Sentiment analysis determines the polarities and strength of the sentiment‐bearing expressions, and it has been an important and attractive research area. In the past decade, resources and tools have been developed for sentiment analysis in order to provide subsequent vital applications, such as product reviews, reputation management, call center robots, automatic public survey, etc. However, most of these resources are for the English language. Being the key to the understanding of business and government issues, sentiment analysis resources and tools are required for other major languages, e.g., Chinese.To overcome this obstacle, we introduce CSentiPackage, where resources for retrieving sentiment from texts in the Chinese language, are provided. The related sentiment analysis technologies and datasets are described to give the readers the opportunities to use resources and tools to process Chinese sentiment texts from the very basic to the advanced, i.e., applying sentiment dictionaries, obtaining sentiment scores, and analyzing stance of social media posts using the deep learning model. The introduced resources and tools in this paper include NTUSD, ANTUSD, the Chinese Morphological Dataset, the Chinese Opinion Treebank, CopeOpi, and UTCNN. These resources are all available at http://academiasinicanlplab.github.io/ and they are free for the research purpose.