feat/v0.1.5

README.md

@@ -28,8 +28,9 @@ English | <a href="README_zh-hans.md">中文</a>
 
 - [Key Function](#key-function)
 - [Changelog](#changelog)
-- [Use Case](#use-case)
+- [Installation](#installation)
 - [Getting Started](#getting-started)
+- [Use Case](#use-case)
 - [More Tips](#more-tips)
 - [LICENSE](#license)
 
@@ -63,26 +64,33 @@ English | <a href="README_zh-hans.md">中文</a>
 
 ## Changelog
 
+[24/01/23] 🚨 We use SQLite database and Peewee to replace the previous basic configuration information reading and writing solution by [#114](https://github.com/SwanHubX/SwanLab/issues/114). It's a major change that is highly beneficial for the future of the project, but the drawback is that it's not compatible with old versions (swanlab<=v0.1.4) of log data files. Therefore, if you need to visualize log files generated by older versions, please install version `<=0.1.4`.
+
+Additionally, we supported export the experiment list as `CSV`, new environment record items `Run path` and `logdir`, added interactive quick copy function, and new API `swanlab.config`.
+
 [24/01/14] 🔥 We supported a new UI, tracking additional environment information, including command, git commit/branch and memory. Additionally, we've added a `logdir` API, allowing developers to set the directory for log files.
 
 [24/01/07] ✨ We supported delete experiment and edit experiment inforamation on Dashboard.
 
-[24/01/01] We fixed some bugs to make SwanLab more stable.
-
 [Full Changelog](https://github.com/SwanHubX/SwanLab/releases)
 
 <br>
 
-## Use Case
+## Installation
 
-Learn how to use SwanLab more effectively by following these use cases:
+### with pip
 
-| Code Cases | Description | 
-| ------- | ------- |
-| [Hello World](https://github.com/SwanHubX/SwanLab-examples/tree/main/Hello_World) | Getting Started |
-| [MNIST](https://github.com/SwanHubX/SwanLab-examples/tree/main/MNIST) | Handwriting recognition based on a plain net and MNIST dataset with pytroch, swanlab. |
-| [Image Classification](https://github.com/SwanHubX/SwanLab-examples/blob/main/Resnet50) | Cat and dog classification based on ResNet50 with pytorch, swanlab and gradio. [Tutorial](https://zhuanlan.zhihu.com/p/676430630). |
-| [Text Generation](https://github.com/SwanHubX/SwanLab-examples/blob/main/Word_language_model) | Text generation based on Word_language_model (RNN/LSTM/GRU/Transformer) |
+Requirement：Python 3.8+.
+
+Use [pip](https://pip.pypa.io/en/stable/) to install our stable release version. The installation command is as follows:
+
+```bash
+pip install -U swanlab
+```
+
+### with source code
+
+If you need the bleeding edge of the code and can't wait for a new release, you must [install the library from source](https://geektechstudio.feishu.cn/wiki/DvxSweHUKiAe8yksci3cMflbnwh#SMXHdJ1c1o4jzTxcDticHcwvnHd)。
 
 <br>
 
@@ -95,7 +103,7 @@ pip install -U swanlab
 ```
 
 2. Second, Use the example code snippet below as a template to integrate SwanLab to your Python script:
-```Python
+```python
 import swanlab
 
 # Start a SwanLab Run with swanlab.init
@@ -120,9 +128,28 @@ That's it! Open http://127.0.0.1:5092 to view a dashboard of your first SwanLab
 
 <br>
 
+## Use Case
+
+Learn how to use SwanLab more effectively by following these use cases:
+
+| Code Cases | Description | 
+| ------- | ------- |
+| [Hello World](https://github.com/SwanHubX/SwanLab-examples/tree/main/Hello_World) | Getting Started |
+| [MNIST](https://github.com/SwanHubX/SwanLab-examples/tree/main/MNIST) | Handwriting recognition based on a plain net and MNIST dataset with pytroch, swanlab. |
+| [Image Classification](https://github.com/SwanHubX/SwanLab-examples/blob/main/Resnet50) | Cat and dog classification based on ResNet50 with pytorch, swanlab and gradio. [Tutorial](https://zhuanlan.zhihu.com/p/676430630). |
+| [Text Generation](https://github.com/SwanHubX/SwanLab-examples/blob/main/Word_language_model) | Text generation based on Word_language_model (RNN/LSTM/GRU/Transformer) |
+
+<br>
+
 ## More Tips
 
-- Set a log directory save path and run the Dashboard using it:
+🏄‍♀️ Experiment Dashboard：
+
+<details>
+<summary>Set a log directory save path and run the Dashboard using it</summary>
+
+Set a log directory save path, such as `./logs`:
+
 ```python
 import swanlab 
 
@@ -131,15 +158,37 @@ swanlab.init(
 )
 ```
 
+Run the Dashboard using it:
+
 ```bash
 $ swanlab watch --logdir ./logs_path
 ```
 
-- Set the Host and Port for the Dashboard: 
+</details>
+
+<details>
+<summary>Set the Host and Port for the Dashboard</summary>
+
 ```bash
 $ swanlab watch --host 0.0.0.0 --port 8080
 ```
-- Use Argparse init swanlab.config: 
+
+</details>
+
+<details>
+<summary>Remotely access Dashboard</summary>
+
+- Link：[Access the SwanLab Dashboard While Training on a Remote Server](https://zhuanlan.zhihu.com/p/677224865)
+
+</details>
+
+⚙️ Other：
+
+<details>
+<summary>argparse init swanlab.config</summary>
+
+`swanlab.config` supports directly passing variables of type `argparse.Namespace`, such as:
+
 ```python
 import argparse
 import swanlab
@@ -150,11 +199,12 @@ args = parser.parse_args()
 
 
 swanlab.init(
-    config=vars(args)
+    config=args
 )
 ```
 
-- [Remotely access Dashboard](https://zhuanlan.zhihu.com/p/677224865): Access the SwanLab Dashboard While Training on a Remote Server.
+</details>
+
 
 <br>
 

README_zh-hans.md

@@ -28,8 +28,9 @@
 
 - [核心功能](#核心功能)
 - [更新日志](#更新日志)
-- [案例](#案例)
+- [安装](#安装)
 - [快速开始](#快速开始)
+- [案例](#案例)
 - [更多技巧](#更多技巧)
 - [协议](#协议)
 
@@ -57,32 +58,37 @@
 - **🥔 离线支持**: SwanLab可以完全离线运行，无需任何对互联网的访问。例如，它可以在您的本地计算机上、企业防火墙后面或数据中心中运行。
 
 > [!NOTE]
-> See the SwanLab <a href="https://geektechstudio.feishu.cn/wiki/MwXmw9yDeiZWyQkPnNgcixwWnwu">Documentaion</a> and <a href="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/SwanHubX/SwanLab-examples">Examples</a> for a full description of the SwanLab.
+> 请查看SwanLab的<a href="https://geektechstudio.feishu.cn/wiki/MwXmw9yDeiZWyQkPnNgcixwWnwu">文档</a>和<a href="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/SwanHubX/SwanLab-examples">示例</a>，以获取有关SwanLab的完整介绍。
 
 <br>
 
 ## 更新日志
 
+[24/01/23] 🚨 我们使用SQLite数据库和Peewee库替代了之前的基础配置信息读写方案（[#114](https://github.com/SwanHubX/SwanLab/issues/114)），这是个极大有利于项目未来的改动，但缺陷是不兼容旧版本（swanlab<=v0.1.4）的日志数据文件，所以如需可视化旧版本产生的日志文件请安装<=0.1.4的版本。与此同时，我们增加了支持导出实验列表为CSV，新的环境记录项`Run path`和`logdir`，增加了快捷复制的交互，以及新的API `swanlab.config`。
+
 [24/01/14] 🔥 我们发布了一个新的UI界面，以及跟踪更多环境信息，包括Command、git提交/分支、和机器内存。此外，我们还添加了一个`logdir` API，允许开发人员设置日志文件的目录。
 
 [24/01/07] ✨ 我们支持在仪表板上删除实验和编辑实验信息。
 
-[24/01/01] 我们修复了一些错误，使SwanLab更加稳定。
-
 [完整更新日志](https://github.com/SwanHubX/SwanLab/releases)
 
 <br>
 
-## 案例
+## 安装
 
-通过以下用例学习如何更有效地使用SwanLab：
+### pip安装
 
-| 案例 | 介绍 | 
-| ------- | ------- |
-| [Hello World](https://github.com/SwanHubX/SwanLab-examples/tree/main/Hello_World) | 简单入门 |
-| [MNIST](https://github.com/SwanHubX/SwanLab-examples/tree/main/MNIST) | 基于神经网络的MNIST手写体识别（使用pytorch、swanlab库） |
-| [图像分类](https://github.com/SwanHubX/SwanLab-examples/blob/main/Resnet50) | ResNet50猫狗分类（使用pytorch、swanlab、Gradio库） [图文教程](https://zhuanlan.zhihu.com/p/676430630) |
-| [文本生成](https://github.com/SwanHubX/SwanLab-examples/blob/main/Word_language_model) | 基于自然语言模型的文本生成 (RNN/LSTM/GRU/Transformer) |
+环境要求：Python 3.8+
+
+使用[pip](https://pip.pypa.io/en/stable/)将安装我们稳定发布的版本，安装命令如下所示：
+
+```bash
+pip install -U swanlab
+```
+
+### 源码安装
+
+如果您等不及发布，想体验最新的代码与特性，那么必须[从源代码安装此库](https://geektechstudio.feishu.cn/wiki/DvxSweHUKiAe8yksci3cMflbnwh#SMXHdJ1c1o4jzTxcDticHcwvnHd)。
 
 <br>
 
@@ -95,7 +101,7 @@ pip install -U swanlab
 ```
 
 2. 然后，使用下面的示例代码片段作为模板，将SwanLab集成到您的Python脚本中:
-```Python
+```python
 import swanlab
 
 # Start a SwanLab Run with swanlab.init
@@ -120,9 +126,28 @@ $ swanlab watch
 
 <br>
 
+## 案例
+
+通过以下用例学习如何更有效地使用SwanLab：
+
+| 案例 | 介绍 | 
+| ------- | ------- |
+| [Hello World](https://github.com/SwanHubX/SwanLab-examples/tree/main/Hello_World) | 简单入门 |
+| [MNIST](https://github.com/SwanHubX/SwanLab-examples/tree/main/MNIST) | 基于神经网络的MNIST手写体识别（使用pytorch、swanlab库） |
+| [图像分类](https://github.com/SwanHubX/SwanLab-examples/blob/main/Resnet50) | ResNet50猫狗分类（使用pytorch、swanlab、Gradio库） [图文教程](https://zhuanlan.zhihu.com/p/676430630) |
+| [文本生成](https://github.com/SwanHubX/SwanLab-examples/blob/main/Word_language_model) | 基于自然语言模型的文本生成 (RNN/LSTM/GRU/Transformer) |
+
+<br>
+
 ## 更多技巧
 
-- 设置1个日志文件保存路径，以及运行基于它的实验看板：
+🏄‍♀️ 实验看板相关：
+
+<details>
+<summary>设置日志文件保存路径，并运行基于它的实验看板</summary>
+
+设置日志文件保存路径，比如`./logs`: 
+
 ```python
 import swanlab 
 
@@ -131,16 +156,35 @@ swanlab.init(
 )
 ```
 
+运行基于`./logs`的看实验看板：
+
 ```bash
-$ swanlab watch --logdir ./logs_path
+$ swanlab watch --logdir ./logs
 ```
+</details>
+
+
+<details>
+<summary>设置实验看板的主机和端口</summary>
 
-- 设置实验看板的主机和端口：
 ```bash
 $ swanlab watch --host 0.0.0.0 --port 8080
 ```
+</details>
+
+<details>
+<summary>远程访问实验看板</summary>
 
-- 使用Argparse初始化swanlab.config: 
+- 链接：[在远程服务器上进行训练时，访问SwanLab实验看板](https://zhuanlan.zhihu.com/p/677224865)
+
+</details>
+
+⚙️ 其他：
+
+<details>
+<summary>argparse与swanlab.config</summary>
+
+swanlab.config支持直接传入argparse.Namespace类型的变量，如:
 ```python
 import argparse
 import swanlab
@@ -151,11 +195,10 @@ args = parser.parse_args()
 
 
 swanlab.init(
-    config=vars(args)
+    config=args
 )
 ```
-
-- [远程访问实验看板](https://zhuanlan.zhihu.com/p/677224865): 在远程服务器上进行训练时，访问SwanLab实验看板。
+</details>
 
 <br>
 

swanlab/cli/main.py

@@ -10,7 +10,7 @@
 
 import click
 from .utils import is_valid_ip, is_valid_port, is_valid_root_dir, URL
-from ..utils import FONT
+from ..utils import FONT, version_limit
 from ..env import get_server_host, get_server_port, get_swanlog_dir
 import time
 from ..db import connect
@@ -66,12 +66,16 @@ def watch(log_level: str, **kwargs):
     from ..server import app
     import uvicorn
 
-    # 在此处已经完成了路径的检查，所以可以直接导入
-    connect()
+    log_dir = get_swanlog_dir()
+    print(log_dir)
+    version_limit(log_dir, mode="watch")
 
     # debug一下当前日志文件夹的位置
-    swl.debug("Try to explore the swanlab experiment logs in: " + FONT.bold(get_swanlog_dir()))
-
+    swl.debug("Try to explore the swanlab experiment logs in: " + FONT.bold(log_dir))
+    try:
+        connect()
+    except FileNotFoundError:
+        swl.error("Can not find the swanlab db in: " + FONT.bold(log_dir))
     # ---------------------------------- 日志等级处理 ----------------------------------
     swl.setLevel(log_level)
     # ---------------------------------- 服务地址处理 ----------------------------------

swanlab/cli/utils.py

@@ -13,6 +13,7 @@
 import click
 from ..utils import FONT, file
 from ..env import PORT, HOST, ROOT
+import json
 
 
 def is_valid_ip(ctx, param, ip: str) -> tuple:

swanlab/data/run/exp.py

@@ -83,10 +83,10 @@ def add(self, key: str, data: DataType, step: int = None):
             """
             由于添加图表的同时会尝试转换data的类型，但这在注入step之前
             所以此处需要手动注入依赖
-            关于step，如果step格式不正确，会在tag_obj.add的时候被拦截，此处如果格式不正确直接设置为1即可
+            关于step，如果step格式不正确，会在tag_obj.add的时候被拦截，此处如果格式不正确直接设置为0即可
             """
             if isinstance(data, BaseType):
-                data.step = 1 if step is None or not isinstance(step, int) else step
+                data.step = 0 if step is None or not isinstance(step, int) else step
                 data.tag = tag_obj.tag
             tag_obj.create_chart(tag, data)
         # 检查tag创建时图表是否创建成功，如果失败则也没有写入数据的必要了，直接退出
@@ -154,9 +154,9 @@ def add(self, data: DataType, step: int = None):
         if step is not None and not isinstance(step, int):
             swanlog.warning(f"Step {step} is not int, SwanLab will set it automatically.")
             step = None
-        # 转换step，如果step为None，则改为合适的长度，目前step从1开始
+        # 转换step，如果step为None，则改为合适的长度，目前step从0开始
         if step is None:
-            step = len(self.__steps) + 1
+            step = len(self.__steps)
         # 如果step已经存在，打印警告并退出
         if step in self.__steps:
             return swanlog.warning(f"Step {step} on tag {self.tag} already exists, ignored.")

swanlab/data/sdk.py

@@ -17,6 +17,7 @@
 from ..env import init_env, ROOT
 from .utils.file import check_dir_and_create, formate_abs_path
 from ..db import Project, connect
+from ..utils import version_limit
 
 
 run: Optional["SwanLabRun"] = None
@@ -82,7 +83,7 @@ def init(
         except IOError:
             raise IOError("logdir must be a path and have Write permission.")
         os.environ[ROOT] = logdir
-    # 如果没有传入logdir，则使用默认的logdir,即当前工作目录，但是需要保证目录存在
+    # 如果没有传入logdir，则使用默认的logdir, 即当前工作目录，但是需要保证目录存在
     else:
         logdir = os.path.abspath("swanlog")
         try:
@@ -91,7 +92,8 @@ def init(
                 raise IOError
         except:
             raise IOError("logdir must have Write permission.")
-
+    # 检查logdir内文件的版本，如果<=0.1.4则报错
+    version_limit(logdir, mode="init")
     # 初始化环境变量
     init_env()
     # 连接数据库，要求路径必须存在，但是如果数据库文件不存在，会自动创建

swanlab/package.json

@@ -1,6 +1,6 @@
 {
 	"name": "swanlab",
-	"version": "0.1.4",
+	"version": "0.1.5",
 	"description": "",
 	"python": "true"
 }