After some time, I appreciated venv’s simplicity. When I was starting my Python adventure, I did have a couple of depressing moments.
It’s a popular and quite simple tool for creating virtual environments, which I find efficient enough in most situations. To make my point, however, I will have to use something, and I will use venv. I will also discuss some essential aspects of them and of using them. Instead, I will explain why we should use virtual environments and when. In this article, I will not discuss the various ways of creating virtual environments and managing dependencies. I decided to check out Visual Studio Code, and all my problems disappeared, just like that. What matters is that I was unable to solve the issue myself. Perhaps it was my mistake, perhaps there as something wrong with the IDE - it does not matter. After some time, I learned that they were so because of the IDE I used. They were… they were depressing - both my attempts and my virtual environments. I remember my first attempts to use virtual environments. The truth is, anyone using Python for more advanced tasks than what a calculator offers should know how to use virtual environments. Before discussing this aspect, I will have to introduce virtual environments, so that all of you grasp the basic idea behind them. Is that true? Should we never use the Python installed in our system? Or should we use what they call virtual environments? This article discusses when one should use virtual environments and whether this when means always.
You should never use your system installation, as you can do a lot of harm. The main overriding point across all these is that network engineers need easily consumable network state, and doing that is hard across vendors, versions and time.You can often hear that beginners often use their system installation of Python, which is wrong. The customer told me, 'We've stopped asking the hard questions because we rarely get good answers." Because maintaining up-to-date accurate information is so hard, network engineers often make do with stale out-of-date information, and so don't try to even ask many hard questions. To those thinking should we Go, if you must, go Rust 😉Ĥ. SuzieQ often had to slow down to avoid overrunning TACACS servers. A common comment I hear is '****, SuzieQ is fast'.
Python, especially with asyncio, is fast enough. So, to be useful, tools must work with the least common denominator for extracting maximum information from devices, address the most networks. Its incredibly hard for network engineers, even if good programmers, to try and automate many but the most simple tasks, in the context of larger objectives such as network refreshesĢ. Some of them maybe obvious, but given what I've seen discussed and debated, I think they bear repeating:ġ. Here are 5 observations I wanted to share about the recent successful deployment of SuzieQ Enterprise Edition.
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