first commit

.dockerignore

@@ -0,0 +1,131 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+code bank.txt
+.gitignore

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+dev/Streamlit_toolkit filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+code bank.txt
+.gitignore

Datasets/Paitients_Files_Test.csv

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+ID,PRG,PL,PR,SK,TS,M11,BD2,Age,Insurance

Datasets/Paitients_Files_Train.csv

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+ID,PRG,PL,PR,SK,TS,M11,BD2,Age,Insurance,Sepssis

Dockerfile

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+# Use an official Python runtime as a parent image
+FROM python:3.9
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the current directory contents into the container at /app
+COPY requirements.txt .
+
+# Install any needed packages specified in requirements.txt
+RUN pip install -r requirements.txt
+
+COPY . /app
+
+# Expose the port that the application will run on
+EXPOSE 800
+
+# Command to run the application using uvicorn
+CMD ["uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "800"]

dev/Streamlit_toolkit

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+size 4575242

dev/best_model.joblib

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dev/cachedir/joblib/sklearn/pipeline/_fit_transform_one/7da80130da80bc770fb0c7c6ce584447/output.pkl

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dev/cachedir/joblib/sklearn/pipeline/_fit_transform_one/b48fa987af3d915f6f03a058c0333096/metadata.json

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1  172  49  579  42.4  0.702   28\n755    8  188   0    0  47.9  0.137   43\n162    7  194  28    0  35.9  0.745   41\n714    1  115  30   96  34.6  0.529   32\n152    0   95  45   92  36.5  0.330   26\n545    3  122   0    0  23.0  0.254   40\n749    3   78  32   88  31.0  0.248   26\n729    5  168   0    0  32.9  0.135   41\n111    1   97  40    0  38.1  0.218   30\n226    4   76   0    0  34.0  0.391   25\n551    1   93  11    0  22.5  0.417   22\n103    2  100  25   71  38.5  0.324   26\n421    8  109  39  114  27.9  0.640   31\n419    2   71  27    0  28.0  0.586   22\n119    5   95  33    0  37.7  0.370   27\n53     0  141   0    0  42.4  0.205   29\n151    1  196  36  249  36.5  0.875   29\n403    0   93  25   92  28.7  0.532   22\n736    4  171   0    0  43.6  0.479   26\n207    1  112  30  176  34.4  0.528   25\n763    0  140  26  130  42.6  0.431   24\n606    4  156   0    0  48.3  0.238   32\n8      1  122  51  220  49.7  0.325   31\n636    2  144  33  135  31.6  0.422   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5  130   0    0  39.1  0.956   37\n563    3   99  19   74  21.8  0.279   26\n240    6  123  45  230  33.6  0.733   34\n574    9  120  22   56  20.8  0.733   48\n460    6  166   0    0  26.6  0.304   66\n553    3  113  13    0  22.4  0.140   22\n688   15  136  32  110  37.1  0.153   43\n206    3   61  28    0  34.4  0.243   46\n392    5   99  27    0  29.0  0.203   32\n397    4  114   0    0  28.9  0.126   24\n664    1  128  45  194  40.5  0.613   24\n217    7  179  31    0  34.2  0.164   60\n4      5  115   0    0  52.9  0.209   28\n642    2  146  38  360  28.0  0.337   29\n743    3  171  33  135  33.3  0.199   24\n612    4   95   0    0  32.0  0.161   31\n546    3  107  13   48  22.9  0.678   23\n98     0  119  27    0  38.8  0.259   22\n573    0  101  17    0  21.0  0.252   21\n406    1  139  19   83  28.7  0.654   22\n502    8  120   0    0  25.0  0.409   64\n47     8  151  32  210  42.9  0.516   36\n32     0  114  34  285  44.2  0.167   27\n200    0  177  29  478  34.6  1.072   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0\n106    1\n270    0\n435    0\n102    1\nName: Sepssis, dtype: int64", "weight": "None", "message_clsname": "'Pipeline'", "message": "'(step 1 of 2) Processing preprocessor'", "**": "{}"}, "time": 1700726632.0471017}

dev/cachedir/joblib/sklearn/pipeline/_fit_transform_one/func_code.py

@@ -0,0 +1,18 @@
+# first line: 947
+def _fit_transform_one(
+    transformer, X, y, weight, message_clsname="", message=None, **fit_params
+):
+    """
+    Fits ``transformer`` to ``X`` and ``y``. The transformed result is returned
+    with the fitted transformer. If ``weight`` is not ``None``, the result will
+    be multiplied by ``weight``.
+    """
+    with _print_elapsed_time(message_clsname, message):
+        if hasattr(transformer, "fit_transform"):
+            res = transformer.fit_transform(X, y, **fit_params)
+        else:
+            res = transformer.fit(X, y, **fit_params).transform(X)
+
+    if weight is None:
+        return res, transformer
+    return res * weight, transformer

dev/col_pipe.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ee79792ba41fe03828cd3dfd220c31da8c415c68e3f8c1d5ec15948e1f37cf22
+size 1536431

dev/rf_pipline.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a54cb896f816d358ae005a51a7b4b47e6132a9076ff0d1e7f6f18749d7f104e
+size 1536463

src/demo_01/api.py

@@ -0,0 +1,8 @@
+from fastapi import FastAPI
+
+app = FastAPI()
+
+
+@app.get("/")
+async def root():
+    return {"message": "Hello World"}

src/main.py

@@ -0,0 +1,90 @@
+from typing import Union, List, Literal
+from fastapi import FastAPI
+from pydantic import BaseModel
+import uvicorn
+import pandas as pd
+import joblib
+import os
+import numpy as np
+from sklearn.preprocessing import FunctionTransformer
+
+
+def load_ml_components(ml):
+    "load the ml components to re-use in app"
+    with open(ml, "rb") as fold:
+        object = joblib.load(fold)
+    return object
+
+
+app = FastAPI()
+
+
+class Sepsis(BaseModel):
+    PRG: float
+    PL: float
+    SK: float
+    TS: float
+    M11: float
+    BD2: float
+    Age: float
+
+# DIRPATH = os.path.dirname(os.path.realpath(__file__))
+# model = os.path.join(DIRPATH, "best_model.joblib")
+
+# lmc = load_ml_components(model)
+
+# main_pipeline = load_ml_components["best_model.joblib"]
+
+
+model = joblib.load('dev/best_model.joblib')
+# pipline = joblib.load('dev/rf_pipline.joblib')
+
+
+@app.get("/")
+async def root():
+    return {
+        "info": "Sepsis Classification API : Ths is my api floaterface"
+    }
+
+
+@app.post("/classify")
+async def sepsis_classification(Sepsis: Sepsis):
+    try:
+        # craete data frame
+        df = pd.DataFrame({
+            "PRG": [Sepsis.PRG],
+            "PL": [Sepsis.PL],
+            "SK": [Sepsis.SK],
+            "TS": [Sepsis.TS],
+            "M11": [Sepsis.M11],
+            "BD2": [Sepsis.BD2],
+            "Age": [Sepsis.Age]
+        }
+
+        )
+
+        output = model.predict(df)
+        print(
+            f"The data has been classified"
+        )
+        msg = "Execution went Fine"
+        code = 1
+        if output == 0:
+            Sepsis = "Negative"
+        else:
+            Sepsis = "Positive"
+
+    except:
+        print(
+            f"Something went wrong during the Sepssis calssification"
+        )
+        msg = "Execution went wrong"
+        code = 1
+        Sepsis = None
+    result = {"execution_message": msg,
+              "execution_code": code, "prediction": Sepsis}
+    return result
+
+
+if __name__ == "__main__":
+    uvicorn.run("main:app", reload=True)