├── .dockerignore ├── .env.example ├── .github └── workflows │ └── release.yml ├── .gitignore ├── .python-version ├── Dockerfile ├── LICENSE.txt ├── README.md ├── docker-compose.dev.yml ├── docker-compose.yml ├── pyproject.toml ├── supervisord.conf ├── uv.lock └── vfd ├── __init__.py ├── dashboard.py ├── db.py ├── scrapper.py └── utils.py /.dockerignore: -------------------------------------------------------------------------------- 1 | # .env files 2 | .env 3 | .env.example 4 | 5 | # Project files 6 | .git 7 | .gitignore 8 | .idea 9 | 10 | # Data 11 | data/ 12 | 13 | # Python env 14 | .venv/ 15 | -------------------------------------------------------------------------------- /.env.example: -------------------------------------------------------------------------------- 1 | ######################### 2 | # General configuration # 3 | ######################### 4 | 5 | # Database path (must be an absolute path) 6 | VFD_DATABASE=/app/data/vfd.sqlite 7 | 8 | 9 | ########################## 10 | # Scrapper configuration # 11 | ########################## 12 | 13 | # Comma separated list of start dates (in YYYY-MM-DD format) 14 | VFD_SCRAPPER_START_DATES=2025-03-01 15 | 16 | # Comma separated list of end dates (in YYYY-MM-DD format) 17 | VFD_SCRAPPER_END_DATES=2025-03-10 18 | 19 | # Comma separated list of departure airports (in three-letter code format) 20 | VFD_SCRAPPER_DEPARTURE_AIRPORTS=JFK 21 | 22 | # Comma separated list of arrival airports (in three-letter code format) 23 | VFD_SCRAPPER_ARRIVAL_AIRPORTS=NRT 24 | 25 | # (optional) Interval in seconds between each request to the API to avoid being banned. Default is 60 seconds. Set it to 0 to disable the interval. 26 | VFD_SCRAPPER_INTERVAL=60 27 | 28 | # Apprise notification URLs (comma separated) (for more info, check https://github.com/caronc/apprise?tab=readme-ov-file#supported-notifications) 29 | VFD_SCRAPPER_NOTIFICATION_URLS= 30 | 31 | # Enable verbose logging 32 | VFD_SCRAPPER_VERBOSE=True 33 | 34 | ########################### 35 | # Dashboard configuration # 36 | ########################### 37 | 38 | # Host to bind the dashboard 39 | VFD_DASHBOARD_HOST=0.0.0.0 40 | 41 | # Port to bind the dashboard 42 | VFD_DASHBOARD_PORT=4242 43 | -------------------------------------------------------------------------------- /.github/workflows/release.yml: -------------------------------------------------------------------------------- 1 | name: Release 2 | 3 | on: 4 | workflow_dispatch: 5 | inputs: 6 | bump-type: 7 | description: 'Bump type' 8 | required: true 9 | default: 'patch' 10 | type: choice 11 | options: 12 | - major 13 | - minor 14 | - patch 15 | 16 | jobs: 17 | build-and-push-image: 18 | runs-on: ubuntu-latest 19 | permissions: 20 | contents: write 21 | packages: write 22 | steps: 23 | - name: Check out the repo 24 | uses: actions/checkout@v3 25 | 26 | - name: Log in to GHCR 27 | uses: docker/login-action@f4ef78c080cd8ba55a85445d5b36e214a81df20a 28 | with: 29 | registry: ghcr.io 30 | username: ${{ github.actor }} 31 | password: ${{ secrets.GITHUB_TOKEN }} 32 | 33 | - name: Bump version 34 | id: bump 35 | uses: callowayproject/bump-my-version@master 36 | env: 37 | BUMPVERSION_TAG: "true" 38 | with: 39 | args: ${{ inputs.bump-type }} 40 | github-token: ${{ secrets.GITHUB_TOKEN }} 41 | 42 | - name: Build Docker image 43 | run: docker build -t ghcr.io/kiinami/vfd:${{ steps.bump.outputs.current-version }} -t ghcr.io/kiinami/vfd:latest . 44 | env: 45 | DOCKER_CLI_EXPERIMENTAL: enabled 46 | 47 | - name: Push Docker image to Github Container Registry 48 | run: docker push ghcr.io/kiinami/vfd 49 | env: 50 | DOCKER_CLI_EXPERIMENTAL: enabled 51 | 52 | - name: Release 53 | uses: softprops/action-gh-release@v2 54 | with: 55 | tag_name: v${{ steps.bump.outputs.current-version }} 56 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Python-generated files 2 | __pycache__/ 3 | *.py[oc] 4 | build/ 5 | dist/ 6 | wheels/ 7 | *.egg-info 8 | 9 | # Virtual environments 10 | .venv 11 | 12 | # .idea 13 | .idea/ 14 | 15 | # environment 16 | .env 17 | data/ 18 | -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.12 2 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # Use a Python image with uv pre-installed 2 | FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim 3 | 4 | # Install system dependencies 5 | RUN apt-get update && apt-get install -y --no-install-recommends \ 6 | supervisor git \ 7 | && rm -rf /var/lib/apt/lists/* 8 | 9 | # Install playwright browser and dependencies 10 | RUN --mount=type=cache,target=/root/.cache/uv \ 11 | uvx playwright install chromium --with-deps --only-shell 12 | 13 | # Install the project into `/app` 14 | WORKDIR /app 15 | 16 | # Enable bytecode compilation 17 | ENV UV_COMPILE_BYTECODE=1 18 | 19 | # Copy from the cache instead of linking since it's a mounted volume 20 | ENV UV_LINK_MODE=copy 21 | 22 | # Install the project's dependencies using the lockfile and settings 23 | RUN --mount=type=cache,target=/root/.cache/uv \ 24 | --mount=type=bind,source=uv.lock,target=uv.lock \ 25 | --mount=type=bind,source=pyproject.toml,target=pyproject.toml \ 26 | uv sync --frozen --no-install-project --no-dev 27 | 28 | # Then, add the rest of the project source code and install it 29 | # Installing separately from its dependencies allows optimal layer caching 30 | ADD . /app 31 | RUN --mount=type=cache,target=/root/.cache/uv \ 32 | uv sync --frozen --no-dev 33 | 34 | # Place executables in the environment at the front of the path 35 | ENV PATH="/app/.venv/bin:$PATH" 36 | 37 | # Reset the entrypoint, don't invoke `uv` 38 | ENTRYPOINT [] 39 | 40 | # Run the entrypoint command 41 | CMD ["/usr/bin/supervisord", "-c", "/app/supervisord.conf"] 42 | -------------------------------------------------------------------------------- /LICENSE.txt: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) [year] [fullname] 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |
2 | 3 |

4 | ✈️ 👁️ 5 | 6 | VFD 7 |

8 | 9 |
10 | 11 | VFD is a small service that tracks the price of flights on Google Flights, stores the historical data, allows you to 12 | view it in a simple web interface, and sends notifications when there is a new best price. 13 | 14 | The project uses the really nice [fast-flights](https://github.com/AWeirdDev/flights) library to scrape the data from 15 | Google Flights, the [Streamlit](https://streamlit.io/) library to create the web interface, 16 | and [apprise](https://github.com/caronc/apprise) to send notifications. 17 | 18 | > [!warning] 19 | > This project is still in its early stages. There are numerous bugs and general inefficiencies everywhere. There are also a lot of features missing. If you have any suggestions, encounter any bugs or have any comments, feel free to open an issue or a pull request! 20 | 21 | ## Features 22 | 23 | - Continuous scraping of flight prices from Google Flights (currently only in dollars) 24 | - Possibility to set a range of dates and cities to depart and arrive from 25 | - Storing of historical data by hour 26 | - Simple web interface to view the data 27 | - Notifications when a new best price is found 28 | 29 | ## Docker installation 30 | 31 | Installing the project with Docker is the easiest way to get started. You will need to have Docker and Docker Compose 32 | installed on your system. 33 | 34 | 1. Get the `docker-compose.yml` file 35 | from [here](https://raw.githubusercontent.com/kiinami/vfd/refs/heads/main/docker-compose.yml) 36 | 2. Get the `.env` file from [here](https://raw.githubusercontent.com/kiinami/vfd/refs/heads/main/.env.example) and fill 37 | in the necessary information 38 | 3. Run `docker compose up -d` to start VFD 39 | 4. Open `http://localhost:4242` in your browser to view the web interface (although you won't see much until a few 40 | hours' worth of data has been collected) 41 | 42 | ## Local installation 43 | 44 | 1. This project uses [uv](https://docs.astral.sh/uv/) to manage the virtual environment, so you will need to install it first. Refer to the documentation on how to install it on your system. 45 | 2. Clone the repository 46 | 3. Copy the `.env.example` file to `.env` and fill in the necessary information 47 | 4. Run `uv sync` to install the dependencies and set up the project 48 | 5. To run the scrapper, run `uv run scrapper`. You can also run `uv run scrapper --help` to see the available options, 49 | including the possibility to run the scrapper once instead of continuously. 50 | 6. To run the web interface, run `uv run dashboard` 51 | 52 | ## Configuration 53 | 54 | The configuration is done through the `.env` file. Here is a list of the available options: 55 | 56 | | Variable | Description | Default | Required | 57 | |-----------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------|----------| 58 | | `VFD_DATABASE` | The path to the SQLite database file | - | Yes | 59 | | `VFD_SCRAPPER_START_DATES` | The possible dates to start the trip | - | Yes | 60 | | `VFD_SCRAPPER_END_DATES` | The possible dates to end the trip | - | Yes | 61 | | `VFD_SCRAPPER_END_DATES` | The possible dates to end the trip | - | Yes | 62 | | `VFD_SCRAPPER_DEPARTURE_AIRPORTS` | The possible source airports | - | Yes | 63 | | `VFD_SCRAPPER_ARRIVAL_AIRPORTS` | The possible destination airports | - | Yes | 64 | | `VFD_SCRAPPER_INTERVAL` | The interval in seconds between each query | `60` | No | 65 | | `VFD_SCRAPPER_NOTIFICATION_URLS` | Apprise notification URLs (comma separated) (for more info, check [the Apprise documentation](https://github.com/caronc/apprise?tab=readme-ov-file#supported-notifications)) | - | Yes | 66 | | `VFD_SCRAPPER_VERBOSE` | Whether to print debug information for the scrapper | `False` | No | 67 | | `VFD_DASHBOARD_HOST` | The host to run the dashboard on | `0.0.0.0` | No | 68 | | `VFD_DASHBOARD_PORT` | The port to run the dashboard on | `4242` | No | 69 | 70 | ## To-do 71 | 72 | - [x] Dockerize the project with a cron job to run the scrapper regularly 73 | - [x] Job scheduling 74 | - [x] `Dockerfile` and `docker-compose.yml` 75 | - [x] Handling of `.env` file 76 | - [x] `.dockerignore` 77 | - [x] Image building and publishing with GitHub Actions 78 | - [x] Add a small web interface to view the data 79 | - [x] Add a way to send notifications when the price of a flight drops below the last best price 80 | - [x] Stage queries in batches to avoid problems with Google 81 | - [ ] Configurable resolution of the data (currently only by hour) 82 | - [ ] Add support for proxies to avoid being blocked by Google 83 | - [ ] Add authentication support with [streamlit-authenticator](https://github.com/mkhorasani/Streamlit-Authenticator) 84 | - [ ] More granularity in start and end ranges 85 | - [ ] Add support to track different trips at the same time 86 | 87 | ## FAQ 88 | 89 | ### Why this thing? 90 | 91 | I want to go on a trip with my friends to a faraway land, the dates are more or less set, we could arrive and depart 92 | from a set of cities, and I want to get the cheapest flight combination possible. 93 | 94 | I could do this manually, but it would take a great deal of time and effort (96 different combinations to check every 95 | day), so I decided to automate it. 96 | 97 | ### What does VFD stand for? 98 | 99 | Verifiable Flight Data, of course. What else could VFD stand for? 100 | 101 | ## Contributing 102 | 103 | If you have any suggestions, feel free to open an issue or a pull request. The local installation instructions should 104 | suffice to get you started. 105 | 106 | ## License 107 | 108 | This project is licensed under the MIT License - see the [LICENSE](LICENSE.txt) file for details. 109 | -------------------------------------------------------------------------------- /docker-compose.dev.yml: -------------------------------------------------------------------------------- 1 | services: 2 | scrapper: 3 | build: . 4 | container_name: vfd-scrapper 5 | restart: unless-stopped 6 | volumes: 7 | - ./data:/app/data 8 | ports: 9 | - "4242:4242" 10 | env_file: ./.env 11 | -------------------------------------------------------------------------------- /docker-compose.yml: -------------------------------------------------------------------------------- 1 | services: 2 | scrapper: 3 | image: ghcr.io/kiinami/vfd:latest 4 | container_name: vfd-scrapper 5 | restart: unless-stopped 6 | volumes: 7 | - ./data:/app/data 8 | ports: 9 | - "4242:4242" 10 | env_file: ./.env 11 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "vfd" 3 | version = "1.1.0" 4 | description = "Verifiable Flight Data" 5 | readme = "README.md" 6 | requires-python = ">=3.12" 7 | dependencies = [ 8 | "apprise>=1.9.2", 9 | "bump-my-version>=0.32.2", 10 | "dateparser>=1.2.1", 11 | "dotenv>=0.9.9", 12 | "fast-flights[local]", 13 | "loguru>=0.7.3", 14 | "peewee>=3.17.9", 15 | "polars>=1.23.0", 16 | "rich>=13.9.4", 17 | "streamlit>=1.42.2", 18 | "typer>=0.15.1", 19 | ] 20 | 21 | [build-system] 22 | requires = ["hatchling"] 23 | build-backend = "hatchling.build" 24 | 25 | [project.scripts] 26 | scrapper = "vfd.scrapper:main" 27 | dashboard = "vfd.dashboard:entrypoint" 28 | 29 | [tool.bumpversion] 30 | current_version = "1.1.0" 31 | parse = "(?P\\d+)\\.(?P\\d+)\\.(?P\\d+)" 32 | serialize = ["{major}.{minor}.{patch}"] 33 | search = 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1281 | source = { registry = "https://pypi.org/simple" } 1282 | sdist = { url = "https://files.pythonhosted.org/packages/b3/8f/705086c9d734d3b663af0e9bb3d4de6578d08f46b1b101c2442fd9aecaa2/win32_setctime-1.2.0.tar.gz", hash = "sha256:ae1fdf948f5640aae05c511ade119313fb6a30d7eabe25fef9764dca5873c4c0", size = 4867 } 1283 | wheels = [ 1284 | { url = "https://files.pythonhosted.org/packages/e1/07/c6fe3ad3e685340704d314d765b7912993bcb8dc198f0e7a89382d37974b/win32_setctime-1.2.0-py3-none-any.whl", hash = "sha256:95d644c4e708aba81dc3704a116d8cbc974d70b3bdb8be1d150e36be6e9d1390", size = 4083 }, 1285 | ] 1286 | -------------------------------------------------------------------------------- /vfd/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/kiinami/vfd/892806d4f8082caacee395a213f571ea701149c7/vfd/__init__.py -------------------------------------------------------------------------------- /vfd/dashboard.py: -------------------------------------------------------------------------------- 1 | import os 2 | import sys 3 | 4 | import polars as pl 5 | import streamlit as st 6 | from dateutil.relativedelta import relativedelta 7 | from dotenv import load_dotenv 8 | from loguru import logger 9 | from streamlit.web import cli 10 | 11 | from vfd.db import get_best_rn, Flight, get_best_ever, get_best_last_24h, get_all_flights_in_polars 12 | from vfd.utils import now_to_the_hour as now, logger_format 13 | 14 | logger.remove() 15 | logger.add(sys.stderr, level="INFO", format=logger_format) 16 | 17 | 18 | def render_flight(flight: Flight): 19 | if flight.scrapped == now(): 20 | st.success("Most likely still available!") 21 | elif flight.scrapped > now() - relativedelta(hours=24): 22 | st.warning("Might still be available") 23 | else: 24 | st.error("Most likely not available anymore") 25 | st.title(f'{flight.departure_airport} -> {flight.arrival_airport} for ${flight.price}') 26 | st.write(f'Departs **{flight.departure.date()}** at **{flight.departure.strftime("%H:%M")}**') 27 | st.write( 28 | f'Arrives **{flight.arrival.date()}** at **{flight.arrival.strftime("%H:%M")}** ({flight.arrival_time_ahead})') 29 | st.write(f'Operated by **{flight.name}**') 30 | st.caption(f'Scrapped {flight.scrapped.strftime("%Y-%m-%d %H:%M")}') 31 | 32 | 33 | def sidebar(): 34 | with st.sidebar: 35 | st.title('Best flights') 36 | 37 | st.header(':airplane_departure: Outbound') 38 | 39 | best_outbound_rn = get_best_rn("outbound", now()) 40 | if best_outbound_rn: 41 | with st.popover(f"Right now for ${best_outbound_rn.price}"): 42 | render_flight(best_outbound_rn) 43 | else: 44 | with st.popover(f"Right now unknown"): 45 | st.write("We don't have any data for the best outbound flight right now.") 46 | 47 | best_outbound_last_24h = get_best_last_24h("outbound") 48 | if best_outbound_last_24h: 49 | with st.popover(f"In the last 24 hours for ${best_outbound_last_24h.price}"): 50 | render_flight(best_outbound_last_24h) 51 | else: 52 | with st.popover(f"In the last 24 hours unknown"): 53 | st.write("We don't have any outbound flight data for the last 24 hours yet!") 54 | 55 | best_outbound_ever = get_best_ever("outbound") 56 | if best_outbound_ever: 57 | with st.popover(f"Best ever for ${best_outbound_ever.price}"): 58 | render_flight(best_outbound_ever) 59 | else: 60 | with st.popover(f"Best ever unknown"): 61 | st.write("We don't have any data for the best outbound flight ever.") 62 | 63 | st.header(':airplane_arriving: Inbound') 64 | 65 | best_inbound_rn = get_best_rn("inbound", now()) 66 | if best_inbound_rn: 67 | with st.popover(f"Right now for ${best_inbound_rn.price}"): 68 | render_flight(best_inbound_rn) 69 | else: 70 | with st.popover(f"Right now unknown"): 71 | st.write("We don't have any data for the best inbound flight right now.") 72 | 73 | best_inbound_last_24h = get_best_last_24h("inbound") 74 | if best_inbound_last_24h: 75 | with st.popover(f"In the last 24 hours for ${best_inbound_last_24h.price}"): 76 | render_flight(best_inbound_last_24h) 77 | else: 78 | with st.popover(f"In the last 24 hours unknown"): 79 | st.write("We don't have any inbound flight data for the last 24 hours yet!") 80 | 81 | best_inbound_ever = get_best_ever("inbound") 82 | if best_inbound_ever: 83 | with st.popover(f"Best ever for ${best_inbound_ever.price}"): 84 | render_flight(best_inbound_ever) 85 | else: 86 | with st.popover(f"Best ever unknown"): 87 | st.write("We don't have any data for the best inbound flight ever.") 88 | 89 | 90 | def content(): 91 | st.title(':airplane: :eye: Verifiable Flight Data') 92 | 93 | data = get_all_flights_in_polars() 94 | st.header('Price history') 95 | # create a dataframe that for each "scrapped" value has the outbound price and the inbound price 96 | grouped = data.group_by("scrapped").agg( 97 | outbound=pl.col("price").filter(pl.col("type") == "outbound").min(), 98 | inbound=pl.col("price").filter(pl.col("type") == "inbound").min(), 99 | ) 100 | st.line_chart( 101 | grouped, 102 | x="scrapped", 103 | y=["outbound", "inbound"], 104 | color=["#00ff00", "#0000ff"], 105 | x_label="Scrapped time", 106 | y_label="Price", 107 | ) 108 | 109 | 110 | def main(): 111 | st.set_page_config(page_title="✈️ 👁️ Verifiable Flight Data", page_icon="✈️", layout="wide") 112 | sidebar() 113 | content() 114 | 115 | 116 | def entrypoint(): 117 | load_dotenv() 118 | logger.info( 119 | "Dashboard started at http://" + os.getenv("VFD_DASHBOARD_HOST") + ":" + os.getenv("VFD_DASHBOARD_PORT")) 120 | cli.main_run([ 121 | "--server.port=" + os.getenv("VFD_DASHBOARD_PORT", "4242"), 122 | "--server.address=" + os.getenv("VFD_DASHBOARD_HOST", "0.0.0.0"), 123 | "--client.toolbarMode=viewer", 124 | "--server.headless=true", 125 | "--browser.gatherUsageStats=false", 126 | "--theme.font=monospace", 127 | "--theme.base=dark", 128 | __file__, 129 | ]) 130 | 131 | if __name__ == "__main__": 132 | main() 133 | -------------------------------------------------------------------------------- /vfd/db.py: -------------------------------------------------------------------------------- 1 | import os 2 | import sys 3 | from datetime import datetime 4 | 5 | import polars as pl 6 | from dateutil.relativedelta import relativedelta 7 | from dotenv import load_dotenv 8 | from loguru import logger 9 | from peewee import * 10 | 11 | from vfd.utils import now_to_the_hour as now, logger_format 12 | 13 | logger.remove() 14 | logger.add(sys.stderr, level="INFO", format=logger_format) 15 | 16 | load_dotenv() 17 | db = SqliteDatabase(os.getenv("VFD_DATABASE")) 18 | 19 | 20 | class Flight(Model): 21 | scrapped = DateTimeField() 22 | type = CharField() 23 | name = CharField() 24 | departure_airport = CharField() 25 | arrival_airport = CharField() 26 | departure = DateTimeField() 27 | arrival = DateTimeField() 28 | arrival_time_ahead = CharField() 29 | price = IntegerField() 30 | 31 | class Meta: 32 | database = db 33 | indexes = ( 34 | (("scrapped", "type"), True), 35 | ) 36 | 37 | 38 | def init_db(): 39 | try: 40 | db.connect() 41 | db.create_tables([Flight]) 42 | db.close() 43 | logger.debug("Database initialized") 44 | except OperationalError: 45 | logger.error( 46 | f"Database could not be opened, are you sure the path '{os.getenv("VFD_DATABASE")}' is correct and absolute?") 47 | sys.exit(1) 48 | 49 | 50 | def get_best_rn(typ: str, scrapped: datetime): 51 | try: 52 | return Flight.get((Flight.type == typ) & (Flight.scrapped == scrapped)) 53 | except DoesNotExist: 54 | return None 55 | 56 | 57 | def get_best_last_24h(typ: str): 58 | try: 59 | return Flight.select().where( 60 | (Flight.type == typ) & (Flight.scrapped > now() - relativedelta(hours=24))).order_by( 61 | Flight.price).first() 62 | except DoesNotExist: 63 | return None 64 | 65 | 66 | def get_best_ever(typ: str) -> Flight | None: 67 | try: 68 | return Flight.select().where(Flight.type == typ).order_by(Flight.price).first() 69 | except DoesNotExist: 70 | return None 71 | 72 | def save_new_best_flight(best_flight: Flight, old_best_flight: Flight | None): 73 | if old_best_flight: 74 | old_best_flight.delete_instance() 75 | best_flight.save() 76 | 77 | 78 | def get_all_flights_in_polars(): 79 | data_dicts = list(Flight.select().dicts()) 80 | return pl.DataFrame(data_dicts) 81 | -------------------------------------------------------------------------------- /vfd/scrapper.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | from typing import Any, Generator 4 | 5 | import typer 6 | from apprise import Apprise 7 | from dateparser import parse as dateparse 8 | from dotenv import load_dotenv 9 | from fast_flights import FlightData, Passengers, get_flights 10 | from loguru import logger 11 | from rich import print 12 | from typing_extensions import Annotated 13 | 14 | from vfd.db import Flight, init_db, get_best_rn, save_new_best_flight, get_best_ever 15 | from vfd.utils import now_to_the_hour, logger_format 16 | 17 | 18 | def scrape_flights(date: str, departure_airport: str, arrival_airport: str, typ: str) -> Flight | None: 19 | try: 20 | result = get_flights( 21 | flight_data=[ 22 | FlightData(date=date, from_airport=departure_airport, to_airport=arrival_airport) 23 | ], 24 | trip="one-way", 25 | seat="economy", 26 | passengers=Passengers(adults=1), 27 | fetch_mode="local", 28 | ) 29 | except AssertionError: 30 | logger.debug(f"No flights found from {departure_airport} to {arrival_airport} on {date}") 31 | return None 32 | best_flight = sorted( 33 | [flight for flight in result.flights if 34 | flight.price != "Price unavailable" and flight.price != 0 and flight.price != "0"], 35 | key=lambda x: int(x.price[1:]) 36 | )[0] 37 | return Flight( 38 | scrapped=now_to_the_hour(), 39 | type=typ, 40 | name=best_flight.name, 41 | departure_airport=departure_airport, 42 | arrival_airport=arrival_airport, 43 | departure=dateparse(best_flight.departure), 44 | arrival=dateparse(best_flight.arrival), 45 | arrival_time_ahead=best_flight.arrival_time_ahead, 46 | price=int(best_flight.price[1:]), 47 | ) 48 | 49 | def combinations(start_dates: str, end_dates: str, departure_airports: str, arrival_airports: str) -> list[ 50 | tuple[str, str, str, str]]: 51 | start_dates = [sd.strip() for sd in start_dates.split(",")] 52 | end_dates = [ed.strip() for ed in end_dates.split(",")] 53 | departure_airports = [da.strip() for da in departure_airports.split(",")] 54 | arrival_airports = [aa.strip() for aa in arrival_airports.split(",")] 55 | 56 | combinations = [] 57 | 58 | for sdate in start_dates: 59 | for darp in departure_airports: 60 | for aarp in arrival_airports: 61 | combinations.append((sdate, darp, aarp, "outbound")) 62 | outbound_len = len(combinations) 63 | logger.debug(f"Computed {outbound_len} outbound combinations") 64 | 65 | for edate in end_dates: 66 | for darp in departure_airports: 67 | for aarp in arrival_airports: 68 | combinations.append((edate, aarp, darp, "inbound")) 69 | inbound_len = len(combinations) - outbound_len 70 | logger.debug(f"Computed {inbound_len} inbound combinations") 71 | 72 | return combinations 73 | 74 | 75 | def combgen(start_dates: str, end_dates: str, departure_airports: str, arrival_airports: str) -> Generator[ 76 | tuple[str, str, str, str], Any, Any]: 77 | combs = combinations(start_dates, end_dates, departure_airports, arrival_airports) 78 | while True: 79 | for comb in combs: 80 | yield comb 81 | 82 | 83 | def scrapper(start_dates: str, end_dates: str, departure_airports: str, arrival_airports: str, interval: int): 84 | for date, darp, aarp, typ in combgen(start_dates, end_dates, departure_airports, arrival_airports): 85 | logger.debug(f"Getting flights from {darp} to {aarp} on {date}") 86 | 87 | best_flight_scrapped = scrape_flights(date, darp, aarp, typ) 88 | 89 | if best_flight_scrapped: 90 | best_flight_saved_rn = get_best_rn(typ, now_to_the_hour()) 91 | if best_flight_saved_rn is None or best_flight_scrapped.price < best_flight_saved_rn.price: 92 | save_new_best_flight(best_flight_scrapped, best_flight_saved_rn) 93 | logger.debug( 94 | f"Saved new best flight from {darp} to {aarp} on {date} for scrapped hour {best_flight_scrapped.scrapped}") 95 | 96 | best_flight_saved_ever = get_best_ever(typ) 97 | 98 | if best_flight_scrapped == best_flight_saved_ever: 99 | logger.log("NOTIFY", 100 | f"New best {best_flight_saved_ever.type} flight found: from {darp} to {aarp} on {date} for ${best_flight_saved_ever.price}") 101 | 102 | if interval > 0: 103 | logger.debug(f"Waiting {interval} seconds before next request") 104 | time.sleep(interval) 105 | 106 | 107 | def run_once_and_print(start_dates: str, end_dates: str, departure_airports: str, arrival_airports: str): 108 | for date, darp, aarp, typ in combgen(start_dates, end_dates, departure_airports, arrival_airports): 109 | logger.debug(f"Getting flights from {darp} to {aarp} on {date}") 110 | best_flight_rn = scrape_flights(date, darp, aarp, typ) 111 | print(best_flight_rn) 112 | 113 | def entrypoint( 114 | start_dates: Annotated[str, typer.Option(..., help="Comma separated list of start dates (in YYYY-MM-DD format)", envvar="VFD_SCRAPPER_START_DATES"),], 115 | end_dates: Annotated[str, typer.Option(..., help="Comma separated list of end dates (in YYYY-MM-DD format)", envvar="VFD_SCRAPPER_END_DATES"),], 116 | departure_airports: Annotated[str, typer.Option(..., help="Comma separated list of departure airports (in three-letter code format)", envvar="VFD_SCRAPPER_DEPARTURE_AIRPORTS"),], 117 | arrival_airports: Annotated[str, typer.Option(..., help="Comma separated list of arrival airports (in three-letter code format)", envvar="VFD_SCRAPPER_ARRIVAL_AIRPORTS"),], 118 | interval: Annotated[ 119 | int, typer.Option("--interval", "-i", help="Interval in seconds between each request to the API", 120 | envvar="VFD_SCRAPPER_INTERVAL")] = 60, 121 | notification_urls: Annotated[str, typer.Option("--notification-urls", "-n", 122 | help="Comma separated list of Apprise URLs to notify when a new best flight is found", 123 | envvar="VFD_SCRAPPER_NOTIFICATION_URLS")] = "", 124 | run_once: Annotated[bool, typer.Option("--run-once", "-r", help="Run the scrapper once, print the data and exit")] = False, 125 | verbose: Annotated[bool, typer.Option("--verbose", "-v", help="Enable verbose logging", envvar="VFD_SCRAPPER_VERBOSE")] = False, 126 | ): 127 | logger.remove() 128 | 129 | if verbose: 130 | logger.add(sys.stderr, level="DEBUG", format=logger_format) 131 | else: 132 | logger.add(sys.stderr, level="INFO", format=logger_format) 133 | 134 | logger.level("NOTIFY", no=55) 135 | if notification_urls: 136 | notification_urls = [url.strip() for url in notification_urls.split(",")] 137 | notifier = Apprise() 138 | notifier.add(notification_urls) 139 | 140 | logger.add(notifier.notify, level="NOTIFY", filter={"apprise": False}, format="{message}") 141 | 142 | logger.info(f"Notifier configured, added {len(notification_urls)} destinations") 143 | 144 | if run_once: 145 | logger.debug("Running scrapper once") 146 | run_once_and_print(start_dates, end_dates, departure_airports, arrival_airports) 147 | else: 148 | scrapper(start_dates, end_dates, departure_airports, arrival_airports, interval) 149 | 150 | def main(): 151 | load_dotenv() 152 | init_db() 153 | typer.run(entrypoint) 154 | 155 | if __name__ == "__main__": 156 | main() 157 | -------------------------------------------------------------------------------- /vfd/utils.py: -------------------------------------------------------------------------------- 1 | from datetime import datetime 2 | 3 | logger_format = "{time:YYYY-MM-DD HH:mm:ss} | {level:<7} | {name:<15} | {message}" 4 | 5 | def now_to_the_hour() -> datetime: 6 | return datetime.now().replace(minute=0, second=0, microsecond=0, tzinfo=None) 7 | 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