Begin by setting up a Python environment suitable for working with AWS and HTTP requests. Ensure you have Python installed, and use a virtual environment to manage dependencies. Install necessary packages using pip:
```bash
pip install boto3 requests
```
`boto3` is the Amazon Web Services (AWS) Software Development Kit (SDK) for Python, which allows you to interact with AWS services like DynamoDB.

Use the `requests` library to fetch data from PyPI. Identify the PyPI package URL from which you want to pull data. For example, to get information about a package, use the API endpoint `https://pypi.org/pypi/{package-name}/json`. Here’s a sample code snippet:
```python
import requests

package_name = "requests" # replace with your desired package
response = requests.get(f"https://pypi.org/pypi/{package_name}/json")
if response.status_code == 200:
package_data = response.json()
else:
raise Exception("Failed to fetch data from PyPI")
```

DynamoDB requires data to be in a specific format. Examine the structure of the JSON data fetched from PyPI and decide on a schema for your DynamoDB table. Extract and format the necessary fields from the JSON response into a dictionary that matches your DynamoDB schema.

To interact with AWS services, you need to configure your AWS credentials. You can set up your credentials by creating a configuration file at `~/.aws/credentials` with the following:
```
[default]
aws_access_key_id = YOUR_ACCESS_KEY
aws_secret_access_key = YOUR_SECRET_KEY
```
Alternatively, you can set these credentials as environment variables.

Use `boto3` to create a DynamoDB table if it does not already exist. Define the primary key structure based on your data needs. Here's a basic example of creating a table:
```python
import boto3

dynamodb = boto3.resource('dynamodb', region_name='your-region')

table = dynamodb.create_table(
TableName='PyPI_Data',
KeySchema=[
{
'AttributeName': 'package_name',
'KeyType': 'HASH' # Partition key
}
],
AttributeDefinitions=[
{
'AttributeName': 'package_name',
'AttributeType': 'S'
}
],
ProvisionedThroughput={
'ReadCapacityUnits': 5,
'WriteCapacityUnits': 5
}
)

table.wait_until_exists()
```

With your table ready, insert the structured data into DynamoDB using `boto3`. Use the `put_item` method to add each data item:
```python
table = dynamodb.Table('PyPI_Data')
item = {
'package_name': package_name,
'version': package_data['info']['version'],
'summary': package_data['info']['summary']
# Add other fields as necessary
}

table.put_item(Item=item)
```

Ensure that the data has been correctly inserted into your DynamoDB table. You can do this by querying the table and checking if the data matches what you expected. Use the `get_item` method to retrieve and verify the data:
```python
response = table.get_item(
Key={
'package_name': package_name
}
)

if 'Item' in response:
print("Data successfully inserted:", response['Item'])
else:
print("Data insertion failed")
```

By following these steps, you can efficiently move data from PyPI to DynamoDB without relying on third-party connectors or integrations.