Improve python sdk docs

docs/docs.json

@@ -326,18 +326,7 @@
             "pages": [
               "python-sdk/api-reference/overview",
               "python-sdk/api-reference/test-decorators",
-              "python-sdk/api-reference/table-assets",
-              "python-sdk/api-reference/tests",
-              "python-sdk/api-reference/test-executions"
-            ]
-          },
-          {
-            "group": "Guides",
-            "pages": [
-              "python-sdk/guides/authentication",
-              "python-sdk/guides/test-decorators",
-              "python-sdk/guides/sending-data",
-              "python-sdk/guides/best-practices"
+              "python-sdk/api-reference/table-assets"
             ]
           }
         ]

docs/python-sdk/api-reference/overview.mdx

@@ -39,7 +39,7 @@ client = ElementaryCloudClient(project_id, api_key, url)
 Where:
 - `project_id` is your Python project identifier (chosen by you, used to deduplicate and identify reported assets)
 - `api_key` is your API token (generated from the steps above)
-- `url` is the full SDK ingest endpoint URL: `{base_url}/sdk-ingest/{env_id}/batch`
+- `url` is the full SDK ingest endpoint URL (the Elementary team will provide you with this URL): `{base_url}/sdk-ingest/{env_id}/batch`
   - Example: `https://app.elementary-data.com/sdk-ingest/a6b2425d-36e2-4e13-8458-9825688ca1f2/batch`
 
 ## Test Context
@@ -58,6 +58,17 @@ with elementary_test_context(asset=asset) as ctx:
     client.send_to_cloud(ctx)
 ```
 
+### `raise_on_error`
+
+By default, `elementary_test_context` uses `raise_on_error=False`. This means that if a decorated test (or something inside the context) raises an exception, the SDK **captures it and records an `ERROR` execution** so you can still send results to Elementary Cloud without crashing your pipeline.
+
+If you prefer **fail-fast** behavior (for example in CI), pass `raise_on_error=True` to re-raise exceptions after they are recorded:
+
+```python
+with elementary_test_context(asset=asset, raise_on_error=True) as ctx:
+    run_my_tests(df)
+```
+
 ## Test Decorators
 
 The SDK provides decorators to define tests:
@@ -75,15 +86,17 @@ You can also use context managers for inline tests:
 with elementary_test_context(asset=asset) as ctx:
     # Using context managers
     with ctx.boolean_test(name="my_test", description="Inline test") as my_bool_test:
-        my_bool_test.assert_value(False)
+        my_bool_test.assert_value(my_test_function())
 
     with ctx.expected_values_test(
         name="country_count",
         expected=[2, 3],
         allow_none=True,
         metadata={"my_metadata_field": "my_metadata_value"},
     ) as my_expected_values_test:
+        # This will fail
         my_expected_values_test.assert_value(5)
+        # This will pass
         my_expected_values_test.assert_value(3)
 
     with ctx.expected_range_test(
@@ -103,17 +116,14 @@ with elementary_test_context(asset=asset) as ctx:
 
 ## Supported Objects
 
-The SDK supports three types of objects:
+The SDK supports reporting table assets and test results.
 
-<CardGroup cols={3}>
+<CardGroup cols={2}>
   <Card title="Table Assets" icon="table" href="/python-sdk/api-reference/table-assets" >
     Register tables and views in your data warehouse
   </Card>
-  <Card title="Tests" icon="flask" href="/python-sdk/api-reference/tests" >
-    Define data quality tests
-  </Card>
-  <Card title="Test Executions" icon="play" href="/python-sdk/api-reference/test-executions" >
-    Report test execution results
+  <Card title="Test Decorators" icon="flask" href="/python-sdk/api-reference/test-decorators" >
+    Define data quality tests using decorators
   </Card>
 </CardGroup>
 
@@ -143,7 +153,6 @@ except Exception as e:
 - **Run multiple tests in one context** - All tests in a single `elementary_test_context` are automatically batched
 - **Use descriptive test names** - Clear names help identify tests in the Elementary UI
 - **Include asset metadata** - Add descriptions, owners, tags, and dependencies to assets
-- **Handle errors gracefully** - Wrap `send_to_cloud` calls in try-except blocks
 
 <Tip>
 All tests run within a single `elementary_test_context` are automatically batched and sent together.
@@ -153,6 +162,5 @@ All tests run within a single `elementary_test_context` are automatically batche
 
 - [Test Decorators](/python-sdk/api-reference/test-decorators) - Complete reference for all test decorators
 - [Table Assets](/python-sdk/api-reference/table-assets) - Learn about table asset structure
-- [Tests](/python-sdk/api-reference/tests) - Understand test definitions
-- [Test Executions](/python-sdk/api-reference/test-executions) - See how to report test results
+- [Quickstart](/python-sdk/quickstart) - Send your first test results to Elementary Cloud
 

docs/python-sdk/api-reference/table-assets.mdx

@@ -17,7 +17,7 @@ asset = TableAsset(
     description="string",           # Optional: Table description
     owners=["string"],              # Optional: List of owners (emails or usernames)
     tags=["string"],               # Optional: List of tags
-    depends_on=["string"]           # Optional: List of upstream asset IDs
+    depends_on=["string"]           # Optional: List of upstream fully qualified table names
 )
 ```
 
@@ -37,7 +37,7 @@ asset = TableAsset(
 | `description` | string | Human-readable description of the table |
 | `owners` | list[string] | List of owners (email addresses or usernames) |
 | `tags` | list[string] | List of tags for categorization |
-| `depends_on` | list[string] | List of upstream asset IDs (e.g., `["prod.public.customers", "prod.public.orders"]`) for lineage tracking |
+| `depends_on` | list[string] | List of upstream fully qualified table names (e.g., `["prod.public.customers", "prod.public.orders"]`) for lineage tracking |
 
 ## Example
 
@@ -75,7 +75,6 @@ Table assets are updated on each ingest, so include all current metadata in ever
 
 ## Related Documentation
 
-- [Tests](/python-sdk/api-reference/tests) - Define tests for your table assets
-- [Test Executions](/python-sdk/api-reference/test-executions) - Report test results
-- [Sending Data Guide](/python-sdk/guides/sending-data) - Learn how to send table assets
+- [Test Decorators](/python-sdk/api-reference/test-decorators) - Define tests for your table assets
+- [API Reference](/python-sdk/api-reference/overview) - Overview of the SDK API
 

docs/python-sdk/api-reference/test-decorators.mdx

@@ -49,8 +49,8 @@ def test_function(df: pd.DataFrame) -> bool:
 | `tags` | list[str] | No | `None` | List of tags |
 | `owners` | list[str] | No | `None` | List of owners |
 | `metadata` | dict | No | `None` | Additional metadata |
-| `quality_dimension` | QualityDimension | No | `None` | Quality dimension (defaults to VALIDITY if column_name is set) |
-| `skip` | bool | No | `False` | Whether to skip this test |
+| `quality_dimension` | QualityDimension | No | `None` | Quality dimension (defaults to VALIDITY) |
+| `skip` | bool | No | `False` | Whether to skip this test. Useful if you want the test to appear in Elementary Cloud, but you don't want to execute it in this run. |
 
 ### Example
 
@@ -68,7 +68,7 @@ def test_unique_ids(df: pd.DataFrame) -> bool:
 
 ## @expected_range
 
-Tests that return a numeric value that should fall within a range.
+Tests that return a numeric value that should fall within a range. They can also return a list of numeric values or a pandas Series.
 
 ### Signature
 
@@ -86,9 +86,11 @@ Tests that return a numeric value that should fall within a range.
     quality_dimension: QualityDimension | None = None,
     skip: bool = False,
 )
-def test_function(df: pd.DataFrame) -> float:
+def test_function(df: pd.DataFrame) -> float | list[float] | pd.Series:
     # Your test logic
-    return 25.5  # Numeric value
+    return df["age"].mean()  # Numeric value
+    # return [1, 2, 3]  # Numeric values
+    # return df["age"]  # pandas Series
 ```
 
 ### Parameters
@@ -98,10 +100,7 @@ def test_function(df: pd.DataFrame) -> float:
 | `name` | str | Yes | - | Test name |
 | `min` | float | No | `None` | Minimum expected value (inclusive) |
 | `max` | float | No | `None` | Maximum expected value (inclusive) |
-| `severity` | str | No | `"ERROR"` | Test severity |
-| `description` | str | No | `None` | Test description |
-| `column_name` | str | No | `None` | Column being tested |
-| `tags`, `owners`, `metadata`, `quality_dimension`, `skip` | - | No | - | Same as `@boolean_test` |
+| `severity`, `description`, `column_name`, `tags`, `owners`, `metadata`, `quality_dimension`, `skip` | - | No | - | Same as `@boolean_test` |
 
 ### Example
 
@@ -120,7 +119,7 @@ def test_average_age(df: pd.DataFrame) -> float:
 
 ## @expected_values
 
-Tests that return a value that should match one of a list of expected values.
+Tests that return a value (or values) that should match one of a list of expected values.
 
 ### Signature
 
@@ -150,10 +149,7 @@ def test_function(df: pd.DataFrame) -> Any:
 | `name` | str | Yes | - | Test name |
 | `expected` | Any \| list[Any] | Yes | - | Expected value(s) - can be single value or list |
 | `allow_none` | bool | No | `False` | Whether to allow None values |
-| `severity` | str | No | `"ERROR"` | Test severity |
-| `description` | str | No | `None` | Test description |
-| `column_name` | str | No | `None` | Column being tested |
-| `tags`, `owners`, `metadata`, `quality_dimension`, `skip` | - | No | - | Same as `@boolean_test` |
+| `severity`, `description`, `column_name`, `tags`, `owners`, `metadata`, `quality_dimension`, `skip` | - | No | - | Same as `@boolean_test` |
 
 ### Example
 
@@ -199,9 +195,7 @@ def test_function(df: pd.DataFrame) -> Sized:
 | `name` | str | Yes | - | Test name |
 | `min` | int | No | `None` | Minimum expected row count (inclusive) |
 | `max` | int | No | `None` | Maximum expected row count (inclusive) |
-| `severity` | str | No | `"ERROR"` | Test severity |
-| `description` | str | No | `None` | Test description |
-| `tags`, `owners`, `metadata`, `skip` | - | No | - | Same as `@boolean_test` |
+| `severity`, `description`, `tags`, `owners`, `metadata`, `skip` | - | No | - | Same as `@boolean_test` |
 
 ### Example
 
@@ -214,7 +208,7 @@ def test_function(df: pd.DataFrame) -> Sized:
     description="Validate user count is within expected range",
 )
 def get_users_df(df: pd.DataFrame) -> pd.DataFrame:
-    """Return the dataframe - decorator calls len() on it."""
+    """Return the DataFrame; the decorator calls len() on it."""
     return df
 ```
 
@@ -240,6 +234,6 @@ All decorators support these common parameters:
 ## Related Documentation
 
 - [Quickstart](/python-sdk/quickstart) - Get started with test decorators
-- [Sending Data](/python-sdk/guides/sending-data) - Learn how to send test results
-- [Best Practices](/python-sdk/guides/best-practices) - Best practices for using the SDK
+- [API Reference](/python-sdk/api-reference/overview) - Overview of the SDK API
+- [Table Assets](/python-sdk/api-reference/table-assets) - Register tables and views in your data warehouse