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Auto-Generate Nim API Client for REST APIs

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Auto-Generate Nim API Client for REST APIs

We've added a new generator to OpenAPI Generator (https://github.com/OpenAPITools/openapi-generator) to generate Nim API clients. To generate the client given an OpenAPI/Swagger specification file, please follow 3 simple steps below: 1. Download the Java JAR (https://oss.sonatype.org/content/repositories/snapshots/org/openapitools/openapi-generator-cli/4.1.3-SNAPSHOT/openapi-generator-cli-4.1.3-20190913.092234-8.jar) 2. Rename the JAR as "openapi-generator-cli.jar" 3. Run the following command to generate a Ruby API client for the Petstore API (https://raw.githubusercontent.com/OpenAPITools/openapi-generator/master/modules/openapi-generator/src/test/resources/2_0/petstore.yaml): Mac/Linux: $ java -jar openapi-generator-cli.jar generate -g nim -i https://raw.githubusercontent.com/OpenAPITools/openapi-generator/master/modules/openapi-generator/src/test/resources/2_0/petstore.yaml -o /var/tmp/nim/ Windows: $ java -jar openapi-generator-cli.jar generate -g nim -i https://raw.githubusercontent.com/OpenAPITools/openapi-generator/master/modules/openapi-generator/src/test/resources/2_0/petstore.yaml -o C:\tmp\nim If you've any feedback or question, please let us know via https://github.com/OpenAPITools/openapi-generator/issues/new Thanks for the new generator by Hideki Okamoto (https://github.com/hokamoto) Ref: https://github.com/OpenAPITools/openapi-generator/pull/3879

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, user, new · Missing: agents, macos, agent
39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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