Set widget id in query header #154

JCZuurmond · 2024-06-13T11:29:54Z

Resolves #133

github-actions · 2024-06-13T11:34:35Z

✅ 27/27 passed, 2 skipped, 7m10s total

_{Running from acceptance #153}

docs/dashboards.md

src/databricks/labs/lsql/dashboards.py

nfx · 2024-06-14T04:46:21Z

src/databricks/labs/lsql/dashboards.py

+    height: int = 0
+    id: str = ""
+
+    def __post_init__(self):


Don't do dataclass here, do a normal class

Done: 01c814a.

Intuively I prefer a data class here. It makes sense to me for Metadata to be represented by a dataclass. We use a dataclass more often for similar objects, like the DashboardMetadata and Specs.

Though, I do recognize that the __post_init and other methods make this class (maybe) too complicated to remain a dataclass.

Note that a couple times dataclasses.<method> were used, which I had to replace when refactoring this to a normal class.

In any case, we can always revert.

nfx · 2024-06-14T04:47:56Z

src/databricks/labs/lsql/dashboards.py

+        """
+        if self.spec_type is None:
+            return 0, 0
+        if self.spec_type == CounterSpec:


This should be overridden in the CounterSpec class, not in this class

What do you mean with overriden? There is nothing overriden here

src/databricks/labs/lsql/dashboards.py

nfx · 2024-06-14T04:52:47Z

src/databricks/labs/lsql/dashboards.py

-    def _get_text_widget(path: Path) -> Widget:
-        widget = Widget(name=path.stem, textbox_spec=path.read_text())
+    def _get_text_widget(widget_metadata: WidgetMetadata) -> Widget:
+        widget = Widget(


Don't you want to create Widget instance from a method of Tile instance?.. eg turning "abstract tiles" into "concrete widgets"

yes, I like that idea. I am planning to do that in two PRs, this and #150. The tile's make more sense when introducing more specs. I'll rework the other PR on top of this one, so that we can discuss EOD

nfx

approving PR to unblock

Resolves #127 Resolves #137 Stacked on top of #154 <img width="1713" alt="Screenshot 2024-06-12 at 17 13 17" src="https://github.com/databrickslabs/lsql/assets/5946784/f5cc3738-55d0-4e59-9183-c6f2b8a9c2b6">

* Added Command Execution backend which uses Command Execution API on a cluster ([#95](#95)). In this release, the databricks labs lSQL library has been updated with a new Command Execution backend that utilizes the Command Execution API. A new `CommandExecutionBackend` class has been implemented, which initializes a `CommandExecutor` instance taking a cluster ID, workspace client, and language as parameters. The `execute` method runs SQL commands on the specified cluster, and the `fetch` method returns the query result as an iterator of Row objects. The existing `StatementExecutionBackend` class has been updated to inherit from a new abstract base class called `ExecutionBackend`, which includes a `save_table` method for saving data to tables and is meant to be a common base class for both Statement and Command Execution backends. The `StatementExecutionBackend` class has also been updated to use the new `ExecutionBackend` abstract class and its constructor now accepts a `max_records_per_batch` parameter. The `execute` and `fetch` methods have been updated to use the new `_only_n_bytes` method for logging truncated SQL statements. Additionally, the `CommandExecutionBackend` class has several methods, `execute`, `fetch`, and `save_table` to execute commands on a cluster and save the results to tables in the databricks workspace. This new backend is intended to be used for executing commands on a cluster and saving the results in a databricks workspace. * Added basic integration with Lakeview Dashboards ([#66](#66)). In this release, we've added basic integration with Lakeview Dashboards to the project, enhancing its capabilities. This includes updating the `databricks-labs-blueprint` dependency to version 0.4.2 with the `[yaml]` extra, allowing for additional functionality related to handling YAML files. A new file, `dashboards.py`, has been introduced, providing a class for interacting with Databricks dashboards, along with methods for retrieving and saving dashboard configurations. Additionally, a new `__init__.py` file under the `src/databricks/labs/lsql/lakeview` directory imports all classes and functions from the `model.py` module, providing a foundation for further development and customization. The release also introduces a new file, `model.py`, containing code generated from OpenAPI specs by the Databricks SDK Generator, and a template file, `model.py.tmpl`, used for handling JSON data during integration with Lakeview Dashboards. A new file, `polymorphism.py`, provides utilities for checking if a value can be assigned to a specific type, supporting correct data typing and formatting with Lakeview Dashboards. Furthermore, a `.gitignore` file has been added to the `tests/integration` directory as part of the initial steps in adding integration testing to ensure compatibility with the Lakeview Dashboards platform. Lastly, the `test_dashboards.py` file in the `tests/integration` directory contains a function, `test_load_dashboard(ws)`, which uses the `Dashboards` class to save a dashboard from a source to a destination path, facilitating testing during the integration process. * Added dashboard-as-code functionality ([#201](#201)). This commit introduces dashboard-as-code functionality for the UCX project, enabling the creation and management of dashboards using code. The feature resolves multiple issues and includes a new `create-dashboard` command for creating unpublished dashboards. The functionality is available in the `lsql` lab and allows for specifying the order and width of widgets, overriding default widget identifiers, and supporting various SQL and markdown header arguments. The `dashboard.yml` file is used to define top-level metadata for the dashboard. This commit also includes extensive documentation and examples for using the dashboard as a library and configuring different options. * Automate opening integration test dashboard in debug mode ([#167](#167)). A new feature has been added to automatically open the integration test dashboard in debug mode, making it easier for software engineers to debug and troubleshoot. This has been achieved by importing the `webbrowser` and `is_in_debug` modules from "databricks.labs.blueprint.entrypoint", and adding a check in the `create` function to determine if the code is running in debug mode. If it is, a dashboard URL is constructed from the workspace configuration and dashboard ID, and then opened in a web browser using "webbrowser.open". This allows for a more streamlined debugging process for the integration test dashboard. No other parts of the code have been affected by this change. * Automatically tile widgets ([#109](#109)). In this release, we've introduced an automatic widget tiling feature for the dashboard creation process in our open-source library. The `Dashboards` class now includes a new class variable, `_maximum_dashboard_width`, set to 6, representing the maximum width allowed for each row of widgets in the dashboard. The `create_dashboard` method has been updated to accept a new `self` parameter, turning it into an instance method. A new `_get_position` method has been introduced to calculate and return the next available position for placing a widget, and a `_get_width_and_height` method has been added to return the width and height for a widget specification, initially handling `CounterSpec` instances. Additionally, we've added new unit tests to improve testing coverage, ensuring that widgets are created, positioned, and sized correctly. These tests also cover the correct positioning of widgets based on their order and available space, as well as the expected width and height for each widget. * Bump actions/checkout from 4.1.3 to 4.1.6 ([#102](#102)). In the latest release, the 'actions/checkout' GitHub Action has been updated from version 4.1.3 to 4.1.6, which includes checking the platform to set the archive extension appropriately. This release also bumps the version of github/codeql-action from 2 to 3, actions/setup-node from 1 to 4, and actions/upload-artifact from 2 to 4. Additionally, the minor-actions-dependencies group was updated with two new versions. Disabling extensions.worktreeConfig when disabling sparse-checkout was introduced in version 4.1.4. The release notes and changelog for this update can be found in the provided link. This commit was made by dependabot[bot] with contributions from cory-miller and jww3. * Bump actions/checkout from 4.1.6 to 4.1.7 ([#151](#151)). In the latest release, the 'actions/checkout' GitHub action has been updated from version 4.1.6 to 4.1.7 in the project's push workflow, which checks out the repository at the start of the workflow. This change brings potential bug fixes, performance improvements, or new features compared to the previous version. The update only affects the version number in the YAML configuration for the 'actions/checkout' step in the release.yml file, with no new methods or alterations to existing functionality. This update aims to ensure a smooth and enhanced user experience for those utilizing the project's push workflows by taking advantage of the possible improvements or bug fixes in the new version of 'actions/checkout'. * Create a dashboard with a counter from a single query ([#107](#107)). In this release, we have introduced several enhancements to our dashboard-as-code approach, including the creation of a `Dashboards` class that provides methods for getting, saving, and deploying dashboards. A new method, `create_dashboard`, has been added to create a dashboard with a single page containing a counter widget. The counter widget is associated with a query that counts the number of rows in a specified dataset. The `deploy_dashboard` method has also been added to deploy the dashboard to the workspace. Additionally, we have implemented a new feature for creating dashboards with a counter from a single query, including modifications to the `test_dashboards.py` file and the addition of four new tests. These changes improve the robustness of the dashboard creation process and provide a more automated way to view important metrics. * Create text widget from markdown file ([#142](#142)). A new feature has been implemented in the library that allows for the creation of a text widget from a markdown file, enhancing customization and readability for users. This development resolves issue [#1](#1) * Design document for dashboards-as-code ([#105](#105)). "The latest release introduces 'Dashboards as Code,' a method for defining and managing dashboards through configuration files, enabling version control and controlled changes. The building blocks include `.sql`, `.md`, and `dashboard.yml` files, with `.sql` defining queries and determining tile order, and `dashboard.yml` specifying top-level metadata and tile overrides. Metadata can be inferred or explicitly defined in the query or files. The tile order can be determined by SQL file order, `tiles` order in `dashboard.yml`, or SQL file metadata. This project can also be used as a library for embedding dashboard generation in your code. Configuration precedence follows command-line flags, SQL file headers, `dashboard.yml`, and SQL query content. The command-line interface is utilized for dashboard generation from configuration files." * Ensure propagation of `lsql` version into `User-Agent` header when it is used as library ([#206](#206)). In this release, the `pyproject.toml` file has been updated to ensure that the correct version of the `lsql` library is propagated into the `User-Agent` header when used as a library, improving attribution. The `databricks-sdk` version has been updated from `0.22.0` to `0.29.0`, and the `__init__.py` file of the `lsql` library has been modified to add the `with_user_agent_extra` function from the `databricks.sdk.core` package for correct attribution. The `backends.py` file has also been updated with improved type handling in the `_row_to_sql` and `save_table` functions for accurate SQL insertion and handling of user-defined classes. Additionally, a test has been added to ensure that the `lsql` version is correctly propagated in the `User-Agent` header when used as a library. These changes offer improved functionality and accurate type handling, making it easier for developers to identify the library version when used in other projects. * Fixed counter encodings ([#143](#143)). In this release, we have improved the encoding of counters in the lsql dashboard by modifying the `create_dashboard` function in the `dashboards.py` file. Previously, the counter field encoding was hardcoded as "count," but has been changed to dynamically determine the first field name of the given fields, ensuring that counters are expected to have only one field. Additionally, a new integration test has been added to the `tests/integration/test_dashboards.py` file to ensure that the dashboard deployment functionality correctly handles SQL queries that do not perform a count. A new test for the `Dashboards` class has also been added to check that counter field encoding names are created as expected. The `WorkspaceClient` is mocked and not called in this test. These changes enhance the accuracy of counter encoding and improve the overall functionality and reliability of the lsql dashboard. * Fixed non-existing reference and typo in the documentation ([#104](#104)). In this release, we've made improvements to the documentation of our open-source library, specifically addressing issue [#104](#104). The changes include fixing a non-existent reference and a typo in the `Library size comparison` section of the "comparison.md" document. This section provides guidance for selecting a library based on factors like library size, unified authentication, and compatibility with various Databricks warehouses and SQL Python APIs. The updates clarify the required dependency size for simple applications and scripts, and offer more detailed information about each library option. We've also added a new subsection titled `Detailed comparison` to provide a more comprehensive overview of each library's features. These changes are intended to help software engineers better understand which library is best suited for their specific needs, particularly for applications that require data transfer of large amounts of data serialized in Apache Arrow format and low result fetching latency, where we recommend using the Databricks SQL Connector for Python for efficient data transfer and low latency. * Fixed parsing message ([#146](#146)). In this release, the warning message logged during the creation of a dashboard when a ParseError occurs has been updated to provide clearer and more detailed information about the parsing error. The new error message now includes the specific query being parsed and the exact parsing error, enabling developers to quickly identify the cause of parsing issues. This change ensures that engineers can efficiently diagnose and address parsing errors, improving the overall development and debugging experience with a more informative log format: "Parsing {query}: {error}". * Improve dashboard as code ([#108](#108)). The `Dashboards` class in the 'dashboards.py' file has been updated to improve functionality and usability, with changes such as the addition of a type variable `T` for type checking and more descriptive names for methods. The `save_to_folder` method now accepts a `Dashboard` object and returns a `Dashboard` object, and a new static method `create_dashboard` has been added. Additionally, two new methods `_with_better_names` and `_replace_names` have been added for improved readability. The `get_dashboard` method now returns a `Dashboard` object instead of a dictionary. The `save_to_folder` method now also formats SQL code before saving it to file. These changes aim to enhance the functionality and readability of the codebase and provide more user-friendly methods for interacting with the `Dashboards` class. In addition to the changes in the `Dashboards` class, there have been updates in the organization of the project structure. The 'queries/counter.sql' file has been moved to 'dashboards/one_counter/counter.sql' in the 'tests/integration' directory. This modification enhances the organization of the project. Furthermore, several tests for the `Dashboards` class have been introduced in the 'databricks.labs.lsql.dashboards' module, demonstrating various functionalities of the class and ensuring that it functions as intended. The tests cover saving SQL and YML files to a specified folder, creating a dataset and a counter widget for each query, deploying dashboards with a given display name or dashboard ID, and testing the behavior of the `save_to_folder` and `deploy_dashboard` methods. Lastly, the commit removes the `test_load_dashboard` function and updates the `test_dashboard_creates_one_dataset_per_query` and `test_dashboard_creates_one_counter_widget_per_query` functions to use the updated `Dashboard` class. A new `replace_recursively` function is introduced to replace specific fields in a dataclass recursively. A new test function `test_dashboards_deploys_exported_dashboard_definition` has been added, which reads a dashboard definition from a JSON file, deploys it, and checks if it's successfully deployed using the `Dashboards` class. A new test function `test_dashboard_deploys_dashboard_the_same_as_created_dashboard` has also been added, which compares the original and deployed dashboards to ensure they are identical. Overall, these changes aim to improve the functionality and readability of the codebase and provide more user-friendly methods for interacting with the `Dashboards` class, as well as enhance the organization of the project structure and add new tests for the `Dashboards` class to ensure it functions as intended. * Infer fields from a query ([#111](#111)). The `Dashboards` class in the `dashboards.py` file has been updated with the addition of a new method, `_get_fields`, which accepts a SQL query as input and returns a list of `Field` objects using the `sqlglot` library to parse the query and extract the necessary information. The `create_dashboard` method has been modified to call this new function when creating `Query` objects for each dataset. If a `ParseError` occurs, a warning is logged and iteration continues. This allows for the automatic population of fields when creating a new dashboard, eliminating the need for manual specification. Additionally, new tests have been added for invalid queries and for checking if the fields in a query have the expected names. These tests include `test_dashboards_skips_invalid_query` and `test_dashboards_gets_fields_with_expected_names`, which utilize the caplog fixture and create temporary query files to verify functionality. Existing functionality related to creating dashboards remains unchanged. * Make constant all caps ([#140](#140)). In this release, the project's 'dashboards.py' file has been updated to improve code readability and maintainability. A constant variable `_maximum_dashboard_width` has been changed to all caps, becoming '_MAXIMUM_DASHBOARD_WIDTH'. This modification affects the `Dashboards` class and its methods, particularly `_get_fields` and '_get_position'. The `_get_position` method has been revised to use the new all caps constant variable. This change ensures better visibility of constants within the code, addressing issue [#140](#140). It's important to note that this modification only impacts the 'dashboards.py' file and does not affect any other functionalities. * Read display name from `dashboard.yml` ([#144](#144)). In this release, we have introduced a new `DashboardMetadata` dataclass that reads the display name of a dashboard from a `dashboard.yml` file located in the dashboard's directory. If the `dashboard.yml` file is absent, the folder name will be used as the display name. This change improves the readability and maintainability of the dashboard configuration by explicitly defining the display name and reducing the need to specify widget information in multiple places. We have also added a new fixture called `make_dashboard` for creating and cleaning up lakeview dashboards in the test suite. The fixture handles creation and deletion of the dashboard and provides an option to set a custom display name. Additionally, we have added and modified several unit tests to ensure the proper handling of the `DashboardMetadata` class and the dashboard creation process, including tests for missing, present, or incorrect `display_name` keys in the YAML file. The `dashboards.deploy_dashboard()` function has been updated to handle cases where only `dashboard_id` is provided. * Set widget id in query header ([#154](#154)). In this release, we've made significant improvements to widget metadata handling in our open-source library. We've introduced a new `WidgetMetadata` class that replaces the previous `WidgetMetadata` dataclass, now featuring a `path` attribute, `spec_type` property, and optional parameters for `order`, `width`, `height`, and `_id`. The `_get_widgets` method has been updated to accept an Iterable of `WidgetMetadata` objects, and both `_get_layouts` and `_get_widgets` methods now sort widgets using the order field. A new class method, `WidgetMetadata.from_path`, handles parsing widget metadata from a file path, replacing the removed `_get_width_and_height` method. Additionally, the `WidgetMetadata` class is now used in the `deploy_dashboard` method, and the test suite for the `dashboards` module has been enhanced with updated `test_widget_metadata_replaces_width_and_height` and `test_widget_metadata_replaces_attribute` functions, as well as new tests for specific scenarios. Issue [#154](#154) has been addressed by setting the widget id in the query header, and the aforementioned changes improve flexibility and ease of use for dashboard development. * Use order key in query header if defined ([#149](#149)). In this release, we've introduced a new feature to use an order key in the query header if defined, enhancing the flexibility and control over the dashboard creation process. The `WidgetMetadata` dataclass now includes an optional `order` parameter of type `int`, and the `_get_arguments_parser()` method accepts the `--order` flag with type `int`. The `replace_from_arguments()` method has been updated to support the new `order` parameter, with a default value of `self.order`. The `create_dashboard()` method now implements a new `_get_datasets()` method to retrieve datasets from the dashboard folder and introduces a `_get_widgets()` method, which accepts a list of files, iterates over them, and yields tuples containing widgets and their corresponding metadata, including the order. These improvements enable the use of an order key in query headers, ensuring the correct order of widgets in the dashboard creation process. Additionally, a new test case has been added to verify the correct behavior of the dashboard deployment with a specified order key in the query header. This feature resolves issue [#148](#148). * Use widget width and height defined in query header ([#147](#147)). In this release, the handling of metadata in SQL files has been updated to utilize the header of the file, instead of the first line, for improved readability and flexibility. This change includes a new WidgetMetadata class for defining the width and height of a widget in a dashboard, as well as new methods for parsing the widget metadata from a provided path. The release also includes updates to the documentation to cover the supported widget arguments `-w or --width` and '-h or --height', and resolves issue [#114](#114) by adding a test for deploying a dashboard with a big widget using a new function `test_dashboard_deploys_dashboard_with_big_widget`. Additionally, new test cases have been added for creating dashboards with custom-sized widgets based on query header width and height values, improving functionality and error handling. Dependency updates: * Bump actions/checkout from 4.1.3 to 4.1.6 ([#102](#102)). * Bump actions/checkout from 4.1.6 to 4.1.7 ([#151](#151)).

JCZuurmond added 9 commits June 13, 2024 10:28

Add id to WidgetMetadata

c21b40d

Use id for sorting

27b1f40

Add path to widget metadata

c11ff25

Add path to widget metadata

17856fc

Let as_dict only return str

8ffd82b

Rework

84df731

Fix default width height

af3799c

Order based on id and order

20aed8d

Format

e71b85d

JCZuurmond requested a review from nfx June 13, 2024 11:29

JCZuurmond self-assigned this Jun 13, 2024

JCZuurmond temporarily deployed to runtime June 13, 2024 11:30 — with GitHub Actions Inactive

Make id empty string by default

da31599

JCZuurmond temporarily deployed to runtime June 13, 2024 11:43 — with GitHub Actions Inactive

JCZuurmond added 4 commits June 13, 2024 13:46

Refactor widgets metdata to separate method

d735855

Remove redundant continue

960acb6

Move widget spec type into WidgetMetdadata

4f9318c

Refactor get widgets into separate methods

cca0d54

JCZuurmond force-pushed the feat/add-widget-id-to-query-header branch from d241581 to cca0d54 Compare June 13, 2024 11:59

JCZuurmond temporarily deployed to runtime June 13, 2024 11:59 — with GitHub Actions Inactive

JCZuurmond added 2 commits June 13, 2024 14:00

Update TODO

d7a1019

Let get widgets only return widgets

402cb47

JCZuurmond temporarily deployed to runtime June 13, 2024 12:30 — with GitHub Actions Inactive

JCZuurmond added 4 commits June 13, 2024 14:55

Reorder method calling

d09b7d5

Refactory function signature

ab7364e

Update header in docs

6ef3072

Change signature

2e459ab

JCZuurmond temporarily deployed to runtime June 13, 2024 13:16 — with GitHub Actions Inactive

Move parse widget metadata into WidgetMetadata.from_path

073396e

JCZuurmond temporarily deployed to runtime June 13, 2024 13:20 — with GitHub Actions Inactive

JCZuurmond added 7 commits June 13, 2024 15:21

Remove redundant id setting

9fe49c9

Rename get_width_and_height_to_size

659e354

Redo setting id

cf86e96

Make maximum dashboard width a global

791991b

Add missing type hint

e7eaf37

Set widget name from metadata id

f835ace

Consistent argument ordering for dataset

565e426

JCZuurmond temporarily deployed to runtime June 13, 2024 13:31 — with GitHub Actions Inactive

JCZuurmond mentioned this pull request Jun 13, 2024

Create table from query with multiple columns and introduce tiles #150

Merged

Remove need for dataset to create widget

bc4a621

JCZuurmond temporarily deployed to runtime June 13, 2024 14:24 — with GitHub Actions Inactive

Make size hidden

b670931

JCZuurmond had a problem deploying to runtime June 13, 2024 14:29 — with GitHub Actions Failure

JCZuurmond temporarily deployed to runtime June 13, 2024 14:44 — with GitHub Actions Inactive

JCZuurmond enabled auto-merge (squash) June 13, 2024 15:06

nfx requested changes Jun 14, 2024

View reviewed changes

JCZuurmond added 3 commits June 14, 2024 09:12

Make header one line

7a0b434

Add is_markdown

f15061f

Make WidgetMetadata a class

01c814a

JCZuurmond temporarily deployed to runtime June 14, 2024 07:39 — with GitHub Actions Inactive

Remove MarkdownSpec

e2f001e

JCZuurmond temporarily deployed to runtime June 14, 2024 07:45 — with GitHub Actions Inactive

nfx approved these changes Jun 16, 2024

View reviewed changes

JCZuurmond merged commit a79d40f into main Jun 16, 2024
10 checks passed

JCZuurmond deleted the feat/add-widget-id-to-query-header branch June 16, 2024 01:30

nfx mentioned this pull request Jul 3, 2024

Release v0.5.0 #207

Merged

Provide feedback

Saved searches

Use saved searches to filter your results more quickly

Set widget id in query header #154

Set widget id in query header #154

JCZuurmond commented Jun 13, 2024

github-actions bot commented Jun 13, 2024 •

edited

Loading

nfx Jun 14, 2024

JCZuurmond Jun 14, 2024 •

edited

Loading

nfx Jun 14, 2024

JCZuurmond Jun 14, 2024

nfx Jun 14, 2024

JCZuurmond Jun 14, 2024

nfx left a comment

Set widget id in query header #154

Set widget id in query header #154

Conversation

JCZuurmond commented Jun 13, 2024

github-actions bot commented Jun 13, 2024 • edited Loading

nfx Jun 14, 2024

Choose a reason for hiding this comment

JCZuurmond Jun 14, 2024 • edited Loading

Choose a reason for hiding this comment

nfx Jun 14, 2024

Choose a reason for hiding this comment

JCZuurmond Jun 14, 2024

Choose a reason for hiding this comment

nfx Jun 14, 2024

Choose a reason for hiding this comment

JCZuurmond Jun 14, 2024

Choose a reason for hiding this comment

nfx left a comment

Choose a reason for hiding this comment

github-actions bot commented Jun 13, 2024 •

edited

Loading

JCZuurmond Jun 14, 2024 •

edited

Loading