HTML good first issues

Module pages in the application are failing to display evidence details for pathophysiology nodes, only showing a count. This prevents users from understanding the source of the evidence (e.g., human cohort, mouse model, or in vitro experiment) without manually inspecting the YAML files. This is a critical gap for module pages, which abstract mechanisms across diseases and rely heavily on diverse evidence sources.

This issue proposes controlling the concurrency of GitHub Actions workflows to prevent multiple jobs from running simultaneously. This is particularly important for workflows that interact with external systems, such as pushing artifacts, to ensure ordered execution and avoid conflicts. The provided GitHub documentation link offers guidance on implementing workflow and job concurrency controls.

This issue requests the addition of a GitHub Actions workflow to verify the Hyperfoil website's functionality. The workflow should run on pull requests and master pushes, specifically when changes occur in the `docs/site` directory, and utilize Hugo for building. An optional stretch goal involves hosting a temporary website for pull requests.

This issue requests the creation of a 'Getting Started' page for KEDA. The page should guide new users through the essential steps of installing KEDA, deploying a sample application, setting up authentication for triggers, creating a scaled object, and finally, monitoring the deployment using the KEDA dashboard.

This issue tracks the migration of several Odoo modules related to fleet management to version 19.0. A checklist of modules is provided, with one module already migrated. The linked wiki page offers guidance on the migration process.

The `--protocolVersion` argument description in `dotnet nuget add source --help` incorrectly states the default value. While it claims to default to 2, the actual default behavior depends on the NuGet source URL, defaulting to 3 for URLs ending in `.json`.

This issue tracks the migration of various 'product' related modules to version 19.0. It serves as a checklist for maintainers, indicating which modules have been migrated (marked with 'x') and which still require attention. The migration process likely involves updating code to be compatible with the new Odoo version.

The profiler incorrectly treats labels that differ only in case or surrounding whitespace as distinct groups. This leads to inaccurate reporting of group counts, dimension scores, and imbalance ratios. The suggested solution is to add a flag to indicate such discrepancies rather than merging the labels.

This issue tracks the migration of various Odoo modules to version 19.0. It lists the modules that need to be migrated, with some already marked as completed. The migration process likely involves updating code to be compatible with the new Odoo version and its associated changes.

This issue outlines a migration task for a large number of Odoo modules to version 20.0. It provides a checklist of modules that need to be updated and links to relevant documentation for guidance. The goal is to ensure these modules are compatible with the new Odoo version.

An empty CSV file causes the command-line interface (CLI) and MCP server to display a generic 'No columns to parse' error, while the web interface correctly identifies the file as empty. The JavaScript engine also handles empty files differently, returning an empty profile. The suggested fix is to standardize the error message across all interfaces to clearly indicate an empty dataset and to ensure consistent behavior.

This issue identifies duplicated function definitions across two JavaScript files (`profiler-ui.js` and `profiler-compare.js`) that were not fully resolved by a previous refactoring. The duplicated functions relate to common UI elements and data handling, leading to maintenance overhead. The suggested solution involves consolidating pure functions into a shared module and refactoring others to accept dynamic element IDs.

The command-line interface for generating figures in the faircode package is not tested. This means that changes to the argument parsing or default behavior of this interface could go unnoticed, potentially breaking the figure regeneration process for users. The suggested solution involves adding tests that simulate running the command-line interface with various inputs and verifying the output and generated files.

This issue identifies untested code paths in `get_xlsx_sheet_info` and `held_out_encoding_ignored_notes` within the `faircode` library. Specifically, the code that handles unreadable workbooks and malformed encoding suffixes is not covered by tests. The proposed solution involves creating tests for these scenarios to ensure proper error handling and silent failures where intended.

This issue identifies a gap in the delimiter sniffing logic for CSV-like data. Specifically, there's no test case to handle doubled quotes within quoted fields, which are used to escape a single quote. While the current implementation appears to handle these cases correctly based on manual testing, the lack of a dedicated test means this functionality is not verified in the test suite for both Python and JavaScript implementations.

The error message displayed when trying to read an Excel file without the 'openpyxl' package installed is not being tested. This means the specific informative message is never verified to ensure it's correct and helpful to users. The issue proposes adding tests to cover this scenario.

This issue highlights that two specific branches within the `faircode/metrics.py` file are not being tested. These branches handle edge cases where insufficient data exists for ratio calculations or when the False Positive Rate (FPR) gap is undefined for equalized odds. The goal is to add tests to ensure these documented outcomes are correctly handled and reported.

The `parse_reference` function in the Python profiler silently skips rows with non-numeric 'share' values, such as 'n/a' or empty cells. This behavior is not covered by existing tests, and it's unclear if the JavaScript web engine exhibits the same behavior. The issue proposes adding tests to verify this and to ensure consistent handling of such data across both engines.

This issue identifies untested code paths in the `compare_to_html` function within `faircode/report.py`. Specifically, the 'and N more groups' line and the guard preventing division by zero when no shares exist are not covered by existing tests. The suggested solution involves creating tests that trigger these specific conditions to ensure correct rendering and error handling.

The browser smoke test is not covering key user interactions like file uploads, editing thresholds, typing keywords, or adding held-out rows. The issue proposes adding specific test cases to address these gaps and ensure more comprehensive browser testing.

The current implementation of `RowFilter` in `faircode/manifest.py` allows multiple operators within a single filter, contradicting the `MANIFEST_SPEC.md` which states only one operator should be used. This leads to unexpected behavior, such as filters silently narrowing the data twice and inconsistent handling of NaN values depending on the operator used.

The AGENTS.md documentation incorrectly states that the repository lacks linting, testing, and package setup. This is outdated information as the repository now includes a `pyproject.toml` with pytest and ruff configurations, a `Makefile` for tests and linting, pre-commit hooks, and several relevant GitHub workflows. The documentation needs to be updated to reflect these existing configurations.

This issue highlights a gap in the project's testing setup for browser smoke tests. Currently, there's no straightforward way for contributors to run these tests, requiring manual installation of Playwright and Chromium, and the tests are silently skipped by default. The suggested solution involves adding a `browser` extra, a dedicated `make test-browser` target, and updating documentation to make this testing functionality accessible.

The web provenance version is hard-coded in two JavaScript files and is not validated against the Python package version. This can lead to outdated version information in web exports and comparison views after a release. The suggested solution involves centralizing the version constant and adding automated checks.

The `faircode-mcp` command-line script currently crashes with a `ModuleNotFoundError` if the optional `mcp` extra is not installed. The suggested fix is to gracefully catch this `ImportError`, inform the user to install the `mcp` extra, and exit cleanly.

This issue describes a bug in the faircode profiler where pandas Categorical columns with unused categories are incorrectly counted as zero-row groups. This leads to a lower score and inconsistent profiling results across different file formats, as only Parquet files can produce these zero-row groups. The suggested fix involves using `observed=True` in `value_counts()` to only count present categories.

The Python profiler incorrectly separates integer `1` and string `"1"` into distinct groups, leading to duplicate labels in the report. The JavaScript profiler correctly combines them. This inconsistency arises from how each engine handles mixed-type columns, causing different profiling results for the same data.

This issue describes a discrepancy between how nested JSON objects are handled by the Python and JavaScript profilers. The Python loader flattens nested objects into dotted column names (e.g., 'loc.state'), while the JavaScript engine keeps them as single cells, leading to different profiled dimensions. The proposed solution is to implement similar flattening logic in the JavaScript engine.

This issue tracks the migration of various Point of Sale (POS) modules to version 16.0. It lists completed and pending modules, indicating that the migration process is underway and requires further attention for the uncompleted items.

This issue outlines a large-scale effort to curate and categorize 3,079 rare diseases from a prioritized list. The categorization is based on matching MONDO IDs and various metadata fields, with specific examples provided for neurodevelopmental, neurodegenerative, neuroimmune, and cardiac disease groups. The goal is to enhance the existing knowledge base by organizing these diseases into relevant categories.