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
bash
# 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
bash
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。
python
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 type
if not isinstance(obj, dict):
return False
if "id" not in obj or "type" not in obj:
return False
panel_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 False
return True
def 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 panels
def 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_UID
render_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 True
else:
print(f"❌ [{panel_id}] '{title}' → 渲染失败: {response.status_code}")
print(f" 响应: {response.text[:200]}")
return False
except Exception as e:
print(f"❌ [{panel_id}] '{title}' → 异常: {e}")
return False
def 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1:1.414
cover = 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 True
except Exception as e:
print(f"❌ PDF 生成失败: {e}")
import traceback
traceback.print_exc()
return False
def 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 = 0
image_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 += 1
image_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：
