Parse, validate and document your Power BI Project
Project description
pbipinspect
Parse, validate and document your Power BI Project
Installation
pip install pbipinspect
Usage
This library transforms your Power BI project into a structured and validated state. It provides a set of tools to analyze, validate, and document your project.
First, you need to create an inspect object. The create_inspect function takes a path to your project and returns a PbipInspect object. You can also instantiate the object directly using the PbipInspect class, but using create_inspect is recommended.
>>> from pbipinspect import create_inspect
>>> inspect = create_inspect('your-project.pbip')
Inspect parse you Power BI Project and gives you the ability to validate and document it. ou can view the model generated from your project by accessing the pbip.model attribute.
>>> print(inspect.pbip.model)
{'model': {
'tables': [{
'name': 'table',
'lineageTag': 'id',
'columns': [{...}],
'measures': [{...}],
'partitions': [{...}],
'isHidden': False,
'annotations': [{...}]
}],
'relationships': [{...}],
'expressions': [{...}]
}}
Expectations
Now, it's possible to validate your project. pbipinspect already comes with some expects that you can use to validate your project.
>>> from pbipinspect.expectations import *
>>> inspect.expectations(steps=[
... expect_col_starts_with(col_type='dateTime', pattern='dt_', state='Info'),
... expect_measure_starts_with(pattern='m_'),
... expect_table_starts_with(pattern='t_'),
... expect_table_name_no_spaces(),
... expect_cols_in_relationship_has_same_type(),
... expect_dax_lines_length(max_length=60),
... expect_m_lines_length(max_length=60),
... expect_measures_in_specific_table('_measures'),
... expect_no_calculated_columns(state='Error'),
... expect_all_relationships_active()
>>> ])
>>> inspect.run_expectations()
>>> print(inspect.expects)
[{'expect': 'expect_col_starts_with',
'state': 'Warning',
'message': "Column 'Column1' in table 'Table1' must start with 'dt_'"},
{'expect': 'expect_no_calculated_columns',
'state': 'Error',
'message': "Table 'Table1' has calculated columns: 'Column2' and 'Column3'"}
]
Building documentation
Additionally, you can generate documentation for your project using the build_report method.
>>> report = inspect.build_report()
By default, this approach will create a report using the default template. However, you can change the template and the variables by specifying the report_template and render parameters.
You can also use the add_metadata method to include metadata in your report. This metadata will be displayed at the top of the report in the "Overview" section. Therefore, metadata should be used to provide information about your project, such as its name, description, author, etc.
>>> inspect.add_metadata({
... 'name': 'Project name',
... 'description': 'Project description',
... 'author': 'Author'
... })
>>> report = inspect.build_report()
Tables, columns and measures descriptions
pbipinspect introduces a method for generating descriptions for tables, columns, and measures. In your Power BI project, you can add a comment in the source code of a table following this pattern:
/* @doc
Table description
@col column1:
column1 description
@col column2:
column2 description
*/
let
Source = Table.FromRecords({
[column1 = 1, column2 = 2]
}),
#"Changed Type" = Table.TransformColumnTypes(
Source,
{{"col1", number}, {"col2", number}}
)
in
#"Changed Type"
The same pattern can be used for measures:
/* @doc
Measure description
*/
var = 1
return var + 1
These descriptions are added to the "description" field of each corresponding property in the parsed model.
The model
The pbip.model field of the PbipInspect object contains the parsed model of your Power BI Project.
Currently, the model contains the following fields:
{
"type": "object",
"properties": {
"model": {
"type": "object",
"properties": {
"tables": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"lineageTag": { "type": "string" },
"isHidden": { "type": "boolean" },
"isPrivate": { "type": "boolean" },
"columns": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"expression": { "type": "string" },
"isHidden": { "type": "boolean" },
"isNameInferred": { "type": "boolean" },
"dataType": { "type": "string" },
"lineageTag": { "type": "string" },
"summarizeBy": { "type": "string" },
"sourceColumn": { "type": "string" },
"annotations": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"value": { "type": "string" }
}
}
},
"calculated": { "type": "boolean" },
"description": { "type": "string" }
}
}
},
"measures": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"lineageTag": { "type": "string" },
"annotations": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"value": { "type": "string" }
}
}
},
"displayFolder": { "type": "string" },
"expression": { "type": "string" },
"formatString": { "type": "string" },
"description": { "type": "string" },
"references": {
"type": "array",
"items": {
"type": "object",
"properties": {
"type": { "type": "string" },
"name": { "type": "string" },
"column": { "type": "string" }
}
}
}
}
}
},
"partitions": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"type": { "type": "string" },
"mode": { "type": "string" },
"raw_expression": { "type": "string" },
"expression": { "type": "string" },
"description": { "type": "string" }
}
}
}
}
}
},
"relationships": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"fromTable": { "type": "string" },
"fromColumn": { "type": "string" },
"toTable": { "type": "string" },
"toColumn": { "type": "string" },
"crossFilteringBehavior": { "type": "string" },
"filteringSymbol": { "type": "string" },
"fromCardinalitySymbol": { "type": "string" },
"toCardinalitySymbol": { "type": "string" },
"isActive": { "type": "boolean" }
}
}
},
"expressions": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": { "type": "string" },
"lineageTag": { "type": "string" },
"type": { "type": "string" },
"expression": { "type": "string" },
"description": { "type": "string" }
}
}
}
}
}
}
}
Getting help
If you encounter a clear bug, please file an issue with a minimal reproducible example on GitHub.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pbipinspect-0.2.0.tar.gz.
File metadata
- Download URL: pbipinspect-0.2.0.tar.gz
- Upload date:
- Size: 21.1 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
48668d465e3ebf8d1ba4bb97c3167c1241be36411ae6610514a43b8f417f0bae
|
|
| MD5 |
194a2aeab585f009d75c9990739c6641
|
|
| BLAKE2b-256 |
f25f3a9f8dd3b5cce210635e792679c8c4f2c8a8a16455c61dce7ff6f35618a4
|
File details
Details for the file pbipinspect-0.2.0-py3-none-any.whl.
File metadata
- Download URL: pbipinspect-0.2.0-py3-none-any.whl
- Upload date:
- Size: 23.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.12.8
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
56d0ef22c61eb81628cac8f658d1ed6021f262fd3a35ccf32f14f412b6318dba
|
|
| MD5 |
b341b41f1f06ccdff423af81788ff2ed
|
|
| BLAKE2b-256 |
137fc4c02f4da320297f7bfdc269475c41c593584cce0ee55ed1350af857217d
|