59 lines
1.7 KiB
Python
59 lines
1.7 KiB
Python
import tensorflow as tf
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import keras
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import sqlite3
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from datetime import date, datetime
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# Initilize SqLite
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dbconn = sqlite3.connect("./data/appdata.db")
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dbcursor = dbconn.cursor()
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# Create keystore table if it doesnt exist already
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dbcursor.execute('''
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CREATE TABLE IF NOT EXISTS keystore (
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key TEXT PRIMARY KEY,
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value TEXT
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)
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''')
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def SetKey(Key, Value):
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dbcursor.execute('INSERT OR REPLACE INTO keystore (key, value) VALUES (?, ?)', (Key, Value))
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dbconn.commit()
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def GetKey(Key):
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dbcursor.execute('SELECT value FROM keystore WHERE key = ?', (Key, ))
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result = dbcursor.fetchone()
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return result[0] if result else None
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# Pull the last run data
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lastrundata = GetKey("LastRun")
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lastrun = None
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if lastrundata != None:
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lastrun = datetime.strptime( lastrundata, "%Y-%m-%d" )
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else:
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lastrun = datetime.strptime( "2000-01-01", "%Y-%m-%d" )
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# If the strings dont match becuase were only checking day it has to be a new day so update the data
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if lastrun != str(date.today()):
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# This will update the data store in the data folder
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import datapuller
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# Update the last run to today
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SetKey("LastRun", str(date.today()))
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# Load in the AI algorithm
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from keras.layers import Dense, Flatten, Conv2D
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from keras import Model
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mnist = keras.datasets.mnist
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(x_train, y_train), (x_test, y_test) = mnist.load_data()
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x_train, x_test = x_train / 255.0, x_test / 255.0
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# Add a channels dimension
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x_train = x_train[..., tf.newaxis].astype("float32")
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x_test = x_test[..., tf.newaxis].astype("float32")
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# batch and shuffle the dataset
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train_ds = tf.data.Dataset.from_tensor_slices(
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(x_train, y_train)).shuffle(10000).batch(32)
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test_ds = tf.data.Dataset.from_tensor_slices((x_test, y_test)).batch(32) |