From ee05baed7b35df6918a8899b955222748ac21161 Mon Sep 17 00:00:00 2001
From: Martin Czygan <martin.czygan@gmail.com>
Date: Wed, 12 Aug 2020 11:43:38 +0200
Subject: add basic str utils

---
 fuzzycat/main.py  |  1 +
 fuzzycat/utils.py | 82 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 83 insertions(+)
 create mode 100644 fuzzycat/utils.py

diff --git a/fuzzycat/main.py b/fuzzycat/main.py
index 5a6f4a7..8da283b 100644
--- a/fuzzycat/main.py
+++ b/fuzzycat/main.py
@@ -1,4 +1,5 @@
 from fuzzycat import __version__
 
+
 def main():
     print("hello fuzzycat {}".format(__version__))
diff --git a/fuzzycat/utils.py b/fuzzycat/utils.py
new file mode 100644
index 0000000..e3e04c0
--- /dev/null
+++ b/fuzzycat/utils.py
@@ -0,0 +1,82 @@
+# coding: utf-8
+
+import collections
+from typing import Any, Callable, DefaultDict, Dict, List
+
+"""
+A couple of utilities, may be split up into separate modules.
+"""
+
+
+class StringPipeline:
+    """
+    Minimalistic grouping of functions applied on an input string to produce
+    some cleaned or normalized output. Pipeline functions are Func[[str], str].
+
+        >>> cleanups = StringPipeline([
+        ...     str.lower,
+        ...     remove_html_tags,
+        ...     normalize_whitespace,
+        ...     normalize_ampersand,
+        ... ])
+        >>> cleanups.run("<a>Input  & Output</a>")
+        input and output
+
+    """
+
+    def __init__(self, fs: List[Callable[[str], str]]):
+        self.fs = fs
+
+    def run(self, s: str) -> str:
+        """
+        Apply all function and return result.
+        """
+        for f in self.fs:
+            s = f(s)
+        return s
+
+
+class StringAnnotator:
+    """
+    Experimental, rationale: In some way, feature engineering; we want to
+    derive metrics, number from the string, do this consistently and compactly.
+    E.g. once we have dozens of "speaking" characteristics, a case based method
+    might become more readble.
+
+    if s.is_single_token and s.some_ratio > 0.4:
+        return MatchStatus.AMBIGIOUS
+
+    Could also subclass string and pluck more methods on it (might be even
+    reusable).
+
+    ....
+
+    Given a string, derive a couple of metrics, based on functions. The
+    annotation is a dict, mapping an annotation key to a value of any type.
+
+        >>> metrics = StringAnnotator([
+        ...    has_html_tags,
+        ...    has_only_printable_characters,
+        ...    is_single_token,
+        ...    length,
+        ...    has_year_in_parentheses,
+        ... ])
+        >>> metrics.run("Journal of Pataphysics 2038-2032")
+        {"value": "Journal of Pataphysics 2038-2032", "is_single_token": False, ... }
+
+    TODO(martin):
+
+    * SimpleNamespace, dotdict, Dataclass.
+    * string_utils.py or similar
+    * maybe adopt SpaCy or similar
+    """
+
+    def __init__(self, fs: List[Callable[[str], Dict[str, Any]]]):
+        self.fs = fs
+
+    def run(self, s: str) -> Dict[str, Any]:
+        annotations: DefaultDict[str, Any] = collections.defaultdict(dict)
+        for f in self.fs:
+            result = f(s)
+            annotations.update(result)
+        return annotations
-- 
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