move tensorflow as a lazyload and wrap in main
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@@ -1,8 +1,8 @@
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import tensorflow as tf
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import keras
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import sqlite3
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import sqlite3
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from datetime import date, datetime
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from datetime import date, datetime
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from datapuller import DataPuller
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def main():
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# Initilize SqLite
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# Initilize SqLite
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dbconn = sqlite3.connect("./data/appdata.db")
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dbconn = sqlite3.connect("./data/appdata.db")
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dbcursor = dbconn.cursor()
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dbcursor = dbconn.cursor()
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@@ -35,11 +35,13 @@ else:
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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 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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if lastrun != str(date.today()):
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# This will update the data store in the data folder
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# This will update the data store in the data folder
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import datapuller
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DataPuller.pull()
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# Update the last run to today
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# Update the last run to today
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SetKey("LastRun", str(date.today()))
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SetKey("LastRun", str(date.today()))
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# Load in the AI algorithm
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# Load in the AI algorithm late so yfinance works properly
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import tensorflow as tf
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import keras
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from keras.layers import Dense, Flatten, Conv2D
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from keras.layers import Dense, Flatten, Conv2D
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from keras import Model
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from keras import Model
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@@ -57,3 +59,6 @@ train_ds = tf.data.Dataset.from_tensor_slices(
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(x_train, y_train)).shuffle(10000).batch(32)
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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)
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test_ds = tf.data.Dataset.from_tensor_slices((x_test, y_test)).batch(32)
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if __name__ == "__main__":
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main()
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