Add script for crawling quotes

CrawlingQuotes.py

@@ -0,0 +1,70 @@
+import bs4, re, bz2, shutil
+from urllib.request import urlretrieve
+import pandas as pd
+
+# Download and unpack file
+filename = "dewikiquote-latest-pages-articles.xml.bz2"
+urlretrieve("https://dumps.wikimedia.org/dewikiquote/latest/" + filename, filename)
+with bz2.BZ2File(filename) as fr, open(filename[:-4],"wb") as fw:
+    shutil.copyfileobj(fr,fw)
+
+# Open file and parse it
+with open("dewikiquote-latest-pages-articles.xml") as fp:
+    soup = bs4.BeautifulSoup(fp, "xml")
+pages = soup.mediawiki.findAll('page')
+
+
+# Return all quotes on a single page
+def get_quotes(text: str) -> [str]:
+    res = []
+    # usually a quote is in ONE line
+    for line in text.split("\n"):
+        # remove leading and trailing whitespaces
+        stripped = line.strip()
+        # Usually at the bottom, quotes are not from the current author so stop here
+        if "zitate mit bezug auf" in stripped.lower():
+            return res
+        match = re.search("\*\s*(\"[^\"]+\")", stripped)
+        if match:
+            quote = match.group(1)
+            cleaned = re.sub(r'\[\[[^\[]+\]\]', lambda x: x.group()[2:].split("|")[-1][:-2], quote)
+            cleaned = re.sub(r'{{[^{}\|]+\|([^{}]+)}}', lambda x: x.group(1), cleaned)
+            cleaned = re.sub(r'<[^<>]+>', "",cleaned)
+            cleaned = cleaned.replace("//", "")  # removes //
+            cleaned = re.sub(' +', ' ', cleaned) # remove whitespaces
+            if "http" not in cleaned and len(cleaned) > 5:
+                res.append(cleaned)
+    return res
+
+# Get categorie to which a page belongs to
+def get_categories(text: str) -> str:
+    return re.findall(r"\[\[Kategorie:([^\]|]+)[^]]*\]\]", text)
+
+# def get_movie_quotes(text: str):
+#     match = re.search(r"== Zitate ==(.*)== Dialoge ==", text, flags=re.DOTALL)
+#     if match:
+#         segment = match.group(1)
+#         match = re.findall(r"=== ([^=]+) === ([^])", segment)
+#     return []
+
+# Extract quotes and authors
+data = []
+omitted = set()
+for page in pages:
+    author = page.title.text
+    raw_text = page.find("text").text
+    categories = get_categories(raw_text)
+    if "Person" in categories:
+        quotes = get_quotes(raw_text)
+        for quote in quotes:
+            data.append((author, quote))
+#     elif "== Filminfo" in raw_text:
+#         fiction = get_movie_quotes(raw_text)
+
+#         break
+    else:
+        omitted.add(author)
+
+# Save results to csv
+df = pd.DataFrame(data, columns=["author", "quote"]).drop_duplicates()
+df.to_csv("train.csv")