Initialize main directory

When you run log.py you can customize the session, then run graph.py to pull up a chart

Author: erikdkosberg

Charts/control_chart.html

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+from sqlalchemy import create_engine, Column, Integer, Float, String, func
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy.ext.declarative import declarative_base
+
+Base = declarative_base()
+
+class DataRecords(Base):
+    __tablename__ = 'DataRecords'
+    RecordID = Column(Integer, primary_key=True)
+    SessionID = Column(Integer)
+    PartNumber = Column(String)
+    Value = Column(Float)
+    TimeStamp = Column(Float)
+
+def start_engine():
+    global session
+    engine = create_engine('sqlite:///Database.db')
+
+    Base.metadata.create_all(engine)
+
+    Session = sessionmaker(bind=engine)
+    session = Session()
+
+
+def add_record(sessionID, partno, value, dt):
+    record = DataRecords(SessionID=sessionID, RecordID=most_recent_record(), PartNumber=partno, Value=value, TimeStamp=dt)
+    session.add(record)
+    session.commit()
+
+def get_records():
+    records = session.query(DataRecords).order_by(DataRecords.TimeStamp)
+    for record in records:
+        print(record.SessionID, record.RecordID, record.PartNumber, record.Value, record.TimeStamp)
+
+def most_recent_record():
+    max_record_id = session.query(func.max(DataRecords.RecordID)).scalar()
+    if max_record_id == None:
+        return 0
+    else:
+        return max_record_id + 1
+
+def most_recent_session():
+    max_session_id = session.query(func.max(DataRecords.SessionID)).scalar()
+    if max_session_id == None:
+        return 0
+    else:
+        return max_session_id + 1
+
+def test_sensor():
+    start_engine()
+
+    # Query all records where the PartNumber column contains "Engine Speed"
+    results = session.query(DataRecords).filter(DataRecords.PartNumber.like('%Engine Speed%')).all()
+
+    # Iterate over the results and print the values
+    for result in results:
+        print(result.PartNumber, result.Value, result.TimeStamp)
+
+    stop_engine()
+
+def stop_engine():
+    session.close()
+
+
+# Delete all records from the DataRecords table
+def delete_records():
+    start_engine()
+    session.query(DataRecords).delete()
+    session.commit()
+    stop_engine()
+
+def test_engine():
+    import random
+    start_engine()
+    add_record("Engine Speed", random.randint(1,100), str(random.randint(1,10)))
+    get_records()
+    stop_engine()
+
+#test_engine()
+#delete_records()
+#test_sensor()
+

Database.db

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+import plotly.express as px
+import random
+from sqlalchemy import create_engine
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy import func
+import pandas as pd
+from sqlalchemy import create_engine, Column, Integer, Float, String
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy.ext.declarative import declarative_base
+import plotly.offline as pyo
+
+Base = declarative_base()
+
+
+class DataRecords(Base):
+    __tablename__ = "DataRecords"
+    RecordID = Column(Integer, primary_key=True)
+    SessionID = Column(Integer)
+    PartNumber = Column(String)
+    Value = Column(Float)
+    TimeStamp = Column(Float)
+
+
+engine = create_engine("sqlite:///Database.db")
+Session = sessionmaker(bind=engine)
+session = Session()
+
+df = session.query(DataRecords).order_by(DataRecords.TimeStamp).all()
+df = pd.DataFrame(
+    [(record.PartNumber, record.Value, record.TimeStamp) for record in df],
+    columns=["PartNumber", "Value", "TimeStamp"],
+)
+df = df.sort_values(by=["TimeStamp"])
+
+fig = px.scatter(df, x="TimeStamp", y="Value")
+
+# Set number of y-axis and x-axis tick marks
+fig.update_layout(yaxis_nticks=4, xaxis_nticks=10, hovermode="x")
+
+# Group data by PartNumber
+for part_number, group_df in df.groupby(by="PartNumber"):
+    fig.add_scatter(
+        x=group_df["TimeStamp"],
+        y=group_df["Value"],
+        mode="lines+markers",
+        name=part_number,
+        line_shape="spline",
+    )
+    fig.update_traces(
+        marker=dict(
+            size=1, color=["red", "blue", "green", "purple", "orange", "yellow", "pink"]
+        )
+    )
+
+pyo.offline.plot(fig, filename="control_chart.html")
+
+# Show plot
+fig.show()
+
+session.close()

Sessions/session1.CSV

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+import backend as db
+
+def reader(path):
+    directory = "C:/Users/Erik/Desktop/Audi/"
+    with open(directory + path, "r") as f:
+        content = f.read().split("\n")
+
+        # Every other header starting index 1 is time stamp
+        headers = content[5].split(",")[2:][::2]
+
+        # Chop off leading and trailing comma 
+        data = content[7:-1]
+
+        # Tag the current session
+        sessionID = db.most_recent_session()
+
+        # Loop through all data 
+        for record in data:
+            line = record.split(",")[1:-1]
+            times = line[::2]
+            sensors = line[1::2]
+
+            for i, sensor in enumerate(sensors):
+                print(f"Sensor Name: {headers[i]} Sensor Value: {sensor} Time: {times[i]}")
+
+                db.add_record(sessionID, headers[i], float(sensor), times[i])
+
+try:
+    db.start_engine()
+    reader("session3.csv")
+finally:
+    db.stop_engine()