将yaml导入excel答案

【问题标题】：Import yaml to excel将yaml导入excel
【发布时间】：2022-08-04 23:44:02
【问题描述】：

我有以下 .YAML 文件：

Name: Tom
Surname: Smith
Status: Married
Childs:
- ChildName: Willy
  Age: 30
  Grandchild:
  - GrandchildName: John
    Age: 4
  - GrandchildName: Maria
    Age: 3
- ChildName: Arthur
  Age: 40
  Grandchild: N/A

我做了什么：

import openpyxl
import yaml

with open(\'family.yaml\') as file:
    family_list = yaml.load(file, Loader=yaml.FullLoader)

def create_workbook():
    wb = openpyxl.Workbook(\'family.xlsx\')
    wb.save(\'family.xlsx\')

def update_workbook():
    wb = openpyxl.load_workbook(\'family.xlsx\')

    sh1 = wb.active

    for item in family_list.items():
        sh1.append(item)
    wb.save(\'family.xlsx\')

create_workbook()
update_workbook()

此代码允许我将数据（没有“暂停”部分，因此只有姓名、姓氏、状态）添加到 excel 中，但将“姓名”、“姓氏”等添加到 A1 列中（而不是在行中作为我想要）

Final excel workbook I want to get

我不确定如何附加和格式化（每个暂停符号应该是新行）提到的数据。我将不胜感激任何提示！

标签： python excel yaml openpyxl xlsx

【解决方案1】：

由于 Excel 所需的布局，这不是通过 pandas 将数据直接转置到 Excel。可能有几种方法可以做到这一点，我决定将 yaml 加载分成三个字典；
家长
孩子
孙子
因此可以调整它们以适应 excel 布局。然后使用 Pandas 在适当的行/列位置将这些导出到 Excel。

此示例已使用添加/减少和重命名的子元素和孙子元素进行了测试，但可能无法处理丢失或不正确的元素。

代码中说明了它的作用，因此您可以了解此方法的工作原理。

import pandas as pd
import yaml
from yaml.loader import SafeLoader

def write_next_segments(dataf, start_row, startcol):
    header = True
    for ele in dataf:
        dataframe = pd.DataFrame([dataf[ele]])
        dataframe.to_excel(writer, sheet_name=save_sheet,
                           index=False,
                           header=header,
                           startrow=start_row,
                           startcol=startcol)
        if header:
            header = False
            start_row += 2
            adjust_colmns(dataframe, startcol)
        else:
            start_row += 1


def adjust_colmns(dataframe, offset):
    for column in dataframe:
        column_width = max(dataframe[column].astype(str).map(len).max(), len(column)) + 2
        col_idx = dataframe.columns.get_loc(column) + offset
        writer.sheets[save_sheet].set_column(col_idx, col_idx, column_width)

# --- Start ---
yaml_file = 'family.yaml'
yaml_sub_name = 'Childs'
save_file = 'family.xlsx'
save_sheet = 'Sheet1'


# Open the file and load the file
with open(yaml_file) as f:
    yaml_data = yaml.load(f, Loader=SafeLoader)

# Make copy of the original dictionary for modification
print("------ Copy the Parent dictionary                 -------------")
parent_dict = yaml_data.copy()

print("------ Create the Child & GrandChild dictionaries -------------")
# Create new dictionary, 'Child' from the the Parent dictionary using the
# sub Child elements
# Also create a new dictionary, 'Grandchild' from the Child dictionary
# using the sub Grandchild elements
# Then remove the sub elements from their parent dictionaries
# Thus creating three dictionaries with just their top level elements

# Set up the Child and Grandchild Headers
# The first element is the header row and is always empty but needs the
# Headers for Pandas
# Extract the header fields from the parent dictionary
child_dict = {}
grandchild_dict = {}
sub_list = ''
for x in parent_dict[yaml_sub_name][0]:
    if len(child_dict) == 0:
        child_dict['Childs0'] = {x: ''}
    else:
        if type(yaml_data[yaml_sub_name][0][x]) != list:
            child_dict['Childs0'].update({x: ''})
        else:
            sub_list = x

for x in parent_dict[yaml_sub_name][0][sub_list][0]:
    if len(grandchild_dict) == 0:
        grandchild_dict['Grandchilds0'] = {x: ''}
    else:
        grandchild_dict['Grandchilds0'].update({x: ''})

# Remove the Child elements from the Parent dictionary
child_list = parent_dict.pop(yaml_sub_name)

# Create the rest of the Child and Grandchild dictionaries padding the
# elements based on their relation to their parent
# On completion of the dictionary remove the sub elements
row = 1
for enum, ele in enumerate(child_list):
    if row != 1: row += 1
    child_dict[yaml_sub_name + str(row)] = ele
    pop_num = row
    if type(child_list[enum][sub_list]) == list:
        for i in range(len(child_list[enum][sub_list])):
            if i == 0:
                grandchild_dict['Grandchilds' + str(row)] = {'': '', '': ''}
            grandchild_dict['Grandchilds' + str(row + 1)] = ele[sub_list][i]
            row += 1
            child_dict[yaml_sub_name + str(row)] = {'': '', '': ''}
    child_dict[yaml_sub_name + str(pop_num)].pop(sub_list)

# Export dictionaries to excel using Pandas. THe xlsxwriter engine is used to adjust
# columns width
print("------ Export dictionaries to Excel using Pandas --------------")
parent_col_offset = len(parent_dict)
child_col_offset = len(child_dict['Childs0'])
column_offset = 0
writer = pd.ExcelWriter(save_file, engine='xlsxwriter')

df = pd.DataFrame([parent_dict])
df.to_excel(writer, sheet_name=save_sheet, index=False)
adjust_colmns(df, column_offset)

write_next_segments(child_dict, 0, parent_col_offset)
write_next_segments(grandchild_dict, 0, parent_col_offset + child_col_offset)

print("------ Save Excel file to '" + save_file + "' ---------------------")
writer.save()

【讨论】：