import json
import csv
import pandas as pd
from pathlib import Path
from typing import Any
from pprint import pprint as pretty_print
def pprint(print_data: str | list | dict | Path | Any = None, depth: int = 4, max_lines: int = 10, *args, **kwargs) -> None:
""" Pretty prints the given data in a formatted way.
The function handles various data types and structures such as strings, dictionaries, lists, objects, and file paths.
It also supports reading and displaying data from CSV and XLS/XLSX files.
Args:
print_data (str | list | dict | Any, optional): The data to be printed. It can be a string, dictionary, list, object, or file path. Defaults to `None`.
depth (int, optional): The depth to which nested data structures will be printed. Defaults to 4.
max_lines (int, optional): Maximum number of lines to print from a file (CSV/XLS). Defaults to 10.
*args: Additional positional arguments passed to the print or pretty_print function.
**kwargs: Additional keyword arguments passed to the print or pretty_print function.
Returns:
None: The function prints the formatted output and does not return any value.
Example:
>>> pprint("/path/to/file.csv", max_lines=5)
>>> pprint("/path/to/file.xls", max_lines=3)
"""
if not print_data:
return
def _read_text_file(file_path: str | Path, max_lines: int) -> list | None:
"""Reads the content of a text file up to `max_lines` lines."""
path = Path(file_path)
if path.is_file():
try:
with path.open("r", encoding="utf-8") as file:
return [file.readline().strip() for _ in range(max_lines)]
except Exception as ex:
pretty_print(print_data)
return None
def _print_class_info(instance: Any, *args, **kwargs) -> None:
"""Prints class information including class name, methods, and properties."""
class_name = instance.__class__.__name__
class_bases = instance.__class__.__bases__
print(f"Class: {class_name}", *args, **kwargs)
if class_bases:
print([base.__name__ for base in class_bases], *args, **kwargs)
attributes_and_methods = dir(instance)
methods = []
properties = []
for attr in attributes_and_methods:
if not attr.startswith('__'):
try:
value = getattr(instance, attr)
except Exception:
value = "Error getting attribute"
if callable(value):
methods.append(f"{attr}()")
else:
properties.append(f"{attr} = {value}")
pretty_print("Methods:", *args, **kwargs)
for method in sorted(methods):
pretty_print(method, *args, **kwargs)
print("Properties:", *args, **kwargs)
for prop in sorted(properties):
pretty_print(prop, *args, **kwargs)
def _print_csv(file_path: str, max_lines: int) -> None:
"""Prints the first `max_lines` lines from a CSV file."""
try:
with open(file_path, newline='', encoding='utf-8') as csvfile:
reader = csv.reader(csvfile)
header = next(reader)
print(f"CSV Header: {header}")
for i, row in enumerate(reader, start=1):
print(f"Row {i}: {row}")
if i >= max_lines:
break
except Exception as ex:
pretty_print(print_data)
def _print_xls(file_path: str, max_lines: int) -> None:
"""Prints the first `max_lines` rows from an XLS/XLSX file."""
try:
df = pd.read_excel(file_path, nrows=max_lines)
print(df.head(max_lines).to_string(index=False))
except Exception as ex:
pretty_print(print_data)
def json_serializer(obj):
"""Custom handler for unsupported data types in JSON."""
if isinstance(obj, Path):
return str(obj)
# Check if it's a file path
if isinstance(print_data, str):
if Path(print_data).is_file():
file_extension = Path(print_data).suffix.lower()
if file_extension == '.csv':
_print_csv(print_data, max_lines)
elif file_extension in ['.xls', '.xlsx']:
_print_xls(print_data, max_lines)
elif file_extension == '.txt':
content = _read_text_file(print_data, max_lines)
if content:
for line in content:
print(line)
elif file_extension == '.json':
try:
with open(print_data, 'r', encoding='utf-8') as json_file:
json_data = json.load(json_file)
print(json.dumps(json_data, default=json_serializer, indent=4))
except Exception as ex:
pretty_print(print_data)
else:
pretty_print(print_data, *args, **kwargs)
else:
# If the data is not a file, pretty print or handle it as a class
try:
if isinstance(print_data, dict):
print(json.dumps(print_data, default=json_serializer, indent=4))
elif isinstance(print_data, list):
print("[")
for item in print_data:
print(f"\t{item} - {type(item)}")
print("]")
else:
print(print_data, *args, **kwargs)
if hasattr(print_data, '__class__'):
_print_class_info(print_data, *args, **kwargs)
except Exception as ex:
pretty_print(print_data)
