The Views 3 CLI tool
Project description
viewser
This package contains many useful user operations that are used by the views 3 team. These operations include fetching and publishing data, finding documentation on both transforms and database structure, and more.
CLI
viewser
functionality is exposed via a CLI on your system after installation.
An overview of available commands can be seen by running viewser --help
.
API
In addition to the CLI, viewser exposes many useful operations as functions that can be used in scripts.
Configuration
The tool is configured using the viewser config set KEY VALUE
and viewser config load JSON
commands. The settings shown without defaults here, or with
defaults that don't make sense for the average user (REMOTE_URL
) must be
configured before use.
Setting | Description | Default |
---|---|---|
RETRY_FREQUENCY | General request retry frequency in seconds | 5 |
QUERYSET_MAX_RETRIES | How many times a queryset is queried before failing | 500 |
LOG_LEVEL | Determines what logging messages are shown | INFO |
ERROR_DUMP_DIRECTORY | Determines where error dumps are written to | ~/.views/dumps |
REMOTE_URL | URL of a views 3 instance | http://0.0.0.0:4000 |
MODEL_METADATA_DATABASE_HOSTNAME | Hostname of database for storing model metadata | hermes |
MODEL_METADATA_DATABASE_NAME | DBname of database for storing model metadata | forecasts3 |
MODEL_METADATA_DATABASE_USER | Username for database for storing model metadata | Inferred from cert |
MODEL_METADATA_DATABASE_SSLMODE | SSLmode for database for storing model metadata | required |
MODEL_METADATA_DATABASE_PORT | Port of database for storing model metadata | 5432 |
MODEL_METADATA_DATABASE_SCHEMA | Schema of database for storing model metadata | forecasts |
MODEL_METADATA_DATABASE_TABLE | Table of database for storing model metadata | model |
AZURE_BLOB_STORAGE_ACCOUNT_NAME | Name of Azure blob storage account | |
AZURE_BLOB_STORAGE_ACCOUNT_KEY | Access key of Azure blob storage account |
Funding
The contents of this repository is the outcome of projects that have received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 694640, ViEWS) and Horizon Europe (Grant agreement No. 101055176, ANTICIPATE; and No. 101069312, ViEWS (ERC-2022-POC1)), Riksbankens Jubileumsfond (Grant agreement No. M21-0002, Societies at Risk), Uppsala University, Peace Research Institute Oslo, the United Nations Economic and Social Commission for Western Asia (ViEWS-ESCWA), the United Kingdom Foreign, Commonwealth & Development Office (GSRA – Forecasting Fatalities in Armed Conflict), the Swedish Research Council (DEMSCORE), the Swedish Foundation for Strategic Environmental Research (MISTRA Geopolitics), the Norwegian MFA (Conflict Trends QZA-18/0227), and the United Nations High Commissioner for Refugees (the Sahel Predictive Analytics project).
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