JavaScript Object Notation (JSON) is a syntax for storing and exchanging data. Parsing JSON involves converting a JSON string into a usable object inside your software. Power Automate Desktop enables you to parse JSON texts by using built-in actions such as “Parse a JSON string”. For instance, given a JSON string structured with “firstName” and “lastName” fields, the “Parse a JSON string” action converts this string into a dynamic object that can be accessed directly.
# Example JSON String
json_str = '{"firstName": "John", "lastName": "Doe"}'
# Using Parse a JSON String Action
parsed_json = Parse a JSON String(json_str)
# Accessing Parsed Data
first_name = parsed_json.firstName
last_name = parsed_json.lastName
In the above example, the parse action transforms the JSON string into a parsed_json object where you can retrieve the “firstName” and “lastName” properties.
XML Parsing in Desktop Flows
Extensible Markup Language (XML) is a markup language that defines rules for encoding documents in a format that is both human-readable and machine-readable. Similarly, desktop flows have specific actions for parsing XML structures, like the “XML to JSON” action. This action translates an XML structure into JSON format, which then can be parsed like any JSON structure.
# Example XML Structure
xml_str = "
# Using XML to JSON Action
converted_json = XML to JSON(xml_str)
# Parsing the Converted JSON
parsed_json = Parse a JSON String(converted_json)
# Accessing Parsed Data
first_name = parsed_json.firstName
last_name = parsed_json.lastName
The XML to JSON action converts an XML string into a JSON string, which can be parsed the same way as an ordinary JSON string.
CSV Parsing in Desktop Flows
Comma-Separated Values (CSV) is a simple file format used to store tabular data, such as a spreadsheet or database. CSV parsing involves translating a CSV file into a readable format for a program. In desktop flows, CSV files can be converted using the “Excel and CSV files” actions which include actions like “Run Excel Macro” and “Get all rows from a CSV file”.
Consider a CSV file named ‘data.csv’ containing the following data:
firstName, lastName
John, Doe
With the help of Power Automate Desktop, you can parse this CSV file using the following flow:
# Using Get all rows from a CSV file Action
rows = Get all rows from a CSV file('data.csv')
# Accessing row data
for row in rows:
first_name = row['firstName']
last_name = row['lastName']
The “Get all rows from a CSV file” action reads all data from a CSV file as a list of dictionaries, where each dictionary represents a row in the file.
Understanding how to parse JSON, XML, and CSV formats within desktop flows is a key component of the PL-500 Microsoft Power Automate RPA Developer exam. It not only allows you to handle different types of input data, but also aids in building more flexible, powerful flows that can adapt to various data sources and structures.
Practice Test
What is JSON?
- A) A markup language based loosely on HTML
- B) A lightweight data-exchange format that is easy for humans to read and write
- C) A set of rules for building Azure Logic Apps
- D) A row-column-based representation of data
Answer: B) A lightweight data-exchange format that is easy for humans to read and write
Explanation: JSON stands for JavaScript Object Notation. It is a lightweight data-exchange format that is easy for humans to read and write, and easy for machines to parse and generate.
True or False: XML and JSON parsing processes are the same.
Answer: False
Explanation: XML and JSON are different markup languages and, thus, have different parsing processes. XML uses tags similar to HTML, while JSON uses a key-value pair structure.
Which of the following libraries can be used for JSON parsing in Power Automate Desktop Flows?
- A) json
- B) pandas
- C) numpy
- D) matplotlib
Answer: A) json
Explanation: The ‘json’ library in Python can be used to parse JSON data in Power Automate Desktop Flows.
Which one of the following is not a common process for parsing text in Power Automate RPA development?
- A) Parsing XML
- B) Parsing JSON
- C) Parsing CSV
- D) Parsing GIF
Answer: D) Parsing GIF
Explanation: Parsing GIF is not a text-parsing process. Common text-parsing processes include parsing XML, JSON, and CSV.
True or False: XML stands for eXtensible Markup Language
Answer: True
Explanation: XML does stand for eXtensible Markup Language.
What does CSV stand for in the context of text parsing?
- A) Comma Separated Values
- B) Columnar Store Values
- C) Cascading Style Values
- D) Copy Saved Values
Answer: A) Comma Separated Values
Explanation: CSV stands for Comma Separated Values. It is a file format that separates data using commas, making it easy to manage and organize data.
True or False: You need to convert CSV data to JSON format before you can parse it.
Answer: False
Explanation: While it’s possible to convert CSV data to JSON for parsing, CSV data can also be directly parsed without conversion.
In XML, _____________ define the structure and data types of the data.
- A) Roots
- B) Tags
- C) Pairs
- D) Elements
Answer: B) Tags
Explanation: In XML, tags define the structure and types of data. They consist of a start and end tag with the content placed in between.
True or False: Power Automate can extract data from and import data into JSON, XML, and CSV files.
Answer: True
Explanation: Power Automate has capabilities to extract data from and import data into varying data formats including JSON, XML, and CSV files.
What parsing process would you use when extracting data from a tabular structure stored in a plain text?
- A) JSON Parsing
- B) XML Parsing
- C) CSV Parsing
- D) SQL Parsing
Answer: C) CSV Parsing
Explanation: CSV parsing would be used when dealing with tabular data, as CSV stands for “Comma Separated Values” and is typically used for such data structures.
Which of these is a widely used format for data serialization?
- A) CSS
- B) JSON
- C) BLOB
- D) ASP.NET
Answer: B) JSON
Explanation: JSON (JavaScript Object Notation) is a lightweight, text-based, language-independent data interchange format used for data serialization.
True or False: CSV files are harder to read and write compared to XML and JSON.
Answer: False
Explanation: CSV stands for Comma Separated Values, which is easier to read for humans due to its row-column representation.
Is XML case-sensitive when parsing text?
- A) Yes
- B) No
Answer: A) Yes
Explanation: XML tags are case-sensitive. This means that when parsing text in XML, upper case letters are considered different from lower case letters.
Interview Questions
What is JSON parsing in the context of desktop flows in Power Automate?
JSON parsing in Power Automate’s desktop flows is the process of interpreting and converting the JSON data into a format that can be used within the flows. It allows developers to retrieve specific elements of the JSON file and use them in their automation processes.
Which activity in Power Automate can be used to parse the JSON data?
Parse JSON activity can be used in Power Automate to parse the JSON data.
What is XML parsing?
XML parsing is the process of reading an XML document and providing access to its content and structure. Through XML parsing in desktop flows, developers can extract specific data elements from XML files for use in automation processes.
What is CSV parsing in the context of desktop flows in Power Automate?
The process of reading a CSV file and transforming its content into a format that can be manipulated and used within Power Automate’s desktop flows is called CSV parsing. The data can then be used for creating, updating, or performing operations on different elements within the flow.
How can one handle CSV files in Power Automate Desktop?
Power Automate Desktop provides a set of activities for reading from and writing to CSV files, enabling the parsing and handling of CSV data.
How do JSON structures relate to variables in the Power Automate desktop flow?
The elements in a JSON structure can be mapped to variables in the Power Automate desktop flow using the Parse JSON action. The parsed data can then be assigned to Power Automate variables and used within the flow.
How can XML documents be parsed in PowerAutomate desktop flows?
XML documents can be parsed in Power Automate desktop flows by using the XML-related activities like ‘Load XML’, ‘Get XML nodes’, ‘Get XML node attributes’ etc. These activities allow for reading XML documents and accessing specific parts of the documents.
Which are the Common activities used for CSV, XML and JSON parsing in Power Automate Desktop?
The common activities used for parsing these data types include ‘Parse JSON’, ‘Load XML’ for XML and ‘Read from CSV’ for CSV files.
What is the role of schema in parsing a JSON file using Power Automate?
In Power Automate, the schema specifies the structure of the JSON file. When parsing a JSON file, the schema is used to map the JSON elements to flow variables.
Why do we parse XML in Power Automate Desktop flows?
Parsing XML in Power Automate Desktop flows allows us to extract specific information from complex XML structures for use within the automation process.
How can we handle errors while parsing JSON, XML, or CSV files in Power Automate Desktop?
Power Automate provides error handling features such as ‘Try Catch’ blocks that can catch exceptions or errors during the parsing process and allow the developer to manage them appropriately.
Can we modify the parsed data obtained from JSON, XML, or CSV files in Power Automate Desktop?
Yes, once the data from JSON, XML, or CSV files is parsed and assigned to variables in Power Automate Desktop, it can be manipulated or modified as per requirement, using available actions and functionalities in the flow.
Which Power Automate feature is typically used for parsing, reading, or writing CSV files?
The ‘Text-file’ features in Power Automate desktop flows are typically used for parsing, reading, or writing to CSV files.
How can complex structures in XML be effectively parsed using Power Automate Desktop?
Power Automate Desktop provides XML activities like ‘Load XML’ and ‘Get XML Nodes’ which allows the developer to effectively parse complex XML structures by loading the XML file and then getting the specific nodes from the document through XPath expressions.
What data types can be parsed in Power Automate Desktop?
In Power Automate Desktop, you can parse various data types including JSON, XML and CSV.
extutorials.com