A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data
C-Rank Grade: A (Welcoming) - 63/100
External PR Merge Rate: 77%
Response Time: 4d
First Timer Success: 83%
SciTools/iris has a recorded first-timer success rate of 83.3%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.
Maintainers in SciTools/iris respond to incoming external pull requests in approximately 100.8 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.
The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 62.8 places SciTools/iris in the A tier.
The external contributor pull request merge rate for SciTools/iris is 77.4%, based on public PR activity from non-core contributors.
SciTools/iris currently has 2 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".
Rigorous architecture standards (100% critical review signals). Ensure PRs strictly follow guidelines before requesting review in SciTools/iris.
Average Response Latency
Tracks hours until a maintainer leaves a review, comment, or PR response.
External Acceptance Rate
Percentage of community pull requests successfully merged into main.
First PR Conversion
Rate at which developers submitting their first repository PR succeed.
Show contributors that your repository actively reviews and merges external pull requests.
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Historical health & responsiveness evolution
External PR acceptance
First PR success rate
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90% receive response in
Maintainer review activity heatmap & prime window prediction
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Maintainers are most responsive around 11:00 UTC (11:00 UTC in your timezone). Recommended submission window is Monday - Wednesday from 10:00 to 14:00 UTC (10:00 - 14:00 UTC local).
Maintainer Strategy: Maintainer Sweet Spot: PRs under 150 lines merge in ~66 hours (96% approval). Large PRs (>500 lines) take ~484 hours (35% approval). Keep your diff compact for rapid review.
✨ Feature Request Add a step argument to iris.cube.Cube.rolling_window to match the behaviour of iris.util.rolling_window. Currently Cube.rolling_window only supports overlapping windows and uses iris.util.rolling_window applied to the cube data, coordinate points and coordinate bounds. iris.util.rolling_window also has support for strided windows using the step argument, however this is not available at the cube level. A backwards compatible default of step=1 would give identical results to the current implementation of Cube.rolling_window. Motivation This would extend the flexibility of Cube.rolling_window and would enable easier calculation of some common meteorological diagnostics. For example, the calculation of minimum temperature in non-overlapping time periods such as T+1 to T+3, T+4 to T+6 etc.
An artifact from when load_meshes was still experimental. Code should be factored out so that both these routines can call the same convenience. Code iris/lib/iris/loading.py Lines 74 to 105 in 3432ca1 def _generate_cubes(uris, callback, constraints): import iris.io """Return a generator of cubes given the URIs and a callback.""" if ( isinstance(uris, str) or hasattr(uris, "fromcdl") or not isinstance(uris, Iterable) ): # Make a string, Dataset, or other single item, into an
🐛 Bug Report The function iris.experimental.raster.export_geotiff fails with numpy>=2.4.0 with the following GDAL error: File " ... /site-packages/osgeo/gdal.py", line 4468, in SetGeoTransform return _gdal.Dataset_SetGeoTransform(self, *args) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: not a number This is due to how the parameters are passed to the ... How To Reproduce Steps to reproduce the behaviour: from iris.cube import Cube from iris.coords import DimCoord from iris.experimental.raster import export_geotiff import numpy as np lats = DimCoord(np.arange(5), standard_name="latitude", units="degrees") lats.guess_bounds() lons = DimCoord(np.arange(5), standard_name="longitude", units="degrees") lons.guess_bounds() c = Cube( data=np.arange(25, dtype=np.float64).reshape(5,5), standard_name="depth", dim_coords_and_dims=((lats, 0), (lons,1)) ) export_geotiff(c, '/tmp/geo.tiff') # throws a TypeError Expected behaviour Does not throw a TypeErr
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When evaluating whether to contribute to SciTools/iris, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.
Currently, maintainers of SciTools/iris acknowledge new external contributions in approximately 4 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 77.4% were successfully merged into the primary branch.
SciTools/iris has a recorded first-timer success rate of 83.3%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.
The initial maintainer response time averages ~4 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.
The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 62.8 places SciTools/iris in the Welcoming tier.
The external pull request merge rate is 77.4%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.
Yes, SciTools/iris currently has 2 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.
All metrics displayed for SciTools/iris are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.