Automate document generation in Python for MS Word

Automate document generation in Python for MS Word

Table of Contents:

1. Introduction
2. Installing Required Dependencies
3. Creating a Single Word Document
4. Generating Word Documents Based on Excel List
5. Setting Up File Paths
6. Converting Excel Data to Pandas DataFrame
7. Creating a Mapping Table
8. Generating Word Documents
9. Saving and Validating the Documents
10. Conclusion

Generating Multiple Word Documents Based on an Excel List Using Python

Introduction: In this article, we will explore how to use Python to generate multiple word documents based on an Excel list. We will learn how to substitute placeholders in a word document, install the necessary dependencies, and automate the process to save time and effort.

Installing Required Dependencies: Before we begin, we need to install the required dependencies for this project. We will be using the pandas, openpyxl, and docxtpl modules. These can be easily installed using pip.

Creating a Single Word Document: To understand how the docxtpl library works, we will first create a single word document. We will import the necessary modules, specify the path to the word template, and initialize the doc template object. We will then substitute the placeholders in the document using a Python dictionary and save the document.

Generating Word Documents Based on Excel List: Now that we know how to create a single word document, we can use an Excel list to generate multiple documents. We will set up the file paths, load the Excel data into a pandas dataframe, and convert it into a mapping table. Using this mapping table, we will iterate over each record and generate the corresponding word document.

Setting Up File Paths: To organize the generated documents, we will specify the base directory, word template path, and Excel file path. We will also create a dedicated folder named "output" to save the generated documents.

Converting Excel Data to Pandas DataFrame: Using the pandas module, we will convert the Excel data into a pandas dataframe. We will extract the required columns and convert the dates to the desired format. This dataframe will serve as our mapping table for generating the word documents.

Creating a Mapping Table: We will convert the content of the dataframe into a list of dictionaries using the 'records' orient option in pandas. Each dictionary will represent a record in the Excel list, with the keys corresponding to the placeholders in the word template. This mapping table will be used to substitute the placeholders in the word documents.

Generating Word Documents: Using the mapping table, we will iterate over each record and generate the corresponding word document. We will initialize the docxtemplate, render the document, and create the output path based on the vendor name. Finally, we will save the document under the output path.

Saving and Validating the Documents: Once all the word documents are generated, we will save them in the output folder. To validate the process, we can open and compare one of the generated documents with the original Excel data.

Conclusion: Generating multiple word documents based on an Excel list using Python can greatly automate and streamline document creation processes. By using the docxtpl library, we can substitute placeholders in the documents and save them in bulk. This technique can be a time-saver for tasks that involve repetitive document generation.