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This article will explain in detail how to describe the four advantages of Python urce in practical applications. The quality of the article is high, so Xiaobian shares it with you for reference. I hope you have a certain understanding of relevant knowledge after reading this article.

advantages

1. Free, suitable for individuals and small companies

2. Powerful development tools make bug finding easier

3. Cross-platform, Windows and Linux can be used

4. Cool!

1. OGR Vector Library: Simple vector data read and write, part of GDAL

2. GDAL Geospatial Data Abstraction Library:

a) Read and write raster data

b) ArcGIS is also based on GDAL

c) C++ library, but can be called with python

Python urce-related modules

1. Numeric: Fast array processing, especially important for raster data

2. NumPy: Numeric for the next generation

3. More powerful gis library import libraries:

import ogr

Or:

from osgeo import ogr

*** The method is:

try: from osgeo import ogr except: import ogr

To read a certain type of data, you must first load the data driver, which is to initialize an object that Python urce"knows" about a certain data structure.

import ogr driver = ogr.GetDriverByName(‘ESRI Shapefile’)

The open() method of a data-driven driver returns a data source object. The above is a partial introduction to Python urce.

About how to describe the four advantages of Python urce in practical application, I hope the above content can be of some help to everyone and learn more knowledge. If you think the article is good, you can share it so that more people can see it.

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