search
HomeBackend DevelopmentPython Tutorialpython实现目录树生成示例

复制代码 代码如下:

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import optparse

LOCATION_NONE     = 'NONE'
LOCATION_MID      = 'MID'
LOCATION_MID_GAP  = 'MID_GAP'
LOCATION_TAIL     = 'TAIL'
LOCATION_TAIL_GAP = 'TAIL_GAP'

Notations = {
    LOCATION_NONE: '',
    LOCATION_MID: '├─',
    LOCATION_MID_GAP: '│  ',
    LOCATION_TAIL: '└─',
    LOCATION_TAIL_GAP: '    '
}

class Node(object):
    def __init__(self, name, depth, parent=None, location=LOCATION_NONE):
        self.name = name
        self.depth = depth
        self.parent = parent
        self.location = location
        self.children = []

    def __str__(self):
        sections = [self.name]
        parent = self.has_parent()
        if parent:
            if self.is_tail():
                sections.insert(0, Notations[LOCATION_TAIL])
            else:
                sections.insert(0, Notations[LOCATION_MID])
            self.__insert_gaps(self, sections)
        return ''.join(sections)

    def __insert_gaps(self, node, sections):
        parent = node.has_parent()
        # parent exists and parent's parent is not the root node
        if parent and parent.has_parent():
            if parent.is_tail():
                sections.insert(0, Notations[LOCATION_TAIL_GAP])
            else:
                sections.insert(0, Notations[LOCATION_MID_GAP])
            self.__insert_gaps(parent, sections)

    def has_parent(self):
        return self.parent

    def has_children(self):
        return self.children

    def add_child(self, node):
        self.children.append(node)

    def is_tail(self):
        return self.location == LOCATION_TAIL

class Tree(object):
    def __init__(self):
        self.nodes = []

    def debug_print(self):
        for node in self.nodes:
            print(str(node) + '/')

    def write2file(self, filename):
        try:
            with open(filename, 'w') as fp:
                fp.writelines(str(node) + '/\n'
                              for node in self.nodes)
        except IOError as e:
            print(e)
            return 0
        return 1

    def build(self, path):
        self.__build(path, 0, None, LOCATION_NONE)

    def __build(self, path, depth, parent, location):
        if os.path.isdir(path):
            name = os.path.basename(path)
            node = Node(name, depth, parent, location)
            self.add_node(node)
            if parent:
                parent.add_child(node)

            entries = self.list_folder(path)
            end_index = len(entries) - 1
            for i, entry in enumerate(entries):
                childpath = os.path.join(path, entry)
                location = LOCATION_TAIL if i == end_index else LOCATION_MID
                self.__build(childpath, depth + 1, node, location)

    def list_folder(self, path):
        """Folders only."""
        return [d for d in os.listdir(path) if os.path.isdir(os.path.join(path, d))]
        # for entry in os.listdir(path):
        #     childpath = os.path.join(path, entry)
        #     if os.path.isdir(childpath):
        #         yield entry

    def add_node(self, node):
        self.nodes.append(node)

def _parse_args():
    parser = optparse.OptionParser()
    parser.add_option(
        '-p', '--path', dest='path', action='store', type='string',
        default='./', help='the path to generate the tree [default: %default]')
    parser.add_option(
        '-o', '--out', dest='file', action='store', type='string',
        help='the file to save the result [default: pathname.trees]')
    options, args = parser.parse_args()
    # positional arguments are ignored
    return options

def main():
    options = _parse_args()
    path = options.path
    if not os.path.isdir(path):
        print('%s is not a directory' % path)
        return 2

    if not path or path == './':
        filepath = os.path.realpath(__file__)  # for linux
        path = os.path.dirname(filepath)
    tree = Tree()
    tree.build(path)
    # tree.debug_print()
    if options.file:
        filename = options.file
    else:
        name = os.path.basename(path)
        filename = '%s.trees' % name
    return tree.write2file(filename)

if __name__ == '__main__':
    import sys
    sys.exit(main())

运行效果

复制代码 代码如下:

gtest_start/
├─build/
├─lib/
│  └─gtest/
├─output/
│  ├─primer/
│  │  ├─Debug/
│  │  │  ├─lib/
│  │  │  └─obj/
│  │  └─Release/
│  │      ├─lib/
│  │      └─obj/
│  └─thoughts/
│      ├─Debug/
│      │  ├─lib/
│      │  └─obj/
│      └─Release/
│          ├─lib/
│          └─obj/
├─src/
│  ├─primer/
│  └─thoughts/
├─test/
│  ├─primer/
│  └─thoughts/
├─third_party/
│  └─gtest/
└─tools/
Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
How Do I Use Beautiful Soup to Parse HTML?How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Mathematical Modules in Python: StatisticsMathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

How to Perform Deep Learning with TensorFlow or PyTorch?How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Serialization and Deserialization of Python Objects: Part 1Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

What are some popular Python libraries and their uses?What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PM

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationScraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AM

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

How to Create Command-Line Interfaces (CLIs) with Python?How to Create Command-Line Interfaces (CLIs) with Python?Mar 10, 2025 pm 06:48 PM

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.

Explain the purpose of virtual environments in Python.Explain the purpose of virtual environments in Python.Mar 19, 2025 pm 02:27 PM

The article discusses the role of virtual environments in Python, focusing on managing project dependencies and avoiding conflicts. It details their creation, activation, and benefits in improving project management and reducing dependency issues.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

MantisBT

MantisBT

Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.