Tag: Python

Installing Theano and CUDA on Mac OS X

Published 2015/10/28 by Daoyuan Li

I started trying Theano today and wanted to use the GPU (NVIDIA GeForce GT 750M 2048 MB) on my Mac. Here’s a brief instruction on how to use the GPU on Mac, largely following the instructions from http://deeplearning.net/software/theano/install.html#mac-os.

Install Theano:

$ pip install Theano

Download and install CUDA: https://developer.nvidia.com/cuda-downloads

Put the following lines into your ~/.bash_profile:

# Theano and CUDA
PATH="/Developer/NVIDIA/CUDA-7.5/bin/:$PATH"
export LD_LIBRARY_PATH=/Developer/NVIDIA/CUDA-7.5/lib/
export CUDA_ROOT=/Developer/NVIDIA/CUDA-7.5/
export THEANO_FLAGS='mode=FAST_RUN,device=gpu,floatX=float32'

Note that the PATH line is necessary. Otherwise you may see the following message:

ERROR (theano.sandbox.cuda): nvcc compiler not found on $PATH. Check your nvcc installation and try again.

Configure Theano:

$ cat .theanorc 
[gcc]
cxxflags = -L/usr/local/lib -L/Developer/NVIDIA/CUDA-7.5/lib/

Test if GPU is used:

$ cat check.py 
from theano import function, config, shared, sandbox
import theano.tensor as T
import numpy
import time

vlen = 10 * 30 * 768  # 10 x #cores x # threads per core
iters = 1000

rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
f = function([], T.exp(x))
print(f.maker.fgraph.toposort())
t0 = time.time()
for i in xrange(iters):
    r = f()
t1 = time.time()
print("Looping %d times took %f seconds" % (iters, t1 - t0))
print("Result is %s" % (r,))
if numpy.any([isinstance(x.op, T.Elemwise) for x in f.maker.fgraph.toposort()]):
    print('Used the cpu')
else:
    print('Used the gpu')

$ THEANO_FLAGS=mode=FAST_RUN,device=cpu,floatX=float32 time python check.py 
[Elemwise{exp,no_inplace}(<TensorType(float32, vector)>)]
Looping 1000 times took 1.743682 seconds
Result is [ 1.23178029  1.61879337  1.52278066 ...,  2.20771813  2.29967761
  1.62323284]
Used the cpu
        2.47 real         2.19 user         0.27 sys
$ THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 time python check.py 
Using gpu device 0: GeForce GT 750M
[GpuElemwise{exp,no_inplace}(<CudaNdarrayType(float32, vector)>), HostFromGpu(GpuElemwise{exp,no_inplace}.0)]
Looping 1000 times took 1.186971 seconds
Result is [ 1.23178029  1.61879349  1.52278066 ...,  2.20771813  2.29967761
  1.62323296]
Used the gpu
        2.09 real         1.59 user         0.41 sys

A more realistic example:

$ cat lr.py 
import numpy
import theano
import theano.tensor as T
rng = numpy.random

N = 400
feats = 784
D = (rng.randn(N, feats).astype(theano.config.floatX),
rng.randint(size=N,low=0, high=2).astype(theano.config.floatX))
training_steps = 10000

# Declare Theano symbolic variables
x = T.matrix("x")
y = T.vector("y")
w = theano.shared(rng.randn(feats).astype(theano.config.floatX), name="w")
b = theano.shared(numpy.asarray(0., dtype=theano.config.floatX), name="b")
x.tag.test_value = D[0]
y.tag.test_value = D[1]

# Construct Theano expression graph
p_1 = 1 / (1 + T.exp(-T.dot(x, w)-b)) # Probability of having a one
prediction = p_1 > 0.5 # The prediction that is done: 0 or 1
xent = -y*T.log(p_1) - (1-y)*T.log(1-p_1) # Cross-entropy
cost = xent.mean() + 0.01*(w**2).sum() # The cost to optimize
gw,gb = T.grad(cost, [w,b])

# Compile expressions to functions
train = theano.function(
            inputs=[x,y],
            outputs=[prediction, xent],
            updates=[(w, w-0.01*gw), (b, b-0.01*gb)],
            name = "train")
predict = theano.function(inputs=[x], outputs=prediction,
            name = "predict")

if any([x.op.__class__.__name__ in ['Gemv', 'CGemv', 'Gemm', 'CGemm'] for x in
        train.maker.fgraph.toposort()]):
    print('Used the cpu')
elif any([x.op.__class__.__name__ in ['GpuGemm', 'GpuGemv'] for x in
          train.maker.fgraph.toposort()]):
    print('Used the gpu')
else:
    print('ERROR, not able to tell if theano used the cpu or the gpu')
    print(train.maker.fgraph.toposort())

for i in range(training_steps):
    pred, err = train(D[0], D[1])

print("target values for D")
print(D[1])

print("prediction on D")
print(predict(D[0]))
$ THEANO_FLAGS=mode=FAST_RUN,device=cpu,floatX=float32 time python lr.py 
Used the cpu
target values for D
[ 1.  1.  0.  1.  0.  0.  0.  0.  0.  1.  1.  0.  0.  0.  0.  0.  0.  1.
  1.  0.  0.  1.  0.  0.  1.  1.  0.  1.  1.  1.  1.  0.  1.  1.  0.  1.
  0.  0.  0.  0.  0.  1.  0.  0.  0.  1.  1.  0.  1.  1.  1.  0.  1.  0.
  0.  0.  0.  0.  0.  1.  0.  1.  0.  0.  0.  1.  1.  1.  0.  0.  1.  1.
  1.  1.  0.  0.  0.  1.  0.  0.  1.  1.  0.  0.  1.  1.  1.  1.  0.  1.
  0.  0.  0.  0.  1.  0.  0.  1.  1.  1.  0.  0.  1.  1.  1.  1.  1.  1.
  1.  1.  1.  1.  0.  1.  1.  0.  0.  1.  0.  0.  0.  1.  0.  1.  1.  1.
  1.  0.  0.  1.  0.  1.  1.  1.  1.  1.  1.  1.  1.  1.  0.  1.  1.  0.
  1.  0.  1.  1.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  0.  1.  0.  0.
  1.  0.  1.  0.  0.  1.  0.  0.  1.  1.  1.  1.  0.  1.  0.  0.  1.  0.
  0.  0.  1.  1.  1.  1.  1.  1.  1.  0.  1.  1.  1.  0.  1.  0.  1.  0.
  0.  1.  1.  0.  0.  1.  0.  0.  0.  0.  0.  0.  0.  1.  0.  1.  0.  1.
  1.  0.  1.  1.  1.  0.  0.  1.  1.  1.  1.  0.  0.  0.  1.  1.  0.  0.
  1.  0.  0.  0.  0.  1.  1.  1.  0.  1.  1.  1.  0.  1.  0.  0.  0.  0.
  0.  1.  1.  1.  1.  1.  1.  0.  0.  1.  1.  1.  0.  1.  0.  1.  0.  1.
  1.  0.  0.  0.  1.  1.  0.  0.  1.  0.  0.  0.  0.  1.  0.  0.  0.  1.
  0.  1.  0.  1.  1.  0.  1.  1.  0.  0.  0.  0.  1.  0.  0.  0.  0.  1.
  0.  1.  0.  0.  1.  1.  0.  0.  1.  1.  0.  1.  0.  1.  0.  0.  1.  1.
  0.  1.  1.  0.  0.  1.  1.  0.  0.  1.  0.  1.  1.  0.  0.  0.  1.  0.
  0.  0.  1.  0.  0.  0.  0.  1.  1.  0.  1.  1.  1.  0.  1.  1.  1.  1.
  1.  0.  0.  1.  0.  0.  0.  0.  1.  1.  0.  0.  0.  0.  0.  1.  1.  1.
  0.  1.  1.  1.  0.  0.  0.  0.  1.  1.  1.  0.  0.  0.  0.  1.  0.  0.
  1.  1.  0.  1.]
prediction on D
[1 1 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 1 1 0 0 1 0 0 1 1 0 1 1 1 1 0 1 1 0 1 0
 0 0 0 0 1 0 0 0 1 1 0 1 1 1 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1 1 1 0 0 1 1 1 1
 0 0 0 1 0 0 1 1 0 0 1 1 1 1 0 1 0 0 0 0 1 0 0 1 1 1 0 0 1 1 1 1 1 1 1 1 1
 1 0 1 1 0 0 1 0 0 0 1 0 1 1 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 0 1 1 0 1 0 1 1
 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 1 1 1 1 0 1 0 0 1 0 0 0 1 1 1
 1 1 1 1 0 1 1 1 0 1 0 1 0 0 1 1 0 0 1 0 0 0 0 0 0 0 1 0 1 0 1 1 0 1 1 1 0
 0 1 1 1 1 0 0 0 1 1 0 0 1 0 0 0 0 1 1 1 0 1 1 1 0 1 0 0 0 0 0 1 1 1 1 1 1
 0 0 1 1 1 0 1 0 1 0 1 1 0 0 0 1 1 0 0 1 0 0 0 0 1 0 0 0 1 0 1 0 1 1 0 1 1
 0 0 0 0 1 0 0 0 0 1 0 1 0 0 1 1 0 0 1 1 0 1 0 1 0 0 1 1 0 1 1 0 0 1 1 0 0
 1 0 1 1 0 0 0 1 0 0 0 1 0 0 0 0 1 1 0 1 1 1 0 1 1 1 1 1 0 0 1 0 0 0 0 1 1
 0 0 0 0 0 1 1 1 0 1 1 1 0 0 0 0 1 1 1 0 0 0 0 1 0 0 1 1 0 1]
        8.92 real         8.24 user         1.14 sys
$ THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 time python lr.py 
Using gpu device 0: GeForce GT 750M
Used the gpu
target values for D
[ 1.  0.  0.  0.  0.  1.  0.  0.  1.  1.  0.  0.  1.  1.  0.  0.  1.  1.
  0.  0.  0.  1.  1.  0.  1.  1.  1.  0.  0.  1.  1.  1.  1.  1.  1.  0.
  0.  1.  0.  0.  1.  1.  0.  0.  1.  1.  0.  1.  0.  1.  1.  0.  1.  1.
  1.  0.  1.  1.  0.  0.  0.  1.  1.  1.  1.  1.  0.  0.  1.  1.  0.  1.
  1.  1.  1.  0.  1.  1.  0.  1.  1.  1.  0.  0.  0.  1.  1.  0.  0.  0.
  1.  0.  1.  0.  0.  0.  0.  1.  1.  1.  1.  0.  0.  1.  0.  1.  0.  1.
  1.  0.  1.  1.  0.  0.  0.  0.  1.  0.  0.  1.  0.  0.  0.  1.  0.  1.
  1.  1.  0.  0.  0.  1.  0.  1.  0.  1.  0.  1.  1.  1.  1.  1.  0.  1.
  1.  0.  1.  1.  0.  0.  1.  0.  1.  0.  0.  1.  0.  0.  1.  0.  0.  0.
  1.  0.  0.  1.  1.  1.  1.  0.  0.  0.  1.  1.  1.  0.  1.  0.  0.  1.
  1.  1.  1.  1.  1.  1.  1.  1.  0.  0.  0.  0.  0.  1.  1.  1.  0.  1.
  0.  1.  0.  1.  1.  1.  1.  0.  0.  0.  1.  1.  1.  1.  0.  0.  0.  1.
  0.  1.  1.  1.  0.  1.  1.  1.  0.  0.  0.  0.  1.  0.  1.  0.  0.  1.
  0.  0.  1.  1.  0.  1.  0.  1.  1.  1.  0.  0.  1.  1.  0.  0.  0.  0.
  1.  0.  0.  1.  0.  0.  0.  0.  1.  0.  0.  1.  1.  1.  1.  1.  1.  1.
  0.  1.  1.  0.  0.  0.  1.  0.  1.  1.  0.  0.  0.  0.  0.  0.  1.  0.
  1.  1.  1.  0.  0.  1.  0.  1.  0.  0.  1.  0.  1.  0.  0.  1.  0.  0.
  1.  1.  0.  1.  1.  1.  0.  0.  0.  0.  0.  1.  0.  1.  0.  0.  0.  1.
  0.  0.  1.  1.  0.  1.  1.  0.  1.  1.  1.  0.  1.  1.  0.  0.  0.  0.
  0.  0.  1.  1.  1.  1.  1.  1.  1.  1.  0.  1.  1.  1.  0.  1.  0.  1.
  1.  1.  0.  1.  1.  0.  1.  1.  1.  0.  0.  1.  1.  0.  0.  0.  0.  0.
  1.  0.  0.  1.  1.  1.  0.  1.  0.  0.  1.  1.  0.  1.  1.  0.  1.  1.
  0.  0.  1.  0.]
prediction on D
[1 0 0 0 0 1 0 0 1 1 0 0 1 1 0 0 1 1 0 0 0 1 1 0 1 1 1 0 0 1 1 1 1 1 1 0 0
 1 0 0 1 1 0 0 1 1 0 1 0 1 1 0 1 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 1 1
 1 0 1 1 0 1 1 1 0 0 0 1 1 0 0 0 1 0 1 0 0 0 0 1 1 1 1 0 0 1 0 1 0 1 1 0 1
 1 0 0 0 0 1 0 0 1 0 0 0 1 0 1 1 1 0 0 0 1 0 1 0 1 0 1 1 1 1 1 0 1 1 0 1 1
 0 0 1 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 1 1 1 0 0 0 1 1 1 0 1 0 0 1 1 1 1 1 1
 1 1 1 0 0 0 0 0 1 1 1 0 1 0 1 0 1 1 1 1 0 0 0 1 1 1 1 0 0 0 1 0 1 1 1 0 1
 1 1 0 0 0 0 1 0 1 0 0 1 0 0 1 1 0 1 0 1 1 1 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0
 0 1 0 0 1 1 1 1 1 1 1 0 1 1 0 0 0 1 0 1 1 0 0 0 0 0 0 1 0 1 1 1 0 0 1 0 1
 0 0 1 0 1 0 0 1 0 0 1 1 0 1 1 1 0 0 0 0 0 1 0 1 0 0 0 1 0 0 1 1 0 1 1 0 1
 1 1 0 1 1 0 0 0 0 0 0 1 1 1 1 1 1 1 1 0 1 1 1 0 1 0 1 1 1 0 1 1 0 1 1 1 0
 0 1 1 0 0 0 0 0 1 0 0 1 1 1 0 1 0 0 1 1 0 1 1 0 1 1 0 0 1 0]
       19.78 real        17.61 user         1.24 sys

So it seems this GPU does not outperform the CPU. Well,GT 750M may not be the best GPU you can get… Someone else here has a similar experience.

5 Comments

Raspberry Pi as a toy web server

Published 2014/04/24 by Daoyuan Li

1. Tell my router to route certain traffic to the Raspberry Pi. For example, I route HTTP and SSH traffic to one of my Pi’s. I disabled password login for SSH, using public key authentication instead: in /etc/ssh/sshd_config, use the following setting and restart SSH service using `sudo service ssh restart’.

RSAAuthentication yes
PubkeyAuthentication yes

# To disable password authentication:
ChallengeResponseAuthentication no
PasswordAuthentication no
UsePAM no

# To disable root login:
PermitRootLogin no

2. Getting my IP address of the Raspberry Pi. I firstly created a PHP script on my domain to record the IP address in a text file.

<?php                                                                            
                                                                                 
$token = 'secret';                   
                                                                                 
if ($_GET['token'] == $token) {                                                  
    if (!empty($_SERVER['HTTP_CLIENT_IP'])) {                                    
        $ip = $_SERVER['HTTP_CLIENT_IP'];                                        
    } elseif (!empty($_SERVER['HTTP_X_FORWARDED_FOR'])) {                        
        $ip = $_SERVER['HTTP_X_FORWARDED_FOR'];                                  
    } else {                                                                     
        $ip = $_SERVER['REMOTE_ADDR'];                                           
    }                                                                            
    $fp = fopen('home_ip.txt', 'w');                                             
    fwrite($fp, $ip);                                                            
}                                                                                
                                                                                 
?>

Then tell the Raspberry Pi to report its IP address every 5 minutes, using crontab:

pi@alice ~ $ crontab -l
*/5 * * * * curl daoyuan.li/home_ip.php?token=secret

After a while the IP address is recorded in the text file and updated every 5 minutes.

3. Optionally create a DNS record for the Pi. I use Cloudflare to manage DNS settings by myself, so just add/update an entry in Cloudflare’s settings. I point pi.daoyuan.li to the IP address of one Pi. This can be done automatically in the future.

4. Install Flask on the Pi.

sudo apt-get update
sudo apt-get install python-pip
sudo pip install Flask

5. Install nginx and uwsgi on the Pi.

sudo apt-get install nginx
sudo apt-get install build-essential python python-dev
sudo apt-get install python-virtualenv
sudo pip install uwsgi

6. Set up nginx along with uwsgi and Flask.

mkdir flask && cd $_
virtualenv env
. env/bin/activate
pip install Flask

Edit nginx config:

~/flask $ cat flask_nginx.conf 
server {
    listen      5000;
    server_name localhost;
    charset     utf-8;
    client_max_body_size 75M;

    location / { try_files $uri @flask; }
    location @flask{
        include uwsgi_params;
        uwsgi_pass unix:/home/pi/flask/uwsgi.sock;
    }
}

sudo rm /etc/nginx/sites-enabled/default
sudo ln -s flask_nginx.conf /etc/nginx/sites-enabled/default 
sudo service nginx restart

Edit uwsgi config:

~/flask $ cat flask_uwsgi.ini 
[uwsgi]
#application's base folder
base = /home/pi/flask

#python module to import
app = hello
module = %(app)

home = %(base)/env
pythonpath = %(base)

#socket file's location
socket = /home/pi/flask/uwsgi.sock

#permissions for the socket file
chmod-socket    = 666

#the variable that holds a flask application inside the module imported at line #6
callable = app

#location of log files
logto = /home/pi/flask/uwsgi.log

Create a simple Flask app:

~/flask $ cat hello.py
from flask import Flask
app = Flask(__name__)

@app.route("/")
def hello():
    return "Hello World!"

if __name__ == "__main__":
    app.run()

Start up uwsgi:

uwsgi --ini flask_uwsgi.ini &

7. Done! http://pi.daoyuan.li:5000/

Update on June 24, 2014:

Getting the external address in step 2 can be done by running this command in Raspberry Pi:

curl ifconfig.me

See: http://www.commandlinefu.com/commands/view/5427/get-your-external-ip-address

Leave a Comment

NumPy’s ndarray indexing

Published 2014/03/05 by Daoyuan Li

In NumPy a new kind of array is provided: n-dimensional array or ndarray. It’s usually fixed-sized and accepts items of the same type and size. For example, to define a 2×3 matrix:

import numpy as np
a = np.array([[1,2,3,], [4,5,6]], np.int32)

When indexing ndarray, it supports “array indexing” other than single element indexing. (See http://docs.scipy.org/doc/numpy/user/basics.indexing.html)

It is possible to index arrays with other arrays for the purposes of selecting lists of values out of arrays into new arrays. There are two different ways of accomplishing this. One uses one or more arrays of index values. The other involves giving a boolean array of the proper shape to indicate the values to be selected. Index arrays are a very powerful tool that allow one to avoid looping over individual elements in arrays and thus greatly improve performance.

So you basically can do the following:

a = np.array([1, 2, 3], np.int32)
a[np.array([0, 2])) # Fetch the first the third elements, returns np.array([1, 3])
a[np.array([True, False, True])] # Same as the line above

Besides, when you do equals operation on ndarrays, another ndarray is returned by comparing each element:

a = np.array([1, 2, 3], np.int32)
a == 2 # Returns array([False,  True, False], dtype=bool)
a != 2 # Returns array([ True, False,  True], dtype=bool)
a[a != 2] # Returns a sub array that excludes elements with a value 2, in this case array([1, 3], dtype=int32)

Leave a Comment

Statistics of insurance sold on Taobao.com on Valentine’s Day

Published 2014/02/22 by Daoyuan Li

On Feb. 14th Taobao launched a campaign to sell insurance products, which promises 7% yearly interest rate. The sales data is public, so I wrote a script to crawl them down and did a brief study on this data. Here’re the results.

On that day (actually sold out in less than two hours in total) more than 40,000 people participated, resulting a total sales of almost one billion CNY (the exact number: 980,270,000 CNY). Two companies participated in this sales campaign: Zhujiang and Tian’an. The sales statistics are:

	Zhujiang	Tian’an	Total
# of Customers	13831	29092	42923
Sales mean (k CNY)	24.922059	21.847003	22.837872
Sales min (k CNY)	1	1	1
Sales 25% (k CNY)	1	2	2
Sales 50% (k CNY)	10	10	10
Sales 75% (k CNY)	20	25	22
Sales max (k CNY)	1000	900	1000
Sales total (k CNY)	344697	635573	980270

The histograms of how many people pay for each amount.

Zhujiang was extremely popular: in 2 minutes and 56 seconds it reached a sales of 200,212,000 CNY, that’s more than 1 million CNY sales PER SECOND! Indeed Chinese are crazy about online shopping. 😀

Leave a Comment

Statistic analysis of 20 Million Hotel Reservations

Published 2014/02/18 by Daoyuan Li

I did a statistic analysis of the recently leaked 20 million hotel reservation records and here’re some preliminary results.

Leave a Comment

mod_wsgi and mod_xsendfile on OS X 10.9 Mavericks

Published 2013/10/27 by Daoyuan Li

Updated on Nov 4, 2013: The following tricks may still work, however I have found a much easier solution. Simply install Xcode command line developer tools and you should be able to compile source code without issues:

$ xcode-select --install

After upgrading my Mac from 10.8 to 10.9 Mavericks my apache stopped working, so I have to reinstall mod_wsgi and mod_xsendfile. However, tricks are needed to compile and install these mods successfully.

Upgrade Xcode

Upgrade Xcode in App Store. As mentioned by Valerie:

I had to manually upgrade Xcode (after Mavericks upgrade) from the App Store & agree to its license because ./configure hung forever until I did that.

mod_wsgi

For mod_wsgi installation, create a soft link to OSX10.9.xctoolchain:

cd /Applications/Xcode.app/Contents/Developer/Toolchains/
sudo ln -s XcodeDefault.xctoolchain OSX10.9.xctoolchain

Then run configure under mod_wsgi source code directory:

mod_wsgi-3.4$ ./configure

It will generate a Makefile similar as follows:

#  Copyright 2007 GRAHAM DUMPLETON                                               
#                                                                                
#  Licensed under the Apache License, Version 2.0 (the "License");               
#  you may not use this file except in compliance with the License.              
#  You may obtain a copy of the License at                                       
#                                                                                
#      http://www.apache.org/licenses/LICENSE-2.0                                
#                                                                                
#  Unless required by applicable law or agreed to in writing, software           
#  distributed under the License is distributed on an "AS IS" BASIS,             
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.      
#  See the License for the specific language governing permissions and           
#  limitations under the License.                                                

APXS = /usr/sbin/apxs                                                            
PYTHON = /usr/local/bin/python                                                   

DESTDIR =                                                                        
LIBEXECDIR = /usr/libexec/apache2                                                

CPPFLAGS =  -I/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/include/python2.7 -DNDEBUG 
CFLAGS =   -Wc,'-arch x86_64'                                                    
LDFLAGS =  -Wl,-F/usr/local/Cellar/python/2.7.5/Frameworks -framework Python -u _PyMac_Error   -arch x86_64
LDLIBS =  -ldl  -framework CoreFoundation                                        

all : mod_wsgi.la                                                                

mod_wsgi.la : mod_wsgi.c                                                         
    $(APXS) -c $(CPPFLAGS) $(CFLAGS) mod_wsgi.c $(LDFLAGS) $(LDLIBS)             

$(DESTDIR)$(LIBEXECDIR) :                                                        
    mkdir -p $@                                                                  

install : all $(DESTDIR)$(LIBEXECDIR)                                            
    $(APXS) -i -S LIBEXECDIR=$(DESTDIR)$(LIBEXECDIR) -n 'mod_wsgi' mod_wsgi.la 

clean :                                                                          
    -rm -rf .libs                                                                
    -rm -f mod_wsgi.o mod_wsgi.la mod_wsgi.lo mod_wsgi.slo mod_wsgi.loT          
    -rm -f config.log config.status                                              
    -rm -rf autom4te.cache                                                       

distclean : clean                                                                
    -rm -f Makefile Makefile.in                                                  

realclean : distclean                                                            
    -rm -f configure

However, this Makefile is not correct and running ‘make’ the compiler will complain something like:

mod_wsgi.c:34:10: fatal error: 'httpd.h' file not found

Prepend the following line to CPPFLAGS value:

-I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include/apr-1 -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include/apache2

Save the Makefile and it will look something like:

#  Copyright 2007 GRAHAM DUMPLETON                                               
#                                                                                
#  Licensed under the Apache License, Version 2.0 (the "License");               
#  you may not use this file except in compliance with the License.              
#  You may obtain a copy of the License at                                       
#                                                                                
#      http://www.apache.org/licenses/LICENSE-2.0                                
#                                                                                
#  Unless required by applicable law or agreed to in writing, software           
#  distributed under the License is distributed on an "AS IS" BASIS,             
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.      
#  See the License for the specific language governing permissions and           
#  limitations under the License.                                                

APXS = /usr/sbin/apxs                                                            
PYTHON = /usr/local/bin/python                                                   

DESTDIR =                                                                        
LIBEXECDIR = /usr/libexec/apache2                                                

CPPFLAGS =  -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include/apr-1 -I/Applications/Xcode. app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include/apache2 -I/usr/local/Cellar/python/2.7.5/Frameworks/Python.framework/Versions/2.7/include/python2.7 -DNDEBUG
CFLAGS =   -Wc,'-arch x86_64'                                                             
LDFLAGS =  -Wl,-F/usr/local/Cellar/python/2.7.5/Frameworks -framework Python -u _PyMac_Error   -arch x86_64
LDLIBS =  -ldl  -framework CoreFoundation                                        

all : mod_wsgi.la                                                                

mod_wsgi.la : mod_wsgi.c                                                         
    $(APXS) -c $(CPPFLAGS) $(CFLAGS) mod_wsgi.c $(LDFLAGS) $(LDLIBS)             

$(DESTDIR)$(LIBEXECDIR) :                                                        
    mkdir -p $@                                                                  

install : all $(DESTDIR)$(LIBEXECDIR)                                            
    $(APXS) -i -S LIBEXECDIR=$(DESTDIR)$(LIBEXECDIR) -n 'mod_wsgi' mod_wsgi.la 

clean :                                                                          
    -rm -rf .libs                                                                
    -rm -f mod_wsgi.o mod_wsgi.la mod_wsgi.lo mod_wsgi.slo mod_wsgi.loT          
    -rm -f config.log config.status                                              
    -rm -rf autom4te.cache                                                       

distclean : clean                                                                
    -rm -f Makefile Makefile.in                                                  

realclean : distclean                                                            
    -rm -f configure

Then make && install:

mod_wsgi-3.4$ make
mod_wsgi-3.4$ sudo make install

Modify /etc/apache2/httpd.conf to enable mod_wsgi:

LoadModule wsgi_module libexec/apache2/mod_wsgi.so

mod_xsendfile

Use the following command to compile and install mod_xsendfile:

sudo apxs -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include/apr-1 -I/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.9.sdk/usr/include/apache2 -cia mod_xsendfile.c

Enabling HTTPS/SSL

After upgrading OS X the apache configuration was reset, but your original config is save to /etc/apache2/httpd.conf.pre-update. I need to enable SSL in httpd.conf again by uncommenting the following line:

# Include /private/etc/apache2/extra/httpd-ssl.conf

Restart Apache and everything should work fine

sudo apachectl restart

3 Comments

Tastypie error handling with Unauthorized Exception

Published 2013/07/03 by Daoyuan Li

In Tastypie v0.9.15 unauthorized exception messages are not included in the response. The cause lies in the following code: (tastypie/resources.py, Line 601-602 in v0.9.15)

    def unauthorized_result(self, exception):
        raise ImmediateHttpResponse(response=http.HttpUnauthorized())

In the above snippet an empty response is returned, without including messages in `exception`.

In order to fix this, you can override this method in your model resources, for example:

    def unauthorized_result(self, exception):
        """Override tastypie method to return a reasonable error response."""
        raise ImmediateHttpResponse(
            response=HttpUnauthorized(
                json.dumps({'error': exception.message})
            )
        )

Hi, the company I’m working for (yabroad.com) is hiring Website Backend and Frontend Developers to our platform team. We are building an open platform for youngsters to travel beyond boarders and we offer youngsters internship, language study, travel and volunteer opportunities. Please contact me if you are interested.

Leave a Comment