The "Data Formulator" project by Microsoft is an AI-driven tool designed to streamline the creation of data visualizations using a blend of user interface interactions and natural language inputs. It leverages large language models to simplify data transformation tasks, enhancing user experience and efficiency. The project is actively maintained, with a strong community interest reflected in its GitHub stars. It is open-source under the MIT License, promoting community contributions.
Dan Marshall (danmarshall)
Ricardo Leal (ricardoleal20)
Steve (snkashis)
Timespan | Opened | Closed | Comments | Labeled | Milestones |
---|---|---|---|---|---|
7 Days | 1 | 0 | 0 | 1 | 1 |
30 Days | 1 | 0 | 0 | 1 | 1 |
90 Days | 1 | 0 | 0 | 1 | 1 |
All Time | 13 | 6 | - | - | - |
Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.
Developer | Avatar | Branches | PRs | Commits | Files | Changes |
---|---|---|---|---|---|---|
Dan Marshall | ![]() |
1 | 0/1/0 | 2 | 33 | 1457 |
Steve | ![]() |
1 | 1/1/0 | 1 | 1 | 2 |
Ricardo Leal | ![]() |
1 | 1/1/0 | 1 | 1 | 2 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
Risk | Level (1-5) | Rationale |
---|---|---|
Delivery | 4 | The project faces significant delivery risks due to unresolved issues and minimal pull request activity. The lack of issue resolution, as seen with issues like #49 and #34, indicates a backlog that could hinder progress. The absence of merged pull requests over the past 90 days suggests a bottleneck in integrating changes, potentially delaying project milestones. Additionally, the dependency on external APIs, as highlighted in issues like #63, poses challenges that could complicate delivery timelines. |
Velocity | 4 | The project's velocity is at risk due to several factors: minimal commit and pull request activity, reliance on a few key contributors, and unresolved issues. The low number of commits and branches suggests limited parallel development efforts, which can slow down progress. The heavy reliance on Dan Marshall for substantial changes poses a risk if he becomes unavailable. Furthermore, the lack of engagement in issue resolution and pull request reviews indicates a slow pace of development. |
Dependency | 3 | The project has moderate dependency risks due to its reliance on external APIs and libraries. Issues like #63 and #49 highlight challenges with integrating third-party APIs such as Sambanova and LLMs, which could complicate maintenance if these APIs change. While there is proactive management of dependencies through tools like Dependabot, the reliance on automated updates without manual oversight could introduce instability. |
Team | 3 | Team risks are present due to limited engagement from contributors other than Dan Marshall. The low number of commits from other team members suggests potential burnout or disengagement. The lack of collaborative review processes for pull requests further indicates possible communication or prioritization issues within the team. |
Code Quality | 2 | The project demonstrates good code quality practices through the use of ESLint configurations and attention to detail in minor corrections. However, the rollback of refactoring changes related to 'const' usage suggests some ongoing challenges in implementing best practices. Overall, the focus on maintaining coding standards helps mitigate significant code quality risks. |
Technical Debt | 3 | Technical debt is a concern due to the complexity of certain files like 'src/views/DataThread.tsx' and 'src/views/EncodingShelfThread.tsx', which could lead to increased maintenance challenges if not managed properly. The extensive list of disabled ESLint rules also suggests areas where code quality might be compromised. While there are efforts to address technical debt through linting and minor corrections, the lack of substantial feature development indicates potential accumulation of technical debt. |
Test Coverage | 4 | Test coverage is a significant risk as there is a lack of automated testing mechanisms for critical components like 'src/views/ModelSelectionDialog.tsx' and 'src/views/ConceptCard.tsx'. The reliance on manual testing could result in undetected bugs or regressions, impacting overall software quality. The absence of explicit test coverage in files responsible for key functionalities highlights this risk. |
Error Handling | 3 | Error handling presents moderate risks due to unresolved issues like #34 related to API key integration difficulties. While there are mechanisms for error feedback in UI components, the ongoing technical difficulties users face suggest that error handling might not be comprehensive enough to address all scenarios effectively. |
Recent GitHub issue activity for the "Data Formulator" project shows a focus on enhancing flexibility and addressing technical challenges. Notably, issues #63 and #49 highlight a demand for support of third-party endpoints and models, indicating a community interest in expanding the tool's compatibility with various AI models. Issue #34 reveals ongoing difficulties with API key integration, suggesting potential usability or documentation gaps. The persistence of these issues suggests they may be critical to user experience and adoption. Additionally, there is a recurring theme of data handling challenges, as seen in issues #53 and #50, which involve data visualization and JSON import capabilities.
#34: Trouble adding the OpenAI API key
#53: Data Visualization Challenge Discussion
#51: add moving average
These issues highlight ongoing efforts to improve the tool's flexibility and address technical hurdles related to data handling and model integration. The community's active engagement in discussions suggests a collaborative approach to resolving these challenges.
The repository microsoft/data-formulator
currently has no open pull requests and a total of 50 closed pull requests. The recent activity indicates a healthy pace of development with several PRs being merged or closed within the last few days.
#62: Fix typo in README.md
README.md
file, changing "formualtor" to "formulator". It was created and merged on the same day, indicating quick action on documentation fixes.#61: api key entry ui: correct (bank --> blank) typo
#60: Eslint
let
over var
and ensuring React components have keys.#59: Bump vite from 5.3.6 to 5.4.12
#58: Eslint initial
#57: Fix a11y insights
Overall, microsoft/data-formulator
appears to be a well-maintained project with a proactive approach towards code quality, security, and user experience enhancements.
src/views/ModelSelectionDialog.tsx
Structure and Organization: The file is well-organized, with clear separation of imports, component definitions, and utility functions. The use of React hooks like useState
and useSelector
is consistent and appropriate for managing component state and accessing Redux store data.
Code Quality:
any
.Potential Improvements:
src/views/DataThread.tsx
Structure and Organization: This file is quite large (495 lines), indicating potential complexity. It might benefit from breaking down into smaller components or files to enhance maintainability.
Code Quality:
Potential Improvements:
React.memo
) to optimize rendering performance, especially if the component deals with large datasets.src/views/EncodingShelfThread.tsx
Structure and Organization: Similar to DataThread.tsx
, this file is also quite extensive (561 lines). It handles complex logic related to encoding shelves in visualizations.
Code Quality:
Potential Improvements:
any
types with more specific TypeScript interfaces where possible.eslint.config.js
Structure and Organization: The configuration file is concise and well-organized, specifying language options, plugins, and rules clearly.
Code Quality:
Potential Improvements:
package.json
Structure and Organization: The file is structured according to standard conventions, listing dependencies, scripts, and other metadata clearly.
Code Quality:
Potential Improvements:
npm audit
.src/app/App.tsx
Structure and Organization: This central application file integrates various components and manages global states effectively using Redux.
Code Quality:
Potential Improvements:
src/data/utils.ts
Structure and Organization: This utility file provides functions for data processing tasks like loading data from text or inferring types.
Code Quality:
Potential Improvements:
yarn.lock
Structure and Organization: As an auto-generated file by Yarn, it maintains a detailed record of exact dependency versions used in the project.
Code Quality:
Potential Improvements:
Dan Marshall (danmarshall)
const
in code refactoring.Ricardo Leal (ricardoleal20)
Steve (snkashis)
Overall, the recent activities reflect maintenance work focusing on documentation accuracy and code quality improvements.