1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
|
from __future__ import annotations
from functools import lru_cache
from typing import TYPE_CHECKING, Any
import duckdb
from narwhals._utils import Version, isinstance_or_issubclass
if TYPE_CHECKING:
from duckdb import DuckDBPyRelation, Expression
from duckdb.typing import DuckDBPyType
from narwhals._duckdb.dataframe import DuckDBLazyFrame
from narwhals._duckdb.expr import DuckDBExpr
from narwhals.dtypes import DType
from narwhals.typing import IntoDType
UNITS_DICT = {
"y": "year",
"q": "quarter",
"mo": "month",
"d": "day",
"h": "hour",
"m": "minute",
"s": "second",
"ms": "millisecond",
"us": "microsecond",
"ns": "nanosecond",
}
col = duckdb.ColumnExpression
"""Alias for `duckdb.ColumnExpression`."""
lit = duckdb.ConstantExpression
"""Alias for `duckdb.ConstantExpression`."""
when = duckdb.CaseExpression
"""Alias for `duckdb.CaseExpression`."""
def concat_str(*exprs: Expression, separator: str = "") -> Expression:
"""Concatenate many strings, NULL inputs are skipped.
Wraps [concat] and [concat_ws] `FunctionExpression`(s).
Arguments:
exprs: Native columns.
separator: String that will be used to separate the values of each column.
Returns:
A new native expression.
[concat]: https://duckdb.org/docs/stable/sql/functions/char.html#concatstring-
[concat_ws]: https://duckdb.org/docs/stable/sql/functions/char.html#concat_wsseparator-string-
"""
return (
duckdb.FunctionExpression("concat_ws", lit(separator), *exprs)
if separator
else duckdb.FunctionExpression("concat", *exprs)
)
def evaluate_exprs(
df: DuckDBLazyFrame, /, *exprs: DuckDBExpr
) -> list[tuple[str, Expression]]:
native_results: list[tuple[str, Expression]] = []
for expr in exprs:
native_series_list = expr._call(df)
output_names = expr._evaluate_output_names(df)
if expr._alias_output_names is not None:
output_names = expr._alias_output_names(output_names)
if len(output_names) != len(native_series_list): # pragma: no cover
msg = f"Internal error: got output names {output_names}, but only got {len(native_series_list)} results"
raise AssertionError(msg)
native_results.extend(zip(output_names, native_series_list))
return native_results
class DeferredTimeZone:
"""Object which gets passed between `native_to_narwhals_dtype` calls.
DuckDB stores the time zone in the connection, rather than in the dtypes, so
this ensures that when calculating the schema of a dataframe with multiple
timezone-aware columns, that the connection's time zone is only fetched once.
Note: we cannot make the time zone a cached `DuckDBLazyFrame` property because
the time zone can be modified after `DuckDBLazyFrame` creation:
```python
df = nw.from_native(rel)
print(df.collect_schema())
rel.query("set timezone = 'Asia/Kolkata'")
print(df.collect_schema()) # should change to reflect new time zone
```
"""
_cached_time_zone: str | None = None
def __init__(self, rel: DuckDBPyRelation) -> None:
self._rel = rel
@property
def time_zone(self) -> str:
"""Fetch relation time zone (if it wasn't calculated already)."""
if self._cached_time_zone is None:
self._cached_time_zone = fetch_rel_time_zone(self._rel)
return self._cached_time_zone
def native_to_narwhals_dtype(
duckdb_dtype: DuckDBPyType, version: Version, deferred_time_zone: DeferredTimeZone
) -> DType:
duckdb_dtype_id = duckdb_dtype.id
dtypes = version.dtypes
# Handle nested data types first
if duckdb_dtype_id == "list":
return dtypes.List(
native_to_narwhals_dtype(duckdb_dtype.child, version, deferred_time_zone)
)
if duckdb_dtype_id == "struct":
children = duckdb_dtype.children
return dtypes.Struct(
[
dtypes.Field(
name=child[0],
dtype=native_to_narwhals_dtype(child[1], version, deferred_time_zone),
)
for child in children
]
)
if duckdb_dtype_id == "array":
child, size = duckdb_dtype.children
shape: list[int] = [size[1]]
while child[1].id == "array":
child, size = child[1].children
shape.insert(0, size[1])
inner = native_to_narwhals_dtype(child[1], version, deferred_time_zone)
return dtypes.Array(inner=inner, shape=tuple(shape))
if duckdb_dtype_id == "enum":
if version is Version.V1:
return dtypes.Enum() # type: ignore[call-arg]
categories = duckdb_dtype.children[0][1]
return dtypes.Enum(categories=categories)
if duckdb_dtype_id == "timestamp with time zone":
return dtypes.Datetime(time_zone=deferred_time_zone.time_zone)
return _non_nested_native_to_narwhals_dtype(duckdb_dtype_id, version)
def fetch_rel_time_zone(rel: duckdb.DuckDBPyRelation) -> str:
result = rel.query(
"duckdb_settings()", "select value from duckdb_settings() where name = 'TimeZone'"
).fetchone()
assert result is not None # noqa: S101
return result[0] # type: ignore[no-any-return]
@lru_cache(maxsize=16)
def _non_nested_native_to_narwhals_dtype(duckdb_dtype_id: str, version: Version) -> DType:
dtypes = version.dtypes
return {
"hugeint": dtypes.Int128(),
"bigint": dtypes.Int64(),
"integer": dtypes.Int32(),
"smallint": dtypes.Int16(),
"tinyint": dtypes.Int8(),
"uhugeint": dtypes.UInt128(),
"ubigint": dtypes.UInt64(),
"uinteger": dtypes.UInt32(),
"usmallint": dtypes.UInt16(),
"utinyint": dtypes.UInt8(),
"double": dtypes.Float64(),
"float": dtypes.Float32(),
"varchar": dtypes.String(),
"date": dtypes.Date(),
"timestamp": dtypes.Datetime(),
"boolean": dtypes.Boolean(),
"interval": dtypes.Duration(),
"decimal": dtypes.Decimal(),
"time": dtypes.Time(),
"blob": dtypes.Binary(),
}.get(duckdb_dtype_id, dtypes.Unknown())
def narwhals_to_native_dtype(dtype: IntoDType, version: Version) -> str: # noqa: C901, PLR0912, PLR0915
dtypes = version.dtypes
if isinstance_or_issubclass(dtype, dtypes.Decimal):
msg = "Casting to Decimal is not supported yet."
raise NotImplementedError(msg)
if isinstance_or_issubclass(dtype, dtypes.Float64):
return "DOUBLE"
if isinstance_or_issubclass(dtype, dtypes.Float32):
return "FLOAT"
if isinstance_or_issubclass(dtype, dtypes.Int128):
return "INT128"
if isinstance_or_issubclass(dtype, dtypes.Int64):
return "BIGINT"
if isinstance_or_issubclass(dtype, dtypes.Int32):
return "INTEGER"
if isinstance_or_issubclass(dtype, dtypes.Int16):
return "SMALLINT"
if isinstance_or_issubclass(dtype, dtypes.Int8):
return "TINYINT"
if isinstance_or_issubclass(dtype, dtypes.UInt128):
return "UINT128"
if isinstance_or_issubclass(dtype, dtypes.UInt64):
return "UBIGINT"
if isinstance_or_issubclass(dtype, dtypes.UInt32):
return "UINTEGER"
if isinstance_or_issubclass(dtype, dtypes.UInt16): # pragma: no cover
return "USMALLINT"
if isinstance_or_issubclass(dtype, dtypes.UInt8): # pragma: no cover
return "UTINYINT"
if isinstance_or_issubclass(dtype, dtypes.String):
return "VARCHAR"
if isinstance_or_issubclass(dtype, dtypes.Boolean): # pragma: no cover
return "BOOLEAN"
if isinstance_or_issubclass(dtype, dtypes.Time):
return "TIME"
if isinstance_or_issubclass(dtype, dtypes.Binary):
return "BLOB"
if isinstance_or_issubclass(dtype, dtypes.Categorical):
msg = "Categorical not supported by DuckDB"
raise NotImplementedError(msg)
if isinstance_or_issubclass(dtype, dtypes.Enum):
if version is Version.V1:
msg = "Converting to Enum is not supported in narwhals.stable.v1"
raise NotImplementedError(msg)
if isinstance(dtype, dtypes.Enum):
categories = "'" + "', '".join(dtype.categories) + "'"
return f"ENUM ({categories})"
msg = "Can not cast / initialize Enum without categories present"
raise ValueError(msg)
if isinstance_or_issubclass(dtype, dtypes.Datetime):
_time_unit = dtype.time_unit
_time_zone = dtype.time_zone
msg = "todo"
raise NotImplementedError(msg)
if isinstance_or_issubclass(dtype, dtypes.Duration): # pragma: no cover
_time_unit = dtype.time_unit
msg = "todo"
raise NotImplementedError(msg)
if isinstance_or_issubclass(dtype, dtypes.Date): # pragma: no cover
return "DATE"
if isinstance_or_issubclass(dtype, dtypes.List):
inner = narwhals_to_native_dtype(dtype.inner, version)
return f"{inner}[]"
if isinstance_or_issubclass(dtype, dtypes.Struct): # pragma: no cover
inner = ", ".join(
f'"{field.name}" {narwhals_to_native_dtype(field.dtype, version)}'
for field in dtype.fields
)
return f"STRUCT({inner})"
if isinstance_or_issubclass(dtype, dtypes.Array): # pragma: no cover
shape = dtype.shape
duckdb_shape_fmt = "".join(f"[{item}]" for item in shape)
inner_dtype: Any = dtype
for _ in shape:
inner_dtype = inner_dtype.inner
duckdb_inner = narwhals_to_native_dtype(inner_dtype, version)
return f"{duckdb_inner}{duckdb_shape_fmt}"
msg = f"Unknown dtype: {dtype}" # pragma: no cover
raise AssertionError(msg)
def generate_partition_by_sql(*partition_by: str | Expression) -> str:
if not partition_by:
return ""
by_sql = ", ".join([f"{col(x) if isinstance(x, str) else x}" for x in partition_by])
return f"partition by {by_sql}"
def generate_order_by_sql(*order_by: str, ascending: bool) -> str:
if ascending:
by_sql = ", ".join([f"{col(x)} asc nulls first" for x in order_by])
else:
by_sql = ", ".join([f"{col(x)} desc nulls last" for x in order_by])
return f"order by {by_sql}"
|
