Rewards

CLOB rewards API endpoints (clob.polymarket.com/rewards/...) for querying reward configurations, earnings, and percentages.

Cursor-paginated methods return a CursorPage dict with keys data (DataFrame), next_cursor (str), count (int), limit (int). Pass next_cursor from the previous response to fetch the next page. The sentinel value "LTE=" indicates the last page. All cursor-paginated methods have corresponding _all() variants that auto-paginate.

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Public Endpoints

get_rewards_markets_current(sponsored=None, next_cursor=None, expand_rewards_config=False) -> CurrentRewardsCursorPage

Get all currently active reward configurations, organized by market. Cursor-paginated.

page = client.get_rewards_markets_current()
df = page["data"]        # DataFrame[CurrentRewardSchema]
cursor = page["next_cursor"]

# Auto-paginate all:
all_rewards = client.get_rewards_markets_current_all()

# Expand nested rewards_config into flat columns:
page = client.get_rewards_markets_current(expand_rewards_config=True)

Parameter	Type	Description
sponsored	bool	If True, returns sponsored reward configurations
next_cursor	str	Opaque cursor from a previous response
expand_rewards_config	bool	Flatten nested rewards_config list into prefixed columns

get_rewards_markets_multi(**kwargs) -> RewardsMarketMultiCursorPage

Get active markets with their reward configurations. Supports text search, tag filtering, numeric filters, and sorting. Cursor-paginated.

page = client.get_rewards_markets_multi(
    tag_slug="crypto",
    order_by="rate_per_day",
    position="DESC",
    expand_tokens=True,
)

Parameter	Type	Description
q	str	Text search on market question/description
tag_slug	str	Filter by tag slug
event_id	str	Filter by event ID
event_title	str	Case-insensitive event title search
order_by	str	Sort field (e.g. "rate_per_day", "volume_24hr", "spread", "competitiveness")
position	str	Sort direction: "ASC" or "DESC"
min_volume_24hr / max_volume_24hr	float	24h volume filter range
min_spread / max_spread	float	Spread filter range
min_price / max_price	float	First-token price filter range
page_size	int	Items per page (max 500, default 100)
next_cursor	str	Opaque cursor from a previous response
expand_rewards_config	bool	Flatten nested rewards_config list
expand_tokens	bool	Flatten nested tokens list

get_rewards_market(condition_id, sponsored=None, next_cursor=None, expand_rewards_config=False, expand_tokens=False) -> RewardsMarketCursorPage

Get reward configurations for a specific market. Cursor-paginated.

page = client.get_rewards_market(
    condition_id="0xConditionId...",
    expand_rewards_config=True,
    expand_tokens=True,
)

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Private Endpoints (L2 Auth Required)

get_rewards_earnings(date, **kwargs) -> UserEarningsCursorPage

Get per-market user earnings for a specific day. Cursor-paginated.

page = client.get_rewards_earnings(date="2026-03-30")
df = page["data"]  # DataFrame[UserEarningSchema]

# Auto-paginate all:
all_earnings = client.get_rewards_earnings_all(date="2026-03-30")

Parameter	Type	Description
date	str	Target date in YYYY-MM-DD format
signature_type	int	Address derivation type (0=EOA, 1=POLY_PROXY, 2=POLY_GNOSIS_SAFE)
maker_address	str	Ethereum address to query
sponsored	bool	If True, filter to sponsored earnings only
next_cursor	str	Opaque cursor from a previous response

get_rewards_earnings_total(date, **kwargs) -> pd.DataFrame

Get total earnings for a user on a given day, grouped by asset. Not cursor-paginated.

totals = client.get_rewards_earnings_total(date="2026-03-30")
# columns: date, assetAddress, makerAddress, earnings, assetRate

get_rewards_percentages(signature_type=None, maker_address=None) -> dict

Get real-time reward percentages per market for a user. Returns a dict mapping condition_id to percentage (float).

pcts = client.get_rewards_percentages()
# {"0xConditionId1": 0.15, "0xConditionId2": 0.08, ...}

get_rewards_user_markets(**kwargs) -> UserRewardsMarketsCursorPage

Get user earnings combined with full market configurations. Supports search, filtering, and sorting. Cursor-paginated.

page = client.get_rewards_user_markets(
    date="2026-03-30",
    order_by="earnings",
    position="DESC",
    expand_tokens=True,
    expand_rewards_config=True,
    expand_earnings=True,
)

Parameter	Type	Description
date	str	Target date in YYYY-MM-DD format (defaults to today)
q	str	Text search on market question/description
tag_slug	str	Filter by tag slug
favorite_markets	bool	Filter to user-favorited markets only
no_competition	bool	Filter for markets with no competition
only_mergeable	bool	Filter for mergeable markets
only_open_orders	bool	Filter for markets with user's open orders
only_open_positions	bool	Filter for markets with user's open positions
order_by	str	Sort field (e.g. "earnings", "rate_per_day", "earning_percentage")
position	str	Sort direction: "ASC" or "DESC"
page_size	int	Items per page (max 500, default 100)
next_cursor	str	Opaque cursor from a previous response
expand_rewards_config	bool	Flatten nested rewards_config list
expand_tokens	bool	Flatten nested tokens list
expand_earnings	bool	Flatten nested earnings list