I was recently helping a friend who was transitioning from Matlab to Python. Giving him some tips, I realized that many of the cool nuances I learned in Python were taught me by someone in a “do you know that?” style or to solve a very specific problem that could be solved more simply. When helping this friend who is there on the other side of the world, I remembered the time when there was no one to teach me a cool trick and, in fact, I didn’t even know it could exist.
When you start entering the data science world, things can become really messy. There are thousands of concepts and meanings, most of them thrown at you at the same time.
AKA magics to plug holes in your dataset
I’ve been working with Project Jupyter since December of last year and it has been a wonderful experience. The last couple of days I struggled with the SQLAlchemy library that JupyterHub works on its internals. Since I studied this library and had to scratch some Stack Overflow questions to find some answers, I created this post to help digesting some of my doubts and findings.
This week, I finished my Nanodegree in Machine Learning Engineer by Udacity. To finish the course, I had to create a final study. Talking with a dear friend of mine, Pedro, he said that the National Highway Police of Brazil had a dataset on car accidents in federal roads. I decided to study this dataset, and try to predict which types of victims an accident would have based on the local, hour and accident characateristics.
I started to study programming logic when I came across problems that required knowledge in Matlab. After a while studying Matlab I was suggested to switch to Python for its ease, simplicity and for being able to be applied to numerous areas (besides being free).
The lovely Pyladies-Salvador asked for a text to debut their blog and told me that they would publish it on Women’s Day. I reflected a lot on what to write, what I could somehow add to that day that has so much meaning, and decided that I would like to talk to you about ambition. How ambitious do you consider yourself?
As I talked to some people, few new about Django’s Generic Relation and Generic Foreign Key. And when I was studying it to apply on our system, I realised that the documentation can be kind of tricky and sparse. Nevertheless, Generic Relations helped us a lot, and so I decided to write about it in this blog post :)
As I write this article, I am already talking from this world… the one we actually know so well. But I will try to explain, as best as I can, everything that I lived in this awesome week I spent in Portland at the Pycon 2016.
Hello, everybody! :D
On the last post I told everyone a little bit about my story, but now let’s begin the fun part! As I am studying and becoming a programmer I will try my best to pass along the fun and good things I am learning in the process, ok!?
Tutorial given during the OceanHackWeek 2020
This is the fifth post on my internship on the Outreachy Program with Project Jupyter. The previous posts are available and should be read in order if you want to understand the big picture: Outreachy I Outreachy II Outreachy III Outreachy IV Increasing documentation Native Authenticator was pretty advanced, but we still needed more information available on the documentation. And this got me thinking: what is relevant to make a good documentation?
This is the second part of my study on predicting the type of victims an accident can have based on the data from the National Highway Police (Polícia Rodoviária Federal), in Brazil. This was my final report for my Machine Learning Engineer Nanodegree and my first technical diploma in the computer science field (yey!).
In today’s development, tests are a fundamental tool for keeping things nice and easy and to keep programmer’s sanity. I’ve been using a set of tools for developing my web applications with Django and it is time for me to share a little bit about them.
This post could also be called what comes after the tutorials :)
In several Django tutorials, we learn how to receive requests and return responses with html pages having several information. This is very easy to start understanding the process that Django does: receiving requests and returning templates. But what happens after that?
Most of all Django tutorials teach us how to return HTML as response to a request. Sometimes, it is useful to make it a little more RESTful. One option is to use Django REST Framework but sometimes you need something a little bit simpler. Then you have Restless. Restless is a miniframework made by Daniel Lindsley based on what he learned by making Tastypie and some other REST libraries.
Code review is a complicated task and can become overwhelming, specially when you have no idea how to do it. However, code review can be a powerful tool to increase code quality and assure “healthy” deploys.
I just watched an awesome lecture about how to have a five-digit salary in Brazil by Bruno Ticami (Python Brazil 2013). Here are some questions and advises that he talked about:
Being a software engineer at a new company—anywhere—is hard. The codebase is completely new, you have to adapt to new patterns (for both code and culture) and most likely the problem space is completely new to you too.
In April 2018 I started Udacity’s Nanodegree in Machine Learning Engineer. The classes are not cheap and many questions asked me the same thing: does it worth it?
On this post you could have a small idea how SQLAlchemy works. However, all my study on SQLAlchemy basics was due to a problem I was having that took me a lot of time to figure it out. Since the problem was more complex and didn’t actually fit on the last post, I decided to create a new one dedicated to it, so here it is :)
On November I discovered that I was selected for the Outreachy internship program for the batch of December 2018 to March 2019.
I started working with MongoDB for fun and for some side projects in the last year. The main idea of using MongoDB is its flexibility. The pymongo library is really nice for getting some information, but on a project more complex, we may need something a little more intense. A nice alternative is the MongoEngine library, which is an Object-Document Mapper (ODM), which treats MongoDB documents as a kind of ORM.
This week I ran into a case were I should run several scripts with analysis that could run simultaneously. The analysis results would then be used as basis for another analysis, that could only run after all other scripts ended.
One year ago I started my new job as a Backend Python Developer. I have dropped a career, a profession and I almost drop my master degree. When everything happened, I think I didn’t understand the proportions that decision would have in my life. Now, one year later, I want to tell you a little bit about what happened this year.
Few months ago I decided to drop my career as an oceanographer and decided to become a backend developer with Python, as I told some of you here. After my blog post circulates on the internet, I got an invitation to talk on the Caipyra conference, in Ribeirão Preto (thanks Marco Rougeth).
On the last post I have written some tips for those who are starting in the world of programming, but today I want to talk something that happened to me before, and is happening to me now: There is just too much information on the internet! You will say that this is an obvious observation, but when you want to study something, this is just overwhelming!