chore: bump version to 1.0.11

.gitignore

@@ -7,4 +7,6 @@ __pycache__
 dist/
 build/
 
-node_modules
+node_modules
+
+~~

.vscode/settings.json

@@ -1,5 +1,6 @@
 {
     "cSpell.words": [
-        "Jafari"
+        "Jafari",
+        "statsmodels"
     ]
 }

mlModelSaver/__init__.py

@@ -0,0 +1,2 @@
+from mlModelSaver.mlModelSaver import MlModelSaver
+

mlModelSaver/mlModelSaver.py

@@ -1,2 +1,67 @@
-def mlModelSaver():
+import pickle
-    print("mlModelSaver")
+import json
+
+supportedModels = {
+    "sm.OLS": {
+        "supported": True
+    }
+}
+
+supportedDataType = {
+    "int": {
+        "supported": True
+    },
+    "float": {
+        "supported": True
+    },
+    "binary":{
+        "supported": True
+    }
+}
+
+class MlModelSaver:
+
+    def __init__(self, config):
+        self.baseRelativePath = config.get('baseRelativePath', '.')
+        self.modelsFolder = config.get('modelsFolder', '~~modelsFolder')
+
+    def showSupportedModels(self):
+        supported_keys = [key for key, value in supportedModels.items() if value.get('supported')]
+        return supported_keys
+
+    def exportModel(self, model, config):
+        model.mlModelSaverConfig = config
+        isModelSupporter = supportedModels.get(
+            config.get("modelType", ''),
+            {}
+        ).get("supported", False)
+        if not isModelSupporter:
+            raise ValueError(f'only {self.showSupportedModels()} are supported and {config.get("modelType", '')} is not supported')
+        print(model.mlModelSaverConfig)
+        # modelName = config['modelName']
+        # modelsConfig[modelName] = {}
+        # modelsConfig[modelName]['name'] = modelName
+        # model = config['model']
+        # inputs = config['inputs']
+        # output = config['output']
+        # transformers = config.get('transformers', [])
+        # description = config['description']
+        # modelsConfig[modelName]['description'] = description
+        # modelsConfig[modelName]['inputs'] = inputs
+        # if len(transformers) > 0:
+        #     modelsConfig[modelName]['transformers'] = transformers
+        # modelsConfig[modelName]['output'] = output
+        # modelType = config.get('modelType', '')
+        # modelsConfig[modelName]['modelType'] = modelType
+        # if hasattr(model, 'customMetrics'):
+        #     customMetrics = model.customMetrics
+        #     modelsConfig[modelName]['customMetrics'] = customMetrics
+        # else:
+        #     pass
+        # filename = f'{baseRelativePath}/models/{modelName}'
+        # pickle.dump(model, open(filename, 'wb'))
+        # with open(f'{baseRelativePath}/models/configs.json', "w") as outputFile:
+        #     json.dump(modelsConfig, outputFile, indent = 4)
+
+        # loaded_model = pickle.load(open(filename, 'rb'))
+        # return loaded_model

package.json

@@ -1,6 +1,6 @@
 {
   "name": "mlModelSaver",
-  "version": "1.0.10",
+  "version": "1.0.11",
   "description": "Make life easier for save and serving ml models",
   "main": "index.js",
   "repository": "git@github.com:smartdev-ca/mlModelSaver.git",

pytests/test_mlModelSaver.py

@@ -0,0 +1,73 @@
+# test_mlModelSaver.py
+
+import sys
+import os
+
+sys.path.insert(
+    0,
+    os.path.abspath(
+        os.path.join(
+            os.path.dirname(__file__),
+            '../mlModelSaver'
+        )
+    )
+)
+
+
+def test_ensureCLassInstance():
+    from mlModelSaver import MlModelSaver
+    mlModelSaverInstance1 = MlModelSaver({
+        "baseRelativePath": "test_baseRelativePath",
+        "modelsFolder": "test_modelsFolder"
+    })
+    assert mlModelSaverInstance1.baseRelativePath == "test_baseRelativePath"
+    assert mlModelSaverInstance1.modelsFolder == "test_modelsFolder"
+    tesSupportedModels = mlModelSaverInstance1.showSupportedModels()
+    assert tesSupportedModels == ['sm.OLS']
+
+
+def test_OLS_LinearRegression():
+    from mlModelSaver import MlModelSaver
+    import numpy as np
+    import pandas as pd
+    import statsmodels.api as sm
+    salaryMisDf = pd.read_excel("./datasets/Salary_MIS.xlsx")
+    salaryBasedOnGpaMisStatistics = sm.OLS(
+        salaryMisDf["Salary"],
+        sm.add_constant(salaryMisDf[["GPA", "MIS", "Statistics"]])
+    )
+    salaryBasedOnGpaMisStatisticsFit = salaryBasedOnGpaMisStatistics.fit()
+    mlModelSaverInstance2 = MlModelSaver({
+        "baseRelativePath": ".",
+        "modelsFolder": "~~tmp/models"
+    })
+
+    mlModelSaverInstance2.exportModel(
+        salaryBasedOnGpaMisStatisticsFit,
+        {
+            "modelName": "salaryBasedOnGpaMisStatisticsFit",
+            "description": "Predict Salary based on GPA MIS Statistics for sallaryMisDf",
+            "modelType": "sm.OLS",
+            "inputs": [
+                {
+                    "name": "GPA",
+                    "type": "float",
+                },
+                {
+                    "name": "MIS",
+                    "type": "binary"
+                },
+                {
+                    "name": "Statistics",
+                    "type": "binary"
+                }
+            ],
+            "output": [
+                {
+                    "name": "Salary",
+                    "type": "int"
+                }
+            ]
+        }
+    )
+    assert 2 == 2

releaseNewVersionAndAddTag.sh

@@ -8,6 +8,8 @@ new_version=$(node -p "require('./package.json').version")
 rm -rf build
 rm -rf dist
 
+pytest -s -v
+
 python setup.py sdist bdist_wheel
 
 twine upload dist/*

requirements.txt

@@ -1,8 +1,11 @@
+autopep8==2.2.0
 certifi==2024.6.2
 charset-normalizer==3.3.2
 docutils==0.21.2
+et-xmlfile==1.1.0
 idna==3.7
 importlib_metadata==7.1.0
+iniconfig==2.0.0
 jaraco.classes==3.4.0
 jaraco.context==5.3.0
 jaraco.functools==4.0.1
@@ -11,15 +14,29 @@ markdown-it-py==3.0.0
 mdurl==0.1.2
 more-itertools==10.3.0
 nh3==0.2.17
+numpy==1.26.4
+openpyxl==3.1.4
+packaging==24.1
+pandas==2.2.2
+patsy==0.5.6
 pkginfo==1.11.1
+pluggy==1.5.0
+pycodestyle==2.11.1
 Pygments==2.18.0
+pytest==8.2.2
+python-dateutil==2.9.0.post0
+pytz==2024.1
 readme_renderer==43.0
 requests==2.32.3
 requests-toolbelt==1.0.0
 rfc3986==2.0.0
 rich==13.7.1
+scipy==1.13.1
 setuptools==70.0.0
+six==1.16.0
+statsmodels==0.14.2
 twine==5.1.0
+tzdata==2024.1
 urllib3==2.2.1
 wheel==0.43.0
 zipp==3.19.2

setup.py

@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
 
 setup(
     name='mlModelSaver',
-    version='1.0.10',
+    version='1.0.11',
     packages=find_packages(),
     description='Make life easier for saving and serving ML models',
     long_description=open('DOCS.md').read(),  # Assumes you have a README.md file