🕷️ Crawler Inspector

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Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 59 (from laksa061)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa059.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://pypi.org/project/bellmanford/\')), getAhrefsUnparsedNoserviceFromURL(\'https://pypi.org/project/bellmanford/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/pypi.org\/project\/bellmanford\/","crawl_time":1773193022,"first_indexed_time":1495869070,"http_code":200,"src_unparsed":"org,pypi!\/project\/bellmanford\/ s443","src_root_hash":"7813724874982801459","history_drop_reason":null,"meta_title":"bellmanford · PyPI","meta_descriptions":["Small extensions of the Bellman-Ford routines in NetworkX, primarily for convenience (https:\/\/networkx.github.io)."],"attrs_boilerpipe_text":"This package provides a few small extensions of the Bellman-Ford\nroutines in\nNetworkX\n, primarily for\nconvenience.\nInstallation\nbellmanford\nis available on PyPI:\npip\ninstall\nbellmanford\nUsage\nbellman_ford\nlength\n,\nnodes\n,\nnegative_cycle\n=\nbellman_ford\n(\nG\n,\nsource\n,\ntarget\n,\nweight\n=\n'weight'\n)\nCompute shortest path and shortest path lengths between a source node\nand target node in weighted graphs using the Bellman-Ford algorithm.\nParameters\nG\n: NetworkX graph\npred\n: dict - Keyed by node to predecessor in the path\ndist\n: dict - Keyed by node to the distance from the source\nsource\n: node label - Source node\ntarget\n: node label - Target node\nweight\n: string - Edge data key corresponding to the edge weight\nReturns\nlength\n: numeric - Length of a negative cycle if one exists.\nOtherwise, length of a shortest path. Length is\ninf\nif\nsource\nand\ntarget\nare not connected.\nnodes\n: list - Nodes in a negative edge cycle (in order) if one\nexists. Otherwise nodes in a shortest path. List is empty if\nsource\nand\ntarget\nare not connected.\nnegative_cycle\n: bool -\nTrue\nif a negative edge cycle exists,\notherwise\nFalse\n.\nExamples\n>>>\nimport\nnetworkx\nas\nnx\n>>>\nG\n=\nnx\n.\npath_graph\n(\n5\n,\ncreate_using\n=\nnx\n.\nDiGraph\n())\n>>>\nbf\n.\nbellman_ford\n(\nG\n,\nsource\n=\n0\n,\ntarget\n=\n4\n)\n(\n3\n,\n[\n1\n,\n2\n,\n3\n,\n4\n],\nFalse\n)\nnegative_edge_cycle\nlength\n,\nnodes\n,\nnegative_cycle\n=\nnegative_edge_cycle\n(\nG\n,\nweight\n=\n'weight'\n)\nIf there is a negative edge cycle anywhere in\nG\n, returns\nTrue\n.\nAlso returns the total weight of the cycle and the nodes in the cycle.\nParameters\nG\n: NetworkX graph\nweight\n: string, optional (default =\n'weight'\n) - Edge data\nkey corresponding to the edge weight\nReturns\nlength\n: numeric - Length of a negative edge cycle if one exists,\notherwise\nNone\n.\nnodes\n: list - Nodes in a negative edge cycle (in order) if one\nexists, otherwise\nNone\n.\nnegative_cycle\n: bool -\nTrue\nif a negative edge cycle exists,\notherwise\nFalse\n.\nExamples\n>>>\nimport\nnetworkx\nas\nnx\n>>>\nimport\nbellmanford\nas\nbf\n>>>\nG\n=\nnx\n.\ncycle_graph\n(\n5\n,\ncreate_using\n=\nnx\n.\nDiGraph\n())\n>>>\nprint\n(\nbf\n.\nnegative_edge_cycle\n(\nG\n))\n(\nNone\n,\n[],\nFalse\n)\n>>>\nG\n[\n1\n][\n2\n][\n'weight'\n]\n=\n-\n7\n>>>\nprint\n(\nbf\n.\nnegative_edge_cycle\n(\nG\n))\n(\n-\n3\n,\n[\n4\n,\n0\n,\n1\n,\n2\n,\n3\n,\n4\n],\nTrue\n)","attrs_markdown":"[Skip to main content](https:\/\/pypi.org\/project\/bellmanford\/#content)\n\nSwitch to mobile version\n\nWarning  Some features may not work without JavaScript. Please try enabling it if you encounter problems.\n\nJoin the official Python Developers Survey 2026 and have a chance to win a prize [Take the 2026 survey\\!](https:\/\/surveys.jetbrains.com\/s3\/python-developers-survey-2026)\n\n[![PyPI](https:\/\/pypi.org\/static\/images\/logo-small.8998e9d1.svg)](https:\/\/pypi.org\/)\n\n- [Help](https:\/\/pypi.org\/help\/)\n- [Docs](https:\/\/docs.pypi.org\/)\n- [Sponsors](https:\/\/pypi.org\/sponsors\/)\n- [Log in](https:\/\/pypi.org\/account\/login\/?next=https%3A%2F%2Fpypi.org%2Fproject%2Fbellmanford%2F)\n- [Register](https:\/\/pypi.org\/account\/register\/)\n\nMenu\n\n- [Help](https:\/\/pypi.org\/help\/)\n- [Docs](https:\/\/docs.pypi.org\/)\n- [Sponsors](https:\/\/pypi.org\/sponsors\/)\n- [Log in](https:\/\/pypi.org\/account\/login\/?next=https%3A%2F%2Fpypi.org%2Fproject%2Fbellmanford%2F)\n- [Register](https:\/\/pypi.org\/account\/register\/)\n\n# bellmanford 0.2.1\npip install bellmanford Copy PIP instructions\n\n[Latest version](https:\/\/pypi.org\/project\/bellmanford\/)\n\nReleased: May 7, 2018\n\nSmall extensions of the Bellman-Ford routines in NetworkX, primarily for convenience (https:\/\/networkx.github.io).\n\n### Navigation\n- [Project description](https:\/\/pypi.org\/project\/bellmanford\/#description)\n- [Release history](https:\/\/pypi.org\/project\/bellmanford\/#history)\n- [Download files](https:\/\/pypi.org\/project\/bellmanford\/#files)\n\n### Verified details\n*These details have been [verified by PyPI](https:\/\/docs.pypi.org\/project_metadata\/#verified-details)*\n\n###### Maintainers\n[![Avatar for nelsonuhan from gravatar.com](https:\/\/pypi-camo.freetls.fastly.net\/b6e0399a3c5310419441272f5bb761650051f957\/68747470733a2f2f7365637572652e67726176617461722e636f6d2f6176617461722f65613462323932373465633931396664646662326632303232613038373363323f73697a653d3530) nelsonuhan](https:\/\/pypi.org\/user\/nelsonuhan\/)\n\n### Unverified details\n*These details have **not** been verified by PyPI*\n\n###### Project links\n- [Homepage](https:\/\/github.com\/nelsonuhan\/bellmanford)\n\n###### Meta\n- **License:** BSD\n- **Author:** [Nelson Uhan](mailto:nelson@uhan.me)\n\n[Report project as malware](https:\/\/pypi.org\/project\/bellmanford\/submit-malware-report\/)\n\n- [Project description](https:\/\/pypi.org\/project\/bellmanford\/#description)\n- [Project details](https:\/\/pypi.org\/project\/bellmanford\/#data)\n- [Release history](https:\/\/pypi.org\/project\/bellmanford\/#history)\n- [Download files](https:\/\/pypi.org\/project\/bellmanford\/#files)\n\n## Project description\nThis package provides a few small extensions of the Bellman-Ford routines in [NetworkX](https:\/\/networkx.github.io\/), primarily for convenience.\n\n## Installation\nbellmanford is available on PyPI:\n```\npip install bellmanford\n```\n\n## Usage\n### bellman\\_ford\n```\nlength, nodes, negative_cycle = bellman_ford(G, source, target, weight='weight')\n```\nCompute shortest path and shortest path lengths between a source node and target node in weighted graphs using the Bellman-Ford algorithm.\n\n#### Parameters\n- G : NetworkX graph\n- pred : dict - Keyed by node to predecessor in the path\n- dist : dict - Keyed by node to the distance from the source\n- source: node label - Source node\n- target: node label - Target node\n- weight : string - Edge data key corresponding to the edge weight\n\n#### Returns\n- length : numeric - Length of a negative cycle if one exists. Otherwise, length of a shortest path. Length is inf if source and target are not connected.\n- nodes : list - Nodes in a negative edge cycle (in order) if one exists. Otherwise nodes in a shortest path. List is empty if source and target are not connected.\n- negative\\_cycle : bool - True if a negative edge cycle exists, otherwise False.\n\n#### Examples\n```\n>>> import networkx as nx\n>>> G = nx.path_graph(5, create_using = nx.DiGraph())\n>>> bf.bellman_ford(G, source=0, target=4)\n(3, [1, 2, 3, 4], False)\n```\n\n### negative\\_edge\\_cycle\n```\nlength, nodes, negative_cycle = negative_edge_cycle(G, weight='weight')\n```\nIf there is a negative edge cycle anywhere in G, returns True. Also returns the total weight of the cycle and the nodes in the cycle.\n\n#### Parameters\n- G : NetworkX graph\n- weight : string, optional (default = 'weight') - Edge data key corresponding to the edge weight\n\n#### Returns\n- length : numeric - Length of a negative edge cycle if one exists, otherwise None.\n- nodes : list - Nodes in a negative edge cycle (in order) if one exists, otherwise None.\n- negative\\_cycle : bool - True if a negative edge cycle exists, otherwise False.\n\n#### Examples\n```\n>>> import networkx as nx\n>>> import bellmanford as bf\n>>> G = nx.cycle_graph(5, create_using = nx.DiGraph())\n>>> print(bf.negative_edge_cycle(G))\n(None, [], False)\n>>> G[1][2]['weight'] = -7\n>>> print(bf.negative_edge_cycle(G))\n(-3, [4, 0, 1, 2, 3, 4], True)\n```\n\n## Project details\n### Verified details\n*These details have been [verified by PyPI](https:\/\/docs.pypi.org\/project_metadata\/#verified-details)*\n\n###### Maintainers\n[![Avatar for nelsonuhan from gravatar.com](https:\/\/pypi-camo.freetls.fastly.net\/b6e0399a3c5310419441272f5bb761650051f957\/68747470733a2f2f7365637572652e67726176617461722e636f6d2f6176617461722f65613462323932373465633931396664646662326632303232613038373363323f73697a653d3530) nelsonuhan](https:\/\/pypi.org\/user\/nelsonuhan\/)\n\n### Unverified details\n*These details have **not** been verified by PyPI*\n\n###### Project links\n- [Homepage](https:\/\/github.com\/nelsonuhan\/bellmanford)\n\n###### Meta\n- **License:** BSD\n- **Author:** [Nelson Uhan](mailto:nelson@uhan.me)\n\n## Release history  [Release notifications](https:\/\/pypi.org\/help\/#project-release-notifications) \\| [RSS feed](https:\/\/pypi.org\/rss\/project\/bellmanford\/releases.xml)\nThis version\n\n![](https:\/\/pypi.org\/static\/images\/blue-cube.572a5bfb.svg)\n\n[0\\.2.1 May 7, 2018](https:\/\/pypi.org\/project\/bellmanford\/0.2.1\/)\n\n![](https:\/\/pypi.org\/static\/images\/white-cube.2351a86c.svg)\n\n[0\\.1.2 Aug 3, 2017](https:\/\/pypi.org\/project\/bellmanford\/0.1.2\/)\n\n![](https:\/\/pypi.org\/static\/images\/white-cube.2351a86c.svg)\n\n[0\\.1.1 Jan 26, 2017](https:\/\/pypi.org\/project\/bellmanford\/0.1.1\/)\n\n![](https:\/\/pypi.org\/static\/images\/white-cube.2351a86c.svg)\n\n[0\\.1 Jan 12, 2017](https:\/\/pypi.org\/project\/bellmanford\/0.1\/)\n\n## Download files\nDownload the file for your platform. If you're not sure which to choose, learn more about [installing packages](https:\/\/packaging.python.org\/tutorials\/installing-packages\/ \"External link\").\n\n### Source Distribution\n[bellmanford-0.2.1.tar.gz](https:\/\/files.pythonhosted.org\/packages\/ea\/2b\/2c483bdd3c07af70e5ae1a85183f40c980e25b98ac16eb122202cc9a8b18\/bellmanford-0.2.1.tar.gz) (5.2 kB [view details](https:\/\/pypi.org\/project\/bellmanford\/#bellmanford-0.2.1.tar.gz))\n\nUploaded May 7, 2018 `Source`\n\n## File details\nDetails for the file `bellmanford-0.2.1.tar.gz`.\n\n### File metadata\n- Download URL: [bellmanford-0.2.1.tar.gz](https:\/\/files.pythonhosted.org\/packages\/ea\/2b\/2c483bdd3c07af70e5ae1a85183f40c980e25b98ac16eb122202cc9a8b18\/bellmanford-0.2.1.tar.gz)\n- Upload date:\n  May 7, 2018\n- Size: 5.2 kB\n- Tags: Source\n- Uploaded using Trusted Publishing? No\n### File hashes\n| Algorithm | Hash digest |   |\n|---|---|---|\n| SHA256 | `29e4975df1b1c8353d6e495f214e23a470e8eb7021c7a3c0db7c24c78599d39e` | Copy |\n| MD5 | `1ec12aee1d21f0260699dc4a3f60b58b` | Copy |\n| BLAKE2b-256 | `ea2b2c483bdd3c07af70e5ae1a85183f40c980e25b98ac16eb122202cc9a8b18` | Copy |\n\n[See more details on using hashes here.](https:\/\/pip.pypa.io\/en\/stable\/topics\/secure-installs\/#hash-checking-mode \"External link\")\n\n![](https:\/\/pypi.org\/static\/images\/white-cube.2351a86c.svg)\n\n## Help\n- [Installing packages](https:\/\/packaging.python.org\/tutorials\/installing-packages\/ \"External link\")\n- [Uploading packages](https:\/\/packaging.python.org\/tutorials\/packaging-projects\/ \"External link\")\n- [User guide](https:\/\/packaging.python.org\/ \"External link\")\n- [Project name retention](https:\/\/www.python.org\/dev\/peps\/pep-0541\/ \"External link\")\n- [FAQs](https:\/\/pypi.org\/help\/)\n\n## About PyPI\n- [PyPI Blog](https:\/\/blog.pypi.org\/ 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[![](https:\/\/pypi-camo.freetls.fastly.net\/67af7117035e2345bacb5a82e9aa8b5b3e70701d\/68747470733a2f2f73746f726167652e676f6f676c65617069732e636f6d2f707970692d6173736574732f73706f6e736f726c6f676f732f73656e7472792d77686974652d6c6f676f2d4a2d6b64742d706e2e706e67) Sentry Error logging](https:\/\/sentry.io\/for\/python\/?utm_source=pypi&utm_medium=paid-community&utm_campaign=python-na-evergreen&utm_content=static-ad-pypi-sponsor-learnmore)   [![](https:\/\/pypi-camo.freetls.fastly.net\/b611884ff90435a0575dbab7d9b0d3e60f136466\/68747470733a2f2f73746f726167652e676f6f676c65617069732e636f6d2f707970692d6173736574732f73706f6e736f726c6f676f732f737461747573706167652d77686974652d6c6f676f2d5467476c6a4a2d502e706e67) StatusPage Status page](https:\/\/statuspage.io\/)","attrs_readable_markdown":"This package provides a few small extensions of the Bellman-Ford routines in [NetworkX](https:\/\/networkx.github.io\/), primarily for convenience.\n\n## Installation\nbellmanford is available on PyPI:\n```\npip install bellmanford\n```\n\n## Usage\n### bellman\\_ford\n```\nlength, nodes, negative_cycle = bellman_ford(G, source, target, weight='weight')\n```\nCompute shortest path and shortest path lengths between a source node and target node in weighted graphs using the Bellman-Ford algorithm.\n\n#### Parameters\n- G : NetworkX graph\n- pred : dict - Keyed by node to predecessor in the path\n- dist : dict - Keyed by node to the distance from the source\n- source: node label - Source node\n- target: node label - Target node\n- weight : string - Edge data key corresponding to the edge weight\n\n#### Returns\n- length : numeric - Length of a negative cycle if one exists. Otherwise, length of a shortest path. Length is inf if source and target are not connected.\n- nodes : list - Nodes in a negative edge cycle (in order) if one exists. Otherwise nodes in a shortest path. List is empty if source and target are not connected.\n- negative\\_cycle : bool - True if a negative edge cycle exists, otherwise False.\n\n#### Examples\n```\n>>> import networkx as nx\n>>> G = nx.path_graph(5, create_using = nx.DiGraph())\n>>> bf.bellman_ford(G, source=0, target=4)\n(3, [1, 2, 3, 4], False)\n```\n\n### negative\\_edge\\_cycle\n```\nlength, nodes, negative_cycle = negative_edge_cycle(G, weight='weight')\n```\nIf there is a negative edge cycle anywhere in G, returns True. Also returns the total weight of the cycle and the nodes in the cycle.\n\n#### Parameters\n- G : NetworkX graph\n- weight : string, optional (default = 'weight') - Edge data key corresponding to the edge weight\n\n#### Returns\n- length : numeric - Length of a negative edge cycle if one exists, otherwise None.\n- nodes : list - Nodes in a negative edge cycle (in order) if one exists, otherwise None.\n- negative\\_cycle : bool - True if a negative edge cycle exists, otherwise False.\n\n#### Examples\n```\n>>> import networkx as nx\n>>> import bellmanford as bf\n>>> G = nx.cycle_graph(5, create_using = nx.DiGraph())\n>>> print(bf.negative_edge_cycle(G))\n(None, [], False)\n>>> G[1][2]['weight'] = -7\n>>> print(bf.negative_edge_cycle(G))\n(-3, [4, 0, 1, 2, 3, 4], True)\n```","meta_canonical":null}

3. Robots.txt Check

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4. Spam/Ban Check

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5. Seen Status Check

ℹ️ Skipped - page is already crawled

📄

INDEXABLE

✅

CRAWLED

29 days ago

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ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	1 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Page Details

Property	Value
URL	https://pypi.org/project/bellmanford/
Last Crawled	2026-03-11 01:37:02 (29 days ago)
First Indexed	2017-05-27 07:11:10 (8 years ago)
HTTP Status Code	200
Meta Title	bellmanford · PyPI
Meta Description	Small extensions of the Bellman-Ford routines in NetworkX, primarily for convenience (https://networkx.github.io).
Meta Canonical	null
Boilerpipe Text	This package provides a few small extensions of the Bellman-Ford routines in NetworkX , primarily for convenience. Installation bellmanford is available on PyPI: pip install bellmanford Usage bellman_ford length , nodes , negative_cycle = bellman_ford ( G , source , target , weight = 'weight' ) Compute shortest path and shortest path lengths between a source node and target node in weighted graphs using the Bellman-Ford algorithm. Parameters G : NetworkX graph pred : dict - Keyed by node to predecessor in the path dist : dict - Keyed by node to the distance from the source source : node label - Source node target : node label - Target node weight : string - Edge data key corresponding to the edge weight Returns length : numeric - Length of a negative cycle if one exists. Otherwise, length of a shortest path. Length is inf if source and target are not connected. nodes : list - Nodes in a negative edge cycle (in order) if one exists. Otherwise nodes in a shortest path. List is empty if source and target are not connected. negative_cycle : bool - True if a negative edge cycle exists, otherwise False . Examples >>> import networkx as nx >>> G = nx . path_graph ( 5 , create_using = nx . DiGraph ()) >>> bf . bellman_ford ( G , source = 0 , target = 4 ) ( 3 , [ 1 , 2 , 3 , 4 ], False ) negative_edge_cycle length , nodes , negative_cycle = negative_edge_cycle ( G , weight = 'weight' ) If there is a negative edge cycle anywhere in G , returns True . Also returns the total weight of the cycle and the nodes in the cycle. Parameters G : NetworkX graph weight : string, optional (default = 'weight' ) - Edge data key corresponding to the edge weight Returns length : numeric - Length of a negative edge cycle if one exists, otherwise None . nodes : list - Nodes in a negative edge cycle (in order) if one exists, otherwise None . negative_cycle : bool - True if a negative edge cycle exists, otherwise False . Examples >>> import networkx as nx >>> import bellmanford as bf >>> G = nx . cycle_graph ( 5 , create_using = nx . DiGraph ()) >>> print ( bf . negative_edge_cycle ( G )) ( None , [], False ) >>> G [ 1 ][ 2 ][ 'weight' ] = - 7 >>> print ( bf . negative_edge_cycle ( G )) ( - 3 , [ 4 , 0 , 1 , 2 , 3 , 4 ], True )
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Join the official Python Developers Survey 2026 and have a chance to win a prize [Take the 2026 survey\!](https://surveys.jetbrains.com/s3/python-developers-survey-2026) [![PyPI](https://pypi.org/static/images/logo-small.8998e9d1.svg)](https://pypi.org/) - [Help](https://pypi.org/help/) - [Docs](https://docs.pypi.org/) - [Sponsors](https://pypi.org/sponsors/) - [Log in](https://pypi.org/account/login/?next=https%3A%2F%2Fpypi.org%2Fproject%2Fbellmanford%2F) - [Register](https://pypi.org/account/register/) Menu - [Help](https://pypi.org/help/) - [Docs](https://docs.pypi.org/) - [Sponsors](https://pypi.org/sponsors/) - [Log in](https://pypi.org/account/login/?next=https%3A%2F%2Fpypi.org%2Fproject%2Fbellmanford%2F) - [Register](https://pypi.org/account/register/) # bellmanford 0.2.1 pip install bellmanford Copy PIP instructions [Latest version](https://pypi.org/project/bellmanford/) Released: May 7, 2018 Small extensions of the Bellman-Ford routines in NetworkX, primarily for convenience (https://networkx.github.io). ### Navigation - [Project description](https://pypi.org/project/bellmanford/#description) - [Release history](https://pypi.org/project/bellmanford/#history) - [Download files](https://pypi.org/project/bellmanford/#files) ### Verified details These details have been [verified by PyPI](https://docs.pypi.org/project_metadata/#verified-details) ###### Maintainers [![Avatar for nelsonuhan from gravatar.com](https://pypi-camo.freetls.fastly.net/b6e0399a3c5310419441272f5bb761650051f957/68747470733a2f2f7365637572652e67726176617461722e636f6d2f6176617461722f65613462323932373465633931396664646662326632303232613038373363323f73697a653d3530) nelsonuhan](https://pypi.org/user/nelsonuhan/) ### Unverified details These details have not* been verified by PyPI* ###### Project links - [Homepage](https://github.com/nelsonuhan/bellmanford) ###### Meta - License: BSD - Author: [Nelson Uhan](mailto:nelson@uhan.me) [Report project as malware](https://pypi.org/project/bellmanford/submit-malware-report/) - [Project description](https://pypi.org/project/bellmanford/#description) - [Project details](https://pypi.org/project/bellmanford/#data) - [Release history](https://pypi.org/project/bellmanford/#history) - [Download files](https://pypi.org/project/bellmanford/#files) ## Project description This package provides a few small extensions of the Bellman-Ford routines in [NetworkX](https://networkx.github.io/), primarily for convenience. ## Installation bellmanford is available on PyPI: ``` pip install bellmanford ``` ## Usage ### bellman\_ford ``` length, nodes, negative_cycle = bellman_ford(G, source, target, weight='weight') ``` Compute shortest path and shortest path lengths between a source node and target node in weighted graphs using the Bellman-Ford algorithm. #### Parameters - G : NetworkX graph - pred : dict - Keyed by node to predecessor in the path - dist : dict - Keyed by node to the distance from the source - source: node label - Source node - target: node label - Target node - weight : string - Edge data key corresponding to the edge weight #### Returns - length : numeric - Length of a negative cycle if one exists. Otherwise, length of a shortest path. Length is inf if source and target are not connected. - nodes : list - Nodes in a negative edge cycle (in order) if one exists. Otherwise nodes in a shortest path. List is empty if source and target are not connected. - negative\_cycle : bool - True if a negative edge cycle exists, otherwise False. #### Examples ``` >>> import networkx as nx >>> G = nx.path_graph(5, create_using = nx.DiGraph()) >>> bf.bellman_ford(G, source=0, target=4) (3, [1, 2, 3, 4], False) ``` ### negative\_edge\_cycle ``` length, nodes, negative_cycle = negative_edge_cycle(G, weight='weight') ``` If there is a negative edge cycle anywhere in G, returns True. Also returns the total weight of the cycle and the nodes in the cycle. #### Parameters - G : NetworkX graph - weight : string, optional (default = 'weight') - Edge data key corresponding to the edge weight #### Returns - length : numeric - Length of a negative edge cycle if one exists, otherwise None. - nodes : list - Nodes in a negative edge cycle (in order) if one exists, otherwise None. - negative\_cycle : bool - True if a negative edge cycle exists, otherwise False. #### Examples ``` >>> import networkx as nx >>> import bellmanford as bf >>> G = nx.cycle_graph(5, create_using = nx.DiGraph()) >>> print(bf.negative_edge_cycle(G)) (None, [], False) >>> G[1][2]['weight'] = -7 >>> print(bf.negative_edge_cycle(G)) (-3, [4, 0, 1, 2, 3, 4], True) ``` ## Project details ### Verified details These details have been [verified by PyPI](https://docs.pypi.org/project_metadata/#verified-details) ###### Maintainers [![Avatar for nelsonuhan from gravatar.com](https://pypi-camo.freetls.fastly.net/b6e0399a3c5310419441272f5bb761650051f957/68747470733a2f2f7365637572652e67726176617461722e636f6d2f6176617461722f65613462323932373465633931396664646662326632303232613038373363323f73697a653d3530) nelsonuhan](https://pypi.org/user/nelsonuhan/) ### Unverified details These details have not* been verified by PyPI* ###### Project links - [Homepage](https://github.com/nelsonuhan/bellmanford) ###### Meta - License: BSD - Author: [Nelson Uhan](mailto:nelson@uhan.me) ## Release history [Release notifications](https://pypi.org/help/#project-release-notifications) \\| [RSS feed](https://pypi.org/rss/project/bellmanford/releases.xml) This version ![](https://pypi.org/static/images/blue-cube.572a5bfb.svg) [0\.2.1 May 7, 2018](https://pypi.org/project/bellmanford/0.2.1/) ![](https://pypi.org/static/images/white-cube.2351a86c.svg) [0\.1.2 Aug 3, 2017](https://pypi.org/project/bellmanford/0.1.2/) ![](https://pypi.org/static/images/white-cube.2351a86c.svg) [0\.1.1 Jan 26, 2017](https://pypi.org/project/bellmanford/0.1.1/) ![](https://pypi.org/static/images/white-cube.2351a86c.svg) [0\.1 Jan 12, 2017](https://pypi.org/project/bellmanford/0.1/) ## Download files Download the file for your platform. 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Readable Markdown	This package provides a few small extensions of the Bellman-Ford routines in [NetworkX](https://networkx.github.io/), primarily for convenience. ## Installation bellmanford is available on PyPI: ``` pip install bellmanford ``` ## Usage ### bellman\_ford ``` length, nodes, negative_cycle = bellman_ford(G, source, target, weight='weight') ``` Compute shortest path and shortest path lengths between a source node and target node in weighted graphs using the Bellman-Ford algorithm. #### Parameters - G : NetworkX graph - pred : dict - Keyed by node to predecessor in the path - dist : dict - Keyed by node to the distance from the source - source: node label - Source node - target: node label - Target node - weight : string - Edge data key corresponding to the edge weight #### Returns - length : numeric - Length of a negative cycle if one exists. Otherwise, length of a shortest path. Length is inf if source and target are not connected. - nodes : list - Nodes in a negative edge cycle (in order) if one exists. Otherwise nodes in a shortest path. List is empty if source and target are not connected. - negative\_cycle : bool - True if a negative edge cycle exists, otherwise False. #### Examples ``` >>> import networkx as nx >>> G = nx.path_graph(5, create_using = nx.DiGraph()) >>> bf.bellman_ford(G, source=0, target=4) (3, [1, 2, 3, 4], False) ``` ### negative\_edge\_cycle ``` length, nodes, negative_cycle = negative_edge_cycle(G, weight='weight') ``` If there is a negative edge cycle anywhere in G, returns True. Also returns the total weight of the cycle and the nodes in the cycle. #### Parameters - G : NetworkX graph - weight : string, optional (default = 'weight') - Edge data key corresponding to the edge weight #### Returns - length : numeric - Length of a negative edge cycle if one exists, otherwise None. - nodes : list - Nodes in a negative edge cycle (in order) if one exists, otherwise None. - negative\_cycle : bool - True if a negative edge cycle exists, otherwise False. #### Examples ``` >>> import networkx as nx >>> import bellmanford as bf >>> G = nx.cycle_graph(5, create_using = nx.DiGraph()) >>> print(bf.negative_edge_cycle(G)) (None, [], False) >>> G[1][2]['weight'] = -7 >>> print(bf.negative_edge_cycle(G)) (-3, [4, 0, 1, 2, 3, 4], True) ```
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