Run DAX queries against Analysis Services and get Pandas Dataframes
Project description
About
I wanted to consume some info from Azure Analysis Services from python and didn't see a convenient way to to do, so I wrote this. It should also work just fine with XMLA endpoints on Power BI Premium.
pymsasdax is a small Python Module for running DAX queries against Microsoft Analysis Services, using COM Interop. It does some basic typesniffing and returns a best guess Pandas Dataframe.
This does assume that the MSOLAP client is installed - you can get it from here
I've done very little testing, so consider this alpha code. If you run into timeouts, make sure you're setting the timeout to an appropriate duration when creating the Connection.
tidy_column_names will remove brackets and replace spaces with underscores in the returned dataframe's columns. Set it to False in the Connection init if you don't want this behavior.
Also, this is my first module up on pypi and I'm not exactly an expert on python, so feel free to submit an issue or a pull request. If I ended up reinventing the wheel here (ha!) and there was an easier way to do this, also please let me know.
I hope you find this useful!
Python before 3.9
This should actually work fine with for python 3 under 3.9. I've used this code for a couple of years now without incident -- I was just lazy when building this package. I think you'd need backports to support dateparser. Feel free to path and submit a PR if you like.
Usage examples
Have an interactive prompt for Login to the resource
from pymsasdax import dax
with dax.Connection(
data_source='asazure://<region name>.asazure.windows.net/<instance here>,
initial_catalog='<my tabular database>'
) as conn:
df = conn.query('EVALUATE ROW("a", 1)')
print(df)
Use an app id
from pymsasdax import dax
with dax.Connection(
data_source='asazure://<region name>.asazure.windows.net/<instance here>,
initial_catalog='<my tabular database>'
uid='app:<client id>@<tenant id>',
password='<client secret>
) as conn:
df = conn.query('EVALUATE ROW("a", 1)')
df.to_csv("raw_data.csv", index=False)
Rename columns your way
from pymsasdax import dax
def my_column_renamer(colname):
return colname.lower()
with dax.Connection(
data_source='asazure://<region name>.asazure.windows.net/<instance here>,
initial_catalog='<my tabular database>',
tidy_map_function = my_column_renamer
) as conn:
df = conn.query('EVALUATE SUMMARIZECOLUMNS (etc....etc...etc...)')
print(df)
Dev Notes
Version History
- 2023.1013
- Fix issue with column names populating from when i made initial package version
- Allow specificiation of column name cleanup function
- 2023.1001 - Initial
Tests
Yes. There aren't any. Feel free to submit a PR.
Building
This might not be right but if you ever go to update pypi -
bumpver update --minor --tag beta
pip-compile pyproject.toml
python -m pip install -e .
#test
python -m build
twine check dist/*
twine upload dist/*
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