Python’s emergence as a leading programming language is no coincidence. Recognizing its immense potential, we are delighted to announce that Everysk now empowers developers to utilize Python scripts for creating sophisticated automations, enhancing operations across hedge funds, asset management firms, crypto funds, and wealth management companies.
In the global workforce, only one in every 125 professionals knows how to write code. Everysk was formed for the 124 professionals that do not know how to write code – the “citizen developers”. We enable them with a visual interface, where they deploy drag-and-drop digital robots to perform certain tasks. Platforms like Everysk are called no-code, low-code (NC/LC).
With the launch of our new Python Robot, we are letting some code creep in (LC). The Python Robot offers experienced developers the freedom to enhance Everysk’s functionality by injecting localized code into automations. The Python Robot executes this in a seamless and transparent way.
For those with Python coding experience, this new feature expands the potential capabilities within Everysk, and include:
- the ability to develop a robot with powerful custom logic, written in Python
- opportunities to leverage well-known libraries such as Numpy and Pandas and more advanced machine learning open-source libraries
- the production of auditable code for inspection/modifications
- the potential for clients with some Python expertise to substantially expand Everysk’s library of Robots.
- the capabilities for developers to explicitly write code for very technical/custom portions of the automation, while other non-technical aspects of a workflow (data ingestion, exploration, distribution) are taken care of by no-code parts of the automation.
We, at Everysk, are big believers in a hybrid approach as described in item 5 above, i.e. to leave most of the “plumbing” to be taken care of by efficient no-code robots but also provide the ability for developers to quickly utilize our own platform entities (datastores, portfolios, files, etc), to cast them into Python and then leverage the power of a widespread language.
Python Inside Everysk: An Example Use Case
Those familiar with Everysk understand that a workflow consists of one or more Digital Robots. Each Robot completes one task and clients string them together according to their unique requirements.
The following example shows how to deploy Python code within Everysk.
- Retrieve the ID of a Datastore using the Datastore Retriever robot. Then pass this ID to the interface of a For Developer robot. This For Developer below was renamed “fair_allocation” and it computes metrics for fair allocation given a user-supplied datastore of trades from a single trader into various portfolios:
- Set the interface in the fair_allocation robot:
- Associate the ID of the previous robot (Value) with the key “datastore_id”. Inside the fair_allocation code, the ID is now available for the code to use:
- If desired, propagate the changes back to the automation by instantiating a new Everysk datastore with the extra “compliance” column:
Python Within Other Tools
Certainly, Everysk isn’t the first platform to extend Python capabilities to low-code/no-code environments. Just last week, Microsoft announced the public preview of Python in Excel. While extending the basic functionality of Excel, this enhancement does nothing to address the security, maintainability and scalability of such solutions. Today, most major financial institutions have significant efforts underway to reduce the tenuous reliance on User Designed Applications (UDAs) – i.e. those spreadsheets or code that are designed to solve a specific problem – and Excel frequently finds itself at the top of the list of “offenders”.
Meanwhile, other popular low-code, no-code tools like UiPath and Automation Anywhere have released their own Python Script packages as well. While these offerings are more robust and scalable than products like Excel, they lack the precise focus infused within Everysk, the intelligent automation solution designed specifically for capital markets.
Python for Everysk: In Conclusion
For a technology that’s been around for more than three decades, it may seem surprising that a language that’s been around so long is now seeing its day in the sun. But seasoned technologists aren’t surprised.
First, Python was designed to be intuitive as well as welcoming to newcomers. Using plain English as the code’s vocabulary drastically shortcuts the learning curves common to other languages. For this reason, the number of Python developers with deep expertise continues to rise.
But perhaps more vital is that what people want from programming has also changed. In the earliest years of the digital era, development efforts were frequently targeted to completing activities that were beyond the scope of human ability.
Today, more commonly, we’re asking technology to simplify the complex and eliminate the unnecessary. This is the type of work where Python is at its best. This same drive is at the core of Everysk and explains why we’re so thrilled to bring the Python Robot onto the platform.
