200 lines
4.7 KiB
Python
200 lines
4.7 KiB
Python
#!/usr/bin/python3
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import cherrypy
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import config
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import sqlite3
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import os
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class select(object):
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def __init__(self):
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''' SELECT method for API
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Describes tables in DB, or lists the contents
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Args:
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*None*
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Sets:
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*self.html:* dict(), see Cherrypy docs for more
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Returns:
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*self.html:* string(), html code for rendering
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Raises:
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*RuntimeError* If dB file cannot be found
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'''
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__name__ = "SQLite select API component"
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self.html = ''
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self.json = ''
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def CheckSelect(self):
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''' Checks and sanitizes a query
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Escaping, sanitizing and checking what are we sending to the DB
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Args:
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*query* Query to be sent to the DB
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Sets:
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*N/A*
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Returns:
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*result:* bool(), is the code to be executed OK, or not
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Raises:
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*N/A*
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'''
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return True
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def _cp_dispatch(self, vpath):
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''' Modify the request path, REST way
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Format the variables in a row:
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http://server/method/db_file/table/?values=<>&filter=<>
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Args:
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*vpath* vpath - I don't quite understand this one,
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is it internal, or just a dummy?
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Sets:
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*cherrypy.request.params:* list(), various variable parameters
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for processing
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Returns:
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*vpath:* list(), list of path elements
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Raises:
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*N/A*
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'''
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if len(vpath) == 1:
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cherrypy.request.params['schema'] = vpath.pop()
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return self
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if len(vpath) == 2:
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cherrypy.request.params['table'] = vpath.pop()
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cherrypy.request.params['db'] = vpath.pop()
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cherrypy.request.params['values'] = '*'
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return self
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return vpath
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def sqlite_wrapper(self, db, **kwargs):
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''' Calling the actual data from DB
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Connect to DB, execute a query and return data
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Args:
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*db:* str(), database file name
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***kwargs:* dict(), additional arguments to specify the
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table and filters to retrieve the data by
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Sets:
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*N/A*
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Returns:
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*result:* tuple(), rows from table, or DB schema as a tuple
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Raises:
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*N/A*
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'''
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db_file = f"{config._ROOT}/{db}"
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try:
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open(db_file)
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except Exception as e:
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raise RuntimeError(f"ERROR: Unable to read DB file: {e}")
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conn = sqlite3.connect(db_file)
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c = conn.cursor()
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if len(kwargs) == 0:
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query = f"SELECT sql FROM sqlite_master"
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else:
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query = f"SELECT * FROM {kwargs['table']}"
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c.execute(query)
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result = c.fetchall()
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conn.commit()
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conn.close()
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return result
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def tabelize(self, table_list):
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''' Calling the actual data from DB
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Connect to DB, execute a query and return data
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Args:
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*table_list:* tuple() / list(), rows and items as tuples / lists
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Sets:
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*N/A*
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Returns:
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*table:* str(), html table code made from tuples / lists
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Raises:
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*N/A*
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'''
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table = '<table>'
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for row in table_list:
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table += '<tr>'
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for item in row:
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table += f"<td> {item} </td>"
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table += '</tr>'
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table += '</table>'
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return table
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@cherrypy.expose
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def index(self, **kwargs):
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''' Extending the expose - index method
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Returns html / json output
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Args:
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***kwargs:* dict(), arguments needed for SELECT / SCHEMA
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schema=<db_name> or
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db=<db_name> AND table=<table_name> OPTINALLY
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values=<columns_to_select>, filter=<conditions>
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Sets:
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*N/A*
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Returns:
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*result:* str(), rhtml code to be rendered, or JSON
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Raises:
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*N/A*
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'''
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if 'schema' in kwargs.keys():
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result = self.sqlite_wrapper(
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kwargs["schema"]
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)
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else:
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result = self.sqlite_wrapper(
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kwargs['db'],
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table=kwargs['table'],
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values=kwargs['values']
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)
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self.html = ''
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self.html += self.tabelize(result)
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return self.html
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class insert(object):
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def __init__(self):
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pass
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@cherrypy.expose
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def index(self):
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return 'INSERT'
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class delete(object):
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def __init__(self):
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pass
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@cherrypy.expose
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def index(self):
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return 'INSERT'
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