Two Stunning Python Libraries: tqdm and retry

Python is currently my primary programming language for work, computation, and data mining (except for symbolic computation, where I use Mathematica). Of course, basic Python functionality is not inherently powerful, but it excels due to its massive ecosystem of third-party extension libraries. When choosing a third-party Python library, I always consider it carefully, hoping to pick the simplest and most intuitive one (as I am not particularly clever and cannot handle overly complex tools).

In terms of data processing, I use Numpy and Pandas the most; these two are absolute kings in the field. I should also mention Scipy, though I rarely use it directly, usually calling it indirectly through Pandas. For visualization, Matplotlib is the obvious choice. For modeling, I use Keras to build deep learning models directly; Keras has already become a very popular deep learning framework. If I am doing text mining, I usually use jieba (for word segmentation) and Gensim (for topic modeling, which includes models like word2vec). For machine learning, there is the popular Scikit Learn, though I use it less frequently. Regarding networking, I use requests for writing crawlers, as it is a very user-friendly library. For web development, I use bottle, which is a mini-framework in a single file where everything is defined by the user; I don’t write large-scale websites, usually just simple interfaces. Finally, for parallelism, I generally use multiprocessing directly.

However, none of the above are what I want to recommend in this article. What I want to recommend are two libraries that can permeate your daily coding. They implement functions we often need but without requiring much additional code—they are truly eye-opening.

import time
def do_something():
    xxx

for i in range(5):
    try:
        do_something()
        break
    except:
        time.sleep(2)

from retry import retry

@retry(tries=5, delay=2)
def do_something():
    xxx

do_something()