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102 lines
4.5 KiB
Markdown
102 lines
4.5 KiB
Markdown
# FELICITY LIMS (under active development)
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A next generation open source laboratory information management system for clinical/medical laboratories.
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## Descritpion
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The Felicity LIMS project aims to create a Laboratory Information Management System (LIMS) that tracks the complete laboratory workflow providing all the functionalities of a Laboratory Information Management System.
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Felicity strives to promote an accurate flow of sample and associated experimental data to and through a laboratory to produce information that is used to make conclusions and critical decisions.
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Felicity LIMS will ensure that sufficient metadata is captured and clinical laboratory personnel can track the lifecycle of a biospecimen in the laboratory from receipt to dispacth.
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Felicity Backend is developed in Python using the FastAPI framework and strawberry GraphQL.
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Felicity FrontEnd is developed in VueJs, URQL, and Tailwind CSS.
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Felicity is the quality of being good, pleasant, or desirable.
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## Main Features
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- Sample status tracking
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- Flexible batched sample workflow
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- Quality control
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- Reporting
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- Highly customizable and extensible
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- Micro kanban Project management
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- Experimental Markdown Document manager
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## Installation
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### Direct
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#### Backend Installation
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##### using poetry
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Fist install [Poetry](https://python-poetry.org/docs/#installation)
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Then follow instructions below
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```shell
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git clone https://github.com/aurthurm/felicity.git
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cd felicity
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cd backend/felicity_lims
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poetry install
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bash felicity.sh &
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````
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##### using anaconda
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Fist install [Miniconda](https://docs.conda.io/en/latest/miniconda.html)
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Then follow instructions below
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```shell
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conda create -n felicity python=3.9
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conda activate felicity
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git clone https://github.com/aurthurm/felicity.git
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cd felicity
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cd backend/felicity_lims
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pip install -r requirements.txt
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bash felicity.sh &
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````
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#### Frontend Installation
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Install [NodeJs](https://github.com/nodesource/distributions/blob/master/README.md#installation-instructions)
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Install [Yarn](https://yarnpkg.com/getting-started/install)
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Then follow instructions below
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```shell
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cd felicity/frontent/vite
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yarn install
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# for production mode
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yarn build
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yarn start
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# for development mode
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yarn dev
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````
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### Docker
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This method uses Docker and docker-compose which handles the details of installing dependencies for you. On your Linux command line, run:
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```shell
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git clone https://github.com/aurthurm/felicity.git
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cd felicity
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docker-compose up -d
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```
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### Loadtest
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Start the application with gunicorn and experiment with various workers
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```shell
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gunicorn --workers 4 --bind 0.0.0.0:8000 -k uvicorn.workers.UvicornWorker --reload felicity.main:flims
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```
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Experiment with various -c and --rps values
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```shell
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sudo npm install -g loadtest
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loadtest --data '{"query": "query{clientAll{items{uid name code district{uid name email emailCc province{uid name code country{uid name}}}}}}"}' -c 4 --rps 500 http://localhost:8000/felicity-gql -T 'application/json'
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loadtest --data '{"query": "query getAllSamples{sampleAll(pageSize:10 afterCursor:\"\" status:\"\" text:\"\" clientUid:0 sortBy:[\"uid\"]){totalCount pageInfo{hasNextPage hasPreviousPage endCursor startCursor __typename}items{uid analysisRequest{uid clientRequestId patient{uid firstName lastName clientPatientId gender dateOfBirth age ageDobEstimated consentSms __typename}client{uid name __typename}__typename}sampleType{uid name __typename}sampleId priority status analyses{uid name sortKey __typename}profiles{uid name __typename}rejectionReasons{uid reason __typename}__typename}__typename}}"}' -c 10 --rps 10000 http://localhost:8000/felicity-gql -T 'application/json'
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```
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The application seems to be very performant even without using a load balancer and caching.
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## Other projects
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- Felicity Docs - Built with Laboratory QMS in Mind but can be used anywhere for document management
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- Felicity Stocker - Medical Laboratory Inventory Management system
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- Felicity Request - Requests and Approvals (e-Requisitions)
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- Felicity Teams - Project Management Tool
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- Felicity Field - Survey Data Collection Tool, Forms ,Analytics etc
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## Contact
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- [EMail](mailto:aurthurmusendame@gmail.com?subject=[GitHub]%20Felicity%20Lims%20Enquiry)
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- [Facebook](https://www.fb.me/aurthur.musendame)
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- [LinkedIn](https://www.linkedin.com/in/aurthurmusendame)
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- [Whatsapp](https://api.WhatsApp.com/send?phone=263776406399)
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- [Telegram](https://www.t.me/aurthurm)
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