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📊 RobotFramework TableLibrary

TableLibrary is a Robot Framework library designed for easy handling of tabular data formats such as CSV, Excel, Parquet, and more.
It provides a unified interface for reading, modifying, and creating tables directly within your Robot Framework tests.

🔍 Key Features

• Read Tables

  • Supports formats like .csv, .xlsx, .xls, .parquet, .json, .txt (as csv), and more.
  • Access table contents by column name or index.
  • Verifying specific table cells, columns or rows & executing assertions using the robotframework-assertion-engine

• Modify Existing Tables

  • Add, remove, or update rows and columns.
  • Apply dynamic modifications during test execution.

• Create New Tables

  • Create tables from lists, dictionaries, or other data sources.
  • Export tables to multiple file formats (e.g., CSV, Excel, Parquet).
  • Easily generate structured test data in the given file format.

Exception: Excel File Handling

We have included a basic handling of Excel files, but for more complex excel features, please take a look at the following library: robotframework-excelsage

This library got especially written to work with more complex Excel features like e.g. Excel Sheets, etc...

Installation

You can install the library using the following command:

pip install robotframework-tablelibrary

Example

File Format - CSV

# Reading CSV file with header column
${content} =    Tables.Read Table    ${CURDIR}${/}testdata${/}example_01.csv
${result} =    BuiltIn.Evaluate    "${content}[0][0]" == "index"
BuiltIn.Should Be True    ${result}

# Reading CSV file without header column
Tables.Configure Ignore Header    True
${content} =    Tables.Read Table    ${CURDIR}${/}testdata${/}example_01.csv
${result} =    BuiltIn.Evaluate    "index" not in "${content}"
BuiltIn.Should Be True    ${result}

File Format - Parquet

${content} =    Tables.Read Table    ${CURDIR}${/}testdata${/}example_05.parquet
${result} =    BuiltIn.Evaluate    "${content}[0][0]" == "_time"
BuiltIn.Should Be True    ${result}

Create new empty table - don't save to file system

# Create some data which should be inserted into the new table
VAR    @{headers} =    name    age
VAR    @{person1} =    Michael    34
VAR    @{person2} =    John    19

# Create empty table object - internally in cache
${uuid} =    Tables.Create Table    headers=${headers}

# Append some rows
Tables.Append Row    ${person1}
Tables.Append Row    ${person2}
Count Table    ${uuid}    Rows    equal    ${3}

# Append a column
VAR    @{column1} =    city    MG    ERL
Tables.Append Column    ${column1}
Count Table    ${uuid}    Columns    equal    ${3}

# Optional: Set new table cell value
Get Table Cell    1    1    equals    34
Tables.Set Table Cell    25    0    1
Get Table Cell    1    1    equals    25

# Insert a new row into the existing table object
VAR    @{insert_row} =    Lu    26    Hamburg
Insert Row    ${insert_row}    0
Get Table Cell    1    0    equals    Lu
Count Table    ${uuid}    Rows    equal    ${4}

Create new empty table - save to file system

# Generate new headers which should be used in the table
VAR    @{headers} =    name    age

# Create new table object
${uuid} =    Create Table    ${headers}

# Generate some random data & append as rows to new table
FOR    ${_}    IN RANGE    ${100}
    ${a} =    Generate Random String
    ${b} =    Generate Random String
    VAR    @{data}    ${a}    ${b}
    Tables.Append Row    ${data}
END

# Ensure that data got written into internal table object
Count Table    ${uuid}    Rows    equals    ${101}

# Write table to specific file path -> write from cache into persistant file
Write Table    ${uuid}    ${CURDIR}/results/test_writer_new_table.csv

# Check table content again, but now read table from file path!
Count Table    ${CURDIR}/results/test_writer_new_table.csv    Rows    equals    ${101}

Contribution & Development

See Development.md for more information about contributing & developing this library.

License

robotframework-tablelibrary is distributed under the terms of the Apache License 2.0 license.