Metadata-Version: 2.1
Name: localytics
Version: 1.42
Summary: Python API Client for Localytics Raw Data Export
Home-page: https://github.com/lexadavid/localytics
Author: David Lexa
Author-email: david.kaur.lexa@wunder.org
License: MIT
Platform: UNKNOWN
Description-Content-Type: text/markdown

# Python Client for Localytics Raw Data Export
This is a Python API Client for [Localytics Raw Data Export](https://docs.localytics.com/dev/export-apis.html#log-exports-api). It allows to export all events and sessions captured by Localytics. Data is written in JSON and available on hourly basis as log files.


## Installation
The client is currently best installed via Pypi:

```bash
    $ pip install localytics
```


## Usage
Let's have a walk through the functionalities through a couple of examples. Start by loading the library.

```python
    >>> from localytics import Localytics
```


### Setup and Authentication
In order for you to access the KPI Service, you need to authenticate with `api_key`. Your `api_secret`, once you supply it, will be used throughout the entire session.

```python
    >>> localytics = Localytics(api_key = 'XXXXX', api_secret= 'YYYYY')
```


### Download Data
There is a method  `download_data` that downloads data to local folder. Example shows how to export data for last 2 days:

```python
    >>> localytics.download_data(
            app_ids = ['AAAAA', 'BBBBB'],
            start_date = datetime.today() - timedelta(2),
            end_date = datetime.today()
        )
```

You can also specify optional parameters. This is more complex example:

```python
    >>> localytics.download_data(
        app_ids = ['AAAAA', 'BBBBB'],
        start_date = datetime.today() - timedelta(2),
        end_date = datetime.today(),
        destination_folder = 'data',
        compressed=True
    )
```

On default data are stored in `localytics_data` folder and compressed in `gz` format. Please set `compresses = True` if you want to store data decompressed.


## Contributions and bug reports.

Contributions and bug reports are only acceptable as GitHub Pull Requests and issues. Thanks!


