bonzanini

# This code uses Biopython to retrieve lists of articles from pubmed
# you need to install Biopython first.

# If you use Anaconda:
# conda install biopython

# If you use pip/venv:
# pip install biopython

# Full discussion:

bonzanini

# You need to install scikit-learn:
# sudo pip install scikit-learn
#
# Dataset: Polarity dataset v2.0
# http://www.cs.cornell.edu/people/pabo/movie-review-data/
#
# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/19/sentiment-analysis-with-python-and-scikit-learn

bonzanini

consumer_key = 'your-consumer-key'
consumer_secret = 'your-consumer-secret'
access_token = 'your-access-token'
access_secret = 'your-access-secret'

bonzanini

# Print most common words in a corpus collected from Twitter
#
# Full description:
# http://marcobonzanini.com/2015/03/02/mining-twitter-data-with-python-part-1/
# http://marcobonzanini.com/2015/03/09/mining-twitter-data-with-python-part-2/
# http://marcobonzanini.com/2015/03/17/mining-twitter-data-with-python-part-3-term-frequencies/
#
# Run:
# python twitter_most_common_words.py <filename.jsonl>

Munduruca

# you need to install Biopython:
# pip install biopython

# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/12/searching-pubmed-with-python/

from Bio import Entrez

def search(query):
    Entrez.email = 'your.email@example.com'

Munduruca

# You need to install scikit-learn:
# sudo pip install scikit-learn
#
# Dataset: Polarity dataset v2.0
# http://www.cs.cornell.edu/people/pabo/movie-review-data/
#
# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/19/sentiment-analysis-with-python-and-scikit-learn

AlexanderCollins

# Represents a dictionary as an instance (note: cannot yet cast bact to dict type, simple access <InstanceDict>.d
class InstanceDict:
    def __init__(self, d):
        self.d = d
        
    def __getattribute__(self, item):
        return self.__getattr__(item)
        
    def __getattr__(self, key):
        val = self.d[key]