Basic construction of a tensor network library

We present a template tensor network code written in the programming language julia. The code is simple, short, and is also is efficient, competing in speed with some implementations in lower-level languages. The code can provide an efficient means to learn tensor networks as it is well documented for users of all levels, and the code can be used to check other libraries in development. A large number of algorithms have been implemented. Given time, new algorithms developed while creating this library will be discussed.