Help with Python Testing

Technical task Goal Develop a program for automating the flashing of ATmega328P microcontrollers via the NeoProgrammer software on Windows 10 The working algorithm should replicate the actions of the operator. Working algorithm At the beginning of each cycle, execute Ctrl + N. Perform identification (Identify/Detect) of the microcontroller. If the microcontroller is successfully identified — perform its erasure (Erase). Execute Ctrl + O, open the first file, and start its flashing. After the actual completion of the first file's writing, execute Ctrl + O, open the second file, and start its flashing. After the successful completion of the second file, end the cycle and switch to waiting mode for the next microcontroller. Link to video https://drive.google.com/file/d/1ytVcOY17SYN7xKvyiKoKZ80mPUoZbgJt/view?usp=drivesdk https://drive.google.com/file/d/1sh_bxS2bvxcaFzItstsP4RELXtWuIAPW/view?usp=drivesdk Requirements Do not use fixed delays between stages. Transition to the next step should only occur after confirmation of the completion of the current operation. Provide error handling at all stages (microcontroller identification, erasure, file writing, programmer errors, etc.). In case of any error, immediately stop the current cycle, notify the user, and provide the option to restart the cycle from the first step without restarting the program. Provide Start and Stop buttons. The Stop button should allow stopping the process at any moment. The program should operate stably multiple times without freezing and the need for a restart. Additionally Two videos are attached to the technical task: the first — the correct flashing algorithm; the second — an example of an error that the program should handle correctly.

A deep technical verification of three PDF files for authenticity and possible signs of editing or forgery is required. Not only a visual assessment of the documents is needed. The performer must have a good understanding of the internal structure of PDF files and be able to analyze: file metadata; PDF structure and individual objects; creation history and possible editing; software used; embedded fonts, images, layers, and other elements; possible signs of re-saving, conversion, modifications, or backdating of the document; any technical discrepancies that may indicate manipulation of the files. Based on the verification results, a clear written conclusion regarding each file must be provided, indicating the identified signs, risks, and limitations of the verification. We are considering specialists who have practical experience in digital forensics, PDF document analysis, metadata, or verifying electronic files for authenticity. In your response, please briefly describe your experience, methods, and tools that you use for such verification.

The indicator for use in trading should determine certain ranges with history and analyze them with the current one.

Need an experienced Python developer to create an automation program for working with the website. What the bot should do: Log in to my account on the website. Continuously (24/7) monitor for new Work Orders. Upon the appearance of a new order, open its card. Analyze the information about the order (type of work, city, distance, description). Automatically accept orders that meet the specified conditions. If the order does not meet the conditions, skip it. Send notifications in Telegram about accepted and skipped orders. Requirements: Python. Playwright (preferred) or Selenium. Work through a regular browser. Transfer the complete source code after the project is completed. Provide installation and launch instructions. Mandatory experience in developing similar automation systems. When responding, please send examples of similar projects.

A project needs to be implemented for collecting and structuring a large array of images from open web sources (initially 2000 images). The task includes: - automated image collection; - uploading files in the highest available quality; - classifying images by categories. Expected results: - a structured image database; - a clear cataloging system; - delivery of the results via Google Drive or another agreed method;