How to load data from Weatherstack to Postgres destination

First, you need to sign up for an API key from Weatherstack. This key grants you access to their data. Go to the Weatherstack website, create an account, and subscribe to the appropriate plan that suits your data needs. Your API key will be available in your account dashboard.

If you haven't already, install PostgreSQL on your system. You can download the installer from the PostgreSQL official website. After installation, create a new database using the `psql` command-line interface or a GUI tool like pgAdmin. Use the command `CREATE DATABASE weather_data;` to create a database named `weather_data`.

Plan and create a table structure within your PostgreSQL database to store the weather data. Decide on the necessary fields based on the data you wish to extract. For example:
```sql
CREATE TABLE weather (
id SERIAL PRIMARY KEY,
city VARCHAR(50),
temperature DECIMAL,
humidity INTEGER,
weather_description VARCHAR(100),
observation_time TIMESTAMP
);
```
Modify the schema according to the attributes you need from Weatherstack.

Use a programming language like Python to make HTTP requests to the Weatherstack API. Import necessary libraries such as `requests` to send GET requests to the API endpoint. For example:
```python
import requests

api_key = 'YOUR_API_KEY'
location = 'New York'
url = f'http://api.weatherstack.com/current?access_key={api_key}&query={location}'

response = requests.get(url)
data = response.json()
```
Parse the JSON response to extract the desired weather information.

Transform the fetched JSON data into a format suitable for insertion into your PostgreSQL table. Extract fields like temperature, humidity, and description, and convert them to match your database schema. For example:
```python
weather_data = {
'city': data['location']['name'],
'temperature': data['current']['temperature'],
'humidity': data['current']['humidity'],
'weather_description': data['current']['weather_descriptions'][0],
'observation_time': data['current']['observation_time']
}
```

Establish a connection to your PostgreSQL database using a library like `psycopg2` in Python. This library allows you to execute SQL commands within your Python script:
```python
import psycopg2

conn = psycopg2.connect(
dbname='weather_data',
user='yourusername',
password='yourpassword',
host='localhost',
port='5432'
)
cursor = conn.cursor()
```

Insert the transformed data into your PostgreSQL table using SQL `INSERT` commands. Ensure you commit the transaction to save changes:
```python
insert_query = """
INSERT INTO weather (city, temperature, humidity, weather_description, observation_time)
VALUES (%s, %s, %s, %s, %s)
"""
cursor.execute(insert_query, (weather_data['city'], weather_data['temperature'], weather_data['humidity'], weather_data['weather_description'], weather_data['observation_time']))
conn.commit()
cursor.close()
conn.close()
```
This step completes the data transfer from Weatherstack to PostgreSQL without using third-party connectors. Repeat the data fetching and insertion process as needed to keep your database updated.