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Robaina · Sep 11, 2023 · 7b89911 · 7b89911
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diff --git a/envs/brendapyrser-dev.yml b/envs/brendapyrser-dev.yml
@@ -15,5 +15,6 @@ dependencies:
     - mkdocstrings[python]
     - ruff
     - black
+    - black[jupyter]
     - argmark
     - coverage
diff --git a/examples/examples.ipynb b/examples/examples.ipynb
@@ -22,7 +22,7 @@
     "from brendapyrser import BRENDA\n",
     "\n",
     "\n",
-    "dataFile = 'data/brenda_download.txt'"
+    "dataFile = \"data/brenda_download.txt\""
    ]
   },
   {
@@ -98,14 +98,13 @@
    ],
    "source": [
     "# Plot all Km values in the database\n",
-    "BRENDA_KMs = np.array([v for r in brenda.reactions \n",
-    "                       for v in r.KMvalues.get_values()])\n",
+    "BRENDA_KMs = np.array([v for r in brenda.reactions for v in r.KMvalues.get_values()])\n",
     "values = BRENDA_KMs[(BRENDA_KMs < 1000) & (BRENDA_KMs >= 0)]\n",
     "plt.hist(values)\n",
-    "plt.title(f'Median KM value: {np.median(values)}')\n",
-    "plt.xlabel('KM (mM)')\n",
+    "plt.title(f\"Median KM value: {np.median(values)}\")\n",
+    "plt.xlabel(\"KM (mM)\")\n",
     "plt.show()\n",
-    "print(f'Minimum and maximum values in database: {values.min()} mM, {values.max()} mM')"
+    "print(f\"Minimum and maximum values in database: {values.min()} mM, {values.max()} mM\")"
    ]
   },
   {
@@ -135,14 +134,15 @@
    ],
    "source": [
     "# Plot all Km values in the database\n",
-    "BRENDA_Kcats = np.array([v for r in brenda.reactions \n",
-    "                       for v in r.Kcatvalues.get_values()])\n",
+    "BRENDA_Kcats = np.array(\n",
+    "    [v for r in brenda.reactions for v in r.Kcatvalues.get_values()]\n",
+    ")\n",
     "values = BRENDA_Kcats[(BRENDA_Kcats < 1000) & (BRENDA_Kcats >= 0)]\n",
     "plt.hist(values)\n",
-    "plt.title(f'Median Kcat value: {np.median(values)}')\n",
-    "plt.xlabel('Kcat (1/s)')\n",
+    "plt.title(f\"Median Kcat value: {np.median(values)}\")\n",
+    "plt.xlabel(\"Kcat (1/s)\")\n",
     "plt.show()\n",
-    "print(f'Minimum and maximum values in database: {values.min()} 1/s, {values.max()} 1/s')"
+    "print(f\"Minimum and maximum values in database: {values.min()} 1/s, {values.max()} 1/s\")"
    ]
   },
   {
@@ -172,15 +172,19 @@
    ],
    "source": [
     "# Plot all enzyme optimal temperature values in the database\n",
-    "BRENDA_TO = np.array([v for r in brenda.reactions \n",
-    "                       for v in r.temperature.filter_by_condition(\n",
-    "                           'optimum').get_values()])\n",
+    "BRENDA_TO = np.array(\n",
+    "    [\n",
+    "        v\n",
+    "        for r in brenda.reactions\n",
+    "        for v in r.temperature.filter_by_condition(\"optimum\").get_values()\n",
+    "    ]\n",
+    ")\n",
     "values = BRENDA_TO[(BRENDA_TO >= 0)]\n",
     "plt.hist(values)\n",
-    "plt.title(f'Median Optimum Temperature: {np.median(values)}')\n",
-    "plt.xlabel('TO (${}^oC$)')\n",
+    "plt.title(f\"Median Optimum Temperature: {np.median(values)}\")\n",
+    "plt.xlabel(\"TO (${}^oC$)\")\n",
     "plt.show()\n",
-    "print(f'Minimum and maximum values in database: {values.min()} °C, {values.max()} °C')"
+    "print(f\"Minimum and maximum values in database: {values.min()} °C, {values.max()} °C\")"
    ]
   },
   {
@@ -219,15 +223,22 @@
    ],
    "source": [
     "# Plot all enzyme optimal temperature values in the database\n",
-    "species = 'Thermotoga'\n",
-    "BRENDA_TO = np.array([v for r in brenda.reactions.filter_by_organism(species)\n",
-    "                       for v in r.temperature.filter_by_condition('optimum').filter_by_organism(species).get_values()])\n",
+    "species = \"Thermotoga\"\n",
+    "BRENDA_TO = np.array(\n",
+    "    [\n",
+    "        v\n",
+    "        for r in brenda.reactions.filter_by_organism(species)\n",
+    "        for v in r.temperature.filter_by_condition(\"optimum\")\n",
+    "        .filter_by_organism(species)\n",
+    "        .get_values()\n",
+    "    ]\n",
+    ")\n",
     "values = BRENDA_TO[(BRENDA_TO >= 0)]\n",
     "plt.hist(values)\n",
-    "plt.title(f'Median Optimum Temperature: {np.median(values)}')\n",
-    "plt.xlabel('TO (${}^oC$)')\n",
+    "plt.title(f\"Median Optimum Temperature: {np.median(values)}\")\n",
+    "plt.xlabel(\"TO (${}^oC$)\")\n",
     "plt.show()\n",
-    "print(f'Minimum and maximum values in database: {values.min()} °C, {values.max()} °C')"
+    "print(f\"Minimum and maximum values in database: {values.min()} °C, {values.max()} °C\")"
    ]
   },
   {
@@ -279,7 +290,7 @@
    ],
    "source": [
     "# We can retrieve an enzyme entry by its EC number like this\n",
-    "r = brenda.reactions.get_by_id('2.7.1.40')\n",
+    "r = brenda.reactions.get_by_id(\"2.7.1.40\")\n",
     "r"
    ]
   },
@@ -303,11 +314,11 @@
    ],
    "source": [
     "# Here are all the KM values for phosphoenolpyruvate associated with this enzyme class\n",
-    "compound = 'phosphoenolpyruvate'\n",
+    "compound = \"phosphoenolpyruvate\"\n",
     "kms = r.KMvalues.filter_by_compound(compound).get_values()\n",
     "plt.hist(kms)\n",
-    "plt.xlabel('KM (mM)')\n",
-    "plt.title(f'{r.name} ({compound})')\n",
+    "plt.xlabel(\"KM (mM)\")\n",
+    "plt.title(f\"{r.name} ({compound})\")\n",
     "plt.show()"
    ]
   },
@@ -331,11 +342,11 @@
    ],
    "source": [
     "# Here are all the KM values for phosphoenolpyruvate associated with this enzyme class\n",
-    "compound = 'phosphoenolpyruvate'\n",
+    "compound = \"phosphoenolpyruvate\"\n",
     "KMs = r.KMvalues.filter_by_compound(compound).get_values()\n",
     "plt.hist(KMs)\n",
-    "plt.xlabel('KM (mM)')\n",
-    "plt.title(f'{r.name} ({compound})')\n",
+    "plt.xlabel(\"KM (mM)\")\n",
+    "plt.title(f\"{r.name} ({compound})\")\n",
     "plt.show()"
    ]
   },
@@ -357,7 +368,9 @@
    ],
    "source": [
     "# And further filtered by organism\n",
-    "r.KMvalues.filter_by_organism('Bos taurus').filter_by_compound('phosphoenolpyruvate').get_values()"
+    "r.KMvalues.filter_by_organism(\"Bos taurus\").filter_by_compound(\n",
+    "    \"phosphoenolpyruvate\"\n",
+    ").get_values()"
    ]
   },
   {
@@ -380,11 +393,11 @@
    ],
    "source": [
     "# Here are all the Kcat values for phosphoenolpyruvate associated with this enzyme class\n",
-    "compound = 'phosphoenolpyruvate'\n",
+    "compound = \"phosphoenolpyruvate\"\n",
     "kcats = r.Kcatvalues.filter_by_compound(compound).get_values()\n",
     "plt.hist(kcats)\n",
-    "plt.xlabel('Kcat ($s^{-1}$)')\n",
-    "plt.title(f'{r.name} ({compound})')\n",
+    "plt.xlabel(\"Kcat ($s^{-1}$)\")\n",
+    "plt.title(f\"{r.name} ({compound})\")\n",
     "plt.show()"
    ]
   },
@@ -415,17 +428,24 @@
     }
    ],
    "source": [
-    "species, compound = 'Escherichia coli', 'NADH'\n",
-    "KMs = np.array([v for r in brenda.reactions.filter_by_organism(species)\n",
-    "                for v in r.KMvalues.filter_by_compound(compound).filter_by_organism(species).get_values()])\n",
+    "species, compound = \"Escherichia coli\", \"NADH\"\n",
+    "KMs = np.array(\n",
+    "    [\n",
+    "        v\n",
+    "        for r in brenda.reactions.filter_by_organism(species)\n",
+    "        for v in r.KMvalues.filter_by_compound(compound)\n",
+    "        .filter_by_organism(species)\n",
+    "        .get_values()\n",
+    "    ]\n",
+    ")\n",
     "\n",
     "if len(KMs) > 0:\n",
     "    plt.hist(KMs)\n",
-    "    plt.xlabel('KM (mM)')\n",
-    "    plt.title(f'{species} KMs ({compound}), median = {np.median((KMs))}')\n",
+    "    plt.xlabel(\"KM (mM)\")\n",
+    "    plt.title(f\"{species} KMs ({compound}), median = {np.median((KMs))}\")\n",
     "    plt.show()\n",
     "else:\n",
-    "    print('No KM values for compound')"
+    "    print(\"No KM values for compound\")"
    ]
   },
   {

diff --git a/src/brendapyrser/parser.py b/src/brendapyrser/parser.py
@@ -26,7 +26,6 @@ class BRENDA:
     """
 
     def __init__(self, path_to_database):
-
         with open(path_to_database, encoding="iso-8859-1") as file:
             self.__data = file.read()
         self.__ec_numbers = [