need to run a multiprocess python code

Hello, I have 10 years of experience in optimizing Python code for high-performance computing environments. I propose deploying your Python code on AWS using EC2 instances to access 20,000 cores efficiently. I will provide detailed instructions and a concise explanation of the setup. This approach ensures scalability and easy retrieval of results with unique process identifiers. Regards, VishnuLal NB

Hi, Thanks for sharing the details. I have a lot of experience with multi-processing and pooling, so I’d be happy to help. Could you explain a bit more about what you’re trying to do? For example: > How do you want to store the results (e.g., S3 or something else)? > Are the processes independent, or do they need to communicate? Once I know more, I can recommend the best option (Lambda, Batch, or EC2) and guide you through the setup. Looking forward to your reply! Cheers, Rizwan

"Run 20,000 Python jobs at scale with AWS Batch." Hi, Based on your requirements, I will design an efficient solution that allows you to run the code across either one powerful machine or a distributed cluster of machines, with each process storing its intermediate results in a common location. ---> AWS Batch is best way to do this:- 1. Best for High-Volume, Parallel Jobs: It can efficiently manage the orchestration and scheduling of thousands of jobs and is ideal for scenarios like yours where you need to run 20,000 processes. 2. Scalability: AWS Batch automatically provisions the necessary compute resources (EC2 instances) to meet the job requirements, scaling up and down as needed. 3. Simplifies Task Management: Each process can be assigned a unique ID and can store results in a common location like S3. AWS Batch also handles failures and retries automatically. 4. Cost-Efficient: You only pay for the compute resources used, and it’s more cost-effective for high-volume jobs compared to EC2. ## Instructions to do : Step 1: Set up AWS Batch Environment Step 2: Create a Compute Environment in AWS Batch Step 3: Create a Job Definition Step 4: Add Process ID for Each Job Step 5: Submit Jobs to the Queue Step 6: Retrieve Results I would be happy to discuss further details to refine the approach and get started on the solution. Thank you for considering my proposal. I look forward to assisting you with this exciting project. Best regards, Anuj

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Hi Thank you for the opportunity to bid on your project. An experienced AWS developer, I am ready to start right now on setting up your Python code to run concurrently on AWS utilizing 20000 cores. With expertise in Lambda, Batch, and EC2, I will provide detailed instructions on the optimal approach tailored to your specific requirements, along with a comprehensive explanation of the implemented solution for seamless execution and monitoring. Looking forward to delivering efficient and reliable results for your project. Looking forward to the opportunity to collaborate and bring your project to life. Kind regards, Haroon Z .

Leverage my vast experience and comprehensive understanding of Python to successfully run your multiprocess code. I am well-versed in AWS ecosystem, which includes key services like Lambda, Batch, and EC2 that you've mentioned in your project description. Based on my familiarity with these services, I can not only offer you with detailed instructions on the best way forward, but also provide you with an insightful report explaining what I undertook for this project. Having worked with numerous clients across a variety of industries, I have consistently shown myself capable of delivering effective yet concise solutions through clear instructions. I can do the same for you - combining my technical abilities and expertise in data analysis to provide you with a hassle-free guide to running your code efficiently on AWS 20000 cores. Rest assured, as a highly organized professional who pays keen attention to detail, I will ensure that each process is assigned a meticulous and unique identifier. My skill set alongside my work ethic matches perfectly to what you're looking for from the project. Take the first step towards a successful project by choosing me as your freelancer.

Hello Prospect, I have multi multi process programing experience. I would use lambda or ec2 or multi threading depending upon program needed. Thank you,

**Ready to start now to get your work done ASAP ** When you want to start this project? I reviewed your project. I have all relevant skills, experience that you need for your project. I can provide all the assistance within your project scope. Let's do have quick interaction and can share your estimate time hours or fix cost for this app. Waiting here in chat for fruitful discussion. Thanks! Gaurav

Hi, processing large volumes of data using multiprocessing is great, but writing to one file or resource means you're I/O bound. Each worker in a processing pool gets a unique thread ID, but if you want a custom ID or name you have to pass that as an argument.

Hello Olga, Our company, Codenia Technologies LLP, with 10+ years of experience in Amazon Web Services and Python, has carefully reviewed your project requirements. To efficiently run your multiprocess Python code on AWS with 20000 cores, we propose utilizing AWS Batch for managing and executing batch computing workloads at any scale. By setting up a job queue and compute environment on AWS Batch, we can assign unique IDs to each process and store the intermediate results in a common location for easy access. We would like to further discuss your project requirements and implementation details in a chat. Please let us know a convenient time to connect and delve deeper into the specifics. Thanks, Rupesh Kumar

Hello! I propose to create a service in NodeJS, which is in charge of the execution of Python processes. Additionally, a service could also be created to centralize the information obtained by them to coordinate their saving or sending as the case may be. This process could be executed with PM2, so that in case of restart it is executed automatically. Greetings!

As a full-time developer with extensive experience in Python, AWS, and distributed computing, I am confident that I can help you effectively execute your multiprocessing code on a massive scale. With my strong understanding of AWS services like Lambda, Batch, and EC2, I will provide you with comprehensive and tailored instructions for running your code. As part of my offer, I will not only outline the steps and configurations for running 20,000 processes either on a single machine or multiple machines but also provide you with an insightful explanation of the approach I took. My proficiency in communicating complex technical concepts ensures that you will have a clear understanding of what is happening at each stage. With me on board, you won't just get a set of instructions; you'll have a reliable partner who understands your project needs and can proactively troubleshoot any challenges that may arise. Beyond 20,000 cores on AWS, I also have experience building web and mobile projects covering multiple skill sets. Let's team up to push boundaries and achieve unprecedented speed and performance for your python code.

Hello Olga K., I understand that you require running a Python code continuously on AWS with 20000 cores, either on one machine or multiple machines, and assigning an ID to each process for easy tracking. I propose to utilize my expertise in Python to implement a multiprocess solution using AWS services such as Lambda, Batch, or EC2. You can review my portfolio for past projects involving Python development and AWS integration here: https://www.freelancer.com/u/sobia49 I assure you of effective communication throughout the project to ensure your requirements are met. Best regards, Sobia

I am a skilled Python developer with experience in multiprocessing and AWS services. I can help you efficiently run your code on AWS using either Lambda, Batch, or EC2 based on your specific requirements. I will provide clear instructions on setting up the processes and assigning unique IDs for each one, along with a detailed explanation of the implementation. Let's optimize your code's performance together.

Hi "AWS Batch" is the best option, given your requirement for running continuously and managing 20,000 processes. It allows you to efficiently manage a large number of jobs, automatically scaling the resources needed and providing an easier way to handle job outputs. AWS Batch can handle job dependencies and scheduling and easier to manage than EC2 for large-scale batch processing. To carry out your project, we need to define how your Python script should run, including the Docker image if needed. And we should choose the instance types and scaling policies, submit your jobs to AWS Batch, ensuring each job has a unique identifier. Finally, we can use Amazon S3 or another storage service to collect and store the results from each job. According to my experience, I can complete your project perfectly. Please reach out me for more discussion. Thank you.

Hi, this is Vahitha Banu . I am a AWS certified solutions architect associate. I have experience in AWs cloud services. I hope I can do this project in a best way possible

Hello, I'm expert in Python scripts to run on cloud plateforms. Let me help you with this task. Add me for your chat to discussed and proceed further.

As a seasoned full-stack developer who specializes in Python, I possess the expertise needed to execute your project flawlessly. Python is renowned for its multiprocessing capabilities and I'm well-versed in leveraging this feature to optimize performance just like you need. My experience with large-scale projects has familiarized me with the benefits and complexities of running a multiprocess program on cloud platforms like AWS. The deliverables you need perfectly align with what my skillset can produce, whether it's encoding instructions or documenting the entire process in clear and concise terms. My competency goes beyond Python. Over the course of my 8 years career, I've become proficient in various backend technologies such as Node.js, Django, and ASP.NET which are advantageous for manipulating and managing the data generated by each process. These skills would ensure that your multiple outputs from different cores are not only properly organized but also stored centrally, making it easy for you to access and analyze them. I can also provide you with instructions on using a serverless model on AWS (Lambda) or utilizing virtual machines (EC2). Choosing me as your freelancer guarantees more than just skills and experience; it offers a partnership dedicated to delivering innovative and tailored solutions that consistently exceed expectations. So, let's embark on this exciting journey together!

????Hi???? Thank you for the opportunity to bid on your project. An experienced AWS developer, I am ready to start right now on setting up your Python code to run concurrently on AWS utilizing 20000 cores. With expertise in Lambda, Batch, and EC2, I will provide detailed instructions on the optimal approach tailored to your specific requirements, along with a comprehensive explanation of the implemented solution for seamless execution and monitoring. Looking forward to delivering efficient and reliable results for your project. Looking forward to the opportunity to collaborate and bring your project to life. Kind regards.

Hello, I'm excited to help you run your Python code on AWS with 20,000 processes. Here's my approach: Objective: Run the Python code continuously with 20,000 processes on AWS, collecting intermediate results in a common text file with unique IDs for each process. AWS Services Overview: Using AWS EC2 instances for flexibility and control. AWS Batch and Lambda are considered but EC2 suits large-scale operations best. Steps to Accomplish the Task: Provision EC2 Instances: Launch multiple EC2 instances with necessary cores. Use EC2 Auto Scaling for dynamic workload management. Configure Environment: Set up shared storage like Amazon S3 or EFS for storing results. Ensure all EC2 instances write results to shared storage. Run Python Code: Use a task queue system like Celery to distribute tasks across instances. Assign unique IDs using Celery’s task ID feature. Monitor and Optimize: Implement monitoring with AWS CloudWatch. Adjust resources based on performance metrics. Deliverables: Instructions to set up and run the Python code on AWS. A short text file explaining the implementation steps. Why Choose Me: Expertise in AWS and Python for managing large-scale distributed systems. Efficient communication with regular updates and clear documentation. Thank you for considering my proposal. Best regards, Mohammed Zainul Abid Phone: 7899266604