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Commit 0111d3e

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Merge pull request #7 from codefuse-ai/cyz_dev
Add project codespaces config
2 parents 58d7bc0 + 4d43990 commit 0111d3e

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‎.devcontainer/devcontainer.json

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{
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"image": "ghcr.io/lonrun/codefuse-query-tutorial:0.5",
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"hostRequirements": {
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"cpus": 4
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},
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"customizations": {
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"codespaces": {
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"openFiles": ["tutorial/README.md"]
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}
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}
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}

‎tutorial/README.md

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## CodeQuery使用教程
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### 使用Github Codespaces 来体验CodeQuery分析能力
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#### 步骤
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- 在项目主页切换到目标分支
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- 创建 Codespaces,依次点击 Code -> Codespaces,在当前分支创建一个 Codespaces
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- 创建后,打开该 Codespaces,加载完成后,切换至项目 tutorial/notebook 目录下
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- 选择示例下的 jupyter notebook 分析教程,即可开始体验
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#### 注意
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- 打开jupyter页面之后,如果是第一次加载容器,你还需要配置教程所使用的内核,在右上角 "选择内核"弹出框中,依次选择 "Juypter Kernel..." -> "Godel Kernel" 即可。

‎tutorial/notebook/go_analysis.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"这是一个使用CodeFuse-Query分析Go项目的教程。在教程中,你将体验到使用命令行工具对代码仓库进行数据化,然后使用Godel语言来分析这个仓库。"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"检查cli是否就绪"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"!which sparrow"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"STEP 0: 克隆要分析的仓库。我们以 [gorm](https://github.com/go-gorm/gorm.git) 项目为例。"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023年11月22日T08:30:58.387715Z",
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"start_time": "2023年11月22日T08:30:44.572634Z"
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}
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},
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"outputs": [],
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"source": [
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"!git clone https://github.com/go-gorm/gorm.git"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"STEP 1: 代码数据化。使用 `sparrow database create` 命令创建一个db文件,指定待分析的仓库地址(当前目录下的gorm子目录),分析的语言(go),以及db文件的存储路径(放置在当前目录下的/db/gorm)。执行该命令之后,竟会生成一份db文件,该文件存储着代码仓库的结构化数据,之后的分析就是针对这份数据进行。"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023年11月23日T03:46:32.220317Z",
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"start_time": "2023年11月23日T03:46:12.785705Z"
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}
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},
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"outputs": [],
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"source": [
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"!sparrow database create --source-root gorm --data-language-type go --output ./db/gorm"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"STEP 2: 使用Godel分析语言分析db文件。在本教程中,可以点击代码左侧的执行按钮,直接运行分析脚本。在命令行中,你可以使用 `sparrow query run` 命令来执行查询脚本,具体可以使用`sparrow query run -h` 来获取详细参数信息。"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"<b>示例</b> 查询 [gorm](https://github.com/go-gorm/gorm.git) 的文件代码复杂度信息。\n",
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"\n",
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"第一行通过内核魔法命令指定分析的db路径,后面写查询文件代码复杂度Godel脚本。"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%db ./db/gorm\n",
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"// script\n",
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"use coref::go::*\n",
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"\n",
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"fn default_db() -> GoDB {\n",
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" return GoDB::load(\"coref_go_src.db\")\n",
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"}\n",
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"\n",
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"/**\n",
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" * @param name: 文件名\n",
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" * @param func: 函数名\n",
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" * @param cmplx: 函数圈复杂度\n",
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" * @param sl,el,sc,ec: 函数位置信息,依次为函数起始行,结束行\n",
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" */\n",
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"fn out(name: string, func: string, cmplx: int, sl: int, el: int) -> bool {\n",
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" for(f in GoFile(default_db()), function in Function(default_db())) {\n",
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" if ((!f.isAutoGenereatedFile()) &&\n",
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" f.key_eq(function.getBelongsFile()) &&\n",
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" name = f.getName() &&\n",
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" func = function.getName() &&\n",
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" cmplx = function.getCyclomaticComplexity() &&\n",
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" sl = function.getLocation().getStartLineNumber() &&\n",
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" el = function.getLocation().getEndLineNumber()) {\n",
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" return true\n",
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" }\n",
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" }\n",
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"}\n",
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"\n",
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"fn main() {\n",
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" output(out())\n",
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"}"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"保存上一次运行的 query 结果保存到一个JSON文件"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"%%save_to ./query.json"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"STEP 3: 好了,你可以针对分析生成的结果,进行进一步的代码分析了,比如你可以结合pandas库,使用刚刚生成的 query.json 实现最大函数复杂度的排序查询:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2023年11月23日T03:54:56.998681Z",
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"start_time": "2023年11月23日T03:54:56.976694Z"
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},
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"%%python\n",
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"import pandas as pd\n",
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"data = pd.read_json('./query.json')\n",
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"data.sort_values('cmplx', ascending=False, inplace=True)\n",
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"top_10 = data.head(10)\n",
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"print(top_10)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": false
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},
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"source": [
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"Enjoy!"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Godel kernel",
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"language": "rust",
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"name": "godel-jupyter"
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},
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"language_info": {
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"file_extension": ".gdl",
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"help_links": [
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{
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"text": "Godel kernel Magics",
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"url": "https://sparrow.alipay.com"
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}
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],
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"mimetype": "text/rust",
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"name": "rust",
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"version": "0.0.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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