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import logging
from datetime import datetime
import pandas as pd
from markets import (
etl as mkt_etl,
DEFAULT_FILENAME as MARKETS_FILENAME,
fpmmTrades_etl,
update_fpmmTrades_parquet,
)
from tools import generate_tools_file
from profitability import run_profitability_analysis, add_trades_profitability
from utils import (
get_question,
current_answer,
measure_execution_time,
ROOT_DIR,
HIST_DIR,
TMP_DIR,
)
from get_mech_info import (
get_mech_events_since_last_run,
update_json_files,
)
from update_tools_accuracy import compute_tools_accuracy
from cleaning_old_info import clean_old_data_from_parquet_files
from web3_utils import get_timestamp_two_weeks_ago
from manage_space_files import move_files
from cloud_storage import upload_historical_file
from tools_metrics import compute_tools_based_datasets
from get_mech_info import read_all_trades_profitability
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
datefmt="%Y-%m-%d %H:%M:%S",
)
logger = logging.getLogger(__name__)
def add_current_answer(tools_filename: str):
# Get currentAnswer from FPMMS
fpmms = pd.read_parquet(ROOT_DIR / MARKETS_FILENAME)
tools = pd.read_parquet(ROOT_DIR / tools_filename)
# Get the question from the tools
logging.info("Getting the question and current answer for the tools")
tools["title"] = tools["prompt_request"].apply(lambda x: get_question(x))
tools["currentAnswer"] = tools["title"].apply(lambda x: current_answer(x, fpmms))
tools["currentAnswer"] = tools["currentAnswer"].str.replace("yes", "Yes")
tools["currentAnswer"] = tools["currentAnswer"].str.replace("no", "No")
# Save the tools data after the updates on the content
tools.to_parquet(ROOT_DIR / tools_filename, index=False)
del fpmms
def save_historical_data():
"""Function to save a copy of the main trades and tools file
into the historical folder"""
print("Saving historical data copies")
current_datetime = datetime.now()
timestamp = current_datetime.strftime("%Y%m%d_%H%M%S")
try:
tools = pd.read_parquet(TMP_DIR / "tools.parquet")
filename = f"tools_{timestamp}.parquet"
tools.to_parquet(HIST_DIR / filename, index=False)
# save into cloud storage
upload_historical_file(filename)
except Exception as e:
print(f"Error saving tools file in the historical folder {e}")
try:
all_trades = read_all_trades_profitability()
filename = f"all_trades_profitability_{timestamp}.parquet"
all_trades.to_parquet(HIST_DIR / filename, index=False)
# save into cloud storage
upload_historical_file(filename)
except Exception as e:
print(
f"Error saving all_trades_profitability file in the historical folder {e}"
)
@measure_execution_time
def only_new_weekly_analysis():
"""Run weekly analysis for the FPMMS project."""
# Run markets ETL
logging.info("Running markets ETL")
mkt_etl(MARKETS_FILENAME)
logging.info("Markets ETL completed")
# Mech events ETL
logging.info("Generating the mech json files")
# get only new data
latest_timestamp = get_mech_events_since_last_run(logger)
if latest_timestamp == None:
print("Error while getting the mech events")
return
logging.info(f"Finished generating the mech json files from {latest_timestamp}")
# FpmmTrades ETL
trades_timestamp = get_timestamp_two_weeks_ago()
fpmmTrades_etl(
trades_filename="new_fpmmTrades.parquet",
from_timestamp=int(trades_timestamp.timestamp()),
)
# merge with previous file
print("Merging with previous fpmmTrades file")
update_fpmmTrades_parquet(trades_filename="new_fpmmTrades.parquet")
# Run tools ETL
logging.info("Generate and parse the tools content")
# generate only new file
generate_tools_file("new_tools_info.json", "new_tools.parquet")
logging.info("Tools ETL completed")
add_current_answer("new_tools.parquet")
# # Run profitability analysis
logging.info("Running profitability analysis")
run_profitability_analysis(
tools_filename="new_tools.parquet",
trades_filename="new_fpmmTrades.parquet",
merge=True,
)
logging.info("Profitability analysis completed")
# merge new json files with old json files
update_json_files()
save_historical_data()
try:
clean_old_data_from_parquet_files("2024-12-13")
except Exception as e:
print("Error cleaning the oldest information from parquet files")
print(f"reason = {e}")
compute_tools_accuracy()
compute_tools_based_datasets()
# # move to tmp folder the new generated files
move_files()
logging.info("Weekly analysis files generated and saved")
def restoring_trades_data(from_date: str, to_date: str):
# Convert the string to datetime64[ns, UTC]
min_date_utc = pd.to_datetime(from_date, format="%Y-%m-%d", utc=True)
max_date_utc = pd.to_datetime(to_date, format="%Y-%m-%d", utc=True)
logging.info("Running markets ETL")
mkt_etl(MARKETS_FILENAME)
logging.info("Markets ETL completed")
fpmmTrades_etl(
trades_filename="missing_fpmmTrades.parquet",
from_timestamp=int(min_date_utc.timestamp()),
to_timestamp=int(max_date_utc.timestamp()),
)
# merge with the old file
print("Merging with previous fpmmTrades file")
update_fpmmTrades_parquet(trades_filename="missing_fpmmTrades.parquet")
# adding tools information
add_trades_profitability(trades_filename="missing_fpmmTrades.parquet")
if __name__ == "__main__":
only_new_weekly_analysis()
# save_historical_data()
# clean_old_data_from_parquet_files("2024-11-30")
# restoring_trades_data("2024-12-28", "2025-01-07")
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