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How to load private python package when loading a MLFlow model?

I am trying to use a private Python package as a model using the mlflow.pyfunc.PythonModel.
My conda.yaml looks like
channels:
- defaults
dependencies:
- python=3.10.4
- pip
- pip:
- mlflow==2.1.1
- pandas
- --extra-index-url <private-pypa-repo-link>
- <private-package>
name: model_env
python_env.yaml
python: 3.10.4
build_dependencies:
- pip==23.0
- setuptools==58.1.0
- wheel==0.38.4
dependencies:
- -r requirements.txt
requirements.txt
mlflow==2.1.1
pandas
--extra-index-url <private-pypa-repo-link>
<private-package>
When running the following
import mlflow
model_uri = '<run_id>'
# Load model as a PyFuncModel.
loaded_model = mlflow.pyfunc.load_model(model_uri)
# Predict on a Pandas DataFrame.
import pandas as pd
t = loaded_model.predict(pd.read_json("test.json"))
print(t)
The result is
WARNING mlflow.pyfunc: Encountered an unexpected error (InvalidRequirement('Parse error at "\'--extra-\'": Expected W:(0-9A-Za-z)')) while detecting model dependency mismatches. Set logging level to DEBUG to see the full traceback.
Adding in the following before loading the mode makes it work
dep = mlflow.pyfunc.get_model_dependencies(model_uri)
print(dep)
import subprocess
import sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "-r", dep])
Is there a way automatically install these dependencies rather than doing it explicitly? What are my options to get mlflow to install the private package?

Answering my own question here. Turns out the issue is that I was trying to use the keyring library which needs to be pre-installed and is not supported when doing inference in a virtual environment.
There are ways to get around it though.
Add the authentication token to the extra-index-url itself. You can find it documented in this stackoverflow question.
MlFlow allows you to log any dependencies with the model itself using the code_path argument (link). Using this method, you can skip adding in your private package as a requirement. This question also touches on the same topic. The code would look a bit like this.
mlflow.pyfunc.save_model(
path=dest_path,
python_model=MyModel(),
artifacts=_get_artifact_dict(t_dir),
conda_env=conda_env,
# Adding the current script file as dependency
code_path=[os.path.realpath(__file__), #Add any other script]
)
Opt for first approach if saving authentication token in the requirements.txt is feasible, otherwise use the second approach. The downside of using the code_path solution is that with each model, your packages' code is getting replicated.

ModuleNotFoundError: No module named 'onnxruntime'

I'm taking a Microsoft PyTorch course and trying to implement on Kaggle Notebooks but I kept having the same error message over and over again: "ModuleNotFoundError: No module named 'onnxruntime'". I've checked everywhere possible if I could find a solution to it but none, I even tried installing it manually using pip in the notebook, but it's still not working. I've checked the official onnxruntime website and documentation but there's nowhere it states anything about something being outdated or any other issue. Someone help. My code won't run because it says "onnxruntime is not defined". Here are my imports:
%matplotlib inline
import torch
import onnxruntime
from torch import nn
import torch.onnx as onnx
import torchvision.models as models
from torchvision import datasets
from torchvision.transforms import ToTensor
and the code cell I'm trying to run
session = onnxruntime.InferenceSession(onnx_model, None)
input_name = session.get_inputs()[0].name
output_name = session.get_outputs()[0].name
result = session.run([output_name], {input_name: x.numpy()})
predicted, actual = classes[result[0][0].argmax(0)], classes[y]
print(f'Predicted: "{predicted}", Actual: "{actual}"')
And you can find the complete notebook here: https://www.kaggle.com/faisalalbasu/complete-model

the error occurs because "import" cannot find onnxruntime in any of the paths, check where import is searching and see if onnxruntime is in there.
check what path pip install installs to, that way in the future you won't have the same problem! :)

Dependency missing when running AzureML Estimator in docker environment

Scenario description
I'm trying to submit a training script to AzureML (want to use AmlCompute, but I'm starting/testing locally first, for debugging purposes).
The train.py script I have uses a custom package (arcus.ml) and I believe I have specified the right settings and dependencies, but still I get the error:
User program failed with ModuleNotFoundError: No module named 'arcus.ml'
Code and reproduction
This the python code I have:
name='test'
script_params = {
'--test-par': 0.2
}
est = Estimator(source_directory='./' + name,
script_params=script_params,
compute_target='local',
entry_script='train.py',
pip_requirements_file='requirements.txt',
conda_packages=['scikit-learn','tensorflow', 'keras'])
run = exp.submit(est)
print(run.get_portal_url())
This is the (fully simplified) train.py script in the testdirectory:
from arcus.ml import dataframes as adf
from azureml.core import Workspace, Dataset, Datastore, Experiment, Run
# get hold of the current run
run = Run.get_context()
ws = run.get_environment()
print('training finished')
And this is my requirements.txt file
arcus-azureml
arcus-ml
numpy
pandas
azureml-core
tqdm
joblib
scikit-learn
matplotlib
tensorflow
keras
Logs
In the logs file of the run, I can see this section, sot it seems the external module is being installed anyhow.
Collecting arcus-azureml
Downloading arcus_azureml-1.0.3-py3-none-any.whl (3.1 kB)
Collecting arcus-ml
Downloading arcus_ml-1.0.6-py3-none-any.whl (2.1 kB)

It could be there's an issue with arcus-ml 1.0.6 wheel installable, like Anders pointed out it doesn't seem to have any code. Could you try with earlier version arcus-ml==1.0.5 ?

I think this error isn't necessarily about Azure ML. I think the error has to do w/ the difference b/w using a hyphen and a period in your package name. But I'm a python packaging newb.
In a new conda environment on my laptop, I ran the following
> conda create -n arcus python=3.6 -y
> conda activate arcus
> pip install arcus-ml
> python
>>> from arcus.ml import dataframes as adf
ModuleNotFoundError: No module named 'arcus'
When I look in the env's site packages folder, I didn't see the arcus/ml folder structure I was expecting. There's no arcus code there at all, only the .dist-info file
~/opt/anaconda3/envs/arcus/lib/python3.6/site-packages

Python module script.vis install

Really sorry for my novice question.
I am trying to install a module in python for neo4j but I got an error.
here is the import :
from scripts.vis import vis_network
from scripts.vis import draw
Here is the error:
ModuleNotFoundError: No module named 'scripts'
I have tried "pip install scripts"
Thanks in advance

ModuleNotFoundError simply means the Python interpreter couldn't find the module. I suggest that you read about python modules and packaging here.
I have looked at the source code you pointed to and it works perfectly fine. I suspect your paths are not well set up.
Make sure that in you are running importing scripts.vis in app.py, the directory structure looks like this:
./scripts
./scripts/__init__.py
./scripts/vis.py
....
./app.py #in app.py, you can import as 'from scripts.vis import x'
Here's what it looks on my system:
app.py is successfully able to make the import from vis sub-module. You can use a IPython notebook, that should work fine too.

If you want to visualize the graph in the python environment (Jupyter), you can try using neo4jupyter library. Here you will use neo4jupyter.draw to visualize the graph.
Install !pip install neo4jupyter
For example:
import neo4jupyter
neo4jupyter.init_notebook_mode()
from py2neo import Node
nicole = Node("Person", name="Nicole", age=24)
drew = Node("Person", name="Drew", age=20)
graph.create(nicole | drew)
options = {"Person": "name"}
neo4jupyter.draw(graph, options)
You may find this useful:
https://github.com/merqurio/neo4jupyter
https://nicolewhite.github.io/neo4j-jupyter/hello-world.html

ImportError: No module named examples.tutorials.mnist

I am very frustrated by this error, what I did is getting the code from tensor flow tutorial to import moist:
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
However when I run the python shows:
File "/Users/kevinling/Desktop/Machine Learning/tensorflow.py", line 2, in
from tensorflow.examples.tutorials.mnist import input_data
ImportError: No module named examples.tutorials.mnist
When I check into the directory, the file is perfectly there:
And the directory is:
enter image description here
The input_data.py is like:
The input_data.py

Just rename your example from "tensorflow.py" to anything else and it will work. The interpreter is trying to import the necessary files from your script.

Did you already install tensorflow? If not, follow their install instructions or simply install using pip:
pip install tensorflow
Now, make sure you are NOT currently in a folder where tensorflow is located, and try running your script.
python your_script.py