8+ Tqdm 使い方 References
The Basics of tqdm
If you're a Python developer, you've probably come across tqdm at some point. Tqdm is a library that allows you to add progress bars to your code with minimal effort. It's a simple yet powerful tool that can help you keep track of your code's progress, especially when dealing with large datasets or long-running processes. To start using tqdm, all you need to do is install it using pip:pip install tqdm
Once installed, you can import tqdm in your Python code:from tqdm import tqdm
Using tqdm with Loops
One of the most common use cases for tqdm is to add progress bars to loops. Let's say you have a loop that iterates over a large list of items, and you want to know how long it will take to complete. Here's how you can use tqdm to add a progress bar:from tqdm import tqdm
my_list = [1, 2, 3, 4, 5]
for item in tqdm(my_list):
# do some processing here
Customizing Your Progress Bar
Tqdm allows you to customize your progress bar in several ways. For example, you can change the progress bar's color, position, and format. Here's an example of how you can customize your progress bar:from tqdm import tqdm
my_list = [1, 2, 3, 4, 5]
for item in tqdm(my_list, desc="Processing", bar_format="{l_bar}{bar} {n_fmt}/{total_fmt} ETA: {remaining}"):
# do some processing here
Using tqdm with Pandas
Tqdm can also be used with Pandas to add progress bars to data processing tasks. Let's say you have a large dataset that you want to process using Pandas. Here's how you can use tqdm to add a progress bar:import pandas as pd
from tqdm import tqdm
df = pd.read_csv("my_dataset.csv")
for index, row in tqdm(df.iterrows(), total=len(df)):
# do some processing here
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