# main.py
import subprocess
from copy import deepcopy
import json
from markdown import markdown
import time

from parse import parse, parse_proc
from gen_md import gen_md

num_gpus = {
    "s1": 4,
    "s2": 4,
    "s3": 2,
    "s4": 4,
    "s5": 5,
}


def get1GPU(i, j):
    cmd = ["ssh", "-o", "ConnectTimeout=2", f"s{i}", "nvidia-smi", f"-i {j}"]
    try:
        output = subprocess.check_output(cmd)
    except subprocess.CalledProcessError as e:
        return None, None
    ts = int(time.time())
    output = output.decode("utf-8")
    ret = parse(output)
    processes = deepcopy(ret["processes"])
    ret["processes"] = []
    for pid in processes:
        cmd = [
            "ssh",
            f"s{i}",
            "ps",
            "-o",
            "pid,user:30,command",
            "--no-headers",
            "-p",
            pid[0],
        ]
        output = subprocess.check_output(cmd)
        output = output.decode("utf-8")
        proc = parse_proc(output, pid[0])
        ret["processes"].append(proc)
        ret["processes"][-1]["pid"] = pid[0]
        ret["processes"][-1]["used_mem"] = pid[1]
    return ret, ts


def get_html(debug=False):
    results = {}
    for i in range(1, 6):
        results_per_host = {}
        for j in range(num_gpus[f"s{i}"]):
            ret, ts = get1GPU(i, j)
            if ret is None:
                continue
            results_per_host[f"GPU{j}"] = ret
        results[f"s{i}"] = results_per_host
    md = gen_md(results)

    with open("html_template.html", "r") as f:
        template = f.read()
        html = markdown(md, extensions=["tables", "fenced_code"])
        html = template.replace("{{html}}", html)
        html = html.replace(
            "{{update_time}}", time.strftime("%Y-%m-%d %H:%M", time.localtime())
        )
    if debug:
        with open("results.json", "w") as f:
            f.write(json.dumps(results, indent=2))
        with open("results.md", "w", encoding="utf-8") as f:
            f.write(md)
    with open("index.html", "w", encoding="utf-8") as f:
        f.write(html)


if __name__ == "__main__":
    import sys

    debug = False
    if len(sys.argv) > 1 and sys.argv[1] == "debug":
        debug = True
    get_html(debug)

# parse.py
def parse(text: str) -> dict:
    lines = text.split('\n')
    used_mem = lines[9].split('|')[2].split('/')[0].strip()[:-3]
    total_mem = lines[9].split('|')[2].split('/')[1].strip()[:-3]
    temperature = lines[9].split('|')[1].split()[1].replace('C', '')
    used_mem, total_mem, temperature = int(used_mem), int(total_mem), int(temperature)

    processes = []
    for i in range(18, len(lines) - 2):
        line = lines[i]
        if 'xorg/Xorg' in line:
            continue
        if 'gnome-shell' in line:
            continue
        pid = line.split()[4]
        use = line.split()[7][:-3]
        processes.append((pid, int(use)))
    return {
        'used_mem': used_mem,
        'total_mem': total_mem,
        'temperature': temperature,
        'processes': processes
    }

def parse_proc(text: str, pid: str) -> dict:
    lines = text.split('\n')
    for line in lines:
        if not line:
            continue
        if line.split()[0] != pid:
            continue
        user = line.split()[1]
        cmd = ' '.join(line.split()[2:])
        return {
            'user': user,
            'cmd': cmd
        }

# gen_md.py
def per_server(server: str, results: dict) -> str:
    md = f'# {server}\n\n'
    for gpu, ret in results.items():
        used, total, temperature = ret['used_mem'], ret['total_mem'], ret['temperature']
        md += f'<div class="oneGPU">\n'
        md += f'    <code>{gpu}: </code>\n'
        md += f'    <div class="g-container" style="display: inline-block;">\n'
        md += f'        <div class="g-progress" style="width: {used/total*100}%;"></div>\n'
        md += f'    </div>\n'
        md += f'    <code>  {used:5d}/{total} MiB  {temperature}℃</code>\n'
        md += '</div>\n'
    md += '\n'
    if any([len(ret['processes']) > 0 for ret in results.values()]):
        md += '\n| GPU | PID | User | Command | GPU Usage |\n'
        md += '| --- | --- | --- | --- | --- |\n'
        for gpu, ret in results.items():
            for proc in ret['processes']:
                md += f'| {gpu} | {proc["pid"]} | {proc["user"]} | {proc["cmd"]} | {proc["used_mem"]} MB |\n'
    md += '\n\n'
    return md

def gen_md(results: dict) -> dict:
    md = ''
    for server, ret in results.items():
        md += per_server(server, ret)
    return md

# main.py
from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.middleware.gzip import GZipMiddleware
from fastapi.responses import JSONResponse
import uvicorn
from nvitop import Device, bytes2human
import os
import asyncio
from contextlib import asynccontextmanager

suburl = os.environ.get("SUBURL", "")
if suburl != "" and not suburl.startswith("/"):
    suburl = "/" + suburl
frp_path = os.environ.get("FRP_PATH", "/home/peijie/Nvidia-API/frp")
if not os.path.exists(f"{frp_path}/frpc") or not os.path.exists(
    f"{frp_path}/frpc.toml"
):
    raise FileNotFoundError("frpc or frpc.toml not found in FRP_PATH")


@asynccontextmanager
async def run_frpc(app: FastAPI): # frp穿透到我的校内小主机
    command = [f"{frp_path}/frpc", "-c", f"{frp_path}/frpc.toml"]
    process = await asyncio.create_subprocess_exec(
        *command,
        stdout=asyncio.subprocess.DEVNULL,
        stderr=asyncio.subprocess.DEVNULL,
        stdin=asyncio.subprocess.DEVNULL,
        close_fds=True,
    )
    try:
        yield
    finally:
        try:
            process.terminate()
            await process.wait()
        except ProcessLookupError:
            pass


app = FastAPI(lifespan=run_frpc)

app.add_middleware(GZipMiddleware, minimum_size=100)
app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


@app.get(f"{suburl}/count")
async def get_ngpus(request: Request):
    try:
        ngpus = Device.count()
        return JSONResponse(content={"code": 0, "data": ngpus})
    except Exception as e:
        return JSONResponse(
            content={"code": -1, "data": None, "error": str(e)}, status_code=500
        )


@app.get(f"{suburl}/status")
async def get_status(request: Request):
    try:
        ngpus = Device.count()
    except Exception as e:
        return JSONResponse(
            content={"code": -1, "data": None, "error": str(e)}, status_code=500
        )

    idx = request.query_params.get("idx", None)
    if idx is not None:
        try:
            idx = idx.split(",")
            idx = [int(i) for i in idx]
            for i in idx:
                if i < 0 or i >= ngpus:
                    raise ValueError("Invalid GPU index")
        except ValueError:
            return JSONResponse(
                content={"code": 1, "data": None, "error": "Invalid GPU index"},
                status_code=400,
            )
    else:
        idx = list(range(ngpus))
    process_type = request.query_params.get("process", "")
    if process_type not in ["", "C", "G", "NA"]:
        return JSONResponse(
            content={
                "code": 1,
                "data": None,
                "error": "Invalid process type, choose from C, G, NA",
            },
            status_code=400,
        )
    try:
        devices = []
        processes = []
        for i in idx:
            device = Device(i)
            devices.append(
                {
                    "idx": i,
                    "fan_speed": device.fan_speed(),
                    "temperature": device.temperature(),
                    "power_status": device.power_status(),
                    "gpu_utilization": device.gpu_utilization(),
                    "memory_total_human": f"{round(device.memory_total() / 1024 / 1024)}MiB",
                    "memory_used_human": f"{round(device.memory_used() / 1024 / 1024)}MiB",
                    "memory_free_human": f"{round(device.memory_free() / 1024 / 1024)}MiB",
                    "memory_utilization": round(
                        device.memory_used() / device.memory_total() * 100, 2
                    ),
                }
            )
            now_processes = device.processes()
            sorted_pids = sorted(now_processes)
            for pid in sorted_pids:
                process = now_processes[pid]
                if process_type == "" or process_type in process.type:
                    processes.append(
                        {
                            "idx": i,
                            "pid": process.pid,
                            "username": process.username(),
                            "command": process.command(),
                            "type": process.type,
                            "gpu_memory": bytes2human(process.gpu_memory()),
                        }
                    )
        return JSONResponse(
            content={
                "code": 0,
                "data": {"count": ngpus, "devices": devices, "processes": processes},
            }
        )
    except Exception as e:
        return JSONResponse(
            content={"code": -1, "data": None, "error": str(e)}, status_code=500
        )


if __name__ == "__main__":
    port = int(os.environ.get("PORT", "8000"))
    uvicorn.run(app, host="127.0.0.1", port=port, reload=False)

{
  "code": 0,
  "data": {
    "count": 2,
    "devices": [
      {
        "idx": 0,
        "fan_speed": 41,
        "temperature": 71,
        "power_status": "336W / 350W",
        "gpu_utilization": 100,
        "memory_total_human": "24576MiB",
        "memory_used_human": "18653MiB",
        "memory_free_human": "5501MiB",
        "memory_utilization": 75.9
      },
      {
        "idx": 1,
        "fan_speed": 39,
        "temperature": 67,
        "power_status": "322W / 350W",
        "gpu_utilization": 96,
        "memory_total_human": "24576MiB",
        "memory_used_human": "18669MiB",
        "memory_free_human": "5485MiB",
        "memory_utilization": 75.97
      }
    ],
    "processes": [
      {
        "idx": 0,
        "pid": 1741,
        "username": "gdm",
        "command": "/usr/lib/xorg/Xorg vt1 -displayfd 3 -auth /run/user/125/gdm/Xauthority -background none -noreset -keeptty -verbose 3",
        "type": "G",
        "gpu_memory": "4.46MiB"
      },
      {
        "idx": 0,
        "pid": 2249001,
        "username": "xxx",
        "command": "~/.conda/envs/torch/bin/python -u train.py",
        "type": "C",
        "gpu_memory": "18618MiB"
      },
      {
        "idx": 1,
        "pid": 1741,
        "username": "gdm",
        "command": "/usr/lib/xorg/Xorg vt1 -displayfd 3 -auth /run/user/125/gdm/Xauthority -background none -noreset -keeptty -verbose 3",
        "type": "G",
        "gpu_memory": "9.84MiB"
      },
      {
        "idx": 1,
        "pid": 1787,
        "username": "gdm",
        "command": "/usr/bin/gnome-shell",
        "type": "G",
        "gpu_memory": "6.07MiB"
      },
      {
        "idx": 1,
        "pid": 2249002,
        "username": "xxx",
        "command": "~/.conda/envs/torch/bin/python -u train.py",
        "type": "C",
        "gpu_memory": "18618MiB"
      }
    ]
  }
}

<!-- App.vue -->
<script setup>
import GpuMonitor from './components/GpuMonitor.vue';

let urls = [];
let titles = [];
for (let i = 1; i <= 5; i++) {
  urls.push(`https://xxxx/status?process=C`);
  titles.push(`s${i}`);
}
const data_length = 100; // GPU利用率历史数据长度，用于绘制折线图（先画个饼）
const sleep_time = 500;  // 间隔多久刷新一次数据，单位毫秒
</script>

<template>
  <h3><a href="https://www.do1e.cn/posts/citelab/server-help">服务器使用说明</a></h3>
  <GpuMonitor v-for="(url, index) in urls" :key="index" :url="url" :title="titles[index]" :data_length="data_length" :sleep_time="sleep_time" />
</template>

<style scoped>
body {
  margin-left: 20px;
  margin-right: 20px;
}
</style>

<!-- components/GpuMonitor.vue -->
<template>
  <div>
    <h1>{{ title }}</h1>
    <article class="markdown-body">
      <div v-for="device in data.data.devices" :key="device.idx">
        <b>GPU{{ device.idx }}: </b>
        <b>显存： </b>
        <div class="g-container">
          <div class="g-progress" :style="{ width: device.memory_utilization + '%' }"></div>
        </div>
        <code style="width: 25ch;">{{ device.memory_used_human }}/{{ device.memory_total_human }} {{ device.memory_utilization }}%</code>
        <b>利用率： </b>
        <div class="g-container">
          <div class="g-progress" :style="{ width: device.gpu_utilization + '%' }"></div>
        </div>
        <code style="width: 5ch;">{{ device.gpu_utilization }}%</code>
        <b>温度： </b>
        <code style="width: 4ch;">{{ device.temperature }}°C</code>
      </div>
      <table v-if="data.data.processes.length > 0">
        <thead>
          <tr><th>GPU</th><th>PID</th><th>User</th><th>Command</th><th>GPU Usage</th></tr>
        </thead>
        <tbody>
          <tr v-for="process in data.data.processes" :key="process.pid">
            <td>GPU{{ process.idx }}</td>
            <td>{{ process.pid }}</td>
            <td>{{ process.username }}</td>
            <td>{{ process.command }}</td>
            <td>{{ process.gpu_memory }}</td>
          </tr>
        </tbody>
      </table>
    </article>
  </div>
</template>

<script>
import axios from 'axios';
import { Chart, registerables } from 'chart.js';

Chart.register(...registerables);

export default {
  props: {
    url: String,
    title: String,
    data_length: Number,
    sleep_time: Number
  },
  data() {
    return {
      data: {
        code: 0,
        data: {
          count: 0,
          devices: [],
          processes: []
        }
      },
      gpuUtilHistory: {}
    };
  },
  mounted() {
    this.fetchData();
    this.interval = setInterval(this.fetchData, this.sleep_time);
  },
  beforeDestroy() {
    clearInterval(this.interval);
  },
  methods: {
    fetchData() {
      axios.get(this.url)
        .then(response => {
          if (response.data.code !== 0) {
            console.error('Error fetching GPU data:', response.data);
            return;
          }
          this.data = response.data;
          for (let device of this.data.data.devices) {
            if (!this.gpuUtilHistory[device.idx]) {
              this.gpuUtilHistory[device.idx] = Array(this.data_length).fill(0);
            }
            this.gpuUtilHistory[device.idx].push(device.gpu_utilization);
            this.gpuUtilHistory[device.idx].shift();
          }
        })
        .catch(error => {
          console.error('Error fetching GPU data:', error);
        });
    }
  }
};
</script>

<style>
.g-container {
  width: 200px;
  height: 15px;
  border-radius: 3px;
  background: #eeeeee;
  display: inline-block;
}
.g-progress {
  height: inherit;
  border-radius: 3px 0 0 3px;
  background: #6e9bc5;
}
code {
  display: inline-block;
  text-align: right;
  background-color: #ffffff !important;
}
</style>

// main.js
import { createApp } from 'vue'
import App from './App.vue'

createApp(App).mount('#app')

<!DOCTYPE html>
<html lang="">
  <head>
    <meta charset="UTF-8">
    <link rel="icon" href="/favicon.ico">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/github-markdown-css/5.2.0/github-markdown.min.css">
    <title>实验室GPU使用情况</title>
  </head>
  <body>
    <div id="app"></div>
    <script type="module" src="/src/main.js"></script>
  </body>
</html>