Source code for nestedtext.nestedtext

# encoding: utf8
"""
NestedText: A Human Readable and Writable Data Format

NestedText is a file format for holding structured data that is intended to be
entered, edited, or viewed by people.  It allows data to be organized into a
nested collection of itemized lists (dictionaries), ordered lists (lists), and
scalar text (strings).

It is easily created, modified, or viewed with a text editor and easily
understood and used by both programmers and non-programmers.
"""

# MIT License {{{1
# Copyright (c) 2020-2024 Ken and Kale Kundert
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

# Imports {{{1
from inform import (
    cull,
    full_stop,
    set_culprit,
    get_culprit,
    is_str,
    is_collection,
    is_mapping,
    join,
    plural,
    Error,
    Info,
)
import collections.abc
import re
import unicodedata


# Utility functions {{{1
# convert_line_terminators {{{2
def convert_line_terminators(text):
    return text.replace("\r\n", "\n").replace("\r", "\n")


# Unspecified {{{2
# class that is used as a default in functions to signal nothing was given
class _Unspecified:
    def __bool__(self):  # pragma: no cover
        return False


# OnDupCallback {{{2
class _OnDupCallback(_Unspecified):
    pass


# Exceptions {{{1
# NestedTextError {{{2
[docs]class NestedTextError(Error, ValueError): r''' The *load* and *dump* functions all raise *NestedTextError* when they discover an error. *NestedTextError* subclasses both the Python *ValueError* and the *Error* exception from *Inform*. You can find more documentation on what you can do with this exception in the `Inform documentation <https://inform.readthedocs.io/en/stable/api.html#exceptions>`_. All exceptions provide the following attributes: Attributes: args: The exception arguments. A tuple that usually contains the problematic value. template: The possibly parameterized text used for the error message. Exceptions raised by the :func:`loads()` or :func:`load()` functions provide the following additional attributes: Attributes: source: The source of the *NestedText* content, if given. This is often a filename. line: The text of the line of *NestedText* content where the problem was found. prev_line: The text of the meaningful line immediately before where the problem was found. This will not be a comment or blank line. lineno: The number of the line where the problem was found. Line numbers are zero based except when included in messages to the end user. colno: The number of the character where the problem was found on *line*. Column numbers are zero based. codicil: The line that contains the error decorated with the location of the error. The exception culprit is the tuple that indicates where the error was found. With exceptions from :func:`loads()` or :func:`load()`, the culprit consists of the source name, if available, and the line number. With exceptions from :func:`dumps()` or :func:`dump()`, the culprit consists of the keys that lead to the problematic value. As with most exceptions, you can simply cast it to a string to get a reasonable error message. .. code-block:: python >>> from textwrap import dedent >>> import nestedtext as nt >>> content = dedent(""" ... name1: value1 ... name1: value2 ... name3: value3 ... """).strip() >>> try: ... print(nt.loads(content)) ... except nt.NestedTextError as e: ... print(str(e)) 2: duplicate key: name1. 1 ❬name1: value1❭ 2 ❬name1: value2❭ You can also use the *report* method to print the message directly. This is appropriate if you are using *inform* for your messaging as it follows *inform*’s conventions:: >> try: .. print(nt.loads(content)) .. except nt.NestedTextError as e: .. e.report() error: 2: duplicate key: name1. ❬name1: value2❭ The *terminate* method prints the message directly and exits:: >> try: .. print(nt.loads(content)) .. except nt.NestedTextError as e: .. e.terminate() error: 2: duplicate key: name1. ❬name1: value2❭ With exceptions generated from :func:`load` or :func:`loads` you may see extra lines at the end of the message that show the problematic lines if you have the exception report itself as above. Those extra lines are referred to as the codicil and they can be very helpful in illustrating the actual problem. You do not get them if you simply cast the exception to a string, but you can access them using :meth:`NestedTextError.get_codicil`. The codicil or codicils are returned as a tuple. You should join them with newlines before printing them. .. code-block:: python >>> try: ... print(nt.loads(content)) ... except nt.NestedTextError as e: ... print(e.get_message()) ... print(*e.get_codicil(), sep="\n") duplicate key: name1. 1 ❬name1: value1❭ 2 ❬name1: value2❭ Note the ❬ and ❭ characters in the codicil. They delimit the extent of the text on each line and help you see troublesome leading or trailing white space. Exceptions produced by *NestedText* contain a *template* attribute that contains the basic text of the message. You can change this message by overriding the attribute using the *template* argument when using *report*, *terminate*, or *render*. *render* is like casting the exception to a string except that allows for the passing of arguments. For example, to convert a particular message to Spanish, you could use something like the following. .. code-block:: python >>> try: ... print(nt.loads(content)) ... except nt.NestedTextError as e: ... template = None ... if e.template == "duplicate key: {}.": ... template = "llave duplicada: {}." ... print(e.render(template=template)) 2: llave duplicada: name1. 1 ❬name1: value1❭ 2 ❬name1: value2❭ '''
# NotSuitableForInline {{{2 # this is only intended for internal use class NotSuitableForInline(Exception): pass # NestedText Reader {{{1 # Converts NestedText into Python data hierarchies. # constants {{{2 # regular expressions used to recognize dict items dict_item_regex = r""" (?P<key>[^\s].*?) # key (must start with non-space character) \s* # optional white space : # separator (?:\ (?P<value>.*))? # value """ dict_item_recognizer = re.compile(dict_item_regex, re.VERBOSE) # report {{{2 def report(message, line, *args, colno=None, **kwargs): message = full_stop(message) culprits = get_culprit() codicil = [kwargs.get("codicil", "")] if culprits: kwargs["source"] = culprits[0] if line: # line numbers are always 0 based unless included in a message to user include_prev_line = not ( line.prev_line is None or kwargs.pop("suppress_prev_line", False) ) if colno is not None: # build codicil that shows both the line and the preceding line if include_prev_line: codicil += [f"{line.prev_line.lineno+1:>4}{line.prev_line.text}❭"] else: codicil += [] # replace tabs with → so that arrow points to right location. text = line.text.replace("\t", "→") codicil += [ f"{line.lineno+1:>4}{text}❭", " " + (colno*" ") + "▲", ] kwargs["codicil"] = "\n".join(cull(codicil)) kwargs["colno"] = colno else: kwargs["codicil"] = f"{line.lineno+1:>4}{line.text}❭" kwargs["culprit"] = get_culprit(line.lineno + 1) kwargs["line"] = line.text kwargs["lineno"] = line.lineno if include_prev_line: kwargs["prev_line"] = line.prev_line.text else: kwargs["culprit"] = culprits # pragma: no cover raise NestedTextError(template=message, *args, **kwargs) # unrecognized_line {{{2 def unrecognized_line(line): # line will not be recognized if there is invalid white space in indentation first_non_space = line.text.lstrip(" ")[0] index_of_first_non_space = line.text.index(first_non_space) if first_non_space.strip() == "": # first non-space is a white space character # treat it as invalid indentation desc = unicodedata.name(first_non_space, "") if desc: desc = f" ({desc})" report( f"invalid character in indentation: {first_non_space!r}{desc}.", line, colno = index_of_first_non_space, codicil = "Only simple spaces are allowed in indentation." ) else: report("unrecognized line.", line, colno=index_of_first_non_space) # Lines class {{{2 class Lines: # constructor {{{3 def __init__(self, lines, support_inlines): self.lines = lines self.support_inlines = support_inlines self.generator = self.read_lines() self.first_value_line = None self.last_comment_line = None # a location is needed for the top of the data, keys = () # use the first value given, if the data is not empty # use last comment given if data is empty self.next_line = True while self.next_line: self.next_line = next(self.generator, None) if self.next_line and self.next_line.kind not in ["blank", "comment"]: return # Line class {{{3 class Line(Info): def render(self, col=None): result = [f"{self.lineno+1:>4}{self.text}❭"] if col is not None: l = len(self.text) if l < col: col = l result += [" " + (col*" ") + "▲"] return "\n".join(result) def __str__(self): return self.text def __repr__(self): return self.__class__.__name__ + f"({self.lineno+1}: ❬{self.text}❭)" # read_lines() {{{3 def read_lines(self): prev_line = None last_line = None for lineno, line in enumerate(self.lines): key = None value = None line = line.rstrip("\n") # compute indentation stripped = line.lstrip(" ") depth = len(line) - len(stripped) # determine line type and extract values if stripped == "": kind = "blank" value = None depth = None elif stripped[:1] == "#": kind = "comment" value = line[1:].strip() depth = None elif stripped == "-" or stripped.startswith("- "): kind = "list item" value = stripped[2:] elif stripped == ">" or stripped.startswith("> "): kind = "string item" value = line[depth+2:] elif stripped == ":" or stripped.startswith(": "): kind = "key item" value = line[depth+2:] elif stripped[0:1] in ["[", "{"] and self.support_inlines: tag = stripped[0:1] kind = "inline dict" if tag == "{" else "inline list" value = line[depth:] else: matches = dict_item_recognizer.fullmatch(stripped) if matches: kind = "dict item" key = matches.group("key") value = matches.group("value") if value is None: value = "" else: kind = "unrecognized" value = line # bundle information about line this_line = self.Line( text = line, lineno = lineno, kind = kind, depth = depth, key = key, value = value, prev_line = prev_line, ) if kind.endswith(" item") or kind.startswith("inline "): # Create prev_line, which differs from last_line in that it # is a copy of the line without a prev_line attribute of its # own. This avoids keeping a chain of all previous lines. # # In contrast, last_line is the actual this_line from the previous # non-blank/comment iteration prev_line = self.Line( text = this_line.text, value = this_line.value, kind = this_line.kind, depth = this_line.depth, lineno = this_line.lineno, ) # add this line as next_line in prev_line if this is a continued # multiline key or multiline string. if ( last_line and depth == last_line.depth and kind == last_line.kind and kind in ["key item", "string item"] ): last_line.next_line = this_line if kind in ['blank', 'comment']: self.last_comment_line = this_line else: last_line = this_line if not self.first_value_line: self.first_value_line = this_line yield this_line # type_of_next() {{{3e def type_of_next(self): if self.next_line: return self.next_line.kind # still_within_level() {{{3 def still_within_level(self, depth): if self.next_line: return self.next_line.depth >= depth # still_within_string() {{{3 def still_within_string(self, depth): if self.next_line: return ( self.next_line.kind == "string item" and self.next_line.depth >= depth ) # still_within_key() {{{3 def still_within_key(self, depth): return ( self.next_line.kind == "key item" and self.next_line.depth == depth ) # depth_of_next() {{{3 def depth_of_next(self): if self.next_line: return self.next_line.depth return 0 # get_next() {{{3 def get_next(self): line = self.next_line if line.kind == "unrecognized": unrecognized_line(line) # queue up the next useful line # this is needed so type_of_next() and still_within_level() can easily # access the next line that contains actual data. self.next_line = next(self.generator, None) while self.next_line and self.next_line.kind in ["blank", "comment"]: self.next_line = next(self.generator, None) return line # indentation_error {{{3 def indentation_error(self, line, depth): assert line.depth != depth prev_line = line.prev_line codicil = None if not line.prev_line and depth == 0: msg = "top-level content must start in column 1." elif ( prev_line and prev_line.value and prev_line.depth < line.depth and prev_line.kind in ["list item", "dict item"] ): if prev_line.value.strip() == "": obs = ", which in this case consists only of whitespace" else: obs = "" msg = "invalid indentation." codicil = join( "An indent may only follow a dictionary or list item that does", f"not already have a value{obs}.", wrap = True ) elif prev_line and prev_line.depth > line.depth: msg = "invalid indentation, partial dedent." else: msg = "invalid indentation." report(join(msg, wrap=True), line, colno=depth, codicil=codicil) # KeyPolicy class {{{2 # Used to hold and implement the on_dup policy for dictionaries. class KeyPolicy: @classmethod def set_policy(cls, on_dup): if callable(on_dup): # if on_dup is a function, convert it to a data structure that will # hold state during the load on_dup = {_OnDupCallback: on_dup} cls.on_dup = on_dup @classmethod def process_duplicate(cls, dictionary, key, keys, line=None, colno=None): if cls.on_dup is None or cls.on_dup == "error": report("duplicate key: {}.", line, key, colno=colno) if cls.on_dup == "ignore": return None if isinstance(cls.on_dup, dict): dup_handler = cls.on_dup.pop(_OnDupCallback) cls.on_dup.update( dict(dictionary=dictionary, keys=keys) ) try: key = dup_handler(key=key, state=cls.on_dup) if key is None: return None except KeyError: report("duplicate key: {}.", line, key, colno=colno) cls.on_dup[_OnDupCallback] = dup_handler # restore dup_handler elif cls.on_dup != "replace": # pragma: no cover raise AssertionError( f"{cls.on_dup}: unexpected value for on_dup." ) from None return key # Location class {{{2
[docs]class Location: """Holds information about the location of a token. Returned from :func:`load` and :func:`loads` as the values in a *keymap*. Objects of this class holds the line and column numbers of the key and value tokens. """ def __init__(self, line=None, col=None, key_line=None, key_col=None): self.line = line self.key_line = key_line self.col = col self.key_col = key_col def __repr__(self): components = [] components.append(f"lineno={self.line.lineno}") components.append(f"colno={self.col}") key_line = self.key_line if key_line is None: key_line = self.line components.append(f"key_lineno={key_line.lineno}") key_col = self.key_col if key_col is None: key_col = self.col components.append(f"key_colno={key_col}") return f"{self.__class__.__name__}({', '.join(components)})" # as_tuple() {{{3
[docs] def as_tuple(self, kind="value"): """ Returns the location of either the value or the key token as a tuple that contains the line number and the column number. The line and column numbers are 0 based. Args: kind: Specify either “key” or “value” depending on which token is desired. """ if kind == "key": line = self.key_line col = self.key_col if line is None: line = self.line if col is None: col = self.col else: assert kind == "value" line = self.line col = self.col return line.lineno, col
# as_line() {{{3
[docs] def as_line(self, kind="value", offset=0): """ Returns a string containing two lines that identify the token in context. The first line contains the line number and text of the line that contains the token. The second line contains a pointer to the token. Args: kind: Specify either “key” or “value” depending on which token is desired. offset: If *offset* is None, the error pointer is not added to the line. If *offset* is an integer, the pointer is moved to the right by this many characters. The default is 0. If *offset* is a tuple, it must have two values. The first is the row offset and the second is the column offset. This is useful for annotating errors in multiline strings. Raises: *IndexError* if row offset is out of range. """ # get the line and the column number of the key or value if kind == "key": line = self.key_line col = self.key_col if line is None: line = self.line if col is None: col = self.col else: assert kind == "value" line = self.line col = self.col if not line: # this occurs if input is completely empty return "" # process the offset if offset is None: return line.render() col_offset = offset try: row_offset, col_offset = offset while row_offset > 0: line = line.next_line row_offset -= 1 if line is None: raise IndexError(offset[0]) except TypeError: pass return line.render(col + col_offset)
# get_line_numbers() {{{3
[docs] def get_line_numbers(self, kind="value", sep=None): """ Returns the line numbers of a token either as a pair of integers or as a string. Args: kind: Specify either “key” or “value” depending on which token is desired. sep: The separator string. If given a string is returned and *sep* is inserted between two line numbers. In this case the line numbers start at 1. If *sep* is not given, a tuple of integers is returned. In this case the line numbers start at 0, but the second number returned is the last line number plus 1. This form is suitable to use with the Python slice function to extract the lines from the *NestedText* source. """ if kind == "key": line = self.key_line if line is None: line = self.line else: assert kind == "value" line = self.line # find line numbers first_lineno = line.lineno while line: last_lineno = line.lineno line = line.next_line if sep is None: return (first_lineno, last_lineno + 1) if first_lineno != last_lineno: return join(first_lineno+1, last_lineno+1, sep=sep) return str(first_lineno+1)
# _get_original_key() {{{3 def _get_original_key(self, key, strict): try: line = self.key_line if line.kind == "key item": # is multiline key (key fragment is actually held in line.text) key_frags = [line.text[line.depth+2:]] while line.next_line: line = line.next_line key_frags.append(line.text[line.depth+2:]) key = "\n".join(key_frags) else: if line.kind != "list item": key = line.key return key except AttributeError: # this occurs for list indexes return key
# Inline class {{{2 class Inline: # a recursive descent parser to interpret inline lists and dictionaries # constructor() {{{3 def __init__(self, line, keys, loader): self.line = line self.loader = loader self.text = line.value self.max_index = len(self.text) self.starting_col = line.depth try: self.values, self.keymap, index = self.parse_inline_value(keys, 0) except IndexError: self.inline_error("line ended without closing delimiter", self.max_index) if index < self.max_index: extra = self.text[index:] self.inline_error( f"extra {plural(extra):character} after closing delimiter: ‘{{}}’.", index, extra ) assert index == self.max_index # parse_inline_value() {{{3 def parse_inline_value(self, keys, index, forbidden_chars=None): if self.text[index] == "{": return self.parse_inline_dict(keys, index) elif self.text[index] == "[": return self.parse_inline_list(keys, index) else: return self.parse_inline_str(keys, index, forbidden_chars) # parse_inline_dict() {{{3 def parse_inline_dict(self, keys, index): starting_index = index assert self.text[index] == "{" index += 1 values = {} need_another = False while self.text[index] != "}": prev_index = index orig_key, value, location, index = self.parse_inline_dict_item(keys, index) key = self.loader.normalize_key(orig_key, keys) if key in values: key = KeyPolicy.process_duplicate(values, key, keys, self.line, prev_index) if key is not None: values[key] = value self.loader._add_keymap(keys + (key,), location) need_another = False if self.text[index] not in ",}": self.inline_error( "expected ‘,’ or ‘}}’, found ‘{}’", index, self.text[index] ) if self.text[index] == ",": index += 1 need_another = True if need_another: self.inline_error("expected value", index) return ( values, self.location(starting_index), self.adjust_index(index+1) ) # parse_inline_dict_item() {{{3 def parse_inline_dict_item(self, keys, index): forbidden_chars = "{}[],:" key_index = self.adjust_index(index) if self.text[index] in forbidden_chars: key = "" else: key, _, index = self.parse_inline_value(keys, index, forbidden_chars) if self.text[index] != ":": self.inline_error( "expected ‘:’, found ‘{}’", index, self.text[index], culprit=key ) index = self.adjust_index(index+1) if self.text[index] in ",}": value = "" loc = self.location(index) else: value, loc, index = self.parse_inline_value(keys, index, forbidden_chars) self.add_key_location(loc, key_index) return key, value, loc, index # parse_inline_list() {{{3 def parse_inline_list(self, keys, index): forbidden_chars = "{}[]," starting_index = index assert self.text[index] == "[" index += 1 # handle empty list if self.text[index] == "]": return [], self.location(starting_index), self.adjust_index(index+1) key = 0 values = [] value = "" loc = self.location(index) while True: new_keys = keys + (key,) c = self.text[index] if c in ",]": values.append(value) self.loader._add_keymap(new_keys, loc) key += 1 if c == "]": return ( values, self.location(starting_index), self.adjust_index(index+1) ) index += 1 loc = self.location(index) index = self.adjust_index(index) value = "" elif value: self.inline_error( "expected ‘,’ or ‘]’, found ‘{}’", index, self.text[index] ) elif c in "}],": self.inline_error("expected value", index) else: value, loc, index = self.parse_inline_value( new_keys, index, forbidden_chars ) # parse_inline_str() {{{3 def parse_inline_str(self, keys, index, forbidden_chars): starting_index = index while self.text[index] not in forbidden_chars: index = self.adjust_index(index+1) value = self.text[starting_index:index].strip() return value, self.location(starting_index), index # adjust_index() {{{3 def adjust_index(self, index): # if desired index points to white space, shift right until it doesn’t while index < self.max_index and self.text[index] in " \t": index += 1 return index # location() {{{3 def location(self, index, **kwargs): kwargs["line"] = self.line return Location(col=index + self.starting_col, **kwargs) # add_key_location() {{{3 def add_key_location(self, loc, key_index): loc.key_col = key_index + self.starting_col # inline_error {{{3 def inline_error(self, message, index, *args, culprit=None, **kwargs): report( full_stop(message), self.line, *args, colno = index + self.starting_col, culprit = culprit, suppress_prev_line = True, **kwargs, ) # get_values() {{{3 def get_values(self): return self.values, self.keymap # render {{{3 def render(self, index): # pragma: no cover return f"❬{self.text}\n {index*' '}▲" # __repr__ {{{3 def __repr__(self): # pragma: no cover name = self.__class__.__name__ return f"{name}({self.text!r})" # NestedTextLoader class {{{2 class NestedTextLoader: # __init__() {{{3 def __init__(self, lines, top, source, on_dup, keymap, normalize_key, dialect): KeyPolicy.set_policy(on_dup) self.source = source self.keymap = keymap assert self.keymap is None or is_mapping(self.keymap) self.normalize_key = normalize_key if normalize_key else lambda k, ks: k if dialect and "i" in dialect: support_inlines = False else: support_inlines = True with set_culprit(source): lines = self.lines = Lines(lines, support_inlines) if keymap is not None: # add a location for the top-level of the data set if lines.first_value_line: keymap[()] = Location(line=lines.first_value_line, col=0) else: keymap[()] = Location(line=lines.last_comment_line, col=0) next_is = lines.type_of_next() if top in ["any", any]: if next_is is None: self.values, self.keymap = None, None else: self.values, self.keymap = self._read_value(0, ()) elif top in ["dict", dict]: if next_is in ["dict item", "key item", "inline dict"]: self.values, self.keymap = self._read_value(0, ()) elif next_is is None: self.values, self.keymap = {}, None else: report( "content must start with key or brace ({{).", lines.get_next() ) elif top in ["list", list]: if next_is in ["list item", "inline list"]: self.values, self.keymap = self._read_value(0, ()) elif next_is is None: self.values, self.keymap = [], None else: report( "content must start with dash (-) or bracket ([).", lines.get_next(), ) elif top in ["str", str]: if next_is == "string item": self.values, self.keymap = self._read_value(0, ()) elif next_is is None: self.values, self.keymap = "", None else: report( "content must start with greater-than sign (>).", lines.get_next(), ) else: raise NotImplementedError(top) if lines.type_of_next(): report('extra content', lines.get_next()) # get_decoded() {{{3 def get_decoded(self): return self.values # # get_keymap() {{{3 # this method becomes useful when an interface that returns the loader develops # def get_keymap(self): # return self.keymap # # get_source() {{{3 # this method becomes useful when an interface that returns the loader develops # def get_source(self): # return self.source # # get_value() {{{3 # this method becomes useful when an interface that returns the loader develops # def get_value(self, keys): # """ # Return the value associated with a set of keys. # """ # value = self.values # key = None # keys_used = () # try: # for key in keys: # keys_used += (key,) # value = value[key] # except (KeyError, IndexError) as e: # raise NestedTextError( # key, template=f"key not found ({}).", culprit=keys_used # ) # return value # _add_keymap() {{{3 def _add_keymap(self, keys, location): if self.keymap is not None: self.keymap[keys] = location # _read_value() {{{3 def _read_value(self, depth, keys): lines = self.lines if lines.type_of_next() == "list item": return self._read_list(depth, keys) if lines.type_of_next() in ["dict item", "key item"]: return self._read_dict(depth, keys) if lines.type_of_next() == "string item": return self._read_string(depth, keys) if lines.type_of_next() in ["inline dict", "inline list"]: return self._read_inline(keys) unrecognized_line(lines.get_next()) # _read_list() {{{3 def _read_list(self, depth, keys): lines = self.lines values = [] index = 0 first_line = lines.next_line while lines.still_within_level(depth): line = lines.get_next() if line.depth != depth: lines.indentation_error(line, depth) if line.kind != "list item": report("expected list item.", line, colno=depth) new_keys = keys + (index,) if line.value: values.append(line.value) self._add_keymap( new_keys, Location(line=line, key_col=depth, col=depth + 2) ) else: # value may simply be empty, or it may be on next line, in which # case it must be indented. depth_of_next = lines.depth_of_next() if depth_of_next > depth: value, loc = self._read_value(depth_of_next, new_keys) loc.key_line = line loc.key_col = depth else: value = "" loc = Location(line=line, key_col=depth, col=depth + 1) values.append(value) self._add_keymap(new_keys, loc) index += 1 return values, Location(line=first_line, col=first_line.depth) # _read_dict() {{{3 def _read_dict(self, depth, keys): lines = self.lines values = {} first_line = lines.next_line # process all items in dictionary while lines.still_within_level(depth): line = lines.get_next() key_line = line key_col = depth # error checking if line.depth != depth: lines.indentation_error(line, depth) if line.kind not in ["dict item", "key item"]: report("expected dictionary item.", line, colno=depth) # process key if line.kind == "key item": # multiline key original_key = self._read_key(line, depth) value = None else: # key and value on a single line original_key = line.key value = line.value key = self.normalize_key(original_key, keys) if key in values: # found duplicate key key = KeyPolicy.process_duplicate(values, key, keys, line, depth) if key is None: continue new_keys = keys + (key,) # process value if value: # this is a single-line item, value was found above loc = Location(line=line, col=depth + len(key) + 2) else: # value is on subsequent lines depth_of_next = lines.depth_of_next() if depth_of_next > depth: # read indented values value, loc = self._read_value(depth_of_next, new_keys) elif line.kind == "dict item": # found the next key in this dictionary, so value is empty value = "" loc = Location(line=line, col=depth + len(key) + 1) else: report("multiline key requires a value.", line, None, colno=depth) values[key] = value loc.key_line = key_line loc.key_col = key_col self._add_keymap(new_keys, loc) return values, Location(line=first_line, col=first_line.depth) # _read_key() {{{3 def _read_key(self, line, depth): lines = self.lines data = [line.value] while lines.still_within_key(depth): line = lines.get_next() data.append(line.value) return "\n".join(data) # _read_string() {{{3 def _read_string(self, depth, keys): lines = self.lines data = [] loc = Location(line=lines.next_line, key_col=depth) while lines.still_within_string(depth): line = lines.get_next() data.append(line.value) if line.depth != depth: lines.indentation_error(line, depth) value = "\n".join(data) loc.col = depth + (2 if value else 1) return value, loc # _read_inline() {{{3 def _read_inline(self, keys): lines = self.lines line = lines.get_next() return Inline(line, keys, self).get_values() # loads {{{2
[docs]def loads( content, top = "dict", *, source = None, on_dup = None, keymap = None, normalize_key = None, dialect = None ): # description {{{3 r''' Loads *NestedText* from string. Args: content (str): String that contains encoded data. top (str): Top-level data type. The NestedText format allows for a dictionary, a list, or a string as the top-level data container. By specifying top as “dict”, “list”, or “str” you constrain both the type of top-level container and the return value of this function. By specifying “any” you enable support for all three data types, with the type of the returned value matching that of top-level container in content. As a short-hand, you may specify the *dict*, *list*, *str*, and *any* built-ins rather than specifying *top* with a string. source (str or Path): If given, this string is attached to any error messages as the culprit. It is otherwise unused. Is often the name of the file that originally contained the NestedText content. on_dup (str or func): Indicates how duplicate keys in dictionaries should be handled. Specifying "error" causes them to raise exceptions (the default behavior). Specifying "ignore" causes them to be ignored (first wins). Specifying "replace" results in them replacing earlier items (last wins). By specifying a function, the keys can be de-duplicated. This call-back function returns a new key and takes two arguments: key: The new key (duplicates an existing key). state: A dictionary containing other possibly helpful information: dictionary: The entire dictionary as it is at the moment the duplicate key is found. You should not change it. keys: The keys that identify the dictionary. This dictionary is created as *loads* is called and deleted as it returns. Any values placed in it are retained and available on subsequent calls to this function during the load operation. This function should return a new key. If the key duplicates an existing key, the value associated with that key is replaced. If *None* is returned, this key is ignored. If a *KeyError* is raised, the duplicate key is reported as an error. Be aware that key de-duplication occurs after key normalization. As such you should generate keys during de-duplication that are consistent with your normalization scheme. keymap (dict): Specify an empty dictionary or nothing at all for the value of this argument. If you give an empty dictionary it will be filled with location information for the values that are returned. Upon return the dictionary maps a tuple containing the keys for the value of interest to the location of that value in the *NestedText* source document. The location is contained in a :class:`Location` object. You can access the line and column number using the :meth:`Location.as_tuple` method, and the line that contains the value annotated with its location using the :meth:`Location.as_line` method. normalize_key (func): A function that takes two arguments; the original key for a value and the tuple of normalized keys for its parent values. It then transforms the given key into the desired normalized form. Only called on dictionary keys, so the key will always be a string. dialect (str): Specifies support for particular variations in *NestedText*. In general you are discouraged from using a dialect as it can result in *NestedText* documents that are not compliant with the standard. The following deviant dialects are supported. *support inlines*: If "i" is included in *dialect*, support for inline lists and dictionaries is dropped. The default is "I", which enables support for inlines. The main effect of disabling inlines in the load functions is that keys may begin with ``[`` or ``{``. Returns: The extracted data. The type of the return value is specified by the top argument. If top is “any”, then the return value will match that of top-level data container in the input content. If content is empty, an empty data value of the type specified by top is returned. If top is “any” None is returned. Raises: NestedTextError: if there is a problem in the *NextedText* document. Examples: A *NestedText* document is specified to *loads* in the form of a string: .. code-block:: python >>> import nestedtext as nt >>> contents = """ ... name: Kristel Templeton ... gender: female ... age: 74 ... """ >>> try: ... data = nt.loads(contents, "dict") ... except nt.NestedTextError as e: ... e.terminate() >>> print(data) {'name': 'Kristel Templeton', 'gender': 'female', 'age': '74'} *loads()* takes an optional argument, *source*. If specified, it is added to any error messages. It is often used to designate the source of *NestedText* document. For example, if *contents* were read from a file, *source* would be the file name. Here is a typical example of reading *NestedText* from a file: .. code-block:: python >>> filename = "examples/duplicate-keys.nt" >>> try: ... with open(filename, encoding="utf-8") as f: ... addresses = nt.loads(f.read(), source=filename) ... except nt.NestedTextError as e: ... print(e.render()) examples/duplicate-keys.nt, 5: duplicate key: name. 4 ❬name:❭ 5 ❬name:❭ Notice in the above example the encoding is explicitly specified as "utf-8". *NestedText* files should always be read and written using *utf-8* encoding. The following examples demonstrate the various ways of handling duplicate keys: .. code-block:: python >>> content = """ ... key: value 1 ... key: value 2 ... key: value 3 ... name: value 4 ... name: value 5 ... """ >>> print(nt.loads(content)) Traceback (most recent call last): ... nestedtext.nestedtext.NestedTextError: 3: duplicate key: key. 2 ❬key: value 1❭ 3 ❬key: value 2❭ >>> print(nt.loads(content, on_dup="ignore")) {'key': 'value 1', 'name': 'value 4'} >>> print(nt.loads(content, on_dup="replace")) {'key': 'value 3', 'name': 'value 5'} >>> def de_dup(key, state): ... if key not in state: ... state[key] = 1 ... state[key] += 1 ... return f"{key} — #{state[key]}" >>> print(nt.loads(content, on_dup=de_dup)) {'key': 'value 1', 'key — #2': 'value 2', 'key — #3': 'value 3', 'name': 'value 4', 'name — #2': 'value 5'} ''' # code {{{3 lines = convert_line_terminators(content).split("\n") loader = NestedTextLoader( lines, top, source, on_dup, keymap, normalize_key, dialect ) return loader.get_decoded()
# load {{{2
[docs]def load( f, top = "dict", *, source = None, on_dup = None, keymap = None, normalize_key = None, dialect = None ): # description {{{3 r""" Loads *NestedText* from file or stream. Is the same as :func:`loads` except the *NextedText* is accessed by reading a file rather than directly from a string. It does not keep the full contents of the file in memory and so is more memory efficient with large files. Args: f (str, os.PathLike, io.TextIOBase, collections.abc.Iterator): The file to read the *NestedText* content from. This can be specified either as a path (e.g. a string or a `pathlib.Path`), as a text IO object (e.g. an open file, or 0 for stdin), or as an iterator. If a path is given, the file will be opened, read, and closed. If an IO object is given, it will be read and not closed; utf-8 encoding should be used.. If an iterator is given, it should generate full lines in the same manner that iterating on a file descriptor would. kwargs: See :func:`loads` for optional arguments. Returns: The extracted data. See :func:`loads` description of the return value. Raises: NestedTextError: if there is a problem in the *NextedText* document. OSError: if there is a problem opening the file. Examples: Load from a path specified as a string: .. code-block:: python >>> import nestedtext as nt >>> print(open("examples/groceries.nt").read()) groceries: - Bread - Peanut butter - Jam <BLANKLINE> >>> nt.load("examples/groceries.nt") {'groceries': ['Bread', 'Peanut butter', 'Jam']} Load from a `pathlib.Path`: .. code-block:: python >>> from pathlib import Path >>> nt.load(Path("examples/groceries.nt")) {'groceries': ['Bread', 'Peanut butter', 'Jam']} Load from an open file object: .. code-block:: python >>> with open("examples/groceries.nt") as f: ... nt.load(f) ... {'groceries': ['Bread', 'Peanut butter', 'Jam']} """ # code {{{3 # Do not invoke the read method as that would read in the entire contents of # the file, possibly consuming a lot of memory. Instead pass the file # pointer into loader, it will iterate through the lines, discarding # them once they are no longer needed, which reduces the memory usage. if isinstance(f, collections.abc.Iterator): if not source: source = getattr(f, "name", None) loader = NestedTextLoader( f, top, source, on_dup, keymap, normalize_key, dialect ) return loader.get_decoded() else: if not source: if f == 0: source = '<stdin>' else: source = str(f) with open(f, encoding="utf-8") as fp: loader = NestedTextLoader( fp, top, source, on_dup, keymap, normalize_key, dialect ) return loader.get_decoded()
# NestedText Writer {{{1 # Converts Python data hierarchies to NestedText. # add_leader {{{2 def add_leader(s, leader): # split into separate lines # add leader to each non-blank line # add right-stripped leader to each blank line # rejoin and return return "\n".join( leader + line if line else leader.rstrip() for line in s.split("\n") ) # add_prefix {{{2 def add_prefix(prefix, suffix): # A simple formatting of dict and list items will result in a space # after the colon or dash if the value is placed on next line. # This, function simply eliminates that space. if not suffix or suffix.startswith("\n"): return prefix + suffix return prefix + " " + suffix # grow {{{2 # add object to end of a tuple def grow(base, ext): return base + (ext,) # NestedTextDumper class {{{2 class NestedTextDumper: # constructor {{{3 def __init__( self, width, inline_level, sort_keys, indent, converters, default, map_keys, dialect ): assert indent > 0 self.width = width self.inline_level = inline_level self.indent = indent self.converters = converters self.map_keys = map_keys self.default = default self.support_inlines = True if dialect and "i" in dialect: self.support_inlines = False # define key sorting function {{{4 if sort_keys: if callable(sort_keys): def sort(items, keys): return sorted(items, key=lambda k: sort_keys(k, keys)) else: def sort(items, keys): return sorted(items) else: def sort(items, keys): return items self.sort = sort # define object type identification functions {{{4 if default == "strict": self.is_a_dict = lambda obj: isinstance(obj, dict) self.is_a_list = lambda obj: isinstance(obj, list) self.is_a_str = lambda obj: isinstance(obj, str) self.is_a_scalar = lambda obj: False else: self.is_a_dict = is_mapping self.is_a_list = is_collection self.is_a_str = is_str self.is_a_scalar = lambda obj: obj is None or isinstance(obj, (bool, int, float)) if is_str(default): raise NotImplementedError(default) # pragma: no cover # render_key {{{3 def render_key(self, key, keys): key = self.convert(key, keys) if self.is_a_scalar(key): if key is None: key = "" else: key = str(key) if not self.is_a_str(key) and callable(self.default): key = self.default(key) if not self.is_a_str(key): raise NestedTextError( key, template="keys must be strings.", culprit=keys ) from None return convert_line_terminators(key) # render_dict_item {{{3 def render_dict_item(self, key, value, keys, values): multiline_key_required = ( not key or "\n" in key or key.strip() != key or key[:1] == "#" or (key[:1] in "[{" and self.support_inlines) or key[:2] in ["- ", "> ", ": "] or ": " in key ) if multiline_key_required: key = "\n".join(": "+l if l else ":" for l in key.split("\n")) if self.is_a_dict(value) or self.is_a_list(value): return key + self.render_value(value, keys, values) if is_str(value): # force use of multiline value with multiline keys value = convert_line_terminators(value) else: value = self.render_value(value, keys, values) return key + "\n" + add_leader(value, self.indent*" " + "> ") else: return add_prefix(key + ":", self.render_value(value, keys, values)) # render_inline_value {{{3 def render_inline_value(self, obj, exclude, keys, values): obj = self.convert(obj, keys) if self.is_a_dict(obj): return self.render_inline_dict(obj, keys, values) if self.is_a_list(obj): return self.render_inline_list(obj, keys, values) return self.render_inline_scalar(obj, exclude, keys, values) # render_inline_dict {{{3 def render_inline_dict(self, obj, keys, values): exclude = set("\n\r[]{}:,") rendered = [] for k, v in obj.items(): new_keys = grow(keys, k) new_values = grow(values, id(v)) key = self.render_key(k, new_keys) mapped_key = self.map_key(key, new_keys) v = obj[k] rendered_value = self.render_inline_value( v, exclude, new_keys, new_values ) rendered_key = self.render_inline_scalar( mapped_key, exclude, new_keys, new_values ) rendered.append((mapped_key, key, f"{rendered_key}: {rendered_value}",)) items = [v for mk, k, v in self.sort(rendered, keys)] return ''.join(["{", ", ".join(items), "}"]) # render_inline_list {{{3 def render_inline_list(self, obj, keys, values): rendered_values = [] for i, v in enumerate(obj): rendered_value = self.render_inline_value( v, set("\n\r[]{},"), grow(keys, i), grow(values, id(v)) ) rendered_values.append(rendered_value) if len(rendered_values) == 1 and not rendered_values[0]: return "[ ]" content = ", ".join(rendered_values) leading_delimiter = "[ " if content[0:1] == "," else "[" return leading_delimiter + content + "]" # render_inline_scalar {{{3 def render_inline_scalar(self, obj, exclude, keys, values): obj = self.convert(obj, keys) if self.is_a_str(obj): value = obj elif self.is_a_scalar(obj): value = "" if obj is None else str(obj) elif self.default and callable(self.default): try: obj = self.default(obj) except TypeError: raise NestedTextError( obj, template = f"unsupported type ({type(obj).__name__}).", culprit = keys ) from None return self.render_inline_value(obj, exclude, keys, values) else: raise NotSuitableForInline from None if exclude & set(value): raise NotSuitableForInline from None if value.strip() != value: raise NotSuitableForInline from None return value # render value {{{3 def render_value(self, obj, keys, values): level = len(keys) error = None content = "" obj = self.convert(obj, keys) need_indented_block = is_collection(obj) if self.is_a_dict(obj): self.check_for_cyclic_reference(obj, keys, values) try: if not self.support_inlines: raise NotSuitableForInline from None if level < self.inline_level: raise NotSuitableForInline from None if obj and (self.width <= 0 or len(obj) > self.width/5): raise NotSuitableForInline from None content = self.render_inline_dict(obj, keys, values) if obj and (len(content) > self.width): raise NotSuitableForInline from None except NotSuitableForInline: rendered = [] for k, v in obj.items(): new_keys = grow(keys, k) new_values = grow(values, id(v)) key = self.render_key(k, new_keys) mapped_key = self.map_key(key, new_keys) rendered_value = self.render_dict_item( mapped_key, obj[k], new_keys, new_values ) rendered.append((mapped_key, key, rendered_value)) content = "\n".join(v for mk, k, v in self.sort(rendered, keys)) elif self.is_a_list(obj): self.check_for_cyclic_reference(obj, keys, values) try: if not self.support_inlines: raise NotSuitableForInline from None if level < self.inline_level: raise NotSuitableForInline from None if obj and (self.width <= 0 or len(obj) > self.width/3): raise NotSuitableForInline from None content = self.render_inline_list(obj, keys, values) if obj and (len(content) > self.width): raise NotSuitableForInline from None except NotSuitableForInline: content = [] for i, v in enumerate(obj): v = self.render_value(v, grow(keys, i), grow(values, id(v))) content.append(add_prefix("-", v)) content = "\n".join(content) elif self.is_a_str(obj): text = convert_line_terminators(obj) if "\n" in text or level == 0: content = add_leader(text, "> ") need_indented_block = True else: content = text elif self.is_a_scalar(obj): if obj is None: content = "" else: content = str(obj) if level == 0: content = add_leader(content, "> ") need_indented_block = True elif self.default and callable(self.default): try: obj = self.default(obj) except TypeError: error = f"unsupported type ({type(obj).__name__})." else: content = self.render_value(obj, keys, values) else: error = f"unsupported type ({type(obj).__name__})." if need_indented_block and content and level: content = "\n" + add_leader(content, self.indent*" ") if error: raise NestedTextError(obj, template=error, culprit=keys) from None return content # check_for_cyclic_reference {{{3 def check_for_cyclic_reference(self, obj, keys, values): if id(obj) in values[:-1]: raise NestedTextError( obj, template="circular reference.", culprit=keys ) # convert {{{3 # apply externally supplied converter to convert value to string def convert(self, obj, keys): converters = self.converters converter = getattr(obj, "__nestedtext_converter__", None) converter = converters.get(type(obj)) if converters else converter if converter: try: return converter(obj) except TypeError: # is bound method return converter() elif converter is False: raise NestedTextError( obj, template = f"unsupported type ({type(obj).__name__}).", culprit = keys, ) from None return obj # map_key {{{3 # apply externally supplied mapping to convert key to desired form def map_key(self, key, keys): mapper = self.map_keys if not mapper: return key if callable(mapper): new_key = mapper(key, keys[:-1]) if new_key is None: return key return new_key elif is_mapping(mapper): try: loc = mapper.get(keys) if loc: return loc._get_original_key(key, strict=False) else: return key except AttributeError: # pragma: no cover raise AssertionError( "if map_keys is a dictionary, it must be a keymap" ) from None else: # pragma: no cover raise AssertionError( "map_keys must be a callable or a dictionary" ) from None # dumps {{{2
[docs]def dumps( obj, *, width = 0, inline_level = 0, sort_keys = False, indent = 4, converters = None, map_keys = None, default = None, dialect = None ): # description {{{3 '''Recursively convert object to *NestedText* string. Args: obj: The object to convert to *NestedText*. width (int): Enables inline lists and dictionaries if greater than zero and if resulting line would be less than or equal to given width. inline_level (int): Recursion depth must be equal to this value or greater to be eligible for inlining. sort_keys (bool or func): Dictionary items are sorted by their key if *sort_keys* is *True*. In this case, keys at all level are sorted alphabetically. If *sort_keys* is *False*, the natural order of dictionaries is retained. If a function is passed in, it is expected to return the sort key. The function is passed two tuples, each consists only of strings. The first contains the mapped key, the original key, and the rendered item. So it takes the form:: ('<mapped_key>', '<orig_key>', '<mapped_key>: <value>') The second contains the keys of the parent. indent (int): The number of spaces to use to represent a single level of indentation. Must be one or greater. converters (dict): A dictionary where the keys are types and the values are converter functions (functions that take an object and return it in a form that can be processed by *NestedText*). If a value is False, an unsupported type error is raised. An object may provide its own converter by defining the ``__nestedtext_converter__`` attribute. It may be False, or it may be a method that converts the object to a supported data type for *NestedText*. A matching converter specified in the *converters* argument dominates over this attribute. default (func or “strict”): The default converter. Use to convert otherwise unrecognized objects to a form that can be processed. If not provided an error will be raised for unsupported data types. Typical values are *repr* or *str*. If “strict” is specified then only dictionaries, lists, strings, and those types that have converters are allowed. If *default* is not specified then a broader collection of value types are supported, including *None*, *bool*, *int*, *float*, and *list*- and *dict*-like objects. In this case Booleans are rendered as “True” and “False” and None is rendered as an empty string. If *default* is a function, it acts as the default converter. If it raises a TypeError, the value is reported as an unsupported type. map_keys (func or keymap): This argument is used to modify the way keys are rendered. It may be a keymap that was created by :func:`load` or :func:`loads`, in which case keys are rendered into their original form, before any normalization or de-duplication was performed by the load functions. It may also be a function that takes two arguments: the key after any needed conversion has been performed, and the tuple of parent keys. The value returned is used as the key and so must be a string. If no value is returned, the key is not modified. dialect (str): Specifies support for particular variations in *NestedText*. In general you are discouraged from using a dialect as it can result in *NestedText* documents that are not compliant with the standard. The following deviant dialects are supported. *support inlines*: If "i" is included in *dialect*, support for inline lists and dictionaries is dropped. The default is "I", which enables support for inlines. The main effect of disabling inlines in the dump functions is that empty lists and dictionaries are output using an empty value, which is normally interpreted by *NestedText* as an empty string. Returns: The *NestedText* content without a trailing newline. *NestedText* files should end with a newline, but unlike :func:`dump`, this function does not output that newline. You will need to explicitly add that newline when writing the output :func:`dumps` to a file. Raises: NestedTextError: if there is a problem in the input data. Examples: .. code-block:: python >>> import nestedtext as nt >>> data = { ... "name": "Kristel Templeton", ... "gender": "female", ... "age": "74", ... } >>> try: ... print(nt.dumps(data)) ... except nt.NestedTextError as e: ... print(str(e)) name: Kristel Templeton gender: female age: 74 The *NestedText* format only supports dictionaries, lists, and strings. By default, *dumps* is configured to be rather forgiving, so it will render many of the base Python data types, such as *None*, *bool*, *int*, *float* and list-like types such as *tuple* and *set* by converting them to the types supported by the format. This implies that a round trip through *dumps* and *loads* could result in the types of values being transformed. You can restrict *dumps* to only supporting the native types of *NestedText* by passing `default="strict"` to *dumps*. Doing so means that values that are not dictionaries, lists, or strings generate exceptions. .. code-block:: python >>> data = {"key": 42, "value": 3.1415926, "valid": True} >>> try: ... print(nt.dumps(data)) ... except nt.NestedTextError as e: ... print(str(e)) key: 42 value: 3.1415926 valid: True >>> try: ... print(nt.dumps(data, default="strict")) ... except nt.NestedTextError as e: ... print(str(e)) key: unsupported type (int). Alternatively, you can specify a function to *default*, which is used to convert values to recognized types. It is used if no suitable converter is available. Typical values are *str* and *repr*. .. code-block:: python >>> class Color: ... def __init__(self, color): ... self.color = color ... def __repr__(self): ... return f"Color({self.color!r})" ... def __str__(self): ... return self.color >>> data["house"] = Color("red") >>> print(nt.dumps(data, default=repr)) key: 42 value: 3.1415926 valid: True house: Color('red') >>> print(nt.dumps(data, default=str)) key: 42 value: 3.1415926 valid: True house: red If *Color* is consistently used with *NestedText*, you can include the converter in *Color* itself. .. code-block:: python >>> class Color: ... def __init__(self, color): ... self.color = color ... def __nestedtext_converter__(self): ... return self.color.title() >>> data["house"] = Color("red") >>> print(nt.dumps(data)) key: 42 value: 3.1415926 valid: True house: Red You can also specify a dictionary of converters. The dictionary maps the object type to a converter function. .. code-block:: python >>> class Info: ... def __init__(self, **kwargs): ... self.__dict__ = kwargs >>> converters = { ... bool: lambda b: "yes" if b else "no", ... int: hex, ... float: lambda f: f"{f:0.3}", ... Color: lambda c: c.color, ... Info: lambda i: i.__dict__, ... } >>> data["attributes"] = Info(readable=True, writable=False) >>> try: ... print(nt.dumps(data, converters=converters)) ... except nt.NestedTextError as e: ... print(str(e)) key: 0x2a value: 3.14 valid: yes house: red attributes: readable: yes writable: no The above example shows that *Color* in the *converters* argument dominates over the ``__nestedtest__converter__`` class. If the dictionary maps a type to *None*, then the default behavior is used for that type. If it maps to *False*, then an exception is raised. .. code-block:: python >>> converters = { ... bool: lambda b: "yes" if b else "no", ... int: hex, ... float: False, ... Color: lambda c: c.color, ... Info: lambda i: i.__dict__, ... } >>> try: ... print(nt.dumps(data, converters=converters)) ... except nt.NestedTextError as e: ... print(str(e)) value: unsupported type (float). *converters* need not actually change the type of a value, it may simply transform the value. In the following example, *converters* is used to transform dictionaries by removing empty dictionary fields. It is also converts dates and physical quantities to strings. .. code-block:: python >>> import arrow >>> from inform import cull >>> import quantiphy >>> class Dollars(quantiphy.Quantity): ... units = "$" ... form = "fixed" ... prec = 2 ... strip_zeros = False ... show_commas = True >>> converters = { ... dict: cull, ... arrow.Arrow: lambda d: d.format("D MMMM YYYY"), ... quantiphy.Quantity: lambda q: str(q) ... } >>> transaction = dict( ... date = arrow.get("2013-05-07T22:19:11.363410-07:00"), ... description = "Incoming wire from Publisher’s Clearing House", ... debit = 0, ... credit = Dollars(12345.67) ... ) >>> print(nt.dumps(transaction, converters=converters)) date: 7 May 2013 description: Incoming wire from Publisher’s Clearing House credit: $12,345.67 Both *default* and *converters* may be used together. *converters* has priority over the built-in types and *default*. When a function is specified as *default*, it is always applied as a last resort. Use the *map_keys* argument to format the keys as you wish. For example, you may wish to render the keys at the first level of hierarchy in upper case: .. code-block:: python >>> def map_keys(key, parent_keys): ... if len(parent_keys) == 0: ... return key.upper() >>> print(nt.dumps(transaction, converters=converters, map_keys=map_keys)) DATE: 7 May 2013 DESCRIPTION: Incoming wire from Publisher’s Clearing House CREDIT: $12,345.67 It can also be used map the keys back to their original form when round-tripping a dataset when using key normalization or key de-duplication: .. code-block:: python >>> content = """ ... Michael Jordan: ... occupation: basketball player ... Michael Jordan: ... occupation: actor ... Michael Jordan: ... occupation: football player ... """ >>> def de_dup(key, state): ... if key not in state: ... state[key] = 1 ... state[key] += 1 ... return f"{key} ⟪#{state[key]}⟫" >>> keymap = {} >>> people = nt.loads(content, dict, on_dup=de_dup, keymap=keymap) >>> print(nt.dumps(people)) Michael Jordan: occupation: basketball player Michael Jordan ⟪#2⟫: occupation: actor Michael Jordan ⟪#3⟫: occupation: football player >>> print(nt.dumps(people, map_keys=keymap)) Michael Jordan: occupation: basketball player Michael Jordan: occupation: actor Michael Jordan: occupation: football player ''' # code {{{3 dumper = NestedTextDumper( width, inline_level, sort_keys, indent, converters, default, map_keys, dialect ) return dumper.render_value(obj, (), ())
# dump {{{2
[docs]def dump(obj, dest, **kwargs): # description {{{3 """Write the *NestedText* representation of the given object to the given file. Args: obj: The object to convert to *NestedText*. dest (str, os.PathLike, io.TextIOBase): The file to write the *NestedText* content to. The file can be specified either as a path (e.g. a string or a `pathlib.Path`) or as a text IO instance (e.g. an open file, or 1 for stdout). If a path is given, the will be opened, written, and closed. If an IO object is given, it must have been opened in a mode that allows writing (e.g. ``open(path, "w")``), if applicable. It will be written and not closed. The name used for the file is arbitrary but it is tradition to use a .nt suffix. If you also wish to further distinguish the file type by giving the schema, it is recommended that you use two suffixes, with the suffix that specifies the schema given first and .nt given last. For example: flicker.sig.nt. kwargs: See :func:`dumps` for optional arguments. Returns: The *NestedText* content with a trailing newline. This differs from :func:`dumps`, which does not add the trailing newline. Raises: NestedTextError: if there is a problem in the input data. OSError: if there is a problem opening the file. Examples: This example writes to a pointer to an open file. .. code-block:: python >>> import nestedtext as nt >>> from inform import fatal, os_error >>> data = { ... "name": "Kristel Templeton", ... "gender": "female", ... "age": "74", ... } >>> try: ... with open("data.nt", "w", encoding="utf-8") as f: ... nt.dump(data, f) ... except nt.NestedTextError as e: ... e.terminate() ... except OSError as e: ... fatal(os_error(e)) This example writes to a file specified by file name. In general, the file name and extension are arbitrary. However, by convention a ‘.nt’ suffix is generally used for *NestedText* files. .. code-block:: python >>> try: ... nt.dump(data, "data.nt") ... except nt.NestedTextError as e: ... e.terminate() ... except OSError as e: ... fatal(os_error(e)) """ # code {{{3 content = dumps(obj, **kwargs) try: dest.write(content + "\n") except AttributeError: # Avoid nested try-except blocks, since they lead to chained exceptions # (e.g. if the file isn’t found, etc.) that unnecessarily complicate the # stack trace. pass else: return with open(dest, "w", encoding="utf-8") as f: f.write(content + "\n")
# NestedText Utilities {{{1 # Extras that are useful when using NestedText. # get_value_from_keys {{{2
[docs]def get_value_from_keys(data, keys): # description {{{3 ''' Get value from keys. Deprecated in version 3.7 and is to be removed in future versions. :func:`get_value_from_keys` is replaced :func:`get_value`, which is identical. Args: data: Your data set as returned by :meth:`load` or :meth:`loads`. keys: The sequence of normalized keys that identify a value in the dataset. Returns: The value that corresponds to a tuple of keys from a keymap. Examples: .. code-block:: python >>> import nestedtext as nt >>> contents = """ ... names: ... given: Fumiko ... surname: Purvis ... """ >>> data = nt.loads(contents, "dict") >>> get_value_from_keys(data, ("names", "given")) 'Fumiko' ''' # code {{{3 for key in keys: data = data[key] return data
# get_lines_from_keys {{{2
[docs]def get_lines_from_keys(data, keys, keymap, kind="value", sep=None): # description {{{3 ''' Get line numbers from normalized keys. Deprecated in version 3.7 and is to be removed in future versions. Use :func:`get_line_numbers` as a replacement. This function returns the line numbers of the key or value selected by *keys*. It is used when reporting an error in a value that is possibly a multiline string. If the location contained in a keymap were used the user would only see the line number of the first line, which may confuse some users into believing the error is actually contained in the first line. Using this function gives both the starting and ending line number so the user focuses on the whole string and not just the first line. If *sep* is given, either one line number or both the beginning and ending line numbers are returned, joined with the separator. In this case the line numbers start from line 1. If *sep* is not given, the line numbers are returned as a tuple containing a pair of integers that is tailored to be suitable to be arguments to the Python *slice* function (see example). The beginning line number and 1 plus the ending line number is returned as a tuple. In this case the line numbers start at 0. If the value is requested and it is a composite (a dictionary or list), the line on which it ends cannot be easily determined, so the value is treated as if it consists of a single line. This is considered tolerable as it is expected that this function is primarily used to return the line number of leaf values, which are always strings. Args: data: Your data set as returned by :meth:`load` or :meth:`loads`. keys: The collection of keys that identify a value in the dataset. keymap: The keymap returned from :meth:`load` or :meth:`loads`. kind (str): Specify either “key” or “value” depending on which token is desired. sep: The separator string. If given a string is returned and *sep* is inserted between two line numbers. Otherwise a tuple is returned. Example: >>> import nestedtext as nt >>> doc = """ ... key: ... > this is line 1 ... > this is line 2 ... > this is line 3 ... """ >>> data = nt.loads(doc, keymap=(keymap:={})) >>> keys = ("key",) >>> lines = nt.get_lines_from_keys(data, keys, keymap, sep="-") >>> text = doc.splitlines() >>> print( ... f"Lines {lines}:", ... *text[slice(*nt.get_lines_from_keys(data, keys, keymap))], ... sep="\\n" ... ) Lines 3-5: > this is line 1 > this is line 2 > this is line 3 ''' # code {{{3 if type(keys) is not tuple: keys = tuple(keys) line, col = keymap[keys].as_tuple(kind) value = get_value_from_keys(data, keys) if kind == "value": num_lines = len(value.splitlines()) if is_str(value) else 1 else: key = keys[-1] num_lines = len(key.splitlines()) if is_str(key) else 1 if sep is None: return (line, line + num_lines) if num_lines > 1: return join(line + 1, line + num_lines, sep=sep) return str(line + 1)
# get_original_keys {{{2
[docs]def get_original_keys(keys, keymap, strict=False): # description {{{3 ''' Get original keys from normalized keys. Deprecated in version 3.7 and is to be removed in future versions. Use :func:`get_keys` as a replacement. This function is used when the *normalize_key* argument is used with :meth:`load` or :meth:`loads` to transform the keys to a standard form. Given a set of normalized keys that point to a particular value in the returned dataset, this function returns the original keys for that value. Args: keys: The collection of normalized keys that identify a value in the dataset. keymap: The keymap returned from :meth:`load` or :meth:`loads`. strict: If true, a *KeyError* is raised if the given keys are not found in *keymap*. Otherwise, the given normalized keys will be returned rather than the original keys. This is helpful when reporting errors on required keys that do not exist in the data set. Since they are not in the dataset, the original keys are not available. Returns: A tuple containing the original keys names. Examples: .. code-block:: python >>> import nestedtext as nt >>> contents = """ ... Names: ... Given: Fumiko ... """ >>> def normalize_key(key, keys): ... return key.lower() >>> data = nt.loads(contents, "dict", normalize_key=normalize_key, keymap=(keymap:={})) >>> print(get_original_keys(("names", "given"), keymap)) ('Names', 'Given') >>> print(get_original_keys(("names", "surname"), keymap)) ('Names', 'surname') >>> keys = get_original_keys(("names", "surname"), keymap, strict=True) Traceback (most recent call last): ... KeyError: ('names', 'surname') ''' # code {{{3 original_keys = () for i in range(len(keys)): try: loc = keymap[tuple(keys[:i+1])] original_keys += loc._get_original_key(keys[i], strict), except (KeyError, IndexError): if strict: raise original_keys += keys[i], return original_keys
# join_keys {{{2
[docs]def join_keys(keys, sep=", ", keymap=None, strict=False): # description {{{3 ''' Joins the keys into a string. Deprecated in version 3.7 and is to be removed in future versions. Use :func:`get_keys` as a replacement. Args: keys: A tuple of keys. sep: The separator string. It is inserted between each key during the join. keymap: The keymap returned from :meth:`load` or :meth:`loads`. It is optional. If given the given keys are converted to the original keys before the joining. strict: If true, a *KeyError* is raised if the given keys are not found in *keymap*. Otherwise, the given normalized keys will be returned rather than the original keys. This is helpful when reporting errors on required keys that do not exist in the data set. Since they are not in the dataset, the original keys are not available. Returns: A string containing the joined keys. Examples: .. code-block:: python >>> import nestedtext as nt >>> contents = """ ... Names: ... Given: Fumiko ... """ >>> def normalize_key(key, keys): ... return key.lower() >>> data = nt.loads(contents, "dict", normalize_key=normalize_key, keymap=(keymap:={})) >>> join_keys(("names", "given")) 'names, given' >>> join_keys(("names", "given"), sep=".") 'names.given' >>> join_keys(("names", "given"), keymap=keymap) 'Names, Given' >>> join_keys(("names", "surname"), keymap=keymap) 'Names, surname' >>> join_keys(("names", "surname"), keymap=keymap, strict=True) Traceback (most recent call last): ... KeyError: ('names', 'surname') ''' # code {{{3 if keymap: keys = get_original_keys(keys, keymap, strict=strict) return sep.join(str(k) for k in keys)
# get_keys {{{2
[docs]def get_keys(keys, keymap, *, original=True, strict=True, sep=None): # description {{{3 ''' Returns a key sequence given a normalized key sequence. Keys in the dataset output by the load functions are referred to as normalized keys, even though no key normalization may have occurred. This distinguishes them from the original keys, which are the keys given in the NestedText document read by the load functions. The original keys are mapped to normalized keys by the *normalize_key* argument to the load function. If normalization is not performed, the normalized keys are the same as the original keys. By default this function returns the original key sequence that corresponds to *keys*, a normalized key sequence. Args: keys: The sequence of normalized keys that identify a value in the dataset. keymap: The keymap returned from :meth:`load` or :meth:`loads`. original: If true, return keys as originally given in the NestedText document (pre-normalization). Otherwise return keys as they exist in the dataset (post-normalization). The value of this argument has no effect if the keys were not normalized. strict: *strict* controls what happens if the given keys are not found in *keymap*. The various options can be helpful when reporting errors on key sequences that do not exist in the data set. Since they are not in the dataset, the original keys are not available. True or "error": A *KeyError* is raised. False or "all": All keys given in *keys* are returned. "found": Only the initial available keys are returned. "missing": Only the missing final keys are returned. When returning keys, the initial available keys are converted to their original form if *original* is true, The missing keys are always returned as given. Returns: A tuple containing the desired keys. Examples: .. code-block:: python >>> import nestedtext as nt >>> contents = """ ... Names: ... Given: Fumiko ... """ >>> def normalize_key(key, keys): ... return key.lower() >>> data = nt.loads(contents, "dict", normalize_key=normalize_key, keymap=(keymap:={})) >>> print(get_keys(("names", "given"), keymap)) ('Names', 'Given') >>> print(get_keys(("names", "given"), keymap, sep="❭")) Names❭Given >>> print(get_keys(("names", "given"), keymap, original=False)) ('names', 'given') >>> keys = get_keys(("names", "surname"), keymap, strict=True) Traceback (most recent call last): ... KeyError: ('names', 'surname') >>> print(get_keys(("names", "surname"), keymap, strict="found")) ('Names',) >>> print(get_keys(("names", "surname"), keymap, strict="missing")) ('surname',) >>> print(get_keys(("names", "surname"), keymap, strict="all")) ('Names', 'surname') ''' # code {{{3 assert strict in [True, False, "missing", "error", "all", "found"], strict if type(keys) is not tuple: keys = tuple(keys) to_return = () for i in range(len(keys)): try: loc = keymap[tuple(keys[:i+1])] key = loc._get_original_key(keys[i], strict) if original else keys[i] if strict != "missing": to_return += key, except (KeyError, IndexError): if strict in [True, "error"]: raise if strict != "found": to_return += keys[i], if sep: return sep.join(str(k) for k in to_return) return to_return
# get_value{{{2
[docs]def get_value(data, keys): # description {{{3 ''' Get value from keys. Args: data: Your data set as returned by :meth:`load` or :meth:`loads`. keys: The sequence of normalized keys that identify a value in the dataset. Returns: The value that corresponds to a tuple of keys from a keymap. Examples: .. code-block:: python >>> import nestedtext as nt >>> contents = """ ... names: ... given: Fumiko ... surname: Purvis ... """ >>> data = nt.loads(contents, "dict") >>> get_value_from_keys(data, ("names", "given")) 'Fumiko' ''' # code {{{3 for key in keys: data = data[key] return data
# get_line_numbers {{{2
[docs]def get_line_numbers(keys, keymap, kind="value", *, strict=True, sep=None): # description {{{3 ''' Get line numbers from normalized key sequence. This function returns the line numbers of the key or value selected by *keys*. It is used when reporting an error in a value that is possibly a multiline string. If the location contained in a keymap were used the user would only see the line number of the first line, which may confuse some users into believing the error is actually contained in the first line. Using this function gives both the starting and ending line number so the user focuses on the whole string and not just the first line. This only happens for multiline keys and multiline strings. If *sep* is given, either one line number or both the beginning and ending line numbers are returned, joined with the separator. In this case the line numbers start from line 1. If *sep* is not given, the line numbers are returned as a tuple containing a pair of integers that is tailored to be suitable to be arguments to the Python slice function (see example). The beginning line number and 1 plus the ending line number is returned as a tuple. In this case the line numbers start at 0. If *keys* corresponds to a composite value (a dictionary or list), the line on which it ends cannot be easily determined, so the value is treated as if it consists of a single line. This is considered tolerable as it is expected that this function is primarily used to return the line number of leaf values, which are always strings. Args: keys: The sequence of normalized keys that identify a value in the dataset. keymap: The keymap returned from :meth:`load` or :meth:`loads`. kind: Specify either “key” or “value” depending on which token is desired. strict: If *strict* is true, a *KeyError* is raised if *keys* is not found. Otherwise the line number that corresponds to composite value that would contain *keys* if it existed. This composite value corresponds to the largest sequence of keys that does actually exist in the dataset. sep: The separator string. If given a string is returned and *sep* is inserted between two line numbers. Otherwise a tuple is returned. Raises: KeyError: If keys are not in *keymap* and *strict* is true. Example: >>> import nestedtext as nt >>> doc = """ ... key: ... > this is line 1 ... > this is line 2 ... > this is line 3 ... """ >>> data = nt.loads(doc, keymap=(keymap:={})) >>> keys = ("key",) >>> lines = nt.get_line_numbers(keys, keymap, sep="-") >>> text = doc.splitlines() >>> print( ... f"Lines {lines}:", ... *text[slice(*nt.get_line_numbers(keys, keymap))], ... sep="\\n" ... ) Lines 3-5: > this is line 1 > this is line 2 > this is line 3 ''' # code {{{3 loc = get_location(keys, keymap) if not loc: if strict: raise KeyError(keys) else: found = get_keys(keys, keymap, original=False, strict="found") loc = keymap[found] return loc.get_line_numbers(kind, sep)
# get_location {{{2
[docs]def get_location(keys, keymap): # description {{{3 ''' Returns :class:`Location` information from the keys. None is returned if location is unknown. Args: keys: The sequence of normalized keys that identify a value in the dataset. keymap: The keymap returned from :meth:`load` or :meth:`loads`. ''' # code {{{3 if type(keys) is not tuple: keys = tuple(keys) try: return keymap[keys] except KeyError: return None
# vim: set sw=4 sts=4 tw=80 fo=croqj foldmethod=marker et spell: