- Recipes
- Remote NDJSON file to Google BigQuery
Connect Remote NDJSON file and Google BigQuery in our serverless environment
Use this template to Read NDJSON entries from a remote file using them to insert rows into Google BigQuery table.
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Read NDJSON entries from a remote file
Used integrations:
JavaScript
Python
class HttpSourceReadRemoteNdjson {
async init() {
/// TODO: Create your http credential with endpoint information:
// More info at https://yepcode.io/docs/integrations/http/#credential-configuration
// It may manage headers or authentication
this.axiosClient = yepcode.integration.http("your-http-credential-name");
}
async fetch(publish, done) {
// TODO: Customize your ndjson file path to download
await this.axiosClient
.get("/the-ndjson-file-path.ndjson", {
responseType: "stream",
})
.then(({
data
}) => {
data
.pipe(ndjson.parse())
.on("data", async (line) => {
await publish(line);
})
.on("end", done);
});
}
async close() {}
}
import ndjson
class HttpSourceReadRemoteNdjson:
def setup(self):
# TODO: Create your http credential with endpoint information:
# More info at https://yepcode.io/docs/integrations/http/#credential-configuration
# It may manage headers or authentication
self.session = yepcode.integration.http("your-http-ndjson-credential-name")
def generator(self):
response = self.session.get("/the-ndjson-file-path.ndjson", stream=True)
response.raise_for_status()
lines = response.iter_lines(decode_unicode=True)
reader = ndjson.reader(lines)
for row in reader:
yield row
lines.close()
response.close()
def close(self):
pass
Do you need help solving this integration with YepCode?
Let's talkInsert rows into Google BigQuery table
Used integrations:
JavaScript
Python
class GoogleBigqueryTargetInsert {
async init() {
// TODO: Create your google-bigquery credential
// More info at https://yepcode.io/docs/integrations/google-bigquery/#credential-configuration
const googleBigQuery = yepcode.integration.googleBigQuery(
"your-google-bigquery-credential-name"
);
// TODO: Customize dataset and table names
// See how to get dataset name: https://cloud.google.com/bigquery/docs/dataset-metadata#console
this.table = await googleBigQuery
.dataset("your-dataset")
.table("your-table");
}
async consume(item) {
// TODO: Map item to your bigquery table row
this.table.insert([item]);
}
async close() {}
}
class GoogleBigqueryTargetInsert:
def setup(self):
# TODO: Create your BigQuery credential:
# More info at https://yepcode.io/docs/integrations/google-bigquery/#credential-configuration
self.big_query_client = yepcode.integration.googleBigQuery(
"your-bigquery-credential-name"
)
def consume(self, generator, done):
# TODO: Customize dataset and table ids
dataset_id = "dataset_id"
table_id = "table_id"
table_ref = self.big_query_client.dataset(dataset_id).table(table_id)
table = self.big_query_client.get_table(table_ref)
# TODO: Customize the row to insert
for item in generator:
item_to_insert = (item.get("name"), item.get("age"))
self.big_query_client.insert_rows(table, [item_to_insert])
done()
def close(self):
pass
FAQs
YepCode is a SaaS platform that allows to create, execute and monitor integrations and automations using source code in a serverless environment.
We like to call it the Zapier for developers, since we bring all the agility and benefits of NoCode tools (avoid server provisioning, environment configuration, deployments,...), but with all the power of being able to use a programming language like JavaScript or Python.
These recipes are a good starting point for you to build your own YepCode processes and solve your integration and automation problems.
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YepCode has been created with a clear enterprise approach (multi-tenant environment, team management, high security and auditing standards, IdP integrations, on-premise options,...) so we can be the Swiss army knife of any team of engineering, especially those that need to extract or send information to external systems, and where a certain dynamism or adaptation to change is necessary in that process.
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