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I wish I could use Pandas to query Salesforce using SOQL (Salesforce Object Query Language) just as you do with relational databases using pd.read_sql(). Currently, to retrieve Salesforce data into a Pandas DataFrame, users must execute queries using simple_salesforce and manually convert results to DataFrames, which in case of multi-level queries can become quite inefficient (due to the nested format of the outputs of Salesforce REST API).
Feature Description
The function would parallel pd.read_sql() and would look like this:
defread_soql(
query: str, # Equivalent to `query` in `pd.read_sql()`, representing the SOQL query string.con, # Expects a `simple_salesforce.Salesforce` object instead of an SQLAlchemy connection.index_col: str|list[str] |None=None, # Same as in `pd.read_sql()`parse_dates=None, # Same as in `pd.read_sql()`dtype: DtypeArg|None=None, # Same as in `pd.read_sql()`dtype_backend: DtypeBackend|lib.NoDefault=lib.no_default# Same as in `pd.read_sql()`
) ->DataFrame:
# validate connection is Salesforce object# validate dtype_backend is valid option# execute SOQL query and get all records# flatten output and remove metadata# convert records to DataFrame# if dtype specified: convert columns to specified types# if parse_dates specified: convert date columns# if index_col specified: set DataFrame index# if dtype_backend != 'numpy': convert to nullable types# return DataFrame
Alternative Solutions
Alternative naming
Since pd.read_sql() is a convenience wrapper around read_sql_table and read_sql_query, a more "formally" correct name might be read_soql_query, as there is no corresponding read_soql_table. This would maintain a closer parallel to Pandas' SQL functions.
However, I propose read_soql for brevity, and for consistency with other I/O functions such as pd.read_excel(), pd.read_parquet(), pd.read_feather(), pd.read_orc() etc.
Additional Context
I am interested in developing this feature as I have already done some work towards its implementation.
The text was updated successfully, but these errors were encountered:
Feature Type
Adding new functionality to pandas
Changing existing functionality in pandas
Removing existing functionality in pandas
Problem Description
I wish I could use Pandas to query Salesforce using SOQL (Salesforce Object Query Language) just as you do with relational databases using
pd.read_sql()
. Currently, to retrieve Salesforce data into a Pandas DataFrame, users must execute queries using simple_salesforce and manually convert results to DataFrames, which in case of multi-level queries can become quite inefficient (due to the nested format of the outputs of Salesforce REST API).Feature Description
The function would parallel
pd.read_sql()
and would look like this:Alternative Solutions
Alternative naming
Since
pd.read_sql()
is a convenience wrapper aroundread_sql_table
andread_sql_query
, a more "formally" correct name might beread_soql_query
, as there is no correspondingread_soql_table
. This would maintain a closer parallel to Pandas' SQL functions.However, I propose
read_soql
for brevity, and for consistency with other I/O functions such aspd.read_excel()
,pd.read_parquet()
,pd.read_feather()
,pd.read_orc()
etc.Additional Context
I am interested in developing this feature as I have already done some work towards its implementation.
The text was updated successfully, but these errors were encountered: