<? phpclass BaseLogic extends MyDB { protected $tabName; protected $fieldList; protected $messList; function add($postList) { $fieldList=''; $value=''; foreach ($postList as $k=>$v) { if(in_array($k, $this->fieldList)){ $fieldList.=$k.","; if (!get_magic_quotes_gpc()) $value .= "'".addslashes($v)."',"; else $value .= "'".$v."',"; } } $fieldList=rtrim($fieldList, ","); $value=rtrim($value, ","); $sql = "INSERT INTO {$this->tabName} (".$fieldList.") VALUES(".$value.")"; echo $sql; $result=$this->mysqli->query($sql); if($result && $this->mysqli->affected_rows >0 ) return $this->mysqli->insert_id; else return false; }
This is a PHP class for data processing. Friends who need it can download it and use it.
The name of the table and the set of fields, which have the following functions:
Function: add($postList)
Function: Add
Parameters: $postList Submitted variables List
Returns: The newly inserted auto-increment ID
All resources on this site are contributed by netizens or reprinted by major download sites. Please check the integrity of the software yourself! All resources on this site are for learning reference only. Please do not use them for commercial purposes. Otherwise, you will be responsible for all consequences! If there is any infringement, please contact us to delete it. Contact information: admin@php.cn
Related Article

18 Jul 2025
When processing big data, the key to Java performance optimization lies in four aspects: 1. Rationally set JVM memory parameters to avoid frequent GC or resource waste; 2. Reduce the overhead of serialization and deserialization, and choose efficient libraries such as Kryo; 3. Use parallel and concurrency mechanisms to improve processing capabilities, and use thread pools and asynchronous operations reasonably; 4. Choose appropriate data structures and algorithms to reduce memory usage and improve processing speed.

16 Jul 2025
WebStreamsAPI is a standard interface for efficient processing of streaming data. It mainly includes three stream types: ReadableStream, WritableStream and TransformStream. It is suitable for large file uploads, real-time audio and video processing and other scenarios. The advantage is that it can process data in chunks, reduce memory usage and improve response speed. When using it, streaming operations are usually combined with FetchAPI or file reading, such as parsing JSON while downloading, or uploading files while reading. Practical applications include file upload optimization, data analysis speedup and real-time audio and video processing. Notes include checking browser compatibility, improving error handling, reasonable control of back pressure and timely shutting down flow to avoid resource leakage

21 Jul 2025
Geospatial data processing is a technology that ordinary people can master. Its core lies in understanding five steps: first, clarify the data source and format, such as Shapefile, GeoJSON, KML, GPX and PostGIS; second, carry out data cleaning and pre-processing, including deduplication, unified projection, complementary attributes and checking coordinate validity; third, analyze and visualize based on business needs, such as heat map, buffer analysis, distance calculation and cluster analysis; fourth, select appropriate output formats for display or sharing, such as GeoJSON, PDF, PNG, Shapefile or CSV; fifth, attach data descriptions to ensure that others can correctly understand and use them. As long as you master these key points and practice them manually, you can be effective

25 Jul 2025
The core of efficient data processing is to select the right tools and use the right methods. 1. The data input and output should be fast, and binary formats such as Parquet and Feather should be used first. Batch reading will reduce I/O overhead, and add indexes to avoid full table scanning when querying databases. 2. Parallel processing should select multi-process or single-thread according to the task type. Large-scale data can be used to implement distributed computing with Dask or PySpark. 3. Data cleaning requires processing missing values and outliers in advance, unify the field format and delete duplicate data to avoid subsequent errors affecting efficiency. Controlling the details of each link is the key to improving overall performance.

29 Jul 2025
Pythoncanhandleparalleldataprocessingeffectivelybyusingtherighttoolsandapproaches.First,usemultiprocessinginsteadofthreadingforCPU-boundtaskstobypasstheGlobalInterpreterLock(GIL).Second,leveragemultiprocessing.Poolforparallelmap/reducepatternswhilebe

18 Jul 2025
TospeedupPythonforlarge-scaledataprocessing,useefficientdatastructureslikeNumPyarraysandgeneratorstoreducememoryusage.Next,leverageparallelprocessingwithmultiprocessingorlibrarieslikeDasktoutilizemultipleCPUcores.Then,optimizeI/Ooperationsbyreadingan


Hot Tools

PHP library for dependency injection containers
PHP library for dependency injection containers

A collection of 50 excellent classic PHP algorithms
Classic PHP algorithm, learn excellent ideas and expand your thinking

Small PHP library for optimizing images
Small PHP library for optimizing images
