First, ensure you have access to the Harvest API. You will need an account with the necessary permissions. Log into your Harvest account and navigate to the �Developers� section to find API documentation and generate a personal access token.

In the Harvest application, go to "Settings" and select "Developers" or "API" to create a new personal access token. Save this token securely, as it will be required to authenticate your API requests.

Set up your environment for making HTTP requests. You can use programming languages like Python, Ruby, or JavaScript. For simplicity, we�ll use Python. Ensure you have Python installed on your machine along with the `requests` library. You can install it using the command:
```bash
pip install requests
```

Write a script to fetch data from Harvest using the API. Below is a sample Python script that demonstrates how to make a GET request to retrieve data, such as time entries:
```python
import requests
api_url = 'https://api.harvestapp.com/v2/time_entries'
headers = {
'Authorization': 'Bearer YOUR_ACCESS_TOKEN',
'Harvest-Account-Id': 'YOUR_ACCOUNT_ID',
'User-Agent': 'YourApp (your_email@example.com)'
}
response = requests.get(api_url, headers=headers)
data = response.json()
```

Process the JSON data obtained from the API response to extract the necessary fields you want to export to CSV. For time entries, you might extract fields like date, hours, project, task, etc.
```python
time_entries = data['time_entries']
extracted_data = [
{'date': entry['spent_date'], 'hours': entry['hours'], 'project': entry['project']['name'], 'task': entry['task']['name']}
for entry in time_entries
]
```

Use Python�s built-in `csv` module to write the processed data to a CSV file. Here�s how you can do it:
```python
import csv
csv_file = 'harvest_data.csv'
csv_columns = ['date', 'hours', 'project', 'task']
try:
with open(csv_file, 'w', newline='') as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=csv_columns)
writer.writeheader()
for data in extracted_data:
writer.writerow(data)
except IOError:
print("I/O error")
```

After the script completes, open the CSV file to verify that the data has been correctly written. Check for any discrepancies or errors in data formatting. If everything is correct, clean up your script and ensure sensitive information like API tokens are handled securely.
This guide allows you to manually extract data from Harvest and save it locally in a CSV format using the Harvest API and Python without employing third-party tools.