AUM — Assets Under Management

Five sub-modules covering all AMFI AUM pages. All Excel-capable methods have a paired _excel() variant that returns raw bytes.

Data dictionary: AUM field reference →

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Average AUM (fund-wise & scheme-wise)

amfipy.aum.AUMClient.financial_years()

List available financial years for Average AUM.

Returns:

Type	Description
list[dict]	[{"id": 1, "financial_year": "April 2025 - March 2026"}, ...]

amfipy.aum.AUMClient.periods(fy_id)

List periods within a financial year for Average AUM.

Parameters:

Name	Type	Description	Default
fy_id	int	Financial year ID from :meth:financial_years.	required

Returns:

Type	Description
dict	{"financial_year": "...", "periods": [{"id": 1, "period": "January - March 2026"}, ...]}

amfipy.aum.AUMClient.average_aum_fundwise(fy_id, period_id, as_df=False)

Fetch fund-wise Average AUM for a given quarter.

Parameters:

Name	Type	Description	Default
fy_id	int	Financial year ID (from :meth:financial_years).	required
period_id	int	Period ID (from :meth:periods).	required
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	List of fund records with MutualFundName and averageAUM.

amfipy.aum.AUMClient.average_aum_fundwise_excel(fy_id, period_id)

Download fund-wise Average AUM as Excel bytes.

amfipy.aum.AUMClient.average_aum_schemewise(fy_id, period_id, str_type='Categorywise', mf_id=0, as_df=False)

Fetch scheme-wise Average AUM for a given quarter.

Parameters:

Name	Type	Description	Default
fy_id	int	Financial year ID (from :meth:financial_years).	required
period_id	int	Period ID (from :meth:periods).	required
str_type	str	"Categorywise" | "Typewise"	'Categorywise'
mf_id	int | str	AMC numeric ID; 0 = All.	0
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	List of scheme-category records with nested schemes data.

amfipy.aum.AUMClient.average_aum_schemewise_excel(fy_id, period_id, str_type='Categorywise', mf_id=0)

Download scheme-wise Average AUM as Excel bytes.

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AUM–AAUM Disclosure

amfipy.aum.AUMClient.disclosure_years()

List available financial years for AUM–AAUM Disclosure.

Returns:

Type	Description
list[dict]	[{"id": "2025-26", "title": "April 2025-March 2026"}, ...]

amfipy.aum.AUMClient.disclosure_by_category(fy_id, as_df=False)

Quarterly AUM disclosure by fund category.

Parameters:

Name	Type	Description	Default
fy_id	str	Financial year string, e.g. "2025-26".	required
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	List of quarterly records with Period, pdfURL, excelURL.

amfipy.aum.AUMClient.disclosure_by_geography(fy_id, as_df=False)

Quarterly AUM disclosure by geography.

Parameters:

Name	Type	Description	Default
fy_id	str	Financial year string, e.g. "2025-26".	required
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	List of quarterly records with Period, pdfURL, excelURL.

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Age-wise / Folio Data

amfipy.aum.AUMClient.agewise_folio(month, as_df=False)

Age-wise AUM and folio data for a month.

Parameters:

Name	Type	Description	Default
month	str	"March-2026" format (MonthName-YYYY).	required
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	Dict with investorClassification and ageWiseAUM lists.

amfipy.aum.AUMClient.agewise_folio_excel(month)

Download age-wise / folio data as Excel bytes.

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Classified Average AUM

amfipy.aum.AUMClient.classified_dates(mf_id=0)

List available months for Classified Average AUM.

Makes a probe call and returns the monthYear list from the response.

Returns:

Type	Description
list[dict]	[{"date": "April-2026"}, {"date": "March-2026"}, ...]

amfipy.aum.AUMClient.statewise(date, mf_id=0, as_df=False)

State-wise classified Average AUM for a month.

Parameters:

Name	Type	Description	Default
date	str	"01-mon-yyyy" format (lowercase month, always day=01), e.g. "01-apr-2026" or "01-mar-2026".	required
mf_id	int | str	AMC numeric ID; 0 = All.	0
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	Dict with data (list of state records) and monthYear (available dates).

amfipy.aum.AUMClient.statewise_excel(date, mf_id=0)

Download state-wise classified AUM as Excel bytes.

amfipy.aum.AUMClient.scheme_catwise(date, mf_id=0, as_df=False)

Scheme-category-wise classified Average AUM for a month.

Parameters:

Name	Type	Description	Default
date	str	"01-mon-yyyy" format, e.g. "01-apr-2026".	required
mf_id	int | str	AMC numeric ID; 0 = All.	0
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	List of scheme-category records (includes header and data rows).

amfipy.aum.AUMClient.scheme_catwise_excel(date, mf_id=0)

Download scheme-category-wise classified AUM as Excel bytes.

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Bifurcation of AUM

amfipy.aum.AUMClient.bifurcation(date, as_df=False)

Bifurcation of AAUM under Direct Plan for a month.

Parameters:

Name	Type	Description	Default
date	str	"DD-Mon-YYYY" format, e.g. "31-Mar-2026".	required
as_df	bool	Return polars DataFrame.	False

Returns:

Type	Description
Any	List with one record containing TotalAAUMunderDirectPlan,
Any	AAUMunderRegisteredAdvisers, AAUMunderPMS,
Any	AAUMunderDIYclients, Month_Date.

amfipy.aum.AUMClient.bifurcation_excel(date)

Download bifurcation data as Excel bytes.

amfipy.aum.AUMClient.bifurcation_range(dates, as_df=False)

Fetch bifurcation data for multiple dates.

Returns {"31-Mar-2026": <data>, "28-Feb-2026": <data>, ...}.