From the course: Build with AI: Data Pipelines with Cursor, Neon, and Streamlit
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Process and load your data
From the course: Build with AI: Data Pipelines with Cursor, Neon, and Streamlit
Process and load your data
- [Narrator] We are now ready to load our data into the database. So to summarize, we have logic that goes to the API and gets data on papers in a local JSON file. We also have logic to establish the connection to our Postgres cloud database. And finally, we have logic that creates the papers table if it doesn't exist, which is where we will upload our papers data. So now for the next step, I have written this prompt for the agent. And in this prompt I'm saying write a script that takes a JSON file path as input to the script, or argument, like the one we have in temp folder. So I giving the AI a reference of what type of file we will use. The script needs to load the data from this JSON, and it needs to connect to our database using DB connection by script. I'm referencing the script that already exists so that the agent doesn't rewrite the logic that we already have. Then we need to create the papers stable if…
Contents
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OpenAlex quick start: Analyze data for Python data pipelines6m 59s
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(Locked)
Data extraction layer: Get data from OpenAlex22m 40s
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(Locked)
Neon database setup: Cloud PostgreSQL for data pipeline projects9m 50s
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(Locked)
Design table schema and create a table in the database9m 50s
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(Locked)
Process and load your data12m 23s
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(Locked)
Data quality testing11m 21s
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(Locked)
Consolidate pipeline logic8m 38s
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(Locked)
Build a Streamlit dashboard7m 58s
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(Locked)
Deploy the Streamlit dashboard7m 28s
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