List trending repos
Trending repos is an open source alternative to GitHub trends, which showcases recently popular open source projects in the GitHub community.
Note
Please URI encode the requested parameters, e.g.
C++
needs to be encoded asC%2B%2B
.
☁️ Daily run on TiDB Cloud, analyze upon dataset that has over 6 billion GitHub events.
Query Parameters
Possible values: [past_24_hours
, past_week
, past_month
, past_3_months
]
Default value: past_24_hours
Specify the period of time to calculate trending repos.
Possible values: [All
, JavaScript
, Java
, Python
, PHP
, C++
, C#
, TypeScript
, Shell
, C
, Ruby
, Rust
, Go
, Kotlin
, HCL
, PowerShell
, CMake
, Groovy
, PLpgSQL
, TSQL
, Dart
, Swift
, HTML
, CSS
, Elixir
, Haskell
, Solidity
, Assembly
, R
, Scala
, Julia
, Lua
, Clojure
, Erlang
, Common Lisp
, Emacs Lisp
, OCaml
, MATLAB
, Objective-C
, Perl
, Fortran
]
Default value: All
Specify using which programming language to filter trending repos. If not specified, all languages will be included.
- 200
Default Response
Schema
- Array [
- ]
- Array [
- ]
Possible values: [sql_endpoint
]
The type of the endpoint.
data object required
columns object[] required
The name of the column in the query result.
Possible values: [CHAR
, BIGINT
, DECIMAL
, INT
, UNSIGNED BIGINT
, TINYINT
, TIMESTAMP
, TEXT
, VARCHAR
, DATETIME
, DOUBLE
, FLOAT
, DATE
, TIME
, YEAR
, MEDIUMINT
, SMALLINT
, BIT
, BINARY
, VARBINARY
, JSON
, ENUM
, SET
, TINYTEXT
, MEDIUMTEXT
, LONGTEXT
, TINYBLOB
, MEDIUMBLOB
, BLOB
, LONGBLOB
]
The data type of the column.
Whether the column is nullable.
rows object[] required
ID of the repo
Name of the repo
Primary programing language used by the repo
Description of the repo
Number of stars in the period
Number of forks in the period
Number of pull requests in the period
Number of pushes in the period
Total score of the repo
Comma separated list of active contributor logins
Comma separated list of collection names
result object required
The code of the response.
The message of the response.
The start time of the query in milliseconds.
The end time of the query in milliseconds.
The latency of the query.
The number of rows in the query result.
The number of rows affected by the query.
The maximum number of rows in the query result.
The databases used in the query.
{
"type": "sql_endpoint",
"data": {
"columns": [
{
"col": "repo_id",
"data_type": "INT",
"nullable": true
},
{
"col": "repo_name",
"data_type": "VARCHAR",
"nullable": true
},
{
"col": "primary_language",
"data_type": "VARCHAR",
"nullable": true
},
{
"col": "description",
"data_type": "VARCHAR",
"nullable": true
},
{
"col": "stars",
"data_type": "INT",
"nullable": true
},
{
"col": "forks",
"data_type": "INT",
"nullable": true
},
{
"col": "pull_requests",
"data_type": "INT",
"nullable": true
},
{
"col": "pushes",
"data_type": "INT",
"nullable": true
},
{
"col": "total_score",
"data_type": "DOUBLE",
"nullable": true
},
{
"col": "contributor_logins",
"data_type": "VARCHAR",
"nullable": true
},
{
"col": "collection_names",
"data_type": "VARCHAR",
"nullable": true
}
],
"rows": [
{
"collection_names": "CICD",
"contributor_logins": "cplee,nektos-ci,usagirei,ae-ou,MrNossiom",
"description": "Run your GitHub Actions locally 🚀",
"forks": "5",
"primary_language": "Go",
"pull_requests": "6",
"pushes": "17",
"repo_id": "163883279",
"repo_name": "nektos/act",
"stars": "395",
"total_score": "1565.7526"
},
{
"collection_names": "ChatGPT Alternatives",
"contributor_logins": "antonkesy,ruanslv,starplatinum3,AlexandroLuis,realhaik",
"description": "Inference code for LLaMA models",
"forks": "48",
"primary_language": "Python",
"pull_requests": "41",
"pushes": "7",
"repo_id": "601538369",
"repo_name": "facebookresearch/llama",
"stars": "209",
"total_score": "1079.0274"
},
{
"collection_names": "Stable Diffusion Ecosystem",
"contributor_logins": "atiorh,SaladDays831,ZachNagengast,TimYao18,vzsg",
"description": "Stable Diffusion with Core ML on Apple Silicon",
"forks": "5",
"primary_language": "Python",
"pull_requests": "7",
"pushes": "5",
"repo_id": "566576114",
"repo_name": "apple/ml-stable-diffusion",
"stars": "99",
"total_score": "575.2498"
},
{
"collection_names": "Stable Diffusion Ecosystem",
"contributor_logins": "danonymous856,EvilPhi666,FurkanGozukara,Prathyusha-98,ca-kishida",
"description": "High-Resolution Image Synthesis with Latent Diffusion Models",
"forks": "6",
"primary_language": "Python",
"pull_requests": "2",
"pushes": "",
"repo_id": "569927055",
"repo_name": "Stability-AI/stablediffusion",
"stars": "75",
"total_score": "483.0236"
}
],
"result": {
"code": 200,
"message": "Query OK!",
"start_ms": 1690957407469,
"end_ms": 1690957407499,
"latency": "30ms",
"row_count": 4,
"row_affect": 0,
"limit": 50,
"databases": [
"gharchive_dev"
]
}
}
}