Programming Leftovers
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Python Community Interview With Brian Okken
This week, it’s my pleasure to interview Brian Okken. Brian is perhaps best known as the author of Python Testing with pytest, as well as being the host of two podcasts. Read on to find out more about the man behind the voice, his new meetup in Portland, and the advice he has for anyone new to testing software.
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Creating Dashboard to Visualise Data In Python
During one of my university project modules which require us to present our data from the sample dataset of the Scottish Referendum 2014.
There I was exposed to terms like Data Wrangling and the use of D3 to create an interactive dashboard.
Which the process to do data-wrangling was a tedious process and creating the dashboard using D3 was quite bad as well.
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How to Create and Manage Python Virtual Environments
It is pretty common to see Python developers installing and upgrading packages from standard and non-standard sources to develop applications. Reasons could range from using a newer version of a module to using a specific version in case there is a regression.
These requirements and use cases can be a pain to manage when different applications require different versions of the same library. Thankfully, Python provides a robust solution to isolate development environments using virtual environments.
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Best Cloud Based IDEs for Python
Development environments are increasingly moving in the cloud in part or full, allowing programmers to access and collaborate on their projects on the go. Numerous such services have been launched in the past few years, especially for web developers writing code in Node.js, HTML, JavaScript and CSS. However there are very few such options available for Python, despite being one of the most popular and fastest growing programming languages.
This article will list various IDEs and text editors available in the cloud for creating Python programs. -
Keep These Portable Python Builds for Linux Always With You
Most Linux distributions come with pre-installed Python packages. These packages are deeply integrated into the OS and they depend on shared libraries. If you want to keep Python projects isolated, using virtual environments is an excellent option. Another realistic option would be to use Python installed on an external drive as a portable package that you can carry it at your convenience (useful for teaching for example).
Unfortunately, as far as portability of Python is concerned, Linux users don’t have much choice. While compiling Python with shared libraries is easy, building Python with statically linked libraries takes more than a few tweaks, patches and changing lines in source code.This article will list the few portable Python options available for Linux. Note that any of the methods mentioned below will work on external drives formatted in NTFS or EXT3/EXT4 file systems only. FAT32 file system doesn’t support symlinks which is a requirement for these packages to work.
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Linux System Call Tutorial with C
While it’s inevitable you’ll use a system call at some point in your C development career, unless you are targeting high performance or a particular type functionality, the glibc library and other basic libraries included in major Linux distributions will take care of the majority of your needs.
The glibc standard library provides a cross-platform, well-tested framework to execute functions that would otherwise require system-specific system calls. For example, you can read a file with fscanf(), fread(), getc(), etc., or you can use the read() Linux system call. The glibc functions provide more features (i.e. better error handling, formatted IO, etc.) and will work on any system glibc supports.
On the other hand, there are times where uncompromising performance and exact execution are critical. The wrapper that fread() provides is going to add overhead, and although minor, isn’t entirely transparent. Additionally, you may not want or need the extra features the wrapper provides. In that case, you’re best served with a system call.
You can also use system calls to perform functions not yet supported by glibc. If your copy of glibc is up to date, this will hardly be an issue, but developing on older distributions with newer kernels might require this technique.
Now that you’ve read the disclaimers, warnings, and potential detours, now let’s dig into some practical examples.
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subdirmk - ergonomic preprocessing assistant for non-recursive make
Peter Miller's 1997 essay Recursive Make Considered Harmful persuasively argues that it is better to arrange to have a single make invocation with the project's complete dependency tree, rather than the currently conventional $(MAKE) -C subdirectory approach.
These problems are not theoretical for me. In the Xen Project we use recursive make and sadly suffer from occasional concurrency bugs. In my work on secnet (the currently rather unproductised greenend.org.uk vpn program) I have been frustrated by unreliability of the build system (which is developing fairly rapidly, as I overhaul secnet) .
However, actually writing a project's build system in a non-recursive style is not very ergonomic. I was complaining about this in the pub a week or two ago. Accepting my challenge, Mark Wooding demonstrated a proof of concept showing that it was possible to do better. I thought I had a better approach so I took his code and I ran with it.
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