Merge branch 'main' of https://github.com/TobiasSchaeuble-EH/LunchHeroes

backend/.gitignore

@@ -0,0 +1,3 @@
+.env
+.DS_Store
+../.DS_Store

backend/main.py

@@ -1,6 +1,9 @@
+
+import lunchheros
 
-
-from src.routes.users.userFunctions import getAllUsers, getUserWithId
+from fastapi.encoders import jsonable_encoder
+from src.lunchheros.db.dbFetcher import get_encoded_data
+from src.routes.users.userFunctions import getAllQueryListData, getAllUsers, getUserWithId
 from fastapi import FastAPI
 from supabase_client import supabase_client
 
@@ -20,4 +23,13 @@ def load_all_users():
 @app.get("/users/{userId}")
 def load_current_user(userId):
     currentUser = getUserWithId(userId)
-    return { "currentUser" : currentUser}
+    return { "currentUser" : currentUser}
+
+@app.get("/button_trigger/{userId}")
+def load_current_user(userId: str):
+    userData = getUserWithId(userId)
+    queryList = getAllQueryListData() 
+
+    test = lunchheros.match.match(userData)
+
+    return { "currentUser" : userData, "query": queryList}

backend/pyproject.toml

@@ -9,6 +9,9 @@ readme = "README.md"
 python = ">=3.9"
 pandas = "*"
 scikit-learn = "^1.3.2"
+supabase = "^1.2.0"
+fastapi = "^0.104.0"
+python-dotenv = "^1.0.0"
 
 
 [tool.poetry.group.dev.dependencies]

backend/src/__init__.py

@@ -1 +1,4 @@
-"""Lunchheros: Backend to match people for lunch based on their interests."""
+"""Lunchheros: Backend to match people for lunch based on their interests."""
+from lunchheros import match
+
+__all__  = ["match"]

backend/src/lunchheros/clustering/__init__.py

@@ -0,0 +1 @@
+"""Subpackage related to use the distance matrix to  cluster the users into groups."""

backend/src/lunchheros/clustering/userClustering.py

@@ -0,0 +1,13 @@
+import numpy as np
+from sklearn.cluster import DBSCAN
+from scipy.spatial import distance
+
+def generateUserClusters(distanceMatrix):
+    """Generate clusters of users based on the distance matrix."""
+
+    # Apply DBSCAN on the distance matrix
+    dbscan = DBSCAN(metric='precomputed')
+    clusters = dbscan.fit_predict(distanceMatrix)
+
+    # clusters now contains the cluster labels for each user
+    print(clusters)

backend/src/lunchheros/db/__init__.py

@@ -0,0 +1 @@
+"""Subpackage related to matching between users into groups."""

backend/src/lunchheros/db/dbFetcher.py

@@ -0,0 +1,32 @@
+import numpy as np
+import pandas as pd
+import json
+import os 
+
+
+
+
+async def get_encoded_data(time_slot: int, location: str, data):
+    print("get_encoded_data")
+    # Transform data
+    #print(f"Data {time_slot} {location} {data}")
+    #df = pd.DataFrame(data)
+
+
+    # One-hot encode data
+    #one_hot_encoded_df = pd.get_dummies(df, columns=['WIP'])  # wip - replace with actual column names
+    #one_hot_encoded_df.to_dict(orient='records') 
+
+    #return one_hot_encoded_df
+
+
+def parse_user_id_tolist(test_data):
+    data = json.loads(test_data)
+
+    # Extract the id values into a python list
+    ids = [x['id'] for x in data]
+
+    # Convert the python list to a numpy array
+    numpy_array = np.array(ids).tolist()
+
+    return numpy_array

backend/src/lunchheros/match/__init__.py

@@ -1 +1,5 @@
 """Subpackage related to matching between users into groups."""
+
+from lunchheros.match import matching
+
+__all__ = ["matching"]

backend/src/lunchheros/match/_randomize.py

@@ -0,0 +1,54 @@
+import random
+
+from lunchheros.db.dbFetcher import parse_user_id_tolist
+
+
+def _randomize_groups(group_size: int, users: list[str]) -> list[list]:
+    """Randomize the groups of users.
+
+      Makes groups of size ``group_size`` from the list of users ``users``.
+      If the number of users is not a multiple of ``group_size``, the remaining
+      users will be distributed randomly across the groups.
+
+    Args:
+        group_size: size of the groups
+        users: list of users id
+    Returns:
+        A list of lists, each representing a group of users
+    """
+
+    # Shuffle the users randomly
+    random.shuffle(users)
+
+    # Calculate the number of groups needed
+    num_groups = len(users) // group_size
+
+    # Calculate the number of users that will be left alone
+    remaining_users = len(users) % group_size
+
+    # Create the groups
+    groups = []
+    for i in range(num_groups):
+        group = users[i * group_size : (i + 1) * group_size]
+        groups.append(group)
+
+    # Distribute the remaining users across the groups
+    for i in range(remaining_users):
+        groups[i].append(users[num_groups * group_size + i])
+
+    return groups
+
+
+def match(userids):
+
+    # convert userids to list
+    userids = parse_user_id_tolist(userids)
+    # group size
+    groupsize = 5
+    # randomize the groups
+    groups = _randomize_groups(groupsize, userids)
+    # return the groups
+    return groups
+
+
+

backend/src/routes/users/userFunctions.py

@@ -1,13 +1,16 @@
 from supabase_client import supabase_client
 
 
-users_select = "*, company:companies(*)"
+users_select = "*, company:companies(*), users_interests(*, interest(*, category(*))), age_range(*)"
 
 def getUserWithId(userId):
     return supabase_client.table("users").select(users_select).eq("id", userId).single().execute()
 
-from supabase_client import supabase_client
 
 def getAllUsers():
     return  supabase_client.table("users").select(users_select).execute()
-
+
+
+def getAllQueryListData():
+    return  supabase_client.table("waiting_query").select(f"*, user({users_select}), time_range(*), company(*), age_range(*)").execute()
+

backend/tests/match/test_randomize.py

@@ -0,0 +1,40 @@
+from lunchheros.match._randomize import _randomize_groups
+
+import json
+import numpy as np
+
+def test_randomize_groups():
+    """Test randomize groups."""
+    groupsize = 4
+    # make list of 21 users with string id
+    users = [str(i) for i in range(21)]
+    # randomize groups
+    groups = _randomize_groups(groupsize, users)
+    print(groups)
+    # check that all groups are at least 2 users
+    assert all(len(group) >= 2 for group in groups)
+    # check that all groups are at most 4 users
+    assert all(len(group) <= groupsize + groupsize for group in groups)
+
+
+
+
+test_data = '[{"id":"b994511a-4b7c-4d52-bb26-baeffde1df7d"},{"id":"6ea2070c-18e4-4946-83a4-c41584b3eb9a"},{"id":"f60d3486-e6da-45d9-8a68-b39634c2c1c2"},{"id":"89bce073-f759-4290-87dc-87c63a54c553"},{"id":"456732ea-1a2c-42ed-8d9a-4ff83cc9391d"},{"id":"4404a8a1-3429-45f0-b516-2656cfd96643"},{"id":"08e11522-0d52-4014-9c47-d0b4f27b6716"},{"id":"6923fe00-70dd-4bf6-8c7a-7a15c6f8482e"},{"id":"797ee2cb-5c90-4a09-b15d-f4902193b618"},{"id":"aa3e50f0-091a-458f-a62a-caa586b77751"},{"id":"cfc5a3ec-9fdb-4d8a-b380-4737f7e4c5ed"},{"id":"460c2346-459b-4eaa-b821-b6778be53b14"},{"id":"3738d56c-615c-4129-b389-34b75e788580"},{"id":"d50d37d3-f718-40ea-b3b3-c54593b9b048"},{"id":"5e933bdf-29ca-45fb-8f45-3e4c4805ca60"},{"id":"683bcf3c-f855-4164-9057-a5266fb685e3"},{"id":"85e9d50a-a110-44c7-a512-9c6e285fde09"},{"id":"dd1b225d-4320-4aa2-8873-c25ca5307fbf"},{"id":"5423ae0b-0535-443b-89ab-9defd6ee6eda"},{"id":"ad53c0f5-6a93-4904-bfec-22bf7da98ef4"},{"id":"3dc8e3eb-be7c-4e1f-a92d-7ce3b3ee42c3"},{"id":"691888e2-536e-4183-ae98-1d03e643eeb4"},{"id":"a8e24543-0251-41d7-9eff-dbb3b2690d23"},{"id":"da7762a0-5172-4d6f-ab2f-9eb7a953bd9e"},{"id":"a9a3c0b6-df0a-4b39-b613-582703201145"},{"id":"25d411a2-5ac9-445f-a33f-25ece3dde23b"},{"id":"1784f97e-9f3b-4059-a8b4-7c23c3c8897d"},{"id":"7819f098-6772-4aa8-895e-d193199514c8"},{"id":"1df69d95-dbf5-4e68-a102-01974ea7939c"},{"id":"abb3dead-c9e4-4dbd-922a-c7fbe8f448a8"},{"id":"654a36f8-7b36-4ec1-a02e-e45c3673442e"},{"id":"9edeb3f4-ee7e-417e-aaee-d7a40ed0f24a"},{"id":"3f1cec4e-b1ea-4d0f-91d6-f3ff964b2bf1"},{"id":"ce821535-9969-4a93-9b8d-a80a6242f998"},{"id":"f154a6c9-e1b0-4b67-97ab-d65c69ebed69"},{"id":"04b91fd2-78cf-4779-bd7f-0c0bca1c5187"},{"id":"447e63ba-a69b-4b0a-9bfd-6c9d8b19026a"},{"id":"2229ba43-1c63-425e-b157-1368399b2d73"},{"id":"ae4b46d4-984d-44ed-9e3c-cf8823bb0ebf"},{"id":"c9339894-43fb-45e6-b7ba-f527eeb4a3ea"},{"id":"7c047b21-be3c-427e-92c2-82b7fd7459d3"},{"id":"ee3ed5cf-718d-4d34-bfee-b54057870f7e"},{"id":"787dd532-a1c5-4d15-a371-35e6b5e6a169"},{"id":"9bb0689f-4018-40af-9224-1d2595e75801"},{"id":"bb8bd4e1-dce6-46d9-b9b1-20b46a0bfd68"},{"id":"ae93a1ab-921c-4062-95d9-fcd11357a4b6"},{"id":"4837001a-73b0-4b18-bfda-caccee8aef7f"},{"id":"d007dc20-8bae-4c58-b634-ec42e334e0b6"},{"id":"c6e4f2c4-5ed2-4d8f-9075-36b3f77abc37"},{"id":"dc1b7985-aa01-4087-9b35-f6fa6dc6e2b0"},{"id":"00b1fc3d-8e79-4558-af44-ec8d0a6bb3c2"},{"id":"50c17ac7-5e41-4476-b8ba-f59da66885b1"},{"id":"65980da4-879c-401d-9be0-71209c92c62b"},{"id":"bc74a884-7603-4824-be06-6c82091eb24e"},{"id":"a9670953-5906-4190-848c-5a27cdaa12a3"},{"id":"6a23c795-3a9f-4c81-80f8-92ff3088ae36"},{"id":"d2a3fcef-2518-47cd-b038-5bb16599fca9"},{"id":"c549f2c8-862c-4f0a-9302-7784e8ce6608"},{"id":"c7d6a357-368c-454b-a0ef-fcf2da5442b7"},{"id":"dca40f83-27a2-456e-855e-8f5b5df6744e"},{"id":"c93e381b-81a2-485d-9337-5ccb3d33da4c"},{"id":"6bc16283-2b9d-4196-82f1-dafd05805388"},{"id":"541fa596-b1d1-4da2-bb50-26950006c484"},{"id":"7ce5d11c-c44f-4aaf-878e-2e4d14e68339"},{"id":"e77ee698-bdf4-4e62-9dcf-23b10df1bec1"},{"id":"9507a229-592b-4c87-ae04-52e25d22a6bd"},{"id":"fc4ae092-ef73-4cc3-840b-70e9940d33f1"},{"id":"ae29079c-2bfc-4ce3-a924-339b88c59bbf"},{"id":"6e591ada-490e-4174-9ab9-dc4879632c27"},{"id":"e7467801-c20c-4359-b99f-d5d132e51fc7"},{"id":"edc783c5-531f-4f21-a9cc-574451847065"},{"id":"60a7563a-b5b1-4924-936f-9c8deb78cd9d"},{"id":"1cdbc0a9-eba0-4926-b94b-99164328dba3"},{"id":"81be34d5-e71b-456e-a913-21fece836215"},{"id":"48add589-f329-49e9-a151-fae9d44e08f4"},{"id":"dca5539f-c660-488e-99cf-5f9258c6c84e"},{"id":"78888bef-a3e8-4ee1-a54d-c8bd14d30898"},{"id":"aba32f5e-d5a3-4466-bcf6-77eda1de5214"},{"id":"55251bbf-21c0-4f62-a560-ca12f8235342"},{"id":"790de1d5-df0a-4570-943c-f0089d561bc3"},{"id":"90864c9f-612b-457b-8e42-8afb46f3f922"},{"id":"8915ac2c-c740-42df-8fa1-0c1d132bb92e"},{"id":"f48d9896-c80b-4745-abc3-50acfde0a63c"},{"id":"b1434b1c-1a6c-441d-9812-90bdaee1215f"},{"id":"5596fbd9-f33a-4fb0-b844-e6a979a35ac7"},{"id":"bdcf15c4-b164-49ed-a42e-2d6be5fba168"},{"id":"0a1f949e-5d8e-4080-9936-de0f94e26271"},{"id":"57aa5b15-4c93-49c7-8e4c-5c0982353749"},{"id":"8d98509f-464a-4c26-9142-f5903c260a51"},{"id":"5fce6888-9570-4f7b-90c5-be2e9f3f7035"},{"id":"e6940d4a-a287-4dc9-b293-60cabc3b4655"},{"id":"666137b1-ffa8-4612-8e99-08e93691e33b"},{"id":"180d1e45-d8ab-4679-a260-037416c8b9ea"},{"id":"7d11ea4e-f72d-4bf5-a71f-57b373435fd1"},{"id":"81940ce9-34c7-4288-b343-99ea4464493c"},{"id":"3fb80679-0120-4383-8047-e3e8da12d69d"},{"id":"e30ffdaf-2467-42ce-a703-034a478b0417"},{"id":"06cbb2ea-96e0-4896-a425-b098957af37a"},{"id":"cb7e5907-68e7-44bd-95c0-06ccebc075db"},{"id":"bbbbaf3c-1d57-4e11-bf88-9bf92d374b97"},{"id":"bf7c7244-ff86-470c-ba95-07f1e21c9682"},{"id":"4117890c-bdd9-487c-9921-d7a5c9d9b08d"},{"id":"5925b106-1578-45a9-bb30-7fafb37cccdb"},{"id":"00d4050b-614b-4be8-aa16-cab95f6e7dca"},{"id":"4938a261-8083-44d2-955f-c00856f8eb6d"},{"id":"798bdf20-1614-4026-9235-ab10ba228dae"},{"id":"b932c46d-3db7-4cd9-8007-6db3cf2b923b"},{"id":"2e9db169-2094-417e-a775-c8a75790c458"},{"id":"fb16e78e-5ccb-4635-b355-a01f0834389c"},{"id":"9a7ae5aa-b788-49fd-8894-9f899f2a2587"},{"id":"3c3a5aca-6c0e-4e9d-90cb-557fef1256c1"},{"id":"31d574de-869d-4098-be2b-addbfdacebcb"},{"id":"bbaa570b-295b-4bbd-bfd4-02e0b754419e"},{"id":"1e7d409b-03e0-46ef-bdc3-cb55807c10a4"},{"id":"46da386a-c562-4eea-9ae9-c6f87700dbc3"},{"id":"5c5ac49c-a9e9-4fbb-84d1-c5e956f30781"},{"id":"7ddd95e3-3a77-4b61-9d0a-3ffaa1c5a95a"},{"id":"36ad540a-b857-433a-8d07-4087e4d0fe4a"},{"id":"ea88696e-7e9b-49e9-8d65-ace6084425d7"},{"id":"05f6a875-9cc5-4185-8352-0afab880ff4d"},{"id":"6fdb38c9-be3c-44df-9a7a-3f73413842b3"},{"id":"f3313ebc-7b1d-4691-9e65-5ff4e549210a"},{"id":"92cdf84d-485b-4bc6-af29-e9853d20ff5d"},{"id":"878fd4ae-c15c-4325-90f5-4674d04c5455"},{"id":"36e6896d-1814-4348-94f8-a83282d1503b"},{"id":"d6fdf1c7-1333-4382-bac9-4a8a37608b02"},{"id":"37c19c16-e97c-4276-8bf9-97ef7c29d747"}]'
+
+
+def test_randomize_with_real():
+    """Test randomize groups."""
+    # read in the test data
+    # Load the JSON data into a python list of dictionaries
+    data = json.loads(test_data)
+
+    # Extract the id values into a python list
+    ids = [x['id'] for x in data]
+
+    # Convert the python list to a numpy array
+    numpy_array = np.array(ids)
+    print(numpy_array)
+    group_size = 4
+    # randomize groups
+    groups = _randomize_groups(group_size, numpy_array.tolist())
+    print(groups)

docker/Dockerfile

@@ -0,0 +1,58 @@
+# --- Backend Build Stage ---
+FROM python:3.9-slim as backend
+
+WORKDIR /app
+
+# Install Poetry
+RUN pip install poetry
+
+# Copy the Poetry configuration and lock files
+COPY backend/pyproject.toml backend/poetry.lock /app/
+
+# Install dependencies without creating a virtual environment
+RUN poetry config virtualenvs.create false \
+    && poetry install --no-dev --no-interaction --no-ansi
+
+# Install Gunicorn
+RUN pip install gunicorn
+
+# Copy the backend source code into the image
+COPY backend /app/
+
+# --- Frontend Build Stage ---
+FROM node:14 as frontend
+
+WORKDIR /app
+
+# Copy the frontend package configuration files
+COPY frontend/package*.json /app/
+
+# Install dependencies
+RUN npm install
+
+# Copy the frontend source code into the image
+COPY frontend /app/
+
+# Build the frontend
+RUN npm run build
+
+# --- Nginx Stage ---
+FROM nginx:alpine
+
+# Copy the built frontend files to the Nginx server
+COPY --from=frontend /app/build /usr/share/nginx/html
+
+# Copy the backend app to a directory served by Gunicorn
+COPY --from=backend /app /app
+
+# Set up Gunicorn to serve the backend app
+COPY docker/gunicorn.conf /etc/gunicorn/gunicorn.conf
+
+# Set up Nginx to proxy requests to Gunicorn
+COPY docker/nginx.conf /etc/nginx/conf.d/default.conf
+
+# Expose the necessary ports
+EXPOSE 80
+
+# Start Gunicorn and Nginx
+CMD ["sh", "-c", "gunicorn -c /etc/gunicorn/gunicorn.conf app:app & nginx -g 'daemon off;'"]

docker/README.md

@@ -0,0 +1,60 @@
+# LunchHeroes Docker Configuration
+
+This Docker setup is designed to build the Docker image for the LunchHeroes application, which can then be pushed to a Docker registry and deployed on a server.
+
+
+## Preliminary Steps
+
+1. **Building the Docker Image**
+    To build the Docker image, navigate to the directory containing the Dockerfile and run the following command:
+    ```bash
+    docker push lucca93/lunchheroes:latest
+    ```
+
+2. **Pushing Docker Image:**
+   - After building the Docker image, push it to your Docker registry using the following command:
+     ```bash
+     docker push lucca93/lunchheroes:latest
+     ```
+
+
+**Server Hosting:**
+   - The server is hosted on [Flow Swiss](https://my.flow.swiss/).
+
+## File Descriptions
+
+### Dockerfile
+
+The Dockerfile orchestrates the build process for both the frontend and backend of the LunchHeroes application. Here's a brief overview of each stage in the Dockerfile:
+
+- **Backend Build Stage:**
+  - Uses the `python:3.9-slim` base image.
+  - Installs Poetry for dependency management.
+  - Copies and installs the backend dependencies using Poetry.
+  - Installs Gunicorn as the WSGI HTTP server to serve the backend application.
+  - Copies the backend source code into the image.
+
+- **Frontend Build Stage:**
+  - Uses the `node:14` base image.
+  - Copies and installs the frontend dependencies using npm.
+  - Copies the frontend source code into the image.
+  - Builds the frontend assets.
+
+- **Nginx Stage:**
+  - Uses the `nginx:alpine` base image.
+  - Copies the built frontend files to the Nginx server.
+  - Copies the backend app to a directory served by Gunicorn.
+  - Sets up Gunicorn to serve the backend app.
+  - Sets up Nginx to proxy requests to Gunicorn for the `/api` endpoint.
+  - Exposes port 80.
+  - Starts Gunicorn and Nginx.
+
+### gunicorn.conf
+
+This file contains the Gunicorn configuration. Gunicorn is set up to bind to `0.0.0.0:8000` and uses 3 worker processes.
+
+### nginx.conf
+
+This file contains the Nginx configuration. Nginx is set up to serve the static frontend files and to proxy requests to the `/api` endpoint to Gunicorn.
+
+

docker/gunicorn.conf

@@ -0,0 +1,2 @@
+bind = "0.0.0.0:8000"
+workers = 3

docker/nginx.conf

@@ -0,0 +1,15 @@
+server {
+    listen 80;
+
+    location / {
+        root /usr/share/nginx/html;
+        try_files $uri /index.html;
+    }
+
+    location /api {
+        proxy_pass http://localhost:8000;
+        proxy_set_header Host $host;
+        proxy_set_header X-Real-IP $remote_addr;
+        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
+    }
+}

frontend/package.json

@@ -3,6 +3,7 @@
   "version": "0.1.0",
   "private": true,
   "dependencies": {
+    "react-scroll": "^1.8.3",
     "@supabase/supabase-js": "^2.38.4",
     "@testing-library/jest-dom": "^5.17.0",
     "@testing-library/react": "^13.4.0",