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See here for the full documentation <https://getsentry.github.io/snuba-sdk/>
_.
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Snuba SDK is a tool that allows requests to Snuba to be built programatically. A Request consists of a Query, the dataset the Query is targeting, the AppID of the Request, and any flags for the Request. A Query object is a code representation of a SnQL or MQL query, and has a number of attributes corresponding to different parts of the query.
Requests and Queries can be created directly:
.. code-block:: python
request = Request(
dataset = "discover",
app_id = "myappid",
tenant_ids = {"referrer": "my_referrer", "organization_id": 1234}
query = Query(
match=Entity("events"),
select=[
Column("title"),
Function("uniq", [Column("event_id")], "uniq_events"),
],
groupby=[Column("title")],
where=[
Condition(Column("timestamp"), Op.GT, datetime.datetime(2021, 1, 1)),
Condition(Column("project_id"), Op.IN, Function("tuple", [1, 2, 3])),
],
limit=Limit(10),
offset=Offset(0),
granularity=Granularity(3600),
),
flags = Flags(debug=True)
)
Queries can also be built incrementally:
.. code-block:: python
query = (
Query("discover", Entity("events"))
.set_select(
[Column("title"), Function("uniq", [Column("event_id")], "uniq_events")]
)
.set_groupby([Column("title")])
.set_where(
[
Condition(Column("timestamp"), Op.GT, datetime.datetime.(2021, 1, 1)),
Condition(Column("project_id"), Op.IN, Function("tuple", [1, 2, 3])),
]
)
.set_limit(10)
.set_offset(0)
.set_granularity(3600)
)
Once the request is built, it can be translated into a Snuba request that can be sent to Snuba.
.. code-block:: python
# Outputs a formatted Snuba request
request.serialize()
It can also be printed in a more human readable format.
.. code-block:: python
# Outputs a formatted Snuba request
print(request.print())
This outputs:
.. code-block:: JSON
{
"dataset": "discover",
"app_id": "myappid",
"query": "MATCH (events) SELECT title, uniq(event_id) AS uniq_events BY title WHERE timestamp > toDateTime('2021-01-01T00:00:00.000000') AND project_id IN tuple(1, 2, 3) LIMIT 10 OFFSET 0 GRANULARITY 3600",
"debug": true
}
If an expression in the query is invalid (e.g. Column(1)
) then an InvalidExpressionError
exception will be thrown.
If there is a problem with a query, it will throw an InvalidQueryError
exception when .validate()
or .translate()
is called.
If there is a problem with the Request or the Flags, an InvalidRequestError
or InvalidFlagError
will be thrown respectively.
MQL queries can be built in a similar way to SnQL queries. However they use a MetricsQuery
object instead of a Query
object. The query
argument of a MetricsQuery
is either a Timeseries
or Formula
, which is a mathemtical formula of Timeseries
.
The other arguments to the MetricsQuery
are meta data about how to run the query, e.g. start/end timestamps, the granularity, limits etc.
.. code-block:: python
MetricsQuery(
query=Formula(
ArithmeticOperator.DIVIDE.value,
[
Timeseries(
metric=Metric(
public_name="transaction.duration",
),
aggregate="sum",
),
1000,
],
),
start=NOW,
end=NOW + timedelta(days=14),
rollup=Rollup(interval=3600, totals=None, granularity=3600),
scope=MetricsScope(
org_ids=[1], project_ids=[11], use_case_id="transactions"
),
limit=Limit(100),
offset=Offset(5),
)
Please refer to CONTRIBUTING.rst <https://github.com/getsentry/snuba-sdk/blob/master/CONTRIBUTING.rst>
_.
Licensed under FSL-1.0-Apache-2.0, see LICENSE.md <https://github.com/getsentry/snuba-sdk/blob/master/LICENSE.md>
_.
FAQs
Snuba SDK for generating SnQL queries.
We found that snuba-sdk demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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