Loading MlForecast Model in Docker.

[IfenaikeElias]

What happened + What you expected to happen

REST API works fine locally, but when i load my model in docker it gives an error:

---

docker run -p 8000:8000 ensom-forecast-power-api
ERROR:main:An error occurred while loading the model: code expected at most 16 arguments, got 18
Traceback (most recent call last):
File "/usr/local/bin/uvicorn", line 8, in
sys.exit(main())
File "/usr/local/lib/python3.10/site-packages/click/core.py", line 1157, in call
return self.main(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/click/core.py", line 1078, in main
rv = self.invoke(ctx)
File "/usr/local/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "/usr/local/lib/python3.10/site-packages/click/core.py", line 783, in invoke
return __callback(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/uvicorn/main.py", line 412, in main
run(
File "/usr/local/lib/python3.10/site-packages/uvicorn/main.py", line 579, in run
server.run()
File "/usr/local/lib/python3.10/site-packages/uvicorn/server.py", line 65, in run
return asyncio.run(self.serve(sockets=sockets))
File "/usr/local/lib/python3.10/asyncio/runners.py", line 44, in run
return loop.run_until_complete(main)
File "/usr/local/lib/python3.10/asyncio/base_events.py", line 649, in run_until_complete
return future.result()
File "/usr/local/lib/python3.10/site-packages/uvicorn/server.py", line 69, in serve
await self._serve(sockets)
File "/usr/local/lib/python3.10/site-packages/uvicorn/server.py", line 76, in _serve
config.load()
File "/usr/local/lib/python3.10/site-packages/uvicorn/config.py", line 434, in load
self.loaded_app = import_from_string(self.app)
File "/usr/local/lib/python3.10/site-packages/uvicorn/importer.py", line 19, in import_from_string
module = importlib.import_module(module_str)
File "/usr/local/lib/python3.10/importlib/init.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "", line 1050, in _gcd_import
File "", line 1027, in _find_and_load
File "", line 1006, in _find_and_load_unlocked
File "", line 688, in _load_unlocked
File "", line 883, in exec_module
File "", line 241, in _call_with_frames_removed
File "/app/main.py", line 33, in
Power_model = cloudpickle.load(f)
File "/usr/local/lib/python3.10/site-packages/numba/core/serialize.py", line 110, in _unpickle__CustomPickled
ctor, states = loads(serialized)
TypeError: code expected at most 16 arguments, got 18

---

Versions / Dependencies

pandas==2.2.3
numpy==2.0.2
fastapi==0.115.6
plotly==5.24.1
pydantic==2.10.3
joblib==1.4.2
uvicorn==0.32.1
window_ops==0.0.15
MlForecast==0.15.1
xgboost==2.1.3

Reproduction script

import logging
import pandas as pd
import cloudpickle
import os
from mlforecast import MLForecast
from pydantic import BaseModel
from datetime import datetime

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(name)

model_path = r'C:\Users\user\Desktop\Power_forecast\power_model_mlforecast.pkl'

try:
with open(model_path, 'rb') as f:
Power_model = cloudpickle.load(f)
logger.info("Power consumption model loaded successfully.")
except FileNotFoundError:
logger.error(f"Model file not found at {model_path}. Please check the path.")
raise
except Exception as e:
logger.error(f"Error loading model: {e}")
raise

Example Data to forecast

historical_data = [
{"timestamp": "2024-01-01 00:00:00", "site1": 100.5},
{"timestamp": "2024-01-01 01:00:00", "site2": 102.3},
...
]

historical_data_df = pd.DataFrame(historical_data)
historical_data_df['timestamp'] = pd.to_datetime(historical_data_df['timestamp'])

def convert_to_long_format(df, timestamp_col='timestamp', var_name='SiteName', value_name='AC Consumption'):
value_vars = [col for col in df.columns if col != timestamp_col]
long_df = pd.melt(df, id_vars=[timestamp_col], value_vars=value_vars, var_name=var_name, value_name=value_name)
long_df = long_df.sort_values(by=[timestamp_col, var_name]).reset_index(drop=True)
return long_df

long_data = convert_to_long_format(historical_data_df)

try:
forecast = Power_model.forecast(long_data)
logger.info(f"Forecast result: {forecast}")
except Exception as e:
logger.error(f"Error during forecasting: {e}")

Issue Severity

High: It blocks me from completing my task.

[jmoralez]

Are you using the same versions of the libraries and python in both environments? Seems like you saved it with a different python version.

[IfenaikeElias]

Thank you very much @jmoralez It worked.

[IfenaikeElias]

I'll close this for now.