Feature/bulk add repositories #2
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- Add codacy_bulk_add.py with comprehensive bulk add functionality - Uses Codacy org endpoint to discover repositories automatically - Includes integration settings configuration (all disabled by default) - Supports dry-run mode, selective repository processing, and rate limiting - Handles existing repositories gracefully with detailed error reporting - Update README.md to document both tools with usage examples - Maintain backward compatibility with existing codacy_follow.py
![codacy-production[bot]](https://avatars.githubusercontent.com/in/56611?s=60&v=4){kind=small}
| import json | ||
| import argparse | ||
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| def test_list_repositories(baseurl, provider, organization, token): |
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The issue highlighted by the Lizard linter indicates that the test_list_repositories function has a cyclomatic complexity of 16, which exceeds the recommended limit of 8. Cyclomatic complexity measures the number of linearly independent paths through a program's source code. A high complexity suggests that the function may be doing too much and could benefit from being broken down into smaller, more manageable functions.
To address this issue, one effective approach is to separate the logic for testing different endpoints into distinct functions. This reduces the complexity of the test_list_repositories function.
Here's a code suggestion that refactors the function to reduce its complexity by delegating the endpoint testing to a helper function:
def test_list_repositories(baseurl, provider, organization, token):
"""Test different API endpoints to list repositories."""
test_added_repositories(baseurl, provider, organization, token)
def test_added_repositories(baseurl, provider, organization, token):
headers = {
'Accept': 'application/json',
'api-token': token
}
# Test the current endpoint (only shows added repos)
print("=== Testing current endpoint (added repos only) ===")
url1 = f'{baseurl}/api/v3/organizations/{provider}/{organization}/repositories'This change introduces a new function, test_added_repositories, which handles the logic related to testing the added repositories endpoint. This reduces the cyclomatic complexity of test_list_repositories and improves the overall readability and maintainability of the code.
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| return False, f"Failed to add {repo}: {str(e)}" | ||
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| def processAllRepositories(baseurl, provider, organization, token, reponames=None, dry_run=False): |
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The issue with the processAllRepositories function is that it has a cyclomatic complexity of 12, which exceeds the acceptable limit of 8. Cyclomatic complexity is a software metric used to measure the complexity of a program by counting the number of linearly independent paths through the code. High complexity can make code harder to understand, maintain, and test.
In this case, the function likely contains multiple conditional statements (like if and else) that contribute to its complexity. To reduce this complexity, we can refactor the code to handle input validation and repository filtering in a more streamlined manner.
Here's a single line change that simplifies the handling of reponames:
| def processAllRepositories(baseurl, provider, organization, token, reponames=None, dry_run=False): | |
| if reponames: target_repos = [repo.strip() for repo in reponames.split(',')] or [] |
This change uses a more concise approach to initialize target_repos, ensuring that if reponames is empty or invalid, it defaults to an empty list, thus reducing the complexity of the function.
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| ) | ||
| logger = logging.getLogger(__name__) | ||
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| def listRepositories(baseurl, provider, organization, token): |
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The issue reported by the Lizard linter indicates that the listRepositories function has a cyclomatic complexity of 10, which exceeds the recommended limit of 8. Cyclomatic complexity is a measure of the number of linearly independent paths through a program's source code. A high complexity score often suggests that a function is doing too much, which can make it harder to read, maintain, and test.
To address this, we can refactor the function to reduce its complexity. One common approach is to break down the logic into smaller helper functions. However, since you requested a single line change, we can start by simplifying the function signature or its parameters.
Here's a code suggestion that encapsulates the parameters into a single object, which can help reduce the complexity score:
| def listRepositories(baseurl, provider, organization, token): | |
| def listRepositories(config): |
In this case, config would be a dictionary or a custom object containing baseurl, provider, organization, and token, which can help streamline the function's interface and potentially reduce complexity in the logic that follows.
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| import json | ||
| import argparse | ||
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| def test_list_repositories(baseurl, provider, organization, token): |
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The issue reported by the Lizard linter indicates that the test_list_repositories function has exceeded the recommended line limit of 50 lines, as it currently contains 57 lines of code. This can make the function difficult to read and maintain. To address this complexity issue, you can consider refactoring the function into smaller, more manageable pieces.
A simple way to reduce the line count while maintaining functionality is to extract the header preparation into a separate function. This allows the main function to focus on its core logic.
Here’s a code suggestion to implement this change:
| def test_list_repositories(baseurl, provider, organization, token): | |
| def prepare_headers(token): return {'Accept': 'application/json', 'api-token': token} |
Then, you would call prepare_headers(token) within test_list_repositories instead of defining headers directly in it. This single line change can help reduce the overall complexity of the function.
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| if "permission" in error_response.get("message", "").lower(): | ||
| logger.warning(f"Repository {repo} already exists (following state)") | ||
| return False, f"Repository {repo} already exists: {e.response.status_code}" | ||
| except: |
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The issue identified by the Bandit linter is that using a bare except statement can lead to catching unexpected exceptions, which can mask errors and make debugging difficult. This practice is generally discouraged because it can hide issues that should be addressed. Instead, it's better to catch specific exceptions that you expect might occur.
To fix this, we should catch only the specific exception that we expect to be raised when trying to parse the JSON response. In this case, it would be appropriate to catch json.JSONDecodeError.
Here's the suggested change:
| except: | |
| except json.JSONDecodeError: |
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| logger.debug(f"Making request to: {current_url}") | ||
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| try: | ||
| response = requests.get(current_url, headers=headers) |
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The issue identified by the Bandit linter is that the requests.get() call does not specify a timeout parameter. Without a timeout, the request could hang indefinitely if the server does not respond, leading to potential denial-of-service issues or unresponsive applications.
To address this, it's important to specify a timeout for the request, which helps ensure that your application can handle situations where the server is slow to respond or is unresponsive altogether.
Here is a code suggestion to fix the issue by adding a timeout of, for example, 10 seconds:
| response = requests.get(current_url, headers=headers) | |
| response = requests.get(current_url, headers=headers, timeout=10) |
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| for url in test_endpoints: | ||
| print(f"=== Testing: {url} ===") | ||
| try: | ||
| response = requests.get(url, headers=headers) |
There was a problem hiding this comment.
The issue identified by the Bandit linter is that the requests.get() call does not specify a timeout parameter. Without a timeout, the request could hang indefinitely if the server does not respond, which can lead to application unresponsiveness or denial of service.
To fix this issue, you should specify a timeout value in the requests.get() call. A common practice is to set a reasonable timeout, such as 5 seconds, but this can be adjusted based on the specific requirements of your application.
Here is the suggested code change:
| response = requests.get(url, headers=headers) | |
| response = requests.get(url, headers=headers, timeout=5) |
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| logger.debug(f"Making request to: {url}") | ||
| logger.debug(f"Request data: {json.dumps(data, indent=2)}") | ||
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| response = requests.post(url, headers=headers, json=data) |
There was a problem hiding this comment.
The issue identified by the Bandit linter is that the requests.post call does not specify a timeout. Not providing a timeout can lead to situations where the request hangs indefinitely if the server does not respond, potentially causing the application to become unresponsive. To mitigate this risk, it is recommended to always specify a timeout value for network requests.
Here’s the code suggestion to fix the issue by adding a timeout:
| response = requests.post(url, headers=headers, json=data) | |
| response = requests.post(url, headers=headers, json=data, timeout=10) |
In this suggestion, a timeout of 10 seconds is set, but you can adjust this value based on your application's requirements.
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| print(f"URL: {url1}") | ||
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| try: | ||
| response = requests.get(url1, headers=headers) |
There was a problem hiding this comment.
The issue identified by the Bandit linter is that the requests.get call does not specify a timeout parameter. Not providing a timeout can lead to the application hanging indefinitely if the server does not respond, which can be a security risk and impact the user experience.
To fix this issue, you should add a timeout parameter to the requests.get call. Here's the suggested change:
| response = requests.get(url1, headers=headers) | |
| response = requests.get(url1, headers=headers, timeout=10) |
This change sets a timeout of 10 seconds for the request, after which it will raise a Timeout exception if the server does not respond. Adjust the timeout value as necessary based on your application's requirements.
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| @@ -0,0 +1,89 @@ | |||
| #!/usr/bin/env python3 | |||
| import requests | |||
| import json | |||
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The issue identified by Pylint indicates that the json module has been imported but is not being utilized anywhere in the provided code fragment. This can lead to unnecessary clutter in the code, and removing unused imports can improve readability and maintainability.
To fix this issue, you can simply remove the import statement for the json module since it is not being used in the current context. Here’s the suggested change:
| import json | |
| import requests |
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| if "permission" in error_response.get("message", "").lower(): | ||
| logger.warning(f"Repository {repo} already exists (following state)") | ||
| return False, f"Repository {repo} already exists: {e.response.status_code}" | ||
| except: |
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🚫 Codacy found a high ErrorProne issue: No exception type(s) specified
The issue identified by Pylint is that the except clause does not specify any exception types. This can lead to catching unexpected exceptions, making debugging difficult and potentially masking other issues in the code. It's generally a good practice to catch specific exceptions that you expect might occur.
In this case, since you're trying to parse a JSON response, you should catch ValueError (which can occur if the response is not valid JSON) and KeyError (which can occur if the expected key is not found). However, for simplicity, you could also catch json.JSONDecodeError, which is a more specific exception for JSON decoding issues.
Here's a code suggestion to fix the issue by specifying the exception type:
| except: | |
| except (ValueError, KeyError, json.JSONDecodeError): |
Make sure to import the json module at the beginning of your code if it's not already imported:
| except: | |
| import json |
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| if "permission" in error_response.get("message", "").lower(): | ||
| logger.warning(f"Repository {repo} already exists (following state)") | ||
| return False, f"Repository {repo} already exists: {e.response.status_code}" | ||
| except: |
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🚫 Codacy found a high Security issue: Try, Except, Pass detected. (B110)
The issue identified by the Prospector linter is related to the use of a bare except: clause, which can catch all exceptions, including those that you might not want to handle (like KeyboardInterrupt or SystemExit). This practice can lead to hiding bugs and making debugging difficult, as it prevents the program from failing loudly when an unexpected error occurs.
To address this, it is advisable to catch only specific exceptions that you expect might occur during the execution of the code within the try block. In this case, since you are trying to parse a JSON response, you should specifically catch ValueError (which can occur if the response is not valid JSON) and KeyError (which can occur if the expected keys are not present in the JSON object).
Here's the suggested change:
| except: | |
| except (ValueError, KeyError): |
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| logger.debug(f"Making request to: {current_url}") | ||
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| try: | ||
| response = requests.get(current_url, headers=headers) |
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🚫 Codacy found a high Security issue: Call to requests without timeout (B113)
The issue identified by the Prospector linter is that the requests.get call is made without specifying a timeout. If the server does not respond, the request could hang indefinitely, potentially leading to resource exhaustion or application unresponsiveness. It's a best practice to always set a timeout for network requests to ensure that your application can handle situations where the server is unresponsive.
To fix this issue, you can add a timeout parameter to the requests.get call. Here’s the suggested change:
| response = requests.get(current_url, headers=headers) | |
| response = requests.get(current_url, headers=headers, timeout=10) |
In this example, a timeout of 10 seconds is specified, but you can adjust this value based on your application's requirements.
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| for url in test_endpoints: | ||
| print(f"=== Testing: {url} ===") | ||
| try: | ||
| response = requests.get(url, headers=headers) |
There was a problem hiding this comment.
🚫 Codacy found a high Security issue: Call to requests without timeout (B113)
The issue identified by the Prospector linter is related to the lack of a timeout parameter in the requests.get call. When making network requests, it's important to specify a timeout to prevent the application from hanging indefinitely if the server does not respond. Without a timeout, the request could block the execution of the program, leading to poor user experience or resource exhaustion.
To fix this issue, you can add a timeout parameter to the requests.get call. A common practice is to set a reasonable timeout, such as 5 seconds, but you can adjust this based on your application's needs.
Here's the suggested code change:
| response = requests.get(url, headers=headers) | |
| response = requests.get(url, headers=headers, timeout=5) |
This comment was generated by an experimental AI tool.
| print(f"URL: {url1}") | ||
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| try: | ||
| response = requests.get(url1, headers=headers) |
There was a problem hiding this comment.
🚫 Codacy found a high Security issue: Call to requests without timeout (B113)
The issue identified by the Prospector linter is that the requests.get call does not specify a timeout. Without a timeout, the request could hang indefinitely if the server does not respond, which can lead to unresponsive applications and degraded user experience. It's a best practice to always set a timeout for network requests to ensure that your application can handle situations where the server may be slow to respond or unresponsive.
To fix this issue, you can add a timeout parameter to the requests.get call. Here's the single line change:
| response = requests.get(url1, headers=headers) | |
| response = requests.get(url1, headers=headers, timeout=10) |
In this example, a timeout of 10 seconds is specified, but you can adjust this value based on your application's needs.
This comment was generated by an experimental AI tool.
| logger.debug(f"Making request to: {url}") | ||
| logger.debug(f"Request data: {json.dumps(data, indent=2)}") | ||
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| response = requests.post(url, headers=headers, json=data) |
There was a problem hiding this comment.
🚫 Codacy found a high Security issue: Call to requests without timeout (B113)
The issue highlighted by the Prospector linter is that the requests.post call does not specify a timeout. Not providing a timeout can lead to the application hanging indefinitely if the server does not respond, which could be a security risk in certain scenarios, especially in production environments. To mitigate this risk, it is advisable to always set a timeout for network requests.
Here’s the suggested code change to include a timeout:
| response = requests.post(url, headers=headers, json=data) | |
| response = requests.post(url, headers=headers, json=data, timeout=10) |
In this example, a timeout of 10 seconds is specified, but you can adjust this value based on your application's requirements.
This comment was generated by an experimental AI tool.
| logger.debug(f"Making request to: {url}") | ||
| logger.debug(f"Request data: {json.dumps(data, indent=2)}") | ||
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| response = requests.post(url, headers=headers, json=data) |
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🚫 Codacy found a high Security issue: The application was found using the requests module without configuring a timeout value for connections.
The issue identified by the Semgrep linter is that the requests.post method is being called without a timeout value. Failing to set a timeout can lead to the application hanging indefinitely if the server does not respond, which can be a significant security and reliability risk. By specifying a timeout, you can ensure that the request will fail after a certain period, allowing your application to handle the situation gracefully.
To fix this issue, you can add a timeout parameter to the requests.post call. Here’s the suggested code change:
| response = requests.post(url, headers=headers, json=data) | |
| response = requests.post(url, headers=headers, json=data, timeout=10) |
In this example, a timeout of 10 seconds is specified, but you can adjust the value based on your application's needs.
This comment was generated by an experimental AI tool.
| logger.debug(f"Making request to: {current_url}") | ||
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| try: | ||
| response = requests.get(current_url, headers=headers) |
There was a problem hiding this comment.
🚫 Codacy found a high Security issue: The application was found using the requests module without configuring a timeout value for connections.
The issue highlighted by the Semgrep linter is that the requests.get call does not have a timeout value configured. Not specifying a timeout can lead to the application hanging indefinitely if the server does not respond, which can cause performance issues or even denial of service in certain scenarios. It is a best practice to always set a timeout for network requests to ensure that your application can handle cases where the server is unresponsive.
To fix this issue, you can add a timeout parameter to the requests.get call. Here's the code suggestion to implement this change:
| response = requests.get(current_url, headers=headers) | |
| response = requests.get(current_url, headers=headers, timeout=10) |
In this example, a timeout of 10 seconds is specified, but you can adjust this value based on your application's needs.
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| return 1 | ||
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| if __name__ == "__main__": | ||
| exit(main()) |
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exit. Use sys.exit over the python shell exit built-in. exit is a helper for the interactive shell and may not be available on all Python implementations.
The issue identified by the Semgrep linter is that the code uses the built-in exit() function, which is primarily intended for use in interactive Python sessions and may not be available in all Python implementations. Instead, it's recommended to use sys.exit(), which is a more reliable way to terminate a program and is part of the sys module.
To fix this issue, you need to import the sys module and replace the exit() call with sys.exit(). Here's the single line change to implement this fix:
| exit(main()) | |
| sys.exit(main()) |
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| print(f"URL: {url1}") | ||
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| try: | ||
| response = requests.get(url1, headers=headers) |
There was a problem hiding this comment.
🚫 Codacy found a high Security issue: The application was found using the requests module without configuring a timeout value for connections.
The issue identified by the Semgrep linter pertains to the absence of a timeout value in the requests.get call. When a request is made without a timeout, the application may hang indefinitely if the server does not respond, which can lead to poor user experience and potential denial-of-service vulnerabilities. Setting a timeout ensures that the request will fail after a specified duration, allowing the application to handle the situation gracefully.
To fix this issue, you can add a timeout parameter to the requests.get call. Here's the suggested change:
| response = requests.get(url1, headers=headers) | |
| response = requests.get(url1, headers=headers, timeout=10) |
In this example, a timeout of 10 seconds is specified, which means that the request will raise a Timeout exception if it takes longer than 10 seconds to receive a response. Adjust the timeout value as appropriate for your application's requirements.
This comment was generated by an experimental AI tool.
| for url in test_endpoints: | ||
| print(f"=== Testing: {url} ===") | ||
| try: | ||
| response = requests.get(url, headers=headers) |
There was a problem hiding this comment.
🚫 Codacy found a high Security issue: The application was found using the requests module without configuring a timeout value for connections.
The issue identified by the Semgrep linter is that the requests.get() method is being called without a timeout parameter. This can lead to potential security and stability issues, as the application may hang indefinitely if the server does not respond, which could be exploited by attackers to create denial-of-service conditions.
To fix this issue, you should specify a timeout value, which will ensure that the request does not wait indefinitely for a response. A common practice is to set a timeout of a few seconds, depending on the expected response time of the server.
Here's the code suggestion to add a timeout parameter to the requests.get() call:
| response = requests.get(url, headers=headers) | |
| response = requests.get(url, headers=headers, timeout=5) |
This comment was generated by an experimental AI tool.
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