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15 Commits

Author SHA1 Message Date
c53ba05874 MS - Europe 2026-03-25 22:52:28 +01:00
54e3218779 Fix score of leagues 2026-03-25 21:49:57 +01:00
Chlupaty
1aeca0c420 Debugged ticket 8 for image_classifier.py 2026-03-25 21:15:51 +01:00
2a3d7ed230 i forgor 2026-03-25 21:15:37 +01:00
dde5b572fb Api + frontend 2026-03-25 20:55:58 +01:00
7e88e91077 Api + frontend 2026-03-25 20:55:52 +01:00
569b8ee4f8 Fuzzy match leagues 2026-03-25 20:25:34 +01:00
5de0d57612 Stěhování národů 2026-03-25 19:47:10 +01:00
e3b7879eb2 We are no longer on gitlab 2026-03-25 19:40:34 +01:00
d5211572a5 Logging 2026-03-25 19:04:17 +01:00
Chlupaty
ebdf4f1572 Added TBD to tickety.md 2026-03-25 18:32:35 +01:00
Chlupaty
60bbc09ccc Image classifier debugged line separation and block separation 2026-03-22 15:58:30 +01:00
8edd016e39 Strip newline 2026-03-22 14:45:39 +01:00
Chlupaty
fd3a8f4955 Image classifier debugging block separation and line separation 2026-03-22 14:39:35 +01:00
Chlupaty
346318177d Classifier work 2026-03-22 14:39:35 +01:00
54 changed files with 2840 additions and 413 deletions

2
.gitignore vendored
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@@ -1,5 +1,5 @@
.idea/
data/
beaky-backend/data/
report.xml
# Byte-compiled / optimized / DLL files

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@@ -1,40 +0,0 @@
image: python:3.12-slim
cache:
paths:
- .cache/pip
- venv/
variables:
PIP_CACHE_DIR: "$CI_PROJECT_DIR/.cache/pip"
before_script:
- python -V
- python -m venv venv
- source venv/bin/activate
- pip install --upgrade pip
- pip install ruff mypy pytest
- pip install .
stages:
- lint
- test
run_ruff:
stage: lint
script:
- ruff check .
run_mypy:
stage: lint
script:
- mypy src
run_pytest:
stage: test
script:
- pytest --junit-xml=report.xml
artifacts:
when: always
reports:
junit: report.xml

98
CLAUDE.md Normal file
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@@ -0,0 +1,98 @@
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## What This Project Does
Beaky is a CLI tool for verifying the truthfulness of sports betting tickets. It reads ticket URLs from an Excel file, classifies the bets on each ticket (via web scraping or OCR), then resolves each bet against a football statistics API to determine if the ticket is genuine.
## Commands
```bash
# Install (with dev dependencies)
pip install -e ".[dev]"
# Install Playwright browser (required for link classifier and screenshotter)
playwright install chromium
# Run the CLI
beaky <mode> [--config config/application.yml] [--id <ticket_id>] [--classifier {link,img,both}] [--dump]
# Modes:
# screen - screenshot all ticket URLs to data/screenshots/<id>.png
# parse - print all links loaded from Excel
# compare - classify tickets and print bet comparison table
# resolve - classify via link classifier, then resolve bets against football API
# Run the REST API (default: http://0.0.0.0:8000)
beaky-api
# Run tests
pytest
# Lint
ruff check .
# Format
ruff format .
```
## Architecture
Data flows through four stages:
1. **Scanner** (`scanner/scanner.py`) — Reads `data/odkazy.xlsx` and produces `Link` objects (id, url, date).
2. **Classifiers** — Two independent classifiers both produce a `Ticket` (list of typed `Bet` objects):
- **Link classifier** (`link_classifier/classifier.py`) — Launches a headless Chromium browser via Playwright, navigates to the ticket URL (a Czech Fortuna betting site), and parses the DOM using CSS selectors to extract bet details.
- **Image classifier** (`image_classifier/classifier.py`) — Runs pytesseract OCR on screenshots in `data/screenshots/`, then uses regex to parse the raw text into bets. Block segmentation is driven by date-start and sport-prefix end triggers.
3. **Resolver** (`resolvers/resolver.py`) — Takes a classified `Ticket` and resolves each bet's outcome (WIN/LOSE/VOID/UNKNOWN) by querying the `api-sports.io` football API. Matches fixtures using team name similarity (SequenceMatcher) and date proximity. Results are disk-cached in `data/fixture_cache/` to avoid redundant API calls.
4. **CLI** (`cli.py`) — Ties everything together. Handles `--classifier` and `--dump` flags; renders ANSI-colored comparison tables for side-by-side link-vs-image output.
5. **REST API** (`api/`) — FastAPI app exposing a single endpoint. Runs the full pipeline (screenshot → both classifiers → resolve) for a given URL and returns the verdict. Classifiers and resolver are instantiated once at startup (`app.state`) and reused across requests.
### Core Domain Models (`datamodels/ticket.py`)
`Bet` is an abstract Pydantic dataclass with a `resolve(MatchInfo) -> BetOutcome` method. Concrete subtypes include: `WinDrawLose`, `WinDrawLoseDouble`, `WinLose`, `BothTeamScored`, `GoalAmount`, `GoalHandicap`, `HalfTimeResult`, `HalfTimeDouble`, `HalfTimeFullTime`, `CornerAmount`, `TeamCornerAmount`, `MoreOffsides`, `Advance`, `UnknownBet`. Adding a new bet type requires: a new subclass here, detection regex in both classifiers, and a `resolve()` implementation.
### REST API
**Endpoint:** `POST /api/v1/resolve`
```json
{ "url": "<fortuna ticket url>", "debug": false }
```
Response includes `verdict` and per-bet `outcome`/`fixture_id`/`confidence`. With `debug: true` also returns raw `link_ticket`, `img_ticket`, and per-bet `match_info`.
Ticket ID is derived as `md5(url) % 10^9` — stable across restarts. Screenshots are saved to `data/screenshots/{ticket_id}.png`.
**Environment variables** (all optional):
| Var | Default |
|---|---|
| `BEAKY_CONFIG` | `config/application.yml` |
| `BEAKY_HOST` | `0.0.0.0` |
| `BEAKY_PORT` | `8000` |
| `LOG_LEVEL` | value from `config/application.yml``api.log_level` |
OpenAPI docs available at `/docs` when the server is running.
### Logging
All modules use `logging` (no `print()`). The CLI's user-facing output (`cli.py`) still uses `print`. Resolver debug output (fixture matching, API calls) goes through `_ansi.log()` which emits at `DEBUG` level with ANSI colors preserved. Set `api.log_level: DEBUG` in `config/application.yml` (or `LOG_LEVEL=DEBUG` env var) to see it.
### Configuration
Config is loaded from `config/application.yml` into Pydantic dataclasses (`Config`, `ScreenshotterConfig`, `ResolverConfig`, `ImgClassifierConfig`, `ApiConfig`). Key fields:
- `path` — path to the input Excel file
- `resolver.api_key` — api-sports.io API key
- `resolver.league_map` — maps Czech league name patterns to API league IDs (longest-match wins)
- `resolver.cache_path` — disk cache directory (default: `data/fixture_cache`)
- `api.log_level` — logging level for the API server (default: `INFO`)
### Bet text language
All bet type strings are in Czech (from the Fortuna betting platform). Regex patterns in both classifiers match Czech text (e.g. `"Výsledek zápasu"`, `"Počet gólů"`).

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@@ -6,6 +6,7 @@ screenshotter:
resolver:
api_key: 733f6882605be2de8980bbd074091ee4
league_map:
Kvalifikace MS - Evropa: 32
# European cups
liga mistrů: 2
champions league: 2
@@ -62,3 +63,9 @@ resolver:
img_classifier:
target_path: data/screenshots/
log_level: DEBUG # set to DEBUG to see raw classifier and resolver output
api:
host: 0.0.0.0
port: 8000

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@@ -16,6 +16,9 @@ dependencies = [
"playwright==1.58.0",
"requests>=2.32.0",
"diskcache>=5.6",
"pytesseract==0.3.13",
"fastapi>=0.115",
"uvicorn[standard]>=0.34",
]
[project.optional-dependencies]
@@ -30,6 +33,7 @@ dev = [
[project.scripts]
beaky = "beaky.cli:main"
beaky-api = "beaky.api.main:main"
[tool.ruff]

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@@ -1,5 +1,14 @@
from __future__ import annotations
import logging
_logger = logging.getLogger("beaky")
def log(text: str) -> None:
"""Emit a (possibly ANSI-colored) message at DEBUG level."""
_logger.debug("%s", text)
def bold(text: str) -> str:
return f"\033[1m{text}\033[0m"

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@@ -0,0 +1 @@

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@@ -0,0 +1,47 @@
import logging
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from beaky.api.routes import router
from beaky.config import Config, load_config
from beaky.link_classifier.classifier import LinkClassifier
from beaky.resolvers.resolver import TicketResolver
from beaky.screenshotter.screenshotter import Screenshotter
logger = logging.getLogger(__name__)
def create_app(config_path: str = "config/application.yml") -> FastAPI:
app = FastAPI(title="Beaky API", version="0.1.0")
app.add_middleware(
CORSMiddleware,
allow_origins=["http://localhost:5173"],
allow_methods=["POST"],
allow_headers=["Content-Type"],
)
app.include_router(router)
@app.on_event("startup")
def startup() -> None:
config: Config = load_config(config_path)
log_level_str = config.log_level.upper()
log_level: int = getattr(logging, log_level_str, logging.INFO)
logging.basicConfig(
level=log_level,
format="%(asctime)s %(levelname)s %(name)s: %(message)s",
)
logger.info("Config loaded from %s (log_level=%s)", config_path, log_level_str)
app.state.config = config
app.state.screenshotter = Screenshotter(config)
app.state.link_classifier = LinkClassifier()
app.state.resolver = TicketResolver(config.resolver)
logger.info("Beaky API ready")
return app
app = create_app() # default path; overridden by main() via create_app(config_path)

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@@ -0,0 +1,20 @@
import argparse
import uvicorn
from beaky.api.app import create_app
from beaky.config import load_config, Config
def main() -> None:
parser = argparse.ArgumentParser(prog="beaky-api")
parser.add_argument("--config", default="config/application.yml", help="Path to config file.")
args = parser.parse_args()
config: Config = load_config(args.config)
app = create_app(config_path=args.config)
uvicorn.run(app, host=config.api.host, port=config.api.port)
if __name__ == "__main__":
main()

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@@ -0,0 +1,42 @@
import logging
from fastapi import APIRouter, HTTPException, Request
from beaky.datamodels.api import ResolveRequest, ResolveResponse
from beaky.api.service import run_pipeline
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/v1")
@router.post("/resolve", response_model=ResolveResponse)
def resolve(body: ResolveRequest, request: Request) -> ResolveResponse:
logger.info("POST /api/v1/resolve url=%s debug=%s", body.url, body.debug)
config = request.app.state.config
screenshotter = request.app.state.screenshotter
link_classifier = request.app.state.link_classifier
resolver = request.app.state.resolver
try:
resolved, link_ticket, img_ticket = run_pipeline(
url=body.url,
config=config,
screenshotter=screenshotter,
link_classifier=link_classifier,
resolver=resolver,
)
except Exception as exc:
logger.exception("Pipeline failed for url=%s", body.url)
raise HTTPException(status_code=500, detail=str(exc)) from exc
if not body.debug:
for rb in resolved.bets:
rb.match_info = None
return ResolveResponse(
resolved_ticket=resolved,
verdict=resolved.verdict.value,
link_ticket=link_ticket if body.debug else None,
img_ticket=img_ticket if body.debug else None,
)

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@@ -0,0 +1,45 @@
import hashlib
import logging
from pathlib import Path
from beaky.config import Config
from beaky.datamodels.ticket import Ticket
from beaky.image_classifier.classifier import img_classify
from beaky.link_classifier.classifier import LinkClassifier
from beaky.resolvers.resolver import ResolvedTicket, TicketResolver
from beaky.scanner.scanner import Link
from beaky.screenshotter.screenshotter import Screenshotter
logger = logging.getLogger(__name__)
def run_pipeline(
url: str,
config: Config,
screenshotter: Screenshotter,
link_classifier: LinkClassifier,
resolver: TicketResolver,
) -> tuple[ResolvedTicket, Ticket, Ticket]:
ticket_id = int(hashlib.md5(url.encode()).hexdigest(), 16) % (10**9)
link = Link(id=ticket_id, url=url)
logger.info("Pipeline started for ticket_id=%d url=%s", ticket_id, url)
logger.info("Screenshotting ticket_id=%d", ticket_id)
screenshotter.capture_tickets([link])
logger.info("Screenshot done for ticket_id=%d", ticket_id)
logger.info("Link classifying ticket_id=%d", ticket_id)
link_ticket = link_classifier.classify(link)
#link_ticket = img_classify([f"./data/screenshots/{ticket_id}.png"], ticket_id=ticket_id)
logger.info("Link classification done: %d bets for ticket_id=%d", len(link_ticket.bets), ticket_id)
screenshot_path = Path(config.screenshotter.target_path) / f"{ticket_id}.png"
logger.info("Image classifying ticket_id=%d from %s", ticket_id, screenshot_path)
img_ticket = img_classify([str(screenshot_path)], ticket_id=ticket_id)
logger.info("Image classification done: %d bets for ticket_id=%d", len(img_ticket.bets), ticket_id)
logger.info("Resolving ticket_id=%d", ticket_id)
resolved = resolver.resolve(link_ticket)
logger.info("Resolve done for ticket_id=%d verdict=%s", ticket_id, resolved.verdict.value)
return resolved, link_ticket, img_ticket

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@@ -1,13 +1,11 @@
import argparse
import logging
import re as _re
import shutil
from datetime import datetime
import yaml
from pydantic import ValidationError
from beaky import _ansi
from beaky.config import Config
from beaky.config import load_config
from beaky.datamodels.ticket import Bet, Ticket
from beaky.image_classifier.classifier import img_classify
from beaky.link_classifier.classifier import LinkClassifier
@@ -55,7 +53,8 @@ def _bet_fields(bet: Bet) -> dict[str, str]:
for k, v in vars(bet).items():
if k in _SKIP_FIELDS:
continue
fields[k] = v.strftime("%Y-%m-%d %H:%M") if k == "date" and isinstance(v, datetime) else str(v)
val = v.strftime("%Y-%m-%d %H:%M") if k == "date" and isinstance(v, datetime) else str(v)
fields[k] = val.replace("\n", " ").replace("\r", "")
return fields
@@ -190,16 +189,6 @@ def _print_dump(ticket: Ticket, label: str) -> None:
print(f" {k}: {val}")
def load_config(path: str) -> Config | None:
with open(path) as f:
config_dict = yaml.safe_load(f)
try:
return Config(**config_dict)
except ValidationError as e:
print("Bad config")
print(e)
return None
def main() -> None:
parser = argparse.ArgumentParser(prog="beaky")
parser.add_argument("--config", help="Path to config file.", default="config/application.yml")
@@ -211,10 +200,15 @@ def main() -> None:
help="Dump all bet fields untruncated (compare mode only).")
args = parser.parse_args()
try:
config = load_config(args.config)
if config is None:
except RuntimeError as e:
print(e)
return
log_level = getattr(logging, config.log_level.upper(), logging.INFO)
logging.basicConfig(level=log_level, format="%(message)s")
# always load testing data, we will modify that later
data = Links(config)
data.ret_links()

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@@ -0,0 +1,34 @@
from dataclasses import field as _field
import yaml
from pydantic import ValidationError
from pydantic.dataclasses import dataclass
from beaky.image_classifier.config import ImgClassifierConfig
from beaky.resolvers.config import ResolverConfig
from beaky.screenshotter.config import ScreenshotterConfig
def load_config(path: str) -> "Config":
with open(path) as f:
data = yaml.safe_load(f)
try:
return Config(**data)
except ValidationError as exc:
raise RuntimeError(f"Invalid config at {path}: {exc}") from exc
@dataclass
class ApiConfig:
host: str = "0.0.0.0"
port: int = 8000
@dataclass
class Config:
path: str
screenshotter: ScreenshotterConfig
resolver: ResolverConfig
img_classifier: ImgClassifierConfig
log_level: str = "INFO"
api: ApiConfig = _field(default_factory=ApiConfig)

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@@ -0,0 +1,19 @@
from pydantic import BaseModel
from beaky.datamodels.ticket import Ticket
from beaky.resolvers.resolver import ResolvedTicket
class ResolveRequest(BaseModel):
url: str
debug: bool = False
class ResolveResponse(BaseModel):
model_config = {"arbitrary_types_allowed": True}
resolved_ticket: ResolvedTicket
verdict: str
# populated only when debug=True
link_ticket: Ticket | None = None
img_ticket: Ticket | None = None

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@@ -0,0 +1,238 @@
import datetime
import logging
import re
from pathlib import Path
import pytesseract
logger = logging.getLogger(__name__)
from beaky.datamodels.ticket import (
Advance,
Bet,
BetType,
BothTeamScored,
GoalAmount,
GoalHandicap,
Ticket,
UnknownBet,
WinDrawLose,
WinDrawLoseDouble,
WinLose,
)
def img_to_text(path: str) -> str:
"""Read text from image using tesseract; returns empty string on error."""
try:
return pytesseract.image_to_string(path, lang="ces").strip()
except Exception as e:
logger.error("Error processing %s: %s", path, e)
return ""
def _parse_block(lines: list[str]) -> Bet:
"""Parses a single block of text representing exactly one bet."""
team1, team2 = "Unknown", "Unknown"
league = "Unknown"
date_obj = datetime.datetime.now()
raw_text = "\n".join(lines)
# 1. Date extraction
if lines:
# Regex is forgiving of letters attached to numbers due to OCR (e.g., s07.3.2026)
date_m = re.search(r"(\d{1,2})\.\s*(\d{1,2})\.\s*(\d{4})", lines[0])
if date_m:
try:
date_obj = datetime.datetime(int(date_m.group(3)), int(date_m.group(2)), int(date_m.group(1)))
except ValueError:
pass
# 2. Teams extraction (usually the line after the date)
if len(lines) > 1:
ln_norm = re.sub(r"[–—−]", "-", lines[1])
m = re.match(r"^(.+?)\s*-\s*(.+)$", ln_norm)
if m:
team1, team2 = m.group(1).strip(), m.group(2).strip()
# 3. League extraction (typically contains a slash and sport name)
for ln in lines:
if "/" in ln and any(sport in ln for sport in ["Fotbal", "Hokej", "Tenis", "Basketbal"]):
league = ln.strip()
break
base_args = {"team1Name": team1, "team2Name": team2, "date": date_obj, "league": league}
# 4. Bet Type Classification
for ln in lines:
lower_line = ln.lower()
# Výsledek zápasu (1X2)
m_vysl = re.search(r"výsledek zápasu\s*:?\s*(1|0|x|2)$", lower_line)
if m_vysl and "dvojtip" not in lower_line and "remízy" not in lower_line:
pick = m_vysl.group(1).upper()
if pick == "X":
pick = "0"
return WinDrawLose(ticketType=BetType.WIN_DRAW_LOSE, betType=pick, **base_args)
# Výsledek zápasu - dvojtip (01, 02, 12, etc.)
m_dvoj = re.search(r"výsledek zápasu - dvojtip\s*:?\s*(10|01|02|20|12|1x|x1|x2|2x)$", lower_line)
if m_dvoj:
pick = m_dvoj.group(1).replace("x", "0").replace("X", "0")
if pick in ["10", "01"]:
pick = "01"
elif pick in ["20", "02"]:
pick = "02"
elif pick in ["12", "21"]:
pick = "12"
if pick in ["01", "12", "02"]:
return WinDrawLoseDouble(ticketType=BetType.WIN_DRAW_LOSE_DOUBLE, betType=pick, **base_args)
# Výsledek zápasu bez remízy
m_bez = re.search(r"bez remízy\s*:?\s*(1|2)$", lower_line)
if m_bez:
return WinLose(ticketType=BetType.WIN_LOSE, betType=m_bez.group(1), **base_args)
# Každý z týmů dá gól v zápasu
m_btts = re.search(r"každý z týmů dá gól.*?:\s*(ano|ne)$", lower_line)
if m_btts:
if m_btts.group(1) == "ano":
return BothTeamScored(ticketType=BetType.BOTH_TEAM_SCORED, **base_args)
else:
break
# Počet gólů v zápasu
m_goals = re.search(r"počet gólů v zápasu.*?:\s*([+-])\s*([\d.]+)", lower_line)
if m_goals and "tým" not in lower_line:
sign = m_goals.group(1)
val = float(m_goals.group(2))
is_over = sign == "+"
return GoalAmount(ticketType=BetType.GOAL_AMOUNT, line=val, over=is_over, **base_args)
# Kdo postoupí
if "postoupí" in lower_line or "postup" in lower_line:
return Advance(ticketType=BetType.ADVANCED, **base_args)
# Handicap v zápasu
m_hcp = re.search(r"handicap\s*(1|2)\s*:?\s*([+-]?[\d.]+)$", lower_line)
if m_hcp:
team_bet = m_hcp.group(1)
val = float(m_hcp.group(2))
return GoalHandicap(ticketType=BetType.GOAL_HANDICAP, team_bet=team_bet, handicap_amount=val, **base_args)
# Fallback
return UnknownBet(ticketType=BetType.UNKNOWN, raw_text=raw_text, **base_args)
def classify(text: str) -> list[Bet]:
"""Return a list of Bet objects parsed from OCR `text`."""
text = (text or "").strip()
if not text:
return [
UnknownBet(
ticketType=BetType.UNKNOWN,
team1Name="N/A",
team2Name="N/A",
date=datetime.datetime.now(),
league="N/A",
raw_text="No text extracted",
)
]
lines = [ln.strip() for ln in text.splitlines() if ln.strip()]
bets: list[Bet] = []
blocks = []
current_block = []
in_block = False
# START trigger: Looks for 'dnes', 'zítra', or 'DD.MM.'
# date_start_pattern = re.compile(r"(\d{1,2}\.\s*\d{1,2}\.|\b(dnes|zítra|zitra|včera|vcera)\b)", re.IGNORECASE)
date_start_pattern = re.compile(r"(\d{1,2}\.\s*\d{1,2}\.|\b(dnes|zítra|zitra|včera|vcera))", re.IGNORECASE)
# END trigger: Looks for standard Fortuna sport prefixes
# sport_end_pattern = re.compile(r"^(Fotbal|Hokej|Tenis|Basketbal|Florbal|Volejbal|E-sport|Šipky)\s*/", re.IGNORECASE)
sport_end_pattern = re.compile(r"(Fotbal|Hokej|Tenis|Basketbal|Florbal|Volejbal|E-sport|Šipky)\s*/", re.IGNORECASE)
for ln in lines:
logger.debug("Processing line: '%s'", ln)
is_start = date_start_pattern.search(ln)
is_end = sport_end_pattern.match(ln)
if is_start:
# If we somehow hit a start while already in a block (missing end marker fallback),
# save the current block before starting a new one.
if current_block:
logger.warning("Block not properly ended, new block start detected: '%s'", ln)
blocks.append(current_block)
current_block = [ln]
in_block = True
elif is_end:
# We hit the league/sport line. Add it, save the block, and close the window.
current_block.append(ln)
blocks.append(current_block)
current_block = []
in_block = False
elif in_block:
# We are inside a block, gathering standard match info (teams, bet types).
current_block.append(ln)
else:
# We are outside a block. This is noise (e.g. "© osmifinále / 2.zápas 0:1" or "170").
# We simply ignore it and do nothing.
logger.debug("Ignoring line outside of any block: '%s'", ln)
pass
# Catch any dangling block at the very end of the document
if current_block:
blocks.append(current_block)
# Parse each block into a separate Bet object
for block in blocks:
if len(block) > 1: # Ensure the block has enough lines to be valid
bets.append(_parse_block(block))
return bets
def img_classify(paths: list[str], ticket_id: int) -> Ticket:
"""Given a list of file paths to images, classify each and collect bets into a Ticket."""
ticket = Ticket(id=ticket_id, bets=[])
valid_extensions = {".png", ".jpg", ".jpeg", ".bmp", ".tiff", ".webp"}
for file in paths:
file_path = Path(file)
if not (file_path.is_file() and file_path.suffix.lower() in valid_extensions):
logger.warning("Skipping invalid file: %s", file)
continue
extracted_text = img_to_text(str(file_path))
logger.debug("Extracted text from %s", file_path.name)
try:
result = classify(extracted_text)
except Exception as exc:
logger.error("classify() error for %s: %s", file_path, exc)
result = [
UnknownBet(
ticketType=BetType.UNKNOWN,
team1Name="N/A",
team2Name="N/A",
date=datetime.datetime.now(),
league="N/A",
raw_text=extracted_text,
)
]
# for bet in result:
# print(f"-> Parsed: {bet.ticketType.value} | {bet.team1Name} vs {bet.team2Name} | {bet.league}")
ticket.bets.extend(result)
return ticket
if __name__ == "__main__":
# Test script runner
img_classify(["./data/screenshots/26.png", "./data/screenshots/27.png"], ticket_id=2)

View File

@@ -1,9 +1,12 @@
import logging
import re
from datetime import datetime
from typing import Any
from playwright.sync_api import Page, sync_playwright
logger = logging.getLogger(__name__)
from beaky.datamodels.ticket import (
Bet,
BetType,
@@ -130,7 +133,7 @@ def _extract_legs(page: Page, fallback_date: datetime | None) -> list[Bet]:
title = leg.locator("h3").first.get_attribute("title") or ""
date_text = leg.locator(".betslip-leg-date span").first.inner_text()
bet_text = leg.locator("[data-selection-id]").first.inner_text()
league = leg.locator(".f-mt-1.f-leading-tight.f-line-clamp-2").first.inner_text()
league = leg.locator(".f-mt-1.f-leading-tight.f-line-clamp-2").first.inner_text().replace("Fotbal /", "")
team1, team2 = _parse_teams(title)
date = _parse_czech_date(date_text) or fallback_date or datetime.now()
@@ -151,7 +154,7 @@ class LinkClassifier:
page.wait_for_timeout(500)
result = Ticket(id=link.id, bets=_extract_legs(page, link.date))
except Exception as e:
print(f"Error classifying link {link.id}: {e}")
logger.error("Error classifying link %d: %s", link.id, e)
finally:
page.close()
browser.close()

View File

@@ -1,10 +1,14 @@
import logging
import time
from dataclasses import dataclass, field
from dataclasses import field
from datetime import date, datetime, timedelta
from difflib import SequenceMatcher
from enum import Enum
from typing import Any
from pydantic import ConfigDict, SerializeAsAny
from pydantic.dataclasses import dataclass
import diskcache
import requests
@@ -18,9 +22,12 @@ from beaky.datamodels.ticket import (
)
from beaky.resolvers.config import ResolverConfig
logger = logging.getLogger(__name__)
_API_BASE = "https://v3.football.api-sports.io"
_DATE_WINDOW = 3 # days either side of the bet date to search
_NAME_THRESHOLD = 0.5
class TicketVerdict(str, Enum):
@@ -30,9 +37,9 @@ class TicketVerdict(str, Enum):
UNKNOWN = "unknown — could not resolve enough bets to decide"
@dataclass
@dataclass(config=ConfigDict(arbitrary_types_allowed=True))
class ResolvedBet:
bet: Bet
bet: SerializeAsAny[Bet]
outcome: BetOutcome
fixture_id: int | None = None
# Confidence breakdown (each component 0.01.0):
@@ -73,11 +80,11 @@ def _get(url: str, headers: dict[str, str], params: dict[str, str | int], retrie
resp = requests.get(url, headers=headers, params=params)
if resp.status_code == 429:
wait = backoff * (attempt + 1)
print(f" !! rate limited — waiting {wait:.0f}s before retry ({attempt + 1}/{retries})")
logger.warning("rate limited — waiting %.0fs before retry (%d/%d)", wait, attempt + 1, retries)
time.sleep(wait)
continue
return resp
print(f" !! still rate limited after {retries} retries, giving up")
logger.warning("still rate limited after %d retries, giving up", retries)
return resp
@@ -99,17 +106,17 @@ class TicketResolver:
def _resolve_bet(self, bet: Bet) -> ResolvedBet:
bet_type = type(bet).__name__
print(f"\n {_ansi.bold(_ansi.cyan(f'┌─ [{bet_type}]'))} {_ansi.bold(f'{bet.team1Name} vs {bet.team2Name}')}"
f" {_ansi.dim(f'{bet.date.strftime('%Y-%m-%d')} | {bet.league}')}")
_ansi.log(f"\n {_ansi.bold(_ansi.cyan(f'┌─ [{bet_type}]'))} {_ansi.bold(f'{bet.team1Name} vs {bet.team2Name}')}"
f" {_ansi.dim(f'{bet.date.strftime("%Y-%m-%d")} | {bet.league}')}")
if isinstance(bet, UnknownBet):
print(_ansi.gray(f" │ skipping — not implemented: {bet.raw_text!r}"))
print(_ansi.gray(" └─ UNKNOWN"))
_ansi.log(_ansi.gray(f" │ skipping — not implemented: {bet.raw_text!r}"))
_ansi.log(_ansi.gray(" └─ UNKNOWN"))
return ResolvedBet(bet=bet, outcome=BetOutcome.UNKNOWN)
fixture, name_match, date_prox, league_conf = self._find_fixture(bet)
if fixture is None:
print(_ansi.gray(" └─ UNKNOWN — no fixture found"))
_ansi.log(_ansi.gray(" └─ UNKNOWN — no fixture found"))
return ResolvedBet(bet=bet, outcome=BetOutcome.UNKNOWN, league_found=league_conf)
home_name = fixture["teams"]["home"]["name"]
@@ -126,12 +133,12 @@ class TicketResolver:
outcome = BetOutcome.UNKNOWN
goals = fixture["goals"]
print(_ansi.dim(
_ansi.log(_ansi.dim(
f" │ matched #{fixture['fixture']['id']}: {home_name} vs {away_name}"
f" | {goals['home']}:{goals['away']} | {fixture['fixture']['status']['short']}"
f" | confidence {confidence} (name={name_match:.2f} date={date_prox:.2f} league={league_conf} finished={finished})"
))
print(_ansi.bold(_ansi.green(f" └─ {outcome.value.upper()}") if outcome == BetOutcome.WIN
_ansi.log(_ansi.bold(_ansi.green(f" └─ {outcome.value.upper()}") if outcome == BetOutcome.WIN
else _ansi.red(f" └─ {outcome.value.upper()}") if outcome == BetOutcome.LOSE
else _ansi.yellow(f" └─ {outcome.value.upper()}") if outcome == BetOutcome.VOID
else _ansi.gray(f" └─ {outcome.value.upper()}")))
@@ -151,9 +158,9 @@ class TicketResolver:
def _get_statistics(self, fixture_id: int) -> list[dict[str, Any]]:
cache_key = ("stats", fixture_id)
if cache_key in self._disk_cache:
print(_ansi.gray(f" │ /fixtures/statistics served from disk cache (fixture={fixture_id})"))
_ansi.log(_ansi.gray(f" │ /fixtures/statistics served from disk cache (fixture={fixture_id})"))
return self._disk_cache[cache_key] # type: ignore[no-any-return]
print(_ansi.gray(f" │ GET /fixtures/statistics fixture={fixture_id}"))
_ansi.log(_ansi.gray(f" │ GET /fixtures/statistics fixture={fixture_id}"))
resp = _get(f"{_API_BASE}/fixtures/statistics", headers=self._headers, params={"fixture": fixture_id})
resp.raise_for_status()
stats = resp.json().get("response", [])
@@ -173,7 +180,8 @@ class TicketResolver:
if cache_key not in self._fixture_cache:
if cache_key in self._disk_cache and not cache_may_be_stale:
self._fixture_cache[cache_key] = self._disk_cache[cache_key]
print(_ansi.gray(f" │ /fixtures served from disk cache ({len(self._fixture_cache[cache_key])} fixtures)"))
_ansi.log(
_ansi.gray(f" │ /fixtures served from disk cache ({len(self._fixture_cache[cache_key])} fixtures)"))
else:
date_from = (center - timedelta(days=_DATE_WINDOW)).strftime("%Y-%m-%d")
date_to = (center + timedelta(days=_DATE_WINDOW)).strftime("%Y-%m-%d")
@@ -181,17 +189,18 @@ class TicketResolver:
if league_id is not None:
params["league"] = league_id
params["season"] = center.year if center.month >= 7 else center.year - 1
print(_ansi.gray(f" │ GET /fixtures {params}"))
_ansi.log(_ansi.gray(f" │ GET /fixtures {params}"))
resp = _get(f"{_API_BASE}/fixtures", headers=self._headers, params=params)
resp.raise_for_status()
self._fixture_cache[cache_key] = resp.json().get("response", [])
print(_ansi.gray(f"{len(self._fixture_cache[cache_key])} fixtures returned"))
_ansi.log(_ansi.gray(f"{len(self._fixture_cache[cache_key])} fixtures returned"))
cacheable = [f for f in self._fixture_cache[cache_key] if f.get("fixture", {}).get("status", {}).get("short") != "NS"]
if cacheable:
self._disk_cache[cache_key] = cacheable
print(_ansi.gray(f"{len(cacheable)} non-NS fixture(s) written to disk cache"))
_ansi.log(_ansi.gray(f"{len(cacheable)} non-NS fixture(s) written to disk cache"))
else:
print(_ansi.gray(f" │ /fixtures (±{_DATE_WINDOW}d of {date_str}, league={league_id}) served from memory"))
_ansi.log(
_ansi.gray(f" │ /fixtures (±{_DATE_WINDOW}d of {date_str}, league={league_id}) served from memory"))
fixture, name_match, date_prox = _best_fixture_match(
self._fixture_cache[cache_key], bet.team1Name, bet.team2Name, center
@@ -203,29 +212,30 @@ class TicketResolver:
if key in self._league_cache:
return self._league_cache[key]
# Use longest-match so "1. itálie - ženy" beats "1. itálie"
best_pattern, best_id = max(
((p, lid) for p, lid in self._league_map.items() if p in key),
key=lambda t: len(t[0]),
default=(None, None),
)
if best_id is not None:
print(_ansi.gray(f" │ league {league_name!r} -> id={best_id} (static map, pattern={best_pattern!r})"))
self._league_cache[key] = (best_id, 1.0)
return best_id, 1.0
# Static map — fuzzy match
patterns = [x.lower().strip() for x in self._league_map.keys()]
idx, score = _best_match(key, patterns)
if idx is not None:
best_id = self._league_map[patterns[idx]]
_ansi.log(_ansi.gray(f" │ league {league_name!r} -> id={best_id} (static map, pattern={patterns[idx]!r}, score={score:.2f})"))
self._league_cache[key] = (best_id, score)
return best_id, score
# Fall back to API search — lower confidence since first result is taken unverified
print(_ansi.gray(f" │ GET /leagues search={league_name!r}"))
# API fallback — fuzzy match all results
_ansi.log(_ansi.gray(f" │ GET /leagues search={league_name!r}"))
resp = _get(f"{_API_BASE}/leagues", headers=self._headers, params={"search": league_name[:20]})
results = resp.json().get("response", [])
if results:
league_id = results[0]["league"]["id"]
league_found_name = results[0]["league"]["name"]
print(_ansi.gray(f" │ matched {league_found_name!r} id={league_id} (API fallback, confidence=0.7)"))
names = [r["league"]["name"].lower() for r in results]
idx, score = _best_match(key, names)
if idx is not None:
league_id = results[idx]["league"]["id"]
league_found_name = results[idx]["league"]["name"]
_ansi.log(_ansi.gray(f" │ matched {league_found_name!r} id={league_id} (API fallback, score={score:.2f}, confidence=0.7)"))
self._league_cache[key] = (league_id, 0.7)
return league_id, 0.7
print(_ansi.gray(" │ no league found, searching fixtures by date only (confidence=0.3)"))
_ansi.log(_ansi.gray(" │ no league found, searching fixtures by date only (confidence=0.3)"))
self._league_cache[key] = (None, 0.3)
return None, 0.3
@@ -273,6 +283,16 @@ def _similarity(a: str, b: str) -> float:
return SequenceMatcher(None, a.lower(), b.lower()).ratio()
def _best_match(query: str, candidates: list[str], threshold: float = _NAME_THRESHOLD) -> tuple[int | None, float]:
"""Return (index, score) of the best fuzzy match, or (None, score) if below threshold."""
if not candidates:
return None, 0.0
scores = [_similarity(query, c) for c in candidates]
best_idx = max(range(len(scores)), key=lambda i: scores[i])
score = scores[best_idx]
return (best_idx, score) if score >= threshold else (None, score)
def _date_proximity(fixture: dict[str, Any], center: date) -> float:
"""1.0 on exact date, linear decay to 0.0 at _DATE_WINDOW days away."""
fixture_date = datetime.fromisoformat(fixture["fixture"]["date"].replace("Z", "+00:00")).date()
@@ -282,21 +302,21 @@ def _date_proximity(fixture: dict[str, Any], center: date) -> float:
def _best_fixture_match(fixtures: list[dict[str, Any]], team1: str, team2: str, center: date) -> tuple[dict[str, Any] | None, float, float]:
"""Returns (best_fixture, name_score, date_proximity) or (None, 0, 0) if no good match."""
best, best_combined, best_name, best_date = None, 0.0, 0.0, 0.0
for f in fixtures:
home = f["teams"]["home"]["name"]
away = f["teams"]["away"]["name"]
name_score = (_similarity(team1, home) + _similarity(team2, away)) / 2
date_prox = _date_proximity(f, center)
if not fixtures:
return None, 0.0, 0.0
# Name similarity is the primary signal; date proximity is a tiebreaker
combined = name_score * 0.8 + date_prox * 0.2
if combined > best_combined:
best_combined = combined
best_name = name_score
best_date = date_prox
best = f
home_names = [f["teams"]["home"]["name"] for f in fixtures]
away_names = [f["teams"]["away"]["name"] for f in fixtures]
print(home_names)
print(away_names)
name_scores = [(_similarity(team1, h) + _similarity(team2, a)) / 2 for h, a in zip(home_names, away_names)]
print(name_scores)
date_proxies = [_date_proximity(f, center) for f in fixtures]
combined = [n * 0.8 + d * 0.2 for n, d in zip(name_scores, date_proxies)]
best_idx = max(range(len(combined)), key=lambda i: combined[i])
name, date = name_scores[best_idx], date_proxies[best_idx]
# Require minimum name similarity — date alone cannot rescue a bad name match
return (best, best_name, best_date) if best_name > 0.5 else (None, best_name, best_date)
return (fixtures[best_idx], name, date) if name >= _NAME_THRESHOLD else (None, name, date)
def _is_finished(fixture: dict[str, Any]) -> float:

View File

@@ -1,3 +1,4 @@
import logging
from datetime import datetime
from typing import Any, Iterator, List, Optional
@@ -6,6 +7,8 @@ from pydantic.dataclasses import dataclass
from beaky.config import Config
logger = logging.getLogger(__name__)
@dataclass
class Link:
@@ -37,7 +40,7 @@ class Links:
at least: 'id', 'link' (or 'url'), and optionally 'date' (case-insensitive).
Returns the list of Link objects (also stored in self.links).
"""
print("started ret_links()")
logger.debug("started ret_links()")
wb = load_workbook(filename=self._path, read_only=True, data_only=True)
ws = wb.active
@@ -84,7 +87,7 @@ class Links:
if id_idx is None or url_idx is None:
# Required columns missing
print(f"Required 'id' or 'url' column missing in header. Found headers: {list(header_map.keys())}")
logger.warning("Required 'id' or 'url' column missing in header. Found headers: %s", list(header_map.keys()))
return []
for row in rows:

View File

@@ -1,3 +1,4 @@
import logging
from pathlib import Path
from typing import Any
@@ -6,6 +7,8 @@ from playwright.sync_api import sync_playwright
from beaky.config import Config
from beaky.scanner.scanner import Link
logger = logging.getLogger(__name__)
class Screenshotter:
def __init__(self, config: Config):
@@ -18,7 +21,7 @@ class Screenshotter:
context = browser.new_context()
for link in links:
print("capturing link:", link)
logger.debug("capturing link: %s", link)
page = context.new_page()
target_path = Path(self.config.screenshotter.target_path) / f"{link.id}.png"
self.capture_ticket(page, link.url, target_path)

25
beaky-frontend/.gitignore vendored Normal file
View File

@@ -0,0 +1,25 @@
# Logs
.vscode
logs
*.log
npm-debug.log*
yarn-debug.log*
yarn-error.log*
pnpm-debug.log*
lerna-debug.log*
node_modules
dist
dist-ssr
*.local
# Editor directories and files
.vscode/*
!.vscode/extensions.json
.idea
.DS_Store
*.suo
*.ntvs*
*.njsproj
*.sln
*.sw?

43
beaky-frontend/README.md Normal file
View File

@@ -0,0 +1,43 @@
# Svelte + Vite
This template should help get you started developing with Svelte in Vite.
## Recommended IDE Setup
[VS Code](https://code.visualstudio.com/) + [Svelte](https://marketplace.visualstudio.com/items?itemName=svelte.svelte-vscode).
## Need an official Svelte framework?
Check out [SvelteKit](https://github.com/sveltejs/kit#readme), which is also powered by Vite. Deploy anywhere with its serverless-first approach and adapt to various platforms, with out of the box support for TypeScript, SCSS, and Less, and easily-added support for mdsvex, GraphQL, PostCSS, Tailwind CSS, and more.
## Technical considerations
**Why use this over SvelteKit?**
- It brings its own routing solution which might not be preferable for some users.
- It is first and foremost a framework that just happens to use Vite under the hood, not a Vite app.
This template contains as little as possible to get started with Vite + Svelte, while taking into account the developer experience with regards to HMR and intellisense. It demonstrates capabilities on par with the other `create-vite` templates and is a good starting point for beginners dipping their toes into a Vite + Svelte project.
Should you later need the extended capabilities and extensibility provided by SvelteKit, the template has been structured similarly to SvelteKit so that it is easy to migrate.
**Why include `.vscode/extensions.json`?**
Other templates indirectly recommend extensions via the README, but this file allows VS Code to prompt the user to install the recommended extension upon opening the project.
**Why enable `checkJs` in the JS template?**
It is likely that most cases of changing variable types in runtime are likely to be accidental, rather than deliberate. This provides advanced typechecking out of the box. Should you like to take advantage of the dynamically-typed nature of JavaScript, it is trivial to change the configuration.
**Why is HMR not preserving my local component state?**
HMR state preservation comes with a number of gotchas! It has been disabled by default in both `svelte-hmr` and `@sveltejs/vite-plugin-svelte` due to its often surprising behavior. You can read the details [here](https://github.com/sveltejs/svelte-hmr/tree/master/packages/svelte-hmr#preservation-of-local-state).
If you have state that's important to retain within a component, consider creating an external store which would not be replaced by HMR.
```js
// store.js
// An extremely simple external store
import { writable } from 'svelte/store'
export default writable(0)
```

13
beaky-frontend/index.html Normal file
View File

@@ -0,0 +1,13 @@
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="/favicon.svg" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>beaky-frontend</title>
</head>
<body>
<div id="app"></div>
<script type="module" src="/src/main.js"></script>
</body>
</html>

View File

@@ -0,0 +1,33 @@
{
"compilerOptions": {
"moduleResolution": "bundler",
"target": "ESNext",
"module": "ESNext",
/**
* svelte-preprocess cannot figure out whether you have
* a value or a type, so tell TypeScript to enforce using
* `import type` instead of `import` for Types.
*/
"verbatimModuleSyntax": true,
"isolatedModules": true,
"resolveJsonModule": true,
/**
* To have warnings / errors of the Svelte compiler at the
* correct position, enable source maps by default.
*/
"sourceMap": true,
"esModuleInterop": true,
"types": ["vite/client"],
"skipLibCheck": true,
/**
* Typecheck JS in `.svelte` and `.js` files by default.
* Disable this if you'd like to use dynamic types.
*/
"checkJs": true
},
/**
* Use global.d.ts instead of compilerOptions.types
* to avoid limiting type declarations.
*/
"include": ["src/**/*.d.ts", "src/**/*.js", "src/**/*.svelte"]
}

1517
beaky-frontend/package-lock.json generated Normal file

File diff suppressed because it is too large Load Diff

View File

@@ -0,0 +1,18 @@
{
"name": "beaky-frontend",
"private": true,
"version": "0.0.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "vite build",
"preview": "vite preview"
},
"devDependencies": {
"@sveltejs/vite-plugin-svelte": "^7.0.0",
"@tailwindcss/vite": "^4.2.2",
"svelte": "^5.53.12",
"tailwindcss": "^4.2.2",
"vite": "^8.0.1"
}
}

File diff suppressed because one or more lines are too long

After

Width:  |  Height:  |  Size: 9.3 KiB

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@@ -0,0 +1,24 @@
<svg xmlns="http://www.w3.org/2000/svg">
<symbol id="bluesky-icon" viewBox="0 0 16 17">
<g clip-path="url(#bluesky-clip)"><path fill="#08060d" d="M7.75 7.735c-.693-1.348-2.58-3.86-4.334-5.097-1.68-1.187-2.32-.981-2.74-.79C.188 2.065.1 2.812.1 3.251s.241 3.602.398 4.13c.52 1.744 2.367 2.333 4.07 2.145-2.495.37-4.71 1.278-1.805 4.512 3.196 3.309 4.38-.71 4.987-2.746.608 2.036 1.307 5.91 4.93 2.746 2.72-2.746.747-4.143-1.747-4.512 1.702.189 3.55-.4 4.07-2.145.156-.528.397-3.691.397-4.13s-.088-1.186-.575-1.406c-.42-.19-1.06-.395-2.741.79-1.755 1.24-3.64 3.752-4.334 5.099"/></g>
<defs><clipPath id="bluesky-clip"><path fill="#fff" d="M.1.85h15.3v15.3H.1z"/></clipPath></defs>
</symbol>
<symbol id="discord-icon" viewBox="0 0 20 19">
<path fill="#08060d" d="M16.224 3.768a14.5 14.5 0 0 0-3.67-1.153c-.158.286-.343.67-.47.976a13.5 13.5 0 0 0-4.067 0c-.128-.306-.317-.69-.476-.976A14.4 14.4 0 0 0 3.868 3.77C1.546 7.28.916 10.703 1.231 14.077a14.7 14.7 0 0 0 4.5 2.306q.545-.748.965-1.587a9.5 9.5 0 0 1-1.518-.74q.191-.14.372-.293c2.927 1.369 6.107 1.369 8.999 0q.183.152.372.294-.723.437-1.52.74.418.838.963 1.588a14.6 14.6 0 0 0 4.504-2.308c.37-3.911-.63-7.302-2.644-10.309m-9.13 8.234c-.878 0-1.599-.82-1.599-1.82 0-.998.705-1.82 1.6-1.82.894 0 1.614.82 1.599 1.82.001 1-.705 1.82-1.6 1.82m5.91 0c-.878 0-1.599-.82-1.599-1.82 0-.998.705-1.82 1.6-1.82.893 0 1.614.82 1.599 1.82 0 1-.706 1.82-1.6 1.82"/>
</symbol>
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<script>
import BetsTable from './lib/BetsTable.svelte'
const API_URL = 'http://localhost:8000/api/v1/resolve'
let url = $state('')
let loading = $state(false)
let error = $state(null)
let result = $state(null)
let dark = $state(true)
$effect(() => {
document.documentElement.classList.toggle('dark', dark)
})
async function verify(e) {
e.preventDefault()
loading = true
error = null
result = null
try {
const res = await fetch(API_URL, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ url, debug: false }),
})
if (!res.ok) {
let detail = res.statusText
try { const body = await res.json(); detail = body.detail ?? detail } catch {}
throw new Error('Server error: ' + detail)
}
result = await res.json()
} catch (err) {
error = err.name === 'TypeError'
? 'Could not reach the Beaky API at localhost:8000. Is the server running?'
: err.message
} finally {
loading = false
}
}
function verdictStyle(verdict) {
if (verdict === 'truthful') return { label: 'TRUTHFUL', bg: '#22c55e', text: '#fff' }
if (verdict === 'not truthful') return { label: 'NOT TRUTHFUL', bg: '#ef4444', text: '#fff' }
if (verdict?.startsWith('possibly')) return { label: 'POSSIBLY TRUTHFUL — check manually', bg: '#eab308', text: '#111827' }
return { label: 'UNKNOWN — insufficient data', bg: '#6b7280', text: '#fff' }
}
</script>
<div class="page">
<div class="container">
<!-- Header -->
<div class="header-row">
<div>
<h1>Beaky</h1>
<p class="subtitle">Paste a Fortuna ticket URL to verify its truthfulness.</p>
</div>
<button class="theme-toggle" onclick={() => (dark = !dark)} aria-label="Toggle dark mode" title={dark ? 'Switch to light mode' : 'Switch to dark mode'}>
{#if dark}
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="none" viewBox="0 0 24 24" stroke="currentColor" stroke-width="2">
<path stroke-linecap="round" stroke-linejoin="round" d="M12 3v1m0 16v1m9-9h-1M4 12H3m15.364-6.364l-.707.707M6.343 17.657l-.707.707M17.657 17.657l-.707-.707M6.343 6.343l-.707-.707M12 5a7 7 0 100 14A7 7 0 0012 5z" />
</svg>
{:else}
<svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" fill="none" viewBox="0 0 24 24" stroke="currentColor" stroke-width="2">
<path stroke-linecap="round" stroke-linejoin="round" d="M21 12.79A9 9 0 1111.21 3a7 7 0 109.79 9.79z" />
</svg>
{/if}
</button>
</div>
<!-- Input form -->
<form onsubmit={verify} class="form">
<input
type="url"
bind:value={url}
placeholder="https://applink.ifortuna.cz/ticketdetail?id=..."
required
class="url-input"
/>
<button type="submit" disabled={loading} class="submit-btn">
{loading ? 'Verifying…' : 'Verify'}
</button>
</form>
<!-- Spinner -->
{#if loading}
<div class="spinner-wrap">
<div class="spinner"></div>
<p class="spinner-label">Running classifiers and resolving bets — this takes ~20 seconds…</p>
</div>
{/if}
<!-- Error -->
{#if error}
<div class="error-box">{error}</div>
{/if}
<!-- Result -->
{#if result}
{@const vs = verdictStyle(result.verdict)}
<div class="verdict-banner" style="background:{vs.bg}; color:{vs.text}">
{vs.label}
</div>
{#if result.resolved_ticket?.ticket_id}
<p class="ticket-id">Ticket ID: {result.resolved_ticket.ticket_id}</p>
{/if}
<BetsTable bets={result.resolved_ticket?.bets ?? []} />
{/if}
</div>
</div>
<style>
.page {
min-height: 100vh;
background: var(--bg-page);
color: var(--text-primary);
transition: background 0.2s, color 0.2s;
}
.container {
max-width: 960px;
margin: 0 auto;
padding: 3rem 1rem;
}
.header-row {
display: flex;
justify-content: space-between;
align-items: flex-start;
margin-bottom: 2.5rem;
}
h1 {
font-size: 2.25rem;
font-weight: 700;
margin: 0 0 0.25rem;
color: var(--text-primary);
}
.subtitle {
color: var(--text-secondary);
margin: 0;
}
.theme-toggle {
background: none;
border: none;
cursor: pointer;
padding: 0.5rem;
border-radius: 0.5rem;
color: var(--text-secondary);
transition: background 0.15s;
}
.theme-toggle:hover { background: var(--bg-surface-alt); }
.form {
display: flex;
gap: 0.5rem;
margin-bottom: 2rem;
}
.url-input {
flex: 1;
background: var(--bg-input);
border: 1px solid var(--border-input);
border-radius: 0.5rem;
padding: 0.625rem 1rem;
color: var(--text-primary);
font-size: 0.875rem;
outline: none;
transition: border-color 0.15s, background 0.2s;
}
.url-input::placeholder { color: var(--text-muted); }
.url-input:focus { border-color: #3b82f6; box-shadow: 0 0 0 3px rgba(59,130,246,0.2); }
.submit-btn {
background: #2563eb;
color: #fff;
border: none;
border-radius: 0.5rem;
padding: 0.625rem 1.5rem;
font-size: 0.875rem;
font-weight: 500;
cursor: pointer;
transition: background 0.15s;
white-space: nowrap;
}
.submit-btn:hover:not(:disabled) { background: #1d4ed8; }
.submit-btn:disabled { background: #1e3a5f; cursor: not-allowed; }
.spinner-wrap {
display: flex;
flex-direction: column;
align-items: center;
gap: 0.75rem;
padding: 3rem 0;
}
.spinner {
width: 2.5rem;
height: 2.5rem;
border: 4px solid var(--border);
border-top-color: #3b82f6;
border-radius: 50%;
animation: spin 0.8s linear infinite;
}
@keyframes spin { to { transform: rotate(360deg); } }
.spinner-label { color: var(--text-secondary); font-size: 0.875rem; margin: 0; }
.error-box {
background: var(--bg-error);
border: 1px solid var(--border-error);
color: var(--text-error);
border-radius: 0.5rem;
padding: 0.75rem 1rem;
}
.verdict-banner {
border-radius: 0.75rem;
text-align: center;
font-size: 1.75rem;
font-weight: 700;
letter-spacing: 0.05em;
padding: 1.5rem 1rem;
margin-bottom: 0.75rem;
}
.ticket-id {
color: var(--text-muted);
font-size: 0.75rem;
margin: 0 0 1.5rem;
}
</style>

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@import "tailwindcss";
/* ── Light theme (default) ─────────────────────────────────────── */
:root {
--bg-page: #f9fafb;
--bg-surface: #ffffff;
--bg-surface-alt:#f3f4f6;
--bg-header: #f9fafb;
--bg-hover: #eff6ff;
--bg-input: #ffffff;
--bg-error: #fef2f2;
--text-primary: #111827;
--text-secondary:#6b7280;
--text-muted: #9ca3af;
--border: #e5e7eb;
--border-subtle: #f3f4f6;
--border-input: #d1d5db;
--border-error: #fca5a5;
--text-error: #b91c1c;
--outcome-win-bg: #dcfce7;
--outcome-win-text: #15803d;
--outcome-lose-bg: #fee2e2;
--outcome-lose-text: #b91c1c;
--outcome-void-bg: #fef9c3;
--outcome-void-text: #a16207;
--outcome-unknown-bg: #f3f4f6;
--outcome-unknown-text:#6b7280;
--conf-track: #e5e7eb;
}
/* ── Dark theme ─────────────────────────────────────────────────── */
.dark {
--bg-page: #030712;
--bg-surface: #111827;
--bg-surface-alt:#030712;
--bg-header: #111827;
--bg-hover: #1f2937;
--bg-input: #1f2937;
--bg-error: #450a0a;
--text-primary: #f9fafb;
--text-secondary:#9ca3af;
--text-muted: #6b7280;
--border: #1f2937;
--border-subtle: #1f2937;
--border-input: #374151;
--border-error: #991b1b;
--text-error: #fca5a5;
--outcome-win-bg: #14532d;
--outcome-win-text: #86efac;
--outcome-lose-bg: #7f1d1d;
--outcome-lose-text: #fca5a5;
--outcome-void-bg: #422006;
--outcome-void-text: #fde68a;
--outcome-unknown-bg: #1f2937;
--outcome-unknown-text:#9ca3af;
--conf-track: #374151;
}

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<script>
let { bets } = $props()
function formatBetType(t) {
return {
win_draw_lose: '1X2 Result',
win_draw_lose_double: '1X2 Double',
win_lose: 'Win/Lose',
both_team_scored: 'Both Teams Score',
goal_amount: 'Over/Under Goals',
goal_handicap: 'Goal Handicap',
half_time_result: 'HT Result',
half_time_double: 'HT Double',
half_time_full_time: 'HT/FT',
corner_amount: 'Over/Under Corners',
team_corner_amount: 'Team Corners',
more_offsides: 'More Offsides',
advance: 'Advance',
unknown: 'Unknown',
}[t] ?? t
}
function formatBetDetail(bet) {
const result = (code) => ({ '1': 'Home win', '2': 'Away win', '0': 'Draw', 'X': 'Draw' }[code] ?? code)
const double = (code) => ({ '01': 'Home or Draw', '02': 'Home or Away', '12': 'Draw or Away' }[code] ?? code)
const team = (code) => code === '1' ? bet.team1Name : bet.team2Name
const sign = (n) => (n >= 0 ? '+' : '') + n
switch (bet.ticketType) {
case 'win_draw_lose': return result(bet.betType)
case 'win_draw_lose_double': return double(bet.betType)
case 'win_lose': return result(bet.betType)
case 'both_team_scored': return 'Both teams to score'
case 'goal_amount': return (bet.over ? 'Over ' : 'Under ') + bet.line + ' goals'
case 'goal_handicap': return team(bet.team_bet) + ' ' + sign(bet.handicap_amount)
case 'half_time_result': return 'HT: ' + result(bet.betType)
case 'half_time_double': return 'HT: ' + double(bet.betType)
case 'half_time_full_time': return 'HT: ' + result(bet.ht_bet) + ' / FT: ' + result(bet.ft_bet)
case 'corner_amount': return (bet.over ? 'Over ' : 'Under ') + bet.line + ' corners'
case 'team_corner_amount': return team(bet.team_bet) + ' ' + (bet.over ? 'over ' : 'under ') + bet.line
case 'more_offsides': return team(bet.team_bet) + ' more offsides'
case 'advance': return 'Advance'
default: return bet.raw_text || 'Unknown'
}
}
</script>
<div class="table-wrap">
<table>
<thead>
<tr>
<th>Match</th>
<th>Date</th>
<th>League</th>
<th>Bet Type</th>
<th>Pick</th>
<th>Outcome</th>
<th>Confidence</th>
</tr>
</thead>
<tbody>
{#each bets as resolved, i}
{@const bet = resolved.bet}
{@const outcome = (resolved.outcome ?? 'unknown').toLowerCase()}
{@const conf = Math.round((resolved.confidence ?? 0) * 100)}
{@const date = bet.date ? new Date(bet.date) : null}
<tr class:alt={i % 2 !== 0}>
<td class="match">
{bet.team1Name} <span class="vs">vs</span> {bet.team2Name}
</td>
<td class="secondary">
{date ? date.toLocaleDateString('cs-CZ', { day: 'numeric', month: 'short', year: 'numeric' }) : '—'}
</td>
<td class="secondary">{bet.league ?? '—'}</td>
<td>{formatBetType(bet.ticketType)}</td>
<td>{formatBetDetail(bet)}</td>
<td>
<span class="badge outcome-{outcome}">{outcome}</span>
</td>
<td>
<div class="conf">
<div class="conf-track">
<div class="conf-fill" style="width:{conf}%"></div>
</div>
<span class="conf-label">{conf}%</span>
</div>
</td>
</tr>
{/each}
</tbody>
</table>
</div>
<style>
.table-wrap {
overflow-x: auto;
border-radius: 0.75rem;
border: 1px solid var(--border);
}
table {
width: 100%;
border-collapse: collapse;
font-size: 0.875rem;
}
thead tr {
border-bottom: 1px solid var(--border);
background: var(--bg-header);
}
th {
padding: 0.75rem 1rem;
text-align: left;
font-weight: 500;
color: var(--text-secondary);
}
tbody tr {
border-bottom: 1px solid var(--border-subtle);
background: var(--bg-surface);
transition: background 0.1s;
}
tbody tr.alt { background: var(--bg-surface-alt); }
tbody tr:last-child { border-bottom: none; }
tbody tr:hover { background: var(--bg-hover); }
td {
padding: 0.75rem 1rem;
color: var(--text-primary);
}
.match { font-weight: 500; }
.vs { color: var(--text-muted); }
.secondary { color: var(--text-secondary); white-space: nowrap; }
.badge {
display: inline-block;
padding: 0.125rem 0.5rem;
border-radius: 0.25rem;
font-size: 0.75rem;
font-weight: 600;
text-transform: uppercase;
}
.outcome-win { background: var(--outcome-win-bg); color: var(--outcome-win-text); }
.outcome-lose { background: var(--outcome-lose-bg); color: var(--outcome-lose-text); }
.outcome-void { background: var(--outcome-void-bg); color: var(--outcome-void-text); }
.outcome-unknown { background: var(--outcome-unknown-bg); color: var(--outcome-unknown-text); }
.conf {
display: flex;
align-items: center;
gap: 0.5rem;
}
.conf-track {
width: 4rem;
height: 6px;
background: var(--conf-track);
border-radius: 9999px;
overflow: hidden;
}
.conf-fill {
height: 100%;
background: #3b82f6;
border-radius: 9999px;
}
.conf-label {
font-size: 0.75rem;
color: var(--text-muted);
}
</style>

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<script>
let count = $state(0)
</script>
<button class="counter" onclick={() => count++}>Count is {count}</button>

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import { mount } from 'svelte'
import './app.css'
import App from './App.svelte'
const app = mount(App, {
target: document.getElementById('app'),
})
export default app

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/** @type {import("@sveltejs/vite-plugin-svelte").SvelteConfig} */
export default {}

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import { defineConfig } from 'vite'
import { svelte } from '@sveltejs/vite-plugin-svelte'
import tailwindcss from '@tailwindcss/vite'
export default defineConfig({
plugins: [tailwindcss(), svelte()],
})

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@@ -1,88 +0,0 @@
import os
import re
import sys
import argparse
from datetime import datetime
import pytz
from openpyxl import Workbook
def process_files(starting_id, output_filename="output.xlsx"):
# Find all txt files in the current directory
txt_files = [f for f in os.listdir('.') if f.endswith('.txt')]
if not txt_files:
print("No .txt files found in the current directory.")
return
# Regex patterns for input data
date_pattern = re.compile(r'\[.*?(\d{1,2})\s+(\d{1,2}),\s+(\d{4})\s+at\s+(\d{1,2}:\d{2})\]')
url_pattern = re.compile(r'(https?://[^\s]+)')
# Timezone setup (CET to UTC)
local_tz = pytz.timezone("Europe/Prague")
# Set up the Excel Workbook
wb = Workbook()
ws = wb.active
ws.title = "Fortuna Data"
ws.append(["ID", "URL", "Date_UTC"]) # Add headers
current_id = starting_id
success_files = []
for filename in txt_files:
try:
with open(filename, 'r', encoding='utf-8') as f:
content = f.read()
dates = date_pattern.findall(content)
urls = url_pattern.findall(content)
# Extract and format the data
for i in range(min(len(dates), len(urls))):
month, day, year, time_str = dates[i]
# Parse the datetime from the text file
dt_str = f"{year}-{month}-{day} {time_str}"
local_dt = datetime.strptime(dt_str, "%Y-%m-%d %H:%M")
# Convert CET to UTC
localized_dt = local_tz.localize(local_dt)
utc_dt = localized_dt.astimezone(pytz.utc)
# NEW: Format to ISO 8601 with T and Z
formatted_date = utc_dt.strftime("%Y-%m-%dT%H:%M:%SZ")
# Add a new row to the Excel sheet
ws.append([current_id, urls[i], formatted_date])
current_id += 1
# Queue file for deletion
success_files.append(filename)
except Exception as e:
print(f"Error processing {filename}: {e}", file=sys.stderr)
# Save the Excel file
try:
wb.save(output_filename)
print(f"Successfully saved data to {output_filename}")
# Clean up only if save was successful
for filename in success_files:
os.remove(filename)
print(f"Deleted: {filename}")
except Exception as e:
print(f"Failed to save {output_filename}. No text files were deleted. Error: {e}", file=sys.stderr)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Extract URLs to an Excel file with ISO UTC dates.")
parser.add_argument("start_id", type=int, help="Starting ID for the output")
parser.add_argument("--output", type=str, default="extracted_data.xlsx",
help="Output Excel filename (default: extracted_data.xlsx)")
args = parser.parse_args()
process_files(args.start_id, args.output)

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@@ -62,4 +62,4 @@ význam?
- Sázka AS Roma +0.5: prohra (virtuální skóre 2 : 1.5)
- Sázka AS Roma +1: storno (virtuální skóre 2 : 2, vrací se vklad)
- Vin chce implementovat: rohy, karty, offside, střelci

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@@ -1,13 +0,0 @@
from pydantic.dataclasses import dataclass
from beaky.image_classifier.config import ImgClassifierConfig
from beaky.resolvers.config import ResolverConfig
from beaky.screenshotter.config import ScreenshotterConfig
@dataclass
class Config:
path: str
screenshotter: ScreenshotterConfig
resolver: ResolverConfig
img_classifier: ImgClassifierConfig

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@@ -1,194 +0,0 @@
import datetime
import logging
import re
from pathlib import Path
from pytesseract import pytesseract
from beaky.datamodels.ticket import (
Advance,
Bet,
BetType,
BothTeamScored,
GoalAmount,
GoalHandicap,
Ticket,
UnknownBet,
WinDrawLose,
WinDrawLoseDouble,
WinLose,
)
def img_to_text(path: str) -> str:
"""Given a path to an image, return the text contained in that image.
Bypasses PIL and lets Tesseract read the file directly.
"""
try:
text = pytesseract.image_to_string(path, lang="ces")
return text.strip()
except pytesseract.TesseractNotFoundError:
print("Error: Tesseract executable not found on your system.")
return ""
except Exception as e:
print(f"Error processing {path}: {e}")
return ""
def classify(text: str) -> Bet:
"""Given text extracted from an image and a date, return a Bet object that is
relevant to that text."""
logger = logging.getLogger(__name__)
if not text:
return UnknownBet(
ticketType=BetType.UNKNOWN,
team1Name="N/A",
team2Name="N/A",
date=datetime.datetime.now(),
league="N/A",
raw_text="No text extracted",
)
# 1. Defaults & Normalization
text_lower = text.lower()
date_obj = datetime.datetime.now()
team1, team2 = "Unknown", "Unknown"
league = "Unknown"
# 2. Heuristic extraction of Teams (Looking for "Team A - Team B" patterns)
lines = [line.strip() for line in text.split("\n") if line.strip()]
for line in lines:
if " - " in line or " vs " in line or " v " in line:
# Avoid splitting on hyphens in dates or numbers
if not re.search(r"\d\s*-\s*\d", line):
parts = re.split(r" - | vs | v ", line)
if len(parts) >= 2:
team1, team2 = parts[0].strip(), parts[1].strip()
break
# 3. Heuristic extraction of Date (Looking for DD.MM. YYYY HH:MM)
date_match = re.search(r"(\d{1,2}\.\s*\d{1,2}\.?\s*(?:\d{2,4})?)\s*(\d{1,2}:\d{2})?", text)
if date_match:
try:
# Fallback to current year if missing, basic parse attempt
date_str = f"{date_match.group(1).replace(' ', '')} {date_match.group(2) or '00:00'}"
if len(date_str.split(".")[2]) <= 5: # Missing year
date_str = date_str.replace(" ", f"{datetime.datetime.now().year} ")
date_obj = datetime.datetime.strptime(date_str, "%d.%m.%Y %H:%M")
except Exception:
pass # Keep default if parsing fails
# 4. Classification Logic based on keywords
base_args = {"team1Name": team1, "team2Name": team2, "date": date_obj, "league": league}
# Advance / Postup
if any(kw in text_lower for kw in ["postup", "postoupí", "advance"]):
return Advance(ticketType=BetType.ADVANCED, **base_args)
# Both Teams to Score / Oba dají gól
if any(kw in text_lower for kw in ["oba dají gól", "btts", "oba týmy dají gól"]):
return BothTeamScored(ticketType=BetType.BOTH_TEAM_SCORED, **base_args)
# Goal Amount (Over/Under)
if any(kw in text_lower for kw in ["počet gólů", "více než", "méně než", "over", "under"]):
# Attempt to find the goal line (e.g., 2.5, 3.5)
line_match = re.search(r"(\d+\.\d+)", text)
line_val = float(line_match.group(1)) if line_match else 2.5
is_over = any(kw in text_lower for kw in ["více", "over", "+"])
return GoalAmount(ticketType=BetType.GOAL_AMOUNT, line=line_val, over=is_over, **base_args)
# Goal Handicap
if any(kw in text_lower for kw in ["handicap", "hcp"]):
hcp_match = re.search(r"([+-]?\d+\.\d+)", text)
hcp_val = float(hcp_match.group(1)) if hcp_match else 0.0
# Simplistic logic: guess team 1 if not explicitly stated
team_bet = "2" if " 2 " in text else "1"
return GoalHandicap(ticketType=BetType.GOAL_HANDICAP, team_bet=team_bet, handicap_amount=hcp_val, **base_args)
# Win Draw Lose Double (1X, X2, 12)
if any(kw in text_lower for kw in ["1x", "x2", "12", "dvojitá šance", "neprohra"]):
bet_type = "01" if "1x" in text_lower else "02" if "x2" in text_lower else "12"
return WinDrawLoseDouble(ticketType=BetType.WIN_DRAW_LOSE_DOUBLE, betType=bet_type, **base_args)
# Win Lose (Draw no bet / Vítěz do rozhodnutí)
if any(kw in text_lower for kw in ["bez remízy", "vítěz do rozhodnutí", "konečný vítěz"]):
bet_type = "2" if re.search(r"\b2\b", text) else "1"
return WinLose(ticketType=BetType.WIN_LOSE, betType=bet_type, **base_args)
# Win Draw Lose (Standard Match Odds)
if any(kw in text_lower for kw in ["zápas", "výsledek zápasu", "1x2"]):
# Look for isolated 1, X (or 0), or 2
match_pick = re.search(r"\b(1|x|0|2)\b", text_lower)
bet_type = match_pick.group(1).upper() if match_pick else "1"
if bet_type == "X":
bet_type = "0"
return WinDrawLose(ticketType=BetType.WIN_DRAW_LOSE, betType=bet_type, **base_args)
# Fallback Unknown
return UnknownBet(ticketType=BetType.UNKNOWN, raw_text=text, **base_args)
def img_classify(paths: list[str], ticket_id: int) -> Ticket:
"""Given a path to an image and a date, return a list of Tickets that are
relevant to that image and date."""
# Define valid image extensions to ignore system files or text documents
ticket = Ticket(id=ticket_id, bets=[])
valid_extensions = {".png", ".jpg", ".jpeg", ".bmp", ".tiff", ".webp"}
# Iterate through all files in the folder
for file in paths:
file_path = Path(file)
if file_path.is_file() and file_path.suffix.lower() in valid_extensions:
# 1. Extract the text (called separately)
extracted_text = img_to_text(str(file_path))
print(extracted_text)
# 2. Classify based on the extracted text (called separately)
try:
result = classify(extracted_text)
except Exception as exc: # pragma: no cover - defensive fallback
# Ensure result is always defined so downstream code cannot reference an unbound name
print(f"classify() raised an exception: {exc}")
result = UnknownBet(
ticketType=BetType.UNKNOWN,
team1Name="N/A",
team2Name="N/A",
league="N/A",
raw_text=extracted_text,
date=datetime.datetime.now(),
)
# 3. Add the resulting tickets to our main list
# Support classifier returning either a single Bet or a list of Bet
if result is None:
continue
if isinstance(result, list):
for r in result:
print(
r.date,
getattr(r, "ticketType", None),
r.team1Name,
r.team2Name,
r.league,
)
ticket.bets.extend(result)
else:
print(
result.date,
getattr(result, "ticketType", None),
result.team1Name,
result.team2Name,
result.league,
)
ticket.bets.append(result)
return ticket
if __name__ == "__main__":
img_classify(["./data/screenshots/2.png"], ticket_id=1)