execution context fixes #20

example/models/items.py

@@ -5,7 +5,7 @@
 import pandas as pd
 
 from example.helper import iter_dates
-from sqlmesh import EngineAdapter, model
+from sqlmesh import ExecutionContext, model
 from sqlmesh.utils.date import to_ds
 
 ITEMS = [
@@ -63,7 +63,7 @@
     """
 )
 def execute(
-    engine: EngineAdapter,
+    context: ExecutionContext,
     start: datetime,
     end: datetime,
     latest: datetime,

example/models/order_items.py

@@ -1,11 +1,10 @@
 import random
-import typing as t
 from datetime import datetime
 
 import pandas as pd
 
 from example.helper import iter_dates
-from sqlmesh import EngineAdapter, Snapshot, model
+from sqlmesh import ExecutionContext, model
 from sqlmesh.utils.date import to_ds
 
 
@@ -29,23 +28,19 @@
     """
 )
 def execute(
-    engine: EngineAdapter,
+    context: ExecutionContext,
     start: datetime,
     end: datetime,
     latest: datetime,
-    snapshots: t.Dict[str, Snapshot],
-    mapping: t.Optional[t.Dict[str, str]],
     **kwargs,
 ) -> pd.DataFrame:
     dfs = []
 
-    raw_orders = (
-        snapshots["sushi.orders"].table_name if snapshots else mapping["sushi.orders"]
-    )
+    raw_orders = context.table("sushi.orders")
 
     for dt in iter_dates(start, end):
         # this section not super clean, make it easier to fetch other snapshots
-        orders = engine.fetchdf(
+        orders = context.fetchdf(
             f"""
             SELECT *
             FROM {raw_orders}
@@ -56,7 +51,7 @@ def execute(
         if not isinstance(orders, pd.DataFrame):
             orders = orders.toPandas()
 
-        items = engine.fetchdf(
+        items = context.fetchdf(
             f"""
 SELECT *
             FROM {raw_orders}

example/models/orders.py

@@ -4,7 +4,7 @@
 import pandas as pd
 
 from example.helper import iter_dates
-from sqlmesh import EngineAdapter, model
+from sqlmesh import ExecutionContext, model
 from sqlmesh.utils.date import to_ds
 
 CUSTOMERS = list(range(0, 100))
@@ -33,7 +33,7 @@
     """
 )
 def execute(
-    engine: EngineAdapter,
+    context: ExecutionContext,
     start: datetime,
     end: datetime,
     latest: datetime,

sqlmesh/__init__.py

@@ -8,7 +8,7 @@
 import sys
 from enum import Enum
 
-from sqlmesh.core.context import Context
+from sqlmesh.core.context import Context, ExecutionContext
 from sqlmesh.core.engine_adapter import EngineAdapter
 from sqlmesh.core.macros import macro
 from sqlmesh.core.model import Model, model

sqlmesh/cli/main.py

@@ -80,6 +80,36 @@ def render(
     ctx.obj.console.show_sql(sql)
 
 
+@cli.command("evaluate")
+@click.argument("model")
+@opt.start_time
+@opt.end_time
+@opt.latest_time
+@click.option(
+    "--limit",
+    type=int,
+    help="The number of rows which the query should be limited to.",
+)
+@click.pass_context
+def evaluate(
+    ctx,
+    model: str,
+    start: TimeLike,
+    end: TimeLike,
+    latest: t.Optional[TimeLike] = None,
+    limit: t.Optional[int] = None,
+) -> None:
+    """Evaluate a model and return a dataframe with a default limit of 1000."""
+    df = ctx.obj.evaluate(
+        model,
+        start=start,
+        end=end,
+        latest=latest,
+        limit=limit,
+    )
+    ctx.obj.console.log_success(df)
+
+
 @cli.command("format")
 @click.pass_context
 def format(ctx) -> None:

sqlmesh/core/config.py

@@ -266,6 +266,7 @@ class Config(PydanticModel):
         physical_schema: The default schema used to store materialized tables.
         snapshot_ttl: Duration before unpromoted snapshots are removed.
         time_column_format: The default format to use for all model time columns. Defaults to %Y-%m-%d.
+            This time format uses python format codes. https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-codes.
         ddl_concurrent_task: The number of concurrent tasks used for DDL
             operations (table / view creation, deletion, etc). Default: 1.
     """

sqlmesh/core/context.py

@@ -50,7 +50,7 @@
 from sqlmesh.core.context_diff import ContextDiff
 from sqlmesh.core.dag import DAG
 from sqlmesh.core.dialect import extend_sqlglot, format_model_expressions
-from sqlmesh.core.engine_adapter import EngineAdapter
+from sqlmesh.core.engine_adapter import DF, EngineAdapter
 from sqlmesh.core.environment import Environment
 from sqlmesh.core.macros import macro
 from sqlmesh.core.model import Model
@@ -69,10 +69,51 @@
 if t.TYPE_CHECKING:
     import graphviz
 
+    MODEL_OR_SNAPSHOT = t.Union[str, Model, Snapshot]
+
 extend_sqlglot()
 
 
-class Context:
+class ExecutionContext:
+    """The minimal context needed in order to execute a query.
+    Args:
+        engine_adapter: The engine adapter to execute queries against.
+        mapping: A mapping of models to physical tables.
+    """
+
+    def __init__(self, engine_adapter: EngineAdapter, mapping: t.Dict[str, str]):
+        self.engine_adapter = engine_adapter
+        self.spark = self.engine_adapter.spark
+        self._mapping = mapping
+
+    @property
+    def mapping(self) -> t.Dict[str, str]:
+        return self._mapping
+
+    def table(self, model_name: str) -> str:
+        """Gets the physical table name for a given model.
+
+        Args:
+            model_name: The model name.
+
+        Returns:
+            The physical table name.
+        """
+        return self.mapping[model_name]
+
+    def fetchdf(self, query: t.Union[exp.Expression, str]) -> DF:
+        """Fetches a dataframe given a sql string or sqlglot expression.
+
+        Args:
+            query: SQL string or sqlglot expression.
+
+        Returns:
+            The default dataframe is Pandas, but for Spark a PySpark dataframe is returned.
+        """
+        return self.engine_adapter.fetchdf(query)
+
+
+class Context(ExecutionContext):
     """Encapsulates a SQLMesh environment supplying convenient functions to perform various tasks.
 
     Args:
@@ -303,9 +344,22 @@ def snapshots(self) -> t.Dict[str, Snapshot]:
                 snapshots[model.name] = snapshot
         return snapshots
 
+    @property
+    def mapping(self) -> t.Dict[str, str]:
+        """Mapping of model name to physical table name.
+
+        If a snapshot has not been versioned yet, it's view name will be returned.
+        """
+        return {
+            name: snapshot.table_name
+            if snapshot.version
+            else snapshot.qualified_view_name.for_environment(c.PROD)
+            for name, snapshot in self.snapshots.items()
+        }
+
     def render(
         self,
-        model: t.Union[str, Model],
+        model_or_snapshot: MODEL_OR_SNAPSHOT,
         *,
         start: t.Optional[TimeLike] = None,
         end: t.Optional[TimeLike] = None,
@@ -317,7 +371,7 @@ def render(
         """Renders a model's query, expanding macros with provided kwargs, and optionally expanding referenced models.
 
         Args:
-            model: The model name or instance to render.
+            model_or_snapshot: The model, model name, or snapshot to render.
             start: The start of the interval to render.
             end: The end of the interval to render.
             latest: The latest time used for non incremental datasets.
@@ -330,7 +384,14 @@ def render(
             The rendered expression.
         """
         latest = latest or yesterday_ds()
-        model = model if isinstance(model, Model) else self.models[model]
+
+        if isinstance(model_or_snapshot, str):
+            model = self.models[model_or_snapshot]
+        elif isinstance(model_or_snapshot, Snapshot):
+            model = model_or_snapshot.model
+        else:
+            model = model_or_snapshot
+
         expand = self.dag.upstream(model.name) if expand is True else expand or []
 
         return model.render_query(
@@ -345,33 +406,43 @@ def render(
 
     def evaluate(
         self,
-        snapshot: Snapshot | str,
+        model_or_snapshot: MODEL_OR_SNAPSHOT,
         start: TimeLike,
         end: TimeLike,
         latest: TimeLike,
+        limit: t.Optional[int] = None,
         **kwargs,
-    ) -> None:
-        """Evaluate a snapshot (running its query against a DB/Engine).
+    ) -> DF:
+        """Evaluate a model or snapshot (running its query against a DB/Engine).
+
+        This method is used to test or iterate on models without side effects.
 
         Args:
-            snapshot: The snapshot to evaluate.
+            model_or_snapshot: The model, model name, or snapshot to render.
             start: The start of the interval to evaluate.
             end: The end of the interval to evaluate.
             latest: The latest time used for non incremental datasets.
+            limit: A limit applied to the model, this must be > 0.
         """
-        if isinstance(snapshot, str):
-            snapshot = self.snapshots[snapshot]
+        if isinstance(model_or_snapshot, str):
+            snapshot = self.snapshots[model_or_snapshot]
+        elif isinstance(model_or_snapshot, Model):
+            snapshot = self.snapshots[model_or_snapshot.name]
+        else:
+            snapshot = model_or_snapshot
+
+        if not limit or limit <= 0:
+            limit = 1000
 
-        self.snapshot_evaluator.evaluate(
+        return self.snapshot_evaluator.evaluate(
             snapshot,
             start,
             end,
             latest,
-            snapshots=self.snapshots,
+            mapping=self.mapping,
+            limit=limit,
         )
 
-        self.state_sync.add_interval(snapshot.snapshot_id, start, end)
-
     def format(self) -> None:
         """Format all models in a given directory."""
         for model in self.models.values():
@@ -680,7 +751,11 @@ def _load_models(self):
             new = registry.keys() - registered
             registered |= new
             for name in new:
-                model = registry[name].model(module, path)
+                model = registry[name].model(
+                    module=module,
+                    path=path,
+                    time_column_format=self.config.time_column_format,
+                )
                 self.models[model.name] = model
                 self._add_model_to_dag(model)