Fastexcel Python と IronXL for Python の比較

1. Easy Excel File Management

IronXL for Python simplifies the process of managing Excel files. It helps users to create, edit, save, and read excel files efficiently. This capability is vital for anyone who regularly works with complex datasets and needs a reliable tool to manage Excel data without the need for Microsoft Excel. It also makes reading Excel files very easy.

2. Data Handling

With IronXL for Python, users can perform advanced data manipulation tasks. This includes reading and writing data to and from Excel files, handling bulk data operations, and applying data validation rules to ensure data integrity. This feature supports a range of data types and structures.

3. Comprehensive Formula Support

from ironxl import *
# Setting a license key for IronXL
License.LicenseKey = "License-Code"

# Load the Excel workbook
workbook = WorkBook.Load("Realistic_Sample_Excel_File.xlsx")
worksheet = workbook.DefaultWorkSheet

# Set formulas to perform meaningful calculations with the new data
worksheet["E18"].Formula = "SUM(E2:E16)"  # Sum of Total Sales
worksheet["D18"].Formula = "AVERAGE(D2:D16)"  # Average Unit Price
worksheet["E19"].Formula = "MAX(E2:E16)"  # Maximum of Total Sales

# Recalculate all formula values in all sheets.
workbook.EvaluateAll()

# Get the formula's calculated value for the maximum total sales
max_sales_value = worksheet["E19"].ToArray()[0].FormattedCellValue

# Get the formula as a string, e.g., "MAX(E2:E16)"
max_sales_formula = worksheet["E19"].Formula

# Save changes with updated formulas and calculated values.
workbook.Save()

from ironxl import *
# Setting a license key for IronXL
License.LicenseKey = "License-Code"

# Load the Excel workbook
workbook = WorkBook.Load("Realistic_Sample_Excel_File.xlsx")
worksheet = workbook.DefaultWorkSheet

# Set formulas to perform meaningful calculations with the new data
worksheet["E18"].Formula = "SUM(E2:E16)"  # Sum of Total Sales
worksheet["D18"].Formula = "AVERAGE(D2:D16)"  # Average Unit Price
worksheet["E19"].Formula = "MAX(E2:E16)"  # Maximum of Total Sales

# Recalculate all formula values in all sheets.
workbook.EvaluateAll()

# Get the formula's calculated value for the maximum total sales
max_sales_value = worksheet["E19"].ToArray()[0].FormattedCellValue

# Get the formula as a string, e.g., "MAX(E2:E16)"
max_sales_formula = worksheet["E19"].Formula

# Save changes with updated formulas and calculated values.
workbook.Save()

4. Integration with .NET Projects

IronXL for Python offers seamless integration with .NET projects, allowing for cross-platform operations involving Excel file manipulation. This integration is particularly useful for users who work in a .NET environment but need to use Python for specific tasks or data analysis.

5. High Performance and Efficiency

Designed for performance, IronXL for Python handles large and complex Excel files swiftly. Its optimized processing capabilities ensure that operations on Excel files, even those with large datasets, are performed quickly, reducing the time spent on data processing tasks.

6. Advanced Formatting Options

from ironxl import *
# Setting a license key for IronXL
License.LicenseKey = "License-Code"

# Create a new Excel WorkBook document
workbook = WorkBook.Create()

# Convert XLSX to XLS (if needed for compatibility)
xlsWorkBook = WorkBook.Create(ExcelFileFormat.XLSX)

# Create a blank WorkSheet
worksheet = workbook.CreateWorkSheet("new_sheet")

# Add data and styles to the new worksheet
worksheet["A1"].Value = "Welcome"
worksheet["A1"].Style.Font.Bold = True
worksheet["A1"].Style.Font.Size = 14
worksheet["B1"].Value = "Data Overview"
worksheet["B1"].Style.Font.Italic = True
worksheet["A2"].Value = "1200"
worksheet["A4"].Value = "Completed"
worksheet["A4"].Style.TopBorder.Type = BorderType.Thick

# Save the workbook
workbook.SaveAs("modified_test.xlsx")

from ironxl import *
# Setting a license key for IronXL
License.LicenseKey = "License-Code"

# Create a new Excel WorkBook document
workbook = WorkBook.Create()

# Convert XLSX to XLS (if needed for compatibility)
xlsWorkBook = WorkBook.Create(ExcelFileFormat.XLSX)

# Create a blank WorkSheet
worksheet = workbook.CreateWorkSheet("new_sheet")

# Add data and styles to the new worksheet
worksheet["A1"].Value = "Welcome"
worksheet["A1"].Style.Font.Bold = True
worksheet["A1"].Style.Font.Size = 14
worksheet["B1"].Value = "Data Overview"
worksheet["B1"].Style.Font.Italic = True
worksheet["A2"].Value = "1200"
worksheet["A4"].Value = "Completed"
worksheet["A4"].Style.TopBorder.Type = BorderType.Thick

# Save the workbook
workbook.SaveAs("modified_test.xlsx")

7. Security and Protection

IronXL for Python provides features to secure Excel files, including options to encrypt files and set detailed access permissions. It helps handle sensitive or confidential data, ensuring that information is protected against unauthorized access.

8. Support for Excel and CSV Formats

IronXL for Python supports not only traditional Excel file formats like XLSX files but also CSV files. This dual capability allows users to interchangeably work with different types of data files depending on their project needs.

1. High-Speed Excel Processing

FastExcel Python is optimized for speed, allowing users to read and write Excel files at high velocities. This is advantageous for applications that require rapid data processing.

2. Simplified API for Common Tasks

The library offers a simplified API that makes common Excel tasks such as reading, writing, and saving spreadsheets straightforward. Users can accomplish more with fewer lines of code.

3. Minimal Memory Usage

FastExcel Python is designed to use minimal memory, making it ideal for handling large Excel files on systems with limited resources. This feature ensures that performance does not degrade even with large datasets.

4. Lightweight Installation

FastExcel Python has a lightweight footprint, making it easy to install and integrate into existing Python environments. This ease of installation simplifies setup and deployment.

5. Support for Multiple Excel Formats

FastExcel Python supports various Excel formats including .xlsx, .xls, and even .csv files. This flexibility allows users to work seamlessly across different versions of Excel and related data formats.

6. Customizable Cell Formatting

The library provides extensive options for formatting cells. Users can modify fonts, colors, and borders, allowing for highly customized output spreadsheets.

from fast_excel import FastExcel

# Load an existing Excel file
workbook = FastExcel.read_excel("data.xlsx")
worksheet = workbook.get_sheet_by_name("Sheet1")

# Set custom font and color for cells in the first row
for cell in worksheet.iter_rows(min_row=1, max_row=1):
    for c in cell:
        c.font = FastExcel.Font(name='Calibri', size=12, bold=True, color='red')

# Save the changes
workbook.save("styled_data.xlsx")

from fast_excel import FastExcel

# Load an existing Excel file
workbook = FastExcel.read_excel("data.xlsx")
worksheet = workbook.get_sheet_by_name("Sheet1")

# Set custom font and color for cells in the first row
for cell in worksheet.iter_rows(min_row=1, max_row=1):
    for c in cell:
        c.font = FastExcel.Font(name='Calibri', size=12, bold=True, color='red')

# Save the changes
workbook.save("styled_data.xlsx")

Install IronXL for Python

Before proceeding with the IronXL installation, ensure that the .NET 6.0 SDK is installed on your system. This is because IronXL relies on .NET 6.0 to function. If you do not have it installed, download and install it from the official .NET website. To install IronXL, you will need to use pip, the Python package installer.

• Open your command prompt (Windows) or terminal (macOS or Linux).

  • Type the following command and press Enter:

  pip install IronXL

This command will download and install the IronXL library and all necessary dependencies.

Install FastExcel

FastExcel provides efficient operations for reading and writing Excel files in Python. Follow these steps to install it:

• Ensure your command prompt or terminal is still open.

  • Enter the following command and hit Enter:

  pip install fastexcel

  pip install fastexcel

  SHELL

This command installs FastExcel along with any dependencies it requires.

Efficiency in Handling Excel Data

IronXL for Python is designed to be highly efficient when working with complex Excel files in a Python environment. It can handle extensive data manipulations and supports advanced Excel features, which makes it suitable for comprehensive data processing tasks.

In contrast, FastExcel Python focuses on high-speed processing for both reading and writing Excel files. It is lightweight in environments where basic performance and minimal memory usage are critical.

Feature Comparison

IronXL for Python provides a rich set of features that include full support for reading, writing, and manipulating Excel files. It can manage security settings, apply advanced formatting, and perform complex data manipulations. IronXL's capabilities make it a robust choice for developers needing a comprehensive tool for extensive Excel manipulations.

FastExcel Python, on the other hand, emphasizes speed and simplicity. It offers a streamlined API that makes common Excel tasks quick and easy. While it may lack some of the more advanced features of IronXL, it excels in basic Excel operations.

Use Cases

IronXL for Python is ideal for projects needing to handle complex, multi-faceted Excel files. It is particularly suitable for projects where complex operations need to be performed on spreadsheets, such as in finance and legal domains. It's particularly useful for enterprise-level applications where robustness and a wide array of features are necessary.

FastExcel Python is best suited for applications that require rapid processing of Excel data, such as data analyses that need to be efficient and light on resources.

User Experience and Ease of Integration

IronXL for Python has a steeper learning curve due to its extensive feature set and capabilities. It is valuable for developers who are new to the language or want to learn the advanced features of IronXL. Its documentation covers all aspects of the library.

FastExcel Python is recognized for its ease of use, making it accessible for beginners and those who prefer a straightforward approach to Excel file manipulation. Its minimalistic design and focus on core functionalities allow for quick integration and ease of use in a wide range of applications.