diff --git a/Dockerfile b/Dockerfile
index 2ad3734..1bcb66d 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,10 +1,15 @@
 FROM python:3.10
+EXPOSE 80
 WORKDIR /app
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt 
 
 COPY generateurModele.py .
+COPY testFinal.py .
+COPY crontab .
 
-EXPOSE 80
+RUN chmod 0644 /app/crontab
+RUN apt-get update
+RUN apt-get -y install cron
 
-ENTRYPOINT ["python","generateurModele.py"]
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+ENTRYPOINT ["cron"]
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diff --git a/crontab b/crontab
new file mode 100644
index 0000000..8408a52
--- /dev/null
+++ b/crontab
@@ -0,0 +1,3 @@
+00 08 * * * python generateurModele.py
+* * * * * python testFinal.py
+
diff --git a/file_test/Dockerfile b/file_test/Dockerfile
new file mode 100644
index 0000000..2ad3734
--- /dev/null
+++ b/file_test/Dockerfile
@@ -0,0 +1,10 @@
+FROM python:3.10
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt 
+
+COPY generateurModele.py .
+
+EXPOSE 80
+
+ENTRYPOINT ["python","generateurModele.py"]
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diff --git a/testFinal.py b/testFinal.py
new file mode 100644
index 0000000..0ea9d41
--- /dev/null
+++ b/testFinal.py
@@ -0,0 +1,77 @@
+
+from sklearn.linear_model import LinearRegression
+import pandas as pd 
+import numpy as np
+import requests
+import logging
+
+
+# --------------- Fonction -----------------  #
+def generateJsonModel(model:LinearRegression):
+    listCoef = []
+    listIntercept = []
+    for i in range(0,len(model.coef_)):
+        listCoef.append(model.coef_[i][0])
+        listIntercept.append(model.intercept_[i])
+    json = {"coef":listCoef,"intercept":listIntercept}
+    return json
+
+def generateModele(dataJson:dict[str,str]):
+    # -- Préparation des données 
+    arrayBpm = []
+    arrayStartTime = []
+    arrayTimeOfActivity = []
+
+    for data in dataJson["Data"]:
+        arrayBpm.append(data["BpmAvg"])
+        arrayTimeOfActivity.append(data["TimeOfActivity"])
+
+        arrayStartTime.append(data["StartTime"])
+    # -- DataFrame 
+    data = pd.DataFrame({
+        "Bpm": arrayBpm,
+        "TimeOfActivity": arrayTimeOfActivity
+    })
+    # -- Régression linéaire 
+    model = LinearRegression()
+    model.fit(np.array(arrayStartTime).reshape(-1,1),data)
+    return model
+
+
+def getUserWithData(url:str):
+    response = requests.get(urlGetAllData)
+    if ( response.status_code != 200):
+        print('problème lors de l extraction des données avec l api !! ->  "getUserWithData" (status_code != 200)')
+        exit()
+    return response.json
+
+def sendJsonToApi(url,json):
+    response = requests.post(url,json)
+    if ( response.status_code != 200):
+        print('Problème lors de l envoi des données avec l api !! -> "sendJsonToApi" (status_code != 200)')
+        exit()
+    return
+
+# ---------------- Main ------------------- #
+logging.warning("RUNNNNNNNN !")
+
+urlGetAllData = "https://codefirst.iut.uca.fr/containers/SmartFit-smartfit_api/ia/data"
+
+jsonBack = { "Users" : []}
+# --- Call Api 
+dataUser = getUserWithData(url=urlGetAllData)
+for user in dataUser["Users"]:
+    jsonTmp = {}
+
+    jsonTmp["Identifiant"] = user["Identifiant"]
+    jsonTmp["Info"] = []
+
+    for category in user["Info"]:
+        #Mettre la condition longueur ici
+        model = generateModele(category)
+        jsonTmp["Info"].append({"Category": category["Category"],"Model" : generateJsonModel(model)})
+    # Add User
+    jsonBack["Users"].append(jsonTmp)
+
+# -- Send Api 
+sendJsonToApi(urlGetAllData,jsonBack)
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