Improve function help by grouping by function type

.github/workflows/docs.yml

@@ -13,7 +13,7 @@ jobs:
           python-version: '3.11'
       - uses: actions/checkout@v4
       - run: python -m pip install .[docs]
-      - run: python -m sphinx -W -b html docs/ build/html/
+      - run: python docs/make_bql_doc.py
       - uses: actions/upload-pages-artifact@v3
         with:
           path: build/html
@@ -26,6 +26,6 @@ jobs:
     environment:
       name: github-pages
     runs-on: ubuntu-latest
-    if: github.ref == 'refs/heads/master'
+    if: github.ref == 'refs/heads/mlell'
     steps:
       - uses: actions/deploy-pages@v4

README.rst

@@ -5,3 +5,18 @@ beanquery is a customizable and extensible lightweight SQL query tool
 that works on tabular data, including `Beancount`__ ledger data.
 
 __ https://beancount.github.io/
+
+With this tool you can write *queries* to extract information from your
+Beancount ledger. This is the documentation of functions and field names
+which are available for queries. 
+
+Please read the Manual of the `Beancount Query Language (BQL)`__ if you
+do not yet know how to write queries.
+
+
+__ http://furius.ca/beancount/doc/query
+
+After you have learned the BQL, you can use the 
+`list and documentation of available functions and columns`__
+
+__ https://beancount.github.io/beanquery

beanquery/query_compile.py

@@ -406,11 +406,25 @@ def __call__(self, context):
 
 
 class EvalFunction(EvalNode):
+    """Base class for function evaluation nodes.
+
+    Class Attributes:
+        __intypes__: List of input parameter types for type checking.
+        __outtype__: Output type of the function. None means no type
+          annotation. To annotate that the function returns None, use
+          types.NoneType.
+    """
     __slots__ = ('operands',)
 
     # Type constraints on the input arguments.
     __intypes__ = []
 
+    # Output type annotation
+    __outtype__ = None
+
+    # Input argument names for documentation.
+    __param_names__ = []
+
     def __init__(self, context, operands, dtype):
         super().__init__(dtype)
         self.context = context