diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..5ba74c7624a29abd67a2feb4e2a6a9deb1e95549 --- /dev/null +++ b/.gitignore @@ -0,0 +1,7 @@ +.vscode +.idea +.DS_Store +__pycache__ +*.pyc +*.zip +*.out \ No newline at end of file diff --git a/README.md b/README.md index 888040171108ae0af1c59b2cf2b2e23be93deed3..3feabf21db7018a8528517d2eb7f3a6b175fa3ad 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,202 @@ # skill_tree_ai -AI 技能树 \ No newline at end of file +AI 技能树 + +## 初始化技能树 + +技能树合成和id生成脚本目前用 Python 脚本统一处理 + +```bash +pip install -r requirement.txt +``` + + +## 目录结构说明 + +data目录下包含 难度节点/章节点/知识节点 3级目录结构 + +* 技能树`骨架文件`： + * 位置：`data/tree.json` + * 说明：该文件是执行 `python main.py` 生成的，请勿人工编辑 +* 技能树`根节点`配置文件： + * 位置：`data/config.json` + * 说明：可编辑配置关键词等字段，其中 `node_id` 字段是生成的，请勿编辑 +* 技能树`难度节点`： + * 位置：`data/xxx`，例如: `data/1.AI初阶` + * 说明： + * 每个技能树有 3 个等级，目录前的序号是**必要**的，用来保持文件夹目录的顺序 + * 每个目录下有一个 `config.json` 可配置关键词信息，其中 `node_id` 字段是生成的，请勿编辑 +* 技能树`章节点`： + * 位置：`data/xxx/xxx`，例如：`data/1.AI初阶/1.预备知识` + * 说明： + * 每个技能树的每个难度等级有 n 个章节，目录前的序号是**必要**的，用来保持文件夹目录的顺序 + * 每个目录下有一个 `config.json` 可配置关键词信息，其中 `node_id` 字段是生成的，请勿编辑 +* 技能树`知识节点`： + * 位置：`data/xxx/xxx`，例如：`data/1.AI初阶/1.预备知识/1.AI简介` + * 说明： + * 每个技能树的每章有 n 个知识节点，目录前的序号是必要的，用来保持文件夹目录的顺序 + * 每个目录下有一个 `config.json` + * 其中 `node_id` 字段是生成的，请勿编辑 + * 其中 `keywords` 可配置关键字字段 + * 其中 `children` 可配置该`知识节点`下的子树结构信息，参考后面描述 + * 其中 `export` 可配置该`知识节点`下的导出习题信息，参考后面描述 + + +## `知识节点` 子树信息结构 + +例如 `data/1.AI初阶/1.预备知识/1.AI简介/config.json` 里配置对该知识节点子树信息结构，用来增加技能树社区服务在该知识节点上的深度数据匹配： + +```json +{ + // ... + + "children": [ + { + "AI简史": { + "keywords": [ + "AI起源", + "人工智能简史" + ], + "children": [] + } + } + ], +} +``` + + +## `知识节点` 的导出习题编辑 + +例如 `data/1.AI初阶/1.预备知识/1.AI简介/config.json` 里配置对该知识节点导出的习题 + +```json +{ + // ... + "export": [ + "helloworld.json", + // ... + ] +} +``` + +在 `export` 字段中，我们列出习题定义的`json`文件列表 ，下面我们了解如何编写习题。 + +## `知识节点` 的导出习题选项配置编辑 + +目前我们支持使用 markdown 语法直接编辑习题和各选项。 + +如前文内容，我们在知识节点下增加习题 `helloworld`的定义文件，即在`data/1.AI初阶/1.预备知识/1.AI简介` 目录增加一个`helloworld.json`文件： + +```json +{ + "type": "code_options", + "author": "幻灰龙", + "source": "helloworld.md", + "notebook_enable": true +} +``` + +其中 + +* `type` 字段目前都固定是 `code_options`， +* `notebook_enable` 字段决定这个习题是否生成对应的 `notebook` +* `source` 字段代表习题编辑的 `markdwon` 文件。 + +现在我们新建一个 `helloworld.md` 并编辑为： + +````markdown +# Hello World + +HelloWorld, 请阅读如下代码： + +```python +import numpy as np + +def test(): + X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]]) + y = np.dot(X, np.array([1, 2])) + 3 + + // TODO(选择选项中的代码填充此处) + + y_predict = reg.predict(np.array([[3, 5]])) + print(y_predict) + +if __name__ == '__main__': + test() +``` + +若将以下选项中的代码分别填充到上述代码中**TODO**处，哪个选项不是线性模型？ + +## template + +```java +import numpy as np + +def test(): + X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]]) + y = np.dot(X, np.array([1, 2])) + 3 + + // 下面的 code 占位符会被替换成答案和选项代码 + $code + + y_predict = reg.predict(np.array([[3, 5]])) + print(y_predict) + +if __name__ == '__main__': + test() +``` + + +## 答案 + +```python +from sklearn import svm +reg = svm.SVC(kernel='rbf').fit(X, y) +``` + +## 选项 + +### 使用 LinearRegression + +```python +from sklearn.linear_model import LinearRegression +reg = LinearRegression().fit(X, y) +``` + +### 使用岭回归 + +```python +from sklearn.linear_model import Ridge +reg = Ridge(alpha=0.1) +``` + +### 使用拉索算法 + +```python +from sklearn.linear_model import Lasso +reg = Lasso(alpha=0.1).fit(X, y) +``` +```` + +这是一个最基本的习题MarkDown结构，说明如下： + +* 一级标题是`习题标题` +* 一级标题紧接着的段落是`习题描述` +* `## template` 是用于和答案、选项结合合成`NoteBook`代码用的模版 +* `## 答案` 是习题选项中符合题目描述的答案项 +* `## 选项` 下包含几个混淆用的选项 + * 每个选项带有一个三级标题，例如`### 使用 LinearRegression`， + * 最终生成的习题中不包含选项的三级标题，所以这个标题可以用来标注一些编辑信息 + +## 可选的习题源代码项目 + +编辑习题中，为了测试方便，可以直接在3级知识节点目录下创建对应的习题代码子目录 + + + +## 技能树合成 + +在根目录下执行 `python main.py` 会合成技能树文件，合成的技能树文件: `data/tree.json` + +* 合成过程中，会自动检查每个目录下 `config.json` 里的 `node_id` 是否存在，不存在则生成 +* 合成过程中，会自动检查每个知识点目录下 `config.json` 里的 `export` 里导出的习题配置，检查是否存在`exercise_id` 字段，如果不存在则生成 diff --git "a/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/config.json" "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..e3c3ce2b8923f0c833d2887706b7bce53b8c3f38 --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/config.json" @@ -0,0 +1,18 @@ +{ + "node_id": "ai-3387d5d7a7684fbb9187e26d6d8d187b", + "keywords": [], + "children": [ + { + "AI简史": { + "keywords": [ + "AI起源", + "人工智能简史" + ], + "children": [] + } + } + ], + "export": [ + "helloworld.json" + ] +} \ No newline at end of file diff --git "a/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/helloworld.json" "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/helloworld.json" new file mode 100644 index 0000000000000000000000000000000000000000..8bb392f99f3c9a42e20281f66781cffb45750e95 --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/helloworld.json" @@ -0,0 +1,6 @@ +{ + "type": "code_options", + "author": "幻灰龙", + "source": "helloworld.md", + "notebook_enable": true +} \ No newline at end of file diff --git "a/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/helloworld.md" "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/1.AI\347\256\200\344\273\213/helloworld.md" new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git "a/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/2.\347\272\277\346\200\247\345\217\215\345\220\221\344\274\240\346\222\255/config.json" "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/2.\347\272\277\346\200\247\345\217\215\345\220\221\344\274\240\346\222\255/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..bad5017eda2019ee3c11a93c7d1aeb37c8ed4918 --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/2.\347\272\277\346\200\247\345\217\215\345\220\221\344\274\240\346\222\255/config.json" @@ -0,0 +1,6 @@ +{ + "node_id": "ai-861408a897f042fd8044bfc9838d2747", + "keywords": [], + "children": [], + "export": [] +} \ No newline at end of file diff --git "a/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/3.\346\242\257\345\272\246\344\270\213\351\231\215/config.json" "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/3.\346\242\257\345\272\246\344\270\213\351\231\215/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..a63ae81590b06257c4109649ae19dde80a3432fa --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/3.\346\242\257\345\272\246\344\270\213\351\231\215/config.json" @@ -0,0 +1,6 @@ +{ + "node_id": "ai-8deab4930eef40b0bd9c2337e7ad5c51", + "keywords": [], + "children": [], + "export": [] +} \ No newline at end of file diff --git "a/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/config.json" "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..27cba2afa1b10e8febc074b9f462598d7e5e15ae --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/1.\351\242\204\345\244\207\347\237\245\350\257\206/config.json" @@ -0,0 +1,4 @@ +{ + "node_id": "ai-bc6f05e925e147fd8fca53041f70e022", + "keywords": [] +} \ No newline at end of file diff --git "a/data/1.AI\345\210\235\351\230\266/2.\347\272\277\346\200\247\345\233\236\345\275\222/config.json" "b/data/1.AI\345\210\235\351\230\266/2.\347\272\277\346\200\247\345\233\236\345\275\222/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..f3bece3f2cdc708e64d56d9d0849ff3b9382e738 --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/2.\347\272\277\346\200\247\345\233\236\345\275\222/config.json" @@ -0,0 +1,4 @@ +{ + "node_id": "ai-f51cf279b2c94e099da0f3e1fcfc793e", + "keywords": [] +} \ No newline at end of file diff --git "a/data/1.AI\345\210\235\351\230\266/3.\347\272\277\346\200\247\345\210\206\347\261\273/config.json" "b/data/1.AI\345\210\235\351\230\266/3.\347\272\277\346\200\247\345\210\206\347\261\273/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..cead11da45b77cdb3c23a7b5d6354bb3810f574a --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/3.\347\272\277\346\200\247\345\210\206\347\261\273/config.json" @@ -0,0 +1,4 @@ +{ + "node_id": "ai-d7c91624cb92446786eeaad0cd336445", + "keywords": [] +} \ No newline at end of file diff --git "a/data/1.AI\345\210\235\351\230\266/config.json" "b/data/1.AI\345\210\235\351\230\266/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..bc8440d21eaba2865acb2981b412cfb00d1b20cc --- /dev/null +++ "b/data/1.AI\345\210\235\351\230\266/config.json" @@ -0,0 +1,4 @@ +{ + "node_id": "ai-7c98592cf49347b69cc10b653731bd16", + "keywords": [] +} \ No newline at end of file diff --git "a/data/2.AI\344\270\255\351\230\266/config.json" "b/data/2.AI\344\270\255\351\230\266/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..a039167ba39b6189ed1c3d08cc6c9473846ff104 --- /dev/null +++ "b/data/2.AI\344\270\255\351\230\266/config.json" @@ -0,0 +1,4 @@ +{ + "node_id": "ai-8b462755b2014f90bff16ec87d2fb84c", + "keywords": [] +} \ No newline at end of file diff --git "a/data/3.AI\351\253\230\351\230\266/config.json" "b/data/3.AI\351\253\230\351\230\266/config.json" new file mode 100644 index 0000000000000000000000000000000000000000..738807655bfb8a3485436909a5ed0ab4038ae97b --- /dev/null +++ "b/data/3.AI\351\253\230\351\230\266/config.json" @@ -0,0 +1,4 @@ +{ + "node_id": "ai-de60cc83f32541499c62e182ac952d83", + "keywords": [] +} \ No newline at end of file diff --git a/data/config.json b/data/config.json new file mode 100644 index 0000000000000000000000000000000000000000..1ce16d7fed9f5c967175883269afbbd1a6e87dfb --- /dev/null +++ b/data/config.json @@ -0,0 +1,5 @@ +{ + "tree_name": "ai", + "keywords": [], + "node_id": "ai-e199f3e521db4347a8bc662f8f33ca6c" +} \ No newline at end of file diff --git a/data/tree.json b/data/tree.json new file mode 100644 index 0000000000000000000000000000000000000000..c952422bd4e278ccab46edd2c18419b961ba5bc0 --- /dev/null +++ b/data/tree.json @@ -0,0 +1,73 @@ +{ + "ai": { + "node_id": "ai-e199f3e521db4347a8bc662f8f33ca6c", + "keywords": [], + "children": [ + { + "AI初阶": { + "node_id": "ai-7c98592cf49347b69cc10b653731bd16", + "keywords": [], + "children": [ + { + "预备知识": { + "node_id": "ai-bc6f05e925e147fd8fca53041f70e022", + "keywords": [], + "children": [ + { + "AI简介": { + "node_id": "ai-3387d5d7a7684fbb9187e26d6d8d187b", + "keywords": [], + "children": [] + } + }, + { + "线性反向传播": { + "node_id": "ai-861408a897f042fd8044bfc9838d2747", + "keywords": [], + "children": [] + } + }, + { + "梯度下降": { + "node_id": "ai-8deab4930eef40b0bd9c2337e7ad5c51", + "keywords": [], + "children": [] + } + } + ] + } + }, + { + "线性回归": { + "node_id": "ai-f51cf279b2c94e099da0f3e1fcfc793e", + "keywords": [], + "children": [] + } + }, + { + "线性分类": { + "node_id": "ai-d7c91624cb92446786eeaad0cd336445", + "keywords": [], + "children": [] + } + } + ] + } + }, + { + "AI中阶": { + "node_id": "ai-8b462755b2014f90bff16ec87d2fb84c", + "keywords": [], + "children": [] + } + }, + { + "AI高阶": { + "node_id": "ai-de60cc83f32541499c62e182ac952d83", + "keywords": [], + "children": [] + } + } + ] + } +} \ No newline at end of file diff --git a/main.py b/main.py new file mode 100644 index 0000000000000000000000000000000000000000..ed3952b121bd3c8f95afa9bac3974084db3d0b0e --- /dev/null +++ b/main.py @@ -0,0 +1,6 @@ +# -*- coding: utf-8 -*- +from src.tree import TreeWalker + +if __name__ == '__main__': + walker = TreeWalker("data", "ai", "ai") + walker.walk() diff --git a/src/tree.py b/src/tree.py new file mode 100644 index 0000000000000000000000000000000000000000..95e1cbc5812810e30465eccc2632464caa5438e7 --- /dev/null +++ b/src/tree.py @@ -0,0 +1,296 @@ +# -*- coding: utf-8 -*- +import logging +from genericpath import exists +import json +import os +import uuid +import sys +import re + +id_set = set() +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) +handler = logging.StreamHandler(sys.stdout) +formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s') +handler.setFormatter(formatter) +logger.addHandler(handler) + + +def load_json(p): + with open(p, 'r', encoding='utf-8') as f: + return json.loads(f.read()) + + +def dump_json(p, j, exist_ok=False, override=False): + if os.path.exists(p): + if exist_ok: + if not override: + return + else: + logger.error(f"{p} already exist") + sys.exit(0) + + with open(p, 'w+', encoding='utf-8') as f: + f.write(json.dumps(j, indent=2, ensure_ascii=False)) + + +def ensure_config(path): + config_path = os.path.join(path, "config.json") + if not os.path.exists(config_path): + node = {"keywords": []} + dump_json(config_path, node, exist_ok=True, override=False) + return node + else: + return load_json(config_path) + + +def parse_no_name(d): + p = r'(\d+)\.(.*)' + m = re.search(p, d) + + try: + no = int(m.group(1)) + dir_name = m.group(2) + except: + sys.exit(0) + + return no, dir_name + + +def check_export(base, cfg): + flag = False + exports = [] + for export in cfg.get('export', []): + ecfg_path = os.path.join(base, export) + if os.path.exists(ecfg_path): + exports.append(export) + else: + flag = True + if flag: + cfg["export"] = exports + return flag + + +class TreeWalker: + def __init__(self, root, tree_name, title=None, log=None): + self.name = tree_name + self.root = root + self.title = tree_name if title is None else title + self.tree = {} + self.logger = logger if log is None else log + + def walk(self): + root = self.load_root() + root_node = { + "node_id": root["node_id"], + "keywords": root["keywords"], + "children": [] + } + self.tree[root["tree_name"]] = root_node + self.load_levels(root_node) + self.load_chapters(self.root, root_node) + for index, level in enumerate(root_node["children"]): + level_title = list(level.keys())[0] + level_node = list(level.values())[0] + level_path = os.path.join(self.root, f"{index+1}.{level_title}") + self.load_chapters(level_path, level_node) + for index, chapter in enumerate(level_node["children"]): + chapter_title = list(chapter.keys())[0] + chapter_node = list(chapter.values())[0] + chapter_path = os.path.join( + level_path, f"{index+1}.{chapter_title}") + self.load_sections(chapter_path, chapter_node) + for index, section_node in enumerate(chapter_node["children"]): + section_title = list(section_node.keys())[0] + full_path = os.path.join( + chapter_path, f"{index}.{section_title}") + if os.path.isdir(full_path): + self.ensure_exercises(full_path) + + tree_path = os.path.join(self.root, "tree.json") + dump_json(tree_path, self.tree, exist_ok=True, override=True) + return self.tree + + def load_levels(self, root_node): + levels = [] + for level in os.listdir(self.root): + if not os.path.isdir(level): + continue + level_path = os.path.join(self.root, level) + num, config = self.load_level_node(level_path) + levels.append((num, config)) + + levels = self.resort_children(self.root, levels) + root_node["children"] = [item[1] for item in levels] + return root_node + + def load_level_node(self, level_path): + config = self.ensure_level_config(level_path) + num, name = self.extract_node_env(level_path) + + result = { + name: { + "node_id": config["node_id"], + "keywords": config["keywords"], + "children": [], + } + } + + return num, result + + def load_chapters(self, base, level_node): + chapters = [] + for name in os.listdir(base): + full_name = os.path.join(base, name) + if os.path.isdir(full_name): + num, chapter = self.load_chapter_node(full_name) + chapters.append((num, chapter)) + + chapters = self.resort_children(base, chapters) + level_node["children"] = [item[1] for item in chapters] + return level_node + + def load_sections(self, base, chapter_node): + sections = [] + for name in os.listdir(base): + full_name = os.path.join(base, name) + if os.path.isdir(full_name): + num, section = self.load_section_node(full_name) + sections.append((num, section)) + + sections = self.resort_children(base, sections) + chapter_node["children"] = [item[1] for item in sections] + return chapter_node + + def resort_children(self, base, children): + children.sort(key=lambda item: item[0]) + for index, [number, element] in enumerate(children): + title = list(element.keys())[0] + origin = os.path.join(base, f"{number}.{title}") + posted = os.path.join(base, f"{index+1}.{title}") + if origin != posted: + self.logger.info(f"rename [{origin}] to [{posted}]") + os.rename(origin, posted) + return children + + def ensure_chapters(self): + for subdir in os.listdir(self.root): + self.ensure_level_config(subdir) + + def load_root(self): + config_path = os.path.join(self.root, "config.json") + if not os.path.exists(config_path): + config = { + "tree_name": self.name, + "keywords": [], + "node_id": self.gen_node_id(), + } + dump_json(config_path, config, exist_ok=True, override=True) + else: + config = load_json(config_path) + flag, result = self.ensure_node_id(config) + if flag: + dump_json(config_path, result, exist_ok=True, override=True) + + return config + + def ensure_level_config(self, path): + config_path = os.path.join(path, "config.json") + if not os.path.exists(config_path): + config = { + "node_id": self.gen_node_id() + } + dump_json(config_path, config, exist_ok=True, override=True) + else: + config = load_json(config_path) + flag, result = self.ensure_node_id(config) + if flag: + dump_json(config_path, config, exist_ok=True, override=True) + return config + + def ensure_chapter_config(self, path): + config_path = os.path.join(path, "config.json") + if not os.path.exists(config_path): + config = { + "node_id": self.gen_node_id(), + "keywords": [] + } + dump_json(config_path, config, exist_ok=True, override=True) + else: + config = load_json(config_path) + flag, result = self.ensure_node_id(config) + if flag: + dump_json(config_path, config, exist_ok=True, override=True) + return config + + def ensure_section_config(self, path): + config_path = os.path.join(path, "config.json") + if not os.path.exists(config_path): + config = { + "node_id": self.gen_node_id(), + "keywords": [], + "children": [], + "export": [] + } + dump_json(config_path, config, exist_ok=True, override=True) + else: + config = load_json(config_path) + flag, result = self.ensure_node_id(config) + if flag: + dump_json(config_path, config, exist_ok=True, override=True) + return config + + def ensure_node_id(self, config): + if "node_id" not in config: + config["node_id"] = self.gen_node_id() + return True, config + else: + return False, config + + def gen_node_id(self): + return f"{self.name}-{uuid.uuid4().hex}" + + def extract_node_env(self, path): + try: + _, dir = os.path.split(path) + self.logger.info(path) + number, title = dir.split(".", 1) + return int(number), title + except Exception as error: + self.logger.error(f"目录 [{path}] 解析失败，结构不合法，可能是缺少序号") + sys.exit(1) + + def load_chapter_node(self, full_name): + config = self.ensure_chapter_config(full_name) + num, name = self.extract_node_env(full_name) + result = { + name: { + "node_id": config["node_id"], + "keywords": config["keywords"], + "children": [], + } + } + return num, result + + def load_section_node(self, full_name): + config = self.ensure_section_config(full_name) + num, name = self.extract_node_env(full_name) + result = { + name: { + "node_id": config["node_id"], + "keywords": config["keywords"], + "children": config.get("children", []) + } + } + # if "children" in config: + # result["children"] = config["children"] + return num, result + + def ensure_exercises(self, section_path): + config = self.ensure_section_config(section_path) + for e in config.get("export", []): + full_name = os.path.join(section_path, e) + exercise = load_json(full_name) + if "exercise_id" not in exercise: + exercise["exercise_id"] = uuid.uuid4().hex + dump_json(full_name, exercise)