Compare commits
19 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| bf8b64aacf | |||
| 44cd983fb8 | |||
| 89c95063dd | |||
| e41d3f5e3a | |||
| f5cedbc5a0 | |||
| 88dc5dd323 | |||
| c6bb0cddb7 | |||
| 9ccf68d983 | |||
| 132aa5a19b | |||
| 19b0c37a97 | |||
| ecdef605a7 | |||
| e2a918112b | |||
| 96b0718081 | |||
| d9e5d9dac6 | |||
| b0f9d31ee2 | |||
| 54bc9028ad | |||
| 37926e68ec | |||
| e2d3d29956 | |||
| 6921ab57f8 |
@@ -15,18 +15,18 @@ jobs:
|
||||
|
||||
- uses: https://gitea.com/actions/checkout@v4
|
||||
|
||||
- name: Install dependencies
|
||||
- name: Install pylint
|
||||
run: |
|
||||
apt-get update && apt-get install -y python3 python3-pip
|
||||
pip install pipenv
|
||||
pip install pylint
|
||||
|
||||
- name: Install packages
|
||||
run: |
|
||||
ls -la
|
||||
# only install dev-packages
|
||||
pipenv install --categories=dev-packages
|
||||
working-directory: backend
|
||||
# - name: Install packages
|
||||
# run: |
|
||||
# ls -la
|
||||
# # only install dev-packages
|
||||
# uv sync
|
||||
# working-directory: backend
|
||||
|
||||
- name: Run linter
|
||||
run: pipenv run pylint src --fail-under=9
|
||||
run: pylint src --fail-under=9
|
||||
working-directory: backend
|
||||
|
||||
@@ -18,17 +18,17 @@ jobs:
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
apt-get update && apt-get install -y python3 python3-pip
|
||||
pip install pipenv
|
||||
pip install uv
|
||||
|
||||
- name: Install packages
|
||||
run: |
|
||||
ls -la
|
||||
# install all packages, including dev-packages
|
||||
pipenv install --dev
|
||||
uv sync
|
||||
working-directory: backend
|
||||
|
||||
- name: Run Tests
|
||||
run: pipenv run pytest src --html=report.html --self-contained-html --log-cli-level=DEBUG
|
||||
run: uv run pytest src --html=report.html --self-contained-html --log-cli-level=DEBUG
|
||||
working-directory: backend
|
||||
|
||||
- name: Upload HTML report
|
||||
|
||||
3
backend/.gitignore
vendored
3
backend/.gitignore
vendored
@@ -12,6 +12,9 @@ __pycache__/
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Pytest html reports
|
||||
*.html
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
|
||||
1
backend/.python-version
Normal file
1
backend/.python-version
Normal file
@@ -0,0 +1 @@
|
||||
3.12.9
|
||||
@@ -1,11 +1,29 @@
|
||||
FROM python:3.11-slim
|
||||
FROM python:3.12-slim-bookworm
|
||||
|
||||
# The installer requires curl (and certificates) to download the release archive
|
||||
RUN apt-get update && apt-get install -y --no-install-recommends curl ca-certificates
|
||||
|
||||
# Download the latest installer
|
||||
ADD https://astral.sh/uv/install.sh /uv-installer.sh
|
||||
|
||||
# Run the installer then remove it
|
||||
RUN sh /uv-installer.sh && rm /uv-installer.sh
|
||||
|
||||
# Ensure the installed binary is on the `PATH`
|
||||
ENV PATH="/root/.local/bin/:$PATH"
|
||||
|
||||
# Set the working directory
|
||||
WORKDIR /app
|
||||
COPY Pipfile Pipfile.lock .
|
||||
|
||||
RUN pip install pipenv
|
||||
RUN pipenv install --deploy --system
|
||||
# Copy uv files
|
||||
COPY pyproject.toml pyproject.toml
|
||||
COPY uv.lock uv.lock
|
||||
COPY .python-version .python-version
|
||||
|
||||
# Sync the venv
|
||||
RUN uv sync --frozen --no-cache --no-dev
|
||||
|
||||
# Copy application files
|
||||
COPY src src
|
||||
|
||||
EXPOSE 8000
|
||||
@@ -17,4 +35,4 @@ ENV MEMCACHED_HOST_PATH=none
|
||||
ENV LOKI_URL=none
|
||||
|
||||
# explicitly use a string instead of an argument list to force a shell and variable expansion
|
||||
CMD fastapi run src/main.py --port 8000 --workers $NUM_WORKERS
|
||||
CMD uv run fastapi run src/main.py --port 8000 --workers $NUM_WORKERS
|
||||
|
||||
@@ -1,27 +0,0 @@
|
||||
[[source]]
|
||||
url = "https://pypi.org/simple"
|
||||
verify_ssl = true
|
||||
name = "pypi"
|
||||
|
||||
[dev-packages]
|
||||
pylint = "*"
|
||||
pytest = "*"
|
||||
tomli = "*"
|
||||
httpx = "*"
|
||||
exceptiongroup = "*"
|
||||
pytest-html = "*"
|
||||
typing-extensions = "*"
|
||||
dill = "*"
|
||||
|
||||
[packages]
|
||||
numpy = "*"
|
||||
fastapi = "*"
|
||||
pydantic = "*"
|
||||
shapely = "*"
|
||||
pymemcache = "*"
|
||||
fastapi-cli = "*"
|
||||
scikit-learn = "*"
|
||||
loki-logger-handler = "*"
|
||||
pulp = "*"
|
||||
scipy = "*"
|
||||
requests = "*"
|
||||
1246
backend/Pipfile.lock
generated
1246
backend/Pipfile.lock
generated
File diff suppressed because it is too large
Load Diff
@@ -6,31 +6,31 @@ This repository contains the backend code for the application. It utilizes **Fas
|
||||
|
||||
### Directory Structure
|
||||
- The code for the Python application is located in the `src` directory.
|
||||
- Package management is handled with **pipenv**, and the dependencies are listed in the `Pipfile`.
|
||||
- Package management is handled with **uv**, and the dependencies are listed in the `pyproject.toml` file.
|
||||
- Since the application is designed to be deployed in a container, the `Dockerfile` is provided to build the image.
|
||||
|
||||
### Setting Up the Development Environment
|
||||
|
||||
To set up your development environment using **pipenv**, follow these steps:
|
||||
To set up your development environment using **uv**, follow these steps:
|
||||
|
||||
1. Install `pipenv` by running:
|
||||
1. Make sure you find yourself in the `backend` directory:
|
||||
```bash
|
||||
sudo apt install pipenv
|
||||
cd backend
|
||||
```
|
||||
|
||||
2. Create and activate a virtual environment:
|
||||
1. Install `uv` by running:
|
||||
```bash
|
||||
pipenv shell
|
||||
curl -LsSf https://astral.sh/uv/install.sh | sh
|
||||
```
|
||||
|
||||
3. Install the dependencies listed in the `Pipfile`:
|
||||
3. Install the dependencies listed in `pyproject.toml` and create the virtual environment at the same time:
|
||||
```bash
|
||||
pipenv install
|
||||
uv sync
|
||||
```
|
||||
|
||||
4. The virtual environment will be created under:
|
||||
```bash
|
||||
~/.local/share/virtualenvs/...
|
||||
backend/.venv/...
|
||||
```
|
||||
|
||||
### Deployment
|
||||
|
||||
@@ -1,363 +0,0 @@
|
||||
[
|
||||
{
|
||||
"name": "Chinatown",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7554934,
|
||||
4.8444852
|
||||
],
|
||||
"osm_type": "way",
|
||||
"osm_id": 996515596,
|
||||
"attractiveness": 129,
|
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"n_tags": 0,
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"image_url": null,
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"website_url": null,
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"wiki_url": null,
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"keywords": {},
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"description": null,
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"duration": 30,
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"name_en": null,
|
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"uuid": "285d159c-68ee-4b37-8d71-f27ee3d38b02",
|
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"must_do": false,
|
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"must_avoid": false,
|
||||
"is_secondary": false,
|
||||
"time_to_reach_next": 0,
|
||||
"next_uuid": null,
|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Galeries Lafayette",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7627107,
|
||||
4.8556833
|
||||
],
|
||||
"osm_type": "way",
|
||||
"osm_id": 1069872743,
|
||||
"attractiveness": 197,
|
||||
"n_tags": 11,
|
||||
"image_url": null,
|
||||
"website_url": "http://www.galerieslafayette.com/",
|
||||
"wiki_url": null,
|
||||
"keywords": null,
|
||||
"description": null,
|
||||
"duration": 30,
|
||||
"name_en": null,
|
||||
"uuid": "28f1bc30-10d3-4944-8861-0ed9abca012d",
|
||||
"must_do": false,
|
||||
"must_avoid": false,
|
||||
"is_secondary": false,
|
||||
"time_to_reach_next": 0,
|
||||
"next_uuid": null,
|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Muji",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7615971,
|
||||
4.8543781
|
||||
],
|
||||
"osm_type": "way",
|
||||
"osm_id": 1044165817,
|
||||
"attractiveness": 259,
|
||||
"n_tags": 14,
|
||||
"image_url": null,
|
||||
"website_url": "https://www.muji.com/fr/",
|
||||
"wiki_url": null,
|
||||
"keywords": null,
|
||||
"description": null,
|
||||
"duration": 30,
|
||||
"name_en": "Muji",
|
||||
"uuid": "957f86a5-6c00-41a2-815d-d6f739052be4",
|
||||
"must_do": false,
|
||||
"must_avoid": false,
|
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"is_secondary": false,
|
||||
"time_to_reach_next": 0,
|
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"next_uuid": null,
|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "HEMA",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7619133,
|
||||
4.8565239
|
||||
],
|
||||
"osm_type": "way",
|
||||
"osm_id": 1069872750,
|
||||
"attractiveness": 156,
|
||||
"n_tags": 9,
|
||||
"image_url": null,
|
||||
"website_url": "https://fr.westfield.com/lapartdieu/store/HEMA/www.hema.fr",
|
||||
"wiki_url": null,
|
||||
"keywords": null,
|
||||
"description": null,
|
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"duration": 30,
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"uuid": "8dae9d3e-e4c4-4e80-941d-0b106e22c85b",
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"must_do": false,
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|
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"is_secondary": false,
|
||||
"time_to_reach_next": 0,
|
||||
"next_uuid": null,
|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Cordeliers",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7622752,
|
||||
4.8337998
|
||||
],
|
||||
"osm_type": "node",
|
||||
"osm_id": 5545183519,
|
||||
"attractiveness": 813,
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"n_tags": 0,
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"image_url": null,
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"must_do": false,
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"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Halles de Lyon Paul Bocuse",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7628282,
|
||||
4.8505601
|
||||
],
|
||||
"osm_type": "relation",
|
||||
"osm_id": 971529,
|
||||
"attractiveness": 272,
|
||||
"n_tags": 12,
|
||||
"image_url": null,
|
||||
"website_url": "https://www.halles-de-lyon-paulbocuse.com/",
|
||||
"wiki_url": "fr:Halles de Lyon-Paul Bocuse",
|
||||
"keywords": {
|
||||
"importance": "national",
|
||||
"height": null,
|
||||
"place_type": "marketplace",
|
||||
"date": null
|
||||
},
|
||||
"description": "Halles de Lyon Paul Bocuse is a marketplace of national importance.",
|
||||
"duration": 30,
|
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|
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|
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|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Grand Bazar",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7632141,
|
||||
4.8361975
|
||||
],
|
||||
"osm_type": "way",
|
||||
"osm_id": 82399951,
|
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|
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|
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"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Shopping Area",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7673452,
|
||||
4.8438683
|
||||
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|
||||
"osm_type": "node",
|
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|
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"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Cour Oxyg\u00e8ne",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
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|
||||
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|
||||
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|
||||
"osm_type": "way",
|
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|
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|
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|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "P\u00f4le de Commerces et de Loisirs Confluence",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
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|
||||
4.8171031
|
||||
],
|
||||
"osm_type": "way",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Grand H\u00f4tel-Dieu",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7586955,
|
||||
4.8364597
|
||||
],
|
||||
"osm_type": "relation",
|
||||
"osm_id": 300128,
|
||||
"attractiveness": 546,
|
||||
"n_tags": 22,
|
||||
"image_url": null,
|
||||
"website_url": "https://grand-hotel-dieu.com",
|
||||
"wiki_url": "fr:H\u00f4tel-Dieu de Lyon",
|
||||
"keywords": {
|
||||
"importance": "international",
|
||||
"height": null,
|
||||
"place_type": "building",
|
||||
"date": "C17"
|
||||
},
|
||||
"description": "Grand H\u00f4tel-Dieu is an internationally famous building. It was constructed in C17.",
|
||||
"duration": 30,
|
||||
"name_en": null,
|
||||
"uuid": "a91265a8-ffbd-44f7-a7ab-3ff75f08fbab",
|
||||
"must_do": false,
|
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|
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"is_secondary": false,
|
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"time_to_reach_next": 0,
|
||||
"next_uuid": null,
|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Westfield La Part-Dieu",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.761331,
|
||||
4.855676
|
||||
],
|
||||
"osm_type": "way",
|
||||
"osm_id": 62338376,
|
||||
"attractiveness": 546,
|
||||
"n_tags": 22,
|
||||
"image_url": null,
|
||||
"website_url": "https://fr.westfield.com/lapartdieu",
|
||||
"wiki_url": "fr:La Part-Dieu (centre commercial)",
|
||||
"keywords": null,
|
||||
"description": null,
|
||||
"duration": 30,
|
||||
"name_en": null,
|
||||
"uuid": "7d60316f-d689-4fcf-be68-ffc09353b826",
|
||||
"must_do": false,
|
||||
"must_avoid": false,
|
||||
"is_secondary": false,
|
||||
"time_to_reach_next": 0,
|
||||
"next_uuid": null,
|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
},
|
||||
{
|
||||
"name": "Ainay",
|
||||
"type": "shopping",
|
||||
"location": [
|
||||
45.7553105,
|
||||
4.8312084
|
||||
],
|
||||
"osm_type": "node",
|
||||
"osm_id": 5545126047,
|
||||
"attractiveness": 132,
|
||||
"n_tags": 0,
|
||||
"image_url": null,
|
||||
"website_url": null,
|
||||
"wiki_url": null,
|
||||
"keywords": {},
|
||||
"description": null,
|
||||
"duration": 30,
|
||||
"name_en": null,
|
||||
"uuid": "ad214f3d-a4b9-4078-876a-446caa7ab01c",
|
||||
"must_do": false,
|
||||
"must_avoid": false,
|
||||
"is_secondary": false,
|
||||
"time_to_reach_next": 0,
|
||||
"next_uuid": null,
|
||||
"is_viewpoint": false,
|
||||
"is_place_of_worship": false
|
||||
}
|
||||
]
|
||||
6
backend/main.py
Normal file
6
backend/main.py
Normal file
@@ -0,0 +1,6 @@
|
||||
def main():
|
||||
print("Hello from backend!")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
57
backend/pyproject.toml
Normal file
57
backend/pyproject.toml
Normal file
@@ -0,0 +1,57 @@
|
||||
[project]
|
||||
name = "backend"
|
||||
version = "0.1.0"
|
||||
description = "Add your description here"
|
||||
readme = "README.md"
|
||||
requires-python = ">=3.12"
|
||||
dependencies = [
|
||||
"annotated-types==0.7.0 ; python_full_version >= '3.8'",
|
||||
"anyio==4.8.0 ; python_full_version >= '3.9'",
|
||||
"certifi==2024.12.14 ; python_full_version >= '3.6'",
|
||||
"charset-normalizer==3.4.1 ; python_full_version >= '3.7'",
|
||||
"click==8.1.8 ; python_full_version >= '3.7'",
|
||||
"fastapi==0.115.7 ; python_full_version >= '3.8'",
|
||||
"fastapi-cli==0.0.7 ; python_full_version >= '3.8'",
|
||||
"h11==0.14.0 ; python_full_version >= '3.7'",
|
||||
"httptools==0.6.4",
|
||||
"idna==3.10 ; python_full_version >= '3.6'",
|
||||
"joblib==1.4.2 ; python_full_version >= '3.8'",
|
||||
"loki-logger-handler==1.1.0 ; python_full_version >= '2.7'",
|
||||
"markdown-it-py==3.0.0 ; python_full_version >= '3.8'",
|
||||
"mdurl==0.1.2 ; python_full_version >= '3.7'",
|
||||
"numpy==2.2.2 ; python_full_version >= '3.10'",
|
||||
"paypalrestsdk>=1.13.3",
|
||||
"pulp==2.9.0 ; python_full_version >= '3.7'",
|
||||
"pydantic==2.10.6 ; python_full_version >= '3.8'",
|
||||
"pydantic-core==2.27.2 ; python_full_version >= '3.8'",
|
||||
"pygments==2.19.1 ; python_full_version >= '3.8'",
|
||||
"pymemcache==4.0.0 ; python_full_version >= '3.7'",
|
||||
"python-dotenv==1.0.1",
|
||||
"pyyaml==6.0.2",
|
||||
"requests==2.32.3 ; python_full_version >= '3.8'",
|
||||
"rich==13.9.4 ; python_full_version >= '3.8'",
|
||||
"rich-toolkit==0.13.2 ; python_full_version >= '3.8'",
|
||||
"scikit-learn==1.6.1 ; python_full_version >= '3.9'",
|
||||
"scipy==1.15.1 ; python_full_version >= '3.10'",
|
||||
"shapely==2.0.6 ; python_full_version >= '3.7'",
|
||||
"shellingham==1.5.4 ; python_full_version >= '3.7'",
|
||||
"sniffio==1.3.1 ; python_full_version >= '3.7'",
|
||||
"starlette==0.45.3 ; python_full_version >= '3.9'",
|
||||
"supabase>=2.16.0",
|
||||
"threadpoolctl==3.5.0 ; python_full_version >= '3.8'",
|
||||
"typer==0.15.1 ; python_full_version >= '3.7'",
|
||||
"typing-extensions==4.12.2 ; python_full_version >= '3.8'",
|
||||
"urllib3==2.3.0 ; python_full_version >= '3.9'",
|
||||
"uvicorn[standard]==0.34.0 ; python_full_version >= '3.9'",
|
||||
"uvloop==0.21.0",
|
||||
"watchfiles==1.0.4",
|
||||
"websockets==14.2",
|
||||
]
|
||||
|
||||
[dependency-groups]
|
||||
dev = [
|
||||
"httpx>=0.28.1",
|
||||
"ipykernel>=6.30.0",
|
||||
"pytest>=8.4.1",
|
||||
"pytest-html>=4.1.1",
|
||||
]
|
||||
1094
backend/report.html
1094
backend/report.html
File diff suppressed because one or more lines are too long
@@ -28,6 +28,11 @@ This folder defines the commonly used data structures used within the project. T
|
||||
### src/tests
|
||||
This folder contains unit tests and test cases for the application's various modules. It is used to ensure the correctness and stability of the code.
|
||||
|
||||
Run the unit tests with the following command:
|
||||
```bash
|
||||
uv run pytest src --log-cli-level=DEBUG --html=report.html --self-contained-html
|
||||
```
|
||||
|
||||
### src/utils
|
||||
The `utils` folder contains utility classes and functions that provide core functionality for the application. The main component in this folder is the `LandmarkManager`, which is central to the process of fetching and organizing landmarks.
|
||||
|
||||
|
||||
@@ -146,7 +146,7 @@ class ClusterManager:
|
||||
self.valid = False
|
||||
|
||||
else :
|
||||
self.logger.debug(f"Detected 0 {cluster_type} clusters.")
|
||||
self.logger.debug(f"Found 0 {cluster_type} clusters.")
|
||||
self.valid = False
|
||||
|
||||
|
||||
|
||||
@@ -4,7 +4,6 @@ import yaml
|
||||
|
||||
from ..structs.preferences import Preferences
|
||||
from ..structs.landmark import Landmark
|
||||
from ..utils.take_most_important import take_most_important
|
||||
from .cluster_manager import ClusterManager
|
||||
from ..overpass.overpass import Overpass, get_base_info
|
||||
from ..utils.bbox import create_bbox
|
||||
@@ -23,7 +22,7 @@ class LandmarkManager:
|
||||
church_coeff: float # coeff to adjsut score of churches
|
||||
nature_coeff: float # coeff to adjust score of parks
|
||||
overall_coeff: float # coeff to adjust weight of tags
|
||||
n_important: int # number of important landmarks to consider
|
||||
# n_important: int # number of important landmarks to consider
|
||||
|
||||
|
||||
def __init__(self) -> None:
|
||||
@@ -42,7 +41,7 @@ class LandmarkManager:
|
||||
self.wikipedia_bonus = parameters['wikipedia_bonus']
|
||||
self.viewpoint_bonus = parameters['viewpoint_bonus']
|
||||
self.pay_bonus = parameters['pay_bonus']
|
||||
self.n_important = parameters['N_important']
|
||||
# self.n_important = parameters['N_important']
|
||||
|
||||
with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
|
||||
parameters = yaml.safe_load(f)
|
||||
@@ -55,7 +54,12 @@ class LandmarkManager:
|
||||
self.logger.info('LandmakManager successfully initialized.')
|
||||
|
||||
|
||||
def generate_landmarks_list(self, center_coordinates: tuple[float, float], preferences: Preferences) -> tuple[list[Landmark], list[Landmark]]:
|
||||
def generate_landmarks_list(
|
||||
self,
|
||||
center_coordinates: tuple[float, float],
|
||||
preferences: Preferences,
|
||||
allow_clusters: bool = True
|
||||
) -> list[Landmark] :
|
||||
"""
|
||||
Generate and prioritize a list of landmarks based on user preferences.
|
||||
|
||||
@@ -63,16 +67,17 @@ class LandmarkManager:
|
||||
and current location. It scores and corrects these landmarks, removes duplicates, and then selects the most important
|
||||
landmarks based on a predefined criterion.
|
||||
|
||||
Args:
|
||||
center_coordinates (tuple[float, float]): The latitude and longitude of the center location around which to search.
|
||||
preferences (Preferences): The user's preference settings that influence the landmark selection.
|
||||
Parameters :
|
||||
center_coordinates (tuple[float, float]): The latitude and longitude of the center location around which to search.
|
||||
preferences (Preferences): The user's preference settings that influence the landmark selection.
|
||||
allow_clusters (bool, optional) : If set to False, no clusters will be fetched. Mainly used for the option to fetch landmarks nearby.
|
||||
|
||||
Returns:
|
||||
tuple[list[Landmark], list[Landmark]]:
|
||||
- A list of all existing landmarks.
|
||||
- A list of the most important landmarks based on the user's preferences.
|
||||
"""
|
||||
self.logger.debug('Starting to fetch landmarks...')
|
||||
self.logger.info(f'Starting to fetch landmarks around {center_coordinates}...')
|
||||
max_walk_dist = int((preferences.max_time_minute/2)/60*self.walking_speed*1000/self.detour_factor)
|
||||
radius = min(max_walk_dist, int(self.max_bbox_side/2))
|
||||
|
||||
@@ -89,10 +94,11 @@ class LandmarkManager:
|
||||
all_landmarks.update(current_landmarks)
|
||||
self.logger.info(f'Found {len(current_landmarks)} sightseeing landmarks')
|
||||
|
||||
if allow_clusters :
|
||||
# special pipeline for historic neighborhoods
|
||||
neighborhood_manager = ClusterManager(bbox, 'sightseeing')
|
||||
historic_clusters = neighborhood_manager.generate_clusters()
|
||||
all_landmarks.update(historic_clusters)
|
||||
neighborhood_manager = ClusterManager(bbox, 'sightseeing')
|
||||
historic_clusters = neighborhood_manager.generate_clusters()
|
||||
all_landmarks.update(historic_clusters)
|
||||
|
||||
# list for nature
|
||||
if preferences.nature.score != 0:
|
||||
@@ -113,16 +119,19 @@ class LandmarkManager:
|
||||
landmark.duration = 30
|
||||
all_landmarks.update(current_landmarks)
|
||||
|
||||
# special pipeline for shopping malls
|
||||
shopping_manager = ClusterManager(bbox, 'shopping')
|
||||
shopping_clusters = shopping_manager.generate_clusters()
|
||||
all_landmarks.update(shopping_clusters)
|
||||
if allow_clusters :
|
||||
# special pipeline for shopping malls
|
||||
shopping_manager = ClusterManager(bbox, 'shopping')
|
||||
shopping_clusters = shopping_manager.generate_clusters()
|
||||
all_landmarks.update(shopping_clusters)
|
||||
|
||||
|
||||
landmarks_constrained = take_most_important(all_landmarks, self.n_important)
|
||||
# DETAILS HERE
|
||||
# self.logger.info(f'All landmarks generated : {len(all_landmarks)} landmarks around {center_coordinates}, and constrained to {len(landmarks_constrained)} most important ones.')
|
||||
self.logger.info(f'Found {len(all_landmarks)} landmarks in total.')
|
||||
|
||||
return all_landmarks, landmarks_constrained
|
||||
return sorted(all_landmarks, key=lambda x: x.attractiveness, reverse=True)
|
||||
|
||||
|
||||
def set_landmark_score(self, landmark: Landmark, landmarktype: str, preference_level: int) :
|
||||
"""
|
||||
@@ -236,6 +245,17 @@ class LandmarkManager:
|
||||
continue
|
||||
|
||||
tags = elem.get('tags')
|
||||
n_tags=len(tags)
|
||||
|
||||
# Skip this landmark if not suitable
|
||||
if tags.get('building:part') is not None :
|
||||
continue
|
||||
if tags.get('disused') is not None :
|
||||
continue
|
||||
if tags.get('boundary') is not None :
|
||||
continue
|
||||
if tags.get('shop') is not None and landmarktype != 'shopping' :
|
||||
continue
|
||||
|
||||
# Convert this to Landmark object
|
||||
landmark = Landmark(name=name,
|
||||
@@ -244,180 +264,36 @@ class LandmarkManager:
|
||||
osm_id=id,
|
||||
osm_type=osm_type,
|
||||
attractiveness=0,
|
||||
n_tags=len(tags))
|
||||
n_tags=n_tags)
|
||||
|
||||
# Browse through tags to add information to landmark.
|
||||
for key, value in tags.items():
|
||||
# Extract useful information for score calculation later down the road.
|
||||
landmark.image_url = tags.get('image')
|
||||
landmark.website_url = tags.get('website')
|
||||
landmark.wiki_url = tags.get('wikipedia')
|
||||
landmark.name_en = tags.get('name:en')
|
||||
|
||||
# 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 value == 'place_of_worship' :
|
||||
# Check for place of worship
|
||||
if tags.get('place_of_worship') is not None :
|
||||
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
|
||||
landmark.name_en = tags.get('place_of_worship')
|
||||
|
||||
# Set the duration. Needed for the optimization.
|
||||
if tags.get('amenity') in ['aquarium', 'planetarium'] or tags.get('tourism') in ['aquarium', 'museum', 'zoo']:
|
||||
landmark.duration = 60
|
||||
elif tags.get('tourism') == 'viewpoint' :
|
||||
landmark.is_viewpoint = True
|
||||
landmark.duration = 10
|
||||
elif tags.get('building') == 'cathedral' :
|
||||
landmark.is_place_of_worship = False
|
||||
landmark.duration = 10
|
||||
|
||||
# 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
|
||||
|
||||
landmark.description, landmark.keywords = self.description_and_keywords(tags)
|
||||
# Compute the score and add landmark to the list.
|
||||
self.set_landmark_score(landmark, landmarktype, preference_level)
|
||||
landmarks.append(landmark)
|
||||
|
||||
continue
|
||||
|
||||
|
||||
return landmarks
|
||||
|
||||
|
||||
def description_and_keywords(self, tags: dict):
|
||||
"""
|
||||
Generates a description and a set of keywords for a given landmark based on its tags.
|
||||
|
||||
Params:
|
||||
tags (dict): A dictionary containing metadata about the landmark, including its name,
|
||||
importance, height, date of construction, and visitor information.
|
||||
|
||||
Returns:
|
||||
description (str): A string description of the landmark.
|
||||
keywords (dict): A dictionary of keywords with fields such as 'importance', 'height',
|
||||
'place_type', and 'date'.
|
||||
"""
|
||||
# Extract relevant fields
|
||||
name = tags.get('name')
|
||||
importance = tags.get('importance', None)
|
||||
n_visitors = tags.get('tourism:visitors', None)
|
||||
height = tags.get('height')
|
||||
place_type = self.get_place_type(tags)
|
||||
date = self.get_date(tags)
|
||||
|
||||
if place_type is None :
|
||||
return None, None
|
||||
|
||||
# Start the description.
|
||||
if importance is None :
|
||||
if len(tags.keys()) < 5 :
|
||||
return None, None
|
||||
if len(tags.keys()) < 10 :
|
||||
description = f"{name} is a well known {place_type}."
|
||||
elif len(tags.keys()) < 17 :
|
||||
importance = 'national'
|
||||
description = f"{name} is a {place_type} of national importance."
|
||||
else :
|
||||
importance = 'international'
|
||||
description = f"{name} is an internationally famous {place_type}."
|
||||
else :
|
||||
description = f"{name} is a {place_type} of {importance} importance."
|
||||
|
||||
if height is not None and date is not None :
|
||||
description += f" This {place_type} was constructed in {date} and is ca. {height} meters high."
|
||||
elif height is not None :
|
||||
description += f" This {place_type} stands ca. {height} meters tall."
|
||||
elif date is not None:
|
||||
description += f" It was constructed in {date}."
|
||||
|
||||
# Format the visitor number
|
||||
if n_visitors is not None :
|
||||
n_visitors = int(n_visitors)
|
||||
if n_visitors < 1000000 :
|
||||
description += f" It welcomes {int(n_visitors/1000)} thousand visitors every year."
|
||||
else :
|
||||
description += f" It welcomes {round(n_visitors/1000000, 1)} million visitors every year."
|
||||
|
||||
# Set the keywords.
|
||||
keywords = {"importance": importance,
|
||||
"height": height,
|
||||
"place_type": place_type,
|
||||
"date": date}
|
||||
|
||||
return description, keywords
|
||||
|
||||
|
||||
def get_place_type(self, data):
|
||||
"""
|
||||
Determines the type of the place based on available tags such as 'amenity', 'building',
|
||||
'historic', and 'leisure'. The priority order is: 'historic' > 'building' (if not generic) >
|
||||
'amenity' > 'leisure'.
|
||||
|
||||
Params:
|
||||
data (dict): A dictionary containing metadata about the place.
|
||||
|
||||
Returns:
|
||||
place_type (str): The determined type of the place, or None if no relevant type is found.
|
||||
"""
|
||||
amenity = data.get('amenity', None)
|
||||
building = data.get('building', None)
|
||||
historic = data.get('historic', None)
|
||||
leisure = data.get('leisure')
|
||||
|
||||
if historic and historic != "yes":
|
||||
return historic
|
||||
if building and building not in ["yes", "civic", "government", "apartments", "residential", "commericial", "industrial", "retail", "religious", "public", "service"]:
|
||||
return building
|
||||
if amenity:
|
||||
return amenity
|
||||
if leisure:
|
||||
return leisure
|
||||
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def get_date(self, data):
|
||||
"""
|
||||
Extracts the most relevant date from the available tags, prioritizing 'construction_date',
|
||||
'start_date', 'year_of_construction', and 'opening_date' in that order.
|
||||
|
||||
Params:
|
||||
data (dict): A dictionary containing metadata about the place.
|
||||
|
||||
Returns:
|
||||
date (str): The most relevant date found, or None if no date is available.
|
||||
"""
|
||||
construction_date = data.get('construction_date', None)
|
||||
opening_date = data.get('opening_date', None)
|
||||
start_date = data.get('start_date', None)
|
||||
year_of_construction = data.get('year_of_construction', None)
|
||||
|
||||
# Prioritize based on availability
|
||||
if construction_date:
|
||||
return construction_date
|
||||
if start_date:
|
||||
return start_date
|
||||
if year_of_construction:
|
||||
return year_of_construction
|
||||
if opening_date:
|
||||
return opening_date
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def dict_to_selector_list(d: dict) -> list:
|
||||
"""
|
||||
Convert a dictionary of key-value pairs to a list of Overpass query strings.
|
||||
|
||||
123
backend/src/landmarks/landmarks_router.py
Normal file
123
backend/src/landmarks/landmarks_router.py
Normal file
@@ -0,0 +1,123 @@
|
||||
"""Main app for backend api"""
|
||||
import logging
|
||||
import time
|
||||
import random
|
||||
from fastapi import HTTPException, APIRouter
|
||||
|
||||
from ..structs.landmark import Landmark
|
||||
from ..structs.preferences import Preferences, Preference
|
||||
from .landmarks_manager import LandmarkManager
|
||||
|
||||
|
||||
# Setup the logger and the Landmarks Manager
|
||||
logger = logging.getLogger(__name__)
|
||||
manager = LandmarkManager()
|
||||
|
||||
|
||||
# Initialize the API router
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.post("/get/landmarks")
|
||||
def get_landmarks(
|
||||
preferences: Preferences,
|
||||
start: tuple[float, float],
|
||||
) -> list[Landmark]:
|
||||
"""
|
||||
Function that returns all available landmarks given some preferences and a start position.
|
||||
|
||||
Args:
|
||||
preferences : the preferences specified by the user as the post body
|
||||
start : the coordinates of the starting point
|
||||
Returns:
|
||||
list[Landmark] : The full list of fetched landmarks
|
||||
"""
|
||||
if preferences is None:
|
||||
raise HTTPException(status_code=406, detail="Preferences not provided or incomplete.")
|
||||
if (preferences.shopping.score == 0 and
|
||||
preferences.sightseeing.score == 0 and
|
||||
preferences.nature.score == 0) :
|
||||
raise HTTPException(status_code=406, detail="All preferences are 0.")
|
||||
if start is None:
|
||||
raise HTTPException(status_code=406, detail="Start coordinates not provided")
|
||||
if not (-90 <= start[0] <= 90 or -180 <= start[1] <= 180):
|
||||
raise HTTPException(status_code=422, detail="Start coordinates not in range")
|
||||
|
||||
logger.info(f"Requested new trip generation. Details:\n\tCoordinates: {start}\n\tTime: {preferences.max_time_minute}\n\tSightseeing: {preferences.sightseeing.score}\n\tNature: {preferences.nature.score}\n\tShopping: {preferences.shopping.score}")
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
# Generate the landmarks from the start location
|
||||
landmarks = manager.generate_landmarks_list(
|
||||
center_coordinates = start,
|
||||
preferences = preferences
|
||||
)
|
||||
|
||||
if len(landmarks) == 0 :
|
||||
raise HTTPException(status_code=500, detail="No landmarks were found.")
|
||||
|
||||
t_generate_landmarks = time.time() - start_time
|
||||
logger.info(f'Fetched {len(landmarks)} landmarks in \t: {round(t_generate_landmarks,3)} seconds')
|
||||
|
||||
return landmarks
|
||||
|
||||
|
||||
@router.post("/get-nearby/landmarks/{lat}/{lon}")
|
||||
def get_landmarks_nearby(
|
||||
lat: float,
|
||||
lon: float
|
||||
) -> list[Landmark] :
|
||||
"""
|
||||
Suggests nearby landmarks based on a given latitude and longitude.
|
||||
|
||||
This endpoint returns a curated list of up to 5 landmarks around the given geographical coordinates. It uses fixed preferences for
|
||||
sightseeing, shopping, and nature, with a maximum time constraint of 30 minutes to limit the number of landmarks returned.
|
||||
|
||||
Args:
|
||||
lat (float): Latitude of the user's current location.
|
||||
lon (float): Longitude of the user's current location.
|
||||
|
||||
Returns:
|
||||
list[Landmark]: A list of selected nearby landmarks.
|
||||
"""
|
||||
logger.info(f'Fetching landmarks nearby ({lat}, {lon}).')
|
||||
|
||||
# Define fixed preferences:
|
||||
prefs = Preferences(
|
||||
sightseeing = Preference(
|
||||
type='sightseeing',
|
||||
score=5
|
||||
),
|
||||
shopping = Preference(
|
||||
type='shopping',
|
||||
score=2
|
||||
),
|
||||
nature = Preference(
|
||||
type='nature',
|
||||
score=5
|
||||
),
|
||||
max_time_minute=30,
|
||||
detour_tolerance_minute=0,
|
||||
)
|
||||
|
||||
# Find the landmarks around the location
|
||||
landmarks_around = manager.generate_landmarks_list(
|
||||
center_coordinates = (lat, lon),
|
||||
preferences = prefs,
|
||||
allow_clusters=False,
|
||||
)
|
||||
|
||||
if len(landmarks_around) == 0 :
|
||||
raise HTTPException(status_code=500, detail="No landmarks were found.")
|
||||
|
||||
# select 8 - 12 landmarks from there
|
||||
if len(landmarks_around) > 8 :
|
||||
n_imp = random.randint(2,5)
|
||||
rest = random.randint(8 - n_imp, min(12, len(landmarks_around))-n_imp)
|
||||
|
||||
print(f'len = {len(landmarks_around)}\nn_imp = {n_imp}\nrest = {rest}')
|
||||
landmarks_around = landmarks_around[:n_imp] + random.sample(landmarks_around[n_imp:], rest)
|
||||
|
||||
logger.info(f'Found {len(landmarks_around)} landmarks to suggest nearby ({lat}, {lon}).')
|
||||
# logger.debug('Suggested landmarks :\n\t' + '\n\t'.join(f'{landmark}' for landmark in landmarks_around))
|
||||
return landmarks_around
|
||||
@@ -33,14 +33,14 @@ def configure_logging():
|
||||
# silence the chatty logs loki generates itself
|
||||
logging.getLogger('urllib3.connectionpool').setLevel(logging.WARNING)
|
||||
# no need for time since it's added by loki or can be shown in kube logs
|
||||
logging_format = '%(name)s - %(levelname)s - %(message)s'
|
||||
logging_format = '%(name)-55s - %(levelname)-7s - %(message)s'
|
||||
|
||||
else:
|
||||
# if we are in a debug (local) session, set verbose and rich logging
|
||||
from rich.logging import RichHandler
|
||||
logging_handlers = [RichHandler()]
|
||||
logging_level = logging.DEBUG if is_debug else logging.INFO
|
||||
logging_format = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
|
||||
logging_format = '%(asctime)s - %(name)-55s - %(levelname)-7s - %(message)s'
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -1,19 +1,19 @@
|
||||
"""Main app for backend api"""
|
||||
import logging
|
||||
import time
|
||||
from contextlib import asynccontextmanager
|
||||
from fastapi import FastAPI, HTTPException, BackgroundTasks
|
||||
from fastapi import FastAPI, HTTPException
|
||||
|
||||
from .logging_config import configure_logging
|
||||
from .structs.landmark import Landmark
|
||||
from .structs.preferences import Preferences
|
||||
from .structs.linked_landmarks import LinkedLandmarks
|
||||
from .structs.trip import Trip
|
||||
from .landmarks.landmarks_manager import LandmarkManager
|
||||
from .toilets.toilet_routes import router as toilets_router
|
||||
from .toilets.toilets_router import router as toilets_router
|
||||
from .optimization.optimization_router import router as optimization_router
|
||||
from .landmarks.landmarks_router import router as landmarks_router
|
||||
from .payments.payment_router import router as payment_router
|
||||
from .optimization.optimizer import Optimizer
|
||||
from .optimization.refiner import Refiner
|
||||
from .overpass.overpass import fill_cache
|
||||
from .cache import client as cache_client
|
||||
|
||||
|
||||
@@ -37,115 +37,24 @@ app = FastAPI(lifespan=lifespan)
|
||||
|
||||
|
||||
|
||||
# Fetches the global list of landmarks given preferences and start/end coordinates. Two routes
|
||||
# Call with "/get/landmarks/" for main entry point of the trip generation pipeline.
|
||||
# Call with "/get-nearby/landmarks/" for the NEARBY feature.
|
||||
app.include_router(landmarks_router)
|
||||
|
||||
|
||||
# Optimizes the trip given preferences. Second step in the main trip generation pipeline.
|
||||
# Call with "/optimize/trip"
|
||||
app.include_router(optimization_router)
|
||||
|
||||
|
||||
# Fetches toilets near given coordinates.
|
||||
# Call with "/get/toilets" for fetching toilets around coordinates.
|
||||
app.include_router(toilets_router)
|
||||
|
||||
|
||||
@app.post("/trip/new")
|
||||
def new_trip(preferences: Preferences,
|
||||
start: tuple[float, float],
|
||||
end: tuple[float, float] | None = None,
|
||||
background_tasks: BackgroundTasks = None) -> Trip:
|
||||
"""
|
||||
Main function to call the optimizer.
|
||||
|
||||
Args:
|
||||
preferences : the preferences specified by the user as the post body
|
||||
start : the coordinates of the starting point
|
||||
end : the coordinates of the finishing point
|
||||
Returns:
|
||||
(uuid) : The uuid of the first landmark in the optimized route
|
||||
"""
|
||||
if preferences is None:
|
||||
raise HTTPException(status_code=406, detail="Preferences not provided or incomplete.")
|
||||
if (preferences.shopping.score == 0 and
|
||||
preferences.sightseeing.score == 0 and
|
||||
preferences.nature.score == 0) :
|
||||
raise HTTPException(status_code=406, detail="All preferences are 0.")
|
||||
if start is None:
|
||||
raise HTTPException(status_code=406, detail="Start coordinates not provided")
|
||||
if not (-90 <= start[0] <= 90 or -180 <= start[1] <= 180):
|
||||
raise HTTPException(status_code=422, detail="Start coordinates not in range")
|
||||
if end is None:
|
||||
end = start
|
||||
logger.info("No end coordinates provided. Using start=end.")
|
||||
|
||||
logger.info(f"Requested new trip generation. Details:\n\tCoordinates: {start}\n\tTime: {preferences.max_time_minute}\n\tSightseeing: {preferences.sightseeing.score}\n\tNature: {preferences.nature.score}\n\tShopping: {preferences.shopping.score}")
|
||||
|
||||
start_landmark = Landmark(name='start',
|
||||
type='start',
|
||||
location=(start[0], start[1]),
|
||||
osm_type='start',
|
||||
osm_id=0,
|
||||
attractiveness=0,
|
||||
duration=0,
|
||||
must_do=True,
|
||||
n_tags = 0)
|
||||
|
||||
end_landmark = Landmark(name='finish',
|
||||
type='finish',
|
||||
location=(end[0], end[1]),
|
||||
osm_type='end',
|
||||
osm_id=0,
|
||||
attractiveness=0,
|
||||
duration=0,
|
||||
must_do=True,
|
||||
n_tags=0)
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
# Generate the landmarks from the start location
|
||||
landmarks, landmarks_short = manager.generate_landmarks_list(
|
||||
center_coordinates = start,
|
||||
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)
|
||||
|
||||
t_generate_landmarks = time.time() - start_time
|
||||
logger.info(f'Fetched {len(landmarks)} landmarks in \t: {round(t_generate_landmarks,3)} seconds')
|
||||
start_time = time.time()
|
||||
|
||||
# First stage optimization
|
||||
try:
|
||||
base_tour = optimizer.solve_optimization(preferences.max_time_minute, landmarks_short)
|
||||
except Exception as exc:
|
||||
logger.error(f"Trip generation failed: {str(exc)}")
|
||||
raise HTTPException(status_code=500, detail=f"Optimization failed: {str(exc)}") from exc
|
||||
|
||||
t_first_stage = time.time() - start_time
|
||||
start_time = time.time()
|
||||
|
||||
# Second stage optimization
|
||||
# TODO : only if necessary (not enough landmarks for ex.)
|
||||
try :
|
||||
refined_tour = refiner.refine_optimization(landmarks, base_tour,
|
||||
preferences.max_time_minute,
|
||||
preferences.detour_tolerance_minute)
|
||||
except Exception as exc :
|
||||
logger.warning(f"Refiner failed. Proceeding with base trip {str(exc)}")
|
||||
refined_tour = base_tour
|
||||
|
||||
t_second_stage = time.time() - start_time
|
||||
|
||||
logger.debug(f'First stage optimization\t: {round(t_first_stage,3)} seconds')
|
||||
logger.debug(f'Second stage optimization\t: {round(t_second_stage,3)} seconds')
|
||||
logger.info(f'Total computation time\t: {round(t_first_stage + t_second_stage,3)} seconds')
|
||||
linked_tour = LinkedLandmarks(refined_tour)
|
||||
|
||||
# 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.')
|
||||
logger.debug('Detailed trip :\n\t' + '\n\t'.join(f'{landmark}' for landmark in refined_tour))
|
||||
|
||||
background_tasks.add_task(fill_cache)
|
||||
|
||||
return trip
|
||||
|
||||
# Include the payment router for interacting with paypal sdk.
|
||||
# See src/payment/payment_router.py for more information on how to call.
|
||||
app.include_router(payment_router)
|
||||
|
||||
#### For already existing trips/landmarks
|
||||
@app.get("/trip/{trip_uuid}")
|
||||
@@ -224,3 +133,4 @@ def update_trip_time(trip_uuid: str, removed_landmark_uuid: str) -> Trip:
|
||||
trip = Trip.from_linked_landmarks(linked_tour, cache_client)
|
||||
|
||||
return trip
|
||||
|
||||
|
||||
164
backend/src/optimization/optimization_router.py
Normal file
164
backend/src/optimization/optimization_router.py
Normal file
@@ -0,0 +1,164 @@
|
||||
"""API entry point for the trip optimization."""
|
||||
|
||||
import logging
|
||||
import time
|
||||
import yaml
|
||||
from fastapi import HTTPException, APIRouter, BackgroundTasks, Body
|
||||
|
||||
from .optimizer import Optimizer
|
||||
from .refiner import Refiner
|
||||
from ..supabase.supabase import SupabaseClient
|
||||
from ..structs.landmark import Landmark
|
||||
from ..structs.preferences import Preferences
|
||||
from ..structs.linked_landmarks import LinkedLandmarks
|
||||
from ..structs.trip import Trip
|
||||
from ..overpass.overpass import fill_cache
|
||||
from ..cache import client as cache_client
|
||||
from ..constants import OPTIMIZER_PARAMETERS_PATH
|
||||
|
||||
|
||||
# Setup the Logger, Optimizer and Refiner
|
||||
logger = logging.getLogger(__name__)
|
||||
optimizer = Optimizer()
|
||||
refiner = Refiner(optimizer=optimizer)
|
||||
supabase = SupabaseClient()
|
||||
|
||||
|
||||
# Initialize the API router
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.post("/optimize/trip")
|
||||
def optimize_trip(
|
||||
user_id: str = Body(...),
|
||||
preferences: Preferences = Body(...),
|
||||
landmarks: list[Landmark] = Body(...),
|
||||
start: tuple[float, float] = Body(...),
|
||||
end: tuple[float, float] | None = Body(None),
|
||||
background_tasks: BackgroundTasks = None
|
||||
) -> Trip:
|
||||
"""
|
||||
Main function to call the optimizer.
|
||||
|
||||
Args:
|
||||
preferences (Preferences) : the preferences specified by the user as the post body.
|
||||
start (tuple[float, float]) : the coordinates of the starting point.
|
||||
end tuple[float, float] : the coordinates of the finishing point.
|
||||
backgroud_tasks (BackgroundTasks) : necessary to fill the cache after the trip has been returned.
|
||||
Returns:
|
||||
(uuid) : The uuid of the first landmark in the optimized route
|
||||
"""
|
||||
# Check for valid user balance
|
||||
try:
|
||||
if not supabase.check_balance(user_id=user_id):
|
||||
logger.warning('Insufficient credits to perform this action.')
|
||||
raise HTTPException(status_code=418, detail='Insufficient credits')
|
||||
except SyntaxError as se :
|
||||
logger.error(f'SyntaxError: {se}')
|
||||
raise HTTPException(status_code=400, detail=str(se)) from se
|
||||
except ValueError as ve :
|
||||
logger.error(f'SyntaxError: {ve}')
|
||||
raise HTTPException(status_code=406, detail=str(ve)) from ve
|
||||
except Exception as exc:
|
||||
logger.error(f'SyntaxError: {exc}')
|
||||
raise HTTPException(status_code=500, detail=f"Internal Server Error: {str(exc)}") from exc
|
||||
|
||||
# Check for invalid input
|
||||
if preferences is None:
|
||||
raise HTTPException(status_code=406, detail="Preferences not provided or incomplete.")
|
||||
if len(landmarks) == 0 :
|
||||
raise HTTPException(status_code=406, detail="No landmarks provided for computing the trip.")
|
||||
if (preferences.shopping.score == 0 and
|
||||
preferences.sightseeing.score == 0 and
|
||||
preferences.nature.score == 0) :
|
||||
raise HTTPException(status_code=406, detail="All preferences are 0.")
|
||||
if start is None:
|
||||
raise HTTPException(status_code=406, detail="Start coordinates not provided")
|
||||
if not (-90 <= start[0] <= 90 or -180 <= start[1] <= 180):
|
||||
raise HTTPException(status_code=422, detail="Start coordinates not in range")
|
||||
if end is None:
|
||||
end = start
|
||||
logger.info("No end coordinates provided. Using start=end.")
|
||||
|
||||
# Start the timer
|
||||
start_time = time.time()
|
||||
|
||||
logger.info(f"Requested new trip generation. Details:\n\tCoordinates: {start}\n\tTime: {preferences.max_time_minute}\n\tSightseeing: {preferences.sightseeing.score}\n\tNature: {preferences.nature.score}\n\tShopping: {preferences.shopping.score}")
|
||||
|
||||
start_landmark = Landmark(
|
||||
name='start',
|
||||
type='start',
|
||||
location=(start[0], start[1]),
|
||||
osm_type='start',
|
||||
osm_id=0,
|
||||
attractiveness=0,
|
||||
duration=0,
|
||||
must_do=True,
|
||||
n_tags = 0
|
||||
)
|
||||
|
||||
end_landmark = Landmark(
|
||||
name='finish',
|
||||
type='finish',
|
||||
location=(end[0], end[1]),
|
||||
osm_type='end',
|
||||
osm_id=0,
|
||||
attractiveness=0,
|
||||
duration=0,
|
||||
must_do=True,
|
||||
n_tags=0
|
||||
)
|
||||
|
||||
# From the parameters load the length at which to truncate the landmarks list.
|
||||
with OPTIMIZER_PARAMETERS_PATH.open('r') as f:
|
||||
parameters = yaml.safe_load(f)
|
||||
n_important = parameters['N_important']
|
||||
|
||||
# Truncate to the most important landmarks for a shorter list
|
||||
landmarks_short = landmarks[:n_important]
|
||||
|
||||
# insert start and finish to the shorter landmarks list
|
||||
landmarks_short.insert(0, start_landmark)
|
||||
landmarks_short.append(end_landmark)
|
||||
|
||||
# First stage optimization
|
||||
try:
|
||||
base_tour = optimizer.solve_optimization(preferences.max_time_minute, landmarks_short)
|
||||
except Exception as exc:
|
||||
logger.error(f"Trip generation failed: {str(exc)}")
|
||||
raise HTTPException(status_code=500, detail=f"Optimization failed: {str(exc)}") from exc
|
||||
|
||||
t_first_stage = time.time() - start_time
|
||||
start_time = time.time()
|
||||
|
||||
# Second stage optimization
|
||||
try :
|
||||
refined_tour = refiner.refine_optimization(
|
||||
landmarks, base_tour,
|
||||
preferences.max_time_minute,
|
||||
preferences.detour_tolerance_minute
|
||||
)
|
||||
except Exception as exc :
|
||||
logger.warning(f"Refiner failed. Proceeding with base trip {str(exc)}")
|
||||
refined_tour = base_tour
|
||||
|
||||
t_second_stage = time.time() - start_time
|
||||
|
||||
logger.debug(f'First stage optimization\t: {round(t_first_stage,3)} seconds')
|
||||
logger.debug(f'Second stage optimization\t: {round(t_second_stage,3)} seconds')
|
||||
logger.info(f'Total computation time\t: {round(t_first_stage + t_second_stage,3)} seconds')
|
||||
linked_tour = LinkedLandmarks(refined_tour)
|
||||
|
||||
# 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'Optimized a trip of {trip.total_time} minutes with {len(refined_tour)} landmarks in {round(t_first_stage + t_second_stage,3)} seconds.')
|
||||
logger.info('Detailed trip :\n\t' + '\n\t'.join(f'{landmark}' for landmark in refined_tour))
|
||||
|
||||
# Add the cache fill as background task
|
||||
background_tasks.add_task(fill_cache)
|
||||
|
||||
# Finally, decrement the user balance
|
||||
supabase.decrement_credit_balance(user_id=user_id)
|
||||
|
||||
return trip
|
||||
|
||||
@@ -6,7 +6,6 @@ from shapely import buffer, LineString, Point, Polygon, MultiPoint, concave_hull
|
||||
|
||||
from ..structs.landmark import Landmark
|
||||
from ..utils.get_time_distance import get_time
|
||||
from ..utils.take_most_important import take_most_important
|
||||
from .optimizer import Optimizer
|
||||
from ..constants import OPTIMIZER_PARAMETERS_PATH
|
||||
|
||||
@@ -238,7 +237,7 @@ class Refiner :
|
||||
if self.is_in_area(area, landmark.location) and landmark.name not in visited_names:
|
||||
second_order_landmarks.append(landmark)
|
||||
|
||||
return take_most_important(second_order_landmarks, int(self.max_landmarks_refiner*0.75))
|
||||
return sorted(second_order_landmarks, key=lambda x: x.attractiveness, reverse=True)[:int(self.max_landmarks_refiner*0.75)]
|
||||
|
||||
|
||||
# Try fix the shortest path using shapely
|
||||
|
||||
@@ -402,6 +402,8 @@ def fill_cache():
|
||||
n_files = 0
|
||||
total = 0
|
||||
|
||||
overpass.logger.info('Trip successfully returned, starting to fill cache.')
|
||||
|
||||
with os.scandir(OSM_CACHE_DIR) as it:
|
||||
for entry in it:
|
||||
if entry.is_file() and entry.name.startswith('hollow_'):
|
||||
|
||||
@@ -7,5 +7,4 @@ tag_exponent: 1.15
|
||||
image_bonus: 1.1
|
||||
viewpoint_bonus: 10
|
||||
wikipedia_bonus: 1.25
|
||||
N_important: 60
|
||||
pay_bonus: -1
|
||||
|
||||
@@ -6,4 +6,5 @@ max_landmarks_refiner: 20
|
||||
overshoot: 0.0016
|
||||
time_limit: 1
|
||||
gap_rel: 0.025
|
||||
max_iter: 80
|
||||
max_iter: 80
|
||||
N_important: 60
|
||||
|
||||
70
backend/src/payments/payment_handler.py
Normal file
70
backend/src/payments/payment_handler.py
Normal file
@@ -0,0 +1,70 @@
|
||||
from typing import Literal
|
||||
import paypalrestsdk
|
||||
from pydantic import BaseModel
|
||||
from fastapi import HTTPException
|
||||
import logging
|
||||
|
||||
|
||||
# Model for payment request body
|
||||
class PaymentRequest(BaseModel):
|
||||
user_id: str
|
||||
credit_amount: Literal[10, 50, 100]
|
||||
currency: Literal["USD", "EUR", "CHF"]
|
||||
description: str = "Purchase of credits"
|
||||
|
||||
|
||||
# Payment handler class for managing PayPal payments
|
||||
class PaymentHandler:
|
||||
|
||||
payment_id: str
|
||||
|
||||
def __init__(self, transaction_details: PaymentRequest):
|
||||
self.details = transaction_details
|
||||
self.logger = logging.getLogger(__name__)
|
||||
|
||||
# Only support purchase of credit 'bundles': 10, 50 or 100 credits worth of trip generation
|
||||
def fetch_price(self) -> float:
|
||||
"""
|
||||
Fetches the price of credits in the specified currency.
|
||||
"""
|
||||
result = self.supabase.table("prices").select("credit_amount").eq("currency", self.details.currency).single().execute()
|
||||
if result.data:
|
||||
return result.data.get("price")
|
||||
else:
|
||||
self.logger.error(f"Unsupported currency: {self.details.currency}")
|
||||
return None
|
||||
|
||||
def create_paypal_payment(self) -> str:
|
||||
"""
|
||||
Creates a PayPal payment and returns the approval URL.
|
||||
"""
|
||||
price = self.fetch_price()
|
||||
payment = paypalrestsdk.Payment({
|
||||
"intent": "sale",
|
||||
"payer": {
|
||||
"payment_method": "paypal"
|
||||
},
|
||||
"transactions": [{
|
||||
"amount": {
|
||||
"total": f"{price:.2f}",
|
||||
"currency": self.details.currency
|
||||
},
|
||||
"description": self.details.description
|
||||
}],
|
||||
"redirect_urls": {
|
||||
"return_url": "http://localhost:8000/payment/success",
|
||||
"cancel_url": "http://localhost:8000/payment/cancel"
|
||||
}
|
||||
})
|
||||
|
||||
if payment.create():
|
||||
self.logger.info("Payment created successfully")
|
||||
self.payment_id = payment.id
|
||||
|
||||
# Get the approval URL and return it for the user to approve
|
||||
for link in payment.links:
|
||||
if link.rel == "approval_url":
|
||||
return link.href
|
||||
else:
|
||||
self.logger.error(f"Failed to create payment: {payment.error}")
|
||||
raise HTTPException(status_code=500, detail="Payment creation failed")
|
||||
79
backend/src/payments/payment_router.py
Normal file
79
backend/src/payments/payment_router.py
Normal file
@@ -0,0 +1,79 @@
|
||||
import logging
|
||||
import paypalrestsdk
|
||||
from fastapi import HTTPException, APIRouter
|
||||
|
||||
from ..supabase.supabase import SupabaseClient
|
||||
from .payment_handler import PaymentRequest, PaymentHandler
|
||||
|
||||
# Set up logging and supabase
|
||||
logger = logging.getLogger(__name__)
|
||||
supabase = SupabaseClient()
|
||||
|
||||
# Configure PayPal SDK
|
||||
paypalrestsdk.configure({
|
||||
"mode": "sandbox", # Use 'live' for production
|
||||
"client_id": "YOUR_PAYPAL_CLIENT_ID",
|
||||
"client_secret": "YOUR_PAYPAL_SECRET"
|
||||
})
|
||||
|
||||
|
||||
# Define the API router
|
||||
router = APIRouter()
|
||||
|
||||
@router.post("/purchase/credits")
|
||||
def purchase_credits(payment_request: PaymentRequest):
|
||||
"""
|
||||
Handles token purchases. Calculates the number of tokens based on the amount paid,
|
||||
updates the user's balance, and processes PayPal payment.
|
||||
"""
|
||||
payment_handler = PaymentHandler(payment_request)
|
||||
|
||||
# Create PayPal payment and get the approval URL
|
||||
approval_url = payment_handler.create_paypal_payment()
|
||||
|
||||
return {
|
||||
"message": "Purchase initiated successfully",
|
||||
"payment_id": payment_handler.payment_id,
|
||||
"credits": payment_request.credit_amount,
|
||||
"approval_url": approval_url,
|
||||
}
|
||||
|
||||
|
||||
@router.get("/payment/success")
|
||||
def payment_success(paymentId: str, PayerID: str):
|
||||
"""
|
||||
Handles successful PayPal payment.
|
||||
"""
|
||||
payment = paypalrestsdk.Payment.find(paymentId)
|
||||
|
||||
if payment.execute({"payer_id": PayerID}):
|
||||
logger.info("Payment executed successfully")
|
||||
|
||||
# Retrieve transaction details from the database
|
||||
result = supabase.table("pending_payments").select("*").eq("payment_id", paymentId).single().execute()
|
||||
if not result.data:
|
||||
raise HTTPException(status_code=404, detail="Transaction not found")
|
||||
|
||||
# Extract the necessary information
|
||||
user_id = result.data["user_id"]
|
||||
credit_amount = result.data["credit_amount"]
|
||||
|
||||
# Update the user's balance
|
||||
supabase.increment_credit_balance(user_id, amount=credit_amount)
|
||||
|
||||
# Optionally, delete the pending payment entry since the transaction is completed
|
||||
supabase.table("pending_payments").delete().eq("payment_id", paymentId).execute()
|
||||
|
||||
return {"message": "Payment completed successfully"}
|
||||
else:
|
||||
logger.error(f"Payment execution failed: {payment.error}")
|
||||
raise HTTPException(status_code=500, detail="Payment execution failed")
|
||||
|
||||
|
||||
@router.get("/payment/cancel")
|
||||
def payment_cancel():
|
||||
"""
|
||||
Handles PayPal payment cancellation.
|
||||
"""
|
||||
return {"message": "Payment was cancelled"}
|
||||
|
||||
@@ -49,8 +49,8 @@ class Landmark(BaseModel) :
|
||||
image_url : Optional[str] = None
|
||||
website_url : Optional[str] = None
|
||||
wiki_url : Optional[str] = None
|
||||
keywords: Optional[dict] = {}
|
||||
description : Optional[str] = None
|
||||
# keywords: Optional[dict] = {}
|
||||
# description : Optional[str] = None
|
||||
duration : Optional[int] = 5
|
||||
name_en : Optional[str] = None
|
||||
|
||||
|
||||
@@ -2,6 +2,7 @@
|
||||
|
||||
from .landmark import Landmark
|
||||
from ..utils.get_time_distance import get_time
|
||||
from ..utils.description import description_and_keywords
|
||||
|
||||
class LinkedLandmarks:
|
||||
"""
|
||||
@@ -35,18 +36,23 @@ class LinkedLandmarks:
|
||||
Create the links between the landmarks in the list by setting their
|
||||
.next_uuid and the .time_to_next attributes.
|
||||
"""
|
||||
|
||||
# Mark secondary landmarks as such
|
||||
self.update_secondary_landmarks()
|
||||
|
||||
|
||||
for i, landmark in enumerate(self._landmarks[:-1]):
|
||||
# Set uuid of the next landmark
|
||||
landmark.next_uuid = self._landmarks[i + 1].uuid
|
||||
|
||||
# Adjust time to reach and total time
|
||||
time_to_next = get_time(landmark.location, self._landmarks[i + 1].location)
|
||||
landmark.time_to_reach_next = time_to_next
|
||||
self.total_time += time_to_next
|
||||
self.total_time += landmark.duration
|
||||
|
||||
# Fill in the keywords and description. GOOD IDEA, BAD EXECUTION, tags aren't available anymore at this stage
|
||||
# landmark.description, landmark.keywords = description_and_keywords(tags)
|
||||
|
||||
|
||||
self._landmarks[-1].next_uuid = None
|
||||
self._landmarks[-1].time_to_reach_next = 0
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
"""Defines the Preferences used as input for trip generation."""
|
||||
|
||||
from typing import Optional, Literal
|
||||
from pydantic import BaseModel
|
||||
from pydantic import BaseModel, field_validator
|
||||
|
||||
|
||||
class Preference(BaseModel) :
|
||||
@@ -15,6 +15,13 @@ class Preference(BaseModel) :
|
||||
type: Literal['sightseeing', 'nature', 'shopping', 'start', 'finish']
|
||||
score: int # score could be from 1 to 5
|
||||
|
||||
@field_validator("type")
|
||||
@classmethod
|
||||
def validate_type(cls, v):
|
||||
if v not in {'sightseeing', 'nature', 'shopping', 'start', 'finish'}:
|
||||
raise ValueError(f"Invalid type: {v}")
|
||||
return v
|
||||
|
||||
|
||||
# Input for optimization
|
||||
class Preferences(BaseModel) :
|
||||
@@ -32,3 +39,16 @@ class Preferences(BaseModel) :
|
||||
|
||||
max_time_minute: Optional[int] = 3*60
|
||||
detour_tolerance_minute: Optional[int] = 0
|
||||
|
||||
|
||||
def model_post_init(self, __context):
|
||||
"""
|
||||
Method to validate proper initialization of individual Preferences.
|
||||
Raises ValueError if the Preference type does not match with the field name.
|
||||
"""
|
||||
if self.sightseeing.type != 'sightseeing':
|
||||
raise ValueError(f'The sightseeing preference cannot be {self.sightseeing.type}.')
|
||||
if self.nature.type != 'nature':
|
||||
raise ValueError(f'The nature preference cannot be {self.nature.type}.')
|
||||
if self.shopping.type != 'shopping':
|
||||
raise ValueError(f'The shopping preference cannot be {self.shopping.type}.')
|
||||
169
backend/src/supabase/supabase.py
Normal file
169
backend/src/supabase/supabase.py
Normal file
@@ -0,0 +1,169 @@
|
||||
import os
|
||||
import logging
|
||||
import yaml
|
||||
from fastapi import HTTPException, status
|
||||
from supabase import create_client, Client, ClientOptions
|
||||
|
||||
from ..constants import PARAMETERS_DIR
|
||||
|
||||
# Silence the supabase logger
|
||||
logging.getLogger("httpx").setLevel(logging.CRITICAL)
|
||||
logging.getLogger("hpack").setLevel(logging.CRITICAL)
|
||||
logging.getLogger("httpcore").setLevel(logging.CRITICAL)
|
||||
|
||||
|
||||
class SupabaseClient:
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
def __init__(self):
|
||||
|
||||
with open(os.path.join(PARAMETERS_DIR, 'secrets.yaml')) as f:
|
||||
secrets = yaml.safe_load(f)
|
||||
self.SUPABASE_URL = secrets['SUPABASE_URL']
|
||||
self.SUPABASE_ADMIN_KEY = secrets['SUPABASE_ADMIN_KEY']
|
||||
self.SUPABASE_TEST_USER_ID = secrets['SUPABASE_TEST_USER_ID']
|
||||
|
||||
self.supabase = create_client(
|
||||
self.SUPABASE_URL,
|
||||
self.SUPABASE_ADMIN_KEY,
|
||||
options=ClientOptions(schema='public')
|
||||
)
|
||||
self.logger.info('Supabase client initialized.')
|
||||
|
||||
|
||||
def check_balance(self, user_id: str) -> bool:
|
||||
"""
|
||||
Checks if the user has enough 'credit' for generating a new trip.
|
||||
|
||||
Args:
|
||||
user_id (str): The ID of the current user.
|
||||
|
||||
Returns:
|
||||
bool: True if the balance is positive, False otherwise.
|
||||
"""
|
||||
try:
|
||||
# Query the public.credits table to get the user's credits
|
||||
response = (
|
||||
self.supabase.table("credits")
|
||||
.select('*')
|
||||
.eq('id', user_id)
|
||||
.single()
|
||||
.execute()
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
if e.code == '22P02' :
|
||||
self.logger.error(f"Failed querying credits : {str(e)}")
|
||||
raise SyntaxError(f"Failed querying credits : {str(e)}") from e
|
||||
if e.code == 'PGRST116' :
|
||||
self.logger.error(f"User not found : {str(e)}")
|
||||
raise ValueError(f"User not found : {str(e)}") from e
|
||||
else :
|
||||
self.logger.error(f"An unexpected error occured while checking user balance : {str(e)}")
|
||||
raise Exception(f"An unexpected error occured while checking user balance : {str(e)}") from e
|
||||
|
||||
# Proceed to check the user's credit balance
|
||||
credits = response.data['credit_amount']
|
||||
self.logger.debug(f'Credits of user {user_id}: {credits}')
|
||||
|
||||
if credits > 0:
|
||||
self.logger.info(f'Credit balance is positive for user {user_id}. Proceeding with trip generation.')
|
||||
return True
|
||||
|
||||
self.logger.warning(f'Insufficient balance for user {user_id}. Trip generation cannot proceed.')
|
||||
return False
|
||||
|
||||
|
||||
def decrement_credit_balance(self, user_id: str, amount: int=1) -> bool:
|
||||
"""
|
||||
Decrements the user's credit balance by 1.
|
||||
|
||||
Args:
|
||||
user_id (str): The ID of the current user.
|
||||
"""
|
||||
try:
|
||||
# Query the public.credits table to get the user's current credits
|
||||
response = (
|
||||
self.supabase.table("credits")
|
||||
.select('*')
|
||||
.eq('id', user_id)
|
||||
.single()
|
||||
.execute()
|
||||
)
|
||||
except Exception as e:
|
||||
if e.code == '22P02' :
|
||||
self.logger.error(f"Failed decrementing credits : {str(e)}")
|
||||
raise SyntaxError(f"Failed decrementing credits : {str(e)}") from e
|
||||
if e.code == 'PGRST116' :
|
||||
self.logger.error(f"User not found : {str(e)}")
|
||||
raise ValueError(f"User not found : {str(e)}") from e
|
||||
else :
|
||||
self.logger.error(f"An unexpected error occured while decrementing user balance : {str(e)}")
|
||||
raise Exception(f"An unexpected error occured while decrementing user balance : {str(e)}") from e
|
||||
|
||||
|
||||
current_credits = response.data['credit_amount']
|
||||
updated_credits = current_credits - amount
|
||||
|
||||
# Update the user's credits in the table
|
||||
update_response = (
|
||||
self.supabase.table('credits')
|
||||
.update({'credit_amount': updated_credits})
|
||||
.eq('id', user_id)
|
||||
.execute()
|
||||
)
|
||||
|
||||
# Check if the update was successful
|
||||
if update_response.data:
|
||||
self.logger.debug(f'Credit balance successfully decremented.')
|
||||
return True
|
||||
else:
|
||||
raise Exception("Error decrementing credit balance.")
|
||||
|
||||
|
||||
def increment_credit_balance(self, user_id: str, amount: int=1) -> bool:
|
||||
"""
|
||||
Increments the user's credit balance by 1.
|
||||
|
||||
Args:
|
||||
user_id (str): The ID of the current user.
|
||||
"""
|
||||
try:
|
||||
# Query the public.credits table to get the user's current credits
|
||||
response = (
|
||||
self.supabase.table("credits")
|
||||
.select('*')
|
||||
.eq('id', user_id)
|
||||
.single()
|
||||
.execute()
|
||||
)
|
||||
except Exception as e:
|
||||
if e.code == '22P02' :
|
||||
self.logger.error(f"Failed incrementing credits : {str(e)}")
|
||||
raise SyntaxError(f"Failed incrementing credits : {str(e)}") from e
|
||||
if e.code == 'PGRST116' :
|
||||
self.logger.error(f"User not found : {str(e)}")
|
||||
raise ValueError(f"User not found : {str(e)}") from e
|
||||
else :
|
||||
self.logger.error(f"An unexpected error occured while incrementing user balance : {str(e)}")
|
||||
raise Exception(f"An unexpected error occured while incrementing user balance : {str(e)}") from e
|
||||
|
||||
|
||||
current_credits = response.data['credit_amount']
|
||||
updated_credits = current_credits + amount
|
||||
|
||||
# Update the user's credits in the table
|
||||
update_response = (
|
||||
self.supabase.table('credits')
|
||||
.update({'credit_amount': updated_credits})
|
||||
.eq('id', user_id)
|
||||
.execute()
|
||||
)
|
||||
|
||||
# Check if the update was successful
|
||||
if update_response.data:
|
||||
self.logger.debug(f'Credit balance successfully incremented.')
|
||||
return True
|
||||
else:
|
||||
raise Exception("Error incrementing credit balance.")
|
||||
@@ -19,30 +19,50 @@ def invalid_client():
|
||||
([48.8566, 2.3522], {}, 422),
|
||||
|
||||
# Invalid cases: incomplete preferences.
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "nature", "score": 5}, # no shopping
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 5}, # no shopping pref
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
}, 422),
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "nature", "score": 5}, # no nature
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 5}, # no nature pref
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
}, 422),
|
||||
([48.084588, 7.280405], {"nature": {"type": "nature", "score": 5}, # no sightseeing
|
||||
([48.084588, 7.280405], {"nature": {"type": "nature", "score": 5}, # no sightseeing pref
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
}, 422),
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "nature", "score": 1}, # mixed up preferences types. TODO: i suggest reducing the complexity by remove the Preference object.
|
||||
"nature": {"type": "shopping", "score": 1},
|
||||
"shopping": {"type": "shopping", "score": 1},
|
||||
}, 422),
|
||||
([48.084588, 7.280405], {"doesnotexist": {"type": "sightseeing", "score": 2}, # non-existing preferences types
|
||||
"nature": {"type": "nature", "score": 2},
|
||||
"shopping": {"type": "shopping", "score": 2},
|
||||
}, 422),
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 3}, # non-existing preferences types
|
||||
"nature": {"type": "doesntexisteither", "score": 3},
|
||||
"shopping": {"type": "shopping", "score": 3},
|
||||
}, 422),
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": -1}, # negative preference value
|
||||
"nature": {"type": "doesntexisteither", "score": 4},
|
||||
"shopping": {"type": "shopping", "score": 4},
|
||||
}, 422),
|
||||
([48.084588, 7.280405], {"sightseeing": {"type": "sightseeing", "score": 10}, # too high preference value
|
||||
"nature": {"type": "doesntexisteither", "score": 4},
|
||||
"shopping": {"type": "shopping", "score": 4},
|
||||
}, 422),
|
||||
|
||||
# Invalid cases: unexisting coords
|
||||
([91, 181], {"sightseeing": {"type": "nature", "score": 5},
|
||||
([91, 181], {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
}, 422),
|
||||
([-91, 181], {"sightseeing": {"type": "nature", "score": 5},
|
||||
([-91, 181], {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
}, 422),
|
||||
([91, -181], {"sightseeing": {"type": "nature", "score": 5},
|
||||
([91, -181], {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
}, 422),
|
||||
([-91, -181], {"sightseeing": {"type": "nature", "score": 5},
|
||||
([-91, -181], {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
}, 422),
|
||||
@@ -53,8 +73,8 @@ def test_input(invalid_client, start, preferences, status_code): # pylint: dis
|
||||
Test new trip creation with different sets of preferences and locations.
|
||||
"""
|
||||
response = invalid_client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"/get/landmarks",
|
||||
json ={
|
||||
"preferences": preferences,
|
||||
"start": start
|
||||
}
|
||||
|
||||
@@ -1,343 +0,0 @@
|
||||
"""Collection of tests to ensure correct implementation and track progress. """
|
||||
import time
|
||||
from fastapi.testclient import TestClient
|
||||
import pytest
|
||||
|
||||
from .test_utils import load_trip_landmarks, log_trip_details
|
||||
from ..main import app
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def client():
|
||||
"""Client used to call the app."""
|
||||
return TestClient(app)
|
||||
|
||||
|
||||
def test_turckheim(client, request): # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°1 : Custom test in Turckheim to ensure small villages are also supported.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
start_time = time.time() # Start timer
|
||||
duration_minutes = 20
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "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": [45.74445023349939, 4.8222687890538865]
|
||||
# "start": [45.75156398104873, 4.827154464827647]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
|
||||
# checks :
|
||||
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.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
start_time = time.time() # Start timer
|
||||
duration_minutes = 120
|
||||
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
"max_time_minute": duration_minutes,
|
||||
"detour_tolerance_minute": 0},
|
||||
"start": [45.7576485, 4.8330241]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
# 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}"
|
||||
|
||||
def test_cologne(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°3 : Custom test in Cologne to ensure proper decision making in crowded area.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
start_time = time.time() # Start timer
|
||||
duration_minutes = 240
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
"max_time_minute": duration_minutes,
|
||||
"detour_tolerance_minute": 0},
|
||||
"start": [50.942352665, 6.957777972392]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
# 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}"
|
||||
|
||||
|
||||
def test_strasbourg(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°4 : Custom test in Strasbourg to ensure proper decision making in crowded area.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
start_time = time.time() # Start timer
|
||||
duration_minutes = 180
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
"max_time_minute": duration_minutes,
|
||||
"detour_tolerance_minute": 0},
|
||||
"start": [48.5846589226, 7.74078715721]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
# 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}"
|
||||
|
||||
|
||||
def test_zurich(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°5 : Custom test in Zurich to ensure proper decision making in crowded area.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
start_time = time.time() # Start timer
|
||||
duration_minutes = 180
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
"max_time_minute": duration_minutes,
|
||||
"detour_tolerance_minute": 0},
|
||||
"start": [47.377884227, 8.5395114066]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
# 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}"
|
||||
|
||||
|
||||
def test_paris(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
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 = 200
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 0},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
"max_time_minute": duration_minutes,
|
||||
"detour_tolerance_minute": 0},
|
||||
"start": [48.85468881798671, 2.3423925755998374]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
# 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}"
|
||||
|
||||
|
||||
def test_new_york(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°7 : Custom test in New York to ensure proper decision making in crowded area.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
start_time = time.time() # Start timer
|
||||
duration_minutes = 600
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "score": 5},
|
||||
"nature": {"type": "nature", "score": 5},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
"max_time_minute": duration_minutes,
|
||||
"detour_tolerance_minute": 0},
|
||||
"start": [40.72592726802, -73.9920434795]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
# 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}"
|
||||
|
||||
|
||||
def test_shopping(client, request) : # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°8 : Custom test in Lyon centre to ensure shopping clusters are found.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
start_time = time.time() # Start timer
|
||||
duration_minutes = 240
|
||||
|
||||
response = client.post(
|
||||
"/trip/new",
|
||||
json={
|
||||
"preferences": {"sightseeing": {"type": "sightseeing", "score": 0},
|
||||
"nature": {"type": "nature", "score": 0},
|
||||
"shopping": {"type": "shopping", "score": 5},
|
||||
"max_time_minute": duration_minutes,
|
||||
"detour_tolerance_minute": 0},
|
||||
"start": [45.7576485, 4.8330241]
|
||||
}
|
||||
)
|
||||
result = response.json()
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], duration_minutes)
|
||||
|
||||
# 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}"
|
||||
46
backend/src/tests/test_nearby.py
Normal file
46
backend/src/tests/test_nearby.py
Normal file
@@ -0,0 +1,46 @@
|
||||
"""Collection of tests to ensure correct implementation and track progress of the get_landmarks_nearby feature. """
|
||||
|
||||
from fastapi.testclient import TestClient
|
||||
import pytest
|
||||
|
||||
from ..main import app
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def client():
|
||||
"""Client used to call the app."""
|
||||
return TestClient(app)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"location,status_code",
|
||||
[
|
||||
([45.7576485, 4.8330241], 200), # Lyon, France
|
||||
([41.4020572, 2.1818985], 200), # Barcelona, Spain
|
||||
([59.3293, 18.0686], 200), # Stockholm, Sweden
|
||||
([43.6532, -79.3832], 200), # Toronto, Canada
|
||||
([38.7223, -9.1393], 200), # Lisbon, Portugal
|
||||
([6.5244, 3.3792], 200), # Lagos, Nigeria
|
||||
([17.3850, 78.4867], 200), # Hyderabad, India
|
||||
([30.0444, 31.2357], 200), # Cairo, Egypt
|
||||
([50.8503, 4.3517], 200), # Brussels, Belgium
|
||||
([35.2271, -80.8431], 200), # Charlotte, USA
|
||||
([10.4806, -66.9036], 200), # Caracas, Venezuela
|
||||
([9.51074, -13.71118], 200), # Conakry, Guinea
|
||||
]
|
||||
)
|
||||
def test_nearby(client, location, status_code): # pylint: disable=redefined-outer-name
|
||||
"""
|
||||
Test n°1 : Verify handling of invalid input.
|
||||
|
||||
Args:
|
||||
client:
|
||||
request:
|
||||
"""
|
||||
response = client.post(f"/get-nearby/landmarks/{location[0]}/{location[1]}")
|
||||
suggestions = response.json()
|
||||
|
||||
# checks :
|
||||
assert response.status_code == status_code # check for successful planning
|
||||
assert isinstance(suggestions, list) # check that the return type is a list
|
||||
assert len(suggestions) > 0
|
||||
@@ -18,7 +18,7 @@ def client():
|
||||
[
|
||||
({}, None, 422), # Invalid case: no location at all.
|
||||
([443], None, 422), # Invalid cases: invalid location.
|
||||
([443, 433], None, 422), # Invalid cases: invalid location.
|
||||
([443, 433], None, 422), # Invalid cases: invalid location.
|
||||
]
|
||||
)
|
||||
def test_invalid_input(client, location, radius, status_code): # pylint: disable=redefined-outer-name
|
||||
@@ -30,7 +30,7 @@ def test_invalid_input(client, location, radius, status_code): # pylint: disa
|
||||
request:
|
||||
"""
|
||||
response = client.post(
|
||||
"/toilets/new",
|
||||
"/get/toilets",
|
||||
params={
|
||||
"location": location,
|
||||
"radius": radius
|
||||
@@ -58,7 +58,7 @@ def test_no_toilets(client, location, status_code): # pylint: disable=redefin
|
||||
request:
|
||||
"""
|
||||
response = client.post(
|
||||
"/toilets/new",
|
||||
"/get/toilets",
|
||||
params={
|
||||
"location": location
|
||||
}
|
||||
@@ -87,7 +87,7 @@ def test_toilets(client, location, status_code): # pylint: disable=redefined-
|
||||
request:
|
||||
"""
|
||||
response = client.post(
|
||||
"/toilets/new",
|
||||
"/get/toilets",
|
||||
params={
|
||||
"location": location,
|
||||
"radius" : 600
|
||||
|
||||
101
backend/src/tests/test_trip_generation.py
Normal file
101
backend/src/tests/test_trip_generation.py
Normal file
@@ -0,0 +1,101 @@
|
||||
"""Collection of tests to ensure correct implementation and track progress."""
|
||||
import os
|
||||
import time
|
||||
import yaml
|
||||
from fastapi.testclient import TestClient
|
||||
import pytest
|
||||
|
||||
from .test_utils import load_trip_landmarks, log_trip_details
|
||||
from ..supabase.supabase import SupabaseClient
|
||||
from ..structs.preferences import Preferences, Preference
|
||||
from ..constants import PARAMETERS_DIR
|
||||
from ..main import app
|
||||
|
||||
|
||||
# Create a supabase client
|
||||
supabase = SupabaseClient()
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def client():
|
||||
"""Client used to call the app."""
|
||||
return TestClient(app)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"sightseeing, shopping, nature, max_time_minute, start_coords, end_coords",
|
||||
[
|
||||
# Edge cases
|
||||
(0, 0, 5, 240, [45.7576485, 4.8330241], None), # Lyon, Bellecour - test shopping only
|
||||
|
||||
# Realistic
|
||||
(5, 0, 0, 20, [48.0845881, 7.2804050], None), # Turckheim
|
||||
(5, 5, 5, 120, [45.7576485, 4.8330241], None), # Lyon, Bellecour
|
||||
(5, 2, 5, 240, [50.9423526, 6.9577780], None), # Cologne, centre
|
||||
(3, 5, 0, 180, [48.5846589226, 7.74078715721], None), # Strasbourg, centre
|
||||
(2, 4, 5, 180, [47.377884227, 8.5395114066], None), # Zurich, centre
|
||||
(5, 0, 5, 200, [48.85468881798671, 2.3423925755998374], None), # Paris, centre
|
||||
(5, 5, 5, 600, [40.72592726802, -73.9920434795], None), # New York, Lower Manhattan
|
||||
]
|
||||
)
|
||||
def test_trip(client, request, sightseeing, shopping, nature, max_time_minute, start_coords, end_coords):
|
||||
|
||||
start_time = time.time() # Start timer
|
||||
|
||||
prefs = Preferences(
|
||||
sightseeing=Preference(type='sightseeing', score=sightseeing),
|
||||
shopping=Preference(type='shopping', score=shopping),
|
||||
nature=Preference(type='nature', score=nature),
|
||||
max_time_minute=max_time_minute,
|
||||
detour_tolerance_minute=0,
|
||||
)
|
||||
start = start_coords
|
||||
end = end_coords
|
||||
|
||||
# Step 1: request the list of landmarks in the vicinty of the starting point
|
||||
response = client.post(
|
||||
"/get/landmarks",
|
||||
json={
|
||||
"preferences": prefs.model_dump(),
|
||||
"start": start_coords,
|
||||
"end": end_coords,
|
||||
}
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
landmarks = response.json()
|
||||
|
||||
# Step 2: Feed the landmarks to the optimizer to compute the trip
|
||||
response = client.post(
|
||||
"/optimize/trip",
|
||||
json={
|
||||
"user_id": supabase.SUPABASE_TEST_USER_ID,
|
||||
"preferences": prefs.model_dump(),
|
||||
"landmarks": landmarks,
|
||||
"start": start,
|
||||
"end": end,
|
||||
}
|
||||
)
|
||||
assert response.status_code == 200
|
||||
|
||||
# Increment the user balance again
|
||||
supabase.increment_credit_balance(
|
||||
supabase.SUPABASE_TEST_USER_ID,
|
||||
amount=1
|
||||
)
|
||||
|
||||
# Parse the response
|
||||
result = response.json()
|
||||
# print(result)
|
||||
landmarks = load_trip_landmarks(client, result['first_landmark_uuid'])
|
||||
|
||||
# Get computation time
|
||||
comp_time = time.time() - start_time
|
||||
|
||||
# Add details to report
|
||||
log_trip_details(request, landmarks, result['total_time'], prefs.max_time_minute)
|
||||
|
||||
# checks :
|
||||
assert comp_time < 30, f"Computation time exceeded 30 seconds: {comp_time:.2f} seconds"
|
||||
assert prefs.max_time_minute*0.8 < result['total_time'], f"Trip too short: {result['total_time']} instead of {prefs.max_time_minute}"
|
||||
assert prefs.max_time_minute*1.2 > result['total_time'], f"Trip too long: {result['total_time']} instead of {prefs.max_time_minute}"
|
||||
@@ -1,9 +1,12 @@
|
||||
"""Helper methods for testing."""
|
||||
import time
|
||||
import logging
|
||||
from functools import wraps
|
||||
from fastapi import HTTPException
|
||||
|
||||
from ..structs.landmark import Landmark
|
||||
from ..cache import client as cache_client
|
||||
from ..structs.landmark import Landmark
|
||||
from ..structs.preferences import Preferences, Preference
|
||||
|
||||
|
||||
def landmarks_to_osmid(landmarks: list[Landmark]) -> list[int] :
|
||||
@@ -91,3 +94,34 @@ def log_trip_details(request, landmarks: list[Landmark], duration: int, target_d
|
||||
request.node.trip_details = trip_string
|
||||
request.node.trip_duration = str(duration) # result['total_time']
|
||||
request.node.target_duration = str(target_duration)
|
||||
|
||||
|
||||
|
||||
|
||||
def trip_params(
|
||||
sightseeing: int,
|
||||
shopping: int,
|
||||
nature: int,
|
||||
max_time_minute: int,
|
||||
start_coords: tuple[float, float] = None,
|
||||
end_coords: tuple[float, float] = None,
|
||||
):
|
||||
def decorator(test_func):
|
||||
@wraps(test_func)
|
||||
def wrapper(client, request):
|
||||
prefs = Preferences(
|
||||
sightseeing=Preference(type='sightseeing', score=sightseeing),
|
||||
shopping=Preference(type='shopping', score=shopping),
|
||||
nature=Preference(type='nature', score=nature),
|
||||
max_time_minute=max_time_minute,
|
||||
detour_tolerance_minute=0,
|
||||
)
|
||||
|
||||
start = start_coords
|
||||
end = end_coords
|
||||
|
||||
# Inject into test function
|
||||
return test_func(client, request, prefs, start, end)
|
||||
|
||||
return wrapper
|
||||
return decorator
|
||||
@@ -70,6 +70,8 @@ class ToiletsManager:
|
||||
|
||||
toilets_list = self.to_toilets(result)
|
||||
|
||||
self.logger.debug(f'Found {len(toilets_list)} toilets around {self.location}')
|
||||
|
||||
return toilets_list
|
||||
|
||||
|
||||
|
||||
@@ -1,16 +1,20 @@
|
||||
"""Defines the endpoint for fetching toilet locations."""
|
||||
"""API entry point for fetching toilet locations."""
|
||||
|
||||
from fastapi import HTTPException, APIRouter, Query
|
||||
|
||||
from ..structs.toilets import Toilets
|
||||
from .toilets_manager import ToiletsManager
|
||||
from ..structs.toilets import Toilets
|
||||
|
||||
|
||||
# Define the API router
|
||||
# Initialize the API router
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
@router.post("/toilets/new")
|
||||
def get_toilets(location: tuple[float, float] = Query(...), radius: int = 500) -> list[Toilets] :
|
||||
@router.post("/get/toilets")
|
||||
def get_toilets(
|
||||
location: tuple[float, float] = Query(...),
|
||||
radius: int = 500
|
||||
) -> list[Toilets] :
|
||||
"""
|
||||
Endpoint to find toilets within a specified radius from a given location.
|
||||
|
||||
@@ -34,5 +38,6 @@ def get_toilets(location: tuple[float, float] = Query(...), radius: int = 500) -
|
||||
toilets_list = toilets_manager.generate_toilet_list()
|
||||
except KeyError as exc:
|
||||
raise HTTPException(status_code=404, detail="No toilets found") from exc
|
||||
|
||||
|
||||
return toilets_list
|
||||
123
backend/src/utils/description.py
Normal file
123
backend/src/utils/description.py
Normal file
@@ -0,0 +1,123 @@
|
||||
"""Add more information about the landmarks by writing a short description and keywords. """
|
||||
|
||||
|
||||
def description_and_keywords(tags: dict):
|
||||
"""
|
||||
Generates a description and a set of keywords for a given landmark based on its tags.
|
||||
|
||||
Params:
|
||||
tags (dict): A dictionary containing metadata about the landmark, including its name,
|
||||
importance, height, date of construction, and visitor information.
|
||||
|
||||
Returns:
|
||||
description (str): A string description of the landmark.
|
||||
keywords (dict): A dictionary of keywords with fields such as 'importance', 'height',
|
||||
'place_type', and 'date'.
|
||||
"""
|
||||
# Extract relevant fields
|
||||
name = tags.get('name')
|
||||
importance = tags.get('importance', None)
|
||||
n_visitors = tags.get('tourism:visitors', None)
|
||||
height = tags.get('height')
|
||||
place_type = get_place_type(tags)
|
||||
date = get_date(tags)
|
||||
|
||||
if place_type is None :
|
||||
return None, None
|
||||
|
||||
# Start the description.
|
||||
if importance is None :
|
||||
if len(tags.keys()) < 5 :
|
||||
return None, None
|
||||
if len(tags.keys()) < 10 :
|
||||
description = f"{name} is a well known {place_type}."
|
||||
elif len(tags.keys()) < 17 :
|
||||
importance = 'national'
|
||||
description = f"{name} is a {place_type} of national importance."
|
||||
else :
|
||||
importance = 'international'
|
||||
description = f"{name} is an internationally famous {place_type}."
|
||||
else :
|
||||
description = f"{name} is a {place_type} of {importance} importance."
|
||||
|
||||
if height is not None and date is not None :
|
||||
description += f" This {place_type} was constructed in {date} and is ca. {height} meters high."
|
||||
elif height is not None :
|
||||
description += f" This {place_type} stands ca. {height} meters tall."
|
||||
elif date is not None:
|
||||
description += f" It was constructed in {date}."
|
||||
|
||||
# Format the visitor number
|
||||
if n_visitors is not None :
|
||||
n_visitors = int(n_visitors)
|
||||
if n_visitors < 1000000 :
|
||||
description += f" It welcomes {int(n_visitors/1000)} thousand visitors every year."
|
||||
else :
|
||||
description += f" It welcomes {round(n_visitors/1000000, 1)} million visitors every year."
|
||||
|
||||
# Set the keywords.
|
||||
keywords = {"importance": importance,
|
||||
"height": height,
|
||||
"place_type": place_type,
|
||||
"date": date}
|
||||
|
||||
return description, keywords
|
||||
|
||||
|
||||
def get_place_type(tags):
|
||||
"""
|
||||
Determines the type of the place based on available tags such as 'amenity', 'building',
|
||||
'historic', and 'leisure'. The priority order is: 'historic' > 'building' (if not generic) >
|
||||
'amenity' > 'leisure'.
|
||||
|
||||
Params:
|
||||
tags (dict): A dictionary containing metadata about the place.
|
||||
|
||||
Returns:
|
||||
place_type (str): The determined type of the place, or None if no relevant type is found.
|
||||
"""
|
||||
amenity = tags.get('amenity', None)
|
||||
building = tags.get('building', None)
|
||||
historic = tags.get('historic', None)
|
||||
leisure = tags.get('leisure')
|
||||
|
||||
if historic and historic != "yes":
|
||||
return historic
|
||||
if building and building not in ["yes", "civic", "government", "apartments", "residential", "commericial", "industrial", "retail", "religious", "public", "service"]:
|
||||
return building
|
||||
if amenity:
|
||||
return amenity
|
||||
if leisure:
|
||||
return leisure
|
||||
|
||||
|
||||
return None
|
||||
|
||||
|
||||
def get_date(tags):
|
||||
"""
|
||||
Extracts the most relevant date from the available tags, prioritizing 'construction_date',
|
||||
'start_date', 'year_of_construction', and 'opening_date' in that order.
|
||||
|
||||
Params:
|
||||
tags (dict): A dictionary containing metadata about the place.
|
||||
|
||||
Returns:
|
||||
date (str): The most relevant date found, or None if no date is available.
|
||||
"""
|
||||
construction_date = tags.get('construction_date', None)
|
||||
opening_date = tags.get('opening_date', None)
|
||||
start_date = tags.get('start_date', None)
|
||||
year_of_construction = tags.get('year_of_construction', None)
|
||||
|
||||
# Prioritize based on availability
|
||||
if construction_date:
|
||||
return construction_date
|
||||
if start_date:
|
||||
return start_date
|
||||
if year_of_construction:
|
||||
return year_of_construction
|
||||
if opening_date:
|
||||
return opening_date
|
||||
|
||||
return None
|
||||
@@ -1,17 +0,0 @@
|
||||
"""Helper function to return only the major landmarks from a large list."""
|
||||
from ..structs.landmark import Landmark
|
||||
|
||||
def take_most_important(landmarks: list[Landmark], n_important) -> list[Landmark]:
|
||||
"""
|
||||
Given a list of landmarks, return the n_important most important landmarks
|
||||
Args:
|
||||
landmarks: list[Landmark] - list of landmarks
|
||||
n_important: int - number of most important landmarks to return
|
||||
Returns:
|
||||
list[Landmark] - list of the n_important most important landmarks
|
||||
"""
|
||||
|
||||
# Sort landmarks by attractiveness (descending)
|
||||
sorted_landmarks = sorted(landmarks, key=lambda x: x.attractiveness, reverse=True)
|
||||
|
||||
return sorted_landmarks[:n_important]
|
||||
1876
backend/uv.lock
generated
Normal file
1876
backend/uv.lock
generated
Normal file
File diff suppressed because it is too large
Load Diff
1091
report.html
Normal file
1091
report.html
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user