Basics of setting up a Spyder workspace and projects
Question:
I have searched for a basic tutorial regarding workspaces and projects in the Spyder IDE. What I want to understand is the basic concepts of how to use the workspace and projects to organize my code. It seems that this is perhaps basic programming skills and that is the reason why I have issues finding any kind of overview. This page seems to be related, but is actually about Eclipse and rather sparse. The Pythonxy tutorial and the documentation for Spyder does not go into any detail. Neither does the Anaconda documentation.
The questions I have are:
When should I set up a new workspace (if ever)?
When do I create a new project?
How does the PYTHONPATH depend on my workspace and project settings? Is it the same in all cases or can I customize it per workspace/project?
Are there other settings apart from the PYTHONPATH that I should configure?
How specific are the answers above to Spyder? Would it be the same for other IDEs, like Eclipse?
I am running Spyder on 64-bit Windows 7, as part of the Anaconda package.
Answers:
In my experience, setting up a workspace in Spyder is not always necessary.
A workspace is a space on your computer where you create and save all the files you work in. Workspaces usually help in managing your project files.
Once you create a workspace in Spyder, a pane called “Project Explorer” opens up inside Spyder. There you see in real-time the files of your project. For instance, if you generate a file with Python, it will show in that pane.
The pane let’s you keep the files organized, filter them etc. This can be useful for web development for example because helps you keep your content organized.
I use Python to handle files (e.g. csv) and work with data (data analysis), and I find no use in the workspace feature.
Moreover, if you delete a file in the Project Explorer pane, the file cannot be found in the Windows recycle bin.
One critical piece of information that appears to be missing from the Spyder documentation is how to create a new workspace in the first place. When no workspace exists after installing Spyder, creating your first project automatically initiates the creation of a workspace (at least in the Anaconda 3 distribution). However, it is not as obvious how to create a new workspace when a workspace already exists.
This is the only method I have found for creating a new workspace:
(1) Select the Project explorer window in Spyder. If this window or tab doesn’t appear anywhere in the Spyder application, use View > Panes > Project explorer to enable the window.
(2) Click on the folder icon in the upper-right corner of the Project explorer window. This icon brings up a dialog that can create a new workspace. The dialog allows selection of a directory for the .spyderworkspace file.
Update Oct 2016: Spyder 3 now has project facilities similar to that of other IDEs (especially Rstudio).
Now you if you have a folder with scripts, you can go to
Projects > New Projects > Existing Directory
to import it. The selected directory will be set as the base directory for the project.
I use spyder for data analysis and I have just started using the project workspace. I believe that it allows you to write better code due to the organization. As a previous post stated that “This can be helpful in web development”, which is true because web development requires good software engineering due to the complexity of the files and how they interact with each other. This organization/structure can be used in data analysis as well.
Often, data analysts that use Anaconda have an engineering or science background, not necessarily software engineering or computer science. This means that good software engineering principles may be missing (myself included). Setting up a workspace does one critical thing that I believe is missing from the discussion. It adds the workspace to the system path. Set up a project and then try
import sys
print sys.path
You will see your project’s directory added to the PYTHONPATH . This means I can break up my project and import functions from different files within my project. This is highly beneficial when analysis becomes complex or you want to create some type of larger model that will be used on a regular basis. I can create all of my functions in one file, maybe functions for plots in another and then import them in a separate script file.
in myScript.py
from myFunctions import func1
from myFunctions import func2
from myPlots import histPlot
This is a much cleaner approach to data analysis and allows you to focus on one specific task at a time.
In python 3 there is the %autoreload capability so you can work on your functions and then go back to your script file and it will reload them each time if you find errors. I haven’t tried this yet bc the majority of my work is in 2.7, but this would seem to add even greater flexibility when developing.
So when should you do this? I think it is always a good idea, I just started using this setup and I will never go back!
I have searched for a basic tutorial regarding workspaces and projects in the Spyder IDE. What I want to understand is the basic concepts of how to use the workspace and projects to organize my code. It seems that this is perhaps basic programming skills and that is the reason why I have issues finding any kind of overview. This page seems to be related, but is actually about Eclipse and rather sparse. The Pythonxy tutorial and the documentation for Spyder does not go into any detail. Neither does the Anaconda documentation.
The questions I have are:
When should I set up a new workspace (if ever)?
When do I create a new project?
How does the PYTHONPATH depend on my workspace and project settings? Is it the same in all cases or can I customize it per workspace/project?
Are there other settings apart from the PYTHONPATH that I should configure?
How specific are the answers above to Spyder? Would it be the same for other IDEs, like Eclipse?
I am running Spyder on 64-bit Windows 7, as part of the Anaconda package.
In my experience, setting up a workspace in Spyder is not always necessary.
A workspace is a space on your computer where you create and save all the files you work in. Workspaces usually help in managing your project files.
Once you create a workspace in Spyder, a pane called “Project Explorer” opens up inside Spyder. There you see in real-time the files of your project. For instance, if you generate a file with Python, it will show in that pane.
The pane let’s you keep the files organized, filter them etc. This can be useful for web development for example because helps you keep your content organized.
I use Python to handle files (e.g. csv) and work with data (data analysis), and I find no use in the workspace feature.
Moreover, if you delete a file in the Project Explorer pane, the file cannot be found in the Windows recycle bin.
One critical piece of information that appears to be missing from the Spyder documentation is how to create a new workspace in the first place. When no workspace exists after installing Spyder, creating your first project automatically initiates the creation of a workspace (at least in the Anaconda 3 distribution). However, it is not as obvious how to create a new workspace when a workspace already exists.
This is the only method I have found for creating a new workspace:
(1) Select the Project explorer window in Spyder. If this window or tab doesn’t appear anywhere in the Spyder application, use View > Panes > Project explorer to enable the window.
(2) Click on the folder icon in the upper-right corner of the Project explorer window. This icon brings up a dialog that can create a new workspace. The dialog allows selection of a directory for the .spyderworkspace file.
Update Oct 2016: Spyder 3 now has project facilities similar to that of other IDEs (especially Rstudio).
Now you if you have a folder with scripts, you can go to
Projects > New Projects > Existing Directory
to import it. The selected directory will be set as the base directory for the project.
I use spyder for data analysis and I have just started using the project workspace. I believe that it allows you to write better code due to the organization. As a previous post stated that “This can be helpful in web development”, which is true because web development requires good software engineering due to the complexity of the files and how they interact with each other. This organization/structure can be used in data analysis as well.
Often, data analysts that use Anaconda have an engineering or science background, not necessarily software engineering or computer science. This means that good software engineering principles may be missing (myself included). Setting up a workspace does one critical thing that I believe is missing from the discussion. It adds the workspace to the system path. Set up a project and then try
import sys
print sys.path
You will see your project’s directory added to the PYTHONPATH . This means I can break up my project and import functions from different files within my project. This is highly beneficial when analysis becomes complex or you want to create some type of larger model that will be used on a regular basis. I can create all of my functions in one file, maybe functions for plots in another and then import them in a separate script file.
in myScript.py
from myFunctions import func1
from myFunctions import func2
from myPlots import histPlot
This is a much cleaner approach to data analysis and allows you to focus on one specific task at a time.
In python 3 there is the %autoreload capability so you can work on your functions and then go back to your script file and it will reload them each time if you find errors. I haven’t tried this yet bc the majority of my work is in 2.7, but this would seem to add even greater flexibility when developing.
So when should you do this? I think it is always a good idea, I just started using this setup and I will never go back!