Linux Magazine USA – Issue 305 April 2026 – Linux Magazine USA

CSV with Future Data The CSV file in Listing 1 acts as the input for the balance tracker in this column. Like the transaction data you can down- load from your bank, it describes my ac- count movements – only that they are in the future instead of the past or present. Where do the exact amounts come from?

The rent is the same every month, and the electricity bill amount is known a month ahead of time. The amount due for a credit card at the end of the billing period is typically also determined nearly a month in advance. Incidentally, all the amounts in this article are purely fictitious. Sadly, you couldn’t even rent a kennel for your dog for $994 in San Francisco. The CSV file’s rows contain the date, the transaction amount (with a minus sign to the left of debits), and a com- ment field for an identifier.

Reading these lines into a scripting language would be a piece of cake, of course, but in Go, there is some extra work to be done due to Go’s strict typing. Listing 2 shows you how this can be done, and the third-party gocsv package from GitHub keeps the code nice and compact. A date in the 2026-05-01 format (think, May 1, 2026) is stored as a string in the first column of the CSV file, for example, because CSV does not recognize types.

Go, on the other hand, prefers a variable of the time.Time type, because this means that it can check the validity of the date. The time package would imme- diately reject January 32nd, for example. Also, the type makes date calculations downstream easier to handle. Listing 2 defines the Record type in line 27 as a structure with three fields: Date, Amount, and Comment.

Line 30 defines Com- ment as a string and uses `csv:”comment”` to tell the CSV parser that the matching column in the CSV file’s header has comment as its title. Things get trickier with the date and the transaction Amount: The CSV parser Figure 2: Future transactions in a checking account.

Stream your music library to any home device Bash 5.3: Bourne Again Shell is born again Keep your agents safe 10 DELECTABLE FOSS DISCOVERIES! DVD INSIDE + Sometimes the humor in the news isn’t in a single story but in the way they stack up together. I was looking on Slashdot [1] the other day and saw this news item (from the Guardian): Accenture has reportedly started tracking staff use of its AI tools and will take this into consideration when deciding on top promotions, as the consulting company tries to increase uptake of the technology by its workforce.

[2] Right under it – not further down the page, but directly after it – was an item from Financial Times: Workplace grievances that once fit in a single email are now ballooning into 30-page documents stuffed with irrelevant historical detail, made-up legal precedents, and citations to laws from the wrong country – and UK employment lawyers say generative AI is the likely culprit. [3] I couldn’t help but notice the comical juxtaposition of one company declaring, “We all need to use more AI, and if you’re not using AI, you won’t get a promotion” and an- other company saying “all this AI is adding mounds of unnecessary paperwork and driving us crazy.”

To be fair, both reports could be correct. The term “AI” has come to encapsulate a broad range of meanings, and it is accepted truth that AI could be great in some contexts and not in others. The Financial Times story about workplace grievances confines itself to a single use case, which is probably a good way to assess the benefits of AI. The new policy at Accenture doesn’t appear to be about a specific AI use but is more about the company’s AI Refinery tool- set, which allows users to build agents, organize knowl- edge, and construct models.

The point seems to be that Accenture invested a lot of money in developing this toolkit, and they want to make sure their employees are using it – which makes sense, or that is, it would make sense as long as they spent suffi- cient time studying these tools in an actual business con- text to confirm that they do indeed improve productivity. All this underscores the fact that we’re making this AI thing up as we go.

We’re turning these tools loose on the world with the high hopes that they will meet the best- case scenarios we envision for them. And down at the per- sonnel level, real jobs are on the line. Once the money is spent, the shareholders will expect transformation, or at least, higher profits.

The org chart thus bends to conform to the belief that the expected outcome is certain.

This is a short excerpt from the opening of “” by Unknown, quoted for review and introduction purposes. All rights belong to the copyright holders.

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