Development of parsing programmes in Python

About the project: We are launching a B2B service for end-to-end analytics and advertising campaign management for targeters and media buyers. The product will work with the official Meta API. The main technical challenge and focus of the project is the expert handling of Facebook limits, traffic routing between our application pool, and a robust infrastructure protection system against the blocking of gray advertising accounts. We already have a detailed technical specification, the architecture of databases is described, the logic of the load balancer, and the requirements for interfaces. We are looking for a contractor who will take this for turnkey implementation (backend + frontend dashboards). What needs to be done (Key tasks): Integration with Meta API: Set up user authorization and regular asynchronous parsing of advertising account statistics. Requests must be sent exclusively in batches to save limits. Auto-unlinking system for accounts: Write a module that continuously monitors the statuses of advertising accounts. If an account gets banned, the system must automatically revoke the access token within 60 seconds to protect our application from Meta sanctions. Proxy infrastructure: Implement tunneling of all API requests through a SOCKS5 pool. A strict binding of a specific user token to a static IP address is mandatory. Smart routing: Create an algorithm that will distribute bindable advertising accounts among several of our Facebook applications in specified proportions to reduce risks. Interface development: Create a client dashboard with a summary statistics table and an advanced admin panel for manual management of user limits, application bindings, and proxy pool. Expected technology stack: Backend: Python, FastAPI. Asynchronous tasks: Celery, Redis. Databases: PostgreSQL (or ClickHouse for statistics, at your discretion). Frontend: Vue.js or React (you can use ready-made UI libraries and dashboard templates, focusing on functionality rather than complex design). Requirements for the contractor: Confident experience with Meta Graph API and Marketing API. You should understand how sliding limits work, how to read load headers, and how to work with tokens. Understanding the specifics of traffic arbitration. The words "billing," "account ban," "business manager," and "farm" should not raise questions for you. Experience in building asynchronous parsers and working with proxy servers at the network request level. Willingness to work according to a clear technical specification and deliver the project in stages. Conditions: Collaboration format: Project work (with the possibility of transitioning to long-term support and development of new modules). Budget: Discussed individually based on your assessment of the technical specification. Payment: Staged, tied to checkpoints. How to respond: In your cover letter, be sure to indicate your experience with Meta API, attach links to similar projects (or describe their functionality if they are under NDA), and provide an estimated price range and timeline for developing a similar system from scratch. Responses without a description of relevant experience with Facebook API will not be considered.

A local Python script needs to be developed to automatically fill a Google Sheet with data from the company's internal service. Main logic: 1. Connect to the Google Sheet. 2. Find rows where the ID is filled but two target values are missing. 3. Form a link based on the template: https://internal-service.example/item/{ID} 4. Retrieve the two values (via API, if it exists, otherwise via Playwright). 5. Write the values back to the Google Sheet. 6. Mark the row as processed. 7. Continue processing the next rows. Requirements: • Python • Google Sheets API • Priority to use the official API • If no API — Playwright • No OCR, screen recognition, or mouse coordinates • Confidential data must not be logged • Configuration via .env • Test mode (without writing to the sheet) • Do not process already filled rows • Batch write changes to Google Sheets • Proper error handling and retries It is necessary to provide: - source code; - requirements.txt; - example .env.example; - installation instructions; - running instructions; - brief architecture description. Before starting implementation, please: 1. Suggest an architecture. 2. List the necessary accesses. 3. Ask clarifying questions. 4. Indicate the cost, deadlines, and estimated number of hours.

As part of enhancing the cybersecurity level of our infrastructure, we need to abandon the practice of storing "eternal" and static API keys, passwords, and integration tokens in the configuration files (.env, appsettings.json, config.yaml) of our microservices. Business Goal: Create a single secure storage point for confidential data (secrets) with a mechanism for their automatic updating (rotation) in external systems on a schedule. Our other services will request current tokens "on the fly" via API, which will minimize damage in case of compromise of any system component.Security Model and Encryption (Crypto Core) No secret should be stored in plaintext in the database. Upon application startup, a Master Key is passed to the environment variables. If the key is missing or has an invalid length, the service should fail at the initialization stage with a clear error in the logs. Each secret is encrypted before being written to the database using this Master Key. Upon request, it is decrypted in memory and returned in the response body.Audit Logging (Audit Trail) Any action with secrets (creation, reading by the service, successful or unsuccessful rotation) must be recorded in a separate log file audit.log (or a separate table in the database). Strict Taboo: It is strictly prohibited to record the actual values of secrets in the audit log (neither in plaintext nor in encrypted form).

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.

Bot for mirroring positions on Binance Futures (Python) A bot is needed that reads my positions on Hyperliquid (public API) and Bitget Futures (my read-only key) and proportionally replicates them on my Binance USDT-M Futures via API. Logic: opening, increasing, partial closing, full closing — everything is mirrored with a customizable size ratio. Polling every 5–10 seconds. Correct handling of partial closures and averaging is mandatory. Requirements: notifications in Telegram about trades and errors; config (pairs, ratio, limits); deployment on my VPS + instructions; source code is transferred to me. I will enter the keys myself. Stages: 1) Hyperliquid→Binance, test with small amounts; 2) Bitget→Binance. Payment through safe in stages. In your response, indicate your experience with exchange APIs and how you will handle a partial closure of 30% of the position by the leader.