Python 2.7 on Windows installation for Astronomy

Windows binary packages that are often easier to install than the ones you have to compile yourself.In summary, the conversation discusses the difficulty of using Python and installing modules on a non-Linux operating system. The speaker has encountered an error with the pip commands and is seeking a solution. They also mention using an older version of Python for scientific computing and recommend using Windows binary packages for easier installation.
  • #1
Hugom42
Hello people i know this program is better to use on Linux, but for personal reasons i can't change to Linux OS. So I'm having a little problema on how to use python and install the modules of astropy, ipython, I've already installed pip but i have a error on python shell that says: Error syntax, i write the instruction pip install astropy and also sudo pip install and doesn't work. Hope you can answer me quickly and can solve this problem!
 
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  • #2
Hugom42 said:
Hello people i know this program is better to use on Linux, but for personal reasons i can't change to Linux OS. So I'm having a little problema on how to use python and install the modules of astropy, ipython, I've already installed pip but i have a error on python shell that says: Error syntax, i write the instruction pip install astropy and also sudo pip install and doesn't work. Hope you can answer me quickly and can solve this problem!
Why aren't you using a newer version of Python? 2.7 is fairly old, with the current version for Windows being v3.5. The documentation for Python gives all the steps needed for running Python under Windows, which is mostly setting up the environment variables (such as path and a few others) so that Python can find the directories needed.
 
  • #3
Hugom42 said:
i have a error on python shell that says: Error syntax, i write the instruction pip install astropy and also sudo pip install and doesn't work.
The pip commands are not meant to be run within the Python shell- they need to be run at a command prompt in Windows.

I would stay with 2.7 if you are going to be doing scientific computing. A number of packages still aren't fully compatible with version 3, and most of the code you come across will probably have been written in 2.7.
 

1. How do I install Python 2.7 on Windows for Astronomy?

To install Python 2.7 on Windows, you can follow these steps:

  • Navigate to the official Python website and download the Windows installer for Python 2.7.
  • Run the installer and follow the instructions to complete the installation.
  • Make sure to check the option to add Python to your PATH environment variable.
  • Once the installation is complete, you can open the Python shell and start using Python 2.7 for your astronomy projects.

2. Can I use Python 2.7 for astronomy on Windows?

Yes, Python 2.7 is fully compatible with Windows and can be used for astronomy projects. However, it is important to note that Python 2.7 is no longer being actively developed and it is recommended to use the latest version, Python 3, for better performance and support.

3. Do I need any additional packages for astronomy in Python 2.7 on Windows?

Yes, depending on your specific astronomy project, you may need to install additional packages for Python 2.7 on Windows. Some popular packages for astronomy include AstroPy, PyEphem, and matplotlib. You can use the pip command to install these packages or use a package manager like Anaconda.

4. How do I test if Python 2.7 is working correctly on my Windows machine?

To test if Python 2.7 is working correctly on your Windows machine, you can open the Python shell and enter a simple command like print("Hello, world!"). If the output is "Hello, world!", then Python 2.7 is working correctly. You can also import and use any of the astronomy packages mentioned above to test if they are working properly.

5. Can I use Python 2.7 alongside other programming languages for astronomy on Windows?

Yes, you can use Python 2.7 alongside other programming languages for your astronomy projects on Windows. Python has a wide range of libraries and packages that can integrate with other languages, making it a versatile choice for multi-language projects. You can also use tools like Jupyter Notebooks to easily switch between languages in one project.

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