How To Check Nearshore Python Development Team Is Up To The Challenge

When considering the idea of ​​transferring some of the enterprise’s functions to third-party companies, management often encounters proposals to turn to nearshore IT outsourcing. Nearshore outsourcing involves turning to geographically closer teams of developers, R&D center, or IT specialists when the difference in time zones is more than 1-2 hours. In most cases, European companies prefer to give the right to implement a nearshore software development project to local firms, which determines the popularity of nearshore IT outsourcing in Europe.

For the development of your Python team, the nearshoring services are also justified. But how to predict whether the team is ready for various challenges and will it cope with the assigned task? In the article, we will talk about skills a Python developer should have and how to properly organize a team.

Must-Have Skill-Sets for Growing Python Development Team

The Python language is used in machine learning, data processing, building web applications, and much more. The language is fairly easy to learn, allowing scientists and researchers to automate their work and perform large-scale computations. Python developer should have such skills:

1. Knowledge of Core Python

The developer should have a good knowledge of the concepts of the Python core and its aspects: iterators, generators, principles of working with files, variables.

2. Object-relational converters

An object-oriented programming language is used to transform data between two incompatible systems, and this technique is called the Object Relational Mapper. Python developers must use many custom ORM tools.

It’s worth noting that a Python developer can grow significantly in the field of data science. This option is possible if he understands such aspects of data science: good knowledge of SQL, knowledge of using Python packages such as Scikit learn, NumPy, data analysis, data visualization, knowledge of probability.

3. Analytical skills

In terms of analytical knowledge, it is needed to better create useful websites for web development, better visualize datasets for Data Science, optimize algorithms during coding, and write clean code.

4. Version control

Changes to the source code happen multiple times, and you need to be able to track each change. If the developer is already familiar with words such as “commit, pull, push”, then he will efficiently handle different versions of encodings and track changes in codes.

5. Understanding multiple delivery platforms

There are many platforms for displaying results, such as desktop or mobile, and a Python developer should be well aware of the difference between different platforms.

6. Soft skills are a must

Responsibility, striving for professional growth, the ability to manage working hours, and work in a team are basic soft skills that are needed for almost any position in the IT field. It is worth talking over some rules of communication in teams and outlining the responsibilities of everyone in the team before the development team takes on the project. Thus, you can prevent challenges in personal communication between the team members.

Ask the teams to focus on specific goals at a high level, then have them work with ideas and execution. Developers are likely to work in an environment where they can make a difference and learn new things.

Facts Need to Be Considered When Creating a Nearshore Python Development Team

Python developer is additionally expected to be able to quickly master new material, delve into the essence of tasks, understand requirements, and be ready for routine tasks.

Also, Python developers are needed for machine learning tasks. Therefore, when selecting for positions related to Data Science, they check the knowledge of machine learning algorithms and the ability to apply them, the experience of participating in competitions on Kaggle or in hackathons. Applicants are expected to have knowledge of mathematics: probability theory, linear algebra, and mathematical analysis.

When a client decides to outsource a Python project to software companies, most providers will help select the right talent for a company’s needs. This includes CV review, initial assessment of the candidate’s relevant experience, technical interviews.

The dedicated development team model is best suited for long-term projects with changing requirements. It is also ideal for companies looking to extend their Python development team over an extended period of time to delegate tasks. Compared to other collaboration models a client gets a transparent budget, the ability to manage a Python development team workload, and change requirements as your project evolves.

How to Check Nearshore Python Development Team Is up to the Challenge

Software development is considered a poorly measurable process. The first rule of thumb to follow when designing and building processes is to do them in such a way that they leave artifacts in the data. You need to build not just Agile but make it Measurable Agile.

Sometimes for the sake of measurability, you have to sacrifice some of the Agile principles and, for example, somewhere prefer written communication over oral.

Due date practice has shown itself very well, which improves predictability. Its essence is as follows: when a developer takes a task and drags it into “in progress”, he must set a due date when the task is either released or ready for release. This practice teaches the developer to be a conditional micro project manager of his own tasks, that is, to take into account external dependencies and understand that the task is ready only when the client can use its result.

In measuring processes, start from problems. You need to monitor the violation of processes, and not how some practice is followed. Processes often do not work, not because people violate them on purpose, but because the developer and manager do not have enough control and memory to follow them all. By tracking violations of regulations, you can automatically remind people of what to do and get automatic controls

Conclusion

Certain development approaches can help but are not necessary tools for success. To gain experience, teams need to be given the freedom to experiment and make mistakes. They need to start acting. The only exception is code reviews., thus this is the most effective way to improve the overall level of your team. With rigorous code reviews, fast iterations, and actions, your teams will grow faster.

MySQL Shell get_auto_increment_value() method – Python mode

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I recently watched a fantastic Python Pandas library tutorial series on YouTube. Without a doubt, Pandas is great for all sorts of data stuff. On the same token, MySQL Shell in Python mode is quite powerful in the sense that Python and the MySQL Shell (version >= 8.0) are somewhat united in the same environment. Although Pandas is in a league all its own when it comes to data analysis, between the power of MySQL and Python, we can also perform some basic analysis easily in MySQL Shell Python mode. In this blog post, I will cover some basic data analysis using Python mode in the MySQL Shell. Continue reading to see examples…

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MySQL Shell Python mode blog posts compilation

Over the last few months, I have written numerous blog posts on different features of the MySQL Shell ranging from basic CRUD to aggregate functions and DDL. As a part of the MySQL version 8 release, MySQL Shell is a powerful and alternative environment that you can manage and work with your data in using a choice of 3 languages: Python, Javascript, or SQL. So this blog post is a simple compilation of all the Python mode related posts, in one easy-to-access location…

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ALTER TABLE ADD COLUMN – MySQL Shell Python style

We all know as SQL professionals that a common use of the ALTER TABLE command is that we can change a tables’ structure in a myriad number of ways. And, that’s a good thing too because chances are, you won’t always nail down the initial structure. Due to changing business or application requirements, you may even have to add additional columns that were not considered during the schema design phase. Suppose you have many tables that are structured similarly and they all need a specific column added to their already-existing design. Under certain circumstances, using the MySQL Shell in Python mode (\py), can reduce the number of manual ALTER TABLE statements you have to type. Continue reading to see examples in the MySQL Shell…

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