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0_0_lines is the simplest sample game. It covers the core lines win type with wild multipliers, a dedicated freegame reelset, and scatter-triggered freespins.

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Game overview

PropertyValue
Reels5
Rows3 (all reels)
Win typeLines
Paylines20
Win cap5000×
Target RTP97%
SymbolsH1–H4, L1–L5, Wild (W), Scatter (S)

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How to run

make run GAME=0_0_lines
Or directly: 
python3 games/0_0_lines/run.py

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Mechanics

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Basegame

  • Standard 20-payline evaluation left-to-right.
  • Scatter (S) appears on all 5 reels. Minimum 3 Scatters trigger the freegame.
  • Freespin awards: 3S → 8 spins, 4S → 12 spins, 5S → 15 spins.
  • Wild (W) substitutes for all paying symbols.

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Freegame

  • A separate reelset (FR0.csv) is used — denser with Wilds and higher-value symbols.
  • Wilds carry multipliers (minimum 2×). Multipliers add together across all Wilds on a winning line, then multiply the base line win.
  • Retrigger: 2+ Scatters on reels 2, 3, 4 award extra spins (2S → 3, 3S → 5, 4S → 8, 5S → 12).
Wild multipliers in this game are additive, not multiplicative. Two 3× Wilds on the same line produce a 6× multiplier applied to the line win, not 9×. This differs from the Ways game, where multipliers compound.

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Wild multiplier rule

Wilds only pay on 5-of-a-kind by default. If the paytable includes 3- or 4-kind Wild payouts, the line calculation will select whichever combination yields the highest payout. For example: a 3-kind Wild on a line where there is also a 5-kind L4 — the 3-kind Wild is chosen if paytable[(3, "W")] > paytable[(5, "L4")], regardless of the multiplier on the Wild.

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Configuration

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Paytable (game_config.py)

self.paytable = {
    (5, "W"): 50,  (4, "W"): 20,  (3, "W"): 10,
    (5, "H1"): 50, (4, "H1"): 20, (3, "H1"): 10,
    (5, "H2"): 15, (4, "H2"): 5,  (3, "H2"): 3,
    (5, "H3"): 10, (4, "H3"): 3,  (3, "H3"): 2,
    (5, "H4"): 8,  (4, "H4"): 2,  (3, "H4"): 1,
    (5, "L1"): 5,  (4, "L1"): 1,  (3, "L1"): 0.5,
    (5, "L2"): 3,  (4, "L2"): 0.7,(3, "L2"): 0.3,
    (5, "L3"): 3,  (4, "L3"): 0.7,(3, "L3"): 0.3,
    (5, "L4"): 2,  (4, "L4"): 0.5,(3, "L4"): 0.2,
    (5, "L5"): 1,  (4, "L5"): 0.3,(3, "L5"): 0.1,
}

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Reelsets

reels = {"BR0": "BR0.csv", "FR0": "FR0.csv", "WCAP": "FRWCAP.csv"}
  • BR0 — basegame reelset.
  • FR0 — freegame reelset (higher Wild density).
  • WCAP — wincap freegame reelset (higher multiplier density for forced max-win simulations).

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Wild multiplier distribution

Padding symbols carry multiplier attributes drawn from a weighted distribution: 
self.padding_symbol_values = {
    "W": {"multiplier": {2: 100, 3: 50, 4: 50, 5: 50, 10: 30, 20: 20, 50: 5}}
}

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Freespin triggers

self.freespin_triggers = {
    self.basegame_type: {3: 8, 4: 12, 5: 15},
    self.freegame_type: {2: 3, 3: 5, 4: 8, 5: 12},
}

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Bet modes

Two bet modes are configured:
  • base (cost 1×, is_feature=True) — standard play with scatter-triggered freegame.
  • bonus (cost 100×, is_buybonus=True) — direct freegame entry (buy bonus).
Each mode defines Distribution objects covering wincap, freegame, zero-win (0), and basegame simulation criteria with corresponding reel weights and multiplier distributions.

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Game flow (gamestate.py)

def run_spin(self, sim, simulation_seed=None):
    self.reset_seed(sim)
    self.repeat = True
    while self.repeat:
        self.reset_book()
        self.draw_board()

        # Evaluate wins, update wallet, transmit events
        self.evaluate_lines_board()

        self.win_manager.update_gametype_wins(self.gametype)
        if self.check_fs_condition():
            self.run_freespin_from_base()

        self.evaluate_finalwin()
        self.check_repeat()
    self.imprint_wins()

def run_freespin(self):
    self.reset_fs_spin()
    while self.fs < self.tot_fs:
        self.update_freespin()
        self.draw_board()

        self.evaluate_lines_board()

        if self.check_fs_condition():
            self.update_fs_retrigger_amt()

        self.win_manager.update_gametype_wins(self.gametype)

    self.end_freespin()
evaluate_lines_board() is inherited from the SDK’s Executables layer and handles Wild substitution, multiplier application, and event emission in a single call.

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Output files

After running, results appear in games/0_0_lines/library/:
FileContents
books/books_base.jsonlOne JSON object per simulation: id, payoutMultiplier, events, criteria
books/books_bonus.jsonlSame structure for the bonus (buy-bonus) mode
lookup_tables/lookUpTable_base.csvid, weight, payoutMultiplier — used by the optimizer and RGS
lookup_tables/lookUpTableIdToCriteria_base.csvMaps each simulation ID to its distribution criteria
To inspect output in human-readable form, set compression = False and run with a small num_sim_args value in run.py.
To explore event structure interactively, set "base": 100 and compression = False in run.py, then open library/books/books_base.jsonl in any JSON viewer. Each entry includes the full events array returned to the RGS.

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