#Compile python to executable software#
#Compile python to executable code#

If those prerequisites have their own recipes, make executes them and when all the prerequisites are ready for a target, it executes the corresponding recipe for the current target. When make executes a target, it looks at its prerequisites. Finally the recipes are a list of shell commands that will be executed by make as part of building the target. The prerequisites can be a file or another target. The prerequisites list tells make which files are this target dependent on. The target represents a goal that you want to achieve, usually this is a file that needs to be created in your build. Anything other than tabs will result in an error. Note that there are tabs before the recipe lists. The Sample Source CodeДЇirst, youвЂ™ll start by creating a file api.py with the following code: In this tutorial, youвЂ™ll create a simple app that makes requests to and fetches random trivia about a user given number. pyc files.ДЄlthough you cannot compile these modules using make, you can still use make for automation tasks like running tests, installing dependencies, cleaning the. These are stored in a directory named _pycache_ in the current directory, which contains compiled. When you import a module into your code, Python compiles those modules into bytecode for caching purposes. You donвЂ™t have to invoke a compiler manually. The reason Python is regarded to be an interpreted language is because the compilation step is implicit.

#Compile python to executable code#

When you run a Python code, the interpreter implicitly compiles the code into bytecode and interprets it with the VM. The advantage is that you can run Python on any platform as long as the VM is installed.

#Compile python to executable software#

These are similar to CPU instructions, but instead of being run by the actual CPU, these are executed by a software called a Virtual Machine (VM), which acts as a pseudo-microprocessor that runs the bytecodes. When you run a Python code, the Python interpreter reads the file line-by-line and runs it.Д«ut behind-the-scenes, the source code is compiled into bytecode. Now, Python is usually considered to be an interpreted language. This makes make relatively underutilized for an interpreted language. Since in an interpreted language you cannot compile the source files independently beforehand, you cannot utilize make like you would do for a compiled language. Whereas, in case of interpreted language, the source code is read and executed one line at a time. In simple words, in a compiled language, the program is converted from a high level language to machine language. Usually, all the programming languages can be classified into compiled or interpreted languages. In this tutorial, you will learn the basics of make and how it can be used in a Python project. So, whenever one of the files changes, it becomes necessary to recompile it. Also, you need to compile each file and link the resulting object files together. The reason make is very common with compiled languages is because the compilation commands for those languages can be long and complicated and difficult to remember. It can automate the process of building software by tracking its dependencies and compiling the program only when the dependencies change. It is a tool which controls the generation of executable and other non-source files from a programвЂ™s source file. Make is a commonplace tool in the world of software development, especially compiled languages like C or C++. ItвЂ™s honestly an underutilized function, and by integrating it into your routine, you can save time and avoid errors. Even though Python is regarded as an interpreted language and the files need not be compiled separately, many developers are unaware that you can still use make to automate different parts of developing a Python project, like running tests, cleaning builds, and installing dependencies.