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Use Python’s HTTPS tooling to call a GitHub REST endpoint, send the right authentication and API-version headers, check the status code, parse JSON, and follow pagination links for list responses. The direct approach below keeps every request visible. PyGithub is an optional third-party client when you prefer higher-level objects.
What you need before making a request
- Python 3 and a network connection that can reach
api.github.com. - A GitHub endpoint and its required permissions. Public read-only endpoints can often be called without credentials, but unauthenticated public-data requests generally have a lower primary limit.
- For private data or write operations, a credential injected through your environment or a secret manager. Do not place a live token in source code, a public repository, or browser-side JavaScript.
GitHub describes the REST API as a way to create integrations, retrieve data, and automate workflows. Every request is an HTTPS call; Python does not require a special GitHub runtime.
Choose authentication for the job
Use the narrowest credential and permissions that satisfy the endpoint.
Personal access token
A personal access token is suitable for personal scripts. Store it in an environment variable such as GITHUB_TOKEN and grant only the repository, organization, or account permissions the endpoint needs. Endpoint requirements differ, so check the endpoint’s current permission table before creating the token.
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GitHub App
Use a GitHub App when an integration acts for an organization or another user. Installation and user authorization provide more controlled, auditable access than sharing an individual’s credential.
Actions’ built-in token
Inside GitHub Actions, use the workflow’s GITHUB_TOKEN where it provides the required access. Configure the workflow’s permissions explicitly rather than assuming broad defaults.
Unauthenticated requests
An unauthenticated call can be useful for public data and quick experiments. GitHub documents a general limit of 60 requests per hour for unauthenticated public-data requests, with endpoint and traffic exceptions. Treat that as a conditional limit, not a guarantee for every route.
Make a direct request with Python
The following example retrieves a repository, keeps the token out of the file, identifies the API version explicitly, and fails clearly on an HTTP error. The version values documented by GitHub at the time of writing are 2026-03-10 and 2022-11-28. Requests without this header default to 2022-11-28; GitHub documents support for the older version through March 10, 2028. Recheck the version documentation when maintaining a long-lived integration.
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import requests
owner = "octocat"
repo = "Hello-World"
token = os.environ.get("GITHUB_TOKEN")
headers = {
"Accept": "application/vnd.github+json",
"X-GitHub-Api-Version": "2026-03-10",
}
if token:
headers["Authorization"] = f"Bearer {token}"
url = f"https://api.github.com/repos/{owner}/{repo}"
response = requests.get(url, headers=headers, timeout=30)
if response.status_code == 404:
raise RuntimeError("Repository was not found or is not visible to this credential")
response.raise_for_status()
repository = response.json()
print(repository["full_name"])
print(repository["stargazers_count"])Install the HTTP dependency in your project environment with python -m pip install requests. Set a token before running when the endpoint needs authentication:
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# macOS or Linux
export GITHUB_TOKEN='replace-with-a-token'
# PowerShell
$env:GITHUB_TOKEN = 'replace-with-a-token'The bearer header is omitted when no token is present, so the same script can read a public repository anonymously. For production, prefer your platform’s secret store over a shell history or a checked-in .env file.
Read a list endpoint and follow pagination
Most GitHub list endpoints return 30 resources by default. A successful first response therefore does not prove that the collection is complete. Request a deliberate page size where the endpoint supports it, then continue until the response has no Link header pointing to another page.
import os
import requests
headers = {
"Accept": "application/vnd.github+json",
"X-GitHub-Api-Version": "2026-03-10",
}
if token := os.environ.get("GITHUB_TOKEN"):
headers["Authorization"] = f"Bearer {token}"
def iter_repositories(owner, per_page=100):
url = f"https://api.github.com/users/{owner}/repos"
params = {"per_page": per_page, "page": 1, "type": "all"}
while url:
response = requests.get(url, headers=headers, params=params, timeout=30)
response.raise_for_status()
for item in response.json():
yield item
next_url = response.links.get("next", {}).get("url")
url = next_url
params = None # the Link URL already contains its query parameters
for repository in iter_repositories("octocat"):
print(repository["full_name"])Using response.links avoids rebuilding query parameters from assumptions about a particular endpoint. Preserve the query string supplied by GitHub’s link. For large exports, stream results to a file or database instead of holding every object in memory.
Inspect status, headers, and errors
Call raise_for_status() after handling any status you want to explain specially. The JSON error body often contains a useful message, while headers reveal rate-limit state and sometimes a request identifier.
def explain_failure(response):
try:
detail = response.json()
except ValueError:
detail = response.text
print("status:", response.status_code)
print("message:", detail)
print("remaining:", response.headers.get("x-ratelimit-remaining"))
print("reset:", response.headers.get("x-ratelimit-reset"))
print("retry-after:", response.headers.get("retry-after"))Do not log authorization headers or response bodies that may contain private repository data.
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Handle rate limits without making them worse
GitHub documents a general primary limit of 5,000 requests per hour for authenticated user requests, with different limits and rules for some authentication types and endpoints. Secondary limits can also return 403 or 429. Always inspect the response headers rather than hard-coding one universal number.
Primary-limit response
When x-ratelimit-remaining is zero, wait until the Unix time in x-ratelimit-reset before continuing. Queue work and reduce request volume instead of polling.
Secondary-limit response
If retry-after is present, wait that many seconds. If it is absent, GitHub advises waiting at least one minute and increasing delays exponentially if failures continue. Do not immediately retry every failed request.
import random
import time
from datetime import datetime, timezone
def wait_for_limit(response, attempt):
retry_after = response.headers.get("retry-after")
if retry_after:
delay = float(retry_after)
else:
reset = response.headers.get("x-ratelimit-reset")
if response.headers.get("x-ratelimit-remaining") == "0" and reset:
delay = max(0, int(reset) - int(datetime.now(timezone.utc).timestamp()))
else:
delay = min(60 * (2 ** attempt), 900) + random.random()
time.sleep(delay)Retry only operations that are safe to repeat. For writes, design idempotency or reconciliation so a timeout does not create duplicate work.
Use PyGithub when you want a client abstraction
GitHub’s library directory lists PyGithub under Python and identifies it as a third-party project, not an official Octokit library. Check its current documentation, maintenance, endpoint coverage, and authentication behavior before adopting it.
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import os
from github import Github
client = Github(login_or_token=os.environ["GITHUB_TOKEN"])
repository = client.get_repo("octocat/Hello-World")
print(repository.full_name)
print(repository.stargazers_count)
for issue in repository.get_issues(state="open"):
print(issue.number, issue.title)Direct requests calls make URL paths, headers, status codes, pagination, and rate-limit handling explicit. PyGithub can reduce repetitive code and present Python objects. The trade-off is an additional dependency and an abstraction whose endpoint support may differ from GitHub’s newest REST features. Use direct HTTP for a small integration or an endpoint the client does not expose; use the client when its objects and iteration model genuinely simplify your application.
Security and operational checklist
- Keep tokens in environment injection or a secret manager, never in source, notebooks committed to a repository, or front-end code.
- Use a credential type appropriate to the actor: personal token for personal work, GitHub App for organization or other-user access, and
GITHUB_TOKENin Actions where suitable. - Grant only endpoint-specific permissions and rotate or revoke credentials when staff, machines, or integrations change.
- Send an explicit
X-GitHub-Api-Versionheader and plan a review before your selected version’s support window ends. - Paginate every collection and record progress so a restart does not repeat all prior work.
- Cache stable reads, request only needed fields where an endpoint permits it, and avoid parallel bursts that trigger secondary limits.
- Set finite connect and read timeouts; capture status and safe diagnostic headers for support.
Troubleshooting common failures
401 Unauthorized
The token may be missing, revoked, malformed, or sent with the wrong scheme. Confirm that GITHUB_TOKEN is present in the process environment, use Authorization: Bearer ..., and create a replacement credential if it was revoked. Never print the token while debugging.
403 Forbidden
The credential may lack the endpoint’s permission, or you may have hit a primary or secondary limit. Inspect the JSON message and x-ratelimit-remaining, x-ratelimit-reset, and retry-after headers. Add the missing least-privilege permission only when the endpoint requires it; otherwise wait according to the limit guidance.
404 Not Found for a repository you can see in a browser
The owner or repository name may be wrong, the repository may be private, or the credential may not be authorized to see it. Verify the exact owner/name path and test with the same credential used by the script.
The script returns only 30 items
That is the documented default for most list endpoints. Add endpoint-supported pagination parameters and follow the response’s Link header until there is no next link.
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JSON decoding or timeout errors
A proxy, transient network failure, or an upstream error may have returned non-JSON content. Check the status and content type before decoding, use a finite timeout, and retry only safe requests with bounded backoff.
Changes appear inconsistent
Confirm that every process uses the same API-version header, authentication identity, repository, and query parameters. Log those non-secret values and the response status so differences are visible.
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Should I use REST or GraphQL from Python?
This guide focuses on GitHub’s REST API. Choose the interface required by the endpoint and data shape in your integration; the authentication and secret-handling principles still apply.
Can I put a token in a local notebook?
Only if it is injected securely and the notebook is protected from accidental sharing. Environment variables or a notebook platform’s secret store are safer than embedding a token in a cell.
How do I know whether an operation is safe to retry?
GET requests are normally repeatable. Treat POST, PATCH, and DELETE as potentially state-changing and consult the endpoint semantics before adding automatic retries.
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