Living with uncertainty

Just a quick note about Scrum (and Agile in general) on a concept that is often ignored. Scrum is intended for those kinds of work that defined processes have often failed to manage: uncertain requirements combined with unpredictable technology implementation risks (this distinction is not a blasphemy in the Agile context). These conditions usually exist during a new product (in particular software products) development: no matter how carefully you plan the future, it can never be more than a dream, unless you adjust your plan every day. So don't be scared by uncertainty, be ready to live with it and work hard to reduce it. This is what makes the difference between a good member of an Agile Team and a bad one: the good one manages and doesn't ignore uncertainty. This is true at each level of any self proclaimed agile company.

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Turning Python Scripts into Working Web Apps Quickly with Streamlit

I just realized that I am using Streamlit since almost one year now, posted about in Twitter or LinkedIn several times, but never wrote a blog post about it before. Communication in Data Science and Machine Learning is the key. Being able to showcase work in progress and share results with the business makes the difference. Verbal and non-verbal communication skills are important. Having some tool that could support you in this kind of conversation with a mixed audience that couldn't have a technical background or would like to hear in terms of results and business value would be of great help. I found that Streamlit fits well this scenario. Streamlit is an Open Source (Apache License 2.0) Python framework that turns data or ML scripts into shareable web apps in minutes (no kidding). Python only: no front‑end experience required. To start with Streamlit, just install it through pip (it is available in Anaconda too): pip install streamlit and you are ready to execute the working de...

jOOQ: code generation in Eclipse

jOOQ allows code generation from a database schema through ANT tasks, Maven and shell command tools. But if you're working with Eclipse it's easier to create a new Run Configuration to perform this operation. First of all you have to write the usual XML configuration file for the code generation starting from the database: <?xml version="1.0" encoding="UTF-8" standalone="yes"?> <configuration xmlns="http://www.jooq.org/xsd/jooq-codegen-2.0.4.xsd"> <jdbc> <driver>oracle.jdbc.driver.OracleDriver</driver> <url>jdbc:oracle:thin:@dbhost:1700:DBSID</url> <user>DB_FTRS</user> <password>password</password> </jdbc> <generator> <name>org.jooq.util.DefaultGenerator</name> <database> <name>org.jooq.util.oracle.OracleDatabase</name> ...

Load testing MongoDB using JMeter

Apache JMeter ( http://jmeter.apache.org/ ) added support for MongoDB since its 2.10 release. In this post I am referring to the latest JMeter release (2.13). A preliminary JMeter setup is needed before starting your first test plan for MongoDB. It uses Groovy as scripting reference language, so Groovy needs to be set up for our favorite load testing tool. Follow these steps to complete the set up: Download Groovy from the official website ( http://www.groovy-lang.org/download.html ). In this post I am referring to the Groovy release 2.4.4, but using later versions is fine. Copy the groovy-all-2.4.4.jar to the $JMETER_HOME/lib folder. Restart JMeter if it was running while adding the Groovy JAR file. Now you can start creating a test plan for MongoDB load testing. From the UI select the MongoDB template ( File -> Templates... ). The new test plan has a MongoDB Source Config element. Here you have to setup the connection details for the database to be tested: The Threa...

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