nominal-io/nominal-client
Oct 2024 – Oct 2025
13 Months active
Languages Used
PythonShellMarkdownYAMLTOMLprotobufRust
Technical Skills
Backend DevelopmentData EngineeringAPI DevelopmentAPI IntegrationCloud Storage IntegrationData Ingestion
Drake Eidukas
PROFILE
Drake Eidukas
Drake developed and maintained the nominal-io/nominal-client repository over 13 months, delivering 61 features and resolving 15 bugs to advance data ingestion, export, and governance workflows. He engineered robust backend systems using Python and Rust, integrating technologies like Pandas, FFmpeg, and Polars to support high-throughput data pipelines, video processing, and parallelized exports. His work included API design, CLI tooling, and asynchronous logging, with a focus on reliability, performance, and maintainability. By refactoring core modules, modernizing CI/CD, and enhancing security and configuration management, Drake ensured the client remained scalable, cross-platform, and aligned with evolving data engineering requirements.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
123Total
Bugs
15
Commits
123
Features
61
Lines of code
46,064
Activity Months13
Your Network
28 people
Work History
October 2025
10 Commits • 4 Features
Oct 1, 2025October 2025: Delivered key data workflows, performance features, and reliability improvements in nominal-client. Highlights include MATLAB export to .mat with a MATLAB-focused download CLI (supports time ranges, resolutions, forward-filling, and CSV/Parquet outputs), Polars export enhancements for datasources, and Rust-based streaming for the public client. Fixed a misleading channel warning in datasource_to_dataframe, added event_url to data reviews for richer metadata, and ensured ingest/default initialization and CI linting improvements. Tech impact: enables faster data extraction for MATLAB workloads, richer data review context, improved streaming performance, and stronger code quality.
10 Commits • 4 Features
Oct 1, 2025October 2025: Delivered key data workflows, performance features, and reliability improvements in nominal-client. Highlights include MATLAB export to .mat with a MATLAB-focused download CLI (supports time ranges, resolutions, forward-filling, and CSV/Parquet outputs), Polars export enhancements for datasources, and Rust-based streaming for the public client. Fixed a misleading channel warning in datasource_to_dataframe, added event_url to data reviews for richer metadata, and ensured ingest/default initialization and CI linting improvements. Tech impact: enables faster data extraction for MATLAB workloads, richer data review context, improved streaming performance, and stronger code quality.
October 2025
September 2025
9 Commits • 4 Features
Sep 1, 2025September 2025: Delivered substantive enhancements to the Expressions DSL (batch compute and enum support), enabling scalable batch analytics and asset/datasource/run-based enum expressions, along with data exploration improvements via channel tags retrieval. Implemented NominalLogHandler default arguments to ensure default metadata is automatically included in logs, improving observability. Strengthened release engineering and tooling with CI/CD automation, Python policy updates (Python 3.14 support, dropping 3.9), and targeted workspace search refactors to improve developer productivity and release reliability. These changes collectively expand the platform's analytics capabilities, improve data discovery, and accelerate safe deployments, delivering measurable business value and higher team velocity.
September 2025
9 Commits • 4 Features
Sep 1, 2025September 2025: Delivered substantive enhancements to the Expressions DSL (batch compute and enum support), enabling scalable batch analytics and asset/datasource/run-based enum expressions, along with data exploration improvements via channel tags retrieval. Implemented NominalLogHandler default arguments to ensure default metadata is automatically included in logs, improving observability. Strengthened release engineering and tooling with CI/CD automation, Python policy updates (Python 3.14 support, dropping 3.9), and targeted workspace search refactors to improve developer productivity and release reliability. These changes collectively expand the platform's analytics capabilities, improve data discovery, and accelerate safe deployments, delivering measurable business value and higher team velocity.
August 2025
14 Commits • 7 Features
Aug 1, 2025August 2025 milestones for nominal-io/nominal-client focused on coupling pipeline reliability with feature-rich data governance and UX improvements. Implemented a more stable CI/CD pipeline, introduced dataset file management capabilities with per-file ingestion polling and metadata exposure, enabled configurable video processing performance, added asynchronous logging streams with improved timing accuracy, and enhanced core data model provenance and navigation URLs to improve traceability and user experience. These changes deliver faster time-to-market for data-driven features, stronger governance, and a smoother, more reliable developer and user experience.
14 Commits • 7 Features
Aug 1, 2025August 2025 milestones for nominal-io/nominal-client focused on coupling pipeline reliability with feature-rich data governance and UX improvements. Implemented a more stable CI/CD pipeline, introduced dataset file management capabilities with per-file ingestion polling and metadata exposure, enabled configurable video processing performance, added asynchronous logging streams with improved timing accuracy, and enhanced core data model provenance and navigation URLs to improve traceability and user experience. These changes deliver faster time-to-market for data-driven features, stronger governance, and a smoother, more reliable developer and user experience.
August 2025
July 2025
12 Commits • 8 Features
Jul 1, 2025July 2025 monthly summary for nominal-client focused on delivering business value through API modernization, enhanced observability, data delivery capabilities, and maintainability improvements. Highlights include deprecations cleanup aligned with newer dataset/connection APIs, richer event modeling with lifecycle controls, improved logging/export and asynchronous upload, dataset download capabilities, and a substantial codebase refactor with tooling enhancements.
July 2025
12 Commits • 8 Features
Jul 1, 2025July 2025 monthly summary for nominal-client focused on delivering business value through API modernization, enhanced observability, data delivery capabilities, and maintainability improvements. Highlights include deprecations cleanup aligned with newer dataset/connection APIs, richer event modeling with lifecycle controls, improved logging/export and asynchronous upload, dataset download capabilities, and a substantial codebase refactor with tooling enhancements.
June 2025
23 Commits • 14 Features
Jun 1, 2025June 2025 performance summary for nominal-client (nominal-io/nominal-client): Focused on boosting data pipeline performance, data integrity, and developer experience through a set of targeted feature deliveries and reliability fixes. The month delivered significant improvements to data export, ingestion, and management workflows, while aligning dependencies and cross-platform compatibility to support broader adoption and easier maintenance. Key features delivered: - Gzip configuration and export compression: introduced a global gzip level constant and enabled gzip during pandas export. - Parallelize data exports: parallelized exporting data to DataFrames to improve throughput and reduce wall-clock time for large exports. - Upload and attachment enhancements: added support for uploading pandas DataFrames to existing datasets, creating attachments from filepaths, tagging uploads, and TDMS file uploads. - Datasources and runs management: enabled adding datasources to runs and assets with tags and offsets to improve data lineage and organization. - CLI client creation by profile and API/protos version bumps: enable creating clients by profile in CLI decorators and updated nominal-api and nominal-api-protos versions for smoother installations and compatibility. Major bugs fixed: - DataFrame indexing fix: ensured dataframe uses timestamps as the index column when converting from datasource, fixing indexing and downstream query issues. - Windows compatibility fix: resolved Conjure Python Client issues on Windows machines for 2.9.0+ deployments. - Data correctness fixes: timestamps previously returned as strings with incorrect column headers; standardized TypeAlias for Union over string to improve type safety and correctness. Overall impact and accomplishments: - Performance: parallel exports and gzip compression reduce storage footprint and accelerate large-data workflows, enabling faster reporting and analytics. - Data integrity: correct timestamp indexing and data formatting improve reliability of downstream analyses and dashboards. - Ingestion and governance: enriched datasource/run management and attachment workflows streamline data intake, tagging, and provenance. - Developer and deployment experience: profile-based CLI client creation, up-to-date dependencies, and cross-platform fixes reduce onboarding time and maintenance burden. Technologies/skills demonstrated: - Python and pandas optimizations, gzip handling, and data serialization. - Parallel processing and performance-focused design. - API versioning and dependency management (nominal-api, nominal-api-protos). - Data governance features (tags, offsets), attachments, TDMS support, and enhanced CLI tooling. - Cross-platform reliability improvements (Windows compatibility) and code hygiene (deprecations and utilities consolidation).
23 Commits • 14 Features
Jun 1, 2025June 2025 performance summary for nominal-client (nominal-io/nominal-client): Focused on boosting data pipeline performance, data integrity, and developer experience through a set of targeted feature deliveries and reliability fixes. The month delivered significant improvements to data export, ingestion, and management workflows, while aligning dependencies and cross-platform compatibility to support broader adoption and easier maintenance. Key features delivered: - Gzip configuration and export compression: introduced a global gzip level constant and enabled gzip during pandas export. - Parallelize data exports: parallelized exporting data to DataFrames to improve throughput and reduce wall-clock time for large exports. - Upload and attachment enhancements: added support for uploading pandas DataFrames to existing datasets, creating attachments from filepaths, tagging uploads, and TDMS file uploads. - Datasources and runs management: enabled adding datasources to runs and assets with tags and offsets to improve data lineage and organization. - CLI client creation by profile and API/protos version bumps: enable creating clients by profile in CLI decorators and updated nominal-api and nominal-api-protos versions for smoother installations and compatibility. Major bugs fixed: - DataFrame indexing fix: ensured dataframe uses timestamps as the index column when converting from datasource, fixing indexing and downstream query issues. - Windows compatibility fix: resolved Conjure Python Client issues on Windows machines for 2.9.0+ deployments. - Data correctness fixes: timestamps previously returned as strings with incorrect column headers; standardized TypeAlias for Union over string to improve type safety and correctness. Overall impact and accomplishments: - Performance: parallel exports and gzip compression reduce storage footprint and accelerate large-data workflows, enabling faster reporting and analytics. - Data integrity: correct timestamp indexing and data formatting improve reliability of downstream analyses and dashboards. - Ingestion and governance: enriched datasource/run management and attachment workflows streamline data intake, tagging, and provenance. - Developer and deployment experience: profile-based CLI client creation, up-to-date dependencies, and cross-platform fixes reduce onboarding time and maintenance burden. Technologies/skills demonstrated: - Python and pandas optimizations, gzip handling, and data serialization. - Parallel processing and performance-focused design. - API versioning and dependency management (nominal-api, nominal-api-protos). - Data governance features (tags, offsets), attachments, TDMS support, and enhanced CLI tooling. - Cross-platform reliability improvements (Windows compatibility) and code hygiene (deprecations and utilities consolidation).
June 2025
May 2025
2 Commits • 1 Features
May 1, 2025Monthly summary for 2025-05 (nominal-io/nominal-client). Key features delivered: - Gzip compression for POST requests: Introduced GzipRequestsAdapter and updated ClientsBunch to use a factory incorporating this adapter, enabling faster data transfer in bandwidth-constrained environments. Commit: b45fb2b830b7bd21d322f5d5ae133dbb696fc77d. Impact: reduces payload size and improves throughput for large POST payloads. - Include workspace parameter when creating empty video: Fixed by passing workspace RID in the video creation request to correctly associate the video with its workspace. Commit: 1f42e11baddb43743dba2636f064ea6e30f055a3. Impact: ensures correct workspace association and prevents orphaned video records.
May 2025
2 Commits • 1 Features
May 1, 2025Monthly summary for 2025-05 (nominal-io/nominal-client). Key features delivered: - Gzip compression for POST requests: Introduced GzipRequestsAdapter and updated ClientsBunch to use a factory incorporating this adapter, enabling faster data transfer in bandwidth-constrained environments. Commit: b45fb2b830b7bd21d322f5d5ae133dbb696fc77d. Impact: reduces payload size and improves throughput for large POST payloads. - Include workspace parameter when creating empty video: Fixed by passing workspace RID in the video creation request to correctly associate the video with its workspace. Commit: 1f42e11baddb43743dba2636f064ea6e30f055a3. Impact: ensures correct workspace association and prevents orphaned video records.
April 2025
11 Commits • 7 Features
Apr 1, 2025April 2025 performance summary for nominal-client focused on expanding data formats, streaming capabilities, API hygiene, and security features to improve developer productivity, data quality, and platform flexibility.
11 Commits • 7 Features
Apr 1, 2025April 2025 performance summary for nominal-client focused on expanding data formats, streaming capabilities, API hygiene, and security features to improve developer productivity, data quality, and platform flexibility.
April 2025
March 2025
18 Commits • 5 Features
Mar 1, 2025March 2025 – Nominal Client: Delivered major end-to-end media and data-management enhancements that drive faster ingestion, higher data quality, and improved governance. Business value realized through streamlined video asset management with MCAP-based ingestion and a standard ffmpeg dependency, expanded dataset and file ingestion capabilities (including journald JSON logs and improved upload naming), enhanced data discovery and QA via checklist execution and data review search, and flexible configuration for channels and data sources with asset-scoped utilities. A stability fix corrected channel prefix handling to prevent ingestion errors and misassignment.
March 2025
18 Commits • 5 Features
Mar 1, 2025March 2025 – Nominal Client: Delivered major end-to-end media and data-management enhancements that drive faster ingestion, higher data quality, and improved governance. Business value realized through streamlined video asset management with MCAP-based ingestion and a standard ffmpeg dependency, expanded dataset and file ingestion capabilities (including journald JSON logs and improved upload naming), enhanced data discovery and QA via checklist execution and data review search, and flexible configuration for channels and data sources with asset-scoped utilities. A stability fix corrected channel prefix handling to prevent ingestion errors and misassignment.
February 2025
1 Commits • 1 Features
Feb 1, 2025February 2025: Delivered unified Ingest V2 API support in the nominal-client (nominal-io/nominal-client). The Python client now consistently uses the ingest V2 endpoint across datasets, videos, and MCAP, with refactored request structures to align with V2 and improved error handling for dataset and video creation. No major bugs fixed this month. Impact: simplifies ingestion workflows, reduces endpoint fragmentation, and improves reliability for data pipelines. Technologies: Python client development, API versioning, refactoring for API consistency, and enhanced error handling.
1 Commits • 1 Features
Feb 1, 2025February 2025: Delivered unified Ingest V2 API support in the nominal-client (nominal-io/nominal-client). The Python client now consistently uses the ingest V2 endpoint across datasets, videos, and MCAP, with refactored request structures to align with V2 and improved error handling for dataset and video creation. No major bugs fixed this month. Impact: simplifies ingestion workflows, reduces endpoint fragmentation, and improves reliability for data pipelines. Technologies: Python client development, API versioning, refactoring for API consistency, and enhanced error handling.
February 2025
January 2025
7 Commits • 4 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments, major features delivered, and impact for the nominal-client. Emphasis on business value, data governance, searchability, secure artifact handling, and developer tooling improvements.
January 2025
7 Commits • 4 Features
Jan 1, 2025January 2025 monthly summary focusing on key accomplishments, major features delivered, and impact for the nominal-client. Emphasis on business value, data governance, searchability, secure artifact handling, and developer tooling improvements.
December 2024
6 Commits • 2 Features
Dec 1, 2024Concise monthly summary for 2024-12 focusing on business value and technical achievements for nominal-client. This month delivered major security and media-handling features, along with developer tooling improvements that streamline code quality. Key client features include SSL trust store integration and expanded video/data ingestion capabilities. A targeted tooling improvement improved the code cleanup workflow. Overall, these efforts reduce risk, accelerate data onboarding, and enhance developer productivity.
6 Commits • 2 Features
Dec 1, 2024Concise monthly summary for 2024-12 focusing on business value and technical achievements for nominal-client. This month delivered major security and media-handling features, along with developer tooling improvements that streamline code quality. Key client features include SSL trust store integration and expanded video/data ingestion capabilities. A targeted tooling improvement improved the code cleanup workflow. Overall, these efforts reduce risk, accelerate data onboarding, and enhance developer productivity.
December 2024
November 2024
7 Commits • 2 Features
Nov 1, 2024Concise monthly summary for 2024-11 focusing on business value and technical achievements for nominal-io/nominal-client. Highlights delivered features, with traceable commits, and notes on impact and skills demonstrated.
November 2024
7 Commits • 2 Features
Nov 1, 2024Concise monthly summary for 2024-11 focusing on business value and technical achievements for nominal-io/nominal-client. Highlights delivered features, with traceable commits, and notes on impact and skills demonstrated.
October 2024
3 Commits • 2 Features
Oct 1, 2024October 2024 monthly work summary for nominal-client (repo: nominal-io/nominal-client). Key accomplishments include feature delivery for Nominal App Integration and Dataset Bounds support, with code changes enabling better linking in Nominal app and improved data bounds handling. No major bugs fixed documented this month; focus was on data-model evolution and cross-system integration. Overall impact: improved data fidelity, traceability, and maintainability; technologies demonstrated: Python dataclasses, API data propagation, Scout catalog parsing, time conversions, and commit-level traceability.
3 Commits • 2 Features
Oct 1, 2024October 2024 monthly work summary for nominal-client (repo: nominal-io/nominal-client). Key accomplishments include feature delivery for Nominal App Integration and Dataset Bounds support, with code changes enabling better linking in Nominal app and improved data bounds handling. No major bugs fixed documented this month; focus was on data-model evolution and cross-system integration. Overall impact: improved data fidelity, traceability, and maintainability; technologies demonstrated: Python dataclasses, API data propagation, Scout catalog parsing, time conversions, and commit-level traceability.
October 2024
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Quality Metrics
Correctness91.2%
Maintainability89.0%
Architecture89.0%
Performance84.0%
AI Usage20.4%
Skills & Technologies
Programming Languages
MarkdownPythonRustShellTOMLYAMLprotobuf
Technical Skills
API DesignAPI DevelopmentAPI IntegrationAsynchronous ProgrammingBackend DevelopmentBackground ThreadsBug FixBuild ConfigurationBuild System ConfigurationCI/CDCI/CD Pipeline ManagementCLI DevelopmentClickCloud StorageCloud Storage Integration
Repositories Contributed To
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