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1. • • The most important formats are: PBF Format – highly compressed, optimized binary format similar to the API, recommended for data processing OSM XML – XML format provided by the API. Please use PBF if you can.
     wiki.openstreetmap.org › wiki › OSM_file_formats

     OSM file formats - OpenStreetMap Wiki

2. Top results related to what formats are openstreetmap maps available in python

   • What monospace fonts are available in Python and Tkinter?

     Top Answer

     Answered Aug 08, 2020 · 3 votes

     "Monospace" just means that all characters take the same, fixed width for each character.

     The converse is a "proportional" font where narrower letters e.g i take less space and wider letters e.g. m take more space.

     Which ones are available depend on what you have installed.

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     1/5

   • What are the standard, stable file formats used in Python for Data Science?

     Top Answer

     Answered Jun 13, 2024 · 3 votes

     Arbitrary Python data and code can be stored in the .pkl

     pickle format. While pickle files have security concerns because loading them can execute arbitrary code, if you can trust the source of a pickle file, it is a stable format.

     The Python standard library's pickle page:

     The pickle serialization format is guaranteed to be backwards compatible across Python releases provided a compatible pickle protocol is chosen and pickling and unpickling code deals with Python 2 to Python 3 type differences if your data is crossing that unique breaking change language boundary.

     Security concerns around the pickle format continue to grow. While many deep learning models were originally distributed in the .pkl format, hugging face has championed distributing models in their safetensor format instead -- a move I guess the industry is likely to follow.

     Most python data can also be stored in the json format. I haven't used this format much myself, but dawg recommends it. Like the CSV and tab-delimited format I recommend for Pandas, the json format is a plain-text format that is very stable.

     Numpy arrays can be stored in the .npy

     or .npz

     numpy formats. The npy format is a very simple format that stores a single numpy array. I imagine it would be easy to read this format in any language. The npz format allows the storing of multiple arrays in the same file. Adapted from the docs,

     x = np.arange(10)np.save('example.npy',x)y = np.load('example.npy') -

     If the integrity of the file being loaded is not guaranteed, be sure to use allow_pickle=False to avoid arbitrary code execution.

     Note that x.tofile(...)

     does NOT save in the stable npy format. Although it looks more convenient because it simply calls a method on the data to be saved, this is not an option for saving data.

     Pandas dataframes can be stored in a variety of formats. As I wrote in a previous answer, Pandas offers a wide variety of formats. For small datasets, I find plaintext file formats such as CSV and tab-delimited to work well for most purposes. These formats are readable in a wide variety of languages and I have had no issues in working in a bilingual R and Python environment where both environments read from these files.

     Format Type Data Description Reader Writertext CSV read_csv to_csvtext JSON read_json to_jsontext HTML read_html to_htmltext Local clipboard read_clipboard to_clipboardbinary MS Excel read_excel to_excelbinary HDF5 Format read_hdf to_hdfbinary Feather Format read_feather to_featherbinary Parquet Format read_parquet to_parquetbinary Msgpack read_msgpack to_msgpackbinary Stata read_stata to_statabinary SAS read_sas binary Python Pickle Format read_pickle to_pickleSQL SQL read_sql to_sqlSQL Google Big Query read_gbq to_gbq-

     When writing csv and tab files from pandas, I often use the index=False option to avoid saving the index, which loads as an oddly-named column by default.

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     2/5

   • What are the modules to use Google Maps with other data in Python?

     Top Answer

     Answered Jan 12, 2023 · 0 votes

     There are several Python modules that can be used to work with Google Maps data. Some of the most popular ones include:

     Google Maps API: This is the official API for working with Google Maps data. It allows you to access a wide range of data, including street maps, satellite imagery, and places of interest. You can use the API to search for addresses, get directions, and even create custom maps.

     gmaps: This is a Python wrapper for the Google Maps API. It makes it easy to work with the API by providing a simple, Pythonic interface. It also includes support for several popular Python libraries, such as Pandas and Numpy.

     folium: This is a library for creating leaflet maps in Python. It allows you to create interactive maps, add markers and other data, and customize the appearance of your maps.

     geopandas: This library allows you to work with geospatial data in Python. It is built on top of the popular Pandas library and includes support for working with shapefiles, geojson, and more.

     geopy: This is a Python library for working with geocoding and distance calculations. It can be used to convert addresses to latitude and longitude coordinates, as well as to perform distance calculations between two points.

     In general, it's recommended to start with Google Maps API and gmaps and folium, you can also use geopandas and geopy later when you need more advanced functionalities. Try to start with simple examples and gradually increase the complexity of your projects.

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     3/5

   • what are the formats supported in Pygame for playing sound?

     Top Answer

     Answered Aug 25, 2012 · 9 votes

     From pygame documentation:

     The Sound can be loaded from an OGG audio file or from an uncompressed WAV.

     As for Music, it seems to support several different including MP3 (limited), OGG, XM & MOD. See Documentation for music (and the comments on that page).

     Check all answers on Stack Overflow

     4/5

   • What are handlers in python in plain English

     Top Answer

     Answered Oct 30, 2019 · 17 votes

     In general handlers are functions that 'handle' certain events that they are registered for.

     The documentation that you reference is about a Web Server. A web server receives requests from e.g. Browsers for URLs - and returns an answer depending on what was requested. The specific handler they are talking about takes in two arguments:

     • The request that is coming from the browser and contains information like the URL, maybe cookies, an IP etc.
     • A response object. The handler shall take the information from the request to fill that response object accordingly. It might use other information like databases or files as well.

     For example: A web browser requests http://me.com/index.html. The handler is invoked, looks for a file named index.html in the root directory. If the file is found, it is read, appended to the response object and the handler is done. The wgetsrv framework will do the rest of the work and send the response back to the client who will now see a website.

     There are many other types of handlers, for example for user input. A registered keyboard input handler is invoked on every keystroke with the key typed. This allows the programmer to react and display text or invoke shortcuts.

     Handlers are often used to replace polling. Polling is a technique where the program is checking the state of something frequently to react when the state has changed. Staying with the keyboard example. Imagine you are steering a player in a game through a 2D world with your arrow keys. How does the program know which direction you want to go? It needs to check which (if any) of the arrow keys are pressed. For that, it could get the state of the keyboard, check if e.g. the right arrow key is currently pressed and then move the player a bit to the right if that is the case. But the program will only know about this change once it has checked the keyboard. So to be responsive for the player it has to check the state of the keyboard quite often (a couple of times per second) which wastes CPU cycles as most of the time the state has indeed not changed.

     Now turning the model around, the game could ask the keyboard: Hey, when a key is pressed, call this function and tell it which keys are pressed. The function can then accordingly update the players position - but is only called when the state of the keyboard has changed. Polling is like calling the pizza guy every five minutes: "Is my order ready for pickup?" as opposed to calling him once and telling him "Call me back when my order is ready." In the latter case you 'registered a handler for pizza-ready events' and saved both of you a lot of time.

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     5/5

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3. pygis.io › docs › d_access_osmAccessing OSM Data in Python — Python Open Source Spatial ...

   pygis.io › docs › d_access_osm

   • Cached

   This week we will explore a Python module called OSMnx that can be used to retrieve, construct, analyze, and visualize street networks from OpenStreetMap, and also retrieve data about Points of Interest such as restaurants, schools, and lots of different kind of services.

4. People also ask

   Can Python read OpenStreetMap data?

   • Here's a full explanation on downloading features from OSM and visualizing it in Python. I do not recommend writing Python to read .osm files because there's a lot of easy to use software (e.g. GDAL) that handles that for you. You do not need to handle nodes, ways, and relations individually to use OpenStreetMap data.

   How to extract and visualize data from OSM file in Python

   stackoverflow.com/questions/45771809/how-to-extract-and-visualize-data-from-osm-file-in-python

   See all results for this question

   What is OpenStreetMap osmnx?

   • This week we will explore a Python module called OSMnx that can be used to retrieve, construct, analyze, and visualize street networks from OpenStreetMap, and also retrieve data about Points of Interest such as restaurants, schools, and lots of different kind of services.

   Accessing OSM Data in Python — Python Open Source Spatial ... - PyGIS

   pygis.io/docs/d_access_osm.html

   See all results for this question

   Is OpenStreetMap free?

   • Here is my code for others, which are searching a starting point to OSM. (Of course there is still much room for improvements). Please respect the usage policy of Open Street Map! OpenStreetMap data is free for everyone to use. Our tile servers are not. Requirements

   Easy OpenStreetMap tile displaying for Python - Stack Overflow

   stackoverflow.com/questions/28476117/easy-openstreetmap-tile-displaying-for-python

   See all results for this question

   How to retrieve geospatial data from OpenStreetMap (OSM)?

   • OpenStreetMap — Source If you want to retrieve Geospatial data from OpenStreetMap (OSM), you can download it, but that takes time and storage. Without leaving your development environment (Jupyter Notebooks), you can access and retrieve OpenStreetMap data.

   Retrieving OpenStreetMap data in Python

   towardsdatascience.com/retrieving-openstreetmap-data-in-python-1777a4be45bb

   See all results for this question

5. racum.blog › articles › osm-pythonAccessing the OpenStreetMap API with Python directly

   racum.blog › articles › osm-python

   • Cached

   Apr 16, 2024 · On a previous article called "OpenStreetMap to GeoJSON", I explained how to extract Polygons from OSM using an online tool provided by from OSM France. And, on this article, I’ll explain how do that yourself directly using the OSM API and Python.

6. stackoverflow.com › questions › 28476117Easy OpenStreetMap tile displaying for Python - Stack Overflow

   stackoverflow.com › questions › 28476117

   Feb 12, 2015 · contextily is a small Python ... package to retrieve tile maps from the internet. It can add those tiles as basemap to matplotlib figures or write tile maps to disk into geospatial raster files. Showing just a slice of a map. Sample code:

7. wiki.openstreetmap.org › wiki › OSM_file_formatsOSM file formats - OpenStreetMap Wiki

   wiki.openstreetmap.org › wiki › OSM_file_formats

   • Cached

   4 days ago · Map Data. The most important formats are: PBF Format – highly compressed, optimized binary format similar to the API, recommended for data processing; OSM XML – XML format provided by the API. Please use PBF if you can. OSM JSON – JSON format provided by the API, based on Overpass API JSON format.

8. towardsdatascience.com › loading-data-from-openLoading Data from OpenStreetMap with Python and the Overpass ...

   towardsdatascience.com › loading-data-from-open

   Aug 2, 2018 · If you just need to work with a certain region you can use extracts in various formats such as the native .OSM (stored as XML), .PBF (A compressed version of .OSM), Shapefile or GeoJSON. There are also different API possible such as the native OSM API or the Nominatim API .

9. towardsdatascience.com › retrieving-openstreetmapRetrieving OpenStreetMap data in Python | by Abdishakur ...

   towardsdatascience.com › retrieving-openstreetmap

   Dec 8, 2019 · In this tutorial, we learn to retrieve OpenStreetMap data using OSMNX, a python package. OSMnx is a Python package that lets you download spatial geometries and model, project, visualize, and analyze street networks and other spatial data from OpenStreetMap’s API

10. pythongis.org › part2 › chapter-09Retrieving OpenStreetMap data

    pythongis.org › part2 › chapter-09

    • Cached

    This week we will explore a Python module called OSMnx that can be used to retrieve, construct, analyze, and visualize street networks from OpenStreetMap, and also retrieve data about Points of Interest such as restaurants, schools, and lots of different kind of services.