Recent Package Updates
2017-06-25: ffcall-1.13-1 (Foreign function call libraries)Foreign function call libraries commit log from nieder: ffcall 1.132017-06-24: mercurial-4.2.1-1 (Lightweight distributed SCM)
Lightweight distributed SCM commit log from danielj7: New upstream mercurial 4.2.12017-06-24: mercurial-py27-4.2.1-1 (Lightweight distributed SCM)
Mercurial is a fast, lightweight source control management system designed for efficient handling of very large distributed projects. Features include: * O(1) delta-compressed file storage and retrieval scheme * Complete cross-indexing of file and changesets for efficient exploration of project history * Robust SHA1-based integrity checking and append-only storage model * Decentralized development model with arbitrary merging between trees * High-speed HTTP-based network merge protocol * Easy-to-use command-line interface * Integrated stand-alone web interface * Small Python codebase * GPL license commit log from danielj7: New upstream mercurial 4.2.12017-06-24: vim-nox-8.0.673-1 (Improved version of the editor "vi")
VIM adds many of the features that you would expect in an editor: Unlimited undo, syntax coloring, split windows, visual selection, graphical user interface (read: menus, mouse control, scrollbars, text selection), and much much more. commit log from htodd: Welcome to Vim-8.0.673.2017-06-24: vim-8.0.673-1 (Improved version of the editor "vi")
VIM adds many of the features that you would expect in an editor: Unlimited undo, syntax coloring, split windows, visual selection, graphical user interface (read: menus, mouse control, scrollbars, text selection), and much much more. commit log from htodd: Welcome to Vim-8.0.673.2017-06-23: scipy-py27-0.19.1-1 (Scientific tools for Python)
SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try! commit log from dmacks: new version (https://sourceforge.net/p/fink/package-submissions/4934/)2017-06-23: scipy-py35-0.19.1-1 (Scientific tools for Python)
SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try! commit log from dmacks: new version (https://sourceforge.net/p/fink/package-submissions/4934/)2017-06-23: scipy-py34-0.19.1-1 (Scientific tools for Python)
SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try! commit log from dmacks: new version (https://sourceforge.net/p/fink/package-submissions/4934/)2017-06-23: scipy-py36-0.19.1-1 (Scientific tools for Python)
SciPy (pronounced "Sigh Pie") is open-source software for mathematics, science, and engineering. It is also the name of a very popular conference on scientific programming with Python. The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library is built to work with NumPy arrays, and provides many user-friendly and efficient numerical routines such as routines for numerical integration and optimization. Together, they run on all popular operating systems, are quick to install, and are free of charge. NumPy and SciPy are easy to use, but powerful enough to be depended upon by some of the world's leading scientists and engineers. If you need to manipulate numbers on a computer and display or publish the results, give SciPy a try! commit log from dmacks: new version (https://sourceforge.net/p/fink/package-submissions/4934/)