Python install (#469)

* add a working setup.py

* Rename setup.py to python/setup.py

* Fix paths in setup.py

* Use relative imports for python3 compatibility.

* Add python/install Makefile target.

* Fix test target in Makefile.

Makefile

@@ -64,7 +64,8 @@ depend:
 
 test: libfaiss.a py
 	make -C tests run
-	PYTHONPATH=./python $(PYTHON) -m unittest discover tests/ -v
+	PYTHONPATH=./python/build/`ls python/build | grep lib` \
+	$(PYTHON) -m unittest discover tests/ -v
 
 
 #############################
@@ -85,7 +86,7 @@ misc/test_blas: misc/test_blas.cpp
 # Python
 
 py:
-	$(MAKE) -C python
+	$(MAKE) -C python build
 
 
 .PHONY: all clean default demos install installdirs py test uninstall

python/Makefile

@@ -8,7 +8,7 @@
 
 HEADERS = $(wildcard ../*.h)
 
-all: cpu
+all: cpu build
 
 #############################
 # CPU
@@ -43,9 +43,15 @@ _swigfaiss_gpu.so: swigfaiss_gpu_wrap.o ../gpu/libgpufaiss.a ../libfaiss.a
 	$(CXX) $(SHAREDFLAGS) $(NVCCLDFLAGS) -o $@ $^ $(NVCCLIBS)
 
 
+build: cpu
+	$(PYTHON) setup.py build
+
+install: build
+	$(PYTHON) setup.py install
+
 clean:
 	rm -f swigfaiss_wrap.cpp swigfaiss_gpu_wrap.cpp
 	rm -f swigfaiss.py swigfaiss_gpu.py
 	rm -f _swigfaiss.so _swigfaiss_gpu.so
 
-.PHONY: all clean cpu gpu
+.PHONY: all build clean cpu gpu install

python/faiss.py

@@ -18,14 +18,14 @@ import pdb
 # we import * so that the symbol X can be accessed as faiss.X
 
 try:
-    from swigfaiss_gpu import *
+    from .swigfaiss_gpu import *
 except ImportError as e:
 
     if 'No module named' not in e.args[0]:
         # swigfaiss_gpu is there but failed to load: Warn user about it.
         sys.stderr.write("Failed to load GPU Faiss: %s\n" % e.args[0])
         sys.stderr.write("Faiss falling back to CPU-only.\n")
-    from swigfaiss import *
+    from .swigfaiss import *
 
 
 ##################################################################

python/setup.py

@@ -0,0 +1,51 @@
+from __future__ import print_function
+from setuptools import setup, find_packages
+import os
+import shutil
+
+here = os.path.abspath(os.path.dirname(__file__))
+
+check_fpath = os.path.join("_swigfaiss.so")
+if not os.path.exists(check_fpath):
+    print("Could not find {}".format(check_fpath))
+    print("Have you run `make` and `make py` "
+          "(and optionally `cd gpu && make && make py && cd ..`)?")
+
+# make the faiss python package dir
+shutil.rmtree("faiss", ignore_errors=True)
+os.mkdir("faiss")
+shutil.copyfile("faiss.py", "faiss/__init__.py")
+shutil.copyfile("swigfaiss.py", "faiss/swigfaiss.py")
+shutil.copyfile("_swigfaiss.so", "faiss/_swigfaiss.so")
+try:
+    shutil.copyfile("_swigfaiss_gpu.so", "faiss/_swigfaiss_gpu.so")
+    shutil.copyfile("swigfaiss_gpu.py", "faiss/swigfaiss_gpu.py")
+except:
+    pass
+
+long_description="""
+Faiss is a library for efficient similarity search and clustering of dense 
+vectors. It contains algorithms that search in sets of vectors of any size,
+ up to ones that possibly do not fit in RAM. It also contains supporting 
+code for evaluation and parameter tuning. Faiss is written in C++ with 
+complete wrappers for Python/numpy. Some of the most useful algorithms 
+are implemented on the GPU. It is developed by Facebook AI Research.
+"""
+setup(
+    name='faiss',
+    version='0.1',
+    description='A library for efficient similarity search and clustering of dense vectors',
+    long_description=long_description,
+    url='https://github.com/facebookresearch/faiss',
+    author='Matthijs Douze, Jeff Johnson, Herve Jegou',
+    author_email='matthijs@fb.com',
+    license='BSD',
+    keywords='search nearest neighbors',
+
+    install_requires=['numpy'],
+    packages=['faiss'],
+    package_data={
+        'faiss': ['*.so'],
+    },
+
+)