Fink

Recent Package Updates

2017-06-25: ffcall-1.13-1 (Foreign function call libraries)
Foreign function call libraries

commit log from nieder:
ffcall 1.13
2017-06-24: mercurial-4.2.1-1 (Lightweight distributed SCM)
Lightweight distributed SCM

commit log from danielj7:
New upstream mercurial 4.2.1
2017-06-24: 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 4.2.1
2017-06-24: 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/)