breez/spark-sdk
May 2026 – Jun 2026
2 Months active
Languages Used
C#GoJavaScriptKotlinNonePythonRustSwift
Technical Skills
API designAPI developmentAsynchronous ProgrammingC#CI/CDClippy
Peter Rojs
PROFILE
Peter Rojs
Worked on the breez/spark-sdk repository to deliver core improvements for scalable token transfers, focusing on data integrity, reliability, and cross-language consistency. Refactored token output identity to use outpoint-based keys, streamlined SQL and WASM/JS stores, and enhanced the reservation lifecycle to prevent rollback on broadcast errors. Introduced polymorphic observer hooks for unified API behavior across Rust and TypeScript, and strengthened CI infrastructure with macOS toolchain activation. Further enhancements included improved TLS certificate verification and execute-before capabilities for time-sensitive transactions. Emphasized code quality through formatting, logging best practices, and reduced maintenance toil, supporting robust backend development and integration readiness.
Overall Statistics
Feature vs Bugs
61%Features
Repository Contributions
59Total
Bugs
9
Commits
59
Features
14
Lines of code
308,943
Activity Months2
Your Network
18 peopleWork History
June 2026
4 Commits • 3 Features
Jun 1, 2026June 2026 monthly summary for breez/spark-sdk focused on reliability, observability, and security improvements in token transfer flows and TLS handling. Deliveries reduced noisy reporting, improved integration readiness, and strengthened certificate verification for deployments.
4 Commits • 3 Features
Jun 1, 2026June 2026 monthly summary for breez/spark-sdk focused on reliability, observability, and security improvements in token transfer flows and TLS handling. Deliveries reduced noisy reporting, improved integration readiness, and strengthened certificate verification for deployments.
June 2026
May 2026
55 Commits • 11 Features
May 1, 2026May 2026 performance summary for breez/spark-sdk: - Focused on delivering core Spark SDK improvements to support scalable token transfers, improve data integrity, and strengthen CI reliability. - Key features delivered: - Spark Token Broadcast: migrated to V3 single-phase broadcast flow, populated FinalTokenOutput IDs, and aligned token outputs to use the response-provided id, reducing reliance on post-broadcast refresh trips. - TokenOutput identity and dedup refactor: derived TokenOutput.id from outpoints; re-keyed SQL stores and wasm/JS token stores on (prev_tx_hash, prev_tx_vout); implemented outpoint-based dedup to prevent duplicate spends and streamline reconciliation. - Reservation flow resilience: fixed handling so reservations are not canceled on post-broadcast observer failure and are not rolled back when a token tx is broadcast, increasing reliability of multi-output token transfers. - Cross-language consistency: introduced/iterated on after_send_token hooks to correlate provisional and final txids; later refined to a polymorphic after_send model aligned with before_send semantics across Rust, WASM/JS, and bindings. - Major bugs fixed: - Align broadcast final outputs with requested receiver outputs validation; ensure outputs match post-broadcast state; address token signing hash alignment for compatibility with spark-token-primitives. - Prevent post-broadcast path from erasing or duplicating token outputs; fix outpoint-based dedup across Postgres/MySQL backends and wasm/JS stores. - Preserve reservation state through broadcast failures and ensure proper error handling without rolling back worked outputs. - CI, test infra, and quality improvements: - CI triggers and macOS toolchain activation for docs/test jobs; ensure Rust toolchain default and rustls provider are installed for test stability; code formatting and minor cleanups to reduce noise and improve readability. - Technologies/skills demonstrated: - Rust, SQL (Postgres/MySQL), WASM/JS bindings, token primitives, outpoint-based data modeling, migration strategies, CI automation, and cross-language API design. - Overall impact and business value: - Higher throughput and lower latency by removing unnecessary post-broadcast refresh round trips; improved data correctness and stability across stores; more robust reservation lifecycle during token transfers; better developer productivity through unified APIs and improved tooling.
May 2026
55 Commits • 11 Features
May 1, 2026May 2026 performance summary for breez/spark-sdk: - Focused on delivering core Spark SDK improvements to support scalable token transfers, improve data integrity, and strengthen CI reliability. - Key features delivered: - Spark Token Broadcast: migrated to V3 single-phase broadcast flow, populated FinalTokenOutput IDs, and aligned token outputs to use the response-provided id, reducing reliance on post-broadcast refresh trips. - TokenOutput identity and dedup refactor: derived TokenOutput.id from outpoints; re-keyed SQL stores and wasm/JS token stores on (prev_tx_hash, prev_tx_vout); implemented outpoint-based dedup to prevent duplicate spends and streamline reconciliation. - Reservation flow resilience: fixed handling so reservations are not canceled on post-broadcast observer failure and are not rolled back when a token tx is broadcast, increasing reliability of multi-output token transfers. - Cross-language consistency: introduced/iterated on after_send_token hooks to correlate provisional and final txids; later refined to a polymorphic after_send model aligned with before_send semantics across Rust, WASM/JS, and bindings. - Major bugs fixed: - Align broadcast final outputs with requested receiver outputs validation; ensure outputs match post-broadcast state; address token signing hash alignment for compatibility with spark-token-primitives. - Prevent post-broadcast path from erasing or duplicating token outputs; fix outpoint-based dedup across Postgres/MySQL backends and wasm/JS stores. - Preserve reservation state through broadcast failures and ensure proper error handling without rolling back worked outputs. - CI, test infra, and quality improvements: - CI triggers and macOS toolchain activation for docs/test jobs; ensure Rust toolchain default and rustls provider are installed for test stability; code formatting and minor cleanups to reduce noise and improve readability. - Technologies/skills demonstrated: - Rust, SQL (Postgres/MySQL), WASM/JS bindings, token primitives, outpoint-based data modeling, migration strategies, CI automation, and cross-language API design. - Overall impact and business value: - Higher throughput and lower latency by removing unnecessary post-broadcast refresh round trips; improved data correctness and stability across stores; more robust reservation lifecycle during token transfers; better developer productivity through unified APIs and improved tooling.
Activity
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Quality Metrics
Correctness96.4%
Maintainability89.8%
Architecture94.0%
Performance90.6%
AI Usage41.4%
Skills & Technologies
Programming Languages
C#DartGoJavaScriptKotlinNonePythonRustSwiftTypeScript
Technical Skills
API designAPI developmentAsynchronous ProgrammingC#CI/CDClippyCode RefactoringCode quality improvementContinuous IntegrationCross-Platform DevelopmentDartDevOpsGitGitHub ActionsGo
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