count / group_by

count

Returns the number of records matching the filter.

n = await db.post.count()                           # total rows
n = await db.post.count(where={"published": True})  # filtered

Parameters

Parameter	Type	Description
where	dict	Filter conditions
take	int	Count only within a window of this size
skip	int	Skip this many rows before the window
select	dict[str, bool]	Count non-null values per field (returns dict)

Field-level counts

counts = await db.post.count(select={"title": True, "publishedAt": True})
# {"title": 42, "publishedAt": 17}
# publishedAt is lower because nullable rows are not counted

---

group_by

Groups records by one or more fields and computes aggregations.

results = await db.post.group_by(
    by=["authorId"],
    count={"_all": True},
    avg={"score": True},
    order_by={"_avg": {"score": "desc"}},
)
for row in results:
    print(row["authorId"], row["_count"]["_all"], row["_avg"]["score"])

Parameters

Parameter	Type	Description
by	list[str]	Fields to group by
where	dict	Filter applied before grouping
count	dict or True	Count records per group
avg	dict[str, bool]	Average of numeric fields
sum_	dict[str, bool]	Sum of numeric fields
min_	dict[str, bool]	Minimum value
max_	dict[str, bool]	Maximum value
order_by	dict or list[dict]	Sort the groups
take	int	Limit number of groups returned
skip	int	Skip this many groups

Return shape

Each item in the result list contains the group-by field values plus nested aggregation dicts:

{
    "authorId": 1,
    "_count": {"_all": 5},
    "_avg": {"score": 3.8},
    "_sum": {"score": 19.0},
}