Optimizing Manual API Workflows With Playwright

Optimizing Manual API Workflows With Playwright

In today’s fast paced development environment, efficiency and time are critical, especially when working with APIs that require encrypting requests, decrypting responses, extracting values, and reusing them in subsequent calls. Previously, our workflow involved constantly switching between VS Code (for custom JavaScript-based encryption and decryption, due to the absence of a dedicated API) and Postman for actual manual execution. While functional, this approach introduced unnecessary complexity, increased manual effort, and added significant time overhead.

To address these inefficiencies, we explored automation driven solutions aimed at streamlining and optimizing the end to end process through below strategic approach.

The Existing Challenge

Our earlier manual API execution flow involved :

  • Writing JavaScript code in VS Code to encrypt and decrypt the API request and response
  • Managing dependencies like Node.js, NPM, and crypto libraries
  • Switching to Postman for actual API execution
  • Manually handling tokens and dynamic values (token, channel, etc)

Key Pain Points:

  • Frequent context switching between tools
  • Dependency management overhead
  • Manual updates of tokens and IDs
  • Increased risk of human error and system installation permission

Solution : Playwright Based Approach

To overcome these inefficiencies, we leveraged Playwright, a powerful automation framework, to create a unified and automated API execution flow.

Instead of relying on multiple tools, Playwright enables us to:

  • Execute APIs directly through scripts
  • Handle encryption and decryption programmatically
  • Automate request chaining and response parsing
  • Eliminate repetitive manual steps

How the New Workflow Works

  • Automated Token Handling
  • End to End API Execution
  • Dynamic Data Chaining
  • Intelligent Data Handling

Key Benefits

This Playwright driven approach offers significant improvements:

  •  Fully automated API execution
  •  No dependency on Postman or VS Code switching
  •  Built in handling for encryption/decryption
  •  Eliminates manual token and Variable updates
  •  Scalable and reusable scripts
  •  Improved accuracy and reduced human error

Validation & Usage

  • Scripts can be executed directly using Playwright test runner
  • Outputs and logs are available in the console
  • Test scenarios can be easily extended or modified

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Final Thought :

While developer provided solutions often serve as a starting point, relying on them indefinitely can limit innovation and efficiency. In our case, continuing with the prescribed approach would have meant accepting tool fragmentation, manual effort, and avoidable complexity as the norm. Instead, by stepping back and reevaluating the process, we identified an opportunity to build a more streamlined and autonomous solution using Playwright.

This shift highlights an important mindset: solutions should not just be followed they should be challenged and improved. By doing so, we not only reduced dependency on predefined workflows but also created a more flexible, scalable, and efficient system tailored to our needs. If we had simply adhered to the existing process, the motivation to explore better alternatives would never have arisen, and the potential for optimization would have remained untapped. Ultimately, true efficiency comes from continuously questioning the status quo and proactively engineering better ways of working.


Great implementation for addressing the dependencies via Playwright, looking forward to having a GitHub repo for it.

Love this — small process fixes often create outsized impact. In many cases, the biggest gains don’t come from new tools but from removing tiny friction points that repeat daily. Those small inefficiencies compound quietly — so even a 10-minute fix can unlock hours when it sits in a high-frequency workflow.

Love seeing how those tiny adjustments can snowball into such meaningful time savings. It's amazing what happens when teams take a step back and spot those little friction points.

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