spitz-dan-l

from itertools import chain, starmap

def remove_spans(s, spans):
    to_drop = set(chain(*starmap(range, spans)))
    return ''.join(c for (i, c) in enumerate(s) if i not in to_drop)

spitz-dan-l

def remove_spans_gen(s, spans):
    checker = make_range_checker(spans); next(checker)
    return ''.join(c for (i, c) in enumerate(s) if not checker.send(i))

def make_range_checker(spans):
    idx = yield
    for (i, j) in spans:
        while idx < j:
            idx = (yield i <= idx < j)
    while True:

spitz-dan-l

def remove_spans_neg(s, spans):
    return ''.join(s[i:j] for (_, i), (j, _) in zip([(None,0)]+spans, spans+[(len(s),None)]))

spitz-dan-l

dept_prov_apt_types = DepartmentProviderAppointmentType.where("department_provider_id in (?)", @department_providers.map(&:id))
@apt_types = AppointmentType.where("id in (?)", dept_prov_apt_types.map(&:appointment_type_id)).distinct.order(:name)

spitz-dan-l

#  how to get python to look like this haskell?..
#  listOfTuples :: [(Int,Char)]  
#  listOfTuples = do  
#      n <- [1,2]  
#      ch <- ['a','b']  
#      return (n,ch)  
#  -> [(1, 'a'), (1, 'b'), (2, 'a'), (2, 'b')]    
    
#  ..such that we can write a coroutine and apply a decorator that will make    
@list_monad

spitz-dan-l

import numpy as np
import pandas as ps

np.random.seed(0)

index=range(3)
columns = list('abc')

panel = ps.Panel.from_dict(
    {'A' : ps.DataFrame(np.random.randn(3, 3), index=index, columns=columns),

spitz-dan-l

from sklearn.feature_extraction import DictVectorizer
import pandas

def demo1(input_csv, new_csv):
    """Demonstration of one-hot encoding through Scikit-Learn's DictVectorizer object."""
    df = pandas.read_csv(input_csv) #read csv into a DataFrame object

    #create the one hot encoder
    one_hot_encoder = DictVectorizer(sparse=False)

spitz-dan-l

# If you are using anaconda, then you need to install an extra package which is used behind the scenes.
# Run the following command on the command line:
#
# $ conda install pymysql
#
# say yes when it prompts you.

import pandas
from sqlalchemy import create_engine

spitz-dan-l

public void updateWordCount(HashMap<String, Integer> counts, String wordToUpdate){
    if (counts.containsKey(wordToUpdate)) {
        int current_count = counts.get(wordToUpdate);
        counts.put(wordToUpdate, current_count++);
    } else {
        counts.put(wordToUpdate, 1);
    }
}

spitz-dan-l

public class SynchronizedCounter {
    private int c = 0;

    public synchronized void increment() {
        c++;
    }

    public synchronized void decrement() {
        c--;
    }