精准读取CSV/Excel数据 - 灵活指定行列范围的 Python 解决方案

文章目录

源代码
项目简介
导入相关库
[__file_exists 装饰器](#__file_exists 装饰器)
函数的签名和注释
主要功能的实现
运行演示
[读取 Excel 文件](#读取 Excel 文件)

源代码

https://github.com/ma0513207162/PyPrecip。pyprecip\reading\read_api.py 路径下。

项目简介

PyPrecip 是一个专注于气候数据处理的 Python 库，旨在为用户提供方便、高效的气候数据处理和分析工具。该库致力于处理各种气候数据，并特别关注于降水数据的处理和分析。

导入相关库

在这里，读取 csv 和 excel 文件分别使用 csv 库和 openpyxl 库。utits 路径下是笔者自定义的一些工具函数，在源码中可以找到。

python 复制代码

import os, csv 
from openpyxl import load_workbook
from ..utits.except_ import RaiseException as exc 
from ..utits.warn_ import RaiseWarn as warn 
from ..utits.sundries import check_param_type

__file_exists 装饰器

一个简易的 python 装饰器 __file_exists，用于检测 path 参数有无正常输入，否则抛出自定义异常。

python 复制代码

def __file_exists(func):
    def wrapper(*args, **kwargs):     
        if not args and not kwargs:
            exc.raise_exception("The file path is required.", TypeError) 
        return func(*args, **kwargs)
    return wrapper

函数的签名和注释

以 read_csv 函数为示例，定义了一些必要的参数。
by_row 参数表示是否按行读取数据。
其中 row_indices 和 column_indices 参数为 tuple 类型时，表示指定行索引或列索引。指定为 list 类型时，表示指定行范围或列范围。
check_param_type 函数负责检查参数的类型。

python 复制代码

@__file_exists    
def read_csv(path: str, by_row: bool = False, 
            row_indices: (tuple|list) = (), column_indices: (tuple|list) = ()): 
    """     
    Reads data for specified rows and columns from a CSV file.

    Parameters:
     - path: indicates the path of the CSV file
     - row_indices: Specifies the read row range (list length 2) or row index (tuple)
     - column_indices: specifies the read column range (list length 2) or column index (tuple)
     - by_row: If True, read the file by rows (default). If False, read the file by columns.
    Returns:
     - Dictionary. The key indicates the file name and the value indicates the read data
    """

    # 检查参数类型 
    check_param_type(path, str, "path");
    check_param_type(row_indices, (tuple|list), "row_indices"); 
    check_param_type(column_indices, (tuple|list), "column_indices");

主要功能的实现

根据传入的 row_indices 和 column_indices 参数搭配 zip 函数进行行列的转换, 使用切片和索引操作从原始 CSV 数据中提取指定的行列数据区域。++这里最大的特点就是避免了使用大量的 for 循环进行同样功能的实现。++

python 复制代码

	read_csv_result: dict = {}; 
    with open(path, "r", encoding="gbk") as csv_file:
        reader_csv = list(csv.reader(csv_file)) 

    # 指定行范围  
    if isinstance(row_indices, list) and row_indices != []:
        if len(row_indices) == 2:
            start, end = row_indices[0], row_indices[1]
            reader_csv = reader_csv[start-1: end]
        else:
            warn.raise_warning("The row_indices parameter must contain only two elements, otherwise it is invalid.") 
    
    # 指定行索引 
    if isinstance(row_indices, tuple) and row_indices != ():
        row_idx_list = []
        for idx in row_indices:
            if idx >= 1 and idx <= len(reader_csv):
                row_idx_list.append(reader_csv[idx-1]) 
            else:
                exc.raise_exception("The index must be greater than 0 and less than the sequence length.", IndexError)
        reader_csv = row_idx_list; 

    # list 类型指定行范围
    reader_csv = list(zip(*reader_csv)) 
    if isinstance(column_indices, list) and column_indices != []:
        if len(column_indices) == 2:
            start, end = column_indices[0], column_indices[1]; 
            reader_csv = reader_csv[start-1: end]
        else:
            warn.raise_warning("The column_indices parameter must contain only two elements, otherwise it is invalid.") 
    
    # tuple 类型指定列索引 
    if isinstance(column_indices, tuple) and column_indices != ():
        col_idx_list = [] 
        for idx in column_indices:
            if idx >= 1 and idx <= len(reader_csv):
                col_idx_list.append(reader_csv[idx-1]); 
            else:
                exc.raise_exception("The index must be greater than 0 and less than the sequence length.", IndexError)
        reader_csv = col_idx_list;
    
    # 按行读取 
    if by_row:
        reader_csv = list(zip(*reader_csv)) 

    # 封装 dict 对象
    file_name = os.path.splitext(os.path.basename(path))[0]; 
    read_csv_result[file_name] = reader_csv; 

    return read_csv_result;

运行演示

python 复制代码

# 以主进程的方式运行 
if __name__ == "__main__": 
    path = "./static/test_data.xlsx"
    read_result = read_excel(path=path, row_indices=(1,3), column_indices=[1,5]);

    for key in read_result:
        for value in read_result[key]:
            print(value)

读取 Excel 文件

同样的逻辑，也适用于读取 Excel 文件。

python 复制代码

@__file_exists    
def read_excel(path: str, by_row: bool = False,  sheet_names: tuple = (), row_indices: (tuple|list) = (),
            column_indices: (tuple|list) = ()) -> dict: 
    """
    Reads data from a specified worksheet, row, and column from an Excel file.

    Parameters:
     - path: indicates the Excel file path
     - sheet_names: A tuple of sheet names to be read. If empty, the active sheet is read
     - row_indices: Specifies the read row range (list length 2) or row index (tuple)
     - column_indices: specifies the read column range (list length 2) or column index (tuple)
     - by_row: If True, read the file by rows (default). If False, read the file by columns.
    Return:
     - Dictionary. The key is the name of the worksheet and the value is the read data
    """

    # 检查参数类型 
    check_param_type(path, str, "path");
    check_param_type(sheet_names, tuple, "sheet_names");
    check_param_type(row_indices, (tuple|list), "row_indices"); 
    check_param_type(column_indices, (tuple|list), "column_indices");

    workbook = load_workbook(filename = path, data_only = True) 

    # Gets the specified worksheet 
    sheet_list = []
    if sheet_names != ():
        for sheet_name in sheet_names:
            sheet_list.append(workbook[sheet_name])
    else:
        sheet_list.append(workbook.active) 

    read_excel_result: dict = {}; 
    # 遍历工作簿 sheet_list
    for sheet in sheet_list:
        sheet_iter_rows: list = list(sheet.iter_rows(values_only = True)) 
        
        # 指定行范围 
        if isinstance(row_indices, list) and row_indices != []:
            if len(row_indices) == 2:
                start, end = row_indices[0], row_indices[1] 
                sheet_iter_rows = sheet_iter_rows[start-1: end]
            else:
                warn.raise_warning("The row_indices parameter must contain only two elements, otherwise it is invalid.") 

        # 指定行索引 
        if isinstance(row_indices, tuple) and row_indices != ():
            temp_iter_rows = []
            for idx in row_indices:
                if idx >= 1 and idx <= len(sheet_iter_rows):
                    temp_iter_rows.append(sheet_iter_rows[idx-1]) 
                else:
                    exc.raise_exception("The index must be greater than 0 and less than the sequence length.", IndexError)
            sheet_iter_rows = temp_iter_rows   

        # list 类型指定行范围
        sheet_iter_cols = list(zip(*sheet_iter_rows)) 
        if isinstance(column_indices, list) and column_indices != []:
            if len(column_indices) == 2:
                start, end = column_indices[0], column_indices[1]; 
                sheet_iter_cols = sheet_iter_cols[start-1: end]  
            else:
                warn.raise_warning("The column_indices parameter must contain only two elements, otherwise it is invalid.")   

        # tuple 类型指定列索引 
        if isinstance(column_indices, tuple) and column_indices != ():
            col_idx_list = [] 
            for idx in column_indices:
                if idx >= 1 and idx <= len(sheet_iter_cols):
                    col_idx_list.append(sheet_iter_cols[idx-1]); 
                else:
                    exc.raise_exception("The index must be greater than 0 and less than the sequence length.", IndexError)
            sheet_iter_cols = col_idx_list; 
        
        # 是否按行读取 
        if by_row:
            sheet_iter_cols = list(zip(*sheet_iter_cols)) 

        read_excel_result[sheet.title] = sheet_iter_cols; 

    return read_excel_result;