Boto3 download multiple files into single file

Then you create a generic session to s3 and also create a specific s3 session. You can create a session by using the boto3. Session api by passing the access key and the secret access key.

Boto3 looks at various configuration locations until it finds the configuration values such as settings. If you do not want to create a session and access the resource, you can create an s3 client directly by using the following command.

Use the below script to download a single file from S3 using Boto3 Resource. Create necessary sub directories to avoid file replacements if there are one or more files existing in different sub buckets.

Then download the file actually. You cannot download folder from S3 using Boto3 using a clean implementation. Instead you can download all files from a directory using the previous section. Also, how do I pass a list of selected Codes as a list,so that it will read those folders only. The boto3 API does not support reading multiple objects at once.

What you can do is retrieve all objects with a specified prefix and load each of the returned objects with a loop. To do this you can use the filter method and set the Prefix parameter to the prefix of the objects you want to load.

If you have multiple prefixes you are going to want to evaluate you can take the above and turn it into a function where the prefix is a parameter then combine the results together.

The function could like something like this:. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams?

Collectives on Stack Overflow. Learn more. Reading multiple csv files from S3 bucket with boto3 Ask Question. Asked 3 years, 1 month ago. Active 1 year, 3 months ago. Viewed 23k times. Bucket 'test-bucket' for obj in bucket. Next we need to go ahead and install the Python dependencies to be able to use the boto3 library.

You can do this by running the pip tool as shown below. Keep in mind make sure your virtual environment is activated before you run this step. If you wish to use it without having a virtual environment which I do not recommend you can go ahead and simply install it globally in your user account. Now that we have setup our system we need to verify the library is installed properly and it works. You can do this by simply checking in a python shell using the following command shown below, if you encounter an error please delete your virtual environment and try again.

If the problem still persists please drop me a line below and I will try to help you. As you can see above the boto3 library got loaded successfully and the version is 1.

This is as of Late so this may be different in your system based on when you install it. The first thing we need to do is click on create bucket and just fill in the details as shown below. For now these options are not very important we just want to get started and programmatically interact with our setup.

For now you can leave the rest of the options default for example for me the following settings were default at the time of this writing:. Once you verify that go ahead and create your first bucket. For me this looks something like this:. Now that we have our bucket created we need to proceed further into setting up a way to interact with it programmatically.

Those are necessary for the platform to know you are authorized to perform actions in a programmatic way rather than logging in the web interface and accessing the features via the console. So our next task is to find where and how those keys are configured and what is needed to set them up on our local computer to start talking to Amazon AWS S3. First we need to talk about how to add an AWS user. If you do not have a user setup with AWS S3 full permissions then I will walk you through on how to get this done in a simple step by step guide.

In the next steps you can use the defaults except the part that is asking you to set the permissions. In this tab you want to expand below and type in the search S3. Once you do that a bunch of permissions will be loaded for you to select from, for now you can simply select the Full permissions for S3 as shown in the screenshot below.

You can skip the tags and proceed to add the user, the final screen summary should look like this. The final confirmation screen should show you the access key and the secret key. You want to save those for your reference as we would be using them in our code later. This screen looks something like this:. Do note I redacted my access and secret key from the screenshot for obvious reasons but you should have them if everything worked successfully. Now that we have an access and secret key and our environment setup we can start writing some code.

Before we jump into writing code that downloads uploads and lists files from our AWS bucket we need to write a simple wrapper that will be re-used across our applications that does some boiler plate code for the boto3 library. One thing to understand here is that AWS uses sessions. Similar to when you login to the web console a session is initiated with a cookie and everything in a similar way this can be done programmatically. So the first thing we need to do before we start accessing any resource in our AWS environment is to start and setup our session.