Stories with Tag task runner

• Show HN: Hatchet v1 – A task orchestration platform built on Postgres

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  Posted: 2025-04-03 17:17:54

  Verbose tl;dr

  Hatchet v1 is a new open-source task orchestration platform built on top of Postgres. It aims to provide a reliable and scalable way to define, execute, and manage complex workflows, leveraging the robustness and transactional guarantees of Postgres as its backend. Hatchet uses SQL for defining workflows and Python for task logic, allowing developers to manage their orchestration entirely within their existing Postgres infrastructure. This eliminates the need for external dependencies like Redis or RabbitMQ, simplifying deployment and maintenance. The project is designed with an emphasis on observability and debuggability, featuring a built-in web UI and integration with logging and monitoring tools.

  The open-source project, Hatchet v1, introduces a novel approach to task orchestration by leveraging PostgreSQL as its foundational database. Instead of relying on external message queues or specialized workflow engines, Hatchet utilizes Postgres's robust features, including ACID transactions, row-level locking, and the LISTEN/NOTIFY mechanism, to manage and execute complex workflows. This design choice aims to simplify deployment and maintenance by consolidating the orchestration logic within a single, familiar database system.

  Hatchet's core functionality revolves around defining and executing Directed Acyclic Graphs (DAGs) of tasks. These tasks, represented as rows within dedicated Postgres tables, are interconnected to define dependencies and execution order. The platform provides a Python API for constructing these DAGs programmatically, specifying task dependencies, and defining the code to be executed for each task. Leveraging Postgres's transactional capabilities, Hatchet ensures data consistency and reliability throughout the workflow execution. The system manages task scheduling, execution, and state tracking, automatically handling retries and failures according to user-defined policies.

  The reliance on Postgres offers several key advantages. It eliminates the need for separate message queues like RabbitMQ or Kafka, streamlining the infrastructure and reducing operational complexity. Furthermore, it capitalizes on Postgres's inherent reliability and scalability, offering a robust foundation for mission-critical workflows. Using SQL, users can directly query the database to gain insights into workflow execution, task status, and historical performance data. This facilitates monitoring, debugging, and analysis of complex orchestration processes. The developers emphasize that Hatchet is particularly well-suited for scenarios where existing Postgres infrastructure is already in place, allowing for seamless integration and reduced overhead. The project is currently in its initial release (v1) and actively seeking community feedback and contributions. The provided code examples and documentation demonstrate the basic usage and key features of Hatchet, guiding developers on how to integrate it into their own projects.

  • task orchestration
  • workflow management
  • Postgres
  • PostgreSQL
  • Database
  • Open Source
  • hatchet
  • Python
  • task runner
  • job scheduler
  • distributed systems
  • scalability

  Summary of Comments ( 51 )
  https://news.ycombinator.com/item?id=43572733

  Verbose tl;dr

  Hacker News users discussed Hatchet's reliance on Postgres for task orchestration, expressing both interest and skepticism. Some praised the simplicity and the clever use of Postgres features like LISTEN/NOTIFY for real-time updates. Others questioned the scalability and performance compared to dedicated workflow engines like Temporal or Airflow, particularly for complex workflows and high throughput. Several comments focused on the potential limitations of using SQL for defining workflows, contrasting it with the flexibility of code-based approaches. The maintainability and debuggability of SQL-based workflows were also raised as potential concerns. Finally, some commenters appreciated the transparency of the architecture and the potential for easier integration with existing Postgres-based systems.

  The Hacker News post for Hatchet v1 has a moderate number of comments discussing various aspects of the project. Several commenters express interest and approval for the approach of using Postgres as the foundation for a task orchestration platform.

  One compelling line of discussion revolves around the comparison between Hatchet and Temporal. Commenters debate the advantages and disadvantages of each, with some suggesting that Hatchet's simplicity and reliance on Postgres could be beneficial for certain use cases, while others point to Temporal's more mature feature set and scalability. The creator of Hatchet also participates in this discussion, acknowledging the differences and explaining their rationale for focusing on Postgres.

  Another key comment thread focuses on the perceived limitations of using Postgres for this type of workload. Concerns are raised about the potential performance bottlenecks and scaling challenges that might arise as the number of tasks and workflows increases. Commenters discuss strategies for mitigating these issues, such as using a separate Postgres instance dedicated to Hatchet.

  Further comments delve into specific features and aspects of Hatchet's design, including its use of SQL for defining workflows, the choice of Python for the client library, and the potential for integrating with other tools and services. Some commenters inquire about the roadmap for future development, expressing interest in features like retry mechanisms and error handling. The project creator responds to many of these inquiries, providing further context and insights into their design choices and plans for the future.

  Finally, a few comments touch on the broader topic of task orchestration and the landscape of existing solutions. Commenters mention alternative tools and frameworks, and discuss the challenges of choosing the right tool for different use cases.

• Show HN: Werk, a simple build tool and command runner

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  Posted: 2025-01-12 11:40:56

  Verbose tl;dr

  Werk is a new build tool designed for simplicity and speed, focusing on task automation and project management. Written in Rust, it uses a declarative TOML configuration file to define commands and dependencies, offering a straightforward alternative to more complex tools like Make, Ninja, or just shell scripts. Werk aims for minimal overhead and predictable behavior, featuring parallel execution, a human-readable configuration format, and built-in dependency management to ensure efficient builds. It's intended to be a versatile tool suitable for various tasks from simple build processes to more complex workflows.

  Simon Ask has introduced Werk, a novel build tool and command runner meticulously designed for simplicity and speed. Werk aims to address the perceived complexities and performance overhead of existing tools like Make, Just, Ninja, and similar task runners, particularly within the context of Rust development where compilation times can be substantial.

  The core principle behind Werk is a straightforward approach to defining and executing build processes. Instead of relying on complex declarative syntax or domain-specific languages, Werk employs a simple, imperative scripting style using standard shell commands, directly within a werk.py file. This Python script defines functions, each representing a build target, which execute shell commands when invoked. This design choice promotes transparency and ease of understanding, making it readily apparent how the build process unfolds.

  Werk's commitment to speed is realized through several key optimizations. First, it leverages efficient hashing algorithms to meticulously track file dependencies and avoid unnecessary rebuilds. This ensures that only modified files and their dependents are recompiled, significantly reducing build times. Second, Werk supports parallel execution of build targets, effectively utilizing multi-core processors to further accelerate the build process. Finally, it's implemented in Rust, a language renowned for its performance characteristics, contributing to its overall speed and efficiency.

  Werk boasts several notable features designed to enhance the developer experience. It provides robust support for defining and managing dependencies, ensuring that build targets are executed in the correct order. It offers clear and concise error reporting, facilitating swift debugging of build issues. Additionally, Werk includes built-in caching mechanisms, enabling it to efficiently reuse previously compiled artifacts, further minimizing build times.

  While currently geared towards Rust projects, the author emphasizes Werk's potential applicability to other programming languages and build scenarios. Its minimalist design, coupled with its focus on speed and simplicity, positions Werk as a promising alternative to existing build tools, particularly for projects seeking a streamlined and efficient build process. The author also acknowledges that Werk is still in its early stages of development and encourages feedback from the community.

  • build tool
  • command runner
  • werk
  • Automation
  • task runner
  • development tools
  • cli
  • open-source
  • Software Development
  • Python
  • shell scripting
  • productivity
  • DevOps
  • Make
  • Just
  • Task
  • build system
  • Make alternative
  • Just alternative

  Summary of Comments ( 5 )
  https://news.ycombinator.com/item?id=42672863

  Verbose tl;dr

  HN users generally praised Werk's simplicity and speed, particularly for smaller projects. Several compared it favorably to tools like Taskfile, Just, and Make, highlighting its cleaner syntax and faster execution. Some expressed concerns about its reliance on Deno and potential lack of Windows support, though the creator clarified that Windows compatibility is planned. Others questioned the long-term viability of Deno itself. Despite some skepticism, the overall reception was positive, with many appreciating the "fresh take" on build tools and its potential as a lightweight alternative to more complex systems. A few users also offered suggestions for improvements, including better error handling and more comprehensive documentation.

  The Hacker News post for "Show HN: Werk, a simple build tool and command runner" has generated a moderate amount of discussion, with a number of commenters sharing their thoughts and experiences. Several key themes and compelling comments emerge from the discussion:

  • Simplicity and Speed: Several users praised Werk's simplicity and speed, particularly when compared to more complex build tools. One commenter specifically mentioned appreciating its speed and ease of use for simple projects where the overhead of other tools isn't warranted. Another highlighted the appeal of a faster, less complex alternative to tools like Bazel, suggesting that Werk occupies a useful niche for smaller, less demanding projects.

  • Niche and Use Cases: Commenters discussed the specific contexts where Werk shines. The author themselves chimed in to explain they built it for personal use and simple, self-contained projects where a full-blown build system is overkill. This reinforces the idea that Werk isn't trying to be a universal solution, but rather a targeted tool for a specific type of workflow.

  • Comparison to Other Tools: Unsurprisingly, comparisons to other build tools and task runners are frequent. Make, Just, Task, and npm scripts are all mentioned. Some users expressed skepticism about Werk's value proposition over these existing tools, particularly for larger or more complex projects. One commenter questioned the long-term maintainability and feature creep potential, suggesting that starting simple is easy, but maintaining that simplicity over time as needs evolve can be challenging.

  • Language Choice (Zig): The use of Zig as the implementation language for Werk garnered some attention. While some expressed interest in Zig, others questioned the choice, citing concerns about the relatively small community and potential for future maintenance challenges. This sparked a small side discussion about the benefits and drawbacks of using newer, less established languages for tooling.

  • Features and Functionality: Specific features of Werk, such as support for file watching and parallel execution, were also discussed. One commenter suggested a potential integration with a caching mechanism to further improve build speeds.

  • Documentation and Examples: A couple of commenters mentioned the need for clearer documentation and more comprehensive examples to better showcase Werk's capabilities and facilitate adoption. One user specifically requested an example demonstrating how to handle dependencies.

  In summary, the comments generally reflect a cautious but curious reception to Werk. While the simplicity and speed are acknowledged as strengths, there are questions about its long-term viability, its niche compared to established alternatives, and the implications of its implementation in Zig. The discussion highlights the trade-offs inherent in choosing a simpler, more specialized tool versus a more complex, feature-rich one.