Automation of sending requests on page

We are looking for a Middle Python or JavaScript developer for a long-term part-time project involving the evaluation, validation, and technical audit of artificial intelligence responses (LLM models). The work does not involve writing code from scratch but rather analytical verification of already generated scripts and algorithms. What needs to be done: 1. Analyze technical tasks and compare two code options created by different AI models. 2. Conduct mental debugging, find logical errors, syntax bugs, or inefficient use of memory/resources. 3. Evaluate which code option is more optimal and write a clear, detailed analytical report in English. The report should explain where the error is and how to fix it. Candidate requirements: Commercial experience in Python (Django / FastAPI) or JavaScript / TypeScript development for at least 2 years. English language level — B2/C1 (Advanced). Writing technical reports is a key part of the job. High self-discipline and attention to detail. Strict requirement: 100% manual report writing (any use of ChatGPT or other AI assistants during work is completely prohibited, the system undergoes a linguistic anti-fraud audit). Working conditions and format: Fully flexible schedule (Flexible On-Demand). Tasks appear in a stream. You can work at a time convenient for you (morning, afternoon, or evening). Work volume: on average from 3 to 4 hours per day on one work module (can be combined with main work). Depending on your productivity, there is a possibility of expansion and handling multiple modules in parallel, which directly scales income. All tasks are performed exclusively within our configured, secure remote working environment. Payment: fixed hourly rate from 20 to 30 USD per hour (depending on your technical level). Payments are made weekly in a format convenient for you (USDT or currency). Please briefly describe your experience with Python/JS in your response and confirm your English language level. Ready to start as soon as possible.

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.