Data Files are files that you, as the app developer, can attach to your app. These files are available in your Server Modules. Data Files are useful for machine learning models, static datasets and data that stays constant.
In the Data Files panel, you can drag and drop, rename and delete files.
Once uploaded, you can use
data_files['test.txt'] to get the path to the
test.txt file on disk.
Check out the Quickstart to learn how to use the Data File service.
To add the Data Files service to your Anvil app, click the + button in the Sidebar Menu, and select Data Files:
You can add files or directories to the Data Files service by dragging and dropping them from your computer onto the Data Files panel.
Alternatively, select the Upload button and select the file or directory from your local computer.
You access your files in code using the
data API in a Server Module. You get the path to the file on disk from
data_files['filename']. That’s a path to the file on disk, where your Server Modules are running.
from anvil.files import data_files @anvil.server.callable def return_text_from_file(): # Read the contents of a file with open(data_files['test.txt']) as f: text = f.read() return text
Writing to Data Files
Although Data Files are intended for files that change rarely, it is possible to update the contents of Data Files from code, using
with data_files.editing("<filename>") to get a filename you can write to:
@anvil.server.background_task def write_text_to_file(text): with data_files.editing('my_text_file.txt') as path: # path is now a string path on the filesystem. We can write to it with normal Python tools. # For example: with open(path, "w+") as f: f.write(text)
with block ends, changes you have made to that file will be saved to your Data Files.
Anvil provides no concurrency control over Data Files. If you update a data file from multiple places at once, there is no guarantee what will happen – perhaps one update will overwrite the other, or perhaps the two updates will execute concurrently using the same file on disk, producing corrupt data.
We recommend you update Data Files infrequently, via processes that are guaranteed to run one at a time (such as Scheduled Tasks). For more frequently updated data, consider using Data Tables with transactions.
You can use directories you’ve uploaded to the Data Files service in Python code.
For example, you can list all the files in a directory by passing the
scandir() function the path of your directory. The following example displays all files in a directory path that don’t start with ‘.’.
@anvil.server.callable def list_files_in_directory(): # Get the path of my Data Files directory my_directory_path = data_files['my_directory'] with os.scandir(my_directory_path) as directory: for file in directory: if not file.name.startswith('.') and file.is_file(): print(file.name)
To rename a file, open the Data Files panel and select the file. Then, click the pencil icon on the right and change type the new name.
To delete a file, open the Data Files panel and select the file. Then, click the trash icon on the right.
Data Files are stored in your app’s database. When you add the Data Files service to your app, Anvil creates a
Files table where your files are stored as Media objects. This means that each database has its own set of files; if you’re using multiple environments with different databases you’ll need to set up each database’s Data Files separately.
Files and directories are downloaded and cached on disk the first time they are accessed by your app. This makes it faster to access them the next time the file is used.
The version column is updated each time you upload a new file to the same path in the Data Files interface. When the version is changed, the file is re-cached the next time it is accessed.
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