Breaking Down Barriers for Blockchain Developers Worldwide


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  • Security concerns persist regarding Python’s suitability for managing critical financial transactions within Algorand’s blockchain environment.
  • Python’s integration necessitates the development of specialized tools and libraries to ensure robustness and security in Algorand applications.

For Algorand, this represents a shift in its approach towards Python developers. Algorand is adopting Python as its canonical language, which means developers will be able to write smart contracts directly in Python instead of having to learn a specific language like Solidity. 

This change is seen as a way to remove barriers for developers to participate in the Algorand network, as Python is a widely known and used language in the development community.

Mariano Dominguez, a software engineer working at Vestige.fi, a decentralized finance (DeFi) decentralized application (dapp) built on the Algorand blockchain, provided insights to regarding the underlying reasons for this phenomenon:

“Most chains that have a smart contract execution layer operate in a resource constraint scenario that isn’t typical in modern development environments,” Dominguez said.

Developer Accessibility

Algorand aims to make its platform more accessible to a wider audience of developers by adopting Python as its canonical language. Python is known for its ease of use and readability, which could attract developers who are not familiar with specific blockchain languages like Solidity.

This broadens the pool of people capable of building on the Algorand platform, potentially increasing innovation and application development.

“Because of this, it’s oftentimes easier and cheaper to build a Domain Specific Language (so Solidity, PyTEAL/TEAL, or Move for example), than it is to integrate a “normal” language since you can exercise these limitations from the get go.”

Barrier Reduction

Python adoption can significantly lower entry barriers for developers looking to build on Algorand. By not requiring developers to learn a new, blockchain-specific language like Solidity, the time needed to start developing smart contracts on Algorand is drastically reduced. This may encourage greater participation in the network and accelerate the application development cycle.

Dominguez added: “I think it’s fair to say the barrier to entry for the average Python developer is lower,” Stefan told Blockworks. However, he added, “from our experience working with different teams in the ecosystem: It’s not [yet] clear that the barrier is the language so much as everything around it.”

Security Concerns

Despite the accessibility advantages, some experts express concerns about the security of using Python for smart contracts on Algorand. Python has traditionally been used for general-purpose applications and data analysis and has not been widely tested in security-critical environments like smart contracts handling large amounts of financial value.

This concern focuses on the possibility of unidentified vulnerabilities or security risks when using Python in a blockchain environment.

Comparison with Other Languages

The shift to Python is compared with other languages used in blockchain, such as Solidity in Ethereum. While Python may be more accessible to a wide developer base, there are fundamental differences in the maturity and security of these languages.

Solidity, for example, has been extensively used and tested in production applications, leading to greater confidence in its security and reliability.

“At the end of the day, the faster you can go from idea to product, the more things you can try out and the more innovation can occur,” Dominguez said.

Existing Tools and Libraries

An important factor in Python adoption on Algorand is the ability to utilize existing tools and libraries. Compatibility with well-established libraries, such as OpenZeppelin in Solidity, can be crucial to ensuring the security and effectiveness of smart contracts in Python. 

Algorand is developing specific tools and libraries for Python, which may mitigate some concerns about security and provide developers with the necessary tools to build robust applications on the platform.

“I think with Algorand the type of products and solutions that can be built are on par, and in some cases even better, than those that employ legacy systems,” Dominguez said, pointing to real estate tokenization platform Lofty as an example, where “people can invest in individual properties that they proceed to own as a legal DAO, without going through a custodian.”

The shift to Python as the canonical language in Algorand represents a strategy to make the platform more accessible and appealing to a broad group of developers.

However, concerns about the security and maturity of Python compared to other blockchain languages underscore the need for careful implementation and development of specific tools for Python in Algorand.





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