We did our OSL-Python Project on Spam Filtering using Text Classifier.The dataset have 2000 normal HAM mails and 1000 SPAM mails.From which the tokens are generated to categorise the mail. We first preprocessed the dataset and then extracted words occurrence,frequency and probability for filtering. We divided the dataset into 80-20 for training and testing our model. We used bayesian classifier as our training model and we achieved around 90% accuracy for this model.