Parsing contacts from LinkedIn

An experienced 1C programmer is needed for a one-time data migration from 1C to a new CRM system. It is necessary to export data from 1C while preserving all relationships between entities: products, clients, receipts, invoices, balances, product movement history, and other directories. The export format can be JSON, SQL, or any other format convenient for further import. The main requirement is to maintain the data structure and all relationships between documents and objects so that the data can be correctly transferred to another CRM without loss of information. Experience in data migration between 1C and third-party systems will be an advantage. There is no need to migrate to another CRM, just provide a file or create functionality to save a dump file locally on click. Everything is managed locally, so you will need to work through AnyDesk or something similar. I don't know the prices for such work, so please make your offers.

Need a specialist for writing parsers who can bypass CLOUDFRAME. Parsing of products occurs from sites with authorization. There are 10+ donors of varying complexity, with different levels of protection. Parsing of products occurs from sites with authorization. Parses data into a ready-made Mysql database + photographs on the server. It is necessary to write a parser according to the tasks described in the technical assignment and adapt the data to the existing database for full functionality on the site. Technical assignment and example donor upon request. Desktop parsers and C# are not considered.

A Telegram bot needs to be created with a program that will monitor listings on three apartment rental websites (olx, lun, rieltor.ua) and send them structured in Telegram.

it is necessary to organize a way to collect newly created individual entrepreneurs and, if possible, limited liability companies. whether it's parsing or something else - you tell me what this method should be

About the Company Trading company. We work with a product group of more than 2000 items across different categories.Current Situation Currently, the nomenclature is maintained in Google Sheets — data is consolidated by tabs (categories). Tab Structure: Product name Price groups: cost price, wholesale, retail Characteristics: weight, quantity per package, etc. Important: the number of columns varies for different product categories, as they have different characteristics.Why the Current Solution is Inadequate Google Sheets does not allow setting access rights at the level of individual columns. We need to: Grant users rights to view certain columns (for example, only cost prices) Grant rights to edit certain columns (for example, retail prices) While restricting access to other columns in the same tabWhat Needs to Be DoneMain Requirements Flexible Rights Management System Access at the level of individual columns (read/write) Assignment of rights by roles or users Management of rights without the involvement of programmers Support for Different Data Structures Different product categories have different sets of characteristics Adding new columns/characteristics without programming Independence from Developers Administration by internal staff Adding categories, columns, users — through the interface Integration with ERP Exporting current prices to our ERP system Export or automatic integration via API Data Analysis Using AI (preferably) Ability to analyze the entire nomenclature list Enrichment, verification, recommendations — if you have ideas, please describeExpected Result A working solution in which: The nomenclature is structured by categories with different sets of characteristics Column rights are flexibly configured (view/edit) Data is exported to ERP The team can manage the system independentlyWhat We Need from You When Responding Describe in general terms how you envision the solution: What tool/platform do you propose