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Fix merging of data frames for payments #453

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merged 5 commits into from
Dec 12, 2024
Merged

Fix merging of data frames for payments #453

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bdf7113
make solver_name a column of reward target
fhenneke Dec 9, 2024
27966e8
correctly handle empty service fee results
fhenneke Dec 9, 2024
fb30846
restrict dataframes before merging
fhenneke Dec 9, 2024
69c195a
fix tests
fhenneke Dec 9, 2024
e61c8b0
Merge branch 'main' into restrict_dataframes_before_merging
harisang Dec 9, 2024
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37 changes: 18 additions & 19 deletions src/fetch/payouts.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,10 +36,9 @@
}
SLIPPAGE_COLUMNS = {
"solver",
"solver_name",
"eth_slippage_wei",
}
REWARD_TARGET_COLUMNS = {"solver", "reward_target", "pool_address"}
REWARD_TARGET_COLUMNS = {"solver", "solver_name", "reward_target", "pool_address"}
SERVICE_FEE_COLUMNS = {"solver", "service_fee"}
ADDITIONAL_PAYMENT_COLUMNS = {"buffer_accounting_target", "reward_token_address"}

Expand Down Expand Up @@ -416,9 +415,12 @@ def construct_payout_dataframe(

# 3. Merge the three dataframes (joining on solver)
merged_df = (
payment_df.merge(slippage_df, on=join_column, how="left")
.merge(reward_target_df, on=join_column, how="left")
.merge(service_fee_df, on=join_column, how="left")
payment_df[list(PAYMENT_COLUMNS)]
.merge(slippage_df[list(SLIPPAGE_COLUMNS)], on=join_column, how="left")
.merge(
reward_target_df[list(REWARD_TARGET_COLUMNS)], on=join_column, how="left"
)
.merge(service_fee_df[list(SERVICE_FEE_COLUMNS)], on=join_column, how="left")
)

# 4. Add slippage from fees to slippage
Expand Down Expand Up @@ -510,11 +512,15 @@ def construct_payouts(
quote_rewards_df, batch_rewards_df, on="solver", how="outer"
).fillna(0)

service_fee_df = pandas.DataFrame(dune.get_service_fee_status())
service_fee_df["service_fee"] = [
service_fee_flag * config.reward_config.service_fee_factor
for service_fee_flag in service_fee_df["service_fee"]
]
service_fee_dune = dune.get_service_fee_status()
if service_fee_dune:
service_fee_df = pandas.DataFrame(service_fee_dune)
service_fee_df["service_fee"] = [
service_fee_flag * config.reward_config.service_fee_factor
for service_fee_flag in service_fee_df["service_fee"]
]
else:
service_fee_df = DataFrame(columns=["solver", "service_fee"])

vouches = dune.get_vouches()
if vouches:
Expand All @@ -525,15 +531,8 @@ def construct_payouts(
)
# construct slippage df
if ignore_slippage_flag or (not config.buffer_accounting_config.include_slippage):
slippage_df_temp = pandas.merge(
merged_df[["solver"]],
reward_target_df[["solver", "solver_name"]],
on="solver",
how="inner",
)
slippage_df = slippage_df_temp.assign(
eth_slippage_wei=[0] * slippage_df_temp.shape[0]
)
slippage_df = merged_df[["solver"]].copy()
slippage_df["eth_slippage_wei"] = [0] * slippage_df.shape[0]
else:
slippage_df = pandas.DataFrame(dune.get_period_slippage())
# TODO - After CIP-20 phased in, adapt query to return `solver` like all the others
Expand Down
67 changes: 34 additions & 33 deletions tests/unit/test_payouts.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,11 +153,9 @@ def test_validate_df_columns(self):
"quote_reward_cow": [],
}
)
legit_slippages = DataFrame(
{"solver": [], "solver_name": [], "eth_slippage_wei": []}
)
legit_slippages = DataFrame({"solver": [], "eth_slippage_wei": []})
legit_reward_targets = DataFrame(
{"solver": [], "reward_target": [], "pool_address": []}
{"solver": [], "solver_name": [], "reward_target": [], "pool_address": []}
)
legit_service_fees = DataFrame({"solver": [], "service_fee": []})

Expand Down Expand Up @@ -221,14 +219,14 @@ def test_construct_payouts(self):
"solver": self.solvers[:3],
# Note that one of the solvers did not appear,
# in this list (we are testing the left join)
"solver_name": ["S_1", "S_2", "S_3"],
"eth_slippage_wei": [1, 0, -1],
}
)

reward_targets = DataFrame(
{
"solver": self.solvers,
"solver_name": ["S_1", "S_2", "S_3", "S_4"],
"reward_target": self.reward_targets,
"pool_address": self.pool_addresses,
}
Expand All @@ -247,69 +245,72 @@ def test_construct_payouts(self):
)
expected = DataFrame(
{
"solver": self.solvers,
"num_quotes": self.num_quotes,
"primary_reward_eth": [600000000000000.0, 1.2e16, -1e16, 0.0],
"protocol_fee_eth": [
1000000000000000.0,
2000000000000000.0,
0.0,
0.0,
"buffer_accounting_target": [
"0x0000000000000000000000000000000000000005",
str(self.solvers[1]),
str(self.solvers[2]),
str(self.solvers[3]),
],
"eth_slippage_wei": [2000000000000001.0, 4000000000000000.0, -1.0, 0.0],
"network_fee_eth": [
2000000000000000.0,
4000000000000000.0,
0.0,
0.0,
],
"pool_address": [
str(self.config.reward_config.cow_bonding_pool),
"0x0000000000000000000000000000000000000010",
"0x0000000000000000000000000000000000000011",
"0x0000000000000000000000000000000000000012",
],
"primary_reward_cow": [
600000000000000000.0,
12000000000000000000.0,
-10000000000000000000.0,
0.0,
],
"primary_reward_eth": [600000000000000.0, 1.2e16, -1e16, 0.0],
"protocol_fee_eth": [
1000000000000000.0,
2000000000000000.0,
0.0,
0.0,
],
"quote_reward_cow": [
0.00000,
0.00000,
6000000000000000000.00000,
12000000000000000000.00000,
],
"solver_name": ["S_1", "S_2", "S_3", None],
"eth_slippage_wei": [2000000000000001.0, 4000000000000000.0, -1.0, 0.0],
"reward_target": [
"0x0000000000000000000000000000000000000005",
"0x0000000000000000000000000000000000000006",
"0x0000000000000000000000000000000000000007",
"0x0000000000000000000000000000000000000008",
],
"pool_address": [
str(self.config.reward_config.cow_bonding_pool),
"0x0000000000000000000000000000000000000010",
"0x0000000000000000000000000000000000000011",
"0x0000000000000000000000000000000000000012",
"reward_token_address": [
str(self.config.reward_config.reward_token_address),
str(self.config.reward_config.reward_token_address),
str(self.config.reward_config.reward_token_address),
str(self.config.reward_config.reward_token_address),
],
"service_fee": [
Fraction(0, 100),
Fraction(0, 100),
Fraction(0, 100),
Fraction(15, 100),
],
"buffer_accounting_target": [
"0x0000000000000000000000000000000000000005",
str(self.solvers[1]),
str(self.solvers[2]),
str(self.solvers[3]),
],
"reward_token_address": [
str(self.config.reward_config.reward_token_address),
str(self.config.reward_config.reward_token_address),
str(self.config.reward_config.reward_token_address),
str(self.config.reward_config.reward_token_address),
],
"solver": self.solvers,
"solver_name": ["S_1", "S_2", "S_3", "S_4"],
}
)

self.assertIsNone(pandas.testing.assert_frame_equal(expected, result))
self.assertIsNone(
pandas.testing.assert_frame_equal(
expected, result.reindex(sorted(result.columns), axis=1)
)
)

def test_prepare_transfers(self):
# Need Example of every possible scenario
Expand Down
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