WeRead Assistant: A Python Tool for Exporting Books and Notes from WeChat Read

The era of mass reading has arrived, with 210 million users of reading apps and over 5 million daily active users; the majority are young, well‑educated users in major Chinese cities.

To organize books and export notes from WeChat Read, the author created a small utility written in Python.

1. Directory Structure

The project consists of three main files:

├─ excel_func.py      # read/write Excel files
├─ pyqt_gui.py       # PyQt GUI interface
└─ wereader.py       # WeChat Read API interactions

2. excel_func.py

This module uses xlrd and xlwt to read and write Excel workbooks. The key function write_excel_xls creates a workbook, adds sheets, writes data row by row, and saves the file.

def write_excel_xls(path, sheet_name_list, value):
    workbook = xlwt.Workbook()
    index = len(value)
    for sheet_name in sheet_name_list:
        sheet = workbook.add_sheet(sheet_name)
        for i in range(0, index):
            for j in range(0, len(value[i])):
                sheet.write(i, j, value[i][j])
    workbook.save(path)

The workflow is: create Excel file → create sheets → write data → save.

3. pyqt_gui.py

This script builds a PyQt window that embeds a QWebEngineView to load the WeChat Read login page, captures cookies, and triggers login verification.

class MainWindow(QMainWindow):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.DomainCookies = {}
        self.setWindowTitle('微信读书助手')
        self.resize(900, 600)
        self.setWindowFlags(Qt.WindowMinimizeButtonHint)
        self.setFixedSize(self.width(), self.height())
        url = 'https://weread.qq.com/#login'
        self.browser = QWebEngineView()
        QWebEngineProfile.defaultProfile().cookieStore().deleteAllCookies()
        QWebEngineProfile.defaultProfile().cookieStore().cookieAdded.connect(self.onCookieAdd)
        self.browser.loadFinished.connect(self.onLoadFinished)
        self.browser.load(QUrl(url))
        self.setCentralWidget(self.browser)

    def onLoadFinished(self):
        global USER_VID, HEADERS
        cookies = ['{}={};'.format(k, v) for k, v in self.DomainCookies.items()]
        HEADERS.update(Cookie=' '.join(cookies))
        if login_success(HEADERS):
            print('登录微信读书成功!')
            if 'wr_vid' in self.DomainCookies:
                USER_VID = self.DomainCookies['wr_vid']
                print('用户id:{}'.format(USER_VID))
                self.close()
        else:
            print('请扫描二维码登录微信读书...')

    def onCookieAdd(self, cookie):
        if 'weread.qq.com' in cookie.domain():
            name = cookie.name().data().decode('utf-8')
            value = cookie.value().data().decode('utf-8')
            if name not in self.DomainCookies:
                self.DomainCookies.update({name: value})

The flow: create Qt window → instantiate QWebEngineView → bind cookie and load‑finished events → load login page → handle cookies → verify login.

4. wereader.py

Provides API wrappers:

def get_bookshelf(userVid, headers):
    """获取书架上所有书"""
    url = "https://i.weread.qq.com/shelf/friendCommon"
    params = dict(userVid=userVid)
    r = requests.get(url, params=params, headers=headers, verify=False)
    if r.ok:
        data = r.json()
    else:
        raise Exception(r.text)
    books_finish_read = set()
    books_recent_read = set()
    for book in data['recentBooks']:
        if not book['bookId'].isdigit():
            continue
        b = Book(book['bookId'], book['title'], book['author'], book['cover'], book['intro'], book['category'])
        books_recent_read.add(b)
    books_all = books_finish_read + books_recent_read
    return dict(finishReadBooks=books_finish_read, recentBooks=books_recent_read, allBooks=books_all)

And a function to fetch and format notes as markdown:

def get_bookmarklist(bookId, headers):
    """获取某本书的笔记返回md文本"""
    url = "https://i.weread.qq.com/book/bookmarklist"
    params = dict(bookId=bookId)
    r = requests.get(url, params=params, headers=headers, verify=False)
    if r.ok:
        data = r.json()
    else:
        raise Exception(r.text)
    chapters = {c['chapterUid']: c['title'] for c in data['chapters']}
    contents = defaultdict(list)
    for item in sorted(data['updated'], key=lambda x: x['chapterUid']):
        chapter = item['chapterUid']
        text = item['markText']
        start = int(item['range'].split('-')[0])
        contents[chapter].append((start, text))
    chapters_map = {title: level for level, title in get_chapters(int(bookId), headers)}
    res = ''
    for c in sorted(chapters.keys()):
        title = chapters[c]
        res += '#' * chapters_map[title] + ' ' + title + '
'
        for start, text in sorted(contents[c], key=lambda e: e[0]):
            res += '> ' + text.strip() + '

'
        res += '
'
    return res

The workflow: retrieve recent, finished, and all books → filter out public accounts → return a dictionary; then fetch notes, map them to chapters, and output markdown.

5. How to Run

Execute the following commands in the project directory:

# Change to the project directory
cd <directory_name>
# Uninstall existing dependencies
pip uninstall -y -r requirement.txt
# Reinstall dependencies from Tsinghua mirror
pip install -r requirement.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
# Launch the GUI
python pyqt_gui.py

After scanning the QR code and successful login, the tool exports the bookshelf to an Excel file and saves each book's notes as individual text files.