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**Caution:** if you run the application locally, please the following instead: `client = Client(username, password, project_id, uri="http://localhost:4455")`
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Alternatively, you can provide a `secrets.json` file in your repository, looking as follows:
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```json
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{
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df = client.get_record_export()
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```
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Alternatively, you can also just run `kern pull` in your CLI given that you have provided the `secrets.json` file.
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Alternatively, you can also just run `kern pull` in your CLI given that you have provided the `secrets.json` file. This will download the current data and stores it in a `.json`-file with your project name as its file name.
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The `df` contains data of the following scheme:
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- all your record attributes are stored as columns, e.g. `headline` or `running_id` if you uploaded records like `{"headline": "some text", "running_id": 1234}`
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With the `client`, you easily integrate your data into any kind of system; may it be a custom implementation, an AutoML system or a plain data analytics framework 🚀
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