Usage

To use LiteScript in a project:

# imports all the essentials for scripting (setup_logger, tqdm, os, glob, sys, etc.)
from litescript import *

# sets up a logger with a default format and level
logger = setup_logger()

logger.debug("This is a debug message")

# listing out directories
for dir in glob.glob("*"):
    logger.info(f"Found directory: {dir}")

# using tqdm for progress bars
for i in tqdm(range(10)):
    time.sleep(0.1)

# preety print with emojis with help of rich
rprint("Hello, World! :earth_asia:")
# Hello, World! 🌏

Get data science related imports:

# imports all the essentials for data science (pandas, numpy, setup logger, tqdm, much more.)
from litescript.data_science import *

Get vis related imports :

from litescript.vis_utils import * # imports all the essentials for visualization (matplotlib, plotly etc.)

# directly start plotting
fig = px.line(x=[1, 2, 3], y=[1, 3, 2])
fig.show()

# another matplotlib figure
fig = plt.figure()
plt.plot([1, 2, 3], [1, 3, 2])
plt.show()

Detailed imports available

from litescript import *

• setup_logger (colored logger with file handler at app.log)

• os

• time

• sys

• json

• Path

• datetime

• tqdm

• glob

• yaml

• Console (rich console)

• Table (rich table)

• rprint (rich print)

• vis_utils

• data_science

from litescript.data_science import *

• np

• pd

• setup_logger (colored logger with file handler at app.log)

• os

• sys

• json

• Path

• datetime

• tqdm

• glob

• yaml

• Console (rich console)

• Table (rich table)

• rprint (rich print)

from litescript.vis_utils import *

• plt (matplotlib pyplot)

• px (plotly express)