Monte Carlo's CLI
Project description
Monte Carlo CLI
Monte Carlo's Alpha CLI!
Installation
Requires Python 3.7 or greater. Normally you can install and update using pip. For instance:
virtualenv venv
. venv/bin/activate
pip install -U montecarlodata
Developers of the CLI can use:
make install
. venv/bin/activate
Either way confirm the installation by running:
montecarlo --version
If the Python requirement does not work for you please reach out to customer-success@montecarlodata.com
. Docker is an option.
Quick start
First time users can configure the tool by following the onscreen prompts:
montecarlo configure
MCD tokens can be generated from the dashboard.
Any AWS profiles or regions should be for the account the Data Collector (DC) is deployed to. If you are not using the CLI for onboarding, you may leave the AWS configuration blank.
Use the --help
flag for details on any advanced options (e.g. creating multiple montecarlo profiles) or any prompts.
That's it! You can always validate your connection with:
montecarlo validate
User settings
Any configuration set by montecarlo configure
can be found in '~/.mcd/' by default.
The MCD ID and Token can be overwritten, or even set, by the environment:
- MCD_DEFAULT_API_ID
- MCD_DEFAULT_API_TOKEN
These two are required either as part of configure
or as environment variables.
For AWS, system defaults are used if not set as part of configure
.
The following values can also be set by the environment:
- MCD_API_ENDPOINT - Overwrite the default API endpoint
- MCD_VERBOSE_ERRORS - Enable verbose logging on errors (default=false)
Help
Help for commands, options and arguments can be found using the --help
flag.
Additional documentation is available here.
All commands, except configure
and validate
, support an --option-file
flag, which allows you to use a file in place of passing options.
For instance, a --name
flag can be set by creating a file containing:
name="Artemis"
Any dashes must be replaced by underscores. For instance, --foo-bar
would be foo_bar="qux"
.
Resolution is CLI Options > Option File.
Examples
-
Using Docker from a local installation
docker build -t montecarlo . docker run -v ${HOME}/.aws/credentials:/root/.aws/credentials:ro \ -e MCD_DEFAULT_API_ID='<ID>' \ -e MCD_DEFAULT_API_TOKEN='<TOKEN>' \ -e AWS_DEFAULT_PROFILE='<PROFILE>' \ -e AWS_DEFAULT_REGION='us-east-1' \ montecarlo --version
Replace
--version
with any sub-commands or options. If interacting with files those directories will probably need to be mounted too. -
Configure a named profile with custom config-path
$ montecarlo configure --profile-name zeus --config-path . Key ID: 1234 Secret: AWS profile name []: shiva AWS region [us-east-1]: $ cat ./profiles.ini [zeus] mcd_id = 1234 mcd_token = 5678 aws_profile = shiva aws_region = us-east-1
-
List active integrations
$ montecarlo integrations list ╒══════════════════╤══════════════════════════════════════╤══════════════════════════════════╕ │ Integration │ ID │ Created on (UTC) │ ╞══════════════════╪══════════════════════════════════════╪══════════════════════════════════╡ │ Odin │ 58005657-2914-4701-9a11-260ac425b14e │ 2021-01-02T01:30:52.806602+00:00 │ ├──────────────────┼──────────────────────────────────────┼──────────────────────────────────┤ │ Thor │ 926816bd-ab17-4f95-a953-fa14482c59de │ 2021-01-02T01:31:19.892205+00:00 │ ├──────────────────┼──────────────────────────────────────┼──────────────────────────────────┤ │ Loki │ 1cf1dc0d-d8ec-4c85-8e64-57ab2ad8e023 │ 2021-01-02T01:32:37.709747+00:00 │ ╘══════════════════╧══════════════════════════════════════╧══════════════════════════════════╛
-
Apply monitors configuration
$ montecarlo monitors apply --namespace my-monitors Gathering monitor configuration files. - models/customer_success/schema.yml - Embedded monitor configuration found. - models/customer_success/schema.yml - Monitor configuration found. - models/lineage/schema.yml - Embedded monitor configuration found. Modifications: - ResourceModificationType.UPDATE - Monitor: type=stats, table=analytics:prod.customer_360 - ResourceModificationType.UPDATE - Monitor: type=categories, table=analytics:prod.customer_360 - ResourceModificationType.UPDATE - Monitor: type=stats, table=analytics:prod_lineage.lineage_nodes - ResourceModificationType.UPDATE - Freshness SLI: table=analytics:prod.customer_360, freshness_threshold=30
-
Import DBT manifest
$ montecarlo import dbt-manifest --dbt-manifest-file target/manifest.json Importing DBT objects into Monte Carlo catalog. please wait... Imported a total of 51 DBT objects into Monte Carlo catalog.
Tests and Releases
Locally make test
will run all tests. CircleCI manages all testing for deployment.
When ready to release make a PR for master
. After merging CircleCI will test and deploy to PyPI.
Don't forget to increment the version number in setup.py
first! An existing version will not be deployed.
License
Apache 2.0 - See the LICENSE for more information.
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