whitecanvas/__init__.py,sha256=GUXfJvToQLix-a12XzvYlxc-hR8vViHjnUg9ORsIb6s,1229
whitecanvas/_axis.py,sha256=D8rzl2p0WExf0lBqjbZ9SK5dJnWLHOktigFT_orxafU,1800
whitecanvas/_exceptions.py,sha256=x0O52Rc1LJn5nTcYRMzSEzYybwmz7fqx4TkhTimDgJ0,100
whitecanvas/_signal.py,sha256=rltTyrqkknCwiO7eRYWndM6-cq3OFw5Slsy8nRGZr_Q,3777
whitecanvas/animation.py,sha256=AWa4Kgkerlr8KMoeUOuAAHMBfxhclkfVuwUv5pilP7Q,2650
whitecanvas/core.py,sha256=WmEQKaGYchSaGOILverNBqANSukoHCmRRn_6iCPyt4s,6741
whitecanvas/backend/__init__.py,sha256=DmyM-uU4pjtA2hII9JXscuaPDa4E3hlbrWM4yj2tHU4,120
whitecanvas/backend/_app.py,sha256=WzXkMb0_bX8b14oqxiMyvamkyWhzKnavnCmwnb5ilCA,3937
whitecanvas/backend/_instance.py,sha256=bwicDJMKymFA_134XhT3VbxXm3JnYfQbXo3EVqw3x8A,2778
whitecanvas/backend/_not_implemented.py,sha256=tt9VSXTmzGIe4hVxhqQ1oaD-umbz0U815s2ikrihag0,1374
whitecanvas/backend/_window/__init__.py,sha256=IyeYM9bEHYLL5XXeFzo9hRAkXII_6GvXvESknoQQSKc,1164
whitecanvas/backend/_window/_qt.py,sha256=_9WIBpTxmc5D_fOEard0YHiQjtid6Sr8EG_7bRgVXzo,4188
whitecanvas/backend/_window/_tk.py,sha256=PPx9XU3MYJF255v7QHR6nRD-eg4ULaPyrCVIDdB4L-o,4063
whitecanvas/backend/bokeh/__init__.py,sha256=OPN7VT4E_vlKunwZtuiind55mGOtM6M0tt4rd2BrMXQ,436
whitecanvas/backend/bokeh/_base.py,sha256=c0Lgc_ErpSW6CPUN-9KVQd9_t5JDqEM7iA6jFOC7GJU,5562
whitecanvas/backend/bokeh/_labels.py,sha256=GRCN0UGFonE5h0XktlR-FCtHQUS7OSgkAiX4RZUzx8I,8491
whitecanvas/backend/bokeh/_legend.py,sha256=wsHBMUDjBRClh3mwe0gAfaVzhh3Y-St7vxTP58jXw4I,3564
whitecanvas/backend/bokeh/band.py,sha256=9dlDTP1gJMivmyZeDkhWiyCsQR8ci-xqjxkaGdUHl4U,3064
whitecanvas/backend/bokeh/bars.py,sha256=W8wP-Ololoz08-bnWh4_neAriylalYiUvti9_V7HsWE,1737
whitecanvas/backend/bokeh/canvas.py,sha256=wQ-urFTLpDNFGVflM78Q3OIa7mPMNMOjIOafPow5F6E,13076
whitecanvas/backend/bokeh/image.py,sha256=02BxJvgKZzUrYVtUxtrHaFFs8BHR1NLih-l7f5VQzrA,2248
whitecanvas/backend/bokeh/line.py,sha256=S2ircjki6xphE362_pWP-nCZE0gzVI_KjEPWr9gNYDQ,6849
whitecanvas/backend/bokeh/markers.py,sha256=UWkkLzjkuzYitDhLCTMVPzdEIEw8kcRpzLyzx39pmFE,2383
whitecanvas/backend/bokeh/text.py,sha256=5Ela_W4iiBgRvzM7AHIOon-5hZOQ3B5PqGpy5MYV3tc,6765
whitecanvas/backend/matplotlib/__init__.py,sha256=671Rcs5bZ2MS9_bvSOjznkM3a29V8Aay5DHS8-eQOBg,479
whitecanvas/backend/matplotlib/_base.py,sha256=YyTWm4FFMVLuBJVe4V7lwG_ZbaX1OHNp9bXH_3ThKFs,1995
whitecanvas/backend/matplotlib/_labels.py,sha256=lZHwrFs0hCWsBK9K18AquhLA5X7Gyy_s7Cj0NrDx_44,10566
whitecanvas/backend/matplotlib/_legend.py,sha256=4P4mGGpehonBT9ONZRHARHLk48xFmyux56ivTFqev2w,5101
whitecanvas/backend/matplotlib/band.py,sha256=KzDGWXMhSylkWig2KdYrI73aYZ-aq8-jaoDOSplUY3Y,3556
whitecanvas/backend/matplotlib/bars.py,sha256=3PUT_zH_tXeODPfejFyJTtVeZMdfFMbCcz-w6CDK0UM,4631
whitecanvas/backend/matplotlib/canvas.py,sha256=NIjeKGoZEjth30lPbtyFiRDYoVKRNk8IqBQFVlPxD20,14848
whitecanvas/backend/matplotlib/image.py,sha256=oHdhJdioMfVmbOngMXjgYxAqe7nwoIx-jHRgzX4oKek,3088
whitecanvas/backend/matplotlib/line.py,sha256=RK3gWUUIY5Sjpd8M9n7b32vj4lLkYoNlu5Ut_liTRjQ,3710
whitecanvas/backend/matplotlib/markers.py,sha256=WkCQXwnZZf8C0GBK4bHkqBieQK3PWEOByuFgr_rZHvU,4259
whitecanvas/backend/matplotlib/text.py,sha256=tB6_JhoqwV-Vf9m-OSXUpWgfhUe5I30YI7rVCinoNR0,9817
whitecanvas/backend/mock/__init__.py,sha256=M5mIfr0lu1PWKkRKQnU1OJPscc1QXv9hBS3fyd8ZKKg,205
whitecanvas/backend/mock/_base.py,sha256=JWP831WaXweTMlBDnz2zboCvRJY5-DExS_LubrWxTBU,4886
whitecanvas/backend/mock/canvas.py,sha256=-1TcyMIPE30OORprqKJup_eRD8jBpVZfTPiTxucb9_o,6102
whitecanvas/backend/mock/layers.py,sha256=hkRmcXWi8PQQQzGyIn9oJMHIaVRKZeE1dfXLgTQ5_SI,6834
whitecanvas/backend/plotly/__init__.py,sha256=1TVXk2YlUyyLdV_aLIr_U8O3qypUewssaLqIRdowgyw,444
whitecanvas/backend/plotly/_base.py,sha256=sJHvBwLWR9hAhefOWuQ8SIAOkhIoyVrzVeQnyVyIja4,4039
whitecanvas/backend/plotly/_labels.py,sha256=G4vNz-6RMOIZnt4s04pjbDkbR4szTdn-pLblljOfrjo,5375
whitecanvas/backend/plotly/_legend.py,sha256=naNJHvGjB3M3gZwbUDhMYeyWlCWqznTxpOMlqBHZQcE,6677
whitecanvas/backend/plotly/band.py,sha256=vildYB_mo3epKLKPxEr9713HtCbGOxxetgzUBJZ1VHM,4062
whitecanvas/backend/plotly/bars.py,sha256=29BiE9DNSBNXCPd37fhZmMW6yeLy91jX6rOkLU4Oz00,3952
whitecanvas/backend/plotly/canvas.py,sha256=8PxQAc5E2hzfK16BSrMxduge9TwAuiIdI0J88DuBv-0,12967
whitecanvas/backend/plotly/image.py,sha256=XJaXanT6_DahSUuA94XeV4U2yElsTmAYDD07eoCn608,1908
whitecanvas/backend/plotly/line.py,sha256=-YHyzRs2DZ760RB3TcXCGymy_rk5hszaYA2DkEJnCQk,7720
whitecanvas/backend/plotly/markers.py,sha256=9cRErK70s-N9AFJrapUcEeAiWkoZ6fH1dVt08kn2wOQ,3638
whitecanvas/backend/plotly/text.py,sha256=-V8aAuYTTQRYDvqltB7MCG8QfT_LgB7-4pg1AmzU9Nc,5019
whitecanvas/backend/pyqtgraph/__init__.py,sha256=Nfzhxl-RLILlUPRW2BvgZAxBoRGKchNa3O1IZFqstNk,411
whitecanvas/backend/pyqtgraph/_base.py,sha256=1FD8keh14dTYKMVZIsC9Xj200CPaWQbZqPsNi-FBu7Q,295
whitecanvas/backend/pyqtgraph/_labels.py,sha256=jcsMms10CkF7pRChVrBvDq4zpT9bdznW9Oje54QqjEs,8268
whitecanvas/backend/pyqtgraph/_legend.py,sha256=jvhtlO_-soY1tyKS1OTrP7oOuV80NE_k6YKtcW2yxRw,7130
whitecanvas/backend/pyqtgraph/_qt_utils.py,sha256=WBtSVVx7Sv2kruNuib8Ccpxb5j_Tu9PKs0Cr07eWg7I,5124
whitecanvas/backend/pyqtgraph/band.py,sha256=YI9bIOFnaqoEQx1LEYIpto7AvJSBhooI_OrmxKVCl_c,5266
whitecanvas/backend/pyqtgraph/bars.py,sha256=hEBMFKQvLDJ3s-tFxJDK4ygshjEBZNamSZnqU2yXVKI,5641
whitecanvas/backend/pyqtgraph/canvas.py,sha256=kMIOUztC31h6fRyd0DZQsL7lRSoatnXIMJtpCRj2Dpg,14000
whitecanvas/backend/pyqtgraph/image.py,sha256=IwGk19lKXBOxyCmfPDSogFZlDziduL4woygcbApDgUM,2583
whitecanvas/backend/pyqtgraph/line.py,sha256=uj4DYPgpdz3b6KnvE7Eg9V4PRGCtu_5xZekisMeyRS4,8564
whitecanvas/backend/pyqtgraph/markers.py,sha256=0EfDAsnj0nPcEDW9Et0xP0xt1HxvBwjQpbjro3Ien5w,5867
whitecanvas/backend/pyqtgraph/text.py,sha256=ObE9jsJOZH-USBMW1aPMrYfBIt7G8cYNRUcXpeVHVTM,7725
whitecanvas/backend/vispy/__init__.py,sha256=65hJTDacqCPXNjrgUjaofNsDl9CdLSh19U3YkOKLXFM,395
whitecanvas/backend/vispy/_label.py,sha256=j8LRIwH99OkLvfdvVyDutumitG8tGB72WYKzc75KCXg,6243
whitecanvas/backend/vispy/band.py,sha256=S3Spo73DGAgV_k-OiwFtushJ4klPER1oLwlDTngaMdw,5905
whitecanvas/backend/vispy/bars.py,sha256=WXcRw8l61jFokYv4sp-nvNyX9ueruoq74Ur9gcjJKO0,3668
whitecanvas/backend/vispy/canvas.py,sha256=r_QD1H8U_hPJ1PqZclv_Y_1npmHPG9eJDnU3cXQAxew,11349
whitecanvas/backend/vispy/image.py,sha256=7EoHNsYwntRpDXy-BWA_CzY09BvA8ecQrVpx39bV_H4,2500
whitecanvas/backend/vispy/line.py,sha256=7xUKetqTvGEeduGOaRGpeBybeQq25l_gClE86M8_5H0,5183
whitecanvas/backend/vispy/markers.py,sha256=Zhr6xtL4DwbwS0ZlrHcOeZbODfKXTnDxwOab_pqPCZI,5097
whitecanvas/backend/vispy/text.py,sha256=ORPO3F4GAqgrMI2n2ylvR3gVCy4tjEOSofJSQACun-w,6088
whitecanvas/canvas/__init__.py,sha256=abz9yDds4wKxo_nUKTV1XXpkaX9NqKsJ3_1z6iYmD4k,439
whitecanvas/canvas/_base.py,sha256=ffTw96Kb43UOixagbDcLKcp6JunZOZ8NqD7uMSCO5o8,65407
whitecanvas/canvas/_between.py,sha256=kPF9TY_k9PBdHdSoG_UlMqHV2hgRzZ2P3eRRBwInaXA,4018
whitecanvas/canvas/_dims.py,sha256=d5b2Grzk5Mopn9uTHfkZiZwgW60lfVhJ7ZSsHunUAy4,17101
whitecanvas/canvas/_fit.py,sha256=WnKRm0WUNlbGcJGPjX0sI2i-U7mZ_A4VsFZXgrQQ6EU,4482
whitecanvas/canvas/_grid.py,sha256=RhxKbltMpFbYqXj9ludgK8vyBLvcZbhACpW6jOxkews,14012
whitecanvas/canvas/_imageref.py,sha256=_ugpbsS5mxdOetKr3N-Rs7vZdMo2gwnOw6WP806A6dY,4990
whitecanvas/canvas/_joint.py,sha256=IUHrJUVHpD6lP_m61kWvKK1l0YIwxEAiCzXkPQ79xwI,22092
whitecanvas/canvas/_linker.py,sha256=KEQukNqYZ_3a5qXl5nYAIL1JFaweykinOP8g_TiQ-G8,2959
whitecanvas/canvas/_namespaces.py,sha256=P9mwo1XsggtUhVhVYVglkP3G2f8BrGGMposLoKhg0Fk,10723
whitecanvas/canvas/_palette.py,sha256=mtg7ApNw2Apyx5d4wXZW7FKVIdwX0V5DnhskGnqfTUE,1831
whitecanvas/canvas/_stacked.py,sha256=fQ20UYfN-A6bP5yJwveF822NkU4gEiZo0MHuy9wlBig,5104
whitecanvas/canvas/layerlist.py,sha256=YjFuDxb5kITgukEI5x52Z-fVMjuKAjZ9IpZU-j5CxfA,2432
whitecanvas/canvas/dataframe/__init__.py,sha256=zYIoiK2TlGP50KRyuuxjb2i6nDinC17lO-foF08QX4Y,398
whitecanvas/canvas/dataframe/_base.py,sha256=-o14Xs2p980dc0psoUaXOSSthxKOQzsNWuOE56kq57Y,5332
whitecanvas/canvas/dataframe/_both_cat.py,sha256=M3bSw6DS0ovQ0D5-nYDXU7JD0ADLxHDSXDUK_ueqLhE,6449
whitecanvas/canvas/dataframe/_feature_cat.py,sha256=rzSuJeDpLqDa8XaheiziGg9aHIKJAou311k-TtNt-ks,16691
whitecanvas/canvas/dataframe/_joint_cat.py,sha256=_a3Hlv3NbLvx4Vlq_JsSWCkjlhzlFWEer_fMXG3PJlU,6145
whitecanvas/canvas/dataframe/_one_cat.py,sha256=vTW-19MA7X0MUsiCkM2CGetB4Ej6ipB7fC9Pzuwhta4,29836
whitecanvas/layers/__init__.py,sha256=FDhwHBAGUtOh4xMGWmtYXMQShb2aRjLAmlwdvkwg2Cs,699
whitecanvas/layers/_base.py,sha256=oUQ8T-h411bSmU0vyIzx7pZScWDSlbOOUBTvv6kVKmU,11745
whitecanvas/layers/_legend.py,sha256=7AHYCVs57Jp6vviHCrffSrUJTc6uDV7TiVVBmLT1Vp4,3892
whitecanvas/layers/_mixin.py,sha256=75tlcpJmDc-ineYhgfw2yhik2JyFxZl9-c7lkCN5Ieg,34879
whitecanvas/layers/_ndim.py,sha256=n9Tw9kmg04miAAh9GmjGqRb_yf8qk1iiHXIh8OkADc8,9034
whitecanvas/layers/_sizehint.py,sha256=nz3xcxKJtOKIbohz02Uu-GGhvs60h8JQWvR3iiFAE7M,1366
whitecanvas/layers/_primitive/__init__.py,sha256=YB7S03zGcPWihHTT3vSusIYHlkgToHEyasdq6_3doJ0,774
whitecanvas/layers/_primitive/band.py,sha256=Dt_iAa-VZ4qTHBpUprASbfGwDjxS5cgQMLqjlcgFZ6g,4083
whitecanvas/layers/_primitive/bars.py,sha256=UDcVYY7EExQGbjXDrrUzmyYR1a2lONwc1KwMb78O_00,15039
whitecanvas/layers/_primitive/errorbars.py,sha256=RJPaX_aY8ACX6cW8HGyGDXpQ5x_obJnI4N2231_1Qu8,9540
whitecanvas/layers/_primitive/image.py,sha256=hANjZAhkX_HMqxjWi-lCUF75d912_NNblR-IceKzVeQ,10519
whitecanvas/layers/_primitive/inf_curve.py,sha256=z70FRPRoKHmkz_ECXdZuncZk59V2CGRng5UKkrLF6Eg,7374
whitecanvas/layers/_primitive/line.py,sha256=OPEDvmRhcNSUQ2RJD5P5GP46LfNDemIML5fyqB8BRMc,23472
whitecanvas/layers/_primitive/markers.py,sha256=YOmU_1S2HbWxl0gk2mVk-uSvGEozojUg_F-IpUWHfJc,25853
whitecanvas/layers/_primitive/rug.py,sha256=odfDDzjMrcIDh2v8kgmrkqD4oY21zDTclAs-uoT6u2o,9061
whitecanvas/layers/_primitive/spans.py,sha256=UeZSH4MfqedJjyemDAVIhfvWFuyes_HS6Dapv81gEoU,6713
whitecanvas/layers/_primitive/text.py,sha256=wvcR4A2lV0sl2lNkR3SRyhUBG-UiGBBdyTsMlvcufBg,5686
whitecanvas/layers/group/__init__.py,sha256=FEC7QxyXeMsrxhs61zhdjKuIm42NsCB0bCWkpFHRkgg,1248
whitecanvas/layers/group/_cat_utils.py,sha256=JW6fKluAlOYXsb47zyNfRZcfqOpVM3tCUc3T52O29fU,501
whitecanvas/layers/group/_collections.py,sha256=ZC1XyXvoxAlcfC-Q79KmEk4WAWHmJ-024X5jAURX9Ns,4870
whitecanvas/layers/group/_offsets.py,sha256=my35zLdlufURF3RbKozxxSdDPEySI0QfZv2FJszAXHc,1705
whitecanvas/layers/group/band_collection.py,sha256=aZ-WvQ4pbsjCmmB9y1EW6UQOPy-RZ8ppmF0SNIcTuJc,9721
whitecanvas/layers/group/boxplot.py,sha256=CnaUAPH1PQ5Trr3pW7HrVNaQTYfWf3nzoy9NsAXe3is,11317
whitecanvas/layers/group/colorbar.py,sha256=WULX55usAB_o_Z5NywnPteX90Wkrb46YCRgCI6x_D-s,2187
whitecanvas/layers/group/graph.py,sha256=38LTh-pYXZyNpFErukPGWevIOOexbisgbiPOhFQN9lU,3252
whitecanvas/layers/group/labeled.py,sha256=6TSB4-o381-eL5kzEjC_nIys3ySFn1VQigHZvbn0MkM,19303
whitecanvas/layers/group/line_band.py,sha256=TLe2-Db-Oab5DRQngBZk6qAohBWg_CpYcUyaVD7qIWU,1801
whitecanvas/layers/group/line_collection.py,sha256=HkdZlX849Osro8bTPfQ01_uNzYQogKH0SO4eZGqO99Y,4671
whitecanvas/layers/group/line_fill.py,sha256=jTAqrwikRxolNFWh3e0MR2S_WwTBmel2dAN2djezTdM,13379
whitecanvas/layers/group/line_markers.py,sha256=mE99CtaGbSQNfiyKkoqLZD7iEpptDkkLXjl08HQMRMQ,8752
whitecanvas/layers/group/marker_collection.py,sha256=gm2l9b-UQyAMhtYa1RWnJAjAyn0kSKUj_JZ8P-S0mOE,16130
whitecanvas/layers/group/stemplot.py,sha256=JROh9hoP-BK66i-I6U_E15ay66SIV6M8yg5vIlkhsW0,3331
whitecanvas/layers/group/textinfo.py,sha256=8gCHbql5roxr2vCOUusay7rUfXBM1sgejYrSDkTXonA,5486
whitecanvas/layers/tabular/__init__.py,sha256=1Wz7CbD9fxNJW_LpFfK5kbvD20YVG8QKSd2wQmJ_vPw,746
whitecanvas/layers/tabular/_box_like.py,sha256=8Dev3O1-TiNElPGdRsSalL4OFb6rf1irmluMbHkqj1w,22330
whitecanvas/layers/tabular/_dataframe.py,sha256=M9fP_PexecoaWker26sfQfY6qLWRqmSxSd6dWaXKsos,19626
whitecanvas/layers/tabular/_df_compat.py,sha256=uR3DE8CkhkbsqMxmgKYGBOG3h8uFrIdt4LmlVl-lX_o,12262
whitecanvas/layers/tabular/_jitter.py,sha256=HKpgIqKRqdxPsDSJff3Knf42a9QxA5ivqJ8JR2MmlfU,4673
whitecanvas/layers/tabular/_marker_like.py,sha256=izedxVoxQDkF7CoNa3aEe9EVG5F11dOHnNy9IpPstCg,30019
whitecanvas/layers/tabular/_plans.py,sha256=e9f-9dhQdBup0pI6VTuI4V-Z2UZ75FZFDOhIFwfKQFk,16488
whitecanvas/layers/tabular/_shared.py,sha256=weCDyj3uXd5l-DJYithePNkrThO0aYNcsFuvoyO-mBA,4441
whitecanvas/plot/__init__.py,sha256=4vO5J6TsGX7MXFmXi6g9MeLw2f9NxFsJiOhs78RgFCU,808
whitecanvas/plot/_canvases.py,sha256=tR0kLIU-rMNvsFz_sEXb9d9jjEgVel2bBYirGmPn01Y,907
whitecanvas/plot/_methods.py,sha256=TGOa4uUXE56VZb8rssNftq18LuOhu3tvL4RSJ_LWu8s,7744
whitecanvas/protocols/__init__.py,sha256=5xTqZtUMVVpO7pz_Ccp_-Uk3pn4bOvxSDe2Tp1d0BPc,1348
whitecanvas/protocols/canvas_protocol.py,sha256=-dujRZ1K5Gg4HHQPMU2Ry81Sag598YBGoFwnXkq10rg,6701
whitecanvas/protocols/layer_protocols.py,sha256=otM662gihMx8-bZxwE_IO0LbVuBiSVWu3Uy_SqJO55w,9741
whitecanvas/theme/__init__.py,sha256=7w47aIlyNToCfhfUA2ACreaj2Yuhb9ruHrhxzGrXtPo,149
whitecanvas/theme/_api.py,sha256=ovI5d2ZoeOvdV-xA3XbPKuWfMKgOdydeWLCAcX4sR00,2816
whitecanvas/theme/_dataclasses.py,sha256=4uZbZ8H_0MymC0l_qZGM7rBO950PyRJCLSf6pMjRoDg,4024
whitecanvas/types/__init__.py,sha256=9cnFo31kZdjpQ7sWTpGAUbOKB0dCTDG_etnDpa0cmjo,1014
whitecanvas/types/_alias.py,sha256=JDNcdrY4uBN85j8uHB-yvAwRsRsn_kf1k7torNWhGIA,864
whitecanvas/types/_enums.py,sha256=hxAu5KNkcqWCQ-xeE_86Ii5jn1VwBSViN0RipMhsU7Q,6617
whitecanvas/types/_mouse.py,sha256=EUGwZNkdSorYqt7tlHD4dEeGUmkzsCdBJxOAxEMEvMc,734
whitecanvas/types/_tuples.py,sha256=ARRsrI0cch5o4OkUaDZ7QLvQTjdOZX5iLj-1zNA3GXU,1701
whitecanvas/utils/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
whitecanvas/utils/collections.py,sha256=SKkiYX7xs3-u0QL6pwFYJo3qjq3SDktccakpn6XEwsg,701
whitecanvas/utils/hist.py,sha256=bppeV8HqGbvlGltSmJ37Eo3PMACYN1r2zzg4Dir6R9g,1980
whitecanvas/utils/kde.py,sha256=E34gRB2G2qMI1yOwc8nW7e1UYNy3OSeNqw5LfPs6PlU,14353
whitecanvas/utils/normalize.py,sha256=Egv_G7tw3kkqTkAdSSBKeRj_PEgk2SBeXgcBHlq1ILE,5083
whitecanvas/utils/type_check.py,sha256=yF91LVWF48kpqqRcchVxRP1QXjHpZogtHTK0dvyL-j0,1098
whitecanvas-0.2.3.dist-info/METADATA,sha256=fAj0imb8n5XZgit77za-yQwlctEnykgYt0amsvhIofs,7085
whitecanvas-0.2.3.dist-info/WHEEL,sha256=9QBuHhg6FNW7lppboF2vKVbCGTVzsFykgRQjjlajrhA,87
whitecanvas-0.2.3.dist-info/licenses/LICENSE,sha256=rpxKafH9r42sxLLYYB5VbZBHOdtYeLuYJjVU1LBwrxk,1546
whitecanvas-0.2.3.dist-info/RECORD,,
