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Add ClI and ability to create CV in latex from MD
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# Binaries for programs and plugins | ||
anemon | ||
*.exe | ||
*.exe~ | ||
*.dll | ||
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run: | ||
echo "Not yet complete" | ||
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build: | ||
go build | ||
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lint: | ||
golangci-lint run ./... | ||
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package cmd | ||
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import ( | ||
"anemon/internal/parser" | ||
"anemon/internal/walker" | ||
"errors" | ||
"os" | ||
"github.com/spf13/cobra" | ||
) | ||
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var generateCmd = &cobra.Command{ | ||
Use: "generate", | ||
Short: "Generate a CV", | ||
Long: `Generate a CV using the Markdown CV directory in the current work directory`, | ||
RunE: func(cmd *cobra.Command, args []string) error{ | ||
dir, err := os.Getwd() | ||
if err != nil{ | ||
return err | ||
} | ||
CV,err := getSectionMapFrom(dir) | ||
if err != nil { | ||
return err | ||
} | ||
err = createLatexCVFrom(dir,CV) | ||
if err != nil { | ||
return err | ||
} | ||
return nil | ||
}, | ||
} | ||
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//Use a CV map created by `getSectionMapFrom` and write for each lang key a latex CV using the given information | ||
func createLatexCVFrom(dir string, CV map[string]map[string]string )(error){ | ||
for lang := range CV{ | ||
err := parser.Init_output(lang+"-CV",dir) | ||
if err != nil{ | ||
return err | ||
} | ||
for sec_name := range CV[lang]{ | ||
sec, err := parser.Parse(CV[lang][sec_name]) | ||
if err != nil { | ||
return err | ||
} | ||
_,err = parser.ApplyToSection(sec,sec_name,dir+"/assets/latex/output/"+lang+"-CV.tex") | ||
if err != nil { | ||
return err | ||
} | ||
} | ||
} | ||
return nil | ||
} | ||
//TODO consider struct for this map of map | ||
//Walk throught the CV directory and return a map of lang within each their is a map of section | ||
func getSectionMapFrom(dir string)(map[string]map[string]string,error){ | ||
cv_path := dir+"/cv" | ||
_, err := os.Stat(cv_path) | ||
if err != nil{ | ||
if os.IsNotExist(err) { return nil, errors.New("No `cv` directory found at:"+cv_path) } | ||
return nil,err | ||
} | ||
result, err := walker.WalkCV(cv_path) | ||
if err != nil{ | ||
return nil,err | ||
} | ||
return result,nil | ||
} | ||
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func init() { | ||
rootCmd.AddCommand(generateCmd) | ||
} |
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package cmd | ||
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import ( | ||
"os" | ||
"github.com/spf13/cobra" | ||
) | ||
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var rootCmd = &cobra.Command{ | ||
Use: "anemon", | ||
Short: "a CV genrator", | ||
Long: `This CLI tool, written in Go, automates the generation of customized CVs from Markdown files based on a specified configuration. It parses CV sections in | ||
multiple languages, prioritizes key skills or features as defined in an output.yml file, and outputs LaTeX files for each CV version, ready for compilation.`, | ||
} | ||
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func Execute() { | ||
if err := rootCmd.Execute(); err != nil { | ||
os.Exit(1) | ||
} | ||
} |
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# Back-End Intern | ||
## February 2024 -- August 2024 | ||
### Qonto | ||
#### End of studies internship | ||
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- Contributed within a Cross Functional Team (CFT) to the standardization and extension of the onboarding process for four new markets (Austria, Netherlands, Belgium, Portugal). From design to implementation, in coordination with stakeholders (Risk, AML, Product), to ensure a smooth and compliant integration, with deployment scheduled for August. | ||
- Led the extraction of back-office logic from a Ruby monolith into a microservice, deploying in a trunk-based development environment. Collaborated closely with the Ops teams throughout the process. Monitored production using Grafana, Sentry, ArgoCD, and Kibana to ensure quality and reliability, enhancing system maintainability by decoupling microservices. | ||
- Improved the reliability and observability of microservices by completing the tracing mechanisms and implementing Service Level Objectives (SLOs). | ||
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# Full Stack Developer | ||
## June 2023 -- September 2023 | ||
### Coexel | ||
#### Internship then Fixed-Term Contract | ||
|
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- Designed and developed a Python service for Named Entity Recognition (NER) using spaCy to efficiently identify named entities in 92M+ documents. Utilization of Elasticsearch for storage and optimized document search, enabling users to gain further insights into monitored themes. | ||
- Rewrote an old website monitoring system created in Java to Python, enhancing maintainability and system performance. | ||
- Implemented a RESTful API in Python using FastAPI, providing increased flexibility and scalability for data management and requests. | ||
- Created a deployment pipeline with Docker and Github Actions, streamlining the deployment process and enabling faster and more robust updates. | ||
- Significantly improved performance by reducing the number of GET requests from 5 to 1, resulting in an 85\% faster display |
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- [Master's in Computer Science, Software and Data Engineering](https://www.univ-tln.fr/Master-Informatique-parcours-Developpement-et-Ingenierie-des-Donnees.html) | ||
- University of Toulon, 2024 | ||
# Master's in Computer Science, Software and Data Engineering | ||
## https://www.univ-tln.fr/Master-Informatique-parcours-Developpement-et-Ingenierie-des-Donnees.html | ||
### University of Toulon | ||
#### 2024 | ||
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- [Bachelor's in Computer Science](https://www.univ-tln.fr/Licence-Informatique-parcours-Informatique.html) | ||
- University of Toulon, 2022 | ||
# Bachelor's in Computer Science | ||
## https://www.univ-tln.fr/Licence-Informatique-parcours-Informatique.html | ||
### University of Toulon | ||
#### 2024 |
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**Agenda** | ||
*Java, JavaFX, PostgreSQL, Github [GitHub Repository](https://github.com/MasterDID2022/sopra-project-LHD)* | ||
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# Agenda | ||
## Java, JavaFX, PostgreSQL, Github | ||
### https://github.com/MasterDID2022/sopra-project-LHD | ||
- Developed in Java and JavaFX, using PostgreSQL for database management. | ||
- Project executed in an agile environment, emphasizing GitHub Flow, Pull Requests, Kanban, and Continuous Integration for effective collaboration. | ||
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**Epigraphy Tools** | ||
*Java, Hibernate, Docker, REST, JWT [GitHub Repository](https://github.com/MasterDID2022/epicTool)* | ||
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# Epigraphy Tools | ||
## Java, Hibernate, Docker, REST, JWT | ||
### https://github.com/MasterDID2022/epicTool | ||
- Designed and developed an epigraphy annotation tool for deep learning using Java, Docker, REST, and JWT. | ||
- Separated the front-end and back-end using Docker with container orchestration via Docker-Compose. | ||
- Established secure communication between the front-end and back-end through a RESTful API with JWT tokens. | ||
- Worked as a team in an agile context, utilizing the SCRUM method and applying DevOps practices for efficient and collaborative development. | ||
|
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github.com/cpuguy83/go-md2man/v2 v2.0.4/go.mod h1:tgQtvFlXSQOSOSIRvRPT7W67SCa46tRHOmNcaadrF8o= | ||
github.com/google/go-cmp v0.6.0 h1:ofyhxvXcZhMsU5ulbFiLKl/XBFqE1GSq7atu8tAmTRI= | ||
github.com/google/go-cmp v0.6.0/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY= | ||
github.com/inconshreveable/mousetrap v1.1.0 h1:wN+x4NVGpMsO7ErUn/mUI3vEoE6Jt13X2s0bqwp9tc8= | ||
github.com/inconshreveable/mousetrap v1.1.0/go.mod h1:vpF70FUmC8bwa3OWnCshd2FqLfsEA9PFc4w1p2J65bw= | ||
github.com/russross/blackfriday/v2 v2.1.0/go.mod h1:+Rmxgy9KzJVeS9/2gXHxylqXiyQDYRxCVz55jmeOWTM= | ||
github.com/spf13/cobra v1.8.1 h1:e5/vxKd/rZsfSJMUX1agtjeTDf+qv1/JdBF8gg5k9ZM= | ||
github.com/spf13/cobra v1.8.1/go.mod h1:wHxEcudfqmLYa8iTfL+OuZPbBZkmvliBWKIezN3kD9Y= | ||
github.com/spf13/pflag v1.0.5 h1:iy+VFUOCP1a+8yFto/drg2CJ5u0yRoB7fZw3DKv/JXA= | ||
github.com/spf13/pflag v1.0.5/go.mod h1:McXfInJRrz4CZXVZOBLb0bTZqETkiAhM9Iw0y3An2Bg= | ||
golang.org/x/text v0.18.0 h1:XvMDiNzPAl0jr17s6W9lcaIhGUfUORdGCNsuLmPG224= | ||
golang.org/x/text v0.18.0/go.mod h1:BuEKDfySbSR4drPmRPG/7iBdf8hvFMuRexcpahXilzY= | ||
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0= | ||
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM= |
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