main.py

import sys
from PyQt5.QtWidgets import QApplication, QWidget, QVBoxLayout, QHBoxLayout, QLabel, QLineEdit, QPushButton, QComboBox, QTextEdit
from PyQt5.QtCore import Qt, QUrl
from PyQt5.QtGui import QDragEnterEvent, QDropEvent, QClipboard, QGuiApplication, QIcon
import requests
import re
import feedparser
from Levenshtein import distance
import os

class LiteratureSearchApp(QWidget):
    def __init__(self):
        super().__init__()

        self.initUI()

    def initUI(self):
        self.setWindowTitle('文献検索アプリ')
        self.setGeometry(100, 100, 500, 300)

        # ウィンドウアイコンの設定
        self.setWindowIcon(QIcon('app.ico'))

        layout = QVBoxLayout()

        # プルダウンリスト
        self.search_type_combo = QComboBox()
        self.search_type_combo.setFixedWidth(16 * self.search_type_combo.fontMetrics().width('X'))  # 16文字分の横幅
        self.search_type_combo.addItem('Pubmed検索')
        self.search_type_combo.addItem('Crossref検索')
        self.search_type_combo.addItem('arXiv検索')

        # テキストボックス1
        self.textbox1 = QLineEdit()
        self.textbox1.setPlaceholderText('入力欄')
        self.textbox1.setFixedHeight(3 * self.textbox1.fontMetrics().lineSpacing())  # 3行分の縦幅

        # 検索ボタン
        search_button_layout = QHBoxLayout()
        self.search_input_button = QPushButton('入力欄から検索')
        self.search_clipboard_button = QPushButton('クリップボードから検索')
        search_button_layout.addWidget(self.search_input_button)
        search_button_layout.addWidget(self.search_clipboard_button)

        # テキストボックス2
        self.textbox2 = QTextEdit()
        self.textbox2.setPlaceholderText('検索結果がここに表示されます')
        self.textbox2.setFixedHeight(3 * self.textbox2.fontMetrics().lineSpacing())  # 3行分の縦幅

        # 再検索ボタン
        self.research_button = QPushButton('再検索')
        self.research_button.setFixedWidth(7 * self.research_button.fontMetrics().width('X'))  # 7文字分の横幅
        self.research_button.clicked.connect(self.research)

        layout.addWidget(self.search_type_combo)
        layout.addWidget(self.textbox1)
        layout.addLayout(search_button_layout)
        layout.addWidget(self.textbox2)
        layout.addWidget(self.research_button)

        self.setLayout(layout)

        self.setAcceptDrops(True)

        # シグナル・スロットの接続
        self.search_input_button.clicked.connect(self.search_from_input)
        self.search_clipboard_button.clicked.connect(self.search_from_clipboard)

    def dragEnterEvent(self, event: QDragEnterEvent):
        if event.mimeData().hasUrls() and event.mimeData().urls()[0].toString().endswith('.pdf'):
            event.acceptProposedAction()

    def dropEvent(self, event: QDropEvent):
        file_path = event.mimeData().urls()[0].toLocalFile()

        # ファイル名を取得
        file_name = os.path.splitext(os.path.basename(file_path))[0]
        self.textbox1.setText(f'{file_name}')
        search_type = self.search_type_combo.currentText()

        # キーワード検索を行う
        self.perform_search(file_name, search_type)

    def search_from_input(self):
        search_term = self.textbox1.text()
        search_type = self.search_type_combo.currentText()
        self.perform_search(search_term, search_type)

    def search_from_clipboard(self):
        clipboard_text = QGuiApplication.clipboard().text()
        self.textbox1.setText(clipboard_text)
        search_type = self.search_type_combo.currentText()
        self.perform_search(clipboard_text, search_type)

    def perform_search(self, search_term, search_type):
        if search_type == 'Pubmed検索':
            self.pubmed_search(search_term)
        elif search_type == 'Crossref検索':
            self.crossref_search(search_term)
        elif search_type == 'arXiv検索':
            self.arxiv_search(search_term)

    def pubmed_search(self, search_term, exact=False):
        # Pubmed IDかどうかの判定
        #if search_term.isdigit() and len(search_term) == 8:
        if re.match(r'^\d{8}$', search_term):
            search_url = f'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&retmode=json&id={search_term}'
        else:
            search_url = f'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&sort=relevance&retmode=json&term={search_term}'
            self.textbox2.setText("Pubmedキーワード検索実行")

        result_data = self.perform_search_request(search_url)

        if result_data:
            self.show_pubmed_summary(result_data, search_term, exact)
        else:
            self.textbox2.setText('エラー: 文献が見つかりませんでした')

    def crossref_search(self, search_term, exact=False):
        # DOIかどうかの判定
        if 'https://doi.org/' in search_term or 'doi:' in search_term or 'DOI:' in search_term:
            doi = re.sub(r'https://doi.org/|doi:|DOI:', '', search_term).lstrip()
            search_url = f'https://api.crossref.org/works/{doi}'
        else:
            search_url = f'https://api.crossref.org/works?sort=relevance&query={search_term}'

        result_data = self.perform_search_request(search_url)

        if result_data:
            self.show_crossref_summary(result_data, search_term, exact)
        else:
            self.textbox2.setText('エラー: 文献が見つかりませんでした')

    def arxiv_search(self, search_term, exact=False):
        # arXiv IDかどうかの判定
        if 'arXiv:' in search_term:
            arxiv_id = search_term.replace('arXiv:', '')
            search_url = f'http://export.arxiv.org/api/query?&sortBy=relevance&sortOrder=ascending&max_results=10&id_list={arxiv_id}'
        else:
            search_url = f'http://export.arxiv.org/api/query?&sortBy=relevance&sortOrder=ascending&max_results=10&search_query={search_term}'
            search_url = search_url.replace(" ", "%20").replace("-", "%20")

        result_data = feedparser.parse(search_url)

        if result_data:
            self.show_arxiv_summary(result_data, search_term, exact)
        else:
            self.textbox2.setText('エラー: 文献が見つかりませんでした')

    def remove_matching_string(self, A, B):
        # 文字列Aと文字列Bを比較し、BからAと一致する文字列を削除する
        result = B
        for char in A:
            result = result.replace(char, '', 1)  # 1回だけ削除する
        return result

    def perform_search_request(self, search_url):
        try:
            response = requests.get(search_url)
            response.raise_for_status()
            result_data = response.json()
            return result_data
        except Exception as e:
            print(f'検索エラー: {e}')
            return None

    def show_pubmed_summary(self, result_data,search_term, exact):
        try:
            # Pubmedキーワード検索の場合
            if 'esearchresult' in result_data:
                result_data = result_data['esearchresult']
                id_list = result_data.get('idlist', [])

                if not id_list:
                    self.textbox2.setText('エラー: 文献が見つかりませんでした')
                    return

                # Pubmed ID検索を行う
                if not exact:
                    pubmed_id = id_list[0]
                    pubmed_id_search_url = f'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&retmode=json&id={pubmed_id}'
                    pubmed_id_result = self.perform_search_request(pubmed_id_search_url)
                if exact:
                    closest_distance = float('inf')
                    pubmed_id = ''
                    for i in id_list[:10]:
                        pubmed_id_search_url = f'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&retmode=json&id={i}'
                        pubmed_id_result = self.perform_search_request(pubmed_id_search_url)
                        paper = pubmed_id_result['result'][i].get('title', '')

                        # 距離を計算
                        current_distance = distance(search_term, paper)

                        # 最も距離が短い論文を更新
                        if current_distance < closest_distance:
                            closest_distance = current_distance
                            pubmed_id = i

                    pubmed_id_search_url = f'https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&retmode=json&id={pubmed_id}'
                    pubmed_id_result = self.perform_search_request(pubmed_id_search_url)

            # Pubmed ID検索の場合
            else:
                pubmed_id = result_data["result"]["uids"][0]
                pubmed_id_result = result_data

            pub_date, source, authors, last_author, title = (
                pubmed_id_result['result'][pubmed_id].get('pubdate', '').split()[0],
                pubmed_id_result['result'][pubmed_id].get('source', ''),
                pubmed_id_result['result'][pubmed_id].get('authors', []),
                pubmed_id_result['result'][pubmed_id].get('lastauthor', '').split()[0],
                pubmed_id_result['result'][pubmed_id].get('title', ''),
                )

            # 著者名を要約
            author_names = [f"{author.get('name', '')}" for author in authors]
            first_author = author_names[0].split()[0]

            # 要約した情報をテキストボックスに表示
            summary_text = f'{first_author} {last_author} ({source} {pub_date}) {title}'
            summary_text = self.remove_special_characters(summary_text)
            self.textbox2.setText(summary_text)

        except Exception as e:
            print(f'Pubmed検索エラー: {e}')
            self.textbox2.setText('エラー: 文献が見つかりませんでした')

    def show_crossref_summary(self, result_data,search_term, exact):
        try:
            # Crossrefキーワード検索の場合
            if 'message' in result_data and result_data['message'].get('items'):
                items = result_data['message']['items']
                # journal-articleの最初の結果を検索
                if not exact:
                    item = next(
                        (i for i in items if i.get("type") == 'journal-article' or i.get("type") == 'posted-content'),
                        None
                    )
                    item_type = item.get("type")
                    # DOIを使って検索
                    if 'DOI' in item:
                        doi_search_url = f'https://api.crossref.org/works/{item["DOI"]}'
                        doi_result = self.perform_search_request(doi_search_url)

                if exact:
                    item_list = [i for i in items if i.get("type") == 'journal-article' or i.get("type") == 'posted-content']

                    closest_distance = float('inf')
                    closest_item = ''
                    for item in item_list[:10]:
                        doi_search_url = f'https://api.crossref.org/works/{item["DOI"]}'
                        doi_result = self.perform_search_request(doi_search_url)
                        paper = doi_result['message'].get('title', '')[0]

                        # 距離を計算
                        current_distance = distance(search_term, paper)

                        # 最も距離が短い論文を更新
                        if current_distance < closest_distance:
                            closest_distance = current_distance
                            closest_item = item

                    item_type = closest_item.get("type")
                    doi_search_url = f'https://api.crossref.org/works/{closest_item["DOI"]}'
                    doi_result = self.perform_search_request(doi_search_url)

            # Crossref　DOI検索の場合
            else:
                doi_result = result_data
                item_type = doi_result['message'].get("type")

            title = doi_result['message'].get('title', '')[0]
            author_names = [f"{author.get('family', '')}" for author in doi_result['message'].get('author', [])]
            first_author = author_names[0]
            last_author = author_names[-1]
            pub_date = doi_result['message'].get('created', {}).get('date-parts', [])[0][0] if doi_result['message'].get('created') else ''
            if item_type == 'journal-article':
                source = doi_result['message'].get('short-container-title', [''])[0]
            elif item_type == 'posted-content':
                source = doi_result['message'].get('institution', [''])[0].get("name")

            # 要約した情報をテキストボックスに表示
            summary_text = f'{first_author} {last_author} ({source} {pub_date}) {title}'
            summary_text = self.remove_special_characters(summary_text)
            self.textbox2.setText(summary_text)
            QGuiApplication.clipboard().setText(summary_text)

        except Exception as e:
            print(f'Crossref検索エラー: {e}')
            self.textbox2.setText('エラー: 文献が見つかりませんでした')

    def show_arxiv_summary(self, result_data,search_term, exact):
        try:
            entries = result_data['entries']
            if not exact:
                entry = entries[0]

            if exact:
                closest_distance = float('inf')
                closest_entry = ''
                for entry in entries[:10]:
                    paper = entry.title.replace('\n ', '')

                    # 距離を計算
                    current_distance = distance(search_term, paper)

                    # 最も距離が短い論文を更新
                    if current_distance < closest_distance:
                        closest_distance = current_distance
                        closest_entry = entry
                entry = closest_entry

            authors = entry.authors
            if len(authors) == 1:
                author_summary = authors[0]["name"].split(" ")[1]
            else:
                first_author = authors[0]["name"].split(" ")[1]
                last_author = authors[-1]["name"].split(" ")[1]
                author_summary = f"{first_author} {last_author}"

            title  = entry.title.replace('\n ', '')
            date   = entry.published_parsed
            year = date[0]
            journal = "arXiv"

            summary_text = f"{author_summary} ({journal} {year}) {title}"
            summary_text = self.remove_special_characters(summary_text)
            self.textbox2.setText(summary_text)
            QGuiApplication.clipboard().setText(summary_text)

        except Exception as e:
            print(f'arXiv検索エラー: {e}')
            self.textbox2.setText('エラー: 文献が見つかりませんでした')

    def remove_special_characters(self, input_string):
        # 参照：https://x.gd/f0fcI
        pattern = r'[\\|/|:|?|.|"|<|>|\|]'
        result = re.sub(pattern, '', input_string)
        return result

    def research(self):
        search_term = self.textbox1.text()
        search_type = self.search_type_combo.currentText()

        # それぞれの検索メソッドを呼び出し、検索結果を取得
        if search_type == 'Pubmed検索':
            result_data = self.pubmed_search(search_term, exact=True)
        elif search_type == 'Crossref検索':
            result_data = self.crossref_search(search_term, exact=True)
        elif search_type == 'arXiv検索':
            result_data = self.arxiv_search(search_term, exact=True)

def ico_path(relative_path):
    try:
        base_path = sys._MEIPASS
    except Exception:
        base_path = os.path.abspath(".")
    return os.path.join(base_path, relative_path)
    
if __name__ == '__main__':
    app = QApplication(sys.argv)
    app.setWindowIcon(QIcon(ico_path('app.ico')))
    window = LiteratureSearchApp()
    window.show()
    sys.exit(app.exec_())