.
Maybe a better optimization would be to move facets to happening via `fetch()` calls from the client, so the user gets to see their rows instantly and the facets then appear as and when they are available (though it would cause page jank).
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970827674,https://api.github.com/repos/simonw/datasette/issues/1513,970827674,IC_kwDOBm6k_c453aea,9599,simonw,2021-11-16T23:26:58Z,2021-11-16T23:26:58Z,OWNER,"With trace.
https://covid-19.datasettes.com/covid/ny_times_us_counties?_trace=1&_facet_size=3&_size=2&_trace=1 shows the following:
```
fetch rows: 0.41762600005768036 ms
facet state: 284.30423800000426 ms
facet county: 273.2565999999679 ms
facet fips: 197.80996999998024 ms
```
= 755.78843400001ms total
It didn't run a count because that's the homepage and the count is cached. So I dropped the count from the query and ran it:
https://covid-19.datasettes.com/covid?sql=with+cte+as+(%0D%0A++select+rowid%2C+date%2C+county%2C+state%2C+fips%2C+cases%2C+deaths%0D%0A++from+ny_times_us_counties%0D%0A)%2C%0D%0Atruncated+as+(%0D%0A++select+null+as+_facet%2C+null+as+facet_name%2C+null+as+facet_count%2C+rowid%2C+date%2C+county%2C+state%2C+fips%2C+cases%2C+deaths%0D%0A++from+cte+order+by+date+desc+limit+4%0D%0A)%2C%0D%0Astate_facet+as+(%0D%0A++select+%27state%27+as+_facet%2C+state+as+facet_name%2C+count(*)+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A)%2C%0D%0Afips_facet+as+(%0D%0A++select+%27fips%27+as+_facet%2C+fips+as+facet_name%2C+count(*)+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A)%2C%0D%0Acounty_facet+as+(%0D%0A++select+%27county%27+as+_facet%2C+county+as+facet_name%2C+count(*)+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A)%0D%0Aselect+*+from+truncated%0D%0Aunion+all+select+*+from+state_facet%0D%0Aunion+all+select+*+from+fips_facet%0D%0Aunion+all+select+*+from+county_facet&_trace=1
Shows 649.4359889999259 ms for the query - compared to 755.78843400001ms for the separate. So it saved about 100ms.
Still not a huge difference though!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970828568,https://api.github.com/repos/simonw/datasette/issues/1513,970828568,IC_kwDOBm6k_c453asY,9599,simonw,2021-11-16T23:27:11Z,2021-11-16T23:27:11Z,OWNER,One last experiment: I'm going to try running an expensive query in the CTE portion.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970845844,https://api.github.com/repos/simonw/datasette/issues/1513,970845844,IC_kwDOBm6k_c453e6U,9599,simonw,2021-11-16T23:35:38Z,2021-11-16T23:35:38Z,OWNER,"I tried adding `cases > 10000` but the SQL query now takes too long - so moving this to my laptop.
```
cd /tmp
wget https://covid-19.datasettes.com/covid.db
datasette covid.db \
--setting facet_time_limit_ms 10000 \
--setting sql_time_limit_ms 10000 \
--setting trace_debug 1
```
`http://127.0.0.1:8006/covid/ny_times_us_counties?_trace=1&_facet_size=3&_size=2&cases__gt=10000` shows in the traces:
```json
[
{
""type"": ""sql"",
""start"": 12.693033525,
""end"": 12.694056904,
""duration_ms"": 1.0233789999993803,
""traceback"": [
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/base.py\"", line 262, in get\n return await self.view_get(\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/base.py\"", line 477, in view_get\n response_or_template_contexts = await self.data(\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/table.py\"", line 705, in data\n results = await db.execute(sql, params, truncate=True, **extra_args)\n""
],
""database"": ""covid"",
""sql"": ""select rowid, date, county, state, fips, cases, deaths from ny_times_us_counties where \""cases\"" > :p0 order by rowid limit 3"",
""params"": {
""p0"": 10000
}
},
{
""type"": ""sql"",
""start"": 12.694285093,
""end"": 12.814936275,
""duration_ms"": 120.65118200000136,
""traceback"": [
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/base.py\"", line 262, in get\n return await self.view_get(\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/base.py\"", line 477, in view_get\n response_or_template_contexts = await self.data(\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/table.py\"", line 723, in data\n count_rows = list(await db.execute(count_sql, from_sql_params))\n""
],
""database"": ""covid"",
""sql"": ""select count(*) from ny_times_us_counties where \""cases\"" > :p0"",
""params"": {
""p0"": 10000
}
},
{
""type"": ""sql"",
""start"": 12.818812089,
""end"": 12.851172544,
""duration_ms"": 32.360455000000954,
""traceback"": [
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/table.py\"", line 856, in data\n suggested_facets.extend(await facet.suggest())\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/facets.py\"", line 164, in suggest\n distinct_values = await self.ds.execute(\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/app.py\"", line 634, in execute\n return await self.databases[db_name].execute(\n""
],
""database"": ""covid"",
""sql"": ""select county, count(*) as n from (\n select rowid, date, county, state, fips, cases, deaths from ny_times_us_counties where \""cases\"" > :p0 \n ) where county is not null\n group by county\n limit 4"",
""params"": {
""p0"": 10000
}
},
{
""type"": ""sql"",
""start"": 12.851418868,
""end"": 12.871268359,
""duration_ms"": 19.84949100000044,
""traceback"": [
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/table.py\"", line 856, in data\n suggested_facets.extend(await facet.suggest())\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/facets.py\"", line 164, in suggest\n distinct_values = await self.ds.execute(\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/app.py\"", line 634, in execute\n return await self.databases[db_name].execute(\n""
],
""database"": ""covid"",
""sql"": ""select state, count(*) as n from (\n select rowid, date, county, state, fips, cases, deaths from ny_times_us_counties where \""cases\"" > :p0 \n ) where state is not null\n group by state\n limit 4"",
""params"": {
""p0"": 10000
}
},
{
""type"": ""sql"",
""start"": 12.871497655,
""end"": 12.897715027,
""duration_ms"": 26.217371999999628,
""traceback"": [
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/views/table.py\"", line 856, in data\n suggested_facets.extend(await facet.suggest())\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/facets.py\"", line 164, in suggest\n distinct_values = await self.ds.execute(\n"",
"" File \""/usr/local/Cellar/datasette/0.58.1/libexec/lib/python3.9/site-packages/datasette/app.py\"", line 634, in execute\n return await self.databases[db_name].execute(\n""
],
""database"": ""covid"",
""sql"": ""select fips, count(*) as n from (\n select rowid, date, county, state, fips, cases, deaths from ny_times_us_counties where \""cases\"" > :p0 \n ) where fips is not null\n group by fips\n limit 4"",
""params"": {
""p0"": 10000
}
}
]
```
So that's:
```
fetch rows: 1.0233789999993803 ms
count: 120.65118200000136 ms
facet county: 32.360455000000954 ms
facet state: 19.84949100000044 ms
facet fips: 26.217371999999628 ms
```
= 200.1 ms total
Compared to: `http://127.0.0.1:8006/covid?sql=with+cte+as+(%0D%0A++select+rowid%2C+date%2C+county%2C+state%2C+fips%2C+cases%2C+deaths%0D%0A++from+ny_times_us_counties%0D%0A)%2C%0D%0Atruncated+as+(%0D%0A++select+null+as+_facet%2C+null+as+facet_name%2C+null+as+facet_count%2C+rowid%2C+date%2C+county%2C+state%2C+fips%2C+cases%2C+deaths%0D%0A++from+cte+order+by+date+desc+limit+4%0D%0A)%2C%0D%0Astate_facet+as+(%0D%0A++select+%27state%27+as+_facet%2C+state+as+facet_name%2C+count(*)+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A)%2C%0D%0Afips_facet+as+(%0D%0A++select+%27fips%27+as+_facet%2C+fips+as+facet_name%2C+count(*)+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A)%2C%0D%0Acounty_facet+as+(%0D%0A++select+%27county%27+as+_facet%2C+county+as+facet_name%2C+count(*)+as+facet_count%2C%0D%0A++null%2C+null%2C+null%2C+null%2C+null%2C+null%2C+null%0D%0A++from+cte+group+by+facet_name+order+by+facet_count+desc+limit+3%0D%0A)%0D%0Aselect+*+from+truncated%0D%0Aunion+all+select+*+from+state_facet%0D%0Aunion+all+select+*+from+fips_facet%0D%0Aunion+all+select+*+from+county_facet&_trace=1`
Which is 353ms total.
The separate queries ran faster! Really surprising result there.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",1055469073,Research: CTEs and union all to calculate facets AND query at the same time,
https://github.com/simonw/datasette/issues/1513#issuecomment-970853917,https://api.github.com/repos/simonw/datasette/issues/1513,970853917,IC_kwDOBm6k_c453g4d,9599,simonw,2021-11-16T23:41:01Z,2021-11-16T23:41:01Z,OWNER,"One very interesting difference between the two: on the single giant query page:
```json
{
""request_duration_ms"": 376.4317020000476,
""sum_trace_duration_ms"": 370.0828700000329,
""num_traces"": 5
}
```
And on the page that uses separate queries:
```json
{
""request_duration_ms"": 819.012272000009,
""sum_trace_duration_ms"": 201.52852100000018,
""num_traces"": 19
}
```
The separate pages page takes 819ms total to render the page, but spends 201ms across 19 SQL queries.
The single big query takes 376ms total to render the page, spending 370ms in 5 queries
Those 5 queries, if you're interested
```sql
select database_name, schema_version from databases
PRAGMA schema_version
PRAGMA schema_version
explain with cte as (\r\n select rowid, date, county, state, fips, cases, deaths\r\n from ny_times_us_counties\r\n),\r\ntruncated as (\r\n select null as _facet, null as facet_name, null as facet_count, rowid, date, county, state, fips, cases, deaths\r\n from cte order by date desc limit 4\r\n),\r\nstate_facet as (\r\n select 'state' as _facet, state as facet_name, count(*) as facet_count,\r\n null, null, null, null, null, null, null\r\n from cte group by facet_name order by facet_count desc limit 3\r\n),\r\nfips_facet as (\r\n select 'fips' as _facet, fips as facet_name, count(*) as facet_count,\r\n null, null, null, null, null, null, null\r\n from cte group by facet_name order by facet_count desc limit 3\r\n),\r\ncounty_facet as (\r\n select 'county' as _facet, county as facet_name, count(*) as facet_count,\r\n null, null, null, null, null, null, null\r\n from cte group by facet_name order by facet_count desc limit 3\r\n)\r\nselect * from truncated\r\nunion all select * from state_facet\r\nunion all select * from fips_facet\r\nunion all select * from county_facet
with cte as (\r\n select rowid, date, county, state, fips, cases, deaths\r\n from ny_times_us_counties\r\n),\r\ntruncated as (\r\n select null as _facet, null as facet_name, null as facet_count, rowid, date, county, state, fips, cases, deaths\r\n from cte order by date desc limit 4\r\n),\r\nstate_facet as (\r\n select 'state' as _facet, state as facet_name, count(*) as facet_count,\r\n null, null, null, null, null, null, null\r\n from cte group by facet_name order by facet_count desc limit 3\r\n),\r\nfips_facet as (\r\n select 'fips' as _facet, fips as facet_name, count(*) as facet_count,\r\n null, null, null, null, null, null, null\r\n from cte group by facet_name order by facet_count desc limit 3\r\n),\r\ncounty_facet as (\r\n select 'county' as _facet, county as facet_name, count(*) as facet_count,\r\n null, null, null, null, null, null, null\r\n from cte group by facet_name order by facet_count desc limit 3\r\n)\r\nselect * from truncated\r\nunion all select * from state_facet\r\nunion all select * from fips_facet\r\nunion all select * from county_facet
```