Before getting into the details of how to read and modify these attributes, it's helpful to review how geographic datasets are stored in ArcGIS. You need to know this so you can open datasets in your scripts, and on occasion, create new datasets.
Over the years, Esri has developed various ways of storing spatial data. They encourage you to put your data in geodatabases, which are organizational structures for storing datasets and defining relationships between those datasets. Different flavors of geodatabase are offered for storing different magnitudes of data.
- Personal geodatabases are a small, nearly deprecated form of geodatabase that store data on the local file system. The data is held in a Microsoft Access database, which limits how much data can be stored in the geodatabase.
- File geodatabases are a newer way of storing data on the local file system. The data is stored in a proprietary format developed by Esri. A file geodatabase can hold more data than a personal geodatabase: up to terabytes.
- ArcSDE geodatabases or "enterprise geodatabases" store data on a central server in a relational database management system (RDBMS) such as SQL Server, Oracle, or PostgreSQL. These are large databases designed for serving data not just to one computer, but to an entire enterprise. Since working with an RDBMS can be a job in itself, Esri has develped ArcSDE as "middleware" that allows you to configure and read your datasets in ArcCatalog or ArcMap without touching the RDBMS software.
For actions where ArcSDE is required but where it would be too heavy-handed to purchase and configure an enterprise RDBMS, Esri has developed a smaller "workgroup" version of ArcSDE that works with the free database SQL Server Express. This can be configured directly from ArcCatalog or the Catalog window in ArcMap.
In recent years, Esri has also promoted a new feature called query layers, which allow you to pull data directly out of an RDBMS using SQL queries, with no ArcSDE involved.
A single vector dataset within a geodatabase is called a feature class. Feature classes can be optionally organized in feature datasets. Raster datasets can also be stored in geodatabases.
Although geodatabases are essential for long-term data storage and organization, it's sometimes convenient to access datasets in a "standalone" format on the local file system. Esri's shapefile is probably the most ubiquitous standalone vector data format (it even has its own Wikipedia article). A shapefile actually consists of several files that work together to store vector geometries and attributes. The files all have the same root name, but use different extensions. You can zip the participating files together and easily email them or post them in a folder for download. In the Esri file browsers in ArcCatalog or ArcMap, the shapefiles just appear as one file.
Note:Sometimes in ESRI documentation, shapefiles are also referred to as "feature classes." When you see the term "feature class," consider it to mean a vector dataset that can be used in ArcGIS.
Another type of standalone dataset dating back to the early days of ArcGIS is the ArcInfo coverage. Like the shapefile, the coverage consists of several files that work together. Coverages are becoming more and more rare, but you might encounter them if your organization has used (or still uses!) ArcInfo Workstation.
Raster datasets are also often stored in standalone format instead of being loaded into a geodatabase. A raster dataset can be a single file, such as a JPEG or a TIFF, or, like a shapefile, it can consist of multiple files that work together.
Providing paths in Python scripts
Often in a script, you'll need to provide the path to a dataset. Knowing the syntax for specifying the path is sometimes a challenge because of the many different ways of storing data listed above. For example, below is an example of what a file geodatabase looks like if you just browse the file system of Windows Explorer. How do you specify the path to the dataset you need? This same challenge could occur with a shapefile, which, although more intuitively named, actually has three or more participating files.
The safest way to get the paths you need is to browse to the dataset in ArcCatalog and take the path that appears in the Location toolbar. Here's what the same file geodatabase would look like in ArcCatalog. The circled path shows how you would refer to a feature class within the geodatabase.
Below is an example of how you could access the feature class in a Python script using this path. This is similar to one of the examples in Lesson 1.
import arcpy featureClass = "C:\\Data\\USA\\USA.gdb\\Cities" desc = arcpy.Describe(featureClass) spatialRef = desc.SpatialReference print (spatialRef.Name)
Remember that the backslash (\) is a reserved character in Python, so you'll need to use either the double backslash (\\) or forward slash (/) in the path. Another technique you can use for paths is the raw string, which allows you to put backslashes and other reserved characters in your string as long as you put "r" before your quotation marks.
featureClass = r"C:\Data\USA\USA.gdb\Cities" . . .
The Esri geoprocessing framework often uses the notion of a workspace to denote the folder or geodatabase where you're currently working. When you specify a workspace in your script, you don't have to list the full path to every dataset. When you run a tool, the geoprocessor sees the feature class name and assumes that it resides in the workspace you specified.
Workspaces are especially useful for batch processing, when you perform the same action on many datasets in the workspace. For example, you may want to clip all the feature classes in a folder to the boundary of your county. The workflow for this is:
- Define a workspace.
- Create a list of feature classes in the workspace.
- Define a clip feature.
- Configure a loop to run on each feature class in the list.
- Inside the loop, run the Clip tool.
Here's some code that clips each feature class in a file geodatabase to the Alabama state boundary, then places the output in a different file geodatabase. Note how the five lines of code after import arcpy correspond to the five steps listed above.
import arcpy arcpy.env.workspace = "C:\\Data\\USA\\USA.gdb" featureClassList = arcpy.ListFeatureClasses() clipFeature = "C:\\Data\\Alabama\\Alabama.gdb\\StateBoundary" for featureClass in featureClassList: arcpy.Clip_analysis(featureClass, clipFeature, "C:\\Data\\Alabama\\Alabama.gdb\\" + featureClass)
In the above example, the method arcpy.ListFeatureClasses() was the key to making the list. This method looks through a workspace and makes a Python list of each feature class in that workspace. Once you have this list, you can easily configure a for loop to act on each item.
Notice that you designated the path to the workspace using the location of the file geodatabase "C:\\Data\\USA\\USA.gdb". If you were working with shapefiles, you would just use the path to the containing folder as the workspace. You can download the USA.gdb here and the Alabama.gdb here.
If you were working with ArcSDE, you would use the path to the .sde connection file when creating your workspace. This is a file that is created when you connect to ArcSDE in ArcCatalog, and is placed in your local profile directory. We won't be accessing ArcSDE data in this course, but if you do this at work, remember that you can use the Location toolbar in ArcCatalog to help you understand the paths to datasets in ArcSDE.