This chapter synthesizes the most prominent Natural Language Processing (NLP) studies conducted on Persian, focusing on text processing. The first section contains selected tasks from the NLP pipeline, such as text preprocessing, tokenization, POS tagging, syntactic parsing, treebank annotation or semantic analysis along with examples of how researchers approached the problem for Persian and, where applicable, examples of tools developed to perform given tasks. The following section discusses the application of Persian NLP like spell-checking, information retrieval, machine translation or sentiment analysis. Finally, the last section summarizes the Persian NLP corpora and other resources.