Try codeflash (#404)

.github/workflows/codeflash-optimize.yaml

@@ -0,0 +1,53 @@
+name: Codeflash
+
+on:
+  push:
+    branches:
+      - main
+      - renovate/**
+  pull_request:
+  workflow_dispatch:
+
+jobs:
+  optimize:
+    name: Optimize new code in this PR
+    runs-on: ubuntu-latest
+    env:
+      CODEFLASH_API_KEY: ${{ secrets.CODEFLASH_API_KEY }}
+      CODEFLASH_PR_NUMBER: ${{ github.event.number }}
+    steps:
+      - name: Check if PR is from Codeflash bot
+        id: bot_check
+        run: |-
+          echo "Checking if this PR is created by Codeflash bot..."
+          if [ "${{ github.event.pull_request.user.login }}" == "codeflash-ai[bot]" ]; then
+            echo "PR created by Codeflash bot. Skipping optimization."
+            echo "skip_remaining_steps=yes" >> $GITHUB_OUTPUT
+          else
+            echo "skip_remaining_steps=no" >> $GITHUB_OUTPUT
+            echo "It's not. Proceeding with the optimization."
+          fi
+
+      - uses: actions/checkout@v4
+        if: steps.bot_check.outputs.skip_remaining_steps == 'no'
+        with:
+          fetch-depth: 0
+          token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Set up Python
+        if: steps.bot_check.outputs.skip_remaining_steps == 'no'
+        uses: actions/setup-python@v5
+        with:
+          cache-dependency-path: pyproject.toml
+          cache: pip
+          python-version: 3.12
+
+      - name: Install Project Dependencies
+        if: steps.bot_check.outputs.skip_remaining_steps == 'no'
+        run: >-
+          python -m pip install -e .; python -m pip install codeflash
+
+      - name: Run Codeflash to optimize code
+        if: steps.bot_check.outputs.skip_remaining_steps == 'no'
+        id: optimize_code
+        run: codeflash

paper/paper.md

@@ -48,9 +48,9 @@ wavelets are built upon the eigenfunctions of the Slepian concentration problem
 of the manifold [@Slepian1961; @Landau1961; @Landau1962]: a set of bandlimited
 functions that are maximally concentrated within a given region. Wavelets are
 constructed through a tiling of the Slepian harmonic line by leveraging the
-existing scale-discretised framework [@Wiaux2008; @Leistedt2013]. Whilst these wavelets
-were inspired by spherical datasets, like in cosmology, the wavelet construction
-may be utilised for manifold or graph data.
+existing scale-discretised framework [@Wiaux2008; @Leistedt2013]. Whilst these
+wavelets were inspired by spherical datasets, like in cosmology, the wavelet
+construction may be utilised for manifold or graph data.
 
 To the author's knowledge, there is no public software that allows one to
 compute Slepian wavelets (or a similar approach) on the sphere or general

pyproject.toml

@@ -98,6 +98,13 @@ ignore = [
     "src/sleplet/_version.py",
 ]
 
+[tool.codeflash]
+ignore-paths = []
+# All paths are relative to this pyproject.toml's directory.
+module-root = "src"
+test-framework = "pytest"
+tests-root = "tests"
+
 [tool.coverage]
 report = {skip_covered = true, sort = "cover"}
 run = {branch = true, parallel = true, source = [