Python set environment variable for subprocess

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Python set environment variable for subprocess

That depends on what the issue is. If it's to clone and modify the environment one solution could be: subprocess.Popen(my_command, env=dict(os.environ, PATH="path")) But that somewhat depends on that the replaced variables are valid python identifiers, which they most often are (how often do you run into environment variable names that are not alphanumeric+underscore or variables that starts with a number?). Otherwise you'll could write something like: subprocess.Popen(my_command, env=dict(os.environ, **{"Not valid python name":"value"})) In the very odd case (how often do you use control codes or non-ascii characters in environment variable names?) that the keys of the environment are bytes you can't (on python3) even use that construct. As you can see the techniques (especially the first) used here benefits on the keys of the environment normally is valid python identifiers, and also known in advance (at coding time), the second approach has issues. In cases where that isn't the case you should probably look for another approach. By the end of this course, you'll be able to manipulate files and processes on your computer's operating system. You'll also have learned about regular expressions -- a very powerful tool for processing text files -- and you'll get practice using the Linux command line on a virtual machine. And, this might feel like a stretch right now, but you'll also write a program that processes a bunch of errors in an actual log file and then generates a summary file. That's a super useful skill for IT Specialists to know. We'll kick off by exploring how to execute Python locally, and organize and use code across different Python files. We'll then learn how to read and write different types of files, and use subprocesses and input streams. We'll also dive into Bash scripting and regular expressions -- both very powerful tools for anyone working with systems. We'll even touch on automatic testing, which allow us to automate how we check if our code is correct. To finish, we'll put all this together by using the tools that we've acquired to process data and generate automatic reports. We'll also explain how to set up your own developer environment in your machine. This is a key step in being able to write and deploy powerful automation tools.View SyllabusSetting up your Development Environment, Regular Expression (REGEX), Testing in Python, Automating System Administration Tasks with Python, Bash ScriptingThe course really came together in weeks six and seven, but the reading materials in weeks 1-5 were lackluster, containing one or two links without context, pointing to a narrow topic of that week.Definitely a course you need to take. Not easy but that's the point, depending on your knowledge you might start slow on the first lessons but at the end you'll be amaze on how natural you code.Managing Data and ProcessesIn this module, we'll learn about reading and writing to data files based on an interaction with the user. Along the way, we'll dive into standard streams, environment variables, and command line arguments. Next, we'll jump into Python subprocesses, including system commands and how they can be used. We'll review how to obtain output from a system command, and dive into subprocess management, including how to check exit values and manipulate the normal versus error exit values. Finally, we'll rundown processing log files, and will cover what a log file is, how to filter log files using regular expressions, and how to understand the output captured from log files.Select a languageArabicEnglishFrenchGermanItalianRussianSpanishVietnamese__typenameptPtAll right. So we've seen how to run system commands from Python, how to check the exit value, and how to manipulate the normal output and error output of the command. The sub process module offers a lot of extra options that we can use in our scripts. For example, we called out in an earlier video that one way of providing information to our processes is to modify the environment variables. Using this mechanism, we can change where the process looks for executable files, which commands it uses interact with some parts of the system, the kind of output it'll generate and a bunch more things. The usual strategy for modifying the environment of a child process is to first copy the environment seen by our process, do any necessary changes, and then pass that as the environment that the child process will see. Let's take a look at this. So in this code, we start by calling the copy method of the OS environ dictionary that contains the current environment variables. This creates a new dictionary that we can change as needed without modifying the original environment. The change that we're doing in this script is adding one extra directory to the path variable. Remember, the path variable indicates where the operating system will look for the executable programs. By adding one entry to the path, we're telling the OS to look for programs in an additional location. To create the new value, we're calling the join method on the OS path substring. This joins elements of the list that we're passing with a path separator corresponding to the current operating system. So here, we're joining /opt/myapp and the old value of the path variable to the path separator. Finally, we call the myapp command, setting the end parameter to the new environment that we've just prepared. So to recap, this script is modifying the contents of the path environment variable by adding a directory to it. We then call the myapp command with that modified variable. Doing it this way, the command will run in the modified environment with the updated value of path. There are a bunch more options that we can use with the run function. For example, we can use the CWD parameter to change the current working directory where the command will be executed. This can be really helpful when working with a set of directories where you need to run a command on each of them. We could also set the timeout parameter. This will cause the run function to kill the process if it takes longer than a given number of seconds to finish. This might be useful if you're running a command that you know might get stuck. For example, if it's trying to connect to a network and your computer is offline, or we can also set the shell parameter. If we set this to true, Python will first execute an instance of the default system shell and then run the given command inside of it. This means our command line could include variable expansions and other shell operations. Without the shell parameter, this would not be possible. We'll learn more about the things that we can do with the shell later in this course. For now, just keep in mind that if you need to expand variables or globs, you'll need to set this parameter. But using this can be a security risk. So make sure you actually need it and be careful when using it if you do. Before we finish our discussion of the subprocess module, a word of caution. Interfacing the underlying system directly in your Python scripts via subprocesses and system commands can be useful especially if you need to do a specific task quickly. But it comes with some drawbacks. Using these system-level commands built assumptions into our scripts about the infrastructure, our automation will run on. If those assumptions change, it can lead to unexpected effects or failures. These kinds of assumptions can change in multiple ways. What would happen to our automation is the flags where terminal command change and our script continues to use the old flags? What happens if we switch operating systems from Linux to Windows? Will our scripts fail outright or will they succeed in unintended and possibly harmful ways? Any change to the system or external commands our scripts use increases the chances of something breaking. Sometimes that break might be obvious and other times it might be difficult to detect. If we're automating a one-off, well-defined task, we're developing a solution quickly is the biggest requirement, then using system commands and subprocesses can help a lot. But if we're doing something more complex or long-running, it's usually a good idea to use the bait in or external modules that Python provides. So before deciding to use a sub processes, it's a good idea to check the standard library or pypi repository to see if we can do the task with native Python and to check if someone has already created the automation that we wanted to write. Remember that we never want to reinvent the wheel. How's this all sounding? That was a lot of info about advanced subprocesses and it may take a little time for it's all well, sink in. Now, it's a good time to use your local Python installation and try out some functions and commands that we saw. Check out the cheat sheet in the next reading which sums up how to use a subprocess module. See if you would come up with other ideas and other things that you can do with system commands and try those out. Once you feel ready to take the plunge, there's a quick quiz waiting for you after that.

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