# No queues. Just gains.

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PySportBot empowers you to programmatically book fitness classes at any sports center that uses the [Resasports](https://social.resasports.com/en/) booking management software.

## Install
```bash
pip install pysportbot
```

## Quick Start

```python
from pysportbot import SportBot

# Create bot instance, will list available centres if requested
bot = SportBot(log_level='INFO', print_centres=False, time_zone = 'Europe/Madrid')

# Connect to service with email and password as well as the name of the centre
bot.login('email', 'password', 'centre')

# List available activites
bot.activities(limit = 10)

# List bookable slots for an activity on a specific day
bot.daily_slots(activity='YourFavouriteGymClass', day = '2025-01-03', limit = 10)

# Book an activity slot on a specific day and time
bot.book(activity='YourFavouriteGymClass', start_time = '2024-12-30 07:00:00')

# Cancel an activity slot on a specific day and time
bot.cancel(activity='YourFavouriteGymClass', start_time = '2024-12-30 07:00:00')
```

## Advanced usage as service

You can easily run `pysportbot` as a service to manage your bookings automatically with
```bash
python -m pysportbot.service --config config.json
```
The service requires a `json` configuration file that specifies your user data and how you would like to book your classes. Currently, two types of configuration are supported:

### 1. Book an upcoming class now

Let's say you would like to book Yoga next Monday at 18:00:00, then your `config.json` would look like:

```json
{
    "email": "your-email",
    "password": "your-password",
    "center": "your-gym-name",
    "booking_execution": "now",

    "classes": [
        {
            "activity": "Yoga",
            "class_day": "Monday",
            "class_time": "18:00:00",
        }
    ]
}
```
### 2. Book an upcoming class on a specific day and time

Let's say you would like to book Yoga next Monday at 18:00:00, but the execution of the booking should only happen on Friday at 07:30:00 then your `config.json` would look like:

```json
{
    "email": "your-email",
    "password": "your-password",
    "center": "your-gym-name",
    "booking_execution": "Friday 07:30:00",

    "classes": [
        {
            "activity": "Yoga",
            "class_day": "Monday",
            "class_time": "18:00:00",
        }
    ]
}
```

**Note:**
1. Bookings are always scheduled for the following week. For example, if your booking execution is set for Friday at 07:30:00 and your class is on Friday at 18:00:00, the system will schedule the booking for **next Friday** at 18:00:00, not the same day.
2. PySportBot automatically attempts to execute up to *N* bookings in parallel, where *N* corresponds to the number of available CPU cores on your machine.
3. If the number of bookings exceeds the available parallel slots, they will be processed sequentially in the exact order specified in your JSON configuration file.


The service also provides various other options that can be inspected with

```bash
python -m pysportbot.service --help
```
Currently supported options include:

1. `--booking-delay`: sets a global delay in seconds before booking execution [default: 0]
2. `--retry-attempts`: sets the number of retries attempted in case a booking attempt fails [default: 3]
3. `--retry-delay`: sets the delay in seconds between booking retries [default: 5]
4. `--time-zone`: sets the time zone for the service [default: Europe/Madrid]
5. `--log-level`: sets the log-level of the service [default: INFO]
6. `--max-threads`: limits the number of used threads for parallel bookings [default: -1]

## Automating Weekly Bookings with GitHub Actions

While you can use PySportBot as a continuously running service, doing so often becomes cumbersome because it requires a server (or similar machine) that is always online.

Using **[GitHub Actions](https://docs.github.com/en/actions)** is one of the most reliable ways to schedule **automated weekly bookings**. With a simple workflow file, you can ensure your bookings run at a specific time each week — no manual intervention required.

For example, if you have a **Yoga** class on **Monday at 18:00:00**, and you want the **booking** to be executed on **Friday at 07:30:00**, you can automate the process by configuring a **[GitHub Actions workflow](https://docs.github.com/en/actions/writing-workflows)**. Below is a sample workflow file that triggers every **Friday at 06:00 UTC (07:00 CET)**, ensuring there is enough time before the actual booking execution at 07:30:00:

```yml
name: Weekly Booking

on:
  # Runs at 05:00 UTC (07:00 Madrid time during daylight saving time) on Fridays
  # Note: Update to '0 6 * * 5' for winter (standard) time when Madrid shifts to UTC+1
  # GitHub Actions cron expressions are always in UTC and do not support time zones
  # Reference: https://github.com/orgs/community/discussions/13454
  schedule:
    - cron: '0 5 * * 5'

jobs:
  book:
    runs-on: ubuntu-latest

    steps:
      - name: Check out repository
        uses: actions/checkout@v5

      - name: Set up Python 3.12
        uses: actions/setup-python@v6
        with:
          python-version: '3.12'

      - name: Install pysportbot
        run: |
          pip install pysportbot

      - name: Create config file
        run: |
          echo '{
            "email": "your-email",
            "password": "your-password",
            "centre": "your-gym",
            "booking_execution": "Friday 07:30:00",
            "classes": [
              {
                "activity": "Yoga",
                "class_day": "Monday",
                "class_time": "18:00:00"
              }
            ]
          }' > config.json

      - name: Run pysportbot
        run: |
          python -m pysportbot.service --config config.json --log-level INFO --booking-delay 1 --retry-attempts 3 --retry-delay 5
```
**Note:** Make sure the workflow starts early enough — before your booking execution time (e.g., 07:30 CET) — to allow for potential delays in job startup or execution.


## LICENSE

pysportbot is free of use and open-source. All versions are
published under the [MIT License](https://github.com/jbeirer/resasports-bot/blob/main/LICENSE).
