### Install python-osrm via pip

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This snippet demonstrates how to install the python-osrm library using pip, the Python package installer. This is the standard method for adding the library to your Python environment.

```Shell
pip install osrm
```

--------------------------------

### Run python-osrm test suite

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This command executes the test suite for the python-osrm library. It's typically used by developers to verify the installation and functionality of the library.

```Shell
python setup.py test
```

--------------------------------

### Match points to a route using OSRM

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This example shows how to use the `osrm.match` function to snap a series of geographic points to the nearest road segments and return a matched route. It demonstrates basic usage with options for steps and overview geometry.

```Python
import osrm

points = [(-33.45017046193167,-70.65281867980957),
          (-33.45239047269638,-70.65300107002258),
          (-33.453867464504555,-70.65277576446533)]

result = osrm.match(points, steps=False, overview="simplified")
```

--------------------------------

### Route Between OSRM Point Objects

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This example demonstrates using the `osrm.Point` class to define coordinates, improving clarity by explicitly naming latitude and longitude. It then uses these `Point` instances with the `simple_route` function to calculate a route.

```python
In [25]: from osrm import Point, simple_route

In [26]: p1 = Point(latitude=2.386459, longitude=48.512369)

In [27]: p2 = Point(latitude=2.536974, longitude=48.793416)

In [28]: result = simple_route(p1, p2)
```

--------------------------------

### Generate a time matrix using OSRM table service

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This example demonstrates how to use the `osrm.table` function to compute a matrix of travel times between multiple origin and destination points. It shows how to provide a list of coordinates and optional IDs, and how to retrieve the output as a pandas DataFrame, along with snapped coordinates.

```Python
import osrm
import pandas as pd

list_coord = [[21.0566163803209, 42.004088575972],
              [21.3856064050746, 42.0094518118189],
              [20.9574645547597, 41.5286973392856],
              [21.1477394809847, 41.0691482795275],
              [21.5506463080973, 41.3532256406286]]

list_id = ['name1', 'name2', 'name3', 'name4', 'name5']

time_matrix, snapped_coords = osrm.table(list_coord,
                                  				  ids_origin=list_id,
                                  				  output='dataframe')

print(time_matrix)
```

--------------------------------

### Perform OSRM Trip Planning

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This snippet illustrates how to use the `osrm.trip` function to plan a multi-point trip. It takes a list of coordinates and an optional `output` parameter to specify the desired return format, such as only the order of points.

```python
In [5]: coords = [(13.388860,52.517037), (10.00,53.55), (52.374444,9.738611)]

In [6]: result = osrm.trip(coords, output = "only_index")
```

--------------------------------

### Configure OSRM Request Host and Profile

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

These snippets show two ways to configure the OSRM server URL and profile for requests. You can either modify the default `osrm.RequestConfig` globally or create a new `RequestConfig` instance for specific requests, allowing for different hosts, profiles, and basic authentication.

```python
In [31]: import osrm

In [32]: osrm.RequestConfig
Out[32]: http://localhost:5000/*/v1/driving

In [33]: osrm.RequestConfig.host = "router.project-osrm.org"

In [34]: result = osrm.simple_route(p1, p2)
```

```python
In [35]: MyConfig = osrm.RequestConfig("localhost:9999/v1/biking", basic_auth=("user", "pass"))

In [36]: MyConfig
Out[36]: localhost:9999/*/v1/biking

In [37]: MyConfig.profile = "driving"

In [38]: MyConfig
Out[38]: localhost:9999/*/v1/driving

In [39]: result = osrm.simple_route(p1, p2, url_config=MyConfig)
```

--------------------------------

### Calculate a simple route between two points

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This snippet illustrates how to calculate a route between two specified geographic coordinates using `osrm.simple_route`. It demonstrates how to request the output as a route, with full overview geometry, and decoded into WKT (Well-Known Text) format. It also shows how to access the distance and geometry from the result.

```Python
import osrm
result = osrm.simple_route(
                      [21.0566163803209,42.004088575972], [20.9574645547597, 41.5286973392856],
                      output='route', overview="full", geometry='wkt')

print(result[0]['distance'])
print(result[0]['geometry'])
```

--------------------------------

### Visualize OSRM Accessibility Grid

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This code shows how to plot the underlying grid of points used for accessibility calculations. The `grid` attribute of the `AccessIsochrone` object is a GeoDataFrame, allowing direct visualization of the generated grid.

```python
In [5]: Accessibility.grid.plot()
```

--------------------------------

### Generate Accessibility Isochrones with OSRM Python

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This snippet demonstrates how to use the `osrm.AccessIsochrone` class to calculate and visualize accessibility isochrones. It initializes an `AccessIsochrone` object with a central point and grid precision, then renders the contours into a GeoDataFrame for plotting.

```python
In [1]: import osrm

In [2]: Accessibility = osrm.AccessIsochrone((10.00,53.55), points_grid=450)

In [3]: gdf = Accessibility.render_contour(n_class=8)

In [4]: gdf.plot(cmap="YlOrRd")
```

--------------------------------

### Find the nearest road segment to a coordinate

Source: https://github.com/ustroetz/python-osrm/blob/master/README.md

This snippet shows how to use the `osrm.nearest` function to find the closest road segment and its associated waypoint information for a given geographic coordinate. It returns details such as the name of the road, hint, location, and distance from the input point.

```Python
import osrm

res = osrm.nearest([22.1021271845936,	41.5078687005805])

print(res)
```

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