xhluca

import numpy as np
import scipy.sparse as sp
import jax.lax
import timeit


def random_sparse_matrix(n_rows, n_cols, num_elements, seed=0):
    # Create a random scipy sprase matrix by randomly assigning values and constructing the matrix
    np.random.seed(seed)

xhluca

import json
from pathlib import Path
import time
from typing import Optional
import warnings
from functools import partial
import subprocess
import json
from pathlib import Path
import sys

xhluca

from functools import partial

def curry(func):
    def curried(*args, **kwargs):
        if args or kwargs:
            return curry(partial(func, *args, **kwargs))
        else:
            return func()
    
    return curried

xhluca

xhluca

xhluca

How to dynamically create functions in Python

Context

I was interested in creating functions without having to manually define them. This is useful if we want to automatically create a large number of functions, for instance inside a for loop and using a builder function. Unfortunately I wasn't able to find a canonical example of this.

This should cover everything need for the dynamic creation.

Example - Simple add function

xhluca

import json
from typing import List

try:
    from sklearn.decomposition import TruncatedSVD
    from sklearn.feature_extraction.text import TfidfVectorizer
    from sklearn.metrics.pairwise import cosine_similarity
except:
    error_msg = (
        "Couldn't import scikit-learn. To use the toy models, you will need to "

xhluca

See full code

xhluca

from base64 import b64encode

import dash
import dash_table
import dash_html_components as html
import dash_core_components as dcc
from dash.dependencies import Input, Output
import numpy as np
import pandas as pd

xhluca

/* monochrome theme */
/* Colors */
/* Typography */
/* Borders */
/* Shadows */
/* Layout */
body {
  user-select: none;
  background: #000;
  font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Arial, sans-serif;