Eventual-Inc/Daft
Oct 2024 – Feb 2026
17 Months active
Languages Used
PythonRustSQLMakefileMarkdownTOMLTypeScriptHTML
Technical Skills
Backend DevelopmentCompiler DesignData EngineeringData TypesDistributed SystemsError Handling
Cory Grinstead
PROFILE
Cory Grinstead
Cory Grinstead developed core analytics and data infrastructure for the Eventual-Inc/Daft repository, delivering features such as SQL query planning, distributed data processing, and robust file I/O. He engineered modular systems in Rust and Python, refactoring APIs for maintainability and integrating Arrow for high-performance data structures. Cory expanded Daft’s capabilities with advanced UDF execution, Spark and PySpark integration, and support for diverse data formats including Parquet and Delta Lake. His work emphasized reliability, performance optimization, and extensibility, addressing complex backend challenges and enabling scalable analytics pipelines. The depth of his contributions reflects strong backend engineering and cross-language integration skills.
Overall Statistics
Feature vs Bugs
76%Features
Repository Contributions
198Total
Bugs
23
Commits
198
Features
72
Lines of code
113,137
Activity Months17
Your Network
55 people
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for Eventual-Inc/Daft: - Key feature delivered: ScalarUDF Interface Enhancement with EvalContext. Refactored the ScalarUDF interface to include an EvalContext parameter in the call method, enabling richer execution context for UDFs and paving the way for more powerful and context-aware UDFs. Commit: 2a8cd2cf74221bfad3f804a1ab7fcc2cc29be87a (refactor(scalarudf): followup to uuid pr (#6129)). - Major bugs fixed: No major bugs fixed this period; focus was on feature refactor and groundwork for future capabilities. - Overall impact and accomplishments: Enables richer UDF execution context, improving expressiveness and flexibility of data transformations in Daft, and setting a foundation for advanced analytics workflows. Improves API consistency and traceability through alignment with existing PR flow. - Technologies/skills demonstrated: API design and refactor, context propagation, code maintainability, version-control discipline, and PR/commit traceability (UUID PR #6129).
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for Eventual-Inc/Daft: - Key feature delivered: ScalarUDF Interface Enhancement with EvalContext. Refactored the ScalarUDF interface to include an EvalContext parameter in the call method, enabling richer execution context for UDFs and paving the way for more powerful and context-aware UDFs. Commit: 2a8cd2cf74221bfad3f804a1ab7fcc2cc29be87a (refactor(scalarudf): followup to uuid pr (#6129)). - Major bugs fixed: No major bugs fixed this period; focus was on feature refactor and groundwork for future capabilities. - Overall impact and accomplishments: Enables richer UDF execution context, improving expressiveness and flexibility of data transformations in Daft, and setting a foundation for advanced analytics workflows. Improves API consistency and traceability through alignment with existing PR flow. - Technologies/skills demonstrated: API design and refactor, context propagation, code maintainability, version-control discipline, and PR/commit traceability (UUID PR #6129).
February 2026
January 2026
28 Commits • 8 Features
Jan 1, 2026January 2026 monthly summary for Eventual-Inc/Daft. Focused on migrating Arrow2 to arrow-rs across modules, core refactors for Arrow2, and CI/stability improvements. Delivered API enhancements, performance optimizations, and developer experience gains while reducing noise in the codebase and improving maintainability.
January 2026
28 Commits • 8 Features
Jan 1, 2026January 2026 monthly summary for Eventual-Inc/Daft. Focused on migrating Arrow2 to arrow-rs across modules, core refactors for Arrow2, and CI/stability improvements. Delivered API enhancements, performance optimizations, and developer experience gains while reducing noise in the codebase and improving maintainability.
December 2025
14 Commits • 2 Features
Dec 1, 2025December 2025 summary for Eventual-Inc/Daft: focused on long-term maintainability and performance via codebase cleanup and Arrow ecosystem modernization across the repository. The work reduces maintenance burden, streamlines dependencies, aligns APIs across crates, and lays the groundwork for future performance improvements in data processing kernels and FFI paths.
14 Commits • 2 Features
Dec 1, 2025December 2025 summary for Eventual-Inc/Daft: focused on long-term maintainability and performance via codebase cleanup and Arrow ecosystem modernization across the repository. The work reduces maintenance burden, streamlines dependencies, aligns APIs across crates, and lays the groundwork for future performance improvements in data processing kernels and FFI paths.
December 2025
November 2025
12 Commits • 6 Features
Nov 1, 2025November 2025 — Eventual-Inc/Daft: Delivered a focused set of API improvements, reliability fixes, and efficiency enhancements across the core library, translating into clearer integration points, smaller distribution costs, and improved throughput. The team advanced data handling ergonomics, confirmed embedding reliability with tests, tightened packaging with size reductions, and laid groundwork for scalable pipelines and future API evolution.
November 2025
12 Commits • 6 Features
Nov 1, 2025November 2025 — Eventual-Inc/Daft: Delivered a focused set of API improvements, reliability fixes, and efficiency enhancements across the core library, translating into clearer integration points, smaller distribution costs, and improved throughput. The team advanced data handling ergonomics, confirmed embedding reliability with tests, tightened packaging with size reductions, and laid groundwork for scalable pipelines and future API evolution.
October 2025
12 Commits • 7 Features
Oct 1, 2025October 2025 was a productive sprint for Eventual-Inc/Daft, delivering core performance and reliability enhancements alongside developer productivity improvements. Major work focused on robust data handling, safer UDF execution, and streamlined AI provider integration, with targeted fixes to ensure data source reliability and test coverage. These changes reduce latency, improve reliability, and simplify development and operations across the repository.
12 Commits • 7 Features
Oct 1, 2025October 2025 was a productive sprint for Eventual-Inc/Daft, delivering core performance and reliability enhancements alongside developer productivity improvements. Major work focused on robust data handling, safer UDF execution, and streamlined AI provider integration, with targeted fixes to ensure data source reliability and test coverage. These changes reduce latency, improve reliability, and simplify development and operations across the repository.
October 2025
September 2025
6 Commits • 2 Features
Sep 1, 2025September 2025 (2025-09) – Eventual-Inc/Daft delivered meaningful File API improvements, reliability fixes, and targeted documentation cleanups that directly support external tool integrations and sustained developer velocity. Key features released include: new File constructors from Python lists/tuples; PySeries.from_pylist support for lists of File objects; a File.to_tempfile() helper to facilitate interactions with external tools; optimized HTTP range requests with a full-buffer fallback; a new file_size expression; and a refactor that clarifies the separation between core FileReference/DaftFile logic and Python bindings. Documentation updates cover the File datatype usage (including header-based file-type detection) and clarified URL/file functions, with obsolete CLI docs removed. A critical IOConfig handling bug fix was applied to revert a change that caused build/test failures and restore proper IOConfig behavior across modules. These changes collectively improve file handling performance, reliability, and integration capabilities, contributing to faster data workflows and stronger API stability. Technologies demonstrated include Python bindings design, API surface evolution, HTTP performance optimization, codebase modularization, and documentation discipline.
September 2025
6 Commits • 2 Features
Sep 1, 2025September 2025 (2025-09) – Eventual-Inc/Daft delivered meaningful File API improvements, reliability fixes, and targeted documentation cleanups that directly support external tool integrations and sustained developer velocity. Key features released include: new File constructors from Python lists/tuples; PySeries.from_pylist support for lists of File objects; a File.to_tempfile() helper to facilitate interactions with external tools; optimized HTTP range requests with a full-buffer fallback; a new file_size expression; and a refactor that clarifies the separation between core FileReference/DaftFile logic and Python bindings. Documentation updates cover the File datatype usage (including header-based file-type detection) and clarified URL/file functions, with obsolete CLI docs removed. A critical IOConfig handling bug fix was applied to revert a change that caused build/test failures and restore proper IOConfig behavior across modules. These changes collectively improve file handling performance, reliability, and integration capabilities, contributing to faster data workflows and stronger API stability. Technologies demonstrated include Python bindings design, API surface evolution, HTTP performance optimization, codebase modularization, and documentation discipline.
August 2025
9 Commits • 3 Features
Aug 1, 2025August 2025: Focused delivery of performance, concurrency, and data-access capabilities for Daft (Eventual-Inc/Daft). Key features and enhancements include substantial UDF performance improvements, async UDF support with improved return_dtype inference, and a new file-oriented data model with object-store integration, complemented by practical examples and improved documentation. These efforts collectively accelerate analytics workloads, broaden data-source reach, and enhance developer ergonomics and clarity for typing and usage.
9 Commits • 3 Features
Aug 1, 2025August 2025: Focused delivery of performance, concurrency, and data-access capabilities for Daft (Eventual-Inc/Daft). Key features and enhancements include substantial UDF performance improvements, async UDF support with improved return_dtype inference, and a new file-oriented data model with object-store integration, complemented by practical examples and improved documentation. These efforts collectively accelerate analytics workloads, broaden data-source reach, and enhance developer ergonomics and clarity for typing and usage.
August 2025
July 2025
6 Commits • 4 Features
Jul 1, 2025July 2025 monthly summary for Eventual-Inc/Daft, focusing on delivering data transformation capabilities, robust data ingestion, and reliability improvements that drive business value and developer productivity. Key features delivered: - List_map: Added element-wise transformation capability for list columns with tests, enabling more expressive data pipelines and reducing workaround code. - JSON reader arrays: JSON reader now supports arrays of objects, auto-handling arrays or falling back to NDJSON for flexible ingestion. - ScalarUDF cleanup: Refactored ScalarUDF with API name improvements to align with Rust practices and improve developer ergonomics. - Hugging Face URL cache-busting: Added a cache-busting parameter to Hugging Face URLs with integration tests to ensure retrieval of latest artifacts. Major bugs fixed: - CI stability: Disabled a flaky runtime statistics test to stabilize CI (no production code changes). - Delta Lake Windows path fix: Corrected object storage path handling by using forward slashes and a path-construction helper to enable reliable Windows reads. Overall impact and accomplishments: - Improved CI reliability and faster feedback cycles, reducing time-to-ship blockers. - Enhanced data ingestion capabilities with flexible JSON and list-based transformations, expanding supported data formats. - Strengthened cross-platform reliability (Windows) for Delta Lake reads and safer asset retrieval through URL cache-busting. - Heightened code quality and maintainability through API cleanups and Rust-aligned practices. Technologies/skills demonstrated: - Rust-based API refactoring and naming clarity - Cross-platform path handling and OS-agnostic data access - Data ingestion enhancements (JSON, arrays, and list transformations) - Test-driven development with integration tests for URL caching - CI reliability discipline and reproducible builds
July 2025
6 Commits • 4 Features
Jul 1, 2025July 2025 monthly summary for Eventual-Inc/Daft, focusing on delivering data transformation capabilities, robust data ingestion, and reliability improvements that drive business value and developer productivity. Key features delivered: - List_map: Added element-wise transformation capability for list columns with tests, enabling more expressive data pipelines and reducing workaround code. - JSON reader arrays: JSON reader now supports arrays of objects, auto-handling arrays or falling back to NDJSON for flexible ingestion. - ScalarUDF cleanup: Refactored ScalarUDF with API name improvements to align with Rust practices and improve developer ergonomics. - Hugging Face URL cache-busting: Added a cache-busting parameter to Hugging Face URLs with integration tests to ensure retrieval of latest artifacts. Major bugs fixed: - CI stability: Disabled a flaky runtime statistics test to stabilize CI (no production code changes). - Delta Lake Windows path fix: Corrected object storage path handling by using forward slashes and a path-construction helper to enable reliable Windows reads. Overall impact and accomplishments: - Improved CI reliability and faster feedback cycles, reducing time-to-ship blockers. - Enhanced data ingestion capabilities with flexible JSON and list-based transformations, expanding supported data formats. - Strengthened cross-platform reliability (Windows) for Delta Lake reads and safer asset retrieval through URL cache-busting. - Heightened code quality and maintainability through API cleanups and Rust-aligned practices. Technologies/skills demonstrated: - Rust-based API refactoring and naming clarity - Cross-platform path handling and OS-agnostic data access - Data ingestion enhancements (JSON, arrays, and list transformations) - Test-driven development with integration tests for URL caching - CI reliability discipline and reproducible builds
June 2025
13 Commits • 6 Features
Jun 1, 2025June 2025 performance summary for Eventual-Inc/Daft: Delivered major modularization and feature work across the expression system, dashboard/telemetry, SQL semantics, Spark integration, and API stability, with improved observability and maintainability. A notable bug fix improved error messaging for missing Spark functions, speeding debugging and user guidance.
13 Commits • 6 Features
Jun 1, 2025June 2025 performance summary for Eventual-Inc/Daft: Delivered major modularization and feature work across the expression system, dashboard/telemetry, SQL semantics, Spark integration, and API stability, with improved observability and maintainability. A notable bug fix improved error messaging for missing Spark functions, speeding debugging and user guidance.
June 2025
May 2025
16 Commits • 3 Features
May 1, 2025In May 2025, Daft delivered major dashboard integration enhancements, targeted SQL improvements, and foundational architecture refactors that improve observability, reliability, and performance. Key outcomes include configurable dashboards via environment variables, JSON representations of plans for JavaScript dashboards, and expanded broadcast data showing both unoptimized and optimized query plans; a critical bug fix ensuring GROUP BY aliases reuse existing columns; enhancements to SQL expressions (list operations and substring) with robust argument parsing and tests; and comprehensive core architecture/API refactors for expressions, function registry, JSON handling, and serialization that improve maintainability and future velocity.
May 2025
16 Commits • 3 Features
May 1, 2025In May 2025, Daft delivered major dashboard integration enhancements, targeted SQL improvements, and foundational architecture refactors that improve observability, reliability, and performance. Key outcomes include configurable dashboards via environment variables, JSON representations of plans for JavaScript dashboards, and expanded broadcast data showing both unoptimized and optimized query plans; a critical bug fix ensuring GROUP BY aliases reuse existing columns; enhancements to SQL expressions (list operations and substring) with robust argument parsing and tests; and comprehensive core architecture/API refactors for expressions, function registry, JSON handling, and serialization that improve maintainability and future velocity.
April 2025
12 Commits • 4 Features
Apr 1, 2025April 2025 - Eventual-Inc/Daft: Delivered core time/data tooling, enhanced Spark integration, and SQL planning reliability to boost data accuracy and pipeline resilience. Key features delivered: - Date/Time Utilities, Formatting, and Time Type Enhancements: adds millisecond/microsecond/nanosecond extraction, day_of_year, unix_timestamp, strftime, timezone-aware to_datetime parsing, expanded DataType is_t with inner properties, and TimeUnit representation fixes. Commits include: 720b87e998f54c04bafe6156b5392072b2712b6d; 17a4fee4abdfa0fafe2af28f02e74d2c73eabaa6; d22915fcff56a6f127276e8cc833b914953758b0; f56d50e5b0f4a612256078362e21519b28c0a59d; 923ff62bce9d355edeccebce4eb761417cac4842; 823243e1ee24298639df916a9dc046a8ed347c0c; e651eae7e9d6e24643da87bbd296f15eb7e94147. - Spark Integration Enhancements: io config for Spark (S3/Azure/GCS/HTTP) and Python UDF support in SQL. Commits: a4b5b3807a40f05022631410a49c02e54ff31fed; 8e2065e412ac9707df1e38772667a94a904d0e49. - Sorting Enhancements and Bug Fixes: fixes for sorting with nulls_first and multicolumn sorts. Commits: f0b4469dff22507a98d37784b2864efc1a3b9b94; 301f732ddecc8769e732bd75b0514697ffff0f93. - SQL Planner Refactor and Internal Improvements: rework SQLPlanner to use session references and updates for better lifetime management and local bindings (bound_tables). Commit: f1f425220b389e7116ddbf70b10268d85fc32ad4. Overall impact and accomplishments: - Enhanced data reliability and pipeline resilience through robust time handling, cross-cloud data access, and a more maintainable SQL planning stack. - Accelerated analytics capabilities with UDFs in SQL and flexible sort semantics across large datasets. Technologies/skills demonstrated: - Python and SQL development, Spark IO configuration, time and date semantics, data type introspection, UDF integration, and code refactoring for lifetime management and testability.
12 Commits • 4 Features
Apr 1, 2025April 2025 - Eventual-Inc/Daft: Delivered core time/data tooling, enhanced Spark integration, and SQL planning reliability to boost data accuracy and pipeline resilience. Key features delivered: - Date/Time Utilities, Formatting, and Time Type Enhancements: adds millisecond/microsecond/nanosecond extraction, day_of_year, unix_timestamp, strftime, timezone-aware to_datetime parsing, expanded DataType is_t with inner properties, and TimeUnit representation fixes. Commits include: 720b87e998f54c04bafe6156b5392072b2712b6d; 17a4fee4abdfa0fafe2af28f02e74d2c73eabaa6; d22915fcff56a6f127276e8cc833b914953758b0; f56d50e5b0f4a612256078362e21519b28c0a59d; 923ff62bce9d355edeccebce4eb761417cac4842; 823243e1ee24298639df916a9dc046a8ed347c0c; e651eae7e9d6e24643da87bbd296f15eb7e94147. - Spark Integration Enhancements: io config for Spark (S3/Azure/GCS/HTTP) and Python UDF support in SQL. Commits: a4b5b3807a40f05022631410a49c02e54ff31fed; 8e2065e412ac9707df1e38772667a94a904d0e49. - Sorting Enhancements and Bug Fixes: fixes for sorting with nulls_first and multicolumn sorts. Commits: f0b4469dff22507a98d37784b2864efc1a3b9b94; 301f732ddecc8769e732bd75b0514697ffff0f93. - SQL Planner Refactor and Internal Improvements: rework SQLPlanner to use session references and updates for better lifetime management and local bindings (bound_tables). Commit: f1f425220b389e7116ddbf70b10268d85fc32ad4. Overall impact and accomplishments: - Enhanced data reliability and pipeline resilience through robust time handling, cross-cloud data access, and a more maintainable SQL planning stack. - Accelerated analytics capabilities with UDFs in SQL and flexible sort semantics across large datasets. Technologies/skills demonstrated: - Python and SQL development, Spark IO configuration, time and date semantics, data type introspection, UDF integration, and code refactoring for lifetime management and testability.
April 2025
March 2025
16 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for Eventual-Inc/Daft focused on delivering a cohesive analytics dashboard experience, expanding the DataFrame API with SQL-like capabilities, stabilizing distributed workloads, and strengthening CI tooling. The work aligned with business goals to accelerate data-driven decision making, improve deployment reliability, and reduce time-to-value for analytics features.
March 2025
16 Commits • 2 Features
Mar 1, 2025March 2025 monthly summary for Eventual-Inc/Daft focused on delivering a cohesive analytics dashboard experience, expanding the DataFrame API with SQL-like capabilities, stabilizing distributed workloads, and strengthening CI tooling. The work aligned with business goals to accelerate data-driven decision making, improve deployment reliability, and reduce time-to-value for analytics features.
February 2025
12 Commits • 6 Features
Feb 1, 2025February 2025: Delivered a robust, Rust-enhanced Daft core with expanded data source support and stronger type fidelity, enabling broader interoperability and scalability. Key business outcomes include improved data compatibility across CSV/Parquet/JSON and Delta Lake, stronger SQL datatype handling with support for custom types, and a foundation for Spark analytics through PySpark integration. The Rust port and targeted refactors improve reuse across components and code quality, while enhanced DataFrame operations and consistent sorting semantics reduce pipeline friction. This work accelerates onboarding for new data sources, improves reliability, and positions Daft for accelerated integration with enterprise data ecosystems.
12 Commits • 6 Features
Feb 1, 2025February 2025: Delivered a robust, Rust-enhanced Daft core with expanded data source support and stronger type fidelity, enabling broader interoperability and scalability. Key business outcomes include improved data compatibility across CSV/Parquet/JSON and Delta Lake, stronger SQL datatype handling with support for custom types, and a foundation for Spark analytics through PySpark integration. The Rust port and targeted refactors improve reuse across components and code quality, while enhanced DataFrame operations and consistent sorting semantics reduce pipeline friction. This work accelerates onboarding for new data sources, improves reliability, and positions Daft for accelerated integration with enterprise data ecosystems.
February 2025
January 2025
11 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for Eventual-Inc/Daft: Delivered robust Spark Connect core features and expanded streaming capabilities, while improving test maintainability and error handling. This work strengthens Spark Connect integration, accelerates streaming data pipelines, and enhances code quality and extensibility across the repository.
January 2025
11 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for Eventual-Inc/Daft: Delivered robust Spark Connect core features and expanded streaming capabilities, while improving test maintainability and error handling. This work strengthens Spark Connect integration, accelerates streaming data pipelines, and enhances code quality and extensibility across the repository.
December 2024
9 Commits • 4 Features
Dec 1, 2024December 2024 delivered a strong set of feature enhancements, stability fixes, and performance-oriented refactors across Eventual-Inc/Daft. The work improves debugging visibility, reduces runtime noise, and enhances robustness in data processing and Spark Connect workflows.
9 Commits • 4 Features
Dec 1, 2024December 2024 delivered a strong set of feature enhancements, stability fixes, and performance-oriented refactors across Eventual-Inc/Daft. The work improves debugging visibility, reduces runtime noise, and enhances robustness in data processing and Spark Connect workflows.
December 2024
November 2024
17 Commits • 11 Features
Nov 1, 2024November 2024 highlights for Eventual-Inc/Daft: Accelerated SQL capability and benchmarking readiness with substantive feature delivery, targeted bug fixes, and architectural refinements that drive business value and reliability. Implemented TPC-DS dataset generation and benchmarking setup, added EXTRACT temporal function, and extended the engine with set operations (UNION, INTERSECT, EXCEPT) and subqueries (including EXISTS) for expressive analytics. Improved query planning and correctness through fixes for GROUP BY/ORDER BY aliases, aggregates in ORDER BY, partially qualified joins, and join alias handling, along with new HAVING support. Refactored dependencies to reduce coupling and added flexible filtering with is_in. Overall, this work increases throughput for analytics workloads, enables standardized performance benchmarks, and paves the way for more complex queries in production.
November 2024
17 Commits • 11 Features
Nov 1, 2024November 2024 highlights for Eventual-Inc/Daft: Accelerated SQL capability and benchmarking readiness with substantive feature delivery, targeted bug fixes, and architectural refinements that drive business value and reliability. Implemented TPC-DS dataset generation and benchmarking setup, added EXTRACT temporal function, and extended the engine with set operations (UNION, INTERSECT, EXCEPT) and subqueries (including EXISTS) for expressive analytics. Improved query planning and correctness through fixes for GROUP BY/ORDER BY aliases, aggregates in ORDER BY, partially qualified joins, and join alias handling, along with new HAVING support. Refactored dependencies to reduce coupling and added flexible filtering with is_in. Overall, this work increases throughput for analytics workloads, enables standardized performance benchmarks, and paves the way for more complex queries in production.
October 2024
4 Commits • 1 Features
Oct 1, 2024October 2024 – Eventual-Inc/Daft: Delivered major SQL capabilities and strengthened reliability, enabling richer analytics and more robust data processing. Implemented cross-join handling and optimization, Common Table Expressions (CTEs), and new SQL functions (stddev, concat). Fixed a critical robustness issue in the between operation by adding explicit non-numeric type checks and returning a ValueError, preventing panics. These changes enhance expressiveness, performance, and reliability for production analytics workloads.
4 Commits • 1 Features
Oct 1, 2024October 2024 – Eventual-Inc/Daft: Delivered major SQL capabilities and strengthened reliability, enabling richer analytics and more robust data processing. Implemented cross-join handling and optimization, Common Table Expressions (CTEs), and new SQL functions (stddev, concat). Fixed a critical robustness issue in the between operation by adding explicit non-numeric type checks and returning a ValueError, preventing panics. These changes enhance expressiveness, performance, and reliability for production analytics workloads.
October 2024
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Quality Metrics
Correctness91.8%
Maintainability89.0%
Architecture88.8%
Performance82.6%
AI Usage25.0%
Skills & Technologies
Programming Languages
C++CSSHTMLJSONJavaScriptMakefileMarkdownN/APythonPythonI
Technical Skills
AI DevelopmentAI IntegrationAI/ML IntegrationAPI DesignAPI DevelopmentAPI IntegrationAPI RefactoringAPI designAPI developmentAlgorithm DesignAlgorithm OptimizationArgument HandlingArrowArrow Library IntegrationAsset Management
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