Keck-DataReductionPipelines/KPF-Pipeline
Oct 2024 – Dec 2025
15 Months active
Languages Used
PythonShellBashCSVRSTSQLcfgrst
Technical Skills
Data AnalysisData VisualizationDocumentationImage ProcessingPythonQuality Control
Andrew Howard
PROFILE
Andrew Howard
Andrew Howard developed core data reduction and analysis capabilities for the Keck-DataReductionPipelines/KPF-Pipeline, focusing on robust data quality control, visualization, and scalable ingestion workflows. He engineered features such as parallelized data ingestion, YAML-driven plotting, and advanced quality checks, integrating Python, SQL, and Pandas to streamline scientific data processing. His work included implementing database access controls, refining time series analysis, and enhancing observability through improved logging and diagnostics. By addressing concurrency, configuration management, and documentation, Andrew ensured the pipeline delivered reliable, reproducible results. The depth of his contributions strengthened both backend reliability and user-facing analytics for astronomical data workflows.
Overall Statistics
Feature vs Bugs
74%Features
Repository Contributions
909Total
Bugs
134
Commits
909
Features
375
Lines of code
411,884
Activity Months15
Your Network
15 people
Work History
December 2025
15 Commits • 3 Features
Dec 1, 2025December 2025 — Keck-DataReductionPipelines/KPF-Pipeline delivered a focused set of visualization and pipeline improvements, strengthening user experience, data quality checks, and documentation. The work enhanced plotting robustness, clarified configuration, and streamlined data ingestion validation, aligning technical execution with business value and faster insight generation.
15 Commits • 3 Features
Dec 1, 2025December 2025 — Keck-DataReductionPipelines/KPF-Pipeline delivered a focused set of visualization and pipeline improvements, strengthening user experience, data quality checks, and documentation. The work enhanced plotting robustness, clarified configuration, and streamlined data ingestion validation, aligning technical execution with business value and faster insight generation.
December 2025
November 2025
22 Commits • 8 Features
Nov 1, 2025November 2025 focused on delivering robust data processing enhancements for the Keck-DataReductionPipelines/KPF-Pipeline, improving metadata accuracy, data definitions, and pipeline reliability while strengthening CI/CD and documentation for safer, faster deployments.
November 2025
22 Commits • 8 Features
Nov 1, 2025November 2025 focused on delivering robust data processing enhancements for the Keck-DataReductionPipelines/KPF-Pipeline, improving metadata accuracy, data definitions, and pipeline reliability while strengthening CI/CD and documentation for safer, faster deployments.
October 2025
41 Commits • 16 Features
Oct 1, 2025October 2025 saw the KPF-Pipeline deliver diagnostic and data-management enhancements, targeted bug fixes, and tooling improvements that improve data quality, observability, and pipeline reliability. The work reduces downstream errors, accelerates diagnostics and plotting, and strengthens the data architecture for scalable analyses.
41 Commits • 16 Features
Oct 1, 2025October 2025 saw the KPF-Pipeline deliver diagnostic and data-management enhancements, targeted bug fixes, and tooling improvements that improve data quality, observability, and pipeline reliability. The work reduces downstream errors, accelerates diagnostics and plotting, and strengthens the data architecture for scalable analyses.
October 2025
September 2025
49 Commits • 17 Features
Sep 1, 2025September 2025: Delivered core analytics and observability enhancements for Keck-DataReductionPipelines/KPF-Pipeline, while stabilizing CI and improving data quality workflows. Key outputs include a Days Since Calculation feature for data quality monitoring; standardized CI Docker image/tag usage to improve reliability; RV time series plotting enhancements with start/ timebin support; added plotting for nightly campaigns to visualize performance; updated KPfera definitions CSV to latest values to ensure accurate calibration workflows. These efforts reduce operational risk, improve data quality, and accelerate science-ready results.
September 2025
49 Commits • 17 Features
Sep 1, 2025September 2025: Delivered core analytics and observability enhancements for Keck-DataReductionPipelines/KPF-Pipeline, while stabilizing CI and improving data quality workflows. Key outputs include a Days Since Calculation feature for data quality monitoring; standardized CI Docker image/tag usage to improve reliability; RV time series plotting enhancements with start/ timebin support; added plotting for nightly campaigns to visualize performance; updated KPfera definitions CSV to latest values to ensure accurate calibration workflows. These efforts reduce operational risk, improve data quality, and accelerate science-ready results.
August 2025
56 Commits • 24 Features
Aug 1, 2025Aug 2025 performance summary for Keck-DataReductionPipelines/KPF-Pipeline. Delivered security hardening, data integrity improvements, core science capabilities, and governance enhancements, while expanding observability and external integrations. Focused on reducing risk, improving data quality, and accelerating robust analysis workflows for downstream users and teams.
56 Commits • 24 Features
Aug 1, 2025Aug 2025 performance summary for Keck-DataReductionPipelines/KPF-Pipeline. Delivered security hardening, data integrity improvements, core science capabilities, and governance enhancements, while expanding observability and external integrations. Focused on reducing risk, improving data quality, and accelerating robust analysis workflows for downstream users and teams.
August 2025
July 2025
99 Commits • 47 Features
Jul 1, 2025July 2025 highlights for Keck-DataReductionPipelines/KPF-Pipeline: Delivered core feature enhancements, improved data quality controls, and targeted fixes across the pipeline, driving reliability and faster time-to-insight for downstream analyses.
July 2025
99 Commits • 47 Features
Jul 1, 2025July 2025 highlights for Keck-DataReductionPipelines/KPF-Pipeline: Delivered core feature enhancements, improved data quality controls, and targeted fixes across the pipeline, driving reliability and faster time-to-insight for downstream analyses.
June 2025
67 Commits • 26 Features
Jun 1, 20252025-06 Monthly Summary for Keck-DataReductionPipelines/KPF-Pipeline. This month focused on delivering secure, reliable data processing capabilities, improving observability, and enhancing developer experience through a combination of backend, tooling, and documentation work. Major stability and security wins were achieved while expanding capabilities for data analysis and API usage. Business value centers on strengthened data governance, increased pipeline reliability, and faster, clearer data insights for the team and stakeholders.
67 Commits • 26 Features
Jun 1, 20252025-06 Monthly Summary for Keck-DataReductionPipelines/KPF-Pipeline. This month focused on delivering secure, reliable data processing capabilities, improving observability, and enhancing developer experience through a combination of backend, tooling, and documentation work. Major stability and security wins were achieved while expanding capabilities for data analysis and API usage. Business value centers on strengthened data governance, increased pipeline reliability, and faster, clearer data insights for the team and stakeholders.
June 2025
May 2025
85 Commits • 40 Features
May 1, 2025Month: 2025-05 Overview: Delivered a set of feature enhancements and stability fixes to the KPF-Pipeline, with a focus on data quality, reproducibility, and maintainability. Strong emphasis on robust data access (DB/TSDB), enhanced plotting/diagnostics for faster insight, and integrated reprocessing workflows to support repeatable science. Improved observability, error handling, and configuration flexibility to scale across backends and environments.
May 2025
85 Commits • 40 Features
May 1, 2025Month: 2025-05 Overview: Delivered a set of feature enhancements and stability fixes to the KPF-Pipeline, with a focus on data quality, reproducibility, and maintainability. Strong emphasis on robust data access (DB/TSDB), enhanced plotting/diagnostics for faster insight, and integrated reprocessing workflows to support repeatable science. Improved observability, error handling, and configuration flexibility to scale across backends and environments.
April 2025
109 Commits • 46 Features
Apr 1, 2025April 2025 performance summary for Keck-DataReductionPipelines/KPF-Pipeline focused on delivering business value through reliability, performance, and clearer data insights. Key investments included robust Xdisp offset utilities, refined plotting for actionable visuals, and hardened concurrency for higher throughput. The month also saw improvements in data ingestion workflows, QC robustness, and maintainability, enabling faster capability delivery and easier future enhancements.
109 Commits • 46 Features
Apr 1, 2025April 2025 performance summary for Keck-DataReductionPipelines/KPF-Pipeline focused on delivering business value through reliability, performance, and clearer data insights. Key investments included robust Xdisp offset utilities, refined plotting for actionable visuals, and hardened concurrency for higher throughput. The month also saw improvements in data ingestion workflows, QC robustness, and maintainability, enabling faster capability delivery and easier future enhancements.
April 2025
March 2025
87 Commits • 39 Features
Mar 1, 2025March 2025 summary for Keck-DataReductionPipelines/KPF-Pipeline: Delivered a strong set of core data-reduction features, expanded QC coverage, and improved performance and developer ergonomics. Key features include: (1) measure_good_comb_orders implemented with initial and working versions, enabling robust combination ordering for downstream calibration; (2) L1/LFC lines handling with L1_LFC_lines() and add_headers_L1_LFC_lines(), improving header parsing and line association; (3) LFC line diagnostics and Etalon line tests with accompanying tutorials updates to reflect QC/diagnostics; (4) keyboard/keyword ecosystem expansion, including STDWREF keyword and extensive keyword support; (5) L1 standard WLS header support and dispersion-related updates; (6) performance and reliability improvements via multithreading (20 threads per data level), dispersion arrays initialization, and updated plot configurations. Major bugs fixed include syntax errors, merge conflicts, and multiple data-quality/compatibility issues (Astropy table fixes, escape sequence handling, numeric validation for TARG, and keyword/comment inconsistencies), along with cleanup of debug prints and filename standardization. The cumulative impact is a more reliable, scalable, and faster data-reduction pipeline with broader QC coverage (LFC/Etalon, Guider performance) and stronger documentation around keywords and usage. Technologies and skills demonstrated include Python, multithreading, QC workflow design, Astropy compatibility considerations, keyword architecture and metadata management, code readability improvements, and Sphinx/documentation tooling and Python version compatibility updates.
March 2025
87 Commits • 39 Features
Mar 1, 2025March 2025 summary for Keck-DataReductionPipelines/KPF-Pipeline: Delivered a strong set of core data-reduction features, expanded QC coverage, and improved performance and developer ergonomics. Key features include: (1) measure_good_comb_orders implemented with initial and working versions, enabling robust combination ordering for downstream calibration; (2) L1/LFC lines handling with L1_LFC_lines() and add_headers_L1_LFC_lines(), improving header parsing and line association; (3) LFC line diagnostics and Etalon line tests with accompanying tutorials updates to reflect QC/diagnostics; (4) keyboard/keyword ecosystem expansion, including STDWREF keyword and extensive keyword support; (5) L1 standard WLS header support and dispersion-related updates; (6) performance and reliability improvements via multithreading (20 threads per data level), dispersion arrays initialization, and updated plot configurations. Major bugs fixed include syntax errors, merge conflicts, and multiple data-quality/compatibility issues (Astropy table fixes, escape sequence handling, numeric validation for TARG, and keyword/comment inconsistencies), along with cleanup of debug prints and filename standardization. The cumulative impact is a more reliable, scalable, and faster data-reduction pipeline with broader QC coverage (LFC/Etalon, Guider performance) and stronger documentation around keywords and usage. Technologies and skills demonstrated include Python, multithreading, QC workflow design, Astropy compatibility considerations, keyword architecture and metadata management, code readability improvements, and Sphinx/documentation tooling and Python version compatibility updates.
February 2025
40 Commits • 13 Features
Feb 1, 2025February 2025 – Keck-DataReductionPipelines/KPF-Pipeline: Delivered substantial usability, reliability, and capability improvements across documentation, plotting, performance, and new instrument-diagnostic features. Enhancements were implemented through a breadth of commits spanning documentation, UI/plot improvements, keyword system upgrades, and plotting refinements, with a strong emphasis on reproducibility and data quality. Key features delivered include: - Documentation improvements: docstrings and wording updates, tutorials, and updated citations to improve onboarding and usage clarity. - Plotting and visualization: enhancements for annotations, formatting, and reference comparisons; new quicklook plots (e.g., BCVel per order); improved row handling and alphabetically sorted plot states; integration of dark-subtraction and bias-subtraction within QA workflows. - Ingestion and performance: faster data ingestion to reduce processing bottlenecks. - Instrument diagnostics and keywords: addition of power-meter keywords; TIMEERR and vignetting keywords; L1_FLAT_SNR QC; Gold lamps support. - Maintenance and cleanup: ongoing maintenance commits to keep the codebase healthy. Major bugs fixed: - General bug fixes across the batch processing pipeline. - Added KeyError handling and key existence checks to prevent crashes. - Filename-related fixes and error corrections to improve stability. Overall impact and accomplishments: - Raised data quality, reliability, and reproducibility of the Keck KPF pipeline, enabling faster, more dependable analyses and better instrument diagnostics. - Improved user experience and documentation, reducing onboarding time and support needs for new users. - Strengthened pipeline robustness against common edge cases and file issues, contributing to smoother day-to-day operations. Technologies/skills demonstrated: - Python development, data visualization, and plotting techniques - Debugging, exception handling, and defensive programming - Performance optimization (faster ingestion) - Documentation discipline (docstrings, tutorials, citations) - Instrument diagnostics and keyword-driven metadata enhancements
40 Commits • 13 Features
Feb 1, 2025February 2025 – Keck-DataReductionPipelines/KPF-Pipeline: Delivered substantial usability, reliability, and capability improvements across documentation, plotting, performance, and new instrument-diagnostic features. Enhancements were implemented through a breadth of commits spanning documentation, UI/plot improvements, keyword system upgrades, and plotting refinements, with a strong emphasis on reproducibility and data quality. Key features delivered include: - Documentation improvements: docstrings and wording updates, tutorials, and updated citations to improve onboarding and usage clarity. - Plotting and visualization: enhancements for annotations, formatting, and reference comparisons; new quicklook plots (e.g., BCVel per order); improved row handling and alphabetically sorted plot states; integration of dark-subtraction and bias-subtraction within QA workflows. - Ingestion and performance: faster data ingestion to reduce processing bottlenecks. - Instrument diagnostics and keywords: addition of power-meter keywords; TIMEERR and vignetting keywords; L1_FLAT_SNR QC; Gold lamps support. - Maintenance and cleanup: ongoing maintenance commits to keep the codebase healthy. Major bugs fixed: - General bug fixes across the batch processing pipeline. - Added KeyError handling and key existence checks to prevent crashes. - Filename-related fixes and error corrections to improve stability. Overall impact and accomplishments: - Raised data quality, reliability, and reproducibility of the Keck KPF pipeline, enabling faster, more dependable analyses and better instrument diagnostics. - Improved user experience and documentation, reducing onboarding time and support needs for new users. - Strengthened pipeline robustness against common edge cases and file issues, contributing to smoother day-to-day operations. Technologies/skills demonstrated: - Python development, data visualization, and plotting techniques - Debugging, exception handling, and defensive programming - Performance optimization (faster ingestion) - Documentation discipline (docstrings, tutorials, citations) - Instrument diagnostics and keyword-driven metadata enhancements
February 2025
January 2025
137 Commits • 55 Features
Jan 1, 2025January 2025: Delivered configurable plotting and data handling capabilities for the Keck-DataReductionPipelines/KPF-Pipeline, strengthening visualization fidelity, data integrity, and deployment reliability. Key milestones include YAML-driven plot configuration enabling centralized YAML-based plotting and multi-panel layouts; Delta plot feature for visual data comparisons; KPFERA 2.6 integration; ingestion pathway enhancements plus dispersion plotting; and CI/QA improvements with documentation updates enabling safer, faster releases.
January 2025
137 Commits • 55 Features
Jan 1, 2025January 2025: Delivered configurable plotting and data handling capabilities for the Keck-DataReductionPipelines/KPF-Pipeline, strengthening visualization fidelity, data integrity, and deployment reliability. Key milestones include YAML-driven plot configuration enabling centralized YAML-based plotting and multi-panel layouts; Delta plot feature for visual data comparisons; KPFERA 2.6 integration; ingestion pathway enhancements plus dispersion plotting; and CI/QA improvements with documentation updates enabling safer, faster releases.
December 2024
57 Commits • 26 Features
Dec 1, 2024December 2024 monthly summary for Keck-DataReductionPipelines/KPF-Pipeline: Delivered a set of substantial improvements spanning ingestion performance, QC capabilities, metadata management, and data handling, with a focus on reliability, speed, and maintainability. The work enhanced throughput, data discoverability, and user-facing QC visibility, setting the stage for more robust reductions and analyses going into 2025.
57 Commits • 26 Features
Dec 1, 2024December 2024 monthly summary for Keck-DataReductionPipelines/KPF-Pipeline: Delivered a set of substantial improvements spanning ingestion performance, QC capabilities, metadata management, and data handling, with a focus on reliability, speed, and maintainability. The work enhanced throughput, data discoverability, and user-facing QC visibility, setting the stage for more robust reductions and analyses going into 2025.
December 2024
November 2024
42 Commits • 13 Features
Nov 1, 2024November 2024: Delivered a targeted set of plotting, data access, and configuration improvements for the KPF-Pipeline that directly enhance data quality, visualization, and maintainability. The work strengthens decision-making through more expressive plots, robust data handling, and clearer metadata management. Key updates include updating KPFERA definitions to reflect the latest constants, expanding plotting capabilities with error bars, histograms, and bounding boxes, enabling ObsID persistence and retrieval via a new DB interface, normalizing CAHKPR identifiers to uppercase, and broadening data retrieval API coverage to query all columns and support new keywords. Documentation and docstring improvements further improved maintainability. Critical fixes addressed telemetry extension handling and safer L1 file processing, along with stability improvements for monthly data plotting. Overall, these changes reduce troubleshooting time, improve reproducibility, and enable faster, data-driven decisions.
November 2024
42 Commits • 13 Features
Nov 1, 2024November 2024: Delivered a targeted set of plotting, data access, and configuration improvements for the KPF-Pipeline that directly enhance data quality, visualization, and maintainability. The work strengthens decision-making through more expressive plots, robust data handling, and clearer metadata management. Key updates include updating KPFERA definitions to reflect the latest constants, expanding plotting capabilities with error bars, histograms, and bounding boxes, enabling ObsID persistence and retrieval via a new DB interface, normalizing CAHKPR identifiers to uppercase, and broadening data retrieval API coverage to query all columns and support new keywords. Documentation and docstring improvements further improved maintainability. Critical fixes addressed telemetry extension handling and safer L1 file processing, along with stability improvements for monthly data plotting. Overall, these changes reduce troubleshooting time, improve reproducibility, and enable faster, data-driven decisions.
October 2024
3 Commits • 2 Features
Oct 1, 2024October 2024 for Keck-DataReductionPipelines/KPF-Pipeline delivered two major features focused on data quality and visualization, with documentation updates to support adoption. The work emphasizes business value through improved data quality assessment, clearer diagnostics, and faster data-driven decisions.
3 Commits • 2 Features
Oct 1, 2024October 2024 for Keck-DataReductionPipelines/KPF-Pipeline delivered two major features focused on data quality and visualization, with documentation updates to support adoption. The work emphasizes business value through improved data quality assessment, clearer diagnostics, and faster data-driven decisions.
October 2024
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture86.6%
Performance82.8%
AI Usage20.6%
Skills & Technologies
Programming Languages
BashBibTeXCSSCSVConfigurationDockerfileGitJSONJupyter NotebookMakefile
Technical Skills
API DevelopmentAccess ControlAlgorithm ImplementationArgument ParsingAstronomyAstronomy Data AnalysisAstronomy Data ReductionAstronomy SoftwareAstronomy Software DevelopmentAstrophysics Data ProcessingAstrophysics Data ReductionAstrophysics SoftwareAstropyAutomationBackend Development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline