def test_find_jupytext_configuration_file(tmpdir):
nested = tmpdir.mkdir("nested")
# Start with no configuration
assert find_jupytext_configuration_file(str(nested)) is None
# Configuration file in the parent directory
root_config = tmpdir.join("jupytext.yml")
root_config.write("\n")
assert os.path.samefile(
find_jupytext_configuration_file(str(tmpdir)), str(root_config)
)
assert os.path.samefile(
find_jupytext_configuration_file(str(nested)), str(root_config)
)
# Local configuration file
local_config = nested.join(".jupytext")
local_config.write("\n")
assert os.path.samefile(
find_jupytext_configuration_file(str(tmpdir)), str(root_config)
)
assert os.path.samefile(
find_jupytext_configuration_file(str(nested)), str(local_config)
)
def test_jupytext_py_is_not_a_configuration_file(tmpdir):
jupytext_py = tmpdir.join("jupytext.py")
jupytext_py.write("# Not a config file!")
assert find_jupytext_configuration_file(str(tmpdir)) is None
dot_jupytext_py = tmpdir.join(".jupytext.py")
dot_jupytext_py.write("# This is a config file!")
assert find_jupytext_configuration_file(str(tmpdir)) == str(dot_jupytext_py)
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.6.0
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
# %% [markdown]
# ### From https://www.kaggle.com/prmohanty/python-how-to-save-and-load-ml-models
# %%
from jupytext.config import find_jupytext_configuration_file
find_jupytext_configuration_file('.')
# %% [markdown]
# # Entraînement du modèle
# %%
# Import Required packages
#-------------------------
# Import the Logistic Regression Module from Scikit Learn
from sklearn.linear_model import LogisticRegression
# Import the IRIS Dataset to be used in this Kernel
from sklearn.datasets import load_iris
# Load the Module to split the Dataset into Train & Test