Merge branch 'Serious-senpai:main' into main

.github/workflows/compare.yml

@@ -21,6 +21,7 @@ jobs:
           problem="${{ github.event.comment.body }}"
           problem=$(echo ${problem#"/d2d-compare"} | xargs)
           echo -n "$problem" > input.txt
+          echo "$problem"
           [[ "$problem" =~ ^[0-9]+$dot[0-9]+$dot[0-9]+$ ]]
           exit $?
 
@@ -67,6 +68,9 @@ jobs:
     name: Test on PR
     runs-on: ubuntu-latest
     needs: input-check
+    strategy:
+      matrix:
+        counter: [1, 2]
 
     steps:
       - name: Checkout PR branch
@@ -88,18 +92,21 @@ jobs:
           --drone-config-mapping 3 3 3 3 \
           --propagation-priority min-distance \
           --pool-size 8 \
-          --dump pr-#${{ github.event.issue.number }}.json 
+          --dump PR#${{ github.event.issue.number }}-run#${{ matrix.counter }}.json
 
       - name: Upload solution
         uses: actions/upload-artifact@v3
         with:
           name: solutions
-          path: pr-#${{ github.event.issue.number }}.json
+          path: PR#${{ github.event.issue.number }}-run#${{ matrix.counter }}.json
 
   main-test:
     name: Test on main
     runs-on: ubuntu-latest
     needs: input-check
+    strategy:
+      matrix:
+        counter: [1, 2]
 
     steps:
       - name: Checkout main branch
@@ -123,13 +130,13 @@ jobs:
           --drone-config-mapping 3 3 3 3 \
           --propagation-priority min-distance \
           --pool-size 8 \
-          --dump main.json 
+          --dump main-run#${{ matrix.counter }}.json 
 
       - name: Upload solution
         uses: actions/upload-artifact@v3
         with:
           name: solutions
-          path: main.json
+          path: main-run#${{ matrix.counter }}.json
 
   compare:
     name: Compare solutions
@@ -152,30 +159,37 @@ jobs:
       - name: Combine solutions and compare
         run: |
           export PYTHONPATH=$GITHUB_WORKSPACE
-          python scripts/d2d-compare.py pr-#${{ github.event.issue.number }}.json main.json
+          python scripts/d2d-compare.py PR#${{ github.event.issue.number }}-run#1.json PR#${{ github.event.issue.number }}-run#2.json main-run#1.json main-run#2.json
 
-      - name: Upload compare result
+      - name: Upload compare result as artifact
         uses: actions/upload-artifact@v3
         with:
           name: solutions
           path: compare.png
 
+      - name: Upload compare result to catbox.moe
+        run: |
+          url=$(curl -F "reqtype=fileupload" -F "fileToUpload=@compare.png" "https://catbox.moe/user/api.php")
+          errorcode=$?
+          echo "$url"
+          echo -n "$url" > url.txt
+          exit $errorcode
+
       - name: Send completion notification
         uses: actions/github-script@v7
         with:
           retries: 3
           script: |
             var fs = require("fs");
-            await fs.readFile(
-              "input.txt",
-              "utf-8",
-              function(error, data) {
+            await fs.readFile("input.txt", "utf-8", async function (error, input) {
+              if (error) throw error;
+              await fs.readFile("url.txt", "utf-8", async function (error, url) {
                 if (error) throw error;
                 github.rest.issues.createComment({
                   owner: context.repo.owner,
                   repo: context.repo.repo,
                   issue_number: ${{ github.event.issue.number }},
-                  body: `🎉 Comparison request for D2D problem \`${data.trim()}\` completed! You can view the workflow results [here](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}).`,
+                  body: `🎉 Comparison request for D2D problem \`${input.trim()}\` completed! You can view the workflow results [here](${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}).\n![compare.png](${url.trim()})`,
                 });
-              }
-            );
+              });
+            });

.github/workflows/lint.yml

@@ -10,8 +10,8 @@ permissions:
   contents: read
 
 jobs:
-  python:
-    name: Python lint
+  autopep8:
+    name: Run autopep8
     runs-on: ubuntu-latest
 
     steps:
@@ -21,8 +21,33 @@ jobs:
       - name: Install dependencies
         run: pip install -r dev-requirements.txt
 
-      - name: Check code format
+      - name: Run autopep8
         run: autopep8 --exit-code --diff -aaar .
 
-      - name: Check typings
+  mypy:
+    name: Run mypy
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Install dependencies
+        run: pip install -r dev-requirements.txt
+
+      - name: Run mypy
         run: mypy .
+
+  flake8:
+    name: Run flake8
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Install dependencies
+        run: pip install -r dev-requirements.txt
+
+      - name: Run flake8
+        run: flake8 .

README.md

@@ -5,7 +5,7 @@
 Tabu search technique for solving optimization problems. TSP problems are taken from [TSPLIB](http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95).
 
 ## Setup
-- It is highly recommended to create a virtual environment by running `python -m venv .venv`
+- It is highly recommended to create a virtual environment by running `python3 -m venv .venv`
 - Install dependencies for running the optimizers
 ```
 $ pip install -r requirements.txt
@@ -16,11 +16,3 @@ $ pip install -r requirements.txt
 ```
 $ pip install -r dev-requirements.txt
 ```
-- Codes must be formatted using [autopep8](https://pypi.org/project/autopep8). Run `autopep8` at the root of the repository
-```
-$ autopep8 -aaair .
-```
-- Codes must pass the [mypy](https://pypi.org/project/mypy) type-checking.
-```
-$ mypy .
-```

d2d.py

@@ -183,4 +183,4 @@ def _ideal_distance_key(pareto_costs: Dict[Tuple[float, ...], int], candidate: d
         print(f"Saved solution to {namespace.dump!r}")
 
     if len(errors) > 0:
-        raise ValueError(f"Some calculations were incorrect:\n" + "\n".join(errors))
+        raise ValueError("Some calculations were incorrect:\n" + "\n".join(errors))

dev-requirements.txt

@@ -10,20 +10,23 @@ cycler==0.12.1
 Deprecated==1.2.14
 dill==0.3.7
 exceptiongroup==1.2.0
+flake8==6.1.0
 fonttools==4.45.1
 future==0.18.3
 grapheme==0.6.0
 iniconfig==2.0.0
 kiwisolver==1.4.5
 matplotlib==3.8.2
+mccabe==0.7.0
 mypy==1.7.0
 mypy-extensions==1.0.0
 numpy==1.26.2
 packaging==23.2
 Pillow==10.1.0
 pluggy==1.3.0
 pycodestyle==2.11.1
-pymoo==0.6.1
+pyflakes==3.1.0
+pymoo==0.6.1.1
 pyparsing==3.1.1
 pytest==7.4.3
 python-dateutil==2.8.2

requirements.txt

@@ -15,7 +15,7 @@ matplotlib==3.8.2
 numpy==1.26.2
 packaging==23.2
 Pillow==10.1.0
-pymoo==0.6.1
+pymoo==0.6.1.1
 pyparsing==3.1.1
 python-dateutil==2.8.2
 scipy==1.11.4

setup.cfg

@@ -11,3 +11,7 @@ exclude_also =
     def __repr__
     raise NotImplementedError
     return NotImplemented
+
+[flake8]
+extend-ignore = E501
+exclude = .git,.venv,__pycache__,__init__.py

ts/abc/multi_ob/solutions.py

@@ -96,7 +96,7 @@ def tabu_search(
         current = [initial]
         candidate_costs = {initial.cost()} if plot_pareto_front else None
         if len(initial.cost()) != 2:
-            message = f"Cannot plot the Pareto front when the number of objectives is not 2"
+            message = "Cannot plot the Pareto front when the number of objectives is not 2"
             raise ValueError(message)
 
         with Pool(pool_size) as pool:

ts/tsp/solutions.py

@@ -1,11 +1,10 @@
 from __future__ import annotations
-from multiprocessing import pool
 
 import itertools
 import random
 import re
 from math import sqrt
-from multiprocessing import pool
+from multiprocessing import pool as p
 from os import path
 from typing import Any, Callable, ClassVar, Final, List, Optional, Tuple, Union, TYPE_CHECKING
 
@@ -81,7 +80,7 @@ def path(self) -> Tuple[int, ...]:
     def cost(self) -> float:
         return self._cost
 
-    def post_optimization(self, *, pool: pool.Pool, pool_size: int, use_tqdm: bool, logger: Optional[Callable[[str], Any]]) -> TSPPathSolution:
+    def post_optimization(self, *, pool: p.Pool, pool_size: int, use_tqdm: bool, logger: Optional[Callable[[str], Any]]) -> TSPPathSolution:
         result = self
         iterations: Union[Tuple[SingleObjectiveNeighborhood[TSPPathSolution, Any], ...], tqdm[SingleObjectiveNeighborhood[TSPPathSolution, Any]]] = self.get_neighborhoods()
         if use_tqdm: