Merge branch 'splitter_refactor' into dev

parser/__main__.py

@@ -3,11 +3,11 @@ import time
 
 import schedule
 
-from . import pipeline
+from . import pipeline, LenenergoParser
 
 
 def job():
-    parser = pipeline()
+    parser = pipeline(LenenergoParser(file_path="./data.csv"))
     parser.save_df(f'./data_{parser.today.strftime("%d-%m-%y_%H.%M")}.csv')
 
 

parser/address.py

@@ -2,12 +2,13 @@ from __future__ import annotations
 
 import re
 from typing import Iterable, List, TypeVar
+from collections.abc import Sequence
 
 import pandas as pd
 
 T = TypeVar("T")
 
-CLASSES = ("w", "d", "c", "t", "s", "h", "b","e", "l", "r")
+CLASSES = ("w", "d", "c", "t", "s", "h", "b", "e", "l", "r")
 DISTRICTS_PREFIXES = ("мо ", "р-н","городское","лесхоз")
 COUNTRYSIDE_PREFIXES = (
     "г", "п", "д", "гп", "рп", "кп", "пгт", "c", "хутор", " урочище")
@@ -61,7 +62,7 @@ def find_litera(token: pd.Series, pre_token: pd.Series) -> str:
         return "l"
     if (re.search(r"\b([А-Я]|[а-я]){1}$", token['obj']) \
         and ("l" in pre_token['class'] or "h" in pre_token['class'])) \
-            and not (" ш" in token["obj"]) \
+            and (" ш" not in token["obj"]) \
             and not find_countryside(token, pre_token):
         return "l"
     return ""
@@ -73,7 +74,7 @@ def find_edifice(token: pd.Series, pre_token: pd.Series) -> str:
 def find_building(token: pd.Series, pre_token: pd.Series) -> str:
     if re.search(r"\d", token['obj']) and not find_room(token,pre_token):
         if any_of_in(BUILDING_PREFIXES, token['obj'].lower()) \
-                or "b" in pre_token['class'] and not ("h" in token['class']) and not find_edifice(token,pre_token)\
+                or "b" in pre_token['class'] and ("h" not in token['class']) and not find_edifice(token,pre_token)\
                 or re.search(r"к\.* ?\d", token['obj']):
             return "b"
     return ""
@@ -155,7 +156,7 @@ def cut_address(ad: pd.Series, cl: str) -> pd.Series:
             ad["address"] = re.sub(r"[мкдтпучасток]*\.? ?\d{1,4} ?\/*\d* ?", "",
                                             ad["address"].lower())
         elif ad["class"][-1] == "b":
-            num = re.findall("к{0,1}\.? ?\d", ad["address"])[-1]
+            num = re.findall(r"к{0,1}\.? ?\d", ad["address"])[-1]
             ad["address"] = re.sub(num, "", ad["address"])
         elif ad["class"][-1] == "e":
             ad["address"] = re.sub(r"cтр\.? ?\d", "", ad["address"])
@@ -167,102 +168,226 @@ def cut_address(ad: pd.Series, cl: str) -> pd.Series:
     return ad
 
 
-# TODO: переработать систему из if в нормальный вид
+def is_valid_token(string: str) -> bool:
-def split_address(address: str) -> List[str]:
+    return string not in ("", "уг.", "д.")
-    if ";" in address:
-        address = address.replace(";", ",")
-    if "," in address:
-        tokens = address.split(",")
 
-        t = list(map(str.strip, filter(lambda token: token != "", tokens)))
 
-        tokens = pd.DataFrame()
+def create_token(obj: str = "", token_class: str = ""):
-        tokens['obj'] = t
+    return pd.Series(
-        for el in ("", "уг.", "д."):
+        {
-            tokens = tokens[tokens["obj"] != el]
+            "obj": obj,
-        tokens.insert(len(tokens.columns), "class", "")
+            "class": token_class,
-        res = []
+        }
-        accumulator = pd.Series(data={"address": "", "class": ""})
+    )
 
-        for i in range(len(tokens)):
-            cur_tk = tokens.iloc[i]
 
-            if i == 0:
+class AddressSplitter(Sequence):
-                pre_token = pd.Series(data=["", ""], index=['obj', 'class'])
+    def __init__(self, address: str):
-            else:
+        self.input = address
-                pre_token = tokens.iloc[i - 1]
 
-            cur_tk = address_classification(cur_tk, pre_token)
+        self.addresses = self.split()
-            tokens.iloc[i] = cur_tk
-            print(tokens.iloc[i])
 
-            if not accumulator["class"]:
+    ## Sequence abstract methods implementation
-                accumulator["class"] = cur_tk['class']
+
-                accumulator["address"] = cur_tk["obj"]
+    def __getitem__(self, key: int):
+        if key < len(self.addresses):
+            return self.addresses[key]
+        else:
+            raise IndexError()
+
+    def __len__(self):
+        return len(self.addresses)
+
+    ## Address token class manipulations
+
+    def next_class(self) -> str:
+        return self.token["class"][0]
+
+    def correct_order(self) -> bool:
+        prev_class = self.accumulator["class"][-1]
+
+        return (
+            CLASSES.index(prev_class) < CLASSES.index(self.next_class())
+            and self.accumulator["class"] != "w"
+        )
+
+    def next_class_is(self, comparing_class: str) -> bool:
+        return len(self.token["class"]) > 0 and self.next_class() == comparing_class[0]
+
+    def has_no_class(self, comparing_class: str) -> bool:
+        return comparing_class[0] not in self.accumulator["class"]
+
+    def pop_token_class(self):
+        self.token["class"] = self.token["class"][1:]
+
+    ## Accumulator constrains
+
+    def next_is_street_or_upper(self) -> bool:
+        is_unknown_class = self.accumulator["class"] in ("", "w")
+
+        return (
+            CLASSES.index(self.next_class()) <= CLASSES.index("s") or is_unknown_class
+        )
+
+    def has_numbered_street(self) -> bool:
+        return any_of_in(("-я", "-й", "-Я"), self.accumulator["address"])
+
+    ## Accumulator manipulation
+
+    # House
+
+    def substitue_house(self) -> str:
+        house_regex = re.compile(r"\d{1,4} ?[\/\-]?\d* ?")
+
+        number = house_regex.findall(self.token['obj'])[0]
+
+        if self.has_numbered_street():
+            house_number_index = 1
+        else:
+            house_number_index = 0
+
+        number_in_accumulator = house_regex.findall(self.accumulator["address"])
+
+        if number_in_accumulator:
+            return re.sub(number_in_accumulator[house_number_index], number, self.accumulator["address"])
+        else:
+            return self.accumulator["address"]
+
+    # Building
+
+    def append_building(self, number: int) -> pd.Series:
+        self.accumulator["class"] += "b"
+        self.accumulator["address"] += "к." + number
+
+        return self.accumulator
+
+    def substitue_building(self, number: int) -> str:
+        return re.sub(r"\d$", number, self.accumulator["address"])
+
+    def insert_building(self):
+        number = re.findall(r"\d", self.token["obj"])[-1]
+
+        if number and self.has_no_class("building"):
+            self.accumulator = self.append_building(number)
+        else:
+            self.accumulator["address"] = self.substitue_building(number)
+
+    # Edifice
+
+    def substitue_edifice(self, number: int) -> str:
+        return re.sub(r"cтр\. ?\d", number, self.accumulator["address"].strip())
+
+    def insert_edifice(self):
+        number = re.findall("стр\.? ?\d", self.token["obj"])[-1]
+
+        self.accumulator["address"] = self.substitue_edifice(number)
+
+        if number and self.has_no_class("edifice"):
+            self.accumulator["class"] += "e"
+
+    # Letter
+
+    def without_letter(self) -> str:
+        return re.sub(r"[А-Яа-я]$", "", self.accumulator["address"].strip())
+
+    def substitue_letter(self, letter: str) -> str:
+        address_without_letter = self.without_letter()
+
+        return address_without_letter + letter
+
+    def insert_letter(self):
+        letter = re.findall(r"[А-Яа-я]", self.token["obj"])[-1]
+        self.accumulator["address"] = self.substitue_letter(letter)
+
+        if letter and self.has_no_class("litera"):
+            self.accumulator["class"] += "l"
+
+    def has_letter_in(self) -> bool:
+        return (
+            re.search(r"\d{1,3}([А-Я]|[а-я])( |$)", self.accumulator["address"])
+        )
+
+    # Room
+
+    def substitue_room(self, number: int) -> str:
+        return re.sub(r"пом\. ?\d\-?\d*\w?", number, self.accumulator["address"].strip())
+
+    def insert_room(self):
+        number = re.findall("пом\. ?\-?\d*\w?", self.token["obj"])[-1]
+        self.accumulator["address"] = self.substitue_room(number)
+        
+        if number and self.has_no_class("room"):
+            self.accumulator["class"] += "r"
+
+    ## Data preprocessing
+
+    def split_tokens(self) -> list[pd.Series]:
+        address = self.input.replace(";", ",")
+
+        parts = address.split(",")
+        parts = map(str.strip, parts)
+        parts = filter(is_valid_token, parts)
+
+        tokens = map(lambda part: create_token(part, ""), parts)
+
+        return list(tokens)
+
+    def split(self):
+        self.tokens = self.split_tokens()
+
+        result = []
+
+        self.accumulator = pd.Series({"address": "", "class": ""})
+
+        prev_token = create_token()
+
+        for cursor in self.tokens:
+            self.token = address_classification(cursor, prev_token)
+            prev_token = self.token.copy()
+
+            if self.accumulator["class"] == "":
+                self.accumulator = self.token.rename({"obj": "address"})
                 continue
 
-            if CLASSES.index(accumulator["class"][-1]) < CLASSES.index(cur_tk["class"][0]) and accumulator["class"]!="w":
+            if self.correct_order():
-                accumulator["class"] += cur_tk['class']
+                self.accumulator["address"] += " "
-                accumulator["address"] += " " + cur_tk["obj"]
+                self.accumulator += self.token.rename({"obj": "address"})
             else:
-                ad_no_ranges = unfold_house_ranges(accumulator["address"])
+                unfolded_address = unfold_house_ranges(self.accumulator["address"])
-                accumulator["address"] = ad_no_ranges[-1]
+                self.accumulator["address"] = unfolded_address[-1]
 
-                res.extend(ad_no_ranges)
+                result.extend(unfolded_address)
 
-                accumulator = cut_address(accumulator, cur_tk["class"])
+                self.accumulator = cut_address(self.accumulator, self.token["class"])
 
-                if not accumulator["class"] or CLASSES.index(cur_tk["class"][0]) <= CLASSES.index("s") or accumulator["class"]=="w":
+                if self.next_is_street_or_upper():
-                    accumulator["class"] = cur_tk["class"]
+                    self.accumulator = self.token.rename({"obj": "address"})
-                    accumulator["address"] = cur_tk["obj"]
 
-                if cur_tk["class"][0] == "h":
+                if self.next_class_is("house"):
-                    num = re.findall("\d{1,4} ?[\/\-]?\d* ?", cur_tk['obj'])[0]
+                    self.accumulator["address"] = self.substitue_house()
-                    if any_of_in(("-я", "-й", "-Я"), accumulator["address"]):
+                    self.pop_token_class()
-                        idx = 1
-                    else:
-                        idx = 0
-                    num_ac = re.findall("\d{1,4} ?[\/\-]?\d* ?", accumulator["address"])
-                    if num_ac:
-                        accumulator["address"] = re.sub(num_ac[idx], num, accumulator["address"])
-                    cur_tk["class"] =cur_tk["class"][1:]
 
-                if cur_tk["class"] and cur_tk["class"][0] == "b":
+                if self.next_class_is("building"):
-                    num = re.findall("\d", cur_tk["obj"])[-1]
+                    self.insert_building()
-                    if num and not "b" in accumulator["class"]:
+                    self.pop_token_class()
-                        accumulator["class"] += "b"
-                        accumulator["address"] += "к." + num
-                    else:
-                        accumulator["address"] = re.sub(r"\d$", num, accumulator["address"])
-                    cur_tk["class"] = cur_tk["class"][1:]
 
-                if cur_tk["class"] and cur_tk["class"][0] == "e":
+                if self.next_class_is("edifice"):
-                    num = re.findall("стр\.? ?\d", cur_tk["obj"].strip())[-1]
+                    self.insert_edifice()
-                    accumulator["address"] = re.sub(r"cтр\. ?\d", num, accumulator["address"].strip())
+                    self.pop_token_class()
-                    if num and not "e" in accumulator["class"]:
-                        accumulator["class"] += "e"
-                    cur_tk["class"] = cur_tk["class"][1:]
 
-                if cur_tk["class"] and cur_tk["class"][0] == "l":
+                if self.next_class_is("letter"):
-                    num = re.findall("[А-Яа-я]", cur_tk["obj"].strip())[-1]
+                    self.insert_letter()
-                    accumulator["address"] = re.sub(r"[А-Яа-я]$", "", accumulator["address"].strip())
+                elif self.has_letter_in():
-                    accumulator["address"] += num
+                    self.accumulator["address"] = self.without_letter()
-                    if num and not "l" in accumulator["class"]:
+
-                        accumulator["class"] += "l"
+                if self.next_class_is("room"):
-                else:
+                    self.insert_room()
-                    if re.search(r"\d{1,3}([А-Я]|[а-я])( |$)",  accumulator["address"]):
+                    self.pop_token_class()
-                        accumulator["address"] = re.sub(r"[А-Яа-я]$", "", accumulator["address"].strip())
+
-                if cur_tk["class"] and cur_tk["class"][0] == "r":
+        result.extend(unfold_house_ranges(self.accumulator["address"]))
-                    num = re.findall("пом\. ?\-?\d*\w?", cur_tk["obj"].strip())[-1]
+
-                    accumulator["address"] = re.sub(r"пом\. ?\d\-?\d*\w?", num, accumulator["address"].strip())
+        return result
-                    if num and not "r" in accumulator["class"]:
-                        accumulator["class"] += "r"
-                    cur_tk["class"] = cur_tk["class"][1:]
-        res.extend(unfold_house_ranges(accumulator["address"]))
-        print(res)
-        return res
 
-    return [address]
 
 def split_pesoch_res(address: str) -> List[str]:
     t = re.sub(r",", " ", address)
@@ -283,7 +408,7 @@ def process_row(row: pd.Series[str]) -> pd.Series[str]:
         if row["РЭС"] == "Песочинский РЭС":
             addresses = split_pesoch_res(row["Улица"])
         else:
-            addresses = split_address(row["Улица"])
+            addresses = AddressSplitter(row["Улица"])
         row["Улица"] = addresses
 
     return row

parser/util.py

@@ -10,7 +10,7 @@ from . import (
 
 def pipeline(parser: Optional[LenenergoParser] = None) -> LenenergoParser:
     if parser is None:
-        parser = LenenergoParser(file_path = r"C:\Users\Юля\PycharmProjects\machine_learning\lenengro_parser\data_Rosseti.csv")
+        parser = LenenergoParser(parser)
 
     print(parser)