#313 - Python script to copy an excel file, open and extract some information, and add the data to a database

- Python script to handle excel data and populate a database, which is simpler, easier to troubleshoot and maintain and does not fill the drive with error dumps:

#257 - How to find a regular expression (regex) in Notepad++

Open the find box (Control + F) and select the Regular Expression mode in the Search Mode.

Type the expression in the find what box: \w+\.IsValveCfg\[[^\]]+\] := true

#209 - Tips on writing software for industrial automation

- DRY (Don't Repeat Yourself)

- Single codebase for similar functions. Create parameters to configure / enable specific functions but keeping a single code base for better code development and maintenance. Examples: Loading / Offloading. Think about instances, for example rather than 87 different functions create 3 instances.

#152 - Chat with Francisco Bruno Dias Ribeiro Da Silva

 (English version at the bottom)

Tive o prazer de bater um papo com Francisco Bruno Dias Ribeiro Da Silva, estudante do último ano de engenharia do Instituto Tecnológico Aeronáutico (ITA) e líder de desenvolvimento de software na ITAndroids. Conversamos sobre as suas experiências otimizando algoritmos para aplicações de robôs humanoides que jogam futebol de forma autônoma, além do seu interesse por competições de programação.

#144 - Install Python and VSCode in a Windows PC without admin rights

1. From SW Center install Microsoft Visual Studio Code and install the extension Python (shortcut is CTRL + SHIFT + X)

2. From Python download the latest available release of the "Windows embeddable package (64-bit)", currently v3.11.0

#140 - Chat with Alisson Luan Daga

 (English version at the bottom)

Tive o prazer de bater um papo com Alisson Luan Daga, engenheiro eletricista e empresário paranaense. Conversamos sobre suas experiências trabalhando em sistemas de transmissão de energia, além da sua trajetória como co-fundador de uma startup cuja missão é trazer agricultura de precisão ao pequeno e médio produtor, por meio de tecnologia e inovação.

#121 - Web TLS Protocol

The TLS (Transport Layer Protocol) is used by the web browsers for authentication of the server and client as well as encryption of data. The current latest version is 1.3 and the previous versions are 1.2, 1.1 and 1.0.

#115 - Chat with Luiz Vitor Lima

(English version at the bottom)

Tive o prazer de bater um papo com Luiz Vitor Lima, formado em ciência da computação, consultor SQL Server e especialista em otimizar bancos de dados. Conversamos sobre suas experiências e técnicas de melhoria de desempenho de bancos de dados.

#114 - Learn Linux by playing CTF

Linux is one of the key Operating Systems that runs many of the devices and services we use everyday such as mobile, IoT, servers in datacenters, cars, robots, among many other applications. Although learning Linux can be difficult at the beginning, there is a fun way to do it by playing a game inspired by the hacking competitions Capture The Flag (CTF). 

#103 - Time-series classification of power demand comparison between Sktime and Sklearn

Using the public dataset that represents the power consumption in Italy in 1997, the task is to classify whether it corresponds to winter (from October to March) or summer (from April to September). This will be done using different techniques from both sklearn and sktime. 

#102 - Public time-series datasets

The following website http://timeseriesclassification.com/ has a great amount of public time-series datasets for several applications such as data from sensors, motion, image, audio, among others. In this post is shown how to use these datasets in a python framework.

#101 - Time-series forecast with sktime and python

Several applications in production, from finance to industrial systems, have the data being recorded and indexed by timestamps. In this post we are presenting a great open source library for python called sktime, which  was recently launched and has been developed and optimized for machine learning time-series classification, regression and forecasting. 

#100 - Switching between Python versions

Sometimes it may be required to switch between Python versions. For example, if some library does not have support yet for the current installed Python version. One way to overcome this is by checking the stable version required for that library then downloading and installing it from the python website.

#94 - MySQL how to add, remove and check a constraint in a table

In this post is shown a simple example about how to add, remove and check a constraint in a MySQL table. In this case the constraint is that the grade field is a INT value between 0 and 10.

#93 - MySQL command line client options

This link has the list of command line options that can be used by the clients. Here below some examples using for instance the option “-e” that means execute the SQL statement inside the double quotes and quit: 

#90 - MySQL cleaning imported database

In real world applications involving databases, often the data has to be cleaned. In this post, some techniques are presented, such as converting the data type of a field, creating a script to repeat the steps in different columns and using functions from MySQL such as ENUM(), IF(), SUBSTRING(), CONCAT(), REGEX, PREPARE and EXECUTE statement. Some of the commands are sent from the MySQL Workbench while other commands are sent directly from the windows prompt.

#89 - Tips Windows prompt commands

Here below some tips about Windows prompt commands that are helpful, in particular for networking configuration and troubleshooting:

#87 - Machine Learning classification comparison between GridSearchCV and RandomizedSearchCV

In a dataset with 13 features that represent different wine properties, such as color intensity and alcohol content, a machine learning model is created for a classification task. The goal is to predict in which class these wines belong, that could be class 0, class 1 or class 2. 

#85 - Using Pandas to transform categorical data for machine learning models

When creating machine learning models in python, using for instance the libraries numpy, pandas and sklearn, depending on the algorithms selected, the input data should be on the numerical format.

#81 - MySQL using the RANK() function

The RANK() function was introduced on MySQL Server 8.0, and it enables the programmer to rank the data by different ways.