Writing to Google Cloud Storage

Oct 13, 2025 by pinkandtrash.com 142 views

Introduction

When working with geospatial data, it's often necessary to write multiple layers of a geopackage (.gpkg) file. However, when dealing with large datasets, writing each layer locally and then copying it to a cloud storage service like Google Cloud Storage (GCS) can be inefficient. In this article, we'll explore how to write two Geopandas dataframes as layers of a .gpkg file in memory using Python.

Prerequisites

Before we dive into the code, make sure you have the following packages installed:

Geopandas: A library that allows you to easily work with geospatial data in Python.
Fiona: A library that provides a Pythonic interface to the OGR (Open Geospatial Consortium) library, which is used to read and write geospatial data.
Shapely: A library that provides a Pythonic interface to the GEOS (Geometry Engine - Open Source) library, which is used to perform geometric operations.

You can install these packages using pip:

pip install geopandas fiona shapely

Writing Geopandas Dataframes as Layers of a .gpkg File

To write two Geopandas dataframes as layers of a .gpkg file in memory, we'll use the geopandas.GeoDataFrame class and the fiona.open function. Here's an example code snippet:

import geopandas as gpd
from fiona import open as fiona_open
import shapely.geometry as shp
gdf1 = gpd.GeoDataFrame(
geometry=[shp.Point(0, 0), shp.Point(1, 1)],
crs="EPSG:4326",
columns=["geometry"]
)
gdf2 = gpd.GeoDataFrame(
geometry=[shp.Point(2, 2), shp.Point(3, 3)],
crs="EPSG:4326",
columns=["geometry"]
)
with fiona_open("memory:gpkg", "w", driver="GPKG") as dst:
# Write the first layer
dst.write(
"geometry" gdf1.geometry.iloc[0],
"properties": {"name": "Layer 1"
})
# Write the second layer
dst.write({
    &quot;geometry&quot;: gdf2.geometry.iloc[0],
    &quot;properties&quot;: {&quot;name&quot;: &quot;Layer 2&quot;}
})

In this example, we create two sample Geopandas dataframes gdf1 and gdf2 with two points each. We then create a new .gpkg file in memory using the fiona.open function with the driver="GPKG" argument. We write the first layer using the dst.write method, passing in the geometry and properties of the first point in gdf1. We then write the second layer using the same method, passing in the geometry and properties of the first point in gdf2.

Writing to Google Cloud Storage

To write the .gpkg file to Google Cloud Storage, we can use the google-cloud-storage library. Here's an example code snippet:

from google.cloud import storage
client = storage.Client()
bucket = client.get_bucket("your-bucket-name")
blob = bucket.blob("path/to/your/file.gpkg")
with fiona_open("memory:gpkg", "r", driver="GPKG") as src:
with blob.open("wb") as dst:
src.copy(dst)

In this example, we create a client instance using the google-cloud-storage library. We then create a bucket instance using the client.get_bucket method, passing in the name of the bucket. We create a blob instance using the bucket.blob method, passing in the path to the file. We then write the .gpkg file to the blob using the src.copy method, passing in the destination blob.

Conclusion

In this article, we've explored how to write two Geopandas dataframes as layers of a .gpkg file in memory using Python. We've also shown how to write the .gpkg file to Google Cloud Storage using the google-cloud-storage library. By following these steps, you can efficiently write multiple layers of a geopackage to a cloud storage service without having to write each layer locally.

Example Use Cases

Here are some example use cases for writing Geopandas dataframes as layers of a .gpkg file in memory:

Data integration: When integrating data from multiple sources, you may need to write multiple layers of a geopackage to a cloud storage service.
Data processing: When processing large datasets, you may need to write multiple layers of a geopackage to a cloud storage service to avoid running out of memory.
Data sharing: When sharing data with others, you may need to write multiple layers of a geopackage to a cloud storage service to make it easily accessible.

Best Practices

Here are some best practices to keep in mind when writing Geopandas dataframes as layers of a .gpkg file in memory:

Use a consistent CRS: Make sure to use a consistent Coordinate Reference System (CRS) for all layers in the geopackage.
Use a consistent geometry type: Make sure to use a consistent geometry type for all layers in the geopackage.
Use a consistent properties schema: Make sure to use a consistent properties schema for all layers in the geopackage.

By following these best practices, you can ensure that your geopackage is well-organized and easily accessible.

Q: What is a .gpkg file?

A: A .gpkg file is a geopackage, which is a file format that stores geospatial data in a SQLite database. It's a popular format for storing and sharing geospatial data.

Q: What is Geopandas?

A: Geopandas is a library that allows you to easily work with geospatial data in Python. It provides a powerful and flexible way to manipulate and analyze geospatial data.

Q: How do I install Geopandas?

A: You can install Geopandas using pip:

pip install geopandas

Q: How do I create a Geopandas dataframe?

A: You can create a Geopandas dataframe using the geopandas.GeoDataFrame class. Here's an example:

import geopandas as gpd
from shapely.geometry import Point
gdf = gpd.GeoDataFrame(geometry=[Point(0, 0), Point(1, 1)])

Q: How do I write a Geopandas dataframe to a .gpkg file?

A: You can write a Geopandas dataframe to a .gpkg file using the fiona.open function. Here's an example:

import fiona
with fiona.open("path/to/your/file.gpkg", "w", driver="GPKG") as dst:
dst.write(
"geometry" gdf.geometry.iloc[0],
"properties": {"name": "Layer 1"
})

Q: How do I write multiple layers to a .gpkg file?

A: You can write multiple layers to a .gpkg file by creating multiple Geopandas dataframes and writing each one to the file using the fiona.open function. Here's an example:

import fiona
with fiona.open("path/to/your/file.gpkg", "w", driver="GPKG") as dst:
dst.write(
"geometry" gdf1.geometry.iloc[0],
"properties": {"name": "Layer 1"
})
dst.write({
    &quot;geometry&quot;: gdf2.geometry.iloc[0],
    &quot;properties&quot;: {&quot;name&quot;: &quot;Layer 2&quot;}
})

Q: How do I write a .gpkg file to Google Cloud Storage?

A: You can write a .gpkg file to Google Cloud Storage using the google-cloud-storage library. Here's an example:

from google.cloud import storage
client = storage.Client()
bucket = client.get_bucket("your-bucket-name")
blob = bucket.blob("path/to/your/file.gpkg")
with fiona.open("path/to/your/file.gpkg", "r", driver="GPKG") as src:
with blob.open("wb") as dst:
src.copy(dst)

Q: What are some best practices for working with Geopandas dataframes?

A: Here are some best practices for working with Geopandas dataframes:

Use a consistent CRS: Make sure to use a consistent Coordinate Reference System (CRS) for all layers in the geopackage.
Use a consistent geometry type: Make sure to use a consistent geometry type for all layers in the geopackage.
Use a consistent properties schema: Make sure to use a consistent properties schema for all layers in the geopackage.

Q: What are some common errors that can occur when working with Geopandas dataframes?

A: Here are some common errors that can occur when working with Geopandas dataframes:

CRS mismatch: Make sure that the CRS of the Geopandas dataframe matches the CRS of the .gpkg file.
Geometry type mismatch: Make sure that the geometry type of the Geopandas dataframe matches the geometry type of the .gpkg file.
Properties schema mismatch: Make sure that the properties schema of the Geopandas dataframe matches the properties schema of the .gpkg file.

Q: How do I troubleshoot issues with Geopandas dataframes?

A: Here are some steps you can take to troubleshoot issues with Geopandas dataframes:

Check the CRS: Make sure that the CRS of the Geopandas dataframe matches the CRS of the .gpkg file.
Check the geometry type: Make sure that the geometry type of the Geopandas dataframe matches the geometry type of the .gpkg file.
Check the properties schema: Make sure that the properties schema of the Geopandas dataframe matches the properties schema of the .gpkg file.
Check for errors in the .gpkg file: Use the fiona.open function to open the .gpkg file and check for errors.

By following these best practices and troubleshooting steps, you can ensure that your Geopandas dataframes are accurate and reliable.