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context = {
    'title': '项目报告',
    'user': {
        'name': '张三',
        'email': 'zhangsan@example.com'
    },
    'tasks': [
        {'description': '需求分析', 'deadline': '2023-12-31'},
        {'description': '代码开发', 'deadline': '2024-01-15'}
    ],
    'special_note': '请尽快完成初稿评审',
    'name': '项目经理',
    'date': '2025-08-04',
    'employees': [
        {'name': '张三', 'department': '研发部', 'hire_date': '2020-01-15', 'salary': 15000},
        {'name': '李四', 'department': '市场部', 'hire_date': '2019-05-20', 'salary': 12000},
        {'name': '王五', 'department': '财务部', 'hire_date': '2021-03-10', 'salary': 18000},
    ],
    	"node_config": {
		"ip1": {
			"check_hostnamectl": {
				"hostname": "node01",
				"operating_system": "Tencent tlinux 2.6",
				"kernel": "Linux 5.4.119-1-tlinux4-0010",
				"architecture": "x86-64"
			},
			"check_cpu_metrics": {
				"cpu_num": "4C",
				"model_name": "Intel(R) Xeon(R) CPU E5-2670 v3 @ 2.30GHz"
			},
			"check_physical_cpu": {
				"physical_cpu": "4C"
			},
			"check_physical_mem": {
				"physical_mem": "8G"
			},
			"check_nvme": {
				"nvme_size": "1.80TB*4"
			}
		},
		"ip2": {
			"check_hostnamectl": {
				"hostname": "node02",
				"operating_system": "Tencent tlinux 2.6",
				"kernel": "Linux 5.4.119-1-tlinux4-0010",
				"architecture": "x86-64"
			},
			"check_cpu_metrics": {
				"cpu_num": "4C",
				"model_name": "Intel(R) Xeon(R) CPU E5-2670 v3 @ 2.30GHz"
			},
			"check_physical_cpu": {
				"physical_cpu": "4C"
			},
			"check_physical_mem": {
				"physical_mem": "8G"
			},
			"check_nvme": {
				"nvme_size": "1.80TB*4"
			}
		},
		"ip3": {
			"check_hostnamectl": {
				"hostname": "node03",
				"operating_system": "Tencent tlinux 2.6",
				"kernel": "Linux 5.4.119-1-tlinux4-0010",
				"architecture": "x86-64"
			},
			"check_cpu_metrics": {
				"cpu_num": "4C",
				"model_name": "Intel(R) Xeon(R) CPU E5-2670 v3 @ 2.30GHz"
			},
			"check_physical_cpu": {
				"physical_cpu": "4C"
			},
			"check_physical_mem": {
				"physical_mem": "8G"
			},
			"check_nvme": {
				"nvme_size": "1.80TB*4"
			}
		}
	},
    "test_vm": "AAA"
}

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from docxtpl import DocxTemplate, InlineImage
from docx.shared import Pt
import os
# 数据准备
context = {
    'title': '项目报告',
    'user': {
        'name': '张三',
        'email': 'zhangsan@example.com'
    },
    'tasks': [
        {'description': '需求分析', 'deadline': '2023-12-31'},
        {'description': '代码开发', 'deadline': '2024-01-15'}
    ],
    'special_note': '请尽快完成初稿评审',
    'name': '项目经理',
    'date': '2025-08-04',
    'employees': [
        {'name': '张三', 'department': '研发部', 'hire_date': '2020-01-15', 'salary': 15000},
        {'name': '李四', 'department': '市场部', 'hire_date': '2019-05-20', 'salary': 12000},
        {'name': '王五', 'department': '财务部', 'hire_date': '2021-03-10', 'salary': 18000},
    ],
    	"node_config": {
		"ip1": {
			"check_hostnamectl": {
				"hostname": "node01",
				"operating_system": "Tencent tlinux 2.6",
				"kernel": "Linux 5.4.119-1-tlinux4-0010",
				"architecture": "x86-64"
			},
			"check_cpu_metrics": {
				"cpu_num": "4C",
				"model_name": "Intel(R) Xeon(R) CPU E5-2670 v3 @ 2.30GHz"
			},
			"check_physical_cpu": {
				"physical_cpu": "4C"
			},
			"check_physical_mem": {
				"physical_mem": "8G"
			},
			"check_nvme": {
				"nvme_size": "1.80TB*4"
			}
		},
		"ip2": {
			"check_hostnamectl": {
				"hostname": "node02",
				"operating_system": "Tencent tlinux 2.6",
				"kernel": "Linux 5.4.119-1-tlinux4-0010",
				"architecture": "x86-64"
			},
			"check_cpu_metrics": {
				"cpu_num": "4C",
				"model_name": "Intel(R) Xeon(R) CPU E5-2670 v3 @ 2.30GHz"
			},
			"check_physical_cpu": {
				"physical_cpu": "4C"
			},
			"check_physical_mem": {
				"physical_mem": "8G"
			},
			"check_nvme": {
				"nvme_size": "1.80TB*4"
			}
		},
		"ip3": {
			"check_hostnamectl": {
				"hostname": "node03",
				"operating_system": "Tencent tlinux 2.6",
				"kernel": "Linux 5.4.119-1-tlinux4-0010",
				"architecture": "x86-64"
			},
			"check_cpu_metrics": {
				"cpu_num": "4C",
				"model_name": "Intel(R) Xeon(R) CPU E5-2670 v3 @ 2.30GHz"
			},
			"check_physical_cpu": {
				"physical_cpu": "4C"
			},
			"check_physical_mem": {
				"physical_mem": "8G"
			},
			"check_nvme": {
				"nvme_size": "1.80TB*4"
			}
		}
	},
    "test_vm": "AAA"
}
#  加载模板
doc = DocxTemplate("template.docx")
# 创建InlineImage对象并添加到context
context['my_image'] = InlineImage(doc, 'test.png', width=Pt(100)) # Pt(100) 表示一个 100 磅 的长度。
# 在排版和印刷领域，1 磅 (Pt) = 1/72 英寸 ≈ 0.0353 厘米 ≈ 0.3527 毫米    1 英寸 = 2.54 厘米
context['my_image_2'] = InlineImage(doc, 'test.png', width=Pt(300))
# 渲染Word文档
doc.render(context)
output_docx = "output.docx"
doc.save(output_docx)
# 转换为PDF
def convert_to_pdf(docx_path):
    pdf_path = docx_path.replace('.docx', '.pdf')
    cmd = f"libreoffice --headless --convert-to pdf {docx_path} --outdir ."
    os.system(cmd)
    return pdf_path
pdf_output = convert_to_pdf(output_docx)
print(f"PDF生成成功: {pdf_output}")

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数字列表的总和是：{{ numbers | sum }}
总支出：{{ expenses | sum(attribute='amount') }}

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{% set ns = namespace(total=0) %}
{% for expense in expenses %}
    {% set ns.total = ns.total + expense.amount %}
    当前累计支出：{{ ns.total }}
{% endfor %}
总支出：{{ ns.total }}

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公式运算示例：
a = {{a}}, b = {{b}}
算术运算
        ◦ +：加法 {{ a + b }}
        ◦ -：减法 {{ a - b }}
        ◦ *：乘法 {{ a * b }}
        ◦ /：除法 {{ a / b }} (结果是浮点数)
        ◦ //：整除 {{ a // b }} (结果是整数)
        ◦ %：取模 {{ a % b }}
        ◦ **：幂运算 {{ a ** 2 }}
==：等于 {{a==b}}
    • !=：不等于  {{a!=b}}
    • >：大于   {{a>b}}
    • >=：大于等于{{a>=b}}
    • <：小于 {{a<b}}
    • <=：小于等于 {{a<=b}}
逻辑运算 (常用于 if 语句)
    • and {{a and b}}
    • or {{a or b}}
    • not {{not a}}
    • ( )：用于改变优先级 {{(a + b) * b}}
字符串连接: {{ s1 + " ----- " + s2 }}
列表/元组索引: {{ my_list[0] }}
    • 字典键值访问:
        ◦ {{ my_dict['key'] }}
        ◦ 或 {{ my_dict.key }} (如果键是有效的标识符)
    • 获取属性: {{ obj.test_attr }}
    • 函数： {{ first | get_full_name(last) }}
    • 三元表达式: {{ "Yes" if a > 1 else "No" }}
百分比表示：{{ a, b | my_filterA }}
多元素求和
1. 内置过滤器 
数字列表的总和是：{{ numbers | sum }}
总支出：{{ expenses | sum(attribute='amount') }}
2. for 循环自定义变量
{% set ns = namespace(total=0) %}
{% for expense in expenses %}
    {% set ns.total = ns.total + expense.amount %}
    当前累计支出：{{ ns.total }}
{% endfor %}
总支出：{{ ns.total }}
3. 自定义过滤器
所有支出总和：{{ expenses | sum_if('amount') }}

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from docxtpl import DocxTemplate, InlineImage
from docx.shared import Pt
import os
import jinja2
# 添加全局函数而不是过滤器
def calculate_percentage_vvd(a):
    return f"{(a ) * 100:.2f}%"
class Test:
    pass
test_obj = Test()
test_obj.test_attr = "test_attr"
# 自定义过滤器：条件求和
def sum_if(items, attribute=None, condition=None):
    total = 0
    for item in items:
        value = item[attribute] if attribute else item
        # 如果没有条件或者条件满足，则累加
        if condition is None or condition(item):
            total += value
    return total
# 数据准备
context = {
    "test_vm": "AAA",
    "a": 1,
    "b": 4,
    "s1": 'test_str1',
    "s2": 'test_str2',
    "my_list": [1, 2, 3, 4, 5],
    "my_dict": {
        "key": "dict_key",
    },
    "obj": test_obj,
	"first": "John",
    "last": "Doe",
	'numbers': [10, 20, 30, 40, 50],
    'expenses': [
        {'amount': 100, 'category': 'food'},
        {'amount': 200, 'category': 'transport'},
        {'amount': 150, 'category': 'entertainment'},
    ]
}
def get_full_name(first, last):
    return f"{first} {last}"
jinja_env = jinja2.Environment()
jinja_env.filters['my_filterA'] = calculate_percentage_vvd
jinja_env.filters['get_full_name'] = get_full_name
jinja_env.filters['sum_if'] = sum_if
#  加载模板
doc = DocxTemplate("template_plus.docx")
# 创建InlineImage对象并添加到context
context['my_image'] = InlineImage(doc, 'test.jpg', width=Pt(100))
context['my_image_2'] = InlineImage(doc, 'test.jpg', width=Pt(300))
# 渲染Word文档
doc.render(context, jinja_env)
output_docx = "output.docx"
doc.save(output_docx)
# 转换为PDF
def convert_to_pdf(docx_path):
    pdf_path = docx_path.replace('.docx', '.pdf')
    cmd = f"libreoffice --headless --convert-to pdf {docx_path} --outdir ."
    os.system(cmd)
    return pdf_path
pdf_output = convert_to_pdf(output_docx)
print(f"PDF生成成功: {pdf_output}")