Month: August 2014

Song Tags/Beats/Timing and Other Metadata

An awesome, free initiative called the Million Song Dataset. It’s a great candidate dataset for a MapReduce project, and a great start if you want to write your own song-recognition algorithm.

Million Song Dataset

Data Structure

Data Sample

 

Dynamically Compiling and Implementing a Function

Python allows you to dynamically compile things at the module-level. That’s why the compile() builtin keyword accepts sourcecode and dictionaries of locals and globals, and doesn’t provide a direct way to call a fragment of dynamic (read: textual) sourcecode with arguments (“xyz(arg1, arg2)”). You also can’t directly invoke compiled-code as a generator (where a function that uses “yield” is interpreted as a generator rather than just a function).

However, there’s a loophole, and it’s very elegant and consistent to Python. You simply have to wrap your code in a function definition, and then pull the function from the local scope. You can then call it as desired:

import hashlib
import random

def _compile(arg_names, code):
    name = "(lambda compile)"
    # Needs to start with a letter.
    id_ = 'a' + str(random.random())
    code = "def " + id_ + "(" + ', '.join(arg_names) + "):n" + 
           'n'.join(('  ' + line) for line in code.replace('r', '').split('n')) + 'n'

    c = compile(code, name, 'exec')
    locals_ = {}
    exec(c, globals(), locals_)
    return locals_[id_]

code = """
return a * b * c
"""

c = _compile(['a', 'b', 'c'], code)
print(c(1, 2, 3))

Serialize a Generator in Python

2 Comments

Simply inherit from the list class, and override the __iter__ method. A great example, from SO:

import json

def gen():
    yield 20
    yield 30
    yield 40

class StreamArray(list):
    def __iter__(self):
        return gen()

a = [1,2,3]
b = StreamArray()

print(json.dumps([1,a,b]))