Excel tables are suitable for manual maintenance, while JSON files are suitable for program reading and system import. When a large amount of table data needs to be delivered to technical systems, manually converting each file will consume a significant amount of time. From the perspective of office efficiency, this article explains how to use the Excel to Json conversion feature in HeSoft Doc Batch Tool to batch export multiple xlsx files as json files, and uses screenshots to illustrate key steps such as before and after processing effects, importing files, checking lists, setting save locations, and starting the process.
In many enterprise collaboration workflows, Excel is responsible for carrying original business data, while JSON handles system usage. For example, operations staff maintain product catalogs, finance personnel organize reports, sales teams submit data lists, and project managers maintain timelines. These contents often exist first as xlsx spreadsheets. When this data needs to enter web pages, interfaces, database import tools, or automation scripts, the Excel data must be exported as JSON files.
If only one spreadsheet needs processing, the cost of manual conversion is not high. However, in real office scenarios, batches of Excel files often need to be converted simultaneously. At this point, repeatedly opening files, selecting formats, saving results, and checking filenames consumes a significant amount of time. This article will introduce how to use the office software " HeSoft Doc Batch Tool " to complete the task of batch exporting Excel data to JSON files. It is oriented towards the batch processing of office files such as documents and spreadsheets, helping users hand over repetitive tasks to the software.
Applicable Scenarios: The Value of Converting Spreadsheets to JSON in Office and Data Collaboration
JSON is a common data exchange format with a clear structure, easy for programs to read. Excel, on the other hand, is more suitable for business personnel to edit and view. Converting Excel to JSON often occurs at the point where business data transitions from "manual maintenance" to "system use."
The following scenarios can be considered for using a batch conversion process:
- Business Configuration Deployment: Activity configurations, product configurations, and copy configurations are first maintained in Excel, then exported as JSON for the system to read.
- API Integration Testing: Development or testing personnel need multiple JSON data files for API requests, mock data, or automated testing.
- Data Handover: Business departments submit multiple Excel files, and the technical team requires uniformly formatted JSON files.
- Report Structuring: Finance, inventory, sales, and other spreadsheets need to be converted into structured files more suitable for script processing.
- Historical Data Conversion: Accumulated xlsx files from the past need to be standardized and organized for subsequent systematic management.
If the number of spreadsheets is large, the value of batch processing becomes very apparent. It can transform the pattern of "one operation per file" into a model of "uniformly process after selecting a batch of files," which is the key to office software enhancing efficiency.
Effect Preview: From Excel Folder to JSON Results Folder
Before processing, the folder contains multiple Excel spreadsheet files. The screenshot shows 8 xlsx files, with names covering different business topics: customer_feedback.xlsx represents customer feedback, employee_records.xlsx represents employee records, financial_report.xlsx represents financial reports, inventory_list.xlsx represents inventory lists, marketing_analysis.xlsx represents marketing analysis, product_catalog.xlsx represents product catalogs, project_timeline.xlsx represents project timelines, and sales_data.xlsx represents sales data.
If these files were processed individually, the conversion action would have to be repeated at least 8 times; if there are more files, the repetitive labor continues to multiply. More importantly, manual operation might also lead to some files being forgotten during conversion, or the output filenames being mistakenly altered.
After processing, the same batch of data has become JSON files. The screenshot shows that the file extensions are uniformly changed to .json, while the main part of the filenames still corresponds to the original spreadsheets, for example, product_catalog.xlsx is converted to product_catalog.json, and project_timeline.xlsx is converted to project_timeline.json.
This output effect has two benefits: first, it is easy to confirm that every Excel file has a corresponding JSON result; second, it is convenient for later searching and use by business topic. For data files that need to be delivered to a system or development team, maintaining a clear naming correspondence is very important.
Steps: Batch Export Excel Data to JSON
The following introduces the complete process based on screenshots of the software operation. The software name in the screenshot is HeSoft Doc Batch Tool , with the version interface displayed in the upper left corner of the window. This article uses the batch conversion of xlsx files to JSON as an example. Please refer to the software interface display and file import results during actual use.
Step 1: Enter Excel Tools, find Excel to Json
After opening the software, the left navigation bar provides multiple file processing categories. This task is related to Excel spreadsheets, so click Excel Tools. After entering, the main area on the right displays multiple Excel conversion function cards.
Among the function cards, find and select Excel to Json. In the screenshot, this function is located in the lower part of the list and is highlighted with a red box and arrow. Its description is to batch convert Excel files to Json format, which precisely corresponds to the "convert spreadsheet to JSON" requirement addressed in this article.
The result to achieve in this step is: entering the correct conversion tool, rather than mistakenly selecting other formats like Excel to PDF, Excel to CSV, or Excel to XML. The output results of different target formats differ, so it's crucial to confirm the function when selecting.
Step 2: Enter the task page, prepare to select the records to process
After entering "Excel to Json," the top of the page displays the current task name. The process flow bar shows that it is currently on step 1: Select the records to process. The subsequent steps are "Set save location" and "Start processing."
This process design is suitable for batch file processing because it allows users to first confirm input files collectively, then set the output directory uniformly, and finally execute the task. Compared to selecting and converting simultaneously, step-by-step confirmation is less prone to errors.
Step 3: Add files or import files from a folder
In the upper right area of the page, you can see two import-related buttons: Add files and Import files from folder. These two entry points apply to different situations.
If the number of Excel files to be converted is small or they are distributed in different directories, you can click Add files to select specific spreadsheets as needed. If all source files have already been organized into one folder, you can click Import files from folder to add the files from that directory to the task at once. The screenshot shows that 8 xlsx files have been imported, with file information displayed row by row in the list.
The expected result of this step is: all Excel spreadsheets that need to be exported as JSON appear in the task list. For batch processing, it is recommended to gather the source files into a dedicated folder in advance, making import and checking more efficient.
Step 4: Check the import results based on name, path, and extension
After importing the files, don't rush to start processing. Check the list first. The table columns in the screenshot include sequence number, name, path, extension, creation time, modification time, and actions. Through these fields, you can confirm whether the correct files have been selected.
For example, the name column displays customer_feedback.xlsx, employee_records.xlsx, etc., the path column shows they are located in the same test folder, and the extension column shows xlsx. The summary area at the bottom shows the record count is 8. For this example, it means the 8 Excel files have been added to the pending processing queue.
If you find files in the list that don't need converting, you can remove them through the action area on the right side of each row. Doing so avoids unrelated files being exported as JSON, which would affect the cleanliness of the results directory.
Step 5: Click Next to set the save location
After confirming the list is correct, click the Next button at the bottom of the page. The process will proceed to step 2: Set save location. The save location is a critical aspect of batch exporting JSON, as it relates to whether the resulting files are easy to find, deliver, and back up.
It is recommended to save the JSON results to a separate directory rather than mixing them with the original Excel files. For example, you could create a folder named "JSON Output," "Spreadsheet to JSON Results," or one named after the project. This way, even if re-conversion is needed later, you can clearly distinguish source files from result files.
Step 6: Start processing, batch generate JSON files
After setting the save location, proceed to step 3: Start processing. The software will execute the Excel to JSON conversion for the records in the list, either sequentially or in batch. The user does not need to repeat the operation for each xlsx file, which is the most direct efficiency benefit of batch office software.
After the task is complete, open the output directory to check if the corresponding JSON files have been generated. Combined with the post-processing screenshot, you can see that the 8 Excel files were converted into 8 JSON files, with the main part of the filenames consistent and the extension changed. At this point, these JSON files can be used for system import, API testing, frontend reading, or handed over to relevant personnel for further processing.
Common Issues or Considerations: Making Excel to JSON Results More Reliable
1. Standardize Excel headers before batch conversion
JSON files are typically read in the form of fields and values. If Excel headers are not uniform, for example, some sheets use "Name" while others use "Employee Name," subsequent program parsing may require additional adaptation. It is recommended to standardize field naming before conversion to reduce downstream processing costs.
2. Minimize complex merged cells
For visual appeal in Excel, merged cells, multi-level headers, or comment areas are often used. However, JSON is more concerned with structured data. If the spreadsheet is intended for system reading, it is recommended to use a regular data area and avoid overly complex formatting.
3. Always check the record count after batch import
The screenshot bottom shows a record count of 8, and this information is very useful. After importing a folder, the user should compare the number of files in the source directory with the record count in the software's list. If the quantities do not match, first check if some files were not imported or if unrelated files were mixed in.
4. The output directory should facilitate subsequent delivery
JSON results are usually handed over to development, testing, or system administrators. It is recommended to use a clear name for the output directory and retain the conversion date or project name. This makes it less likely to get confused during multiple conversions or multi-version deliveries.
5. Different Excel formats depend on actual recognition
The file extension in the example for this article is xlsx. In actual work, users may also encounter Excel files like .xls, .xlsm, etc. Since the screenshot shows xlsx in the import list, it is recommended to test the import of other formats in the software first to confirm they can be correctly recognized before proceeding with batch processing.
6. It is recommended to sample-check JSON content after conversion
Generation of the file does not necessarily mean the data fully meets the subsequent system requirements. After batch conversion is complete, you can sample and open a few JSON files to check if the fields, data count, and special characters meet expectations. For critical business data, pre-import verification should also be performed by the user party.
Summary: Using Office Software to Centralize the Repetitive Task of Converting Spreadsheets to JSON
Batch exporting Excel data to JSON files is a typical high-frequency, repetitive, and error-prone office task. Using HeSoft Doc Batch Tool , you can add multiple xlsx files to the processing queue at once and convert them uniformly through the "Excel to Json" function, avoiding opening and manually saving each one individually. The entire process is clear: enter Excel Tools, select the conversion function, add files or import from a folder, check the pending processing list, set the save location, and finally start processing.
For users who frequently need to handle Excel to JSON, xlsx to JSON, or spreadsheet data export to JSON, this batch processing method can save a significant amount of time and also make file naming and output results more standardized. If you are preparing a batch of Excel data to deliver to a system or development team, it is recommended to organize the source folder first, then follow the process in this article to complete the batch conversion, turning format conversion from a repetitive chore into a one-time task.