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Copy file name to clipboardExpand all lines: articles/azure-monitor/app/opencensus-python-dependency.md
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title: Dependency Tracking in Azure Application Insights with OpenCensus Python | Microsoft Docs
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description: Monitor dependency calls for your Python apps via OpenCensus Python.
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ms.topic: conceptual
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ms.date: 10/15/2019
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ms.date: 8/19/2022
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ms.devlang: python
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ms.custom: devx-track-python
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ms.reviewer: mmcc
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---
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# Track dependencies with OpenCensus Python
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}
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```
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You can find a Django sample application that uses dependencies in the Azure Monitor OpenCensus Python samples repository located [here](https://github.com/Azure-Samples/azure-monitor-opencensus-python/tree/master/azure_monitor/django_sample).
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## Dependencies with "mysql" integration
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Track your MYSQL dependencies with the OpenCensus `mysql` integration. This integration supports the [mysql-connector](https://pypi.org/project/mysql-connector-python/) library.
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title: Incoming Request Tracking in Azure Application Insights with OpenCensus Python | Microsoft Docs
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description: Monitor request calls for your Python apps via OpenCensus Python.
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ms.topic: conceptual
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ms.date: 10/15/2019
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ms.date: 8/19/2022
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ms.devlang: python
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ms.custom: devx-track-python
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ms.reviewer: mmcc
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}
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```
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You can find a Django sample application in the sample Azure Monitor OpenCensus Python samples repository located [here](https://github.com/givenscj/azure-monitor-opencensus-python/tree/master/azure_monitor/django_sample).
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## Tracking Flask applications
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1. Download and install `opencensus-ext-flask`from [PyPI](https://pypi.org/project/opencensus-ext-flask/) and instrument your application with the `flask` middleware. Incoming requests sent to your `flask` application will be tracked.
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> [!NOTE]
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> To run Flask under uWSGI in a Docker environment, you must first add `lazy-apps = true` to the uWSGI configuration file (uwsgi.ini). For more information, see the [issue description](https://github.com/census-instrumentation/opencensus-python/issues/660).
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You can find a Flask sample application that tracks requests in the Azure Monitor OpenCensus Python samples repository located [here](https://github.com/Azure-Samples/azure-monitor-opencensus-python/tree/master/azure_monitor/flask_sample).
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## Tracking Pyramid applications
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1. Download and install `opencensus-ext-django`from [PyPI](https://pypi.org/project/opencensus-ext-pyramid/) and instrument your application with the `pyramid` tween. Incoming requests sent to your `pyramid` application will be tracked.
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title: Monitor Python applications with Azure Monitor | Microsoft Docs
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description: Provides instructions to wire up OpenCensus Python with Azure Monitor
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ms.topic: conceptual
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ms.date: 10/12/2021
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ms.date: 8/19/2022
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## Prerequisites
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- An Azure subscription. If you don't have an Azure subscription, create a [free account](https://azure.microsoft.com/free/) before you begin.
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- Python installation. This article uses [Python 3.7.0](https://www.python.org/downloads/release/python-370/), although other versions will likely work with minor changes. The Opencensus Python SDK only supports Python v2.7 and v3.4+.
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- Create an Application Insights [resource](./create-new-resource.md). You'll be assigned your own instrumentation key (ikey) for your resource.
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python -m pip install opencensus-ext-azure
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```
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> [!NOTE]
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> The `python -m pip install opencensus-ext-azure` command assumes that you have a `PATH` environment variable set for your Python installation. If you haven't configured this variable, you need to give the full directory path to where your Python executable is located. The result is a command like this: `C:\Users\Administrator\AppData\Local\Programs\Python\Python37-32\python.exe -m pip install opencensus-ext-azure`.
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The SDK uses three Azure Monitor exporters to send different types of telemetry to Azure Monitor. They're trace, metrics, and logs. For more information on these telemetry types, see [the data platform overview](../data-platform.md). Use the following instructions to send these telemetry types via the three exporters.
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The SDK uses three Azure Monitor exporters to send different types of telemetry to Azure Monitor. They are `trace`, `metrics`, and `logs`. For more information on these telemetry types, see [the data platform overview](../data-platform.md). Use the following instructions to send these telemetry types via the three exporters.
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## Telemetry type mappings
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main()
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```
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1. The exporter sends log data to Azure Monitor. You can find the data under `traces`.
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1. The exporter sends log data to Azure Monitor. You can find the data under `traces`.
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> [!NOTE]
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> In this context, `traces` isn't the same as `tracing`. Here, `traces` refers to the type of telemetry that you'll see in Azure Monitor when you utilize `AzureLogHandler`. But `tracing` refers to a concept in OpenCensus and relates to [distributed tracing](./distributed-tracing.md).
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