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Get Metrics About Your Project

tip

Once you're project is indexed, you can get metrics about your project using pyoso. It's always safer to query on the project_id field rather than the name or display_name fields.

Find Your project_id​

You can lookup your project's project_id using SQL:

query = """
SELECT
  project_id,
  project_name,
  display_name,
  description
FROM projects_v1
WHERE project_name = 'opensource-observer'
"""
df = client.to_pandas(query)

In the case of opensource-observer, we get back the following:

{
  "projectId": "UuWbpo5bpL5QsYvlukUWNm2uE8HFjxQxzCM0e+HMZfk=",
  "projectName": "opensource-observer",
  "displayName": "Open Source Observer",
  "description": "Open Source Observer is a free analytics suite that helps funders measure the impact of open source software contributions to the health of their ecosystem."
}

Browse Available Metrics​

OSO maintains a directory of available metrics in metrics_v0. To see all available metrics, you can run the following query:

query = """
SELECT
  metric_id,
  metric_name,
  display_name,
  description
FROM metrics_v0
"""
df = client.to_pandas(query)

In the case of daily GitHub commits, we get back the following:

{
  "metricId": "0xy+em6XN6wQKZMqtspcmc49ze3hD4BofTyMG+PU2OE=",
  "metricName": "GITHUB_commits_daily",
  "displayName": "GitHub commits daily",
  "description": "..."
},

Get a Single Metric Value​

For any particular metric, you can get a current value (e.g. to display on a website):

query = """
SELECT
  metric_id,
  project_id,
  amount
FROM key_metrics_by_project_v0
WHERE project_id = 'UuWbpo5bpL5QsYvlukUWNm2uE8HFjxQxzCM0e+HMZfk='
  AND metric_id = '1zNSDLeL7d1bqMgJ4b/AGBd0lQs4Q4Wy9jIf2ge72kw='
"""
df = client.to_pandas(query)

In the case of daily GitHub commits, we get back the following:

{
  "projectId": "UuWbpo5bpL5QsYvlukUWNm2uE8HFjxQxzCM0e+HMZfk=",
  "metricId": "1zNSDLeL7d1bqMgJ4b/AGBd0lQs4Q4Wy9jIf2ge72kw=",
  "amount": 2930
},

Timeseries Metrics​

OSO also maintains a standard set of timeseries metrics for each project (e.g. to power graphs):

query = """
SELECT
  tm.project_id,
  tm.sample_date,
  tm.amount,
  tm.unit,
  m.metric_name
FROM timeseries_metrics_by_project_v0 tm
JOIN metrics_v0 m ON tm.metric_id = m.metric_id
WHERE tm.project_id = 'UuWbpo5bpL5QsYvlukUWNm2uE8HFjxQxzCM0e+HMZfk='
  AND tm.metric_id = '0xy+em6XN6wQKZMqtspcmc49ze3hD4BofTyMG+PU2OE='
ORDER BY tm.sample_date ASC
"""
df = client.to_pandas(query)