Merge branch 'master' of https://github.com/tk3369/SASLib.jl

Author: tk3369

LICENSE_SAS7BDAT.md

@@ -0,0 +1,19 @@
+Copyright (c) 2015 Jared Hobbs
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+of the Software, and to permit persons to whom the Software is furnished to do
+so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -92,3 +92,21 @@ results = SASLib.read(handler, 3)   # read 3 rows
 results = SASLib.read(handler, 4)   # read next 4 rows
 SASLib.close(handler)              # remember to close the handler when done
 ```
+
+## Read Performance
+
+I would have expected Julia to be 10x faster than Python but depending on the characterisitc of the data file and target platform I am getting mixed results.  Pandas uses Cython to speed up the core section of the code.  
+
+When I have time I will publish some test results.  I would also be happy to hear about your experience - feel free to create an issue with your performance test results. 
+
+## Why another package?
+
+At first, I was just going to use ReadStat.  However, ReadStat does not support reading files with compressed binary data.  I could have chosen to contribute to that project instead but I would rather learn and code in Julia instead ;-)  The implementation in Pandas is fairly straightforward, making it a relatively easy porting project.  
+
+## Porting Notes
+
+I chose to copy the code from Pandas and made minimal changes so I can have a working version quickly.  Hence, the code isn't very Julia-friendly e.g. variable and function naming are all mixed up.  It is not a priority at this point but I would think some major refactoring would be required to make it more clean & performant.
+
+## Credits
+
+Many thanks to Jared Hobbs, the original author of the SAS I/O code from Python Pandas.