diff --git a/.gitea/workflows/backend_run_test.yaml b/.gitea/workflows/backend_run_test.yaml
index b5fa349..4591358 100644
--- a/.gitea/workflows/backend_run_test.yaml
+++ b/.gitea/workflows/backend_run_test.yaml
@@ -28,7 +28,7 @@ jobs:
working-directory: backend
- name: Run Tests
- run: pipenv run pytest src --html=report.html --self-contained-html --log-cli-level=INFO
+ run: pipenv run pytest src --html=report.html --self-contained-html --log-cli-level=DEBUG
working-directory: backend
- name: Upload HTML report
diff --git a/backend/.pylintrc b/backend/.pylintrc
index eabcaa6..a054d18 100644
--- a/backend/.pylintrc
+++ b/backend/.pylintrc
@@ -445,7 +445,9 @@ disable=raw-checker-failed,
logging-fstring-interpolation,
duplicate-code,
relative-beyond-top-level,
- invalid-name
+ invalid-name,
+ too-many-arguments,
+ too-many-positional-arguments
# Enable the message, report, category or checker with the given id(s). You can
# either give multiple identifier separated by comma (,) or put this option
diff --git a/backend/report.html b/backend/report.html
index 1b97bae..e6bf3cb 100644
--- a/backend/report.html
+++ b/backend/report.html
@@ -328,7 +328,7 @@ div.media {
</head>
<body>
<h1 id="title">Backend Testing Report</h1>
- <p>Report generated on 24-Jan-2025 at 16:01:23 by <a href="https://pypi.python.org/pypi/pytest-html">pytest-html</a>
+ <p>Report generated on 29-Jan-2025 at 09:35:03 by <a href="https://pypi.python.org/pypi/pytest-html">pytest-html</a>
v4.1.1</p>
<div id="environment-header">
<h2>Environment</h2>
@@ -382,7 +382,7 @@ div.media {
<h2>Summary</h2>
<div class="additional-summary prefix">
</div>
- <p class="run-count">8 tests took 00:01:20.</p>
+ <p class="run-count">1 test took 97 ms.</p>
<p class="filter">(Un)check the boxes to filter the results.</p>
<div class="summary__reload">
<div class="summary__reload__button hidden" onclick="location.reload()">
@@ -392,10 +392,10 @@ div.media {
<div class="summary__spacer"></div>
<div class="controls">
<div class="filters">
- <input checked="true" class="filter" name="filter_checkbox" type="checkbox" data-test-result="failed" />
- <span class="failed">3 Failed,</span>
+ <input checked="true" class="filter" name="filter_checkbox" type="checkbox" data-test-result="failed" disabled/>
+ <span class="failed">0 Failed,</span>
<input checked="true" class="filter" name="filter_checkbox" type="checkbox" data-test-result="passed" />
- <span class="passed">5 Passed,</span>
+ <span class="passed">1 Passed,</span>
<input checked="true" class="filter" name="filter_checkbox" type="checkbox" data-test-result="skipped" disabled/>
<span class="skipped">0 Skipped,</span>
<input checked="true" class="filter" name="filter_checkbox" type="checkbox" data-test-result="xfailed" disabled/>
@@ -432,7 +432,7 @@ div.media {
</table>
</body>
<footer>
- <div id="data-container" data-jsonblob="{"environment": {"Python": "3.12.3", "Platform": "Linux-6.8.0-51-generic-x86_64-with-glibc2.39", "Packages": {"pytest": "8.3.4", "pluggy": "1.5.0"}, "Plugins": {"html": "4.1.1", "anyio": "4.8.0", "metadata": "3.1.1"}}, "tests": {"src/tests/test_main.py::test_turckheim": [{"extras": [], "result": "Passed", "testId": "src/tests/test_main.py::test_turckheim", "resultsTableRow": ["<td class=\"col-result\">Passed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_turckheim</td>", "<td>start (0 | 5) - 5 - Porte de France (157 | 5) - 5 - finish (0 | 5) - 0</td>", "<td>20 min</td>", "<td>20 min</td>", "<td class=\"col-duration\">110 ms</td>", "<td class=\"col-links\"></td>"], "log": "------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 5 landmarks in \t: 0.004 seconds\nINFO src.main:main.py:122 Total computation time\t: 0.035 seconds\nINFO src.main:main.py:127 Generated a trip of 20 minutes with 3 landmarks in 0.039 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}], "src/tests/test_main.py::test_bellecour": [{"extras": [], "result": "Passed", "testId": "src/tests/test_main.py::test_bellecour", "resultsTableRow": ["<td class=\"col-result\">Passed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_bellecour</td>", "<td>start (0 | 5) - 5 - H\u00f4tel de l'Europe (217 | 5) - 4 - Palais archi\u00e9piscopal (217 | 5) - 6 - \u00c9glise Saint-Georges (461 | 5) - 3 - Grande Synagogue de Lyon (217 | 5) - 10 - \u00c9glise Saint-Just (460 | 5) - 13 - Basilique Notre-Dame de Fourvi\u00e8re (281 | 5) - 5 - Site historique de Lyon (414 | 5) - 4 - Temple du Change (406 | 5) - 13 - Basilique Saint-Bonaventure (414 | 5) - 12 - finish (0 | 5) - 0</td>", "<td>125 min</td>", "<td>120 min</td>", "<td class=\"col-duration\">00:00:09</td>", "<td class=\"col-links\"></td>"], "log": "------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 182 landmarks in \t: 0.042 seconds\nINFO src.main:main.py:122 Total computation time\t: 8.903 seconds\nINFO src.main:main.py:127 Generated a trip of 125 minutes with 11 landmarks in 8.945 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}], "src/tests/test_main.py::test_cologne": [{"extras": [], "result": "Failed", "testId": "src/tests/test_main.py::test_cologne", "resultsTableRow": ["<td class=\"col-result\">Failed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_cologne</td>", "<td>start (0 | 5) - 2 - Excelsior Hotel Ernst (793 | 5) - 2 - St.Andreas (632 | 5) - 4 - K\u00f6lner Dom (1474 | 10) - 2 - R\u00f6misch-Germanisches Museum (901 | 60) - 5 - Gro\u00df St. Martin (582 | 5) - 9 - St. Maria im Kapitol (633 | 5) - 4 - Trinitatiskirche (604 | 5) - 11 - St. Peter (538 | 5) - 7 - Oper der Stadt K\u00f6ln (601 | 5) - 3 - Galeria (531 | 30) - 4 - St. Maria in der Kupfergasse (518 | 5) - 9 - St. Gereon (1059 | 5) - 11 - St. Ursula (529 | 5) - 10 - St. Kunibert (691 | 5) - 10 - finish (0 | 5) - 0</td>", "<td>253 min</td>", "<td>240 min</td>", "<td class=\"col-duration\">00:00:53</td>", "<td class=\"col-links\"></td>"], "log": "client = &lt;starlette.testclient.TestClient object at 0x7b7aaac3a000&gt;\nrequest = &lt;FixtureRequest for &lt;Function test_cologne&gt;&gt;\n\n def test_cologne(client, request) : # pylint: disable=redefined-outer-name\n &quot;&quot;&quot;\n Test n\u00b02 : Custom test in Lyon centre to ensure proper decision making in crowded area.\n \n Args:\n client:\n request:\n &quot;&quot;&quot;\n start_time = time.time() # Start timer\n duration_minutes = 240\n \n response = client.post(\n &quot;/trip/new&quot;,\n json={\n &quot;preferences&quot;: {&quot;sightseeing&quot;: {&quot;type&quot;: &quot;sightseeing&quot;, &quot;score&quot;: 5},\n &quot;nature&quot;: {&quot;type&quot;: &quot;nature&quot;, &quot;score&quot;: 5},\n &quot;shopping&quot;: {&quot;type&quot;: &quot;shopping&quot;, &quot;score&quot;: 5},\n &quot;max_time_minute&quot;: duration_minutes,\n &quot;detour_tolerance_minute&quot;: 0},\n &quot;start&quot;: [50.942352665, 6.957777972392]\n }\n )\n result = response.json()\n landmarks = load_trip_landmarks(client, result[&#x27;first_landmark_uuid&#x27;])\n \n # Get computation time\n comp_time = time.time() - start_time\n \n # Add details to report\n log_trip_details(request, landmarks, result[&#x27;total_time&#x27;], duration_minutes)\n \n # for elem in landmarks :\n # print(elem)\n \n # checks :\n assert response.status_code == 200 # check for successful planning\n&gt; assert comp_time &lt; 30, f&quot;Computation time exceeded 30 seconds: {comp_time:.2f} seconds&quot;\nE AssertionError: Computation time exceeded 30 seconds: 53.27 seconds\nE assert 53.27033972740173 &lt; 30\n\nsrc/tests/test_main.py:137: AssertionError\n\n------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 244 landmarks in \t: 0.069 seconds\nINFO src.main:main.py:122 Total computation time\t: 53.196 seconds\nINFO src.main:main.py:127 Generated a trip of 253 minutes with 16 landmarks in 53.265 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}], "src/tests/test_main.py::test_strasbourg": [{"extras": [], "result": "Passed", "testId": "src/tests/test_main.py::test_strasbourg", "resultsTableRow": ["<td class=\"col-result\">Passed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_strasbourg</td>", "<td>start (0 | 5) - 8 - \u00c9glise protestante Saint-Pierre-le-Jeune (347 | 5) - 6 - \u00c9glise catholique Saint-Pierre-le-Jeune (197 | 5) - 8 - H\u00f4tel de Ville (295 | 5) - 4 - De la Grande \u00eele \u00e0 la Neustadt (414 | 5) - 8 - Bains municipaux de Strasbourg (518 | 5) - 5 - \u00c9glise Saint-\u00c9tienne (259 | 5) - 20 - Centre Administratif Ville et Eurom\u00e9tropole de Strasbourg (405 | 5) - 8 - Porte de l'H\u00f4pital (207 | 5) - 3 - \u00c9glise Saint-Nicolas (303 | 5) - 8 - Cath\u00e9drale Notre-Dame (728 | 10) - 8 - Circuit \u00ab Petite France \u00bb (414 | 5) - 9 - Barrage Vauban (391 | 5) - 10 - \u00c9glise Catholique Saint-Jean-Baptiste (281 | 5) - 1 - finish (0 | 5) - 0</td>", "<td>181 min</td>", "<td>180 min</td>", "<td class=\"col-duration\">00:00:05</td>", "<td class=\"col-links\"></td>"], "log": "------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 118 landmarks in \t: 0.027 seconds\nINFO src.main:main.py:122 Total computation time\t: 5.281 seconds\nINFO src.main:main.py:127 Generated a trip of 181 minutes with 15 landmarks in 5.308 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}], "src/tests/test_main.py::test_zurich": [{"extras": [], "result": "Passed", "testId": "src/tests/test_main.py::test_zurich", "resultsTableRow": ["<td class=\"col-result\">Passed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_zurich</td>", "<td>start (0 | 5) - 14 - Johanneskirche (351 | 5) - 11 - Evangelisch-Lutherische Kirche Z\u00fcrich (391 | 5) - 9 - Russisch-Orthodoxe Auferstehungskirche (369 | 5) - 6 - Liebfrauenkirche (281 | 5) - 11 - Predigerkirche (351 | 5) - 8 - St. Peter (489 | 5) - 5 - Grossm\u00fcnster (483 | 5) - 1 - Wasserkirche (238 | 5) - 3 - Fraum\u00fcnster (531 | 5) - 0 - Fraum\u00fcnster Kreuzgang (174 | 5) - 1 - Stadthaus (191 | 5) - 5 - Rebekkabrunnen (174 | 5) - 4 - Zentralhofbrunnen (173 | 5) - 5 - Augustinerkirche (238 | 5) - 4 - St. Anna-Kapelle (191 | 5) - 6 - Globus (369 | 30) - 5 - finish (0 | 5) - 0</td>", "<td>208 min</td>", "<td>180 min</td>", "<td class=\"col-duration\">00:00:04</td>", "<td class=\"col-links\"></td>"], "log": "------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 133 landmarks in \t: 0.024 seconds\nINFO src.main:main.py:122 Total computation time\t: 4.107 seconds\nINFO src.main:main.py:127 Generated a trip of 208 minutes with 18 landmarks in 4.131 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}], "src/tests/test_main.py::test_paris": [{"extras": [], "result": "Passed", "testId": "src/tests/test_main.py::test_paris", "resultsTableRow": ["<td class=\"col-result\">Passed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_paris</td>", "<td>start (0 | 5) - 21 - \u00c9glise Saint-Eug\u00e8ne Sainte-C\u00e9cile (871 | 5) - 21 - \u00c9glise Saint-Leu - Saint-Gilles (546 | 5) - 6 - Centre Georges Pompidou (1118 | 5) - 3 - \u00c9glise Saint-Merri (529 | 5) - 13 - Square Jean XXIII (492 | 5) - 12 - \u00c9glise Saint-\u00c9tienne-du-Mont (696 | 5) - 13 - Cath\u00e9drale Notre-Dame de Paris (1469 | 10) - 10 - Tour Saint-Jacques (793 | 5) - 7 - Sainte-Chapelle (1469 | 60) - 1 - Palais de Justice de Paris (531 | 5) - 9 - \u00c9glise Saint-Germain l'Auxerrois (662 | 5) - 8 - Pyramide du Louvre (557 | 5) - 3 - Tunnel des Tuileries (506 | 5) - 3 - Palais du Louvre (891 | 5) - 6 - Temple de l'Oratoire du Louvre (840 | 5) - 6 - Jardin Nelson Mandela (492 | 5) - 3 - finish (0 | 5) - 0</td>", "<td>290 min</td>", "<td>300 min</td>", "<td class=\"col-duration\">00:00:07</td>", "<td class=\"col-links\"></td>"], "log": "------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 363 landmarks in \t: 0.077 seconds\nINFO src.main:main.py:122 Total computation time\t: 7.226 seconds\nINFO src.main:main.py:127 Generated a trip of 290 minutes with 18 landmarks in 7.304 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}], "src/tests/test_main.py::test_new_york": [{"extras": [], "result": "Failed", "testId": "src/tests/test_main.py::test_new_york", "resultsTableRow": ["<td class=\"col-result\">Failed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_new_york</td>", "<td>start (0 | 5) - 7 - New Museum (406 | 60) - 8 - Capitale (810 | 5) - 10 - Columbus Park (646 | 5) - 3 - Thomas Paine Park (394 | 5) - 3 - Collect Pond Park (485 | 5) - 10 - Tribeca Park (455 | 5) - 4 - Albert Capsouto Park (454 | 5) - 7 - New York City Fire Museum (461 | 60) - 6 - Duarte Square (685 | 5) - 12 - Petrosino Square (394 | 5) - 5 - Saint Patrick's Old Cathedral (489 | 10) - 14 - Judson Memorial Church (518 | 5) - 12 - Grace Church (518 | 5) - 7 - Union Square Park (646 | 5) - 10 - Flatiron Building (780 | 5) - 5 - Cathedral of St. Sava (518 | 10) - 4 - Madison Square Park (646 | 5) - 7 - Calvary Church (461 | 5) - 17 - Immaculate Conception Church (546 | 5) - 6 - St. Nicholas of Myra Orthodox Church (546 | 5) - 8 - Saint Mark's in-the-Bowery (633 | 5) - 11 - finish (0 | 5) - 0</td>", "<td>406 min</td>", "<td>600 min</td>", "<td class=\"col-duration\">735 ms</td>", "<td class=\"col-links\"></td>"], "log": "client = &lt;starlette.testclient.TestClient object at 0x7b7aaac3a000&gt;\nrequest = &lt;FixtureRequest for &lt;Function test_new_york&gt;&gt;\n\n def test_new_york(client, request) : # pylint: disable=redefined-outer-name\n &quot;&quot;&quot;\n Test n\u00b02 : Custom test in New York (les Halles) centre to ensure proper decision making in crowded area.\n \n Args:\n client:\n request:\n &quot;&quot;&quot;\n start_time = time.time() # Start timer\n duration_minutes = 600\n \n response = client.post(\n &quot;/trip/new&quot;,\n json={\n &quot;preferences&quot;: {&quot;sightseeing&quot;: {&quot;type&quot;: &quot;sightseeing&quot;, &quot;score&quot;: 5},\n &quot;nature&quot;: {&quot;type&quot;: &quot;nature&quot;, &quot;score&quot;: 5},\n &quot;shopping&quot;: {&quot;type&quot;: &quot;shopping&quot;, &quot;score&quot;: 5},\n &quot;max_time_minute&quot;: duration_minutes,\n &quot;detour_tolerance_minute&quot;: 0},\n &quot;start&quot;: [40.72592726802, -73.9920434795]\n }\n )\n result = response.json()\n landmarks = load_trip_landmarks(client, result[&#x27;first_landmark_uuid&#x27;])\n \n # Get computation time\n comp_time = time.time() - start_time\n \n # Add details to report\n log_trip_details(request, landmarks, result[&#x27;total_time&#x27;], duration_minutes)\n \n # for elem in landmarks :\n # print(elem)\n \n # checks :\n assert response.status_code == 200 # check for successful planning\n assert comp_time &lt; 30, f&quot;Computation time exceeded 30 seconds: {comp_time:.2f} seconds&quot;\n&gt; assert duration_minutes*0.8 &lt; result[&#x27;total_time&#x27;], f&quot;Trip too short: {result[&#x27;total_time&#x27;]} instead of {duration_minutes}&quot;\nE AssertionError: Trip too short: 406 instead of 600\nE assert (600 * 0.8) &lt; 406\n\nsrc/tests/test_main.py:302: AssertionError\n\n------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 211 landmarks in \t: 0.028 seconds\nINFO src.main:main.py:122 Total computation time\t: 0.701 seconds\nINFO src.main:main.py:127 Generated a trip of 406 minutes with 23 landmarks in 0.729 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}], "src/tests/test_main.py::test_shopping": [{"extras": [], "result": "Failed", "testId": "src/tests/test_main.py::test_shopping", "resultsTableRow": ["<td class=\"col-result\">Failed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_shopping</td>", "<td>start (0 | 5) - 9 - Shopping Area (538 | 40) - 4 - Grand Bazar (93 | 30) - 20 - Halles de Lyon Paul Bocuse (272 | 30) - 7 - Galeries Lafayette (197 | 30) - 3 - Westfield La Part-Dieu (546 | 30) - 2 - Muji (259 | 30) - 25 - Grand H\u00f4tel-Dieu (546 | 30) - 5 - finish (0 | 5) - 0</td>", "<td>300 min</td>", "<td>240 min</td>", "<td class=\"col-duration\">60 ms</td>", "<td class=\"col-links\"></td>"], "log": "client = &lt;starlette.testclient.TestClient object at 0x7b7aaac3a000&gt;\nrequest = &lt;FixtureRequest for &lt;Function test_shopping&gt;&gt;\n\n def test_shopping(client, request) : # pylint: disable=redefined-outer-name\n &quot;&quot;&quot;\n Test n\u00b03 : Custom test in Lyon centre to ensure shopping clusters are found.\n \n Args:\n client:\n request:\n &quot;&quot;&quot;\n start_time = time.time() # Start timer\n duration_minutes = 240\n \n response = client.post(\n &quot;/trip/new&quot;,\n json={\n &quot;preferences&quot;: {&quot;sightseeing&quot;: {&quot;type&quot;: &quot;sightseeing&quot;, &quot;score&quot;: 0},\n &quot;nature&quot;: {&quot;type&quot;: &quot;nature&quot;, &quot;score&quot;: 0},\n &quot;shopping&quot;: {&quot;type&quot;: &quot;shopping&quot;, &quot;score&quot;: 5},\n &quot;max_time_minute&quot;: duration_minutes,\n &quot;detour_tolerance_minute&quot;: 0},\n &quot;start&quot;: [45.7576485, 4.8330241]\n }\n )\n result = response.json()\n landmarks = load_trip_landmarks(client, result[&#x27;first_landmark_uuid&#x27;])\n \n # Get computation time\n comp_time = time.time() - start_time\n \n # Add details to report\n log_trip_details(request, landmarks, result[&#x27;total_time&#x27;], duration_minutes)\n \n for elem in landmarks :\n print(elem)\n \n # checks :\n assert response.status_code == 200 # check for successful planning\n assert comp_time &lt; 30, f&quot;Computation time exceeded 30 seconds: {comp_time:.2f} seconds&quot;\n assert duration_minutes*0.8 &lt; result[&#x27;total_time&#x27;], f&quot;Trip too short: {result[&#x27;total_time&#x27;]} instead of {duration_minutes}&quot;\n&gt; assert duration_minutes*1.2 &gt; result[&#x27;total_time&#x27;], f&quot;Trip too long: {result[&#x27;total_time&#x27;]} instead of {duration_minutes}&quot;\nE AssertionError: Trip too long: 300 instead of 240\nE assert (240 * 1.2) &gt; 300\n\nsrc/tests/test_main.py:344: AssertionError\n\n----------------------------- Captured stdout call -----------------------------\nLandmark(start): [start @(45.7576485, 4.8330241), score=0, time_to_next=9]\nLandmark(shopping): [Shopping Area @(np.float64(45.76223053940519), np.float64(4.833794685873603)), score=538, time_to_next=4]\nLandmark(shopping): [Grand Bazar @(45.7632141, 4.8361975), score=93, time_to_next=20]\nLandmark(shopping): [Halles de Lyon Paul Bocuse @(45.7628282, 4.8505601), score=272, time_to_next=7]\nLandmark(shopping): [Galeries Lafayette @(45.7627107, 4.8556833), score=197, time_to_next=3]\nLandmark(shopping): [Westfield La Part-Dieu @(45.761331, 4.855676), score=546, time_to_next=2]\nLandmark(shopping): [Muji @(45.7615971, 4.8543781), score=259, time_to_next=25]\nLandmark(shopping): [Grand H\u00f4tel-Dieu @(45.7586955, 4.8364597), score=546, time_to_next=5]\nLandmark(finish): [finish @(45.7576485, 4.8330241), score=0]\n\n------------------------------ Captured log call -------------------------------\nINFO src.main:main.py:65 No end coordinates provided. Using start=end.\nINFO src.main:main.py:97 Fetched 7 landmarks in \t: 0.009 seconds\nINFO src.main:main.py:122 Total computation time\t: 0.047 seconds\nINFO src.main:main.py:127 Generated a trip of 300 minutes with 9 landmarks in 0.056 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}]}, "renderCollapsed": ["passed"], "initialSort": "result", "title": "Backend Testing Report"}"></div>
+ <div id="data-container" data-jsonblob="{"environment": {"Python": "3.12.3", "Platform": "Linux-6.8.0-51-generic-x86_64-with-glibc2.39", "Packages": {"pytest": "8.3.4", "pluggy": "1.5.0"}, "Plugins": {"html": "4.1.1", "anyio": "4.8.0", "metadata": "3.1.1"}}, "tests": {"src/tests/test_main.py::test_turckheim": [{"extras": [], "result": "Passed", "testId": "src/tests/test_main.py::test_turckheim", "resultsTableRow": ["<td class=\"col-result\">Passed</td>", "<td class=\"col-testId\">src/tests/test_main.py::test_turckheim</td>", "<td>start (0 | 0) - 3 - Mairie du 2e arrondissement (78 | 5) - 1 - Basilique Saint-Martin d'Ainay (406 | 5) - 3 - Chapelle Paul Couturier (109 | 5) - 1 - finish (0 | 0) - 0</td>", "<td>23 min</td>", "<td>20 min</td>", "<td class=\"col-duration\">97 ms</td>", "<td class=\"col-links\"></td>"], "log": "------------------------------ Captured log call -------------------------------\nDEBUG asyncio:selector_events.py:64 Using selector: EpollSelector\nINFO src.main:main.py:67 No end coordinates provided. Using start=end.\nDEBUG src.utils.landmarks_manager:landmarks_manager.py:76 Starting to fetch landmarks...\nDEBUG src.utils.landmarks_manager:landmarks_manager.py:88 Fetching sightseeing landmarks...\nINFO src.overpass.overpass:overpass.py:55 Cache hit for 2/2 quadrants.\nINFO src.overpass.overpass:overpass.py:55 Cache hit for 2/2 quadrants.\nINFO src.overpass.overpass:overpass.py:55 Cache hit for 2/2 quadrants.\nINFO src.overpass.overpass:overpass.py:55 Cache hit for 2/2 quadrants.\nINFO src.overpass.overpass:overpass.py:55 Cache hit for 2/2 quadrants.\nINFO src.overpass.overpass:overpass.py:55 Cache hit for 2/2 quadrants.\nDEBUG src.utils.landmarks_manager:landmarks_manager.py:204 Fetched 16 landmarks of type sightseeing in (45.74643460077641, 4.819803369760263, 45.756693361321055, 4.834505559895031)\nINFO src.utils.landmarks_manager:landmarks_manager.py:91 Found 16 sightseeing landmarks\nINFO src.overpass.overpass:overpass.py:55 Cache hit for 2/2 quadrants.\nINFO src.utils.cluster_manager:cluster_manager.py:145 Found 0 sightseeing clusters.\nINFO src.main:main.py:104 Fetched 12 landmarks in \t: 0.011 seconds\nDEBUG src.optimization.optimizer:optimizer.py:597 First results are out. Looking out for circles and correcting.\nINFO src.optimization.optimizer:optimizer.py:637 Re-optimized 0 times, objective value : 593\nDEBUG src.optimization.refiner:refiner.py:345 Using 2 minor landmarks around the predicted path\nDEBUG src.optimization.optimizer:optimizer.py:597 First results are out. Looking out for circles and correcting.\nINFO src.optimization.optimizer:optimizer.py:637 Re-optimized 0 times, objective value : 593\nDEBUG src.main:main.py:130 First stage optimization\t: 0.045 seconds\nDEBUG src.main:main.py:131 Second stage optimization\t: 0.025 seconds\nINFO src.main:main.py:132 Total computation time\t: 0.071 seconds\nINFO src.main:main.py:137 Generated a trip of 23 minutes with 5 landmarks in 0.082 seconds.\nINFO httpx:_client.py:1025 HTTP Request: POST http://testserver/trip/new &quot;HTTP/1.1 200 OK&quot;\n\n"}]}, "renderCollapsed": ["passed"], "initialSort": "result", "title": "Backend Testing Report"}"></div>
<script>
(function(){function r(e,n,t){function o(i,f){if(!n[i]){if(!e[i]){var c="function"==typeof require&&require;if(!f&&c)return c(i,!0);if(u)return u(i,!0);var a=new Error("Cannot find module '"+i+"'");throw a.code="MODULE_NOT_FOUND",a}var p=n[i]={exports:{}};e[i][0].call(p.exports,function(r){var n=e[i][1][r];return o(n||r)},p,p.exports,r,e,n,t)}return n[i].exports}for(var u="function"==typeof require&&require,i=0;i<t.length;i++)o(t[i]);return o}return r})()({1:[function(require,module,exports){
const { getCollapsedCategory, setCollapsedIds } = require('./storage.js')
diff --git a/backend/src/constants.py b/backend/src/constants.py
index 60a26c7..df811f7 100644
--- a/backend/src/constants.py
+++ b/backend/src/constants.py
@@ -2,6 +2,7 @@
import os
from pathlib import Path
+from typing import List, Literal, Tuple
LOCATION_PREFIX = Path('src')
@@ -14,6 +15,8 @@ OPTIMIZER_PARAMETERS_PATH = PARAMETERS_DIR / 'optimizer_parameters.yaml'
cache_dir_string = os.getenv('OSM_CACHE_DIR', './cache')
OSM_CACHE_DIR = Path(cache_dir_string)
+OSM_TYPES = List[Literal['way', 'node', 'relation']]
+BBOX = Tuple[float, float, float, float]
MEMCACHED_HOST_PATH = os.getenv('MEMCACHED_HOST_PATH', None)
if MEMCACHED_HOST_PATH == "none":
diff --git a/backend/src/main.py b/backend/src/main.py
index cdae598..104ff08 100644
--- a/backend/src/main.py
+++ b/backend/src/main.py
@@ -3,7 +3,7 @@
import logging
import time
from contextlib import asynccontextmanager
-from fastapi import FastAPI, HTTPException, Query
+from fastapi import FastAPI, HTTPException, BackgroundTasks, Query
from .logging_config import configure_logging
from .structs.landmark import Landmark, Toilets
@@ -14,8 +14,10 @@ from .utils.landmarks_manager import LandmarkManager
from .utils.toilets_manager import ToiletsManager
from .optimization.optimizer import Optimizer
from .optimization.refiner import Refiner
+from .overpass.overpass import fill_cache
from .cache import client as cache_client
+
logger = logging.getLogger(__name__)
manager = LandmarkManager()
@@ -35,11 +37,11 @@ async def lifespan(app: FastAPI):
app = FastAPI(lifespan=lifespan)
-
@app.post("/trip/new")
def new_trip(preferences: Preferences,
start: tuple[float, float],
- end: tuple[float, float] | None = None) -> Trip:
+ end: tuple[float, float] | None = None,
+ background_tasks: BackgroundTasks = None) -> Trip:
"""
Main function to call the optimizer.
@@ -91,6 +93,9 @@ def new_trip(preferences: Preferences,
preferences = preferences
)
+ if len(landmarks) == 0 :
+ raise HTTPException(status_code=500, detail="No landmarks were found.")
+
# insert start and finish to the landmarks list
landmarks_short.insert(0, start_landmark)
landmarks_short.append(end_landmark)
@@ -114,6 +119,9 @@ def new_trip(preferences: Preferences,
refined_tour = refiner.refine_optimization(landmarks, base_tour,
preferences.max_time_minute,
preferences.detour_tolerance_minute)
+ except TimeoutError as te :
+ logger.error(f'Refiner failed : {str(te)} Using base tour.')
+ refined_tour = base_tour
except Exception as exc :
raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(exc)}") from exc
@@ -127,6 +135,9 @@ def new_trip(preferences: Preferences,
# upon creation of the trip, persistence of both the trip and its landmarks is ensured.
trip = Trip.from_linked_landmarks(linked_tour, cache_client)
logger.info(f'Generated a trip of {trip.total_time} minutes with {len(refined_tour)} landmarks in {round(t_generate_landmarks + t_first_stage + t_second_stage,3)} seconds.')
+
+ background_tasks.add_task(fill_cache)
+
return trip
diff --git a/backend/src/optimization/optimizer.py b/backend/src/optimization/optimizer.py
index 54d5769..d368b07 100644
--- a/backend/src/optimization/optimizer.py
+++ b/backend/src/optimization/optimizer.py
@@ -55,6 +55,9 @@ class Optimizer:
self.average_walking_speed = parameters['average_walking_speed']
self.max_landmarks = parameters['max_landmarks']
self.overshoot = parameters['overshoot']
+ self.time_limit = parameters['time_limit']
+ self.gap_rel = parameters['gap_rel']
+ self.max_iter = parameters['max_iter']
def init_ub_time(self, prob: pl.LpProblem, x: pl.LpVariable, L: int, landmarks: list[Landmark], max_time: int):
@@ -490,10 +493,21 @@ class Optimizer:
def warm_start(self, x: list[pl.LpVariable], L: int) :
+ """
+ This function sets the initial values of the decision variables to a feasible solution.
+ This can help the solver start with a feasible or heuristic solution,
+ potentially speeding up convergence.
+ Args:
+ x (list[pl.LpVariable]): A list of PuLP decision variables (binary variables).
+ L (int): The size parameter, representing a dimension (likely related to a grid or matrix).
+
+ Returns:
+ list[pl.LpVariable]: The modified list of PuLP decision variables with initial values set.
+ """
for i in range(L*L) :
x[i].setInitialValue(0)
-
+
x[1].setInitialValue(1)
x[2*L-1].setInitialValue(1)
@@ -573,7 +587,10 @@ class Optimizer:
prob, x = self.pre_processing(L, landmarks, max_time, max_landmarks)
# Solve the problem and extract results.
- prob.solve(pl.PULP_CBC_CMD(msg=False, gapRel=0.1, timeLimit=10, warmStart=False))
+ try :
+ prob.solve(pl.PULP_CBC_CMD(msg=False, timeLimit=self.time_limit+1, gapRel=self.gap_rel))
+ except Exception as exc :
+ raise Exception(f"No solution found: {exc}") from exc
status = pl.LpStatus[prob.status]
solution = [pl.value(var) for var in x] # The values of the decision variables (will be 0 or 1)
@@ -588,18 +605,21 @@ class Optimizer:
circles = self.is_connected(solution)
i = 0
- timeout = 40
while circles is not None :
i += 1
- if i == timeout :
- self.logger.error(f'Timeout: No solution found after {timeout} iterations.')
- raise TimeoutError(f"Optimization took too long. No solution found after {timeout} iterations.")
+ if i == self.max_iter :
+ self.logger.error(f'Timeout: No solution found after {self.max_iter} iterations.')
+ raise TimeoutError(f"Optimization took too long. No solution found after {self.max_iter} iterations.")
for circle in circles :
self.prevent_circle(prob, x, circle, L)
# Solve the problem again
- prob.solve(pl.PULP_CBC_CMD(msg=False))
+ try :
+ prob.solve(pl.PULP_CBC_CMD(msg=False, timeLimit=self.time_limit, gapRel=self.gap_rel))
+ except Exception as exc :
+ raise Exception(f"No solution found: {exc}") from exc
+
solution = [pl.value(var) for var in x]
if pl.LpStatus[prob.status] != 'Optimal' :
@@ -614,5 +634,5 @@ class Optimizer:
order = self.get_order(solution)
tour = [landmarks[i] for i in order]
- self.logger.debug(f"Re-optimized {i} times, objective value : {int(pl.value(prob.objective))}")
+ self.logger.info(f"Re-optimized {i} times, objective value : {int(pl.value(prob.objective))}")
return tour
diff --git a/backend/src/overpass/caching_strategy.py b/backend/src/overpass/caching_strategy.py
index 9ca11b7..f334872 100644
--- a/backend/src/overpass/caching_strategy.py
+++ b/backend/src/overpass/caching_strategy.py
@@ -1,9 +1,8 @@
-"""Module defining the caching strategy for overpass requests."""
import os
-import xml.etree.ElementTree as ET
+import json
import hashlib
-from ..constants import OSM_CACHE_DIR
+from ..constants import OSM_CACHE_DIR, OSM_TYPES
def get_cache_key(query: str) -> str:
@@ -17,10 +16,6 @@ def get_cache_key(query: str) -> str:
class CachingStrategyBase:
"""
Base class for implementing caching strategies.
-
- This class defines the structure for a caching strategy with basic methods
- that must be implemented by subclasses. Subclasses should define how to
- retrieve, store, and close the cache.
"""
def get(self, key):
"""Retrieve the cached data associated with the provided key."""
@@ -30,111 +25,108 @@ class CachingStrategyBase:
"""Store data in the cache with the specified key."""
raise NotImplementedError('Subclass should implement set')
+ def set_hollow(self, key, **kwargs):
+ """Create a hollow (empty) cache entry with a specific key."""
+ raise NotImplementedError('Subclass should implement set_hollow')
+
def close(self):
"""Clean up or close any resources used by the caching strategy."""
-class XMLCache(CachingStrategyBase):
+class JSONCache(CachingStrategyBase):
"""
- A caching strategy that stores and retrieves data in XML format.
-
- This class provides methods to cache data as XML files in a specified directory.
- The directory is automatically suffixed with '_XML' to distinguish it from other
- caching strategies. The data is stored and retrieved using XML serialization.
-
- Args:
- cache_dir (str): The base directory where XML cache files will be stored.
- Defaults to 'OSM_CACHE_DIR' with a '_XML' suffix.
-
- Methods:
- get(key): Retrieve cached data from a XML file associated with the given key.
- set(key, value): Store data in a XML file with the specified key.
+ A caching strategy that stores and retrieves data in JSON format.
"""
def __init__(self, cache_dir=OSM_CACHE_DIR):
# Add the class name as a suffix to the directory
- self._cache_dir = f'{cache_dir}_XML'
+ self._cache_dir = f'{cache_dir}'
if not os.path.exists(self._cache_dir):
os.makedirs(self._cache_dir)
def _filename(self, key):
- return os.path.join(self._cache_dir, f'{key}.xml')
+ return os.path.join(self._cache_dir, f'{key}.json')
def get(self, key):
- """Retrieve XML data from the cache and parse it as an ElementTree."""
+ """Retrieve JSON data from the cache and parse it as an ElementTree."""
filename = self._filename(key)
if os.path.exists(filename):
try:
- # Parse and return the cached XML data
- tree = ET.parse(filename)
- return tree.getroot() # Return the root element of the parsed XML
- except ET.ParseError:
- # print(f"Error parsing cached XML file: {filename}")
- return None
+ # Open and parse the cached JSON data
+ with open(filename, 'r', encoding='utf-8') as file:
+ data = json.load(file)
+ # Return the data as a list of dicts.
+ return data
+ except json.JSONDecodeError:
+ return None # Return None if parsing fails
return None
def set(self, key, value):
- """Save the XML data as an ElementTree to the cache."""
+ """Save the JSON data as an ElementTree to the cache."""
filename = self._filename(key)
- tree = ET.ElementTree(value) # value is expected to be an ElementTree root element
try:
- # Write the XML data to a file
- with open(filename, 'wb') as file:
- tree.write(file, encoding='utf-8', xml_declaration=True)
+ # Write the JSON data to the cache file
+ with open(filename, 'w', encoding='utf-8') as file:
+ json.dump(value, file, ensure_ascii=False, indent=4)
except IOError as e:
raise IOError(f"Error writing to cache file: {filename} - {e}") from e
+ def set_hollow(self, key, cell: tuple, osm_types: list,
+ selector: str, conditions: list=None, out='center'):
+ """Create an empty placeholder cache entry for a future fill."""
+ hollow_key = f'hollow_{key}'
+ filename = self._filename(hollow_key)
+
+ # Create the hollow JSON structure
+ hollow_data = {
+ "key": key,
+ "cell": list(cell),
+ "osm_types": list(osm_types),
+ "selector": selector,
+ "conditions": conditions,
+ "out": out
+ }
+ # Write the hollow data to the cache file
+ try:
+ with open(filename, 'w', encoding='utf-8') as file:
+ json.dump(hollow_data, file, ensure_ascii=False, indent=4)
+ except IOError as e:
+ raise IOError(f"Error writing hollow cache to file: {filename} - {e}") from e
+
+ def close(self):
+ """Cleanup method, if needed."""
+ pass
class CachingStrategy:
"""
A class to manage different caching strategies.
-
- This class provides an interface to switch between different caching strategies
- (e.g., XMLCache, JSONCache) dynamically. It allows caching data in different formats,
- depending on the strategy being used. By default, it uses the XMLCache strategy.
-
- Attributes:
- __strategy (CachingStrategyBase): The currently active caching strategy.
- __strategies (dict): A mapping between strategy names (as strings) and their corresponding
- classes, allowing dynamic selection of caching strategies.
"""
- __strategy = XMLCache() # Default caching strategy
+ __strategy = JSONCache() # Default caching strategy
__strategies = {
- 'XML': XMLCache,
+ 'JSON': JSONCache,
}
@classmethod
- def use(cls, strategy_name='XML', **kwargs):
- """
- Set the caching strategy based on the strategy_name provided.
-
- Args:
- strategy_name (str): The name of the caching strategy (e.g., 'XML').
- **kwargs: Additional keyword arguments to pass when initializing the strategy.
- """
- # If a previous strategy exists, close it
+ def use(cls, strategy_name='JSON', **kwargs):
if cls.__strategy:
cls.__strategy.close()
- # Retrieve the strategy class based on the strategy name
strategy_class = cls.__strategies.get(strategy_name)
-
if not strategy_class:
raise ValueError(f"Unknown caching strategy: {strategy_name}")
- # Instantiate the new strategy with the provided arguments
cls.__strategy = strategy_class(**kwargs)
return cls.__strategy
@classmethod
def get(cls, key):
- """Get data from the current strategy's cache."""
- if not cls.__strategy:
- raise RuntimeError("Caching strategy has not been set.")
return cls.__strategy.get(key)
@classmethod
def set(cls, key, value):
- """Set data in the current strategy's cache."""
- if not cls.__strategy:
- raise RuntimeError("Caching strategy has not been set.")
cls.__strategy.set(key, value)
+
+ @classmethod
+ def set_hollow(cls, key, cell: tuple, osm_types: OSM_TYPES,
+ selector: str, conditions: list=None, out='center'):
+ """Create a hollow cache entry."""
+ cls.__strategy.set_hollow(key, cell, osm_types, selector, conditions, out)
diff --git a/backend/src/overpass/overpass.py b/backend/src/overpass/overpass.py
index 505053c..9180e9a 100644
--- a/backend/src/overpass/overpass.py
+++ b/backend/src/overpass/overpass.py
@@ -1,14 +1,17 @@
"""Module allowing connexion to overpass api and fectch data from OSM."""
-from typing import Literal, List
+import os
import urllib
+import math
import logging
-import xml.etree.ElementTree as ET
+import json
+from typing import List, Tuple
from .caching_strategy import get_cache_key, CachingStrategy
-from ..constants import OSM_CACHE_DIR
+from ..constants import OSM_CACHE_DIR, OSM_TYPES, BBOX
-logger = logging.getLogger('Overpass')
-osm_types = List[Literal['way', 'node', 'relation']]
+
+RESOLUTION = 0.05
+CELL = Tuple[int, int]
class Overpass :
@@ -16,7 +19,10 @@ class Overpass :
Overpass class to manage the query building and sending to overpass api.
The caching strategy is a part of this class and initialized upon creation of the Overpass object.
"""
- def __init__(self, caching_strategy: str = 'XML', cache_dir: str = OSM_CACHE_DIR) :
+ logger = logging.getLogger(__name__)
+
+
+ def __init__(self, caching_strategy: str = 'JSON', cache_dir: str = OSM_CACHE_DIR) :
"""
Initialize the Overpass instance with the url, headers and caching strategy.
"""
@@ -25,17 +31,109 @@ class Overpass :
self.caching_strategy = CachingStrategy.use(caching_strategy, cache_dir=cache_dir)
- @classmethod
- def build_query(self, area: tuple, osm_types: osm_types,
- selector: str, conditions=[], out='center') -> str:
+ def send_query(self, bbox: BBOX, osm_types: OSM_TYPES,
+ selector: str, conditions: list=None, out='center') -> List[dict]:
+ """
+ Sends the Overpass QL query to the Overpass API and returns the parsed json response.
+
+ Args:
+ bbox (tuple): Bounding box for the query.
+ osm_types (list[str]): List of OSM element types (e.g., 'node', 'way').
+ selector (str): Key or tag to filter OSM elements (e.g., 'highway').
+ conditions (list): Optional list of additional filter conditions in Overpass QL format.
+ out (str): Output format ('center', 'body', etc.). Defaults to 'center'.
+
+ Returns:
+ list: Parsed json response from the Overpass API, or cached data if available.
+ """
+ # Determine which grid cells overlap with this bounding box.
+ overlapping_cells = Overpass._get_overlapping_cells(bbox)
+
+ # Retrieve cached data and identify missing cache entries
+ cached_responses, non_cached_cells = self._retrieve_cached_data(overlapping_cells, osm_types, selector, conditions, out)
+
+ self.logger.info(f'Cache hit for {len(overlapping_cells)-len(non_cached_cells)}/{len(overlapping_cells)} quadrants.')
+
+ # If there is no missing data, return the cached responses after filtering.
+ if not non_cached_cells :
+ return Overpass._filter_landmarks(cached_responses, bbox)
+
+ # If there is no cached data, fetch all from Overpass.
+ elif not cached_responses :
+ query_str = Overpass.build_query(bbox, osm_types, selector, conditions, out)
+ return self.fetch_data_from_api(query_str)
+
+ # Hybrid cache: some data from Overpass, some data from cache.
+ else :
+ # Resize the bbox for smaller search area and build new query string.
+ non_cached_bbox = Overpass._get_non_cached_bbox(non_cached_cells, bbox)
+ query_str = Overpass.build_query(non_cached_bbox, osm_types, selector, conditions, out)
+ non_cached_responses = self.fetch_data_from_api(query_str)
+ return Overpass._filter_landmarks(cached_responses, bbox) + non_cached_responses
+
+
+ def fetch_data_from_api(self, query_str: str) -> List[dict]:
+ """
+ Fetch data from the Overpass API and return the json data.
+
+ Args:
+ query_str (str): The Overpass query string.
+
+ Returns:
+ dict: Combined cached and fetched data.
+ """
+ try:
+ data = urllib.parse.urlencode({'data': query_str}).encode('utf-8')
+ request = urllib.request.Request(self.overpass_url, data=data, headers=self.headers)
+
+ with urllib.request.urlopen(request) as response:
+ response_data = response.read().decode('utf-8') # Convert the HTTPResponse to a string
+ data = json.loads(response_data) # Load the JSON from the string
+ elements = data.get('elements', [])
+ # self.logger.debug(f'Query = {query_str}')
+ return elements
+
+ except urllib.error.URLError as e:
+ self.logger.error(f"Error connecting to Overpass API: {e}")
+ raise ConnectionError(f"Error connecting to Overpass API: {e}") from e
+ except Exception as exc :
+ raise Exception(f'An unexpected error occured: {str(exc)}') from exc
+
+
+ def fill_cache(self, json_data: dict) :
+ """
+ Fill cache with data by using a hollow cache entry's information.
+ """
+ query_str, cache_key = Overpass._build_query_from_hollow(json_data)
+ try:
+ data = urllib.parse.urlencode({'data': query_str}).encode('utf-8')
+ request = urllib.request.Request(self.overpass_url, data=data, headers=self.headers)
+
+ with urllib.request.urlopen(request) as response:
+
+ # Convert the HTTPResponse to a string and load data
+ response_data = response.read().decode('utf-8')
+ data = json.loads(response_data)
+
+ # Get elements and set cache
+ elements = data.get('elements', [])
+ self.caching_strategy.set(cache_key, elements)
+ self.logger.debug(f'Cache set for {cache_key}')
+ except urllib.error.URLError as e:
+ raise ConnectionError(f"Error connecting to Overpass API: {e}") from e
+ except Exception as exc :
+ raise Exception(f'An unexpected error occured: {str(exc)}') from exc
+
+
+ @staticmethod
+ def build_query(bbox: BBOX, osm_types: OSM_TYPES,
+ selector: str, conditions: list=None, out='center') -> str:
"""
Constructs a query string for the Overpass API to retrieve OpenStreetMap (OSM) data.
Args:
- area (tuple): A tuple representing the geographical search area, typically in the format
- (radius, latitude, longitude). The first element is a string like "around:2000"
- specifying the search radius, and the second and third elements represent
- the latitude and longitude as floats or strings.
+ bbox (tuple): A tuple representing the geographical search area, typically in the format
+ (lat_min, lon_min, lat_max, lon_max).
osm_types (list[str]): A list of OSM element types to search for. Must be one or more of
'Way', 'Node', or 'Relation'.
selector (str): The key or tag to filter the OSM elements (e.g., 'amenity', 'highway', etc.).
@@ -52,82 +150,203 @@ class Overpass :
Notes:
- If no conditions are provided, the query will just use the `selector` to filter the OSM
elements without additional constraints.
- - The search area must always formatted as "(radius, lat, lon)".
"""
- if not isinstance(conditions, list) :
- conditions = [conditions]
- if not isinstance(osm_types, list) :
- osm_types = [osm_types]
+ query = '[out:json];('
- query = '('
+ # convert the bbox to string.
+ bbox_str = f"({','.join(map(str, bbox))})"
- # Round the radius to nearest 50 and coordinates to generate less queries
- if area[0] > 500 :
- search_radius = round(area[0] / 50) * 50
- loc = tuple((round(area[1], 2), round(area[2], 2)))
- else :
- search_radius = round(area[0] / 25) * 25
- loc = tuple((round(area[1], 3), round(area[2], 3)))
-
- search_area = f"(around:{search_radius}, {str(loc[0])}, {str(loc[1])})"
-
- if conditions :
+ if conditions is not None and len(conditions) > 0:
conditions = '(if: ' + ' && '.join(conditions) + ')'
else :
conditions = ''
for elem in osm_types :
- query += elem + '[' + selector + ']' + conditions + search_area + ';'
+ query += elem + '[' + selector + ']' + conditions + bbox_str + ';'
query += ');' + f'out {out};'
return query
- def send_query(self, query: str) -> ET:
+ def _retrieve_cached_data(self, overlapping_cells: CELL, osm_types: OSM_TYPES,
+ selector: str, conditions: list, out: str) -> Tuple[List[dict], list[CELL]]:
"""
- Sends the Overpass QL query to the Overpass API and returns the parsed JSON response.
+ Retrieve cached data and identify missing cache quadrants.
Args:
- query (str): The Overpass QL query to be sent to the Overpass API.
+ overlapping_cells (list): Cells to check for cached data.
+ osm_types (list): OSM types (e.g., 'node', 'way').
+ selector (str): Key or tag to filter OSM elements.
+ conditions (list): Additional conditions to apply.
+ out (str): Output format.
Returns:
- dict: The parsed JSON response from the Overpass API, or None if the request fails.
+ tuple: A tuple containing:
+ - cached_responses (list): List of cached data found.
+ - non_cached_cells (list(tuple)): List of cells with missing data.
+ """
+ cell_key_dict = {}
+ for cell in overlapping_cells :
+ for elem in osm_types :
+ key_str = f"{elem}[{selector}]{conditions}({','.join(map(str, cell))})"
+
+ cell_key_dict[cell] = get_cache_key(key_str)
+
+ cached_responses = []
+ non_cached_cells = []
+
+ # Retrieve the cached data and mark the missing entries as hollow
+ for cell, key in cell_key_dict.items():
+ cached_data = self.caching_strategy.get(key)
+ if cached_data is not None :
+ cached_responses += cached_data
+ else:
+ self.caching_strategy.set_hollow(key, cell, osm_types, selector, conditions, out)
+ non_cached_cells.append(cell)
+
+ return cached_responses, non_cached_cells
+
+
+ @staticmethod
+ def _build_query_from_hollow(json_data: dict) -> Tuple[str, str]:
+ """
+ Build query string using information from a hollow cache entry.
+ """
+ # Extract values from the JSON object
+ key = json_data.get('key')
+ cell = tuple(json_data.get('cell'))
+ bbox = Overpass._get_bbox_from_grid_cell(cell)
+ osm_types = json_data.get('osm_types')
+ selector = json_data.get('selector')
+ conditions = json_data.get('conditions')
+ out = json_data.get('out')
+
+
+ query_str = Overpass.build_query(bbox, osm_types, selector, conditions, out)
+ return query_str, key
+
+
+ @staticmethod
+ def _get_overlapping_cells(query_bbox: tuple) -> List[CELL]:
+ """
+ Returns a set of all grid cells that overlap with the given bounding box.
+ """
+ # Extract location from the query bbox
+ lat_min, lon_min, lat_max, lon_max = query_bbox
+
+ min_lat_cell, min_lon_cell = Overpass._get_grid_cell(lat_min, lon_min)
+ max_lat_cell, max_lon_cell = Overpass._get_grid_cell(lat_max, lon_max)
+
+ overlapping_cells = set()
+ for lat_idx in range(min_lat_cell, max_lat_cell + 1):
+ for lon_idx in range(min_lon_cell, max_lon_cell + 1):
+ overlapping_cells.add((lat_idx, lon_idx))
+
+ return overlapping_cells
+
+
+ @staticmethod
+ def _get_grid_cell(lat: float, lon: float) -> CELL:
+ """
+ Returns the grid cell coordinates for a given latitude and longitude.
+ Each grid cell is 0.05°lat x 0.05°lon resolution in size.
+ """
+ lat_index = math.floor(lat / RESOLUTION)
+ lon_index = math.floor(lon / RESOLUTION)
+ return (lat_index, lon_index)
+
+
+ @staticmethod
+ def _get_bbox_from_grid_cell(cell: CELL) -> BBOX:
+ """
+ Returns the bounding box for a given grid cell index.
+ Each grid cell is resolution x resolution in size.
+
+ The bounding box is returned as (min_lat, min_lon, max_lat, max_lon).
+ """
+ # Calculate the southwest (min_lat, min_lon) corner of the bounding box
+ min_lat = round(cell[0] * RESOLUTION, 2)
+ min_lon = round(cell[1] * RESOLUTION, 2)
+
+ # Calculate the northeast (max_lat, max_lon) corner of the bounding box
+ max_lat = round((cell[0] + 1) * RESOLUTION, 2)
+ max_lon = round((cell[1] + 1) * RESOLUTION, 2)
+
+ return (min_lat, min_lon, max_lat, max_lon)
+
+
+ @staticmethod
+ def _get_non_cached_bbox(non_cached_cells: List[CELL], original_bbox: BBOX):
+ """
+ Calculate the non-cached bounding box by excluding cached cells.
+
+ Args:
+ non_cached_cells (list): The list of cells that were not found in the cache.
+ original_bbox (tuple): The original bounding box (min_lat, min_lon, max_lat, max_lon).
+
+ Returns:
+ tuple: The new bounding box that excludes cached cells, or None if all cells are cached.
+ """
+ if not non_cached_cells:
+ return None # All cells were cached
+
+ # Initialize the non-cached bounding box with extreme values
+ min_lat, min_lon, max_lat, max_lon = float('inf'), float('inf'), float('-inf'), float('-inf')
+
+ # Iterate over non-cached cells to find the new bounding box
+ for cell in non_cached_cells:
+ cell_min_lat, cell_min_lon, cell_max_lat, cell_max_lon = Overpass._get_bbox_from_grid_cell(cell)
+
+ min_lat = min(min_lat, cell_min_lat)
+ min_lon = min(min_lon, cell_min_lon)
+ max_lat = max(max_lat, cell_max_lat)
+ max_lon = max(max_lon, cell_max_lon)
+
+ # If no update to bounding box, return the original
+ if min_lat == float('inf') or min_lon == float('inf'):
+ return None
+
+ return (max(min_lat, original_bbox[0]),
+ max(min_lon, original_bbox[1]),
+ min(max_lat, original_bbox[2]),
+ min(max_lon, original_bbox[3]))
+
+
+ @staticmethod
+ def _filter_landmarks(elements: List[dict], bbox: BBOX) -> List[dict]:
+ """
+ Filters elements based on whether their coordinates are inside the given bbox.
+
+ Args:
+ - elements (list of dict): List of elements containing coordinates.
+ - bbox (tuple): A bounding box defined as (min_lat, min_lon, max_lat, max_lon).
+
+ Returns:
+ - list: A list of elements whose coordinates are inside the bounding box.
"""
- # Generate a cache key for the current query
- cache_key = get_cache_key(query)
+ filtered_elements = []
+ min_lat, min_lon, max_lat, max_lon = bbox
- # Try to fetch the result from the cache
- cached_response = self.caching_strategy.get(cache_key)
- if cached_response is not None :
- logger.debug("Cache hit.")
- return cached_response
+ for elem in elements:
+ # Extract coordinates based on the 'type' of element
+ if elem.get('type') != 'node':
+ center = elem.get('center', {})
+ lat = float(center.get('lat', 0))
+ lon = float(center.get('lon', 0))
+ else:
+ lat = float(elem.get('lat', 0))
+ lon = float(elem.get('lon', 0))
- # Prepare the data to be sent as POST request, encoded as bytes
- data = urllib.parse.urlencode({'data': query}).encode('utf-8')
+ # Check if the coordinates fall within the given bounding box
+ if min_lat <= lat <= max_lat and min_lon <= lon <= max_lon:
+ filtered_elements.append(elem)
- try:
- # Create a Request object with the specified URL, data, and headers
- request = urllib.request.Request(self.overpass_url, data=data, headers=self.headers)
-
- # Send the request and read the response
- with urllib.request.urlopen(request) as response:
- # Read and decode the response
- response_data = response.read().decode('utf-8')
- root = ET.fromstring(response_data)
-
- # Cache the response data as an ElementTree root
- self.caching_strategy.set(cache_key, root)
- logger.debug("Response data added to cache.")
-
- return root
-
- except urllib.error.URLError as e:
- raise ConnectionError(f"Error connecting to Overpass API: {e}") from e
+ return filtered_elements
-def get_base_info(elem: ET.Element, osm_type: osm_types, with_name=False) :
+def get_base_info(elem: dict, osm_type: OSM_TYPES, with_name=False) :
"""
Extracts base information (coordinates, OSM ID, and optionally a name) from an OSM element.
@@ -136,7 +355,7 @@ def get_base_info(elem: ET.Element, osm_type: osm_types, with_name=False) :
extracting coordinates either directly or from a center tag, depending on the element type.
Args:
- elem (ET.Element): The XML element representing the OSM entity.
+ elem (dict): The JSON element representing the OSM entity.
osm_type (str): The type of the OSM entity (e.g., 'node', 'way'). If 'node', the coordinates
are extracted directly from the element; otherwise, from the 'center' tag.
with_name (bool): Whether to extract and return the name of the element. If True, it attempts
@@ -150,7 +369,7 @@ def get_base_info(elem: ET.Element, osm_type: osm_types, with_name=False) :
"""
# 1. extract coordinates
if osm_type != 'node' :
- center = elem.find('center')
+ center = elem.get('center')
lat = float(center.get('lat'))
lon = float(center.get('lon'))
@@ -165,7 +384,31 @@ def get_base_info(elem: ET.Element, osm_type: osm_types, with_name=False) :
# 3. Extract name if specified and return
if with_name :
- name = elem.find("tag[@k='name']").get('v') if elem.find("tag[@k='name']") is not None else None
+ name = elem.get('tags', {}).get('name')
return osm_id, coords, name
else :
return osm_id, coords
+
+
+def fill_cache():
+ """
+ Scans the specified cache directory for files starting with 'hollow_' and attempts to load
+ their contents as JSON to fill the cache of the Overpass system.
+ """
+ overpass = Overpass()
+
+ with os.scandir(OSM_CACHE_DIR) as it:
+ for entry in it:
+ if entry.is_file() and entry.name.startswith('hollow_'):
+
+ try :
+ # Read the whole file content as a string
+ with open(entry.path, 'r') as f:
+ # load data and fill the cache with the query and key
+ json_data = json.load(f)
+ overpass.fill_cache(json_data)
+ # Now delete the file as the cache is filled
+ os.remove(entry.path)
+
+ except Exception as exc :
+ overpass.logger.error(f'An error occured while parsing file {entry.path} as .json file')
diff --git a/backend/src/parameters/landmark_parameters.yaml b/backend/src/parameters/landmark_parameters.yaml
index 159f19f..581777f 100644
--- a/backend/src/parameters/landmark_parameters.yaml
+++ b/backend/src/parameters/landmark_parameters.yaml
@@ -1,4 +1,4 @@
-city_bbox_side: 7500 #m
+max_bbox_side: 4000 #m
radius_close_to: 50
church_coeff: 0.55
nature_coeff: 1.4
@@ -8,5 +8,5 @@ image_bonus: 1.1
viewpoint_bonus: 5
wikipedia_bonus: 1.25
name_bonus: 3
-N_important: 40
+N_important: 60
pay_bonus: -1
diff --git a/backend/src/parameters/optimizer_parameters.yaml b/backend/src/parameters/optimizer_parameters.yaml
index 79cd24c..2603e08 100644
--- a/backend/src/parameters/optimizer_parameters.yaml
+++ b/backend/src/parameters/optimizer_parameters.yaml
@@ -4,3 +4,6 @@ average_walking_speed: 4.8
max_landmarks: 10
max_landmarks_refiner: 20
overshoot: 0.0016
+time_limit: 1
+gap_rel: 0.05
+max_iter: 40
\ No newline at end of file
diff --git a/backend/src/structs/landmark.py b/backend/src/structs/landmark.py
index 50c9d78..ecb27ec 100644
--- a/backend/src/structs/landmark.py
+++ b/backend/src/structs/landmark.py
@@ -2,7 +2,7 @@
from typing import Optional, Literal
from uuid import uuid4, UUID
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
# Output to frontend
@@ -144,8 +144,4 @@ class Toilets(BaseModel) :
"""
return f'Toilets @{self.location}'
- class Config:
- """
- This allows us to easily convert the model to and from dictionaries
- """
- from_attributes = True
+ model_config = ConfigDict(from_attributes=True)
diff --git a/backend/src/tests/test_main.py b/backend/src/tests/test_main.py
index 8cbcdd3..b3f1c1a 100644
--- a/backend/src/tests/test_main.py
+++ b/backend/src/tests/test_main.py
@@ -27,11 +27,13 @@ def test_turckheim(client, request): # pylint: disable=redefined-outer-name
"/trip/new",
json={
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
- "nature": {"type": "nature", "score": 5},
- "shopping": {"type": "shopping", "score": 5},
+ "nature": {"type": "nature", "score": 0},
+ "shopping": {"type": "shopping", "score": 0},
"max_time_minute": duration_minutes,
"detour_tolerance_minute": 0},
- "start": [48.084588, 7.280405]
+ # "start": [48.084588, 7.280405]
+ # "start": [45.74445023349939, 4.8222687890538865]
+ "start": [45.75156398104873, 4.827154464827647]
}
)
result = response.json()
@@ -51,11 +53,11 @@ def test_turckheim(client, request): # pylint: disable=redefined-outer-name
assert response.status_code == 200 # check for successful planning
assert isinstance(landmarks, list) # check that the return type is a list
assert len(landmarks) > 2 # check that there is something to visit
+ assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
# assert 2!= 3
-
def test_bellecour(client, request) : # pylint: disable=redefined-outer-name
"""
Test n°2 : Custom test in Lyon centre to ensure proper decision making in crowded area.
@@ -97,10 +99,9 @@ def test_bellecour(client, request) : # pylint: disable=redefined-outer-name
assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
-
def test_cologne(client, request) : # pylint: disable=redefined-outer-name
"""
- Test n°2 : Custom test in Lyon centre to ensure proper decision making in crowded area.
+ Test n°3 : Custom test in Cologne to ensure proper decision making in crowded area.
Args:
client:
@@ -141,7 +142,7 @@ def test_cologne(client, request) : # pylint: disable=redefined-outer-name
def test_strasbourg(client, request) : # pylint: disable=redefined-outer-name
"""
- Test n°2 : Custom test in Lyon centre to ensure proper decision making in crowded area.
+ Test n°4 : Custom test in Strasbourg to ensure proper decision making in crowded area.
Args:
client:
@@ -182,7 +183,7 @@ def test_strasbourg(client, request) : # pylint: disable=redefined-outer-name
def test_zurich(client, request) : # pylint: disable=redefined-outer-name
"""
- Test n°2 : Custom test in Lyon centre to ensure proper decision making in crowded area.
+ Test n°5 : Custom test in Zurich to ensure proper decision making in crowded area.
Args:
client:
@@ -223,24 +224,24 @@ def test_zurich(client, request) : # pylint: disable=redefined-outer-name
def test_paris(client, request) : # pylint: disable=redefined-outer-name
"""
- Test n°2 : Custom test in Paris (les Halles) centre to ensure proper decision making in crowded area.
+ Test n°6 : Custom test in Paris (les Halles) centre to ensure proper decision making in crowded area.
Args:
client:
request:
"""
start_time = time.time() # Start timer
- duration_minutes = 300
+ duration_minutes = 200
response = client.post(
"/trip/new",
json={
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
- "nature": {"type": "nature", "score": 5},
+ "nature": {"type": "nature", "score": 0},
"shopping": {"type": "shopping", "score": 5},
"max_time_minute": duration_minutes,
"detour_tolerance_minute": 0},
- "start": [48.86248803298562, 2.346451131285925]
+ "start": [48.85468881798671, 2.3423925755998374]
}
)
result = response.json()
@@ -264,7 +265,7 @@ def test_paris(client, request) : # pylint: disable=redefined-outer-name
def test_new_york(client, request) : # pylint: disable=redefined-outer-name
"""
- Test n°2 : Custom test in New York (les Halles) centre to ensure proper decision making in crowded area.
+ Test n°7 : Custom test in New York to ensure proper decision making in crowded area.
Args:
client:
@@ -305,7 +306,7 @@ def test_new_york(client, request) : # pylint: disable=redefined-outer-name
def test_shopping(client, request) : # pylint: disable=redefined-outer-name
"""
- Test n°3 : Custom test in Lyon centre to ensure shopping clusters are found.
+ Test n°8 : Custom test in Lyon centre to ensure shopping clusters are found.
Args:
client:
@@ -334,11 +335,11 @@ def test_shopping(client, request) : # pylint: disable=redefined-outer-name
# Add details to report
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
- for elem in landmarks :
- print(elem)
+ # for elem in landmarks :
+ # print(elem)
# checks :
assert response.status_code == 200 # check for successful planning
assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
assert duration_minutes*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {duration_minutes}"
- assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
+ assert duration_minutes*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {duration_minutes}"
\ No newline at end of file
diff --git a/backend/src/utils/cluster_manager.py b/backend/src/utils/cluster_manager.py
index 95d3f14..d7e7673 100644
--- a/backend/src/utils/cluster_manager.py
+++ b/backend/src/utils/cluster_manager.py
@@ -9,7 +9,8 @@ from pydantic import BaseModel
from ..overpass.overpass import Overpass, get_base_info
from ..structs.landmark import Landmark
from .get_time_distance import get_distance
-from ..constants import OSM_CACHE_DIR
+from .utils import create_bbox
+
# silence the overpass logger
@@ -79,8 +80,7 @@ class ClusterManager:
bbox: The bounding box coordinates (around:radius, center_lat, center_lon).
"""
# Setup the caching in the Overpass class.
- self.overpass = Overpass(caching_strategy='XML', cache_dir=OSM_CACHE_DIR)
-
+ self.overpass = Overpass()
self.cluster_type = cluster_type
if cluster_type == 'shopping' :
@@ -95,32 +95,29 @@ class ClusterManager:
raise NotImplementedError("Please choose only an available option for cluster detection")
# Initialize the points for cluster detection
- query = self.overpass.build_query(
- area = bbox,
+ try:
+ result = self.overpass.send_query(
+ bbox = bbox,
osm_types = osm_types,
selector = sel,
out = out
)
- self.logger.debug(f"Cluster query: {query}")
-
- try:
- result = self.overpass.send_query(query)
except Exception as e:
- self.logger.error(f"Error fetching landmarks: {e}")
+ self.logger.error(f"Error fetching clusters: {e}")
if result is None :
- self.logger.error(f"Error fetching {cluster_type} clusters, overpass query returned None.")
+ self.logger.debug(f"Found no {cluster_type} clusters, overpass query returned no datapoints.")
self.valid = False
else :
points = []
- for osm_type in osm_types :
- for elem in result.findall(osm_type):
-
- # Get coordinates and append them to the points list
- _, coords = get_base_info(elem, osm_type)
- if coords is not None :
- points.append(coords)
+ for elem in result:
+ osm_type = elem.get('type')
+
+ # Get coordinates and append them to the points list
+ _, coords = get_base_info(elem, osm_type)
+ if coords is not None :
+ points.append(coords)
if points :
self.all_points = np.array(points)
@@ -137,7 +134,7 @@ class ClusterManager:
# Check that there are is least 1 cluster
if len(set(labels)) > 1 :
- self.logger.debug(f"Found {len(set(labels))} different clusters.")
+ self.logger.info(f"Found {len(set(labels))} different {cluster_type} clusters.")
# Separate clustered points and noise points
self.cluster_points = self.all_points[labels != -1]
self.cluster_labels = labels[labels != -1]
@@ -145,7 +142,7 @@ class ClusterManager:
self.valid = True
else :
- self.logger.debug(f"Detected 0 {cluster_type} clusters.")
+ self.logger.info(f"Found 0 {cluster_type} clusters.")
self.valid = False
else :
@@ -218,9 +215,8 @@ class ClusterManager:
"""
# Define the bounding box for a given radius around the coordinates
- lat, lon = cluster.centroid
- bbox = (1000, lat, lon)
-
+ bbox = create_bbox(cluster.centroid, 1000)
+
# Query neighborhoods and shopping malls
selectors = ['"place"~"^(suburb|neighborhood|neighbourhood|quarter|city_block)$"']
@@ -238,37 +234,34 @@ class ClusterManager:
osm_types = ['node', 'way', 'relation']
for sel in selectors :
- query = self.overpass.build_query(
- area = bbox,
- osm_types = osm_types,
- selector = sel,
- out = 'ids center'
- )
-
try:
- result = self.overpass.send_query(query)
+ result = self.overpass.send_query(bbox = bbox,
+ osm_types = osm_types,
+ selector = sel,
+ out = 'ids center'
+ )
except Exception as e:
- self.logger.error(f"Error fetching landmarks: {e}")
+ self.logger.error(f"Error fetching clusters: {e}")
continue
if result is None :
- self.logger.error(f"Error fetching landmarks: {e}")
+ self.logger.error(f"Error fetching clusters: {e}")
continue
- for osm_type in osm_types :
- for elem in result.findall(osm_type):
+ for elem in result:
+ osm_type = elem.get('type')
- id, coords, name = get_base_info(elem, osm_type, with_name=True)
+ id, coords, name = get_base_info(elem, osm_type, with_name=True)
- if name is None or coords is None :
- continue
+ if name is None or coords is None :
+ continue
- d = get_distance(cluster.centroid, coords)
- if d < min_dist :
- min_dist = d
- new_name = name
- osm_type = osm_type # Add type: 'way' or 'relation'
- osm_id = id # Add OSM id
+ d = get_distance(cluster.centroid, coords)
+ if d < min_dist :
+ min_dist = d
+ new_name = name
+ osm_type = osm_type # Add type: 'way' or 'relation'
+ osm_id = id # Add OSM id
return Landmark(
name=new_name,
diff --git a/backend/src/utils/landmarks_manager.py b/backend/src/utils/landmarks_manager.py
index 6aabace..5523e26 100644
--- a/backend/src/utils/landmarks_manager.py
+++ b/backend/src/utils/landmarks_manager.py
@@ -1,19 +1,15 @@
"""Module used to import data from OSM and arrange them in categories."""
import logging
-import xml.etree.ElementTree as ET
import yaml
-
from ..structs.preferences import Preferences
from ..structs.landmark import Landmark
from .take_most_important import take_most_important
from .cluster_manager import ClusterManager
from ..overpass.overpass import Overpass, get_base_info
+from .utils import create_bbox
-from ..constants import AMENITY_SELECTORS_PATH, LANDMARK_PARAMETERS_PATH, OPTIMIZER_PARAMETERS_PATH, OSM_CACHE_DIR
-
-# silence the overpass logger
-logging.getLogger('Overpass').setLevel(level=logging.CRITICAL)
+from ..constants import AMENITY_SELECTORS_PATH, LANDMARK_PARAMETERS_PATH, OPTIMIZER_PARAMETERS_PATH
class LandmarkManager:
@@ -37,8 +33,7 @@ class LandmarkManager:
with LANDMARK_PARAMETERS_PATH.open('r') as f:
parameters = yaml.safe_load(f)
- self.max_bbox_side = parameters['city_bbox_side']
- self.radius_close_to = parameters['radius_close_to']
+ self.max_bbox_side = parameters['max_bbox_side']
self.church_coeff = parameters['church_coeff']
self.nature_coeff = parameters['nature_coeff']
self.overall_coeff = parameters['overall_coeff']
@@ -56,7 +51,7 @@ class LandmarkManager:
self.detour_factor = parameters['detour_factor']
# Setup the caching in the Overpass class.
- self.overpass = Overpass(caching_strategy='XML', cache_dir=OSM_CACHE_DIR)
+ self.overpass = Overpass()
self.logger.info('LandmakManager successfully initialized.')
@@ -80,39 +75,39 @@ class LandmarkManager:
"""
self.logger.debug('Starting to fetch landmarks...')
max_walk_dist = int((preferences.max_time_minute/2)/60*self.walking_speed*1000/self.detour_factor)
- reachable_bbox_side = min(max_walk_dist, self.max_bbox_side)
+ radius = min(max_walk_dist, int(self.max_bbox_side/2))
# use set to avoid duplicates, this requires some __methods__ to be set in Landmark
all_landmarks = set()
# Create a bbox using the around technique, tuple of strings
- bbox = tuple((min(2000, reachable_bbox_side/2), center_coordinates[0], center_coordinates[1]))
+ bbox = create_bbox(center_coordinates, radius)
# list for sightseeing
if preferences.sightseeing.score != 0:
self.logger.debug('Fetching sightseeing landmarks...')
current_landmarks = self.fetch_landmarks(bbox, self.amenity_selectors['sightseeing'], preferences.sightseeing.type, preferences.sightseeing.score)
all_landmarks.update(current_landmarks)
- self.logger.debug('Fetching sightseeing clusters...')
+ self.logger.info(f'Found {len(current_landmarks)} sightseeing landmarks')
# special pipeline for historic neighborhoods
neighborhood_manager = ClusterManager(bbox, 'sightseeing')
historic_clusters = neighborhood_manager.generate_clusters()
all_landmarks.update(historic_clusters)
- self.logger.debug('Sightseeing clusters done')
# list for nature
if preferences.nature.score != 0:
self.logger.debug('Fetching nature landmarks...')
current_landmarks = self.fetch_landmarks(bbox, self.amenity_selectors['nature'], preferences.nature.type, preferences.nature.score)
all_landmarks.update(current_landmarks)
+ self.logger.info(f'Found {len(current_landmarks)} nature landmarks')
# list for shopping
if preferences.shopping.score != 0:
self.logger.debug('Fetching shopping landmarks...')
current_landmarks = self.fetch_landmarks(bbox, self.amenity_selectors['shopping'], preferences.shopping.type, preferences.shopping.score)
- self.logger.debug('Fetching shopping clusters...')
+ self.logger.info(f'Found {len(current_landmarks)} shopping landmarks')
# set time for all shopping activites :
for landmark in current_landmarks :
@@ -123,8 +118,6 @@ class LandmarkManager:
shopping_manager = ClusterManager(bbox, 'shopping')
shopping_clusters = shopping_manager.generate_clusters()
all_landmarks.update(shopping_clusters)
- self.logger.debug('Shopping clusters done')
-
landmarks_constrained = take_most_important(all_landmarks, self.n_important)
@@ -179,7 +172,7 @@ class LandmarkManager:
"""
return_list = []
- if landmarktype == 'nature' : query_conditions = []
+ if landmarktype == 'nature' : query_conditions = None
else : query_conditions = ['count_tags()>5']
# caution, when applying a list of selectors, overpass will search for elements that match ALL selectors simultaneously
@@ -190,117 +183,115 @@ class LandmarkManager:
osm_types = ['way', 'relation']
if 'viewpoint' in sel :
- query_conditions = []
+ query_conditions = None
osm_types.append('node')
- query = self.overpass.build_query(
- area = bbox,
- osm_types = osm_types,
- selector = sel,
- conditions = query_conditions, # except for nature....
- out = 'center'
- )
- self.logger.debug(f"Query: {query}")
-
+ # Send the overpass query
try:
- result = self.overpass.send_query(query)
+ result = self.overpass.send_query(
+ bbox = bbox,
+ osm_types = osm_types,
+ selector = sel,
+ conditions = query_conditions, # except for nature....
+ out = 'ids center tags'
+ )
except Exception as e:
self.logger.error(f"Error fetching landmarks: {e}")
continue
- return_list += self.xml_to_landmarks(result, landmarktype, preference_level)
+ return_list += self._to_landmarks(result, landmarktype, preference_level)
self.logger.debug(f"Fetched {len(return_list)} landmarks of type {landmarktype} in {bbox}")
return return_list
- def xml_to_landmarks(self, root: ET.Element, landmarktype, preference_level) -> list[Landmark]:
+ def _to_landmarks(self, elements: list, landmarktype, preference_level) -> list[Landmark]:
"""
Parse the Overpass API result and extract landmarks.
- This method processes the XML root element returned by the Overpass API and
+ This method processes the JSON elements returned by the Overpass API and
extracts landmarks of types 'node', 'way', and 'relation'. It retrieves
relevant information such as name, coordinates, and tags, and converts them
into Landmark objects.
Args:
- root (ET.Element): The root element of the XML response from Overpass API.
+ elements (list): The elements of json response from Overpass API.
elem_type (str): The type of landmark (e.g., node, way, relation).
Returns:
- list[Landmark]: A list of Landmark objects extracted from the XML data.
+ list[Landmark]: A list of Landmark objects extracted from the JSON data.
"""
- if root is None :
+ if elements is None :
return []
landmarks = []
- for osm_type in ['node', 'way', 'relation'] :
- for elem in root.findall(osm_type):
+ for elem in elements:
+ osm_type = elem.get('type')
- id, coords, name = get_base_info(elem, osm_type, with_name=True)
-
- if name is None or coords is None :
- continue
-
- tags = elem.findall('tag')
-
- # Convert this to Landmark object
- landmark = Landmark(name=name,
- type=landmarktype,
- location=coords,
- osm_id=id,
- osm_type=osm_type,
- attractiveness=0,
- n_tags=len(tags))
-
- # Browse through tags to add information to landmark.
- for tag in tags:
- key = tag.get('k')
- value = tag.get('v')
-
- # Skip this landmark if not suitable.
- if key == 'building:part' and value == 'yes' :
- break
- if 'disused:' in key :
- break
- if 'boundary:' in key :
- break
- if 'shop' in key and landmarktype != 'shopping' :
- break
- # if value == 'apartments' :
- # break
-
- # Fill in the other attributes.
- if key == 'image' :
- landmark.image_url = value
- if key == 'website' :
- landmark.website_url = value
- if key == 'place_of_worship' :
- landmark.is_place_of_worship = True
- if key == 'wikipedia' :
- landmark.wiki_url = value
- if key == 'name:en' :
- landmark.name_en = value
- if 'building:' in key or 'pay' in key :
- landmark.n_tags -= 1
-
- # Set the duration.
- if value in ['museum', 'aquarium', 'planetarium'] :
- landmark.duration = 60
- elif value == 'viewpoint' :
- landmark.is_viewpoint = True
- landmark.duration = 10
- elif value == 'cathedral' :
- landmark.is_place_of_worship = False
- landmark.duration = 10
-
- else:
- self.set_landmark_score(landmark, landmarktype, preference_level)
- landmarks.append(landmark)
+ id, coords, name = get_base_info(elem, osm_type, with_name=True)
+ if name is None or coords is None :
continue
+ tags = elem.get('tags')
+
+ # Convert this to Landmark object
+ landmark = Landmark(name=name,
+ type=landmarktype,
+ location=coords,
+ osm_id=id,
+ osm_type=osm_type,
+ attractiveness=0,
+ n_tags=len(tags))
+
+ # self.logger.debug('added landmark.')
+
+ # Browse through tags to add information to landmark.
+ for key, value in tags.items():
+
+ # Skip this landmark if not suitable.
+ if key == 'building:part' and value == 'yes' :
+ break
+ if 'disused:' in key :
+ break
+ if 'boundary:' in key :
+ break
+ if 'shop' in key and landmarktype != 'shopping' :
+ break
+ # if value == 'apartments' :
+ # break
+
+ # Fill in the other attributes.
+ if key == 'image' :
+ landmark.image_url = value
+ if key == 'website' :
+ landmark.website_url = value
+ if key == 'place_of_worship' :
+ landmark.is_place_of_worship = True
+ if key == 'wikipedia' :
+ landmark.wiki_url = value
+ if key == 'name:en' :
+ landmark.name_en = value
+ if 'building:' in key or 'pay' in key :
+ landmark.n_tags -= 1
+
+ # Set the duration.
+ if value in ['museum', 'aquarium', 'planetarium'] :
+ landmark.duration = 60
+ elif value == 'viewpoint' :
+ landmark.is_viewpoint = True
+ landmark.duration = 10
+ elif value == 'cathedral' :
+ landmark.is_place_of_worship = False
+ landmark.duration = 10
+
+ else:
+ self.set_landmark_score(landmark, landmarktype, preference_level)
+ landmarks.append(landmark)
+
+ continue
+
return landmarks
def dict_to_selector_list(d: dict) -> list:
diff --git a/backend/src/utils/toilets_manager.py b/backend/src/utils/toilets_manager.py
index e15dd0a..57c0d83 100644
--- a/backend/src/utils/toilets_manager.py
+++ b/backend/src/utils/toilets_manager.py
@@ -1,10 +1,9 @@
"""Module for finding public toilets around given coordinates."""
import logging
-import xml.etree.ElementTree as ET
from ..overpass.overpass import Overpass, get_base_info
from ..structs.landmark import Toilets
-from ..constants import OSM_CACHE_DIR
+from .utils import create_bbox
# silence the overpass logger
@@ -41,7 +40,7 @@ class ToiletsManager:
self.location = location
# Setup the caching in the Overpass class.
- self.overpass = Overpass(caching_strategy='XML', cache_dir=OSM_CACHE_DIR)
+ self.overpass = Overpass()
def generate_toilet_list(self) -> list[Toilets] :
@@ -53,73 +52,71 @@ class ToiletsManager:
list[Toilets]: A list of `Toilets` objects containing detailed information
about the toilets found around the given coordinates.
"""
- bbox = tuple((self.radius, self.location[0], self.location[1]))
+ bbox = create_bbox(self.location, self.radius)
osm_types = ['node', 'way', 'relation']
toilets_list = []
- query = self.overpass.build_query(
- area = bbox,
- osm_types = osm_types,
- selector = '"amenity"="toilets"',
- out = 'ids center tags'
- )
- self.logger.debug(f"Query: {query}")
-
+ query = Overpass.build_query(
+ bbox = bbox,
+ osm_types = osm_types,
+ selector = '"amenity"="toilets"',
+ out = 'ids center tags'
+ )
try:
- result = self.overpass.send_query(query)
+ result = self.overpass.fetch_data_from_api(query_str=query)
except Exception as e:
self.logger.error(f"Error fetching landmarks: {e}")
return None
- toilets_list = self.xml_to_toilets(result)
+ toilets_list = self.to_toilets(result)
return toilets_list
- def xml_to_toilets(self, root: ET.Element) -> list[Toilets]:
+ def to_toilets(self, elements: list) -> list[Toilets]:
"""
Parse the Overpass API result and extract landmarks.
- This method processes the XML root element returned by the Overpass API and
+ This method processes the JSON elements returned by the Overpass API and
extracts landmarks of types 'node', 'way', and 'relation'. It retrieves
relevant information such as name, coordinates, and tags, and converts them
into Landmark objects.
Args:
- root (ET.Element): The root element of the XML response from Overpass API.
+ list (osm elements): The root element of the JSON response from Overpass API.
elem_type (str): The type of landmark (e.g., node, way, relation).
Returns:
- list[Landmark]: A list of Landmark objects extracted from the XML data.
+ list[Landmark]: A list of Landmark objects extracted from the JSON data.
"""
- if root is None :
+ if elements is None :
return []
toilets_list = []
- for osm_type in ['node', 'way', 'relation'] :
- for elem in root.findall(osm_type):
- # Get coordinates and append them to the points list
- _, coords = get_base_info(elem, osm_type)
- if coords is None :
- continue
+ for elem in elements:
+ osm_type = elem.get('type')
+ # Get coordinates and append them to the points list
+ _, coords = get_base_info(elem, osm_type)
+ if coords is None :
+ continue
- toilets = Toilets(location=coords)
+ toilets = Toilets(location=coords)
- # Extract tags as a dictionary
- tags = {tag.get('k'): tag.get('v') for tag in elem.findall('tag')}
+ # Extract tags as a dictionary
+ tags = elem.get('tags')
- if 'wheelchair' in tags.keys() and tags['wheelchair'] == 'yes':
- toilets.wheelchair = True
+ if 'wheelchair' in tags.keys() and tags['wheelchair'] == 'yes':
+ toilets.wheelchair = True
- if 'changing_table' in tags.keys() and tags['changing_table'] == 'yes':
- toilets.changing_table = True
+ if 'changing_table' in tags.keys() and tags['changing_table'] == 'yes':
+ toilets.changing_table = True
- if 'fee' in tags.keys() and tags['fee'] == 'yes':
- toilets.fee = True
+ if 'fee' in tags.keys() and tags['fee'] == 'yes':
+ toilets.fee = True
- if 'opening_hours' in tags.keys() :
- toilets.opening_hours = tags['opening_hours']
+ if 'opening_hours' in tags.keys() :
+ toilets.opening_hours = tags['opening_hours']
- toilets_list.append(toilets)
+ toilets_list.append(toilets)
return toilets_list
diff --git a/backend/src/utils/utils.py b/backend/src/utils/utils.py
new file mode 100644
index 0000000..23e9b52
--- /dev/null
+++ b/backend/src/utils/utils.py
@@ -0,0 +1,27 @@
+"""Various helper functions"""
+import math as m
+
+def create_bbox(coords: tuple[float, float], radius: int):
+ """
+ Create a bounding box around the given coordinates.
+
+ Args:
+ coords (tuple[float, float]): The latitude and longitude of the center of the bounding box.
+ radius (int): The half-side length of the bounding box in meters.
+
+ Returns:
+ tuple[float, float, float, float]: The minimum latitude, minimum longitude, maximum latitude, and maximum longitude
+ defining the bounding box.
+ """
+ # Earth's radius in meters
+ R = 6378137
+ lat, lon = coords
+ d_lat = radius / R
+ d_lon = radius / (R * m.cos(m.pi * lat / 180))
+
+ lat_min = lat - d_lat * 180 / m.pi
+ lat_max = lat + d_lat * 180 / m.pi
+ lon_min = lon - d_lon * 180 / m.pi
+ lon_max = lon + d_lon * 180 / m.pi
+
+ return (lat_min, lon_min, lat_max, lon_max)
\ No newline at end of file