PyPI 官网下载 | trifacta-2.0.tar.gz

# trifacta Trifacta client that makes it easy to integrate Trifacta into your production and data science workflows ### Usage Scenarios - **Jupyter**: Invoke Trifacta jobs from a Jupyter notebook and pass data back and forth between Jupyter and Trifacta - **Other Notebooks**: Integrate Trifacta with Azure Databricks, Zepellin or any other notebook-style interface that supports Python - **Scripts**: Automate Trifacta jobs and input/output using python scripts that can be easily executed from the command line or called from an external scheduler ### Functionality This library makes it simple to do the following: 1. Connect to a Trifacta instance 2. Run a job 3. Download results to a pandas dataframe OR Download results as text/csv 4. Upload files to Trifacta Note that file uploads and downloads are performed using httpfs, and require that port 14000 be opened on the Trifacta server ```python #!pip install trifacta import trifacta ``` ```python #Step 1: Connect to Trifacta by providing the URL, username and password t = trifacta.Client('https://partnerdemo.trifacta.net', 'userid@mydomain.com', 'mypassword') ``` #### Get the wrangled dataset id from the URL in the Trifacta UI Make sure that you have run the job manually at least once  #### Note the output path (be sure to set it to "replace")  ```python #Step 2: Run the job t.run_job(14478) ``` About to run job {'jobgroupId': 3926, 'jobIds': [7513, 7514], 'reason': 'JobStarted', 'sessionId': 'b9d327f0-8e19-11e8-8feb-9fabf204e996'} 2018-07-22 18:43:01.427594 InProgress 2018-07-22 18:43:06.791576 Complete True ```python #Step 3a: Get a pandas dataframe with the results df = t.get_dataframe('/trifacta/queryResults/demo@trifacta.com/demo_output.csv') ``` ```python df ``` <div> <table border="1" class="dataframe"> <thead> <tr style="text-align: right;"> <th></th> <th>Neighborhood</th> <th>HouseStyle</th> <th>row_count</th> <th>sum_LotArea</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>NAmes</td> <td>1Story</td> <td>159</td> <td>1589811</td> </tr> <tr> <th>1</th> <td>CollgCr</td> <td>1Story</td> <td>91</td> <td>841644</td> </tr> <tr> <th>2</th> <td>Gilbert</td> <td>2Story</td> <td>60</td> <td>668112</td> </tr> <tr> <th>3</th> <td>Timber</td> <td>1Story</td> <td>23</td> <td>554694</td> </tr> <tr> <th>4</th> <td>CollgCr</td> <td>2Story</td> <td>53</td> <td>546602</td> </tr> <tr> <th>5</th> <td>NridgHt</td> <td>1Story</td> <td>51</td> <td>537687</td> </tr> <tr> <th>6</th> <td>Sawyer</td> <td>1Story</td> <td>53</td> <td>528438</td> </tr> <tr> <th>7</th> <td>Edwards</td> <td>1Story</td> <td>53</td> <td>511296</td> </tr> <tr> <th>8</th> <td>NoRidge</td> <td>2Story</td> <td>33</td> <td>485691</td> </tr> <tr> <th>9</th> <td>NWAmes</td> <td>1Story</td> <td>35</td> <td>403813</td> </tr> <tr> <th>10</th> <td>ClearCr</td> <td>1Story</td> <td>11</td> <td>395797</td> </tr> <tr> <th>11</th> <td>Mitchel</td> <td>1Story</td> <td>32</td> <td>394436</td> </tr> <tr> <th>12</th> <td>Somerst</td> <td>1Story</td> <td>37</td> <td>350820</td> </tr> <tr> <th>13</th> <td>NWAmes</td> <td>2Story</td> <td>29</td> <td>348885</td> </tr> <tr> <th>14</th> <td>Somerst</td> <td>2Story</td> <td>49</td> <td>323495</td> </tr> <tr> <th>15</th> <td>NridgHt</td> <td>2Story</td> <td>26</td> <td>300685</td> </tr> <tr> <th>16</th> <td>OldTown</td> <td>2Story</td> <td>32</td> <td>274465</td> </tr> <tr> <th>17</th> <td>SawyerW</td> <td>1Story</td> <td>28</td> <td>271008</td> </tr> <tr> <th>18</th> <td>OldTown</td> <td>1.5Fin</td> <td>33</td> <td>267283</td> </tr> <tr> <th>19</th> <td>ClearCr</td> <td>1.5Fin</td> <td>6</td> <td>266593</td> </tr> <tr> <th>20</th> <td>Crawfor</td> <td>1Story</td> <td>19</td> <td>260639</td> </tr> <tr> <th>21</th> <td>SawyerW</td> <td>2Story</td> <td>25</td> <td>255102</td> </tr> <tr> <th>22</th> <td>NAmes</td> <td>2Story</td> <td>22</td> <td>249793</td> </tr> <tr> <th>23</th> <td>OldTown</td> <td>1Story</td> <td>33</td> <td>240257</td> </tr> <tr> <th>24</th> <td>Edwards</td> <td>1.5Fin</td> <td>22</td> <td>228970</td> </tr> <tr> <th>25</th> <td>Crawfor</td> <td>2Story</td> <td>20</td> <td>222029</td> </tr> <tr> <th>26</th> <td>NAmes</td> <td>SLvl</td> <td>21</td> <td>221177</td> </tr> <tr> <th>27</th> <td>Edwards</td> <td>2Story</td> <td>14</td> <td>185799</td> </tr> <tr> <th>28</th> <td>Timber</td> <td>1.5Fin</td> <td>2</td> <td>178418</td> </tr> <tr> <th>29</th> <td>BrkSide</td> <td>1.5Fin</td> <td>25</td> <td>172233</td> </tr> <tr> <th>...</th> <td>...</td> <td>...</td> <td>...</td> <td>...</td> </tr> <tr> <th>66</th> <td>CollgCr</td> <td>SLvl</td> <td>3</td> <td>30135</td> </tr> <tr> <th>67</th> <td>BrDale</td> <td>2Story</td> <td>16</td> <td>28816</td> </tr> <tr> <th>68</th> <td>Veenker</td> <td>SLvl</td> <td>2</td> <td>25757</td> </tr> <tr> <th>69</th> <td>NoRidge</td> <td>1.5Fin</td> <td>2</td> <td>25398</td> </tr> <tr> <th>70</th> <td>SawyerW</td> <td>SFoyer</td> <td>3</td> <td>25267</td> </tr> <tr> <th>71</th> <td>CollgCr</td> <td>SFoyer</td> <td>3</td> <td>24491</td> </tr> <tr> <th>72</th> <td>MeadowV</td> <td>2Story</td> <td>8</td> <td>19611</td> </tr> <tr> <th>73</th> <td>NPkVill</td> <td>1Story</td> <td>4</td> <td>17942</td> </tr> <tr> <th>74</th> <td>Veenker</td> <td>2Story</td> <td>1</td> <td>17542</td> </tr> <tr> <th>75</th> <td>NAmes</td> <td>1.5Unf</td> <td>2</td> <td>16827</td> </tr> <tr> <th>76</th> <td>SWISU</td> <td>1Story</td> <td>2</td> <td>14692</td> </tr> <tr> <th>77</th> <td>OldTown</td> <td>SFoyer</td> <td>2</td> <td>14179</td> </tr> <tr> <th>78</th> <td>NWAmes</td> <td>1.5Fin</td> <td>1</td> <td>13837</td> </tr> <tr> <th>79</th> <td>SawyerW</td> <td>SLvl</td> <td>1</td> <td>12800</td> </tr> <tr> <th>80</th> <td>IDOTRR</td> <td>1.5Unf</td> <td>2</td> <td>12449</td> </tr> <tr> <th>81</th> <td>SawyerW</td> <td>1.5Fin</td> <td>1</td> <td>12327</td> </tr> <tr> <th>82</th> <td>Gilbert</td> <td>1.5Fin</td> <td>1</td> <td>12134</td> </tr> <tr>