Python Requests Get
Python Requests
Release v2. 26. 0. (Installation)
Requests is an elegant and simple HTTP library for Python, built for human beings.
Behold, the power of Requests:
>>> r = (”, auth=(‘user’, ‘pass’))
>>> atus_code
200
>>> r. headers[‘content-type’]
‘application/json; charset=utf8’
>>> r. encoding
‘utf-8’
>>>
‘{“type”:”User”… ‘
>>> ()
{‘private_gists’: 419, ‘total_private_repos’: 77,… }
See similar code, sans Requests.
Requests allows you to send HTTP/1. 1 requests extremely easily.
There’s no need to manually add query strings to your
URLs, or to form-encode your POST data. Keep-alive and HTTP connection pooling
are 100% automatic, thanks to urllib3.
Beloved Features¶
Requests is ready for today’s web.
Keep-Alive & Connection Pooling
International Domains and URLs
Sessions with Cookie Persistence
Browser-style SSL Verification
Automatic Content Decoding
Basic/Digest Authentication
Elegant Key/Value Cookies
Automatic Decompression
Unicode Response Bodies
HTTP(S) Proxy Support
Multipart File Uploads
Streaming Downloads
Connection Timeouts
Chunked Requests
Support
Requests officially supports Python 2. 7 & 3. 6+, and runs great on PyPy.
The User Guide¶
This part of the documentation, which is mostly prose, begins with some
background information about Requests, then focuses on step-by-step
instructions for getting the most out of Requests.
Installation of Requests
$ python -m pip install requests
Get the Source Code
Quickstart
Make a Request
Passing Parameters In URLs
Response Content
Binary Response Content
JSON Response Content
Raw Response Content
Custom Headers
More complicated POST requests
POST a Multipart-Encoded File
Response Status Codes
Response Headers
Cookies
Redirection and History
Timeouts
Errors and Exceptions
Advanced Usage
Session Objects
Request and Response Objects
Prepared Requests
SSL Cert Verification
Client Side Certificates
CA Certificates
Body Content Workflow
Keep-Alive
Streaming Uploads
Chunk-Encoded Requests
POST Multiple Multipart-Encoded Files
Event Hooks
Custom Authentication
Streaming Requests
Proxies
Compliance
HTTP Verbs
Custom Verbs
Link Headers
Transport Adapters
Blocking Or Non-Blocking?
Header Ordering
Authentication
Basic Authentication
Digest Authentication
OAuth 1 Authentication
OAuth 2 and OpenID Connect Authentication
Other Authentication
New Forms of Authentication
The API Documentation / Guide¶
If you are looking for information on a specific function, class, or method,
this part of the documentation is for you.
Developer Interface
Main Interface
Exceptions
Request Sessions
Lower-Level Classes
Lower-Lower-Level Classes
Encodings
Status Code Lookup
Migrating to 1. x
Migrating to 2. x
The Contributor Guide¶
If you want to contribute to the project, this part of the documentation is for
you.
Contributor’s Guide
Be Cordial
Get Early Feedback
Contribution Suitability
Code Contributions
Steps for Submitting Code
Code Review
New Contributors
Kenneth Reitz’s Code Style™
Documentation Contributions
Bug Reports
Feature Requests
Authors
Keepers of the Crystals
Previous Keepers of Crystals
Patches and Suggestions
There are no more guides. You are now guideless.
Good luck.
Python Requests get Method – W3Schools
❮ Requests Module
Example
Make a request to a web page, and return the status code:
import requestsx = (”)print(atus_code)
Run Example »
Definition and Usage
The get() method sends a GET request to the specified url.
Syntax
(url, params={key: value}, args)
args means zero or more of the named arguments in the parameter table below. Example:
(url, timeout=2. 50)
Parameter Values
Parameter
Description
url
Try it
Required. The url of the request
params
Optional. A dictionary, list of tuples or bytes to send as a query fault None
allow_redirects
Optional. A Boolean to enable/disable fault
True (allowing redirects)
auth
Optional. A tuple to enable a certain HTTP fault
None
cert
Optional. A String or Tuple specifying a cert file or fault
cookies
Optional. A dictionary of cookies to send to the specified fault
headers
Optional. A dictionary of HTTP headers to send to the specified fault None
proxies
Optional. A dictionary of the protocol to the proxy fault
stream
Optional. A Boolean indication if the response should be immediately downloaded (False) or streamed (True). Default
False
timeout
Optional. A number, or a tuple, indicating how many seconds to wait for the client to make a connection and/or send a fault None which means the request will continue
until the connection is closed
verify
Optional. A Boolean or a String indication to verify the servers TLS certificate or fault True
Return Value
The get() method returns a sponse object.
❮ Requests Module
How to Use the Python Requests Module With REST APIs
Learn how to use the Python Requests module to interact with any REST API in the world.
Ben Lloyd Pearson | June 11, 2020
The clear, simple syntax of Python makes it an ideal language to interact with REST APIs, and in typical Python fashion, there’s a library made specifically to provide that functionality:. Python Requests is a powerful tool that provides the simple elegance of Python to make HTTP requests to any API in the world. At Nylas, we built our REST APIs for email, calendar, and contacts on Python, and we process over 500 million API requests a day, so naturally, we depend a ton on the Python Requests library.
In this guide, we’ll take a comprehensive look at making HTTP requests with Python Requests and learn how to use this functionality to integrate with REST a PDF of this article? Share it with a friend or save it for later reading.
Contents:
The roles of HTTP, APIs, and REST
How to use Python Requests with REST APIs
How to authenticate to a REST API
How to handle HTTP errors with Python Requests
How to make robust API Requests
The Roles of HTTP, APIs, and REST
An Application Programming Interface (API) is a web service that grants access to specific data and methods that other applications can access – and sometimes edit – via standard HTTP protocols, just like a website. This simplicity makes it easy to quickly integrate APIs into a wide variety of applications. REpresentational State Transfer (REST), is probably the most popular architectural style of APIs for web services. It consists of a set of guidelines designed to simplify client / server communication. REST APIs make data access much more straightforward and logical.
The Request
When you want to interact with data via a REST API, this is called a request. A request is made up of the following components:
Endpoint – The URL that delineates what data you are interacting with. Similar to how a web page URL is tied to a specific page, an endpoint URL is tied to a specific resource within an API.
Method – Specifies how you’re interacting with the resource located at the provided endpoint. REST APIs can provide methods to enable full Create, Read, Update, and Delete (CRUD) functionality. Here are common methods most REST APIs provide:
GET – Retrieve data
PUT – Replace data
POST – Create data
DELETE – Delete data
Data – If you’re using a method that involves changing data in a REST API, you’ll need to include a data payload with the request that includes all data that will be created or modified.
Headers – Contain any metadata that needs to be included with the request, such as authentication tokens, the content type that should be returned, and any caching policies.
The Response
When you perform a request, you’ll get a response from the API. Just like in the request, it’ll have a response header and response data, if applicable. The response header consists of useful metadata about the response, while the response data returns what you actually requested. This can be any sort of data, as it’s really dependent on the API. The text is usually returned as JSON, but other markdown languages like XML are also possible.
Let’s look at a simple example of a request and a response. In the terminal, we’ll use curl to make a GET request to the Open Notify API. This is a simple, yet nifty API that has information about astronauts that are currently in space:
curl -X GET ”
You should see a response in JSON format that lists data about these astronauts, at the time of this article there are three people on a historic trip to the International Space Station:
{
“number”: 3,
“message”: “success”,
“people”: [
“craft”: “ISS”,
“name”: “Chris Cassidy”},
“name”: “Anatoly Ivanishin”},
“name”: “Ivan Vagner”}]}
How to Use Python Requests with REST APIs
Now, let’s take a look at what it takes to integrate with a REST API using Python Requests. First, you’ll need to have the necessary software; make sure you have Python and pip installed on your machine. Then, head over to the command line and install the python requests module with pip:
pip install requests
Now you’re ready to start using Python Requests to interact with a REST API, make sure you import the Requests library into any scripts you want to use it in:
import requests
How Request Data With GET
The GET method is used to access data for a specific resource from a REST API; Python Requests includes a function to do exactly this.
response = (“)
print(response)
>>>> Response<200>
The response object contains all the data sent from the server in response to your GET request, including headers and the data payload. When this code example prints the response object to the console it simply returns the name of the object’s class and the status code the request returned (more on status codes later).
While this information might be useful, you’re most likely interested in the content of the request itself, which can be accessed in a few ways:
ntent() # Return the raw bytes of the data payload
() # Return a string representation of the data payload
() # This method is convenient when the API returns JSON
How to Use Query Parameters
Queries can be used to filter the data that an API returns, and these are added as query parameters that are appended to the endpoint URL. With Python Requests, this is handled via the params argument, which accepts a dictionary object; let’s see what that looks like when we use the Open Notify API to GET an estimate for when the ISS will fly over a specified point:
query = {‘lat’:’45’, ‘lon’:’180′}
response = (”, params=query)
print(())
The print command would return something that looks like this:
‘message’: ‘success’,
‘request’: {
‘altitude’: 100,
‘datetime’: 1590607799,
‘latitude’: 45. 0,
‘longitude’: 180. 0,
‘passes’: 5},
‘response’: [
{‘duration’: 307, ‘risetime’: 1590632341},
{‘duration’: 627, ‘risetime’: 1590637934},
{‘duration’: 649, ‘risetime’: 1590643725},
{‘duration’: 624, ‘risetime’: 1590649575},
{‘duration’: 643, ‘risetime’: 1590655408}]}
How to Create and Modify Data With POST and PUT
In a similar manner as the query parameters, you can use the data argument to add the associated data for PUT and POST method requests.
# Create a new resource
response = (”, data = {‘key’:’value’})
# Update an existing resource
(”, data = {‘key’:’value’})
How to Access REST Headers
You can also retrieve metadata from the response via headers. For example, to view the date of the response, just specify that with the `headers` property:
print(response. headers[“date”])
>>>> ‘Wed, 11 June 2020 19:32:24 GMT’
For open APIs, that covers the basics. However, many APIs can’t be used by just anyone. For those, let’s go over how to authenticate to REST APIs.
How to Authenticate to a REST API
So far you’ve seen how to interact with open REST APIs that don’t require any authorization. However, many REST APIs require you to authenticate to them before you can access specific endpoints, particularly if they deal with sensitive data.
There are a few common authentication methods for REST APIs that can be handled with Python Requests. The simplest way is to pass your username and password to the appropriate endpoint as HTTP Basic Auth; this is equivalent to typing your username and password into a website.
(
”,
auth=HTTPBasicAuth(‘username’, ‘password’))
A more secure method is to get an access token that acts as an equivalent to a username/password combination; the method to get an access token varies widely from API to API, but the most common framework for API authentication is OAuth. Here at Nylas, we use three-legged OAuth to grant an access token for user accounts that is restricted to scopes that define the specific data and functionality that can be accessed. This process is demonstrated in the Nylas Hosted Auth service.
Once you have an access token, you can provide it as a bearer token in the request header: this is the most secure way to authenticate to a REST API with an access token:
my_headers = {‘Authorization’: ‘Bearer {access_token}’}
response = (”, headers=my_headers)
There are quite a few other methods to authenticate to a REST API, including digest, Kerberos, NTLM, and AuthBase. The use of these depends on the architecture decisions of the REST API producer.
Use Sessions to Manage Access Tokens
Session objects come in handy when working with Python Requests as a tool to persist parameters that are needed for making multiple requests within a single session, like access tokens. Also, managing session cookies can provide a nice performance increase because you don’t need to open a new connection for every request.
session = ssion()
({‘Authorization’: ‘Bearer {access_token}’})
response = (”)
How to Handle HTTP Errors With Python Requests
API calls don’t always go as planned, and there’s a multitude of reasons why API requests might fail that could be the fault of either the server or the client. If you’re going to use a REST API, you need to understand how to handle the errors they output when things go wrong to make your code more robust. This section covers everything you need to know about handling HTTP errors with Python Requests.
The Basics of HTTP Status Codes
Before we dive into the specifics of Python Requests, we first need to take a step back and understand what HTTP status codes are and how they relate to errors you might encounter.
All status codes fall into one of five categories.
1xx Informational – Indicates that a request has been received and that the client should continue to make the requests for the data payload. You likely won’t need to worry about these status codes while working with Python Requests.
2xx Successful – Indicates that a requested action has been received, understood, and accepted. You can use these codes to verify the existence of data before attempting to act on it.
3xx Redirection – Indicates that the client must make an additional action to complete the request like accessing the resource via a proxy or a different endpoint. You may need to make additional requests, or modify your requests to deal with these codes.
4xx Client Error – Indicates problems with the client, such as a lack of authorization, forbidden access, disallowed methods, or attempts to access nonexistent resources. This usually indicates configuration errors on the client application.
5xx Server Error – Indicates problems with the server that provides the API. There are a large variety of server errors and they often require the API provider to resolve.
How to Check for HTTP Errors With Python Requests
The response objects has a status_code attribute that can be used to check for any errors the API might have reported. The next example shows how to use this attribute to check for successful and 404 not found HTTP status codes, and you can use this same format for all HTTP status codes.
if (atus_code == 200):
print(“The request was a success! “)
# Code here will only run if the request is successful
elif (atus_code == 404:
print(“Result not found! “)
# Code here will react to failed requests
To see this in action, try removing the last letter from the URL endpoint, the API should return a 404 status code.
If you want requests to raise an exception for all error codes (4xx and 5xx), you can use the raise_for_status() function and catch specific errors using Requests built-in exceptions. This next example accomplishes the same thing as the previous code example.
try:
response. raise_for_status()
# Additional code will only run if the request is successful
except TPError as error:
print(error)
# This code will run if there is a 404 error.
TooManyRedirects
Something that is often indicated by 3xx HTTP status codes is the requirement to redirect to a different location for the resource you’re requesting. This can sometimes result in a situation where you end up with an infinite redirect loop. The Python Requests module has the TooManyRedirects error that you can use to handle this problem. To resolve this problem, it’s likely the URL you’re using to access the resource is wrong and needs to be changed.
except oManyRedirects as error:
You can optionally use the request options to set the maximum number of redirects:
response = (”, max_redirects=2)
Or disable redirecting completely within your request options:
response = (”, allow_redirects=False)
ConnectionError
So far, we’ve only looked at errors that come from an active server. What happens if you don’t receive a response from the server at all? Connection errors can occur for many different reasons, including a DNS failure, refused connection, internet connectivity issues or latency somewhere in the network. Python Requests offers the ConnectionError exception that indicates when your client is unable to connect to the server.
except nnectionError as error:
This type of error might be temporary, or permanent. In the former scenario, you should retry the request again to see if there is a different result. In the latter scenario, you should make sure you’re able to deal with a prolonged inability to access data from the API, and it might require you to investigate your own connectivity issues.
Timeout
Timeout errors occur when you’re able to connect to the API server, but it doesn’t complete the request within the allotted amount of time. Similar to the other errors we’ve looked at, Python Requests can handle this error with a Timeout exception:
response = (”, timeout=0. 00001)
except requests. Timeout as error:
In this example, the timeout was set as a fraction of a second via the request options. Most APIs are unable to respond this quickly, so the code will produce a timeout exception. You can avoid this error by setting longer timeouts for your script, optimizing your requests to be smaller, or setting up a retry loop for the request. This can also sometimes indicate a problem with the API provider. One final solution is to incorporate asynchronous API calls to prevent your code from stopping while it waits for larger responses.
How to Make Robust API Requests
As we’ve seen, the Requests module elegantly handles common API request errors by utilizing exception handling in Python. If we put all of the errors we’ve talked about together, we have a rather seamless way to handle any HTTP request error that comes our way:
response = (”, timeout=5)
except TPError as errh:
print(errh)
except nnectionError as errc:
print(errc)
except requests. exceptions. Timeout as errt:
print(errt)
except questException as err:
print(err)
If you’ve made it this far, congrats! You’re well on your way to becoming a Python Requests wizard for whom no REST API is too great a match. Want to keep learning? We have tons of knowledgable Python experts here at Nylas, and we have in-depth content on our blog about packaging and deploying Python code to production, and using environment variables to make your Python code more secure.
Ben Lloyd Pearson
Ben is the Developer Advocate for Nylas. He is a triathlete, musician, avid gamer, and loves to seek out the best breakfast tacos in Austin, Texas.
Frequently Asked Questions about python requests get
What is Requests get in Python?
When the method is GET, all form data is encoded into the URL, appended to the action URL as query string parameters. With POST, form data appears within the message body of the HTTP request. In GET method, the parameter data is limited to what we can stuff into the request line (URL).Sep 21, 2021
Does Python come with requests?
Requests is one of the most popular Python libraries that is not included with Python. It has been proposed that Requests be distributed with Python by default. Requests is an Apache2 Licensed HTTP library, written in Python, for human beings.
What does Python requests get return?
When one makes a request to a URI, it returns a response. This Response object in terms of python is returned by requests. method(), method being – get, post, put, etc. Response is a powerful object with lots of functions and attributes that assist in normalizing data or creating ideal portions of code.Jul 23, 2021
