Nextcloud Tasks Synchronization Client

Introduction

The Nextcloud Tasks Synchronization Client is a desktop application developed with PyQt5, designed to help users manage and synchronize tasks on Nextcloud across Windows and Linux platforms. The script nextcloudtasks.py utilizes the nextcloud-tasks project. The icon is from iconfinder.com. This client features:

• Task Management: Supports adding, editing, and deleting tasks, with the ability to synchronize them to the Nextcloud server.
• Offline Mode: In the event of network issues or when in offline mode, task data is saved locally in a JSON file and synchronized once the network is restored.
• Multi-language Support: Comes with built-in Chinese and English interfaces, making it convenient for users of different languages.
• System Tray Notifications: Automatically pops up tray reminders before task deadlines to ensure users do not miss important tasks.

Installing with conda

To facilitate dependency management, it is recommended to use conda to create an isolated Python environment. Please follow the steps below for installation and configuration:

1. Create a conda Environment

Open a terminal or command prompt and execute the following command to create a new conda environment (for example, named nextcloud_task) and specify the Python version (Python 3.11 or higher is recommended):

conda create -n nextcloud_task python=3.11

2. Activate the Environment

Once the environment is created, activate it:

conda activate nextcloud_task

3. Install Dependencies

pip install pyqt5 caldav

4. Configure the Configuration File

Fill in the following content in the conf.json file, and please remove the comments (the text following #), or just fill these in config menu:

{

"language": "zh", # zh/en,

"tasks_json_path": "/path/tasks.json",

"icon_path": "/path/icon.png",

"url": "xxx/nextcloud/remote.php/dav/calendars/xxx/x/",

"username": "user",

"password": "passwd",

"check_interval": 60, # in seconds

"show_ddl_message_box": true, # if show ddl warning box

"ssl_verify_cert": false, # check cert or not

"offline_mode": false # on-line or off-line mode

}

5. Run the Program

Within the activated conda environment, run the main program (for example, main.py):

python main.py

or

python main.py conf.json

or just run the exe file.

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