dash-fastapi-admin/dash-fastapi-frontend/utils/mod_mag.py

#获取supervisor信息
def get_supervisor_info(data):
 # 生成表格数据
    supervisor_data = []
    
    # 计算 Supervisor 的数量
    supervisor_count = sum(1 for node in data if node["node_type"] == "Supervisor")

    # 获取 Supervisor 的 ip_address
    supervisor_ip_address = next((node["ip_address"] for node in data if node["node_type"] == "Supervisor"), "")

    # 计算 CPU-Info
    cpu_info_value = f'{data[0]["cpu_count"] - data[0]["cpu_available"]:.2f}'
    cpu_info_other = data[0]["cpu_count"]

    # 计算 CPU-Memory-Info
    cpu_memory_info_value = (data[0]["mem_total"] - data[0]["mem_available"]) / 1024 / 1024
    cpu_memory_info_other = data[0]["mem_total"] / 1024 / 1024

    # 填充表格数据
    supervisor_data.append({
        '字段1': "Count",
        '字段2': supervisor_count,
        '字段3': "",  # other 为空
    })
    supervisor_data.append({
        '字段1': "Address",
        '字段2': supervisor_ip_address,
        '字段3': "",  # other 为空
    })
    supervisor_data.append({
        '字段1': "CPU-Info",
        '字段2': cpu_info_value,
        '字段3': cpu_info_other,
    })
    supervisor_data.append({
        '字段1': "CPU-Memory-Info",
        '字段2': f'{cpu_memory_info_value:.2f}',
        '字段3': f'{cpu_memory_info_other:.2f}',
    })
    return supervisor_data

def get_workers_info(data):
    # 生成表格数据
    workers_data = []

    # 计算 Worker 的数量
    workers_count = sum(1 for node in data if node["node_type"] == "Worker")

    # 计算所有 Worker 的 CPU 信息
    total_cpu_count = sum(node["cpu_count"] for node in data if node["node_type"] == "Worker")
    total_cpu_available = sum(node["cpu_available"] for node in data if node["node_type"] == "Worker")
    cpu_info_value = f'{total_cpu_count - total_cpu_available:.2f}'
    cpu_info_other = total_cpu_count

    # 计算所有 Worker 的 CPU 内存信息
    total_mem_total = sum(node["mem_total"] for node in data if node["node_type"] == "Worker")
    total_mem_available = sum(node["mem_available"] for node in data if node["node_type"] == "Worker")
    cpu_memory_info_value = (total_mem_total - total_mem_available) / 1024 / 1024
    cpu_memory_info_other = total_mem_total / 1024 / 1024

    # 计算所有 Worker 的 GPU 数量
    total_gpu_count = sum(node["gpu_count"] for node in data if node["node_type"] == "Worker")

    # 计算所有 Worker 的 GPU 内存信息
    total_gpu_vram_total = sum(node["gpu_vram_total"] for node in data if node["node_type"] == "Worker")
    total_gpu_vram_available = sum(node["gpu_vram_available"] for node in data if node["node_type"] == "Worker")
    gpu_memory_info_value = (total_gpu_vram_total - total_gpu_vram_available) / 1024 / 1024
    gpu_memory_info_other = total_gpu_vram_total / 1024 / 1024

    # 填充表格数据
    workers_data.append({
        '字段1': "Count",
        '字段2': workers_count,
        '字段3': "",  # other 为空
    })
    workers_data.append({
        '字段1': "CPU-Info",
        '字段2': cpu_info_value,
        '字段3': cpu_info_other,
    })
    workers_data.append({
        '字段1': "CPU-Memory-Info",
        '字段2': f'{cpu_memory_info_value:.2f} MB',
        '字段3': f'{cpu_memory_info_other:.2f} MB',
    })
    workers_data.append({
        '字段1': "GPU-Count",
        '字段2': total_gpu_count,
        '字段3': "",  # other 为空
    })
    workers_data.append({
        '字段1': "GPU-Memory-Info",
        '字段2': f'{gpu_memory_info_value:.2f} MB',
        '字段3': f'{gpu_memory_info_other:.2f} MB',
    })

    return workers_data

def get_worker_detail_info(data):
    # 生成表格数据
    worker_detail_data = []

    # 遍历所有的 Worker 节点
    for node in data:
        if node["node_type"] == "Worker":
            # 获取 Worker 的详细信息
            address = node["ip_address"]
            cpu_usage = f'{node["cpu_count"] - node["cpu_available"]:.2f}'
            cpu_total = node["cpu_count"]
            mem_usage = (node["mem_total"] - node["mem_available"]) / 1024 / 1024
            mem_total = node["mem_total"] / 1024 / 1024
            gpu_count = node["gpu_count"]
            gpu_mem_usage = (node["gpu_vram_total"] - node["gpu_vram_available"]) / 1024 / 1024
            gpu_mem_total = node["gpu_vram_total"] / 1024 / 1024

            # 填充表格数据
            worker_detail_data.append({
                '字段1': "Worker",
                '字段2': address,
                '字段3': f'{cpu_usage} cores',
                '字段4': f'{cpu_total} cores',
                '字段5': f'{mem_usage:.2f} MB',
                '字段6': f'{mem_total:.2f} MB',
                '字段7': gpu_count,
                '字段8': f'{gpu_mem_usage:.2f} MB',
                '字段9': f'{gpu_mem_total:.2f} MB',
            })

    return worker_detail_data


# def get_model_run_data(data):
#     # 生成表格数据
#     mode_run_data = []

#     # 遍历所有的 Worker 节点
#     for node in data:
#         if node["node_type"] == "Worker":
#             # 获取 Worker 的详细信息
#             address = node["ip_address"]
#             cpu_usage = f'{node["cpu_count"] - node["cpu_available"]:.2f}'
#             cpu_total = node["cpu_count"]
#             mem_usage = (node["mem_total"] - node["mem_available"]) / 1024 / 1024
#             mem_total = node["mem_total"] / 1024 / 1024
#             gpu_count = node["gpu_count"]
#             gpu_mem_usage = (node["gpu_vram_total"] - node["gpu_vram_available"]) / 1024 / 1024
#             gpu_mem_total = node["gpu_vram_total"] / 1024 / 1024

#             # 填充表格数据
#             worker_detail_data.append({
#                 '字段1': "Worker",
#                 '字段2': address,
#                 '字段3': f'{cpu_usage} cores',
#                 '字段4': f'{cpu_total} cores',
#                 '字段5': f'{mem_usage:.2f} MB',
#                 '字段6': f'{mem_total:.2f} MB',
#                 '字段7': gpu_count,
#                 '字段8': f'{gpu_mem_usage:.2f} MB',
#                 '字段9': f'{gpu_mem_total:.2f} MB',
#             })

#     return worker_detail_data