CandyJar — developer’s profile under the microscope

I always hear: “It is so hard to search developers when I’m not a developer myself”. In CandyJar, we know how! Let me tell you.

To attract candidate, we have to study him(her): look at what he(she) is interested in, what technologies he(she) uses for a work, what projects he(she) participate. Let’s have a look at how CandyJar can provide such information.

When we visit a developer’s profile, we come across the picture below.

The profile consists of: “Contacts”, “Languages”, “Experience”, “Projects”. Let’s sort it out.

Section “Contacts”

This is simple. CandyJar tries to gather as many contacts as possible, such as social media, CV, email, messengers.

Section “Languages”. Do you speak C++? — Nein, Ich spreche Python

Within the section, we can see a list of utilized languages. We easily can indicate current languages or those ones which have already been abandoned. Considering this case, we can see Python was the main one from 2013 and later was substituted by Scala.

Then we look at the detailed information of each language.

1. Years — the number of years of opensource experience in Python. By the way, we should take the developer’s experience as an entire period but not the exact time of sitting in front of a screen and pressing the keyboard. Solving a programming problem (task), the most portion of time is spent thinking it through. Within the time, the developer can be lounging on a sofa, walking in a park or communicating with other developers. That is why this number of years’ experience should be taken as: “he has at least 6 real years of experience in Python”.
2. Projects — number of projects in which he participated as a Python developer. In the given case, there are 39 projects.
3. LOC (lines of code) — The indicator demonstrates the number of code lines in Python. We should also take into account that there is no direct interdependency between the quality of code and quantity of the lines. An amount doesn’t equate to quality. It is rather diametrically opposed situations wherein an accomplished developer solves a problem with fewer amount of code. However, to reach the level, he has to make thousands of lines of “wrong” code.
4. Year — this is the year of last commitment in the language. Since the developer doesn’t use the language in his(her) current work it means he(she) probably is out of trend and technologies around the language.
5. Projects list — the projects are coded in the language. You can click each one and get it on GitHub.
6. Skills — it is a set of additional technologies and frameworks supporting developers during the coding. This is handy information if you are looking for such a skillset. In the given case we see the developer has 17 projects based on Tornado and 2 projects based on Django.
7. Productivity — the indicator demonstrates the intensity of developers’ coding. Each green square is a week of coding. Darker color means more commitments per week. These squares implicitly show the style of coding: sometimes the developer codes hard by short sprints (maybe he just decided to train new skills), and sometimes he codes evenly with no rush (daily coding for an opensource project).

What else can the rate of productivity tell you

Let’s consider the case. The entire rate of productivity is evenly filled with green squares. Each square is a day of coding. The developer was evenly in hardworking for the whole year, but we have some nuances.

1. July has no squares. They all are grey. It means, the developer didn’t work at that time. Obviously, he was on vocations. So, the person was working for almost the whole year to have rest with no thinking about the work.
2. Also, we don’t see the squares in the first and last lines. The squares reflect Saturdays and Sundays. It demonstrates that the person has a rest on the days and it would be not a good idea to persuade him to work these days.
3. We have noticed that he had darker squares in December. It means he made more commitments and solved more tasks at that time. Hope he completed his project eventually 😊

Section “Experience”

This is simple. We use LinkedIn to gather information about his job. Many recruiters find it as hugely important to see developers’ experience of working on commercial products.

Section “Projects”

Projects — in fact, these are developers’ repositories on GitHub. For instance, the considered person has 39 projects in Python. However, the amount is not so crucial point. The more essential questions are: what projects are coded by him in the current year? What are the projects? What task did he in the projects? Does he have experience in large open-source projects’ developing?

Let’s look at what of the information we can get from CandyJar.

1. The sign “my” indicate that the considered developer is an owner of the project. If there is no such sign. It means he just adhered to a team of developers who are working on the project.
2. Project name
3. The main programing language of the project. If you looking for a Python developer, thus you would like to know something about his projects coded in Python.
4. Commits — the number of commitments in the project. If we imagine that a project is a house, the commit would be a brick. The project is constructed of commits the same as a house is built of bricks. The more commits, the bigger the project is. Each commit is a small solved task. When many developers work on a project, each of them solves his own tasks and make his own commits. For instance, the project ‘gae-init’ has only 1K (1000) commits. This is not a large “house”. The developers have made 175 commits there, which means he completed 175 tasks.
5. Dev — the number of developers. For successful teamwork, the guys should have sufficient soft skills: communication, know how to define the problem correctly, know how to ask questions properly, positive reaction to a critic.
6. Stars. What is the star in GitHub? It is a sort of “like” on Facebook. But if the “like” in social media is given for nice photos or interesting post, the stars in GitHub are given for useful and helpful projects. For example, we need to solve a programming problem but somewhere in GitHub a guy has already faced such a problem and created a program solving it. As he is open-source friendly, he published it. So, the situation simplifies our life and we don’t need to code it then. In that case, I definitely give a start to the guy to save the project in my bookmarks. And also, that programmer will see that his effort is not in vain.
7. Year — this is the year last commit. It indicates when the last piece of work of the project was. By the way, first of all, CandyJar shows the most actual projects, and old ones put down.

And eventually let’s consider what projects show us:

Here is a project for Artem.

The project is called “gae-init”. It is composed of Python (92%). Also, here is a bit of JavaScript. The team of the project consists of 18 developers. This is many people. They made 1000 commits in total. Artem made 175 commits. The project is well known inasmuch as it received 504 stars from other developers. And this is cool! From the description, we can see that it is a Google engine for application development. The project itself was developed in the framework Flask. The productivity rate shows us that the work goes with breaks (there was not coding from March 2018 till June 2018). By the way, those blue dots show the exact time when Artem made his code.

What’s in sum?

CandyJar tries to reflect all necessary information that lets you study a developer and get the situation clear about his(her) skills and experience. Obviously, the data has a slight approximation to his(her) real skills, because these are open repositories and open source projects. And it is definitely impossible to avoid real communication to developers to clarify their skills. Here, CandyJar is rather more as a tool to make smart matching you to relevant candidates.

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