Merge pull request #230 from jseabold/python-install

Make the Python wrappers installable without path munging

demo/binary_classification/mapfeat.py

@@ -1,5 +1,4 @@
 #!/usr/bin/python
-import sys
 
 def loadfmap( fname ):
     fmap = {}

demo/guide-python/basic_walkthrough.py

@@ -1,10 +1,6 @@
 #!/usr/bin/python
-import sys
 import numpy as np
 import scipy.sparse
-# append the path to xgboost, you may need to change the following line
-# alternatively, you can add the path to PYTHONPATH environment variable
-sys.path.append('../../wrapper')
 import xgboost as xgb
 
 ### simple example

demo/guide-python/boost_from_prediction.py

@@ -1,7 +1,5 @@
 #!/usr/bin/python
-import sys
 import numpy as np
-sys.path.append('../../wrapper')
 import xgboost as xgb
 
 dtrain = xgb.DMatrix('../data/agaricus.txt.train')

demo/guide-python/cross_validation.py

@@ -1,7 +1,5 @@
 #!/usr/bin/python
-import sys
 import numpy as np
-sys.path.append('../../wrapper')
 import xgboost as xgb
 
 ### load data in do training

demo/guide-python/custom_objective.py

@@ -1,7 +1,5 @@
 #!/usr/bin/python
-import sys
 import numpy as np
-sys.path.append('../../wrapper')
 import xgboost as xgb
 ###
 # advanced: cutomsized loss function

demo/guide-python/generalized_linear_model.py

@@ -1,6 +1,4 @@
 #!/usr/bin/python
-import sys
-sys.path.append('../../wrapper')
 import xgboost as xgb
 ##
 #  this script demonstrate how to fit generalized linear model in xgboost

demo/guide-python/predict_first_ntree.py

@@ -1,7 +1,5 @@
 #!/usr/bin/python
-import sys
 import numpy as np
-sys.path.append('../../wrapper')
 import xgboost as xgb
 
 ### load data in do training

demo/guide-python/predict_leaf_indices.py

@@ -1,7 +1,5 @@
 #!/usr/bin/python
-import sys
 import numpy as np
-sys.path.append('../../wrapper')
 import xgboost as xgb
 
 ### load data in do training

demo/guide-python/sklearn_examples.py

@@ -4,8 +4,6 @@ Created on 1 Apr 2015
 @author: Jamie Hall
 '''
 
-import sys
-sys.path.append('../../wrapper')
 import xgboost as xgb
 
 import numpy as np

demo/kaggle-higgs/higgs-cv.py

@@ -1,7 +1,5 @@
 #!/usr/bin/python
-import sys
 import numpy as np
-sys.path.append('../../wrapper')
 import xgboost as xgb
 
 ### load data in do training

demo/kaggle-higgs/higgs-numpy.py

@@ -1,14 +1,6 @@
 #!/usr/bin/python
 # this is the example script to use xgboost to train
-import inspect
-import os
-import sys
 import numpy as np
-# add path of xgboost python module
-code_path = os.path.join(
-    os.path.split(inspect.getfile(inspect.currentframe()))[0], "../../wrapper")
-
-sys.path.append(code_path)
 
 import xgboost as xgb
 

demo/kaggle-higgs/higgs-pred.py

@@ -1,9 +1,6 @@
 #!/usr/bin/python
 # make prediction
-import sys
 import numpy as np
-# add path of xgboost python module
-sys.path.append('../../wrapper/')
 import xgboost as xgb
 
 # path to where the data lies

demo/kaggle-higgs/speedtest.py

@@ -1,9 +1,6 @@
 #!/usr/bin/python
 # this is the example script to use xgboost to train
-import sys
 import numpy as np
-# add path of xgboost python module
-sys.path.append('../../wrapper/')
 import xgboost as xgb
 from sklearn.ensemble import GradientBoostingClassifier
 import time

demo/multiclass_classification/train.py

@@ -1,7 +1,5 @@
 #! /usr/bin/python
-import sys
 import numpy as np
-sys.path.append('../../wrapper/')
 import xgboost as xgb
 
 # label need to be 0 to num_class -1

demo/regression/mapfeat.py

@@ -1,5 +1,4 @@
 #!/usr/bin/python
-import sys
 
 fo = open( 'machine.txt', 'w' )
 cnt = 6

windows/README.md

@@ -10,13 +10,17 @@ This should give you xgboost.exe for CLI version and xgboost_wrapper.dll for pyt
 
 Use Python Module
 =====
-* After you build the dll, you can simply add the path to [../wrapper](../wrapper) to sys.path and import xgboost
+* After you build the dll, you can install the Python package from the [../wrapper](../wrapper) folder
+
+```
+python setup.py install
+```
+
+And import it as usual
+
 ```
-sys.path.append('path/to/xgboost/wrapper')
 import xgboost as xgb
 ```
-* Alternatively, you can add that path to system enviroment variable ```PYTHONPATH```
-  - Doing so allows you to import xgboost directly like other python packages
 
 R Package
 ====

wrapper/README.md

@@ -5,6 +5,7 @@ This folder provides wrapper of xgboost to other languages
 Python
 =====
 * To make the python module, type ```make``` in the root directory of project
+* Install with `python setup.py install` from this directory.
 * Refer also to the walk through example in [demo folder](../demo/guide-python)
 
 R

wrapper/setup.py

@@ -0,0 +1,28 @@
+import os
+
+from setuptools import setup
+
+
+class XGBoostLibraryNotFound(Exception):
+    pass
+
+
+cur_dir = os.path.dirname(os.path.abspath(__file__))
+
+if os.name == 'nt':
+    dll_path = os.path.join(cur_dir,
+                            '../windows/x64/Release/xgboost_wrapper.dll')
+else:
+    dll_path = os.path.join(cur_dir, 'libxgboostwrapper.so')
+
+if not os.path.exists(dll_path):
+    raise XGBoostLibraryNotFound("XGBoost library not found. Did you run "
+                                 "../make?")
+
+setup(name="xgboost",
+      version="0.32",
+      description="Python wrappers for XGBoost: eXtreme Gradient Boosting",
+      zip_safe=False,
+      py_modules=['xgboost'],
+      data_files=[dll_path],
+      url="https://github.com/dmlc/xgboost")