https://github.com/Techtonique/techtonique-apis
High level Python functions for interacting with Techtonique forecasting API
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (9.0%) to scientific vocabulary
Keywords
Repository
High level Python functions for interacting with Techtonique forecasting API
Basic Info
- Host: GitHub
- Owner: Techtonique
- License: mit
- Language: HTML
- Default Branch: main
- Homepage: https://www.techtonique.net/docs
- Size: 1.23 MB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
techtonique_apis
High level Python functions for interacting with Techtonique APIs
Installation
bash
pip install techtonique_apis
Usage
- File examples: https://github.com/Techtonique/datasets/tree/main/time_series
- Get a token: https://www.techtonique.net/token (store in .env, in current directory as
TECHTONIQUE_TOKEN)
There are 100 free API calls in the free tier/months.
```python from techtonique_apis import TechtoniqueAPI
api = TechtoniqueAPI()
Example 1: Forecasting
forecastresult = api.forecasting( filepath="/Users/t/Documents/datasets/timeseries/univariate/a10.csv", basemodel="RidgeCV", nhiddenfeatures=5, lags=25, typepi="kde", replications=10, h=5 ) print("Forecasting result:", forecastresult)
Example 2: Machine Learning Regression
regressionresult = api.mlregression( filepath="/Users/t/Documents/datasets/tabular/regression/mtcars2.csv", basemodel="ElasticNet", nhiddenfeatures=5, returnpi=True ) print("Regression result:", regression_result)
Example 3: GBDT Classification
gbdtclassificationresult = api.gbdtclassification( filepath="/Users/t/Documents/datasets/tabular/classification/irisdataset2.csv", modeltype="lightgbm" ) print("GBDT Classification result:", gbdtclassificationresult)
Example 4: Reserving
reservingresult = api.reserving( filepath="/Users/t/Documents/datasets/tabular/triangle/raa.csv", method="chainladder" ) print("Reserving result:", reserving_result)
Example 5: Survival Analysis
survivalresult = api.survivalcurve( filepath="/Users/t/Documents/datasets/tabular/survival/kidney.csv", method="km", patientid=123 ) print("Survival curve result:", survival_result)
Example 6: Scenarios
scenariosresult = api.simulatescenario( model="GBM", n=10, frequency="quarterly", x0=100, horizon=5, theta1=0, theta2=0.5, theta3=0.5, ) print("Scenarios result:", scenarios_result) ```
License
MIT
Owner
- Name: Techtonique
- Login: Techtonique
- Kind: organization
- Website: https://docs.techtonique.net/
- Repositories: 12
- Profile: https://github.com/Techtonique
tech, stats, machine learning, computer simulation, numerical optimization
GitHub Events
Total
- Push event: 10
Last Year
- Push event: 10