
William de Montmollin developed and maintained core data infrastructure for DemocracyClub’s EveryElection and UK-Polling-Stations repositories, focusing on backend reliability, geospatial data accuracy, and automation. He engineered robust data importers and management commands in Python and Django, integrating AWS S3 for scalable storage and leveraging PMTiles for efficient map delivery. His work included refining data pipelines, implementing event-driven notifications, and enhancing CI/CD processes to ensure timely, accurate election and boundary data. By addressing data integrity, security, and user experience, William delivered maintainable solutions that improved data quality, streamlined workflows, and supported both administrative and public-facing features across the platform.

Monthly performance summary for 2026-01 highlighting delivered features, major fixes, impact, and technical proficiency across the DemocracyClub repositories.
Monthly performance summary for 2026-01 highlighting delivered features, major fixes, impact, and technical proficiency across the DemocracyClub repositories.
December 2025 consolidated reliability, risk reduction, and user clarity across DemocracyClub repositories. Delivered targeted features, fixed critical bugs, and reinforced maintainability, aligning with business value goals: accurate map tiles, stable data pipelines, and clearer election coverage boundaries.
December 2025 consolidated reliability, risk reduction, and user clarity across DemocracyClub repositories. Delivered targeted features, fixed critical bugs, and reinforced maintainability, aligning with business value goals: accurate map tiles, stable data pipelines, and clearer election coverage boundaries.
October 2025 monthly summary focused on delivering core features, stabilizing infrastructure, and improving data pipelines across DemocracyClub repos. The work emphasizes security, reliability, and user-facing accuracy, with a strong emphasis on business value, faster deployments, and better data visibility.
October 2025 monthly summary focused on delivering core features, stabilizing infrastructure, and improving data pipelines across DemocracyClub repos. The work emphasizes security, reliability, and user-facing accuracy, with a strong emphasis on business value, faster deployments, and better data visibility.
Concise monthly summary for 2025-09 focusing on both DemocracyClub/EveryElection and DemocracyClub/UK-Polling-Stations. Highlighted achievements center on PMTiles improvements, layer management, UI reliability, data integrity, and messaging clarity that drive business value and system resilience.
Concise monthly summary for 2025-09 focusing on both DemocracyClub/EveryElection and DemocracyClub/UK-Polling-Stations. Highlighted achievements center on PMTiles improvements, layer management, UI reliability, data integrity, and messaging clarity that drive business value and system resilience.
August 2025 monthly summary for Democracy Club developer work across the Elections and UK-Polling-Stations repos, focusing on end-to-end map delivery improvements, geospatial context enrichments, testing and tooling enhancements, and CI/CD robustness.
August 2025 monthly summary for Democracy Club developer work across the Elections and UK-Polling-Stations repos, focusing on end-to-end map delivery improvements, geospatial context enrichments, testing and tooling enhancements, and CI/CD robustness.
July 2025 — DemocracyClub/EveryElection Key features delivered: - Election historic data update command: Django management command to import historic election data from a CSV, updating seats_contested and seats_total in the Election model; includes a dry-run to preview changes before applying. - Boundary data import commands for SP and Senedd: Django management commands to import Scottish Parliament and Senedd boundaries from shapefiles, creating divisions and geography records and linking them to organisations; includes data integrity checks. - Code quality improvement: Refactored get_geography_link to use f-strings for readability without changing functionality. Major bugs fixed: - No major bugs reported this month. Stability improved via focused data-import workflows and a minor code-quality refactor. Overall impact and accomplishments: - Significantly improved data integrity and maintainability: safer, scalable data updates for historic elections and regional boundaries. Dry-run support reduces risk of unintended changes, and boundary imports extend data coverage to SP and Senedd, enabling richer analytics and reporting. Technologies/skills demonstrated: - Python, Django management commands, CSV parsing, shapefile data import, data integrity handling, code refactoring, and use of f-strings; emphasis on maintainability and automated validation. Business value: - Reduces manual data curation, improves accuracy of historic election data and boundary geography, enabling faster reporting and better decision-making for stakeholders.
July 2025 — DemocracyClub/EveryElection Key features delivered: - Election historic data update command: Django management command to import historic election data from a CSV, updating seats_contested and seats_total in the Election model; includes a dry-run to preview changes before applying. - Boundary data import commands for SP and Senedd: Django management commands to import Scottish Parliament and Senedd boundaries from shapefiles, creating divisions and geography records and linking them to organisations; includes data integrity checks. - Code quality improvement: Refactored get_geography_link to use f-strings for readability without changing functionality. Major bugs fixed: - No major bugs reported this month. Stability improved via focused data-import workflows and a minor code-quality refactor. Overall impact and accomplishments: - Significantly improved data integrity and maintainability: safer, scalable data updates for historic elections and regional boundaries. Dry-run support reduces risk of unintended changes, and boundary imports extend data coverage to SP and Senedd, enabling richer analytics and reporting. Technologies/skills demonstrated: - Python, Django management commands, CSV parsing, shapefile data import, data integrity handling, code refactoring, and use of f-strings; emphasis on maintainability and automated validation. Business value: - Reduces manual data curation, improves accuracy of historic election data and boundary geography, enabling faster reporting and better decision-making for stakeholders.
May 2025 summary: Implemented automatic normalization of electoral boundary name mapping in DemocracyClub/EveryElection to improve data consistency with legislation names and robustness of imports. The change automatically strips common suffixes from boundary names during mapping, stores the original boundary names for accurate matching and prompts, and enhances import reliability for electoral divisions.
May 2025 summary: Implemented automatic normalization of electoral boundary name mapping in DemocracyClub/EveryElection to improve data consistency with legislation names and robustness of imports. The change automatically strips common suffixes from boundary names during mapping, stores the original boundary names for accurate matching and prompts, and enhances import reliability for electoral divisions.
April 2025 highlights for DemocracyClub/UK-Polling-Stations focused on data quality, geolocation accuracy, and UX improvements. Key features delivered: 1) Polling Station Data Accuracy and Geolocation Improvements — consolidated council data to improve coordinates, UPRN mappings, and address fields; importer logic updated to better ingest council feeds. 2) Example Page SEO and Error UX Improvements — prevented indexing of the example page and refined error UX so the postcode form displays only when relevant. Major bugs fixed: removal of wrong coordinates for SGC and GED stations, reducing mis-location risk and data noise. Overall impact: higher data quality and reliability of polling station information across councils, improved voter experience, and more robust data ingestion. Technical accomplishments: geospatial data handling and cleansing, ETL/importer enhancements, UPRN mapping, SEO/meta-tag adjustments, and UX-focused error handling. Business value: reduced voter confusion and support queries, improved trust in official polling information, and smoother onboarding of new council data sources.
April 2025 highlights for DemocracyClub/UK-Polling-Stations focused on data quality, geolocation accuracy, and UX improvements. Key features delivered: 1) Polling Station Data Accuracy and Geolocation Improvements — consolidated council data to improve coordinates, UPRN mappings, and address fields; importer logic updated to better ingest council feeds. 2) Example Page SEO and Error UX Improvements — prevented indexing of the example page and refined error UX so the postcode form displays only when relevant. Major bugs fixed: removal of wrong coordinates for SGC and GED stations, reducing mis-location risk and data noise. Overall impact: higher data quality and reliability of polling station information across councils, improved voter experience, and more robust data ingestion. Technical accomplishments: geospatial data handling and cleansing, ETL/importer enhancements, UPRN mapping, SEO/meta-tag adjustments, and UX-focused error handling. Business value: reduced voter confusion and support queries, improved trust in official polling information, and smoother onboarding of new council data sources.
March 2025 performance summary for DemocracyClub/UK-Polling-Stations. Delivered end-to-end polling station data accuracy enhancements that unify and correct station data across councils, increasing importer reliability and overall data integrity. Implemented extensive data corrections (coordinates, postcodes, UPRNs) and station reassignment to ensure polling places reflect current governance. Strengthened data governance, ETL reliability, and traceability, delivering clear business value in voter experience and council operations.
March 2025 performance summary for DemocracyClub/UK-Polling-Stations. Delivered end-to-end polling station data accuracy enhancements that unify and correct station data across councils, increasing importer reliability and overall data integrity. Implemented extensive data corrections (coordinates, postcodes, UPRNs) and station reassignment to ensure polling places reflect current governance. Strengthened data governance, ETL reliability, and traceability, delivering clear business value in voter experience and council operations.
February 2025: Delivered key features and fixes across DemocracyClub projects with focus on data integrity, UX accessibility, and geospatial visibility. Stabilized critical data pipelines, refined admin behavior, and expanded map-based representation of polling station data. Result: more reliable datasets, improved user experience for admins and voters, and a solid foundation for future enhancements.
February 2025: Delivered key features and fixes across DemocracyClub projects with focus on data integrity, UX accessibility, and geospatial visibility. Stabilized critical data pipelines, refined admin behavior, and expanded map-based representation of polling station data. Result: more reliable datasets, improved user experience for admins and voters, and a solid foundation for future enhancements.
January 2025 (Month: 2025-01) performance overview for DemocracyClub/EveryElection. Focused on delivering high-value features, improving API performance, enhancing governance workflows, and increasing maintainability.
January 2025 (Month: 2025-01) performance overview for DemocracyClub/EveryElection. Focused on delivering high-value features, improving API performance, enhancing governance workflows, and increasing maintainability.
December 2024 monthly summary for DemocracyClub/EveryElection. Focus this month was delivering clearer UX for command usage and improving data relevance in boundary data collection, with strong test coverage to prevent regressions. Key features delivered: - Clearer User Command Example: removed an unnecessary article from the example command to improve clarity and reduce user confusion. This aligns with a smoother onboarding experience for new users and reduces support questions. (Commit: 797b6697fb9ef0c415f2751e5203f5f699353433) - Boundary Bot Enhancement: Targeted Shapefile Scraping: updated boundary bot to scrape shapefiles only from final reports, increasing data relevance and reducing noise. Tests were updated to reflect the new behavior. (Commit: d2997cd2ad4a17a9cfb276ce91b4c48cb7321ff2) Major bugs fixed: - No high-severity bugs closed this month; focus remained on feature improvements and strengthening test coverage to prevent regressions. Overall impact and accomplishments: - Improved data accuracy and reliability for boundary information by ensuring only final report shapefiles are collected, leading to cleaner datasets for downstream consumers. - Enhanced user experience with clearer command examples, reducing learning curve and potential misusage. - Improved maintainability and quality assurance through updated tests that reflect the new scraping behavior. Technologies/skills demonstrated: - API/CLI UX refinement, Python scripting for data collection, and shapefile handling. - Test-driven development and test updates to align with behavior changes. - Clear traceability to commits and repository changes within DemocracyClub/EveryElection.
December 2024 monthly summary for DemocracyClub/EveryElection. Focus this month was delivering clearer UX for command usage and improving data relevance in boundary data collection, with strong test coverage to prevent regressions. Key features delivered: - Clearer User Command Example: removed an unnecessary article from the example command to improve clarity and reduce user confusion. This aligns with a smoother onboarding experience for new users and reduces support questions. (Commit: 797b6697fb9ef0c415f2751e5203f5f699353433) - Boundary Bot Enhancement: Targeted Shapefile Scraping: updated boundary bot to scrape shapefiles only from final reports, increasing data relevance and reducing noise. Tests were updated to reflect the new behavior. (Commit: d2997cd2ad4a17a9cfb276ce91b4c48cb7321ff2) Major bugs fixed: - No high-severity bugs closed this month; focus remained on feature improvements and strengthening test coverage to prevent regressions. Overall impact and accomplishments: - Improved data accuracy and reliability for boundary information by ensuring only final report shapefiles are collected, leading to cleaner datasets for downstream consumers. - Enhanced user experience with clearer command examples, reducing learning curve and potential misusage. - Improved maintainability and quality assurance through updated tests that reflect the new scraping behavior. Technologies/skills demonstrated: - API/CLI UX refinement, Python scripting for data collection, and shapefile handling. - Test-driven development and test updates to align with behavior changes. - Clear traceability to commits and repository changes within DemocracyClub/EveryElection.
November 2024: DemocracyClub/EveryElection focused on stabilizing data collection pipelines and improving parsing accuracy to support reliable downstream analytics. Key work included stabilizing the Boundary Bot by refining the ignore list to exclude disruptive organizations, and enhancing election text parsing to include 'division' in councillor elections contexts. These changes reduce noise, improve data quality, and speed up processing across the data workflow.
November 2024: DemocracyClub/EveryElection focused on stabilizing data collection pipelines and improving parsing accuracy to support reliable downstream analytics. Key work included stabilizing the Boundary Bot by refining the ignore list to exclude disruptive organizations, and enhancing election text parsing to include 'division' in councillor elections contexts. These changes reduce noise, improve data quality, and speed up processing across the data workflow.
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