Czech Athletics Scraper

Apify actor that scrapes public results from atletika.cz, the official website of the Czech Athletics Federation.

The actor exposes three independent scrapers — meet results, athlete profiles, and calendar lookup — and returns raw parsed dictionaries. It performs no ETL, aggregation, or post-processing; downstream consumers are expected to transform the records into whatever shape they need.

Modes

Set the mode input to one of:

Mode	Inputs used	Returned records
meet	meetIds: int[]	One row per athlete performance (or attempt for field/vertical events). record_type = "meet_result".
athlete	athleteIds: int[]	Athlete profile (record_type = "athlete_profile"), plus one row per medal (athlete_medal) and one row per achievement entry (athlete_achievement).
calendar	dateFrom, dateTo (YYYY-MM-DD)	One row per meet ID found in the range. record_type = "calendar_meet_id".

All records are pushed to a single default dataset. Use the record_type field to route them.

Inputs

Field	Type	Description
mode	string (enum)	meet, athlete, or calendar.
meetIds	int[]	Meet IDs to scrape (for mode = meet).
athleteIds	int[]	Athlete CAS IDs to scrape (for mode = athlete).
dateFrom	string	ISO date, defaults to today (for mode = calendar).
dateTo	string	ISO date, defaults to dateFrom + 31 days.
requestDelayMs	int	Delay between HTTP requests.
requestTimeoutSecs	int	Per-request timeout. Defaults to 30.
proxyConfiguration	object	Apify Proxy config. Recommended — atletika.cz rate-limits aggressively.

Output Data Structure

All records are pushed to a single default dataset. Use the record_type field to route them in your downstream pipelines.

1. Meet Results (mode = "meet")

{
  "meet_id": "Integer: Unique identifier of the athletics meet",
  "meet_name": "String: Official name of the competition",
  "location": "String: Competition location",
  "date": "String: Competition date (YYYY-MM-DD)",
  "time": "String: Event start time or null",
  "is_indoor": "Boolean: Indoor or outdoor competition flag",
  "event_id": "String: Unique identifier of the event",
  "discipline": "String: Discipline name",
  "specification": "String: Event-specific parameters (e.g., hurdle height, javelin weight) or null",
  "main_phase": "String: Main competition phase (e.g., Final, Heat, Qualification)",
  "sub_phase": "String: Subdivision of phase (e.g., Heat 2, Final A)",
  "name": "String: Athlete name",
  "cas_id": "String: Unique federation athlete identifier",
  "category": "String: Competition category",
  "sex": "String: Athlete sex (M/Z)",
  "birth_year": "String: Athlete birth year",
  "age": "Integer: Athlete age at competition date",
  "team": "String: Represented club",
  "lane": "Integer: Assigned lane number or null",
  "order": "Integer: Starting order or null",
  "reaction": "Float: Reaction time or null",
  "performance_raw": "String: Original result text as displayed on the website",
  "numeric_value": "Float: Parsed numerical performance value",
  "wind": "Float: Wind measurement value or null",
  "wa_points": "Integer: World Athletics scoring points",
  "height": "Float: Height value for vertical jump events or null",
  "attempt_in_series": "Integer: Attempt sequence identifier or null",
  "position": "String: Final competition placement",
  "record": "String: Performance status marker (e.g., PB, SB, MR) or null",
  "dq_rule": "String: Disqualification rule code or null",
  "trial_id": "String: Unique UUID of the result record",
  "record_type": "String: Always 'meet_result'"
}

2. Athlete Data (mode = "athlete")

Athlete Info

{
  "cas_id": "Integer: Athlete official CAS federation ID",
  "name": "String: Athlete full name",
  "birth_year": "Integer: Athlete birth year",
  "club": "String: Current represented club",
  "coach_1": "String: Primary coach or null",
  "coach_2": "String: Secondary coach or null",
  "coach_3": "String: Tertiary coach or null",
  "registration_until": "String: Registration validity date (YYYY-MM-DD)",
  "record_type": "String: Always 'athlete_profile'"
}

Athlete Medals

{
  "medal_id": "String: Unique UUID of the medal record",
  "cas_id": "Integer: Athlete official CAS federation ID",
  "year": "Integer: Year of the championship",
  "placement": "Integer: Final placement (1, 2, or 3)",
  "category": "String: Championship category (e.g., MČR)",
  "type": "String: Environment (e.g., dráha, hala)",
  "discipline": "String: Discipline name",
  "location": "String: Host city/location",
  "performance_raw": "String: Original result text",
  "numeric_value": "Float: Parsed numerical performance value",
  "record_type": "String: Always 'athlete_medal'"
}

Athlete Achievements

{
  "achievement_id": "String: Unique UUID of the achievement record",
  "cas_id": "Integer: Athlete official CAS federation ID",
  "year": "Integer: Year of the event",
  "event_name": "String: Name of the major event (e.g., OH, MS)",
  "discipline": "String: Discipline name",
  "result_phase": "String: Reached phase or placement",
  "record_type": "String: Always 'athlete_achievement'"
}

3. Calendar (mode = "calendar")

{
  "record_type": "String: Always 'calendar_meet_id'",
  "meet_id": "Integer: Unique identifier of the meet"
}

Scoring

Meet results include a wa_points field computed via the quadratic model. Coefficients live in src/coefficients-2025.json; replacing that file is all that's required to migrate to a future edition of the tables. The methodology follows Jeff Chen's iaaf-scoring-tables.

Development

Local run (without Apify platform):

pip install -r requirements.txt
$env:APIFY_LOCAL_STORAGE_DIR="apify_storage"; python -m src

The actor reads its input via the standard Apify input mechanism — for local runs, place an apify_storage/key_value_stores/default/INPUT.json file with the desired input.

Layout

.actor/
    actor.json          # Actor metadata
    input_schema.json   # Input UI schema
Dockerfile              # Build recipe
requirements.txt        # apify, requests, selectolax
src/
    __main__.py         # python -m src entrypoint
    main.py             # Async actor orchestrator
    scraper.py          # HTML fetch + parsing logic
    cas_config.py       # Discipline / category / WA mappings
    calculator.py       # Spiriev points calculator
    coefficients-2025.json