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Hello Community,
I have requirement to generate powerbi report including visual part or semantic layer by having CSV as datasource through poewrBi API's .
Generated report will fetch data from CSV and CSV can be stored in some storage space like Amazon S3 Bucket or Azure Storage through some APIs of PowerBi.
As currently i am reading out documentations i think we can use Gateways of PowerBi(https://learn.microsoft.com/en-us/power-bi/connect-data/service-gateway-deployment-guidance)
and may be semantic layer creation api(https://learn.microsoft.com/en-us/rest/api/fabric/semanticmodel/items/create-semantic-model?tabs=HTT...) to create semantic model
Can some one please help on this.
Thanks !!
Solved! Go to Solution.
Hi, @UmeshGoti
Here's a step-by-step solution that combines the Power BI REST API with cloud storage (S3/Azure Blob) to fully automate the generation of reports with semantic models and visualizations.
Cloud Storage Configuration:
Azure Blob example:
from azure.storage.blob import BlobServiceClient
connection_string = "your_azure_connection_string"
blob_service_client = BlobServiceClient.from_connection_string(connection_string)
container_client = blob_service_client.get_container_client("reports")
blob_client = container_client.upload_blob("data.csv", open("local_data.csv", "rb"))
sas_token = blob_client.generate_sas(permissions="r", expiry=datetime.utcnow() + timedelta(hours=2))
csv_url = f"{blob_client.url}?{sas_token}"
Use the Power BI REST API to create datasets and define table structures.
To create a dataset :
POST https://api.powerbi.com/v1.0/myorg/datasets
Authorization: Bearer [Access Token]
Content-Type: application/json
{
"name": "SalesDataset",
"tables": [
{
"name": "Sales",
"columns": [
{"name": "Date", "dataType": "datetime"},
{"name": "Product", "dataType": "string"},
{"name": "Revenue", "dataType": "Int64"}
]
}
]
}
Load CSV data into the dataset:
POST https://api.powerbi.com/v1.0/myorg/datasets/{datasetId}/tables/Sales/rows
Authorization: Bearer [Access Token]
Content-Type: application/json
{
"rows": [
{"Date": "2024-01-01", "Product": "A", "Revenue": 1000},
{"Date": "2024-01-02", "Product": "B", "Revenue": 1500}
]
}
Best Regards
Jianpeng Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
Hi, @UmeshGoti
Here's a step-by-step solution that combines the Power BI REST API with cloud storage (S3/Azure Blob) to fully automate the generation of reports with semantic models and visualizations.
Cloud Storage Configuration:
Azure Blob example:
from azure.storage.blob import BlobServiceClient
connection_string = "your_azure_connection_string"
blob_service_client = BlobServiceClient.from_connection_string(connection_string)
container_client = blob_service_client.get_container_client("reports")
blob_client = container_client.upload_blob("data.csv", open("local_data.csv", "rb"))
sas_token = blob_client.generate_sas(permissions="r", expiry=datetime.utcnow() + timedelta(hours=2))
csv_url = f"{blob_client.url}?{sas_token}"
Use the Power BI REST API to create datasets and define table structures.
To create a dataset :
POST https://api.powerbi.com/v1.0/myorg/datasets
Authorization: Bearer [Access Token]
Content-Type: application/json
{
"name": "SalesDataset",
"tables": [
{
"name": "Sales",
"columns": [
{"name": "Date", "dataType": "datetime"},
{"name": "Product", "dataType": "string"},
{"name": "Revenue", "dataType": "Int64"}
]
}
]
}
Load CSV data into the dataset:
POST https://api.powerbi.com/v1.0/myorg/datasets/{datasetId}/tables/Sales/rows
Authorization: Bearer [Access Token]
Content-Type: application/json
{
"rows": [
{"Date": "2024-01-01", "Product": "A", "Revenue": 1000},
{"Date": "2024-01-02", "Product": "B", "Revenue": 1500}
]
}
Best Regards
Jianpeng Li
If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.
The Power BI Data Visualization World Championships is back! Get ahead of the game and start preparing now!
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