rosacastillo
commited on
Commit
·
10a7862
1
Parent(s):
580ec7b
Added RPC env variable. New updated data
Browse files- data/all_trades_profitability.parquet +2 -2
- data/delivers.parquet +2 -2
- data/fpmmTrades.parquet +2 -2
- data/fpmms.parquet +2 -2
- data/invalid_trades.parquet +2 -2
- data/requests.parquet +2 -2
- data/summary_profitability.parquet +2 -2
- data/t_map.pkl +2 -2
- data/tools.parquet +2 -2
- data/tools_accuracy.csv +1 -1
- notebooks/weekly_analysis.ipynb +25 -247
- scripts/pull_data.py +22 -8
- scripts/tools.py +35 -21
- scripts/utils.py +1 -0
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|
737 |
"metadata": {},
|
738 |
"outputs": [
|
739 |
{
|
@@ -741,31 +519,31 @@
|
|
741 |
"output_type": "stream",
|
742 |
"text": [
|
743 |
"<class 'pandas.core.frame.DataFrame'>\n",
|
744 |
-
"RangeIndex:
|
745 |
"Data columns (total 19 columns):\n",
|
746 |
" # Column Non-Null Count Dtype \n",
|
747 |
"--- ------ -------------- ----- \n",
|
748 |
-
" 0 trader_address
|
749 |
-
" 1 trade_id
|
750 |
-
" 2 creation_timestamp
|
751 |
-
" 3 title
|
752 |
-
" 4 market_status
|
753 |
-
" 5 collateral_amount
|
754 |
-
" 6 outcome_index
|
755 |
-
" 7 trade_fee_amount
|
756 |
-
" 8 outcomes_tokens_traded
|
757 |
-
" 9 current_answer
|
758 |
-
" 10 is_invalid
|
759 |
-
" 11 winning_trade
|
760 |
-
" 12 earnings
|
761 |
-
" 13 redeemed
|
762 |
-
" 14 redeemed_amount
|
763 |
-
" 15 num_mech_calls
|
764 |
-
" 16 mech_fee_amount
|
765 |
-
" 17 net_earnings
|
766 |
-
" 18 roi
|
767 |
"dtypes: bool(3), datetime64[ns, UTC](1), float64(8), int64(2), object(5)\n",
|
768 |
-
"memory usage: 2.
|
769 |
]
|
770 |
}
|
771 |
],
|
|
|
9 |
},
|
10 |
{
|
11 |
"cell_type": "code",
|
12 |
+
"execution_count": 1,
|
13 |
"metadata": {},
|
14 |
"outputs": [],
|
15 |
"source": [
|
|
|
22 |
},
|
23 |
{
|
24 |
"cell_type": "code",
|
25 |
+
"execution_count": 2,
|
26 |
"metadata": {},
|
27 |
"outputs": [],
|
28 |
"source": [
|
|
|
51 |
},
|
52 |
{
|
53 |
"cell_type": "code",
|
54 |
+
"execution_count": 3,
|
55 |
"metadata": {},
|
56 |
"outputs": [],
|
57 |
"source": [
|
|
|
511 |
},
|
512 |
{
|
513 |
"cell_type": "code",
|
514 |
+
"execution_count": 4,
|
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|
515 |
"metadata": {},
|
516 |
"outputs": [
|
517 |
{
|
|
|
519 |
"output_type": "stream",
|
520 |
"text": [
|
521 |
"<class 'pandas.core.frame.DataFrame'>\n",
|
522 |
+
"RangeIndex: 17067 entries, 0 to 17066\n",
|
523 |
"Data columns (total 19 columns):\n",
|
524 |
" # Column Non-Null Count Dtype \n",
|
525 |
"--- ------ -------------- ----- \n",
|
526 |
+
" 0 trader_address 17067 non-null object \n",
|
527 |
+
" 1 trade_id 17067 non-null object \n",
|
528 |
+
" 2 creation_timestamp 17067 non-null datetime64[ns, UTC]\n",
|
529 |
+
" 3 title 17067 non-null object \n",
|
530 |
+
" 4 market_status 17067 non-null object \n",
|
531 |
+
" 5 collateral_amount 17067 non-null float64 \n",
|
532 |
+
" 6 outcome_index 17067 non-null object \n",
|
533 |
+
" 7 trade_fee_amount 17067 non-null float64 \n",
|
534 |
+
" 8 outcomes_tokens_traded 17067 non-null float64 \n",
|
535 |
+
" 9 current_answer 17067 non-null int64 \n",
|
536 |
+
" 10 is_invalid 17067 non-null bool \n",
|
537 |
+
" 11 winning_trade 17067 non-null bool \n",
|
538 |
+
" 12 earnings 17067 non-null float64 \n",
|
539 |
+
" 13 redeemed 17067 non-null bool \n",
|
540 |
+
" 14 redeemed_amount 17067 non-null float64 \n",
|
541 |
+
" 15 num_mech_calls 17067 non-null int64 \n",
|
542 |
+
" 16 mech_fee_amount 17067 non-null float64 \n",
|
543 |
+
" 17 net_earnings 17067 non-null float64 \n",
|
544 |
+
" 18 roi 17067 non-null float64 \n",
|
545 |
"dtypes: bool(3), datetime64[ns, UTC](1), float64(8), int64(2), object(5)\n",
|
546 |
+
"memory usage: 2.1+ MB\n"
|
547 |
]
|
548 |
}
|
549 |
],
|
scripts/pull_data.py
CHANGED
@@ -18,7 +18,7 @@ from tools import (
|
|
18 |
update_tools_accuracy,
|
19 |
)
|
20 |
from profitability import run_profitability_analysis
|
21 |
-
from utils import get_question, current_answer
|
22 |
from get_mech_info import get_mech_info_last_60_days
|
23 |
from update_tools_accuracy import compute_tools_accuracy
|
24 |
import gc
|
@@ -47,8 +47,7 @@ def parallelize_timestamp_conversion(df: pd.DataFrame, function: callable) -> li
|
|
47 |
return results
|
48 |
|
49 |
|
50 |
-
def
|
51 |
-
web3 = Web3(Web3.HTTPProvider(rpc))
|
52 |
# Get currentAnswer from FPMMS
|
53 |
fpmms = pd.read_parquet(DATA_DIR / MARKETS_FILENAME)
|
54 |
tools = pd.read_parquet(DATA_DIR / TOOLS_FILENAME)
|
@@ -60,12 +59,24 @@ def updating_timestamps(rpc: str):
|
|
60 |
|
61 |
tools["currentAnswer"] = tools["currentAnswer"].str.replace("yes", "Yes")
|
62 |
tools["currentAnswer"] = tools["currentAnswer"].str.replace("no", "No")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
63 |
|
64 |
# Convert block number to timestamp
|
65 |
logging.info("Converting block number to timestamp")
|
66 |
t_map = pickle.load(open(DATA_DIR / "t_map.pkl", "rb"))
|
67 |
tools["request_time"] = tools["request_block"].map(t_map)
|
68 |
|
|
|
|
|
|
|
69 |
# Identify tools with missing request_time and fill them
|
70 |
missing_time_indices = tools[tools["request_time"].isna()].index
|
71 |
if not missing_time_indices.empty:
|
@@ -104,14 +115,13 @@ def updating_timestamps(rpc: str):
|
|
104 |
|
105 |
# clean and release all memory
|
106 |
del tools
|
107 |
-
del fpmms
|
108 |
del t_map
|
109 |
gc.collect()
|
110 |
|
111 |
|
112 |
def weekly_analysis():
|
113 |
"""Run weekly analysis for the FPMMS project."""
|
114 |
-
rpc =
|
115 |
|
116 |
# Run markets ETL
|
117 |
logging.info("Running markets ETL")
|
@@ -137,8 +147,12 @@ def weekly_analysis():
|
|
137 |
rpc=rpc,
|
138 |
)
|
139 |
logging.info("Profitability analysis completed")
|
140 |
-
|
141 |
-
|
|
|
|
|
|
|
|
|
142 |
|
143 |
compute_tools_accuracy()
|
144 |
|
@@ -147,5 +161,5 @@ def weekly_analysis():
|
|
147 |
|
148 |
if __name__ == "__main__":
|
149 |
weekly_analysis()
|
150 |
-
# rpc =
|
151 |
# updating_timestamps(rpc)
|
|
|
18 |
update_tools_accuracy,
|
19 |
)
|
20 |
from profitability import run_profitability_analysis
|
21 |
+
from utils import get_question, current_answer, RPC
|
22 |
from get_mech_info import get_mech_info_last_60_days
|
23 |
from update_tools_accuracy import compute_tools_accuracy
|
24 |
import gc
|
|
|
47 |
return results
|
48 |
|
49 |
|
50 |
+
def add_current_answer():
|
|
|
51 |
# Get currentAnswer from FPMMS
|
52 |
fpmms = pd.read_parquet(DATA_DIR / MARKETS_FILENAME)
|
53 |
tools = pd.read_parquet(DATA_DIR / TOOLS_FILENAME)
|
|
|
59 |
|
60 |
tools["currentAnswer"] = tools["currentAnswer"].str.replace("yes", "Yes")
|
61 |
tools["currentAnswer"] = tools["currentAnswer"].str.replace("no", "No")
|
62 |
+
# Save the tools data after the updates on the content
|
63 |
+
tools.to_parquet(DATA_DIR / TOOLS_FILENAME, index=False)
|
64 |
+
del fpmms
|
65 |
+
|
66 |
+
|
67 |
+
def updating_timestamps(rpc: str):
|
68 |
+
web3 = Web3(Web3.HTTPProvider(rpc))
|
69 |
+
|
70 |
+
tools = pd.read_parquet(DATA_DIR / TOOLS_FILENAME)
|
71 |
|
72 |
# Convert block number to timestamp
|
73 |
logging.info("Converting block number to timestamp")
|
74 |
t_map = pickle.load(open(DATA_DIR / "t_map.pkl", "rb"))
|
75 |
tools["request_time"] = tools["request_block"].map(t_map)
|
76 |
|
77 |
+
no_data = tools["request_time"].isna().sum()
|
78 |
+
logging.info(f"Total rows with no request time info = {no_data}")
|
79 |
+
|
80 |
# Identify tools with missing request_time and fill them
|
81 |
missing_time_indices = tools[tools["request_time"].isna()].index
|
82 |
if not missing_time_indices.empty:
|
|
|
115 |
|
116 |
# clean and release all memory
|
117 |
del tools
|
|
|
118 |
del t_map
|
119 |
gc.collect()
|
120 |
|
121 |
|
122 |
def weekly_analysis():
|
123 |
"""Run weekly analysis for the FPMMS project."""
|
124 |
+
rpc = RPC
|
125 |
|
126 |
# Run markets ETL
|
127 |
logging.info("Running markets ETL")
|
|
|
147 |
rpc=rpc,
|
148 |
)
|
149 |
logging.info("Profitability analysis completed")
|
150 |
+
add_current_answer()
|
151 |
+
try:
|
152 |
+
updating_timestamps(rpc)
|
153 |
+
except Exception as e:
|
154 |
+
logging.error("Error while updating timestamps of tools")
|
155 |
+
print(e)
|
156 |
|
157 |
compute_tools_accuracy()
|
158 |
|
|
|
161 |
|
162 |
if __name__ == "__main__":
|
163 |
weekly_analysis()
|
164 |
+
# rpc = RPC
|
165 |
# updating_timestamps(rpc)
|
scripts/tools.py
CHANGED
@@ -166,20 +166,25 @@ def get_events(
|
|
166 |
)
|
167 |
break
|
168 |
sleep = SLEEP * retries
|
169 |
-
|
170 |
-
|
171 |
-
|
172 |
-
|
173 |
-
|
174 |
-
|
175 |
-
|
176 |
-
|
177 |
-
|
178 |
-
|
179 |
-
)
|
180 |
-
|
181 |
-
|
182 |
-
|
|
|
|
|
|
|
|
|
|
|
183 |
time.sleep(sleep)
|
184 |
|
185 |
from_block += batch_size
|
@@ -514,11 +519,16 @@ def update_tools_accuracy(
|
|
514 |
|
515 |
print("Wins dataset")
|
516 |
print(wins.head())
|
517 |
-
|
518 |
-
|
519 |
-
|
520 |
-
|
521 |
-
|
|
|
|
|
|
|
|
|
|
|
522 |
|
523 |
if tools_acc is None:
|
524 |
print("Creating accuracy file for the first time")
|
@@ -534,8 +544,12 @@ def update_tools_accuracy(
|
|
534 |
if tool in existing_tools:
|
535 |
new_accuracy = acc_info[acc_info["tool"] == tool]["tool_accuracy"].values[0]
|
536 |
new_volume = acc_info[acc_info["tool"] == tool]["total_requests"].values[0]
|
537 |
-
|
538 |
-
|
|
|
|
|
|
|
|
|
539 |
tools_acc.loc[tools_acc["tool"] == tool, "tool_accuracy"] = new_accuracy
|
540 |
tools_acc.loc[tools_acc["tool"] == tool, "total_requests"] = new_volume
|
541 |
tools_acc.loc[tools_acc["tool"] == tool, "min"] = new_min_timeline
|
|
|
166 |
)
|
167 |
break
|
168 |
sleep = SLEEP * retries
|
169 |
+
# error_message = ""
|
170 |
+
# if isinstance(exc.args[0], str):
|
171 |
+
# error_message = exc.args[0]
|
172 |
+
# elif isinstance(exc, ValueError):
|
173 |
+
# error_message = exc.args[0].get("message", "")
|
174 |
+
# if (
|
175 |
+
# (
|
176 |
+
# isinstance(exc, ValueError)
|
177 |
+
# and re.match(RE_RPC_FILTER_ERROR, error_message) is None
|
178 |
+
# )
|
179 |
+
# and not isinstance(exc, ValueError)
|
180 |
+
# and not isinstance(exc, MismatchedABI)
|
181 |
+
# ):
|
182 |
+
|
183 |
+
tqdm.write(
|
184 |
+
f"An error was raised from the RPC: {exc}\n Retrying in {sleep} seconds."
|
185 |
+
)
|
186 |
+
if hasattr(exc, "message"):
|
187 |
+
tqdm.write(f"Error message: {exc.messge}\n")
|
188 |
time.sleep(sleep)
|
189 |
|
190 |
from_block += batch_size
|
|
|
519 |
|
520 |
print("Wins dataset")
|
521 |
print(wins.head())
|
522 |
+
no_timeline_info = False
|
523 |
+
try:
|
524 |
+
timeline = tools_non_error.groupby(["tool"])["request_time"].agg(["min", "max"])
|
525 |
+
print("timeline dataset")
|
526 |
+
print(timeline.head())
|
527 |
+
acc_info = wins.merge(timeline, how="left", on="tool")
|
528 |
+
except:
|
529 |
+
print("NO REQUEST TIME INFORMATION AVAILABLE")
|
530 |
+
no_timeline_info = True
|
531 |
+
acc_info = wins
|
532 |
|
533 |
if tools_acc is None:
|
534 |
print("Creating accuracy file for the first time")
|
|
|
544 |
if tool in existing_tools:
|
545 |
new_accuracy = acc_info[acc_info["tool"] == tool]["tool_accuracy"].values[0]
|
546 |
new_volume = acc_info[acc_info["tool"] == tool]["total_requests"].values[0]
|
547 |
+
if no_timeline_info:
|
548 |
+
new_min_timeline = None
|
549 |
+
new_max_timeline = None
|
550 |
+
else:
|
551 |
+
new_min_timeline = acc_info[acc_info["tool"] == tool]["min"].values[0]
|
552 |
+
new_max_timeline = acc_info[acc_info["tool"] == tool]["max"].values[0]
|
553 |
tools_acc.loc[tools_acc["tool"] == tool, "tool_accuracy"] = new_accuracy
|
554 |
tools_acc.loc[tools_acc["tool"] == tool, "total_requests"] = new_volume
|
555 |
tools_acc.loc[tools_acc["tool"] == tool, "min"] = new_min_timeline
|
scripts/utils.py
CHANGED
@@ -47,6 +47,7 @@ INC_TOOLS = [
|
|
47 |
]
|
48 |
|
49 |
SUBGRAPH_API_KEY = os.environ.get("SUBGRAPH_API_KEY", None)
|
|
|
50 |
|
51 |
|
52 |
class MechEventName(Enum):
|
|
|
47 |
]
|
48 |
|
49 |
SUBGRAPH_API_KEY = os.environ.get("SUBGRAPH_API_KEY", None)
|
50 |
+
RPC = os.environ.get("RPC", None)
|
51 |
|
52 |
|
53 |
class MechEventName(Enum):
|