The tensorflow python module - part 001.

TensorFlow™ is an open source software library for numerical computation using data flow graphs.
I used Fedora 25 distro and python version 2.7.
The base of this installation was the official website.
Fist step of the installation was the base python module: tensorflow.

[root@localhost build]# pip install tensorflow  
Collecting tensorflow
  Downloading tensorflow-1.0.1-cp27-cp27mu-manylinux1_x86_64.whl (44.1MB)
    100% |████████████████████████████████| 44.1MB 30kB/s 
Collecting mock>=2.0.0 (from tensorflow)
  Downloading mock-2.0.0-py2.py3-none-any.whl (56kB)
    100% |████████████████████████████████| 61kB 341kB/s 
Requirement already satisfied: six>=1.10.0 in /usr/lib/python2.7/site-packages (from tensorflow)
Requirement already satisfied: numpy>=1.11.0 in /usr/lib64/python2.7/site-packages (from tensorflow)
Collecting protobuf>=3.1.0 (from tensorflow)
  Downloading protobuf-3.2.0-cp27-cp27mu-manylinux1_x86_64.whl (5.6MB)
    100% |████████████████████████████████| 5.6MB 172kB/s 
Collecting wheel (from tensorflow)
  Downloading wheel-0.29.0-py2.py3-none-any.whl (66kB)
    100% |████████████████████████████████| 71kB 532kB/s 
Collecting funcsigs>=1; python_version < "3.3" (from mock>=2.0.0->tensorflow)
  Downloading funcsigs-1.0.2-py2.py3-none-any.whl
Collecting pbr>=0.11 (from mock>=2.0.0->tensorflow)
  Downloading pbr-2.0.0-py2.py3-none-any.whl (98kB)
    100% |████████████████████████████████| 102kB 518kB/s 
Requirement already satisfied: setuptools in /usr/lib/python2.7/site-packages (from protobuf>=3.1.0->tensorflow)
Installing collected packages: funcsigs, pbr, mock, protobuf, wheel, tensorflow
Successfully installed funcsigs-1.0.2 mock-2.0.0 pbr-2.0.0 protobuf-3.2.0 tensorflow-1.0.1 wheel-0.29.0

The next step come with the installation of python module gpu: tensorflow-gpu.

[root@localhost build]# pip install --upgrade tensorflow-gpu
Collecting tensorflow-gpu
  Downloading tensorflow_gpu-1.0.1-cp27-cp27mu-manylinux1_x86_64.whl (94.8MB)
    100% |████████████████████████████████| 94.8MB 15kB/s 
Requirement already up-to-date: mock>=2.0.0 in /usr/lib/python2.7/site-packages (from tensorflow-gpu)
Requirement already up-to-date: six>=1.10.0 in /usr/lib/python2.7/site-packages (from tensorflow-gpu)
Collecting numpy>=1.11.0 (from tensorflow-gpu)
  Downloading numpy-1.12.0-cp27-cp27mu-manylinux1_x86_64.whl (16.5MB)
    100% |████████████████████████████████| 16.5MB 83kB/s 
Requirement already up-to-date: protobuf>=3.1.0 in /usr/lib64/python2.7/site-packages (from tensorflow-gpu)
Requirement already up-to-date: wheel in /usr/lib/python2.7/site-packages (from tensorflow-gpu)
Requirement already up-to-date: funcsigs>=1; python_version < "3.3" in /usr/lib/python2.7/site-packages (from mock>=2.0.0->tensorflow-gpu)
Requirement already up-to-date: pbr>=0.11 in /usr/lib/python2.7/site-packages (from mock>=2.0.0->tensorflow-gpu)
Collecting setuptools (from protobuf>=3.1.0->tensorflow-gpu)
  Downloading setuptools-34.3.1-py2.py3-none-any.whl (389kB)
    100% |████████████████████████████████| 399kB 637kB/s 
Collecting appdirs>=1.4.0 (from setuptools->protobuf>=3.1.0->tensorflow-gpu)
  Downloading appdirs-1.4.3-py2.py3-none-any.whl
Collecting packaging>=16.8 (from setuptools->protobuf>=3.1.0->tensorflow-gpu)
  Downloading packaging-16.8-py2.py3-none-any.whl
Collecting pyparsing (from packaging>=16.8->setuptools->protobuf>=3.1.0->tensorflow-gpu)
  Downloading pyparsing-2.2.0-py2.py3-none-any.whl (56kB)
    100% |████████████████████████████████| 61kB 577kB/s 
Installing collected packages: numpy, tensorflow-gpu, appdirs, pyparsing, packaging, setuptools
  Found existing installation: numpy 1.11.2
    Uninstalling numpy-1.11.2:
      Successfully uninstalled numpy-1.11.2
  Found existing installation: setuptools 25.1.1
    Uninstalling setuptools-25.1.1:
      Successfully uninstalled setuptools-25.1.1
Successfully installed appdirs-1.4.3 numpy-1.12.0 packaging-16.8 pyparsing-2.2.0 setuptools-34.3.1 tensorflow-gpu-1.0.1

I got errors when I try to run this python module (libcudart.so.8.0).
I have a Intel I5 CPU with a video card without CUDA features.

    _mod = imp.load_module('_pywrap_tensorflow', fp, pathname, description)
ImportError: libcudart.so.8.0: cannot open shared object file: No such file or directory


Failed to load the native TensorFlow runtime.

See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/get_started/os_setup.md#import_error

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

So I used this command to fix with the pip upgrade:

[root@localhost ~]# export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc0-cp27-none-linux_x86_64.whl
[root@localhost ~]# pip install --upgrade $TF_BINARY_URL
Collecting tensorflow==0.11.0rc0 from https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc0-cp27-none-linux_x86_64.whl
  Downloading https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.11.0rc0-cp27-none-linux_x86_64.whl (39.7MB)
    100% |████████████████████████████████| 39.8MB 37kB/s 
Requirement already up-to-date: mock>=2.0.0 in /usr/lib/python2.7/site-packages (from tensorflow==0.11.0rc0)
Requirement already up-to-date: six>=1.10.0 in /usr/lib/python2.7/site-packages (from tensorflow==0.11.0rc0)
Requirement already up-to-date: numpy>=1.11.0 in /usr/lib64/python2.7/site-packages (from tensorflow==0.11.0rc0)
Collecting protobuf==3.0.0 (from tensorflow==0.11.0rc0)
  Downloading protobuf-3.0.0-cp27-cp27mu-manylinux1_x86_64.whl (5.2MB)
    100% |████████████████████████████████| 5.2MB 206kB/s 
Requirement already up-to-date: wheel in /usr/lib/python2.7/site-packages (from tensorflow==0.11.0rc0)
Requirement already up-to-date: funcsigs>=1; python_version < "3.3" in /usr/lib/python2.7/site-packages (from mock>=2.0.0->tensorflow==0.11.0rc0)
Requirement already up-to-date: pbr>=0.11 in /usr/lib/python2.7/site-packages (from mock>=2.0.0->tensorflow==0.11.0rc0)
Requirement already up-to-date: setuptools in /usr/lib/python2.7/site-packages (from protobuf==3.0.0->tensorflow==0.11.0rc0)
Requirement already up-to-date: appdirs>=1.4.0 in /usr/lib/python2.7/site-packages (from setuptools->protobuf==3.0.0->tensorflow==0.11.0rc0)
Requirement already up-to-date: packaging>=16.8 in /usr/lib/python2.7/site-packages (from setuptools->protobuf==3.0.0->tensorflow==0.11.0rc0)
Requirement already up-to-date: pyparsing in /usr/lib/python2.7/site-packages (from packaging>=16.8->setuptools->protobuf==3.0.0->tensorflow==0.11.0rc0)
Installing collected packages: protobuf, tensorflow
  Found existing installation: protobuf 3.2.0
    Uninstalling protobuf-3.2.0:
      Successfully uninstalled protobuf-3.2.0
  Found existing installation: tensorflow 1.0.1
    Uninstalling tensorflow-1.0.1:
      Successfully uninstalled tensorflow-1.0.1
Successfully installed protobuf-3.0.0 tensorflow-0.11.0rc0

The basic the python tensorflow works, so I need to test.

import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))

Hello, TensorFlow!

The pattern python module - part 001.

This is a very short presentation of pattern python module.
This python module is full of options and features.
I will try to show you some parts useful for most python users.
About pattern python module:
Pattern is a web mining module for the Python programming language.
It has tools for data mining (Google, Twitter and Wikipedia API, a web crawler, a HTML DOM parser), natural language processing (part-of-speech taggers, n-gram search, sentiment analysis, WordNet), machine learning (vector space model, clustering, SVM), network analysis and visualization.
Pattern developer documentation

Module	Functionality
pattern.web	Asynchronous requests, web services, web crawler, HTML DOM parser.
pattern.db	Wrappers for databases (MySQL, SQLite) and CSV-files.
pattern.text	Base classes for parsers, parse trees and sentiment analysis.
pattern.search	Pattern matching algorithm for parsed text (syntax & semantics).
pattern.vector	Vector space model, clustering, classification.
pattern.graph	Graph analysis & visualization.

I used with Fedora linux and you can see the instalation of this python module:

[root@localhost ~]# pip install pattern
Collecting pattern
  Downloading pattern-2.6.zip (24.6MB)
    100% |████████████████████████████████| 24.6MB 61kB/s 
Installing collected packages: pattern
  Running setup.py install for pattern ... done
Successfully installed pattern-2.6

Frequently used single character variable names:

Variable	Meaning	Example
a	array, all	a = [normalize(w) for w in words]
b	boolean	while b is False:
d	distance, document	d = distance(v1, v2)
e	element	e = html.find('#nav')
f	file, filter, function	f = open('data.csv', 'r')
i	index	for i in range(len(matrix)):
j	index	for j in range(len(matrix[i])):
k	key	for k in vector.keys():
n	list length	n = len(a)
p	parser, pattern	p = pattern.search.compile('NN')
q	query	for r in twitter.search(q):
r	result, row	for r in csv('data.csv):
s	string	s = s.decode('utf-8').strip()
t	time	t = time.time() - t0
v	value, vector	for k, v in vector.items():
w	word	for i, w in enumerate(sentence.words):
x	horizontal position	node.x = 0
y	vertical position	node.y = 0

Pattern contains part-of-speech taggers for a number of languages (including English, Spanish, German, French and Dutch). Part-of-speech tagging is useful in many data mining tasks. A part-of-speech tagger takes a string of text and identifies the sentences and the words in the text along with their word type. 

Language	Code	Speakers	Example countries
Spanish	es	350M	Argentina (40), Colombia (40), Mexico (100), Spain (45)
English	en	340M	Canada (30), United Kingdom (60), United States (300)
German	de	100M	Austria (10), Germany (80), Switzerland (7)
French	fr	70M	France (65), Côte d'Ivoire (20)
Italian	it	60M	Italy (60)
Dutch	nl	27M	The Netherlands (25), Belgium (6), Suriname (1)

import pattern.en  
import pattern.es
import pattern.du  
import pattern.de

You can deal with many websites, see examples:

from pattern.web import Wikipedia
from pattern.web import Yahoo
from pattern.web import Twitter
from pattern.web import Facebook
from pattern.web import Flickr
from pattern.web import GMAIL
from pattern.web import GOOGLE

Now, about pattern.db.
The pattern.db module contains wrappers for databases (SQLite, MySQL), Unicode CSV files and Python's datetime. It offers a convenient way to work with tabular data, for example retrieved with the pattern.web module.

import pattern 
from pattern.db import Database, field, pk, STRING, BOOLEAN, DATE, NOW 
db = Database('people')
db.create('area_people',fields=(
pk(),
field('name', STRING(80), index=True),
field('type', STRING(20)),
field('date_birth', DATE, default=None),
field('date_created', DATE, default=NOW)
))
db.area_people.append(name=u'George', type='male')
1
print db.area_people.rows()[0]
(1, u'George', u'male', None, Date('2017-03-06 22:38:13'))