diff --git a/README.md b/README.md index 99ae859..3fab71d 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ ### What is it? -PyTabular is a python package that allows for programmatic execution on your tabular models! This is possible thanks to [Pythonnet](https://pythonnet.github.io/) and Microsoft's [.Net APIs on Azure Analysis Services](https://docs.microsoft.com/en-us/dotnet/api/microsoft.analysisservices?view=analysisservices-dotnet). The package should have the dll files included when you import it. See [Documentation Here](https://curts0.github.io/PyTabular/) +PyTabular is a python package that allows for programmatic execution on your tabular models! This is possible thanks to [Pythonnet](https://pythonnet.github.io/) and Microsoft's [.Net APIs on Azure Analysis Services](https://docs.microsoft.com/en-us/dotnet/api/microsoft.analysisservices?view=analysisservices-dotnet). The package should have the dll files included when you import it. See [Documentation Here](https://curts0.github.io/PyTabular/). PyTabular is still considered alpha while I'm working on building out the proper tests and testing environments, so I can ensure some kind of stability in features. ### Getting Started @@ -25,21 +25,41 @@ DAX Query ```python model.Query(DAX_QUERY) + + #Example Dax Query + #EVALUATE + #TOPN(100,'Table1') + # Returns a Pandas DataFrame ``` -[Refresh Tables and Partitions](https://curts0.github.io/PyTabular/Tabular/#refresh) +See [Refresh Tables and Partitions](https://curts0.github.io/PyTabular/Tabular/#refresh). ```python - #Can be str(table name only), Table object, Partition object, or an iterable combination of the three. + #You have a few options when refreshing. model.Refresh('Table Name') - tables_to_refresh = ['Table Name 1', 'Table Name 2', , ] - #Queue up the tables and partitions that you want to refresh. - model.Refresh(tables_to_refresh) - #NOTE if you monitor the logs you will notice a Trace is executed on the refreshes. + + #or... + model.Refresh(['Table1','Table2','Table3']) + + #or... + model.Refresh(
) + + #or... + model.Refresh() + + #or... + model.Refresh({'Table Name':'Partition Name'}) + + #or any kind of weird combination like + model.Refresh([{
:,'Table Name':['Partition1','Partition2']},'Table Name','Table Name2']) + + #Add Tracing=True for simple Traces tracking the refresh. + model.Refresh(['Table1','Table2'], Tracing=True) + ``` -Built In Dax Query Helpers +Built In Dax Query Helpers. In-case you want to run some quick queries similar to what vertipaq analyzer will do when getting row counts. ```python #Query Every Column @@ -57,14 +77,14 @@ Built In Dax Query Helpers ''' ``` -Backup & Revert a Table in Memory +Backup & Revert a Table in Memory. USE WITH CAUTION, obviously not in PROD. I have been experimenting with this concept. ```python model.Backup_Table('TableName') #This will backup the table with surround items (columns,measures,relationships,roles,hierarchies,etc.) and will add a suffix of '_backup' #Make any changes to your original table and then revert or delete backup as necessary model.Revert_Table('TableName') #This will essentially replace your original with _backup ``` -Run BPA from TE2 +Run BPA from TE2. Roadmap to make this more robust, and allow you to run all the command line interfaces that TE2 has to offer. ```python TE2 = pytabular.TE2() #Feel free to input your TE2 File path or this will download for you. BPA = pytabular.BPA() #Fee free to input your own BPA file or this will download for you from: https://raw.githubusercontent.com/microsoft/Analysis-Services/master/BestPracticeRules/BPARules.json diff --git a/pytabular/__init__.py b/pytabular/__init__.py index a3a1f63..fc696ad 100644 --- a/pytabular/__init__.py +++ b/pytabular/__init__.py @@ -30,4 +30,5 @@ from . logic_utils import pd_dataframe_to_m_expression, pandas_datatype_to_tabular_datatype from . tabular_tracing import Base_Trace, Refresh_Trace from . tabular_editor import Tabular_Editor -from . best_practice_analyzer import BPA \ No newline at end of file +from . best_practice_analyzer import BPA +logging.debug(f'Import successful...') \ No newline at end of file diff --git a/pytabular/pytabular.py b/pytabular/pytabular.py index e38def9..b2796e9 100644 --- a/pytabular/pytabular.py +++ b/pytabular/pytabular.py @@ -2,19 +2,17 @@ logger = logging.getLogger('PyTabular') logger.debug(f'Importing Microsoft.AnalysisServices.Tabular') -from Microsoft.AnalysisServices.Tabular import Server, Database, RefreshType, DataType, ConnectionDetails, ColumnType, MetadataPermission, Table, DataColumn, Partition, MPartitionSource, PartitionSourceType, Trace, TraceEvent, TraceEventHandler +from Microsoft.AnalysisServices.Tabular import Server, RefreshType, ColumnType, Table, DataColumn, Partition, MPartitionSource logger.debug(f'Importing Microsoft.AnalysisServices.AdomdClient') from Microsoft.AnalysisServices.AdomdClient import (AdomdCommand, AdomdConnection) logger.debug(f'Importing Microsoft.AnalysisServices') -from Microsoft.AnalysisServices import UpdateOptions, TraceEventClass, TraceEventSubclass, TraceEventCollection, TraceColumn +from Microsoft.AnalysisServices import UpdateOptions logger.debug('Importing Other Packages...') -from typing import Any, Dict, List, Optional, Union, Callable +from typing import Any, Dict, List, Union from collections.abc import Iterable from collections import namedtuple -import requests as r import pandas as pd -import json import os import subprocess import atexit @@ -89,7 +87,7 @@ def Refresh(self, str == 'Table_Name' Table == Table Object Partition == Partition Object - Dict[str, Any] == A way to specify a partition of group of partitions. For ex: {'Table_Name':'Partition1'} or {'Table_Name':['Partition1','Partition2']}. NOTE you can also change out the strings for partition or tables objects. + Dict[str, Any] == A way to specify a partition of group of partitions. For ex. {'Table_Name':'Partition1'} or {'Table_Name':['Partition1','Partition2']}. NOTE you can also change out the strings for partition or tables objects. RefreshType (RefreshType, optional): See [RefreshType](https://docs.microsoft.com/en-us/dotnet/api/microsoft.analysisservices.tabular.refreshtype?view=analysisservices-dotnet). Defaults to RefreshType.Full. Tracing (bool, optional): Currently just some basic tracing to track refreshes. Defaults to False. @@ -197,10 +195,11 @@ def property_changes(Property_Changes): Added_Subtree_Roots = Model_Save_Results.Impact.AddedSubtreeRoots Removed_Objects = Model_Save_Results.Impact.RemovedObjects Removed_Subtree_Roots = Model_Save_Results.Impact.RemovedSubtreeRoots - Changes = namedtuple("Changes","Property_Changes Added_Objects Added_Subtree_Roots Removed_Objects Removed_Subtree_Roots") - [property_changes(Property_Changes), Added_Objects, Added_Subtree_Roots, Removed_Objects, Removed_Subtree_Roots] + Xmla_Results = Model_Save_Results.XmlaResults + Changes = namedtuple("Changes","Property_Changes Added_Objects Added_Subtree_Roots Removed_Objects Removed_Subtree_Roots Xmla_Results") + [property_changes(Property_Changes), Added_Objects, Added_Subtree_Roots, Removed_Objects, Removed_Subtree_Roots, Xmla_Results] self.Reload_Model_Info() - return Changes(property_changes(Property_Changes), Added_Objects, Added_Subtree_Roots, Removed_Objects, Removed_Subtree_Roots) + return Changes(property_changes(Property_Changes), Added_Objects, Added_Subtree_Roots, Removed_Objects, Removed_Subtree_Roots, Xmla_Results) def Backup_Table(self,table_str:str) -> bool: '''USE WITH CAUTION, EXPERIMENTAL. Backs up table in memory, brings with it measures, columns, hierarchies, relationships, roles, etc. It will add suffix '_backup' to all objects. @@ -358,7 +357,7 @@ def Query(self,Query_Str:str) -> pd.DataFrame: logger.debug(f'Converting Results into List...') while Query.Read(): Results.append([Query.GetValue(index) for index in range(0,len(Column_Headers))]) - logger.info(f'Data retrieved and closing query...') + logger.debug(f'Data retrieved and closing query...') Query.Close() logger.debug(f'Converting to Pandas DataFrame...') df = pd.DataFrame(Results,columns=[value for _,value in Column_Headers])