背景

• os：centos7
• Grafana：v12
• grafana-image-renderer：v4.0.10
• 插件：否

grafana-image-renderer可以以插件形式启动，也可以以单独服务启动，在centos7插件启动时，报错glibc版本太低，未找到Glibc_2.27，所以以单独服务启动。

一、安装Grafana

# 解压部署
tar zxvf grafana-12.1.0.linux-amd64.tar.gz -C /usr/local/
cd /usr/local/grafana-v12.1.0/
# 编辑配置文件
vi conf/defaults.ini
# 调试简单
[auth.anonymous]
enabled = true
# 配置rendering地址
[rendering]
server_url = http://192.168.113.138:8081/render
callback_url = http://192.168.113.138:3000/
# 启动服务
nohup bin/grafana server &

二、启动grafana-image-renderer

docker network create grafana
docker pull docker.1ms.run/grafana/grafana-image-renderer:v4.0.10
docker run --network grafana --name renderer -p 8081:8081 --rm --detach docker.1ms.run/grafana/grafana-image-renderer:v4.0.10

三、测试接口

直接访问：http://192.168.113.138:3000/render/d-solo/bdd48668-7073-4adc-b548-276133845e71?orgId=1&panelId=2&width=1000&height=500&from=now-24h&to=now

四、编写py脚本及效果

脚本由AI大模型生成。如果有能力可以修改Grafana源码，页面传入DASHBOARD_UID 即可实现点击下载。

import requests
import time
from typing import List, Dict
from PIL import Image, ImageDraw, ImageFont  # ✅ 确保包含 ImageFont
import img2pdf
from datetime import datetime
import os# ================== 配置区 ==================
GRAFANA_HOST = "http://192.168.113.138:3000"
API_KEY = "YOUR_API_KEY"  # Service Account Token 或 API Key
DASHBOARD_UID = "bdd48668-7073-4adc-b548-276133845e71"  # 替换为你的 Dashboard UID
OUTPUT_DIR = "panels_output"  # 输出目录
DELAY_BETWEEN_SHOTS = 1.0  # 每次截图间隔（秒），避免渲染服务压力过大
FROM = "now-24h"
TO = "now"
WIDTH = 1200
HEIGHT = 600
TIMEOUT = 30
# ==========================================
# 创建输出目录
os.makedirs(OUTPUT_DIR, exist_ok=True)
headers = {"Authorization": f"Bearer {API_KEY}","User-Agent": "Grafana-Report-Service/v1.0"
}def get_dashboard_json(uid: str) -> Dict:"""获取 Dashboard JSON 结构"""url = f"{GRAFANA_HOST}/api/dashboards/uid/{uid}"response = requests.get(url, headers=headers, timeout=10)if response.status_code != 200:raise Exception(f"获取 Dashboard 失败: {response.status_code} {response.text}")return response.json()def extract_panels(dashboard_data: Dict) -> List[Dict]:"""精准提取所有可渲染的 panel（排除 row、text 等不可截图类型）基于 Grafana v12 的 Dashboard JSON 结构"""panels = []dashboard = dashboard_data["dashboard"]skip_types = {"row", "text", "alertlist", "dashboard-link", "separator"}def is_renderable_panel(obj):# 必须是字典，有 id 和 typeif not isinstance(obj, dict):return Falseif "id" not in obj or "type" not in obj:return Falsepanel_type = obj["type"]# 排除不可渲染的类型if panel_type in skip_types:return False# 确保 id 是数字（真实的 panel id）if not isinstance(obj["id"], int):return Falsereturn Truedef walk(obj):if isinstance(obj, dict):# 如果当前对象是可渲染 panel，加入结果if is_renderable_panel(obj):title = obj.get("title") or f"Panel_{obj['id']}"panels.append({"id": obj["id"],"title": title.strip(),"type": obj["type"]})# 递归遍历所有值for value in obj.values():walk(value)elif isinstance(obj, list):for item in obj:walk(item)walk(dashboard)return panelsdef sanitize_filename(name: str) -> str:"""清理文件名，移除不合法字符"""return "".join(c if c.isalnum() or c in " _-." else "_" for c in name)def render_panel_to_png(panel_id: int, title: str, output_path: str) -> bool:"""渲染单个 panel 为 PNG"""slug = DASHBOARD_UIDrender_url = f"{GRAFANA_HOST}/render/d-solo/{DASHBOARD_UID}/{slug}"params = {"orgId": 1,"panelId": panel_id,"width": WIDTH,"height": HEIGHT,"tz": "Asia/Shanghai","from": FROM,"to": TO,"deviceScaleFactor": 1.5,"renderFormat": "png"}try:response = requests.get(render_url,params=params,headers=headers,timeout=TIMEOUT)if response.status_code == 200:with open(output_path, "wb") as f:f.write(response.content)print(f"✅ [{panel_id}] '{title}' → 保存成功: {output_path}")return Trueelse:print(f"❌ [{panel_id}] '{title}' → 渲染失败: {response.status_code}")print(f"   响应: {response.text[:200]}")return Falseexcept Exception as e:print(f"❌ [{panel_id}] '{title}' → 异常: {e}")return Falsedef generate_pdf_report(dashboard_title: str, panel_images: list, output_pdf: str):"""使用 img2pdf + Pillow 生成 PDF 报告panel_images: 图片文件路径列表（字符串）"""try:# ========== 1. 创建封面页 ==========try:# 尝试使用黑体（Windows 通常有 simhei.ttf）font_title = ImageFont.truetype("simhei.ttf", 60)font_text = ImageFont.truetype("simhei.ttf", 40)except:# 如果没有中文字体，用默认（可能显示乱码）font_title = ImageFont.load_default()font_text = ImageFont.load_default()# 使用与面板图像相同的宽度panel_width = WIDTH  # 从配置中获取宽度，默认为1200# 保持宽高比计算封面高度（使用A4纸的宽高比）cover_height = int(panel_width * 1.414)  # A4纸的宽高比约为1:1.414cover = Image.new('RGB', (panel_width, cover_height), 'white')draw = ImageDraw.Draw(cover)# 绘制标题title_pos = (panel_width // 2, cover_height // 3)  # 居中 X，Y=1/3处time_pos = (panel_width // 2, cover_height // 2)  # 居中 X，Y=1/2处# 获取文本边界框以居中bbox_title = draw.textbbox((0, 0), dashboard_title, font=font_title)title_width = bbox_title[2] - bbox_title[0]draw.text((panel_width // 2 - title_width // 2, cover_height // 3),dashboard_title, fill="black", font=font_title)generate_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")time_text = f"生成时间：{generate_time}"bbox_time = draw.textbbox((0, 0), time_text, font=font_text)time_width = bbox_time[2] - bbox_time[0]draw.text((panel_width // 2 - time_width // 2, cover_height // 2),time_text, fill="gray", font=font_text)# 保存封面cover_path = os.path.join(OUTPUT_DIR, "cover_page.png")cover.save(cover_path, "PNG")print(f"🎨 封面页已生成: {cover_path} (宽度: {panel_width}px)")# ========== 2. 构建图片路径列表 ==========# 确保所有 panel_images 都是字符串路径，且文件存在image_paths = [cover_path]  # 先加封面for img_path in panel_images:if isinstance(img_path, str) and os.path.exists(img_path):image_paths.append(img_path)else:print(f"⚠️ 跳过不存在的图片: {img_path}")if len(image_paths) < 2:print("❌ 没有足够的图片生成 PDF")return False# ========== 3. 转换为 PDF ==========with open(output_pdf, "wb") as f:f.write(img2pdf.convert(image_paths))print(f"📄 PDF 报告已生成: {output_pdf}")return Trueexcept Exception as e:print(f"❌ PDF 生成失败: {e}")import tracebacktraceback.print_exc()return Falsedef main():print(f"🔍 正在获取 Dashboard: {DASHBOARD_UID}")try:data = get_dashboard_json(DASHBOARD_UID)dashboard_title = data["dashboard"]["title"]print(f"📊 获取成功: '{dashboard_title}'")panels = extract_panels(data)print(f"📦 共找到 {len(panels)} 个可渲染的 panel\n")success_count = 0image_paths = []for i, panel in enumerate(panels, 1):title_clean = sanitize_filename(panel["title"])output_file = f"panel_{panel['id']}_{title_clean}.png"output_path = os.path.join(OUTPUT_DIR, output_file)print(f"🖼️  [{i}/{len(panels)}] 渲染中: {panel['title']}")if render_panel_to_png(panel["id"], panel["title"], output_path):success_count += 1image_paths.append(output_path)  # 收集成功生成的图片time.sleep(DELAY_BETWEEN_SHOTS)print(f"\n🎉 批量截图完成！成功: {success_count}/{len(panels)} 个")# ==== 生成 PDF ====if success_count > 0:output_pdf = f"report_{DASHBOARD_UID}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf"generate_pdf_report(dashboard_title, sorted(image_paths), output_pdf)else:print("❌ 没有成功截图，跳过 PDF 生成")except Exception as e:print(f"💥 执行失败: {e}")if __name__ == "__main__":main()

Grafana可视化：

效果：