Credentials

Boto can be configured in multiple ways. Regardless of the source or sources that you choose, you must have AWS credentials and a region set in order to make requests.

Interactive Configuration

If you have the AWS CLI, then you can use its interactive configure command to set up your credentials and default region:

aws configure

Follow the prompts and it will generate configuration files in the correct locations for you.

Configuring Credentials

There are two types of configuration data in boto3: credentials and non-credentials. Credentials include items such as aws_access_key_id, aws_secret_access_key, and aws_session_token. Non-credential configuration includes items such as which region to use or which addressing style to use for Amazon S3. The distinction between credentials and non-credentials configuration is important because the lookup process is slightly different. Boto3 will look in several additional locations when searching for credentials that do not apply when searching for non-credential configuration.

The mechanism in which boto3 looks for credentials is to search through a list of possible locations and stop as soon as it finds credentials. The order in which Boto3 searches for credentials is:

  1. Passing credentials as parameters in the boto.client() method
  2. Passing credentials as parameters when creating a Session object
  3. Environment variables
  4. Shared credential file (~/.aws/credentials)
  5. AWS config file (~/.aws/config)
  6. Assume Role provider
  7. Boto2 config file (/etc/boto.cfg and ~/.boto)
  8. Instance metadata service on an Amazon EC2 instance that has an IAM role configured.

Each of those locations is discussed in more detail below.

Method Parameters

The first option for providing credentials to boto3 is passing them as parameters when creating clients or when creating a Session. For example:

import boto3
client = boto3.client(
    's3',
    aws_access_key_id=ACCESS_KEY,
    aws_secret_access_key=SECRET_KEY,
    aws_session_token=SESSION_TOKEN,
)

# Or via the Session
session = boto3.Session(
    aws_access_key_id=ACCESS_KEY,
    aws_secret_access_key=SECRET_KEY,
    aws_session_token=SESSION_TOKEN,
)

where ACCESS_KEY, SECRET_KEY and SESSION_TOKEN are variables that contain your access key, secret key, and optional session token. Note that the examples above do not have hard coded credentials. We do not recommend hard coding credentials in your source code. For example:

# Do not hard code credentials
client = boto3.client(
    's3',
    # Hard coded strings as credentials, not recommended.
    aws_access_key_id='AKIAIO5FODNN7EXAMPLE',
    aws_secret_access_key='ABCDEF+c2L7yXeGvUyrPgYsDnWRRC1AYEXAMPLE'
)

Valid uses cases for providing credentials to the client() method and Session objects include:

  • Retrieving temporary credentials using AWS STS (such as sts.get_session_token()).
  • Loading credentials from some external location, e.g the OS keychain.

Environment Variables

Boto3 will check these environment variables for credentials:

AWS_ACCESS_KEY_ID
The access key for your AWS account.
AWS_SECRET_ACCESS_KEY
The secret key for your AWS account.
AWS_SESSION_TOKEN
The session key for your AWS account. This is only needed when you are using temporary credentials. The AWS_SECURITY_TOKEN environment variable can also be used, but is only supported for backwards compatibility purposes. AWS_SESSION_TOKEN is supported by multiple AWS SDKs besides python.

Shared Credentials File

The shared credentials file has a default location of ~/.aws/credentials. You can change the location of the shared credentials file by setting the AWS_SHARED_CREDENTIALS_FILE environment variable.

This file is an INI formatted file with section names corresponding to profiles. With each section, the three configuration variables shown above can be specified: aws_access_key_id, aws_secret_access_key, aws_session_token. These are the only supported values in the shared credential file.

Below is an minimal example of the shared credentials file:

[default]
aws_access_key_id=foo
aws_secret_access_key=bar
aws_session_token=baz

The shared credentials file also supports the concept of profiles. Profiles represent logical groups of configuration. The shared credential file can have multiple profiles defined:

[default]
aws_access_key_id=foo
aws_secret_access_key=bar

[dev]
aws_access_key_id=foo2
aws_secret_access_key=bar2

[prod]
aws_access_key_id=foo3
aws_secret_access_key=bar3

You can then specify a profile name via the AWS_PROFILE environment variable or the profile_name argument when creating a Session:

session = boto3.Session(profile_name='dev')
# Any clients created from this session will use credentials
# from the [dev] section of ~/.aws/credentials.
dev_s3_client = session.client('s3')

AWS Config File

Boto3 can also load credentials from ~/.aws/config. You can change this default location by setting the AWS_CONFIG_FILE environment variable. The config file is an INI format, with the same keys supported by the shared credentials file. The only difference is that profile sections must have the format of [profile profile-name], except for the default profile. For example:

# Example ~/.aws/config file.
[default]
aws_access_key_id=foo
aws_secret_access_key=bar

[profile dev]
aws_access_key_id=foo2
aws_secret_access_key=bar2

[profile prod]
aws_access_key_id=foo3
aws_secret_access_key=bar3

The reason that section names must start with profile in the ~/.aws/config file is because there are other sections in this file that are permitted that aren't profile configurations.

Assume Role Provider

Note

This is a different set of credentials configuration than using IAM roles for EC2 instances, which is discussed in a section below.

Within the ~/.aws/config file, you can also configure a profile to indicate that boto3 should assume a role. When you do this, boto3 will automatically make the corresponding AssumeRole calls to AWS STS on your behalf. It will handle in memory caching as well as refreshing credentials as needed.

You can specify the following configuration values for configuring an IAM role in boto3:

  • role_arn - The ARN of the role you want to assume.
  • source_profile - The boto3 profile that contains credentials we should use for the initial AssumeRole call.
  • external_id - A unique identifier that is used by third parties to assume a role in their customers' accounts. This maps to the ExternalId parameter in the AssumeRole operation. This is an optional parameter.
  • mfa_serial - The identification number of the MFA device to use when assuming a role. This is an optional parameter. Specify this value if the trust policy of the role being assumed includes a condition that requires MFA authentication. The value is either the serial number for a hardware device (such as GAHT12345678) or an Amazon Resource Name (ARN) for a virtual device (such as arn:aws:iam::123456789012:mfa/user).
  • role_session_name - The name applied to this assume-role session. This value affects the assumed role user ARN (such as arn:aws:sts::123456789012:assumed-role/role_name/role_session_name). This maps to the RoleSessionName parameter in the AssumeRole operation. This is an optional parameter. If you do not provide this value, a session name will be automatically generated.

If you do not have MFA authentication required, then you only need to specify a role_arn and a source_profile.

When you specify a profile that has IAM role configuration, boto3 will make an AssumeRole call to retrieve temporary credentials. Subsequent boto3 API calls will use the cached temporary credentials until they expire, in which case boto3 will automatically refresh credentials. boto3 does not write these temporary credentials to disk. This means that temporary credentials from the AssumeRole calls are only cached in memory within a single Session. All clients created from that session will share the same temporary credentials.

If you specify an mfa_serial, then the first time an AssumeRole call is made, you will be prompted to enter the MFA code. Your code will block until you enter your MFA code. You'll need to keep this in mind if you have an mfa_serial configured but would like to use boto3 in some automated script.

Below is an example configuration for the minimal amount of configuration needed to configure an assume role profile:

# In ~/.aws/credentials:
[development]
aws_access_key_id=foo
aws_access_key_id=bar

# In ~/.aws/config
[profile crossaccount]
role_arn=arn:aws:iam:...
source_profile=development

See Using IAM Roles for general information on IAM roles.

Boto2 Config

Boto3 will attempt to load credentials from the Boto2 config file. It first checks the file pointed to by BOTO_CONFIG if set, otherwise it will check /etc/boto.cfg and ~/.boto. Note that only the [Credentials] section of the boto config file is used. All other configuration data in the boto config file is ignored. Example:

# Example ~/.boto file
[Credentials]
aws_access_key_id = foo
aws_secret_access_key = bar

This credential provider is primarily for backwards compatibility purposes with boto2.

IAM Role

If you are running on Amazon EC2 and no credentials have been found by any of the providers above, boto3 will try to load credentials from the instance metadata service. In order to take advantage of this feature, you must have specified an IAM role to use when you launched your EC2 instance. For more information on how to configure IAM roles on EC2 instances, see the IAM Roles for Amazon EC2 guide.

Note that if you've launched an EC2 instance with an IAM role configured, there's no explicit configuration you need to set in boto3 to use these credentials. Boto3 will automatically use IAM role credentials if it does not find credentials in any of the other places listed above.

Best Practices for Configuring Credentials

If you're running on an EC2 instance, use AWS IAM roles. See the IAM Roles for Amazon EC2 guide for more information on how to set this up.

If you want to interoperate with multiple AWS SDKs (e.g Java, Javascript, Ruby, PHP, .NET, AWS CLI, Go, C++), use the shared credentials file (~/.aws/credentials). By using the shared credentials file, you can use a single file for credentials that will work in all the AWS SDKs.

Configuration

In addition to credentials, you can also configure non-credential values. In general, boto3 follows the same approach used in credential lookup: try various locations until a value is found. Boto3 uses these sources for configuration:

  • Explicitly passed as the config paramter when creating a client.
  • Environment variables
  • The ~/.aws/config file.

Environment Variable Configuration

AWS_ACCESS_KEY_ID
The access key for your AWS account.
AWS_SECRET_ACCESS_KEY
The secret key for your AWS account.
AWS_SESSION_TOKEN
The session key for your AWS account. This is only needed when you are using temporary credentials. The AWS_SECURITY_TOKEN environment variable can also be used, but is only supported for backwards compatibility purposes. AWS_SESSION_TOKEN is supported by multiple AWS SDKs besides python.
AWS_DEFAULT_REGION
The default region to use, e.g. us-west-1, us-west-2, etc.
AWS_PROFILE
The default profile to use, if any. If no value is specified, boto3 will attempt to seach the shared credentials file and the config file for the default profile.
AWS_CONFIG_FILE
The location of the config file used by boto3. By default this value is ~/.aws/config. You only need to set this variable if you want to change this location.
AWS_SHARED_CREDENTIALS_FILE
The location of the shared credentials file. By default this value is ~/.aws/credentials. You only need to set this variable if you want to change this location.
BOTO_CONFIG
The location of the boto2 credentials file. This is not set by default. You only need to set this variable if want to use credentials stored in boto2 format in a location other than /etc/boto.cfg or ~/.boto.
AWS_CA_BUNDLE
The path to a custom certificate bundle to use when establishing SSL/TLS connections. Boto3 includes a bundled CA bundle it will use by default, but you can set this environment variable to use a different CA bundle.
AWS_METADATA_SERVICE_TIMEOUT
The number of seconds before a connection to the instance metadata service should time out. When attempting to retrieve credentials on an EC2 instance that has been configured with an IAM role, a connection to the instance metadata service will time out after 1 second by default. If you know you are running on an EC2 instance with an IAM role configured, you can increase this value if needed.
AWS_METADATA_SERVICE_NUM_ATTEMPTS
When attempting to retrieve credentials on an EC2 instance that has been configured with an IAM role, boto3 will only make one attempt to retrieve credentials from the instance metadata service before giving up. If you know your code will be running on an EC2 instance, you can increase this value to make boto3 retry multiple times before giving up.
AWS_DATA_PATH
A list of additional directories to check when loading botocore data. You typically do not need to set this value. There's two built in search paths: <botocoreroot>/data/ and ~/.aws/models. Setting this environment variable indicates additional directories to first check before falling back to the built in search paths. Multiple entries should be separated with the os.pathsep character which is : on linux and ; on windows.

Configuration File

Boto3 will also search the ~/.aws/config file when looking for configuration values. You can change the location of this file by setting the AWS_CONFIG_FILE environment variable.

This file is an INI formatted file that contains at least one section: [default]. You can create multiple profiles (logical groups of configuration) by creating sections named [profile profile-name]. If your profile name has spaces, you'll need to surround this value in quotes: [profile "my profile name"]. Below are all the config variables supported in the ~/.aws/config file:

region
The default region to use, e.g. us-west-1, us-west-2, etc. When specifying a region inline during client initialization, this property is named region_name
aws_access_key_id
The access key to use.
aws_secret_access_key
The secret access key to use.
aws_session_token
The session token to use. This is typically only needed when using temporary credentials. Note aws_security_token is supported for backwards compatibility.
ca_bundle
The CA bundle to use. See the docs above on AWS_CA_BUNDLE for more information.
metadata_service_timeout
The number of seconds before timing out when retrieving data from the instance metadata service. See the docs above on AWS_METADATA_SERVICE_TIMEOUT for more information.
metadata_service_num_attempts
The number of attempts to make before giving up when retrieving data from the instance metadata service. See the docs above on AWS_METADATA_SERVICE_NUM_ATTEMPTS for more information.
parameter_validation
Disable parameter validation (default is true; parameters are validated by default). This is a boolean value that can have a value of either true or false. Whenever you make an API call using a client, the parameters you provide are run through a set of validation checks including (but not limited to): required parameters provided, type checking, no unknown parameters, minimum length checks, etc. You generally should leave parameter validation enabled.
role_arn
The ARN of the role you want to assume.
source_profile
The profile name that contains credentials we should use for the initial AssumeRole call.
external_id
Unique identifier to pass when making AssumeRole calls.
mfa_serial
Serial number of ARN of an MFA device to use when assuming a role.
role_session_name
The role name to use when assuming a role. If this value is not provided, a session name will be automatically generated.
s3

Set S3 specific configuration data. You typically will not need to set these values. Boto3 will automatically switching signature versions and addressing styles if necessary. This is a nested configuration value. See the Nested Configuration section for more information on the format. The sub config keys supported for s3 are:

  • addressing_style: Specifies which addressing style to use. This controls if the bucket name is in the hostname or part of the URL. Value values are: path, virtual, and auto.
  • signature_version: Which AWS signature version to use when signing requests. Value values are: s3 and s3v4.