Merge pull request #3 from 0xfdf/new-test-branch

another small change to test CI
0xfdf · Aug 5, 2024 · 706be4d · 706be4d
2 parents 652c129 + 15de327
commit 706be4d
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diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -5,6 +5,11 @@ on:
     branches:
       - main
 
+defaults:
+  run:
+    working-directory: toraniko
+    shell: bash
+
 jobs:
   test:
     runs-on: ubuntu-latest
@@ -21,7 +26,7 @@ jobs:
       - name: Install deps
         run: |
           python -m pip install --upgrade pip
-          pip install -r dev-requirements.txt
+          pip install -r ../dev-requirements.txt
 
       - name: Run tests
         run: |

diff --git a/README.md b/README.md
@@ -4,5 +4,5 @@ Toraniko is a complete implementation of a risk model for quantitative and syste
 
 Using this library, you can create new custom factors and estimate their returns. From there you will be able to estimate a factor covariance matrix suitable for portfolio optimization with factor risk constraints (e.g. to main a market neutral portfolio).
 
-The only dependencies are numpy and Polars. It supports market, sector and style factors; three styles are included: value, size and momentum. The functions you broadly want to have for constructing more style factors (or custom fundamental factors of any kind) are included.
+The only dependencies are numpy and polars. It supports market, sector and style factors; three styles are included: value, size and momentum. The functions you broadly want to have for constructing more style factors (or custom fundamental factors of any kind) are included.
Original file line number	Diff line number	Diff line change
Expand Up		@@ -4,5 +4,5 @@ Toraniko is a complete implementation of a risk model for quantitative and syste

		Using this library, you can create new custom factors and estimate their returns. From there you will be able to estimate a factor covariance matrix suitable for portfolio optimization with factor risk constraints (e.g. to main a market neutral portfolio).

		The only dependencies are numpy and Polars. It supports market, sector and style factors; three styles are included: value, size and momentum. The functions you broadly want to have for constructing more style factors (or custom fundamental factors of any kind) are included.
		The only dependencies are numpy and polars. It supports market, sector and style factors; three styles are included: value, size and momentum. The functions you broadly want to have for constructing more style factors (or custom fundamental factors of any kind) are included.