graphtage.csv¶

A graphtage.Filetype for parsing, diffing, and rendering CSV files.

csv classes¶

CSV¶

class graphtage.csv.CSV¶

Bases: graphtage.Filetype

The CSV filetype.

__init__()¶

Initializes the CSV filetype.

CSV identifies itself with the MIME types csv and text/csv.

build_tree(path: str, allow_key_edits: bool = True) → graphtage.TreeNode ¶: Equivalent to build_tree()

build_tree_handling_errors(path: str, allow_key_edits: bool = True) → graphtage.TreeNode ¶

Same as Filetype.build_tree(), but it should return a human-readable error string on failure.

This function should never throw an exception.

Parameters

path – Path to the file to parse
allow_key_edits – Whether to allow dictionary keys to be editable

Returns

On success, the root tree node, or a string containing the error message on failure.

Return type

Union[str, TreeNode]

get_default_formatter() → graphtage.csv.CSVFormatter ¶: Returns the default formatter for printing files of this type.

CSVFormatter¶

class graphtage.csv.CSVFormatter¶

Bases: graphtage.GraphtageFormatter

Top-level formatter for CSV files.

DEFAULT_INSTANCE: Formatter[T] = <graphtage.csv.CSVFormatter object>¶

__init__()¶: Initialize self. See help(type(self)) for accurate signature.

static __new__(cls, *args, **kwargs) → graphtage.formatter.Formatter[~T][T]¶

Instantiates a new formatter.

This automatically instantiates and populates Formatter.sub_formatters and sets their parent to this new formatter.

get_formatter(item: T) → Optional[Callable[[graphtage.printer.Printer, T], Any]]¶

Looks up a formatter for the given item using this formatter as a base.

Equivalent to:

get_formatter(item.__class__, base_formatter=self)

is_partial: bool = False¶

parent: Optional[Formatter[T]] = None¶

print(printer: graphtage.printer.Printer, node_or_edit: Union[TreeNode, Edit], with_edits: bool = True)¶

Prints the given node or edit.

Parameters

printer – The printer to which to write.
node_or_edit – The node or edit to print.
with_edits – If :keyword:True, print any edits associated with the node.

Note

The protocol for determining how a node or edit should be printed is very complex due to its extensibility. See the Printing Protocol for a detailed description.

print_LeafNode(printer: graphtage.printer.Printer, node: graphtage.LeafNode)¶

Prints a leaf node, which should always be a column in a CSV row.

The node is escaped by first writing it to csv.writer():

csv.writer(...).writerow([node.object])

property root¶: Returns the root formatter.

sub_format_types: Sequence[Type[Formatter[T]]] = [<class 'graphtage.csv.CSVRows'>, <class 'graphtage.json.JSONFormatter'>]¶

sub_formatters: List[Formatter[T]] = []¶

CSVNode¶

class graphtage.csv.CSVNode(nodes: Iterable[T])¶

Bases: graphtage.ListNode

A node representing zero or more CSV rows.

__init__(nodes: Iterable[T])¶

Initializes a sequence node.

Parameters: children – A sequence of TreeNodes. This is assigned to the protected member SequenceNode._children.

__iter__() → Iterator[graphtage.TreeNode]¶

Iterates over this sequence’s child nodes.

This is equivalent to:

return iter(self._children)

__len__() → int ¶

The number of children of this sequence.

This is equivalent to:

return len(self._children)

all_children_are_leaves() → bool ¶

Tests whether all of the children of this container are leaves.

Equivalent to:

all(c.is_leaf for c in self)

Returns: True if all children are leaves.
Return type: bool

calculate_total_size()¶

Calculates the total size of this sequence.

This is equivalent to:

return sum(c.total_size for c in self)

children() → List[graphtage.TreeNode]¶

The children of this node.

Equivalent to:

list(self)

property container_type¶

The container type required by graphtage.sequences.SequenceNode

Returns: tuple
Return type: Type[Tuple[T, ..]]

dfs() → Iterator[graphtage.TreeNode]¶

Performs a depth-first traversal over all of this node’s descendants.

self is always included and yielded first.

This implementation is equivalent to:

stack = [self]
while stack:
    node = stack.pop()
    yield node
    stack.extend(node.children())

diff(node: graphtage.TreeNode) → Union[graphtage.EditedTreeNode, T]¶

Performs a diff against the provided node.

Parameters: node – The node against which to perform the diff.
Returns: An edited version of this node with all edits being completed.
Return type: Union[EditedTreeNode, T]

edit_modifiers: Optional[List[Callable[[TreeNode, TreeNode], Optional[graphtage.Edit]]]] = None¶

editable_dict() → Dict[str, Any]¶

Copies self.__dict__, calling TreeNode.editable_dict() on all children.

This is equivalent to:

ret = dict(self.__dict__)
ret['_children'] = self.container_type(n.make_edited() for n in self)
return ret

This is used by SequenceNode.make_edited().

property edited¶

Returns whether this node has been edited.

The default implementation returns False, whereas EditedTreeNode.edited() returns True.

classmethod edited_type() → Type[Union[graphtage.EditedTreeNode, T]]¶

Dynamically constructs a new class that is both a TreeNode and an EditedTreeNode.

The edited type’s member variables are populated by the result of TreeNode.editable_dict() of the TreeNode it wraps:

new_node.__dict__ = dict(wrapped_tree_node.editable_dict())

Returns: A class that is both a TreeNode and an EditedTreeNode. Its constructor accepts a TreeNode that it will wrap.
Return type: Type[Union[EditedTreeNode, T]]

edits(node: graphtage.TreeNode) → graphtage.Edit ¶

Calculates the best edit to transform this node into the provided node.

Parameters: node – The node to which to transform.
Returns: The best possible edit.
Return type: Edit

get_all_edits(node: graphtage.TreeNode) → Iterator[graphtage.Edit]¶

Returns an iterator over all edits that will transform this node into the provided node.

Parameters: node – The node to which to transform this one.
Returns: An iterator over edits. Note that this iterator will automatically explode any CompoundEdit in the sequence.
Return type: Iterator[Edit]

property is_leaf¶

Container nodes are never leaves, even if they have no children.

Returns: False
Return type: bool

make_edited() → Union[graphtage.EditedTreeNode, T]¶

Returns a new, copied instance of this node that is also an instance of EditedTreeNode.

This is equivalent to:

return self.edited_type()(self)

Returns: A copied version of this node that is also an instance of EditedTreeNode and thereby mutable.
Return type: Union[EditedTreeNode, T]

print(printer: graphtage.printer.Printer)¶

Prints a sequence node.

By default, sequence nodes are printed like lists:

SequenceFormatter('[', ']', ',').print(printer, self)

to_obj()¶

Returns a pure Python representation of this node.

For example, a node representing a list, like graphtage.ListNode, should return a Python list. A node representing a mapping, like graphtage.MappingNode, should return a Python dict. Container nodes should recursively call TreeNode.to_obj() on all of their children.

This is used solely for the providing objects to operate on in the commandline expressions evaluation, for options like –match-if and –match-unless.

property total_size¶

The size of this node.

This is an arbitrary, immutable value that is used to calculate the bounded costs of edits on this node.

The first time this property is called, its value will be set and memoized by calling TreeNode.calculate_total_size().

Returns: An arbitrary integer representing the size of this node.
Return type: int

CSVRow¶

class graphtage.csv.CSVRow(nodes: Iterable[T])¶

Bases: graphtage.ListNode

A node representing a row of a CSV file.

__init__(nodes: Iterable[T])¶

Initializes a sequence node.

Parameters: children – A sequence of TreeNodes. This is assigned to the protected member SequenceNode._children.

__iter__() → Iterator[graphtage.TreeNode]¶

Iterates over this sequence’s child nodes.

This is equivalent to:

return iter(self._children)

__len__() → int ¶

The number of children of this sequence.

This is equivalent to:

return len(self._children)

all_children_are_leaves() → bool ¶

Tests whether all of the children of this container are leaves.

Equivalent to:

all(c.is_leaf for c in self)

Returns: True if all children are leaves.
Return type: bool

calculate_total_size()¶

Calculates the total size of this sequence.

This is equivalent to:

return sum(c.total_size for c in self)

children() → List[graphtage.TreeNode]¶

The children of this node.

Equivalent to:

list(self)

property container_type¶

The container type required by graphtage.sequences.SequenceNode

Returns: tuple
Return type: Type[Tuple[T, ..]]

dfs() → Iterator[graphtage.TreeNode]¶

Performs a depth-first traversal over all of this node’s descendants.

self is always included and yielded first.

This implementation is equivalent to:

stack = [self]
while stack:
    node = stack.pop()
    yield node
    stack.extend(node.children())

diff(node: graphtage.TreeNode) → Union[graphtage.EditedTreeNode, T]¶

Performs a diff against the provided node.

Parameters: node – The node against which to perform the diff.
Returns: An edited version of this node with all edits being completed.
Return type: Union[EditedTreeNode, T]

edit_modifiers: Optional[List[Callable[[TreeNode, TreeNode], Optional[graphtage.Edit]]]] = None¶

editable_dict() → Dict[str, Any]¶

Copies self.__dict__, calling TreeNode.editable_dict() on all children.

This is equivalent to:

ret = dict(self.__dict__)
ret['_children'] = self.container_type(n.make_edited() for n in self)
return ret

This is used by SequenceNode.make_edited().

property edited¶

Returns whether this node has been edited.

The default implementation returns False, whereas EditedTreeNode.edited() returns True.

classmethod edited_type() → Type[Union[graphtage.EditedTreeNode, T]]¶

Dynamically constructs a new class that is both a TreeNode and an EditedTreeNode.

The edited type’s member variables are populated by the result of TreeNode.editable_dict() of the TreeNode it wraps:

new_node.__dict__ = dict(wrapped_tree_node.editable_dict())

Returns: A class that is both a TreeNode and an EditedTreeNode. Its constructor accepts a TreeNode that it will wrap.
Return type: Type[Union[EditedTreeNode, T]]

edits(node: graphtage.TreeNode) → graphtage.Edit ¶

Calculates the best edit to transform this node into the provided node.

Parameters: node – The node to which to transform.
Returns: The best possible edit.
Return type: Edit

get_all_edits(node: graphtage.TreeNode) → Iterator[graphtage.Edit]¶

Returns an iterator over all edits that will transform this node into the provided node.

Parameters: node – The node to which to transform this one.
Returns: An iterator over edits. Note that this iterator will automatically explode any CompoundEdit in the sequence.
Return type: Iterator[Edit]

property is_leaf¶

Container nodes are never leaves, even if they have no children.

Returns: False
Return type: bool

make_edited() → Union[graphtage.EditedTreeNode, T]¶

Returns a new, copied instance of this node that is also an instance of EditedTreeNode.

This is equivalent to:

return self.edited_type()(self)

Returns: A copied version of this node that is also an instance of EditedTreeNode and thereby mutable.
Return type: Union[EditedTreeNode, T]

print(printer: graphtage.printer.Printer)¶

Prints a sequence node.

By default, sequence nodes are printed like lists:

SequenceFormatter('[', ']', ',').print(printer, self)

to_obj()¶

Returns a pure Python representation of this node.

For example, a node representing a list, like graphtage.ListNode, should return a Python list. A node representing a mapping, like graphtage.MappingNode, should return a Python dict. Container nodes should recursively call TreeNode.to_obj() on all of their children.

This is used solely for the providing objects to operate on in the commandline expressions evaluation, for options like –match-if and –match-unless.

property total_size¶

The size of this node.

This is an arbitrary, immutable value that is used to calculate the bounded costs of edits on this node.

The first time this property is called, its value will be set and memoized by calling TreeNode.calculate_total_size().

Returns: An arbitrary integer representing the size of this node.
Return type: int

CSVRowFormatter¶

class graphtage.csv.CSVRowFormatter¶

Bases: graphtage.sequences.SequenceFormatter

A formatter for CSV rows.

DEFAULT_INSTANCE: Formatter[T] = <graphtage.csv.CSVRowFormatter object>¶

__init__()¶

Initializes the formatter.

Equivalent to:

super().__init__('', '', ',')

static __new__(cls, *args, **kwargs) → graphtage.formatter.Formatter[~T][T]¶

Instantiates a new formatter.

This automatically instantiates and populates Formatter.sub_formatters and sets their parent to this new formatter.

edit_print(printer: graphtage.printer.Printer, edit: graphtage.Edit)¶

Called when the edit for an item is to be printed.

If the SequenceNode being printed either is not edited or has no edits, then the edit passed to this function will be a Match(child, child, 0).

This implementation simply delegates the print to the Formatting Protocol:

self.print(printer, edit)

get_formatter(item: T) → Optional[Callable[[graphtage.printer.Printer, T], Any]]¶

Looks up a formatter for the given item using this formatter as a base.

Equivalent to:

get_formatter(item.__class__, base_formatter=self)

is_partial: bool = True¶

item_newline(printer: graphtage.printer.Printer, is_first: bool = False, is_last: bool = False)¶: An empty implementation, since each row should be printed as a single line.

items_indent(printer: graphtage.printer.Printer) → graphtage.printer.Printer ¶

Returns a Printer context with an indentation.

This is called as:

with self.items_indent(printer) as p:

immediately after the self.start_symbol is printed, but before any of the items have been printed.

This default implementation is equivalent to:

return printer.indent()

parent: Optional[Formatter[T]] = None¶

print(printer: graphtage.printer.Printer, node_or_edit: Union[TreeNode, Edit], with_edits: bool = True)¶

Prints the given node or edit.

Parameters

printer – The printer to which to write.
node_or_edit – The node or edit to print.
with_edits – If :keyword:True, print any edits associated with the node.

Note

The protocol for determining how a node or edit should be printed is very complex due to its extensibility. See the Printing Protocol for a detailed description.

print_CSVRow(*args, **kwargs)¶

Prints a CSV row.

Equivalent to:

super().print_SequenceNode(*args, **kwargs)

print_SequenceNode(printer: graphtage.printer.Printer, node: graphtage.sequences.SequenceNode)¶

Formats a sequence node.

The protocol for this function is as follows:

Print self.start_symbol
With the printer returned by self.items_indent:
- For each edit in the sequence (or just a sequence of graphtage.Match for each child, if the node is not edited):
  
  Call self.item_newline(printer, is_first=index == 0)
  
  Call self.edit_print(printer, edit)
If at least one edit was printed, then call self.item_newline(printer, is_last=True)
Print self.start_symbol

property root¶: Returns the root formatter.

sub_format_types: Sequence[Type[Formatter[T]]] = ()¶

sub_formatters: List[Formatter[T]] = []¶

CSVRows¶

class graphtage.csv.CSVRows¶

Bases: graphtage.sequences.SequenceFormatter

A sub formatter for printing the sequence of rows in a CSV file.

DEFAULT_INSTANCE: Formatter[T] = <graphtage.csv.CSVRows object>¶

__init__()¶

Initializes the formatter.

Equivalent to:

super().__init__('', '', '')

static __new__(cls, *args, **kwargs) → graphtage.formatter.Formatter[~T][T]¶

Instantiates a new formatter.

This automatically instantiates and populates Formatter.sub_formatters and sets their parent to this new formatter.

edit_print(printer: graphtage.printer.Printer, edit: graphtage.Edit)¶

Called when the edit for an item is to be printed.

If the SequenceNode being printed either is not edited or has no edits, then the edit passed to this function will be a Match(child, child, 0).

This implementation simply delegates the print to the Formatting Protocol:

self.print(printer, edit)

get_formatter(item: T) → Optional[Callable[[graphtage.printer.Printer, T], Any]]¶

Looks up a formatter for the given item using this formatter as a base.

Equivalent to:

get_formatter(item.__class__, base_formatter=self)

is_partial: bool = True¶

item_newline(printer: graphtage.printer.Printer, is_first: bool = False, is_last: bool = False)¶: Prints a newline on all but the first and last items.

items_indent(printer: graphtage.printer.Printer)¶: Returns printer because CSV rows do not need to be indented.

parent: Optional[Formatter[T]] = None¶

print(printer: graphtage.printer.Printer, node_or_edit: Union[TreeNode, Edit], with_edits: bool = True)¶

Prints the given node or edit.

Parameters

printer – The printer to which to write.
node_or_edit – The node or edit to print.
with_edits – If :keyword:True, print any edits associated with the node.

Note

The protocol for determining how a node or edit should be printed is very complex due to its extensibility. See the Printing Protocol for a detailed description.

print_CSVNode(*args, **kwargs)¶

Prints a CSV node.

Equivalent to:

super().print_SequenceNode(*args, **kwargs)

print_SequenceNode(printer: graphtage.printer.Printer, node: graphtage.sequences.SequenceNode)¶

Formats a sequence node.

The protocol for this function is as follows:

Print self.start_symbol
With the printer returned by self.items_indent:
- For each edit in the sequence (or just a sequence of graphtage.Match for each child, if the node is not edited):
  
  Call self.item_newline(printer, is_first=index == 0)
  
  Call self.edit_print(printer, edit)
If at least one edit was printed, then call self.item_newline(printer, is_last=True)
Print self.start_symbol

property root¶: Returns the root formatter.

sub_format_types: Sequence[Type[Formatter[T]]] = [<class 'graphtage.csv.CSVRowFormatter'>]¶

sub_formatters: List[Formatter[T]] = []¶

csv functions¶

build_tree¶

graphtage.csv.build_tree(path: str, allow_key_edits=True, *args, **kwargs) → graphtage.csv.CSVNode ¶

Constructs a CSVNode from a CSV file.

The file is parsed using Python’s csv.reader(). The elements in each row are constructed by delegating to graphtage.json.build_tree():

CSVRow([json.build_tree(i, allow_key_edits=allow_key_edits) for i in row])

Parameters

path – The path to the file to be parsed.
allow_key_edits – This is effectively ignored since CSV files cannot contain mappings.
*args – Any extra positional arguments are passed on to csv.reader().
**kwargs – Any extra keyword arguments are passed on to csv.reader().

Returns

The resulting CSV node object.

Return type

CSVNode