使用字典中存储的字符串调用类

Question

我带回了十几个不完整的条目类型，将它们清理并存储在SQL中的各个表中。我可以为每一项编写说明，但是以编程方式管理各种列表/数据帧/表创建似乎更整洁。你知道吗

• 不幸的是，当我试图通过引用dict中的一个条目来调用scrapy项时，Python将其作为字符串而不是类型或类来读取。你知道吗
• 类似地，当我尝试引用一个列表名时，Python仍然看到一个字符串不允许我使用.append（）。你知道吗

如果您能帮助Python将字符串作为类引用或列表引用来读取，我们将不胜感激。你知道吗

以下是我的代码版本：

from scrapy import signals
from dealinfo.items import List, Details, Rd, Status, CompletedDetails, Syndicate
from dealinfo.items import CompanyDetails, CompanyContactInfo, CompanyTeam, Compadvisors, CompanyPInvestors
from dealinfo.items import CompanyExecSum, CurrentRd, PastRd, AnnFin#, CompanyDocs

import pandas as pd
from sqlalchemy import create_engine

class SQLPipeline(object):
    engine=create_engine('mssql+pyodbc://username:password@database')

    #### matrix of table names by type ######
    prep = {'item_names': ['List', 'Details', 'Rd', 'Fin', 'Status', 'CompletedDetails', 'Syndicate', 'CompanyDetails', 'CompanyContactInfo', 'CompanyTeam', 'Compadvisors', 'CompanyPInvestors', 'CompanyExecSum', 'CompanyCurrentRd', 'CompanyPastRd', 'CompannFin', 'CompanyDocs'],
            'temp_table': ['items_dl', 'items_dd', 'items_dr', 'items_df', 'items_nds', 'items_ncd', 'items_ns', 'items_cd', 'items_cci', 'items_ct', 'items_ca', 'items_cpi', 'items_es', 'items_cr', 'items_pr', 'items_af', 'items_cdoc'],            
            'data_frame': ['dl', 'dd', 'dr', 'df', 'nds', 'ncd', 'ns', 'cd', 'cci', 'ct', 'ca', 'cpi', 'es', 'cr', 'pr', 'af', 'cdoc'],
            'sql_table': ['list', 'details', 'rd', 'fin', 'status', 'completed_details', 'syndicate', 'company_details', 'company_contact_info', 'company_team', 'company_advisors', 'company_pinvestors', 'company_execsum', 'company_current_rd', 'company_past_rd', 'company_ann_fin', 'company_docs']
            }

    #### assigning temporary lists for capturing parsed items ######
    for x in prep['temp_table']:
        globals()[x] = []

    #### create sql schema to receive final output ######
    def __init__(self):
        try: ## Check schema exists, create if not
            SQLPipeline.engine.execute("create schema dealinfo")
        except:
            pass   

    #### clean each scrapy item and add contents to temporary list (ahead of conversion to dataframe) ######
    def process_item(self, item, spider):
        for i in range(len(SQLPipeline.prep['item_names'])):
            if isinstance(item, SQLPipeline.prep['item_names'][i]):####<<---error - not able to call item using string
                for key,value in item.items(): 
                    if isinstance(item[key], list):
                        item[key] = [x.strip() for x in item[key] if x]
                        item[key] = [x for x in item[key] if x]
                        item[key] = ', '.join(item[key])
                SQLPipeline.prep['temp_table'][i].append(item.copy())####<<---error - not able to call item using string

    #### convert parsed items to pandas dataframe before sending to sql as tables ######     
    def close_spider(self, spider):
        for i in SQLPipeline.prep['item_names']:
            try:
                SQLPipeline.prep['data_frame'][i] = pd.DataFrame(SQLPipeline.prep['temp_table'][i])
                print(SQLPipeline.prep['data_frame'][i])
                SQLPipeline.prep['data_frame'][i].to_sql(SQLPipeline.prep['sql_table'][i], SQLPipeline.engine, schema='dealinfo', if_exists='replace', index=False)
            except Exception as ex:
                print(ex)
                pass

Answer 1

我想eval可能对你有帮助。你知道吗

>>> class MyClass():
...     pass
... 
>>> myinstance = Myclass()

>>> type(myinstance)
<class '__main__.Myclass'>

>>> type('myinstance')
<class 'str'>

>>> type(eval('myinstance'))
<class '__main__.Myclass'>

Answer 2

你知道吗胡安帕.阿里维拉加对我的情况有正确的答案-解决了所有问题-现在一切正常。我向上声明了一个列表列表，然后将列表和条目添加到字典中。不需要其他任何东西！你知道吗

    for x in ['items_dl','items_dd','items_dr','items_df','items_nds','items_ncd','items_ns','items_cd','items_cci','items_ct','items_ca','items_cpi','items_es','items_cr','items_pr','items_af','items_cdoc']:
    globals()[x] = []
    prep = {'temp_table': [items_dl, items_dd, items_dr, items_df, items_nds, items_ncd, items_ns, items_cd, items_cci, items_ct, items_ca, items_cpi, items_es, items_cr, items_pr, items_af, items_cdoc],
        'item_names': [List, Details, Rd, Status, CompletedDetails, Syndicate, CompanyDetails, CompanyContactInfo, CompanyTeam, Compadvisors, CompanyPInvestors, CompanyExecSum, CompanyCurrentRd, CompanyPastRd, CompannFin, CompanyDocs],
        'data_frame': ['dl', 'dd', 'dr', 'df', 'nds', 'ncd', 'ns', 'cd', 'cci', 'ct', 'ca', 'cpi', 'es', 'cr', 'pr', 'af', 'cdoc'],
        'sql_table': ['list', 'details', 'rd', 'fin', 'status', 'completed_details', 'syndicate', 'company_details', 'company_contact_info', 'company_team', 'company_advisors', 'company_pinvestors', 'company_execsum', 'company_current_rd', 'company_past_rd', 'company_ann_fin', 'company_docs']
        }

Answer 3

我相信你要找的是getattr()