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Corrected outputs and made cosmetic edits in GeoDjango tutorial.

Mariusz Felisiak 3 years ago
parent
commit
b5bf026813
1 changed files with 20 additions and 15 deletions
  1. 20 15
      docs/ref/contrib/gis/tutorial.txt

+ 20 - 15
docs/ref/contrib/gis/tutorial.txt

@@ -78,9 +78,9 @@ file. Edit the database connection settings to match your setup::
 
 
     DATABASES = {
     DATABASES = {
         'default': {
         'default': {
-             'ENGINE': 'django.contrib.gis.db.backends.postgis',
-             'NAME': 'geodjango',
-             'USER': 'geo',
+            'ENGINE': 'django.contrib.gis.db.backends.postgis',
+            'NAME': 'geodjango',
+            'USER': 'geo',
         },
         },
     }
     }
 
 
@@ -258,7 +258,7 @@ This command should produce the following output:
     -- Create model WorldBorder
     -- Create model WorldBorder
     --
     --
     CREATE TABLE "world_worldborder" (
     CREATE TABLE "world_worldborder" (
-        "id" serial NOT NULL PRIMARY KEY,
+        "id" bigserial NOT NULL PRIMARY KEY,
         "name" varchar(50) NOT NULL,
         "name" varchar(50) NOT NULL,
         "area" integer NOT NULL,
         "area" integer NOT NULL,
         "pop2005" integer NOT NULL,
         "pop2005" integer NOT NULL,
@@ -273,7 +273,7 @@ This command should produce the following output:
         "mpoly" geometry(MULTIPOLYGON,4326) NOT NULL
         "mpoly" geometry(MULTIPOLYGON,4326) NOT NULL
     )
     )
     ;
     ;
-    CREATE INDEX "world_worldborder_mpoly_id" ON "world_worldborder" USING GIST ( "mpoly" );
+    CREATE INDEX "world_worldborder_mpoly_id" ON "world_worldborder" USING GIST ("mpoly");
     COMMIT;
     COMMIT;
 
 
 If this looks correct, run :djadmin:`migrate` to create this table in the
 If this looks correct, run :djadmin:`migrate` to create this table in the
@@ -367,13 +367,20 @@ system associated with it.  If it does, the ``srs`` attribute will return a
 
 
     >>> srs = lyr.srs
     >>> srs = lyr.srs
     >>> print(srs)
     >>> print(srs)
-    GEOGCS["GCS_WGS_1984",
-        DATUM["WGS_1984",
-            SPHEROID["WGS_1984",6378137.0,298.257223563]],
-        PRIMEM["Greenwich",0.0],
-        UNIT["Degree",0.0174532925199433]]
+    GEOGCS["WGS 84",
+    DATUM["WGS_1984",
+        SPHEROID["WGS 84",6378137,298.257223563,
+            AUTHORITY["EPSG","7030"]],
+        AUTHORITY["EPSG","6326"]],
+    PRIMEM["Greenwich",0,
+        AUTHORITY["EPSG","8901"]],
+    UNIT["degree",0.0174532925199433,
+        AUTHORITY["EPSG","9122"]],
+    AXIS["Latitude",NORTH],
+    AXIS["Longitude",EAST],
+    AUTHORITY["EPSG","4326"]]
     >>> srs.proj # PROJ representation
     >>> srs.proj # PROJ representation
-    '+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs '
+    '+proj=longlat +datum=WGS84 +no_defs'
 
 
 This shapefile is in the popular WGS84 spatial reference
 This shapefile is in the popular WGS84 spatial reference
 system -- in other words, the data uses longitude, latitude pairs in
 system -- in other words, the data uses longitude, latitude pairs in
@@ -389,7 +396,7 @@ The following code will let you examine the OGR types (e.g. integer or
 string) associated with each of the fields:
 string) associated with each of the fields:
 
 
     >>> [fld.__name__ for fld in lyr.field_types]
     >>> [fld.__name__ for fld in lyr.field_types]
-    ['OFTString', 'OFTString', 'OFTString', 'OFTInteger', 'OFTString', 'OFTInteger', 'OFTInteger', 'OFTInteger', 'OFTInteger', 'OFTReal', 'OFTReal']
+    ['OFTString', 'OFTString', 'OFTString', 'OFTInteger', 'OFTString', 'OFTInteger', 'OFTInteger64', 'OFTInteger', 'OFTInteger', 'OFTReal', 'OFTReal']
 
 
 You can iterate over each feature in the layer and extract information from both
 You can iterate over each feature in the layer and extract information from both
 the feature's geometry (accessed via the ``geom`` attribute) as well as the
 the feature's geometry (accessed via the ``geom`` attribute) as well as the
@@ -423,11 +430,10 @@ Boundary geometries may be exported as WKT and GeoJSON::
     >>> print(geom.json)
     >>> print(geom.json)
     { "type": "Polygon", "coordinates": [ [ [ 12.415798, 43.957954 ], [ 12.450554, 43.979721 ], ...
     { "type": "Polygon", "coordinates": [ [ [ 12.415798, 43.957954 ], [ 12.450554, 43.979721 ], ...
 
 
-
 ``LayerMapping``
 ``LayerMapping``
 ----------------
 ----------------
 
 
-To import the data, use a LayerMapping in a Python script.
+To import the data, use a ``LayerMapping`` in a Python script.
 Create a file called ``load.py`` inside the ``world`` application,
 Create a file called ``load.py`` inside the ``world`` application,
 with the following code::
 with the following code::
 
 
@@ -685,7 +691,6 @@ GeoDjango also offers a set of geographic annotations to compute distances and
 several other operations (intersection, difference, etc.). See the
 several other operations (intersection, difference, etc.). See the
 :doc:`functions` documentation.
 :doc:`functions` documentation.
 
 
-
 Putting your data on the map
 Putting your data on the map
 ============================
 ============================