Implement CIP-36 (#339)

[CIP-36](https://snapshot.org/#/cow.eth/proposal/0x4e58f9c1208121c0e06282b5541b458bc8c8b76090263e25448848f3194df986)
changed the capping of rewards:
- Rewards are capped asymmetrically with an upper bound changed from
0.01ETH to 0.012ETH.
- The soft budget for rewards was changed from 306,645 COW to 250,000
COW.
- Consistency rewards are capped at 6ETH worth of COW tokens.
- Quoter rewards are the minumum of 6 COW and 0.0006 ETH worth of COW
per quote.

This PR implements these changes. These changes need be implemented in
dune-sync and on dune as well.

The scripts in this PR need to be used for the next payment.

queries/orderbook/batch_rewards.sql

@@ -205,10 +205,10 @@ reward_per_auction as (
         -- Capped Reward = CLAMP_[-E, E + exec_cost](uncapped_reward_eth)
         LEAST(
             GREATEST(
-                - {{EPSILON}},
+                - {{EPSILON_LOWER}},
                 surplus + protocol_fee + fee - network_fee_correction - reference_score
             ),
-            {{EPSILON}} + execution_cost
+            {{EPSILON_UPPER}} + execution_cost
         ) as capped_payment,
         winning_score,
         reference_score,

src/fetch/payouts.py

@@ -1,4 +1,5 @@
 """Logic for Post CIP 20 Solver Payout Calculation"""
+
 from __future__ import annotations
 
 import logging
@@ -22,8 +23,10 @@
 from src.pg_client import MultiInstanceDBFetcher
 from src.utils.print_store import Category
 
-PERIOD_BUDGET_COW = 306646 * 10**18
-QUOTE_REWARD = 9 * 10**18
+PERIOD_BUDGET_COW = 250000 * 10**18
+CONSISTENCY_REWARD_CAP_ETH = 6 * 10**18
+QUOTE_REWARD_COW = 6 * 10**18
+QUOTE_REWARD_CAP_ETH = 6 * 10**14
 
 PROTOCOL_FEE_SAFE = Address("0xB64963f95215FDe6510657e719bd832BB8bb941B")
 
@@ -270,7 +273,13 @@ def extend_payment_df(pdf: DataFrame, converter: TokenConversion) -> DataFrame:
     pdf["reward_eth"] = pdf["payment_eth"] - pdf["execution_cost_eth"]
     pdf["reward_cow"] = pdf["reward_eth"].apply(converter.eth_to_token)
 
-    secondary_allocation = max(PERIOD_BUDGET_COW - pdf["reward_cow"].sum(), 0)
+    secondary_allocation = max(
+        min(
+            PERIOD_BUDGET_COW - pdf["reward_cow"].sum(),
+            converter.eth_to_token(CONSISTENCY_REWARD_CAP_ETH),
+        ),
+        0,
+    )
     participation_total = pdf["num_participating_batches"].sum()
     pdf["secondary_reward_cow"] = (
         secondary_allocation * pdf["num_participating_batches"] / participation_total
@@ -281,7 +290,10 @@ def extend_payment_df(pdf: DataFrame, converter: TokenConversion) -> DataFrame:
 
     # Pandas has poor support for large integers, must cast the constant to float here,
     # otherwise the dtype would be inferred as int64 (which overflows).
-    pdf["quote_reward_cow"] = float(QUOTE_REWARD) * pdf["num_quotes"]
+    pdf["quote_reward_cow"] = (
+        float(min(QUOTE_REWARD_COW, converter.eth_to_token(QUOTE_REWARD_CAP_ETH)))
+        * pdf["num_quotes"]
+    )
 
     for number_col in NUMERICAL_COLUMNS:
         pdf[number_col] = pandas.to_numeric(pdf[number_col])

src/pg_client.py

@@ -34,7 +34,8 @@ def get_solver_rewards(self, start_block: str, end_block: str) -> DataFrame:
             open_query("orderbook/batch_rewards.sql")
             .replace("{{start_block}}", start_block)
             .replace("{{end_block}}", end_block)
-            .replace("{{EPSILON}}", "10000000000000000")
+            .replace("{{EPSILON_LOWER}}", "10000000000000000")
+            .replace("{{EPSILON_UPPER}}", "12000000000000000")
         )
         results = [
             self.exec_query(query=batch_reward_query, engine=engine)

tests/queries/test_batch_rewards.py

@@ -31,8 +31,8 @@ def test_get_batch_rewards(self):
                 "payment_eth": [
                     9.534313722772278e15,
                     10.5e15,
-                    600000000000000.00000,
-                    10450000000000000.00000,
+                    6600000000000000.00000,
+                    12450000000000000.00000,
                     -10000000000000000.00000,
                     0.00000,
                 ],

tests/unit/test_payouts.py

@@ -13,7 +13,7 @@
     TokenConversion,
     prepare_transfers,
     RewardAndPenaltyDatum,
-    QUOTE_REWARD,
+    QUOTE_REWARD_COW,
     PROTOCOL_FEE_SAFE,
 )
 from src.models.accounting_period import AccountingPeriod
@@ -110,22 +110,22 @@ def test_extend_payment_df(self):
                 0,
             ],
             "secondary_reward_cow": [
-                97569245454545450000000.00000,
-                27876927272727270000000.00000,
-                97569245454545450000000.00000,
-                83630781818181820000000.00000,
+                1909090909090909000000.00000,
+                545454545454545440000.00000,
+                1909090909090909000000.00000,
+                1636363636363636200000.00000,
             ],
             "secondary_reward_eth": [
-                97569245454545450000.00000,
-                27876927272727273000.00000,
-                97569245454545450000.00000,
-                83630781818181810000.00000,
+                1909090909090909000.00000,
+                545454545454545440.00000,
+                1909090909090909000.00000,
+                1636363636363636200.00000,
             ],
             "quote_reward_cow": [
                 0.00000,
                 0.00000,
-                90000000000000000000.00000,
-                180000000000000000000.00000,
+                6000000000000000000.00000,
+                12000000000000000000.00000,
             ],
         }
         expected = DataFrame(expected_data_dict)
@@ -244,22 +244,22 @@ def test_construct_payouts(self):
                     0,
                 ],
                 "secondary_reward_cow": [
-                    97569245454545450000000.00000,
-                    27876927272727270000000.00000,
-                    97569245454545450000000.00000,
-                    83630781818181820000000.00000,
+                    1909090909090909000000.00000,
+                    545454545454545440000.00000,
+                    1909090909090909000000.00000,
+                    1636363636363636200000.00000,
                 ],
                 "secondary_reward_eth": [
-                    97569245454545450000.00000,
-                    27876927272727273000.00000,
-                    97569245454545450000.00000,
-                    83630781818181810000.00000,
+                    1909090909090909000.00000,
+                    545454545454545440.00000,
+                    1909090909090909000.00000,
+                    1636363636363636200.00000,
                 ],
                 "quote_reward_cow": [
                     0.00000,
                     0.00000,
-                    90000000000000000000.00000,
-                    180000000000000000000.00000,
+                    6000000000000000000.00000,
+                    12000000000000000000.00000,
                 ],
                 "solver_name": ["S_1", "S_2", "S_3", None],
                 "eth_slippage_wei": [1.0, 0.0, -1.0, None],
@@ -401,7 +401,7 @@ def sample_record(
             secondary_reward_eth=participation,
             secondary_reward_cow=participation * self.conversion_rate,
             slippage_eth=slippage,
-            quote_reward_cow=QUOTE_REWARD * num_quotes,
+            quote_reward_cow=QUOTE_REWARD_COW * num_quotes,
         )
 
     def test_invalid_input(self):