錯誤：沒有這樣的模塊：fts4； 使用 - 帶有 anaconda jupyter 筆記本的模糊匹配器包

Question

我正在使用 jupyter notebook 並嘗試運行此代碼：

import pubchempy as pcp
from rdkit import Chem
import numpy as np
import pandas as pd
import json
import time
import fuzzymatcher

start_time = time.time()
#     CD = pd.read_excel(excelpathin)

    data = pd.ExcelFile(r"C:\Users\USER\Downloads\MOD_REINJ_NEG_ChemSpider Results.xlsx")
    data = pd.ExcelFile(excelpathin)

    df = data.parse (sheet_name=0)
    inKey = list()
    for idx,sd in enumerate(df['Structure']):
        print(idx)
        F = open ("temp.sdf","w")
        F.writelines (sd)
        F.close()
        suppl = Chem.SDMolSupplier ('temp.sdf')
        mol = next (suppl)
        if mol==None:
            inKey.append (np.nan)
        else:
            inKey.append (Chem.MolToInchiKey (mol))

    inKey = pd.DataFrame(inKey)
    inKey.columns = ['InChIKey']
    CD = pd.concat([df, inKey], axis=1, sort=False)
    
    
    print("--- %s seconds --f-add 3 cols" % (time.time() - start_time))

    # From here is the joindata function with modification
    # Load the parse HMDB file
    with open(jsonpathin, 'r') as read_file:
        data = json.load(read_file)

    start_time = time.time()
    # Load the parse HMDB file
    # with open('D:/BCDD/Documents/Tal/Projects/HMDB/DataSets/Parser_HMDB.py Output/serum_metabolites.json', 'r') as read_file:
    #     data = json.load(read_file)


    # Create a data frame from the list of dictionaries
    # df_hmdb = pd.DataFrame(data,  columns=['accession', 'name', 'chemical_formula', 'inchikey', 'disease_name' ])
    df_hmdb = pd.DataFrame(data)
    df_hmdb.drop(['description', 'synonyms', 'kegg_id', 'meta_cyc_id', 'pathway_name'], axis=1)

    df_excel = CD
    # Merge by inchikey
    joindata_by_inchikey = pd.merge(left=df_excel, right=df_hmdb, how='inner', left_on='InChIKey', right_on='inchikey')

    print("--- %s seconds --f-merge by inchikey " % (time.time() - start_time))

    start_time = time.time()
    # Reduce the rows to those we DID find a match by inchkey in bothe data sets
    df_hmdb_reduce_byinchik = df_hmdb.loc[~df_hmdb['inchikey'].isin(df_excel['InChIKey'])]
    df_excel_reduce_byinchik = df_excel.loc[~df_excel['InChIKey'].isin(joindata_by_inchikey['InChIKey'])]


    # joindata_by_name = fuzzymatcher.fuzzy_left_join(df_excel, df_hmdb, left_on="Name", right_on="name")
    joindata_by_name = fuzzymatcher.fuzzy_left_join(df_excel_reduce_byinchik, df_hmdb_reduce_byinchik, left_on="Name",
                                                    right_on="name")

    # Selecting threshold  best_match_score>0.25 maybe adjustments needed
    joindata_by_name = joindata_by_name[joindata_by_name['best_match_score'] > 0.55]
    # Drop columns the
    joindata_by_name.drop(['best_match_score', '__id_left', '__id_right'], axis=1, inplace=True)
    print("--- %s seconds --f-merge by name" % (time.time() - start_time))

    start_time = time.time()
    # Reduce the rows to those we DID find a match by inchkey in and by name both data sets
    df_hmdb_reduce_byname = df_hmdb_reduce_byinchik.loc[~df_hmdb_reduce_byinchik['name'].isin(joindata_by_name['name'])]
    df_excel_reduce_byname = df_excel_reduce_byinchik.loc[
        ~df_excel_reduce_byinchik['Name'].isin(joindata_by_name['Name'])]
    # Remove spaces between letters on  'Formula' ( there is  a warning)
    df_excel_reduce_byname.loc[:, 'Formula'] = df_excel_reduce_byname['Formula'].str.replace(' ', '')

    # Merge by chemical_formula
    joindata_by_CF = pd.merge(left=df_excel_reduce_byname, right=df_hmdb_reduce_byname, how='inner', left_on='Formula',
                              right_on='chemical_formula')

    # This data inculed rows from the original EXCEL file that we did NOT find and match ( by inchikey nor name nor CF)
    df_excel_reduce_byCF = df_excel_reduce_byname.loc[
        ~df_excel_reduce_byname['Formula'].isin(joindata_by_CF['chemical_formula'])]

    # Create a list of all columns of the HMDB JSON data
    colnames = joindata_by_inchikey.columns[6:]
    # Add those names as empty columns to the df_excel_reduce_byCF. reducedata in all the rows from the original Excel
    # that did NOT find a match and added the columns of the HMDB
    reducedata = df_excel_reduce_byCF.reindex(columns=[*df_excel_reduce_byCF.columns.tolist(), *colnames])

    # Append all the data sets
    # out = joindata_by_inchikey.append(joindata_by_name.append(joindata_by_CF))
    out = joindata_by_inchikey.append(joindata_by_name.append(joindata_by_CF.append(reducedata)))

    print("--- %s seconds --f-merge by CF" % (time.time() - start_time))
    

（我不確定代碼是否相關，因為我加載了未在問題中共享的文件）

這是我得到的錯誤：

OperationalError                          Traceback (most recent call last)
<ipython-input-8-26c4a723b687> in <module>
     23 # joindata_by_name = fuzzymatcher.fuzzy_left_join(df_excel, df_hmdb, left_on="Name", right_on="name")
     24 joindata_by_name = fuzzymatcher.fuzzy_left_join(df_excel_reduce_byinchik, df_hmdb_reduce_byinchik, left_on="Name",
---> 25                                                 right_on="name")
     26 
     27 # Selecting threshold  best_match_score>0.25 maybe adjustments needed

~\Anaconda3\lib\site-packages\fuzzymatcher\__init__.py in fuzzy_left_join(df_left, df_right, left_on, right_on, left_id_col, right_id_col)
     39     m = Matcher(dp, dg, s)
     40     m.add_data(df_left, df_right, left_on, right_on,  left_id_col, right_id_col)
---> 41     m.match_all()
     42 
     43     return m.get_left_join_table()

~\Anaconda3\lib\site-packages\fuzzymatcher\matcher.py in match_all(self)
     87         self.scorer.add_data(self)
     88 
---> 89         self.data_getter.add_data(self)
     90 
     91         # Get a table that contains only the matches, scores and ids

~\Anaconda3\lib\site-packages\fuzzymatcher\data_getter_sqlite.py in add_data(self, matcher)
     58                  USING fts4({} TEXT, _concat_all TEXT, _concat_all_alternatives TEXT);
     59               """.format(matcher.right_id_col)
---> 60         con.execute(sql)
     61         con.execute("INSERT INTO fts_target SELECT * FROM df_right_processed")
     62 

OperationalError: no such module: fts4

與fuzzymatcher的錯誤線用於不同的計算機上使用Pycharme工作，但對jupyter筆記本事實並非如此。

我檢查了這個答案：

1. 操作錯誤：沒有這樣的模塊：fts4
2. OperationalError：沒有這樣的模塊：fts4

但沒有用，我不明白該怎么做

任何幫助想法暗示想法都得到贊賞

Answer 1

我遇到了與您描述的相同的問題，我找到了解決方案。

1. 您必須轉到https://www.sqlite.org/download.html並從本頁的 Windows 預編譯二進制文件部分下載適當的 dll 文件。 您必須根據您的硬件架構下載 32 位或 64 位。

2. 解壓縮 zip 文件並復制內容並粘貼，然后手動將其粘貼到“您的 python \\bin 文件夾”中。

在 (1) 和 (2) 之后，我可以在 Jupyter Notebook 中毫無問題地使用 Fuzzymatcher 包。

如果這些步驟不能解決您的問題，您將看到以下網站： https : //deshmukhsuraj.wordpress.com/2015/02/07/windows-python-users-update-your-sqlite3/comment-page-1/?未批准=947&moderation-hash=9de09b93a31bd079256474474e71b32d#comment-947

查看該網站對我找到問題的答案非常有用。 我希望它對你有用。 最好的事物