Result for B9639D12CFAF3D59C96381348446E96A91C0EE82

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Children (1765)

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Key Value
FileSize1620574
MD56ED5B7AFA8815D7C7DFE4586C06CBA71
PackageDescriptionPYthon Optimization Modeling Objects Pyomo is a tool for formulating and analyzing mathematical models that represent real-world systems for complex optimization applications as applied in different areas of business, engineering, research, and administration. It's used to define symbolic problems, create concrete problem instances, and solve this instances with standard solvers. Pyomo provides a capability that is commonly associated with algebraic modeling languages (AML) and applications like AMPL, AIMMS, or GAMS, but has its modeling objects within the Python environment. Pyomo features a versatile set of modeling components, and supports concrete models (defined with data) as well as abstract models (defined without data). . For the processing of instantiated models Pyomo supports a wide range of independent solvers that could be written either in Python or other languages. Pyomo supports the general ASL (AMPL Solver Library) compatible interface, and has invidividual backends for solvers which some of them are available within Debian (GLPK, COIN-OR CPC, OPENOPT). Pyomo's solver manager could also employ the public NEOS Server to remotely optimize models if network access is available. . Pyomo was formerly released as the Coopr software library, and includes the PySP package (Pyomo Stochastic Programming) which provides generic solvers for stochastic programming.
PackageMaintainerDaniel Stender <stender@debian.org>
PackageNamepyomo
PackageSectionmath
PackageVersion4.3.11388+git20160622.d3e3f0a-1
SHA-1B9639D12CFAF3D59C96381348446E96A91C0EE82
SHA-256598CEE09DCA99DBB2E0E214C28EB863D319A7725035D380146119D461DB60FD1
hashlookup:children-total1765
hashlookup:trust50

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Children (Total: 1765)

The searched file hash includes 1765 children files known and seen by metalookup. A sample is included below:

Key Value
FileName./usr/share/doc/pyomo/examples/doc/pyomobook/ref-data/rangeset.py
FileSize307
MD589124901D2FC958A751C59580079DEC0
SHA-10003C43D95A2236DFCF71CDB26BED658A07E802E
SHA-2568379A582DFC92AE1845A588FC268F5A73F02C46330C6EAF884C3EA02C6468245
SSDEEP6:1VMVLTW/lQnoPUnuvXMpkdkFR7f2/mZKXikGmhL1yXGq7cU8RaWbgY/9Rm6MLXGn:1V2y/1vMpkdkvT2/mwXHGI1817cVXXMO
TLSHT158E0121EB773494E275DE30CE7547B0F03AA0272CD1C4016053F3D73AC510599B59119
Key Value
FileName./usr/share/pyomo/pysp2smps
FileSize294
MD5CF622B803B4502B0F7B8F85AF15CADF8
SHA-1004C4CF82B6786DCC47F417A0D9AA7BE1F2F5248
SHA-256694BA9E0F0FCE491DD0DF3602CC9B715BC1B4334D8C3C9601CEA1F0DB461540F
SSDEEP6:HWaHwelgxtKX+i7BiC0XFvVAoLGtrVV1CFAjaj+kSbrVVbzUwT:HsKuCQZAoi9VrCF2aLSfVVzUE
TLSHT1D1E02B725851CEA356B046C739B1205A2182DF4FEB20B186F2C822477FC23D40C70E34
Key Value
FileName./usr/lib/python3/dist-packages/pyomo/pysp/plugins/sorgw.py
FileSize9484
MD5B8400E9CB9FC784FB6EA25BB02FAD472
SHA-10077AD1254E75E1A1C7A25F97E2726D2D4CDD6F9
SHA-2564703FAC2345ED15B4A8F655203CED26013164E59CDAD3989485D8CE6904205EA
SSDEEP192:Eeb6HzZ9QpOW/WjRZ0mPh+obvQFrPaiSuqndyqCd9:EeuTTxqWVZ0mp1bvQFrPzDqoqI
TLSHT15612C8315C4A66157753BE79241BC01F2F963E63C14D10283DFC8258BF80B369BA2DE9
Key Value
FileName./usr/share/doc/pyomo/examples/pysp/networkflow/config/aggregategetter.py
FileSize1542
MD5118D8033FBD81A27AF23273C99EC9470
SHA-1008D071605B0B561190C215E6A3E35C31AE6FAC6
SHA-2565649125FB10FF0F4DCC8A909717DB054594ABB53A5185ADCB6067CC55CBE3F9E
SSDEEP48:JAbQDBYNchnc7G+S37hnjjHGAOxuXGucbDv:JLNYNchnctSdj1rYz
TLSHT13F3198093290E26509FB79FA164B82DC731AF4A3DB73209536ECC7463782D3182A754D
Key Value
FileName./usr/share/doc/pyomo/examples/pyomo/p-median/ampl1.in
FileSize59
MD5C7CE3D8A4311BBF4E884E40331AA67C3
SHA-100A77B58780F9B5C34247049D79AAABDB84F0E8F
SHA-2565068F8EFE3E5A97A6CDD551B72F9FCD5A08B0289BF39D305FF18CA8547D86258
SSDEEP3:3BkTB0ERWRSB4wFRikMEUn:xkTSERIy4cRikMEU
TLSHT10EA00208755E56014D67F718D04491102619AC534A8047028C8C21800700A15140FE24
Key Value
FileName./usr/share/doc/pyomo/examples/doc/samples/pyomo_book/nonlinear_ReactorDesign.py
FileSize1121
MD50A1040560164B67A2DEE5BC48237A56B
SHA-100D345939E70E3BFA6DF074CCA69F1883E2F0D31
SHA-25620558231189198238465E78E8368EE4239FB1697C2DE846AE910C5B4E4FB7F67
SSDEEP24:1LpB3nhz1FzuoegGFYsFnRcN4CV+V1dEopWbYrnb/o:TVrFCoegGFYsFnaN4CVGvEgc
TLSHT1DC21266536702C35E42CF4AA37EA3DD1169DE0490E881084B5FED9F99B12CEEC8041B7
Key Value
FileName./usr/share/doc/pyomo/examples/doc/pyomobook/overview/attic/script1.txt
FileSize2969
MD599EB55BAEF2A6424A10705CC1FFA7CC9
SHA-101155E49837292B137F1B56FA0454AB6DE39098D
SHA-256C47E01FBE3C9A226C6B914C327BCA28466B4D1190D3F9D8118E581CA1BB6F88B
SSDEEP48:dehEBshEBVcBFqin13Sn13PNehEBshEBVcBFqin13Sn13Ew+6iPJJ2GQoOC+:chjhuEBMVMhjhuEBMoj0GQhC+
TLSHT18F514B42DE40A6662532C61530A3D141C8278E97FE8605B4BB4F4251FB17B7397CEACF
Key Value
FileName./usr/share/doc/pyomo/examples/pyomo/draft/diet2.dat
FileSize871
MD51FC73C69769D9D08B46482D108A623DE
SHA-10131977CA6B144BBF01CC042725B96ED4FBB40AA
SHA-256D242112749E405CC81E8760ED793B51F2A2CB951CA588B34B305AEFF30FF38DC
SSDEEP12:FBs790FFFun8nJFFF29hVXSe6ahpglF/wiDfOvN3XcFFFhlT9Z9ViIMAcQTi:F658FF08JkbH6aha/w4AN3MJnidAni
TLSHT1071196629C063540B97DC1629776484A480CFB16B4576C5AF20E0EE10FCE868FBCF457
Key Value
FileName./usr/share/doc/pyomo/examples/doc/pyomobook/ref-data-abstract/ABCD5.py
FileSize463
MD52B7F504FEB1F60D05176EE1F92ABBBA2
SHA-1016DE4D8953D74090C41F193BCC4527F150F2A02
SHA-25618F699BCC86263D2C124319BF3855AC2AAF8960E042F88879924B65E5AE8A941
SSDEEP12:1V2y/1vle98bVqkXrYv5XMifB8KuwAq2uwXcuJCxuy2uWXcufbCxuM:1LtXTC5XxfqKui2uwXcuJKuy2uWXcufQ
TLSHT10BF05567B7730A082CBE099BBF09B6579A4B403CF7B83A404BAC2401CD4790F44A785E
Key Value
FileName./usr/share/doc/pyomo/examples/pyomo/amplbook2/iocol1.mod
FileSize392
MD55AE824A35FE3683226543E27A6789F12
SHA-101801826FC1A2B76DDBD3EBCDD27324E4968C0DC
SHA-2562A86B9F34D474A9AF6C3DA103E57DCC35CE64D021D4F8C2D10E056DD074BB461
SSDEEP6:dobESo5oXGRM1DmnkxJk7us7l32eFLtmNvg5dk8CxLwktDig7hxPoIf6CxLwh656:EEJSGyi4q7usB32nvgDze2EFV6DQbBuF
TLSHT137E0688011558581833D91947A381032BA971262F85D3ED77A6CAD150B5B399F3B060F





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