#Build git annex source how to#
#Build git annex source code#

The figure below illustrates the approach. The design of the ExternalData solution follows that of distributed version control systems using hash-based file indentifiers and object stores, but it also takes advantage of the presence of a dependency-based build system. It is encapsulated in an ExternalData CMake module, downloads large data on an as-needed basis, retains version information, and allows distributed storage. The solution is ideal for projects using CMake as their build system. However, their implementations require additional dependencies like Haskell, Ruby, or Python, and their interfaces add extra Git commands to developer and user workflows.ДЄ CMake-based solution to the large-data Git repository problem was developed during the ITK version 4 Git migration. These are all good tools and their approach is similar to that covered in this article.

#Build git annex source how to#

They fetch the actual files on demand from remote repositories and tell Git how to check them out into the local work tree. These do not store large files directly in the local repository history, but instead store hash-based references to them. the ITK ITK Testing/Data submodule used prior to the solution covered in this article.ДЄ few third-party Git extensions have been created to address this problem, such as git-annex, git-media, and git-fat. Such correspondence can be maintained, at the cost of workflow complexity, using a Git submodule e.g.

#Build git annex source code#

Finally, each version of the source code repository must maintain an unambiguous reference to a corresponding version of the data repository or the history of that correspondence is lost. Some projects even maintain multiple separate repositories to store вЂњnormalвЂќ data and вЂњlargeвЂќ data. Furthermore, the data repository still grows large over time. The separate repository requires extra work for users to checkout and developers to maintain. One common approach is using a separate Git repository to store testing data, e.g. Several existing approaches attempt to address this problem. Many projects at Kitware use binary images for testing data that are large relative to source code files. A common source of large files are testing data. Yet, large data files cannot be avoided altogether. It is challenging to keep distributed source repositories lightweight. Even if large files are removed from HEAD, their presence in the history increases storage requirements and network transmission time for clones. One problem is the addition of large files into a repository. The benefits of distributed version control systems, such as Git, often stem from complete, local storage of a repositoryвЂ™s history however, such local storage is not without disadvantages.